Create List of Column Names Based On Type in Python (Example Code)
In this tutorial you’ll learn how to return a list of column names grouped by the type of the column in Python programming.
Setting up the Example
import pandas as pd # Import pandas library to Python |
import pandas as pd # Import pandas library to Python
my_df = pd.DataFrame({'A':[3, 6, 2, 5, 1, 9], # Construct example DataFrame 'B':['g', 'g', 'w', 'a', 'g', 'f'], 'C':['a', 'b', 'c', 'd', 'e', 'f'], 'D':range(1, 7)}) print(my_df) # Display example DataFrame in console # A B C D # 0 3 g a 1 # 1 6 g b 2 # 2 2 w c 3 # 3 5 a d 4 # 4 1 g e 5 # 5 9 f f 6 |
my_df = pd.DataFrame({'A':[3, 6, 2, 5, 1, 9], # Construct example DataFrame 'B':['g', 'g', 'w', 'a', 'g', 'f'], 'C':['a', 'b', 'c', 'd', 'e', 'f'], 'D':range(1, 7)}) print(my_df) # Display example DataFrame in console # A B C D # 0 3 g a 1 # 1 6 g b 2 # 2 2 w c 3 # 3 5 a d 4 # 4 1 g e 5 # 5 9 f f 6
Example: Grouping Column Names by Types
print(my_df.columns.to_series().groupby(my_df.dtypes).groups) # {int64: ['A', 'D'], object: ['B', 'C']} |
print(my_df.columns.to_series().groupby(my_df.dtypes).groups) # {int64: ['A', 'D'], object: ['B', 'C']}