In [9]:
using DataFrames
using Gadfly

# Os imports das bibliotecas Cairo e Images permitem a publicação
# do notebook sem os erros em alguns gráficos do Gadfly
import Cairo
import Images

In [10]:
pop = readtable("../data/populationbycountry19802010millions.csv", nastrings=["","NA","--"])
pop


Out[10]:
Paisx1980x1981x1982x1983x1984x1985x1986x1987x1988x1989x1990x1991x1992x1993x1994x1995x1996x1997x1998x1999x2000x2001x2002x2003x2004x2005x2006x2007x2008x2009x2010
1North America320.27638324.44694328.62014332.72487336.72143340.74811344.89548349.07829353.2939357.68457362.4468367.70684373.29069378.74233383.9166388.97216393.9428398.97205403.85585408.60296413.3245417.83236422.05268426.06238430.26938434.47232438.82964443.3473447.67394451.83698456.59331
2Bermuda0.054730.054910.055170.055510.055850.056180.056510.056830.057170.057490.057780.05810.05870.059240.059750.060290.060870.061450.061980.062510.063060.063610.064180.064760.065340.065910.066440.066920.067390.067840.06827
3Canada24.593324.925.201925.456325.701825.941626.203826.549726.894827.379327.790628.117928.5448928.9533429.3308129.6905330.0263230.305630.5516630.8202631.0995631.3767431.6409631.8893132.1347632.3863832.6566832.9359633.212733.4872133.75974
4Greenland0.050210.051030.051660.052110.052630.053150.053640.05410.054850.055410.055630.055540.055490.055640.055920.056190.056340.056510.056610.05670.056890.057130.057360.057540.05770.057780.057640.057530.057560.05760.05764
5Mexico68.3474869.9692671.640973.3628875.0801476.7672378.4424380.1224981.7818283.3668484.9136586.4880388.1110389.7491491.337992.8803594.3985895.8951597.3250698.6169199.92662101.24696102.47993103.71806104.95959106.2029107.44953108.70089109.9554111.21179112.46886
6Saint Pierre and Miquelon0.005990.006010.006050.006070.006110.006160.006210.006250.006280.006310.006320.006330.006360.006380.00640.00640.006410.006420.006420.006430.006410.006370.006330.006290.006250.00620.006150.00610.006050.0060.00594
7United States227.22468229.46571231.66446233.79199235.8249237.9238240.13289242.28892244.49898246.81923249.62281252.98094256.51422259.91859263.12582266.27839269.39428272.64693275.8541279.04017282.17196285.08156287.80391290.32642293.04574295.75315298.59321301.5799304.37485307.00655310.23286
8Central & South America293.05856299.43033305.95253312.51136318.87955325.22704331.82291338.59859345.44544352.20471358.79973365.15137371.43224377.7438384.26984390.75665397.13002403.41352409.62879415.63607421.4539427.24012433.05116438.97976445.01525451.05504457.01699462.89157468.73872474.53897480.01228
9AntarcticaNANANANANANANANANANANANANANANANANANANANANANANANANANANANANANANA
10Antigua and Barbuda0.068550.068260.068010.065620.064470.06440.06440.064420.064430.064390.064160.064030.065180.066330.067490.068710.070060.071450.072780.074020.075350.076730.077940.079070.080190.081280.082340.083430.084520.085630.08675
11Argentina28.369828.8480629.3298829.7935530.2306430.6717631.1449931.6246232.0993232.5716233.0355833.5044133.9668534.4071534.8468935.2738435.6829636.1021636.5179236.9234237.3356537.6941737.9994538.3368838.7418339.1812639.6144340.0488240.48240.9135841.3432
12ArubaNANANANANANA0.05980.059180.05950.060690.063030.06630.069480.074070.077850.079960.083070.086210.08820.089260.090.090970.092170.093720.095460.096980.09850.100020.101540.103070.10459
13Bahamas, The0.209760.213450.217130.220860.224620.22820.231430.234480.237710.241240.245130.249310.253560.257660.261510.265180.268880.272560.275990.279310.282590.285690.288580.291350.294060.296710.299290.301970.304730.307550.31043
14Barbados0.251970.252360.253480.254850.256110.257250.258270.259120.259950.261090.262260.263340.26460.26570.266630.267670.268810.270060.271290.27250.273680.274910.276220.277550.278820.280040.281210.282360.28350.284590.28565
