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