Final_Project.Rmd

---
title: "Stats 133 Final Project Code"
author: "Siyao Ma, Dannver Wu, Sudeshna Barman"
date: ""
output: 
  html_document:
    fig_height: 3
    fig_width: 5
---
<!-- Don't edit in between this line and the one below -->
```{r include=FALSE}
# Don't delete this chunk if you are using the DataComputing package
library(DataComputing)
```
*Source file* 
```{r, results='asis', echo=FALSE}
includeSourceDocuments()
```
<!-- Don't edit the material above this line -->


**Downloading and Formatting the Data**
```{r}
#2009

#yellow taxi data 12/2009
y09_12 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-12_clean.csv')

#yellow taxi data 11/2009
y09_11 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-11_clean.csv')

#yellow taxi data 10/2009
y09_10 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-10_clean.csv')

#yellow taxi data 09/2009
y09_09 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-09_clean.csv')

#yellow taxi data 08/2009
y09_08 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-08_clean.csv')

#yellow taxi data 07/2009
y09_07 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-07_clean.csv')

#yellow taxi data 06/2009
y09_06 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-06_clean.csv')

#yellow taxi data 05/2009
y09_05 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-05_clean.csv')

#yellow taxi data 04/2009
y09_04 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-04_clean.csv')

#yellow taxi data 03/2009
y09_03 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-03_clean.csv')

#yellow taxi data 02/2009
y09_02 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-02_clean.csv')

#yellow taxi data 01/2009
y09_01 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2009-01_clean.csv')


y09 <- rbind(y09_12, y09_11, y09_10, y09_09, y09_08, y09_07, y09_06, y09_05, y09_04, y09_03, y09_02, y09_01)

y09 <- y09 %>%
  mutate(year = 2009) %>%
  mutate(month = lubridate::month(p_time)) %>%
  mutate(yday = lubridate::yday(p_time)) %>%
  mutate(mday = lubridate::mday(p_time)) %>%
  mutate(weekday = lubridate::wday(p_time)) %>%
  mutate(hour = str_sub(p_time, -9, -7))
```


```{r}
#2010

#yellow taxi data 12/2010
y10_12 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-12_clean.csv')

#yellow taxi data 11/2010
y10_11 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-11_clean.csv')

#yellow taxi data 10/2010
y10_10 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-10_clean.csv')

#yellow taxi data 09/2010
y10_09 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-09_clean.csv')

#yellow taxi data 08/2010
y10_08 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-08_clean.csv')

#yellow taxi data 07/2010
y10_07 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-07_clean.csv')

#yellow taxi data 06/2010
y10_06 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-06_clean.csv')

#yellow taxi data 05/2010
y10_05 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-05_clean.csv')

#yellow taxi data 04/2010
y10_04 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-04_clean.csv')

#yellow taxi data 03/2010
y10_03 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-03_clean.csv')

#yellow taxi data 02/2010
y10_02 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-02_clean.csv')

#yellow taxi data 01/2010
y10_01 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2010-01_clean.csv')

y10 <- rbind(y10_12, y10_11, y10_10, y10_09, y10_08, y10_07, y10_06, y10_05, y10_04, y10_03, y10_02, y10_01)

y10 <- y10 %>%
  mutate(year = 2010) %>%
  mutate(month = lubridate::month(p_time)) %>%
  mutate(yday = lubridate::yday(p_time)) %>%
  mutate(mday = lubridate::mday(p_time)) %>%
  mutate(weekday = lubridate::wday(p_time)) %>%
  mutate(hour = str_sub(p_time, -9, -7))
```


```{r}
#2011

#yellow taxi data 12/2011
y11_12 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-12_clean.csv')

