• summary(x): quantile information
• count(x): what unique values do you have?
  • distinct(): what are the distinct values?
  • n_distinct() with pull(): how many distinct values?
• group_by(): changes all subsequent functions
  • combine with summarize() to get statistics per group
  • combine with mutate() to add column
• summarize() with n() gives the count (NAs included)

📃Day 4 Cheatsheet

• There are two types of number class objects: integer and double
• Logic class objects only have TRUE or FALSE (without quotes)
• class() can be used to test the class of an object x
• as.CLASS_NAME(x) can be used to change the class of an object x
• Factors are a special character class that has levels - more on that soon!
• tibbles show column classes!
• two dimensional object classes include: data frames, tibbles, matrices, and lists
• Dates can be handled with the lubridate package
• Make sure you choose the right function for the way the date is formatted!

📃Day 4 Cheatsheet

One of the most important aspects of data cleaning is missing values.

Types of “missing” data:

• NA - general missing data
• NaN - stands for “Not a Number”, happens when you do 0/0.
• Inf and -Inf - Infinity, happens when you divide a positive number (or negative number) by 0.

any() can help you check if there are any NA values in a vector

test

[1]  NaN   NA -Inf

any(is.na(test))

[1] TRUE

count() is a great option because it helps you check if rare values make sense.

Let’s look at the CO heat-related ER visits dataset again.

er <- read_csv(file =
    "https://daseh.org/data/CO_ER_heat_visits.csv")
er %>% count(visits)

# A tibble: 37 × 2
   visits     n
    <dbl> <int>
 1      0   339
 2     11     2
 3     12     5
 4     13     8
 5     14     3
 6     15     2
 7     16     3
 8     17     3
 9     18     5
10     19     7
# ℹ 27 more rows

Sometimes you need to look at lots of data though… the naniar package is a good option.

#install.packages("naniar")
library(naniar)

“Artwork by @allison_horst”. https://allisonhorst.com/

This can tell you if there are missing values in the dataset.

pct_complete(er)

[1] 73.65451

Or for a particular variable:

er %>% select(visits) %>% 
  pct_complete()

[1] 60.54688

er %>% select(rate) %>% 
  pct_complete()

[1] 60.54688

To get the percent missing (and counts) for each variable as a table, use this function:

miss_var_summary(er)

# A tibble: 6 × 3
  variable  n_miss pct_miss
  <chr>      <int>    <num>
1 lower95cl    304     39.6
2 upper95cl    304     39.6
3 rate         303     39.5
4 visits       303     39.5
5 county         0      0  
6 year           0      0  

The gg_miss_var() function creates a nice plot about the number of missing values for each variable, (need a data frame).

gg_miss_var(er, show_pct = TRUE)

Recall that mathematical operations with NA often result in NAs.

sum(c(1,2,3,NA))

[1] NA

mean(c(1,2,3,NA))

[1] NA

median(c(1,2,3,NA))

[1] NA

This is also true for logical data. Recall that TRUE is evaluated as 1 and FALSE is evaluated as 0.

x <- c(TRUE, TRUE, TRUE, TRUE, FALSE, NA)
sum(x)

[1] NA

sum(x, na.rm = TRUE)

[1] 4

Be careful with missing data using subsetting!

filter() removes missing values by default. Because R can’t tell for sure if an NA value meets the condition. To keep them need to add is.na() conditional.

Think about if this is OK or not - it depends on your data!

is.na() can help us keep them.

er %>% filter(visits > 0 | is.na(visits))

# A tibble: 429 × 6
   county  rate lower95cl upper95cl visits  year
   <chr>  <dbl>     <dbl>     <dbl>  <dbl> <dbl>
 1 Adams   6.73     NA         9.24     29  2011
 2 Adams   4.84      2.85     NA        23  2012
 3 Adams   6.84      4.36      9.31     31  2013
 4 Adams   3.08      1.71      4.85     15  2014
 5 Adams   3.36      1.89      5.23     16  2015
 6 Adams   8.85      6.12     11.6      42  2016
 7 Adams   6.63      4.29      8.98     32  2017
 8 Adams   7.11      4.77      9.44     37  2018
 9 Adams   6.76      4.53      8.99     36  2019
10 Adams   4.76      2.82      6.70     24  2020
# ℹ 419 more rows

A function from the tidyr package. (Need a data frame to start!)

Disclaimer: Don’t do this unless you have thought about if dropping NA values makes sense based on knowing what these values mean in your data. Also consider if you need those rows for values for other variables.

dim(er)

[1] 768   6

er_drop <- er %>% drop_na(lower95cl)
dim(er_drop)

[1] 464   6

Can still have NAs for other columns

er_drop 

# A tibble: 464 × 6
   county  rate lower95cl upper95cl visits  year
   <chr>  <dbl>     <dbl>     <dbl>  <dbl> <dbl>
 1 Adams   4.84      2.85     NA        23  2012
 2 Adams   6.84      4.36      9.31     31  2013
 3 Adams   3.08      1.71      4.85     15  2014
 4 Adams   3.36      1.89      5.23     16  2015
 5 Adams   8.85      6.12     11.6      42  2016
 6 Adams   6.63      4.29      8.98     32  2017
 7 Adams   7.11      4.77      9.44     37  2018
 8 Adams   6.76      4.53      8.99     36  2019
 9 Adams   4.76      2.82      6.70     24  2020
10 Adams   6.93      4.61      9.25     35  2021
# ℹ 454 more rows

This function of the tidyr package drops rows with any missing data in any column when used on a df.

er_drop <- er %>% drop_na()
er_drop

# A tibble: 463 × 6
   county  rate lower95cl upper95cl visits  year
   <chr>  <dbl>     <dbl>     <dbl>  <dbl> <dbl>
 1 Adams   6.84      4.36      9.31     31  2013
 2 Adams   3.08      1.71      4.85     15  2014
 3 Adams   3.36      1.89      5.23     16  2015
 4 Adams   8.85      6.12     11.6      42  2016
 5 Adams   6.63      4.29      8.98     32  2017
 6 Adams   7.11      4.77      9.44     37  2018
 7 Adams   6.76      4.53      8.99     36  2019
 8 Adams   4.76      2.82      6.70     24  2020
 9 Adams   6.93      4.61      9.25     35  2021
10 Adams   8.23      5.81     10.6      45  2022
# ℹ 453 more rows

Use the miss_var_which() function from naniar

miss_var_which(er)# which columns have missing values

[1] "rate"      "lower95cl" "upper95cl" "visits"   

Let’s say we think that all 0 values should be NA.

Maybe we think the person who entered the CO heat-related ER visits data made a mistake in how they coded missing data.

er %>% count(visits)

# A tibble: 37 × 2
   visits     n
    <dbl> <int>
 1      0   339
 2     11     2
 3     12     5
 4     13     8
 5     14     3
 6     15     2
 7     16     3
 8     17     3
 9     18     5
10     19     7
# ℹ 27 more rows

The na_if() function of dplyr can be helpful for changing all 0 values to NA.

er_nozero <- er %>% 
  mutate(visits = na_if(visits, 0))

er_nozero %>% count(visits)

# A tibble: 36 × 2
   visits     n
    <dbl> <int>
 1     11     2
 2     12     5
 3     13     8
 4     14     3
 5     15     2
 6     16     3
 7     17     3
 8     18     5
 9     19     7
10     20     2
# ℹ 26 more rows

⚠️ Sometimes removing NA values leads to distorted math - be careful!

⚠️ Think about what your NA means for your data (are you sure ?).

• Is an NA for values so low they could not be reported?

• Or is it if it was too low and also if there was a different issue (like no one reported)?

If it is something more like a zero then you might want it included in your data like a zero instead of an NA.

Example: - survey reports NA if student has never tried cigarettes - survey reports 0 if student has tried cigarettes but did not smoke that week

⚠️ You might want to keep the NA values so that you know the original sample size.

count(er, visits) %>% mutate(percent = (n/(sum(n)) *100))

# A tibble: 37 × 3
   visits     n percent
    <dbl> <int>   <dbl>
 1      0   339  44.1  
 2     11     2   0.260
 3     12     5   0.651
 4     13     8   1.04 
 5     14     3   0.391
 6     15     2   0.260
 7     16     3   0.391
 8     17     3   0.391
 9     18     5   0.651
10     19     7   0.911
# ℹ 27 more rows

er %>% drop_na(visits) %>% 
  count(visits) %>% mutate(percent = (n/(sum(n)) *100))

# A tibble: 36 × 3
   visits     n percent
    <dbl> <int>   <dbl>
 1      0   339  72.9  
 2     11     2   0.430
 3     12     5   1.08 
 4     13     8   1.72 
 5     14     3   0.645
 6     15     2   0.430
 7     16     3   0.645
 8     17     3   0.645
 9     18     5   1.08 
10     19     7   1.51 
# ℹ 26 more rows

Should you be dividing by the total count with NA values included?
It depends on your data and what NA might mean.
Pay attention to your data and your NA values!

• Extra or Missing commas
  
• Extra or Missing parentheses
  
• Case sensitivity
  
• Spelling

A. drop_nulls()

B. drop_na()

C. rem_na()

A. include | is.na()

B. include & is.na()

• is.na(),any(is.na()), all(is.na()),count(), and functions from naniar like gg_miss_var() and miss_var_summary can help determine if we have NA values
• miss_var_which() can help you drop columns that have any missing values.
• filter() automatically removes NA values - can’t confirm or deny if condition is met (need | is.na() to keep them)
• drop_na() can help you remove NA values from a variable or an entire data frame
• NA values can change your calculation results
• think about what NA values represent - don’t drop them if you shouldn’t
• na_if() will make NA values for a particular value
• replace_na() will replace `NA values with a particular value

🏠 Class Website
💻 Lab. 📃 Day 5 Cheatsheet

Let’s upload some practice data about microplastics. Maybe we measured the level of microplastics in someone who eats a fish versus someone who is a vegetarian.

https://www.medicalnewstoday.com/articles/what-do-we-know-about-microplastics-in-food#Common-microplastics-in-food https://www.sciencedirect.com/science/article/pii/S0045653523028072 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5708064/

plastics <- read_csv(file =
    "https://daseh.org/data/microplastics_in_blood.csv")

Rows: 12 Columns: 4
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr (2): Foods, microplastic
dbl (2): blood_level_start_nM, blood_level_change_nM

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

plastics

# A tibble: 12 × 4
   Foods microplastic blood_level_start_nM blood_level_change_nM
   <chr> <chr>                       <dbl>                 <dbl>
 1 A     Dioxin                          1                   2.5
 2 B     Dioxin                          7                   2.5
 3 B     Other                           2                   0.5
 4 A     Bisphenol A                     3                  -0.5
 5 B     BPA                             5                   0.5
 6 B     dioxin                          8                   0.5
 7 A     bpa                             6                   2.5
 8 B     Other                           5                   3.5
 9 B     dioxin                          2                   0.5
10 A     bpa                             1                   1.5
11 B     BPA                             7                   1.5
12 B     Other                           3                   2.5

This needs lots of recoding.

plastics %>%
  count(microplastic)

# A tibble: 6 × 2
  microplastic     n
  <chr>        <int>
1 BPA              2
2 Bisphenol A      1
3 Dioxin           2
4 Other            3
5 bpa              2
6 dioxin           2

The case_when() function of dplyr can help us to do this as well.

It is more flexible and powerful.

plastics %>% 
  mutate(microplastic_recoded = case_when(
                               microplastic == "Bisphenol A" ~ "BPA",
                               microplastic == "bpa" ~ "BPA",
                               microplastic == "dioxin" ~"Dioxin"))  %>% 
  count(microplastic, microplastic_recoded)

# A tibble: 6 × 3
  microplastic microplastic_recoded     n
  <chr>        <chr>                <int>
1 BPA          <NA>                     2
2 Bisphenol A  BPA                      1
3 Dioxin       <NA>                     2
4 Other        <NA>                     3
5 bpa          BPA                      2
6 dioxin       Dioxin                   2

Note that automatically values not reassigned explicitly by case_when() will be NA unless otherwise specified.

# General Format - this is not code!
{data_input} %>%
  mutate({variable_to_fix} = case_when({Variable_fixing}   
             /some condition/ ~ {value_for_con},
                     .default = {value_for_not_meeting_condition}) # need this to avoid NAs

{value_for_not_meeting_condition} could be something new or it can be the original values of the column

plastics %>% 
  mutate(microplastic_recoded = case_when(
                               microplastic == "Bisphenol A" ~ "BPA",
                               microplastic == "bpa" ~ "BPA",
                               microplastic =="dioxin" ~"Dioxin",
                               .default = microplastic)) %>%
  count(microplastic_recoded)

# A tibble: 3 × 2
  microplastic_recoded     n
  <chr>                <int>
1 BPA                      5
2 Dioxin                   4
3 Other                    3

You never know if you might be missing something - and if a value already was an NA it will stay that way.

plastics %>% 
  mutate(microplastic_recoded = case_when(
                               microplastic == "Bisphenol A" ~ "BPA",
                               microplastic == "bpa" ~ "BPA",
                               microplastic == "dioxin" ~"Dioxin",
                               .default = microplastic)) %>%
  count(microplastic, microplastic_recoded)

You need to specify what we want in the first part of mutate.

plastics %>% 
  mutate(microplastic = case_when(
                              microplastic == "Bisphenol A" ~ "BPA",
                              microplastic == "bpa" ~ "BPA",
                              microplastic == "dioxin" ~"Dioxin",
                              .default = microplastic)) %>%
  count(microplastic)

# A tibble: 3 × 2
  microplastic     n
  <chr>        <int>
1 BPA              5
2 Dioxin           4
3 Other            3

case_when can do complicated statements and can match many patterns at a time.

plastics %>% 
  mutate(microplastic_recoded = case_when(
    microplastic %in% c("dioxin", "Dioxin") ~ "Dioxin", 
    microplastic %in% c("BPA", "bpa", "Bisphenol A") ~ "BPA",
                     .default = microplastic)) %>%

  count(microplastic, microplastic_recoded)

# A tibble: 6 × 3
  microplastic microplastic_recoded     n
  <chr>        <chr>                <int>
1 BPA          BPA                      2
2 Bisphenol A  BPA                      1
3 Dioxin       Dioxin                   2
4 Other        Other                    3
5 bpa          BPA                      2
6 dioxin       Dioxin                   2

case_when can do very sophisticated comparisons!

Here we create a new variable called Effect.

plastics <- plastics %>% 
      mutate(Effect = case_when(
                    blood_level_change_nM > 0 ~ "Increase",
                    blood_level_change_nM == 0 ~ "Same",
                    blood_level_change_nM < 0 ~ "Decrease"))

head(plastics)

# A tibble: 6 × 5
  Foods microplastic blood_level_start_nM blood_level_change_nM Effect  
  <chr> <chr>                       <dbl>                 <dbl> <chr>   
1 A     Dioxin                          1                   2.5 Increase
2 B     Dioxin                          7                   2.5 Increase
3 B     Other                           2                   0.5 Increase
4 A     Bisphenol A                     3                  -0.5 Decrease
5 B     BPA                             5                   0.5 Increase
6 B     dioxin                          8                   0.5 Increase

plastics %>% 
  count(Foods, Effect)

# A tibble: 3 × 3
  Foods Effect       n
  <chr> <chr>    <int>
1 A     Decrease     1
2 A     Increase     3
3 B     Increase     8

plastics <- plastics %>% 
      mutate(Effect = case_when(
                    blood_level_change_nM > 0 ~ "Increase",
                    blood_level_change_nM == 0 ~ "Same",
                    blood_level_change_nM < 0 ~ "Decrease",
                    .default = blood_level_change_nM)) 
# this will give an error!

plastics <- plastics %>% 
      mutate(Effect = case_when(
                    blood_level_change_nM > 0 ~ "Increase",
                    blood_level_change_nM == 0 ~ "Same",
                    blood_level_change_nM < 0 ~ "Decrease",
                    .default = as.character(blood_level_change_nM))) 
# this works!

plastics %>% 
      mutate(Amt_change = case_when(
                    blood_level_change_nM > 0 & blood_level_change_nM < 2 ~ "Small",
                    blood_level_change_nM >= 2 ~ "Large",
                    blood_level_change_nM < 0 & blood_level_change_nM > -2 ~ "Small",
                    blood_level_change_nM <= -2 ~ "Large",
                    blood_level_change_nM == 0 ~ "none")) %>%
  head()

# A tibble: 6 × 6
  Foods microplastic blood_level_start_nM blood_level_change_nM Effect  
  <chr> <chr>                       <dbl>                 <dbl> <chr>   
1 A     Dioxin                          1                   2.5 Increase
2 B     Dioxin                          7                   2.5 Increase
3 B     Other                           2                   0.5 Increase
4 A     Bisphenol A                     3                  -0.5 Decrease
5 B     BPA                             5                   0.5 Increase
6 B     dioxin                          8                   0.5 Increase
# ℹ 1 more variable: Amt_change <chr>

A. modify()

B. select()

C. mutate()

A. = the name of the variable we are modifying or using as source

B. = “same”

• R can do much more than find exact matches for a whole string!

The stringr package:

• Modifying or finding part or all of a character string
• We will not cover grep or gsub - base R functions
  • are used on forums for answers
• Almost all functions start with str_*

str_detect, and str_replace search for matches to argument pattern within each element of a character vector (not data frame or tibble!).

