Free Python Institute PCED Exam Questions
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Python Institute PCED Exam Questions
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Provided By: Python Institute
- Exam: Certified Entry-Level Data Analyst with Python
- Certification: PCED
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Total Questions: 382
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Updated On: Mar 08, 2026
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Rated: 4.9 |
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Online Users: 764
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Question 1
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Your Python script is taking significantly longer than expected to complete. Which Python standard library could provide you with granular insights into the time taken by different parts of your code?
Answer: B
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Your Python script is taking significantly longer than expected to complete. Which Python standard library could provide you with granular insights into the time taken by different parts of your code?
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Question 2
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While transforming extracted data to fit operational needs, which of the following operations is least likely to be performed?
Answer: C
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While transforming extracted data to fit operational needs, which of the following operations is least likely to be performed?
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Question 3
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You need to collect data from an Excel file with multiple sheets. One of the sheets is named "Sales" and another is named "Inventory". You want to load the "Sales" sheet into a DataFrame named df_sales and the "Inventory" sheet into a DataFrame named df_inventory. Which of the following code snippets accomplishes this?
Answer: B
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You need to collect data from an Excel file with multiple sheets. One of the sheets is named "Sales" and another is named "Inventory". You want to load the "Sales" sheet into a DataFrame named df_sales and the "Inventory" sheet into a DataFrame named df_inventory. Which of the following code snippets accomplishes this?
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Question 4
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What is the primary reason to use PCA (Principal Component Analysis) over t-SNE when visualizing high-dimensional data?
Answer: B
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What is the primary reason to use PCA (Principal Component Analysis) over t-SNE when visualizing high-dimensional data?
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Question 5
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Which of the following NumPy methods would you use to apply a function element-wise on a 1-D array, while maintaining the shape of the original array?
Answer: D
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Which of the following NumPy methods would you use to apply a function element-wise on a 1-D array, while maintaining the shape of the original array?