Why exploratory inspection guides analysis in Data Analysis Python - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load the CSV file into a DataFrame.

Data Analysis Python

import pandas as pd
data = pd.[1]('data.csv')

Drag options to blanks, or click blank then click option'

Aimport_csv

Bload_csv

Copen_csv

Dread_csv

Attempts:

3 left

💡 Hint

Common Mistakes

Using non-existent functions like load_csv or open_csv.

Use pd.read_csv to load CSV files into a DataFrame.

2fill in blank

medium

Complete the code to show the first 5 rows of the DataFrame.

Data Analysis Python

print(data.[1]())

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Atop

Bhead

Cfirst

Dshow

Attempts:

3 left

💡 Hint

Common Mistakes

Using methods like top() or show() which do not exist.

The head() method shows the first 5 rows by default.

3fill in blank

hard

Fix the error in the code to get summary statistics of the DataFrame.

Data Analysis Python

summary = data.[1]()

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Adescribe

Bsummary

Cinfo

Dstats

Attempts:

3 left

💡 Hint

Common Mistakes

Using info() which shows data types but not statistics.

The describe() method provides summary statistics like mean and median.

4fill in blank

hard

Fill both blanks to create a dictionary of word lengths for words longer than 3 letters.

Data Analysis Python

lengths = {word: [1] for word in words if len(word) [2] 3}

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Alen(word)

B>

C<

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' in the condition.

We use len(word) to get length and filter words with length greater than 3 using >.

5fill in blank

hard

Fill all three blanks to create a filtered dictionary with uppercase keys and values greater than 0.

Data Analysis Python

result = { [1]: [2] for k, v in data.items() if v [3] 0 }

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Ak.upper()

Bv

C>

Dk

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'k' instead of 'k.upper()' for keys.

Keys are converted to uppercase with k.upper(), values are v, and filtered where v > 0.