Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.
Impara Combining Your Knowledge | Extracting Data
Advanced Techniques in pandas

bookCombining Your Knowledge

If you remember, several chapters ago you were provided with information on how to write several conditions simultaneously. With the .isin() statement, you can use the same rules. For instance, an example from the previous chapter could look like this:

# The initial example
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
data_extracted = data.loc[data['Manufacturer'].isin(models)]
print(data_extracted.head())

# The modified example
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
condition = data['Manufacturer'].isin(models)
data_extracted = data.loc[condition]
print(data_extracted.head())

The output in these two cases will be the same.

question-icon

Your task here is to make the data satisfy three conditions: cars' categories are 'Sedan', 'Jeep', 'Coupe', AND the car has a leather interior ('Leather_interior' == Yes), AND the types of gear box are 'Variator' or 'Automatic'.

import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)

categories = ['Sedan', 'Jeep', 'Coupe']
gear_box = ['Variator', 'Automatic']

condition_1 = data['Category'].

(categories)
condition_2 = data['Leather_interior']
'Yes'
condition_3 = data['Gear_box_type'].


data_extracted = data.loc[condition_1
condition_2condition_3]

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 3. Capitolo 2

Chieda ad AI

expand

Chieda ad AI

ChatGPT

Chieda pure quello che desidera o provi una delle domande suggerite per iniziare la nostra conversazione

Awesome!

Completion rate improved to 3.03

bookCombining Your Knowledge

Scorri per mostrare il menu

If you remember, several chapters ago you were provided with information on how to write several conditions simultaneously. With the .isin() statement, you can use the same rules. For instance, an example from the previous chapter could look like this:

# The initial example
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
data_extracted = data.loc[data['Manufacturer'].isin(models)]
print(data_extracted.head())

# The modified example
import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)
models = ['HONDA', 'FORD', 'MERCEDES-BENZ', 'HYUNDAI']
condition = data['Manufacturer'].isin(models)
data_extracted = data.loc[condition]
print(data_extracted.head())

The output in these two cases will be the same.

question-icon

Your task here is to make the data satisfy three conditions: cars' categories are 'Sedan', 'Jeep', 'Coupe', AND the car has a leather interior ('Leather_interior' == Yes), AND the types of gear box are 'Variator' or 'Automatic'.

import pandas as pd
data = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/4bf24830-59ba-4418-969b-aaf8117d522e/cars.csv', index_col = 0)

categories = ['Sedan', 'Jeep', 'Coupe']
gear_box = ['Variator', 'Automatic']

condition_1 = data['Category'].

(categories)
condition_2 = data['Leather_interior']
'Yes'
condition_3 = data['Gear_box_type'].


data_extracted = data.loc[condition_1
condition_2condition_3]

Tutto è chiaro?

Come possiamo migliorarlo?

Grazie per i tuoi commenti!

Sezione 3. Capitolo 2
some-alt