Using the following data example, I would like to generate a table of summing the numeric obs by variable label. The following describes how the variables are labeled:
Vars "basicneeds transportation housing childeldercare employment" fall under a domain called "financial stability" and vars "employment experience school_readiness1 emotions1 school_readiness2 emotions2" fall under the domain "education and training". I would like to sum the observations by domain. I have labeled the variables accordingly. Thanks for any helkp! I alway struggle with creating tables... I get sort of in the weeds between tabulate, table, using parens, options, etc.
Vars "basicneeds transportation housing childeldercare employment" fall under a domain called "financial stability" and vars "employment experience school_readiness1 emotions1 school_readiness2 emotions2" fall under the domain "education and training". I would like to sum the observations by domain. I have labeled the variables accordingly. Thanks for any helkp! I alway struggle with creating tables... I get sort of in the weeds between tabulate, table, using parens, options, etc.
Code:
* Example generated by -dataex-. For more info, type help dataex clear input str8 id str10 date int ffy str25 admin_times byte(num_adults num_child num_schoolagechild basicneeds transportation housing childeldercare employment experience school_readiness1 emotions1 school_readiness2 emotions2) "210211" "1/27/2021" 2021 "1st time" 2 1 0 3 1 4 3 3 1 0 0 0 0 "210111" "2/4/2021" 2021 "1st time" 1 3 1 3 3 2 0 0 3 3 2 0 0 "210311" "3/29/2021" 2021 "1st time" 2 1 0 4 4 4 4 0 3 0 0 0 0 "210411" "4/16/2021" 2021 "1st time" 2 3 2 3 2 3 0 0 3 3 3 3 0 "211011" "5/24/2021" 2021 "1st time" 1 1 0 4 4 2 0 0 2 0 0 0 0 "210711" "5/25/2021" 2021 "1st time" 2 1 0 2 0 2 1 0 2 0 0 0 0 "210211" "7/29/2021" 2021 "2nd time" 2 1 1 3 2 3 3 2 1 2 4 0 0 "211111" "7/29/2021" 2021 "1st time" 1 1 1 3 4 1 3 2 3 3 3 0 0 "211311" "8/27/2021" 2021 "1st time" 3 3 0 3 1 3 2 2 2 0 0 0 0 "210F11" "9/1/2021" 2021 "1st time" 1 5 3 0 0 2 1 1 3 4 4 4 3 "210611" "9/20/2021" 2021 "1st time" 1 1 1 4 4 4 3 4 4 4 3 0 0 "210C11" "9/21/2021" 2021 "1st time" 1 2 2 2 2 3 1 0 3 4 4 1 1 "210B11" "9/24/2021" 2021 "1st time" 4 1 0 3 2 3 3 0 2 0 0 0 0 "211711" "9/28/2021" 2021 "1st time" 1 1 0 2 2 4 2 0 3 0 0 0 0 "211411" "9/29/2021" 2021 "1st time" 2 1 0 3 0 3 2 3 2 0 0 0 0 "211811" "11/12/2021" 2022 "1st time" 2 1 0 2 2 3 3 0 3 0 0 0 0 "211B11" "11/23/2021" 2022 "1st time" 1 1 1 2 2 3 0 4 4 2 3 0 0 "211C11" "12/8/2021" 2022 "1st time" 2 3 0 3 4 3 0 0 2 0 0 0 0 "211D11" "12/21/2021" 2022 "1st time" 