Let’s see how to count number of all rows in a Dataframe or rows that satisfy a condition in Pandas.
1) Count all rows in a Pandas Dataframe using Dataframe.shape.
Dataframe.shape returns tuple of shape (Rows, columns) of dataframe/series.
Let’s create a pandas dataframe.
# import pandas library as pdimport pandas as pd # List of Tuplesstudents = [('Ankit', 22, 'Up', 'Geu'), ('Ankita', 31, 'Delhi', 'Gehu'), ('Rahul', 16, 'Tokyo', 'Abes'), ('Simran', 41, 'Delhi', 'Gehu'), ('Shaurya', 33, 'Delhi', 'Geu'), ('Harshita', 35, 'Mumbai', 'Bhu' ), ('Swapnil', 35, 'Mp', 'Geu'), ('Priya', 35, 'Uk', 'Geu'), ('Jeet', 35, 'Guj', 'Gehu'), ('Ananya', 35, 'Up', 'Bhu') ] # Create a DataFrame object from# list of tuples with columns# and indices.details = pd.DataFrame(students, columns =['Name', 'Age', 'Place', 'College'], index =['a', 'b', 'c', 'd', 'e', 'f', 'g', 'i', 'j', 'k']) details |
Output:
Code: Count all rows
# import pandas library as pdimport pandas as pd # List of Tuplesstudents = [('Ankit', 22, 'Up', 'Geu'), ('Ankita', 31, 'Delhi', 'Gehu'), ('Rahul', 16, 'Tokyo', 'Abes'), ('Simran', 41, 'Delhi', 'Gehu'), ('Shaurya', 33, 'Delhi', 'Geu'), ('Harshita', 35, 'Mumbai', 'Bhu' ), ('Swapnil', 35, 'Mp', 'Geu'), ('Priya', 35, 'Uk', 'Geu'), ('Jeet', 35, 'Guj', 'Gehu'), ('Ananya', 35, 'Up', 'Bhu') ] # Create a DataFrame object from# list of tuples with columns# and indices.details = pd.DataFrame(students, columns =['Name', 'Age', 'Place', 'College'], index =['a', 'b', 'c', 'd', 'e', 'f', 'g', 'i', 'j', 'k']) # 0th index of tuple returned by shape# attribute give the number# of rows in a given dataframenum_rows = details.shape[0] print('Number of Rows in given dataframe : ', num_rows) |
Output:
Number of Rows in given dataframe : 10
2) Count all rows in a Pandas Dataframe using Dataframe.index.
Dataframe.index attribute gives a sequence of index or row labels.
Code:
import pandas as pd # List of Tuplesstudents = [('Ankit', 22, 'Up', 'Geu'), ('Ankita', 31, 'Delhi', 'Gehu'), ('Rahul', 16, 'Tokyo', 'Abes'), ('Simran', 41, 'Delhi', 'Gehu'), ('Shaurya', 33, 'Delhi', 'Geu'), ('Harshita', 35, 'Mumbai', 'Bhu' ), ('Swapnil', 35, 'Mp', 'Geu'), ('Priya', 35, 'Uk', 'Geu'), ('Jeet', 35, 'Guj', 'Gehu'), ('Ananya', 35, 'Up', 'Bhu') ] # Create a DataFrame object from# list of tuples with columns# and indices.details = pd.DataFrame(students, columns =['Name', 'Age', 'Place', 'College'], index =['a', 'b', 'c', 'd', 'e', 'f', 'g', 'i', 'j', 'k']) # count number of rows in given dataframe # by finding the length of indicesnum_rows = len(details.index) print('Number of Rows in given dataframe : ', num_rows) |
Output:
Number of Rows in given dataframe : 10
3) Count rows in a Pandas Dataframe that satisfies a condition using Dataframe.apply().
Dataframe.apply(), apply function to all the rows of a dataframe to find out if elements of rows satisfies a condition or not, Based on the result it returns a bool series.
Code:
# import pandas library as pdimport pandas as pd # List of Tuplesstudents = [('Ankit', 22, 'Up', 'Geu'), ('Ankita', 31, 'Delhi', 'Gehu'), ('Rahul', 16, 'Tokyo', 'Abes'), ('Simran', 41, 'Delhi', 'Gehu'), ('Shaurya', 33, 'Delhi', 'Geu'), ('Harshita', 35, 'Mumbai', 'Bhu' ), ('Swapnil', 35, 'Mp', 'Geu'), ('Priya', 35, 'Uk', 'Geu'), ('Jeet', 35, 'Guj', 'Gehu'), ('Ananya', 35, 'Up', 'Bhu') ] # Create a DataFrame object from# list of tuples with columns# and indices.details = pd.DataFrame(students, columns =['Name', 'Age', 'Place', 'College'], index =['a', 'b', 'c', 'd', 'e', 'f', 'g', 'i', 'j', 'k']) # Get a bool series representing which row# satisfies the condition i.e. True for# row in which 'College' is 'Geu'details = details.apply(lambda x : True if x['College'] == "Geu" else False, axis = 1) # Count number of True in the seriesnum_rows = len(details[details == True].index) print('Number of Rows in dataframe in which College is Geu : ', num_rows ) |
Output:
Number of Rows in dataframe in which College is Geu : 4
