ggplot Exercises

The USAID/Saturn team is interested in knowing where partners are seeing less than ideal linkage to treatment. Using df_linkage, help them create a scatter plot that looks at testing and treatment, flagging where they’re far from a 1:1 relationship. Consider using different aesthetics to convey a message to your audience.

```{r setup, include=FALSE} knitr::opts_chunk$set(echo = TRUE)

## Overivew

Below are three questions to work on to test our ggplot skills.


## Setup

```{r}
#Dependencies
  library(tidyverse)
  library(scales)

#import data
  df_trends <- read_csv("https://raw.githubusercontent.com/USAID-OHA-SI/coRps/master/2020-04-13/FY18-20_Jupiter_txtrends.csv")

  df_linkage <- read_csv("https://raw.githubusercontent.com/USAID-OHA-SI/coRps/master/2020-04-13/FY19_Saturn_linkage.csv")

  df_achievement <- read_csv("https://raw.githubusercontent.com/USAID-OHA-SI/coRps/master/2020-04-13/FY20_Neptune_txnew_achievement.csv")

Linkage

```{r linkage}

glimpse(df_linkage)

ggplot(df_linkage)

## Treatment Trends

A number of questions have come up recently about treatment trends in Jupiter. You will want to use `df_trends` to review trends in TX_CURR, TX_NEW, and TX_NET_NEW from FY18 to the present visualize through a line chart. Consider using different aesthetics to convey a message to your audience.

```{r trends}

glimpse(df_trends)

ggplot(df_trends)

Target Achievement

In preparation for the FY20Q1 POART, you want to assess different partners’ achievement for TX_NEW by sex in Neptune. You will want to show both the real results/targets as well as the percent achievement. Consider using different aesthetics to convey a message to your audience.

```{r achievement}

glimpse(df_achievement)

ggplot(df_achievement)

```