A New Week!

We aren’t computer scientists and that’s okay!

We make lots of mistakes. Mistakes are funny. You can laugh with us.

Let’s go, Simba, Pumbaa, and Timon!

1 bind multiple data frames

1.1 bind_cols()

Bind multiple data frames by column.

All data frames must have the same number of rows.

library(tidyverse)

one <- airquality[1:4, 1:2]
two <- airquality[9:12, 4:5]

bind_cols(one, two)

# rows are matched by position.

1.2 bind_rows()

Bind multiple data frame by rows.

one <- airquality[1:4, 1:3]

two <- airquality[9:10, 1:3]

three <- airquality[11, 1:4] # a dataframe with four columns

bind_rows(one, two, three)

# Columns are matched by name. Missing columns will be filled with NA.

2 reshape data

2.1 pivot_longer()

We use this function to increase the number of rows and decrease the number of columns.

# create a data frame 
df <- data.frame(site = 1:3,
                 jan = runif(3, 0, 1),
                 feb = rnorm(3, 5),
                 mar = rnorm(3, 10))

long_df <- df %>% 
  pivot_longer(-site, names_to = "month", values_to = "value" )

df %>% 
  pivot_longer(jan:mar, names_to = "month", values_to = "value")

cheatsheet of tidyr

https://raw.githubusercontent.com/rstudio/cheatsheets/main/tidyr.pdf

Exercise

Apply the pivot_longer() function to reshape the billboard dataset

2.2 pivot_wider()

This function is the inverse transformation of pivot_longer().

pivot_wider(long_df, names_from = month, values_from = value)