Loop & Iterate Through pandas DataFrame Columns in Python (Example Code)
This post explains how to loop through the columns of a pandas DataFrame in Python programming.
Constructing Example Data
import pandas as pd # Import pandas |
import pandas as pd # Import pandas
my_df = pd.DataFrame({'A':range(8, 14), # Construct pandas DataFrame 'B':['x', 'y', 'y', 'y', 'x', 'x'], 'C':range(15, 9, - 1)}) print(my_df) # A B C # 0 8 x 15 # 1 9 y 14 # 2 10 y 13 # 3 11 y 12 # 4 12 x 11 # 5 13 x 10 |
my_df = pd.DataFrame({'A':range(8, 14), # Construct pandas DataFrame 'B':['x', 'y', 'y', 'y', 'x', 'x'], 'C':range(15, 9, - 1)}) print(my_df) # A B C # 0 8 x 15 # 1 9 y 14 # 2 10 y 13 # 3 11 y 12 # 4 12 x 11 # 5 13 x 10
Example: Print Columns of pandas DataFrame Using for Loop
for column in my_df: # Run for loop over columns print(my_df[column]) # 0 8 # 1 9 # 2 10 # 3 11 # 4 12 # 5 13 # Name: A, dtype: int64 # 0 x # 1 y # 2 y # 3 y # 4 x # 5 x # Name: B, dtype: object # 0 15 # 1 14 # 2 13 # 3 12 # 4 11 # 5 10 # Name: C, dtype: int64 |
for column in my_df: # Run for loop over columns print(my_df[column]) # 0 8 # 1 9 # 2 10 # 3 11 # 4 12 # 5 13 # Name: A, dtype: int64 # 0 x # 1 y # 2 y # 3 y # 4 x # 5 x # Name: B, dtype: object # 0 15 # 1 14 # 2 13 # 3 12 # 4 11 # 5 10 # Name: C, dtype: int64
Related Articles
Please find some related Python tutorials on topics such as descriptive statistics, numeric values, and naming data below: