Fuel-Poverty-Project

Fuel Poverty Project is a collaborate work with a team of Code Division. Project Link

Gantt

Tools we used for collaborating:

Slack
spatial.chat
Moodle
Miro
Trello
GitHub
Google shared Drive
Colab & VSCode
Excel , Python

data-analysis

All data analysis for the project - including python, excel(.csv) and other documents.

Python -

Plotly Choropleth Map shows % income deprived >= 25% AND Average Energy Efficiency <= 80%.

File used - fp_peopleincomedeprived_energyefficiency.py,

        - Glasgow.geojson 
        - SIMD_MSOA_domestic_gas_elec_2020.xlsx
        - D_EPC_data_2020_Q1_extract_0721.zip
        - D_EPC_data_2020_Q2_extract_0721.zip
        - D_EPC_data_2020_Q3_extract_0721.zip
        - D_EPC_data_2020_Q4_extract_0721.zip
        - D_EPC_data_2021_Q1_extract_0721.zip
        - D_EPC_data_2021_Q2_extract_0721.zip

Python plot Result link : https://sysphcd.github.io/percetincomedeprived_avgenergyefficiency_plot.html

POWER BI Result link : https://sysphcd.github.io/incomedeprived_medianenergy.html

Plotly Choropleth Map shows Median Energy Efficiency and Median Energy Consumption in Glasgow.

File used - fp_epc_onmap.py,

        - Glasgow.geojson 
        - D_EPC_data_2020_Q1_extract_0721.zip
        - D_EPC_data_2020_Q2_extract_0721.zip
        - D_EPC_data_2020_Q3_extract_0721.zip
        - D_EPC_data_2020_Q4_extract_0721.zip
        - D_EPC_data_2021_Q1_extract_0721.zip
        - D_EPC_data_2021_Q2_extract_0721.zip

Result link : (Python Plots)

[https://sysphcd.github.io/Glasgow-Districts-Median-current-energy-efficiency-plot.html]
[https://sysphcd.github.io/Glasgow-Districts-Median-Energy-Consumption-plot.html]

Excel

File name : glasgow_ee_incomedeprived_dataset.xlsx made a Correlation Coefficient and linear regression statistical analysis in the Excel file

sysphcd/Fuel-Poverty-Project