Introduction to R: Basics

Kevin Reuning

Who am I

  • I’m Kevin Reuning (ROY-ning).
  • I’m an Associate Professor in Political Science.
  • Prior to grad school I had very little experience in coding.

Goals For this Bootcamp

  • Not be afraid of R/Rstudio
  • Able to load data in and calculate useful statistics with it.
    • Difference of means and linear regression.
  • Make a variety of beautiful plots.

Where We Are Going

library(tidyverse)
setwd("images")
df <- read_csv("country_data.csv")
df %>%
  mutate(
    type = cut(
      fh_polity2,
      breaks = c(0, 3, 7, 10),
      labels = c("Autocracy", "Anocracy", "Democracy")
    )
  ) %>%
  drop_na(type) %>%
  ggplot(aes(y = wdi_afp, x = mad_gdppc)) +
  geom_smooth(method = "lm", color = 'black') +
  geom_point(color = 'orangered3') +
  facet_wrap(~type) +
  scale_x_log10(labels = scales::label_dollar()) +
  theme_minimal() +
  theme(strip.text = element_text(size = 20)) +
  labs(
    y = "Percent of Labor\nForce in Military",
    x = "GDP per Capita\n(Log scale)"
  )

Where We Are Going

Goals for Today

  • Start using R and RStudio, realize you cannot break it.
  • How to use R as a calculator.
  • Understand the basics of variables and functions in R.
  • Load data into R and calculate the average of different variables.

R and RStudio

  • R is a statistical language used to do analysis.
  • R is free.
  • R makes it easy to create reproducible analysis.
  • RStudio is an interface that sits on top of R and makes life easier.

Following along

You need to learn by doing. If you haven’t opened RStudio yet, do so now. You should have something like:

Rscripts

  • R Scripts allow you to save and re-run everything you did to your data. This is incredibly helpful.
  • To start a new R Script: File \(\rightarrow\) New File \(\rightarrow\) R Script.
  • When you are done you can save the R Script.

Rscripts in RStudio

You should now have 4 panes.

Running things in R/RStudio

To run parts of your script in R you have to two do things: 1) indicate what you want to run, and 2) tell RStudio to run it.

  • Indicating: In the Script part of the Window you will highlight large blocks of code or leave your cursor on the specific line you want to run.
  • Running: Click the button that says “Run” to the top right of the script window. Or hit Ctrl + Enter (Windows) or Command + Return (Mac)

Notes about Slides

Throughout this I will show you code and the output in R (Note: You can leave comments to yourself using “#” and R won’t run that line).

## The code is here
1
[1] 1

The output will be immediately below it. This should be similar to how you’ll have code in the RScript pane and the results in the pane below.

R as a calculator

R can be used to add, subtract, multiply... Type something similar in the RScript pane, highlight it and then click “Run”

1 + 2
[1] 3
3 - 4
[1] -1
5 * 6
[1] 30
7/3
[1] 2.333333

R as a calculator

You can also exponentiate things and even access special numbers such as \(\pi\)

5^2
[1] 25
pi
[1] 3.141593
2*pi
[1] 6.283185

General Advice

  • The hardest part of learning to code is that there are lot of rules but also a lot of flexibility. Sometimes you have to be very precise and sometimes you don’t.
    • You’ll learn these rules as you try different things. Don’t be afraid to try to break R.
  • You can (and should) save scripts so you can re-run and change things. Every R script should be a self contained world.

Spaces

Spaces (or not) between things often don’t matter

3 * 2 
[1] 6
3*2 
[1] 6
3          *      2
[1] 6

Check

At this point you should have RStudio open, and be able to type things in the RScript pane and run it in the console pane below. Your screen will look something like this.

Variables

In R you can store information in order to retrieve it later. These are called variables.

You use an arrow <- (less than and dash) to save a value as a variable.

a_variable <- 1 # Running this alone will return nothing
a_variable # By calling the vector alone it returns the result
[1] 1

Variable Names

You can name a variable almost anything with numbers, character

therearenoreallimitsonhowlongavariablenameis <- 1
Variable_1 <- 4

There are some limits, they cannot start with numbers and cannot use some symbols

# fmt: skip
1_variable <- 2 # variables cannot start with a number though
Error in parse(text = input): <text>:2:2: unexpected input
1: # fmt: skip
2: 1_
    ^

Rstudio and Variables

One of the benefits of RStudio is that it will show the stored variables in the top right pane.

