Pages

Showing posts with label Philippines. Show all posts
Showing posts with label Philippines. Show all posts

Sunday, June 15, 2014

Creating Inset Map with ggplot2

According to wiki.GIS.com one of the reason for using inset map is to provide a reference for an area for unfamiliar readers.  Inset map is also considered a great asset for cartographers.  Most of the GIS software available in the market have a provision for non-cartographer and beginners to create inset map. However, for R users who are into making maps, creating inset map is a bit challenging. Thanks to the post of Pascal Mickelson and Scott Chamberlain which gave users like me a guide on how to create inset map in R using ggplot2. Below is an example of map with inset created using R.

Saturday, May 31, 2014

Mindoro Digital Elevation Map Updated

Almost 2 years ago, I made a post on creating digital elevation map using R. For that post, I used the basic R plotting function to create the map. Recently, I started learning to use ggplot2 package for visualizing data. Today, I created the same map that I did two years ago, using raster and gpplot2, its for you guys to tell the difference.

Happy Coding! Use R!


































Before                                                       

















After



Thursday, October 17, 2013

Mapping Earthquake in Bohol using R

On my previous post a year ago (on mapping earthquake recorded for the Philippines), it can be seen that there were no earthquake (epicenter) recorded for the province of Bohol. But on the 15th of October there were more than 40 quakes recorded that hit the island from early in the morning till late midnight with magnitude ranging from 2.7 to 7.2.

Below is the map, created using R, of earthquakes that hit the province:


Friday, October 26, 2012

NSCB Sexy Stats Version 2

This was a revised version of my previous post about the NSCB article. With the suggestion from Tal Galili, below were the new pie charts and the R codes to produce these plots by directly scrapping the data from the webpage using XML and RColorBrewer pagkage.

Unemployment by Age Group

Unemployment by Gender

Unemployment by Civil Status

Unemployment by Educational Level

Thursday, October 25, 2012

NSCB Sexy Statistics (Unemployment)


Recently, my friend posted on her Facebook account about the article published by the National Statistical Coordination Board (NSCB) about poverty and unemployment in the country.  Looking at the report I saw a lot of tables, so I thought why not use R to make some graphs out of these tables (with some inspiration from the mazmascience).


Percent Unemployed Per Age Group




Percent Unemployed by Sex Group



 Percent Unemployed by Civil Status





Wednesday, August 8, 2012

Rainfall Amount Flooding Quezon City Philippines

The rainfall received by Quezon City, Philippines was almost double of what the city normally receive for the entire month of August, causing flooding and land slide to various villages in the area.




August 6-7 Rainfall on Metro Manila

Majority of Metro Manila is affected by floods. Looking at the hourly data from PAGASA weather  station located at Bicutan, Taguig, the graph below will gave the viewers of this blog on the rainfall situation in Manila from August 6 (12:00am)-7(11:15 pm), 2012.

Tuesday, August 7, 2012

Provincial Monthly Rainfall of the Philippines from WORLDCLIM

Preparing for a future conference on climate change, I downloaded and extracted average monthly rainfall in the Philippines from worldclim.org. Using maptools, raster, and animation package in R, I produced an animation of average monthly rainfall of the country.


Monday, August 6, 2012

Provincial Map using GADM

This blog demonstrates how to produce political/provincial boundary map (below) using R maptools and raster packages.


 

Monday, July 9, 2012

Trend and Spatial Pattern of Poverty in the Philippines

In a teaching demo that I have conducted, I discussed on how R can be used to analyze trends and spatial pattern of poverty incidence in the Philippines. Playing on the data I got from the National Statistical Coordination Board below is what I got.


 Scatter  Plot Matrix

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Histogram

 


Poverty Incidence Map

 

 

Spatial Pattern