Pandas: Split a given dataframe into groups and create a new column with count from GroupBy
Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-17 with Solution
Write a Pandas program to split a given dataframe into groups and create a new column with count from GroupBy.
Test Data:
book_name book_type book_id 0 Book1 Math 1 1 Book2 Physics 2 2 Book3 Computer 3 3 Book4 Science 4 4 Book1 Math 1 5 Book2 Physics 2 6 Book3 Computer 3 7 Book5 English 5
Sample Solution:
Python Code :
import pandas as pd
pd.set_option('display.max_rows', None)
df = pd.DataFrame({
'book_name':['Book1','Book2','Book3','Book4','Book1','Book2','Book3','Book5'],
'book_type':['Math','Physics','Computer','Science','Math','Physics','Computer','English'],
'book_id':[1,2,3,4,1,2,3,5]})
print("Original Orders DataFrame:")
print(df)
print("\nNew column with count from groupby:")
result = df.groupby(["book_name", "book_type"])["book_type"].count().reset_index(name="count")
print(result)
Sample Output:
Original Orders DataFrame: book_name book_type book_id 0 Book1 Math 1 1 Book2 Physics 2 2 Book3 Computer 3 3 Book4 Science 4 4 Book1 Math 1 5 Book2 Physics 2 6 Book3 Computer 3 7 Book5 English 5 New column with count from groupby: book_name book_type count 0 Book1 Math 2 1 Book2 Physics 2 2 Book3 Computer 2 3 Book4 Science 1 4 Book5 English 1
Python Code Editor:
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Previous: Write a Pandas program to split a given dataframe into groups and list all the keys from the GroupBy object.
Next: Write a Pandas program to split a given dataframe into groups with bin counts.
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