Chi-squared test in Data Analysis Python - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to import the chi2_contingency function from scipy.stats.

Data Analysis Python

from scipy.stats import [1]

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Achi2_contingency

Bchi_square

Ccontingency_table

Dchi2_test

Attempts:

3 left

💡 Hint

Common Mistakes

Using a function name that does not exist in scipy.stats.

Confusing the function name with similar sounding names.

The chi2_contingency function is the correct function to perform the chi-squared test on a contingency table.

2fill in blank

medium

Complete the code to create a contingency table from two categorical columns in a pandas DataFrame named df.

Data Analysis Python

contingency_table = pd.crosstab(df['Category1'], [1])

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Adf['Count']

Bdf['Category1']

Cdf['Value']

Ddf['Category2']

Attempts:

3 left

💡 Hint

Common Mistakes

Using the same column twice in crosstab.

Using a non-categorical column like 'Value' or 'Count'.

The pd.crosstab function takes two categorical series to create a contingency table. The second argument should be the other categorical column, here df['Category2'].

3fill in blank

hard

Fix the error in the code to perform the chi-squared test on the contingency table named table.

Data Analysis Python

chi2, p, dof, expected = [1](table)

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Achi2_contingency

Bchi_test

Cchi_square

Dcontingency_test

Attempts:

3 left

💡 Hint

Common Mistakes

Using a non-existent function name.

Confusing the function name with similar sounding names.

The correct function to perform the chi-squared test on a contingency table is chi2_contingency.

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 len(word) [2] 3}

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Alen(word)

B<

C>

Dword

Attempts:

3 left

💡 Hint

Common Mistakes

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

Using the wrong comparison operator.

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

5fill in blank

hard

Fill all three blanks to create a dictionary comprehension that maps each key uppercased to its value only if the value is 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 the original key instead of uppercased key.

Using the wrong comparison operator in the condition.

The dictionary comprehension uses k.upper() as the key, v as the value, and filters items where v > 0.