15Belize0.144420.149210.15330.156850.160810.165560.171240.176350.18140.186430.190870.195750.200820.206090.211550.217170.222970.228950.235130.241480.2480.254640.26130.267960.274620.281290.287950.294610.301270.30790.31452
16Bolivia5.44135.545225.642225.737435.834295.934946.041356.156376.283166.423146.57396.731486.893457.054347.214817.374877.53447.695157.85898.025568.19518.367458.542498.719068.895979.072949.249719.425949.601269.775259.94742
17Brazil123.01963125.99213129.02765131.96012134.69947137.38198140.19628143.02654145.87275148.65864151.17006153.58396156.03206158.51205161.01706163.54428166.08586168.63874171.20116173.76387176.31962178.86966181.41759183.95992186.4886188.99308191.46901193.91858196.34259198.73927201.10333
18Cayman Islands0.017080.01790.018520.019090.020020.020850.021440.022070.02450.025070.026360.027510.028680.030010.03130.032490.033680.034870.036060.037250.038440.039620.04080.041990.043160.044340.045520.046690.047860.049040.05021
19Chile11.0937211.282311.4871111.6866211.8797712.067812.26112.4645212.6786912.9023213.1289213.3536713.5741613.7894314.0012214.2066114.4054114.6010914.7921614.9765515.1557415.3318915.5039415.6719115.8356315.9950416.1508416.3038516.4541416.6017116.74649
20Colombia26.6312927.2148927.8260428.4549929.0954629.7476230.4103931.085331.7708732.4608533.1472533.8322134.5203235.205635.8876236.5318337.0979137.6199438.1325938.5638638.9103539.3124539.8049540.3510240.9221541.4877842.0462542.5973243.1411143.6773744.20529
21Costa Rica2.299122.357292.424372.494352.56762.644312.723382.799342.874122.949893.023273.093023.168363.256533.35123.444743.5363.625323.713743.800173.882583.956214.020954.083824.14674.208694.269774.331134.393244.455054.51622
22Cuba9.652989.711989.789229.881269.9737310.0656310.1443810.2168210.3055210.407910.5134410.6111410.6919110.7566710.8132610.8654510.911710.9518610.9985311.0529811.1058611.1558211.2026911.2466811.2878511.3261511.3615511.3940411.4239511.4516511.47746
23Dominica0.073890.073520.073810.074290.073990.073110.072380.071820.071340.070510.070010.070120.070280.070420.070920.071420.0710.070280.070040.070350.070820.071210.071530.071730.071930.072120.072250.072380.072510.072660.07281
24Dominican Republic5.696865.831715.968746.105826.241556.378556.516826.656966.798776.941877.083627.22487.362937.494287.624137.758977.898988.039948.182218.32528.468918.613558.75698.896589.032399.164479.295049.426239.558189.690799.82382
25Ecuador7.92058.141088.365858.593498.825839.061669.301089.545169.7941210.0482210.3180410.4299210.5538110.7536811.0125511.2656111.5264811.7924712.0506312.2683112.4458412.6291212.8272813.0741813.368413.6623213.9170614.1349614.3544714.573114.79061
26El Salvador4.570414.519724.479924.526714.593754.671054.758324.850144.938995.024785.109825.196245.286015.334155.39525.479835.564115.636815.711575.788375.849825.88375.901835.919855.935125.956225.970895.981756.006456.03066.05206
27Falkland Islands (Islas Malvinas)0.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.0020.002430.00260.00280.002850.00290.002930.002970.002970.002970.002970.002970.003140.003140.00314
28French Guiana0.070.070.070.080.080.090.090.10.110.110.120.120.130.130.140.150.150.160.170.170.170.177560.182240.186920.191310.191310.191310.191310.191310.191310.19131
29Grenada0.090160.092350.092410.092530.092740.093060.093550.094060.094290.09430.09420.094060.094650.095760.096750.097740.098650.099570.100390.100990.101610.102290.102840.103320.103970.104590.10520.105890.106560.10720.10782
30Guadeloupe0.3370.3390.3410.3450.350.3540.3580.3630.3670.380.390.40.410.410.420.420.430.430.430.430.430.431170.435680.440190.444520.444520.444520.444520.444520.444520.44452
&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip

