From e83c414cb618ff28042684a87be8d64a49148b3a Mon Sep 17 00:00:00 2001 From: Prabhas Pokharel Date: Mon, 22 Jul 2013 21:53:40 +0545 Subject: [PATCH] text update --- Poverty/index.html | 10 +++------- Poverty/index.md | 12 +++--------- Poverty/index.rmd | 6 +++--- 3 files changed, 9 insertions(+), 19 deletions(-) diff --git a/Poverty/index.html b/Poverty/index.html index 5da5420..88e9acc 100644 --- a/Poverty/index.html +++ b/Poverty/index.html @@ -183,7 +183,7 @@

Poverty by District in Nepal, mapped

-

Chandan Sapkota, who one of my friend Bigyan calls the “Ezra Klein of Nepal”, produces amazing analysis about Nepal, taking data sources from the obscure reports of government institutions and writing them up in accessible blog posts. When he posted about “Poverty by District in Nepal”, I thought that I'd map the poverty, since it is hard for me to place all the districts in Nepal, and I wanted to see what the visual spread of poverty was. This html is generated automatically using R markdown; see the git repository to see the data and to get the rmd file.

+

Chandan Sapkota, who one of my friend Bigyan calls the “Ezra Klein of Nepal”, produces amazing analysis about Nepal, taking data sources from the obscure reports of government institutions and writing them up in accessible blog posts. When he posted about “Poverty by District in Nepal”, I thought that I'd map the poverty, since it is hard for me to place all the districts in Nepal, and I wanted to see what the visual spread of poverty was. This html is generated automatically using R markdown; see the git repository to see the data and to get the rmd file. The git repository also contains a library in the making, NepalMapUtils, which has some convenience functions for making choropleth maps (of Nepal).

0. Data preparation

@@ -209,7 +209,7 @@

0. Data preparation

"PovertyGap", "S.E-P.G.", "PovertySeverity", "S.E-P.S.") -

And now the 2001 data, which has been modified to have the exact same columns already:

+

And now we will also load the 2001 data, which has been modified to have the exact same column names already:

poverty2001 <- read.csv("PovertyEstimates2001.csv")
@@ -264,13 +264,9 @@

3. Comparisons with 2001

high = muted("red")) -
Scale for 'fill' is already present. Adding another scale for 'fill',
-which will replace the existing scale.
-
-

plot of chunk unnamed-chunk-8

-

The message here seems to be that most of the country has become less poor, with an exception of an icnrease in poverty in: Mustang / Manang, the Far Western Mountains, and in the central-eastern Terai (Parsa/Bara/Rautahat and Siraha/Saptari).

+

The units here are in difference of percentage points; bigger negative numbers are better. The message here seems to be that most of the country has become less poor, with an exception of an increase in poverty in: Mustang / Manang, the Far Western Mountains, and in the central-eastern Terai (Parsa/Bara/Rautahat and Siraha/Saptari).

