Higher-Order Functions in Package purrr

(Sections 14.3 - 14.4)

Packages

Make sure the following packages are attached:

library(tidyverse)
library(Lahman)
library(bcscr)

The purrr package is part of the tidyverse. It provides many higher-order functions.

Each higher-order function iterates over a given iterable data structure (vector, data frame, etc.) with the help of another given function.

`map()` and Variations

A Task

Suppose that we want to generate five vectors, each of which consists of a different given number of real numbers, randomly chosen between 0 and 1.

Solve With a Loop

Solve with `map()`

How `map()` Works

map(.x, .f, ...)

In the template above:

.x can be a list or any atomic vector;
.f is a function that is to be applied to each element of .x.
... consists of other arguments that are supplied as arguments for the .f function.

The result is always a list.

More Control

What if we want the random real numbers of be between 4 and 8?

No problem!

What is This Code Doing?

Try, and see if you can figure out what’s going on:

How It Works

lower_bounds <- 1:3
lower_bounds |>
  map(runif, n = 2, max = 8)

the .x argument is lower_bounds;
the .f argument is runif();
the n = 2 becomes the first argument of runif();
the max = 8 becomes the max argument of runif();
so R deduces that the min parameter of runif() must iterate over lower_bounds!

Vary Two or More Parameters of a Function

Use pmap() for this:

How This Works

how_many <- c(3,1,4)
upper_bounds <- c(1, 5, 10)
list(how_many, upper_bounds) |>
  pmap(runif, min = 0)

The first argument of pmap() is called .l. This is set to list(how_many, upper_bounds), and they supply values for two arguments of runif().
min = 0 Takes care of the min parameter of runif().
So R deduces that how_many covers the n parameter, and upper_bounds covers the max parameter.

Why Not Vary All Three Parameters?

Write Your Own Helper Function

r_letters <- function(n, upper) {
  if (upper ) {
    sample(LETTERS, size = n, replace = TRUE)
  } else {
    sample(letters, size = n, replace = TRUE)
  }
}

Try It Out

Now Map!

Map with an Anonymous Function

Shorthand for Anonymous Functions

Mapping With Data Frames

.x can be any object that can be coerced to a list. A data frame will do:

Options for Other Types of Output

When the result can take on a form other than a list, it is possible to use variants of map() such as:

map_int()
map_dbl()
map_lgl()
map_chr()

Example

Another Example

Here are the types of each variable in m111survey:

Yet Another Example

Here is a statement of whether or not each variable is a factor:

When Output is a List of Data Frames

We would like to produce a graph of the number of home-runs hit by each of the top five home-run hitters in the Major Leagues, for each season since 1900.

The Data

library(Lahman)
?Batting

A Helper Function

top_hr_hitters <- function(x, n) {
  x |>
    arrange(desc(HR)) |> 
    select(playerID, yearID, HR) |> 
    head(n)
}

Split the Data

We need a list in which each element is a data frame covering a single season.

dplyr’s group_split() is our friend:

lst <-
  Batting |> 
  filter(yearID >= 1900) |> 
  select(playerID, yearID, HR) |> 
  group_split(yearID)
str(lst)

