Notice: This page requires JavaScript to function properly.
Please enable JavaScript in your browser settings or update your browser.Accessing Rows and Columns | Accessing DataFrame Values
Introduction to pandas [track]
course content

Conteúdo do Curso

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 Rows and Columns

If you need to get particular rows and columns, you can easily combine both methods learned previously, in any order. That is, you can get certain row, and then choose the columns you need, or vice versa. Look at the example below, and compare both outputs.


              
12345678

            
# 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 'mileage' column value of the first row
print(df[0:1]['mileage'])
print(df['mileage'][0])
copy

Remember that you need to use slicing even for getting a single row.

Tudo estava claro?

Como podemos melhorá-lo?

Obrigado pelo seu feedback!

Seção 3. Capítulo 5
some-alt