filter() for group-level filtering in Data Analysis Python - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of group filtering with filter()

What is the output DataFrame after applying filter() to keep groups with mean value greater than 3?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'group': ['A', 'A', 'B', 'B', 'C', 'C'],
    'value': [2, 4, 5, 6, 1, 2]
})
result = df.groupby('group').filter(lambda x: x['value'].mean() > 3)
print(result)

A

  group  value
0     A      2
1     A      4
2     B      5
3     B      6

B

  group  value
2     B      5
3     B      6

C

  group  value
0     A      2
1     A      4
2     B      5
3     B      6
4     C      1
5     C      2

D

Empty DataFrame
Columns: [group, value]
Index: []

💡 Hint

Calculate the mean of 'value' for each group and keep groups where mean > 3.

Group 'B' has mean (5+6)/2 = 5.5 > 3, so only group 'B' rows remain after filtering.

❓ data_output

intermediate

Number of groups after filtering

After filtering groups with sum of 'score' >= 10, how many groups remain?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'team': ['X', 'X', 'Y', 'Y', 'Z', 'Z'],
    'score': [4, 7, 3, 2, 6, 5]
})
filtered = df.groupby('team').filter(lambda g: g['score'].sum() >= 10)
num_groups = filtered['team'].nunique()
print(num_groups)

A 0

B 1

C 3

D 2

💡 Hint

Sum scores per team and count teams with sum >= 10.

Team X sum is 11, team Y sum is 5, team Z sum is 11. Teams X and Z remain, so 2 groups.

🔧 Debug

advanced

Identify the error in group filtering code

What error does this code raise when filtering groups with mean > 2?

df.groupby('cat').filter(lambda x: x['val'].mean > 2)

Data Analysis Python

import pandas as pd

df = pd.DataFrame({'cat': ['a', 'a', 'b'], 'val': [1, 3, 4]})
result = df.groupby('cat').filter(lambda x: x['val'].mean > 2)

A No error, outputs filtered DataFrame

B AttributeError: 'DataFrameGroupBy' object has no attribute 'filter'

C TypeError: 'method' object is not callable

D SyntaxError: invalid syntax

💡 Hint

Check if mean is called as a method or accessed as an attribute.

mean is a method and must be called with parentheses (). Missing () causes a method object to be returned, which is not callable in comparison.

🚀 Application

advanced

Filter groups with more than 2 rows and average value below 5

Which option correctly filters groups with more than 2 rows and average 'score' less than 5?

Data Analysis Python

import pandas as pd

df = pd.DataFrame({
    'group': ['G1', 'G1', 'G1', 'G2', 'G2', 'G3', 'G3', 'G3'],
    'score': [4, 3, 2, 6, 7, 1, 2, 3]
})

A df.groupby('group').filter(lambda g: len(g) > 2 and g['score'].mean() < 5)

B df.groupby('group').filter(lambda g: len(g) >= 2 and g['score'].mean() <= 5)

C df.groupby('group').filter(lambda g: len(g) > 3 and g['score'].mean() < 5)

D df.groupby('group').filter(lambda g: len(g) > 2 or g['score'].mean() < 5)

💡 Hint

Use both conditions with 'and' and strict inequalities as stated.

Only groups with more than 2 rows and mean score less than 5 are kept. G1 has 3 rows and mean 3, G3 has 3 rows and mean 2, G2 has 2 rows so excluded.

🧠 Conceptual

expert

Understanding filter() behavior on groupby objects

Which statement about filter() on a pandas GroupBy object is TRUE?

A filter() returns a DataFrame containing only groups where the filter function returns True for the entire group.

B filter() modifies the original DataFrame in place by removing groups that do not meet the condition.

C filter() applies the function to each row individually and returns rows where the function returns True.

D filter() returns a Series with group names as index and boolean values indicating if group passed the filter.

💡 Hint

Think about how filter works on groups, not individual rows.

filter() applies the function to each group and keeps groups where the function returns True. It returns a filtered DataFrame, not a Series or in-place modification.