A small repo for code that I write for my A-level Geography coursework/non-examined assessment (NEA)
Includes a word cloud generator that uses the wordcloud module and a requirements.txt file for easy installation of dependencies
Now also includes "crime_analyser.py" which is a script that summarises the data from the crime data set
The wordcloud generator is a Python server that handles requests from the client and generates a wordcloud based on the data sent from the client. You can view it at https://wordcloud.pages.dev.
The Replit instance that this is running on is available here: https://replit.com/@Draggie/Geog-NEA-Wordcloud
Firstly, clone this repository with git clone https://github.com/Draggie306/Geography-ALevel-NEA.git
Then, run pip -r requirements.txt to install dependencies.
Make sure the code has bool repl_save to True if you're running on a Linux distro like Replit
You might want to change the parameters in the WordCloud function from an 8K output to something smaller like:
width=1920, # This is a 1920x1080 16:9 monitor
height=1080,
max_words=1000,
background_color="white",Change the code to not have any Flask stuff - just the wordcloud generation (should be fairly easy to do) Pass in the data you want to generate the wordcloud from as a string and magic should happen
This script is a simple script that analyses the crime data set from https://data.police.uk/data/ and outputs a list of crime types and their average count per month for any given area (in this case, Norwich 007E) from Oct 2020 to Sept 2023. You can change the area and time period by changing the folder_path variable in the for loop.
Firstly, clone this repository with git clone https://github.com/Draggie306/Geography-ALevel-NEA.git
The only dependencies are os, csv and collections, so you should be able to run it without installing anything
Currently, there is no support for changing directories so you will have to change the folder_path variable in the for loop to the directory of the data set you want to analyse
Go to https://data.police.uk/data/ and download the data set you want to analyse, and unzip it into the directory you have hardcoded into the script.
Then, run the script with python crime_analyser.py and it should output a list of crime types and their average count per month for any given area (in this case, Norwich 007E) from Oct 2020 to Sept 2023.
Example output:
Analytics:
Found 4,916 crime records across 30 months.
14 different crime types matched the LSOA code Norwich 007A.
Total crimes in Norfolk: 191,723
Crime Type Total Count Average crimes/month
-----------------------------------------------------------------------------
Violence and sexual offences 1302 43.40
Anti-social behaviour 951 31.70
Shoplifting 702 23.40
Public order 665 22.17
Criminal damage and arson 265 8.83
Other theft 260 8.67
Bicycle theft 198 6.60
Drugs 165 5.50
Burglary 110 3.67
Theft from the person 87 2.90
Other crime 76 2.53
Possession of weapons 54 1.80
Robbery 50 1.67
Vehicle crime 31 1.03
4,916 crimes in total, average of 163.87 crimes per month.
From this data, you can then analyse it - I trust you! :)
Pull requests are welcome! Please make sure that you have tested your code before submitting a pull request.
If you find any issues, please submit an issue and I will try to fix it as soon as possible.