How To Check Columns In Python

In Python, data is often represented in the form of tables which can be manipulated using various operations. One such operation is to check the columns in a table.

Checking columns in Python can be useful for various purposes like selecting certain columns, renaming columns, or modifying column data. In this tutorial, we will learn how to check columns in Python.

Steps:

1. Firstly, you need to import the required library or module in your Python script. Here, we will be using the Pandas library for data manipulation. You can install pandas using pip by running the following command in your terminal:

2. Once you have installed pandas, you can import it into your Python script using the following command:

3. Now, let’s create a sample dataset with columns. You can create a DataFrame in pandas by passing a dictionary of key-value pairs, where keys represent the column names and values represent the data for that column. For example:

This will create a DataFrame with three columns named ‘Name’, ‘Age’, and ‘Gender’ respectively.

4. To check the columns in our DataFrame, we can use the columns attribute of the DataFrame. This will return an Index object containing the list of column names. For example:

Output:

This will print the list of column names in the DataFrame.

5. You can also select a specific column from the DataFrame using the column name. For example, to select the ‘Name’ column, you can use the following command:

Output:

0 John
1 Abby
2 Steve
3 Lucy

Name: Name, dtype: object

This will print the values in the ‘Name’ column.

Conclusion:

In this tutorial, we learned how to check columns in Python using the Pandas library. We created a sample dataset with columns and used the columns attribute of the DataFrame to check the list of column names.

We also learned how to select a specific column from the DataFrame using its name. This can be useful for various data manipulation tasks.

Full Code: