Introduction to Python for Data Analysis

Introduction to Python for Data Analysis

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1. Introduction to Python 1/2

Here, we will face challenges related to data types in python. In this section, we will learn the Python syntax necessary for each person who wants to work with this language. After the section, we will undoubtedly be able to cope with simple Python tasks.

First Step in Programming

Deal with Variables

Practice Math Skills

Deal with Percents

How to Attract One User?

Boolean Numbers

Work with Strings

Get Familiar with Lists

How to Append New Element?

2. Introduction to Python 2/2

This section will teach you simple Python functions. We will be able to work with if/else statements and loops. Such skills are necessary for everyone who wants to start programming and doing fascinating Python tasks.

3. Explore Dataset

This section is the most complicated than the previous one, but it is gripping. Here, we will manage the most commonly used pandas function to help we do essential operations with data. Also, we will learn the basics of the NumPy library.

Operations with the File

How to Explore the Data

Max, min, mean, median

Dive Deeper into Grouping Data

Introduction to NumPy

Deal with Several Conditions

Visualization: First Steps

Dive Deeper into Visualization

4. Becoming an Analyst

This section allows you to become a real analyst. Let's go!

Examine Dataset

Costly Customers

Organic Traffic

How Much Do We Earn

Is Our Project Profitable? ROI 1/2

Conteúdo do Curso

Introduction to Python for Data Analysis

Introduction to Python for Data Analysis

1. Introduction to Python 1/2

First Step in Programming Deal with Variables Practice Math Skills Challenge Deal with Percents How to Attract One User?Challenge Learn Numbers Boolean Numbers Challenge Work with Strings Get Familiar with Lists How to Append New Element?

2. Introduction to Python 2/2

If/Else Challenge If/Elif/Else Challenge For Loop While Loop Challenge

3. Explore Dataset

Data Study Operations with the File How to Explore the Data Sorting Data Max, min, mean, median Challenge Group Data Dive Deeper into Grouping Data Group Data 2.0 Introduction to NumPy Pivot Tables Recall Loops .loc Function Deal with Several Conditions Challenge Visualization: First Steps Dive Deeper into Visualization

4. Becoming an Analyst

Data Study Examine Dataset Challenge СAC 1/2 CAC 2/2 Costly Customers Organic Traffic How Much Do We Earn Is Our Project Profitable? ROI 1/2 ROI 2/2 Visualize ROI

Get Familiar with Lists

Another crucial data type is called list! It is used to store variables:

list = [1, 3, 6, 'a', True]

You just need to put variables inside square brackets. You don't have restrictions, so in one list, you can store numbers, strings, and boolean data; that's all!

It is necessary to know how to get a specific element from the list to work with lists.

The list's first item has the index 0, the next one 1, and so on.

If we start from the end, the last item has the index -1, and the second-to-last has the index -2, and so on.


              12345678910111213
            
list_1 = ['P', 'y', 't', 'h', 'o', 'n']

print("The first item is", list_1[0])
print("The third item is", list_1[2])
print("The fifth item is", list_1[4])
print("The last item is", list_1[5])

# And using negative indexation

print("The first item is", list_1[-6])
print("The third item is", list_1[-4])
print("The fifth item is", list_1[-2])
print("The last item is", list_1[-1])

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Seção 1. Capítulo 12

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