Basic DataFrame info (shape, dtypes, describe) in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to get the number of rows and columns in the DataFrame.

Data Analysis Python

print(df.[1])

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Acolumns

Bshape

Cinfo

Ddtypes

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'columns' returns only the column names, not the shape.

Using 'dtypes' returns data types, not the size.

The shape attribute gives the number of rows and columns as a tuple.

2fill in blank

medium

Complete the code to see the data types of each column in the DataFrame.

Data Analysis Python

print(df.[1])

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

Adtypes

Bshape

Cdescribe

Dhead

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'shape' returns size, not data types.

Using 'describe' gives statistics, not data types.

The dtypes attribute shows the data type of each column.

3fill in blank

hard

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

Data Analysis Python

summary = df.[1]()

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Adtypes

Bshape

Cinfo

Ddescribe

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'info' gives info about the DataFrame but not statistics.

Using 'shape' is an attribute, not a method.

The describe() method returns summary statistics like mean, count, and std.

4fill in blank

hard

Fill both blanks to create a dictionary with 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 '>' filters wrong words.

Using 'word' as value stores the word, not its length.

The dictionary comprehension uses len(word) for values and filters words with length greater than 3.

5fill in blank

hard

Fill all three blanks to create a 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.lower()

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'k.lower()' makes keys lowercase, not uppercase.

Using '<' instead of '>' filters wrong values.

The dictionary comprehension uses uppercase keys with k.upper(), keeps values v, and filters values greater than 0.