Udemy

Platform

English

Language

Data Science

Category

Crack Pandas and NumPy: Python Data Science Made Easy

Take this essential course on programming in the Internet’s most popular programming language! Beginner friendly.

3.60 (16 reviews)

Students

26.5 hours

Content

Apr 2018

Last Update
Regular Price


What you will learn

Code in the Python 3.5 programming language

Create and manipulate dataframes with pandas

Create NumPy arrays


Description

This course was funded by a #1 Kickstarter project

Learn a skill that is not only highly requested by employers but also has a greater demand than supply.

Python is the single best language to start learning to code in with an online course. 

Python is 100% readily available online. Simply install Python on your computer, open a text editor & get coding.

This is the most practical course on Python you’ll find. You will make projects while you learn. Every piece of theory we explain with an example.

Learn on free, open source software that is changing the world

Whether you have no Python programming experience or are an experienced developer who wants to learn specializations of pandas & NumPy, you should take this course.

You’ll get lifetime access to this course, which includes 70 lectures & hours of video.

“Why should I learn pandas?”

Pandas is the most important tool in data science. According to Datacrunch, millions of people around the world use Pandas. The world wouldn't be the same without it. 

Pandas is used for a variety of tasks like data loading, renaming, grouping, statistics, mapping, aggregating & more.

“Why should I learn NumPy?”

NumPy is going to be your new best friend. Its optimizations make the already amazing Python language even more useful.

What are you waiting for? Learn Python to advance your career. You can learn this new skill right now.

  • Make games with Python

  • Read & write data to & from CSV

  • Recognize analytical approaches to data, including: analyzing data, locating, making statistical descriptions & plots of data

  • Resize & manipulate arrays

  • Perform calculations, functions & statistics with NumPy

  • & more!

Included in this course is material for beginners to get comfortable with the interfaces. Please note that we reuse this content in similar courses because it is introductory material. You can find some material in this course in the following related courses:

  • Data Science & Analysis: Make DataFrames in Pandas & Python

  • Learn Python Data Analysis with Pandas and Make a Unity Game

  • Create Arrays in Python NumPy - Learn Scientific Computing

Testimonials

"An easily understood course, with detailed instruction & good explanation of the concepts involved in making this clone game. 

A very well done tutorial, especially for someone like me is just now learning how to write code."

"I really like the approach the presenter takes – not just the technical details, but also the very human, personal development information & recommendations he provides."

"The instructor is very good at teaching. He teaches at a great pace & covers anything a beginner would need to understand (every little detail). 

I am already learning a lot & I just started yesterday."

Enroll right now to join the community



Screenshots

Crack Pandas and NumPy: Python Data Science Made Easy
Crack Pandas and NumPy: Python Data Science Made Easy
Crack Pandas and NumPy: Python Data Science Made Easy
Crack Pandas and NumPy: Python Data Science Made Easy

Content

Introduction

Introduction to Python

Python Programming Basics

Variables

Functions

If Statements

Python Lists

Introduction to Lists

Python Loops

Introduction to For Loops (with Examples)

Getting Familiar with While Loops

Breaking and Continuing In Loops

Making Shapes with Loops

Nested Loops & Printing Tic Tac Toe Field

Python Sets and Dictionaries

Understanding Sets and Dictionaries

Inventory List Example

Python Input and Output

Introduction and Implementation

Inputting Files and Integrating Output

Tic Tac Toe Game Example

Tic Tac Toe Game Example Continued

Writing Participant Data to File Example

Reading Data from File Example

Statistics with Participant Data from File

Python Classes

Introduction to Classes

Inheritance and Classes

Pets Example

Dogs Example

Cats Example

Adding Humans to the Pets Example!

Python Importing

Importing and the Random Library

Importing and Using Lists with Random

Using the Time Library

Math Library

Creating a User-Guessing Game with Random

Making a Computer Guess a Random Number

Making a Python Blackjack Game

Creating and Shuffling a Card Deck

Creating a Player Class

Expanding the Player Class

Implementing a Bet and Win

Implementing Player Moves

Running the Game (Final)

Python Error Handling

Getting Started with Error Handling

Introduction to Pandas

Installing Pandas

Setting up Pandas

Pandas Data Structures

Creating a DataFrame

Sorting and Series

Expanding a DataFrame

Manipulating DataFrames

Getting Values and Handling NaN Values

Dropping Rows and Columns

Reading and Writing Data

Reading from CSV

Writing to CSV

Analytical Approaches to Data

Starting with an Analysis

Locating Data by Labels

Statistical Description of Data

Histogram Plots in Pandas

Starting to Analyze All Our Data

Continuing to Analyze All Our Data

Introduction to NumPy

Introduction to NumPy

NumPy Arrays

Creating and Reshaping NumPy Arrays

Creating Standard NumPy Arrays

Creating Standard 2D Arrays

Attributes on NumPy Arrays

Resizing Arrays

Manipulating NumPy Arrays

Writing an Array to File and Formatting Strings

Random Numbers

Sorting in NumPy

Calculations and Math

Calculations within NumPy Arrays

Math Functions with NumPy

Integrating with NumPy

Statistics with NumPy

Polynomials Part 1

Polynomials Part 2

Free Stuff for Students

Please rate this course

Bonus Lecture: Free $200 Webinar


Reviews

Z
Zhang22 October 2018

I study a lot from teacher. In depth explain and step by step organization for material is pretty good for students. English accent is good for me to understand as a non english people.


1526546

Udemy ID

1/26/2018

Course created date

5/5/2020

Course Indexed date
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