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Summary Python for data analysts

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Basics for Python to become a data analyst

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  • February 3, 2022
  • 47
  • 2021/2022
  • Summary
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Python for Data Analysts
Overview
What is Python and What does it help Data Analysts do?
Preparation
Installing Python through conda
Download VSCode
Jupyter Notebooks
Basic Python
Python Files
Jupyter Notebooks
Objects
Variables
Commenting in Python
Markdown Cells
Data Types/Structures
Operations
Functions
Libraries and Installing new libraries
Importing a Library
Methods
Control Statements
NumPy
NumPy Calculations
Special NumPy Arrays
Pandas
Install Pandas
Import Pandas
Series
DataFrames
Columns
Rows
List out Columns
Basic Descriptive Statistics



Python for Data Analysts 1

, See Unique Values in a Column
Filtering DataFrames
DateTimes
Splitting Columns
Renaming Columns
Dealing with Null Values - Fill Na
Applying a Function to Every Row
GroupBy, Aggregation, and Sorting Values
Joins and Unions
Pivot and Melt
Summary



Overview
Welcome to my course: Python for Data Analysts. The purpose of this course is to
give you the skills to get started using Python like a Data Analyst. It doesn't teach you
how to be a developer and I skip over or lightly cover any concepts that I think are less
important to getting started. The idea is to just teach you what you need to get started
as a Data Analyst and get you motivated enough to start learning Python in depth by
yourself as you need to.
Coding is a difficult skill to pick up and doesn't come naturally to a lot of people including
myself. If you are just learning how to code then I highly recommend you set up your
Python environment the same way I did. Development environments can be
complicated even for experienced individuals.

Instructions are highlighted
I've released a YouTube video to accompany this document and highly recommend
that you follow along with that as well. You can find it on my YouTube channel here:

Also make sure you download the datasets necessary for this tutorial here.

One more thing. If this is your first time coding or you're just starting your journey, don't
worry! You will probably need to go through this at least twice in order to start
understanding


What is Python and What does it help Data Analysts
do?


Python for Data Analysts 2

, Python is a high-level, object-oriented programming language.

High-level: What you program in Python is abstracted away from the actual
operations a computer performs to get there. This means that programming is
easier to understand

Object-Oriented: Your code is designed around the idea of Objects. We'll be going
over what Objects are shortly

It is one of the most popular languages used by Data Analysts and Scientists because it
is open-source, very flexible, easy to learn, and VERY well-supported. That last point is
very important because many languages have all the prior features, but because Python
has gained critical mass in the Analytics industry, almost everyone who designs an
application to be used by Data Analysts or Data Scientists will design it with Python
compatibility. Aspects of Analytics that are well supported by Python and their
respective supported libraries include:

Connecting to Data

SQL Alchemy: Connect to SQL Databases

PySpark: Connect to Big Data

Exploring Data

SciPy: Run statistical analyses on data

Pandas: Explore data stored in tables

Modeling Data

skLearn: Machine Learning

Tensorflow: Artificial Intelligence

Visualizing and Presenting Data

Dash/Plotly/Streamlit: Make full web-applications

Let's get started:



Preparation
You'll need three things to get started with this course:



Python for Data Analysts 3

, Python: This will get the Python programming language + interpreter on your
computer

Text Editor: This will help you edit and deploy your code. We'll be using VSCode

Jupyter Notebook: This is a program used by Data Analysts to easily explore data
using Python

Installing Python through conda
We'll be installing Python using a program called Conda. Conda was designed for Data
Analysts and makes it easy to manage all the extra programs you'll need to organize as
you develop your skills.

Conda can be downloaded through a visual interface called Anaconda or a Command-
Line interface called MiniConda

I highly recommend using MiniConda instead of Anaconda because it’s way lighter
on your system. I've had major issues getting Anaconda to work well on my
computer and recommend against it unless you know exactly what you need it for

Download the appropriate version of MiniConda from the official website

If you have a Windows computer and want to know whether you have 32-Bit or 64-Bit
version of the operating system, check here: https://support.microsoft.com/en-
us/windows/32-bit-and-64-bit-windows-frequently-asked-questions-c6ca9541-8dce-
4d48-0415-94a3faa2e13d

Download VSCode
I prefer to use a text editor instead of an IDE because they're just much simpler and
have all the functionality a beginning Data Analyst needs

VSCode is a very well supported editor made by Microsoft

Download the appropriate version of VSCode from the official website

Jupyter Notebooks
Install the Python and Jupyter extensions

I recommend using Visual Studio Code that way if you want to make .py files it's
easy



Python for Data Analysts 4

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