Here I’ve saved the number 341.24 to the variable bank_account_balance

Overwriting Variables

There is nothing stopping you from saving on top of the variable with a new value.

bank_account_balance <- 341.24
bank_account_balance <- 341.24 + 100 
bank_account_balance
[1] 441.24

You can do math to a variable and save it back to itself

bank_account_balance <- bank_account_balance - 1000
bank_account_balance
[1] -558.76

Warning

Modifying and then saving a variable as itself can lead to mistakes so be careful.

Types of Variables

There are two base types of variables you can use:

  • Numeric/Doubles: These are just numbers. You don’t include a commas just numbers.
  • Strings: This is anything as long as it is surrounded by " " (quotation marks).
  • Factors: This is a combination of the two and we’ll discuss it more later.

String Examples

hello <- "I'm learning how to do R"
hello 
[1] "I'm learning how to do R"

Anything with quotes around it will be treated as a string.

a_number <- "1234"
a_number 
[1] "1234"
a_number * 12
Error in a_number * 12: non-numeric argument to binary operator

Vectors

You can also store a series of numbers or characters. This is called a vector

  • To store a vector you surround everything with c( ) and put commas between each item in the vector.
  • Everything in a vector has to be the same type (all numbers or all strings)

Vectors Examples

ages <- c(34,23,41,4,6)
ages
[1] 34 23 41  4  6
names <- c("Kevin", "Claire", "Mike", "Dominick", "Leona")
names
[1] "Kevin"    "Claire"   "Mike"     "Dominick" "Leona"   
names_ages <- c("Kevin", 34, "Claire", 23)
names_ages # What happens here? 
[1] "Kevin"  "34"     "Claire" "23"

Warning

If any item in a vector is a string then R will make everything a string.

Vector Math

You can do math on vectors

ages <- c(34,23,41,4,6)
ages + 5
[1] 39 28 46  9 11
assets <- c(534, 1694)
debts <- c(100, 50)
assets - debts
[1]  434 1644

Check

Using R as a calculator, calculate the volume of a sphere with a radius of 2 and store that value as the variable vol

  • You can do this all in a single line.
  • The formula is \(\frac{4}{3} \pi \cdot \text{r}^3\)
  • Then use a vector to calculate the volume of 3 different spheres with radii 3, 6, and 8.

How I did it

vol <- pi * (2^3) * (4/3)
vol 
[1] 33.51032
rad <- c(3, 6, 8)
vol <- pi * (rad^3) * (4/3)
vol 
[1]  113.0973  904.7787 2144.6606

Functions

Functions in R take the form of function(X, Y, Z) where function is the function, and X, Y, X are a bunch of arguments that give the function an input and/or tell it what specifically to do.

precinct_voters <- c(123,44,32,67)
sum(precinct_voters)
[1] 266

sum() is a pretty simple function, it takes a single vector and adds together all of its components.

Caution

Never have a space between the function name, and the parentheses.

Additional Arguments and Missing Data

sum() has an additional argument that you can use to tell R what to do with missing values. First, how does R no a value is missing? These are recorded as NA.

precinct_voters <- c(123,44,32,67, NA) # missing the data for the last precinct 
precinct_voters * 1.2 # 20% population growth 
[1] 147.6  52.8  38.4  80.4    NA

What if we sum together this new vector?

sum(precinct_voters)
[1] NA

sum() has a second argument na.rm that tells it what to do with missing values. If we want to ignore them we need to set this argument to TRUE:

sum(precinct_voters, na.rm=TRUE)
[1] 266

na.rm is a logical argument. It can either be TRUE or FALSE and so acts as switch. If TRUE then missing values are ignored, if FALSE (the default) they are not ignore and so a missing value is returned.

Accessing the Manual

R has a manual for each function. These are a good place to look if you don’t know what arguments a function has, but they can take practice to read.

You can access the manual by typing ? followed by the function name in the console: ?sum

The manual itself will appear on the bottom right pane.

