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: Jun 06, 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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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 2
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You are pulling data from various databases using Python to compile a large dataset for analysis. How would you ensure the data’s accuracy and reliability?
Answer: C
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You are pulling data from various databases using Python to compile a large dataset for analysis. How would you ensure the data’s accuracy and reliability?
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Question 3
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You have the following Pandas DataFrame with some missing values:
import pandas as pd
import numpy as np
df = pd.DataFrame(
{"A": [1, np.nan, 3], "B": [4, 5, np.nan], "C": [7, 8, 9]}
)
How would you fill the missing values in column 'A' with the mean value of that column?
Answer: B
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You have the following Pandas DataFrame with some missing values:
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Question 4
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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 5
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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?