#yellow taxi data 11/2011
y11_11 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-11_clean.csv')

#yellow taxi data 10/2011
y11_10 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-10_clean.csv')

#yellow taxi data 09/2011
y11_09 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-09_clean.csv')

#yellow taxi data 08/2011
y11_08 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-08_clean.csv')

#yellow taxi data 07/2011
y11_07 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-07_clean.csv')

#yellow taxi data 06/2011
y11_06 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-06_clean.csv')

#yellow taxi data 05/2011
y11_05 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-05_clean.csv')

#yellow taxi data 04/2011
y11_04 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-04_clean.csv')

#yellow taxi data 03/2011
y11_03 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-03_clean.csv')

#yellow taxi data 02/2011
y11_02 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-02_clean.csv')

#yellow taxi data 01/2011
y11_01 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2011-01_clean.csv')

y11 <- rbind(y11_12, y11_11, y11_10, y11_09, y11_08, y11_07, y11_06, y11_05, y11_04, y11_03, y11_02, y11_01)

y11 <- y11 %>%
  mutate(year = 2011) %>%
  mutate(month = lubridate::month(p_time)) %>%
  mutate(yday = lubridate::yday(p_time)) %>%
  mutate(mday = lubridate::mday(p_time)) %>%
  mutate(weekday = lubridate::wday(p_time)) %>%
  mutate(hour = str_sub(p_time, -9, -7))
```


```{r}
#2012

#yellow taxi data 12/2012
y12_12 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-12_clean.csv')

#yellow taxi data 11/2012
y12_11 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-11_clean.csv')

#yellow taxi data 10/2012
y12_10 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-10_clean.csv')

#yellow taxi data 09/2012
y12_09 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-09_clean.csv')

#yellow taxi data 08/2012
y12_08 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-08_clean.csv')

#yellow taxi data 07/2012
y12_07 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-07_clean.csv')

#yellow taxi data 06/2012
y12_06 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-06_clean.csv')

#yellow taxi data 05/2012
y12_05 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-05_clean.csv')

#yellow taxi data 04/2012
y12_04 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-04_clean.csv')

#yellow taxi data 03/2012
y12_03 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-03_clean.csv')

#yellow taxi data 02/2012
y12_02 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-02_clean.csv')

#yellow taxi data 01/2012
y12_01 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2012-01_clean.csv')

y12 <- rbind(y12_12, y12_11, y12_10, y12_09, y12_08, y12_07, y12_06, y12_05, y12_04, y12_03, y12_02, y12_01)

y12 <- y12 %>%
  mutate(year = 2012) %>%
  mutate(month = lubridate::month(p_time)) %>%
  mutate(yday = lubridate::yday(p_time)) %>%
  mutate(mday = lubridate::mday(p_time)) %>%
  mutate(weekday = lubridate::wday(p_time)) %>%
  mutate(hour = str_sub(p_time, -9, -7))
```


```{r}
#2013

#yellow taxi data 12/2013
y13_12 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-12_clean.csv')

#yellow taxi data 11/2013
y13_11 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-11_clean.csv')

#yellow taxi data 10/2013
y13_10 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-10_clean.csv')

#yellow taxi data 09/2013
y13_09 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-09_clean.csv')

#yellow taxi data 08/2013
y13_08 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-08_clean.csv')

#yellow taxi data 07/2013
y13_07 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-07_clean.csv')

#yellow taxi data 06/2013
y13_06 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-06_clean.csv')

#yellow taxi data 05/2013
