Open troboukis opened 6 years ago
Interesting subject clear grafik
I love this story idea! I'm excited to see more detailed break downs by race and gender, and I think this could be really effective as stacked bar graphs, to show under observation/not observation by race and gender. Great work! Although you don't like the font, I do like how impactful it is, maybe something similar but a little less bold
I spent more time trying to understand the data. The dataset reflects the population of NYC jails on one given date. Thus, I had to change some of the graphics I had in mind. Also, I found some research published from the Department of Justice, which shows that 21% of local jail prisoners have “a recent history” of a mental health condition. In NYC thought 43% of the inmates are put under mental observation. This difference is a good starting point to look further into the subject.
I spent way too much time trying to understand which visualisation would work better with my data. For the time being I'll choose the simple bar graphs. I'll try to figure out which other graphics could work well with my data.
Since we have a homework with which we'll practise with matplotlib, I decided to focus on illustrator for this project.
Trying to figure out what to do with the title. Should I keep the same title to all illustrations or change? Any ideas?
Your graphs are beautiful.
When you break it down by race, I think you should calculate it in the same way you do for gender. Give the percentage of, for ex, blacks under mental obs, based on how many black men or women there are, not based on the total number of inmates.
I also don't think you need to give the percentage of men/women who are not under mental obs. Just the percentage of those who are is enough. Since it's a yes or no thing, i can imagine the size of one half if you give me another.
Maybe would be interesting to know, how many % of blacks in prison are under mental observation, and also of all the other races. nice looking grafics! !
Howdy! I'm a little robot, checking in on your project.
You need some feedback, let me summon @dbaptistr, @adrianblanco, @linleysanders for you
These visuals are designed to live alone in the web. They provide some information regarding the issue of mental health in the jails. The most important finding of the project is the fact that almost 8 out of 10 women in the NYC jails are under mental observation. Overall more than 40% of inmates are under mental observation, figure which shows that mentally ill people are being jailed instead of hospitalised. I' ve sent questions to the Department of Corrections to ask what does 'mental observation' means and how is someone under mental observation.
Headline: Mental Health Crisis in NY Jails?
Published website version:
Code repository: https://github.com/troboukis/DATA_STUDIO/tree/master/CODE/1_PROJECT_INMATES_NYC Final data set(s):
I'm afraid that it's a bit overstyled.
Good job! I don't think it is over-styled. The only thing regarding styles I'd change are the colours in "The most crimes inmates are accused of in NYC jails" graphic. I think you can find a nicer scale of colours for the background you have chosen
This is very well done, and well-designed to stand alone. The one thing I would change in the headline is saying "NYC Jails" if you did indeed only focus on New York City jails as your outline mentioned. If you did the entire state of New York, then the use of NY makes sense.
The majority of the population of the NYC jails are black men, therefore the data are going to show that majority of those under mental health observation will be...black men. This is not a finding about the mental health data, it's a reflection of the population. ditto the chart showing how many women vs men.
you are accurately slicing and dicing the data, but i'm not sure which part i should be enlightened by?the interesting datasets here are the unexpected ones.
the percentage chart at the bottom- what order are the data in? i can't look at this an get a takeaway at all. is there a takeaway? is there a difference between first degree & second & third in all crimes? or burglary vs robbery? it's all the data but it's not organized in anyway that i can see a pattern or compare things easily.
what you've done successfully here is display all the data clearly. but there is no one thing, or things that i am suprised by or learning here. can you pull out one data point and follow it through further? make a story?
The main finding is that 76% of women in NYC jails were under mental observation. This is a very very high rate. The male's rate is high too. I'm waiting from the nyc correction's department to answer me what 'mental observation' is and how does one end under mental observation. After that The rest of the graphs were made mostly for practice while I was analysing the data. I probably wouldn't use them in the final story. However I want to understand how the system works and then have a look again at the data under a new prism.
Please complete all of the following sections, or the ghost of Joseph Pulitzer will spookily dance around your issue! A completed version of this template can be found at https://github.com/jsoma/data-studio-projects/issues/1
Pitch
Summary
I have found a dataset which has the daily inmates who are in custody in NYC. By looking at the data, I noticed that almost 40% of the inmates are under mental observation. This is a pretty high number, which means that the 'system' instead of taking care the people with mental health problems in specialized facilities, it puts them away in prizon. We'll focus on the inmates who are under mental observation and will try to find more information about them.
I found the data at the https://opendata.cityofnewyork.us/ .
After reading the documentation about their API I connected to their data.
Details
Possible headline(s):
Data set(s): https://data.cityofnewyork.us/Public-Safety/Daily-Inmates-In-Custody/7479-ugqb
Code repository: https://github.com/troboukis/DATA_STUDIO/tree/master/CODE/1_PROJECT_INMATES_NYC
Possible problems/fears/questions: Need to find data to compare the NYC data to. For instance, compare it to other States.
Work so far
This is the first graphic I've made. I've done a preliminary analysis.
Checklist
[Project]
in the title