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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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df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outer
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#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')
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import pandas as pd
T1 = pd.merge(T1, T2, on=T1.index, how='outer')
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import pandas
dfinal = df1.merge(df2, on="movie_title", how = 'inner')
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merged_df = left_df.merge(right_df, how='inner', left_on=["A", "B"], right_on=["A2","B2"])
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df_cd = pd.merge(df_SN7577i_c, df_SN7577i_d, how='inner', left_on = 'Id', right_on = 'Id')
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# First dataframe with three columns
dlist=["vx","vy","vz"]
df=pd.DataFrame(columns=dlist)
df["vx"]=df1["v2x"]
df["vy"]=df1["v2y"]
df["vz"]=df1["v2z"]
# second dataframe with three columns
dlist=["vx","vy","vz"]
df0=pd.DataFrame(columns=dlist)
df0["vx"]=df2["v1x"]
df0["vy"]=df2["v1y"]
df0["vz"]=df2["v1z"]
# Here with concat we can create new dataframe with garther both in one
# YOU CAN PUT SOME VALUES IN EACH AND CHECK IT
# WHAT INSIDE THE CONCAT MUST BE A LIST OF DATAFRAME
v = pd.concat([df,df0])
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df_2017.merge(df_2018, left_on = 'Textbook?', right_on = 'Textbook?', how = 'inner', suffixes = ('_2017', '_2018'))\
.merge(df_2019, left_on = 'Textbook?', right_on = 'Textbook?', how = 'inner')\
.merge(df_2020, left_on = 'Textbook?', right_on = 'Textbook?', how = 'inner', suffixes = ('_2019', '_2020'))\
.merge(df_2021, left_on = 'Textbook?', right_on = 'Textbook?', how = 'inner')\
.merge(df_2022, left_on = 'Textbook?', right_on = 'Textbook?', how = 'inner', suffixes = ('_2021', '_2022'))\