mspu.pandas.df_diffs#

mspu.pandas.df_diffs(df1: DataFrame, df2: DataFrame, left_suffix: str = '_df1', right_suffix: str = '_df2') → DataFrame[source]#

Get rows in two dfs that are different to each other.

Comparison is based on df MultiIndex.

Parameters:

df1pd.DataFrame: First DataFrame to compare.
df2pd.DataFrame: Second DataFrame to compare.
left_suffixstr: Suffix to append to column names from df1 in the output DataFrame.
right_suffixstr: Suffix to append to column names from df2 in the output DataFrame.

Returns:

pd.DataFrame: DataFrame containing rows that are different between df1 and df2, with suffixes indicating the source of each column.

Examples

>>> import pandas as pd
>>> from mspu.pandas import df_diffs
>>> df1 = pd.DataFrame({
...     'fruit': ['apple', 'banana', 'apple'],
...     'id': [1, 2, 4],
...     'store': ['us', 'uk', 'cn'],
...     'price': [4, 3.1, 2.5],
... }).set_index(['fruit', 'id'])
>>> print(df1)
        store  price
fruit  id
apple  1     us    4.0
banana 2     uk    3.1
apple  4     cn    2.5
>>> df2 = pd.DataFrame({
...     'fruit': ['apple', 'banana', 'apple'],
...     'id': [1, 3, 4],
...     'store': ['us', 'uk', 'cn'],
...     'price': [4, 3.2, 2.5],
... }).set_index(['fruit', 'id'])
>>> print(df2)
        store  price
fruit  id
apple  1     us    4.0
banana 3     uk    3.2
apple  4     cn    2.5
>>> diff = df_diffs(df1, df2)
>>> print(diff)
          store_df1  price_df1 store_df2  price_df2
fruit  id
banana 2         uk        3.1       NaN        NaN
       3        NaN        NaN        uk        3.2