How to Identify Differences Between Two Dataframes in Python?

Comparing Two Dataframes to Identify Differences

To compare two dataframes, df1 and df2, and determine the differences between them, the following steps can be taken:

As the provided code df1 != df2 is only applicable for dataframes with identical rows and columns, an alternative approach is required. Concatenating the two dataframes into a single dataframe, df, will allow for a more thorough comparison.

<code class="python">import pandas as pd

df = pd.concat([df1, df2])</code>

Once concatenated, reset the index of df to avoid potential index conflicts.

<code class="python">df = df.reset_index(drop=True)</code>

Group the dataframe by each column to identify unique records.

<code class="python">df_gpby = df.groupby(list(df.columns))</code>

Extract the index of unique records, where the length of the group is 1.

<code class="python">idx = [x[0] for x in df_gpby.groups.values() if len(x) == 1]</code>

Filter the dataframe based on the unique index to obtain the differences between df1 and df2.

<code class="python">result = df.reindex(idx)</code>

The resulting result dataframe will contain the rows that are in df2 but not in df1.

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