Dear All,

I have a dataset with daily frequency. A small example is attached.

Code:
* Example generated by -dataex-. For more info, type help dataex
clear
input str8 iso_code str13 continent str32 country long total_cases float(si date2)
"AFG" "Asia"          "Afghanistan"              146523     . 22493
"AFG" "Asia"          "Afghanistan"              147985     . 22494
"AFG" "Asia"          "Afghanistan"              148572     . 22495
"ALB" "Europe"        "Albania"                  133121 37.96 22493
"ALB" "Europe"        "Albania"                  133146 37.96 22494
"ALB" "Europe"        "Albania"                  133211 37.96 22495
"DZA" "Africa"        "Algeria"                  172564     . 22493
"DZA" "Africa"        "Algeria"                  173922     . 22494
"DZA" "Africa"        "Algeria"                  175229     . 22495
"AND" "Europe"        "Andorra"                   14678  46.3 22493
"AND" "Europe"        "Andorra"                   14747  46.3 22494
"AND" "Europe"        "Andorra"                   14766     . 22495
"AGO" "Africa"        "Angola"                    42815     . 22493
"AGO" "Africa"        "Angola"                    42970     . 22494
"AGO" "Africa"        "Angola"                    43070     . 22495
"ATG" "North America" "Antigua and Barbuda"        1303     . 22493
"ATG" "North America" "Antigua and Barbuda"        1303     . 22494
"ATG" "North America" "Antigua and Barbuda"        1303     . 22495
"ARG" "South America" "Argentina"               4935847 73.61 22493
"ARG" "South America" "Argentina"               4947030 73.61 22494
"ARG" "South America" "Argentina"               4961880     . 22495
"ARM" "Asia"          "Armenia"                  230339     . 22493
"ARM" "Asia"          "Armenia"                  230476     . 22494
"ARM" "Asia"          "Armenia"                  230713     . 22495
"ABW" "North America" "Aruba"                         .  28.7 22493
"ABW" "North America" "Aruba"                         .  28.7 22494
"ABW" "North America" "Aruba"                         .  28.7 22495
"AUS" "Oceania"       "Australia"                 34612     . 22493
"AUS" "Oceania"       "Australia"                 34836     . 22494
"AUS" "Oceania"       "Australia"                 35089     . 22495
"AUT" "Europe"        "Austria"                  659508     . 22493
"AUT" "Europe"        "Austria"                  659872     . 22494
"AUT" "Europe"        "Austria"                  660262     . 22495
"AZE" "Asia"          "Azerbaijan"               344520 61.11 22493
"AZE" "Asia"          "Azerbaijan"               344951     . 22494
"AZE" "Asia"          "Azerbaijan"               345882     . 22495
"BHS" "North America" "Bahamas"                   14840 57.41 22493
"BHS" "North America" "Bahamas"                   14840     . 22494
"BHS" "North America" "Bahamas"                   15011     . 22495
"BHR" "Asia"          "Bahrain"                  269303     . 22493
"BHR" "Asia"          "Bahrain"                  269401     . 22494
"BHR" "Asia"          "Bahrain"                  269495     . 22495
"BGD" "Asia"          "Bangladesh"              1264328     . 22493
"BGD" "Asia"          "Bangladesh"              1280317     . 22494
"BGD" "Asia"          "Bangladesh"              1296093     . 22495
"BRB" "North America" "Barbados"                   4407     . 22493
"BRB" "North America" "Barbados"                   4417     . 22494
"BRB" "North America" "Barbados"                   4422     . 22495
"BLR" "Europe"        "Belarus"                  446998     . 22493
"BLR" "Europe"        "Belarus"                  447754     . 22494
"BLR" "Europe"        "Belarus"                  448335     . 22495
"BEL" "Europe"        "Belgium"                 1124715     . 22493
"BEL" "Europe"        "Belgium"                 1129018     . 22494
"BEL" "Europe"        "Belgium"                 1130758     . 22495
"BLZ" "North America" "Belize"                    14163 63.89 22493
