This project was developed in the unit Introduction to Data Science of the Master of Data Science from Monash University. We develop an extensive exploratory data analysis about cryptocurrencies, Immigration and crimes in Australia.
We use primarily pandas in python. The file EDA.ipynb contains the analysis and all others are supporting dataset.
The following data files used in this task were originally downloaded from the Australian Bureau of Statistics:
Births.csv- This file contains yearly data regarding the recorded number of births by Australian state/territory of registration between 1977 and 2016.Deaths.csv-This file contains yearly data regarding the recorded number of deaths by Australian state/territory of registration between 1977 and 2016.TFR.csv- This file contains yearly data on the recorded average number of births per woman over her lifetime by each state/territory between 1971 and 2016.NOM.csv- This data file contains yearly data on the net gain or loss of population through immigration (migrant arrivals) to Australia and emigration (migrant departures) from Australia, for the period between 1977 and 2016.NIM.csv- This data file contains yearly data on the net gain or loss of population through the movement of people from one state or territory to another, for the period between 1977 and 2016.
This dataset is publicly available from data.sa.gov.au on a yearly basis:
Crime_Statistics_SA_2014_2019.csv- The Crime statistics dataset contains all offences against the person and property that were reported to police between 2014 to 2019 in South Australiansuburbs. The dataset contains information about the crime reported date, suburb incidentoccurred, Postcode, 3 levels of description of the offence, and the offence count.
The last dataset was obtained from the World Bank (world development indicators series about GHG Emissions) Databank:
Others- Prices of cryptocurrencies sushc as Bitcoin, Ethereum, Litecoin and so on.
