Introduction

d$date = as.Date(d$timeStamp)
d = d[d$timeStamp >= "2016-01-01 00:00:00",]




d %>% count(title,twp,date) %>%
summarise( 
   DayMax = max(n),
   DayMean = sprintf("%.2f",mean(n)),
   DayVar  = sprintf("%.2f",var(n)),
   Year_Total = sum(n) ) %>% arrange(.,desc(Year_Total)) %>% head(15) %>%
  
  formattable(
    list(  
      area(col = c(DayMax)) ~ normalize_bar("pink", 0.3), 
      area(col = c(DayMean)) ~ normalize_bar("orange", 0.3),
      area(col = c(DayVar)) ~ normalize_bar("yellow", 0.3),
      area(col = c(Year_Total)) ~ normalize_bar("lightblue", 0.3)),
    align = 'llrrrr')
title twp DayMax DayMean DayVar Year_Total
Traffic: VEHICLE ACCIDENT - LOWER MERION 23 9.52 19.19 3448
Traffic: VEHICLE ACCIDENT - UPPER MERION 19 6.90 13.62 2491
Traffic: VEHICLE ACCIDENT - ABINGTON 14 5.30 8.03 1898
Traffic: VEHICLE ACCIDENT - CHELTENHAM 16 5.05 8.81 1794
Traffic: VEHICLE ACCIDENT - PLYMOUTH 14 3.93 5.05 1370
Traffic: VEHICLE ACCIDENT - NORRISTOWN 15 3.84 4.92 1337
Traffic: VEHICLE ACCIDENT - UPPER MORELAND 11 3.68 4.38 1254
Traffic: VEHICLE ACCIDENT - MONTGOMERY 18 3.64 5.11 1236
Traffic: VEHICLE ACCIDENT - HORSHAM 14 3.64 4.67 1189
Traffic: VEHICLE ACCIDENT - UPPER DUBLIN 12 3.58 4.90 1128
Fire: FIRE ALARM LOWER MERION 11 3.30 3.59 1122
Traffic: DISABLED VEHICLE - LOWER MERION 25 3.27 4.50 1107
Traffic: VEHICLE ACCIDENT - WHITEMARSH 16 2.95 4.15 907
Traffic: VEHICLE ACCIDENT - UPPER PROVIDENCE 9 2.79 2.70 856
Traffic: VEHICLE ACCIDENT - WHITPAIN 10 2.79 3.89 833