Indian sales data analysis, data analysis using seaborn and pyplot in python, Data visualization in python

What you will learn

How to analyze large dataset in python

How to visually see important components of data

In-depth knowledge of patterns of seaborn in python

Graphs handling through matplotlib

Description

Hi there, welcome to this course of Sales data analysis in python. Its for you if you want to get started or in field of data analysis. We will go advanced in data analysis through graphs in python.

We hope you are already familiar with the language ‘English’ just. Yeah! Even if you are beginner you can start this course and will hopefully enjoy it!

I this course we will be extracting meaningful information from a large dataset with 11k data points. Its a large data with many columns like customer id, name, number of orders, amount spent etc.

We will be using an Indian sales dataset. The dataset contain almost 10k rows of data with many columns like customer name, costumer id, product customer bought, amount he spent, number of orders he made and a few more.


Get Instant Notification of New Courses on our Telegram channel.


What we will do in this course:

  • Clean our data
  • Analyze it
  • Extract some patterns in data
  • Extract product giving good result economically
  • Extract the type of audience interested in shopping

And much more! gear up!

It is advanced that you should practice the codes as well with us. This will create a strong base of yours in the field of data science and analytics.

Good luck for your journey!

English
language

Content

Introduction

What you need to start
What in this course
Dataset we will be working with
Downloading dataset

Working with our data

Importing data in python
Importing dataset in python environment
Dealing with missing data
Dealing with missing data video
Plotting graphs, Extracting data
Plotting graphs in python, video
Plotting graphs in python again, video
Comparison Graphs: CG
CG: Advanced Plotting, classifying sales on bases of Occupation and Gender both
Video for upper details
CG: Classifying sales on the bases of Category of product and Gender
CG: Analyzing sales with Age Group and Occupation
Video for upper details

What next

you should..
Congratulations