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: Feb 18, 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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Given a DataFrame df:
df = pd.DataFrame({
'A': [1, 2, 3],
'B': [4, 5, 6]
})
You want to square each individual element in the DataFrame. Which of the following code will accomplish this?
Answer: A
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Given a DataFrame df:
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Question 2
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You are evaluating a logistic regression model using the ROC curve. Which of the following is true regarding the Area Under the Curve (AUC)?
Answer: C
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You are evaluating a logistic regression model using the ROC curve. Which of the following is true regarding the Area Under the Curve (AUC)?
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Question 3
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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 4
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You have a dataset with 15 features and you want to visualize it on a 2D plot for exploratory data analysis. What would be the first step in using PCA (Principal Component Analysis) to achieve this?
Answer: D
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You have a dataset with 15 features and you want to visualize it on a 2D plot for exploratory data analysis. What would be the first step in using PCA (Principal Component Analysis) to achieve this?
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Question 5
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While working with a dataset, you notice some outliers that are not errors but extreme values that are relevant to your analysis. How should you handle them for ensuring the reliability and accuracy of your Python data analysis?
Answer: B
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While working with a dataset, you notice some outliers that are not errors but extreme values that are relevant to your analysis. How should you handle them for ensuring the reliability and accuracy of your Python data analysis?