suppressMessages(library(tidyverse))
suppressMessages(library(glue))
PRE = "/Users/haekyungim/Library/CloudStorage/Box-Box/LargeFiles/imlab-data/data-Github/web-data"
##PRE="/Users/margaretperry/Library/CloudStorage/Box-Box/imlab-data/data-Github/web-data "
##PRE="/Users/temi/Library/CloudStorage/Box-Box/imlab-data/data-Github/web-data"
## COPY THE DATE AND SLUG fields FROM THE HEADER
SLUG="parg-fall-social-2022" ## copy the slug from the header
bDATE='2022-10-20' ## copy the date from the blog's header here
DATA = glue("{PRE}/{bDATE}-{SLUG}")
if(!file.exists(DATA)) system(glue::glue("mkdir {DATA}"))
WORK=DATA
## move data to DATA
#tempodata=("~/Downloads/tempo/gwas_catalog_v1.0.2-associations_e105_r2022-04-07.tsv")
#system(glue::glue("cp {tempodata} {DATA}/"))
system(glue("open {DATA}")) ## this will open the folder df <- readxl::read_excel(glue("{WORK}/report-2022-10-20T1314.xlsx"))## New names:
## • `Please explain` -> `Please explain...26`
## • `Please explain` -> `Please explain...27`names(df)## [1] "Order #"
## [2] "Order Date"
## [3] "First Name"
## [4] "Last Name"
## [5] "Email"
## [6] "Quantity"
## [7] "Price Tier"
## [8] "Ticket Type"
## [9] "Attendee #"
## [10] "Group"
## [11] "Order Type"
## [12] "Currency"
## [13] "Total Paid"
## [14] "Fees Paid"
## [15] "Eventbrite Fees"
## [16] "Eventbrite Payment Processing"
## [17] "Attendee Status"
## [18] "Home Address 1"
## [19] "Home Address 2"
## [20] "Home City"
## [21] "Home State"
## [22] "Home Zip"
## [23] "Home Country"
## [24] "Will you be attending the event?"
## [25] "Do you have any allergies or dietary requirements?"
## [26] "Please explain...26"
## [27] "Please explain...27"
## [28] "Are you interested in participating in the talent show?"
## [29] "What equipment would you need?"
## [30] "Campus affiliation (dept/div) and role (undergrad, grad, staff, faculty, other)"
## [31] "Is this your first time attending a Pan-Asian Resource Group event?"
## [32] "How did you hear about us?"df %>% count(`Campus affiliation (dept/div) and role (undergrad, grad, staff, faculty, other)`) %>% arrange(desc(n))## # A tibble: 59 × 2
## Campus affiliation (dept/div) and role (undergrad, grad, staff, facu…¹ n
## <chr> <int>
## 1 Grad 19
## 2 grad 7
## 3 Harris 6
## 4 BSD 5
## 5 Grad student 3
## 6 Harris student 3
## 7 PSD, grad 3
## 8 Harris MPP 2
## 9 PSD grad 2
## 10 Booth 1
## # … with 49 more rows, and abbreviated variable name
## # ¹`Campus affiliation (dept/div) and role (undergrad, grad, staff, faculty, other)`
## # ℹ Use `print(n = ...)` to see more rowsnot very helpful, better to have list to select from rather than free text next time
df %>% count(`How did you hear about us?`) %>% arrange(desc(n)) ## # A tibble: 5 × 2
## `How did you hear about us?` n
## <chr> <int>
## 1 International House newsletter 40
## 2 Through a friend 30
## 3 Through the Pan Asian or the Pan Asian Resource Group list serves 17
## 4 Divisional/departmental events 12
## 5 International House newsletter | Through the Pan Asian or the Pan Asian… 1I-house newsletter was the most effective dissemination