Getting Started with Pandas: Reading Data from Excel

Quick Start pandas: How to read Excel files, specific code examples are required

Introduction: pandas is a popular data processing and analysis tool in Python, which provides It provides rich data structures and functions to facilitate users to clean, convert and analyze data. This article will introduce how to use the pandas library to read Excel files and give specific code examples.

1. Install the pandas library

Before using pandas, you need to install the library first. You can install pandas by entering the following command on the command line:

pip install pandas

2. Import the pandas library

Before you start using pandas, you need to import the library first. It is generally customary to import pandas as pd, because this is a common usage and facilitates subsequent code writing and reading.

import pandas as pd

3. Reading Excel files

Next, we will demonstrate how to use pandas to read Excel files.

Before reading the Excel file, you need to place the Excel file to be read in the current working directory. You can use the following command to view the current working directory:

import os

print(os.getcwd())

In the current working directory, we have placed an Excel file named "sample.xlsx" as a sample.

The following is a code example for reading an Excel file:

df = pd.read_excel('sample.xlsx')
print(df)

In the above code, we use the read_excel function to read the Excel file and save the result in a In a DataFrame object named df.

4. Display data

After reading the Excel file, we can use various operations to process the data. Next, we will demonstrate how to display the read data.

1. Display the first few rows of data

print(df.head())  # 默认显示前5行数据
print(df.head(10))  # 显示前10行数据

2. Display the next few rows of data

print(df.tail())  # 默认显示后5行数据
print(df.tail(10))  # 显示后10行数据

3. Display the specified rows and columns The data

print(df.iloc[0])  # 显示第一行数据（索引从0开始）
print(df['column_name'])  # 显示指定列的数据，其中column_name为列名
print(df[['column1', 'column2']])  # 显示多个列的数据

5. Save the data

After processing the data, we may need to save the results to an Excel file. pandas provides the to_excel function for saving data to Excel. The following is a code example for saving data:

df.to_excel('result.xlsx', index=False)

In the above code, we use the to_excel function to save the data as an Excel file named "result.xlsx". index=FalseThe parameter indicates not to save the index.

Conclusion:

This article introduces how to use the pandas library to read Excel files and gives specific code examples. I hope readers can quickly get started with pandas through the introduction of this article, so as to better process and analyze data. At the same time, readers are also recommended to consult the official pandas documentation to further understand the rich functions and functions provided by pandas.

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