Hi. I have the following data which is both in wide and long format where the variables date_ymd status together identify unique observations. I am trying to reshape this to a long dataset where each of the st* variables is a row, with three new columns with the status variable values of Confirmed, Recovered, and Deceased. So each st variable will have one date against it and the corresponding values for that date in the Confirmed, Recovered, and Deceased variable columns.
I have tried the code below which yields output #2 below. This does not give me the three new columns with the status variable values of Confirmed, Recovered, and Deceased. Is there anyway I can do this with the reshape command or in a short manner without reshaping, then generating three separate variables for Confirmed, Recovered, and Deceased, replacing those values with the equivalent status variable value, and then copying values from multiple observations for the same date for the Confirmed, Recovered, and Deceased variables to bring it to one st-date observation?
reshape long st_, i(date_ymd status) j(tp, string)
I have tried the code below which yields output #2 below. This does not give me the three new columns with the status variable values of Confirmed, Recovered, and Deceased. Is there anyway I can do this with the reshape command or in a short manner without reshaping, then generating three separate variables for Confirmed, Recovered, and Deceased, replacing those values with the equivalent status variable value, and then copying values from multiple observations for the same date for the Confirmed, Recovered, and Deceased variables to bring it to one st-date observation?
reshape long st_, i(date_ymd status) j(tp, string)
Code:
1. original data input str10 date_ymd str9 status long sttt int(st_an st_ap st_as st_br) "2021-05-30" "Confirmed" 153396 20 13400 3245 1475 "2020-08-01" "Recovered" 55117 88 9276 1457 3521 "2020-10-02" "Confirmed" 79883 10 6555 1416 1431 "2020-09-15" "Confirmed" 91098 17 8846 2409 1575 "2020-04-26" "Confirmed" 1607 0 81 0 26 "2021-07-13" "Confirmed" 40314 3 2567 2169 102 "2020-06-07" "Confirmed" 10882 0 199 208 239 "2021-04-13" "Recovered" 185297 8 4228 590 4157 "2020-11-26" "Recovered" 43174 5 1031 150 682 "2020-11-01" "Confirmed" 45928 8 2618 166 777 "2021-04-28" "Confirmed" 379404 52 14669 3045 13374 "2020-08-02" "Confirmed" 52672 98 8555 1178 2762 "2021-01-18" "Deceased" 9987 5 81 33 144 "2021-03-28" "Deceased" 68206 2 1005 48 351 "2020-10-18" "Confirmed" 56519 25 3986 318 1152 "2020-05-06" "Confirmed" 3602 0 60 1 7 "2021-01-14" "Confirmed" 15677 7 179 19 314 "2021-01-01" "Recovered" 20159 1 326 40 463 "2020-07-28" "Confirmed" 49631 25 7948 1371 2480 "2020-05-27" "Confirmed" 7246 0 134 101 68 "2021-06-05" "Confirmed" 114488 17 10373 3781 1007 "2021-02-03" "Deceased" 12925 0 95 14 92 "2020-09-01" "Deceased" 78168 28 10368 2684 1928 "2021-10-27" "Confirmed" 16351 2 567 244 5 2. reshaped data clear input str10 date_ymd str2 state str9 status long st_ "2020-04-01" "an" "Deceased" 0 "2020-04-01" "an" "Confirmed" 0 "2020-04-01" "an" "Recovered" 0 "2020-04-01" "ap" "Confirmed" 67 "2020-04-01" "ap" "Recovered" 1 "2020-04-01" "ap" "Deceased" 0 "2020-04-01" "ar" "Confirmed" 0 "2020-04-01" "ar" "Deceased" 0 "2020-04-01" "ar" "Recovered" 0 "2020-04-01" "as" "Confirmed" 15 "2020-04-01" "as" "Recovered" 0 "2020-04-01" "as" "Deceased" 0 "2020-04-01" "br" "Confirmed" 3 "2020-04-01" "br" "Recovered" 0 "2020-04-01" "br" "Deceased" 0 "2020-04-01" "ch" "Recovered" 0 "2020-04-01" "ch" "Deceased" 0 "2020-04-01" "ch" "Confirmed" 2
Comment