Why groupby summarizes data by category in Data Analysis Python - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to group the DataFrame by the 'Category' column.

Data Analysis Python

grouped = df.groupby([1])

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A'Category'

B'Date'

C'Value'

D'Amount'

Attempts:

3 left

💡 Hint

Common Mistakes

Grouping by a numeric column like 'Value' instead of 'Category'.

Using a column name that does not exist in the DataFrame.

The groupby function groups data based on the values in the specified column. Here, grouping by 'Category' means data will be summarized for each category.

2fill in blank

medium

Complete the code to calculate the sum of values for each category.

Data Analysis Python

summary = df.groupby('Category').[1]()

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Amax

Bmean

Ccount

Dsum

Attempts:

3 left

💡 Hint

Common Mistakes

Using mean() which calculates average instead of sum.

Using count() which counts rows, not sums values.

The sum() function adds up all values in each group, giving the total per category.

3fill in blank

hard

Fix the error in the code to group by 'Category' and get the average value.

Data Analysis Python

result = df.[1]('Category').mean()

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Agroup_by

Bgroup

Cgroupby

Daggregate

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'group' or 'group_by' which are not pandas methods.

Using 'aggregate' without specifying grouping first.

The correct method to group data in pandas is groupby(). Other options are invalid and cause errors.

4fill in blank

hard

Fill both blanks to create a dictionary comprehension that maps each word to its length only if the length is greater than 3.

Data Analysis Python

lengths = {word: [1] for word in words if [2]

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Alen(word)

Bword

Clen(word) > 3

Dword > 3

Attempts:

3 left

💡 Hint

Common Mistakes

Using the word itself as the value instead of its length.

Checking if the word is greater than 3 instead of its length.

The dictionary comprehension maps each word to its length using len(word). The condition len(word) > 3 filters words longer than 3 characters.

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps uppercase keys to values, including only items where value is positive.

Data Analysis Python

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

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Ak.upper()

Bv

Ck

Dv.upper()

Attempts:

3 left

💡 Hint

Common Mistakes

Using value as key or uppercase value instead of uppercase key.

Not iterating over key and value pairs correctly.

The comprehension uses k.upper() as keys, v as values, and iterates over k, v pairs from data.items(). It filters to keep only positive values.