twoway connected

[Sana Elahi]

County Country_code Region_Name Income MIT2003 MIT2004 MIT2005 mean_MIT2003 mean_2004 mean_2005

Aruba ABW Latin America & the Carribean High 60.6 58.5 62.5
Afghanistan AFG South Asia Low 20 20 20.5

So above is my data set in this form. I have data on marginal tax rate for a couple of years by country. I created a mean variable by region for all the years ( for e.g. mean_MIT2003).
I want to put the data in the following way:

Reg_Name	2003	2004	2005	2006	2007	2008	2009	2010	2011	2012	2013	2014	2015	2016	2017	2018
East Asia & Pacific	36.967	36.333	36.2	36	35.667	35.6	34.8	34.567	34.4	34.6	31.324	31.324	29.886	30.682	30.787	30.247
Europe & Central Asia	37.17	35.879	34.855	34.956	34.151	32.984	32.526	32.988	32.895	33.277	31.883	32.117	31.661	31.807	32.408	32.28
Latin America & The Caribbean	26.445	26.386	26.062	26.004	27.085	27.615	27.747	28.303	27.747	28.392	27.776	27.776	27.933	27.878	28.391	28.732
Middle East & North Africa	14.917	15.25	15.25	15.25	14	13.917	13.833	13.917	12.583	12.833	16.933	16.933	16.933	16.813	17.031	17.031
North America	21.333	21.333	21.333	21.333	21.333	21.333	21.333	21.333	21.333	21.333	22.867	22.867	22.867	24.2	24.2	23.333
South Asia	25	25	26.25	26.25	23.75	23.75	23.75	23.75	23.75	23.75	24.598	25.598	25.598	24.108	24.308	25.976
Sub - Saharan Africa	29.817	29.817	29.244	28.672	29.27	27.881	26.805	27.005	26.732	28.696	31.059	31	31.361	31.079	31.524	31.286

So that I can create a twoway connected graph as attached.

Should I reshape the data? Can someone help please. Thank you.

[Nick Cox]

As far as I can understand it, your present data layout is not good for what you want, as you know, but you don't want to get to the data layout you outline either.

Let me repeat advice given to you in three previous threads you started.

https://www.statalist.org/forums/for...query-in-stata

https://www.statalist.org/forums/for...wer-thresholds

https://www.statalist.org/forums/for...-the-bar-graph

To give good advice, we need to see a data example, and we need to see an example in a way we ourselves can copy and paste into Stata. That means using dataex.

Here's the important advice all at one place. https://www.statalist.org/forums/help#stata

[Sana Elahi]

