Task: Transform-by-output-target-schema (source dataset: github-pipelines)

Your task is to create a data transformation pipeline in Python using pandas libraries.

Given Source Tables below, and a Target Schema provided by users that demonstrates how the desired output table should look like schematically, please write Python pandas code that can transform the Source Tables into an output table, that matches the schema/structure given by the Target Schema.  Please note that the data values in the Target Schema are intended to represent the format and layout of the output table, but may not exactly match the actual data generated from the Source Tables when the python code is run on the Source Tables.

Use operations such as merge, groupby, pivot, apply, or any appropriate python or pandas steps. Your code should save the resulting DataFrame to a CSV file named 'output.csv'. Ensure that the code is executable and can be run directly as is, in a Python environment with pandas installed.

Source Tables:


Table #1
Filename: source_0.csv
Sample Rows in Markdown:
| Country Name                                 | Country Code   | Indicator Name                           | Indicator Code   | 1960             | 1961             | 1962             | 1963             | 1964             | 1965             | 1966             | 1967             | 1968             | 1969             | 1970             | 1971             | 1972             | 1973             | 1974             | 1975             | 1976             | 1977             | 1978             | 1979             | 1980             | 1981             | 1982             | 1983             | 1984             | 1985             | 1986             | 1987             | 1988             | 1989             | 1990             | 1991             | 1992             | 1993             | 1994             | 1995             | 1996             | 1997             | 1998             | 1999             | 2000             | 2001             | 2002             | 2003             | 2004             | 2005             | 2006             | 2007             | 2008             | 2009             |        2010 | 2011              | 2012             | 2013             | 2014             | 2015             |
|:---------------------------------------------|:---------------|:-----------------------------------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|:-----------------|------------:|:------------------|:-----------------|:-----------------|:-----------------|:-----------------|
| Latin America & Caribbean                    | LCN            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   | 803492775873.73  | 855792516560.91  | 896332360603.19  | 918608440831.59  | 987179926351.33  | 1038345019636.03 | 1079987315360.1  | 1127446052644.87 | 1215718573711.55 | 1292608845512.47 | 1379445187762.22 | 1471137532260.83 | 1576329120935.16 | 1711801326651.32 | 1820987958568.73 | 1889059822966.05 | 2005147417794.85 | 2101919442461.44 | 2184154321386.97 | 2328780651995.4  | 2472821137035.86 | 2478330458346.96 | 2458532710887.2  | 2392232376950.36 | 2487688956245.23 | 2576849084249.63 | 2694543860775.02 | 2786948139597.17 | 2811915926072.34 | 2849488889898.49 | 2863308943317.15 | 2970144261326.46 | 3056858353671.76 | 3176854219523.04 | 3322465539752.78 | 3379511742275.24 | 3493595762867.2  | 3671461535826.69 | 3749327081167.21 | 3750171041692.96 | 3890245734886.18 | 3929826757578.77 | 3941515772815.7  | 4005528586604.86 | 4254863315937.74 | 4448018711859.55 | 4686198072832.65 | 4951043779487.34 | 5143422555736.13 | 5079715995191.5  | 5.37141e+12 | 5617852993488.28  | 5783815964922.36 | 5947359876834.43 | 6005712877419.32 | 5949253110743.19 |
| Least developed countries: UN classification | LDC            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  | 231902869710.59  | 234976892317.06  | 243647990482.4   | 256002585699.96  | 263947913982.23  | 269608361594.57  | 270693327156.87  | 274391789886.05  | 274132349275.54  | 270546837698.85  | 275719597991.34  | 290632469638.97  | 307774809357.5   | 324334230129.24  | 338274198907.16  | 352186016340.38  | 366348951068.8   | 386472197704.43  | 398305292431.19  | 419899836177.49  | 447872259494.02  | 484875993201.5   | 524673924193.4   | 573881121152.14  | 616405655304.96  | 643868091980.84  | 6.78321e+11 | 703712767747.74   | 733216921317.4   | 773931630291.01  | 816427072781.96  | 852680108728.95  |
| Low income                                   | LIC            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  | 123596122575.81  | 124650988050.14  | 126578655663.25  | 129689351855.76  | 134191757295.56  | 138372118363.24  | 143289894438.36  | 145516469948.75  | 146138388943.5   | 146526910536.92  | 141107774848.77  | 140803602032.49  | 143060087092.56  | 148590010896.56  | 157432500810.56  | 162843585627.14  | 167866854686.44  | 173162797926.55  | 176301638180.71  | 184204020516.56  | 188349788536.15  | 194136142150.86  | 204631534828.05  | 217242808395.76  | 228873853670.31  | 243750946262.29  | 256483839242.58  | 270963748763.51  | 2.89212e+11 | 306224526424.11   | 319094281579.07  | 337853612417.38  | 358219286655.45  | 375031695102.66  |
| Liechtenstein                                | LIE            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  | 5.08234e+09 |                   |                  |                  |                  |                  |
