flower_analysis.Rmd

---
title: "Initial Analysis of White Sage Data"
author: "Xingyao Chen"
date: "6/20/2017"
output:
  html_document: default
  pdf_document: default
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
knitr::opts_chunk$set(cache = TRUE)
# install.packages('gsheet')
# install.packages("ggplot2")
# install.packages("reshape2")
#install.packages("devtools")
#install_github("ggobi/ggally")
library(devtools)
library(ggplot2)
library(GGally)
library(reshape2)
library(gsheet)
```

## Load in the clean dataset
```{r}
setwd('~/bee/')
mydat_small=read.csv('pollinator_visitation_fullData.csv')
```

##Plot Honeybees vs. Explainatory variable, with groupings
```{r}
ggplot(mydat_small, aes(x=Total.inflorescenses, y=Honeybees, color=Size, group=Pair))+
  geom_line(color='gray')+
  geom_point()+
  facet_wrap(~Date)+
  theme_bw()

ggplot(mydat_small, aes(x=Avg.open.flowers.per.inflorescence, y=Honeybees, color=Size, group=Pair))+
  geom_line(color='gray')+
  geom_point()+
  facet_wrap(~Date)+
  theme_bw()

ggplot(mydat_small, aes(x=Total.Flowers, y=Honeybees, color=Size, group=Pair))+
  geom_line(color='gray')+
  geom_point()+
  facet_wrap(~Date)+
  labs(x="Total Flowers")+
  theme_bw()

ggplot(mydat_small, aes(x=Sugar_conc, y=Honeybees, group=Pair, color=Size))+
  geom_point()+
  geom_line(color='gray')+
  facet_wrap(~Date)+
  theme_bw()

ggplot(mydat_small, aes(x=Sugar_content, y=Honeybees, group=Pair, color=Size))+
  geom_point()+
  geom_line(color='gray')+
  facet_wrap(~Date)+
  theme_bw()

ggplot(mydat_small, aes(x=Volume, y=Honeybees, group=Pair, color=Size))+
  geom_point()+
  geom_line(color='gray')+
  facet_wrap(~Date)+
  theme_bw()
```

#Load in the raw nectar data from Gdrive
```{r}
url='docs.google.com/spreadsheets/d/1LKr8Ken8p1jpTGpbn2a_napP6uNJ4sEnN8gdDSEQGxY/edit#gid=212997740'
nect=read.csv(text=gsheet2text(url, format='csv'))
head(nect)
size=strsplit(as.character(nect$Location), ' ')
df=as.data.frame(t(matrix(unlist(size), 3)))
names(df)=c('non', 'Pair', 'Size')
nect=cbind(nect, df[,2:3])
nect$sugar.concentration=as.numeric(as.character(nect$sugar.concentration))
nect$sugar.content..µg.=as.numeric(as.character(nect$sugar.content..µg.))
#Clean up outliers
nect=nect[which(nect$sugar.concentration<1.9),]
zeros=which(nect$sugar.concentration==0)
nect=nect[-zeros, ]
```

#Make some boxplots
```{r}
ggplot(nect, aes(y=sugar.concentration, x=Pair, fill=Size))+
  geom_boxplot()+
  facet_wrap(~Date)+
  theme_bw()

ggplot(nect, aes(y=sugar.content..µg., x=Pair, fill=Size))+
  geom_boxplot()+
  facet_wrap(~Date)+
  theme_bw()


ggplot(nect, aes(y=volume.of.nectar..µl., x=Pair, fill=Size))+
  geom_boxplot()+
  facet_wrap(~Date)+
  theme_bw()
```