Data Analytics Flashcards

What is the primary purpose of normalization in data preprocessing?

Answer: Scale numerical features to a common range

Normalization (e.g., min-max scaling) rescales features so they share a common range, preventing features with large magnitudes from dominating algorithms.

In pandas, what does the method df.groupby('category').agg({'sales': 'sum'}) return?

Answer: The sum of sales for each unique category

groupby().agg() groups the DataFrame by the specified column and applies the aggregation function (sum) to the 'sales' column within each group.

Which type of join returns only rows that have matching values in both tables?

Answer: INNER JOIN

An INNER JOIN returns only the rows where the join condition is satisfied in both tables, excluding non-matching rows from either side.

A dataset has mean=50 and standard deviation=10. What percentage of data falls between 40 and 60 assuming a normal distribution?

Answer: 68%

By the empirical rule (68-95-99.7), approximately 68% of normally distributed data falls within one standard deviation (±1σ) of the mean.

What is a 'pivot table' used for in data analysis?

Answer: Summarizing and reorganizing data by grouping and aggregating

A pivot table summarizes data by grouping rows and columns and applying aggregate functions, making it easy to compare values across categories.

Which Python code correctly calculates the mean of a list [10, 20, 30, 40]?

Answer: sum([10,20,30,40]) / len([10,20,30,40])

The mean is calculated by dividing the sum of all values by the count of values; sum()/len() implements this directly.

In a heatmap used for correlation analysis, what does a cell value close to 1 (dark color) represent?

Answer: The two variables have a strong positive correlation

In a correlation heatmap, values near +1 indicate that as one variable increases, the other tends to increase strongly as well.