list<tibble[,3]> [1:126] 
$ : tibble [223 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:223] "allenbo01" "baileha01" "barreji01" "barrysh01" ...
 ..$ yearID  : int [1:223] 1900 1900 1900 1900 1900 1900 1900 1900 1900 1900 ...
 ..$ HR      : int [1:223] 0 0 5 1 0 5 2 0 0 0 ...
$ : tibble [421 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:421] "anderjo01" "bakerbo01" "bakerbo01" "barreji01" ...
 ..$ yearID  : int [1:421] 1901 1901 1901 1901 1901 1901 1901 1901 1901 1901 ...
 ..$ HR      : int [1:421] 8 0 0 4 0 1 0 1 8 6 ...
$ : tibble [467 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:467] "adamsjo01" "adkindo01" "altroni01" "anderjo01" ...
 ..$ yearID  : int [1:467] 1902 1902 1902 1902 1902 1902 1902 1902 1902 1902 ...
 ..$ HR      : int [1:467] 0 0 0 4 0 2 0 3 4 3 ...
$ : tibble [436 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:436] "abbated01" "abbotfr01" "adkindo01" "altroni01" ...
 ..$ yearID  : int [1:436] 1903 1903 1903 1903 1903 1903 1903 1903 1903 1903 ...
 ..$ HR      : int [1:436] 1 1 0 0 0 0 2 0 0 0 ...
$ : tibble [432 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:432] "abbated01" "abbotfr01" "altroni01" "amesre01" ...
 ..$ yearID  : int [1:432] 1904 1904 1904 1904 1904 1904 1904 1904 1904 1904 ...
 ..$ HR      : int [1:432] 3 0 1 0 3 0 0 0 0 0 ...
$ : tibble [470 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:470] "abbated01" "abbotfr01" "ablesha01" "adamsri01" ...
 ..$ yearID  : int [1:470] 1905 1905 1905 1905 1905 1905 1905 1905 1905 1905 ...
 ..$ HR      : int [1:470] 3 0 0 0 0 0 0 0 1 0 ...
$ : tibble [553 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:553] "abbotji02" "abstebi01" "adamsba01" "almeira01" ...
 ..$ yearID  : int [1:553] 1906 1906 1906 1906 1906 1906 1906 1906 1906 1906 ...
 ..$ HR      : int [1:553] 0 0 0 0 3 1 0 0 3 0 ...
$ : tibble [513 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:513] "abbated01" "abbotji02" "adamsba01" "almeira01" ...
 ..$ yearID  : int [1:513] 1907 1907 1907 1907 1907 1907 1907 1907 1907 1907 ...
 ..$ HR      : int [1:513] 2 0 0 0 2 2 0 1 1 0 ...
$ : tibble [538 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:538] "abbated01" "alperwh01" "altizda01" "altizda01" ...
 ..$ yearID  : int [1:538] 1908 1908 1908 1908 1908 1908 1908 1908 1908 1908 ...
 ..$ HR      : int [1:538] 1 1 0 0 0 0 0 0 0 0 ...
$ : tibble [641 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:641] "abbated01" "ablesha01" "abstebi01" "adamsba01" ...
 ..$ yearID  : int [1:641] 1909 1909 1909 1909 1909 1909 1909 1909 1909 1909 ...
 ..$ HR      : int [1:641] 1 0 1 0 1 1 0 0 0 0 ...
$ : tibble [676 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:676] "abbated01" "abbated01" "abbotod01" "abstebi01" ...
 ..$ yearID  : int [1:676] 1910 1910 1910 1910 1910 1910 1910 1910 1910 1910 ...
 ..$ HR      : int [1:676] 0 0 0 0 0 0 0 0 0 0 ...
$ : tibble [730 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:730] "ablesha01" "adamsba01" "adamsbe01" "addiske01" ...
 ..$ yearID  : int [1:730] 1911 1911 1911 1911 1911 1911 1911 1911 1911 1911 ...
 ..$ HR      : int [1:730] 0 0 0 0 0 0 0 0 0 0 ...
$ : tibble [741 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:741] "adamsba01" "adamsbe01" "adamswi01" "aglerjo01" ...
 ..$ yearID  : int [1:741] 1912 1912 1912 1912 1912 1912 1912 1912 1912 1912 ...
 ..$ HR      : int [1:741] 0 0 0 0 0 0 0 2 0 1 ...
$ : tibble [737 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:737] "acostme01" "adamsba01" "adamswi01" "agnewsa01" ...
 ..$ yearID  : int [1:737] 1913 1913 1913 1913 1913 1913 1913 1913 1913 1913 ...
 ..$ HR      : int [1:737] 0 0 0 2 2 0 0 1 0 0 ...
$ : tibble [910 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:910] "acostme01" "adamsba01" "adamsda01" "adamska01" ...
 ..$ yearID  : int [1:910] 1914 1914 1914 1914 1914 1914 1914 1914 1914 1914 ...
 ..$ HR      : int [1:910] 0 1 1 0 0 0 0 0 0 0 ...
$ : tibble [900 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:900] "acostme01" "adamsba01" "adamsbe01" "adamsda01" ...
 ..$ yearID  : int [1:900] 1915 1915 1915 1915 1915 1915 1915 1915 1915 1915 ...
 ..$ HR      : int [1:900] 0 0 0 0 0 0 0 0 0 0 ...
$ : tibble [708 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:708] "acostme01" "adamsba01" "adamsbe01" "agnewsa01" ...