• str_detect - returns TRUE if pattern is found
• str_replace - replaces pattern with replacement

The string argument specifies what to check
The pattern argument specifies what to check for (case sensitive)

Effect <- pull(plastics) %>% head(n = 6)
Effect

[1] "Increase" "Increase" "Increase" "Decrease" "Increase" "Increase"

str_detect(string = Effect, pattern = "d")

[1] FALSE FALSE FALSE FALSE FALSE FALSE

str_detect(string = Effect, pattern = "D")

[1] FALSE FALSE FALSE  TRUE FALSE FALSE

The string argument specifies what to check
The pattern argument specifies what to check for
The replacement argument specifies what to replace the pattern with

str_replace(string = Effect, pattern = "D", replacement = "d")

[1] "Increase" "Increase" "Increase" "decrease" "Increase" "Increase"

str_replace_all() can be used to replace all instances within each value

str_replace(string = Effect, pattern = "e", replacement = "E")

[1] "IncrEase" "IncrEase" "IncrEase" "DEcrease" "IncrEase" "IncrEase"

str_replace_all(string = Effect, pattern = "e", replacement = "E")

[1] "IncrEasE" "IncrEasE" "IncrEasE" "DEcrEasE" "IncrEasE" "IncrEasE"

str_sub() allows you to subset part of a string
The string argument specifies what strings to work with
The start argument specifies position of where to start
The end argument specifies position of where to end

str_sub(string = Effect, start = 1, end = 3)

[1] "Inc" "Inc" "Inc" "Dec" "Inc" "Inc"

head(plastics, n = 4)

# A tibble: 4 × 5
  Foods microplastic blood_level_start_nM blood_level_change_nM Effect  
  <chr> <chr>                       <dbl>                 <dbl> <chr>   
1 A     Dioxin                          1                   2.5 Increase
2 B     Dioxin                          7                   2.5 Increase
3 B     Other                           2                   0.5 Increase
4 A     Bisphenol A                     3                  -0.5 Decrease

plastics %>% 
  filter(str_detect(string = microplastic,
                    pattern = "B"))

# A tibble: 3 × 5
  Foods microplastic blood_level_start_nM blood_level_change_nM Effect  
  <chr> <chr>                       <dbl>                 <dbl> <chr>   
1 A     Bisphenol A                     3                  -0.5 Decrease
2 B     BPA                             5                   0.5 Increase
3 B     BPA                             7                   1.5 Increase

count(plastics, microplastic)

# A tibble: 6 × 2
  microplastic     n
  <chr>        <int>
1 BPA              2
2 Bisphenol A      1
3 Dioxin           2
4 Other            3
5 bpa              2
6 dioxin           2

But we still might miss a strange value - like a misspelling

plastics %>% 
  mutate(microplastic_recoded = case_when(
    microplastic %in% c("Dioxin", "dioxin") ~ "Dioxin",
    microplastic %in% c("BPA", "bpa", "Bisphenol A") ~ "BPA",
    .default = microplastic))

^ indicates the beginning of a character string $ indicates the end

plastics %>% 
  mutate(microplastic_recoded = case_when(
    str_detect(string = microplastic, pattern = "^b|^B") ~ "BPA",
    str_detect(string = microplastic, pattern = "^d|^D") ~ "Dioxin",
    .default =  microplastic)) %>%
  count(microplastic, microplastic_recoded)

# A tibble: 6 × 3
  microplastic microplastic_recoded     n
  <chr>        <chr>                <int>
1 BPA          BPA                      2
2 Bisphenol A  BPA                      1
3 Dioxin       Dioxin                   2
4 Other        Other                    3
5 bpa          BPA                      2
6 dioxin       Dioxin                   2

This is a more robust solution! It will catch typos as long as the first letter is correct.

A. str_replace()

B. str_find()

C. str_detect()

The unite() function can help combine columns
The col argument specifies new column name
The sep argument specifies what separator to use when combining -default is “_” The remove argument specifies if you want to drop the old columns

plastics_comb <- plastics %>% 
  unite(Foods, Effect, col = "change", remove = TRUE)

plastics_comb

# A tibble: 12 × 4
   change     microplastic blood_level_start_nM blood_level_change_nM
   <chr>      <chr>                       <dbl>                 <dbl>
 1 A_Increase Dioxin                          1                   2.5
 2 B_Increase Dioxin                          7                   2.5
 3 B_Increase Other                           2                   0.5
 4 A_Decrease Bisphenol A                     3                  -0.5
 5 B_Increase BPA                             5                   0.5
 6 B_Increase dioxin                          8                   0.5
 7 A_Increase bpa                             6                   2.5
 8 B_Increase Other                           5                   3.5
 9 B_Increase dioxin                          2                   0.5
10 A_Increase bpa                             1                   1.5
11 B_Increase BPA                             7                   1.5
12 B_Increase Other                           3                   2.5

The separate() function from tidyr can split a column into multiple columns.
The col argument specifies what column to work with
The into argument specifies names of new columns
The sep argument specifies what to separate by

plastics_comb <- plastics_comb %>% 
  separate(col = change, into = c("Foods", "Change"), sep = "_" )
plastics_comb

# A tibble: 12 × 5
   Foods Change   microplastic blood_level_start_nM blood_level_change_nM
   <chr> <chr>    <chr>                       <dbl>                 <dbl>
 1 A     Increase Dioxin                          1                   2.5
 2 B     Increase Dioxin                          7                   2.5
 3 B     Increase Other                           2                   0.5
 4 A     Decrease Bisphenol A                     3                  -0.5
 5 B     Increase BPA                             5                   0.5
 6 B     Increase dioxin                          8                   0.5
 7 A     Increase bpa                             6                   2.5
 8 B     Increase Other                           5                   3.5
 9 B     Increase dioxin                          2                   0.5
10 A     Increase bpa                             1                   1.5
11 B     Increase BPA                             7                   1.5
12 B     Increase Other                           3                   2.5

• case_when() requires mutate() when working with dataframes/tibbles
• case_when() can recode entire values based on conditions (need quotes for conditions and new values)
  • remember case_when() needs .default = varaible to keep values that aren’t specified by conditions, otherwise will be NA

Note: you might see the recode() function, it only does some of what case_when() can do, so we skipped it, but it is in the extra slides at the end.

“Artwork by @allison_horst”. https://allisonhorst.com/

• stringr package has great functions for looking for specific parts of values especially filter() and str_detect() combined
• stringr also has other useful string functions like str_detect() (finding patterns in a column or vector), str_subset() (parsing text), str_replace() (replacing the first instance in values), str_replace_all() (replacing all instances in each value) and more!
• separate() can split columns into additional columns
• unite() can combine columns
• : can indicate when you want to start and end with columns next to one another

🏠 Class Website
💻 Lab. 📃 Day 5 Cheatsheet 📃 Posit’s stringr Cheatsheet

Image by Gerd Altmann from Pixabay

head(plastics_comb)

# A tibble: 6 × 5
  Foods Change   microplastic blood_level_start_nM blood_level_change_nM
  <chr> <chr>    <chr>                       <dbl>                 <dbl>
1 A     Increase Dioxin                          1                   2.5
2 B     Increase Dioxin                          7                   2.5
3 B     Increase Other                           2                   0.5
4 A     Decrease Bisphenol A                     3                  -0.5
5 B     Increase BPA                             5                   0.5
6 B     Increase dioxin                          8                   0.5

head(plastics_comb) %>% n_complete_row()

[1] 5 5 5 5 5 5

This is similar to case_when() but it can’t do as much.

# General Format - this is not code!
{data_input} %>%
  mutate({variable_to_fix_or_new} = recode({Variable_fixing}, {old_value} = {new_value},
                                       {another_old_value} = {new_value}))

plastics %>% 
  mutate(microplastic_recoded = recode(microplastic,  
                        "Bisphenol A" =  "BPA",
                                "bpa" = "BPA",
                             "dioxin" = "Dioxin") %>%
  count(microplastic, microplastic_recoded)

plastics %>% 
  mutate(microplastic_recoded = recode(microplastic,  
                        "Bisphenol A" =  "BPA",
                                "bpa" = "BPA",
                             "dioxin" = "Dioxin")) %>%
  count(microplastic, microplastic_recoded)

# A tibble: 6 × 3
  microplastic microplastic_recoded     n
  <chr>        <chr>                <int>
1 BPA          BPA                      2
2 Bisphenol A  BPA                      1
3 Dioxin       Dioxin                   2
4 Other        Other                    3
5 bpa          BPA                      2
6 dioxin       Dioxin                   2

Just use the same variable name to change the variable within mutate.

plastics %>% 
  mutate(microplastic = recode(microplastic,  
                        "Bisphenol A" =  "BPA",
                                "bpa" = "BPA",
                             "dioxin" = "Dioxin")) %>%
  count(microplastic)

# A tibble: 3 × 2
  microplastic     n
  <chr>        <int>
1 BPA              5
2 Dioxin           4
3 Other            3

ces <- read_csv(file = "https://daseh.org/data/CalEnviroScreen_data.csv")

Rows: 8035 Columns: 67
── Column specification ────────────────────────────────────────────────────────
Delimiter: ","
chr  (3): CaliforniaCounty, ApproxLocation, CES4.0PercRange
dbl (64): CensusTract, ZIP, Longitude, Latitude, CES4.0Score, CES4.0Percenti...

ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

set.seed(123)
ces %>% mutate(new_col_case_when = 
                 case_when(Longitude < -121 & Latitude > 37.8 ~ "Distract A",  
                           .default = "District B")) %>% 
                 select(Longitude, Latitude, new_col_case_when) %>%
                 slice_sample(n = 6)

# A tibble: 6 × 3
  Longitude Latitude new_col_case_when
      <dbl>    <dbl> <chr>            
1     -118.     34.1 District B       
2     -118.     34.2 District B       
3     -118.     34.1 District B       
4     -122.     37.9 Distract A       
5     -118.     33.7 District B       
6     -118.     33.9 District B       

ces %>% mutate(num_col_mutate = Longitude * Latitude) %>% pull(num_col_mutate) 

