Using conditional to generate new column in pandas dataframe

Question

I have a pandas dataframe that looks like this:

   portion  used 0        1   1.0 1        2   0.3 2        3   0.0 3        4   0.8 

I'd like to create a new column based on the used column, so that the df looks like this:

   portion  used    alert 0        1   1.0     Full 1        2   0.3  Partial 2        3   0.0    Empty 3        4   0.8  Partial 

• Create a new alert column based on
• If used is 1.0, alert should be Full.
• If used is 0.0, alert should be Empty.
• Otherwise, alert should be Partial.

What's the best way to do that?

Answer 1

You can define a function which returns your different states "Full", "Partial", "Empty", etc and then use df.apply to apply the function to each row. Note that you have to pass the keyword argument axis=1 to ensure that it applies the function to rows.

import pandas as pd  def alert(row):   if row['used'] == 1.0:     return 'Full'   elif row['used'] == 0.0:     return 'Empty'   elif 0.0 < row['used'] < 1.0:     return 'Partial'   else:     return 'Undefined'  df = pd.DataFrame(data={'portion':[1, 2, 3, 4], 'used':[1.0, 0.3, 0.0, 0.8]})  df['alert'] = df.apply(alert, axis=1)  #    portion  used    alert # 0        1   1.0     Full # 1        2   0.3  Partial # 2        3   0.0    Empty # 3        4   0.8  Partial