 ..$ yearID  : int [1:708] 1916 1916 1916 1916 1916 1916 1916 1916 1916 1916 ...
 ..$ HR      : int [1:708] 0 0 0 0 0 0 0 0 0 0 ...
$ : tibble [623 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:623] "adamsbe01" "agnewsa01" "ainsmed01" "aldrivi01" ...
 ..$ yearID  : int [1:623] 1917 1917 1917 1917 1917 1917 1917 1917 1917 1917 ...
 ..$ HR      : int [1:623] 1 0 0 0 1 0 0 0 0 0 ...
$ : tibble [669 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:669] "acostme01" "acostme01" "adamsba01" "adamsbe01" ...
 ..$ yearID  : int [1:669] 1918 1918 1918 1918 1918 1918 1918 1918 1918 1918 ...
 ..$ HR      : int [1:669] 0 0 0 0 0 0 0 0 0 0 ...
$ : tibble [689 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:689] "abreueu01" "adamsba01" "adamsbe01" "adamswi01" ...
 ..$ yearID  : int [1:689] 1919 1919 1919 1919 1919 1919 1919 1919 1919 1919 ...
 ..$ HR      : int [1:689] 0 0 1 0 0 3 0 0 0 0 ...
$ : tibble [796 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:796] "abreueu01" "acostjo01" "adamsba01" "ainsmed01" ...
 ..$ yearID  : int [1:796] 1920 1920 1920 1920 1920 1920 1920 1920 1920 1920 ...
 ..$ HR      : int [1:796] 0 0 1 1 1 1 0 0 0 0 ...
$ : tibble [819 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:819] "abreueu01" "acostjo01" "adamsba01" "ainsmed01" ...
 ..$ yearID  : int [1:819] 1921 1921 1921 1921 1921 1921 1921 1921 1921 1921 ...
 ..$ HR      : int [1:819] 1 0 0 0 0 0 1 0 1 0 ...
$ : tibble [808 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:808] "acostjo01" "adamsba01" "adamssp01" "ainsmed01" ...
 ..$ yearID  : int [1:808] 1922 1922 1922 1922 1922 1922 1922 1922 1922 1922 ...
 ..$ HR      : int [1:808] 0 1 0 13 0 0 0 0 0 0 ...
$ : tibble [900 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:900] "abramge01" "abreueu01" "adamsba01" "adamssp01" ...
 ..$ yearID  : int [1:900] 1923 1923 1923 1923 1923 1923 1923 1923 1923 1923 ...
 ..$ HR      : int [1:900] 0 0 0 4 0 3 0 0 0 0 ...
$ : tibble [942 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:942] "abreueu01" "adamsba01" "adamssp01" "ainsmed01" ...
 ..$ yearID  : int [1:942] 1924 1924 1924 1924 1924 1924 1924 1924 1924 1924 ...
 ..$ HR      : int [1:942] 1 0 1 0 0 0 0 1 2 2 ...
$ : tibble [935 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:935] "abreueu01" "adamsba01" "adamsbo01" "adamssp01" ...
 ..$ yearID  : int [1:935] 1925 1925 1925 1925 1925 1925 1925 1925 1925 1925 ...
 ..$ HR      : int [1:935] 0 0 0 2 0 0 1 0 0 2 ...
$ : tibble [904 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:904] "adamsba01" "adamssp01" "adamssp02" "aldrivi01" ...
 ..$ yearID  : int [1:904] 1926 1926 1926 1926 1926 1926 1926 1926 1926 1926 ...
 ..$ HR      : int [1:904] 0 0 0 0 0 0 0 1 0 1 ...
$ : tibble [889 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:889] "adamssp01" "adamssp02" "aldrivi01" "alexach01" ...
 ..$ yearID  : int [1:889] 1927 1927 1927 1927 1927 1927 1927 1927 1927 1927 ...
 ..$ HR      : int [1:889] 0 0 0 0 0 2 2 2 0 0 ...
$ : tibble [876 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:876] "adamssp01" "adkingr01" "aldrivi01" "alexach01" ...
 ..$ yearID  : int [1:876] 1928 1928 1928 1928 1928 1928 1928 1928 1928 1928 ...
 ..$ HR      : int [1:876] 0 0 1 1 1 4 1 2 0 0 ...
$ : tibble [839 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:839] "adamssp01" "adkingr01" "akersbi01" "albrith01" ...
 ..$ yearID  : int [1:839] 1929 1929 1929 1929 1929 1929 1929 1929 1929 1929 ...
 ..$ HR      : int [1:839] 0 0 1 0 25 0 1 6 3 1 ...
$ : tibble [813 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:813] "adamssp01" "akersbi01" "alexada01" "alexape01" ...
 ..$ yearID  : int [1:813] 1930 1930 1930 1930 1930 1930 1930 1930 1930 1930 ...
 ..$ HR      : int [1:813] 0 9 20 0 5 3 7 2 0 0 ...
$ : tibble [764 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:764] "adairji01" "adamsbo02" "adamssp01" "akersbi01" ...
 ..$ yearID  : int [1:764] 1931 1931 1931 1931 1931 1931 1931 1931 1931 1931 ...
 ..$ HR      : int [1:764] 0 0 1 0 3 5 1 1 0 0 ...
$ : tibble [1,031 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1031] "adamsbo02" "adamsem01" "adamssp01" "akersbi01" ...
 ..$ yearID  : int [1:1031] 1932 1932 1932 1932 1932 1932 1932 1932 1932 1932 ...
 ..$ HR      : int [1:1031] 0 0 0 1 0 0 8 0 1 0 ...
$ : tibble [734 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:734] "adamssp01" "adamssp01" "alexada01" "allenet01" ...
