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To sort the columns of a Pandas dataframe by their names, you can use the DataFrame.sort_index() method and specify the axis parameter as “1” for columns. This will sort the columns in ascending order by their names. Alternatively, you can also use the DataFrame.sort_values() method and specify the by parameter as the column name to sort the dataframe by a particular column name.
You can use the following syntax to quickly sort a pandas DataFrame by column names:
df = df[['column1', 'column4', 'column3', 'column2']]
The following examples show how to use this syntax in practice.
Example 1: Sort Pandas DataFrame by Column Names
The following code shows how to sort a pandas DataFrame by column names:
import pandas as pd #create DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23, 25, 29], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12], 'steals': [2, 3, 3, 2, 5, 3, 2, 1]}) #list column names list(df) ['points', 'assists', 'rebounds', 'steals'] #sort columns by names df = df[['steals', 'assists', 'rebounds', 'points']] df steals assists rebounds points 0 2 5 11 25 1 3 7 8 12 2 3 7 10 15 3 2 9 6 14 4 5 12 6 19 5 3 9 5 23 6 2 9 9 25 7 1 4 12 29
Example 2: Sort Pandas DataFrame by List
The following code shows how to sort a pandas DataFrame by a list of names:
import pandas as pd #create DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23, 25, 29], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12], 'steals': [2, 3, 3, 2, 5, 3, 2, 1]}) #define list of column names name_order = ['steals', 'assists', 'rebounds', 'points'] #sort columns by list df = df[name_order] df steals assists rebounds points 0 2 5 11 25 1 3 7 8 12 2 3 7 10 15 3 2 9 6 14 4 5 12 6 19 5 3 9 5 23 6 2 9 9 25 7 1 4 12 29
Example 3: Sort Pandas DataFrame Alphabetically
The following code shows how to sort a pandas DataFrame alphabetically:
import pandas as pd #create DataFrame df = pd.DataFrame({'points': [25, 12, 15, 14, 19, 23, 25, 29], 'assists': [5, 7, 7, 9, 12, 9, 9, 4], 'rebounds': [11, 8, 10, 6, 6, 5, 9, 12], 'steals': [2, 3, 3, 2, 5, 3, 2, 1]}) #sort columns alphabetically df = df[sorted(df.columns)] df assists points rebounds steals 0 5 25 11 2 1 7 12 8 3 2 7 15 10 3 3 9 14 6 2 4 12 19 6 5 5 9 23 5 3 6 9 25 9 2 7 4 29 12 1