Reading the Manual

The manual can be hard to read at first. A few tips:

  • The Description is often very general (to a point of sometimes not being useful).
  • The Usage shows all the arguments and their defaults (if they have any). There is more info about the arguments in the Arguments section
  • At the very bottom there is usually an Examples section. You can often copy these into the script pane, run them, and see what happens.

Some Other Functions:

  • mean()
  • median()
  • sd()
  • range()

Take a moment now, and look at the manual of one of these functions.

Libraries

  • R is powerful/useful because anyone can extend it (add more functions).
  • Bundles of functions are called libraries/packages.
  • You can install a library with install.package() and then tell R you want to use it with library.

Tidyverse

  • A lot of data science work is done using the Tidyverse suite of packages.
  • We can install the entire suite using: install.package()
  • We are going to install a few other packages we will use during the bootcamp now as well.

Run:

install.packages(c("tidyverse", "huxtable", "flextable", "officer"))

There might be a popup asking about installing things from “Source” you can hit no on it.

Using a Package

  • To use a package you use the function library().
  • It is a norm to load all the packages you use in a script at the top of a script.

Loading Data

  • readr is a library used to load datasets.
  • We are going to start with loading it using RStudio’s interface.

Download this data and we are going to open it in R. It has data on the number veterans in each county receiving disability benefits.

Importing Data with RStudio

  • In the bottom right you can look through files, it shows the working directory.
  • You can change the working directory by going to Session \(\rightarrow\) Set Working Directory \(\rightarrow\) Choose Directory…
  • Find ‘disability_comp.csv’, click on it and select ‘Import Dataset…’
  • The first time you do this there might again be a popup asking you to install something, click “Yes” on this one.

Importing Data with just R

We can do the same thing but just using R:

library(readr) # load readr package
setwd("images") # Set working directory 
# yours will look something like C:/users/reunink/Downloads
# or ~/Downloads
df <- read_csv("disability_comp.csv")

Note

Mac computers file paths start with ~/ and Windows start with C:/.

If you write setwd("C:/") you can then hit tab and walk through the folders.

Looking at your data

Once you have the data loaded start by just running the data by itself. It will show you the first 10 rows of data.

df
# A tibble: 3,142 × 9
    FIPS State   County   Total Age_under_44 Age_45_65 Age_over_65  Male Female
   <dbl> <chr>   <chr>    <dbl>        <dbl>     <dbl>       <dbl> <dbl>  <dbl>
 1  1001 Alabama Autauga   2000          466       957         576  1687    313
 2  1003 Alabama Baldwin   5073          936      1553        2584  4648    425
 3  1005 Alabama Barbour    605           97       242         266   537     68
 4  1007 Alabama Bibb       278           56        95         127   252     26
 5  1009 Alabama Blount     771          159       217         395   724     47
 6  1011 Alabama Bullock    152           22        67          63   133     19
 7  1013 Alabama Butler     414           82       168         164   362     52
 8  1015 Alabama Calhoun   3228          540      1177        1511  2847    381
 9  1017 Alabama Chambers   663          127       201         335   601     62
10  1019 Alabama Cherokee   419           59       124         236   395     24
# ℹ 3,132 more rows

Accessing individual columns

To access a specific column of data you’ll use the $: data$column.

