100% Free PCED-30-01 Practice Exam Questions (2026)

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Python Institute PCED-30-01 Dumps & Practice Test Questions 2026

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Total 382 Questions | Updated On: Aug 02, 2026

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Question 1

You have a Pandas DataFrame that contains missing values. Which of the following methods will replace all NaNs with zeros?

A : df.fillna(value=0)

B : df.replace(to_replace=np.nan, value=0)

C : df['column_name'] = 0

D : df.dropna(subset=['column_name'])

Answer: A

Question 2

You are given a JSON file containing social data about users' interactions on a website. The JSON object includes an array named likes that should contain integers representing the number of likes each post has received. Which of the following Python code snippets would be most appropriate to validate that all elements in the likes array are indeed integers?

A : import json data = json.load(open('data.json')) if len(data['likes']) > 0: print("Data is valid")else: print("Data is invalid")

B : import json data = json.load(open('data.json')) if all(isinstance(x, int) for x in data['likes']): print("Data is valid")else: print("Data is invalid")

C : import json data = json.loads('data.json') if isinstance(data['likes'], list): print("Data is valid")else: print("Data is invalid")

D : import json data = json.load(open('data.json')) if 'likes' in data.keys(): print("Data is valid")else: print("Data is invalid")

Answer: B

Question 3

In Python, which of the following methods is not a common statistical approach to identify outliers within a dataset?

A : Interquartile Range (IQR)

B : Z-score

C : Tukey's Fences

D : Mean Squared Error (MSE)

Answer: D

Question 4

You are working with a large dataset containing multi-dimensional features related to customer behavior. The dataset is too large and complex to analyze easily. What technique could be most effective for reducing the dataset's dimensionality while retaining most of its original variance?

A : Principal Component Analysis (PCA)

B : One-hot encoding

C : Linear Discriminant Analysis (LDA)

D : Max-Min Scaling

Answer: A

Question 5

You are working with a small dataset and want to assess your model's performance. Your colleague recommends using k-fold cross-validation. However, you are concerned about the reliability of the evaluation. What cross-validation technique would be most appropriate for your small dataset?

A : Leave-One-Out Cross-Validation (LOOCV)

B : Shuffle-Split Cross-Validation

C : Regular k-Fold Cross-Validation

D : Stratified k-Fold Cross-Validation

E : Time Series Cross-Validation

Answer: A

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Total 382 Questions | Updated On: Aug 02, 2026

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