I need to change the value of myCol if a condition is true. If the condition is not true, nothing should happen (if I do else None, it writes None as value to myCol)
tmp_df = someDataframe.groupby('ID').myCol.apply(lambda x: 'a' if (x=='A').any() else *DO NOTHING, THE myCol VALUE HAS TO STAY SAME*)
tmp_df=tmp_df.to_frame()
If you want to leave the value unchanged you can set the else value to the lambda argument x:
df.col.apply(lambda x: new_value if some_condition else x)
In your language:
tmp_df = someDataframe.groupby('ID').myCol.apply(lambda x: 'a' if (x=='A').any() else x)
Depending on the complexity there is probably a more efficient answer here. I use np.where to get your answer.
import numpy as np
df['conditional'] = np.where(
(df['conditional'] == 'A'), # Condition
'a', # Value if true
df['conditional'] # Value if false
# /\ this is equal to the original value so it has no effect
)
Documentation: https://docs.scipy.org/doc/numpy/reference/generated/numpy.where.html
did you try this:
tmp_df = someDataframe.groupby('ID').myCol.apply(lambda x: 'a' if (x=='A').any() else x)
