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Explore LinkedIn Connections in R

Jyoti Kumar
6 min readMar 28, 2021

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In this blog I have made an attempt to create a shiny dashboard using connections data downloaded from LinkedIn.

Requirements- Knowledge of shiny, shinydashboard and data cleaning and transformation using dplyr.

Final Dashboard

The data can be downloaded from LinkedIn using the following steps:

  1. Go to LinkedIn
  2. Click on Me and then Click Settings & Privacy
  3. Go to Data Privacy and Click on How LinkedIn uses your data
  4. Click on Get a copy of your data
  5. Select Connections
  6. Click on Request Archive
  7. Mention your password
  8. Request will be processed and a mail will be sent in 10–15 mins
  9. Click on the Link in the mail and download the zip file
  10. The zip file contains the file Connections.csv that is used in the dashboard

The code used to create the dashboard is mentioned below. I have made an attempt to add comments in the code so that it is self explanatory.

library(shiny)
library(shinydashboard)
library(tidyverse)# Loading data
# Skipping two rowsdata <- read_csv(“Connections.csv”, skip = 2)# Cleaning names using janitor package
# Modified connected_on for proper format
# Added connected_year columndata <- data %>% janitor::clean_names() %>% 
 mutate(connected_on = as.Date(connected_on, format = ‘%d %B %Y’)) %>% 
 mutate(connected_year = format(connected_on, format = ‘%Y’))# Removed email from the data as it will be displayed at the end of the dashboarddataem <- data %>% select(-email_address)# Calculated first date and last date for default values in the date selectorfirstdate <- min(dataem$connected_on)lastdate <- max(dataem$connected_on)# Extracted first name of first connection to be displayed in a boxfirstname <- dataem %>% arrange(connected_on) %>% head(1) %>% select(first_name) %>% pull()# Color for plotsstriptext <- “#99000D”
plotbk <- “lightblue”colr <- “darkorange2”header = dashboardHeader(title = “LinkedIn Connections”, titleWidth = 450)sidebar = dashboardSidebar(
 # To disable sidebar
 disable = TRUE,
 sidebarMenu(
 
 menuItem(“Connections”, tabName = “LinePlot”)
 
 )
)body = dashboardBody(
 ### Adding the CSS style
 tags$head(tags$style(HTML(‘
 .main-header .logo {
 font-family: “Georgia”, Times, “Times New Roman”, serif;
 font-weight: bold;
 font-size: 24px;
 }
 ‘))), 
 
 
 # Boxes need to be put in a row (or column)
 tabItems(
 
 tabItem(tabName = “LinePlot”,
 
 # Output box with text
 
 fluidRow(
 valueBoxOutput(“journey”, width =12)),
 
 # Date selector
 
 fluidRow(
 
 box(width = 6, background = “teal”,
 br(), “ “,
 dateInput(“start_date”, “Select Start Date”, value = firstdate,
 min = “2001–01–01”, max=”2040–12–31")),
 
 box(width = 6, background = “teal”,
 br(), “ “,
 dateInput(“end_date”, “Select End Date”, value = lastdate,
 min = “2001–01–01”, max=”2040–12–31"))
 
 ),
 
 # Output boxes for stats
 
 fluidRow(
 valueBoxOutput(“totconnd”, width =3),
 valueBoxOutput(“firstconnd”, width =3),
 valueBoxOutput(“ncompd”, width =3),
 valueBoxOutput(“nposd”, width =3)),
 
 # Plot outputs 
 
 fluidRow(
 
 column(width = 6,
 
 box(
 width = 12, status = “info”, solidHeader = TRUE, background = “aqua”,
 #title = “Connections by date”,
 plotOutput(“lineplot”))),
 
 column(width = 6,
 
 box(
 width = 12, status = “info”, solidHeader = TRUE, background = “aqua”,
 #title = “Connections by year”,
 plotOutput(“yearplot”)))
 
 ),
 
 
 
 fluidRow(
 # Output for Top 20 companies
 column(width = 6,
 
 box(
 width = 12, status = “info”, solidHeader = TRUE, background = “aqua”,
 #title = “Top Companies”,
 plotOutput(“barcompdy”))),
 
 # Output for Top 20 positions
 column(width = 6,
 
 box(
 width = 12, status = “info”, solidHeader = TRUE, background = “aqua”,
 #title = “Top Position”,
 plotOutput(“barpostdy”)))),
 
