Foundational exploratory data analysis (EDA) of climate data of Ghana since 1973, in jupyter lab environment.
This is a foundational exploratoty data analysis (eda) of climate data of Ghana from 1973, as my first attempt at datascience. Data was obtained from open sources at https://www.ncdc.noaa.gov/cdo-web, inspired by the famous hottest month Global Climate Report April 2019 (https://www.ncdc.noaa.gov/sotc/global/201904). The goal was to obtain from historical records the hottest day, month, year and in what amounts in comparison with the conclusions reached in the global study among other facts.
Analysis follwed the familair pattern used in data science, such as data wranglings, EDA before concluding with visualisation. The project goes further to group the data according the hydro-climatic zones of Ghana: Zone 1 - Coastal High Forest, Zone 2 - Coastal Savanna, Zone 3 - Deciduous Forest & Transition and Zone 4 - Northern Savanna. and compares it with the national average. This is done to investigate how the mean national temperature defer from the implicit sub climatic zones of Ghana.