[R] Melt and compute Max, Mean, Min
Miluji Sb
milujisb at gmail.com
Fri Nov 18 15:10:18 CET 2016
Dear Petr,
Thank you for the code, apologies though as I copied the wrong data, This
is precipitation data and not temperature.
For the loop, could I do something like this?
filelist <- list.files(pattern=".csv")
myDTs <- lapply(filelist, function(.file) {
apply(temp[,-(1:3)],1, mean, na.rm=T)
}
Thanks again!
Sincerely,
Milu
On Fri, Nov 18, 2016 at 2:46 PM, PIKAL Petr <petr.pikal at precheza.cz> wrote:
> Hi
>
> I am not completely sure what you want to do but
>
> > apply(temp[,-(1:3)],1, mean, na.rm=T)
> 1 2 3 4 5
> NaN NaN 2.159516 1.519914 1.514007
> > apply(temp[,-(1:3)],1, max, na.rm=T)
> 1 2 3 4 5
> -Inf -Inf 57.36528 39.45348 45.23904
> Warning messages:
> 1: In FUN(newX[, i], ...) :
> no non-missing arguments to max; returning -Inf
> 2: In FUN(newX[, i], ...) :
> no non-missing arguments to max; returning -Inf
> > apply(temp[,-(1:3)],1, min, na.rm=T)
> 1 2 3 4 5
> Inf Inf 0 0 0
>
> gives you mentioned summary for each row. If you have duplicate rows you
> shall first aggregate them. However, it seems to me that your data are not
> correct. It is quite strange that for given lat/lon you have one day value
> 23 and the next day 0.
>
> temp[1:5, 1:10]
> ISO3 lon lat day_1 day_2 day_3 day_4 day_5 day_6 day_7
> 1 CHL -69 -55 NA NA NA NA NA NA NA
> 2 CHL -68 -55 NA NA NA NA NA NA NA
> 3 CHL -72 -54 0 0 0.00000 0 0 0 2.83824
> 4 <NA> -71 -54 0 0 23.37984 0 0 0 11.80116
> 5 CHL -70 -54 0 0 0.00000 0 0 0 1.24956
>
> If you want to process all your files you can do it in cycle. The function
>
> list.files()
>
> can be handy for that task.
>
> Cheers
> Petr
>
> > -----Original Message-----
> > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Miluji
> Sb
> > Sent: Friday, November 18, 2016 1:49 PM
> > To: r-help mailing list <r-help at r-project.org>
> > Subject: [R] Melt and compute Max, Mean, Min
> >
> > Dear all,
> >
> > I have 51 years of data (1960 - 2010) in csv format, where each file
> represents
> > one year of data. Below is what each file looks like.
> >
> > These are temperature data by coordinates, my goal is to to compute max,
> > min, and mean by year for each of the coordinates and construct a panel
> > dataset. Any help will be appreciated, thank you!
> >
> > Sincerely,
> >
> > Milu
> >
> > temp <- dput(head(df,5))
> > structure(list(ISO3 = structure(c(28L, 28L, 28L, NA, 28L), .Label =
> c("AFG",
> > "AGO", "ALB", "ARE", "ARG", "ARM", "AUS", "AUT", "AZE", "BDI", "BEL",
> > "BEN", "BFA", "BGD", "BGR", "BHS", "BIH", "BLR", "BLZ", "BOL", "BRA",
> > "BRN", "BTN", "BWA", "CAF", "CAN", "CHE", "CHL", "CHN", "CIV", "CMR",
> > "COD", "COG", "COL", "CRI", "CUB", "CYP", "CZE", "DEU", "DJI", "DNK",
> > "DOM", "DZA", "ECU", "EGY", "ERI", "ESH", "ESP", "EST", "ETH", "FIN",
> "FJI",
> > "FLK", "FRA", "GAB", "GBR", "GEO", "GHA", "GIN", "GNB", "GNQ", "GRC",
> > "GRL", "GTM", "GUF", "GUY", "HND", "HRV", "HTI", "HUN", "IDN", "IND",
> > "IRL", "IRN", "IRQ", "ISL", "ISR", "ITA", "JAM", "JOR", "JPN", "KAZ",
> "KEN",
> > "KGZ", "KHM", "KIR", "KOR", "KWT", "LAO", "LBN", "LBR", "LBY", "LCA",
> > "LKA", "LSO", "LTU", "LUX", "LVA", "MAR", "MDA", "MDG", "MEX", "MKD",
> > "MLI", "MMR", "MNE", "MNG", "MOZ", "MRT", "MWI", "MYS", "NAM",
