Data-Science-11

What does np.nan stand for?

• Not a Null

• Not a Number

• Null Array

• Not Available

Which library provides np.nan?

• pandas

• matplotlib

• numpy

• sklearn

What is the main purpose of handling missing values?

• To improve prediction accuracy

• To speed up the model

• To remove all columns

• To avoid using pandas

Which method drops all rows with missing data?

• fillna()

• isnull()

• replace()

• dropna()

What function replaces missing values with a specific value?

• fillna()

• isnull()

• drop()

• cut()

Which method returns the most frequent value in a column?

• df.count()

• df.mode()

• df.median()

• df.mean()

What happens if you use dropna() on a DataFrame?

• It fills missing values

• It merges columns

• It duplicates data

• It deletes rows with any missing value

How to find columns with missing values?

• df.describe()

• df.isnull().sum()

• df.mean()

• df.count()

How is the mean calculated?

• df.mean()

• np.mean(df)

• df['Age'].mean()

• df.fillna.mean()

Which pandas method helps to see missing value locations as True/False?

• isnull()

• fillna()

• dropna()

• unique()