df$Total
   [1]  2000  5073   605   278   771   152   414  3228   663   419   736   241
  [13]   485   269   190  2853  1071   274   239   862   290  1345  2629   879
  [25]   831  2659   735  1857   314   293   720   159   277   413  2696   724
  [37] 10724   222  1574   382  3999  2257   230   532 11686   428   398  1444
  [49]  8234   440  7674  1857   147    10   372   706   420  3191  1385  2970
  [61]   210  1482  1028  3658  1078   241   157   379    NA    35 10388    91
  [73]    18    65    43  4954    49    38   502  1426   255   383    28    16
  [85]  3760    66    34    33    57   111   138    14   259   194    47    NA
  [97]    44   753  7481  1871  1070   424   122   582 65815  5434  1751 22491
 [109]  8370   451  5800  4695   234   271   999  3714   622   146    70   445
 [121]   149   313   264   566   116   296   374  1373  1108   690   254   116
 [133]   173   256  2023   293   295  1928   291   757   278   496   171   518
 [145]   285   198  1229   393    97   220    92   162   219   386  2342   248
 [157]   371   659   614   137   204   141   128   454   188   245   169   303
 [169]   437   984   105  9963   353   328  2008   185   158  2228   175   441
 [181]   260   545   435  3099  1405   112   292 11666    13   792  3317   919
 [193]   202 10439   565  3013 11678   325  2058  2106   335 12071  3942  1453
 [205]   607 71255  1928  1709   376  1280  2840   179   156  6132  1766   119
 [217]  1862 26528  6221   490 37114 21131   751 28457 88830  5178  7758  4024
 [229]  4691  5780 11221  2163  3763    44   897 12346  5173  5393  1807  1093
 [241]   239  5181  1097 10180  2307  2291  6371   236 10544   301    45   141
 [253]  3047   895   382    25   144   125   114    91   233   741  8391    38
 [265]  4903   333   490 38877  1297   701    81   230   224    22   189    23
 [277]  8038    19    84   138   728  5690   353    81   309  3865    25   249
 [289]   605   876   323   364    87   492    51   116   204  4239   131   248
 [301]   271    93    15    79    52   295  1023    59  4235    87  5456  8558
 [313]  1908  1754  8088  5033  1531  1573  5132  6105  3762  7677  4667   490
 [325]  7895   486 18197 20468   237  4513  4243  8184  4356  1802   509   341
 [337] 26484 13312  2547   251   823   364   293   449   295   278   464  4914
 [349]  2416 30498   468  3214  1045   254    92  8189 12219  4486  1020   118
 [361]   344  6603  8130  2421 18968  2423  2106 15263   759 21034  6432 15807
 [373] 12405 19698 12519  1619  5073  5896  8960  7258  7691  3611   966   428
 [385]   216 12801   596  2202   645   269   105   139    58   814   231  1077
 [397]  1713   298   430  3550   251   294   317  1955  1224   501   390   113
 [409]  2689   164  1679  1037   227  9400   996   419  3531  1560    86  6469
 [421]    99 11078   597   597  7380   345  2651   264   328   268   408   418
 [433] 11634   328   165  2518  2935   179    39  1676   310   351   181   612
 [445]  2453  1350  2082   294 14877   653    44  1920   717   323   316 10884
 [457]   652  2593   237   381  1236   368   171  6085  8660   131  1110   240
 [469]   208   313   124   143   497   322   291  1132   824  7691   219  1172
 [481]  3648   593   485   318   208   454   213   414    81   321   493   113
 [493]   306   448 11126  2122   439   235  2790   839   540   335   322   647
 [505]   208   434    72   333   138  9520  2090    65   222   137  1203   432
 [517]   106   517   195    26   521   147   172   188   812   648   424   349
 [529]    98  1390   173   182   769   442  1076  1360   686   101   354   659
 [541]    38    98   551  1016   116   222   178   380  3230 27935    NA  1158
 [553]  2068  8775   116  1481    84   256   572   182   302  1149  1546   309
 [565]    49    14  3619   100   213    NA   241    89  1946   120   227   432
 [577]   163   416   314   232  3808   569   193   189    50   223   161   883
 [589]    68   188   447    84   323    79  1161   380   218  1064   135   249
 [601]   501    67   332    68   213   144  1828   432   225   168   648   608
 [613] 32832   254   128   970   207   201  5522   207    74   385   231   166
 [625]   794   436   116   161   546   100   308    56   108   643   343   882
 [637]   112   636   297   298   217  3285  1135  1054   634  7938  1173   221