transposição dos dados


In [11]:
paises = DataFrame()
paises[:Ano] = 1980:2010
for pais in pop[:Pais]
    dados = convert(DataArray{Float64,2}, pop[pop[:Pais] .== pais,2:end]).'
    paises[symbol(pais)] = dados[:,1]
end
paises


Out[11]:
AnoNorth AmericaBermudaCanadaGreenlandMexicoSaint Pierre and MiquelonUnited StatesCentral & South AmericaAntarcticaAntigua and BarbudaArgentinaArubaBahamas, TheBarbadosBelizeBoliviaBrazilCayman IslandsChileColombiaCosta RicaCubaDominicaDominican RepublicEcuadorEl SalvadorFalkland Islands (Islas Malvinas)French GuianaGrenadaGuadeloupeGuatemalaGuyanaHaitiHondurasJamaicaMartiniqueMontserratNetherlands AntillesNicaraguaPanamaParaguayPeruPuerto RicoSaint Kitts and NevisSaint LuciaSaint Vincent/GrenadinesSurinameTrinidad and TobagoTurks and Caicos IslandsUruguayVenezuelaVirgin Islands, U.S.Virgin Islands, BritishEuropeAlbaniaAustriaBelgiumBosnia and HerzegovinaBulgariaCroatiaCyprusCzech RepublicDenmarkFaroe IslandsFinlandFormer CzechoslovakiaFormer Serbia and MontenegroFormer YugoslaviaFranceGermanyGermany, EastGermany, WestGibraltarGreeceHungaryIcelandIrelandItalyLuxembourgMacedoniaMaltaMontenegroNetherlandsNorwayPolandPortugalRomaniaSerbiaSlovakiaSloveniaSpainSwedenSwitzerlandTurkeyUnited KingdomEurasiaArmeniaAzerbaijanBelarusEstoniaFormer U.S.S.R.GeorgiaKazakhstanKyrgyzstanLatviaLithuaniaMoldovaRussiaTajikistanTurkmenistanUkraineUzbekistanMiddle EastBahrainIranIraqIsraelJordanKuwaitLebanonOmanPalestineQatarSaudi ArabiaSyriaUnited Arab EmiratesYemenAfricaAlgeriaAngolaBeninBotswanaBurkina FasoBurundiCameroonCape VerdeCentral African RepublicChadComorosCongo (Brazzaville)Congo (Kinshasa)Cote dIvoire (IvoryCoast)DjiboutiEgyptEquatorial GuineaEritreaEthiopiaGabonGambia, TheGhanaGuineaGuinea-BissauKenyaLesothoLiberiaLibyaMadagascarMalawiMaliMauritaniaMauritiusMoroccoMozambiqueNamibiaNigerNigeriaReunionRwandaSaint HelenaSao Tome and PrincipeSenegalSeychellesSierra LeoneSomaliaSouth AfricaSudanSwazilandTanzaniaTogoTunisiaUgandaWestern SaharaZambiaZimbabweAsia & OceaniaAfghanistanAmerican SamoaAustraliaBangladeshBhutanBruneiBurma (Myanmar)CambodiaChinaCook IslandsFijiFrench PolynesiaGuamHawaiian Trade ZoneHong KongIndiaIndonesiaJapanKiribatiKorea, NorthKorea, SouthLaosMacauMalaysiaMaldivesMongoliaNauruNepalNew CaledoniaNew ZealandNiuePakistanPapua New GuineaPhilippinesSamoaSingaporeSolomon IslandsSri LankaTaiwanThailandTimor-Leste (East Timor)TongaU.S. Pacific IslandsVanuatuVietnamWake IslandWorld
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21981324.446940.0549124.90.0510369.969260.00601229.46571299.43033NA0.0682628.84806NA0.213450.252360.149215.54522125.992130.017911.282327.214892.357299.711980.073525.831718.141084.519720.0020.070.092350.3396.828680.761935.622873.543062.258370.3410.011790.234492.901731.99893.2508417.75483.238970.043480.1240.09920.352511.107840.007792.9481315.166260.099850.01142532.629472.724277.564639.8524NA8.86944NA0.63805NA5.121570.043864.7999615.3116NA21.9049754.27995NA16.7418361.660.029279.7293510.711850.23083.443456.52420.3654NA0.36365NA14.246054.099735.901969.8500822.25655NANANA37.75088.320496.4511246.2532356.58903268.11401NANANANA268.11401NANANANANANANANANANANA97.619150.3634341.4508213.70313.801342.253771.432192.95171.24951NA0.2492810.654939.049231.069729.39014493.6338619.407046.879573.564850.934446.474374.477769.047920.30022.412774.514940.340881.7237429.808028.922470.3448344.19610.27178NA40.359370.730840.6926611.170964.540360.8070616.987221.395181.9133.207688.938766.459676.950021.577650.9790519.8462212.36323NA6.23977.149580.515.308990.006580.096445.754460.06473.402155.828831.2431720.196610.6313119.2122.719576.6057112.725250.139095.830637.429222518.1368913.673680.033614.9232694.143140.461950.1928333.981817.0792997.000720.017650.646770.155690.10917NA5.1834699.15377154.13906117.648090.0584517.3840138.7233.336980.2609313.875210.157251.708830.0078515.010860.14253.183450.00290.975082.9171652.22760.160922.535370.2387415.3154918.1774347.9365NA0.091770.142830.1202654.90268NA4534.01064
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302009451.836980.0678433.487210.0576111.211790.006307.00655474.53897NA0.0856340.913580.103070.307550.284590.30799.77525198.739270.0490416.6017143.677374.4550511.451650.072669.6907914.57316.03060.003140.191310.10720.4445213.276520.752949.777977.83372.825930.4260.00510.227055.89123.360476.2908829.546963.967290.049480.160270.104570.481271.229950.022943.4943826.814840.109810.02449604.067252.982548.2102810.414344.613417.204694.489411.0847510.21195.500510.048865.25028NANANA62.9829682.32976NANA0.028810.7374310.007170.306694.5858.157330.491782.066720.405170.6721816.7164.6605438.4829210.7079222.011829.184185.463052.0056946.295249.059657.6392376.8055262.25857283.289682.9678.238679.648531.29937NA4.6158115.399445.431752.23153.555184.32075140.041257.349154.8848945.700427.60601208.441340.7287175.9676128.945577.23376.269292.692534.099322.909634.013130.8332925.3288721.762984.7984922.85824992.5822534.1781912.799298.791831.9908815.746239.5113318.87930.501184.7419210.329210.752444.0128168.6925420.617070.7246278.866640.633445.6471785.237341.514991.7780823.8878110.057981.5339639.002771.916133.583396.3243620.6535615.0287613.443233.129491.2842631.2851721.669282.1086615.30625149.229090.7661510.746310.007640.172112.008070.087485.132149.8320249.0524942.811281.3371941.048536.4050110.4863432.369560.4760113.0606811.392633762.1609928.395720.0656321.26264153.700330.691140.3881952.8261214.206231323.591580.011870.86850.287030.17843NA7.055071156.89777240.27152127.078680.0981922.6653548.508976.256870.5598527.817870.396333.041140.0092128.563380.248414.211260.00216181.457285.9407897.97660.19094.657540.5464921.3247922.9743566.644811.131610.12090.244240.2185288.57676NA6776.91747
&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip&vellip

