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Ask HN: What do you use for basic data analysis, visualization, and graphing?

47 points by transitivebs ↗ HN
I often find myself with some JSON data that I want to visualize. I usually end up converting to CSV, uploading to a Google Sheet, and manually creating charts. BUT this is really time consuming and I find Google Sheets charts pretty difficult and painful for quickly exploring different views of the original data.

So what do you use for this type of thing?

I know python has lots of good utils for data wrangling & graphing, but I'd prefer a solution which is: no-code, gives me a bunch of common graph views I can quickly choose between, and that "just works" 99% of the time.

Thanks!

94 comments

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ghiculescu
If you can connect it to the data source, Metabase is exactly what you want. https://www.metabase.com/
djbusby
I love metabase. I'd also suggest to take a look at Apache Superset.
epgui
Personally I find Metabase lacks flexibility, but then again I think that’s just the predicament you’re stuck with in no-code/low-code.
ReDeiPirati
What do you mean with lacks of flexibility? I've used MB for 5y+ and I've never found myself limited by the tool as long as I was able to connect the data source, that's IMHO the main friction with this tool
epgui
There is only so many things you can do with it is what I mean. You can’t make arbitrary graphs and you can only do very basic exploratory data analysis.

It’s great for cookie-cutter jobs, and for writing custom SQL, but not much more.

ReDeiPirati
This! As long as you can connect the data source you can go quite forward with this tool. It's probably the one that have the quickest learning curve.
n8henrie
Consider adding "no code" to the title somewhere to save a click for the hundreds of people that are planning to cheerfully suggest jupyter + pandas / matplotlib / Altair / seaborn / R / etc etc.
transitivebs
Good call; I realized that after the fact and unfortunately can't edit the title anymore.
__mharrison__
I use pandas. I'm pretty biased but I generally prefer to create things programmatically rather than drag and drop tooling. Especially if I need to do it in the future.

(I just made a course covering visualization w/ Pandas, Seaborn, Excel, Tableau, and a few others. My takeaway is that unless your data is good, you will need some preprocessing. Also, making good visualizations and tweaking them is difficult with code and no-code tooling. You need to figure out how to do the 20% of things (if you are even able to) in both code/no-code tools.)

gooseyman
What is the name of your new course? I’m struggling to determine if it’s effective pandas or one of the others.
__mharrison__
This is a pending course that will come out through Coursera
flat-pluto
I know you said wanted a no-code solution but in case you don't get a satisfactory answer try this out.

Earlier today there was a Show HN post[1] which showed how to visualize a Pandas dataframe (can come from CSV, JSON whatever). I tried it for basic tasks and it is pretty good. It's minimal code (<5 lines) - just reading the json and calling pygwalker in a Google Colab environment[2] or something. Something like this:

    import pandas as pd
    import pygwalker as pyg
    df = pd.read_json('{filename}.json')
    gwalker = pyg.walk(df)
Should be decent for most basic use-cases.

[1] - https://news.ycombinator.com/item?id=34869244

[2] - https://colab.research.google.com/

ellisv
I use R and ggplot2 for most plotting/visualization but I’d recommend something like Apache Superset if you want no-code (although setup is still required).
wanderingmind
You can use superset[0]. Its a Flask app that can connect to databases, read csv, json and create good plots

[0] https://superset.apache.org/

transitivebs
Looks very promising.

I think I'm looking for the AI-powered equivalent of this that's one level of abstraction higher. Apache projects are obviously super high quality, but I want to offload the cognitive load of thinking about the graph specifics to an ML algo that "just works" for the majority of use cases (and is tweakable after the fact).

aeontech
Datasette seems like it might be a good fit?

https://datasette.io/

cldellow
OP said they "find Google Sheets charts pretty difficult and painful for quickly exploring different views of the original data"

And that they want "a bunch of common graph views I can quickly choose between"

That doesn't sound like Datasette to me, although I'd be happy to be wrong -- how would you recommend someone achieve this in Datasette?

aeontech
Well, datasette has some simple exploratory viz built in, and is easy to extend if you want something more complicated. At least, I have been impressed with examples on the author's blog that come up here every so often.

I agree it's not the same as something like superset, but it is still a useful tool that some people might benefit from if they don't already know of it.

acomjean
Rstudio is a pretty nice user interface to the R language. datasets can be browsed like spreadsheet tables. ggplot2 is a great graphing tool. Used in science a lot by non programmers.

there is an online book too thats pretty decent: R for data science

https://r4ds.had.co.nz/

employee42
Can't believe someone hasn't suggested Grafana[0] yet. It sounds perfect for your needs (although there is some coding required to make the queries).

[0] https://grafana.com/

rvrst
Marple[0] is a pretty awesome tool for quick visualization and browsing through data.

[0] https://www.marpledata.com/

transitivebs
Looks very promising.

They seem to imply it's only for time-series data, but I like their marketing & UX so far. So many of the projects people link to are probably awesome, but if you don't nail the UX / DX, people bounce really quickly.

Thanks!

kasperset
Usually R tidyverse with GGplot2 does it for me. You could create shiny app and explore with "No code".
ies7
Since you're already using Google sheet, fastest nocode dashboard available should be Google Data Studio.
transitivebs
Ahhh; didn't know about this. I guess it's called Looker Studio now? Will give it a try. Thanks!
geophph
I might suggest pandas + plotly express. Not no code, and dependent on your data structure, but if you can form it into a tidy data frame plotly express will let you easily customize into different chart types and styles from there
ComputerGuru
I used to do this with Matlab. Haven’t in a long time, but if you speak that lingua franca, it’s a great way to go. Every kind of chart, lots of flexibility, customizable, etc. but I think everyone has moved to Python or R now.
shubhamjain
Shameless plug: This is exactly the problem the I am trying to solve with my app - TextQuery [1]. Creating even a basic graph means dealing with multiple tools. I wanted to create a simple app where you can import all common types of data, run SQL over it, and visualize it quickly.

[1]: https://textquery.app/

transitivebs
Awesome; glad I helped validate the pain point && always happy to try and help fellow indie hackers.

btw adding a screenshot to the home page of the goal UX would help 1000x even if it's just a design mockup.

For my use case, I'd want to drag & drop a JSON file.

Thanks!

shubhamjain
Thank you! I would love to add screenshots as soon as I have something solid. Would it be okay to reach out to you for feedback on some of the things I have done?
transitivebs
For sure; feel free to DM me on twitter transitive_bs
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noddingham
Power BI Desktop is free and handles JSON files as a data source.
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