@@ -8,16 +8,24 @@ The objective is to get the Excel data, published by the [General Directorate of
The [Data folder](https://github.com/paddytobias/15census_timor_dataclean/tree/master/data) holds all 45 Excel workbooks as well as a pdf of the Preliminary Report of the 2015 Population and Housing Census.
## Scripts
The [Scripts folder](https://github.com/paddytobias/15census_timor_dataclean/tree/master/data) holds all of the scripts I have been writing.
The [Scripts folder](https://github.com/paddytobias/15census_timor_dataclean/tree/master/data) holds all of the scripts I have been writing to process and analyse.
### Data Cleaning
[Scripts_DataCleaning](https://github.com/paddytobias/15census_timor_dataclean/tree/master/Scripts/Scripts_DataCleaning) comprises five scripts used to clean and process the data, including:
* convert from .xls format into .csv format
* using the table names to name each .csv file
* removing any redundant features in the dataframes (e.g., all empty rows, two headings, all 'Totals' rows since can be computed by R, etc.)
* and insert all data tables into an SQLite database
[Scripts_DataReview](https://github.com/paddytobias/15census_timor_dataclean/tree/master/Scripts/Scripts_DataReview) holds a bunch of scripts I am currently writing to do meta-analysis over the data. One script currently being worked on is to see how each district compares to the national average, either above or below, in each relevant data-table.
### Data Review
*These scripts must be run after the DataCleaning scripts because they rely on the data being processed and “clean”.*
[Scripts_DataReview](https://github.com/paddytobias/15census_timor_dataclean/tree/master/Scripts/Scripts_DataReview) holds a bunch of scripts I am currently writing to do meta-analysis over the data.
DataReview is now including a script to create a table for each district that compares its totals to the national average and counts the number of times this is above or below, in relevant census data-table. The plan is to then remove all NA rows from these tables and then cbind district tables together to get a national overview of the district breakdown
## DOI
The DOI for this collection is
Please feel free to use these scripts for your own work, but if you do, please site their origin using the DOI for this collection:
