Filling missing values with fillna() in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of fillna() with a scalar value?

Given the DataFrame below, what will be the result after filling missing values with 0 using fillna(0)?

Pandas

import pandas as pd
import numpy as np
df = pd.DataFrame({'A': [1, np.nan, 3], 'B': [4, 5, np.nan]})
result = df.fillna(0)
print(result)

A {'A': [1.0, 0.0, 3.0], 'B': [4.0, 5.0, 0.0]}

B {'A': [1, nan, 3], 'B': [4, 5, nan]}

C {'A': [1.0, nan, 3.0], 'B': [4.0, 5.0, nan]}

D {'A': [1, 0, 3], 'B': [4, 5, 0]}

💡 Hint

Remember that fillna replaces all NaN values with the given scalar.

fillna(0) replaces all missing values (NaN) with 0. The resulting DataFrame has no NaNs and numeric columns become floats because of NaN replacement.

❓ data_output

intermediate

How many missing values remain after fillna() with method='ffill'?

Consider the DataFrame below. After applying fillna(method='ffill'), how many missing values remain?

Pandas

import pandas as pd
import numpy as np
df = pd.DataFrame({'X': [np.nan, 2, np.nan, 4, np.nan]})
filled = df.fillna(method='ffill')
missing_count = filled.isna().sum().iloc[0]
print(missing_count)

A 2

B 0

C 3

D 1

💡 Hint

Forward fill cannot fill NaN at the start of the column.

Forward fill replaces NaNs with the last valid value above. The first NaN remains because there is no previous value to fill from.

🔧 Debug

advanced

Why does this fillna() call raise an error?

What error will this code raise and why?

import pandas as pd
import numpy as np
df = pd.DataFrame({'A': [1, np.nan, 3]})
df.fillna(inplace=True, value=[0, 0])

Pandas

import pandas as pd
import numpy as np
df = pd.DataFrame({'A': [1, np.nan, 3]})
df.fillna(inplace=True, value=[0, 0])

A ValueError: Length of values does not match length of index

B TypeError: fillna() got multiple values for argument 'value'

C AttributeError: 'NoneType' object has no attribute 'fillna'

D No error, fills NaN with 0

💡 Hint

Check if the length of the list matches the DataFrame length.

The value parameter expects a scalar or dict matching columns. Passing a list of length 2 for a DataFrame with 3 rows causes a ValueError due to length mismatch.

🚀 Application

advanced

Which fillna() call fills missing values with column means?

You want to fill missing values in each column with that column's mean. Which code does this correctly?

Pandas

import pandas as pd
import numpy as np
df = pd.DataFrame({'A': [1, np.nan, 3], 'B': [4, 5, np.nan]})

A df.fillna(df.median())

B df.fillna(df.mean())

C df.fillna({'A': df['A'].mean(), 'B': df['B'].median()})

D df.fillna(0)

💡 Hint

Use a Series with means for each column as the fill value.

df.mean() returns a Series with mean of each column. Passing it to fillna fills NaNs per column with that mean.

🧠 Conceptual

expert

What is the effect of fillna() with limit parameter?

Given a column with consecutive NaNs, what does fillna(method='bfill', limit=1) do?

A Fills NaNs only if they are at the start of the column

B Fills all NaNs in the column with the next valid value

C Fills only the first NaN in each consecutive group, leaving others as NaN

D Raises an error because limit cannot be used with method

💡 Hint

Limit controls how many consecutive NaNs get filled.

The limit parameter restricts the number of consecutive NaNs filled. With limit=1, only the first NaN in each consecutive group is filled.