"BLZ" "North America" "Belize"                    14163 63.89 22494
"BLZ" "North America" "Belize"                    14284     . 22495
"BEN" "Africa"        "Benin"                      8394 38.89 22493
"BEN" "Africa"        "Benin"                      8394 38.89 22494
"BEN" "Africa"        "Benin"                      8394     . 22495
"BTN" "Asia"          "Bhutan"                     2518     . 22493
"BTN" "Asia"          "Bhutan"                     2524     . 22494
"BTN" "Asia"          "Bhutan"                     2532     . 22495
"BOL" "South America" "Bolivia"                  473899     . 22493
"BOL" "South America" "Bolivia"                  474538     . 22494
"BOL" "South America" "Bolivia"                  475265     . 22495
"BIH" "Europe"        "Bosnia and Herzegovina"   205655     . 22493
"BIH" "Europe"        "Bosnia and Herzegovina"   205785     . 22494
"BIH" "Europe"        "Bosnia and Herzegovina"   205825     . 22495
"BWA" "Africa"        "Botswana"                 106690     . 22493
"BWA" "Africa"        "Botswana"                 115220     . 22494
"BWA" "Africa"        "Botswana"                 115220     . 22495
"BRA" "South America" "Brazil"                 19938358     . 22493
"BRA" "South America" "Brazil"                 19953501     . 22494
"BRA" "South America" "Brazil"                 19985817     . 22495
"BRN" "Asia"          "Brunei"                      337     . 22493
"BRN" "Asia"          "Brunei"                      338     . 22494
"BRN" "Asia"          "Brunei"                      338     . 22495
"BGR" "Europe"        "Bulgaria"                 425148     . 22493
"BGR" "Europe"        "Bulgaria"                 425541     . 22494
"BGR" "Europe"        "Bulgaria"                 426003     . 22495
"BFA" "Africa"        "Burkina Faso"              13588     . 22493
"BFA" "Africa"        "Burkina Faso"              13591     . 22494
"BFA" "Africa"        "Burkina Faso"              13591     . 22495
"BDI" "Africa"        "Burundi"                    7080     . 22493
"BDI" "Africa"        "Burundi"                    7505     . 22494
"BDI" "Africa"        "Burundi"                    7518     . 22495
"KHM" "Asia"          "Cambodia"                  77914 68.98 22493
"KHM" "Asia"          "Cambodia"                  78474 68.98 22494
"KHM" "Asia"          "Cambodia"                  79051 68.98 22495
"CMR" "Africa"        "Cameroon"                  82064 29.63 22493
"CMR" "Africa"        "Cameroon"                  82064 29.63 22494
"CMR" "Africa"        "Cameroon"                  82064     . 22495
"CAN" "North America" "Canada"                  1438817     . 22493
"CAN" "North America" "Canada"                  1439032     . 22494
"CAN" "North America" "Canada"                  1441275     . 22495
"CPV" "Africa"        "Cape Verde"                33822     . 22493
"CPV" "Africa"        "Cape Verde"                33830     . 22494
"CPV" "Africa"        "Cape Verde"                33858     . 22495
end
format %td date2
I have a Master do file from where I recall other do files. In one of them (say myfile.do), I choose for instance to keep only observations at (01Aug2021 - date2 22493). However in some other cases, I would like to keep observations if date2==22494 (02Aug2021) and in other situations I would like to keep only observations if date2=22495 (03Aug2021). My idea would be to include in the Master do file a command to tell Stata to use myfile.do if I want to keep observations at 01Aug2021, myfile2.do, if I want to keep observations at 02Aug2021 and myfile3.do, if I want to keep observations at 03Aug2021.

I probably need to create an index variable taking the value of 1, 2 or 3 and then using something like:

if index==1

do myfile.do

else if index==2

do myfile2.do

else if index==3

do myfile3.do

However, I cannot figure out how I can do this. or whether there is a simpler approach. Any help?

Thanks in advance.

Dario