Quiz for Week 09!

How do you rename the "Age" column to "Years" in a DataFrame df?

• A) df.rename(columns={"Age": "Years"}, inplace=True)
• B) df.columns = ["Years"]
• C) df.columns.rename("Age", "Years")
• D) df.rename_column("Age", "Years")

If a DataFrame df has some rows with missing values, how can you remove these rows?

• A) df.remove_na()
• B) df.delete_na(inplace=True)
• C) df.dropna(inplace=True)
• D) df.clean_na()

How do you sort a DataFrame df by the "Age" column in descending order?

• A) df.sort_values("Age", ascending=False)
• B) df.sort(column="Age", descending=True)
• C) df.order_by("Age", reverse=True)
• D) df.arrange("Age", ascending=False)

If you want to reset the index of df and drop the existing index, which command should you use?

• A) df.reset_index()
• B) df.index.reset(drop=True)
• C) df.reset_index(drop=True, inplace=True)
• D) df.index.reset()

How do you group the data in df by the "City" column and calculate the mean "Age" for each city?

• A) df.groupby("City").Age.mean()
• B) df.group_by("City").mean("Age")
• C) df.groupby(["City"], mean("Age"))
• D) df.group("City").average("Age")