PlotDisparities.Rmd

---
title: "R Notebook"
output: html_notebook
---

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```{r}
plot(cars)
```

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```{r}
library(gdata)
library(ggpubr)
library(wesanderson)
```
```{r}
racial_data  = read.csv("~/Project/EquityInSentiment/race_data_with_scores.csv")
gender_data  = read.csv("~/Project/EquityInSentiment/gender_data_with_scores.csv")

```

Now plot the data
```{r}
ggboxplot(racial_data, y = "AWS.Score", x = "Race", palette = wes_palette("GrandBudapest2"),
          facet.by = "Emotion", color = "Race", add = "jitter",
          legend = "none", 
          title = "AWS scores Black names score angrier than European names.") +
   stat_compare_means(label.y.npc = 0.7) 
```
```{r}
ggboxplot(gender_data, y = "AWS.Score", x = "Gender", facet.by = "Emotion", color = "Gender", palette = wes_palette("GrandBudapest2"), add = "jitter", legend = "none", title = "AWS Comprehend scores men are angrier than women.") + stat_compare_means(label.y.npc = 0.7)
```
```{r}
ggboxplot(gender_data, y = "Google.Score", x = "Gender", facet.by = "Emotion", color = "Gender", palette = wes_palette("GrandBudapest2"), add = "jitter", legend = "none", title = "Google is balanced in scoring emotions by gender.") + stat_compare_means(label.y.npc = 0.1)
```

```{r}
ggboxplot(racial_data, y = "Google.Score", x = "Race", 
          facet.by = "Emotion", color = "Race", add = "jitter", 
          legend = "none", palette = wes_palette("GrandBudapest2"),
          title = "Google is slightly more balanced in scoring -- aside from sadness.") + stat_compare_means(label.y.npc = 0.1)

```
```{r}
names(wes_palettes)
```