text: 8.0 7.04.6 87.413.4 16.11409.525.9 11.1 3.6315.41983 1850.71984PANAMA 14.5 16.3 10.0 15.7 iO.8 !1.7 17.7 15.5 4.5 6.3 ,0.8 1.1 0.9 8.4 6.3 '.5 5.3 1.0 1.4 1.0 1.5 i.38.0 7.0 8.0 7.0 6.5 8~.3 70.0 40.1 35.0 40.1 35.0 40.1 8.0 7.0 8.0 8.0 7.0 200.7 175.0 8.0 7.0 8.0 7.0 8.0 7.0 7.088.4 44.3 26.3 167.6 48.1 657.4 177.1 136.4 88.6 42.1 44.3 91.2 13.5 12.4 76.1 11.8 1039.7 836.8 3.1 70.2 98.9 88.66.4 101.7 48.2 8.9 398.3 223.1 40.2 100.0 13.0 7.0 6.1 7.1 79.6 67.6 19.9 16.0 13.4 16.95.4 2.3 17.8 40.1 97.5 95.9 36.7 39.5 18.2 137.4 2.7 1.3 114.5 133.6 3.1 2.0 366.726.0 29.4 176.1 55.8 156.5151.2 8.6 58.2 54.8 28.7 30.012.0 36.1 16.6 70.8 600.3 721.9 84.3 45.6 22.0 18.8 472.2 686.2 8.9 .4 81.4 34.8 -13-.9 .2 3.1 3.1 703.7 18.8 .9 .5 .2 1.2 .5 .2 56.8 29.7 .3 .6 .3 .26.3 .3 21.7 10.7 .1 96.3 3.6 17.0 1.3 .7 .3 2.0 .7 .3 297.7 119.5 .4 1.2 .3 28.9 25.0 .3246.91983 197.71984 56.41983 111.01904 443.21983 606.51984 1680.91983 996.11984 12376.11983 16135.21984 3063.41983 3280.41984 444.21983 867.81984 473.01983 732.11984 230.81983 151.51984 1983 42.81984 63.11983 28.01984 81.61983 93.41984 118.51983 94.71984 242.91983 55.01984 13189.01983 14042.01984 227.11983 190.61984 145.61983 118.21984 65.11983 120.21984 1502.21983 1300.11984 58.81983 104.51984PAPUANEWGUINEA PARAGUAY PERU PHILIPPINES POLAND POR'l'IlGAL QATAR ROMANIA RWANDA SAINTCHRISTOPHER ANDNEVIS SAINTLUCIA SAINTVINCENT AND THEGRENADINES SAMOA SADTOMEAND PRINCIPE SAUDIARABIA SENEGAL SEYCHELLES SIERRA LEONE SINGAPORE SOLOMON ISLANDSUNITED NATIONS UNITED NATIONS COUNTRY YEAR REGULAR lIUDGET TRUSTFUNDS ILO FAO UNESCO WHO IC'AOUP SOMALIA 1983 104.9 17.1 58.1 21.3 1984 10.7 37.7 SOUTHAFRICA 1983 125.881984 154.47 SPAIN 1983 17135.7 7329.5 3412.7 3748.7 385.6 1984 12538.9 10.4 4518.0 4718.5 2115.6 4475.5 544.5200 175 SRILANKA 1983 58.8 1.0 24.7 34.6 14.5401984 65.0 12.7 19.7 94.4 90.035
analysis: The text appears to be a dataset containing statistical information related to countries, with columns for country names, years, and various economic and financial indicators. The data seems to be related to international organizations and countries' budgets, making it likely that it is related to economic development, international trade, or humanitarian aid and relief.