Innovative Pandas Test - 73+ MCQs: Pandas test: Evaluate Your Data Manipulation Skills with Pandas Questions and Answers

1. Which Pandas function is used to merge two DataFrames based on a common column?

merge()

concat()

combine()

join()

2. What is the purpose of the Pandas function 'df.mean()'?

Calculating the median of the DataFrame

Computing the mean of each column

Finding the mode of the DataFrame

Summing up all values in the DataFrame

3. In Pandas, how do you efficiently calculate a rolling window average for a specific column?

df['col'].rolling(window=3).average()

df['col'].rolling(window=3).mean()

averageRollingWindow(df['col'], window=3)

meanRollingWindow(df['col'], window=3)

4. In Pandas, what does the `isin()` method do?

Checks if a value is NaN

Filters rows based on a condition

Identifies duplicate values

Checks if a value is in a list

5. What does the Pandas function 'df.info()' provide?

Summary statistics of the DataFrame

Information about null values and data types

A concise summary of the DataFrame

Details about the unique values in each column

6. How can you convert a Pandas DataFrame to a NumPy array?

toNumpyArray()

asArray()

toArray()

values()

7. What is the purpose of the Pandas function 'df.iloc[]'?

Selecting rows and columns by labels

Accessing a group of rows and columns by integer positions

Filtering rows based on a condition

Sorting the DataFrame by specified columns

8. What is the purpose of the `pivot_table()` function in Pandas?

Create a pivot chart

Create a pivot table

Transpose a DataFrame

Sort values in a DataFrame

9. How can you efficiently handle missing values in a Pandas DataFrame considering both forward and backward filling?

fillna(method='ffill', limit=1)

forwardBackwardFill()

fillna(method='bfill', limit=1)

handleMissingValues('fb')

10. What does the `diff()` function in Pandas allow you to calculate?

Difference between consecutive elements in a column

Differentiate a DataFrame

Count the number of differences in each column

Calculate differentiated values based on a specified interval

11. In Pandas, what is the purpose of the `nunique()` function?

Calculate the number of unique elements

Count occurrences of each unique element

Count unique values in each column

Find the nth unique element

12. How can you calculate the median of a specific column 'column_name' in a Pandas DataFrame 'df'?

df.median(column_name)

df.calculate_median('column_name')

df['column_name'].median()

df.find_median(column_name)

13. Which Pandas function is used to perform element-wise mathematical operations on two DataFrames?

elementwise()

applyElementwise()

mathOps()

add()

14. Which method is used to fill missing values in a Pandas DataFrame?

fill()

replace()

fillna()

fix()

15. What is the purpose of the `resample()` method in Pandas?

Reshape a DataFrame

Convert time series to desired frequency

Aggregate data based on a time interval

Calculate time series entropy

16. In Pandas, what does the `explode()` function do?

Remove duplicate values

Expand lists into separate rows

Explode the entire DataFrame

Filter rows based on a condition

17. What is the purpose of the `ffill()` and `bfill()` functions in Pandas?

Calculate forward and backward fill for numerical columns

Fill missing values forward and backward in a column

Perform fast fill operations on a DataFrame

Filter rows based on forward and backward conditions

18. How do you efficiently apply a function to elements in a specific column of a Pandas DataFrame?

applyFunction(df, 'col', func)

df['col'].apply(func)

transformColumn(df, 'col', func)

func.apply(df['col'])

19. Which Pandas method is used to calculate the correlation between columns in a DataFrame?

correlation()

corr()

correlate()

calculateCorrelation()

20. How can you efficiently calculate the percentage change in a Pandas DataFrame for multiple columns?

pct_change(columns=['col1', 'col2'])

percentageChange(['col1', 'col2'])

df.pct_change().select(['col1', 'col2'])

df[['col1', 'col2']].pct_change()

Pandas MCQ Test 4