y13_05 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-05_clean.csv')

#yellow taxi data 04/2013
y13_04 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-04_clean.csv')

#yellow taxi data 03/2013
y13_03 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-03_clean.csv')

#yellow taxi data 02/2013
y13_02 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-02_clean.csv')

#yellow taxi data 01/2013
y13_01 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2013-01_clean.csv')

y13 <- rbind(y13_12, y13_11, y13_10, y13_09, y13_08, y13_07, y13_06, y13_05, y13_04, y13_03, y13_02, y13_01)

y13 <- y13 %>%
  mutate(year = 2013) %>%
  mutate(month = lubridate::month(p_time)) %>%
  mutate(yday = lubridate::yday(p_time)) %>%
  mutate(mday = lubridate::mday(p_time)) %>%
  mutate(weekday = lubridate::wday(p_time)) %>%
  mutate(hour = str_sub(p_time, -9, -7))
```

```{r}
#2014

#yellow taxi data 12/2014
y14_12 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-12_clean.csv')

#yellow taxi data 11/2014
y14_11 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-11_clean.csv')

#yellow taxi data 10/2014
y14_10 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-10_clean.csv')

#yellow taxi data 09/2014
y14_09 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-09_clean.csv')

#yellow taxi data 08/2014
y14_08 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-08_clean.csv')

#yellow taxi data 07/2014
y14_07 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-07_clean.csv')

#yellow taxi data 06/2014
y14_06 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-06_clean.csv')

#yellow taxi data 05/2014
y14_05 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-05_clean.csv')

#yellow taxi data 04/2014
y14_04 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-04_clean.csv')

#yellow taxi data 03/2014
y14_03 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-03_clean.csv')

#yellow taxi data 02/2014
y14_02 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-02_clean.csv')

#yellow taxi data 01/2014
y14_01 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2014-01_clean.csv')

y14 <- rbind(y14_12, y14_11, y14_10, y14_09, y14_08, y14_07, y14_06, y14_05, y14_04, y14_03, y14_02, y14_01)

y14 <- y14 %>%
  mutate(year = 2014) %>%
  mutate(month = lubridate::month(p_time)) %>%
  mutate(yday = lubridate::yday(p_time)) %>%
  mutate(mday = lubridate::mday(p_time)) %>%
  mutate(weekday = lubridate::wday(p_time)) %>%
  mutate(hour = str_sub(p_time, -9, -7))
```


```{r}
#yellow taxi data 12/2015
y15_12 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-12_clean.csv')

#yellow taxi data 11/2015
y15_11 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-11_clean.csv')

#yellow taxi data 10/2015
y15_10 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-10_clean.csv')

#yellow taxi data 09/2015
y15_09 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-09_clean.csv')

#yellow taxi data 08/2015
y15_08 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-08_clean.csv')

#yellow taxi data 07/2015
y15_07 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-07_clean.csv')

#yellow taxi data 06/2015
y15_06 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-06_clean.csv')

#yellow taxi data 05/2015
y15_05 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-05_clean.csv') 

#yellow taxi data 04/2015
y15_04 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-04_clean.csv') 

#yellow taxi data 03/2015
y15_03 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-03_clean.csv') 

#yellow taxi data 02/2015
y15_02 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-02_clean.csv') 

#yellow taxi data 01/2015
y15_01 <- read.csv('/Users/siyaoma/Desktop/Stats133 Project/Stat133-Final/taxi_data/yellow_tripdata_2015-01_clean.csv') 

y15 <- rbind(y15_12, y15_11, y15_10, y15_09, y15_08, y15_07, y15_06, y15_05, y15_04, y15_03, y15_02, y15_01)

y15 <- y15 %>%