 [649]   394   379   292   456  2554  1631  1321   672  4074   623   149   189
 [661]   260   191   247   445   393   461   166   565  2068   293   192   223
 [673]    88   133    61   413   217  1862  8446   411  2535   116    71   272
 [685]    60   531  1588   269  1184   139   157   209   200   229   691  5077
 [697]  1334  2926   402   333  5253  1135    84   265   699   380   292   702
 [709]  2066   460   332   233   381   741   309   767  1782   536  1982   367
 [721]  1372   213   338   429   425  1750   602  3645  1306   755  2752   778
 [733]  2207   749   490   398   340   579   414  2734   570   921   286  5058
 [745]  1221   955  2194 13569   576   229  1295  1717   448  1245   155   722
 [757]    85   334   386   277   326   154  1917   335   160   595   336   431
 [769]   198  3395   363   623   307   302   603   311   148  1761   276   100
 [781]  2461   253  1483   672   103   878   492   979   444   399   528    96
 [793]    50   207   217   101   316  1546   493   283   233   231   189   162
 [805]   334   257   242   848   201   152   187    61   208   297   558   219
 [817]  1164   101   139   181   485   290  1157   147   252   260   155   186
 [829]   141   154   224   257   190   246   325   240   153   165   106   181
 [841]   282   554   149  1260   287   113   246   475  2527   126   146   155
 [853]   304   295   605   535   419   141   178   167   182   464   191    83
 [865]   266   169   267   104  6599  1913   237    88   195  2425   254   254
 [877]  1020   196   100   212   109   432   888   279   121   685   173   225
 [889]  1330   135   193   146    82   254    47   269   186   156   973    37
 [901]    52   268    32    26   291   144   124    17   480   442    35   652
 [913]   107  1256    27    67   296    94   244   259   330  4726    35    28
 [925]    38    49   106    16    50   409    34    21   219   345    54  5872
 [937]    31    89    26   222    17  3866    38   176    26   368   314   108
 [949]   153    42   391    74   501   135    27   115   143    34    56   316
 [961]    32    73    79    91   514   103    42   798    75   126  2529    66
 [973]    42    91   800    60  7871   138  3183    28    72    63    46    NA
 [985]    33   314    96    50   143    20    80    23   146    44  1857   262
 [997]   289   377   129   636   149   373  1755   250   947   417   109   178
[1009]   452  1225   220   211   574  1068    81   130   373   234  5025   625
[1021]   215   156   157   117  1350   203    61   212  3658   196   476   704
[1033]   100    81   288   359   487   458   163   711   132  7136    NA   474
[1045]   266   257   562   196    63   747   167 10030   638   409  1992   192
[1057]   428   286   945   271   111   115   300   197   345   129   434   182
[1069]  1079   322   112  1591   115   230   556   112   213  1513    95   333
[1081]   116   134   411   143   410   731   110   326   784   141    53   220
[1093]   434   783   219  1236    30   253   293   281   690   574   291   265
[1105]   356   241   484   157   207  1755   144   310   177   619    82   347
[1117]   685   322  1448   245   749  1150   222  4510  4837  3073   144    82
[1129]   139   227   313   422  5721    77   275   378   244   440   882   399
[1141]   233  5601   400  3455   875   191   554  1673   149   411   655  5428
[1153]  2370   555   283  3369    85   262   482   539   651   165   265   577
[1165]  1345   692   633  4460  1791    62  1208   328   728  4128   755   616
[1177]   356   130   133   209  2334  1920  4668   660  1087  3387   808   840
[1189]  1190  3390   477  1084  1374   874   975  4035   960 13968  8730  2105
[1201]   394  1882  1715  5278   439  4100   426  5268  4108   232  9562 17527
[1213]   614  4173   322   430  2161  1294   920  6937  3806  1427  6778   191
[1225]  7252   998  5910  1908 13365    63  6594  7346  6390  9447   318   237
[1237]  1065   505   410   299   189   717  1679   338  1840   592  2142   647
[1249]   403   588   869   760   790   405  1022   735  1299   564  5201   566
[1261]   337  1372   624   640   708   569  2859   702   713   346   770  2075
[1273]  2630   374  5792    93   309  1176   317  1321  2020   138   260  9139
[1285]   467  1713   450   619   520  1267   235  1723   843   283  2142   825
