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import pandas
dfinal = df1.merge(df2, on="movie_title", how = 'inner')
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pd.merge(df1, df2, left_index=True, right_index=True, how='outer')
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df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outer
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import pandas as pd
import numpy as np
df1 = pd.DataFrame({'fruit': ['apple', 'banana', 'orange'] * 3,
'weight': ['high', 'medium', 'low'] * 3,
'price': np.random.randint(0, 15, 9)})
df2 = pd.DataFrame({'pazham': ['apple', 'orange', 'pine'] * 2,
'kilo': ['high', 'low'] * 3,
'price': np.random.randint(0, 15, 6)})
out = df1.merge(df2,left_on=('fruit','weight'),right_on=('pazham','kilo'),how='inner',suffixes=('_left','_right')).head(10)
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# Merging 3 or more dataframes base on a common column
import pandas as pd
from functools import reduce
#Create a list of df to combine
list_of_df = [df_1,df_2,df_3]
#merge them together
df_combined = reduce(lambda left,right: pd.merge(left,right,on='common column'), list_of_df)
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dfinal = df1.merge(df2, how='inner', left_on='movie_title', right_on='movie_name')