DownloadOpen data often comes with little or no metadata. You will profile a large collection of open data sets and derive metadata that can be used for data discovery, querying, and identification of data quality problems. For each column, identify and summarize the semantic types present in the column. These can be generic types (e.g., city, state) or collection-specific types (NYU school names, NYC agency). For each semantic type T identified, enumerate all the values encountered for T in all columns present in the collection.
Features
- Number of non-empty cells
- Number of empty cells (i.e., cell with no data)
- Top-5 most frequent value(s)
- Data types (a column may contain values belonging to multiple types)
- Semantic Profiling
- Data Analysis
Project Samples
Categories
Data ProfilingLicense
MIT LicenseFollow NYCOpenData-Profiling-Analysis
You Might Also Like
Boost application security and continuity with SKUDONET ADC, our Open Source Load Balancer, that maximizes IT infrastructure flexibility. Additionally, save up to $470 K per incident with AI and SKUDONET solutions, further enhancing your organization’s risk management and cost-efficiency strategies.
Rate This Project
Login To Rate This Project
User Reviews
Be the first to post a review of NYCOpenData-Profiling-Analysis!