diff --git a/Poverty/index.md b/Poverty/index.md index 7520925..188fd86 100644 --- a/Poverty/index.md +++ b/Poverty/index.md @@ -3,7 +3,7 @@ Poverty by District in Nepal, mapped --- -Chandan Sapkota, who one of my friend Bigyan calls the "Ezra Klein of Nepal", produces amazing analysis about Nepal, taking data sources from the obscure reports of government institutions and writing them up in accessible blog posts. When he posted about ["Poverty by District in Nepal"](http://sapkotac.blogspot.com/2013/07/poverty-by-district-in-nepal.html), I thought that I'd map the poverty, since it is hard for me to place all the districts in Nepal, and I wanted to see what the visual spread of poverty was. This html is generated automatically using R markdown; see the [git repository](https://github.com/prabhasp/NepalMaps/tree/gh-pages/Poverty) to see the data and to get the rmd file. +Chandan Sapkota, who one of my friend Bigyan calls the "Ezra Klein of Nepal", produces amazing analysis about Nepal, taking data sources from the obscure reports of government institutions and writing them up in accessible blog posts. When he posted about ["Poverty by District in Nepal"](http://sapkotac.blogspot.com/2013/07/poverty-by-district-in-nepal.html), I thought that I'd map the poverty, since it is hard for me to place all the districts in Nepal, and I wanted to see what the visual spread of poverty was. This html is generated automatically using R markdown; see the [git repository](https://github.com/prabhasp/NepalMaps/tree/gh-pages/Poverty) to see the data and to get the rmd file. The git repository also contains a library in the making, NepalMapUtils, which has some convenience functions for making choropleth maps (of Nepal). ## 0. Data preparation @@ -36,7 +36,7 @@ names(poverty11) <- c("District", "Population", "PovertyIncidence", "S.E-P.I.", ``` -And now the 2001 data, which has been modified to have the exact same columns already: +And now we will also load the 2001 data, which has been modified to have the exact same column names already: ```r @@ -104,13 +104,7 @@ npchoropleth(poverty, "District", "PovertyTenYrChange") + scale_fill_gradient2(l high = muted("red")) ``` -``` -Scale for 'fill' is already present. Adding another scale for 'fill', -which will replace the existing scale. -``` - ![plot of chunk unnamed-chunk-8](figure/unnamed-chunk-8.png) -The message here seems to be that most of the country has become less poor, with an exception of an icnrease in poverty in: Mustang / Manang, the Far Western Mountains, and in the central-eastern Terai (Parsa/Bara/Rautahat and Siraha/Saptari). - +The units here are in difference of percentage points; bigger negative numbers are better. The message here seems to be that most of the country has become less poor, with an exception of an increase in poverty in: Mustang / Manang, the Far Western Mountains, and in the central-eastern Terai (Parsa/Bara/Rautahat and Siraha/Saptari). diff --git a/Poverty/index.rmd b/Poverty/index.rmd index 0a5b1a3..5e146e7 100644 --- a/Poverty/index.rmd +++ b/Poverty/index.rmd @@ -3,7 +3,7 @@ Poverty by District in Nepal, mapped --- -Chandan Sapkota, who one of my friend Bigyan calls the "Ezra Klein of Nepal", produces amazing analysis about Nepal, taking data sources from the obscure reports of government institutions and writing them up in accessible blog posts. When he posted about ["Poverty by District in Nepal"](http://sapkotac.blogspot.com/2013/07/poverty-by-district-in-nepal.html), I thought that I'd map the poverty, since it is hard for me to place all the districts in Nepal, and I wanted to see what the visual spread of poverty was. This html is generated automatically using R markdown; see the [git repository](https://github.com/prabhasp/NepalMaps/tree/gh-pages/Poverty) to see the data and to get the rmd file. +Chandan Sapkota, who one of my friend Bigyan calls the "Ezra Klein of Nepal", produces amazing analysis about Nepal, taking data sources from the obscure reports of government institutions and writing them up in accessible blog posts. When he posted about ["Poverty by District in Nepal"](http://sapkotac.blogspot.com/2013/07/poverty-by-district-in-nepal.html), I thought that I'd map the poverty, since it is hard for me to place all the districts in Nepal, and I wanted to see what the visual spread of poverty was. This html is generated automatically using R markdown; see the [git repository](https://github.com/prabhasp/NepalMaps/tree/gh-pages/Poverty) to see the data and to get the rmd file. The git repository also contains a library in the making, NepalMapUtils, which has some convenience functions for making choropleth maps (of Nepal). ## 0. Data preparation @@ -64,11 +64,11 @@ npchoropleth(poverty11, 'District', 'Population') Now, lets us compare the data to the 2001 small area povery estimates. We will first create a new dataframe containing data from both years, then take the difference and map it (while remembering to flip the color scheme, a decrease is poverty incidence is good!): -```{r echo=T, comment=NA, fig.height=7.2, fig.width=12, cache=TRUE} +```{r echo=T, comment=NA, fig.height=7.2, fig.width=12, cache=TRUE, message=FALSE} poverty <- merge(poverty11, poverty2001, by="District", suffixes=c("_2011", "_2001")) poverty$PovertyTenYrChange <- poverty$PovertyIncidence_2011 - poverty$PovertyIncidence_2001 npchoropleth(poverty, 'District', 'PovertyTenYrChange') + scale_fill_gradient2(low=muted('blue'), high=muted('red')) ``` -The units here are in difference of percentage points; bigger negative numbers are better. The message here seems to be that most of the country has become less poor, with an exception of an icnrease in poverty in: Mustang / Manang, the Far Western Mountains, and in the central-eastern Terai (Parsa/Bara/Rautahat and Siraha/Saptari). \ No newline at end of file +The units here are in difference of percentage points; bigger negative numbers are better. The message here seems to be that most of the country has become less poor, with an exception of an increase in poverty in: Mustang / Manang, the Far Western Mountains, and in the central-eastern Terai (Parsa/Bara/Rautahat and Siraha/Saptari). \ No newline at end of file