Welcome to out project!
Team: Chloé Koura, Irina Mateescu, Mayumi (Mayu) Hamaoka, Patricia Pedro, Oludare (Dáre) Soniran
All the source code can be found under team_project.ipynb, which can be run as a normal jupyter notebook. We also saved all graphs and data separately. They are available in separate directories as seen in the tree directory structure below.
[nina@Irinas-MBP CFG-FinalProject]$ tree
.
├── README.md
├── data --------------------------> all our data saved to csv
│ ├── basic_water.csv
│ ├── children_receiving_ORS.csv
│ ├── cholera_cases_1971_2016.csv
│ ├── cholera_deaths.csv
│ ├── cholera_fatality_rate.csv
│ ├── diarrhea_deaths.csv
│ ├── health_per_county.csv
│ ├── inadequate_water.csv
│ ├── safe_drinking_water.csv
│ └── school_data.csv
├── graphs ------------------------> all our graphs saved to png
│ ├── children_ORS.png
│ ├── cholera_cases.png
│ ├── counties_malaria_expected_behavior.png
│ ├── counties_malaria_unexpected_behavior.png
│ ├── counties_to_benchmark.png
│ ├── counties_to_improve.png
│ ├── diarrhea_deaths.png
│ ├── diarrhea_inadequate_water.png
│ ├── edu_malaria_county_corr_matrix.png
│ ├── education_enrollment.png
│ ├── education_gender_scatterplots.png
│ ├── education_map.png
│ ├── female_edu_malaria_county_corr_matrix.png
│ ├── malaria_corr_matrix.png
│ ├── male_edu_malaria_county_corr_matrix.png
│ ├── pop_using_basic_drinking_water.png
│ ├── pop_using_safe_water.png
│ └── sleeping_under_bed_net_malaria_scatterplots.png
├── kenya_shapefiles --------------> shape files used through geopandas to generate our choropleth maps
│ ├── ken_admbnda_adm1_iebc_20180607.cpg
│ ├── ken_admbnda_adm1_iebc_20180607.dbf
│ ├── ken_admbnda_adm1_iebc_20180607.prj
│ ├── ken_admbnda_adm1_iebc_20180607.shp
│ ├── ken_admbnda_adm1_iebc_20180607.shp.xml
│ └── ken_admbnda_adm1_iebc_20180607.shx
├── new_data ----------------------> empty dir where all csvs and pngs will go once the code is run
└── team_project.ipynb ------------> our code
- Clone the git repo locally
- Install the following packages via pip (or conda, depending on preference):
- pandas, numpy, sklearn, matplotlib.pyplot, matplotlib.dates, seaborn, plotly.graph_objects, geopandas, mpl_toolkits.axes_grid1
- requests, logging, urllib.request, json, pprint, datetime, collections, pyodata, string
- Open team_project.ipynb in jupyter notebook
- Run the code (that simple :) )