4 7 0 3 4 4 3 0 3 0 0 0 0 "211F11" "1/6/2022" 2022 "1st time" 2 1 1 4 2 3 3 3 3 3 3 0 0 "220311" "1/10/2022" 2022 "1st time" 2 1 1 3 3 0 0 0 3 4 4 0 0 "210411" "1/14/2022" 2022 "2nd time" 1 3 2 3 2 2 2 2 3 3 3 3 3 "210211" "1/19/2022" 2022 "3rd time" 2 1 1 3 3 4 0 2 2 2 2 0 0 "211911" "1/27/2022" 2022 "1st time" 1 2 1 2 1 2 3 3 2 0 4 0 0 "220211" "2/2/2022" 2022 "1st time" 1 1 0 2 4 3 3 3 0 0 0 0 0 "211011" "2/3/2022" 2022 "2nd time" 1 1 0 3 4 0 2 0 4 0 0 0 0 "211111" "2/8/2022" 2022 "2nd time" 1 1 1 2 3 3 3 2 3 0 0 0 0 "220611" "2/10/2022" 2022 "1st time" 1 4 4 3 4 2 0 2 3 4 3 3 3 "211811" "2/21/2022" 2022 "2nd time" 2 1 1 2 2 2 4 2 3 3 2 0 0 "210F11" "3/1/2022" 2022 "2nd time" 3 6 3 3 4 3 3 0 3 4 4 0 4 "211311" "3/17/2022" 2022 "2nd time" 3 1 0 2 3 2 0 0 2 0 0 0 0 "220911" "3/18/2022" 2022 "1st time" 2 3 0 4 4 3 4 0 4 0 0 0 0 "210C11" "4/22/2022" 2022 "2nd time" 1 2 2 4 4 3 3 1 3 3 4 2 2 "220511" "5/4/2022" 2022 "1st time" 2 2 2 2 3 2 0 0 2 2 2 2 2 "211B11" "5/31/2022" 2022 "2nd time" 1 1 1 3 3 3 0 3 4 2 3 0 0 "221711" "6/14/2022" 2022 "1st time" 1 5 5 1 2 2 2 2 3 3 3 3 3 "211D11" "6/20/2022" 2022 "2nd time" 4 7 0 3 3 3 0 0 2 0 0 0 0 "221B11" "6/24/2022" 2022 "1st time" 1 1 0 2 2 2 3 1 2 0 0 0 0 "210B11" "7/5/2022" 2022 "2nd time" 3 1 0 3 4 3 3 2 3 0 0 0 0 "221D11" "7/14/2022" 2022 "1st time" 1 1 1 3 2 2 0 3 2 2 1 0 0 "2.2E+13" "7/25/2022" 2022 "1st time" 2 2 0 3 3 3 0 3 3 0 0 0 0 "211411" "7/26/2022" 2022 "2nd time" 2 2 1 4 4 2 0 0 0 4 3 0 0 "210211" "7/27/2022" 2022 "4th time" 2 1 1 2 2 2 3 2 1 3 2 0 0 "221A11" "7/27/2022" 2022 "1st time" 1 1 1 3 4 4 3 2 4 4 2 0 0 "2.21E+13" "7/28/2022" 2022 "1st time" 1 1 1 4 1 3 4 4 4 4 4 0 0 "210411" "7/29/2022" 2022 "3rd time" 2 3 . 3 2 3 3 3 3 0 0 0 0 "221811" "8/2/2022" 2022 "1st time" 2 1 0 2 2 2 3 3 4 0 0 0 0 "220611" "8/5/2022" 2022 "2nd time" 2 4 4 3 4 2 3 3 3 4 3 4 3 "220311" "8/17/2022" 2022 "2nd time" 2 2 2 2 2 3 3 3 2 0 3 3 3 "211111" "8/29/2022" 2022 "3rd time" 2 1 1 2 3 2 3 2 3 2 3 0 0 "220022" "9/2/2022" 2022 "1st time" 8 6 4 4 4 4 4 0 2 4 4 4 4 "220011" "9/2/2022" 2022 "1st time" 8 6 . 4 4 4 4 0 2 0 0 0 0 "220611" "9/22/2022" 2022 "3rd time" 2 6 4 4 3 3 0 0 3 4 4 4 4 "211B11" "9/26/2022" 2022 "3rd time" 1 1 1 3 3 3 0 3 3 2 3 0 0 "211911" "10/19/2022" 2023 "2nd time" 2 2 1 4 4 4 3 0 4 4 2 0 0 "211F11" "11/2/2022" 2023 "2nd time" 1 1 1 3 2 2 3 0 3 4 3 0 0 "211311" "11/4/2022" 2023 "3rd time" 2 1 0 3 4 4 1 0 2 0 0 0 0 "211B11" "11/14/2022" 2023 "4th time" 1 1 1 3 3 3 0 3 3 1 3 0 0 "221C11" "11/29/2022" 2023 "1st time" 2 1 0 2 2 2 3 2 2 0 0 0 0 "220511" "11/30/2022" 2023 "2nd time" 2 3 3 2 3 3 3 0 3 3 3 3 3 end
