Easy way to delete specific columns in Pandas

Quick Start: Tips for deleting specified columns in Pandas

Pandas is a powerful data analysis library that provides many convenient functions and methods to handle and Operation data. During data analysis, sometimes we need to delete some unnecessary columns from the data set. This article will introduce the technique of deleting specified columns in Pandas and provide specific code examples.

Before we begin, we need to import the Pandas library and create a sample data set to demonstrate the operation of deleting columns.

import pandas as pd

# 创建示例数据集
data = {'姓名': ['小明', '小红', '小刚'],
        '年龄': [18, 20, 22],
        '性别': ['男', '女', '男'],
        '成绩': [90, 95, 80]}

df = pd.DataFrame(data)

Now we have a data set containing name, age, gender and grades. Suppose we want to remove the gender column from our dataset. Here are a few common ways to achieve this goal.

1. Use the drop() method

drop()The method can accept one parametercolumns , used to specify the column name to be deleted. The following is sample code to delete the gender column using the drop() method:

df_drop = df.drop(columns=['性别'])

This will generate a new DataFrame df_drop that does not contain the Gender column.

2. Using the del keyword

In Python, we can delete objects using the del keyword. For DataFrame objects, we can use similar syntax to delete columns. The following is sample code to delete the gender column using the del keyword:

del df['性别']

This will directly delete the gender column in the original data set.

3. Use pop()method

pop() method is used to delete the specified column and return the deleted column Content. The following is a sample code that uses the pop() method to delete the gender column:

sex = df.pop('性别')

This will delete the gender column in the original data set and assign the contents of the deleted column to the variablesex.

4. Using the reindex() method

The reindex() method can be used to reindex the DataFrame object. If we delete the index of the column to be deleted from the DataFrame, the delete operation will also be performed. The following is sample code to remove the gender column using the reindex() method:

df_reindex = df.reindex(columns=['姓名', '年龄', '成绩'])

This will generate a new DataFrame df_reindex that does not contain the Gender column.

Each method in the above sample code can achieve the function of deleting the specified column. Which method you choose depends on your needs and personal preferences.

In actual applications, we may encounter more complex situations, such as deleting multiple columns, deleting discontinuous columns, etc. In these cases, you can combine and adapt the above methods as needed.

Summary:

This article introduces several common methods to delete specified columns in Pandas: using the drop() method, del keyword , pop() method and reindex() method. Whether it is simply deleting a single column or complex operations, Pandas provides many convenient functions and methods to meet different needs.

I hope this article can help you quickly get started with the technique of deleting specified columns in Pandas. If you have any questions or suggestions, please feel free to share them with us.

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