Question

State whether the following statement is True or False:
In Python, we cannot create an empty DataFrame.

Hint:

Always remember: pandas is a very flexible library — you can create empty DataFrames and build them up later as your data processing needs grow.

Answer 1

The statement given is False.
In Python, using the pandas library, it is entirely possible and very common to create an empty DataFrame.
An empty DataFrame is simply a DataFrame object that contains no rows and no columns initially.
This is often useful when you want to create a structure first and then append data later through operations such as loops, conditional statements, or by reading in data from external sources.
Example:
To create an empty DataFrame, you can write:

import pandas as pd
df = pd.DataFrame()
print(df)

When you run this code, the output will be:

Empty DataFrame
Columns: []
Index: []

This shows that the DataFrame has no columns and no index values, confirming that it is empty.
Moreover, you can also create an empty DataFrame with specified column names but no data. For example:

df2 = pd.DataFrame(columns=['Name', 'Age', 'Marks'])
print(df2)

This will output:

Empty DataFrame
Columns: [Name, Age, Marks]
Index: []

This is very useful when you know the structure of your data in advance but will fill it dynamically later.
Therefore, the claim that we cannot create an empty DataFrame in Python is not correct.