   [1] -4628.628 -4626.923 -4626.181 -4627.226 -4627.539 -4626.747 -4626.999
   [8] -4627.869 -4627.019 -4625.697 -4625.301 -4625.090 -4623.895 -4624.469
  [15] -4625.011 -4624.364 -4625.312 -4624.039 -4623.577 -4623.748 -4623.065
  [22] -4622.705 -4623.340 -4622.929 -4622.560 -4621.886 -4622.292 -4620.986
  [29] -4622.073 -4623.599 -4623.264 -4622.834 -4622.748 -4622.293 -4622.547
  [36] -4623.105 -4624.034 -4624.719 -4624.272 -4624.876 -4626.124 -4625.382
  [43] -4623.124 -4623.478 -4621.235 -4621.058 -4620.332 -4620.480 -4621.368
  [50] -4621.776 -4621.443 -4621.355 -4621.027 -4620.606 -4620.087 -4620.586
  [57] -4620.667 -4620.065 -4619.671 -4619.019 -4619.601 -4619.386 -4617.044
  [64] -4618.494 -4617.961 -4618.796 -4619.591 -4618.345 -4618.680 -4619.270
  [71] -4619.649 -4618.712 -4617.975 -4617.781 -4617.642 -4617.198 -4617.174
  [78] -4614.951 -4615.876 -4615.344 -4616.535 -4616.034 -4616.425 -4617.171
  [85] -4619.375 -4615.766 -4615.195 -4614.288 -4613.738 -4613.512 -4614.361
  [92] -4614.937 -4614.010 -4613.137 -4610.191 -4610.268 -4609.656 -4610.560
  [99] -4611.650 -4612.492 -4612.416 -4612.547 -4612.646 -4612.075 -4609.889
 [106] -4611.035 -4610.860 -4611.366 -4610.500 -4623.748 -4634.191 -4634.396
 [113] -4634.714 -4634.751 -4633.355 -4633.094 -4633.820 -4633.931 -4633.377
 [120] -4632.642 -4632.643 -4631.540 -4631.832 -4631.933 -4632.268 -4630.211
 [127] -4631.774 -4631.392 -4631.163 -4630.990 -4630.892 -4630.246 -4629.335
 [134] -4629.593 -4630.078 -4630.249 -4630.470 -4630.591 -4629.353 -4629.166
 [141] -4628.991 -4628.580 -4629.126 -4628.569 -4627.522 -4628.107 -4628.018
 [148] -4628.139 -4628.419 -4627.845 -4627.639 -4627.768 -4626.305 -4622.760
 [155] -4623.706 -4616.068 -4619.294 -4619.348 -4619.609 -4618.471 -4618.285
 [162] -4617.670 -4616.879 -4615.446 -4614.954 -4612.562 -4614.192 -4615.984
 [169] -4616.531 -4617.827 -4620.699 -4603.301 -4611.086 -4604.367 -4605.354
 [176] -4605.684 -4604.115 -4603.565 -4603.244 -4601.757 -4602.313 -4601.495
 [183] -4600.486 -4600.793 -4609.306 -4609.328 -4609.417 -4607.750 -4607.706
 [190] -4608.804 -4608.021 -4608.092 -4606.686 -4606.445 -4604.696 -4605.782
 [197] -4606.684 -4605.159 -4605.163 -4603.880 -4603.362 -4603.112 -4602.213
 [204] -4603.910 -4603.591 -4602.627 -4595.667 -4592.883 -4593.376 -4599.815
 [211] -4599.492 -4599.352 -4600.591 -4600.162 -4601.227 -4601.169 -4601.766
 [218] -4601.590 -4600.821 -4600.616 -4599.781 -4598.740 -4598.378 -4596.880
 [225] -4596.964 -4597.099 -4596.731 -4598.546 -4597.292 -4598.695 -4596.779
 [232] -4592.692 -4594.617 -4596.668 -4595.120 -4595.724 -4595.561 -4594.543
 [239] -4594.079 -4594.655 -4595.050 -4594.733 -4590.606 -4590.880 -4593.271
 [246] -4591.261 -4592.745 -4593.974 -4592.558 -4588.493 -4588.092 -4588.952
 [253] -4588.478 -4587.246 -4587.938 -4587.950 -4586.946 -4590.116 -4588.221
 [260] -4590.627 -4588.881 -4586.607 -4585.560 -4583.980 -4584.186 -4583.850
 [267] -4584.190 -4585.391 -4586.549 -4586.259 -4569.645 -4585.899 -4587.468
 [274] -4584.649 -4584.160 -4583.894 -4582.747 -4581.928 -4581.905 -4578.967
 [281] -4580.656 -4581.897 -4579.723 -4579.178 -4579.794 -4579.791 -4579.012
 [288] -4577.046 -4576.950 -4577.929 -4577.844 -4579.049 -4580.318 -4581.065
 [295] -4579.837 -4578.323 -4576.299 -4575.429 -4575.575 -4573.141 -4574.691
 [302] -4576.076 -4575.122 -4569.549 -4568.163 -4570.974 -4569.919 -4582.577
 [309] -4581.907 -4581.599 -4578.306 -4580.747 -4580.207 -4578.909 -4576.610
 [316] -4595.689 -4597.837 -4598.950 -4597.603 -4598.400 -4598.048 -4600.005
 [323] -4591.080 -4592.535 -4594.673 -4592.830 -4591.552 -4591.901 -4589.945
 [330] -4573.933 -4589.461 -4588.928 -4594.494 -4593.940 -4591.711 -4591.239
 [337] -4594.815 -4595.470 -4595.062 -4579.371 -4585.342 -4591.238 -4594.919
 [344] -4591.188 -4589.974 -4590.195 -4589.326 -4586.239 -4588.105 -4589.051
 [351] -4587.735 -4587.164 -4586.530 -4587.440 -4588.009 -4587.914 -4586.872
 [358] -4624.103 -4622.254 -4621.585 -4626.351 -4637.747 -4634.606 -4646.893
 [365] -4651.418 -4638.155 -4629.070 -4636.789 -4632.584 -4626.433 -4843.443
 [372] -4844.488 -4845.122 -4847.182 -4845.206 -4845.794 -4847.274 -4845.387
 [379] -4843.494 -4841.534 -4843.455 -4841.924 -4842.102 -4842.136 -4842.223
 [386] -4836.416 -4838.589 -4840.960 -4840.407 -4838.923 -4835.809 -4838.310
 [393] -4851.244 -4824.553 -4855.916 -4843.778 -4842.954 -4855.207 -4837.859
 [400] -4836.794 -4834.137 -4835.740 -4827.714 -4823.762 -4813.491 -4810.550
 [407] -4795.992 -4801.619 -4803.093 -4802.521 -4805.444 -4800.314 -4798.838
 [414] -4798.340 -4791.934 -4786.424 -4786.667 -4793.912 -4789.479 -4804.419
 [421] -4807.021 -4582.660 -4589.835 -4593.245 -4616.551 -4602.451 -4611.053
 [428] -4620.993 -4598.125 -4600.765 -4616.725 -4758.936 -4781.746 -4782.180
 [435] -4809.479 -4794.970 -4626.576 -4625.768 -4627.760 -4622.832 -4622.143
 [442] -4622.951 -4623.775 -4619.747 -4615.748 -4619.903 -4618.129 -4619.378
 [449] -4616.287 -4613.841 -4612.306 -4604.397 -4607.990 -4608.978 -4612.707
 [456] -4631.605 -4627.903 -4629.028 -4628.857 -4627.358 -4629.049 -4630.564
 [463] -4629.907 -4628.926 -4627.815 -4627.280 -4625.749 -4635.624 -4635.116
 [470] -4634.572 -4632.901 -4632.338 -4631.344 -4628.942 -4633.277 -4631.749
 [477] -4634.828 -4633.871 -4636.699 -4638.631 -4636.721 -4640.988 -4641.627
 [484] -4644.004 -4642.956 -4644.350 -4641.134 -4642.323 -4639.927 -4639.194
 [491] -4638.510 -4636.530 -4636.645 -4636.531 -4634.273 -4632.710 -4630.652
 [498] -4632.388 -4630.947 -4631.705 -4636.189 -4634.460 -4636.647 -4635.607
 [505] -4633.564 -4633.693 -4630.584 -4629.507 -4631.651 -4631.573 -4630.680
 [512] -4629.641 -4622.639 -4632.991 -4633.259 -4633.357 -4633.000 -4632.208
 [519] -4631.341 -4631.102 -4629.014 -4631.377 -4630.451 -4628.820 -4628.979
 [526] -4627.902 -4626.989 -4625.177 -4625.020 -4626.953 -4629.250 -4628.307
 [533] -4625.445 -4624.699 -4625.684 -4623.239 -4600.979 -4602.926 -4601.425
 [540] -4610.421 -4607.283 -4604.572 -4604.156 -4608.861 -4610.193 -4603.511
 [547] -4606.266 -4607.019 -4613.059 -4617.135 -4621.748 -4618.750 -4616.143
 [554] -4613.519 -4612.111 -4632.410 -4629.136 -4626.486 -4626.506 -4620.576
 [561] -4623.512 -4621.877 -4623.911 -4620.706 -4617.697 -4623.335 -4621.251
 [568] -4625.375 -4627.679 -4630.033 -4630.912 -4622.248 -4621.725 -4625.280
 [575] -4623.322 -4624.814 -4607.939 -4608.772 -4606.583 -4603.811 -4603.855
 [582] -4601.123 -4634.946 -4627.162 -4626.154 -4627.272 -4620.180 -4647.637
 [589] -4637.670 -4648.435 -4651.537 -4648.085 -4648.029 -4647.728 -4649.054
 [596] -4643.554 -4646.798 -4646.098 -4644.766 -4642.221 -4643.385 -4640.047
 [603] -4641.343 -4645.148 -4647.314 -4645.646 -4646.218 -4646.221 -4645.543
 [610] -4644.964 -4644.579 -4643.800 -4644.615 -4643.480 -4643.243 -4640.865
 [617] -4641.216 -4642.625 -4643.036 -4641.565 -4642.060 -4642.555 -4641.690
 [624] -4644.629 -4640.786 -4636.924 -4640.196 -4637.998 -4636.717 -4639.793
 [631] -4637.968 -4638.862 -4638.527 -4637.478 -4636.351 -4635.372 -4635.501
 [638] -4636.628 -4635.393 -4635.455 -4635.369 -4648.524 -4649.658 -5184.813
 [645] -5185.031 -5188.229 -5195.939 -5196.945 -5170.902 -5156.484 -4670.211
 [652] -4670.110 -4671.727 -4671.511 -4667.966 -4667.187 -4666.806 -4659.501
 [659] -4700.043 -4707.536 -4682.270 -4690.565 -4668.349 -4682.677 -4683.092
 [666] -4682.975 -4687.058 -4679.321 -4672.735 -4678.651 -4680.208 -4677.590
 [673] -4680.790 -4689.727 -4680.905 -4682.973 -4680.359 -4676.555 -4676.592
 [680] -4675.402 -4653.061 -4670.215 -4672.202 -4667.822 -4675.131 -4663.922
 [687] -4669.559 -4670.859 -4686.253 -4680.584 -4657.835 -4673.520 -4400.818
 [694] -4401.114 -4399.868 -4399.099 -4400.848 -4401.301 -4401.575 -4401.815
 [701] -4398.609 -4398.072 -4398.946 -4396.549 -4397.150 -4396.398 -4394.817
 [708] -4398.688 -4398.156 -4397.657 -4397.859 -4397.027 -4396.804 -4394.986
 [715] -4397.857 -4396.884 -4394.301 -4394.848 -4391.442 -4384.323 -4384.059
 [722] -4391.787 -4400.887 -4404.731 -4404.313 -4403.809 -4403.171 -4402.952
 [729] -4402.669 -4401.796 -4400.925 -4400.051 -4400.262 -4399.389 -4401.576
 [736] -4398.726 -4399.595 -4400.453 -4401.334 -4400.248 -4398.055 -4398.926
 [743] -4406.124 -4405.431 -4403.256 -4403.660 -4402.801 -4404.415 -4403.545
 [750] -4404.578 -4405.135 -4405.701 -4405.826 -4406.772 -4409.241 -4408.758
 [757] -4408.063 -4405.704 -4406.350 -4410.350 -4411.164 -4409.364 -4411.054
 [764] -4409.740 -4415.331 -4410.307 -4414.687 -4417.574 -4415.072 -4414.925
 [771] -4412.988 -4412.735 -4414.186 -4415.973 -4418.235 -4415.708 -4413.390
 [778] -4411.638 -4413.683 -4414.736 -4413.067 -4415.967 -4414.325 -4412.533
 [785] -4411.897 -4410.167 -4410.819 -4409.952 -4409.090 -4409.938 -4408.759
 [792] -4407.893 -4407.196 -4407.977 -4406.923 -4407.651 -4408.441 -4406.387
 [799] -4405.061 -4405.282 -4406.150 -4407.182 -4408.047 -4407.132 -4406.277
 [806] -4408.747 -4410.644 -4411.498 -4410.679 -4408.769 -4409.615 -4409.676
 [813] -4419.925 -4416.983 -4415.239 -4414.145 -4413.496 -4411.752 -4412.398
 [820] -4409.531 -4410.377 -4411.071 -4419.514 -4415.726 -4417.158 -4410.163
 [827] -4410.796 -4411.804 -4412.825 -4414.293 -4408.093 -4409.794 -4409.377
 [834] -4407.959 -4407.104 -4408.261 -4407.591 -4405.849 -4406.548 -4404.774
 [841] -4403.979 -4403.020 -4400.478 -4394.265 -4399.202 -4394.597 -4407.134
 [848] -4404.533 -4402.437 -4404.833 -4390.567 -4387.245 -4385.203 -4389.011
 [855] -4378.936 -4429.575 -4375.182 -4405.830 -4424.344 -4369.053 -4372.954
 [862] -4370.420 -4373.011 -4372.022 -4370.496 -4373.547 -4381.471 -4374.083
 [869] -4377.546 -4374.253 -4373.953 -4368.684 -4365.166 -4372.874 -4364.098
 [876] -4377.771 -4387.583 -4370.146 -4340.929 -4361.195 -4344.389 -4359.315
 [883] -4352.344 -4349.728 -4395.437 -4431.254 -4416.303 -4441.988 -4448.545
 [890] -4374.165 -4378.119 -4856.037 -4856.934 -4851.700 -4830.041 -4847.642
 [897] -4821.200 -5066.713 -5064.627 -5062.778 -5061.440 -5065.693 -5063.911
 [904] -5061.422 -5064.241 -5061.423 -5070.733 -5074.108 -5034.561 -5072.201
 [911] -5114.539 -5108.814 -5070.314 -5086.046 -5081.068 -5077.895 -5050.328
 [918] -5051.504 -5050.058 -5039.801 -5014.037 -5035.192 -5016.879 -5012.691
 [925] -4978.129 -4975.777 -5082.188 -3831.918 -3841.145 -3824.403 -3808.554
 [932] -3811.117 -3811.514 -3809.144 -3808.373 -3779.102 -3786.091 -3797.853
 [939] -3792.521 -3792.123 -3791.064 -3785.383 -3789.179 -3790.236 -3788.923
 [946] -3787.686 -3789.321 -3788.909 -3786.279 -3776.337 -3772.776 -3773.505
 [953] -3774.082 -3774.210 -3817.582 -3855.838 -3821.959 -3756.064 -4415.746
 [960] -4423.958 -4425.271 -4424.202 -4355.837 -4240.120 -4219.315 -4216.705
 [967] -4215.821 -4214.937 -4214.496 -4219.634 -4217.312 -4216.378 -4214.648
 [974] -4213.267 -4212.518 -4212.157 -4212.238 -4211.891 -4211.414 -4209.875
 [981] -4208.691 -4208.081 -4207.462 -4210.777 -4209.255 -4210.949 -4203.367
 [988] -4206.088 -4206.946 -4207.809 -4210.117 -4209.009 -4210.068 -4211.137
 [995] -4208.911 -4210.402 -4211.244 -4209.609 -4210.671 -4209.168 -4208.750
[1002] -4208.277 -4207.837 -4207.570 -4205.790 -4206.929 -4201.743 -4204.852
[1009] -4206.556 -4207.252 -4208.442 -4210.536 -4209.068 -4207.935 -4209.364
[1016] -4208.492 -4207.620 -4206.730 -4205.807 -4206.030 -4206.435 -4207.560
[1023] -4206.350 -4207.046 -4206.246 -4205.614 -4204.959 -4201.645 -4204.403
[1030] -4203.857 -4202.621 -4202.073 -4203.231 -4201.503 -4204.786 -4203.856
[1037] -4197.410 -4212.128 -4196.627 -4200.839 -4199.261 -4189.204 -4213.433
[1044] -4140.206 -4161.140 -4201.075 -4198.403 -4196.646 -4226.629 -4221.115
[1051] -4219.313 -4218.065 -4217.321 -4215.705 -4215.143 -4216.157 -4214.609
[1058] -4213.978 -4212.741 -4212.968 -4231.148 -4236.822 -4234.913 -4233.767
[1065] -4235.888 -4245.772 -4249.929 -4248.027 -4247.296 -4269.940 -4269.360
[1072] -4267.838 -4252.960 -4253.839 -4253.054 -4265.114 -4267.073 -4266.494
[1079] -4261.802 -4265.113 -4222.046 -4210.961 -4228.943 -4200.446 -4207.997
[1086] -4206.271 -4194.924 -4193.192 -4190.633 -4189.492 -4191.516 -4127.607
[1093] -4143.772 -4144.681 -4121.151 -4115.729 -4120.057 -4118.702 -4142.304
[1100] -4163.372 -4163.387 -4171.662 -4167.359 -4147.871 -4176.320 -4160.032
[1107] -4193.958 -4182.656 -4185.742 -4183.606 -4182.671 -4193.943 -4193.197
[1114] -4190.331 -4150.608 -4352.531 -4356.400 -4353.883 -4344.867 -4350.441
[1121] -4348.959 -4347.979 -4349.094 -4350.576 -4350.161 -4349.848 -4348.137
[1128] -4345.518 -4347.170 -4348.015 -4346.272 -4344.834 -4343.563 -4334.274
[1135] -4318.267 -4314.547 -4316.005 -4316.958 -4314.056 -4310.875 -4311.428
[1142] -4320.839 -4834.710 -4800.711 -4799.972 -4805.438 -4806.514 -4790.445
[1149] -4781.283 -4779.337 -4775.075 -4777.644 -4782.046 -4791.217 -4772.327
[1156] -4758.885 -4749.431 -4927.983 -4899.322 -4870.643 -4881.695 -4874.865
[1163] -4884.066 -4867.779 -4854.896 -4822.009 -4052.655 -4053.534 -4051.809
[1170] -4051.336 -4050.637 -4050.730 -4050.681 -4049.328 -4048.713 -4052.052
[1177] -4054.795 -4053.612 -4055.916 -4054.548 -4052.826 -4058.746 -4058.457
[1184] -4057.892 -4059.071 -4060.074 -4059.037 -4059.852 -4059.326 -4058.633
[1191] -4058.339 -4057.420 -4057.831 -4056.734 -4057.086 -4056.905 -4057.909
[1198] -4055.840 -4056.987 -4055.618 -4055.352 -4055.423 -4065.610 -4064.866
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[1212] -4063.626 -4064.065 -4066.978 -4064.274 -4066.855 -4064.072 -4064.658
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[7981] -4689.610 -4709.392 -4687.484 -4687.955 -4688.453 -4684.515 -4686.205
[7988] -4685.161 -4674.649 -4681.185 -4693.219 -4698.663 -4695.834 -4695.268
[7995] -4697.025 -4695.556 -4694.653 -4694.762 -4692.710 -4692.606 -4693.097
[8002] -4690.458 -4691.409 -4693.448 -4694.418 -4694.119 -4710.266 -4711.807
[8009] -4710.928 -4709.998 -4709.047 -4708.874 -4708.510 -4708.140 -4708.478
[8016] -4707.381 -4707.594 -4707.687 -4707.538 -4729.663 -4742.744 -4760.600
[8023] -4760.608 -4756.138 -4756.791 -4754.825 -4753.870 -4752.789 -4750.555
[8030] -4742.729 -4740.894 -4755.380 -4749.511 -4768.697 -4780.838

ces %>% mutate(num_new =  case_when(
  Longitude < -121 & Latitude > 37.8 ~  Longitude * Latitude),
  .defualt = NA) %>% 
  pull(num_new)

