This repo analyses the data coming from Kaggle's Death in the United States dataset

• The data contains the log file of deaths in the united states from the year 2005 till the year 2015. It has a long list of attributes that can be analyses and related to each other like race , year of death, education, gender, cause of death , education level and so on.
• Each year has its own CSV file of around 500 Mb and the schema of the legal attributes of each year. The total size of the dataset after decompression is 4 Gb.
• Some fields may be empty or not filled for a specific case.

In this section we get the relation between multiple attributes of the dataset along with others. The list of of the search analytics are as follows :

• The relation between education and cause of death.(Mousa)

  • The relation between work and death. (don't know if it will work)
  • sports and cause of death.
  • How does education affect lifespan?
  • How does education affect cause of death?

• Business report. (Each did his part)

• The most frequent causes of death generally. (Moustafa)

  • The most frequent causes of death for each race.(done)
  • and for each gender (done)
  • The day and month that most people died in.(done)

• time series analysis (Khalid)

  • The causes of death for each year.(done)
  • The most dangerous causes of death for each season .(done)
  • Trend fitting (Machine learning) (done)

• Violence and death (Ahmed)

  • Gun vs Vehicle Deaths. (done)
  • Guns and race. (done)
  • Homicide Vs other causes of death.
  • suicide correlation of age and education. (done)

  (interesting but not required)

  • Comparative analysis between men and women in attributes.
  • Race - age record - place of death.
  • Cardiovascular disease for men and women : it's a medical fact that men usually die out of cardiovascular disease more than women so let's test it.
  • Heart disease analysis