I have dataframe
city_reg city_live reg_region live_region
Moscow Tver 77 69
Tambov Tumen' 86 86
I need to replace values in city_reg to values from city_live if reg_region == live_region
I try to use
df.loc[df.reg_region == df.live_region, 'city_reg'] = df['city_live']
but it returnes
ValueError: cannot reindex from a duplicate axis
How can I fix that?
Use mask or numpy.where which working with duplicated indices very nice:
#create duplicated indices for test
df.index = [0,0]
print (df)
city_reg city_live reg_region live_region
0 Moscow Tver 77 69
0 Tambov Tumen' 86 86
df['city_reg'] = df['city_reg'].mask(df.reg_region == df.live_region, df['city_live'])
Or:
df['city_reg'] = np.where(df.reg_region == df.live_region, df['city_reg'], df['city_live'])
print (df)
city_reg city_live reg_region live_region
0 Moscow Tver 77 69
0 Tumen' Tumen' 86 86
Try this:
mask = df.reg_region == df.live_region
df.loc[mask, 'city_reg'] = df.loc[mask, 'city_live']
# city_reg city_live reg_region live_region
# 0 Moscow Tver 77 69
# 1 Tumen' Tumen' 86 86
The reason this works is that the indices are aligned between the left and right hand sides of the assignment when you apply the same mask.
