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This is the report about the Suicide rate from 1985 to 2016, completed data cleaning, data mining and analysis with Python.

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Suicide rate from 1985 to 2016

Introduction:

This is the report about the Suicide rate from 1985 to 2016, the dataset was got from Kaggle website (https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016), in this dataset, it contains country, year, sex, age, suicide number, population, suicide/100k pop, country-year, HDI for year, gdp_for_year, gdp_per_capita and generation.

From this suicide rate dataset, we can know the trend of the suicide number by year, and also know which generation/age group has the highest suicide number.

In this report, we also compared the suicide number to the other three factors to see is there any correlation between them, we compared the suicide number to GDP (https://data.worldbank.org/indicator/NY.GDP.MKTP.CD), life expectancy (https://www.kaggle.com/kumarajarshi/life-expectancy-who) and happiness score to (http://worldhappiness.report/ed/2017/) find the correlation.

Conclusion:

1. The suicide number of the male is higher than female.

2. The age group has the highest suicide number is 35-54 years.

3. The country which has the highest suicide number is Russian.

4. GDP, life expectancy and happiness score do not have a strong correlation with the suicide number.

5. Happiness score has a strong correlation with life expectancy.

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This is the report about the Suicide rate from 1985 to 2016, completed data cleaning, data mining and analysis with Python.

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