Merge pull request #1 from PSYC-259-Data-Science/master

Merge up from class to include binder stuff

01_vocab.R

@@ -4,10 +4,13 @@ library(visdat) #Means "visualize data"
 
 rm(list = ls()) #clean variables out of environment
 
+ds <- read_csv('vocab.csv')
+getwd()
+
 #Read the data file (all defaults work so all we need is a filename)
 ds <- read_csv('data_raw/vocab.csv')
 
-#Look at whole dataset, check basic assumptions
+#Check for 'missing' values
 vis_miss(ds) 
 
 #Wide to long (we'll go over this next week)

02_eye_tracking_basic.R

@@ -26,7 +26,8 @@ ds %>% ggplot(aes(x = por_x, y = por_y)) +
 #Were they parsed correctly? Yes 
 vis_dat(ds)
 
-#Let's set bad values to missing and save to a ds_cleaned tibble
+#Let's set bad values to missing and save to a ds_cleaned tibble 
+#(more on this next week)
 ds_cleaned <- ds %>% 
   mutate(por_x = ifelse(por_x < 0 | por_x > 640, NA, por_x),
          por_y = ifelse(por_y < 0 | por_y > 480, NA, por_y))
@@ -38,15 +39,14 @@ ds_cleaned %>%
   theme_minimal()
 
 #Save the plot to eda as a data check
-ggsave(paste0("eda/et_distribution_figs/",id,"_check.png"), width = 8, height = 6, units = "in")
+ggsave(paste0("eda/et_distribution_figs/101_check.png"), width = 8, height = 6, units = "in")
 
 #Let's also add a row with the subject id to the data file
 ds_cleaned <- ds_cleaned %>% 
   add_column(id = 101, .before = "record_frames")
 
-#Decide what to save
+#Drop NA?
 #ds_cleaned <- ds_cleaned %>% drop_na() #Is this actually a good idea?
-ds_cleaned <- ds_cleaned %>% select(record_frame_count:pupil_y)
 
 #Write to file
 ds_cleaned %>% write_csv("data_cleaned/101.csv")

README.md

@@ -1,3 +1,8 @@
-<!-- badges: start -->
-[![Launch Rstudio Binder](http://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/JohnFranchak/259-files-import/master?urlpath=rstudio)
-<!-- badges: end -->
+
+[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/PSYC-259-Data-Science/259-files-import.git/HEAD?urlpath=rstudio)
+
+<a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-nc-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-nc-sa/4.0/">Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License</a>.
+
+# 259-files-import
+
+This is a tutorial for reading data into R from various types of files using tidyverse functions. The scripts (01-03) are increasingly advanced to show a range of examples from simple to more involved data import.

data_cleaned/vocab.csv

@@ -6,7 +6,7 @@ age,word
 13.5,cat
 14,baby
 14.5,socks/shoes
-14.5,dog
+14.5,dog (animal)
 15,banana
 15,llama
 15.5,cheese

install.R

@@ -0,0 +1,4 @@
+install.packages("janitor")
+install.packages("stringr")
+install.packages("tidyverse")
+install.packages("visdat")

runtime.txt

@@ -0,0 +1 @@
+r-2021-01-01