Sort a CSV by a Column in Descending Order with Pandas

1. Introduction

A user asked how to sort a CSV file while preserving the header row, arranging the data by the fourth column in descending order and saving the result as a new CSV file.

2. Solution Process

The following straightforward Pandas approach solves the problem.

import pandas as pd
# Set the appropriate encoding for your file
df = pd.read_csv("test.csv", encoding="gbk")
print(df.head())
# Sort by the "总价" column in descending order and reset the index
df = df.sort_values(by=["总价"], ascending=[False], ignore_index=True)
print(df.head())
# Save to a new file without writing the index
df.to_csv("test2.csv", index=False)

For multiple‑column sorting you can pass a list of column names to by and a corresponding list of booleans to ascending, e.g., df.sort_values([col1, col2], ascending=[True, False]).

3. Summary

The provided code reads the original CSV, sorts it by the specified column in descending order while keeping the header unchanged, and writes the sorted data to a new CSV file. This method offers a quick, reproducible solution for common data‑processing tasks in Python.