  mutate(year = 2015) %>%
  mutate(month = lubridate::month(p_time)) %>%
  mutate(yday = lubridate::yday(p_time)) %>%
  mutate(mday = lubridate::mday(p_time)) %>%
  mutate(weekday = lubridate::wday(p_time)) %>%
  mutate(hour = str_sub(p_time, -9, -7))
```

```{r}
tot <- Reduce(function(x, y) merge(x, y, all=TRUE), list(y15, y14, y13, y12, y11, y10, y09))
```

**OUTLIERS FILTERED OUT FOR ALL SUBSEQUENT GRAPHS**
```{r}
tot <- tot %>%
  filter(distance < 50, total > 0, total < 100) 
```

**Fares**
```{r}
#total amount paid (including surchage, tolls, etc) v. distance traveled

tot %>% #all years
  ggplot(aes(y = total, x = distance)) +
  geom_point() +
  geom_smooth(se = FALSE) +
  ggtitle("Amount v. Distance - All Years")

tot %>% #faceted by year
  ggplot(aes(y = total, x = distance)) +
  geom_point() +
  geom_smooth(se = FALSE) +
  facet_wrap(~ year) +
  ggtitle("Amount v. Distance - Yearly")

tot %>% #faceted by month
  ggplot(aes(y = total, x = distance)) +
  geom_point() +
  geom_smooth(se = FALSE) +
  facet_wrap(~ month) +
  ggtitle("Amount v. Distance - Monthly")
```

```{r}
#average fare by month
tot_month_ave_fare <- tot %>%
  group_by(month)%>%
  summarize(ave=mean(total))

tot_month_ave_fare %>%
  ggplot(aes(x=month, y=ave)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks=seq(1,12,1)) + 
  ggtitle("Average Fare v. Month")

#average fare by day of the week
tot_day_ave_fare <- tot %>%
  group_by(weekday)%>%
  summarize(ave=mean(total))
  
tot_day_ave_fare %>%
  ggplot(aes(x=weekday, y=ave)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks=seq(1,7,1)) + 
  ggtitle("Average Fare v. Day")

tot_day_ave_fare %>%
  ggplot(aes(x=weekday, y=ave)) +
  geom_bar(stat ="identity") +
  scale_x_continuous(breaks=seq(1,7,1)) + 
  ggtitle("Average Fare v. Day")

#average fare by time of day
tot_hour_ave_fare <- tot %>%
  group_by(hour) %>%
  summarize(ave=mean(total))

tot_hour_ave_fare %>%
  ggplot(aes(x=hour, y=ave)) +
  geom_point() +
  geom_line() +
  ggtitle("Average Fare v. Hour")

tot_hour_ave_fare %>%
  ggplot(aes(x=hour, y=ave)) +
  geom_bar(stat ="identity") + 
  ggtitle("Average Fare v. Hour")
```

**Trip Length**
```{r}
#average trip length by month
tot_month_ave_dist <- tot %>%
  filter(distance > 0, distance < 50) %>%
  group_by(month)%>%
  summarize(ave=mean(distance))

tot_month_ave_dist %>%
  ggplot(aes(x=month, y=ave)) +
  geom_point() +
  geom_line() + 
  scale_x_continuous(breaks=seq(1,12,1)) + 
  ggtitle("Average Trip Length v. Month")

tot_month_ave_dist %>%
  ggplot(aes(x=month, y=ave)) +
  geom_bar(stat ="identity") + 
  scale_x_continuous(breaks=seq(1,12,1)) + 
  ggtitle("Average Trip Length v. Month")

#average trip length by day of the week
tot_day_ave_dist <- tot %>%
  filter(distance > 0, distance < 50) %>%
  group_by(weekday)%>%
  summarize(ave=mean(distance))

tot_day_ave_dist %>%
  ggplot(aes(x=weekday, y=ave)) +
  geom_point() +
  geom_line() +
  scale_x_continuous(breaks=seq(1,7,1)) + 
  ggtitle("Average Trip Length v. Day")

tot_day_ave_dist %>%
  ggplot(aes(x=weekday, y=ave)) +
  geom_bar(stat ="identity") + 
  scale_x_continuous(breaks=seq(1,7,1)) + 
  ggtitle("Average Trip Length v. Day")

#average trip length by time of day
tot_hour_ave_dist <- tot %>%
  filter(distance > 0, distance < 50) %>%
  group_by(hour) %>%
  summarize(ave=mean(distance))

tot_hour_ave_dist %>%
  ggplot(aes(x=hour, y=ave)) +
  geom_point() +
  geom_line() + 
  ggtitle("Average Trip Length v. Hour")

tot_hour_ave_dist %>%
  ggplot(aes(x=hour, y=ave)) +
  geom_bar(stat ="identity") + 
  ggtitle("Average Trip Length v. Hour")
```

**Number of Trips**
```{r}
#total number of taxi rides for each day of the year
tot_year <- tot %>%
  group_by(yday) %>%
  summarise(tot = n())

tot_year %>%
  ggplot(aes(y = tot, x = yday, col = yday)) +
  geom_bar(stat ="identity") + 
  ggtitle("Number of Trips v. Day of Year")

tot_year %>%
