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flight<-df %>%
  filter(type == 'HKQuantityTypeIdentifierFlightsClimbed') %>%
  group_by(year,month) %>%
  summarize(flights=sum(value)) %>%
  print (n=100) %>%
  ggplot(aes(x=month, y=flights, fill=year)) + 
  geom_bar(position='dodge', stat='identity') +
  scale_y_continuous(labels = scales::comma) +
  theme(panel.grid.major = element_blank())+
  ggtitle("Total flights climbed")

akshat3096

# calendar heatmap: year wise calories burned
f <- df %>%
  filter(type == 'HKQuantityTypeIdentifierActiveEnergyBurned') %>% 
  filter(year==2018) %>% 
  mutate(week_date = ceiling(day(creationDate) / 7)) %>%
  group_by(week_date, month, dayofweek) %>%
  summarise(total_cal = sum(value))

p <- ggplot(f,
    aes(dayofweek, week_date, fill = f$total_cal)) +

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energy <- df %>%
  filter(type == 'HKQuantityTypeIdentifierActiveEnergyBurned') %>%
  group_by(date,year,month) %>%
  summarize(energy_burned=sum(value))

energy$date <- as.Date(energy$date,"%Y-%m-%d")

plot3 <- ggplot(energy,aes(x=date, y=energy_burned, group=year)) + 
  geom_line(aes(colour=year))+
  ggtitle("Total Energy burned")

akshat3096

step_count <- df %>%
  filter(type == 'HKQuantityTypeIdentifierStepCount') %>%
  filter(year==2019) %>% 
  group_by(dayofweek,year,month) %>%
  summarize(step_count=median(value))

plot <- ggplot(step_count,aes(x=month, y=step_count, group=dayofweek)) + 
  geom_line(aes(colour=dayofweek),size=1.5)+
  theme_minimal()+
  ggtitle("Weekly median stepcount")

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plot+
  geom_point() +
  transition_reveal(as.numeric(month))

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install.packages("gganimate")
library(gganimate)

#animating the above plot
p1+transition_reveal(as.numeric(date))

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#convert the date format first
heart_rate$date <- as.Date(heart_rate$date,"%Y-%m-%d")
p1 <- p1+scale_x_date(date_labels = "%b/%Y")

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install.packages("tidyverse")
install.packages("ggplot2")
library(tidyverse)
library(ggplot2)

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steps <- df %>%
  filter(type == 'HKQuantityTypeIdentifierStepCount') %>%
  group_by(date,year,month) %>%
  summarize(steps=sum(value))

steps$date <- as.Date(steps$date,"%Y-%m-%d")

plot2 <- ggplot(steps,aes(x=date, y=steps, group=year)) + 
  geom_line(aes(colour=year))+
  geom_snooth(se=F)+

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heart_rate <- df %>%
  filter(type == 'HKQuantityTypeIdentifierHeartRate') %>%
  group_by(date,year,month) %>%
  summarize(heart_rate=median(value))+
  xlab("Month/Year")

heart_rate$date <- as.Date(heart_rate$date,"%Y-%m-%d")

plot <- ggplot(heart_rate,aes(x=date, y=heart_rate, group=year)) + 
  geom_line(aes(colour=year))+