Pandas: Split the specified dataframe into groups and count unique values of 'value' column
Pandas Grouping and Aggregating: Split-Apply-Combine Exercise-15 with Solution
Write a Pandas program to split the following dataframe into groups and count unique values of 'value' column.
Test Data:
id value 0 1 a 1 1 a 2 2 b 3 3 None 4 3 a 5 4 a 6 4 None 7 4 b
Sample Solution:
Python Code :
import pandas as pd
df = pd.DataFrame({
'id': [1, 1, 2, 3, 3, 4, 4, 4],
'value': ['a', 'a', 'b', None, 'a', 'a', None, 'b']
})
print("Original DataFrame:")
print(df)
print("Count unique values:")
print (df.groupby('value')['id'].nunique())
Sample Output:
Original DataFrame: id value 0 1 a 1 1 a 2 2 b 3 3 None 4 3 a 5 4 a 6 4 None 7 4 b Count unique values: value a 3 b 2 Name: id, dtype: int64
Python Code Editor:
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Previous: Write a Pandas program to split the following dataframe into groups based on all columns and calculate Groupby value counts on the dataframe.
Next: Write a Pandas program to split a given dataframe into groups and list all the keys from the GroupBy object.
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