   [1] -4628.628 -4626.923 -4626.181 -4627.226 -4627.539 -4626.747 -4626.999
   [8] -4627.869 -4627.019 -4625.697 -4625.301 -4625.090 -4623.895 -4624.469
  [15] -4625.011 -4624.364 -4625.312 -4624.039 -4623.577 -4623.748 -4623.065
  [22] -4622.705 -4623.340 -4622.929 -4622.560 -4621.886 -4622.292        NA
  [29] -4622.073 -4623.599 -4623.264 -4622.834 -4622.748 -4622.293 -4622.547
  [36] -4623.105 -4624.034 -4624.719 -4624.272 -4624.876 -4626.124 -4625.382
  [43] -4623.124 -4623.478 -4621.235 -4621.058 -4620.332 -4620.480 -4621.368
  [50] -4621.776 -4621.443 -4621.355        NA        NA        NA        NA
  [57] -4620.667        NA        NA        NA        NA        NA        NA
  [64]        NA        NA        NA        NA        NA        NA        NA
  [71] -4619.649        NA        NA        NA        NA        NA        NA
  [78]        NA        NA        NA        NA        NA        NA        NA
  [85] -4619.375        NA        NA        NA        NA        NA        NA
  [92]        NA        NA        NA        NA        NA        NA        NA
  [99]        NA        NA        NA        NA        NA        NA        NA
 [106]        NA        NA        NA        NA -4623.748 -4634.191 -4634.396
 [113] -4634.714 -4634.751 -4633.355 -4633.094 -4633.820 -4633.931 -4633.377
 [120] -4632.642 -4632.643 -4631.540 -4631.832 -4631.933 -4632.268 -4630.211
 [127] -4631.774 -4631.392 -4631.163 -4630.990 -4630.892 -4630.246 -4629.335
 [134] -4629.593 -4630.078 -4630.249 -4630.470 -4630.591 -4629.353 -4629.166
 [141] -4628.991 -4628.580 -4629.126 -4628.569 -4627.522 -4628.107 -4628.018
 [148] -4628.139 -4628.419 -4627.845 -4627.639 -4627.768 -4626.305 -4622.760
 [155] -4623.706        NA        NA        NA        NA        NA        NA
 [162]        NA        NA        NA        NA        NA        NA        NA
 [169]        NA        NA        NA        NA        NA        NA        NA
 [176]        NA        NA        NA        NA        NA        NA        NA
 [183]        NA        NA        NA        NA        NA        NA        NA
 [190]        NA        NA        NA        NA        NA        NA        NA
 [197]        NA        NA        NA        NA        NA        NA        NA
 [204]        NA        NA        NA        NA        NA        NA        NA
 [211]        NA        NA        NA        NA        NA        NA        NA
 [218]        NA        NA        NA        NA        NA        NA        NA
 [225]        NA        NA        NA        NA        NA        NA        NA
 [232]        NA        NA        NA        NA        NA        NA        NA
 [239]        NA        NA        NA        NA        NA        NA        NA
 [246]        NA        NA        NA        NA        NA        NA        NA
 [253]        NA        NA        NA        NA        NA        NA        NA
 [260]        NA        NA        NA        NA        NA        NA        NA
 [267]        NA        NA        NA        NA        NA        NA        NA
 [274]        NA        NA        NA        NA        NA        NA        NA
 [281]        NA        NA        NA        NA        NA        NA        NA
 [288]        NA        NA        NA        NA        NA        NA        NA
 [295]        NA        NA        NA        NA        NA        NA        NA
 [302]        NA        NA        NA        NA        NA        NA        NA
 [309]        NA        NA        NA        NA        NA        NA        NA
 [316]        NA        NA        NA        NA        NA        NA        NA
 [323]        NA        NA        NA        NA        NA        NA        NA
 [330]        NA        NA        NA        NA        NA        NA        NA
 [337]        NA        NA        NA        NA        NA        NA        NA
 [344]        NA        NA        NA        NA        NA        NA        NA
 [351]        NA        NA        NA        NA        NA        NA        NA
 [358] -4624.103        NA        NA        NA        NA        NA        NA
 [365]        NA        NA        NA        NA        NA        NA -4843.443
 [372] -4844.488 -4845.122 -4847.182 -4845.206 -4845.794 -4847.274 -4845.387
 [379] -4843.494 -4841.534 -4843.455 -4841.924 -4842.102 -4842.136 -4842.223
 [386] -4836.416 -4838.589 -4840.960 -4840.407 -4838.923 -4835.809 -4838.310
 [393] -4851.244 -4824.553 -4855.916 -4843.778 -4842.954 -4855.207 -4837.859
 [400] -4836.794 -4834.137 -4835.740 -4827.714 -4823.762 -4813.491 -4810.550
 [407] -4795.992 -4801.619 -4803.093 -4802.521 -4805.444 -4800.314 -4798.838
 [414] -4798.340 -4791.934 -4786.424 -4786.667 -4793.912 -4789.479 -4804.419
 [421] -4807.021        NA        NA        NA        NA        NA        NA
 [428]        NA        NA        NA        NA -4758.936 -4781.746 -4782.180
 [435] -4809.479 -4794.970 -4626.576 -4625.768 -4627.760 -4622.832 -4622.143
 [442] -4622.951 -4623.775 -4619.747 -4615.748 -4619.903 -4618.129 -4619.378
 [449] -4616.287 -4613.841 -4612.306 -4604.397 -4607.990 -4608.978 -4612.707
 [456] -4631.605 -4627.903 -4629.028 -4628.857 -4627.358 -4629.049 -4630.564
 [463] -4629.907 -4628.926 -4627.815 -4627.280 -4625.749 -4635.624 -4635.116
 [470] -4634.572 -4632.901 -4632.338 -4631.344 -4628.942 -4633.277 -4631.749
 [477] -4634.828 -4633.871 -4636.699 -4638.631 -4636.721 -4640.988 -4641.627
 [484] -4644.004 -4642.956 -4644.350 -4641.134 -4642.323 -4639.927 -4639.194
 [491] -4638.510 -4636.530 -4636.645 -4636.531 -4634.273 -4632.710 -4630.652
 [498] -4632.388 -4630.947 -4631.705 -4636.189 -4634.460 -4636.647 -4635.607
 [505] -4633.564 -4633.693 -4630.584 -4629.507 -4631.651 -4631.573 -4630.680
 [512] -4629.641 -4622.639 -4632.991 -4633.259 -4633.357 -4633.000 -4632.208
 [519] -4631.341 -4631.102 -4629.014 -4631.377 -4630.451 -4628.820 -4628.979
 [526] -4627.902 -4626.989 -4625.177 -4625.020 -4626.953 -4629.250 -4628.307
 [533] -4625.445 -4624.699 -4625.684 -4623.239        NA        NA        NA
 [540]        NA        NA        NA        NA        NA        NA        NA
 [547]        NA        NA -4613.059 -4617.135 -4621.748 -4618.750 -4616.143
 [554] -4613.519 -4612.111 -4632.410 -4629.136 -4626.486 -4626.506 -4620.576
 [561] -4623.512 -4621.877 -4623.911 -4620.706 -4617.697 -4623.335 -4621.251
 [568] -4625.375 -4627.679 -4630.033 -4630.912 -4622.248 -4621.725 -4625.280
 [575] -4623.322 -4624.814 -4607.939 -4608.772        NA        NA        NA
 [582]        NA -4634.946 -4627.162 -4626.154 -4627.272 -4620.180 -4647.637
 [589] -4637.670 -4648.435 -4651.537 -4648.085 -4648.029 -4647.728 -4649.054
 [596] -4643.554 -4646.798 -4646.098 -4644.766 -4642.221 -4643.385 -4640.047
 [603] -4641.343 -4645.148 -4647.314 -4645.646 -4646.218 -4646.221 -4645.543
 [610] -4644.964 -4644.579 -4643.800 -4644.615 -4643.480 -4643.243 -4640.865
 [617] -4641.216 -4642.625 -4643.036 -4641.565 -4642.060 -4642.555 -4641.690
 [624] -4644.629 -4640.786 -4636.924 -4640.196 -4637.998 -4636.717 -4639.793
 [631] -4637.968 -4638.862 -4638.527 -4637.478 -4636.351 -4635.372 -4635.501
 [638] -4636.628 -4635.393 -4635.455 -4635.369 -4648.524 -4649.658 -5184.813
 [645] -5185.031 -5188.229 -5195.939 -5196.945 -5170.902 -5156.484        NA
 [652]        NA        NA        NA        NA        NA        NA        NA
 [659] -4700.043        NA        NA -4690.565        NA -4682.677 -4683.092
 [666] -4682.975 -4687.058        NA        NA -4678.651 -4680.208        NA
 [673]        NA        NA        NA        NA        NA        NA        NA
 [680]        NA        NA        NA        NA        NA        NA        NA
 [687]        NA        NA -4686.253 -4680.584        NA        NA        NA
 [694]        NA        NA        NA        NA        NA        NA        NA
 [701]        NA        NA        NA        NA        NA        NA        NA
 [708]        NA        NA        NA        NA        NA        NA        NA
 [715]        NA        NA        NA        NA        NA        NA        NA
 [722]        NA        NA        NA        NA        NA        NA        NA
 [729]        NA        NA        NA        NA        NA        NA        NA
 [736]        NA        NA        NA        NA        NA        NA        NA
 [743]        NA        NA        NA        NA        NA        NA        NA
 [750]        NA        NA        NA        NA        NA        NA        NA
 [757]        NA        NA        NA        NA        NA        NA        NA
 [764]        NA        NA        NA        NA        NA        NA        NA
 [771]        NA        NA        NA        NA        NA        NA        NA
 [778]        NA        NA        NA        NA        NA        NA        NA
 [785]        NA        NA        NA        NA        NA        NA        NA
 [792]        NA        NA        NA        NA        NA        NA        NA
 [799]        NA        NA        NA        NA        NA        NA        NA
 [806]        NA        NA        NA        NA        NA        NA        NA
 [813]        NA        NA        NA        NA        NA        NA        NA
 [820]        NA        NA        NA        NA        NA        NA        NA
 [827]        NA        NA        NA        NA        NA        NA        NA
 [834]        NA        NA        NA        NA        NA        NA        NA
 [841]        NA        NA        NA        NA        NA        NA        NA
 [848]        NA        NA        NA        NA        NA        NA        NA
 [855]        NA        NA        NA        NA        NA        NA        NA
 [862]        NA        NA        NA        NA        NA        NA        NA
 [869]        NA        NA        NA        NA        NA        NA        NA
 [876]        NA        NA        NA        NA        NA        NA        NA
 [883]        NA        NA        NA        NA        NA        NA        NA
 [890]        NA        NA -4856.037 -4856.934 -4851.700 -4830.041 -4847.642
 [897] -4821.200 -5066.713 -5064.627 -5062.778 -5061.440 -5065.693 -5063.911
 [904] -5061.422 -5064.241 -5061.423 -5070.733 -5074.108 -5034.561 -5072.201
 [911] -5114.539 -5108.814 -5070.314 -5086.046 -5081.068 -5077.895 -5050.328
 [918] -5051.504 -5050.058 -5039.801 -5014.037 -5035.192 -5016.879 -5012.691
 [925] -4978.129 -4975.777 -5082.188        NA        NA        NA        NA
 [932]        NA        NA        NA        NA        NA        NA        NA
 [939]        NA        NA        NA        NA        NA        NA        NA
 [946]        NA        NA        NA        NA        NA        NA        NA
 [953]        NA        NA        NA        NA        NA        NA        NA
 [960]        NA        NA        NA        NA        NA        NA        NA
 [967]        NA        NA        NA        NA        NA        NA        NA
 [974]        NA        NA        NA        NA        NA        NA        NA
 [981]        NA        NA        NA        NA        NA        NA        NA
 [988]        NA        NA        NA        NA        NA        NA        NA
 [995]        NA        NA        NA        NA        NA        NA        NA
[1002]        NA        NA        NA        NA        NA        NA        NA
[1009]        NA        NA        NA        NA        NA        NA        NA
[1016]        NA        NA        NA        NA        NA        NA        NA
[1023]        NA        NA        NA        NA        NA        NA        NA
[1030]        NA        NA        NA        NA        NA        NA        NA
[1037]        NA        NA        NA        NA        NA        NA        NA
[1044]        NA        NA        NA        NA        NA        NA        NA
[1051]        NA        NA        NA        NA        NA        NA        NA
[1058]        NA        NA        NA        NA        NA        NA        NA
[1065]        NA        NA        NA        NA        NA        NA        NA
[1072]        NA        NA        NA        NA        NA        NA        NA
[1079]        NA        NA        NA        NA        NA        NA        NA
[1086]        NA        NA        NA        NA        NA        NA        NA
[1093]        NA        NA        NA        NA        NA        NA        NA
[1100]        NA        NA        NA        NA        NA        NA        NA
[1107]        NA        NA        NA        NA        NA        NA        NA
[1114]        NA        NA        NA        NA        NA        NA        NA
[1121]        NA        NA        NA        NA        NA        NA        NA
[1128]        NA        NA        NA        NA        NA        NA        NA
[1135]        NA        NA        NA        NA        NA        NA        NA
[1142]        NA -4834.710 -4800.711 -4799.972 -4805.438 -4806.514 -4790.445
[1149] -4781.283 -4779.337 -4775.075 -4777.644 -4782.046 -4791.217 -4772.327
[1156] -4758.885 -4749.431        NA        NA        NA        NA        NA
[1163]        NA        NA        NA        NA        NA        NA        NA
[1170]        NA        NA        NA        NA        NA        NA        NA
[1177]        NA        NA        NA        NA        NA        NA        NA
[1184]        NA        NA        NA        NA        NA        NA        NA
[1191]        NA        NA        NA        NA        NA        NA        NA
[1198]        NA        NA        NA        NA        NA        NA        NA
[1205]        NA        NA        NA        NA        NA        NA        NA
[1212]        NA        NA        NA        NA        NA        NA        NA
[1219]        NA        NA        NA        NA        NA        NA        NA
[1226]        NA        NA        NA        NA        NA        NA        NA
[1233]        NA        NA        NA        NA        NA        NA        NA
[1240]        NA        NA        NA        NA        NA        NA        NA
[1247]        NA        NA        NA        NA        NA        NA        NA
[1254]        NA        NA        NA        NA        NA        NA        NA
[1261]        NA        NA        NA        NA        NA        NA        NA
[1268]        NA        NA        NA        NA        NA        NA        NA
[1275]        NA        NA        NA        NA        NA        NA        NA
[1282]        NA        NA        NA        NA        NA        NA        NA
[1289]        NA        NA        NA        NA        NA        NA        NA
[1296]        NA        NA        NA        NA        NA        NA        NA
[1303]        NA        NA        NA        NA        NA        NA        NA
[1310]        NA        NA        NA        NA        NA        NA        NA
[1317]        NA        NA        NA        NA        NA        NA        NA
[1324]        NA        NA        NA        NA        NA        NA        NA
[1331]        NA        NA        NA        NA        NA        NA        NA
[1338]        NA        NA        NA        NA        NA        NA        NA
[1345]        NA        NA        NA        NA        NA        NA        NA
[1352]        NA        NA        NA        NA        NA        NA        NA
[1359]        NA        NA        NA        NA        NA        NA        NA
[1366]        NA        NA        NA        NA        NA        NA        NA
[1373]        NA        NA        NA        NA        NA        NA        NA
[1380]        NA        NA        NA        NA        NA        NA        NA
[1387]        NA        NA        NA        NA        NA        NA        NA
[1394]        NA        NA        NA        NA        NA        NA        NA
[1401]        NA        NA        NA        NA        NA        NA        NA
[1408]        NA        NA        NA        NA        NA        NA        NA
[1415]        NA        NA        NA        NA        NA        NA        NA
[1422]        NA        NA        NA        NA        NA        NA        NA
[1429]        NA        NA        NA        NA        NA        NA        NA
[1436]        NA        NA        NA        NA        NA        NA        NA
[1443]        NA        NA        NA        NA        NA        NA        NA
[1450]        NA        NA        NA        NA        NA        NA        NA
[1457]        NA        NA        NA        NA        NA        NA        NA
[1464]        NA        NA        NA        NA        NA        NA        NA
[1471]        NA        NA        NA        NA        NA        NA        NA
[1478]        NA        NA        NA        NA        NA        NA        NA
[1485]        NA        NA        NA        NA        NA        NA        NA
[1492]        NA        NA        NA        NA        NA        NA        NA
[1499]        NA        NA        NA        NA        NA        NA        NA
[1506]        NA        NA        NA        NA        NA        NA        NA
[1513]        NA        NA        NA        NA        NA        NA        NA
[1520]        NA        NA        NA        NA        NA        NA        NA
[1527]        NA        NA        NA        NA        NA        NA        NA
[1534]        NA        NA        NA        NA        NA        NA        NA
[1541]        NA        NA        NA        NA        NA        NA        NA
[1548]        NA        NA        NA        NA        NA        NA        NA
[1555]        NA        NA        NA        NA        NA        NA        NA
[1562]        NA        NA        NA        NA        NA        NA        NA
[1569]        NA        NA        NA        NA        NA        NA        NA
[1576]        NA        NA        NA        NA        NA        NA        NA
[1583]        NA        NA        NA        NA        NA        NA        NA
[1590]        NA        NA        NA        NA        NA        NA        NA
[1597]        NA        NA        NA        NA        NA        NA        NA
[1604]        NA        NA        NA        NA        NA        NA        NA
[1611]        NA        NA        NA        NA        NA        NA        NA
[1618]        NA        NA        NA        NA        NA        NA        NA
[1625]        NA        NA        NA        NA        NA        NA        NA
[1632]        NA        NA        NA        NA        NA        NA        NA
[1639]        NA        NA        NA        NA        NA        NA        NA
[1646]        NA        NA        NA        NA        NA        NA        NA
[1653]        NA        NA        NA        NA        NA        NA        NA
[1660]        NA        NA        NA        NA        NA        NA        NA
[1667]        NA        NA        NA        NA        NA        NA        NA
[1674]        NA        NA        NA        NA        NA        NA        NA
[1681]        NA        NA        NA        NA        NA        NA        NA
[1688]        NA        NA        NA        NA        NA        NA        NA
[1695]        NA        NA        NA        NA        NA        NA        NA
[1702]        NA        NA        NA        NA        NA        NA        NA
[1709]        NA        NA        NA        NA        NA        NA        NA
[1716]        NA        NA        NA        NA        NA        NA        NA
[1723]        NA        NA        NA        NA        NA        NA        NA
[1730]        NA        NA        NA        NA        NA        NA        NA
[1737]        NA        NA        NA        NA        NA        NA        NA
[1744]        NA        NA        NA        NA        NA        NA        NA
[1751]        NA        NA        NA        NA        NA        NA        NA
[1758]        NA        NA        NA        NA        NA        NA        NA
[1765]        NA        NA        NA        NA        NA        NA        NA
[1772]        NA        NA        NA        NA        NA        NA        NA
[1779]        NA        NA        NA        NA        NA        NA        NA
[1786]        NA        NA        NA        NA        NA        NA        NA
[1793]        NA        NA        NA        NA        NA        NA        NA
[1800]        NA        NA        NA        NA        NA        NA        NA
[1807]        NA        NA        NA        NA        NA        NA        NA
[1814]        NA        NA        NA        NA        NA        NA        NA
[1821]        NA        NA        NA        NA        NA        NA        NA
[1828]        NA        NA        NA        NA        NA        NA        NA
[1835]        NA        NA        NA        NA        NA        NA        NA
[1842]        NA        NA        NA        NA        NA        NA        NA
[1849]        NA        NA        NA        NA        NA        NA        NA
[1856]        NA        NA        NA        NA        NA        NA        NA
[1863]        NA        NA        NA        NA        NA        NA        NA
[1870]        NA        NA        NA        NA        NA        NA        NA
[1877]        NA        NA        NA        NA        NA        NA        NA
[1884]        NA        NA        NA        NA        NA        NA        NA
[1891]        NA        NA        NA        NA        NA        NA        NA
[1898]        NA        NA        NA        NA        NA        NA        NA
[1905]        NA        NA        NA        NA        NA        NA        NA
[1912]        NA        NA        NA        NA        NA        NA        NA
[1919]        NA        NA        NA        NA        NA        NA        NA
[1926]        NA        NA        NA        NA        NA        NA        NA
[1933]        NA        NA        NA        NA        NA        NA        NA
[1940]        NA        NA        NA        NA        NA        NA        NA
[1947]        NA        NA        NA        NA        NA        NA        NA
[1954]        NA        NA        NA        NA        NA        NA        NA
[1961]        NA        NA        NA        NA        NA        NA        NA
[1968]        NA        NA        NA        NA        NA        NA        NA
[1975]        NA        NA        NA        NA        NA        NA        NA
[1982]        NA        NA        NA        NA        NA        NA        NA
[1989]        NA        NA        NA        NA        NA        NA        NA
[1996]        NA        NA        NA        NA        NA        NA        NA
[2003]        NA        NA        NA        NA        NA        NA        NA
