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Introduction to pandas [track]
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Introduction to pandas [track]

Introduction to pandas [track]

1. Basics
What is pandas?SeriesIndexes and ValuesChallengeDataFramesIndexes and ColumnsChallenge
2. Reading and Exploring Data
Reading CSV FilesReading XLS/XLSX FilesExploring Data [1/3]ChallengeExploring Data [2/3]Exploring Data [3/3]Challenge
3. Accessing DataFrame Values
Accessing Specific ColumnsChallengeAccessing Specific RowsChallengeAccessing Rows and ColumnsAccessing using .loc[] [1/3]Accessing using .loc[] [2/3]Accessing using .loc[] [3/3]
4. Aggregate Functions
Number of ObservationsUnique ObservationsCounting ValuesChallengeSum and ProductMean and MedianChallengeMinimum and Maximum

bookAccessing 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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Seção 3. Capítulo 7
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