I would like to reshape the folowing dataframe
into
Could somebody help me with that?
CodePudding user response:
You can try
out = df.pivot(index=['A', 'B'], columns='C', values='D').reset_index()
print(out)
C A B X Y
0 a aa 1 5
1 b bb 6 2
2 c cc 3 7
3 d dd 8 4
CodePudding user response:
Have you tried df.pivot()
or pd.pivot()
? The values in column C
will become column headers. After that, flatten the multi-index columns, and rename them.
import pandas as pd
#df = df.pivot(['A', 'B'], columns='C').reset_index() #this also works
df = pd.pivot(data=df, index=['A', 'B'], columns='C').reset_index()
df.columns = ['A', 'B', 'X', 'Y']
print(df)
Output
A B X Y
0 a aa 1 5
1 b bb 6 2
2 c cc 3 7
3 d dd 8 4
Sometimes, there might be repeated records with the same index, then you'd have to use pd.pivot_table()
instead. The param aggfunc=np.mean
will take the mean of these repeated records, and become type float
as you can see from the output.
import pandas as pd
import numpy as np
df = pd.pivot_table(data=df, index=['A', 'B'], columns='C', aggfunc=np.mean).reset_index()
df.columns = ['A', 'B', 'X', 'Y']
print(df)
Output
A B X Y
0 a aa 1.0 5.0
1 b bb 6.0 2.0
2 c cc 3.0 7.0
3 d dd 8.0 4.0