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Taxi_Data_Linear_Regression.R
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Taxi_Data_Linear_Regression.R
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# set your own working directory. This is mine.
# setwd("SET THE Working Director to THE PATH TO THIS DIRECTORY")
# get the Taxi dataset from
# http://www.nyc.gov/html/tlc/html/about/trip_record_data.shtml
# Be carefull because the data files are large.
# green taxi data is smaller than yellow taxis.
# For example this one https://s3.amazonaws.com/nyc-tlc/trip+data/green_tripdata_2017-01.csv
taxi <- read.csv("./Datasets/green_tripdata_2017-01.csv")
head(taxi, n=4)
# plot(taxi$total_amount~taxi$trip_distance)
# filter the taxi data
# we want to have only trip records that the total amoint is between 15 and 50 dollar
# and trip distance is
taxi<-taxi[ which(taxi$fare_amount > 5 & taxi$fare_amount < 50 & taxi$trip_distance > 5 & taxi$trip_distance < 20), ]
# taxi<-taxi[taxi$total_amount < 200, ]
# taxi<-taxi[taxi$trip_distance > 5, ]
# taxi<-taxi[taxi$trip_distance < 50, ]
# && taxi$fare_amount<200 && taxi$trip_distance > 50 && taxi$trip_distance<50
# find the correlation
cor(taxi$fare_amount , taxi$trip_distance)
# plot the scatterplot
plot(taxi$fare_amount~taxi$trip_distance)
my.model<-lm(taxi$fare_amount~taxi$trip_distance)
print(my.model)
abline(my.model, col="blue")