merge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outermerge two dataframes based on column
df_outer = pd.merge(df1, df2, on='id', how='outer') #here id is common column
df_outerjoin on column pandas
# df1 as main df and use the feild from df2 and map it into df1
df1.merge(df2,on='columnName',how='left')pandas merge multiple dataframes
import pandas as pd
from functools import reduce
# 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=['key_col'],
how='outer'), data_frames)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')Copyright © 2021 Codeinu
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