https://github.com/nits2612/data-science-projects

Portfolio of data science projects completed by me during PGP AI/ML, self learning, and hobby purposes.
https://github.com/nits2612/data-science-projects

data data-science dataanalysis deep deep-learning keras machine-learning matplotlib numpy opencv pandas python scikit-learn seaborn surprise-python tensorflow transfer-learning

Last synced: 7 days ago
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Portfolio of data science projects completed by me during PGP AI/ML, self learning, and hobby purposes.

• Host: GitHub
• URL: https://github.com/nits2612/data-science-projects
• Owner: nits2612
• Created: 2024-09-11T14:10:07.000Z (22 days ago)
• Default Branch: main
• Last Pushed: 2024-09-12T07:02:43.000Z (21 days ago)
• Last Synced: 2024-09-26T04:03:22.446Z (7 days ago)
• Topics: data, data-science, dataanalysis, deep, deep-learning, keras, machine-learning, matplotlib, numpy, opencv, pandas, python, scikit-learn, seaborn, surprise-python, tensorflow, transfer-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 9.94 MB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

# Sales Analysis

## Project statement:

AAL, established in 2000, is a well-known brand in Australia, particularly 

recognized for its clothing business. It has opened branches in various states, 

metropolises, and tier-1 and tier-2 cities across the country.

The brand caters to all age groups, from kids to the elderly.

Currently experiencing a surge in business, AAL is actively pursuing expansion 

opportunities. To facilitate informed investment decisions, the CEO has assigned 

the responsibility to the head of AAL’s sales and marketing (S&M) department. 

The specific tasks include:

1) Identify the states that are generating the highest revenues.

2) Develop sales programs for states with lower revenues. The head of sales 

and marketing has requested your assistance with this task.

## Task at Hand:

My job is to analyze the sales data of the company for the fourth quarter in Australia, 

examining it on a state-by-state basis and providing insights to assist the company in 

making data-driven decisions for the upcoming year.

## Approach to the problem:

I performed the following steps as part of data analysis to come up with conclusions to help company make an informed decision:

1) Data Wrangling: Utilized the EDA techniques to deal with the null values, normalized some fields in data using min max scaling and used pandas function to present an analysis about the sales pattern in a day based on different time.

2) Data Analysis: Performed descriptive analysis on the data for some columns to draw inference on mean, median, std deviation and identified group with highest sale. Generated weekly, montly and quarterly sales report using pandas.

3) Data Visualization: Used matplotlib and seaborn packages to visualize the data to understand the trends of sales and gave my recommendation based on the findings.

## Tech Stack

Python, Pandas, Numpy, Matplotlib, Seaborn, Jupyter Notebook.