Data Wrangling 01

What function would you use to create a NumPy array filled with zeros?

• • a) np.zeros()

• b) np.empty()

• c) np.ones()

• d) np.array()

Which function would you use to read a CSV file into a DataFrame?

• • a) pd.read_table()

• b) pd.read_excel()

• c) pd.read_csv()

• d) pd.read_json()

How can you display the first five rows of a DataFrame?

• • a) df.first

• b) df.head()

• c) df.tail()

• d) df.sample()

How do you drop a column named 'Age' from a DataFrame df?

• • a) df.drop_column('Age')

• b) df.remove('Age')

• c) df.drop('Age', axis=1)

• d) df.delete('Age')

What method is used to check for missing values in a DataFrame?

• • a) df.isna()

• b) df.isnull()

• c) df.check_na()

• d) Both a and b

Which method is used to concatenate two DataFrames vertically?

• • a) pd.concat([df1, df2], axis=1)

• b) pd.merge([df1, df2])

• c) pd.concat([df1, df2], axis=0)

• d) pd.join([df1, df2])

Which function will you use to merge two DataFrames on a common column?

• • a) pd.concat()

• b) pd.append()

• c) pd.merge()

• d) pd.join()

How can you filter rows of a DataFrame based on a condition in a column?

• • a) df.filter('column > 10')

• b) df.query('column > 10')

• c) df[df['column'] > 10]

• d) Both B and C

How do you filter rows in a DataFrame where the values in the column 'Age' are greater than 30?

• • a) df.filter(df['Age'] > 30)

• b) df.query('Age > 30')

• • c) df[df.Age > 30]

• d) Both b and c

How can you filter rows in a DataFrame where the column 'town' is either 'BEDOK' or 'ANG MO KIO'?

• • a) df[df['town'] in ['BEDOK', 'ANG MO KIO']]

• b) df[df['town'].isin(['BEDOK', 'ANG MO KIO'])]

• c) df("town == 'BEDOK' == 'ANG MO KIO'")

• d) Both b and c