| Sri Lanka                                    | LKA            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   |                  | 5924493033.62    | 6150691336.36    | 6305488774.1     | 6551808520.8     | 6718024859.26    | 7055524282.15    | 7509831214.04    | 7945483594.76    | 8558622235.09    | 8887840752.84    | 9003996423.28    | 8967036826.76    | 9599876388.25    | 9969071394.64    | 10579799952.23   | 10932647568.42   | 11490277125.88   | 12139918649.08   | 12917305250.54   | 13672454340.66   | 14451719262.01   | 15050236594.15   | 15774753624.7    | 16579131431.17   | 17407989583.82   | 18166202737.37   | 18479680674.3    | 18936624973.35   | 19372035058.74   | 20611844394.12   | 21559986606.75   | 22508624131.35   | 24061733433.57   | 25409170950.2    | 26806697009.22   | 27825342704.38   | 29607667121.86   | 30998760577.36   | 32331874829.85   | 34271798040.94   | 33742158886.29   | 35079926055.48   | 37163768055.4    | 39187357999.19   | 41633334150.86   | 44825899741.29   | 47872638202.97   | 50721102373.42   | 52516077578.72   | 5.67257e+10 | 61493395362.82    | 67116707719.92   | 69395796204.82   | 72781341623.58   | 76264645401.51   |
| Lower middle income                          | LMC            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   | 525762516667.12  | 544989806881.86  | 564392867681.16  | 592080758998.55  | 628319327881.36  | 638027873499.0   | 644513970526.53  | 657315438848.66  | 687892817047.77  | 742144893162.8   | 802215163223.06  | 841668628645.51  | 860506511351.18  | 904831720784.64  | 953488539186.43  | 995456509187.53  | 1052443419558.61 | 1123984702863.02 | 1172498702764.27 | 1192957588064.43 | 1258222444113.3  | 1292530753011.84 | 1327842208678.22 | 1384438344944.73 | 1424254696374.37 | 1480380341886.16 | 1527425737283.83 | 1568555255433.73 | 1666198816958.44 | 1758435266817.65 | 1832529392680.27 | 1861335848182.54 | 1909068387576.59 | 1955516156018.81 | 2013735916576.92 | 2109874242324.22 | 2232486100694.97 | 2319162536594.93 | 2331053458277.18 | 2437217356146.36 | 2543239266653.39 | 2652431438549.63 | 2754006660327.36 | 2928139416321.77 | 3173936873435.2  | 3383451291348.84 | 3633146863611.6  | 3895562896471.63 | 4080416700807.0  | 4284426432092.9  | 4.60154e+12 | 4849873628068.09  | 5098203082659.83 | 5382492748134.26 | 5682391878693.79 | 5993615561341.78 |
| Low & middle income                          | LMY            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   | 2054620647431.25 | 2093274785702.67 | 2182874344801.12 | 2302578939468.0  | 2473393228700.0  | 2604222573541.16 | 2726945110564.33 | 2828390963296.82 | 3016766807864.45 | 3242829597530.21 | 3515468100599.44 | 3735116787108.46 | 3982382576863.52 | 4287452008595.33 | 4546644471437.42 | 4754083555052.71 | 5092416866772.74 | 5312250247908.3  | 5509581878372.01 | 5720978842684.08 | 5978197400641.91 | 6098640585313.9  | 6265337030310.67 | 6343776311800.08 | 6632526847102.54 | 6957920380429.14 | 7223130304136.32 | 7542444479044.07 | 7842787608623.9  | 8096702906928.17 | 8279711169538.0  | 8353954606315.69 | 8390604470058.07 | 8614351693634.12 | 8813994547200.36 | 9152037770591.46 | 9586837271189.19 | 10043574520871.1 | 10229975266163.6 | 10581749299974.1 | 11190464394783.6 | 11603993120683.4 | 12121970123539.6 | 12769877032161.3 | 13795963846946.4 | 14767250351505.0 | 15959067366171.9 | 17333009519927.6 | 18322969434214.8 | 18782902860568.0 | 2.01885e+13 | 21389841895354.39 | 22476856222199.2 | 23580436917544.0 | 24604834350986.0 | 25483438593057.1 |
| Lesotho                                      | LSO            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   | 208563606.9      | 212452896.37     | 245025776.08     | 271035439.62     | 293398890.39     | 299719009.12     | 298503584.12     | 331076484.58     | 329861038.84     | 334965753.31     | 342258199.59     | 359760323.7      | 359031052.11     | 453832770.8      | 503664013.48     | 435601395.84     | 483731557.89     | 589228734.49     | 697157030.71     | 717332189.68     | 697642997.45     | 702489100.71     | 720450353.57     | 737078003.01     | 773554130.44     | 793342233.31     | 837006794.25     | 837018802.91     | 908639798.01     | 958402701.29     | 1012496725.37    | 1052031720.07    | 1128361019.66    | 1165942171.29    | 1228268697.24    | 1252804220.87    | 1318121378.4     | 1371973072.43    | 1395900136.91    | 1401512097.7     | 1473554577.85    | 1535874197.27    | 1544050824.69    | 1616484633.44    | 1653530871.14    | 1698250617.27    | 1771401813.4     | 1855250499.99    | 1961620803.13    | 2027490711.28    | 2.18748e+09 | 2276044148.4      | 2389701173.48    | 2496306485.34    | 2587149144.08    |                  |
| Late-demographic dividend                    | LTE            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   | 1027826175090.95 | 1023379622852.27 | 1057263300659.56 | 1095855613836.74 | 1168607651136.28 | 1242153452203.93 | 1322276972357.64 | 1357682058697.46 | 1450816171380.4  | 1594156296627.79 | 1753831314141.22 | 1901710110108.79 | 2059442390344.79 | 2260480426618.85 | 2406404816272.17 | 2522743450943.81 | 2702368240299.43 | 2873181310448.02 | 3029230521502.85 | 3255006936267.12 | 3525664007447.28 | 3519249062314.39 | 3582502128354.28 | 3603908268042.39 | 3865955897179.12 | 4148664721417.77 | 4397070976383.02 | 4657311874005.91 | 4866658275655.15 | 5079590059373.19 | 5097402095113.98 | 5117000377165.69 | 5077870205975.88 | 5242700219632.98 | 5417815598352.63 | 5690940440614.7  | 5941419864120.9  | 6237879076820.82 | 6368925825507.41 | 6628012206408.17 | 7071334760694.95 | 7410956460598.67 | 7816777614383.49 | 8314372182086.73 | 8953338775600.77 | 9596721718936.97 | 10433040517155.9 | 11433935872898.3 | 12180529524202.3 | 12490094899749.6 | 1.34404e+13 | 14329639738667.9  | 15091313294262.6 | 15859913824034.3 | 16567845863790.6 | 17123636815101.3 |
| Lithuania                                    | LTU            | GDP at market prices (constant 2010 US$) | NY.GDP.MKTP.KD   |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  |                  | 19321871754.1    | 20316940116.58   | 22001870429.25   | 23644788818.23   | 23376504901.96   | 24272214758.87   | 25855838632.75   | 27603887122.41   | 30512940646.52   | 32511563593.0    | 35023864732.37   | 37617887784.84   | 41788565845.25   | 42886801934.28   | 36533481054.58   | 3.71326e+10 | 39377194356.12    | 40887547827.23   | 42336907127.71   | 43620761128.77   | 44315977742.44   |


