bikes_reading_data.R

# Libraries
library(tidyverse)
library(lubridate)
library(prophet)
library(forecast)

# Read data
bikes <- read_csv('bikes.csv') %>%
    mutate(datetime = date(datetime))

# Separate data
train <- bikes %>% select(datetime, count) %>%
    filter(datetime < as.Date("2012-01-01")) %>%
    group_by(datetime) %>%
    summarise(y = sum(count))
names(train) <- c('ds', 'y')

valid <- bikes %>% select(datetime, count) %>%
    filter(datetime >= as.Date("2012-01-01") & datetime < as.Date("2012-07-01")) %>%
    group_by(datetime) %>%
    summarise(y = sum(count))
names(valid) <- c('ds', 'y')

test <- bikes %>% select(datetime, count) %>%
    filter(datetime >= as.Date("2012-07-01")) %>%
    group_by(datetime) %>%
    summarise(y = sum(count))
names(test) <- c('ds', 'y')