Challenge 1
Compito
Swipe to start coding
In this challenge, you will need to work with the 'adult-census.csv'
dataset. It contains both categorical and numerical data. Your task will be to prepare the data for processing.
- Read the dataset
'adult-census.csv'
- Explore the dataset. Carefully check which character indicates the missed data in the dataset and replace it with the
np.nan
object - Remove rows with missing values
- Let's start with processing categorical data - columns
'workclass'
,'sex'
Use a one-hot encoding method to encode them - For numeric data (
'age'
,'hours-per-week'
), you will need to scale the data - Print processed data
Soluzione
Tutto è chiaro?
Grazie per i tuoi commenti!
Sezione 6. Capitolo 1
single
Chieda ad AI
Chieda ad AI
Chieda pure quello che desidera o provi una delle domande suggerite per iniziare la nostra conversazione
Awesome!
Completion rate improved to 3.33
Challenge 1
Scorri per mostrare il menu
Compito
Swipe to start coding
In this challenge, you will need to work with the 'adult-census.csv'
dataset. It contains both categorical and numerical data. Your task will be to prepare the data for processing.
- Read the dataset
'adult-census.csv'
- Explore the dataset. Carefully check which character indicates the missed data in the dataset and replace it with the
np.nan
object - Remove rows with missing values
- Let's start with processing categorical data - columns
'workclass'
,'sex'
Use a one-hot encoding method to encode them - For numeric data (
'age'
,'hours-per-week'
), you will need to scale the data - Print processed data
Soluzione
Tutto è chiaro?
Grazie per i tuoi commenti!
Awesome!
Completion rate improved to 3.33Sezione 6. Capitolo 1
single