Sales Data Analysis With Python | Solving Real World Data Science Problems | Python Case Study | EDS

In this video we use Python Pandas & Python Matplotlib to analyze and answer business questions about 3 years worth of sales data. The data contains thousands of store purchases broken down by month, product type, cost, purchase address, etc.

Setup!

Detailed video description! (timeline can be found in comments)

We have answered these 5 questions through our data analysis mainly using pandas and matplotlib library.

Q1. What is the overall sales trend?
Q2. Which are the Top 10 products by sales?
Q3. Which are the Most Selling Products?
Q4. Which is the most preferred Ship Mode?
Q5. Which are the Most Profitable Category and Sub-Category?

To answer these questions we walk through many different pandas & matplotlib and seaborn library methods. They include:
- Adding columns
- Parsing cells as strings to make new columns (.str)
- Using the .apply() method
- Using groupby to perform aggregate analysis
- Plotting bar charts and lines graphs to visualize our results

If you enjoy this video, make sure to leave it a like and subscribe to not miss any future similar tutorials :).

Video Timeline!
0:00 - Intro
0:20 - Downloading the Data
1:30 - Opening Jupyter Notebok

2:05 - Objective
3:30 - Importing Libraries
4:23 - Importing Dataset

5:03 - Data Audit

11:10 - Q1. What is the overall sales trend?
16:35 - Q2. Which are the Top 10 products by sales?
20:22 - Q3. Which are the Most Selling Products?
23:40 - Q4. Which is the most preferred Ship Mode?
25:30 - Q5. Which are the Most Profitable Category and Sub-Category?

Thanks for watching! If you enjoyed, please consider subscribing :).

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[vialyticsgrowthacademy]

Video Timeline!
@ - Intro
0:20 - Downloading the Data
1:30 - Opening Jupyter Notebok

2:05 - Objective
3:30 - Importing Libraries
4:23 - Importing Dataset

5:03 - Data Audit

11:10 - Q1. What is the overall sales trend?  
16:35 - Q2. Which are the Top 10 products by sales?
20:22 - Q3. Which are the Most Selling Products?
23:40 - Q4. Which is the most preferred Ship Mode?
25:30 - Q5. Which are the Most Profitable Category and Sub-Category?

Thanks for watching! If you enjoyed, please consider subscribing :).

[mrinalinimadhusudan]

you should be really making more such videos, with different difficulty levels. This is great

[photoshopsuraj]

This is the gold for beginners in python and data science! Great video

[lakshminarasimhanv]

Great! Your video is best for new persons like me. God bless you .

[NerdyBird]

This case study is very helpful for beginners, thank you.

[bilalhassankhan]

Awesome simple and easy to understand ... keep uploading

[mishudhar]

very helpful for beginers, thanks a TON bro, wish to see much more ...

[vialyticsgrowthacademy]

Thanks for watching! If you enjoyed, please consider subscribing :).

[minalgupta]

bhaut ache se explain kiye more videos upload pls

[villajinbernadette]

I think on the "most selling products", you can base it on the number of transactions, not on the quantity. Say, Product A was bought in bulk (e.g., 1000) on January, but the rest of the year, people don't buy it usually. Product B was being bought by customers throughout the year but its count is only 900+, so on the report, Product A will be the most selling product when in fact Product B is the product being patronized by customers.

But I like this tutorial, very informative and straightforward.

[repulotaska]

This vid saved my university project! Thanks sir<3

[avnibhardwaj]

Great tutorial! Hope to see more projects coming! :D

[AIdevel]

Absolutely extraordinary I really benefited from this tutorial

[narendra]

very useful, thanks for your efforts. Appreciate

[rajmansharma]

Great video, very beautifully explained each and every line.
Thank you for making this video. Very helpful 🙏🙏🙏

[hendrag]

Thank you very much. This great video has helped me to understand more about Python. God bless.

[Pyazdan]

Great tutorial! Hope to see more projects coming!

[saswatleo]

Nice Video...

Also Make Some Video on Feature Engineering, Feature Selection, Hyperparameter Tuning


And Most important Missing Value Handing Sir Plz

[shubhamsahoo]

Many thanks sir for your amazing tutorial, and special thanks for your coding structure, really its motivated.

[kaifsajid]

Very helpful....can u please make more video's in real worlds probs