Country	Country_Code	Region_Name	Income	MIT2003	MIT2004	MIT2005	MIT2006	MIT2007	MIT2008	MIT2009	MIT2010	MIT2011	MIT2012	MIT2013	MIT2014	MIT2015	MIT2016	MIT2017	MIT2018	mean_MIT_03	mean_MIT_04	mean_MIT_05	mean_MIT_06	mean_MIT_07	mean_MIT_08	mean_MIT_09	mean_MIT_10	mean_MIT_11	mean_MIT_12	mean_MIT_13	mean_MIT_14	mean_MIT_15	mean_MIT_16	mean_MIT_17	mean_MIT_18
Aruba	ABW	Latin America & The Caribbean	High	60.06	60.06	60.06	60.06	58.95	58.95	58.95	58.95	58.95	58.95	58.95	58.95	58.95	58.95	58.95	59	28.0975	28.035	27.69125	27.62875	28.77813	29.34063	29.37941	29.96765	29.37941	29.96944	28.20227	28.20227	28.42955	28.36136	29.0413	29.41304
Afghanistan	AFG	South Asia	Low Income	20	20	20	20	20	20	20	20	20	20	20	20	20	20	20	20	25	25	26.25	26.25	23.75	23.75	23.75	23.75	23.75	23.75	24.598	25.598	25.598	24.108	24.308	25.976
Angola	AGO	Sub-Saharan Africa	Upper-Middle Income	15	15	15	15	15	15	15	17	17	17	17	17	17	17	17	17	30.41875	30.41875	29.775	29.13125	29.80375	28.24125	27.00556	27.22778	26.905	29.03182	31.4375	31.35294	31.73529	31.41667	31.85	31.6
Albania	ALB	Europe and Central Asia	Upper-Middle Income					25	10	10	10	10	10	10	23	23	23	23	23	37.49429	36.12886	35.04629	35.23111	34.42892	33.19316	32.71105	33.14579	33.04763	33.44895	31.97463	32.21762	31.74048	31.89286	32.52214	32.38833
United Arab Emirates	ARE	Middle East & North Africa	High	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	14.91667	15.25	15.25	15.25	14	13.91667	13.83333	13.91667	12.58333	12.83333	16.93333	16.93333	16.93333	16.8125	17.03125	17.03125
Argentina	ARG	Latin America & The Caribbean	Upper-Middle Income	35	35	35	35	35	35	35	35	35	35	35	35	35	35	35	35	28.0975	28.035	27.69125	27.62875	28.77813	29.34063	29.37941	29.96765	29.37941	29.96944	28.20227	28.20227	28.42955	28.36136	29.0413	29.41304
Armenia	ARM	Europe and Central Asia	Lower-Middle Income	20	20	20	20	20	20	20	20	20	25	25	36	36	36	36	36	37.49429	36.12886	35.04629	35.23111	34.42892	33.19316	32.71105	33.14579	33.04763	33.44895	31.97463	32.21762	31.74048	31.89286	32.52214	32.38833
Antigua and Barbuda	ATG	Latin America & The Caribbean	High											25	25	25	25	25	25	28.0975	28.035	27.69125	27.62875	28.77813	29.34063	29.37941	29.96765	29.37941	29.96944	28.20227	28.20227	28.42955	28.36136	29.0413	29.41304
Australia	AUS	East Asia & Pacific	High	47	47	47	47	45	45	45	45	45	45	45	45	45	45	45	45	36.75	36.07143	35.92857	35.71429	35.35714	35.28571	34.42857	34.17857	34	34.21429	30.81412	30.81412	29.04667	29.88611	29.99722	29.73421
Austria	AUT	Europe and Central Asia	High	50	50	50	50	50	50	50	50	50	50	50	50	50	55	55	55	37.49429	36.12886	35.04629	35.23111	34.42892	33.19316	32.71105	33.14579	33.04763	33.44895	31.97463	32.21762	31.74048	31.89286	32.52214	32.38833
Belgium	BEL	Europe and Central Asia	High	50	50	50	50	50	50	50	50	50	50	50	50	50	50	50	50	37.49429	36.12886	35.04629	35.23111	34.42892	33.19316	32.71105	33.14579	33.04763	33.44895	31.97463	32.21762	31.74048	31.89286	32.52214	32.38833
Bangladesh	BGD	South Asia	Lower-Middle Income	25	25	25	25	25	25	25	25	25	25	25	30	30	30	30	30	25	25	26.25	26.25	23.75	23.75	23.75	23.75	23.75	23.75	24.598	25.598	25.598	24.108	24.308	25.976
Bulgaria	BGR	Europe and Central Asia	Upper-Middle Income	29	29	24	24	24	10	10	10	10	10	10	10	10	10	10	10	37.49429	36.12886	35.04629	35.23111	34.42892	33.19316	32.71105	33.14579	33.04763	33.44895	31.97463	32.21762	31.74048	31.89286	32.52214	32.38833
Bahrain	BHR	Middle East & North Africa	High	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	14.91667	15.25	15.25	15.25	14	13.91667	13.83333	13.91667	12.58333	12.83333	16.93333	16.93333	16.93333	16.8125	17.03125	17.03125
Bahamas	BHS	Latin America & The Caribbean	High	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	28.0975	28.035	27.69125	27.62875	28.77813	29.34063	29.37941	29.96765	29.37941	29.96944	28.20227	28.20227	28.42955	28.36136	29.0413	29.41304
Bosnia and Herzegovina	BIH	Europe and Central Asia	Upper-Middle Income	10	10	10	10	10	10	10	10	10	10	10	10	10	10	10	10	37.49429	36.12886	35.04629	35.23111	34.42892	33.19316	32.71105	33.14579	33.04763	33.44895	31.97463	32.21762	31.74048	31.89286	32.52214	32.38833
Belarus	BLR	Europe and Central Asia	Upper-Middle Income											12	12	13	13	13	13	37.49429	36.12886	35.04629	35.23111	34.42892	33.19316	32.71105	33.14579	33.04763	33.44895	31.97463	32.21762	31.74048	31.89286	32.52214	32.38833
Brazil	BRA	Latin America & The Caribbean	Upper-Middle Income	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	27.5	28.0975	28.035	27.69125	27.62875	28.77813	29.34063	29.37941	29.96765	29.37941	29.96944	28.20227	28.20227	28.42955	28.36136	29.0413	29.41304
Barbados	BRB	Latin America & The Caribbean	High										35	35	35	35	33.5	33.5	40	28.0975	28.035	27.69125	27.62875	28.77813	29.34063	29.37941	29.96765	29.37941	29.96944	28.20227	28.20227	28.42955	28.36136	29.0413	29.41304
Brunei Darussalam	BRN	East Asia & Pacific	High													0	0	0	0	36.75	36.07143	35.92857	35.71429	35.35714	35.28571	34.42857	34.17857	34	34.21429	30.81412	30.81412	29.04667	29.88611	29.99722	29.73421
Canada	CAN	North America	High	29	29	29	29	29	29	29	29	29	29	29	29	29	33	33	33	32	32	32	32	32	32	32	32	32	32	34.3	34.3	34.3	36.3	36.3	35

[Nick Cox]

Sorry, no; that is not using dataex.

[Sana Elahi]

I have attached the data in excel.

[Nick Cox]

The link in #2 explains why spreadsheet attachments are really not a good idea either.