Pandas group by with empty dataframe

Working with an empty pandas DataFrame and trying to apply a groupby operation can raise questions about what exactly happens and what you can expect in terms of output. Let's explore what occurs when you perform a groupby operation on an empty DataFrame and how to handle potential issues or considerations.

Creating an Empty DataFrame

First, let’s define what an empty DataFrame in pandas looks like:

import pandas as pd

# Create an empty DataFrame with predefined columns
df = pd.DataFrame(columns=['Group', 'Data'])

print(df)

In this example, df is an empty DataFrame with columns 'Group' and 'Data' but no rows.

Applying GroupBy on an Empty DataFrame

When you apply groupby to an empty DataFrame, the result will also be an empty DataFrame-like object, but it will be a GroupBy object with no groups.

# Perform a groupby operation
grouped = df.groupby('Group')

# Attempt to perform an aggregation
result = grouped.sum()

print(result)

Since there are no rows to group, the result of any aggregation (sum, mean, count, etc.) will also be empty, but the structure will respect the intended aggregation:

Empty DataFrame
Columns: [Data]
Index: []