Free Python Institute PCED Exam Questions
Try our Free Demo Practice Tests for Comprehensive PCED Exam Preparation
-
Python Institute PCED Exam Questions
-
Provided By: Python Institute
- Exam: Certified Entry-Level Data Analyst with Python
- Certification: PCED
-
Total Questions: 382
-
Updated On: Sep 25, 2024
-
Rated: 4.9 |
-
Online Users: 764
-
Question 1
-
You are working on a project that requires real-time data collection from a WebSocket API. Which of the following Python libraries would be most appropriate for this task?
Answer: B
-
You are working on a project that requires real-time data collection from a WebSocket API. Which of the following Python libraries would be most appropriate for this task?
-
Question 2
-
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
-
You have the following Pandas DataFrame with some missing values:
-
Question 3
-
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
-
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?
-
Question 4
-
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
-
Given a DataFrame df:
-
Question 5
-
You have a dataset of a retail company's sales transactions, which includes details like customer ID, transaction amount, transaction date, and store ID. You're tasked with summarizing monthly revenue for each store. What would be the most appropriate data aggregation technique?
Answer: D
-
You have a dataset of a retail company's sales transactions, which includes details like customer ID, transaction amount, transaction date, and store ID. You're tasked with summarizing monthly revenue for each store. What would be the most appropriate data aggregation technique?