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    • Python Numpy Quiz

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    Question 1

    How can you calculate the element-wise square root of a NumPy array arr?

    • A

      np.sqrt(arr)

    • B

      arr.sqrt()

    • C

      np.square_root(arr)

    • D

      arr.square_root()

    Question 2

    Question: How can you save a Pandas DataFrame to a CSV file?

    • A

      df.save_csv("filename.csv")

    • B

      df.write_csv("filename.csv")

    • C

      df.to_csv("filename.csv")

    • D

      df.export_csv("filename.csv")

    Question 3

    How can you perform a time-based resampling in Pandas?

    • A

      df.resample()

    • B

      df.time_resample()

    • C

      df.groupby("time_column").resample()

    • D

      df.time_groupby().resample()

    Question 4

    What is the purpose of the melt() function in Pandas?

    • A

      To melt a DataFrame into a longer format

    • B

      To create a melted cheese plot

    • C

      To melt a DataFrame into a wider format

    • D

      To melt a DataFrame into a binary format

    Question 5

    How can you handle duplicate values in a Pandas DataFrame?

    • A

      Use the df.drop_duplicates() method

    • B

      Use the df.remove_duplicates() method

    • C

      Use the df.drop_duplicate_rows() method

    • D

      Use the df.eliminate_duplicates() method

    Question 6

    How can you handle missing values in a Pandas DataFrame?

    • A

      Use df.fillna(value) to replace missing values

    • B

      Use df.dropna() to remove rows with missing values

    • C

      Both A and B

    • D

      Neither A nor B

    Question 7

    How can you merge two DataFrames in Pandas?

    • A

      df.concat()

    • B

      df.join()

    • C

      df.merge()

    • D

      df.combine()

    Question 8

    Write code to normalize a NumPy array arr by scaling its values to be between 0 and 1.

    • A

      normalized_arr = (arr - arr.min()) / (arr.max() - arr.min())

    • B

      normalized_arr = np.scale(arr)

    • C

      normalized_arr = arr.normalize()

    • D

      normalized_arr = (arr - arr.mean()) / arr.std()

    Question 9

    How can you calculate the mean along a specific axis of a 2D NumPy array arr?

    • A

      mean_values = np.mean(arr, axis=1)

    • B

      mean_values = arr.mean(axis=0)

    • C

      mean_values = np.average(arr, axis=1)

    • D

      mean_values = arr.mean(axis=2)

    Question 10

    Write code to find the intersection of two NumPy arrays a and b.

    • A

      intersection = np.intersect(a, b)

    • B

      intersection = np.common(a, b)

    • C

      intersection = np.intersect1d(a, b)

    • D

      intersection = a.intersection(b)

    There are 25 questions to complete.

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