 ..$ yearID  : int [1:734] 1933 1933 1933 1933 1933 1933 1933 1933 1933 1933 ...
 ..$ HR      : int [1:734] 0 1 5 0 0 0 1 0 0 0 ...
$ : tibble [758 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:758] "adamssp01" "allenet01" "allenha03" "allenjo02" ...
 ..$ yearID  : int [1:758] 1934 1934 1934 1934 1934 1934 1934 1934 1934 1934 ...
 ..$ HR      : int [1:758] 0 10 0 0 0 0 0 1 2 0 ...
$ : tibble [744 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:744] "adamspa01" "allenet01" "allenjo02" "allenne02" ...
 ..$ yearID  : int [1:744] 1935 1935 1935 1935 1935 1935 1935 1935 1935 1935 ...
 ..$ HR      : int [1:744] 0 8 1 0 3 0 1 0 0 0 ...
$ : tibble [725 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:725] "albrith01" "allenet01" "allenet01" "allenjo02" ...
 ..$ yearID  : int [1:725] 1936 1936 1936 1936 1936 1936 1936 1936 1936 1936 ...
 ..$ HR      : int [1:725] 0 1 3 0 0 1 0 0 5 0 ...
$ : tibble [899 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:899] "adamsem01" "alberjo02" "alexahu01" "allenbo03" ...
 ..$ yearID  : int [1:899] 1937 1937 1937 1937 1937 1937 1937 1937 1937 1937 ...
 ..$ HR      : int [1:899] 0 0 0 0 0 0 0 1 1 1 ...
$ : tibble [919 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:919] "adamsem01" "alexate01" "allencl02" "allenet01" ...
 ..$ yearID  : int [1:919] 1938 1938 1938 1938 1938 1938 1938 1938 1938 1938 ...
 ..$ HR      : int [1:919] 0 0 0 0 1 1 1 3 0 0 ...
$ : tibble [912 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:912] "adamsbu01" "adamsem01" "aderhmo01" "alexate01" ...
 ..$ yearID  : int [1:912] 1939 1939 1939 1939 1939 1939 1939 1939 1939 1939 ...
 ..$ HR      : int [1:912] 0 0 1 0 0 0 1 0 0 0 ...
$ : tibble [898 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:898] "adamsem01" "aderhmo01" "alexasp01" "alexate01" ...
 ..$ yearID  : int [1:898] 1940 1940 1940 1940 1940 1940 1940 1940 1940 1940 ...
 ..$ HR      : int [1:898] 0 0 0 0 0 0 0 0 3 0 ...
$ : tibble [890 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:890] "adamsac01" "adamsem01" "aderhmo01" "albosed01" ...
 ..$ yearID  : int [1:890] 1941 1941 1941 1941 1941 1941 1941 1941 1941 1941 ...
 ..$ HR      : int [1:890] 0 0 0 0 1 1 0 0 1 0 ...
$ : tibble [891 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:891] "abernte01" "abreujo01" "adams01" "adamsac01" ...
 ..$ yearID  : int [1:891] 1942 1942 1942 1942 1942 1942 1942 1942 1942 1942 ...
 ..$ HR      : int [1:891] 0 1 0 0 0 0 0 0 0 0 ...
$ : tibble [920 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:920] "abernte01" "adamsac01" "adamsbu01" "adamsbu01" ...
 ..$ yearID  : int [1:920] 1943 1943 1943 1943 1943 1943 1943 1943 1943 1943 ...
 ..$ HR      : int [1:920] 0 0 0 4 0 0 0 0 0 0 ...
$ : tibble [902 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:902] "abernte01" "adamsac01" "adamsbu01" "aderhmo01" ...
 ..$ yearID  : int [1:902] 1944 1944 1944 1944 1944 1944 1944 1944 1944 1944 ...
 ..$ HR      : int [1:902] 0 0 17 0 0 1 0 0 0 0 ...
$ : tibble [922 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:922] "abernro01" "adamsac01" "adamsbu01" "adamsbu01" ...
 ..$ yearID  : int [1:922] 1945 1945 1945 1945 1945 1945 1945 1945 1945 1945 ...
 ..$ HR      : int [1:922] 0 0 2 20 0 0 2 0 0 0 ...
$ : tibble [1,023 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1023] "abernwo01" "adamsac01" "adamsbo03" "adamsbu01" ...
 ..$ yearID  : int [1:1023] 1946 1946 1946 1946 1946 1946 1946 1946 1946 1946 ...
 ..$ HR      : int [1:1023] 0 0 4 5 0 0 0 0 0 0 ...
$ : tibble [907 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:907] "abernro01" "abernwo01" "aberscl01" "adamsbo03" ...
 ..$ yearID  : int [1:907] 1947 1947 1947 1947 1947 1947 1947 1947 1947 1947 ...
 ..$ HR      : int [1:907] 0 0 4 4 2 2 0 2 0 0 ...
$ : tibble [869 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:869] "abernro01" "aberscl01" "adamsbo03" "adamshe01" ...
 ..$ yearID  : int [1:869] 1948 1948 1948 1948 1948 1948 1948 1948 1948 1948 ...
 ..$ HR      : int [1:869] 0 1 1 0 0 1 0 0 0 0 ...
$ : tibble [573 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:573] "aberscl01" "abramca01" "adamsbo03" "adamshe01" ...
 ..$ yearID  : int [1:573] 1949 1949 1949 1949 1949 1949 1949 1949 1949 1949 ...
 ..$ HR      : int [1:573] 0 0 0 0 1 0 1 0 5 0 ...