In [12]:
paises = DataFrame()
paises[:Ano] = 1980:2010
by(pop, :Pais) do df
    paises[symbol(df[:Pais][1])] = convert(DataArray{Float64,2}, df[1,2:end]).'[:,1]
end
paises[:,[:Ano,:Brazil]]


Out[12]:
AnoBrazil
11980123.01963
21981125.99213
31982129.02765
41983131.96012
51984134.69947
61985137.38198
71986140.19628
81987143.02654
91988145.87275
101989148.65864
111990151.17006
121991153.58396
131992156.03206
141993158.51205
151994161.01706
161995163.54428
171996166.08586
181997168.63874
191998171.20116
201999173.76387
212000176.31962
222001178.86966
232002181.41759
242003183.95992
252004186.4886
262005188.99308
272006191.46901
282007193.91858
292008196.34259
302009198.73927
&vellip&vellip&vellip

Os comandos draw e display permitem a publicação do notebook

no GitHub sem que ocorram erros em alguns dos gráficos gerados.


In [20]:
set_default_plot_size(22cm, 15cm)
p=plot(paises, x=:Ano, y=:Brazil)
draw(PNG("max_speeds.png", 22cm, 15cm), p)
display("image/png", p)



In [21]:
p=plot(paises, x=:Ano, y=:Brazil, Geom.line)
draw(PNG("max_speeds.png", 22cm, 15cm), p)
display("image/png", p)



In [22]:
p=plot(
layer(x=paises[:Ano], y=paises[symbol("Central & South America")], Theme(default_color=colorant"blue"), Geom.bar, order=1),
layer(x=paises[:Ano], y=paises[symbol("Brazil")], Theme(default_color=colorant"red"), Geom.bar, order=2),
Guide.Title("Evolução da População"))
draw(PNG("max_speeds.png", 22cm, 15cm), p)
display("image/png", p)


Referências:

Os dados utilizados na confecção deste notebook foram obtidos a partir do site:

http://catalog.data.gov/dataset/population-by-country-1980-2010-d0250

O acesso ao site foi feito no dia 04/11/2015 e a licença para uso dos dados, conforme o site no momento do acesso, é a licença:

Public: This dataset is intended for public access and use. License: Creative Commons CCZero