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Poverty_Analysis.Rmd
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---
title: "Poverty Analysis"
author: "AMDeines"
date: "1/18/2022"
output: html_document
---
# Analysis
```{r load_mainData}
source("InFish_Auxillary.R")
#most recent output from "Poverty_CompileData.Rmd"
load(file="Output/MainData.RDATA")
str(MPI_FAO_Income)
```
Based on [working MS](https://tnc.box.com/s/8zlpzrojm6vl9dai4mn26st7t35pq6h1) as of 2022_01_19.
#Results
## Relationship between MPI and animal protein consumption
###Contribution of freshwater fish in people’s diet in different levels of poverty (MPI)
Animal protein consumed (g/person/day; y axis) ~ Multidimensional poverty (0-1, x axis) and size of points is the percentage freshwater fish makes up of the total animal protein consumed
Data sources; Animal protein consumed is from ABC; MPI is from MPI Table 1
```{r }
plot01 <-
ggplot(
data = MPI_FAO_Income %>%
mutate(Protein_fwf = FAO_FreshwaterFishProtein_g.capita.day /
FAO_TotalProtein_g.capita.day),
aes(y = FAO_TotalProtein_g.capita.day, x = MPI, size = Protein_fwf)
) +
expAnnotate(scpt="`Poverty_Analysis.Rmd`",
figID="plot01")+
geom_point()+
ylab("Animal protein consumed (g/person/day)")+
scale_size("Freshwater fish % of Protein")+
expTheme
```
### Contribution of freshwater of freshwater fish in people’s diet in each region at different levels of poverty (MPI) and the trend/relationship between them.
Freshwater fish as a % of animal protein (%; y axis) ~ Multidimensional poverty (0-1, x axis) and size of points is the percentage freshwater fish makes up of the total and disaggregated by region (MPI table definition) and a trend line showing the regression between fish as a % of animal proteinand multidimensional poverty
Data sources; Animal protein consumed is from ABC; MPI is from MPI Table 1
```{r }
plot02 <-
ggplot(
data = MPI_FAO_Income %>%
mutate(Protein_fwf = FAO_FreshwaterFishProtein_g.capita.day /
FAO_TotalProtein_g.capita.day),
aes(y =Protein_fwf , x = MPI, size = FAO_TotalProtein_g.capita.day) #
) +
expAnnotate(scpt="`Poverty_Analysis.Rmd`",
figID="plot02")+
geom_point()+
geom_smooth(method="lm", show.legend = FALSE)+
facet_wrap(~`World region`,scale="free")+
ylab("Freshwater fish % of Protein")+ #
scale_size("Animal protein consumed (g/person/day)")+
expTheme
plot07<-
ggplot(
data = MPI_FAO_Income %>%
mutate(Protein_fwf = FAO_FreshwaterFishProtein_g.capita.day /
FAO_TotalProtein_g.capita.day)%>%
filter(`World region`%in%"Sub-Saharan Africa"),
aes(y =Protein_fwf , x = MPI,color=FAO_TotalProtein_g.capita.day) #
) +
expAnnotate(scpt="`Poverty_Analysis.Rmd`",
figID="plot07")+
geom_point()+
ggrepel::geom_text_repel(aes(label=Country))+
ylab("Freshwater fish % of Protein")+ #
expTheme
```
### Contribution of freshwater of freshwater fish in people’s diet in each region at different levels of NUTRITIONAL poverty (MPI) and the trend/relationship between them.
Animal protein consumed (g/person/day; y axis) ~ Multidimensional poverty Nutrition (0-1, x axis) and size of points is the percentage freshwater fish makes up of the total and disaggregated by region (MPI table definition) and a trend line showing the regression between protein consumed and multidimensional poverty.
Data sources; Animal protein consumed is from ABC; MPI is from MPI Table 1
```{r }
# By POPULATION
plot03 <-
ggplot(
data = MPI_FAO_Income %>%
mutate(Protein_fwf = FAO_FreshwaterFishProtein_g.capita.day /
FAO_TotalProtein_g.capita.day),
aes(size = FAO_TotalProtein_g.capita.day,
x = `MPI_Nutrition_%Population`,
y = Protein_fwf)
) +
expAnnotate(scpt="`Poverty_Analysis.Rmd`",
figID="plot03")+
geom_point()+
geom_smooth(method="lm", show.legend = FALSE)+
facet_wrap(~`World region`,scale="free")+
ylab("Freshwater fish % of Protein")+
xlab("MPI Nutrition Deprivation (% Population, Uncensored Headcounts)")+
scale_size("Animal protein consumed (g/person/day)")+
expTheme
# By CONTRIBUTION
plot04 <-
ggplot(
data = MPI_FAO_Income %>%
mutate(Protein_fwf = FAO_FreshwaterFishProtein_g.capita.day /
FAO_TotalProtein_g.capita.day),
aes(size = FAO_TotalProtein_g.capita.day,
x = `MPI_Nutrition_%Contribution`,
y = Protein_fwf)
) +
expAnnotate(scpt="`Poverty_Analysis.Rmd`",
figID="plot04")+
geom_point()+
geom_smooth(method="lm", show.legend = FALSE)+
facet_wrap(~`World region`,scale="free")+
ylab("Freshwater fish % of Protein")+
xlab("MPI Nutrition Deprivation (% Contribution)")+
scale_size("Animal protein consumed (g/person/day)")+
expTheme
```
### Contribution of freshwater of freshwater fish in people’s diet in each region at different levels of conventional poverty measure and the trend/relationship between them.
Animal protein consumed (g/person/day; y axis) ~ Percentage of population living on < US$1.90 a day (0-1, x axis) and size of points is the percentage freshwater fish makes up of the total and disaggregated by region (MPI table definition) and a trend line showing the regression between protein consumed and Poverty Gap
```{r }
plot05 <-
ggplot(
data = MPI_FAO_Income %>%
mutate(Protein_fwf = FAO_FreshwaterFishProtein_g.capita.day /
FAO_TotalProtein_g.capita.day),
aes(size = FAO_TotalProtein_g.capita.day,
x = WB_PovertyGap_1.90,
y = Protein_fwf)
) +
expAnnotate(scpt="`Poverty_Analysis.Rmd`",
figID="plot05")+
geom_point()+
geom_smooth(method="lm", show.legend = FALSE)+
facet_wrap(~`World region`,scale="free")+
ylab("Freshwater fish % of Protein")+
xlab("Poverty gap at $1.90 a day (%)")+
scale_size("Animal protein consumed (g/person/day)")+
expTheme
```
### Contribution of freshwater of freshwater fish in people’s diet in Africa region at different levels of poverty (MPI) and the trend/relationship between them but controlled (in the loosest definition) for available of water to fish from.
Only for Africa countries – show the above relationship but transformed to account for freshwater area / borders in a country.
```{r }
plot06 <-"TBD"
```