join on column pandas
# df1 as main df and use the feild from df2 and map it into df1
df1.merge(df2,on='columnName',how='left')join on column pandas
# df1 as main df and use the feild from df2 and map it into df1
df1.merge(df2,on='columnName',how='left')join in pandas
import pandas as pd
clients = {'Client_ID': [111,222,333,444,555],
'Client_Name': ['Jon Snow','Maria Green', 'Bill Jones','Rick Lee','Pamela Lopez']
}
df1 = pd.DataFrame(clients, columns= ['Client_ID','Client_Name'])
countries = {'Client_ID': [111,222,333,444,777],
'Client_Country': ['UK','Canada','Spain','China','Brazil']
}
df2 = pd.DataFrame(countries, columns= ['Client_ID', 'Client_Country'])
Inner_Join = pd.merge(df1, df2, how='inner', on=['Client_ID', 'Client_ID'])
print(Inner_Join)join pandas dataframe by column
df_outer = pd.merge(df1, df2, on='id', how='outer')
df_inner = pd.merge(df1, df2, on='id', how='inner')join to dataframes pandas
>>> df.join(other.set_index('key'), on='key')
key A B
0 K0 A0 B0
1 K1 A1 B1
2 K2 A2 B2
3 K3 A3 NaN
4 K4 A4 NaN
5 K5 A5 NaNpandas join dataframe
#https://pandas.pydata.org/docs/user_guide/merging.htmlCopyright © 2021 Codeinu
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