# welcome to week 8!

library(tidyverse)

species.dot <- read.csv("data/raw_data/species.csv")
species.dot

species_underscore <- read_csv("data/raw_data/species.csv")
species_underscore

str(species.dot)

surveys.dot2 <- read.csv("data/raw_data/species.csv", stringsAsFactors = FALSE)
str(surveys.dot2)

read.csv2()
read.csv(sep = ";")
read_csv()
?read_table

read_csv("data/wide_eg.csv")

read_csv("data/wide_eg.csv", skip = 2)

# exporting a CSV

write_csv(x = species.dot, path = "data/cleaned_data/species_dot_written.csv")

# .rda and .rds files

save(species.dot, species_underscore, file = "data/cleaned_data/species_dataframes.rda")

load(file = "data/cleaned_data/species_dataframes.rda")

species.dot
species_underscore

saveRDS(species_underscore, file = "data/cleaned_data/species_underscore.rds")

new_species_underscore <- readRDS(file = "data/cleaned_data/species_underscore.rds")


gapminder <- read_csv("data/gapminder.csv")

surveys <- read_csv("data/raw_data/portal_data_joined.csv")

surveys %>% 
  ggplot(aes(x = year, y = hindfoot_length, color = )) +
  geom_jitter()

ggsave(filename = "surveys_hindfoot_year_species.jpg", width = 6, height = 6)
?ggsave

# some cool packages to import and export weird data types
#readxl::
#googlesheets4::
#foreign::
#rio::
  
  
  
#Datetimes in R!

#Date is a data format that R recognizes 

#Three basic time classes in R
#1. Date: just for dates (2/25/2019)
#2. Datetime: POSIXct best for dates with times
#3. POSIXlt 


#PRO TIP! 
#When you enter your data in seperate columns for year, month, day and time 

sample_dates_1 <- c("2018-02-01", "2018-03-21", "2020-02-25", "2019-04-04")

sample_dates_1 <- as.Date(sample_dates_1)

#The only reason that worked is because the format is correct: YYYY MM DD

sample_date_2 <- c("02-25-2020", "04-04-1988", "05-05-2019", "06-01-2020")

sample_date_2 <- as.Date(sample_date_2)
#R doesn't like this format 

sample_date_2 <- as.Date(sample_date_2, format = "%m-%d-%Y")
#see lesson for cheatsheet

#05A21A1998

# format = %mA%dA%Y

july <- c("July 04, 2019", "Nov 08, 2019", "July 17, 2019")

july <- as.Date(july, format = "%B %d, %Y")
july

time <- c("2016-07-24 22:55:01", "2013-04-12 18:50:11")
#Nice format, YYYY MM DD, HH:MM:SS this is what R is looking for 

time <- as.POSIXct(time, tz = "GMT")
time