Pandas Slicing Quiz1

Which of the following commands will return the first five rows of a DataFrame named df?

• df.head(5)

• df.first(5)

• df.slice(0, 5)

• df[0:6]

What is the output of df.iloc[0:3, 1] if df is a DataFrame with multiple columns?

• The first three rows of all columns.

• The first three rows of the second column.

• All rows of the second column.

• An error because of an invalid index.

Which of the following is a correct way to slice rows conditionally in a DataFrame df where the column 'A' is greater than 10?

• df[df['A'] > 10]

• df.loc[df['A'] > 10]

• Both A and B

• df.iloc[df['A'] > 10]

What does df.loc[:, 'A':'C'] return when applied to a DataFrame df?

• All rows and only columns A, B, and C.

• All columns from A to C, excluding C.

• All rows and all columns up to C, including C.

• Only column A and all rows.

How would you access the value in the second row and third column of a DataFrame df using iloc?

• df.iloc[2, 3]

• df.iloc[1:2, 2]

• df[1, 3]

• df.iloc[1, 2]

If df is a DataFrame, which statement is true about df.loc[0]?

• It returns the entire DataFrame.

• It will raise an error if the index starts from 1.

• It accesses the first row by integer index position.

• It accesses the first row by index label.

Which of the following methods can be used to set the index of a DataFrame df to a column named 'ID'?

• df.set('ID')

• df['ID'].set_index()

• df.set_index('ID', inplace=True)

• df.index = 'ID'

Which command will return rows where the value in column 'B' is equal to 'Yes'?

• df[df['B'] == 'Yes']

• df.loc[df['B'] == 'Yes']

• Both A and B

• df.iloc[df['B'] == 'Yes']

If you want to retrieve rows from a DataFrame df where column 'A' is greater than 5 and less than 15, which command would you use?

• df[(df['A'] > 5) & (df['A'] < 15)]

• df.loc[5 < df['A'] < 15]

• df.iloc[5 < df['A'] < 15]

• df['A'].between(5, 15)

What will be the result of executing df.loc[df['A'] > 5, ['B', 'C']] in a DataFrame df?

• A Series containing only the values in column 'B' where 'A' is greater than 5.

• A DataFrame containing only the columns 'B' and 'C' for rows where 'A' is greater than 5.

• An error, because you cannot select multiple columns with loc.

• A DataFrame containing all columns for rows where 'A' is greater than 5.