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Write a Python program to reshape a given dataframe in different ways
We can reshape a dataframe using melt(),stack(),unstack() and pivot() function.
Solution 1
Define a dataframe.
Apply melt() function to convert wide dataframe column as rows. It is defined below,
df.melt()
Example
Let’s see the below code to get a better understanding −
import pandas as pd
df = pd.DataFrame({'Id':[1,2,3],'Age':[13,14,13],'Mark':[80,90,85]})
print("Dataframe is:\n",df)
print(df.melt())Output
Dataframe is: Id Age Mark 0 1 13 80 1 2 14 90 2 3 13 85 variable value 0 Id 1 1 Id 2 2 Id 3 3 Age 13 4 Age 14 5 Age 13 6 Mark 80 7 Mark 90 8 Mark 85
Solution 2
Define a dataframe.
Apply stack() function to increase the level of the index in a dataframe. It is defined below,
df.stack().to_frame()
If you want to revert back the changes, you can use unstack().
df.unstack().to_frame()
Example
Let’s see the below implementation to get a better understanding −
import pandas as pd
df = pd.DataFrame({'Id':[1,2,3],'Age':[13,14,13],'Mark':[80,90,85]})
print("Dataframe is:\n",df)
print(df.stack().to_frame())
print(df.unstack().to_frame())Output
Dataframe is: Id Age Mark 0 1 13 80 1 2 14 90 2 3 13 85 0 0 Id 1 Age 13 Mark 80 1 Id 2 Age 14 Mark 90 2 Id 3 Age 13 Mark 85 0 Id 0 1 1 2 2 3 Age 0 13 1 14 2 13 Mark 0 80 1 90 2 85
Solution 3
Define a dataframe
Apply pivot() function to reshape a dataframe based on Id column,
df.pivot(columns='Id')
Example
Let’s see the below implementation to get a better understanding −
import pandas as pd
df = pd.DataFrame({'Id':[1,2,3],'Age':[13,14,13],'Mark':[80,90,85]})
print("Dataframe is:\n",df)
print(df.pivot(columns='Id'))Output
Dataframe is: Id Age Mark 0 1 13 80 1 2 14 90 2 3 13 85 Age Mark Id 1 2 3 1 2 3 0 13.0 NaN NaN 80.0 NaN NaN 1 NaN 14.0 NaN NaN 90.0 NaN 2 NaN NaN 13.0 NaN NaN 85.0
Updated on: 25-Feb-2021
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