pip install a-pandas-ex-df-updater
# Update a DataFrame/Series with the values of another.
from a_pandas_ex_df_updater import pd_add_df_updater
pd_add_df_updater()
df1 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]),
columns=['a', 'b', 'c'])
df2 = pd.DataFrame(np.array([[11, 2, 3], [4, 55, 6], [7, 8, 9], [17, 2, 93]]),
columns=['a', 'x', 'y'])
df3=df1.ds_update(forupdate=df2,update_existing_values=True, add_new_columns=False,add_new_rows=False)
df1
a b c
0 1 2 3
1 4 5 6
2 7 8 9
df2
a x y
0 11 2 3
1 4 55 6
2 7 8 9
3 17 2 93
df3
a b c
0 11 2 3
1 4 5 6
2 7 8 9
df3=df1.ds_update(forupdate=df2,update_existing_values=True, add_new_columns=True,add_new_rows=False)
df1
a b c
0 1 2 3
1 4 5 6
2 7 8 9
df2
a x y
0 11 2 3
1 4 55 6
2 7 8 9
3 17 2 93
df3
a b c x y
0 11 2 3 2 3
1 4 5 6 55 6
2 7 8 9 8 9
df3=df1.ds_update(forupdate=df2,update_existing_values=True, add_new_columns=True,add_new_rows=True)
df1
a b c
0 1 2 3
1 4 5 6
2 7 8 9
df2
a x y
0 11 2 3
1 4 55 6
2 7 8 9
3 17 2 93
df3
a b c x y
0 11 2.0 3.0 2 3
1 4 5.0 6.0 55 6
2 7 8.0 9.0 8 9
3 17 NaN NaN 2 93
df1.ds_update(forupdate=df2,update_existing_values=False, add_new_columns=True,add_new_rows=True)
df1
a b c
0 1 2 3
1 4 5 6
2 7 8 9
df2
a x y
0 11 2 3
1 4 55 6
2 7 8 9
3 17 2 93
df3
a b c x y
0 1 2.0 3.0 2 3
1 4 5.0 6.0 55 6
2 7 8.0 9.0 8 9
3 17 NaN NaN 2 93
Parameters:
df: Union[pd.Series, pd.DataFrame]
forupdate: Union[pd.Series, pd.DataFrame]
update_existing_values:bool
(default=True)
add_new_columns=True
(default=True)
add_new_rows=True
(default=True)
Returns:
Union[pd.Series, pd.DataFrame]
1 maintainer
Metadata
1 maintainer
Release files for a-pandas-ex-df-updater 0.11
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