.Rhistory

library(dplyr)
library(tidyr)
library(ggplot2)
library(vioplot)
library(corrplot)
library(gmodels)
library(matrixStats)
PSDS_PATH <- file.path(dirname(dirname(getwd())))
PSDS_PATH
PSDS_PATH = getwd()
state <- read.csv(file.path(PSDS_PATH, 'data', 'state.csv'))
dfw <- read.csv(file.path(PSDS_PATH, 'data', 'dfw_airline.csv'))
sp500_px <- read.csv(file.path(PSDS_PATH, 'data', 'sp500_data.csv.gz'), row.names=1)
sp500_sym <- read.csv(file.path(PSDS_PATH, 'data', 'sp500_sectors.csv'), stringsAsFactors = FALSE)
kc_tax <- read.csv(file.path(PSDS_PATH, 'data', 'kc_tax.csv.gz'))
lc_loans <- read.csv(file.path(PSDS_PATH, 'data', 'lc_loans.csv'))
airline_stats <- read.csv(file.path(PSDS_PATH, 'data', 'airline_stats.csv'), stringsAsFactors = FALSE)
airline_stats$airline <- ordered(airline_stats$airline,
levels=c('Alaska', 'American', 'Jet Blue', 'Delta', 'United', 'Southwest'))
graph <- ggplot(kc_tax0, (aes(x=SqFtTotLiving, y=TaxAssessedValue))) +
stat_binhex(color='white') +
theme_bw() +
scale_fill_gradient(low='white', high='blue') +
scale_y_continuous(labels = function(x) format(x, scientific = FALSE)) +
labs(x='Finished Square Feet', y='Tax-Assessed Value')
kc_tax0 <- subset(kc_tax, TaxAssessedValue < 750000 &
SqFtTotLiving > 100 &
SqFtTotLiving < 3500)
nrow(kc_tax0)
graph <- ggplot(kc_tax0, (aes(x=SqFtTotLiving, y=TaxAssessedValue))) +
stat_binhex(color='white') +
theme_bw() +
scale_fill_gradient(low='white', high='blue') +
scale_y_continuous(labels = function(x) format(x, scientific = FALSE)) +
labs(x='Finished Square Feet', y='Tax-Assessed Value')
graph
graph <- ggplot(kc_tax0, (aes(x=SqFtTotLiving, y=TaxAssessedValue))) +
stat_binhex(color='white')
graph
graph + scale_fill_gradient(low='white', high='blue')
graph <- ggplot(kc_tax0, (aes(x=SqFtTotLiving, y=TaxAssessedValue))) +
stat_binhex()
graph
ggplot(kc_tax0, (aes(x=SqFtTotLiving, y=TaxAssessedValue))) +
stat_binhex(color='white') +
# theme_bw() +
scale_fill_gradient(low='white', high='blue')