Creating a column in pandas dataframe

Question

I have a pandas dataframe as below:

import pandas as pd
import numpy as np
df = pd.DataFrame({'ORDER':["A", "A", "A", "A", "B","B"], 'A':[80, 23, np.nan, 60, 1,22], 'B': [80, 55, 5, 76, 67,np.nan]})
df

       ORDER    A        B
0       A       80.0    80.0
1       A       23.0    55.0
2       A       NaN     5.0
3       A       60.0    76.0
4       B       1.0     67.0
5       B       22.0    NaN

I want to create a column "new" as below: If ORDER == 'A', then new=df['A'] If ORDER == 'B', then new=df['B']

This can be achieved using the below code:

df['new'] = np.where(df['ORDER'] == 'A', df['A'],  np.nan)
df['new'] = np.where(df['ORDER'] == 'B', df['B'],  df['new'])

The tweak here is if ORDER doesnot have the value "B", Then B will not be present in the dataframe.So the dataframe might look like below. And if we use the above code o this dataframe, it will give an error because column "B" is missing from this dataframe.

       ORDER    A    
0       A       80.0
1       A       23.0
2       A       NaN  
3       A       60.0
4       A       1.0  
5       A       22.0

Erfan · Accepted Answer · 2020-07-10 17:03:40Z

1

Use DataFrame.lookup, so you dont need to hardcode df['B'], but it looksup the column value:

df['new'] = df.lookup(df.index, df['ORDER'])

  ORDER     A     B   new
0     A  80.0  80.0  80.0
1     A  23.0  55.0  23.0
2     A   NaN   5.0   NaN
3     A  60.0  76.0  60.0
4     B   1.0  67.0  67.0
5     B  22.0   NaN   NaN

answered Jul 10, 2020 at 17:03

Erfan

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