Data Science with Python Certification Introduction to Python for Data Science 5

Question 1

What does `df.groupby('category').mean()` compute in pandas?

Accepted Answer

The mean of all numeric columns grouped by unique values in 'category'

Answer

`groupby` splits the DataFrame by unique values in 'category' and `.mean()` computes the column-wise mean for each group.

Question 2

What is the output of `list(map(lambda x: x*2, [1, 2, 3]))`?

Accepted Answer

[2, 4, 6]

Answer

`map` applies the lambda function (doubling each element) to every item in the list, producing [2, 4, 6].

Question 3

Which seaborn function is best suited for visualizing the distribution of a single continuous variable?

Accepted Answer

sns.histplot()

Answer

`sns.histplot()` displays the distribution of a single variable using histogram bins, optionally with a KDE overlay.

Question 4

What is the purpose of `np.reshape()` in NumPy?

Accepted Answer

Returns a new array with the same data but a different shape

Answer

`np.reshape(array, new_shape)` returns a view or copy of the array rearranged into the specified shape without altering data.

Question 5

In Python, what is the difference between `deepcopy` and a shallow copy of an object?

Accepted Answer

Deepcopy creates independent copies of nested objects; shallow copy only copies the top-level container

Answer

A shallow copy copies the container but references the same nested objects; `deepcopy` recursively copies all nested objects as well.

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