Introduction to pandas [track]

Introduction to pandas [track]

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1. Basics

In the first section of the course you will learn two basic objects provided by pandas - Series and DataFrame. You will learn how to create them and change their indexes or column names.

What is pandas?

Indexes and Values

Indexes and Columns

2. Reading and Exploring Data

Often the necessary data are stored in some files. You need to be able to load these data and gain the first insights.

Reading CSV Files

Reading XLS/XLSX Files

Exploring Data [1/3]

Exploring Data [2/3]

Exploring Data [3/3]

3. Accessing DataFrame Values

Once you have loaded the data as Series/DataFrame, you need to be able to get certain data based on needs. You will learn how to access rows, columns, and filter observations by conditions.

Accessing Specific Columns

Accessing Specific Rows

Accessing Rows and Columns

Accessing using .loc[] [1/3]

Accessing using .loc[] [2/3]

Accessing using .loc[] [3/3]

4. Aggregate Functions

In the last section of the course, you will get to know how to calculate some aggregate statistics of your data, such as mean, median, sum, product. Also you will learn how to count values and get only unique observations.

Number of Observations

Unique Observations

Counting Values

Sum and Product

Mean and Median

Minimum and Maximum

Conteúdo do Curso

Introduction to pandas [track]

Introduction to pandas [track]

Accessing 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.


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

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

Tudo estava claro?

Seção 3. Capítulo 5

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