Table #2
Filename: source_1.csv
Sample Rows in Markdown:
|   Rank | Country            |   Documents |   Citable documents |   Citations |   Self-citations |   Citations per document |   H index |
|-------:|:-------------------|------------:|--------------------:|------------:|-----------------:|-------------------------:|----------:|
|      1 | China              |      127050 |              126767 |      597237 |           411683 |                     4.7  |       138 |
|      2 | United States      |       96661 |               94747 |      792274 |           265436 |                     8.19 |       230 |
|      3 | Japan              |       30504 |               30287 |      223024 |            61554 |                     7.31 |       134 |
|      4 | United Kingdom     |       20944 |               20357 |      206091 |            37874 |                     9.84 |       139 |
|      5 | Russian Federation |       18534 |               18301 |       34266 |            12422 |                     1.85 |        57 |
|      6 | Canada             |       17899 |               17620 |      215003 |            40930 |                    12.01 |       149 |
|      7 | Germany            |       17027 |               16831 |      140566 |            27426 |                     8.26 |       126 |
|      8 | India              |       15005 |               14841 |      128763 |            37209 |                     8.58 |       115 |
|      9 | France             |       13153 |               12973 |      130632 |            28601 |                     9.93 |       114 |
|     10 | South Korea        |       11983 |               11923 |      114675 |            22595 |                     9.57 |       104 |


