Record arrays in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a record array from a list of tuples.

NumPy

import numpy as np

data = [(1, 'Alice', 3.5), (2, 'Bob', 4.0)]
dtype = [('id', 'i4'), ('name', 'U10'), ('score', 'f4')]
record_array = np.array(data, dtype=[1])

Drag options to blanks, or click blank then click option'

Arecord

Bdata

Clist

Ddtype

Attempts:

3 left

💡 Hint

Common Mistakes

Passing the data list as dtype instead of the dtype variable.

Forgetting to specify dtype when creating the array.

We use the 'dtype' variable to specify the data types when creating the record array.

2fill in blank

medium

Complete the code to access the 'name' field from the record array.

NumPy

names = record_array[1]

Drag options to blanks, or click blank then click option'

A[0]

B.name

C['name']

D[['name']]

Attempts:

3 left

💡 Hint

Common Mistakes

Using double brackets which returns a subarray instead of a field.

Using string indexing which is invalid for record arrays.

You can access fields in a record array using dot notation with the field name.

3fill in blank

hard

Fix the error in the code to create a record array with named fields.

NumPy

import numpy as np

values = [(10, 'John', 2.5), (20, 'Jane', 3.0)]
dtype = [('age', 'i4'), ('name', 'U5'), ('height', 'f4')]
rec_arr = np.array(values, [1]=dtype)

Drag options to blanks, or click blank then click option'

Adtypes

Btype

Cdtype

Dformat

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'type' instead of 'dtype'.

Using 'dtypes' which is not recognized.

The correct keyword argument to specify data types is 'dtype'.

4fill in blank

hard

Fill both blanks to create a record array and access the 'score' field.

NumPy

import numpy as np

values = [(1, 'Ann', 4.2), (2, 'Ben', 3.8)]
dtype = [('id', 'i4'), ('name', 'U10'), ('score', 'f4')]
rec_arr = np.array([1], dtype=[2])
scores = rec_arr.score

Drag options to blanks, or click blank then click option'

Avalues

Bdtype

Cdata

Drecords

Attempts:

3 left

💡 Hint

Common Mistakes

Swapping the data and dtype variables.

Using undefined variables for data or dtype.

We pass the data list 'values' and the data type 'dtype' to create the record array.

5fill in blank

hard

Fill all three blanks to create a record array, filter by score > 3.5, and get names.

NumPy

import numpy as np

values = [(1, 'Tom', 3.2), (2, 'Sue', 4.5), (3, 'Max', 3.8)]
dtype = [('id', 'i4'), ('name', 'U10'), ('score', 'f4')]
rec_arr = np.array([1], dtype=[2])
high_scores = rec_arr[rec_arr.score [3] 3.5]
names = high_scores.name

Drag options to blanks, or click blank then click option'

Avalues

Bdtype

C>

D<

Attempts:

3 left

💡 Hint

Common Mistakes

Using '<' instead of '>' for filtering.

Using wrong variable names for data or dtype.

We create the record array from 'values' and 'dtype', then filter scores greater than 3.5 using '>'.