Split pandas DataFrame Rows at Index Position in Python (Example Code)
In this article, I’ll demonstrate how to divide a pandas DataFrame at a particular row index position in the Python programming language.
Preparing 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':range(1, 8), # Construct pandas DataFrame 'B':['y', 'w', 'w', 'r', 's', 'w', 'y'], 'C':range(11, 18)}) print(my_df) # A B C # 0 1 y 11 # 1 2 w 12 # 2 3 w 13 # 3 4 r 14 # 4 5 s 15 # 5 6 w 16 # 6 7 y 17 |
my_df = pd.DataFrame({'A':range(1, 8), # Construct pandas DataFrame 'B':['y', 'w', 'w', 'r', 's', 'w', 'y'], 'C':range(11, 18)}) print(my_df) # A B C # 0 1 y 11 # 1 2 w 12 # 2 3 w 13 # 3 4 r 14 # 4 5 s 15 # 5 6 w 16 # 6 7 y 17
Example: Slicing pandas DataFrame Rows at Partocular Index Position
df_up = my_df.iloc[:4] # Extract rows above index print(df_up) # A B C # 0 1 y 11 # 1 2 w 12 # 2 3 w 13 # 3 4 r 14 |
df_up = my_df.iloc[:4] # Extract rows above index print(df_up) # A B C # 0 1 y 11 # 1 2 w 12 # 2 3 w 13 # 3 4 r 14
df_low = my_df.iloc[4:] # Extract rows below index print(df_low) # A B C # 4 5 s 15 # 5 6 w 16 # 6 7 y 17 |
df_low = my_df.iloc[4:] # Extract rows below index print(df_low) # A B C # 4 5 s 15 # 5 6 w 16 # 6 7 y 17
Further Resources & Related Tutorials
You may find some related Python tutorials below.