I have a panel data set with 159 countries between 2009 and 2017.
When I use Stargazer to create a table with summary statistics it uses the values for all years. E.g. the mean of GDP would be the mean value for all countries and years.
What I would like to get is the summary statistics of each year. E.g. Summary statistics for 2009, 2010,..., 2017.
The panel data set looks like this:
area_code year area_name area_group Executive Constraints Government Effectiveness
1 AFG 2009 Afghanistan Asia-Pacific 39.60269 28.00944
2 AFG 2010 Afghanistan Asia-Pacific 39.60269 28.07446
3 AFG 2011 Afghanistan Asia-Pacific 39.60269 20.82287
4 AFG 2012 Afghanistan Asia-Pacific 39.60269 20.85591
5 AFG 2013 Afghanistan Asia-Pacific 39.60269 21.32710
6 AFG 2014 Afghanistan Asia-Pacific 39.60269 21.19488
7 AFG 2015 Afghanistan Asia-Pacific 39.60269 21.48040
8 AFG 2016 Afghanistan Asia-Pacific 38.26936 21.52523
9 AFG 2017 Afghanistan Asia-Pacific 38.93603 26.52632
10 AGO 2009 Angola Sub-Saharan Africa 37.83082 22.59876
11 AGO 2010 Angola Sub-Saharan Africa 37.83082 23.14201
12 AGO 2011 Angola Sub-Saharan Africa 37.83082 32.67216
13 AGO 2012 Angola Sub-Saharan Africa 37.83082 32.39330
14 AGO 2013 Angola Sub-Saharan Africa 37.83082 33.26756
15 AGO 2014 Angola Sub-Saharan Africa 37.83082 32.09595
Ideally I would like to get an output for a the year(s) specified.
E.g. For 2009:
Descriptive statistics 2009
================================================================================================================
Statistic N Mean St. Dev. Min Pctl(25) Pctl(75) Max
----------------------------------------------------------------------------------------------------------------
Executive Constraints 1,412 55.484 16.464 17.545 42.888 64.848 94.848
Government Effectiveness 1,412 52.581 21.991 8.305 36.281 65.687 96.493
You could use stargazer in an lapply after using split on your data frame to split by year. Here I have used the mtcars data set since there isn't really enough sample data in the question to demonstrate. This produces a summary table for each group of cars according to the number of cylinders they have. Of course, in your case you would instead split by year.
result <- lapply(split(mtcars, mtcars$cyl), stargazer::stargazer, type = "text")
#>
#> =============================================================
#> Statistic N Mean St. Dev. Min Pctl(25) Pctl(75) Max
#> -------------------------------------------------------------
#> mpg 11 26.664 4.510 21.400 22.800 30.400 33.900
#> cyl 11 4.000 0.000 4 4 4 4
#> disp 11 105.136 26.872 71 78.8 120.7 147
#> hp 11 82.636 20.935 52 65.5 96 113
#> drat 11 4.071 0.365 3.690 3.810 4.165 4.930
#> wt 11 2.286 0.570 1.513 1.885 2.622 3.190
#> qsec 11 19.137 1.682 16.700 18.560 19.950 22.900
#> vs 11 0.909 0.302 0 1 1 1
#> am 11 0.727 0.467 0 0.5 1 1
#> gear 11 4.091 0.539 3 4 4 5
#> carb 11 1.545 0.522 1 1 2 2
#> -------------------------------------------------------------
#>
#> ============================================================
#> Statistic N Mean St. Dev. Min Pctl(25) Pctl(75) Max
#> ------------------------------------------------------------
#> mpg 7 19.743 1.454 18 18.6 21 21
#> cyl 7 6.000 0.000 6 6 6 6
#> disp 7 183.314 41.562 145 160 196.3 258
#> hp 7 122.286 24.260 105 110 123 175
#> drat 7 3.586 0.476 2.760 3.350 3.910 3.920
#> wt 7 3.117 0.356 2.620 2.822 3.440 3.460
#> qsec 7 17.977 1.707 15.500 16.740 19.170 20.220
#> vs 7 0.571 0.535 0 0 1 1
#> am 7 0.429 0.535 0 0 1 1
#> gear 7 3.857 0.690 3 3.5 4 5
#> carb 7 3.429 1.813 1 2.5 4 6
#> ------------------------------------------------------------
#>
#> =============================================================
#> Statistic N Mean St. Dev. Min Pctl(25) Pctl(75) Max
#> -------------------------------------------------------------
#> mpg 14 15.100 2.560 10.400 14.400 16.250 19.200
#> cyl 14 8.000 0.000 8 8 8 8
#> disp 14 353.100 67.771 276 301.8 390 472
#> hp 14 209.214 50.977 150 176.2 241.2 335
#> drat 14 3.229 0.372 2.760 3.070 3.225 4.220
#> wt 14 3.999 0.759 3.170 3.533 4.014 5.424
#> qsec 14 16.772 1.196 14.500 16.098 17.555 18.000
#> vs 14 0.000 0.000 0 0 0 0
#> am 14 0.143 0.363 0 0 0 1
#> gear 14 3.286 0.726 3 3 3 5
#> carb 14 3.500 1.557 2 2.2 4 8
#> -------------------------------------------------------------
Created on 2020-08-22 by the reprex package (v0.3.0)