I'm trying to build three tables (each one for a country based on var country_id) in excel. AN example of a country looks like this:
I can get produce results for each category (safe water, adeq food and basic edu) by collapsing data, for example:
Code:
preserve collapse (mean) share_clean_fuels (count)num_obs [weight=wt_hh], by ( country_id adeq_food inc_decile_wght_hh) xpose,clear
So:
1) Is there a way to append results from stata to an existing excel sheet by specifying column and row?
2) is it possible to build a table in stata that looks like the one above? which function should I use?
Any help will be very appreciated as it would save me tons of time in producing these tables in excel. Thank you!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(country_id inc_decile_wght_hh) double wt_hh float(share_clean_fuels clean_drink_water adeq_food basic_edu_both num_obs) 1 9 293.0574035644531 13.016968 1 1 0 1 1 6 293.05743408203125 5.097307 1 1 1 1 1 1 293.05743408203125 .13516809 0 1 0 1 1 8 293.05743408203125 10.114495 1 1 0 1 1 9 293.05743408203125 2.1032376 0 1 0 1 1 3 293.05743408203125 2.638437 1 1 0 1 1 3 280.3486022949219 100 1 1 0 1 1 3 280.3486022949219 2.58706 1 1 0 1 1 10 280.3486022949219 .1801425 1 1 1 1 1 6 280.3486022949219 .6729252 1 1 0 1 1 2 280.3486022949219 1.2994117 0 1 0 1 1 8 292.9923400878906 43.59368 0 1 1 1 1 7 292.9923400878906 1.845998 1 1 0 1 1 8 292.9923400878906 2.721675 0 1 0 1 1 4 292.9923400878906 .2703528 0 1 0 1 1 8 292.9923400878906 100 0 1 0 1 1 5 292.9923400878906 100 1 1 1 1 1 4 621.49072265625 .9786306 1 1 0 1 1 3 621.49072265625 .5164462 1 1 0 1 1 1 621.49072265625 .5868586 1 1 0 1 1 4 621.49072265625 .4348797 1 1 1 1 1 4 621.49072265625 .879786 1 1 0 1 1 3 621.49072265625 1.496123 1 1 0 1 1 2 621.49072265625 .14939886 1 1 1 1 1 8 621.49072265625 10.10629 0 1 1 1 1 9 621.49072265625 9.39954 1 1 0 1 1 4 621.49072265625 100 1 1 1 1 1 9 621.49072265625 100 1 1 1 1 1 3 621.49072265625 .8172332 1 1 1 1 1 10 594.6710815429688 2.669023 1 1 0 1 1 7 594.6710205078125 .7204735 1 1 0 1 1 1 594.6710205078125 1.1096567 1 1 0 1 1 6 594.6710815429688 2.948138 1 1 0 1 1 6 594.6710205078125 2.185974 1 1 0 1 1 4 594.6710815429688 8.831465 1 1 1 1 1 5 621.49072265625 .39879015 0 1 0 1 1 10 621.49072265625 2.721675 1 1 0 1 1 5 621.49072265625 1.1613582 1 1 0 1 1 1 621.49072265625 .9239903 1 1 0 1 1 10 621.49072265625 2.723702 1 1 0 1 1 5 621.49072265625 1.4160714 1 1 0 1 1 5 709.1865234375 100 1 1 0 1 1 5 709.1865844726563 44.9127 1 1 0 1 1 7 709.1865234375 35.05869 1 1 1 1 1 10 709.1865234375 100 1 1 0 1 1 10 709.1865234375 46.91713 1 1 0 1 1 4 709.1865234375 5.002633 1 1 0 1 1 10 709.3441162109375 54.03467 1 1 1 1 1 9 709.3440551757813 100 1 1 0 1 1 8 709.3441162109375 100 1 1 1 1 1 10 709.3440551757813 79.49864 1 1 1 1 1 9 709.3440551757813 100 1 1 1 1 1 1 709.3440551757813 100 1 1 0 1 1 10 709.3441162109375 29.13664 1 1 1 1 1 10 709.3440551757813 100 1 1 1 1 1 4 709.1865234375 100 0 1 0 1 1 1 709.1865234375 2.331698 1 1 0 1 1 3 709.1865234375 1.523302 1 1 1 1 1 6 709.1865234375 2.0540721 1 1 0 1 1 7 709.1865234375 1.837703 1 1 0 1 1 8 709.1865844726563 9.268721 1 1 1 1 1 10 678.5824584960938 100 1 1 1 1 1 10 678.5824584960938 100 1 1 0 1 1 7 678.5824584960938 100 1 1 0 1 1 5 678.5824584960938 .50563604 1 1 0 1 1 8 709.1865844726563 3.384126 1 1 0 1 1 6 709.1865234375 2.161576 1 1 0 1 1 6 709.1865234375 3.7826114 1 1 0 1 1 7 709.1865844726563 18.756695 1 1 1 1 1 8 709.1865234375 100 1 1 1 1 1 6 709.1865234375 1.1050651 1 1 0 1 1 5 709.3441162109375 8.61513 1 1 0 1 1 8 709.3441162109375 4.841481 1 1 0 1 1 4 709.3440551757813 .4212497 1 1 0 1 1 6 709.3440551757813 .3847249 1 1 0 1 1 8 709.3441162109375 3.522251 1 0 0 1 1 7 709.3441162109375 .3755092 1 1 0 1 1 6 1357.1649169921875 100 1 1 0 1 1 5 1357.1649169921875 .48106995 1 1 0 1 1 2 1357.1649169921875 2.3599381 1 0 0 1 1 4 1357.1649169921875 2.162031 1 1 0 1 1 6 1357.1649169921875 .7953057 1 1 0 1 1 2 1357.1649169921875 .7133285 1 1 0 1 1 9 709.1865234375 1.4885077 1 1 0 1 1 2 709.1865234375 .6814974 1 1 0 1 1 7 709.1865234375 1.0896412 1 0 0 1 1 7 709.1865234375 .4216659 1 0 0 1 1 6 709.1865844726563 .4804441 1 0 0 1 1 6 709.1865234375 14.915644 1 1 0 1 1 5 709.3440551757813 100 1 1 0 1 1 9 709.3440551757813 100 1 1 1 1 1 8 709.3440551757813 1.288522 1 0 1 1 1 8 709.3440551757813 42.56044 1 1 0 1 1 7 709.3440551757813 20.40264 1 0 0 1 1 9 709.3440551757813 7.307757 1 1 0 1 1 5 1357.1649169921875 18.288853 1 1 0 1 1 1 1357.1649169921875 100 1 1 1 1 1 4 1357.1649169921875 100 1 1 1 1 1 8 1357.1649169921875 100 1 1 0 1 1 8 1357.1649169921875 100 1 1 1 1 end
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