Reputation: 175
I have got this dataset in julia:
julia> import Downloads
julia> using DLMReader, VegaLite, InMemoryDatasets
julia> data=Downloads.download("https://raw.githubusercontent.com/akshdfyehd/salary/main/ds_salaries.csv");
julia> ds=filereader(data,emptycolname=true);
julia> new=filter(ds,:employment_type,by= ==("FT"));
julia> select!(new,:job_title,:salary_in_usd,:work_year)
588×4 Dataset
Row │ job_title work_year experience_level salary_in_usd
│ identity identity identity identity
│ String? Int64? String? Int64?
─────┼────────────────────────────────────────────────────────────────────────
1 │ Data Scientist 2020 MI 79833
2 │ Machine Learning Scientist 2020 SE 260000
3 │ Big Data Engineer 2020 SE 109024
4 │ Product Data Analyst 2020 MI 20000
5 │ Machine Learning Engineer 2020 SE 150000
6 │ Data Analyst 2020 EN 72000
7 │ Lead Data Scientist 2020 SE 190000
8 │ Data Scientist 2020 MI 35735
9 │ Business Data Analyst 2020 MI 135000
10 │ Lead Data Engineer 2020 SE 125000
11 │ Data Scientist 2020 EN 51321
12 │ Data Scientist 2020 MI 40481
13 │ Data Scientist 2020 EN 39916
14 │ Lead Data Analyst 2020 MI 87000
⋮ │ ⋮ ⋮ ⋮ ⋮
576 │ Data Analytics Manager 2022 SE 150260
577 │ Data Analytics Manager 2022 SE 109280
578 │ Data Scientist 2022 SE 210000
579 │ Data Analyst 2022 SE 170000
580 │ Data Scientist 2022 MI 160000
581 │ Data Scientist 2022 MI 130000
582 │ Data Analyst 2022 EN 67000
583 │ Data Analyst 2022 EN 52000
584 │ Data Engineer 2022 SE 154000
585 │ Data Engineer 2022 SE 126000
586 │ Data Analyst 2022 SE 129000
587 │ Data Analyst 2022 SE 150000
588 │ AI Scientist 2022 MI 200000
561 rows omitted
But these are not really represent the info quite clearly, because I don't have quite good ideas about how to visualize these info now, this graph is a good one but I'm not sure if my dataset can produce this kind of graph:
can I please have any sugesstions to make a better graph? any other packages as long as it can show good graph.
Thanks in advance.
Upvotes: 2
Views: 136
Reputation: 30304
I suggest you read the following to get a good idea of better dataviz practices.
https://clauswilke.com/dataviz/
In answer to your question, it really depends what you're trying to show. In the first instance, I would switch the axes and that will make the data a lot more readable.
Upvotes: 4