[1297] 10728   426   451   252   430   270   491  2281   327   711  2664  2602
[1309]   647   599   239  1003   924   849  2966 17924   555   529  5985   763
[1321]   932  1062   218  1163   603   971  1310  1071   250  1075  1042   225
[1333]   139   263  2104  6730   336   976   325   443   721   962   153 13274
[1345]   391   736  1011  1421   159   486   907    85   375   223   342   104
[1357]   627    96   437   754    69   219   476   657   964  1227   700   164
[1369]   668   250   131  2271  1244   272   812   101   566   292  5839    72
[1381]   350   352   974   131   247  5054  2000  2184   373  4332   584   143
[1393]   209   763    87   542   450   466  3556   253   117   723  2240   240
[1405]   489   531   163   239    70   365   185   141   190   101   132   226
[1417]   268   274   456   272  2684  1723   102   320   148   372   910  8366
[1429]  3658   180    89    10   230  3754   233    84   200   838   146   547
[1441]  1166  1546   216   262  1064   336   438  1688  1416   337   352   521
[1453]   170   307   345   104   562   392  1171   203   635   354   275   103
[1465]  2206   280    56   345   178   386   258   130   344   231   258   158
[1477]   299   177   790   660   236   148    93   241   191   318   385   271
[1489]    94   443   550   164   259   678   212  2929  1353  1165   164  1052
[1501]  1223  1345   138   164  1797   302   158  1500    96  3662   348  1543
[1513]   378   498   128   333   157   176   353   283   460  1332   276    98
[1525]  4603   206   153   536   268    88   215   857   241  9551  1727  3144
[1537]  2109    78   988   589   693   179   804   262   242   283   356   299
[1549]   269   523    91   565   179   264   219   218   608   337   885   289
[1561]   252   261   249   260   311  1033  1337   268  1864   514  4625    81
[1573]   203   528   399   188   303  4734   227   262  1306 10733   417    66
[1585]    74   785   199   130   724   693    82  1160   851   298   524   371
[1597]   313   679    38   411  3911   193   136   110   168   232    15  3546
[1609]    95   222    27   149   227    42   204  2151  1719    21   209    24
[1621]    74   339   373    67   578  2051    23   603    17   186    50   141
[1633]  2117   131   311    11    68    88    23   159    32  1198   143   139
[1645]   143   387    45   655   194    83   137   113    12   159    40    NA
[1657]  3054   742   172    NA    25    NA   159   226    52    74  1070   135
[1669]   208  1010   171    53   101   298   159   158   161   293   346   187
[1681]   371    63   922  8931    35   187   140    59   154   706    46    80
[1693]    89    15    81  1634   299   123    17    75   231    NA   240   193
[1705]    84   128   201    12    83   277  5947   812    15    24    NA   577
[1717]   290   119   101   138   135   368    61    45   267   108   677   162
[1729]   295   199    28   258  7938   593   832   484   113   124    16    91
[1741]   141    23   131   342   155    95    14   526  1198 44181  1049   798
[1753]    17    34   245    91    93  1579   127  1770    92   109  8243   173
[1765]  1156  1277  1092  1214   748  1529  6390  2479  4643  2151   849  2766
[1777]  4525  7542  4840  1751  1282  4669  3142  3093   794  2449  4422  4756
[1789]  2677  6527  2430   715  1767  1249  3081   966 14054   109   937   387
[1801]   280  1828    42  4237   772   606    98    21    73   635   547   266
[1813]   370   795   126  3054   219   551   365  3305  1550   555  2315   348
[1825]   287   661   326    74  1582  3002   856  6491  2003  1520   978  2020
[1837]  1355   653  1549   649   598   604  2644 11653   696   768   697   858
[1849]   642    86   824  6052  9941   485   753   825  7054   653  7178  8078
[1861]  2969  3413  5020  1533  4268   559  1654   778   720  8806  1806  2765
[1873]  1757  1791  2940  1481   460   292   478  1755 10549   920   628   661
[1885]  1728   951   855  1228  5086   573   383  2278   544   220   362   481
[1897]   375  1026   336   680  4369  4223  1502  3240  1259   423  2923   372
[1909]  2460   858   796   286   294  1572  1107  5342 26300   986   749  2194
[1921]   577  1105  4354   954  5520  1022  3417   267   148   919   305  7440
[1933]  1028  5417  1447  1868   381  3193    83  2541   748  3632   368  1518
