我正在寻找一种方法，将数据框中的所有列与另一个df中的列的值相除。可以使用下面提到的2个选项中的任何一个。
df_amenity_normalized = df_amenity.apply(
lambda row: row / df_targets['Population'].loc[row.name], axis=1)
或加入表，然后计算：
ndf=df_amenity.merge(df_targets, left_index=True, right_index=True)
ndft=ndf.apply(lambda x: x/ndf.Population, axis='rows' )
df_amenity_normalized1 = ndft.drop(columns=['Population', 'GNI', 'GDP', 'BM Dollar', 'HDI'])
还有其他方法可以达到相同的结果吗？
数据可在此处...
df_targets = pd.read_csv('https://raw.githubusercontent.com/njanakiev/osm-predict-economic-measurements/master/data/economic_measurements.csv', index_col='country')
df_targets.drop(columns='country_code', inplace=True)
df_targets = df_targets[['Population', 'GNI', 'GDP', 'BM Dollar', 'HDI']]
df_amenity = pd.read_csv('https://raw.githubusercontent.com/njanakiev/osm-predict-economic-measurements/master/data/country_amenity_counts.csv')
df_amenity.set_index('country', inplace=True)
df_amenity.drop(columns='country_code', inplace=True)