Pandas DataFrame: Manipulate value in one column based von value in other column-CodePudding

I got two Pandas DataFrames df and df_0:

df = pd.DataFrame({'condition': [1, 2, 3], 
                     'value': [1, 2, 3]})
df_0 = pd.DataFrame({'condition': [1, 2], 
                     'value': [1, 3]})
   condition  value
0          1      1
1          2      2
1          3      3
   condition  value
0          1      1
1          2      3

I want to subtract (-=) the value in df_0 from the value (column) in df, if the resp. condition value/column is the same.

Pseudo code 
df_desired_result = pd.DataFrame({'condition': [1, 2, 3], 
                     'value': [0, -1, 3]})

   condition  value
0          1      0
1          2     -1
2          3      3

How can I achiev this?

Thanks a lot in advance for your reply!

Lucy

CodePudding user response：

Pandas does an index wise arithmetic operations. just set the 'condition' to be the index, and then fill the NaN values

import pandas as pd
import numpy as np
df = pd.DataFrame({'condition': [1, 2, 3], 
                     'value': [1, 2, 3]})
df_0 = pd.DataFrame({'condition': [1, 2], 
                     'value': [1, 3]})
df_desired_result  = df.set_index('condition')-df_0.set_index('condition').reindex(df.condition,fill_value=0)
print(df_desired_result)