Mastering Pandas: A Comprehensive Test

What is a DataFrame in Pandas?

• A DataFrame is a one-dimensional array in Pandas.

• A DataFrame is a two-dimensional labeled data structure in Pandas.

• A DataFrame is a type of database in Pandas.

• A DataFrame is a graphical representation of data in Pandas.

How do you create a DataFrame from a dictionary?

• Use pd.DataFrame(your_dict) where your_dict is your dictionary.

• Call pd.createDataFrame(your_dict) to generate a DataFrame.

• Convert your_dict to a list before creating a DataFrame.

• Use your_dict.DataFrame() to create a DataFrame.

What method would you use to view the first five rows of a DataFrame?

• df.slice(5)

• df.take(5)

• df.head(5)

• df.first(5)

How can you filter rows in a DataFrame based on a condition?

• df.where(condition)

• df.filter(condition)

• df.select(condition)

• df[condition] where condition is a boolean mask.

What function is used to sort a DataFrame by a specific column?

• filter_values

• order_by

• group_by

• sort_values

How do you handle missing values in a DataFrame?

• Ignore missing values and proceed with analysis.

• Use 'remove()' to delete missing values.

• Replace missing values with zero using 'replace()'.

• Use 'dropna()' to remove or 'fillna()' to replace missing values.

Which method would you use to visualize data in a DataFrame?

• Use the 'plot' method.

• Use the 'render' method.

• Use the 'show' method.

• Use the 'display' method.

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

• To sort data in ascending order.

• To merge two DataFrames together.

• To group data for aggregation or transformation.

• To filter out specific rows from a DataFrame.

How can you calculate the mean of a grouped DataFrame?

• Use sum() followed by count() on the DataFrame.

• Calculate the mean using the median() function.

• Apply mean() directly without grouping.

• Use groupby() followed by mean() on the DataFrame.

What is the difference between the agg() and transform() methods in groupby operations?

• agg() and transform() are identical in functionality.

• agg() summarizes data while transform() returns a modified version of the original data.

• agg() can only be used on numeric data while transform() works on all data types.

• agg() modifies the original data while transform() summarizes it.