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Updated on 2025-03-02

Use Pandas to efficiently read and filter csv data

Preface

Pandas is one of the most commonly used libraries in Python for data processing and analysis in the fields of data analytics and data science. This article will describe how to use Pandas to read and process data files in CSV format.

What is a CSV file

CSV (comma-separated values) files are a common text file format used to store tabular data, where each row represents a record and fields are separated by commas or other specific separators. CSV files can be opened using any text editor and are easy to read and edit.

Environmental preparation

First, make sure the Pandas library is installed. Pandas can be installed on the command line using pip:

pip install pandas

Read CSV files using Pandas

To read a CSV file using Pandas, follow these steps:

Import the Pandas library

Import the Pandas library in a Python script or Jupyter Notebook:

import pandas as pd

Read CSV files

Use the pd.read_csv() function to read a CSV file:

df = pd.read_csv('')

Here is the path to the CSV file to be read.

Parameters and options

The pd.read_csv() function provides many parameters and options to read various types of CSV files. Here are some commonly used options:

  • sep: Specify a separator, such as a comma, or a tab character \t.
  • header: Specifies which row is used as the column name (usually the first row), and the default is 0.
  • names: Custom column name, pass in a list.
  • index_col: Specify which column is used as the index column.
  • dtype: Specifies the data type for each column.
  • skiprows: skip data with specified number of rows.
  • na_values: Treats the specified value as a null value.

For example:

df = pd.read_csv('', sep=';', header=0, names=['col1', 'col2', 'col3'])

View data

After reading a CSV file using Pandas, you can quickly view the data by:

Check the first few lines of data:

()  # The first 5 lines are displayed by default

View basic information about the data:

()

Example

Suppose we have a CSV file named , containing the following data:

Name,Age,City
John,30,New York
Alice,25,San Francisco
Bob,35,Los Angeles

import pandas as pd

# Read CSV filedf = pd.read_csv('')

# View the first few lines of dataprint(())

----------
The output result is as follows：

    Name  Age           City
0   John   30       New York
1  Alice   25  San Francisco
2    Bob   35    Los Angeles

Summarize

This article describes how to use the Pandas library to read data files in CSV format. With a few simple lines of code, you can quickly load CSV data and start data analysis and processing. Pandas provides a wealth of features and options to meet a variety of data processing needs and is one of the important tools in data science work.

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