[2010]        NA        NA        NA        NA        NA        NA        NA
[2017]        NA        NA        NA        NA        NA        NA        NA
[2024]        NA        NA        NA        NA        NA        NA        NA
[2031]        NA        NA        NA        NA        NA        NA        NA
[2038]        NA        NA        NA        NA        NA        NA        NA
[2045]        NA        NA        NA        NA        NA        NA        NA
[2052]        NA        NA        NA        NA        NA        NA        NA
[2059]        NA        NA        NA        NA        NA        NA        NA
[2066]        NA        NA        NA        NA        NA        NA        NA
[2073]        NA        NA        NA        NA        NA        NA        NA
[2080]        NA        NA        NA        NA        NA        NA        NA
[2087]        NA        NA        NA        NA        NA        NA        NA
[2094]        NA        NA        NA        NA        NA        NA        NA
[2101]        NA        NA        NA        NA        NA        NA        NA
[2108]        NA        NA        NA        NA        NA        NA        NA
[2115]        NA        NA        NA        NA        NA        NA        NA
[2122]        NA        NA        NA        NA        NA        NA        NA
[2129]        NA        NA        NA        NA        NA        NA        NA
[2136]        NA        NA        NA        NA        NA        NA        NA
[2143]        NA        NA        NA        NA        NA        NA        NA
[2150]        NA        NA        NA        NA        NA        NA        NA
[2157]        NA        NA        NA        NA        NA        NA        NA
[2164]        NA        NA        NA        NA        NA        NA        NA
[2171]        NA        NA        NA        NA        NA        NA        NA
[2178]        NA        NA        NA        NA        NA        NA        NA
[2185]        NA        NA        NA        NA        NA        NA        NA
[2192]        NA        NA        NA        NA        NA        NA        NA
[2199]        NA        NA        NA        NA        NA        NA        NA
[2206]        NA        NA        NA        NA        NA        NA        NA
[2213]        NA        NA        NA        NA        NA        NA        NA
[2220]        NA        NA        NA        NA        NA        NA        NA
[2227]        NA        NA        NA        NA        NA        NA        NA
[2234]        NA        NA        NA        NA        NA        NA        NA
[2241]        NA        NA        NA        NA        NA        NA        NA
[2248]        NA        NA        NA        NA        NA        NA        NA
[2255]        NA        NA        NA        NA        NA        NA        NA
[2262]        NA        NA        NA        NA        NA        NA        NA
[2269]        NA        NA        NA        NA        NA        NA        NA
[2276]        NA        NA        NA        NA        NA        NA        NA
[2283]        NA        NA        NA        NA        NA        NA        NA
[2290]        NA        NA        NA        NA        NA        NA        NA
[2297]        NA        NA        NA        NA        NA        NA        NA
[2304]        NA        NA        NA        NA        NA        NA        NA
[2311]        NA        NA        NA        NA        NA        NA        NA
[2318]        NA        NA        NA        NA        NA        NA        NA
[2325]        NA        NA        NA        NA        NA        NA        NA
[2332]        NA        NA        NA        NA        NA        NA        NA
[2339]        NA        NA        NA        NA        NA        NA        NA
[2346]        NA        NA        NA        NA        NA        NA        NA
[2353]        NA        NA        NA        NA        NA        NA        NA
[2360]        NA        NA        NA        NA        NA        NA        NA
[2367]        NA        NA        NA        NA        NA        NA        NA
[2374]        NA        NA        NA        NA        NA        NA        NA
[2381]        NA        NA        NA        NA        NA        NA        NA
[2388]        NA        NA        NA        NA        NA        NA        NA
[2395]        NA        NA        NA        NA        NA        NA        NA
[2402]        NA        NA        NA        NA        NA        NA        NA
[2409]        NA        NA        NA        NA        NA        NA        NA
[2416]        NA        NA        NA        NA        NA        NA        NA
[2423]        NA        NA        NA        NA        NA        NA        NA
[2430]        NA        NA        NA        NA        NA        NA        NA
[2437]        NA        NA        NA        NA        NA        NA        NA
[2444]        NA        NA        NA        NA        NA        NA        NA
[2451]        NA        NA        NA        NA        NA        NA        NA
[2458]        NA        NA        NA        NA        NA        NA        NA
[2465]        NA        NA        NA        NA        NA        NA        NA
[2472]        NA        NA        NA        NA        NA        NA        NA
[2479]        NA        NA        NA        NA        NA        NA        NA
[2486]        NA        NA        NA        NA        NA        NA        NA
[2493]        NA        NA        NA        NA        NA        NA        NA
[2500]        NA        NA        NA        NA        NA        NA        NA
[2507]        NA        NA        NA        NA        NA        NA        NA
[2514]        NA        NA        NA        NA        NA        NA        NA
[2521]        NA        NA        NA        NA        NA        NA        NA
[2528]        NA        NA        NA        NA        NA        NA        NA
[2535]        NA        NA        NA        NA        NA        NA        NA
[2542]        NA        NA        NA        NA        NA        NA        NA
[2549]        NA        NA        NA        NA        NA        NA        NA
[2556]        NA        NA        NA        NA        NA        NA        NA
[2563]        NA        NA        NA        NA        NA        NA        NA
[2570]        NA        NA        NA        NA        NA        NA        NA
[2577]        NA        NA        NA        NA        NA        NA        NA
[2584]        NA        NA        NA        NA        NA        NA        NA
[2591]        NA        NA        NA        NA        NA        NA        NA
[2598]        NA        NA        NA        NA        NA        NA        NA
[2605]        NA        NA        NA        NA        NA        NA        NA
[2612]        NA        NA        NA        NA        NA        NA        NA
[2619]        NA        NA        NA        NA        NA        NA        NA
[2626]        NA        NA        NA        NA        NA        NA        NA
[2633]        NA        NA        NA        NA        NA        NA        NA
[2640]        NA        NA        NA        NA        NA        NA        NA
[2647]        NA        NA        NA        NA        NA        NA        NA
[2654]        NA        NA        NA        NA        NA        NA        NA
[2661]        NA        NA        NA        NA        NA        NA        NA
[2668]        NA        NA        NA        NA        NA        NA        NA
[2675]        NA        NA        NA        NA        NA        NA        NA
[2682]        NA        NA        NA        NA        NA        NA        NA
[2689]        NA        NA        NA        NA        NA        NA        NA
[2696]        NA        NA        NA        NA        NA        NA        NA
[2703]        NA        NA        NA        NA        NA        NA        NA
[2710]        NA        NA        NA        NA        NA        NA        NA
[2717]        NA        NA        NA        NA        NA        NA        NA
[2724]        NA        NA        NA        NA        NA        NA        NA
[2731]        NA        NA        NA        NA        NA        NA        NA
[2738]        NA        NA        NA        NA        NA        NA        NA
[2745]        NA        NA        NA        NA        NA        NA        NA
[2752]        NA        NA        NA        NA        NA        NA        NA
[2759]        NA        NA        NA        NA        NA        NA        NA
[2766]        NA        NA        NA        NA        NA        NA        NA
[2773]        NA        NA        NA        NA        NA        NA        NA
[2780]        NA        NA        NA        NA        NA        NA        NA
[2787]        NA        NA        NA        NA        NA        NA        NA
[2794]        NA        NA        NA        NA        NA        NA        NA
[2801]        NA        NA        NA        NA        NA        NA        NA
[2808]        NA        NA        NA        NA        NA        NA        NA
[2815]        NA        NA        NA        NA        NA        NA        NA
[2822]        NA        NA        NA        NA        NA        NA        NA
[2829]        NA        NA        NA        NA        NA        NA        NA
[2836]        NA        NA        NA        NA        NA        NA        NA
[2843]        NA        NA        NA        NA        NA        NA        NA
[2850]        NA        NA        NA        NA        NA        NA        NA
[2857]        NA        NA        NA        NA        NA        NA        NA
[2864]        NA        NA        NA        NA        NA        NA        NA
[2871]        NA        NA        NA        NA        NA        NA        NA
[2878]        NA        NA        NA        NA        NA        NA        NA
[2885]        NA        NA        NA        NA        NA        NA        NA
[2892]        NA        NA        NA        NA        NA        NA        NA
[2899]        NA        NA        NA        NA        NA        NA        NA
[2906]        NA        NA        NA        NA        NA        NA        NA
[2913]        NA        NA        NA        NA        NA        NA        NA
[2920]        NA        NA        NA        NA        NA        NA        NA
[2927]        NA        NA        NA        NA        NA        NA        NA
[2934]        NA        NA        NA        NA        NA        NA        NA
[2941]        NA        NA        NA        NA        NA        NA        NA
[2948]        NA        NA        NA        NA        NA        NA        NA
[2955]        NA        NA        NA        NA        NA        NA        NA
[2962]        NA        NA        NA        NA        NA        NA        NA
[2969]        NA        NA        NA        NA        NA        NA        NA
[2976]        NA        NA        NA        NA        NA        NA        NA
[2983]        NA        NA        NA        NA        NA        NA        NA
[2990]        NA        NA        NA        NA        NA        NA        NA
[2997]        NA        NA        NA        NA        NA        NA        NA
[3004]        NA        NA        NA        NA        NA        NA        NA
[3011]        NA        NA        NA        NA        NA        NA        NA
[3018]        NA        NA        NA        NA        NA        NA        NA
[3025]        NA        NA        NA        NA        NA        NA        NA
[3032]        NA        NA        NA        NA        NA        NA        NA
[3039]        NA        NA        NA        NA        NA        NA        NA
[3046]        NA        NA        NA        NA        NA        NA        NA
[3053]        NA        NA        NA        NA        NA        NA        NA
[3060]        NA        NA        NA        NA        NA        NA        NA
[3067]        NA        NA        NA        NA        NA        NA        NA
[3074]        NA        NA        NA        NA        NA        NA        NA
[3081]        NA        NA        NA        NA        NA        NA        NA
[3088]        NA        NA        NA        NA        NA        NA        NA
[3095]        NA        NA        NA        NA        NA        NA        NA
[3102]        NA        NA        NA        NA        NA        NA        NA
[3109]        NA        NA        NA        NA        NA        NA        NA
[3116]        NA        NA        NA        NA        NA        NA        NA
[3123]        NA        NA        NA        NA        NA        NA        NA
[3130]        NA        NA        NA        NA        NA        NA        NA
[3137]        NA        NA        NA        NA        NA        NA        NA
[3144]        NA        NA        NA        NA        NA        NA        NA
[3151]        NA        NA        NA        NA        NA        NA        NA
[3158]        NA        NA        NA        NA        NA        NA        NA
[3165]        NA        NA        NA        NA        NA        NA        NA
[3172]        NA        NA        NA        NA        NA        NA        NA
[3179]        NA        NA        NA        NA        NA        NA        NA
[3186]        NA        NA        NA        NA        NA        NA        NA
[3193]        NA        NA        NA        NA        NA        NA        NA
[3200]        NA        NA        NA        NA        NA        NA        NA
[3207]        NA        NA        NA        NA        NA        NA        NA
[3214]        NA        NA        NA        NA        NA        NA        NA
[3221]        NA        NA        NA        NA        NA        NA        NA
[3228]        NA        NA        NA        NA        NA        NA        NA
[3235]        NA        NA        NA        NA        NA        NA        NA
[3242]        NA        NA        NA        NA        NA        NA        NA
[3249]        NA        NA        NA        NA        NA        NA        NA
[3256]        NA        NA        NA        NA        NA        NA        NA
[3263]        NA        NA        NA        NA        NA        NA        NA
[3270]        NA        NA        NA        NA        NA        NA        NA
[3277]        NA        NA        NA        NA        NA        NA        NA
[3284]        NA        NA        NA        NA        NA        NA        NA
[3291]        NA        NA        NA        NA        NA        NA        NA
[3298]        NA        NA        NA        NA        NA        NA        NA
[3305]        NA        NA        NA        NA        NA        NA        NA
[3312]        NA        NA        NA        NA        NA        NA        NA
[3319]        NA        NA        NA        NA        NA        NA        NA
[3326]        NA        NA        NA        NA        NA        NA        NA
[3333]        NA        NA        NA        NA        NA        NA        NA
[3340]        NA        NA        NA        NA        NA        NA        NA
[3347]        NA        NA        NA        NA        NA        NA        NA
[3354]        NA        NA        NA        NA        NA        NA        NA
[3361]        NA        NA        NA        NA        NA        NA        NA
[3368]        NA        NA        NA        NA        NA        NA        NA
[3375]        NA        NA        NA        NA        NA        NA        NA
[3382]        NA        NA        NA        NA        NA        NA        NA
[3389]        NA        NA        NA        NA        NA        NA        NA
[3396]        NA        NA        NA        NA        NA        NA        NA
[3403]        NA        NA        NA        NA        NA        NA        NA
[3410]        NA        NA        NA        NA        NA        NA        NA
[3417]        NA        NA        NA        NA        NA        NA        NA
[3424]        NA        NA        NA        NA        NA        NA        NA
[3431]        NA        NA        NA        NA        NA        NA        NA
[3438]        NA        NA        NA        NA        NA        NA        NA
[3445]        NA        NA        NA        NA        NA        NA        NA
[3452]        NA        NA        NA        NA        NA        NA        NA
[3459]        NA        NA        NA        NA        NA        NA        NA
[3466]        NA        NA        NA        NA        NA        NA        NA
[3473]        NA        NA        NA        NA        NA        NA        NA
[3480]        NA        NA        NA        NA        NA        NA        NA
[3487]        NA        NA        NA        NA        NA        NA        NA
[3494]        NA        NA        NA        NA        NA        NA        NA
[3501]        NA        NA        NA        NA        NA        NA        NA
[3508]        NA        NA        NA        NA        NA        NA        NA
[3515]        NA        NA        NA        NA        NA        NA        NA
[3522]        NA        NA        NA        NA        NA        NA        NA
[3529]        NA        NA        NA        NA -4672.139 -4668.568 -4674.611
[3536] -4672.763 -4671.209 -4674.429 -4670.324 -4667.163 -4668.030 -4665.078
[3543] -4664.451 -4662.699 -4659.416 -4655.789 -4662.924 -4659.571 -4656.673
[3550] -4653.897 -4654.804 -4653.491 -4652.257 -4652.759 -4651.006 -4651.044
[3557] -4649.399 -4663.036 -4655.668 -4659.150 -4658.858 -4655.388 -4654.324
[3564] -4652.889 -4650.106 -4649.418 -4649.908 -4648.507 -4646.570 -4647.521
[3571] -4647.313 -4638.005 -4642.659 -4638.211 -4641.584 -4645.773 -4643.602
[3578] -4646.247 -4640.496 -4643.623 -4639.482 -4636.209 -4636.509 -4648.983
[3585] -4652.469 -4675.188 -4688.978        NA        NA        NA        NA
[3592]        NA        NA -4897.101 -4919.404 -4878.175 -4884.102 -4881.653
[3599] -4868.278 -4863.422 -4845.038 -4842.364 -4843.349 -4844.216 -4865.705
[3606] -4804.391 -4828.431 -4820.868 -4823.535 -4824.170 -4821.629 -4821.306
[3613] -4793.791        NA        NA        NA        NA        NA        NA
[3620]        NA        NA        NA        NA        NA        NA        NA
[3627]        NA        NA        NA        NA        NA        NA        NA
[3634]        NA        NA        NA        NA        NA        NA        NA
[3641]        NA        NA        NA        NA        NA        NA        NA
[3648]        NA        NA        NA        NA        NA        NA        NA
[3655]        NA        NA        NA        NA        NA        NA        NA
[3662]        NA        NA -5032.137        NA        NA        NA        NA
[3669]        NA        NA        NA        NA        NA        NA        NA
[3676]        NA        NA        NA        NA        NA        NA        NA
[3683]        NA        NA        NA        NA        NA        NA        NA
[3690]        NA        NA        NA        NA        NA        NA        NA
[3697]        NA        NA        NA        NA        NA        NA        NA
[3704]        NA        NA        NA        NA        NA        NA        NA
[3711]        NA        NA        NA        NA        NA        NA        NA
[3718]        NA        NA        NA        NA        NA        NA        NA
[3725]        NA        NA        NA        NA        NA        NA        NA
[3732]        NA        NA        NA        NA        NA        NA        NA
[3739]        NA        NA        NA        NA        NA        NA        NA
[3746]        NA        NA        NA        NA        NA        NA        NA
[3753]        NA        NA        NA        NA        NA        NA        NA
[3760]        NA        NA        NA -4683.008 -4682.982 -4682.098 -4681.598
[3767] -4681.039 -4684.004 -4685.486 -4684.236 -4685.858 -4685.233 -4688.451
[3774] -4688.279 -4686.422 -4686.559 -4685.191 -4689.012 -4687.745 -4680.397
[3781] -4684.307 -4683.721 -4679.899 -4673.812 -4664.822 -4671.976 -4666.828
[3788] -4665.531 -4686.720 -4686.314 -4694.908 -4698.343 -4696.421 -4683.983
[3795] -4694.488 -4712.075 -4714.799 -4716.439 -4720.218 -4725.214 -4733.753
[3802] -4729.413 -4736.060 -4727.800 -4740.033 -4731.193 -4738.792 -4744.228
[3809] -4755.843 -4752.837 -4749.888 -4747.813 -4746.310        NA -4738.684
[3816]        NA -4751.162        NA        NA        NA        NA        NA
[3823]        NA        NA        NA        NA        NA        NA        NA
[3830]        NA        NA        NA        NA        NA        NA        NA
[3837]        NA        NA        NA        NA        NA        NA        NA
[3844]        NA        NA        NA        NA        NA        NA        NA
[3851]        NA        NA        NA        NA        NA        NA        NA
[3858]        NA        NA        NA        NA        NA        NA        NA
[3865]        NA        NA        NA        NA        NA        NA        NA
[3872]        NA        NA        NA        NA        NA        NA        NA
[3879]        NA        NA        NA        NA        NA        NA        NA
[3886]        NA        NA        NA        NA        NA        NA        NA
[3893]        NA        NA        NA        NA        NA        NA        NA
[3900]        NA        NA        NA        NA        NA        NA        NA
[3907]        NA        NA        NA        NA        NA        NA        NA
[3914]        NA        NA        NA        NA        NA        NA        NA
[3921]        NA        NA        NA        NA        NA        NA        NA
[3928]        NA        NA        NA        NA        NA        NA        NA
[3935]        NA        NA        NA        NA        NA        NA        NA
[3942]        NA        NA        NA        NA        NA        NA        NA
[3949]        NA        NA        NA        NA        NA        NA        NA
[3956]        NA        NA        NA        NA        NA        NA        NA
[3963]        NA        NA        NA        NA        NA        NA        NA
[3970]        NA        NA        NA        NA        NA        NA        NA
[3977]        NA        NA        NA        NA        NA        NA        NA
[3984]        NA        NA        NA        NA        NA        NA        NA
[3991]        NA        NA        NA        NA        NA        NA        NA
[3998]        NA        NA        NA        NA        NA        NA        NA
[4005]        NA        NA        NA        NA        NA        NA        NA
[4012]        NA        NA        NA        NA        NA        NA        NA