$ : tibble [577 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:577] "aberal01" "abramca01" "adamsbo03" "adamshe01" ...
 ..$ yearID  : int [1:577] 1950 1950 1950 1950 1950 1950 1950 1950 1950 1950 ...
 ..$ HR      : int [1:577] 0 0 3 0 8 0 0 0 0 0 ...
$ : tibble [616 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:616] "abramca01" "adamsbo03" "adcocjo01" "addisbo01" ...
 ..$ yearID  : int [1:616] 1951 1951 1951 1951 1951 1951 1951 1951 1951 1951 ...
 ..$ HR      : int [1:616] 3 5 10 1 0 7 4 2 10 0 ...
$ : tibble [632 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:632] "abernbi01" "abramca01" "abramca01" "adamsbo03" ...
 ..$ yearID  : int [1:632] 1952 1952 1952 1952 1952 1952 1952 1952 1952 1952 ...
 ..$ HR      : int [1:632] 0 0 2 6 13 1 0 0 0 1 ...
$ : tibble [586 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:586] "aberal01" "aberal01" "abramca01" "adamsbo03" ...
 ..$ yearID  : int [1:586] 1953 1953 1953 1953 1953 1953 1953 1953 1953 1953 ...
 ..$ HR      : int [1:586] 0 0 15 8 18 0 0 0 0 1 ...
$ : tibble [576 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:576] "aaronha01" "aberal01" "abramca01" "abramca01" ...
 ..$ yearID  : int [1:576] 1954 1954 1954 1954 1954 1954 1954 1954 1954 1954 ...
 ..$ HR      : int [1:576] 13 0 0 6 3 23 11 3 4 0 ...
$ : tibble [655 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:655] "aaronha01" "aberal01" "abernte02" "abramca01" ...
 ..$ yearID  : int [1:655] 1955 1955 1955 1955 1955 1955 1955 1955 1955 1955 ...
 ..$ HR      : int [1:655] 27 0 0 6 2 0 15 0 0 0 ...
$ : tibble [621 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:621] "aaronha01" "aberal01" "abernte02" "abramca01" ...
 ..$ yearID  : int [1:621] 1956 1956 1956 1956 1956 1956 1956 1956 1956 1956 ...
 ..$ HR      : int [1:621] 26 0 0 0 0 0 38 0 0 16 ...
$ : tibble [615 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:615] "aaronha01" "aberal01" "aberal01" "abernte02" ...
 ..$ yearID  : int [1:615] 1957 1957 1957 1957 1957 1957 1957 1957 1957 1957 ...
 ..$ HR      : int [1:615] 44 0 0 0 0 1 12 0 0 0 ...
$ : tibble [638 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:638] "aaronha01" "ackerto01" "adairje01" "adamsbo03" ...
 ..$ yearID  : int [1:638] 1958 1958 1958 1958 1958 1958 1958 1958 1958 1958 ...
 ..$ HR      : int [1:638] 30 0 0 0 19 0 0 0 4 0 ...
$ : tibble [632 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:632] "aaronha01" "ackerto01" "adairje01" "adamsbo03" ...
 ..$ yearID  : int [1:632] 1959 1959 1959 1959 1959 1959 1959 1959 1959 1959 ...
 ..$ HR      : int [1:632] 39 0 0 0 25 0 30 10 12 0 ...
$ : tibble [637 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:637] "aaronha01" "abernte02" "adairje01" "adcocjo01" ...
 ..$ yearID  : int [1:637] 1960 1960 1960 1960 1960 1960 1960 1960 1960 1960 ...
 ..$ HR      : int [1:637] 40 0 1 25 0 15 8 0 13 0 ...
$ : tibble [698 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:698] "aaronha01" "adairje01" "adcocjo01" "aguirha01" ...
 ..$ yearID  : int [1:698] 1961 1961 1961 1961 1961 1961 1961 1961 1961 1961 ...
 ..$ HR      : int [1:698] 34 9 35 0 0 29 18 6 27 3 ...
$ : tibble [760 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:760] "aaronha01" "aaronto01" "adairje01" "adcocjo01" ...
 ..$ yearID  : int [1:760] 1962 1962 1962 1962 1962 1962 1962 1962 1962 1962 ...
 ..$ HR      : int [1:760] 45 8 11 29 0 0 12 0 29 25 ...
$ : tibble [752 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:752] "aaronha01" "aaronto01" "abernte02" "acklefr01" ...
 ..$ yearID  : int [1:752] 1963 1963 1963 1963 1963 1963 1963 1963 1963 1963 ...
 ..$ HR      : int [1:752] 44 1 0 0 6 13 0 1 0 9 ...
$ : tibble [754 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:754] "aaronha01" "abernte02" "acklefr01" "adairje01" ...
 ..$ yearID  : int [1:754] 1964 1964 1964 1964 1964 1964 1964 1964 1964 1964 ...
 ..$ HR      : int [1:754] 24 0 0 9 21 0 0 0 0 6 ...
$ : tibble [751 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:751] "aaronha01" "aaronto01" "abernte02" "adairje01" ...
 ..$ yearID  : int [1:751] 1965 1965 1965 1965 1965 1965 1965 1965 1965 1965 ...
 ..$ HR      : int [1:751] 32 0 0 7 14 0 0 0 0 0 ...
$ : tibble [774 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:774] "aaronha01" "abernte02" "abernte02" "adairje01" ...
