Show HN: Vizly – Query and visualize your data in seconds (vizly.fyi)
My friend Sami and I built Vizly, a project that lets you query and visualize your data in seconds
It works for any data so you can upload and starting querying/visualizing your dataset right away
5 comments
[ 4.9 ms ] story [ 23.0 ms ] threadOne, you need more content to explain the concept to the user. A table and an input box is not sufficient. Sure, I could mess around and figure it out, but for all I know I’d be missing out on all the cool features.
Two, provide some examples, and some alternative datasets (e.g. tabular, nested, relational).
I’m not sure how to use it, so I gave the prompt:
> plot speed vs defence
on the Pokémon dataset. It provided me with an empty scatter plot.
Three, you need an FAQ. Some example questions: Can I run this locally? Can I integrate this with private data sources such as Prometheus? How does the project work? Who worked on it? Are there terms and conditions? What kind of data sources does it currently work on? What are the ongoing plans? Etc.
[1] https://datachat.ai/ [2] Iris Agent - https://youtu.be/3VZZbKoXDVM
```sql SELECT DISTINCT type_1 FROM roles AS r1 WHERE NOT EXISTS( SELECT * FROM roles AS r2 WHERE r2.type_1 = r1.type_1 AND r2.legendary = 'True' ); ```
This queries all "`TYPE_1`s that all characters in this type are not legendary", and it is near impossible for a newcomer who had never learnt about SQL before to figure out the query, yet typing the sentence in quotes in `Vizly` gives exactly what is needed. Sure it took 1 minute to execute (which is probably why some thought it is down), but formulating the above SQL statement took much longer, and I am not sure that statement even works (I haven't touched SQL for quite some time).
At least for investigative workflows (where it's pretty common for data scientist to often have to rebuild custom dashboards), it'd be really cool to have the system handle prompts such as "give me a regex on email address that seem to incur the most amount of fraud" -- or unveil some insight on the data that is usually just a mix of operator/data scientist domain specific knowledge + pattern matching.