Digging into my own collected brewing data with Rstudio and some tidyverse tools.

brew-data.Rmd

---
title: "Crunching Brew Data"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
library("dplyr")
library("ggplot2")
library("reshape2")

setwd("~")

# RE: reading CSV from Google Spreadsheets
# https://stackoverflow.com/questions/33713084/download-link-for-google-spreadsheets-csv-export-with-multiple-sheets

#
# BREW DATA
#
brew.data <- read.csv("https://docs.google.com/spreadsheets/d/1pIYEBEaHMjfSST8Nbwr6ehsT0njU_K0cgG9BKqV1EDM/gviz/tq?tqx=out:csv&sheet=BrewData") %>%
    # drop unused columns
    select(-starts_with("X.Br")) %>%
    # prices to numbers
    mutate_at(vars(X., X..12.oz.), ~as.numeric(sub("\\$", "", .))) %>%
    # percents to numbers
    mutate_at(vars(Brew.House.Efficiency, ABV..), ~as.numeric(sub("%", "", .))) %>%
    # dates-as-strings (...as factors) to dates
    mutate_at(vars(Brew.date, Packaged, Ready.date, Racked), ~as.Date(., format="%m/%d/%Y"))

#
# MASH DATA
#
mash.data <- read.csv("https://docs.google.com/spreadsheets/d/1NNg8FCR10g1T_B9z8Aeuy9oL9wZPJTelA22V79QCo98/gviz/tq?tqx=out:csv&sheet=offsets-applied") %>%
    # remove extraneous columns
    select_if(~!all(is.na(.))) %>%
    # dates!
    mutate_at(vars(Brew.Date), ~as.Date(., format="%m/%d/%Y"))

#
# YEAST DATA
#
yeast.data <- read.csv("https://docs.google.com/spreadsheets/d/1MbKuvXEQJGV58vjzOcdTAzcuB5o4JtNExPNzMKCamhI/gviz/tq?tqx=out:csv&sheet=individuals") %>%
    # remove extraneous columns
    select_if(~!all(is.na(.))) %>% select(-c(URL)) %>%
    # dates!
    mutate_at(vars(ends_with("Date")), ~as.Date(., format="%m/%d/%Y"))

#
# bubble-per-minute data
#
bpm.data <- read.csv("https://docs.google.com/spreadsheets/d/1pIYEBEaHMjfSST8Nbwr6ehsT0njU_K0cgG9BKqV1EDM/gviz/tq?tqx=out:csv&sheet=bubbles-per-minute%20data")
```

```{r target.vs.original.gravity}
ggplot(brew.data %>% filter(Brewed.as == "Tilde Gravitywerks"),
       aes(Target.Gravity, Original.Gravity)) +
  #geom_point(aes(color = Brewed.as)) +
  #labs(color="Brewed As") +
  geom_point() +
  ggtitle("Target vs. Actual Original Gravity") +
  scale_x_continuous(breaks = c(1.040, 1.050, 1.060, 1.070, 1.080, 1.090),
                     labels = c("1.040", "1.050", "1.060", "1.070", "1.080", "1.090")) +
  xlab("Target Original Gravity") +
  scale_y_continuous(breaks = c(1.040, 1.050, 1.060, 1.070, 1.080, 1.090, 1.100),
                     labels = c("1.040", "1.050", "1.060", "1.070", "1.080", "1.090", "1.100")) +
  ylab("Actual Original Gravity") +
  geom_smooth(method = "lm") +
  theme(legend.position = "bottom")
```

```{r price.over.time}
ggplot(brew.data, aes(Brew.date, X..12.oz.)) +
  geom_point(aes(color=Brewed.as)) +
  labs(color="Brewed As") +
  scale_y_continuous(breaks = c(0.5, 1, 1.5, 2, 2.5),
                     labels = c("$0.50", "$1.00", "$1.50", "$2.00", "$2.50")) +
  ylab("$/12 oz.") +
  scale_x_date() + xlab("Brew Date") +
  geom_smooth(method = "lm") +
  theme(legend.position = "bottom")
```


```{r abv.by.batch.size.over.time}
ggplot(brew.data, aes(Brew.date, ABV..)) +
  geom_point(aes(color=Brewed.as, size=Batch.Size.Packaged..gal..)) +
  guides(size = FALSE) +
  labs(color="Brewed As") +
  scale_y_continuous() +
  ylab("% ABV") +
  scale_x_date() + xlab("Brew Date") +
  geom_smooth(method = "lm") +
  theme(legend.position = "bottom")
```

```{r qt.lb.ratio.to.gravity.delta}
ggplot(mash.data, aes(qt..lb..ratio, Δ...0.003.)) +
  geom_point() +
  scale_y_continuous() +
  ylab("O.G. delta") +
  scale_x_continuous() +
  xlab("qt./lb.") +
  geom_smooth(method = "lm") +
  theme(legend.position = "bottom") +
  coord_cartesian(xlim=c(2,5), ylim=c(-0.03,0.03))
```

```{r yeast.obs.att.vs.starter.size}
ggplot(yeast.data, aes(Starter.Size..ml., Obs....Att.)) +
  geom_point(aes(color = Manufacturer), na.rm=TRUE) +
  scale_x_continuous() + xlab("Starter Size (ml)") +
  scale_y_continuous() + ylab("Observed % Apparent Attenuation") +
  geom_smooth(method = "lm", na.rm=TRUE) +
  coord_cartesian(xlim = c(500, 2000), ylim=c(60, 90))
```

```{r bpm.chart}
# trying - https://stackoverflow.com/questions/28775036/ggplot-line-graph-with-na-values
bpm.data2 <- melt(bpm.data, id.var="hours.after.pitching")
bpm.data2 <- na.omit(bpm.data2)

ggplot(bpm.data2, aes(x=hours.after.pitching, y=value, color=variable)) +
  geom_line() +
  theme(legend.position = "none")
  #geom_smooth(method = "rlm", na.rm = TRUE)
```

```{r srm.by.abv}
ggplot(brew.data, aes(SRM, ABV..)) +
  geom_point(na.rm=TRUE, aes(color=SRM)) +
  #scale_colour_gradient(low="#FEE287", high="#28060A")
  scale_colour_gradient(low="#FED265", high="#28060A") +
  ylab("% ABV")
```

```{r srm.by.ibu}
ggplot(brew.data, aes(ABV.., IBU)) +
  geom_point(na.rm=TRUE, aes(color=SRM)) +
  #scale_colour_gradient(low="#FEE287", high="#28060A")
  scale_colour_gradient(low="#FED265", high="#28060A") +
  xlab("% ABV") +
  geom_smooth(method = "lm")
```