I am developing a metric of estimated vs. actual costs. I have collected the data and broken it out by year and month for the past 12 months. What is the best way to plot this to show the mean percent difference by month across years?
EstAct%<>%
select(ccmasterid, esmasterid, jcestimatedcost, jcactcost, ccdatesetup)%<>%
filter(ccdatesetup >= today() - months(12))%<>%
dplyr::mutate(year = lubridate::year(ccdatesetup),
month = lubridate::month(ccdatesetup))%<>%
mutate(pct_change = ((jcestimatedcost-jcactcost)/jcestimatedcost) * 100)
head(EstAct, 10)
ccmasterid esmasterid jcestimatedcost jcactcost ccdatesetup year
1 C17428B MM27526.2 1184.23 827.23 2019-06-13 2019
2 C17438A MM27537.1 832.34 678.27 2018-09-11 2018
3 C17445A MM27546.1 911.50 733.69 2019-03-29 2019
4 C18586A MM29017.1 196.82 132.34 2018-12-10 2018
5 C19079B MM28159.3 15593.92 11450.46 2018-09-04 2018
6 C19398A MM30068.1 2029.60 1625.02 2018-07-16 2018
7 C19398B MM30068.2 2010.66 1670.82 2018-08-15 2018
8 C19398C MM30068.3 7297.40 6103.94 2019-01-16 2019
9 C19399A MM30069.1 4290.74 3263.09 2018-07-13 2018
10 C19399B MM30069.2 4227.80 3334.62 2018-08-16 2018
month pct_change
1 6 30.14617
2 9 18.51046
3 3 19.50741
4 12 32.76090
5 9 26.57100
6 7 19.93398
7 8 16.90191
8 1 16.35459
9 7 23.95041
10 8 21.12635