Why Python is the top choice for data analysis in Data Analysis Python - Challenge Your Understanding

Challenge - 5 Problems

🧠 Conceptual

intermediate

Why is Python popular for data analysis?

Which of the following reasons best explains why Python is widely used for data analysis?

A Python has a large number of libraries like pandas and NumPy that simplify data manipulation and analysis.

B Python is the fastest programming language available for all types of computing tasks.

C Python requires no installation and runs only in web browsers.

D Python automatically understands data without any coding.

💡 Hint

Think about tools that help with handling data easily.

Python's popularity in data analysis comes from its rich ecosystem of libraries like pandas and NumPy that make data tasks easier and faster.

❓ Predict Output

intermediate

Output of Python code using pandas

What is the output of this Python code snippet?

Data Analysis Python

import pandas as pd

data = {'Name': ['Anna', 'Bob', 'Cara'], 'Age': [28, 34, 22]}
df = pd.DataFrame(data)

print(df['Age'].mean())

A TypeError

B 28.0

C 30.0

D 28.5

💡 Hint

Calculate the average of the ages: 28, 34, and 22.

The mean of 28, 34, and 22 is (28 + 34 + 22) / 3 = 28.0.

❓ data_output

advanced

Result of filtering data with pandas

Given the DataFrame below, what is the output after filtering rows where 'Score' is greater than 80?

Data Analysis Python

import pandas as pd

data = {'Student': ['John', 'Jane', 'Dave', 'Dana'], 'Score': [75, 82, 90, 60]}
df = pd.DataFrame(data)

filtered_df = df[df['Score'] > 80]
print(filtered_df)

A

  Student  Score
1    Jane     82
2    Dave     90

B

  Student  Score
0    John     75
3    Dana     60

C

  Student  Score
1    Jane     82
3    Dana     60

D

Empty DataFrame
Columns: [Student, Score]
Index: []

💡 Hint

Keep only rows where Score is more than 80.

Only Jane and Dave have scores above 80, so only their rows remain.

❓ visualization

advanced

Interpreting a Python matplotlib plot

What does the following Python code plot?

Data Analysis Python

import matplotlib.pyplot as plt

x = [1, 2, 3, 4]
y = [10, 20, 25, 30]

plt.plot(x, y, marker='o')
plt.title('Sales Over Time')
plt.xlabel('Quarter')
plt.ylabel('Sales (in thousands)')
plt.show()

A A pie chart showing sales distribution.

B A line graph showing sales increasing over four quarters with points marked.

C A scatter plot with no connecting lines.

D A bar chart showing sales for four quarters.

💡 Hint

Look at the plot type and markers used.

The code creates a line plot with points marked, showing sales increasing over four quarters.

🔧 Debug

expert

Identify the error in this Python data analysis code

What error will this code produce when run?

Data Analysis Python

import pandas as pd

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

result = df['C'].sum()
print(result)

A 0

B TypeError: unsupported operand type(s) for +: 'int' and 'str'

C KeyError: 'C'

D AttributeError: 'DataFrame' object has no attribute 'sum'

💡 Hint

Check if the column 'C' exists in the DataFrame.

The DataFrame has columns 'A' and 'B' only. Accessing 'C' causes a KeyError.