Pandas for Tabular Analysis: 10 practice questions

Question 1 of 10

Which pandas object represents a two-dimensional table with rows and columns?

1. AA Series with two independent column axes
2. BA scalar carrying multiple heterogeneous columns
3. CA DataFrame with labeled rows and columns
4. DAn Index containing every table value

Question 2 of 10

What gives a Series value identity beyond its numeric position?

1. AIts column position in a second axis
2. BIts display order after every operation
3. CIts associated label within the Index
4. DIts conversion to an unlabeled array

Question 3 of 10

How do arithmetic operations between Series pair their values by default?

1. AThey align values according to their Index labels
2. BThey pair values by displayed row position
3. CThey require identical ordering before any calculation
4. DThey discard labels before calculating values

Question 4 of 10

Two numeric Series have unique but different index labels. Which labels appear in the result when you add them with `+`?

1. AThe left Series labels with all values filled
2. BA new range based on the longer Series
3. CThe intersection with unmatched labels removed
4. DThe union containing labels from both Series

Question 5 of 10

Which conventional statement loads pandas under the alias used in its beginner guide?

1. Aimport pandas as pd
2. Bfrom DataFrame import pd
3. Cload pandas into Index
4. Dimport Series as pandas

Question 6 of 10

Which structure best fits one labeled sequence of daily temperatures?

1. AA Series indexed by the day labels
2. BA scalar repeated without any day labels
3. CAn Index used as the temperature values
4. DA DataFrame with no rows or columns

Question 7 of 10

Two Series contain no missing values before addition, but only the first contains `Mar`. What will the aligned result contain at `Mar`?

1. AA new RangeIndex entry replacing the `Mar` label
2. BA missing value because `Mar` has no match in the second Series
3. CA positional match with the second Series value at the same offset
4. DThe first Series value copied unchanged because `Mar` exists there

Question 8 of 10

Two monthly Series arrive in different orders, and one lacks March. You must add matching months without hiding the missing observation. What should you rely on?

1. ADisplayed position, which pairs the first rows and drops March
2. BLabel alignment, which pairs months and leaves March missing
3. CArray conversion, which preserves labels and fills March
4. DRangeIndex replacement, which restores the absent month automatically

Question 9 of 10

A dataset has many observations, named variables, and different types across variables. Which representation preserves both the table shape and variable types?

1. AA scalar whose repeated value stands for each typed variable
2. BA Series with every variable forced into one labeled dimension
3. CAn Index containing observations, variables, and values together
4. DA DataFrame with observations as rows and variables as columns

Question 10 of 10

An analyst must subtract one regional measure from another when the row order differs, and must retain regions present in just one input. Which model best meets both needs?

1. ASeries converted to arrays before their labels are compared
2. BUnlabeled arrays paired by their current row positions
3. CScalar values repeated over the left input positions
4. DLabeled Series aligned over the union of region labels