isin() for value matching in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of isin() with multiple values

What is the output of this code snippet?

Pandas

import pandas as pd

s = pd.Series([10, 20, 30, 40, 50])
result = s.isin([20, 40, 60])
print(result.tolist())

A [True, False, True, False, True]

B [True, True, False, True, False]

C [False, False, False, False, False]

D [False, True, False, True, False]

💡 Hint

Check which values in the series are exactly in the list [20, 40, 60].

The isin() method returns True for elements that are in the given list. Here, 20 and 40 are in the list, so their positions are True; others are False.

❓ data_output

intermediate

Filtering DataFrame rows using isin()

Given the DataFrame below, which rows remain after filtering with isin()?

Pandas

import pandas as pd

df = pd.DataFrame({
    'Name': ['Anna', 'Bob', 'Cathy', 'David'],
    'City': ['NY', 'LA', 'NY', 'Chicago']
})
filtered = df[df['City'].isin(['NY', 'Chicago'])]
print(filtered)

A

   Name     City
0  Anna       NY
2  Cathy      NY
3  David  Chicago

B

   Name     City
1  Bob        LA
3  David  Chicago

C

   Name     City
0  Anna       NY
1  Bob        LA

D

   Name     City
2  Cathy      NY
3  David  Chicago

💡 Hint

Look for rows where City is either 'NY' or 'Chicago'.

Rows with City 'NY' or 'Chicago' are kept. That includes Anna, Cathy, and David.

🧠 Conceptual

advanced

Behavior of isin() with empty list

What is the output of this code snippet?

Pandas

import pandas as pd

s = pd.Series([1, 2, 3])
result = s.isin([])
print(result.tolist())

A [True, True, True]

B [False, False, False]

C []

D [None, None, None]

💡 Hint

Think about what it means to check if values are in an empty list.

No values can be in an empty list, so all results are False.

🔧 Debug

advanced

Error caused by wrong argument type in isin()

What error does this code raise?

Pandas

import pandas as pd

s = pd.Series([1, 2, 3])
result = s.isin(2)
print(result)

A TypeError: argument of type 'int' is not iterable

B ValueError: wrong number of arguments

C AttributeError: 'int' object has no attribute 'isin'

D No error, outputs [False, True, False]

💡 Hint

Check what type the argument to isin() should be.

isin() expects an iterable like list or set. Passing an int causes a TypeError because int is not iterable.

🚀 Application

expert

Count how many DataFrame rows match multiple conditions using isin()

Given this DataFrame, how many rows have 'Category' in ['A', 'C'] and 'Score' in [10, 30]?

Pandas

import pandas as pd

df = pd.DataFrame({
    'Category': ['A', 'B', 'C', 'A', 'B', 'C'],
    'Score': [10, 20, 30, 40, 10, 30]
})
filtered = df[df['Category'].isin(['A', 'C']) & df['Score'].isin([10, 30])]
count = filtered.shape[0]
print(count)

A 5

B 4

C 3

D 2

💡 Hint

Check rows where Category is 'A' or 'C' and Score is 10 or 30 simultaneously.

Rows matching both conditions are: (A,10), (C,30), and (C,30) again. Total 3 rows.

Practice

1. What does the isin() function do in pandas?

easy

A. Checks if each value in a Series or DataFrame is in a given list and returns True or False.

B. Sorts the values in a DataFrame or Series.

C. Calculates the sum of values in a DataFrame column.

D. Removes duplicate values from a DataFrame.

Solution

1. Step 1: Understand the purpose of isin()

   isin() checks if each element in a pandas Series or DataFrame exists in a list or another iterable.

2. Step 2: Identify the output type

   The function returns a boolean Series or DataFrame with True where the value is found and False otherwise.

3. Final Answer:

   Checks if each value in a Series or DataFrame is in a given list and returns True or False. -> Option A

4. Quick Check:

   isin() = membership check [OK]

Hint: Remember: isin() returns True/False for membership [OK]

Common Mistakes:

• Thinking isin() sorts data
• Confusing isin() with aggregation functions
• Assuming it removes duplicates

2. Which of the following is the correct syntax to filter rows in a DataFrame df where column col has values in the list [1, 2, 3]?

easy

A. df.isin(col, [1, 2, 3])

B. df.col.isin([1, 2, 3]) = True

C. df[df.isin(col, [1, 2, 3])]

D. df[df.col.isin([1, 2, 3])]

Solution

1. Step 1: Use isin() on the column

   The correct way is to call isin() on the Series: df.col.isin([1, 2, 3]).

