Главная
Study mode:
on
1
- Tutorial Starts
2
- Content Introduction
3
- Phase 1: Starts
4
- Retail Data Management
5
- Gnerating User Profile Master Data
6
- Faker Tutorial
7
- User Profile - Personal Info
8
- User Profile - Job Info
9
- User Profile - Credit card Info
10
- User Profile - Income group Info
11
- User Profile - Marital Status
12
- User Profile - Vehicle Info
13
- User Profile - Geo based Address
14
- Accessing Walmart Locations
15
- Show Walmart and user address in Map
16
- Combining everything so far
17
- Master Function to generate data
18
- Saving master profile data
19
- Phase 2: Product List Creation
20
- Instacart Product Data
21
- Phase 3: Master Store List Creation
22
- Phase 4: Purchase History Creation
23
- Important concept for Geo Proximity
24
- Finalizing Data Creation
25
- Phase 5: Data Viz and Retail analytics
26
- Store and user proximity map
27
- Phase 6: Retail/Consumer Analytics
28
- Retail data analytics
29
- Future Extensions
30
- Recap
Description:
Dive into a comprehensive 2-hour tutorial on Retail Data Analytics using real-world Walmart store data. Learn to develop geo-traceable consumer profiles, including family details, vehicle information, and credit card data for over 4,500 Walmart locations. Create purchase histories spanning three years for each customer and construct a retail data analytics dashboard featuring consumer and store maps. Master complex applications of Python libraries such as Pandas, Matplotlib, Faker, NumPy, and datetime, with a focus on advanced Plotly mapping techniques for multi-layered visualizations. Explore potential project extensions using Streamlit, Dask, and H2O Wave, and discover how to build full-stack applications with Python, Java Quarkus, React, and Next.js using the generated dataset.

Getting Started with Retail Data Analytics

Prodramp
Add to list
0:00 / 0:00