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How to SORT ROWs within a Pandas DataFrame in Python

Sorting rows within a Pandas DataFrame in Python can be done by using the sort_values() function. This function allows you to sort the rows of a DataFrame based on one or more columns.

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', 'Eggplant'],

'price': [1.2, 2.3, 2.5, 1.7, 2.0],

'quantity': [3, 5, 2, 4, 8]}

df = pd.DataFrame(data)

Next, you can use the sort_values() function to sort the rows of the DataFrame based on one or more columns.

For example, if you want to sort the DataFrame by the ‘product’ column in alphabetical order, you can use the following code:

df.sort_values(by='product')

You can also sort the dataframe by multiple columns by passing the list of column names to sort by

df.sort_values(by=['product','price'])

You can also use the ascending parameter to define if the sorting should be in ascending or descending order.

df.sort_values(by='product', ascending=False)

By using the sort_values() function, you can easily sort the rows of a Pandas DataFrame in Python. This can be useful for data analysis, as it allows you to better understand and organize the data. It can also be used to sort data according to the business logic before performing any analysis on the same.

In this Learn through Codes example, you will learn: How to SORT ROWs within a Pandas DataFrame in Python.

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