 # Raw table output
 
 fluidRow(
 
 box(
 width = 12, solidHeader = TRUE,
 title = “Filtered Table”,
 DT::dataTableOutput(“linetable”))
 )
 
 
 )
 ),
 
 # Link to my webiste
 
 p(“To connect with me please visit my”,
 a(“website”, 
 href = “https://jyoti05iitd.pagexl.com/”), align = “right”),
 br(),
 
)ui <- dashboardPage(skin = “blue”,
 header = header,
 sidebar = sidebar,
 body = body)server <- function(input, output) {
 
 # Creating a filtered reactive data frame based on date selector
 
 data_selected <- reactive({
 dataem %>%
 filter(connected_on >= input$start_date, connected_on <= input$end_date)
 
 })
 
 # Creating a reactive filtered data frame for count of connections by date
 
 data_conn <- reactive({
 dataem %>%
 filter(connected_on >= input$start_date, connected_on <= input$end_date) %>% 
 group_by(connected_on) %>% 
 summarise(n = n()) %>% 
 ungroup()
 
 })
 
 # Creating a reactive filtered data frame for count of connections by year
 
 data_year <- reactive({
 dataem %>%
 filter(connected_on >= input$start_date, connected_on <= input$end_date) %>% 
 group_by(connected_year) %>% 
 summarise(n = n()) %>% 
 ungroup()
 
 })
 
 # Creating a reactive filtered data frame for count of connections by company
 
 data_comp <- reactive({
 dataem %>%
 filter(connected_on >= input$start_date, connected_on <= input$end_date) %>% 
 group_by(company) %>% 
 summarise(n = n()) %>% 
 arrange(desc(n)) %>% 
 ungroup() %>% 
 filter(company != ‘’) %>% 
 mutate(company = fct_reorder(company, desc(n)))
 
 })
 
 # Creating a reactive filtered data frame for count of connections by position
 
 data_post <- reactive({
 dataem %>%
 filter(connected_on >= input$start_date, connected_on <= input$end_date) %>% 
 group_by(position) %>% 
 summarise(n = n()) %>% 
 arrange(desc(n)) %>% 
 ungroup() %>% 
 filter(position != ‘’) %>% 
 mutate(position = fct_reorder(position, desc(n)))
 
 })
 
 
 # Text Output at the top
 
 output$journey <- renderValueBox({
 valueBox(
 
 value = paste(“My LinkedIn Journey from “, firstdate, “ to “, lastdate),
 subtitle = “ “
 #icon = icon(“route”)
 )
 })
 
 # Total connections
 output$totconnd <- renderValueBox({
 valueBox(
 
 value = nrow(data_selected()),
 subtitle = “Total Connections”,
 icon = icon(“users”),
 color = “teal”
 )
 })
 
 # First connection
 output$firstconnd <- renderValueBox({
 valueBox(
 
 value = paste(firstname),
 subtitle = “First connection”,
 icon = icon(“user-tie”),
 color = “teal”
 )
 })
 
 # Count of different number of companies
 output$ncompd <- renderValueBox({
 valueBox(
 
 value = nrow(data_comp()),
 subtitle = “Number of companies”,
 icon = icon(“building”),
 color = “teal”
 )
 })
 
 # Count of different number of positions
 output$nposd <- renderValueBox({
 valueBox(
 
 value = nrow(data_post()),
 subtitle = “Number of Positions”,
 icon = icon(“user-tie”),
 color = “teal”
 )
 })
 
 
 
 # Line Plot showing number of connections for a day
 output$lineplot <- renderPlot({
 
 dataconn2 <- data_conn()
 
 
 
 ggplot(dataconn2) + 
 geom_line(
 mapping = aes(x = dataconn2[,1,drop=TRUE], y = dataconn2[,2,drop=TRUE], 
 col = colr), show.legend = FALSE
 ) +
 labs(title = “Number of connections by date”,
 x = “Date of connection”,
 y = “Count of connections”) +
 theme(panel.background = element_blank(),
 legend.key = element_blank(),
 legend.background = element_blank(),
 strip.background = element_blank(),
 plot.background = element_rect(fill = plotbk, color = “black”, size = 3),
 panel.grid = element_blank(),
 axis.line = element_line(color = “red”),
 axis.ticks = element_line(color = “red”),
 strip.text = element_text(size = 16, color = striptext),
 axis.title.y = element_text(color = striptext, hjust = 0, face = “italic”),
 axis.title.x = element_blank(),
 axis.text = element_text(color = “black”, angle = 90),
 legend.position = “none”)
 
