Weeks 5-6 Quiz Exploratory Data

What is the primary purpose of Exploratory Data Analysis (EDA)?

• A. To clean and preprocess data

• B. To identify patterns, trends, and outliers in the data

• C. To train machine learning models

• D. To visualize final insights

Which of the following is NOT typically a part of EDA?

• A. Summary statistics

• B. Data cleaning

• C. Model training

• D. Data visualization

Which function is commonly used to calculate summary statistics in pandas?

• A. describe()

• B. summary()

• C. calc_stats()

• D. analyze()

What type of plot is useful for visualizing the distribution of a single numerical variable?

• A. Line plot

• B. Bar plot

• C. Histogram

• D. Box plot

How can you visualize the relationship between two numerical variables in pandas?

• A. plot()

• B. scatter()

• C. line()

• D. groupby()

Which of the following is a method to handle missing data in pandas?

• A. fillna()

• B. dropna()

• C. replace()

• D. All of the above

Which of the following pandas functions is used to check for missing values?

• A. isnull()

• B. isna()

• C. both()

• D. A and B

What is the default behavior of the dropna() function?

• A. Drops columns with missing values

• B. Drops rows with missing values

• C. Replaces missing values with zeros

• D. Replaces missing values with the mean

Which of the following would you use to fill missing values with the mean of a column?

• A. fillna(method='mean')

• B. fillna(mean())

• C. fillna(df.mean())

• D. replace_na(df.mean())

How do you replace missing values with a specific value, such as 0?

• A. df.fillna(0)

• B. df.replace(0)

• C. df.fill(0)

• D. df.replace_na(0)