Cyclistic Report

Load the neccesary packages

library(flexdashboard)
library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
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## ✔ forcats   1.0.0     ✔ stringr   1.5.0
## ✔ ggplot2   3.4.4     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.0
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(lubridate)
library(patchwork)
options(scipen = 999)

Load all data needed for the plot

trips_summary2 <- read_csv("analysis2.csv", show_col_types = FALSE)
trips_summary3 <- read_csv("analysis3.csv", show_col_types = FALSE)
trips_summary4 <- read_csv("analysis4.csv", show_col_types = FALSE)

Average Duration By Seasons

spring_plot02 <- trips_summary3%>%
  filter(yearmonth =="Apr"|yearmonth =="May"|yearmonth =="Jun")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=average_duration, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = 'yearmonth', title = "Spring")

summer_plot02 <- trips_summary3%>%
  filter(yearmonth =="Jul"|yearmonth =="Aug"|yearmonth =="Sep")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=average_duration, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = 'yearmonth', title = "Summer")

fall_plot02 <- trips_summary3%>%
  filter(yearmonth =="Oct"|yearmonth =="Nov"|yearmonth =="Dec")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=average_duration, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = 'yearmonth', title = "Fall")

winter_plot02 <- trips_summary3%>%
  filter(yearmonth =="Jan"|yearmonth =="Feb"|yearmonth =="Mar")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=average_duration, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = "yearmonth", title = "Winter")

(spring_plot02 | summer_plot02) / (fall_plot02 | winter_plot02)

Number of Rides By Seasons

spring_plot01 <- trips_summary3%>%
  filter(yearmonth =="Apr"|yearmonth =="May"|yearmonth =="Jun")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=number_of_rides, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = "yearmonth", title = "Spring")

summer_plot01 <- trips_summary3%>%
  filter(yearmonth =="Jul"|yearmonth =="Aug"|yearmonth =="Sep")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=number_of_rides, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = "yearmonth", title = "Summer")

fall_plot01 <- trips_summary3%>%
  filter(yearmonth =="Oct"|yearmonth =="Nov"|yearmonth =="Dec")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=number_of_rides, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = "yearmonth", title = "Fall")

winter_plot01 <- trips_summary3%>%
  filter(yearmonth =="Jan"|yearmonth =="Feb"|yearmonth =="Mar")%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=number_of_rides, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs(x = "yearmonth", title = "Winter")

(spring_plot01 | summer_plot01) / (fall_plot01 | winter_plot01)

Number of Rides / Average Duration By Rider Type - Weekly

weekly_plot01 <- trips_summary2%>%
  ggplot(aes(x=factor(weekday,levels=c('Sun','Mon','Tue','Wed','Thu','Fri','Sat')), y=number_of_rides, fill=member_casual)) +
  geom_col(position = "dodge") +
  labs( x = "weekday", title = "Weekly Number of Rides")

weekly_plot02 <- trips_summary2%>%
  ggplot(aes(x=factor(weekday,levels=c('Sun','Mon','Tue','Wed','Thu','Fri','Sat')), y=average_duration, fill=member_casual))  +
  geom_col(position = "dodge") +
  labs(x = "weekday", title = "Weekly Average Duration")

weekly_plot01 / weekly_plot02

Number of Rides - Hourly

trips_summary4%>%
  ggplot(aes(x=day_hours, y=number_of_rides, fill=member_casual)) +
  geom_col(position = "dodge") +
  scale_x_continuous(breaks=seq(0,24, by=3)) +
  labs(title = "Number of Rides By Rider Type - Hourly",
       caption = "24 hour time format")

Number of Rides - Monthly

trips_summary3%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=number_of_rides, fill=member_casual)) +
  geom_col(position = "dodge") +
  theme(axis.text.x=element_text(angle=90,vjust=0.5,hjust=1)) +
  labs(x = 'yearmonth', title = "Monthly Number of Rides")

Average Duration - Monthly

trips_summary3%>%
  ggplot(aes(x=factor(yearmonth,levels=c('Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec','Jan','Feb','Mar')), y=average_duration, fill=member_casual)) +
  geom_col(position = "dodge") +
  theme(axis.text.x=element_text(angle=90,vjust=0.5,hjust=1)) +
  labs(x = 'yearmonth', title = "Monthly Average Duration")