Datascience Foodie
A project which implements the Data Science pipeline - Extracting raw data, Data Cleaning, Feature Extraction, Entity Matching, Data Matching, Data Merging and OLAP style exploration. The two entities chosen are Yelp and Zomato. Restaurant data from the same localities will be extracted from both sites and similar restaurants will be merged into one big table. OLAP style exploration will be done on that table to find out the insights from the collected data (Eg, Which is the most highly rated restaurant in California)
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Chdb | 1,686 | 16 days ago | 42 | December 10, 2023 | 32 | apache-2.0 | C++ | |||
| chDB is an embedded OLAP SQL Engine 🚀 powered by ClickHouse | ||||||||||
| Prosto | 53 | 2 years ago | 5 | November 21, 2021 | 5 | mit | Python | |||
| Prosto is a data processing toolkit radically changing how data is processed by heavily relying on functions and operations with functions - an alternative to map-reduce and join-groupby | ||||||||||
| Ides | 32 | 10 months ago | 6 | apache-2.0 | Scala | |||||
| 智能数据探索服务(Intelligent Data Exploration Service)，一站式Data + AI数据解决方案！ | ||||||||||
| Cl Duckdb | 23 | 6 months ago | 2 | mit | Common Lisp | |||||
| Common Lisp CFFI wrapper around the DuckDB C API | ||||||||||
| Road To Data Science In 50 Days | 18 | 4 years ago | Jupyter Notebook | |||||||
| Chdb Server | 17 | 5 months ago | 3 | apache-2.0 | Python | |||||
| API Server for chDB, an in-process SQL OLAP Engine powered by ClickHouse | ||||||||||
| Datascience Foodie | 6 | 6 years ago | Jupyter Notebook | |||||||
| A project which implements the Data Science pipeline - Extracting raw data, Data Cleaning, Feature Extraction, Entity Matching, Data Matching, Data Merging and OLAP style exploration. The two entities chosen are Yelp and Zomato. Restaurant data from the same localities will be extracted from both sites and similar restaurants will be merged into one big table. OLAP style exploration will be done on that table to find out the insights from the collected data (Eg, Which is the most highly rated restaurant in California) | ||||||||||
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Python
Jupyter Notebook
Machine Learning
Data Science
Numpy
Pandas
Scrapy
Scikit Learn
Olap