How to Create Empty Data Frame | Pandas Data Frame | Pandas Tutorial | Pandas

In Pandas, you can create an empty DataFrame with column labels and data types specified, like this:

import pandas as pd

# Create an empty DataFrame with column labels and data types specified
df = pd.DataFrame(columns=['Name', 'Age'], dtype='int')

# Print the DataFrame
print(df)
In this example, we use the pd.DataFrame constructor to create an empty DataFrame df with column labels 'Name' and 'Age' specified as a list of strings. We also specify the data type of each column as 'int' using the dtype parameter. The resulting DataFrame has no rows, but the specified column labels and data types.

Alternatively, you can create an empty DataFrame and add columns and rows later, like this:

# Create an empty DataFrame
df = pd.DataFrame()

# Add columns to the DataFrame
df['Name'] = []
df['Age'] = []

# Print the DataFrame
print(df)
In this example, we create an empty DataFrame df with no column labels or data types specified. We then add two empty columns to the DataFrame using the indexing operator [], where each empty column is represented as an empty list. The resulting DataFrame has no rows or data, but the specified column labels.

@ParagDhawan
code snippet

import pandas as pd
import numpy as np

# Create a empty dataframe
df = pd.DataFrame()
print(df)

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