• Obtain data from websites, APIs, databases, and spreadsheets
• Perform scrub operations on text, CSV, HTML/XML, and JSON
• Explore data, compute descriptive statistics, and create visualizations
• Manage your data science workflow
• Create reusable command-line tools from one-liners and existing Python or R code
• Parallelize and distribute data-intensive pipelines
• Model data with dimensionality reduction, clustering, regression, and classification algorithms

This lightweight tool helps you get a sense of your application's schema, as well as any outliers to that schema. Particularly useful when you inherit a codebase with data dump and want to quickly learn how the data's structured. Also useful for finding rare keys.

$ mongo test --eval "var collection = 'users'" variety.js

+------------------------------------------------------------------+
| key                | types              | occurrences | percents |
| ------------------ | ------------       | ----------- | -------- |
| _id                | ObjectId           |           5 |    100.0 |
| name               | String             |           5 |    100.0 |
| bio                | String             |           3 |     60.0 |
| birthday           | Date               |           2 |     40.0 |
| pets               | Array(1),String(1) |           2 |     40.0 |
| someBinData        | BinData-old        |           1 |     20.0 |
| someWeirdLegacyKey | String             |           1 |     20.0 |
+------------------------------------------------------------------+