How to Convert Text Files to DataFrames in Python?

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To convert text files to DataFrames in Python, you can use the pandas library. pandas provides various functions to read text files and create DataFrames from them. Here’s an example of how to convert a text file to a DataFrame:

import pandas as pd

# Read the text file into a DataFrame
df = pd.read_csv('input.txt', delimiter='\t')

# Print the DataFrame
print(df)

In this example, we use pd.read_csv() from pandas to read the text file 'input.txt' into a DataFrame. You might need to adjust the delimiter parameter based on the actual delimiter used in your text file. By default, read_csv() assumes the delimiter is a comma (,), but you can specify a different delimiter using the delimiter parameter.

Once the text file is read into the DataFrame, you can perform various operations on it or manipulate the data as needed. The print(df) statement in the example simply prints the DataFrame to the console for demonstration purposes.

Make sure to have the pandas library installed before running the code. You can install it using pip:

pip install pandas

After running the code, the text file will be converted to a DataFrame, and you can work with the DataFrame using the functionality provided by pandas.

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