[1945]  1413  1099   878   923   346   439 13437   276   458  3542  1670  4731
[1957]   400 16747  1355   385  1389  1822   406   561  3312   334  1921  1023
[1969]  2481  1306  2618  1149  1193   718   825   662  1018   285   555    63
[1981]  2454   644 14209   343   252   795  4683   992  1587   538   388    43
[1993]   223    82    16   141    36    33  1517  3046    58    74    48    67
[2005]    37    49    42    31  1705    31    58    42    23    71    20   131
[2017]    31   208   195   141   519   153    78    36   126    64   196   107
[2029]    83   251   144    74    16    37    NA   460    47   342    40   181
[2041]   147  2428    57   571   459  1299   729  1624   885   516  1122   684
[2053]  4892   395   528  2389  2906   712  1595   547   571 14782   607   695
[2065]  1707  1024  2140   431 14086   539   516   921  4928   667  8615   797
[2077]   401   232   334   708   460   223   766   607  1036   781  3153  1096
[2089]  3015   656  3750  4481   459  2902   763  2004   427   494  1517   216
[2101] 10126   313   495  1183   234   732   262   464   900   626  1960   563
[2113]   330  1874  1545   841  1363   661   574  4525  5935  3055  1373   717
[2125]   385   222  2727  1057  1182   586  1404   240   379    94   351    68
[2137]   317   155  1115   599  3312  1009  1151   376    29  8428   110  9776
[2149]   216   358  1483   445   980    67    64  1482   731  1281    68   157
[2161]    59    59   371   345  1463   121   273   825   254   240   331  1158
[2173]   942   977   189  1212   671   823   106   434   927   378  2221   202
[2185]   219   266 20326  1052   958   758   437  1299  1451   832  1983   386
[2197]    58  2198   568  1114  1413   156   169 11668  1727  1111   170   129
[2209]   333   514  1353  6172   989  1312  2008   726   833  3826  3998    59
[2221]   219   209   357  5348   568  2356  2205   312  7253  1514  3091   436
[2233]  5293   202  9120  1629    66   777  1497   562   228   566  8023    47
[2245]  1635  1280 12380   872  2143   737  3696  2173   970  5181  2397  2293
[2257]   107   987  1669  4398   498  1254   830   828  1518  4202  3601  4692
[2269]   440  4177  1787   154  2249   150   496   684  1027   621   203  2788
[2281]  4554  1032  2080  3019  4649  1678   778  1385   537  2189  6474   253
[2293]  2713  1266   652 14375   914   389  1963   359  1076   121   594   831
[2305]   369   839   891  2455   874  4131   385  5251   639  2712  2220  7124
[2317]  1925   510  3706   173  3208   302   364  5584  7562   332  9359   825
[2329]   506   766   947   919  1171   495  5312   537   477  2653  1305  7088
[2341]  1179   404  8505   621  2124  1410  1336   337  6282   285   699   501
[2353]   646  1452  1883  1729 15632   330  4527  5598   477   698  4187    46
[2365]   226    43   103   438   557    72    38   217    19   143    45   223
[2377]   420    51   339   353   117    78    70    39    51   427    33   151
[2389]    92    17    90    57   105    12   283   118    23    34    35    NA
[2401]    89   281   656   873    48   102    43    60  1220    21    32  3642
[2413]    99   143  4258    55    43   171    26    98    65    26    92    69
[2425]   166   269   104   371    13  1647   657   348   205  2833  1571   921
[2437]   201   481  1411   757   260   579   134   927  1089   224  1469  8908
[2449]   247   269   904   580   598   367   840   821   510   405  1428   250
[2461]  1126  5365   117   390   494  1279   286   376   741   355   220   412
[2473]   186  1177   431  7653    68   329   697   218   605  1107  1050   432
[2485]   276  1609   442   508  1344   232   880 16702   110   429   501   330
[2497]   170   126   291  1209   573  1118  1230  5268   344   292  2306 13790
[2509]   272   731  3296  2911  1406   126   452   339   100   561  3327   251
[2521]   487   433  2205  2248   837   162  1518   785   158    33  1164   373
[2533]    63   891  1640    83   553 30501 67347   236    NA   394  2061  5750
[2545]  2912   186    19   140   778   335  1014   693   423   349  6894   198
[2557]   101   675    39   617   641    90   278    24    65   169 10803    44
[2569]   300  6076   237    47   591  6693    13    47    29    69    23    79
[2581] 26317   122   126   100 10955   377    44   134    65   169   338  1515
