This dataset was provided by the IHME with profiles highlighting performance of each US county in terms of mortality rates for select causes, life expectancy at birth, and prevalence of select risk factors. The dataset consists of data taken every five years from 1980-2014.
The indicators include the following:
Bladder cancer, Brain and nervous system cancers, Breast cancer, Cancers, Cervix uteri cancer, Colon and rectum cancers, Corpus uteri cancer, Gallbladder and biliary tract cancers, Hodgkin lymphoma, Kidney and other urinary organ cancers, Larynx cancer, Leukemia, Liver cancer, Melanoma, Mesothelioma, Mortality, Mouth cancer, Multiple myeloma, Non-Hodgkin lymphoma, Oesophagus cancer, Ovary cancer, Pancreas cancer, Pharynx cancers, Prostate cancer, Skin cancers, Stomach cancer, Testicular cancer, Thyroid cancer, Trachea, bronchus, and lung cancers
The main goal of this US cancer mortalitiy visualization is to better understand national and localized trends across the United States. It is helpful to improve my ability to visualize data using standard and non-standard libraries.
Geographical data is particularly difficult to display eligantly using standard libraries such as matplot lib or seaborn so I will be utilizing highcharts html library with a python plugin to properly display the state and county data.
Trends and further analysis is available here.
How Americans die has a correlation to their geographical location: FiveThirtyEight
Here is a simple analysis of the data provided by Institute for Health Metrics and Evaluation (IHME)
Check out the Kaggle Kernels for more information and visualizations.
Due to the use of a highcharts, to view the notebook with visualized maps, Click Here