pivot_wider (long to wide) in R Programming - Step-by-Step Execution

Concept Flow - pivot_wider (long to wide)

Start with long data

↓

Identify key columns: id, names, values

↓

Spread 'names' into columns

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Fill cells with corresponding 'values'

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Result: wide data frame

pivot_wider takes a long table and spreads key-value pairs into new columns, making data wider.

Execution Sample

R Programming

library(tidyr)
data_long <- data.frame(
  id = c(1,1,2,2),
  key = c('A','B','A','B'),
  value = c(10,20,30,40)
)
data_wide <- pivot_wider(data_long, names_from = key, values_from = value)

This code converts a long data frame with keys and values into a wide format with keys as columns.

Execution Table

Step	Action	Input Data	Transformation	Output Data
1	Start	[id=1,A,10; 1,B,20; 2,A,30; 2,B,40]	None	Same as input
2	Identify columns	id, key, value	Set names_from=key, values_from=value	Ready to spread
3	Spread keys	Keys: A, B	Create columns A and B	Columns A and B added
4	Fill values	Match id and key	Fill cells with values	id=1: A=10, B=20; id=2: A=30, B=40
5	Result	Wide data frame	No further change	id | A | B 1 |10 |20 2 |30 |40

💡 All keys spread into columns, values filled, transformation complete.

Variable Tracker

Variable	Start	After Step 3	After Step 4	Final
data_long	[1,A,10;1,B,20;2,A,30;2,B,40]	[1,A,10;1,B,20;2,A,30;2,B,40]	[1,A,10;1,B,20;2,A,30;2,B,40]	[1,A,10;1,B,20;2,A,30;2,B,40]
data_wide	NULL	Columns A and B created, empty	Values filled in columns A and B	id=1: A=10, B=20; id=2: A=30, B=40

Key Moments - 2 Insights

Why do we need to specify 'names_from' and 'values_from'?

Because pivot_wider needs to know which column's values become new column names ('names_from') and which column's values fill those new columns ('values_from'). See execution_table step 2.

What happens if there are multiple values for the same id and key?

pivot_wider will give an error or summarize values if specified. Here, each id-key pair is unique, so values fill directly (execution_table step 4).

Visual Quiz - 3 Questions

Look at the execution_table at step 4, what values are assigned to id=2 in columns A and B?

A A=20, B=10

B A=30, B=40

C A=40, B=30

D A=10, B=20

💡 Hint

Check the 'Output Data' column in step 4 of execution_table.

At which step are new columns created in the wide data frame?

A Step 5

B Step 1

C Step 3

D Step 2

💡 Hint

Look at the 'Transformation' column describing column creation.

If the 'key' column had a third unique value 'C', how would the variable_tracker for data_wide change after step 3?

A Columns A, B, and C would be created

B Only columns A and B would be created

C No new columns would be created

D Columns would be deleted

💡 Hint

Refer to variable_tracker showing columns created after step 3.

Concept Snapshot

pivot_wider(data, names_from, values_from)
- Converts long data to wide format
- 'names_from' picks column for new column names
- 'values_from' picks column for filling values
- Each unique id gets one row
- Useful to reshape data for analysis

Full Transcript

pivot_wider is a function in R that changes data from long format to wide format. It takes a data frame with repeated ids and keys and spreads the keys into new columns. The values fill these new columns. The process starts by identifying which columns to use for new column names and which for values. Then it creates new columns for each unique key and fills them with corresponding values. The final result is a wider data frame with one row per id and multiple columns for keys. This helps organize data for easier analysis or visualization.