Table #3
Filename: source_2.csv
Sample Rows in Markdown:
| Country             | Energy Supply   | Energy Supply per Capita   |   % Renewable |
|:--------------------|:----------------|:---------------------------|--------------:|
| Afghanistan         | 321.0           | 10.0                       |         78.66 |
| Albania             | 102.0           | 35.0                       |        100    |
| Algeria             | 1959.0          | 51.0                       |          0.55 |
| American Samoa      |                 |                            |          0.64 |
| Andorra             | 9.0             | 121.0                      |         88.69 |
| Angola              | 642.0           | 27.0                       |         70.9  |
| Anguilla            | 2.0             | 136.0                      |          0    |
| Antigua and Barbuda | 8.0             | 84.0                       |          0    |
| Argentina           | 3378.0          | 79.0                       |         24.06 |
| Armenia             | 143.0           | 48.0                       |         28.23 |


Target Schema:
|   Rank |   Documents |   Citable documents |   Citations |   Self-citations |   Citations per document |   H index |   Energy Supply |   Energy Supply per Capita |   % Renewable |   2006 |   2007 |   2008 |   2009 |   2010 |   2011 |   2012 |   2013 |   2014 |   2015 |
|-------:|------------:|--------------------:|------------:|-----------------:|-------------------------:|----------:|----------------:|---------------------------:|--------------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|-------:|
|      1 |           1 |                   1 |           1 |                1 |                        1 |         1 |               1 |                          1 |             1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |
|      1 |           1 |                   1 |           1 |                1 |                        1 |         1 |               1 |                          1 |             1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |
|      1 |           1 |                   1 |           1 |                1 |                        1 |         1 |               1 |                          1 |             1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |
|      1 |           1 |                   1 |           1 |                1 |                        1 |         1 |               1 |                          1 |             1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |      1 |

Return only the final code in markdown codeblock format, without any additional text or explanation. 



target: target.csv
train: source_0.csv
source_1.csv
source_2.csv
test: test_0.csv
test_1.csv
test_2.csv