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Leer Accessing using .loc[] [2/3] | Accessing DataFrame Values
Introduction to pandas [track]
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Cursusinhoud

Introduction to pandas [track]

Introduction to pandas [track]

1. Basics
2. Reading and Exploring Data
3. Accessing DataFrame Values
4. Aggregate Functions

book
Accessing using .loc[] [2/3]

Not only you can get certain rows, but you can also get specific columns. To set column/columns you want to receive, pass it as the second parameter between square brackets of .loc[].

If you want to indicate only one column, just place its name. If you want to indicate several columns, you need to pass list of their names.

Note that the first parameter must be set, even if you don't want to indicate specific rows (use : instead).

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# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Get the first five rows (indexes 0-4) and column 'fuelType' print(df.loc[:4, 'fuelType']) # Get the 9th - 11th rows (indexes 8, 9, 10) and columns 'model', 'year', and 'price' print(df.loc[8:10, ['model', 'year', 'price']])
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Sectie 3. Hoofdstuk 7

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course content

Cursusinhoud

Introduction to pandas [track]

Introduction to pandas [track]

1. Basics
2. Reading and Exploring Data
3. Accessing DataFrame Values
4. Aggregate Functions

book
Accessing using .loc[] [2/3]

Not only you can get certain rows, but you can also get specific columns. To set column/columns you want to receive, pass it as the second parameter between square brackets of .loc[].

If you want to indicate only one column, just place its name. If you want to indicate several columns, you need to pass list of their names.

Note that the first parameter must be set, even if you don't want to indicate specific rows (use : instead).

123456789
# Importing library import pandas as pd # Reading csv file df = pd.read_csv('https://codefinity-content-media.s3.eu-west-1.amazonaws.com/67798cef-5e7c-4fbc-af7d-ae96b4443c0a/audi.csv') # Get the first five rows (indexes 0-4) and column 'fuelType' print(df.loc[:4, 'fuelType']) # Get the 9th - 11th rows (indexes 8, 9, 10) and columns 'model', 'year', and 'price' print(df.loc[8:10, ['model', 'year', 'price']])
copy

Was alles duidelijk?

Hoe kunnen we het verbeteren?

Bedankt voor je feedback!

Sectie 3. Hoofdstuk 7
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