np.genfromtxt() for handling missing data in NumPy - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to load data from 'data.csv' using numpy's genfromtxt.

NumPy

import numpy as np
data = np.genfromtxt('data.csv', delimiter=[1])

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

A,

B;

C:

D|

Attempts:

3 left

💡 Hint

Common Mistakes

Using semicolon or other characters as delimiter when the file uses commas.

The delimiter for CSV files is a comma, so we use ',' in genfromtxt.

2fill in blank

medium

Complete the code to skip the first row (header) when loading data.

NumPy

data = np.genfromtxt('data.csv', delimiter=',', [1]=1)

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

Askip_header

Busecols

Cskip_footer

Ddtype

Attempts:

3 left

💡 Hint

Common Mistakes

Using skip_footer instead of skip_header.

Not skipping header and getting errors or wrong data.

skip_header=1 tells genfromtxt to skip the first row, often used for headers.

3fill in blank

hard

Fix the error in the code to correctly handle missing values represented by 'NA'.

NumPy

data = np.genfromtxt('data.csv', delimiter=',', skip_header=1, [1]='NA')

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

Amissing

Bfilling_values

Cinvalid_raise

Dmissing_values

Attempts:

3 left

💡 Hint

Common Mistakes

Using filling_values instead of missing_values to specify missing data.

Not specifying missing values and getting errors.

missing_values='NA' tells genfromtxt which strings represent missing data.

4fill in blank

hard

Complete the code to load data, skip header, and replace missing values with 0.

NumPy

data = np.genfromtxt('data.csv', delimiter=,, skip_header=[1], filling_values=0)

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

A,

B;

C1

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Using wrong delimiter or skip_header value.

Not using filling_values to replace missing data.

Delimiter is ',' for CSV. skip_header=1 skips the first row. filling_values=0 replaces missing data with zero.

5fill in blank

hard

Fill both blanks to load data, skip header, specify missing values as 'NA', and fill them with -1.

NumPy

data = np.genfromtxt('data.csv', delimiter=,, skip_header=[1], missing_values=[2], filling_values=-1)

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

A,

B1

C'NA'

D0

Attempts:

3 left

💡 Hint

Common Mistakes

Not specifying missing_values correctly.

Using wrong delimiter or skip_header values.

Delimiter is ',', skip_header=1 skips the first row, missing_values='NA' marks missing data, and filling_values=-1 replaces missing data with -1.