Jack.R

getwd()
options(scipen = 999) #this prevents conversion to scientific notation

# putting a HASHTAG or number sign prevents everything
# to the right on that line from being run

'''
For comments that are too long to be a single line
one can insert 3 single quote marks like
i did here.
'''

library(tidyverse)
library(lubridate)
#library(readODS)


###############  DATA:  https://databank.worldbank.org/reports.aspx?source=world-development-indicators#

data<- read_csv("Data_2.csv")
View(data)  # See the data in its entiruity
dim(data)  # rowss & columns
head(data, 5) #  see the first 5 rows.(Ommit 5 and defaults to 10)
tail(data) # you guessed it
glimpse(data)  # pointless option
ls(data) #list of variables


A<- data
A<- data%>%
     rename(variable = Years)
#US_deaths<- US_deaths %>%
#rename(Country = Entity ,Deaths = `Daily confirmed deaths (deaths)`)

skinny_2<- A%>%
  gather("year" , "value", -variable)



skinny_1<- A%>%
            gather("category" , "value", -Years)

skinny_1
View(skinny_1)

#skinny_1 <- pivot_longer(data, c( 1960,1961,1962,1963,1964,1965,1966,1967,1968,
                                 1969,1970,1971,1972,1973,1974,1975,1976,1977,1978,1979,1980))

#skinny_1<- pivot_longer(data, c(`1960` : `1980`))

#skinny_1 <- data%>%
  mutate_if(is.numeric,as.character, is.factor, as.character) %>%
  pivot_longer(  names_to = "key",
                values_to = "val")


#small_diamonds %>%
  small_diamonds %>%
  mutate_if(is.numeric,as.character, is.factor, as.character) %>%
  pivot_longer( - row_num,
                names_to = "key",
                values_to = "val")






  stocks <- tibble(
    time = as.Date('2009-01-01') + 0:9,
    X = rnorm(10, 0, 1),
    Y = rnorm(10, 0, 2),
    Z = rnorm(10, 0, 4)
  )
stocks

gather(stocks, "stock", "price", -time)



test<- read_csv("test_data.csv")
 test$year <- as.Date(as.character(test$year) , format = "%Y")
 test$pop <- as.numeric(test$pop)
 test$city<- as.factor(test$city)


 p<- ggplot(test, aes(year , pop, color = city, group = city))+
     geom_line()
p

str(test)

Boston<-
    filter(test, city == "Boston")

Boston

p<- ggplot(Boston, aes(year , pop))+
  geom_line()
p