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Pandas provides three methods to get the column names of a dataframe. These include the columns attribute, df.columns.tolist() method, and the df.keys() method. The columns attribute returns the column names as an Index object. The df.columns.tolist() method returns the column names as a list. The df.keys() method returns the column names as a pandas.core.indexes.base.Index object. All three methods can be used to get the column names of a dataframe in Pandas.
You can use the following methods to get the column names in a pandas DataFrame:
Method 1: Get All Column Names
list(df) Method 2: Get Column Names in Alphabetical Order
sorted(df)
Method 3: Get Column Names with Specific Data Type
list(df.select_dtypes(include=['int64', 'bool']))
The following examples show how to use each method with the following pandas DataFrame:
import pandas as pd #create DataFrame df = pd.DataFrame({'team': ['A', 'B', 'C', 'D', 'E', 'F'], 'points': [18, 22, 19, 14, 14, 11], 'assists': [5, 7, 7, 9, 12, 9], 'playoffs': [True, False, False, True, True, True]}) #view DataFrame print(df) team points assists playoffs 0 A 18 5 True 1 B 22 7 False 2 C 19 7 False 3 D 14 9 True 4 E 14 12 True 5 F 11 9 True
Example 1: Get All Column Names
The easiest way to get all of the column names in a pandas DataFrame is to use list() as follows:
#get all column names
list(df)
['team', 'points', 'assists', 'playoffs']
The result is a list that contains all four column names from the pandas DataFrame.
Example 2: Get Column Names in Alphabetical Order
To get the column names in a pandas DataFrame in alphabetical order, you can use the sorted() function as follows:
#get column names in alphabetical order
sorted(df)
['assists', 'playoffs', 'points', 'team']
The result is a list that contains all four column names from the pandas DataFrame listed in alphabetical order.
#get column names in reverse alphabetical order
sorted(df, reverse=True)
['team', 'points', 'playoffs', 'assists']
Example 3: Get Column Names with Specific Data Type
You can use the following syntax to view the data type of each column in the DataFrame:
#view data type of each column
df.dtypes
team object
points int64
assists int64
playoffs bool
dtype: object
You can then use the select_dtypes() function to only get the column names with a specific data type.
For example, we can use the following syntax to only get the column names that have a data type of int64 or bool:
#get all columns that have data type of int64 or bool
list(df.select_dtypes(include=['int64', 'bool']))
['points', 'assists', 'playoffs']
The result is a list of column names that have a data type of int64 or bool.