DataFrame as labeled two-dimensional table in Pandas - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

What is the output of this DataFrame selection?

Given the DataFrame below, what will be the output of df.loc['b', 'Y']?

Pandas

import pandas as pd

df = pd.DataFrame({
    'X': [10, 20, 30],
    'Y': [40, 50, 60],
    'Z': [70, 80, 90]
}, index=['a', 'b', 'c'])

result = df.loc['b', 'Y']
print(result)

A 80

B 20

C 50

D KeyError

💡 Hint

Remember that loc selects by label for both rows and columns.

The row labeled 'b' has values X=20, Y=50, Z=80. Selecting column 'Y' gives 50.

❓ data_output

intermediate

How many rows and columns does this DataFrame have?

Consider the DataFrame created below. What is the shape (rows, columns) of df?

Pandas

import pandas as pd

df = pd.DataFrame({
    'A': range(5),
    'B': range(5, 10),
    'C': range(10, 15)
})

print(df.shape)

A (5, 3)

B (3, 5)

C (5, 5)

D (3, 3)

💡 Hint

Shape returns (number of rows, number of columns).

The DataFrame has 5 rows (0 to 4) and 3 columns (A, B, C).

🔧 Debug

advanced

What error does this code raise?

What error will this code produce when run?

Pandas

import pandas as pd

df = pd.DataFrame({'col1': [1, 2], 'col2': [3, 4]})

value = df.loc[2, 'col1']
print(value)

A No error, prints 2

B ValueError

C IndexError

D KeyError

💡 Hint

Check if the row label 2 exists in the DataFrame index.

The DataFrame index is [0,1]. Accessing label 2 with loc causes a KeyError.

❓ visualization

advanced

Which plot shows the correct bar chart of column sums?

Given the DataFrame below, which option shows the correct bar chart of the sum of each column?

Pandas

import pandas as pd
import matplotlib.pyplot as plt

df = pd.DataFrame({
    'A': [1, 2, 3],
    'B': [4, 5, 6],
    'C': [7, 8, 9]
})

col_sums = df.sum()

plt.bar(col_sums.index, col_sums.values)
plt.show()

A Bar chart with bars at A=6, B=15, C=24

B Bar chart with bars at A=3, B=5, C=7

C Bar chart with bars at A=1, B=4, C=7

D Line chart with points at A=6, B=15, C=24

💡 Hint

Sum each column and plot those sums as bar heights.

Sum of A is 6 (1+2+3), B is 15 (4+5+6), C is 24 (7+8+9). The bar chart should reflect these values.

🚀 Application

expert

What is the value of 'result' after filtering and grouping?

Given the DataFrame below, what is the value of result after filtering rows where 'score' > 70 and grouping by 'team' to get the mean 'score'?

Pandas

import pandas as pd

df = pd.DataFrame({
    'team': ['A', 'B', 'A', 'B', 'C'],
    'score': [65, 85, 75, 90, 60]
})

filtered = df[df['score'] > 70]
result = filtered.groupby('team')['score'].mean()
print(result)

A team\nA 75.0\nB 90.0\nName: score, dtype: float64

B team\nA 75.0\nB 87.5\nName: score, dtype: float64

C team\nA 70.0\nB 87.5\nName: score, dtype: float64

D team\nA 70.0\nB 90.0\nName: score, dtype: float64

💡 Hint

Filter first, then group by team and calculate mean score.

Filtered rows have scores > 70: A=75, B=85 and 90. Mean for A is 75, for B is (85+90)/2=87.5.