Free Python Institute PCED Exam Questions
Absolute Free PCED Exam Practice for Comprehensive Preparation
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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: Nov 24, 2025
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Rated: 4.9 |
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Online Users: 764
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Question 1
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You are given a DataFrame df with a column 'Date' of type string in the format 'YYYY-MM-DD'. You want to filter the rows where the year is 2020. Which of the following code snippets is the most efficient way to do so?
Answer: C
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You are given a DataFrame df with a column 'Date' of type string in the format 'YYYY-MM-DD'. You want to filter the rows where the year is 2020. Which of the following code snippets is the most efficient way to do so?
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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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When creating a dashboard using Tableau, which option allows you to integrate real-time Python code execution into your dashboard?
Answer: E
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When creating a dashboard using Tableau, which option allows you to integrate real-time Python code execution into your dashboard?
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Question 4
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You are implementing an ETL pipeline to fetch data from a JSON-based API and load it into a data lake. The API provides a pagination feature that shows 100 records per page. Which of the following Python libraries is most suitable for performing HTTP requests to extract data from this API?
Answer: A
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You are implementing an ETL pipeline to fetch data from a JSON-based API and load it into a data lake. The API provides a pagination feature that shows 100 records per page. Which of the following Python libraries is most suitable for performing HTTP requests to extract data from this API?
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Question 5
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You are working with a dataset that includes both categorical and continuous features. Which of the following feature scaling techniques would be most appropriate for scaling only the continuous features?
Answer: A
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You are working with a dataset that includes both categorical and continuous features. Which of the following feature scaling techniques would be most appropriate for scaling only the continuous features?