Sales Analysis With Python & Pandas

Pandas for Sales Analysis

4.00 (1 reviews)
Udemy
platform
English
language
Data Science
category
instructor
5
students
2.5 hours
content
Mar 2021
last update
$84.99
regular price

What you will learn

You will learn how to install Python

You will learn how to use Pandas

You will learn how to use Jupyter

You will learn how to import data

You will learn how to manipulate date

You will learn how to group data

You will learn how to analyze your sales data

You will learn how to apply statistical functions to your data

You will learn how to plot your data

You will learn how to create Line Chart, Pie Chart, Bar Chart

You will learn how to save and export your data

Description

This courses will teach you how to analyze sales data using Python programming language & Pandas library. Python was described as the language that is capable of doing anything and everything. The good news about this course is that you don't need advanced knowledge in Python nor in any programming language. All you need is just simple knowledge of how to create simple Python functions/scripts.

Being able to analyze sales data will surly help you increase your sales and fix what went wrong and avoid it in the future. Python can do all of this super efficiently with it's Pandas and MatPlotLib Libraries.

Python provides super powerful libraries such as Pandas that you can use to perform sales analysis.

Therefore, in this course you will learn how to use the most important features that these Python libraries provide to analyze your sales data. These two Python libraries -Pandas & Matplotlib- are super powerful modules that are capable of extracting data, cleaning data, manipulating data, analyzing data and of course plotting data.

By the end of this course you will have the skills required to analyze your sales data using Python programming language.


Why should you take this course?

There are many reasons why this course is extremely important.

  • First and most prominently is that you will learn one of the most amazing Python capabilities and libraries, Pandas, As you know, Python is pretty much able to do anything!

  • Secondly you will improve your Python skills by learning two new libraries.

  • Third this course is a starting point towards a career in data science/analysis, and this course will give you the basics you need to start moving forward confidently.


What you will learn in this course?

1. How to install Python.

2. How to install Pandas and Matplotlib libraries.

3. How to use Jupiter notebook.

4. How to import data from excel.

5. How to get a specific part of data.

6. How to use different techniques in Pandas.

6. How to plot data.

7. How to apply statistical functions to data (e.g. Mean,Median, Standard deviation,etc).

8. How to analyze data draw conclusion.

9. Much much more...


Note: The code/project that will be created throughout this course will be provided so that you can download it and use it for commercial and non-commercial purposes.

Screenshots

Sales Analysis With Python & Pandas - Screenshot_01Sales Analysis With Python & Pandas - Screenshot_02Sales Analysis With Python & Pandas - Screenshot_03Sales Analysis With Python & Pandas - Screenshot_04

Content

Introduction

Introduction
Install Python Mac
Install Python Windows
Install Jupyter
How to use Jupyter
Project folder
Install pandas
Pandas

The basics

Importing data
Manipulate data
Subdata
Sales by date
Data info

Sales analysis & plotting

Goals
Pulling out data
Matplotlib introduction
Plot cake
Formatting date
Plot details
Analyzing plots
Analyzing plots two
Analyzing plots three
All in one
Sales in thousand

Statistics

Statistical functions
Statistical functions on one item
NaN data

More features

Group by
Group by date
Pie chart
Bar chart
Save file

Project Files

Sales data
Python project

Charts

Price

Sales Analysis With Python & Pandas - Price chart

Rating

Sales Analysis With Python & Pandas - Ratings chart

Enrollment distribution

Sales Analysis With Python & Pandas - Distribution chart

Related Topics

3810302
udemy ID
1/29/2021
course created date
2/28/2021
course indexed date
Bot
course submited by