Author: Ray Han; with advice from Steven Jia

---
title: "NYC Yellow Cab Data Analysis & Visualization"
output: 
  flexdashboard::flex_dashboard:
    orientation: rows
    source_code: embed
---


Author: Ray Han; 
with advice from Steven Jia

TLC Yellow Cab Data
=============

Row
-----------------------------------------------------------------------

### Glimpse of the Data

```{r warning = F, message = F, echo = F}
library(readr)
library(DT)
library(dplyr)
setwd("/Users/stevenjia93/Desktop/ColumbiaU/CU_Spring/DataVis/Project/Data")
df <- readr::read_csv("df.csv")

#----------- Remove Later
set.seed(1) # Remove Later
smalldf <- sample_frac(df, 0.01) # Remove
df <- smalldf
#----------- Remove Later
datatable(head(df, 100), options = list(
  initComplete = JS(
    "function(settings, json) {",
    "$(this.api().table().header()).css({'background-color': '#000', 'color': '#fff'});",
    "}"))
)
```

Row
-----------------------------------------------------------------------

### Use your time wisely as taxi drivers

```{r}
library(ggplot2)
library(dplyr)
stats1 <- df %>% group_by(pickup_hour) %>% summarise(mean(fare_per_min))
stats2 <-  df %>% group_by(pickup_hour) %>% summarise(N = n())
stats <- left_join(stats1, stats2, by = "pickup_hour")
names(stats) <- c("pickup_hour", "mean_fare_per_min", "counts")

# install.packages("plotly")
library(plotly)
## Second axis
ay <- list(tickfont = list(color = "red"), 
           overlaying = "y",
           side = "right",
           title = "Avg fare/min")

plot_ly(stats, x =~ pickup_hour, y =~ counts,
        name = "# of Trips" ,type = "bar") %>% 
  add_trace(y = ~ mean_fare_per_min, type = "scatter", 
            name = "Avg $ / min", mode = "line + markers", yaxis = "y2") %>% 
  layout(
    title = "Average Fare per Minute ($ / min)",
    xaxis = list(title = "Pickup Hour"),
    yaxis = list(title = "Number of Trips"),
    yaxis2 = ay
  )
```

Clustering Analysis - Pickup Hotspot in Manhattan
=============

### Chart C

```{r}
library(RColorBrewer)
library(leaflet)
pal = colorFactor("Set1", domain = df$day)
color_weekday <- pal(df$day)

circle_popup <- paste("Weekday: ", df$day, "
",
                      "Total fare: ", df$total_amount,"USD","
",
                      "Trip distance: ", df$trip_distance, 
                      "miles", "
",
                      "Number of passengers: ", 
                      df$passenger_count)
leaflet(df) %>% 
      addTiles('http://{s}.tile.openstreetmap.de/tiles/osmde/{z}/{x}/{y}.png') %>%
      setView(-73.985131, 40.758895, zoom = 10) %>% 
      addCircleMarkers(lng=~pickup_longitude, lat=~pickup_latitude,
                       color=color_weekday, 
                       popup = circle_popup,
                       clusterOptions = markerClusterOptions())
```