xxxxxxxxxx
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outer
xxxxxxxxxx
# Stack the DataFrames on top of each other
vertical_stack = pd.concat([survey_sub, survey_sub_last10], axis=0)
# Place the DataFrames side by side
horizontal_stack = pd.concat([survey_sub, survey_sub_last10], axis=1)
xxxxxxxxxx
merged_df = DF2.merge(DF1, how = 'inner', on = ['date', 'hours'])
xxxxxxxxxx
#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')
xxxxxxxxxx
# 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)
xxxxxxxxxx
import pandas as pd
T1 = pd.merge(T1, T2, on=T1.index, how='outer')
xxxxxxxxxx
import pandas
dfinal = df1.merge(df2, on="movie_title", how = 'inner')