library(readxl)
library(dplyr)
library(tidyr)
library(ggrepel)
library(stringr)
library(lubridate)
library(plotly)

Introduction

Welcome to this informative R Markdown document, where we present a comprehensive overview of our members’ statistics. You will find a wealth of insightful data and analytics that shed light on the diverse characteristics and trends among our esteemed community.

rladies_paris <- read_excel("~/Desktop/Mouna/R-Ladies Paris/Statistics from Meetup_June 2023/rladies_paris_Member_List_on_2023_06_03.xlsx") # data can't be made public as it includes personal information.

Evolution of the number of our members on our Meetup group

You can also embed plots, for example:

rladies_paris$Joined_Group_on <- mdy(rladies_paris$Joined_Group_on) # convert character to date format.
rladies_paris_year <- rladies_paris %>% mutate(year = year(rladies_paris$Joined_Group_on)) %>% group_by(year) %>% count()

rladies_paris_year %>%
  ungroup() %>% plot_ly(type = 'scatter', 
                        mode = 'lines + markers') %>% 
  add_trace(x = ~year, y = ~cumsum(n),
            marker = list(color = '#fdc538', size = 12),
            line = list(color = '#2568b0'),
            hoverinfo = "text",
            text = ~paste(n, "New members\n", cumsum(n), 'Total number of members on', year)) %>% 
  layout(xaxis = list(title = list(text='Year', font=list(size=18))), 
         yaxis = list(title = list(text='Total Number', font=list(size=18))), 
         title = "Evolution of the Number of Members on Meetup",
         showlegend = FALSE)