Python Institute PCED Exam Real Questions

Prepare and pass your Certified Entry-Level Data Analyst with Python with free PCED exam questions.

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Total 382 Questions | Updated On: Sep 13, 2024

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Question 1

When would you typically use the iloc attribute as opposed to the loc attribute in a pandas DataFrame?

A : When you want to apply a lambda function to each row

B : When you want to drop missing values from the DataFrame

C : When you want to access rows and columns by label

D : When you want to access rows and columns by integer-location

Answer: D

Question 2

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?

A : Perform clustering on the dataset

B : Apply a linear regression model to reduce dimensions

C : Use a scatter plot to visualize all the features

D : Standardize the dataset

Answer: D

Question 3

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?

A : df['A'] = df['A'].fillna(df['C'].mean())

B : df['A'].fillna(df['A'].mean(), inplace=True)

C : df.fillna({'A': df['A'].mean()})

D : df['A'].apply(lambda x: x.fillna(x.mean()))

Answer: B

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?

A : df.applymap(lambda x: x**2)

B : df['A'].apply(lambda x: x**2)

C : df.map(lambda x: x**2)

D : df.apply(lambda x: x**2, axis=1)

Answer: A

Question 5

While evaluating a logistic regression model using a confusion matrix, you notice that the True Positive rate is significantly higher than the True Negative rate. What does this observation imply?

A : The model is better at identifying the positive class than the negative class

B : The model performs equally well for both classes

C : The model has a high level of bias

D : The model is overfitting

Answer: A

Page: 1 / 77

Total 382 Questions | Updated On: Sep 13, 2024

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