Predict traffic from count of cars.

A friend recently shared a data set that got a count of cars coming in on specific roads at specific times. I wanted to predict the count of cars on future dates basing on the small data set that was shared. Apparently using times series we can forecast this. 

Feel free to follow along the steps to achieve this with basic packages xts() and forecast. This is my initial stab at this but i'm sure there are better models to use around this. I'll follow up with better models soon. 

       
# Simple script to use
# Default ts() package to forecast traffic count. 
# Dataset: traffic_data.csv

# Author: 'Richard Ngamta', 'ngamita@gmail.com'

# check for directory, else create one. 
if(!file('traffic')){
  #print('hello')
  dir.create('traffic')
}

# Load the forecasting and time series packages. 
require(forecast)
require(xts)

# Set wd to 'traffic'
setwd('traffic/')

# Download the traffic_data.csv from dropbox.
fileUrl <- 'https://www.dropbox.com/s/cbufz4f0rd11tl1/traffic_data.csv'
download.file(fileUrl, destfile='traffic_data.csv', method='wget') # Use method='curl' non *nix 

# Load data into R memory/data frame. df == data frame, csv and got a header. 
traffic_df <- read.csv('traffic_data.csv', sep=',', header=TRUE)

# Check if loaded fine. 
head(traffic_df)

# Format the date, to R readable date and
# not Char strings.
traffic_df$datetime = as.Date(traffic_df$datetime,format="%Y-%m-%d")

# Convert to xts
traffic_df_xts = xts(x=traffic_df$count, order.by=traffic_df$datetime)

# We need to get a start date from data, i got (68)
# How did i do that. Check next
# > head(traffic_df)
# > as.POSIXlt(i = "2014-03-10", origin="2014-03-10")$yday
##    [1] 68
# Add one since that starts at "0" and convert to normal ts()
traffic_df_ts = ts(traffic_df_xts, freq=365, start=c(2014, 68))
png('Traffic_forecast.png')
plot(forecast(ets(traffic_df_ts), 1), main="Traffic Forecast")
dev.off()


# Ignore the frequenxy warnings.
# Check the downloaded plot in same folder/dir. 
# Note from graphs that 2014.4 means "day number 365 * 0.4" (day 146 in the year).
# So actual date is run > as.Date(146, origin="2014-03-10")
# Answer: "2014-08-03"
# This is just the default method, using othee methods lile ARIMA, works better.