Learn Python Data Basics
Python Data Basics
Python is a vast tool that we can use to interact with our computer much like a mouse. When working with a mouse we need to learn the physical position of different options and features to use the program well. Python is much the same, at DataSimple we believe we need focus on learning how to use Python not like computer scientist but like Data Scientist.
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Learning Python is such a raw way as just studying functions and loops, the clicking part of using a mouse, can make it difficult to transition into working and manipulating data, especially for those comfortable with spreadsheets already. Do you need to understand how Excel is built to use it?
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In DataSimple education programs we learn from with a data perspective from the beginning. Working with data from class one. This allows students a faster and more comfortable learning experience. Start with the easier-to-use higher-level tools first and later on if you want you can learn how to build them yourself.
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All programs are supported with quizzes, guided follow-along projects, and presentations covering each concept to you learn and gain practical experience with Python.
DataSimple
Data Python Basics
Learning Path
Data Types
Pandas Intro
In our first Python basics lesson we cover the basics needed to know to work with Python code. Data types become incredibly important at the level of interaction with a computer.
Logics Statements
Filter Data in Pandas
In Python Logic statements allow you to control the flow or how your code will develop and what will run in certain situations. In Data Science where logic statements are used the most to filter and select which subset of data we would like to work with.
Loops
Automation in Pandas
In Python loops allow you to repeat simple or complex tasks. In Data Science this will take on many forms, iterating through each row in a DataFrame or setting up experiments that test many variations of hyperparameters or architecture.
on a DataFrame
In Python Functions allows us to save how to do tasks and use them later. On the simple side, it's like saving the click of a mouse while using excel, on the more complex side they hold the math and how to use it found in the layers of a neural network. Let's start with the simpler side and use Python User Defined Functions to work with data like we were using Excel.