 ..$ yearID  : int [1:774] 1966 1966 1966 1966 1966 1966 1966 1966 1966 1966 ...
 ..$ HR      : int [1:774] 44 0 0 0 4 18 0 22 0 0 ...
$ : tibble [786 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:786] "aaronha01" "abernte02" "adairje01" "adairje01" ...
 ..$ yearID  : int [1:786] 1967 1967 1967 1967 1967 1967 1967 1967 1967 1967 ...
 ..$ HR      : int [1:786] 39 0 0 3 0 1 14 0 0 0 ...
$ : tibble [715 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:715] "aaronha01" "aaronto01" "abernte02" "adairje01" ...
 ..$ yearID  : int [1:715] 1968 1968 1968 1968 1968 1968 1968 1968 1968 1968 ...
 ..$ HR      : int [1:715] 29 1 0 2 0 0 5 0 0 2 ...
$ : tibble [932 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:932] "aaronha01" "aaronto01" "abernte02" "adairje01" ...
 ..$ yearID  : int [1:932] 1969 1969 1969 1969 1969 1969 1969 1969 1969 1969 ...
 ..$ HR      : int [1:932] 44 1 0 5 0 0 26 0 0 0 ...
$ : tibble [919 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:919] "aaronha01" "aaronto01" "abernte02" "abernte02" ...
 ..$ yearID  : int [1:919] 1970 1970 1970 1970 1970 1970 1970 1970 1970 1970 ...
 ..$ HR      : int [1:919] 38 2 0 0 0 0 0 24 0 0 ...
$ : tibble [883 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:883] "aaronha01" "aaronto01" "abernte02" "acosted01" ...
 ..$ yearID  : int [1:883] 1971 1971 1971 1971 1971 1971 1971 1971 1971 1971 ...
 ..$ HR      : int [1:883] 47 0 0 0 14 0 0 4 23 1 ...
$ : tibble [889 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:889] "aaronha01" "abernte02" "acostcy01" "acosted01" ...
 ..$ yearID  : int [1:889] 1972 1972 1972 1972 1972 1972 1972 1972 1972 1972 ...
 ..$ HR      : int [1:889] 34 0 0 0 0 13 0 0 0 9 ...
$ : tibble [892 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:892] "aaronha01" "abbotgl01" "acostcy01" "adamsmi02" ...
 ..$ yearID  : int [1:892] 1973 1973 1973 1973 1973 1973 1973 1973 1973 1973 ...
 ..$ HR      : int [1:892] 40 0 0 3 8 3 0 0 0 0 ...
$ : tibble [914 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:914] "aaronha01" "abbotgl01" "acostcy01" "akerja01" ...
 ..$ yearID  : int [1:914] 1974 1974 1974 1974 1974 1974 1974 1974 1974 1974 ...
 ..$ HR      : int [1:914] 20 0 0 0 0 0 0 0 32 0 ...
$ : tibble [907 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:907] "aaronha01" "abbotgl01" "acostcy01" "adamsgl01" ...
 ..$ yearID  : int [1:907] 1975 1975 1975 1975 1975 1975 1975 1975 1975 1975 ...
 ..$ HR      : int [1:907] 12 0 0 4 0 0 0 0 12 0 ...
$ : tibble [886 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:886] "aaronha01" "abbotgl01" "adamsgl01" "adamsmi02" ...
 ..$ yearID  : int [1:886] 1976 1976 1976 1976 1976 1976 1976 1976 1976 1976 ...
 ..$ HR      : int [1:886] 10 0 0 0 0 0 0 0 2 0 ...
$ : tibble [984 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:984] "aasedo01" "abbotgl01" "adamsbo04" "adamsgl01" ...
 ..$ yearID  : int [1:984] 1977 1977 1977 1977 1977 1977 1977 1977 1977 1977 ...
 ..$ HR      : int [1:984] 0 0 2 6 0 0 0 1 0 5 ...
$ : tibble [960 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:960] "aasedo01" "abbotgl01" "adamsgl01" "adamsmi02" ...
 ..$ yearID  : int [1:960] 1978 1978 1978 1978 1978 1978 1978 1978 1978 1978 ...
 ..$ HR      : int [1:960] 0 0 7 0 0 0 10 17 0 0 ...
$ : tibble [961 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:961] "aasedo01" "abbotgl01" "adamsgl01" "aikenwi01" ...
 ..$ yearID  : int [1:961] 1979 1979 1979 1979 1979 1979 1979 1979 1979 1979 ...
 ..$ HR      : int [1:961] 0 0 8 21 2 0 15 0 0 3 ...
$ : tibble [950 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:950] "aasedo01" "abbotgl01" "adamsgl01" "aguaylu01" ...
 ..$ yearID  : int [1:950] 1980 1980 1980 1980 1980 1980 1980 1980 1980 1980 ...
 ..$ HR      : int [1:950] 0 0 6 1 20 0 0 5 0 0 ...
$ : tibble [944 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:944] "aasedo01" "abbotgl01" "adamsgl01" "agostju01" ...
 ..$ yearID  : int [1:944] 1981 1981 1981 1981 1981 1981 1981 1981 1981 1981 ...
 ..$ HR      : int [1:944] 0 0 2 0 1 17 0 0 1 0 ...
$ : tibble [992 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:992] "aasedo01" "adamsgl01" "adamsri02" "agostju01" ...
 ..$ yearID  : int [1:992] 1982 1982 1982 1982 1982 1982 1982 1982 1982 1982 ...
 ..$ HR      : int [1:992] 0 1 0 0 3 17 0 6 0 4 ...