[4019]        NA        NA        NA        NA        NA        NA        NA
[4026]        NA        NA        NA        NA        NA        NA        NA
[4033]        NA        NA        NA        NA        NA        NA        NA
[4040]        NA        NA        NA        NA        NA        NA        NA
[4047]        NA        NA        NA        NA        NA        NA        NA
[4054]        NA        NA        NA        NA        NA        NA        NA
[4061]        NA        NA        NA        NA        NA        NA        NA
[4068]        NA        NA        NA        NA        NA        NA        NA
[4075]        NA        NA        NA        NA        NA        NA        NA
[4082]        NA        NA        NA        NA        NA        NA        NA
[4089]        NA        NA        NA        NA        NA        NA        NA
[4096]        NA        NA        NA        NA        NA        NA        NA
[4103]        NA        NA        NA        NA        NA        NA        NA
[4110]        NA        NA        NA        NA        NA        NA        NA
[4117]        NA        NA        NA        NA        NA        NA        NA
[4124]        NA        NA        NA        NA        NA        NA        NA
[4131]        NA        NA        NA        NA        NA        NA        NA
[4138]        NA        NA        NA        NA        NA        NA        NA
[4145]        NA        NA        NA        NA        NA        NA        NA
[4152]        NA        NA        NA        NA        NA        NA        NA
[4159]        NA        NA        NA        NA        NA        NA        NA
[4166]        NA        NA        NA        NA        NA        NA        NA
[4173]        NA        NA        NA        NA        NA        NA        NA
[4180]        NA        NA        NA        NA        NA        NA        NA
[4187]        NA        NA        NA        NA        NA        NA        NA
[4194]        NA        NA        NA        NA        NA        NA        NA
[4201]        NA        NA        NA        NA        NA        NA        NA
[4208]        NA        NA        NA        NA        NA        NA        NA
[4215]        NA        NA        NA        NA        NA        NA        NA
[4222]        NA        NA        NA        NA        NA        NA        NA
[4229]        NA        NA        NA        NA        NA        NA        NA
[4236]        NA        NA        NA        NA        NA        NA        NA
[4243]        NA        NA        NA        NA        NA        NA        NA
[4250]        NA        NA        NA        NA        NA        NA        NA
[4257]        NA        NA        NA        NA        NA        NA        NA
[4264]        NA        NA        NA        NA        NA        NA        NA
[4271]        NA        NA        NA        NA        NA        NA        NA
[4278]        NA        NA        NA        NA        NA        NA        NA
[4285]        NA        NA        NA        NA        NA        NA        NA
[4292]        NA        NA        NA        NA        NA        NA        NA
[4299]        NA        NA        NA        NA        NA        NA        NA
[4306]        NA        NA        NA        NA        NA        NA        NA
[4313]        NA        NA        NA        NA        NA        NA        NA
[4320]        NA        NA        NA        NA        NA        NA        NA
[4327]        NA        NA        NA        NA        NA        NA        NA
[4334]        NA        NA        NA        NA        NA        NA        NA
[4341]        NA        NA        NA        NA        NA        NA        NA
[4348]        NA        NA        NA        NA        NA        NA        NA
[4355]        NA        NA        NA        NA        NA        NA        NA
[4362]        NA        NA        NA        NA        NA        NA        NA
[4369]        NA        NA        NA        NA        NA        NA        NA
[4376]        NA        NA        NA        NA        NA        NA        NA
[4383]        NA        NA        NA        NA        NA        NA        NA
[4390]        NA        NA        NA        NA        NA        NA        NA
[4397]        NA        NA        NA        NA        NA        NA        NA
[4404]        NA        NA        NA        NA        NA        NA -4710.453
[4411] -4708.968 -4707.398 -4711.244 -4705.537 -4696.063 -4701.829 -4697.159
[4418] -4694.037 -4692.781 -4695.136 -4696.716 -4697.548 -4697.184 -4696.333
[4425] -4695.427 -4698.548 -4697.558 -4698.895 -4698.684 -4699.722 -4701.201
[4432] -4704.429 -4703.314 -4703.179 -4702.142 -4706.593 -4705.314 -4705.045
[4439] -4705.784 -4701.009 -4702.448 -4703.118 -4704.112 -4701.798 -4701.059
[4446] -4707.714 -4709.363 -4703.356 -4702.050 -4706.424 -4705.413 -4705.846
[4453] -4710.276 -4726.381 -4708.904 -4715.448 -4717.600 -4717.512 -4713.824
[4460] -4711.806 -4717.532 -4723.491 -4719.484 -4715.049        NA -4721.037
[4467]        NA        NA        NA        NA        NA        NA        NA
[4474] -4699.940 -4701.538 -4703.440 -4704.224 -4705.570 -4707.039 -4707.741
[4481] -4714.074 -4716.340 -4721.707 -4711.676 -4711.932 -4714.526 -4714.045
[4488] -4718.317        NA        NA -4820.610        NA        NA -4900.963
[4495] -4876.807        NA        NA        NA        NA        NA        NA
[4502]        NA        NA        NA        NA        NA        NA        NA
[4509]        NA        NA        NA        NA        NA        NA        NA
[4516]        NA        NA        NA        NA        NA        NA        NA
[4523]        NA        NA        NA        NA        NA        NA        NA
[4530]        NA        NA        NA        NA        NA        NA        NA
[4537]        NA        NA        NA        NA        NA        NA        NA
[4544]        NA        NA        NA        NA        NA        NA        NA
[4551]        NA        NA        NA        NA        NA        NA        NA
[4558]        NA        NA        NA        NA        NA        NA        NA
[4565]        NA        NA        NA        NA        NA        NA        NA
[4572]        NA        NA        NA        NA        NA        NA        NA
[4579]        NA        NA        NA        NA        NA        NA        NA
[4586]        NA        NA        NA        NA        NA        NA        NA
[4593]        NA        NA        NA        NA        NA        NA        NA
[4600]        NA        NA        NA        NA        NA        NA        NA
[4607]        NA        NA        NA        NA        NA        NA        NA
[4614]        NA        NA        NA        NA        NA        NA        NA
[4621]        NA        NA        NA        NA        NA        NA        NA
[4628]        NA        NA        NA        NA        NA        NA        NA
[4635]        NA        NA        NA        NA        NA        NA        NA
[4642]        NA        NA        NA        NA        NA        NA        NA
[4649]        NA        NA        NA        NA        NA        NA        NA
[4656]        NA        NA        NA        NA        NA        NA        NA
[4663]        NA        NA        NA        NA        NA        NA        NA
[4670]        NA        NA        NA        NA        NA        NA        NA
[4677]        NA        NA        NA        NA        NA        NA        NA
[4684]        NA        NA        NA        NA        NA        NA        NA
[4691]        NA        NA        NA        NA        NA        NA        NA
[4698]        NA        NA        NA        NA        NA        NA        NA
[4705]        NA        NA        NA        NA        NA        NA        NA
[4712]        NA        NA        NA        NA        NA        NA        NA
[4719]        NA        NA        NA        NA        NA        NA        NA
[4726]        NA        NA        NA        NA        NA        NA        NA
[4733]        NA        NA        NA        NA        NA        NA        NA
[4740]        NA        NA        NA        NA        NA        NA        NA
[4747]        NA        NA        NA        NA        NA        NA        NA
[4754]        NA        NA        NA        NA        NA        NA        NA
[4761]        NA        NA        NA        NA        NA        NA        NA
[4768]        NA        NA        NA        NA        NA        NA        NA
[4775]        NA        NA        NA        NA        NA        NA        NA
[4782]        NA        NA        NA        NA        NA        NA        NA
[4789]        NA        NA        NA        NA        NA        NA        NA
[4796]        NA        NA        NA        NA        NA        NA        NA
[4803]        NA        NA        NA        NA        NA        NA        NA
[4810]        NA        NA        NA        NA        NA        NA        NA
[4817]        NA        NA        NA        NA        NA        NA        NA
[4824]        NA        NA        NA        NA        NA        NA        NA
[4831]        NA        NA        NA        NA        NA        NA        NA
[4838]        NA        NA        NA        NA        NA        NA        NA
[4845]        NA        NA        NA        NA        NA        NA        NA
[4852]        NA        NA        NA        NA        NA        NA        NA
[4859]        NA        NA        NA        NA        NA        NA        NA
[4866]        NA        NA        NA        NA        NA        NA        NA
[4873]        NA        NA        NA        NA        NA        NA        NA
[4880]        NA        NA        NA        NA        NA        NA        NA
[4887]        NA        NA        NA        NA        NA        NA        NA
[4894]        NA        NA        NA        NA        NA        NA        NA
[4901]        NA        NA        NA        NA        NA        NA        NA
[4908]        NA        NA        NA        NA        NA        NA        NA
[4915]        NA        NA        NA        NA        NA        NA        NA
[4922]        NA        NA        NA        NA        NA        NA        NA
[4929]        NA        NA        NA        NA        NA        NA        NA
[4936]        NA        NA        NA        NA        NA        NA        NA
[4943]        NA        NA        NA        NA        NA        NA -4684.600
[4950] -4684.463 -4685.406 -4686.300 -4687.205 -4687.815 -4687.761 -4687.286
[4957] -4686.763 -4685.956 -4685.087 -4685.664 -4684.380 -4682.916 -4681.811
[4964] -4682.940 -4684.397 -4685.308 -4686.419 -4685.472 -4684.458 -4683.094
[4971] -4682.561 -4683.643 -4682.421 -4681.358 -4680.446 -4679.394 -4678.086
[4978] -4678.770 -4677.432 -4676.217 -4677.104 -4681.425 -4679.574 -4681.330
[4985] -4680.289 -4680.877 -4680.653 -4678.376 -4682.153 -4678.160 -4680.148
[4992] -4680.326 -4679.583 -4678.334 -4677.940 -4677.050 -4676.661 -4675.720
[4999] -4677.727 -4676.346 -4675.815 -4675.330 -4674.366 -4679.639 -4680.152
[5006] -4678.830 -4676.633 -4677.804 -4678.357 -4675.446 -4676.542 -4675.570
[5013] -4674.579 -4674.915 -4674.239 -4672.705 -4673.478 -4673.271 -4673.085
[5020] -4672.548 -4671.936 -4681.948 -4680.877 -4679.382 -4678.276 -4688.205
[5027] -4686.026 -4682.528 -4682.052 -4687.644 -4686.774 -4685.560 -4683.690
[5034] -4684.751 -4684.474 -4686.129 -4684.799 -4683.476 -4685.393 -4683.389
[5041] -4684.647 -4682.339 -4682.048 -4688.780 -4685.802 -4686.861 -4686.950
[5048] -4689.233 -4688.054 -4688.856 -4687.469 -4688.667 -4688.892 -4689.903
[5055] -4691.878 -4692.893 -4690.676 -4694.255 -4692.304 -4690.334 -4688.501
[5062] -4691.695 -4693.491 -4689.575 -4691.680 -4692.292 -4692.437 -4692.588
[5069] -4691.359 -4697.817 -4695.838 -4693.095 -4695.942 -4695.174 -4692.216
[5076] -4705.105 -4700.627 -4698.099 -4699.431 -4699.317 -4697.216 -4700.556
[5083] -4697.080 -4695.395 -4702.577 -4700.116 -4698.784 -4698.943 -4693.580
[5090] -4695.791 -4694.373 -4697.287 -4690.885 -4695.130 -4693.572 -4694.102
[5097] -4699.670 -4697.538 -4694.898 -4693.321 -4692.609 -4698.555 -4697.942
[5104] -4696.051 -4696.329 -4699.731 -4700.404 -4699.177 -4697.896 -4692.220
[5111] -4691.097 -4690.328 -4689.412 -4687.466 -4685.713 -4683.955 -4686.558
[5118] -4684.706 -4689.641 -4689.020 -4687.458 -4688.109 -4684.454 -4685.774
[5125] -4688.559 -4687.659 -4685.894 -4686.134 -4694.214 -4695.748 -4690.826
[5132] -4690.821 -4691.750 -4688.996 -4694.520 -4693.293 -4696.486 -4696.712
[5139] -4695.421 -4694.955 -4693.110 -4694.310 -4691.379 -4691.694 -4692.504
[5146] -4692.376 -4690.342 -4689.969 -4689.527 -4692.871 -4691.660 -4693.988
[5153] -4695.303 -4690.749 -4691.313 -4691.532 -4688.319 -4687.649 -4686.264
[5160] -4689.161 -4688.376 -4689.769 -4691.063 -4686.148 -4684.908 -4686.589
[5167] -4687.252 -4683.757 -4683.880 -4684.522 -4681.723 -4680.316 -4684.790
[5174] -4683.172 -4683.024 -4680.768 -4663.950 -4683.798 -4682.604 -4673.956
[5181] -4675.696 -4675.196 -4681.851 -4682.934 -4682.071 -4681.348 -4681.771
[5188] -4681.354 -4684.182 -4683.205 -4679.173 -4673.749 -4679.774 -4679.447
[5195] -4680.599 -4680.234 -4678.026 -4678.271 -4680.313 -4680.571 -4680.420
[5202] -4678.301 -4679.126 -4679.792 -4677.601 -4676.541 -4671.654 -4662.289
[5209] -4663.092 -4661.002 -4659.574 -4668.797 -4667.458 -4664.940 -4670.511
[5216] -4668.771 -4671.192 -4670.388 -4669.232 -4668.638 -4666.966 -4664.962
[5223] -4662.563 -4658.925 -4665.542 -4659.586 -4666.677 -4667.431 -4661.591
[5230] -4664.058 -4650.352 -4651.170 -4640.674 -4643.215 -4641.235 -4645.732
[5237] -4642.718 -4642.707 -4639.277 -4672.752 -4670.728 -4668.176 -4668.623
[5244] -4669.946 -4663.595 -4664.154 -4667.513 -4666.524 -4664.805 -4665.164
[5251] -4669.444 -4667.122 -4665.727 -4661.753 -4662.923 -4670.912 -4671.806
[5258] -4662.864 -4663.592 -4661.125 -4654.303 -4665.702 -4636.175 -4651.410
[5265] -4688.041        NA        NA        NA        NA        NA        NA
[5272]        NA        NA        NA        NA        NA        NA        NA
[5279]        NA        NA        NA        NA        NA        NA        NA
[5286]        NA        NA        NA        NA        NA        NA        NA
[5293]        NA        NA        NA        NA        NA        NA        NA
[5300]        NA        NA        NA        NA        NA        NA        NA
[5307]        NA        NA        NA        NA        NA        NA        NA
[5314]        NA        NA        NA        NA        NA        NA        NA
[5321]        NA        NA        NA        NA        NA        NA        NA
[5328]        NA        NA        NA        NA        NA        NA        NA
[5335]        NA        NA        NA        NA        NA        NA        NA
[5342]        NA        NA        NA        NA        NA        NA        NA
[5349]        NA        NA        NA        NA        NA        NA        NA
[5356]        NA        NA        NA        NA        NA        NA        NA
[5363]        NA        NA        NA        NA        NA        NA        NA
[5370]        NA        NA        NA        NA        NA        NA        NA
[5377]        NA        NA        NA        NA        NA        NA        NA
[5384]        NA        NA        NA        NA        NA        NA        NA
[5391]        NA        NA        NA        NA        NA        NA        NA
[5398]        NA        NA        NA        NA        NA        NA        NA
[5405]        NA        NA        NA        NA        NA        NA        NA
[5412]        NA        NA        NA        NA        NA        NA        NA
[5419]        NA        NA        NA        NA        NA        NA        NA
[5426]        NA        NA        NA        NA        NA        NA        NA
[5433]        NA        NA        NA        NA        NA        NA        NA
[5440]        NA        NA        NA        NA        NA        NA        NA
[5447]        NA        NA        NA        NA        NA        NA        NA
[5454]        NA        NA        NA        NA        NA        NA        NA
[5461]        NA        NA        NA        NA        NA        NA        NA
[5468]        NA        NA        NA        NA        NA        NA        NA
[5475]        NA        NA        NA        NA        NA        NA        NA
[5482]        NA        NA        NA        NA        NA        NA        NA
[5489]        NA        NA        NA        NA        NA        NA        NA
[5496]        NA        NA        NA        NA        NA        NA        NA
[5503]        NA        NA        NA        NA        NA        NA        NA
[5510]        NA        NA        NA        NA        NA        NA        NA
[5517]        NA        NA        NA        NA        NA        NA        NA
[5524]        NA        NA        NA        NA        NA        NA        NA
[5531]        NA        NA        NA        NA        NA        NA        NA
[5538]        NA        NA        NA        NA        NA        NA        NA
[5545]        NA        NA        NA        NA        NA        NA        NA
[5552]        NA        NA        NA        NA        NA        NA        NA
[5559]        NA        NA        NA        NA        NA        NA        NA
[5566]        NA        NA        NA        NA        NA        NA        NA
[5573]        NA        NA        NA        NA        NA        NA        NA
[5580]        NA        NA        NA        NA        NA        NA        NA
[5587]        NA        NA        NA        NA        NA        NA        NA
[5594]        NA        NA        NA        NA        NA        NA        NA
[5601]        NA        NA        NA        NA        NA        NA        NA
[5608]        NA        NA        NA        NA        NA        NA        NA
[5615]        NA        NA        NA        NA        NA        NA        NA
[5622]        NA        NA        NA        NA        NA        NA        NA
[5629]        NA        NA        NA        NA        NA        NA        NA
[5636]        NA        NA        NA        NA        NA        NA        NA
[5643]        NA        NA        NA        NA        NA        NA        NA
[5650]        NA        NA        NA        NA        NA        NA        NA
[5657]        NA        NA        NA        NA        NA        NA        NA
[5664]        NA        NA        NA        NA        NA        NA        NA
[5671]        NA        NA        NA        NA        NA        NA        NA
[5678]        NA        NA        NA        NA        NA        NA        NA
[5685]        NA        NA        NA        NA        NA        NA        NA
[5692]        NA        NA        NA        NA        NA        NA        NA
[5699]        NA        NA        NA        NA        NA        NA        NA
[5706]        NA        NA        NA        NA        NA        NA        NA
[5713]        NA        NA        NA        NA        NA        NA        NA
[5720]        NA        NA        NA        NA        NA        NA        NA
[5727]        NA        NA        NA        NA        NA        NA        NA
[5734]        NA        NA        NA        NA        NA        NA        NA
[5741]        NA        NA        NA        NA        NA        NA        NA
[5748]        NA        NA        NA        NA        NA        NA        NA
[5755]        NA        NA        NA        NA        NA        NA        NA
[5762]        NA        NA        NA        NA        NA        NA        NA
[5769]        NA        NA        NA        NA        NA        NA        NA
[5776]        NA        NA        NA        NA        NA        NA        NA
[5783]        NA        NA        NA        NA        NA        NA        NA
[5790]        NA        NA        NA        NA        NA        NA        NA
[5797]        NA        NA        NA        NA        NA        NA        NA
[5804]        NA        NA        NA        NA        NA        NA        NA
[5811]        NA        NA        NA        NA        NA        NA        NA
[5818]        NA        NA        NA        NA        NA        NA        NA
[5825]        NA        NA        NA        NA        NA        NA        NA
[5832]        NA        NA        NA        NA        NA        NA        NA
[5839]        NA        NA        NA        NA        NA        NA        NA
[5846]        NA        NA        NA        NA        NA        NA        NA
[5853]        NA        NA        NA        NA        NA        NA        NA
[5860]        NA        NA        NA        NA        NA        NA        NA
[5867]        NA        NA        NA        NA        NA        NA        NA
[5874]        NA        NA        NA        NA        NA        NA        NA
[5881]        NA        NA        NA        NA        NA        NA        NA
[5888]        NA        NA        NA        NA        NA        NA        NA
[5895]        NA        NA        NA        NA        NA        NA        NA
[5902]        NA        NA        NA        NA        NA        NA        NA
[5909]        NA        NA        NA        NA        NA        NA        NA
[5916]        NA        NA        NA        NA        NA        NA        NA
[5923]        NA        NA        NA        NA        NA        NA        NA
[5930]        NA        NA        NA        NA        NA        NA        NA
[5937]        NA        NA        NA        NA        NA        NA        NA
[5944]        NA        NA        NA        NA        NA        NA        NA
[5951]        NA        NA        NA        NA        NA        NA        NA
[5958]        NA        NA        NA        NA        NA        NA        NA
[5965]        NA        NA        NA        NA        NA        NA        NA
[5972]        NA        NA        NA        NA        NA        NA        NA
[5979]        NA        NA        NA        NA        NA        NA        NA
[5986]        NA        NA        NA        NA        NA        NA        NA
[5993]        NA        NA        NA        NA        NA        NA        NA
[6000]        NA        NA        NA        NA        NA        NA        NA
[6007]        NA        NA        NA        NA        NA        NA        NA
[6014]        NA        NA        NA        NA        NA        NA        NA
[6021]        NA        NA        NA        NA        NA        NA        NA
