Difference between revisions of "Ivan-big-data"

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* 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==
  
 
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.   
 
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.   
  
***Load the data into your Postgres instance  
+
==Load the data into your Postgres instance==
  
 
Data-sets I downloaded were in CSV files. <br/>
 
Data-sets I downloaded were in CSV files. <br/>
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* COPY homicide FROM '/home/postgres/HOMICIDE.csv' DELIMITER ';' CSV;
 
* COPY homicide FROM '/home/postgres/HOMICIDE.csv' DELIMITER ';' CSV;
  
***Develop queries to explore your ideas in the data  
+
==Develop queries to explore your ideas in the data==
***Develop and document the model function you are exploring in the data  
+
==Develop and document the model function you are exploring in the data==
***Develop a visualization to show the model/patterns in the data  
+
==Develop a visualization to show the model/patterns in the data==
  
 
===== Tech Details =====
 
===== Tech Details =====

Revision as of 18:08, 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

Identifying and downloading the target data set

Data sets can be founded here:

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.   

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;

Develop queries to explore your ideas in the data

Develop and document the model function you are exploring in the data

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