$ : tibble [1,006 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1006] "abbotgl01" "abbotgl01" "ackerji01" "adamsri02" ...
 ..$ yearID  : int [1:1006] 1983 1983 1983 1983 1983 1983 1983 1983 1983 1983 ...
 ..$ HR      : int [1:1006] 0 0 0 2 0 0 0 23 0 0 ...
$ : tibble [984 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:984] "aasedo01" "abbotgl01" "ackerji01" "agostju01" ...
 ..$ yearID  : int [1:984] 1984 1984 1984 1984 1984 1984 1984 1984 1984 1984 ...
 ..$ HR      : int [1:984] 0 0 0 0 3 11 0 2 0 0 ...
$ : tibble [998 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:998] "aasedo01" "abregjo01" "ackerji01" "adamsri02" ...
 ..$ yearID  : int [1:998] 1985 1985 1985 1985 1985 1985 1985 1985 1985 1985 ...
 ..$ HR      : int [1:998] 0 0 0 2 0 6 0 1 0 0 ...
$ : tibble [1,017 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1017] "aasedo01" "ackerji01" "ackerji01" "adducji01" ...
 ..$ yearID  : int [1:1017] 1986 1986 1986 1986 1986 1986 1986 1986 1986 1986 ...
 ..$ HR      : int [1:1017] 0 0 0 0 0 0 4 2 0 2 ...
$ : tibble [1,048 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1048] "aasedo01" "abnersh01" "ackerji01" "afenitr01" ...
 ..$ yearID  : int [1:1048] 1987 1987 1987 1987 1987 1987 1987 1987 1987 1987 ...
 ..$ HR      : int [1:1048] 0 2 0 0 0 12 1 0 9 0 ...
$ : tibble [1,035 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1035] "aasedo01" "abnersh01" "ackerji01" "adducji01" ...
 ..$ yearID  : int [1:1035] 1988 1988 1988 1988 1988 1988 1988 1988 1988 1988 ...
 ..$ HR      : int [1:1035] 0 2 0 1 0 3 3 0 0 3 ...
$ : tibble [1,073 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1073] "aasedo01" "abbotji01" "abnersh01" "ackerji01" ...
 ..$ yearID  : int [1:1073] 1989 1989 1989 1989 1989 1989 1989 1989 1989 1989 ...
 ..$ HR      : int [1:1073] 0 0 2 0 0 0 0 1 0 0 ...
$ : tibble [1,115 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1115] "aasedo01" "abbotji01" "abbotpa01" "abnersh01" ...
 ..$ yearID  : int [1:1115] 1990 1990 1990 1990 1990 1990 1990 1990 1990 1990 ...
 ..$ HR      : int [1:1115] 0 0 0 1 0 0 0 0 0 0 ...
$ : tibble [1,086 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1086] "abbotji01" "abbotky01" "abbotpa01" "abnersh01" ...
 ..$ yearID  : int [1:1086] 1991 1991 1991 1991 1991 1991 1991 1991 1991 1991 ...
 ..$ HR      : int [1:1086] 0 0 0 1 2 0 0 0 0 0 ...
$ : tibble [1,066 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1066] "abbotji01" "abbotky01" "abbotpa01" "abnersh01" ...
 ..$ yearID  : int [1:1066] 1992 1992 1992 1992 1992 1992 1992 1992 1992 1992 ...
 ..$ HR      : int [1:1066] 0 0 0 1 0 0 0 0 0 0 ...
$ : tibble [1,180 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1180] "abbotji01" "abbotku01" "abbotpa01" "agostju01" ...
 ..$ yearID  : int [1:1180] 1993 1993 1993 1993 1993 1993 1993 1993 1993 1993 ...
 ..$ HR      : int [1:1180] 0 3 0 0 0 10 0 0 0 3 ...
$ : tibble [1,030 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1030] "abbotji01" "abbotku01" "acrema01" "aguilri01" ...
 ..$ yearID  : int [1:1030] 1994 1994 1994 1994 1994 1994 1994 1994 1994 1994 ...
 ..$ HR      : int [1:1030] 0 9 0 0 4 5 8 14 22 0 ...
$ : tibble [1,253 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1253] "abbotji01" "abbotji01" "abbotku01" "abbotky01" ...
 ..$ yearID  : int [1:1253] 1995 1995 1995 1995 1995 1995 1995 1995 1995 1995 ...
 ..$ HR      : int [1:1253] 0 0 17 0 0 0 0 0 0 0 ...
$ : tibble [1,253 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1253] "abbotji01" "abbotku01" "abbotky01" "abreubo01" ...
 ..$ yearID  : int [1:1253] 1996 1996 1996 1996 1996 1996 1996 1996 1996 1996 ...
 ..$ HR      : int [1:1253] 0 8 0 0 0 0 0 0 0 0 ...
$ : tibble [1,236 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1236] "abbotje01" "abbotku01" "abreubo01" "aceveju01" ...
 ..$ yearID  : int [1:1236] 1997 1997 1997 1997 1997 1997 1997 1997 1997 1997 ...
 ..$ HR      : int [1:1236] 1 6 3 0 0 0 0 0 0 0 ...
$ : tibble [1,322 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr [1:1322] "abbotje01" "abbotji01" "abbotku01" "abbotku01" ...
 ..$ yearID  : int [1:1322] 1998 1998 1998 1998 1998 1998 1998 1998 1998 1998 ...
 ..$ HR      : int [1:1322] 12 0 2 3 0 17 0 0 0 0 ...
 [list output truncated]
@ ptype: tibble [0 × 3] (S3: tbl_df/tbl/data.frame)
 ..$ playerID: chr(0) 
 ..$ yearID  : int(0) 
 ..$ HR      : int(0)

