How to Create an Empty DataFrame in Python

In this tutorial, we’ll explore how to create an empty DataFrame in Python using the well-known data manipulation library, pandas. A DataFrame is a two-dimensional labeled data structure with columns of potentially different types, making it a great tool for data cleaning, transformation, and analysis.

Creating an empty DataFrame is particularly handy when we know the structure of our data but the data itself is not ready yet. Being comfortable with creating and handling empty DataFrames is an important step in becoming proficient with pandas and data manipulation in Python in general.

Step 1: Importing Necessary Libraries

Before we can create a DataFrame, we’ll first need to import the pandas library. If you don’t have pandas installed, you can easily do so with pip:

1
!pip install pandas

Once pandas is installed, it can be imported into your Python environment using the import keyword:

1
import pandas as pd

Step 2: Creating an Empty DataFrame

Creating an empty DataFrame in pandas is quite straightforward. You just need to call the DataFrame() function without passing any arguments.

1
df = pd.DataFrame()

If you print this DataFrame, it will return an empty DataFrame:

1
print(df)

Output:

Empty DataFrame
Columns: []
Index: []

Step 3: Add Columns to the Empty DataFrame

After creating an empty DataFrame, you might want to add columns to it. This can be achieved by defining a list of column names and assigning it to the columns attribute of the DataFrame.

1
2
3
4
5
df['Column1'] = [1, 2, 3]  # Adding a column with values [1, 2, 3]
df['Column2'] = ['A', 'B', 'C']  # Adding a column with string values
 
print("\nDataFrame with added columns:")
print(df)

Full Code:

1
2
3
4
5
6
7
8
9
10
11
import pandas as pd
 
df = pd.DataFrame()
print(df)
 
df['Column1'] = [1, 2, 3]  # Adding a column with values [1, 2, 3]
df['Column2'] = ['A', 'B', 'C']  # Adding a column with string values
 
print("\nDataFrame with added columns:")
print(df)
 

Conclusion:

That’s it! We’ve successfully created an empty DataFrame in Python using Pandas, and we’ve learned how to add columns to the DataFrame. This is a very useful skill when working with data in Python, as it provides a solid foundation for Data Analysis and Data Science operations.