Pandas: Count city wise number of people from a given of data set (city, name of the person)

Last update on April 03 2025 13:11:09 (UTC/GMT +8 hours)

28. City Wise Count

Write a Pandas program to count city wise number of people from a given of data set (city, name of the person).
Sample data:
city Number of people
0 California 4
1 Georgia 2
2 Los Angeles 4

Sample Solution :

Python Code :

import pandas as pd
df1 = pd.DataFrame({'name': ['Anastasia', 'Dima', 'Katherine', 'James', 'Emily', 'Michael', 'Matthew', 'Laura', 'Kevin', 'Jonas'],
'city': ['California', 'Los Angeles', 'California', 'California', 'California', 'Los Angeles', 'Los Angeles', 'Georgia', 'Georgia', 'Los Angeles']})
g1 = df1.groupby(["city"]).size().reset_index(name='Number of people')
print(g1)

Sample Output:

          city  Number of people
0   California                 4
1      Georgia                 2
2  Los Angeles                 4                  

Explanation:

In the above code -

• Creates a Pandas DataFrame called df1 with two columns, "name" and "city", and 10 rows of data.
• Groups the rows of df1 by the "city" column using the groupby() method.
• Applies the size() method to each group to count the number of rows in each group.
• Resets the index of the resulting DataFrame using the reset_index() method and renames the column with the count as "Number of people".
• Stores the resulting DataFrame in a variable called g1.
• The resulting DataFrame has two columns: "city" and "Number of people".
• Prints the contents of g1 to the console.

For more Practice: Solve these Related Problems:

• Write a Pandas program to group a DataFrame by city and count the number of unique persons in each group.
• Write a Pandas program to compute the city-wise count and then sort the results in descending order of count.
• Write a Pandas program to create a pivot table that summarizes the number of people per city and displays it.
• Write a Pandas program to merge two DataFrames on city and then compute the overall count of people per city.

Python-Pandas Code Editor:

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