  ggplot(aes(y = tot, x = yday, col = yday)) +
  geom_line() + 
  ggtitle("Number of Trips v. Day of Year")

#total number of taxi rides per month
tot_month <- tot %>%
  group_by(mday) %>%
  summarise(tot = n()) 

tot_month %>%
  ggplot(aes(y = tot, x = mday, col = mday)) +
  geom_bar(stat ="identity") +
  scale_x_continuous(breaks=seq(1,12,1)) + 
  ggtitle("Number of Trips v. Month")

#total number of taxi rides for each day of week
tot_day <- tot %>%
  group_by(weekday) %>%
  summarise(tot = n())

tot_day %>%
  ggplot(aes(y = tot, x = weekday, col = weekday)) +
  geom_bar(stat ="identity") +
  scale_x_continuous(breaks=seq(1,7,1)) + 
  ggtitle("Number of Trips v. Day of Week")

#total number of taxi rides for each day of the week (normalized)
total <- sum(tot_day$tot)
tot_day_ave <- tot_day %>%
  mutate(ave = tot_day$tot/total)

tot_day_ave %>%
  ggplot(aes(y = ave, x = weekday)) +
  geom_bar(stat ="identity") +
  scale_x_continuous(breaks=seq(1,7,1)) + 
  ggtitle("Number of Trips v. Day of Week - Normalized")

#total number of taxi rides per hour
tot_hour <- tot %>%
  group_by(hour, weekday) %>%
  summarise(tot = n())

tot_hour %>%
  ggplot(aes(y = tot, x = hour, fill = weekday)) +
  geom_bar(stat ="identity") + 
  ggtitle("Number of Trips v. Hour")

#total number of taxi rides per hour (normalized) 
tot_hour_ave <- tot %>%
  group_by(hour) %>%
  summarise(tot = n()) %>%
  mutate(ave = tot/sum(tot))

tot_hour_ave %>%
  ggplot(aes(y = ave, x = hour)) +
  geom_bar(stat ="identity") + 
  ggtitle("Number of Trips v. Hour - Normalized")
```

**Number of Passengers**
```{r}
#number of passengers per day of year
tot_passengers_year <- tot %>%
  group_by(yday) %>%
  summarize(tot = sum(num_passengers))
  
tot_passengers_year %>%
  ggplot(aes(x = yday, y = tot)) +
  geom_bar(stat ="identity") + 
  ggtitle("Number of Passengers v. Day of Year")

#number of passengers per month
tot_passengers_month <- tot %>%
  group_by(month) %>%
  summarize(tot = sum(num_passengers))
  
tot_passengers_month %>%
  ggplot(aes(x = month, y = tot)) +
  geom_bar(stat ="identity") + 
  scale_x_continuous(breaks=seq(1,12,1)) + 
  ggtitle("Number of Passengers v. Month")

#number of passengers per weekday
tot_passengers_day <- tot %>%
  group_by(weekday) %>%
  summarize(tot = sum(num_passengers))
  
tot_passengers_day %>%
  ggplot(aes(x = weekday, y = tot)) +
  geom_bar(stat ="identity") + 
  scale_x_continuous(breaks=seq(1,7,1)) + 
  ggtitle("Number of Passengers v. Day of Week")

#number of passengers per hour
tot_passengers_hour <- tot %>%
  group_by(hour) %>%
  summarize(tot = sum(num_passengers))
  
tot_passengers_hour %>%
  ggplot(aes(x = hour, y = tot)) +
  geom_bar(stat ="identity") + 
  ggtitle("Number of Passengers v. Hour")
```  

**KML**
```{r}
#Filter and isolate lat and long coordinates

y15 <- y15 %>%
  filter(p_lat != 0, p_long !=0, !is.na(p_lat), !is.na(p_long))

lat15 <- y15 %>%
  select(p_lat)
lat15 <- lat15[, 1]

long15 <- y15 %>%
  select(p_long)
long15 <- long15[, 1]

y14 <- y14 %>%
  filter(p_lat != 0, p_long !=0, !is.na(p_lat), !is.na(p_long))

lat14 <- y14 %>%
  select(p_lat)
lat14 <- lat14[, 1]

long14 <- y14 %>%
  select(p_long)
long14 <- long14[, 1]

y13 <- y13 %>%
  filter(p_lat != 0, p_long !=0, !is.na(p_lat), !is.na(p_long))

lat13 <- y13 %>%
  select(p_lat)
lat13 <- lat13[, 1]

long13 <- y13 %>%
  select(p_long)
long13 <- long13[, 1]

y12 <- y12 %>%
  filter(p_lat != 0, p_long !=0, !is.na(p_lat), !is.na(p_long))

lat12 <- y12 %>%
  select(p_lat)
lat12 <- lat12[, 1]

long12 <- y12 %>%
  select(p_long)
long12 <- long12[, 1]

y11 <- y11 %>%
  filter(p_lat != 0, p_long !=0, !is.na(p_lat), !is.na(p_long))

lat11 <- y11 %>%
  select(p_lat)
lat11 <- lat11[, 1]

long11 <- y11 %>%
  select(p_long)
long11 <- long11[, 1]

y10 <- y10 %>%
  filter(p_lat != 0, p_long !=0, !is.na(p_lat), !is.na(p_long))

lat10 <- y10 %>%
  select(p_lat)
lat10 <- lat10[, 1]

long10 <- y10 %>%
