What do you use for basic data analysis, visualization, and graphing?
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!
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.
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/
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/
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/
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.)
If I'm not trying to build a very specific graph or chart, and just exploring data I usually use either Rawgraphs or Sqliteviz. Rawgraphs is nice if you just want to swap visualizations out with smaller data as is, sqliteviz seems to handle much larger datasets and let's you use SQL if you want to change the resultset. Both seem to keep data local too and I know sqliteviz works offline, rawgraphs might too.
https://www.rawgraphs.io/
https://sqliteviz.com/
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).
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/
You can write Trino rest client for a JSON endpoint that will allow you to query the endpoint using SQL and the result table can be push to any number of application for visualization.
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/
Since you're already using Google sheet, fastest nocode dashboard available should be Google Data Studio.
In the robotics world many people use PlotJuggler (https://plotjuggler.io/) that, among other things, sports csv files.
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
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.
Give a try to http://graphext.com . It’s no-code tool that at the same time is as powerful as a Jupyter Notebook
Not no code, but can do simple things using something like nodes in blender.
Usually R tidyverse with GGplot2 does it for me. You could create shiny app and explore with "No code".
Power BI Desktop is free and handles JSON files as a data source.
Does Excel still freeze when trying to open huge .csv files?