PCED Exam: Absolutely Free Online Practice

Question 1
- 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 2
- 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?
  
  A : csv
  
  B : websocket-client
  
  C : urllib
  
  D : scrapy
  
  Answer: B
Question 3
- You are a data analyst who needs to collect large volumes of data from a RESTful API that has pagination implemented. Which Python code snippet would be the most effective way to gather all the available data?
  
  A : import requests
  
  page = 1
  while True:
  response = requests.get(f"https://api.example.com/data?page={page}")
  if response.status_code != 200:
  break
  data = response.json()
  # Process data
  page += 1
  
  B : import requests
  
  response = requests.get("https://api.example.com/data")
  data = response.json()
  
  C : import requests
  
  pages = [1, 2, 3, 4, 5]
  for page in pages:
  response = requests.get(f"https://api.example.com/data?page={page}")
  data = response.json()
  # Process data
  
  D : import requests
  
  for page in range(1, 100):
  response = requests.get(f"https://api.example.com/data?page={page}")
  data = response.json()
  # Process data
  
  Answer: A
Question 4
- You are tasked with merging two datasets, df1 and df2, on a common column 'id'. df1 has a column 'value1' and df2 has a column 'value2'. After merging, you need to create a new column called 'total_value' that sums 'value1' and 'value2'. Which of the following code snippets accomplishes this?
  
  A : df_merged = pd.concat([df1, df2], keys='id')
  df_merged['total_value'] = df_merged['value1'] + df_merged['value2']
  
  B : df_merged = df1.merge(df2)
  df_merged['total_value'] = df1['value1'] + df2['value2']
  
  C : df_merged = df1.join(df2, on='id')
  df_merged['total_value'] = df1['value1'] + df2['value2']
  
  D : df_merged = pd.merge(df1, df2, on='id')
  df_merged['total_value'] = df_merged['value1'] + df_merged['value2']
  
  Answer: D
Question 5
- 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

Free Python Institute PCED Exam Questions

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