Learn to use Pandas: How to delete a column of data in a DataFrame

Pandas Tutorial: How to delete a column of data in a DataFrame?

As the demand for data analysis continues to increase, Python's Pandas library has become one of the important tools for data analysts. Pandas provides powerful data manipulation and processing functions. One common operation is to delete a certain column of data in a DataFrame. This article will introduce in detail how to use Pandas to delete a column of data in a DataFrame and provide specific code examples.

Before starting, you first need to install the Pandas library. Pandas can be installed in a Python environment using the following command:

pip install pandas

After the installation is complete, the Pandas library can be imported through the following code:

import pandas as pd

Next, we will use a sample DataFrame to demonstrate deleting columns operation. Suppose we have a DataFrame named data, containing the following data:

   A   B   C   D
0  1   2   3   4
1  5   6   7   8
2  9  10  11  12

Now, we want to delete column C. You can use the drop method to achieve this goal. The drop method accepts a parameter labels, which is used to specify the labels (column names) to be deleted, and returns a new DataFrame.

The following is a code example to delete column C:

data = pd.DataFrame({'A': [1, 5, 9], 'B': [2, 6, 10], 'C': [3, 7, 11], 'D': [4, 8, 12]})

data = data.drop('C', axis=1)

In this example, we first create a file named data# using the pd.DataFrame method ##DataFrame, and then use the drop method to delete column C. Note that we use the axis=1 parameter to specify the column to delete. If the axis parameter is not specified, rows will be deleted by default.

After this operation, the content of

data will become as follows:

   A   B   D
0  1   2   4
1  5   6   8
2  9  10  12

In addition to using the

drop method, you can also use Python The del keyword to delete columns. The following is a code example that uses the del keyword to delete column C:

data = pd.DataFrame({'A': [1, 5, 9], 'B': [2, 6, 10], 'C': [3, 7, 11], 'D': [4, 8, 12]})

del data['C']

Similarly, after deleting the column, the contents of

data will become the following:

   A   B   D
0  1   2   4
1  5   6   8
2  9  10  12

In addition to the above two methods, you can also use the

pop method to delete columns and return the deleted columns. The following is a code example to delete column C using the pop method:

data = pd.DataFrame({'A': [1, 5, 9], 'B': [2, 6, 10], 'C': [3, 7, 11], 'D': [4, 8, 12]})

C_column = data.pop('C')

In this example,

C_column will save the contents of the deleted column C. After deleting the column, the contents of data are the same as in the previous example.

To sum up, this article introduces how to use Pandas to delete a certain column of data in a DataFrame. Through the

drop method, del keyword and pop method, you can easily delete the specified column and return a new DataFrame or the deleted column.

I hope this article will help you learn and understand the use of Pandas!

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