merge multiple dataframs

1# compile the list of dataframes you want to merge
2data_frames = [df1, df2, df3]
3
4df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
5                                            how='outer'), data_frames)
6
7# if you want to fill the values that don't exist in the lines of merged dataframe simply fill with required strings as
8
9df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
10                                            how='outer'), data_frames).fillna('void')
11

1from functools import reduce
2
3Name of a column in all dataframes is 'DATE'
4
5df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
6                                            how='outer'), data_frames)
7
8# if you want to fill the values that don't exist in the lines of merged dataframe simply fill with required strings as
9
10df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
11                                            how='outer'), data_frames).fillna('void')
12

1from functools import reduce
2import pandas as pd
3
4dfs = [df1, df2, df3, ...]
5nan_value = 0
6
7# solution 1 (fast)
8result_1 = pd.concat(dfs, join='outer', axis=1).fillna(nan_value)
9
10# solution 2
11result_2 = reduce(lambda df_left,df_right: pd.merge(df_left, df_right, 
12                                              left_index=True, right_index=True, 
13                                              how='outer'), 
14                  dfs).fillna(nan_value)
15

1df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
2                                            how='outer'), data_frames)
3
4# if you want to fill the values that don't exist in the lines of merged dataframe simply fill with required strings as
5
6df_merged = reduce(lambda  left,right: pd.merge(left,right,on=['DATE'],
7                                            how='outer'), data_frames).fillna('void')
8