PYTHON

merge two dataframes based on column

df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column

df_outer

how to merge more than 2 dataframes in python

df = pd.concat( [df1,df2,df3], ignore_index=True )

merge three dataframes pandas based on column

# 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)

merge two dataframes based on column

df_merge_col = pd.merge(df_row, df3, on='id')

df_merge_col

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')

Merge multiple dataframs

# compile the list of dataframes you want to merge
data_frames = [df1, df2, df3]

df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
                                            how='outer'), data_frames)

# if you want to fill the values that don't exist in the lines of merged dataframe simply fill with required strings as

df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
                                            how='outer'), data_frames).fillna('void')

Merge multiple dataframs

from functools import reduce

Name of a column in all dataframes is 'DATE'

df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
                                            how='outer'), data_frames)

# if you want to fill the values that don't exist in the lines of merged dataframe simply fill with required strings as

df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
                                            how='outer'), data_frames).fillna('void')

Merge multiple dataframs

from functools import reduce
import pandas as pd

dfs = [df1, df2, df3, ...]
nan_value = 0

# solution 1 (fast)
result_1 = pd.concat(dfs, join='outer', axis=1).fillna(nan_value)

# solution 2
result_2 = reduce(lambda df_left,df_right: pd.merge(df_left, df_right, 
                                              left_index=True, right_index=True, 
                                              how='outer'), 
                  dfs).fillna(nan_value)

Merge multiple dataframs

df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
                                            how='outer'), data_frames)

# if you want to fill the values that don't exist in the lines of merged dataframe simply fill with required strings as

df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
                                            how='outer'), data_frames).fillna('void')