Numpy and Pandas Quiz

What is the function in Numpy used to create an array?

• np.make_array()

• np.create()

• np.arr()

• np.array()

How can you perform element-wise addition of two Numpy arrays?

• array_c = array_a - array_b

• array_c = array_a * array_b

• array_c = array_a + array_b

• array_c = np.add(array_a, array_b)

Explain the difference between loc and iloc in Pandas.

• loc is label-based, iloc is integer position-based

• loc is integer-based, iloc is label-based

• loc is position-based, iloc is index-based

• loc is row-based, iloc is column-based

What is the purpose of Numpy array indexing?

• Numpy array indexing is used to perform mathematical operations on arrays.

• Numpy array indexing is used to access specific elements or groups of elements within a Numpy array.

• Numpy array indexing is used to convert arrays into lists.

• Numpy array indexing is used for sorting elements in an array.

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

• df.filter('column_name' > value)

• df[df['column_name'] > value]

• df.query('column_name' > value)

• df['column_name'].filter(value)

What is the shape attribute of a Numpy array used for?

• Determining the dimensions of the array

• Calculating the mean of the array

• Setting the color of the array

• Sorting the elements of the array

What is the main advantage of using Pandas over Numpy for data manipulation?

• Faster computation speed

• Higher-level data structures and functions

• Limited data manipulation capabilities

• Less flexibility in data handling

How can you perform matrix multiplication using Numpy arrays?

• np.add(array1, array2)

• np.multiply(array1, array2)

• array1 * array2

• np.dot(array1, array2) or array1 @ array2

Explain the concept of broadcasting in Numpy.

• Broadcasting allows for efficient element-wise operations on arrays of different shapes without the need for explicit loops.

• Broadcasting results in errors when arrays have different shapes

• Broadcasting is only applicable to arrays of the same shape

• Broadcasting requires explicit loops for element-wise operations

What method in Pandas is used to drop missing values from a DataFrame?

• filter_nulls()

• remove_missing()

• clean_data()

• dropna()