merge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outer
merge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outer
pd merge on multiple columns
new_df = pd.merge(A_df, B_df, how='left', left_on=['A_c1','c2'], right_on = ['B_c1','c2'])
pandas create a new column based on condition of two columns
conditions = [
df['gender'].eq('male') & df['pet1'].eq(df['pet2']),
df['gender'].eq('female') & df['pet1'].isin(['cat', 'dog'])
]
choices = [5,5]
df['points'] = np.select(conditions, choices, default=0)
print(df)
gender pet1 pet2 points
0 male dog dog 5
1 male cat cat 5
2 male dog cat 0
3 female cat squirrel 5
4 female dog dog 5
5 female squirrel cat 0
6 squirrel dog cat 0
pandas merge two columns from different dataframes
#suppose you have two dataframes df1 and df2, and
#you need to merge them along the column id
df_merge_col = pd.merge(df1, df2, on='id')
how to merge two pandas dataframes on a column
import pandas as pd
T1 = pd.merge(T1, T2, on=T1.index, how='outer')
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