<jupyter_start><jupyter_text>R Code pulled from https://www.statmethods.net/advgraphs/ggplot2.html<jupyter_code># ggplot2 examples
library(ggplot2) 
# create factors with value labels 
mtcars$gear <- factor(mtcars$gear,levels=c(3,4,5),
  	labels=c("3gears","4gears","5gears")) 
mtcars$am <- factor(mtcars$am,levels=c(0,1),
  	labels=c("Automatic","Manual")) 
mtcars$cyl <- factor(mtcars$cyl,levels=c(4,6,8),
   labels=c("4cyl","6cyl","8cyl")) 
# Kernel density plots for mpg
# grouped by number of gears (indicated by color)
qplot(mpg, data=mtcars, geom="density", fill=gear, alpha=I(.5), 
   main="Distribution of Gas Milage", xlab="Miles Per Gallon", 
   ylab="Density")
# Scatterplot of mpg vs. hp for each combination of gears and cylinders
# in each facet, transmittion type is represented by shape and color
qplot(hp, mpg, data=mtcars, shape=am, color=am, 
   facets=gear~cyl, size=I(3),
   xlab="Horsepower", ylab="Miles per Gallon") 
# Separate regressions of mpg on weight for each number of cylinders
qplot(wt, mpg, data=mtcars, geom=c("point", "smooth"), 
   method="lm", formula=y~x, color=cyl, 
   main="Regression of MPG on Weight", 
   xlab="Weight", ylab="Miles per Gallon")
# Boxplots of mpg by number of gears 
# observations (points) are overlayed and jittered
qplot(gear, mpg, data=mtcars, geom=c("boxplot", "jitter"), 
   fill=gear, main="Mileage by Gear Number",
   xlab="", ylab="Miles per Gallon")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14955203308063406, 'fraction_numerical': 0.013094417643004824, 'mean_word_length': 5.914285714285715, 'pattern_counts': {'":': 0, '<': 8, '<?xml version=': 0, '>': 5, 'https://': 1, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '215509', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 583, 'n_tokens_neox': 529, 'n_words': 137, 'path': 'index.ipynb', 'repo_name': 'epifanio/fmars.2020.496688', 'size': '1451'}