[2593]    42  3064 23896   561   379   782   339    75    86    16  7477   158
[2605]   348   180   127  5698    52   561    10   141   256   276  2414  1824
[2617]   457  8130   354    50   145    31    74   959 49804  1073    39    79
[2629]  3818    39  1371  9667   773   259  1232   492   408   732   136  1771
[2641]   309    20    99   198   608    39  3781    91   713  2753   332   197
[2653]  2101  1224    NA    10  1517    72   120   839    33   941   153  1523
[2665]    79   318   279   334  1189   400    29   164   541    NA  4569    55
[2677]   133  5641    20   169   258    49    53   603   478  1569    28  1967
[2689]   482    86    96   385  8732   170   265    22  1011   795   215   264
[2701]  8844    77    45  1667   525   316  2890    73   177  1487  1784    69
[2713]   261  2474    26    80   230   101   201    10   270  1738   185   690
[2725]   317   172   526  1788    83    28   173    48   282    11  3414   157
[2737]   346   145    NA    14    43    89 31847  4591    26   120    18   325
[2749]  3180 15772   361   404   684    37   495  1423   906  1679   916   589
[2761]   158   527  2662   554    83  4583   236   293 11095  1706    82  1144
[2773]   881    61   257   157   106    84   607   948   333    30  5983   183
[2785]    91    71   147   854    88   160   132   178    22    26 10125   133
[2797]   291   290   425  1063   319  3603   242  2535    27  4196   386   488
[2809]   474  1725   147   796   145   330   486   466   915   811   538   966
[2821]   672  1402   293   210   456   244  5286   997    84  1285   140   594
[2833]   328   290   237   737   704   439   118   222  6966   220    95   788
[2845]   159   266   686   176 23858  1192   199   444   852  1343   279  1248
[2857]   287   281   382   188   659  1318  4370   828    43  1281  2499   113
[2869]   996   254   215   414  6000   666   251   185   211   694   264  1035
[2881]   263   500   246   297   316   749   291   295   970   426   425  1997
[2893] 14019   510   107   115  1643   380   819   364   388   713   507   378
[2905]  4112  7330   142   215   876   706   949   430   702   461  3547  4857
[2917]   320    85   420 10343   615   109   726   105   410   233   174   902
[2929]   107  8335   385   814   116  1097   626   297   227  9280 11150    87
[2941]  1389   438  3982   179  3108  1753   456   416  3822 22348   293   412
[2953]   447   147   504  3225  1093  1976  8443    97  2219   519   235   946
[2965]    69  1168  1699  4648   777 22109 12307   639   679  1851   333  2063
[2977]   871   652   368 32794   229  2566   239 11664 12086  1417 11706   100
[2989]  1127  3363   535  2731   305  2887   383   330   340  1770   146   213
[3001]   170  1178   135   190  1012   446   409   243  1574   567  1243  3138
[3013]   378   345   590   347  1147   458   482  1693   506   326  1302   390
[3025]   371   776   609   142   115   239   649  1027  2333   565   230   292
[3037]   389   383   126   149   533   792   232   242   124  1614   400   605
[3049]   322   870   383  3206   248   571   479  1060   516   887   291  5134
[3061]  1027   463  1100   733  1444   133  1188   307   685   476   252   293
[3073]   129   456  1047   612  2303   286  2109   168   460   573  1132  1725
[3085]  1027   341    51  9531  1812   733   866  2259   823   161   718   970
[3097]  1137   379  2295   227  1998   336  1590  1151   491   676  1101   328
[3109]   490   477   674  1194   482  1472  3751   818   561  2311  1328   718
[3121]   178   782   285   276   171   617   344    95   198  4312   280  1356
[3133]    48   599   265   855   177   742   156   307   130   209

You can put this directly in a function like:

mean(df$Total)
[1] NA

Check

Pick two numeric variables and calculate the mean, median and standard deviation for them.

The functions you’ll need are: mean(), median() and sd().

Tip

There is missing data so you’ll have to use the na.rm=TRUE argument.

How I did it

Total number of recipients:

mean(df$Total, na.rm=TRUE)
[1] 1610.01
median(df$Total, na.rm=TRUE)
[1] 438
sd(df$Total, na.rm=TRUE)
[1] 4284.202

Total number of male recipients:

mean(df$Male, na.rm=TRUE)
[1] 1745.597
median(df$Male, na.rm=TRUE)
[1] 580
sd(df$Male, na.rm=TRUE)
[1] 4076.84