[6028]        NA        NA        NA        NA        NA        NA        NA
[6035]        NA        NA        NA        NA        NA        NA        NA
[6042]        NA        NA        NA        NA        NA        NA        NA
[6049]        NA        NA        NA        NA        NA        NA        NA
[6056]        NA        NA        NA        NA        NA        NA        NA
[6063]        NA        NA        NA        NA        NA        NA        NA
[6070]        NA        NA        NA        NA        NA        NA        NA
[6077]        NA        NA        NA        NA        NA        NA        NA
[6084]        NA        NA        NA        NA        NA        NA        NA
[6091]        NA        NA        NA        NA        NA        NA        NA
[6098]        NA        NA        NA        NA        NA        NA        NA
[6105]        NA        NA        NA        NA        NA        NA        NA
[6112]        NA        NA        NA        NA        NA        NA        NA
[6119]        NA        NA        NA        NA        NA        NA        NA
[6126]        NA        NA        NA        NA        NA        NA        NA
[6133]        NA        NA        NA        NA        NA        NA        NA
[6140]        NA        NA        NA        NA        NA        NA        NA
[6147]        NA        NA        NA        NA        NA        NA        NA
[6154]        NA        NA        NA        NA        NA        NA        NA
[6161]        NA        NA        NA        NA        NA        NA        NA
[6168]        NA        NA        NA        NA        NA        NA        NA
[6175]        NA        NA        NA        NA        NA        NA        NA
[6182]        NA        NA        NA        NA        NA        NA        NA
[6189]        NA        NA        NA        NA        NA        NA        NA
[6196]        NA        NA        NA        NA        NA        NA        NA
[6203]        NA        NA        NA        NA        NA        NA        NA
[6210]        NA        NA        NA        NA        NA        NA        NA
[6217]        NA        NA        NA        NA        NA        NA        NA
[6224]        NA        NA        NA        NA        NA        NA        NA
[6231]        NA        NA        NA        NA        NA        NA        NA
[6238]        NA        NA        NA        NA        NA        NA        NA
[6245]        NA        NA        NA        NA        NA        NA        NA
[6252]        NA        NA        NA        NA        NA        NA        NA
[6259]        NA        NA        NA        NA        NA        NA        NA
[6266]        NA        NA        NA        NA        NA        NA        NA
[6273] -4628.075 -4628.304 -4627.511 -4627.284 -4627.013        NA        NA
[6280]        NA        NA        NA        NA        NA        NA        NA
[6287]        NA        NA        NA        NA        NA        NA        NA
[6294]        NA        NA        NA        NA        NA        NA -4628.478
[6301] -4628.862 -4629.021        NA -4627.990 -4628.009        NA        NA
[6308]        NA        NA        NA        NA        NA        NA        NA
[6315]        NA        NA        NA        NA        NA        NA        NA
[6322]        NA        NA        NA        NA        NA        NA        NA
[6329]        NA        NA        NA        NA        NA        NA        NA
[6336]        NA        NA        NA        NA        NA -4635.048        NA
[6343]        NA        NA        NA        NA        NA        NA        NA
[6350]        NA        NA        NA        NA        NA        NA        NA
[6357]        NA        NA        NA        NA        NA        NA        NA
[6364]        NA        NA        NA        NA        NA        NA        NA
[6371]        NA        NA        NA        NA        NA        NA        NA
[6378]        NA        NA        NA        NA        NA        NA        NA
[6385]        NA        NA        NA        NA        NA        NA        NA
[6392]        NA        NA        NA        NA        NA        NA        NA
[6399]        NA        NA        NA        NA        NA        NA        NA
[6406]        NA        NA        NA        NA        NA        NA        NA
[6413]        NA        NA        NA        NA        NA        NA        NA
[6420]        NA        NA        NA        NA        NA        NA        NA
[6427]        NA        NA        NA        NA        NA        NA        NA
[6434]        NA        NA        NA        NA        NA        NA        NA
[6441]        NA        NA        NA        NA        NA        NA        NA
[6448]        NA        NA        NA        NA        NA        NA        NA
[6455]        NA        NA        NA        NA        NA        NA        NA
[6462]        NA        NA        NA        NA        NA        NA -4603.264
[6469] -4603.707 -4604.931 -4604.663 -4603.985 -4602.114 -4602.047 -4602.736
[6476] -4605.335 -4607.090 -4607.605 -4606.431 -4606.404 -4606.063 -4607.580
[6483] -4606.146 -4603.975 -4605.045 -4603.695 -4602.041 -4601.851 -4599.706
[6490] -4599.878 -4599.690 -4599.998 -4600.402 -4598.629 -4599.873 -4600.628
[6497] -4602.699 -4601.711 -4597.416 -4611.815 -4612.891 -4612.229 -4611.073
[6504] -4609.621 -4609.922 -4608.340 -4609.294 -4612.907 -4613.653 -4616.527
[6511] -4614.833 -4615.186 -4615.733 -4616.446 -4616.353 -4614.367 -4614.212
[6518] -4609.907 -4611.458 -4611.599 -4608.591 -4612.914 -4614.256 -4608.931
[6525] -4608.909 -4613.936 -4612.874 -4611.971 -4612.503 -4610.388 -4609.151
[6532] -4610.735 -4610.934 -4605.983 -4605.096 -4597.367 -4598.783 -4597.855
[6539] -4594.333 -4606.536 -4631.452 -4618.655 -4618.029 -4626.011 -4630.693
[6546] -4626.660 -4626.013 -4626.881 -4625.846 -4625.021 -4623.543 -4624.183
[6553] -4622.366 -4621.967 -4621.651 -4620.981 -4623.121 -4622.908 -4625.213
[6560] -4624.142 -4632.311 -4623.322 -4629.380 -4612.633 -4597.081        NA
[6567] -4580.106        NA        NA        NA        NA -4582.702        NA
[6574]        NA -4581.444        NA -4590.664        NA -4583.583 -4583.195
[6581] -4584.967 -4584.531 -4588.563 -4586.895 -4586.730 -4586.253        NA
[6588]        NA -4585.073 -4588.196        NA        NA        NA        NA
[6595]        NA        NA        NA        NA        NA        NA        NA
[6602]        NA        NA        NA        NA        NA        NA        NA
[6609]        NA        NA        NA        NA        NA        NA        NA
[6616]        NA        NA        NA        NA        NA        NA        NA
[6623]        NA        NA        NA        NA        NA        NA        NA
[6630]        NA        NA        NA        NA        NA        NA        NA
[6637]        NA        NA        NA        NA        NA        NA        NA
[6644]        NA        NA        NA        NA        NA        NA        NA
[6651]        NA        NA        NA        NA        NA        NA        NA
[6658]        NA        NA        NA        NA        NA        NA        NA
[6665]        NA        NA        NA        NA        NA        NA        NA
[6672]        NA        NA        NA        NA        NA        NA        NA
[6679]        NA        NA        NA        NA        NA        NA        NA
[6686]        NA        NA        NA        NA        NA        NA        NA
[6693]        NA        NA        NA        NA        NA        NA        NA
[6700]        NA        NA        NA        NA        NA        NA        NA
[6707]        NA        NA        NA        NA        NA        NA        NA
[6714]        NA        NA        NA        NA        NA        NA        NA
[6721]        NA        NA        NA        NA        NA        NA        NA
[6728]        NA        NA        NA        NA        NA        NA        NA
[6735]        NA        NA        NA        NA        NA        NA        NA
[6742]        NA        NA        NA        NA        NA        NA        NA
[6749]        NA        NA        NA        NA        NA        NA        NA
[6756]        NA        NA        NA        NA        NA        NA        NA
[6763]        NA        NA        NA        NA        NA        NA        NA
[6770]        NA        NA        NA        NA        NA        NA        NA
[6777]        NA        NA        NA        NA        NA        NA        NA
[6784]        NA        NA        NA        NA        NA        NA        NA
[6791]        NA        NA        NA        NA        NA        NA        NA
[6798]        NA        NA        NA        NA        NA        NA        NA
[6805]        NA        NA        NA        NA        NA        NA        NA
[6812]        NA        NA        NA        NA        NA        NA        NA
[6819]        NA        NA        NA        NA        NA        NA        NA
[6826]        NA        NA        NA        NA        NA        NA        NA
[6833]        NA        NA        NA        NA        NA        NA        NA
[6840]        NA        NA        NA        NA        NA        NA        NA
[6847]        NA        NA        NA        NA        NA        NA        NA
[6854]        NA        NA        NA        NA        NA        NA        NA
[6861]        NA        NA        NA        NA        NA        NA        NA
[6868]        NA        NA        NA        NA        NA        NA        NA
[6875]        NA        NA        NA        NA        NA        NA        NA
[6882]        NA        NA        NA        NA        NA        NA        NA
[6889]        NA        NA        NA        NA        NA        NA        NA
[6896]        NA        NA        NA        NA        NA        NA        NA
[6903]        NA        NA        NA        NA        NA        NA        NA
[6910]        NA        NA        NA        NA        NA        NA        NA
[6917]        NA        NA        NA        NA        NA        NA        NA
[6924]        NA        NA        NA        NA        NA        NA        NA
[6931]        NA        NA        NA        NA        NA        NA        NA
[6938]        NA        NA        NA        NA        NA        NA        NA
[6945]        NA        NA        NA        NA        NA        NA        NA
[6952]        NA        NA        NA        NA        NA        NA        NA
[6959]        NA        NA        NA        NA        NA        NA        NA
[6966]        NA        NA        NA        NA        NA        NA        NA
[6973]        NA        NA        NA        NA        NA        NA        NA
[6980]        NA        NA        NA        NA        NA        NA        NA
[6987]        NA        NA        NA        NA        NA        NA        NA
[6994]        NA        NA        NA        NA        NA        NA        NA
[7001]        NA        NA        NA        NA        NA        NA        NA
[7008]        NA        NA        NA        NA        NA        NA        NA
[7015]        NA        NA        NA        NA        NA        NA        NA
[7022]        NA        NA        NA        NA        NA        NA        NA
[7029]        NA        NA        NA        NA        NA        NA        NA
[7036]        NA        NA        NA        NA        NA        NA        NA
[7043]        NA        NA        NA        NA        NA        NA        NA
[7050]        NA        NA        NA        NA        NA        NA        NA
[7057]        NA        NA        NA        NA        NA        NA        NA
[7064]        NA        NA        NA        NA        NA        NA        NA
[7071]        NA        NA        NA        NA        NA        NA        NA
[7078]        NA        NA        NA        NA        NA        NA        NA
[7085]        NA        NA        NA        NA        NA        NA        NA
[7092]        NA        NA        NA        NA        NA        NA        NA
[7099]        NA        NA        NA        NA        NA        NA        NA
[7106]        NA        NA        NA        NA        NA        NA        NA
[7113]        NA        NA        NA        NA        NA        NA        NA
[7120]        NA        NA        NA        NA        NA        NA        NA
[7127]        NA        NA        NA        NA        NA        NA        NA
[7134]        NA        NA        NA        NA        NA        NA        NA
[7141]        NA        NA        NA        NA        NA        NA        NA
[7148]        NA        NA        NA        NA        NA        NA        NA
[7155]        NA        NA        NA        NA        NA        NA        NA
[7162]        NA        NA        NA        NA        NA        NA        NA
[7169]        NA        NA        NA        NA        NA        NA        NA
[7176]        NA        NA        NA        NA        NA        NA        NA
[7183]        NA        NA        NA        NA        NA        NA        NA
[7190]        NA        NA        NA        NA        NA        NA        NA
[7197]        NA        NA        NA        NA        NA        NA        NA
[7204]        NA        NA        NA        NA        NA        NA        NA
[7211]        NA        NA        NA        NA        NA        NA        NA
[7218]        NA        NA        NA        NA        NA        NA        NA
[7225]        NA        NA        NA        NA        NA        NA        NA
[7232]        NA        NA        NA        NA        NA        NA        NA
[7239]        NA        NA        NA        NA        NA        NA        NA
[7246]        NA        NA        NA        NA        NA        NA        NA
[7253]        NA        NA        NA        NA        NA        NA        NA
[7260]        NA        NA        NA        NA        NA        NA        NA
[7267]        NA        NA        NA        NA        NA        NA        NA
[7274]        NA        NA        NA        NA        NA        NA        NA
[7281]        NA        NA        NA        NA        NA        NA        NA
[7288]        NA        NA        NA        NA        NA        NA        NA
[7295]        NA        NA        NA        NA        NA        NA        NA
[7302]        NA        NA        NA        NA        NA        NA        NA
[7309]        NA        NA        NA        NA        NA        NA        NA
[7316]        NA        NA        NA        NA        NA        NA        NA
[7323]        NA        NA        NA        NA        NA        NA        NA
[7330] -4966.948 -4966.293 -4964.188 -4962.609 -4966.524 -4965.456 -4968.240
[7337] -4969.360 -4970.492 -4968.095 -4970.992 -4967.987 -4967.500 -4963.416
[7344] -4973.290 -4971.106 -4962.798 -4961.370 -4961.780 -4958.692 -4961.447
[7351] -4962.751 -4960.321 -4959.357 -4960.447 -4954.103 -4978.695 -4975.498
[7358] -4976.937 -4979.539 -4965.716 -4972.135 -4981.928 -4954.241 -4944.479
[7365] -4948.635 -4946.468 -4940.253 -4952.193 -4953.886 -4943.606 -4970.640
[7372] -5015.396 -4986.282 -4928.011 -4944.428 -4971.499 -4969.529        NA
[7379] -5086.604 -5104.087 -5109.949 -5144.119 -5147.665 -5125.346 -5110.729
[7386] -5117.207 -5119.383 -5083.745 -5078.289 -5057.768 -5044.107 -5045.012
[7393] -4658.656 -4657.824 -4659.971 -4659.812 -4656.753 -4657.315 -4656.109
[7400] -4655.521 -4654.680 -4654.603 -4652.541 -4652.265 -4656.313 -4664.378
[7407] -4658.289 -4657.807 -4656.840 -4657.858 -4658.980 -4660.226 -4659.123
[7414] -4659.219 -4660.401 -4661.138 -4661.190 -4662.690 -4665.064 -4661.841
[7421] -4663.373 -4662.742 -4650.396 -4650.708 -4656.098 -4653.235 -4652.739
[7428] -4651.572 -4650.373 -4649.624 -4673.418 -4661.802 -4666.424 -4670.860
[7435] -4675.182 -4673.942 -4671.743 -4674.055 -4671.166 -4671.224 -4670.304
[7442] -4670.351 -4669.137 -4665.541 -4668.653 -4667.857 -4670.195 -4669.917
[7449] -4669.522 -4668.175 -4669.402 -4669.195 -4668.726 -4652.908 -4667.370
[7456] -4666.953 -4666.365 -4666.630 -4667.774 -4667.965 -4667.086 -4690.815
[7463] -4682.682 -4676.123 -4675.168 -4675.365 -4678.947 -4677.450 -4674.435
[7470] -4674.487 -4672.043 -4674.307 -4679.004 -4677.916 -4676.391 -4676.931
[7477] -4676.150 -4681.621 -4680.066 -4682.173 -4680.580 -4683.358 -4679.535
[7484] -4682.985 -4682.593 -4685.622 -4652.287 -4664.964 -4676.317 -4691.734
[7491] -4687.551 -4688.254 -4694.591 -4692.201 -4694.641 -4695.365 -4702.999
[7498] -4688.439 -4688.981 -4690.687 -4694.393 -4692.354 -4692.886 -4686.557
[7505] -4682.115 -4688.511 -4684.439 -4686.868 -4690.861 -4690.796 -4693.445
[7512] -4697.879 -4705.016 -4701.890 -4701.949 -4703.615 -4704.991 -4704.936
[7519] -4708.047 -4706.311 -4702.293 -4703.561 -4701.713 -4712.214 -4710.911
[7526] -4708.056 -4710.491 -4714.865 -4712.377 -4710.486 -4716.230 -4716.589
[7533] -4716.318 -4717.301 -4719.826 -4719.172 -4718.959 -4717.882 -4719.016
[7540] -4722.477 -4718.064 -4719.921 -4724.719 -4729.311 -4727.993 -4723.786
[7547] -4721.045 -4720.567 -4721.518 -4722.581 -4724.338 -4719.343 -4717.982
[7554] -4717.329 -4719.676 -4719.238 -4714.979 -4715.424 -4716.279 -4711.304
[7561] -4713.691 -4718.739 -4713.132 -4714.352 -4707.620 -4710.562 -4721.436
[7568] -4732.750 -4739.995 -4734.702 -4727.788 -4733.660 -4735.231 -4734.331
[7575] -4734.025 -4733.353 -4731.150 -4741.357 -4744.156 -4744.618 -4748.184
[7582] -4753.519 -4774.710 -4774.766 -4719.637 -4761.735 -4760.622        NA
[7589]        NA        NA        NA        NA        NA        NA        NA
[7596]        NA        NA        NA        NA        NA        NA        NA
[7603]        NA        NA        NA        NA        NA        NA        NA
[7610]        NA        NA        NA        NA        NA        NA        NA
[7617]        NA        NA        NA        NA        NA        NA        NA
[7624]        NA        NA        NA        NA        NA        NA        NA
[7631]        NA        NA        NA        NA        NA        NA        NA
[7638]        NA        NA        NA        NA        NA        NA        NA
[7645]        NA        NA        NA        NA        NA        NA        NA
[7652]        NA        NA        NA        NA        NA        NA        NA
[7659]        NA        NA        NA        NA        NA        NA        NA
[7666]        NA        NA        NA        NA        NA        NA        NA
[7673]        NA        NA        NA        NA        NA        NA        NA
[7680]        NA        NA -4762.543 -4761.187 -4759.835 -4759.363 -4758.089
[7687] -4757.887 -4756.396 -4753.420 -4753.746 -4761.331 -4759.400 -4755.849
[7694] -4765.312 -4765.723 -4762.946 -4778.899 -4775.422 -4778.689 -4745.655
[7701] -4749.033 -4722.158 -4897.937 -4932.689 -4913.103 -4922.518 -4914.403
[7708] -4911.660 -4908.343 -4896.138 -4877.314 -4870.960 -4875.019 -5015.078
[7715] -5036.971 -5031.170 -4996.593 -4937.014        NA        NA        NA
[7722]        NA        NA        NA        NA        NA        NA        NA
[7729]        NA        NA        NA        NA        NA        NA        NA
[7736]        NA        NA        NA        NA        NA        NA        NA
[7743]        NA        NA        NA        NA        NA        NA        NA
[7750]        NA        NA        NA        NA        NA        NA        NA
[7757]        NA        NA        NA        NA        NA        NA        NA
[7764]        NA        NA        NA        NA        NA        NA        NA
[7771]        NA        NA        NA        NA        NA        NA        NA
[7778]        NA        NA        NA        NA        NA        NA        NA
[7785]        NA        NA        NA        NA        NA        NA        NA
[7792]        NA        NA        NA        NA        NA        NA        NA
[7799]        NA        NA        NA        NA        NA        NA        NA
[7806]        NA        NA        NA        NA        NA        NA        NA
[7813]        NA        NA        NA        NA        NA        NA        NA
[7820]        NA        NA        NA        NA        NA        NA        NA
[7827]        NA        NA        NA        NA        NA        NA        NA
[7834]        NA        NA        NA        NA        NA        NA        NA
[7841]        NA        NA        NA        NA        NA        NA        NA
[7848]        NA        NA        NA        NA        NA        NA        NA
[7855]        NA        NA        NA        NA        NA        NA        NA
[7862]        NA        NA        NA        NA        NA        NA        NA
[7869]        NA        NA        NA        NA        NA        NA        NA
[7876]        NA        NA        NA        NA        NA        NA        NA
[7883]        NA        NA        NA        NA        NA        NA        NA
[7890]        NA        NA        NA        NA        NA        NA        NA
[7897]        NA        NA        NA        NA        NA        NA        NA
[7904]        NA        NA        NA        NA        NA        NA        NA
[7911]        NA        NA        NA        NA        NA        NA        NA
[7918]        NA        NA        NA        NA        NA        NA        NA
[7925]        NA        NA        NA        NA        NA        NA        NA
[7932]        NA        NA        NA        NA        NA        NA        NA
[7939]        NA        NA        NA        NA        NA        NA        NA
[7946]        NA        NA        NA        NA        NA        NA        NA
[7953]        NA        NA        NA        NA        NA        NA        NA
[7960]        NA        NA        NA        NA        NA        NA        NA
[7967]        NA        NA        NA        NA        NA        NA        NA
[7974]        NA        NA        NA        NA        NA        NA        NA
[7981] -4689.610 -4709.392 -4687.484 -4687.955 -4688.453 -4684.515 -4686.205
[7988] -4685.161 -4674.649 -4681.185 -4693.219 -4698.663 -4695.834 -4695.268
[7995] -4697.025 -4695.556 -4694.653 -4694.762 -4692.710 -4692.606 -4693.097
[8002] -4690.458 -4691.409 -4693.448 -4694.418 -4694.119 -4710.266 -4711.807
[8009] -4710.928 -4709.998 -4709.047 -4708.874 -4708.510 -4708.140 -4708.478
[8016] -4707.381 -4707.594 -4707.687 -4707.538 -4729.663 -4742.744 -4760.600
[8023] -4760.608 -4756.138 -4756.791 -4754.825 -4753.870 -4752.789 -4750.555
[8030] -4742.729 -4740.894 -4755.380 -4749.511 -4768.697 -4780.838

