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How to format STRING in a Pandas DataFrame in Python

Formatting strings in a Pandas DataFrame in Python can be done by using string functions and the apply() function. This can be useful for cleaning and preprocessing data before analysis.

First, you need to import the Pandas library and create a DataFrame. For example, you can create a DataFrame with some sample data.

import pandas as pd

data = {'product': ['Apple', 'Banana', 'Cherry', 'Date'], 'price': [1.2, 2.3, 2.5, 1.7]}

df = pd.DataFrame(data)

Next, you can use string functions and the apply() function to format the strings in the DataFrame. For example, if you want to convert all the strings in the ‘product’ column to uppercase, you can use the following code:

df['product'] = df['product'].apply(lambda x: x.upper())

Alternatively, you can use the .str accessor and chain the method upper() to change the case of string

df['product'] = df['product'].str.upper()

You can also use other string functions such as lower() and title() to change the case of the strings in the DataFrame.

To strip whitespace from the beginning and end of the string in a column, you can use strip() function

df['product'] = df['product'].apply(lambda x: x.strip())

You can also use other string functions such as replace() and find() to format the strings in the DataFrame.

By formatting strings in a Pandas DataFrame, you can clean and preprocess your data to make it easier to work with. This can be especially helpful when working with large datasets or when preparing data for analysis.

In this Learn through Codes example, you will learn: How to format STRING in a Pandas DataFrame in Python.

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