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README.Rmd
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---
title: "Analytics>Forward 2019"
author: "Rick Pack (VP of Research Triangle Analysts)"
date: "March 10, 2019"
output: github_document
---
```{r setup, include=FALSE, cache = FALSE, echo = FALSE}
knitr::opts_chunk$set(echo = FALSE,
base.url = 'https://github.com/RickPack/AnalyticsForward_2019/raw/master/')
################################################
## Get your Meetup key by going to ##
## https://secure.meetup.com/meetup_api/key/ ##
## !!! Then must run the line below! !!! ##
################################################
## Sys.setenv(MEETUP_KEY = "NOT_SHOWN") ##
################################################
## Save images and CSV data files locally?
save_to_folder <- TRUE
####################################
## If need to use github CSV file ##
## rather than use Meetup API ##
####################################
github_file <- FALSE
# What is the Meetup group name?
# Find this in the Meetup URL.
# For example, in https://www.meetup.com/Research-Triangle-Analysts/events/258165094/
# it is:
# 'Research-Triangle-Analysts'
meetupgrp_name <- 'Research-Triangle-Analysts'
source('Meetup_RSVP_Yes_latest.R')
lst_out <- Meetup_RSVP_Yes_Count(save_to_folder, github_file, meetupgrp_name)
allAF_frm <- lst_out[[1]]
allAF_frm_weekday <- lst_out[[2]]
allAF_frm_dt_all <- lst_out[[6]]
allAF_frm <-
allAF_frm %>%
rename(Year = yes_year,
Registration_Count = rsvp_yes_count,
Registration_CumSum = dates_yes_cumsum,
Registration_Date = dates_yes) %>%
mutate(Weekday = wday(ymd(Registration_Date), label = TRUE)) %>%
group_by(Year) %>%
mutate(Meetup_Start_Date = min(Registration_Date)) %>%
select(name, Meetup_Start_Date, Year, Registration_Date, Weekday, Registration_Count,
Registration_CumSum, Registration_Date,
event_date, days_to_event)
max_yes_year <- max(allAF_frm$Year)
today_days_to_event <- allAF_frm %>%
dplyr::filter(Year == max_yes_year) %>%
mutate(min_days_event = min(days_to_event)) %>%
distinct(min_days_event) %>%
pull(min_days_event)
weeks_until_event <- max(0, as.numeric(floor(today_days_to_event / 7)))
```
# "Analytics>Forward" (2019) - 5th annual unconference by Research Triangle Analysts
"Pitch a talk, hear some talks, eat good food" #AnalyticsForward http://bit.ly/AF2019Signup
This page's data visualizations will be updated daily.
They primarily depict Meetup Registrations for Analytics>Forward, with the purpose of indicating sell-out potential and to help the planning comittee with elements including the catering order.
Thank you to R-Ladies for the meetupr package.
## Keynote
## Charts
```{r highchart1}
#print(grp_plot)
```
```{r highchart2}
#print(grp_plot_latestyear)
```
## Week of event average Registrations per day
### Prior to the current year and after 2015 (first year, lower Registrations)
```{r table_notcur}
allAF_frm_dt_all_big_years_not_current <-
allAF_frm_dt_all %>%
dplyr::filter(yes_year > 2015 & yes_year < max_yes_year)
allAF_frm_dt_all_big_years_not_current_weekday <-
allAF_frm_dt_all_big_years_not_current %>%
dplyr::filter(yes_year > 2015 & yes_year < max_yes_year) %>%
dplyr::filter(days_to_event <= 6 * (weeks_until_event + 1) + min(weeks_until_event, 1) &
days_to_event >= 6 * (weeks_until_event + 1) + min(weeks_until_event, 1) - 6) %>%
mutate(hour_rsvp = hour(datetime_rsvp),
weekday_rsvp = wday(ymd_hms(datetime_rsvp), label = TRUE)) %>%
group_by(weekday_rsvp) %>%
summarise(Average_RSVP_weekday = n() /
length(unique(allAF_frm_dt_all_big_years_not_current$yes_year)))
knitr::kable(allAF_frm_dt_all_big_years_not_current_weekday)
```
### Current year
```{r table_curyear}
allAF_frm_dt_all_current <-
allAF_frm_dt_all %>%
dplyr::filter(yes_year == 2019)
allAF_frm_dt_all_current_year_weekday <-
allAF_frm_dt_all_current %>%
dplyr::filter(yes_year == max_yes_year) %>%
dplyr::filter(days_to_event <= 6 * (weeks_until_event + 1) + min(weeks_until_event, 1) &
days_to_event >= 6 * (weeks_until_event + 1) + min(weeks_until_event, 1) - 6) %>%