• str_split(string, pattern) - splits strings up - returns list!

library(stringr)
x <- c("I really like writing R code")
df <- tibble(x = c("I really", "like writing", "R code programs"))
y <- unlist(str_split(x, " "))
y

[1] "I"       "really"  "like"    "writing" "R"       "code"   

length(y)

[1] 6

• http://www.regular-expressions.info/reference.html
• They can use to match a large number of strings in one statement
• . matches any single character
• * means repeat as many (even if 0) more times the last character
• ? makes the last thing optional
• ^ matches start of vector ^a - starts with “a”
• $ matches end of vector b$ - ends with “b”

?modifiers

• fixed - match everything exactly
• ignore_case is an option to not have to use tolower

One example case is when you want to split on a period “.”. In regular expressions . means ANY character, so we need to specify that we want R to interpret “.” as simply a period.

str_split("I.like.strings", ".")

[[1]]
 [1] "" "" "" "" "" "" "" "" "" "" "" "" "" "" ""

str_split("I.like.strings", fixed("."))

[[1]]
[1] "I"       "like"    "strings"

str_split("I.like.strings", "\\.")

[[1]]
[1] "I"       "like"    "strings"

Paste can be very useful for joining vectors together:

paste("Visit", 1:5, sep = "_")

[1] "Visit_1" "Visit_2" "Visit_3" "Visit_4" "Visit_5"

paste("Visit", 1:5, sep = "_", collapse = "_")

[1] "Visit_1_Visit_2_Visit_3_Visit_4_Visit_5"

# and paste0 can be even simpler see ?paste0 
paste0("Visit",1:5) # no space!

[1] "Visit1" "Visit2" "Visit3" "Visit4" "Visit5"

stringr

• str_split(string, pattern) - splits strings up - returns list!

In stringr, str_split splits a vector on a string into a list

library(stringr)
x <- c("I really", "like writing", "R code programs")
y <- str_split(x, pattern =  " ") # returns a list
y

[[1]]
[1] "I"      "really"

[[2]]
[1] "like"    "writing"

[[3]]
[1] "R"        "code"     "programs"

Base R does not use these functions. Here is a “translator” of the stringr function to base R functions

• str_detect - similar to grepl (return logical)
• grep(value = FALSE) is similar to which(str_detect())
• str_subset - similar to grep(value = TRUE) - return value of matched
• str_replace - similar to sub - replace one time
• str_replace_all - similar to gsub - replace many times

Base R:

• Argument order is (pattern, x)
• Uses option (fixed = TRUE)

stringr

• Argument order is (string, pattern) aka (x, pattern)
• Uses function fixed(pattern)

Sal <- read_csv(file =
    "https://daseh.org/data/Baltimore_City_Employee_Salaries_FY2015.csv")

str_extract extracts just the matched string

ss <- str_extract(Sal$Name, "Rawling")

Warning: Unknown or uninitialised column: `Name`.

head(ss)

character(0)

ss[ !is.na(ss)]

character(0)

str_extract_all extracts all the matched strings

head(str_extract(Sal$AgencyID, "\\d"))

[1] "0" "2" "6" "9" "4" "9"

head(str_extract_all(Sal$AgencyID, "\\d"), 2)

[[1]]
[1] "0" "3" "0" "3" "1"

[[2]]
[1] "2" "9" "0" "4" "5"

• Look for any name that starts with:
  • Payne at the beginning,
  • Leonard and then an S
  • Spence then capital C

head(grep("^Payne.*", x = Sal$name, value = TRUE), 3)

[1] "Payne El,Boaz L"         "Payne El,Jackie"        
[3] "Payne Johnson,Nickole A"

head(grep("Leonard.?S", x = Sal$name, value = TRUE))

[1] "Payne,Leonard S"      "Szumlanski,Leonard S"

head(grep("Spence.*C.*", x = Sal$name, value = TRUE))

[1] "Spencer,Charles A"  "Spencer,Clarence W" "Spencer,Michael C" 

head(str_subset( Sal$name, "^Payne.*"), 3)

[1] "Payne El,Boaz L"         "Payne El,Jackie"        
[3] "Payne Johnson,Nickole A"

head(str_subset( Sal$name, "Leonard.?S"))

[1] "Payne,Leonard S"      "Szumlanski,Leonard S"

head(str_subset( Sal$name, "Spence.*C.*"))

[1] "Spencer,Charles A"  "Spencer,Clarence W" "Spencer,Michael C" 

Let’s say we wanted to sort the data set by Annual Salary:

class(Sal$AnnualSalary)

[1] "character"

sort(c("1", "2", "10")) #  not sort correctly (order simply ranks the data)

[1] "1"  "10" "2" 

order(c("1", "2", "10"))

[1] 1 3 2

So we must change the annual pay into a numeric:

head(Sal$AnnualSalary, 4)

[1] "$55314.00" "$74000.00" "$64500.00" "$46309.00"

head(as.numeric(Sal$AnnualSalary), 4)

Warning in head(as.numeric(Sal$AnnualSalary), 4): NAs introduced by coercion

[1] NA NA NA NA

R didn’t like the $ so it thought turned them all to NA.

sub() and gsub() can do the replacing part in base R.

Now we can replace the $ with nothing (used fixed=TRUE because $ means ending):

Sal$AnnualSalary <- as.numeric(gsub(pattern = "$", replacement="", 
                              Sal$AnnualSalary, fixed=TRUE))
Sal <- Sal[order(Sal$AnnualSalary, decreasing=TRUE), ] 
Sal[1:5, c("name", "AnnualSalary", "JobTitle")]

# A tibble: 5 × 3
  name            AnnualSalary JobTitle              
  <chr>                  <dbl> <chr>                 
1 Mosby,Marilyn J       238772 STATE'S ATTORNEY      
2 Batts,Anthony W       211785 Police Commissioner   
3 Wen,Leana             200000 Executive Director III
4 Raymond,Henry J       192500 Executive Director III
5 Swift,Michael         187200 CONTRACT SERV SPEC II 

We can do the same thing (with 2 piping operations!) in dplyr

dplyr_sal <- Sal
dplyr_sal <- dplyr_sal %>% mutate( 
  AnnualSalary = AnnualSalary %>%
    str_replace(
      fixed("$"), 
      "") %>%
    as.numeric) %>%
  arrange(desc(AnnualSalary))
check_Sal = Sal
rownames(check_Sal) = NULL
all.equal(check_Sal, dplyr_sal)

[1] TRUE

A two-way table. If you pass in 2 vectors, table creates a 2-dimensional table.

tab <- table(c(0, 1, 2, 3, 2, 3, 3, 2,2, 3),
             c(0, 1, 2, 3, 2, 3, 3, 4, 4, 3),
              useNA = "always")
tab

      
       0 1 2 3 4 <NA>
  0    1 0 0 0 0    0
  1    0 1 0 0 0    0
  2    0 0 2 0 2    0
  3    0 0 0 4 0    0
  <NA> 0 0 0 0 0    0

tab_df <- tibble(x = c(0, 1, 2, 3, 2, 3, 3, 2,2, 3),
             y = c(0, 1, 2, 3, 2, 3, 3, 4, 4, 3))
tab_df %>% count(x, y)

# A tibble: 5 × 3
      x     y     n
  <dbl> <dbl> <int>
1     0     0     1
2     1     1     1
3     2     2     2
4     2     4     2
5     3     3     4

tab_df %>% 
  count(x, y) %>% 
  group_by(x) %>% mutate(pct_x = n / sum(n))

# A tibble: 5 × 4
# Groups:   x [4]
      x     y     n pct_x
  <dbl> <dbl> <int> <dbl>
1     0     0     1   1  
2     1     1     1   1  
3     2     2     2   0.5
4     2     4     2   0.5
5     3     3     4   1  

library(scales)
tab_df %>% 
  count(x, y) %>% 
  group_by(x) %>% mutate(pct_x = percent(n / sum(n)))

# A tibble: 5 × 4
# Groups:   x [4]
      x     y     n pct_x
  <dbl> <dbl> <int> <chr>
1     0     0     1 100% 
2     1     1     1 100% 
3     2     2     2 50%  
4     2     4     2 50%  
5     3     3     4 100%