Difference between revisions of "Ivan-big-data"

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#Identifying and downloading the target data set
 
#Identifying and downloading the target data set
 
Data sets can be founded here:
 
Data sets can be founded here:
* http://data.un.org/Data.aspx?q=gdp&d=SNAAMA&f=grID%3a101%3bcurrID%3aUSD%3bpcFlag%3a1
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** http://data.un.org/Data.aspx?q=gdp&d=SNAAMA&f=grID%3a101%3bcurrID%3aUSD%3bpcFlag%3a1
* http://data.un.org/Data.aspx?d=UNAIDS&f=inID%3a32
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** http://data.un.org/Data.aspx?d=UNAIDS&f=inID%3a32
* http://data.un.org/Data.aspx?q=population&d=PopDiv&f=variableID%3a12
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** http://data.un.org/Data.aspx?q=population&d=PopDiv&f=variableID%3a12
* http://data.un.org/Data.aspx?q=abortion&d=GenderStat&f=inID%3a12
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** http://data.un.org/Data.aspx?q=abortion&d=GenderStat&f=inID%3a12
* http://data.un.org/Data.aspx?q=education&d=UNESCO&f=series%3aXGOVEXP
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** http://data.un.org/Data.aspx?q=education&d=UNESCO&f=series%3aXGOVEXP
* http://data.un.org/Data.aspx?d=UNODC&f=tableCode%3a1
+
** http://data.un.org/Data.aspx?d=UNODC&f=tableCode%3a1
  
 
#Data cleaning and pre-processing  
 
#Data cleaning and pre-processing  

Revision as of 17:04, 4 December 2011

  • Project title: Relationship between Homicide, Education, Abortion, HIV Incidence, Population and GDP for countries around the globe
  • Project data set: United Nations DB (UNdata)
Project Tasks
  1. Identifying and downloading the target data set

Data sets can be founded here:

  1. Data cleaning and pre-processing

The first obstacle I faced with cleaning and pre-processing was inconsistency in countries naming. For example name China in education and name People's Republic of China in homicide... So when I did full join of country columns I realized that not all of them are in one line (things that are supposed to be in one line). So I changed names and made it unique through all 6 data sets.   

  1. Load the data into your Postgres instance

Data-sets I downloaded were in CSV files.
Here is an example for inserting data-set homicide into my PQSL:

    • drop table homicide;
    • create TABLE homicide (COUNTRY varchar primary key, YEAR int, RATE float);
    • COPY homicide FROM '/home/postgres/HOMICIDE.csv' DELIMITER ';' CSV;
  1. Develop queries to explore your ideas in the data
  2. Develop and document the model function you are exploring in the data
  3. Develop a visualization to show the model/patterns in the data
Tech Details
  • Node: as2
  • Path to storage space: /scratch/big-data/ivan
Results
  • The visualization(s)
  • The story