 })
 
 # Bar plot showing number of connections for a year
 
 output$yearplot <- renderPlot({
 
 datayear <- data_year()
 
 
 ggplot(datayear, aes(x = datayear[,1,drop=TRUE], y = datayear[,2,drop=TRUE])) +
 geom_col(fill= colr) +
 labs(title = “Number of connections by Year”,
 x = “Year”,
 y = “Count of connections”) +
 
 #coord_flip() +
 theme(panel.background = element_blank(),
 legend.key = element_blank(),
 legend.background = element_blank(),
 strip.background = element_blank(),
 plot.background = element_rect(fill = plotbk, color = “black”, size = 3),
 panel.grid = element_blank(),
 axis.line = element_line(color = “red”),
 axis.ticks = element_line(color = “red”),
 strip.text = element_text(size = 16, color = striptext),
 axis.title.y = element_text(color = striptext, hjust = 0, face = “italic”),
 axis.title.x = element_blank(),
 axis.text = element_text(color = “black”, angle = 90),
 legend.position = “none”) 
 
 })
 
 # Bar plot showing Top 20 companies
 output$barcompdy <- renderPlot({
 
 datacomp2 <- data_comp() %>% head(20)
 
 
 ggplot(datacomp2, aes(x = datacomp2[,1,drop=TRUE], y = datacomp2[,2,drop=TRUE])) +
 geom_col(fill= colr) +
 labs(title = “Top 20 companies of my connections”,
 x = “Companies”,
 y = “Count of connections”) +
 
 #coord_flip() +
 theme(panel.background = element_blank(),
 legend.key = element_blank(),
 legend.background = element_blank(),
 strip.background = element_blank(),
 plot.background = element_rect(fill = plotbk, color = “black”, size = 3),
 panel.grid = element_blank(),
 axis.line = element_line(color = “red”),
 axis.ticks = element_line(color = “red”),
 strip.text = element_text(size = 16, color = striptext),
 axis.title.y = element_text(color = striptext, hjust = 0, face = “italic”),
 axis.title.x = element_blank(),
 axis.text = element_text(color = “black”, angle = 90),
 legend.position = “none”)
 
 })
 
 # Bar plot showing Top 20 positions
 output$barpostdy <- renderPlot({
 
 datapost2 <- data_post() %>% head(20) 
 
 ggplot(datapost2, aes(x = datapost2[,1,drop=TRUE], y = datapost2[,2,drop=TRUE])) +
 geom_col(fill= colr) +
 labs(title = “Top 20 Positions of my connections”,
 x = “Positions”,
 y = “Count of connections”) +
 #coord_flip() +
 theme(panel.background = element_blank(),
 legend.key = element_blank(),
 legend.background = element_blank(),
 strip.background = element_blank(),
 plot.background = element_rect(fill = plotbk, color = “black”, size = 3),
 panel.grid = element_blank(),
 axis.line = element_line(color = “red”),
 axis.ticks = element_line(color = “red”),
 strip.text = element_text(size = 16, color = striptext),
 axis.title.y = element_text(color = striptext, hjust = 0, face = “italic”),
 axis.title.x = element_blank(),
 axis.text = element_text(color = “black”, angle = 90),
 legend.position = “none”)
 
 })
 
 # Raw table output
 output$linetable <- DT::renderDataTable({
 
 data_selected()
 
 
 })
 
 
}shinyApp(ui, server)

The app is published on shinyapps.io at https://jyoti05iitd.shinyapps.io/ExploreLinkedInConn/

Please visit the app and add comments for improvements.

R
Shiny
Dashboar
LinkedIn

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Jyoti Kumar
Jyoti Kumar

Written by Jyoti Kumar

102 Followers
19 Following

I have experience in Predictive Modelling and Dashboards. YouTube : LearnToPlayWithData (https://www.youtube.com/channel/UChAOvvDYCu7zHcQq4O3Ov3Q)

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