np.savetxt() and np.loadtxt() for text in NumPy - Practice Problems & Coding Challenges

Challenge - 5 Problems

❓ Predict Output

intermediate

Output of np.savetxt() and np.loadtxt() with default settings

What will be the output of the following code snippet?

import numpy as np
arr = np.array([[1.5, 2.5], [3.5, 4.5]])
np.savetxt('test.txt', arr)
loaded = np.loadtxt('test.txt')
print(loaded)

NumPy

import numpy as np
arr = np.array([[1.5, 2.5], [3.5, 4.5]])
np.savetxt('test.txt', arr)
loaded = np.loadtxt('test.txt')
print(loaded)

A

[[1.5 2.5]
 [3.5 4.5]]

B

[[1 2]
 [3 4]]

C [1.5 2.5 3.5 4.5]

D SyntaxError

💡 Hint

Remember that np.savetxt saves the array in text format and np.loadtxt loads it back as a numpy array with floats by default.

The np.savetxt function saves the 2D array in a text file with default float formatting. When loaded back with np.loadtxt, it returns the same 2D array with float values.

❓ data_output

intermediate

Number of rows loaded by np.loadtxt()

Given a text file data.txt containing the following lines:

10 20 30
40 50 60
70 80 90

What is the number of rows in the numpy array returned by np.loadtxt('data.txt')?

NumPy

import numpy as np
arr = np.loadtxt('data.txt')
print(arr.shape[0])

A 3

B 9

C 1

D 0

💡 Hint

Each line in the text file corresponds to one row in the loaded array.

The file has 3 lines, so np.loadtxt loads 3 rows in the array.

🔧 Debug

advanced

Error raised by np.loadtxt() with mixed data types

What error will the following code raise?

import numpy as np
np.savetxt('mixed.txt', [[1, 2], ['a', 4]], fmt='%s')
np.loadtxt('mixed.txt')

NumPy

import numpy as np
np.savetxt('mixed.txt', [[1, 2], ['a', 4]], fmt='%s')
np.loadtxt('mixed.txt')

A TypeError

B ValueError

C OSError

D No error, returns array

💡 Hint

Consider what happens when np.loadtxt tries to convert non-numeric strings to floats.

np.loadtxt tries to convert all data to floats by default. The string 'a' cannot be converted, so it raises a ValueError.

🚀 Application

advanced

Saving and loading with custom delimiter

You want to save a 2D numpy array with values separated by semicolons and then load it back correctly. Which code snippet will achieve this?

A

np.savetxt('file.csv', arr, delimiter=';')
loaded = np.loadtxt('file.csv')

B

np.savetxt('file.csv', arr)
loaded = np.loadtxt('file.csv', delimiter=';')

C

np.savetxt('file.csv', arr, delimiter=',')
loaded = np.loadtxt('file.csv', delimiter=';')

D

np.savetxt('file.csv', arr, delimiter=';')
loaded = np.loadtxt('file.csv', delimiter=';')

💡 Hint

Both saving and loading must use the same delimiter to match the data format.

Using delimiter=';' in both np.savetxt and np.loadtxt ensures the data is saved and read correctly with semicolon separators.

🧠 Conceptual

expert

Handling missing values with np.loadtxt()

You have a text file with numeric data but some values are missing and represented as empty strings. Which np.loadtxt parameter helps to handle missing values by replacing them with a specified number?

A missing_values

B usecols

C filling_values

D default_value

💡 Hint

Look for the parameter that fills missing data with a default number.

The filling_values parameter in np.loadtxt replaces missing values with a specified number during loading.