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_outerpandas concat two dataframes
# Concating Means putting frames on bottom of one another
# --- ---
# | df1 |
# | df2 |
# Concating => | . |
# | . |
# | dfn |
# --- ---
# Command : pd.concat([df1,df2,...,dfn]) ; df = a dataframe
''':::Eaxmple;::'''
df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],
'B': ['B0', 'B1', 'B2', 'B3'],
'C': ['C0', 'C1', 'C2', 'C3'],
'D': ['D0', 'D1', 'D2', 'D3']},
index=[0, 1, 2, 3])
df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],
'B': ['B4', 'B5', 'B6', 'B7'],
'C': ['C4', 'C5', 'C6', 'C7'],
'D': ['D4', 'D5', 'D6', 'D7']},
index=[4, 5, 6, 7])
df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],
'B': ['B8', 'B9', 'B10', 'B11'],
'C': ['C8', 'C9', 'C10', 'C11'],
'D': ['D8', 'D9', 'D10', 'D11']},
index=[8, 9, 10, 11])
frames = [df1, df2, df3]
result = pd.concat(frames)
# Note : use ignore_index=True if you need it in pd.concatmerge two dataframes based on column
df_merge_col = pd.merge(df_row, df3, on='id')
df_merge_colCopyright © 2021 Codeinu
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