All the Data

df <-
  lst |> 
  ## make the list of data frames:
  map(top_hr_hitters, n = 5) |> 
  ## purrr::list_rbind() makes one df from the list:
  list_rbind()

All at Once (With Chaining)!

Other purr Higher-Order Functions

`keep()`

keep() is similar to dplyr’s filter(), but whereas filter() chooses rows of a data frame based on a given conditions, keep() chooses the elements of the input list or vector .x based on a condition named .p.

Example

From a vector, keep the numbers that are 1 more than a multiple of 3:

Another Example

In a data frame, keep the columns that are factor-variables:

`discard()`

discard(.x,, . p = condition) is equivalent to keep(.x, .p = !condition). Thus:

Another Example

`reduce()`

Given a vector .x and a function .f that takes two inputs, reduce() does the following:

applies f to elements 1 and 2 of .x, getting a result;
applies f to the result and to element 3 of .x, getting another result;
applies f to this new result and to element 4 of .x, getting yet another result …
… and so on until all of the elements of .x have been exhausted.
then reduce() returns the final result in the above series of operations.

Example

Suppose that you want to add up the elements of the vector:

vec <- c(3, 1, 4, 6)

Of course you could just use:

sum(vec)

[1] 14

But we will use reduce().

The Idea

vec <- c(3, 1, 4, 6)

add the 3 and 1 (the first two elements of vec), getting 4;
then add 4 to 4, the third element of vec, getting 8;
then add 8 to 6, the final element of vec, getting 14;
then return 14.

Implement the Idea

Another Example: Intersection

A common application of reduce is to take an operation that is defined on only two items and extend it to operate on any number of items.

Consider the function intersect():

vec1 <- c(3, 4, 5, 6)
vec2 <- c(4, 6, 8, -4)
intersect(vec1, vec2)

[1] 4 6

Limitation of `intersect()`

You cannot intersect three or more vectors at once:

intersect(vec1, vec2, c(4, 7, 9))

Error in `base::intersect()`:
! unused argument (c(4, 7, 9))

Higher-Order Functions in Package purrr

Packages

map() and Variations

A Task

Solve With a Loop

Solve with map()

How map() Works

More Control

What is This Code Doing?

How It Works

Vary Two or More Parameters of a Function

How This Works

Why Not Vary All Three Parameters?

Write Your Own Helper Function

Try It Out

Now Map!

Map with an Anonymous Function

Shorthand for Anonymous Functions

Mapping With Data Frames

Options for Other Types of Output

Example

Another Example

Yet Another Example

When Output is a List of Data Frames

The Data

A Helper Function

Split the Data

All the Data

All at Once (With Chaining)!

Other purr Higher-Order Functions

keep()

Example

Another Example

discard()

Another Example

reduce()

Example

The Idea

Implement the Idea

Another Example: Intersection

Limitation of intersect()

reduce() to the Rescue!

`map()` and Variations

Solve with `map()`

How `map()` Works

`keep()`

`discard()`

`reduce()`

Limitation of `intersect()`

`reduce()` to the Rescue!