if I want to do the following in Pandas, how do I do it using Lambda:
df['c'] = 0
df['c'][(df['a']==1) | (df['b'] ==1)] = 1
Thanks
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2 Answers
I can't justify using a lambda
df.assign(c=df[['a', 'b']].eq(1).any(1).astype(int))
But if you insist:
df.assign(c=lambda d: d[['a', 'b']].eq(1).any(1).astype(int))
2 Comments
RJL
I was used to doing the following (create a two category c variable based on another variable):
df['c'] = df['a'].map(lambda x: 0 if x>5 else 1) can I do something similar using one variable?
piRSquared
Yes but I wouldn’t advise it
You can use apply but change the axis.
import pandas as pd
df =pd.DataFrame({'a':[1,2], 'b':[1,2]})
df['c'] = df.apply(lambda df: 1 if(df['a'] == 1| df['b']==1) else 0, axis = 1)