mutate(hour_rsvp = hour(datetime_rsvp),
weekday_rsvp = wday(ymd_hms(datetime_rsvp), label = TRUE)) %>%
group_by(weekday_rsvp) %>%
summarise(RSVP_weekday = n())
knitr::kable(allAF_frm_dt_all_current_year_weekday)
```
## Highest Performing Days (Registrations)
### All years - 5 Highest Performing Days
```{r table_high_all_years}
high_all_years <- allAF_frm %>%
ungroup() %>%
top_n(5, Registration_Count) %>%
arrange(desc(Registration_Count))
knitr::kable(high_all_years %>%
select(name, Meetup_Start_Date, Registration_Date, Weekday, Registration_Count))
```
### Current year - 5 Highest Performing Days
```{r table_high_cur_year}
high_cur_year <- allAF_frm %>%
ungroup() %>%
dplyr::filter(Year == max_yes_year) %>%
top_n(5, Registration_Count) %>%
arrange(desc(Registration_Count))
knitr::kable(high_cur_year %>%
select(name, Meetup_Start_Date, Registration_Date, Weekday, Registration_Count))
```
## Total Registrations for Analytics>Forward per year
```{r table_peryear}
library(dplyr)
print(paste("As of ", Sys.time()))
knitr::kable(allAF_frm %>% group_by(Year) %>%
dplyr::filter(Registration_Date == max(Registration_Date)) %>%
rename(Total_Registrations = Registration_CumSum) %>%
ungroup() %>%
select(name, Year, Total_Registrations))
```
# Current Year Analytics>Forward Registration Link
[Current Year Meetup Link](http://bit.ly/AF2019Signup "Analytics>Forward 2019 Meetup page")
# For future collaborators
To facilitate engagement by potential collaborators, the following discusses available files.
## Loading the R Project
After installing R and R-Studio, fork this repo by clicking fork at the top-right. Then follow
[these instructions from the RStudio web site](https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN) to create a new project that is a clone of this version-controlled (think Github) repository. In the future, you can then double-click the AnalyticsForward_2019.Rproj file to open RStudio with the files of this project being easily accessible.
## Files
1. Readme.Rmd creates what appears on the Github page, including this text.
+One
2. Meetup_RSVP_Yes_latest.R contains the Meetup_RSVP_Yes_Count() function. You can use Readme.Rmd to understand how to use it.
3. The .csv files contain data one could use with any program for analysis.
+ Chuck Jaeger used Tableau to create this [Tableau storyboard](https://public.tableau.com/profile/chuck.jaeger#!/vizhome/AnalyticsForward2019/Storyboard).
+ Related, although he used the JMP Meetup API, Xan Gregg created images including [this one on Twitter](https://twitter.com/xangregg/status/1104359495059337217). Xan inspired many updates to the data visualizations presented here and Chuck also provided some thoughts, including the key stimulus that began all my early 2019 work.
4. animate_sponsor_coord.R is a quick-reference for stitching together images into an animated .GIF
5. AF_Pres.Rpres is a Xaringan presentation that has obvious imperfections I would love for others to help me fix.
6. The RTAgrp .html files are what I called "Easter eggs" in my A>F presentation. These can be opened in a web browser to see the use of [Joshua Kunst's](https://twitter.com/jbkunst) highcharter package, inspired by the work of 2018 keynoter, [Mara Averick](http://rpubs.com/maraaverick/470388).
7. Other files are images used in the Analytics>Forward presentation I did with Dr. Zeydy Ortiz. You can her gganimate() use for RSVPs at:
+ http://rpubs.com/zortiz/AnimatePlots
+ code available at https://github.com/DrZeydy/share/blob/master/RSVP-animate.R
## Special Notes
Make sure you get your Meetup Key and place that value here in README.Rmd or before you run the Meetup_RSVP_Yes_Count() function, or you will see an Error concerning the Meetup Key environment variable:
You might also consult the [R-Ladies meetupr package on Github](https://github.com/rladies/meetupr).
## More images
Plenty of #AnalyticsForward images are available on Twitter and LinkedIn via #AnalyticsForward as well as this Facebook album: (http://bit.ly/2O126hX)