  select(p_long)
long10 <- long10[, 1]

y09 <- y09 %>%
  filter(p_lat != 0, p_long !=0, !is.na(p_lat), !is.na(p_long))

lat09 <- y09 %>%
  select(p_lat)
lat09 <- lat09[, 1]

long09 <- y09 %>%
  select(p_long)
long09 <- long09[, 1]
```

```{r}
#Rondomly sample 100 rides from each year
rand <- sample(1:240000, 100, replace=F) 

library(XML)
doc <- newXMLDoc()
root <- newXMLNode(name = "kml", namespaceDefinitions = "http://www.opengis.net/kml/2.2", doc = doc)
d <- newXMLNode(name = "Document", parent = root)
nm <- newXMLNode(name = "name", "Taxi", parent = d)
description <- newXMLNode(name = "description", "Taxi Rides in  NYC, 2009-2015", parent = d)

datetime <- as.character(y15$p_time) 
datetime <- gsub("/", "-", datetime)
datetime <- gsub(" ", "T", datetime)
datetime <- gsub("$", "Z", datetime)

for (i in rand){
  pm <- newXMLNode(name = "Placemark", parent = d)
  p <- newXMLNode(name = "Point", parent = pm)
  coor <- newXMLNode(name = "coordinates", c(lat15[i],",", long15[i]), parent = p)
  ts <- newXMLNode(name = "TimeStamp", parent = pm)
  when <- newXMLNode("when", datetime[i], parent = ts)
}

datetime <- as.character(y14$p_time) 
datetime <- gsub("/", "-", datetime)
datetime <- gsub(" ", "T", datetime)
datetime <- gsub("$", "Z", datetime)

for (i in rand){
  pm <- newXMLNode(name = "Placemark", parent = d)
  p <- newXMLNode(name = "Point", parent = pm)
  coor <- newXMLNode(name = "coordinates", c(lat14[i],",", long14[i]), parent = p)
  ts <- newXMLNode(name = "TimeStamp", parent = pm)
  when <- newXMLNode("when", datetime[i], parent = ts)
}

datetime <- as.character(y13$p_time) 
datetime <- gsub("/", "-", datetime)
datetime <- gsub(" ", "T", datetime)
datetime <- gsub("$", "Z", datetime)

for (i in rand){
  pm <- newXMLNode(name = "Placemark", parent = d)
  p <- newXMLNode(name = "Point", parent = pm)
  coor <- newXMLNode(name = "coordinates", c(lat13[i],",", long13[i]), parent = p)
  ts <- newXMLNode(name = "TimeStamp", parent = pm)
  when <- newXMLNode("when", datetime[i], parent = ts)
}

datetime <- as.character(y12$p_time) 
datetime <- gsub("/", "-", datetime)
datetime <- gsub(" ", "T", datetime)
datetime <- gsub("$", "Z", datetime)

for (i in rand){
  pm <- newXMLNode(name = "Placemark", parent = d)
  p <- newXMLNode(name = "Point", parent = pm)
  coor <- newXMLNode(name = "coordinates", c(lat12[i],",", long12[i]), parent = p)
  ts <- newXMLNode(name = "TimeStamp", parent = pm)
  when <- newXMLNode("when", datetime[i], parent = ts)
}

datetime <- as.character(y11$p_time) 
datetime <- gsub("/", "-", datetime)
datetime <- gsub(" ", "T", datetime)
datetime <- gsub("$", "Z", datetime)

for (i in rand){
  pm <- newXMLNode(name = "Placemark", parent = d)
  p <- newXMLNode(name = "Point", parent = pm)
  coor <- newXMLNode(name = "coordinates", c(lat11[i],",", long11[i]), parent = p)
  ts <- newXMLNode(name = "TimeStamp", parent = pm)
  when <- newXMLNode("when", datetime[i], parent = ts)
}

datetime <- as.character(y10$p_time) 
datetime <- gsub("/", "-", datetime)
datetime <- gsub(" ", "T", datetime)
datetime <- gsub("$", "Z", datetime)

for (i in rand){
  pm <- newXMLNode(name = "Placemark", parent = d)
  p <- newXMLNode(name = "Point", parent = pm)
  coor <- newXMLNode(name = "coordinates", c(lat10[i],",", long10[i]), parent = p)
  ts <- newXMLNode(name = "TimeStamp", parent = pm)
  when <- newXMLNode("when", datetime[i], parent = ts)
}

datetime <- as.character(y09$p_time) 
datetime <- gsub("/", "-", datetime)
datetime <- gsub(" ", "T", datetime)
datetime <- gsub("$", "Z", datetime)

for (i in rand){
  pm <- newXMLNode(name = "Placemark", parent = d)
  p <- newXMLNode(name = "Point", parent = pm)
  coor <- newXMLNode(name = "coordinates", c(lat09[i],",", long09[i]), parent = p)
  ts <- newXMLNode(name = "TimeStamp", parent = pm)
  when <- newXMLNode("when", datetime[i], parent = ts)
}
saveXML(doc, "/Users/siyaoma/Desktop/taxi_all.kml")
```