How to Remove Rows of pandas DataFrame in Python (Example Code)
On this page, I’ll demonstrate how to drop rows of a pandas DataFrame in the Python programming language.
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({"x1":range(10, 20), # Constructing pandas DataFrame in Python "x2":range(20, 10, - 1), "x3":["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"], "x4":[1, 1, 0, 1, 1, 1, 0, 0, 1, 0]}) print(my_df) # Displaying pandas DataFrame # x1 x2 x3 x4 # 0 10 20 a 1 # 1 11 19 b 1 # 2 12 18 c 0 # 3 13 17 d 1 # 4 14 16 e 1 # 5 15 15 f 1 # 6 16 14 g 0 # 7 17 13 h 0 # 8 18 12 i 1 # 9 19 11 j 0 |
my_df = pd.DataFrame({"x1":range(10, 20), # Constructing pandas DataFrame in Python "x2":range(20, 10, - 1), "x3":["a", "b", "c", "d", "e", "f", "g", "h", "i", "j"], "x4":[1, 1, 0, 1, 1, 1, 0, 0, 1, 0]}) print(my_df) # Displaying pandas DataFrame # x1 x2 x3 x4 # 0 10 20 a 1 # 1 11 19 b 1 # 2 12 18 c 0 # 3 13 17 d 1 # 4 14 16 e 1 # 5 15 15 f 1 # 6 16 14 g 0 # 7 17 13 h 0 # 8 18 12 i 1 # 9 19 11 j 0
Example: Dropping Rows of pandas DataFrame Based On Logical Condition
my_df_new = my_df[my_df.x1 >= 15] # Using logical condition print(my_df_new) # Displaying new DataFrame # x1 x2 x3 x4 # 5 15 15 f 1 # 6 16 14 g 0 # 7 17 13 h 0 # 8 18 12 i 1 # 9 19 11 j 0 |
my_df_new = my_df[my_df.x1 >= 15] # Using logical condition print(my_df_new) # Displaying new DataFrame # x1 x2 x3 x4 # 5 15 15 f 1 # 6 16 14 g 0 # 7 17 13 h 0 # 8 18 12 i 1 # 9 19 11 j 0