2. Step 2: Use boolean indexing to filter rows

   Wrap the boolean Series inside df[ ... ] to select rows where condition is True.

3. Final Answer:

   df[df.col.isin([1, 2, 3])] -> Option D

4. Quick Check:

   Filter rows with boolean mask = df[df.col.isin([1, 2, 3])] [OK]

Hint: Call isin() on column, then filter with df[...] [OK]

Common Mistakes:

• Calling isin() on DataFrame with wrong arguments
• Using assignment instead of filtering
• Incorrect method call syntax

3. Given the DataFrame:

import pandas as pd
df = pd.DataFrame({'A': [10, 20, 30, 40], 'B': ['x', 'y', 'z', 'x']})

What is the output of df['B'].isin(['x', 'z'])?

medium

A. [True, False, True, True]

B. [False, True, False, False]

C. [True, True, True, True]

D. [False, False, False, False]

Solution

1. Step 1: Check each value in column 'B'

   Values are ['x', 'y', 'z', 'x']. We check if each is in ['x', 'z'].

2. Step 2: Mark True if value is in list, else False

   'x' is in list -> True, 'y' not in list -> False, 'z' in list -> True, 'x' in list -> True.

3. Final Answer:

   [True, False, True, True] -> Option A

4. Quick Check:

   Membership check matches [True, False, True, True] [OK]

Hint: Check each value against list, True if found [OK]

Common Mistakes:

• Mixing True/False order
• Confusing column values
• Assuming all True or all False

4. What is wrong with this code snippet?

df = pd.DataFrame({'num': [1, 2, 3, 4]})
mask = df.isin([1, 3])
filtered = df[mask]

medium

A. The DataFrame df must have a column named 'mask' to filter.

B. The isin() method is called on the whole DataFrame, resulting in a DataFrame of booleans, which cannot be used directly for filtering.

C. The variable mask should be converted to a list before filtering.

D. The list passed to isin() must be a string, not integers.

Solution

1. Step 1: Understand df.isin([1, 3]) output

   This returns a DataFrame of booleans with the same shape as df, not a single boolean Series.

2. Step 2: Why filtering with DataFrame mask fails

   Using a DataFrame of booleans as an index mask causes an error because pandas expects a boolean Series or array matching the index length.

3. Final Answer:

   The isin() method is called on the whole DataFrame, resulting in a DataFrame of booleans, which cannot be used directly for filtering. -> Option B

4. Quick Check:

   Mask must be Series, not DataFrame [OK]

Hint: Use isin() on a column, not whole DataFrame for filtering [OK]

Common Mistakes:

• Using DataFrame mask instead of Series mask for filtering
• Passing wrong data types to isin()
• Trying to filter with a DataFrame of booleans

5. You have a DataFrame df with a column status containing values like 'new', 'pending', 'done', and 'cancelled'. You want to create a new column is_active that is True only if status is 'new' or 'pending'. Which code correctly does this using isin()?

hard

A. df['is_active'] = df['status'] == ['new', 'pending']

B. df['is_active'] = df.isin(['new', 'pending'])

C. df['is_active'] = df['status'].isin(['new', 'pending'])

D. df['is_active'] = df['status'].isin('new', 'pending')

Solution

1. Step 1: Use isin() on the 'status' column with a list of target values

   Correct syntax is df['status'].isin(['new', 'pending']) which returns a boolean Series.

2. Step 2: Assign the boolean Series to new column 'is_active'

   This creates a new column with True where status is 'new' or 'pending', False otherwise.

3. Final Answer:

   df['is_active'] = df['status'].isin(['new', 'pending']) -> Option C

4. Quick Check:

   Use isin() on column with list [OK]

Hint: Assign isin() result directly to new column [OK]

Common Mistakes:

• Calling isin() on whole DataFrame
• Passing multiple arguments instead of a list
• Using equality operator with list