> > "NCL", "NER", "NGA", "NIC", "NLD", "NOR", "NPL", "NZL", "OMN", "PAK",
> > "PAN", "PER", "PHL", "PNG", "POL", "PRI", "PRK", "PRT", "PRY", "QAT",
> > "ROU", "RUS", "RWA", "SAU", "SDN", "SEN", "SJM", "SLB", "SLE", "SLV",
> > "SOM", "SRB", "SUR", "SVK", "SVN", "SWE", "SWZ", "SYR", "TCD", "TGO",
> > "THA", "TJK", "TKM", "TLS", "TUN", "TUR", "TWN", "TZA", "UGA", "UKR",
> > "URY", "USA", "UZB", "VEN", "VNM", "VUT", "YEM", "ZAF", "ZMB", "ZWE"
> > ), class = "factor"), lon = c(-69L, -68L, -72L, -71L, -70L),
> > lat = c(-55L, -55L, -54L, -54L, -54L), day_1 = c(NA, NA,
> > 0, 0, 0), day_2 = c(NA, NA, 0, 0, 0), day_3 = c(NA, NA, 0,
> > 23.37984, 0), day_4 = c(NA, NA, 0, 0, 0), day_5 = c(NA, NA,
> > 0, 0, 0), day_6 = c(NA, NA, 0, 0, 0), day_7 = c(NA, NA, 2.83824,
> > 11.80116, 1.24956), day_8 = c(NA, NA, 0, 1.68588, 14.69448
> > ), day_9 = c(NA, NA, 0, 0, 1.09296), day_10 = c(NA, NA, 0,
> > 0, 0), day_11 = c(NA, NA, 3.78, 3.7422, 0), day_12 = c(NA,
> > NA, 0.54, 0, 0), day_13 = c(NA, NA, 0, 0, 0), day_14 = c(NA,
> > NA, 0, 0, 0.39204), day_15 = c(NA, NA, 0, 0, 11.58732), day_16 =
> c(NA,
> > NA, 0, 0, 0), day_17 = c(NA, NA, 0, 1.14048, 12.26448), day_18 =
> c(NA,
> > NA, 0, 1.1934, 7.59024), day_19 = c(NA, NA, 9.74268, 0, 0
> > ), day_20 = c(NA, NA, 0, 0, 0), day_21 = c(NA, NA, 1.96776,
> > 0, 0), day_22 = c(NA, NA, 0, 0, 0), day_23 = c(NA, NA, 0,
> > 0, 0), day_24 = c(NA, NA, 6.21756, 2.74752, 0), day_25 = c(NA,
> > NA, 0, 0, 3.37932), day_26 = c(NA, NA, 4.8384, 0, 0), day_27 = c(NA,
> > NA, 0, 0, 0), day_28 = c(NA, NA, 0, 0, 0), day_29 = c(NA,
> > NA, 22.37328, 0, 0), day_30 = c(NA, NA, 28.97424, 11.25468,
> > 0), day_31 = c(NA, NA, 0, 0, 0), day_32 = c(NA, NA, 0, 0,
> > 2.00448), day_33 = c(NA, NA, 0, 0, 0), day_34 = c(NA, NA,
> > 0, 0, 0), day_35 = c(NA, NA, 0, 0, 0), day_36 = c(NA, NA,
> > 0, 0, 0), day_37 = c(NA, NA, 0, 0, 0), day_38 = c(NA, NA,
> > 32.7132, 31.71852, 0), day_39 = c(NA, NA, 0, 0, 5.84604),
> > day_40 = c(NA, NA, 0, 0, 0), day_41 = c(NA, NA, 0, 0, 0),
> > day_42 = c(NA, NA, 0, 0, 0), day_43 = c(NA, NA, 0, 0, 0),
> > day_44 = c(NA, NA, 0, 0, 1.78416), day_45 = c(NA, NA, 0,
> > 0, 0), day_46 = c(NA, NA, 33.84504, 0, 0), day_47 = c(NA,
> > NA, 0, 0, 0), day_48 = c(NA, NA, 0, 0, 0), day_49 = c(NA,
> > NA, 0, 0, 0), day_50 = c(NA, NA, 0, 0.4752, 0), day_51 = c(NA,
> > NA, 0, 0, 22.02012), day_52 = c(NA, NA, 0, 0, 0), day_53 = c(NA,
> > NA, 0, 0, 3.48084), day_54 = c(NA, NA, 0, 0, 0), day_55 = c(NA,
> > NA, 0.58212, 0, 0), day_56 = c(NA, NA, 0.35316, 0, 0), day_57 = c(NA,
> > NA, 0, 0, 12.65436), day_58 = c(NA, NA, 0, 0, 0), day_59 = c(NA,
> > NA, 0, 0, 0), day_60 = c(NA, NA, 3.03372, 22.05576, 0), day_61 =
> c(NA,
> > NA, 2.5758, 0, 0), day_62 = c(NA, NA, 0, 0, 0), day_63 = c(NA,
> > NA, 3.67416, 25.22016, 4.21524), day_64 = c(NA, NA, 0.52488,
> > 3.60288, 0), day_65 = c(NA, NA, 12.82608, 0, 0), day_66 = c(NA,
> > NA, 0, 0, 0), day_67 = c(NA, NA, 0, 0, 0), day_68 = c(NA,
> > NA, 0, 0, 0), day_69 = c(NA, NA, 0, 0, 0), day_70 = c(NA,
> > NA, 1.11564, 5.17536, 0), day_71 = c(NA, NA, 1.18584, 0,
> > 0), day_72 = c(NA, NA, 0, 0, 0.10584), day_73 = c(NA, NA,
> > 0.62748, 14.39748, 7.50708), day_74 = c(NA, NA, 7.20252,
> > 20.02644, 1.07244), day_75 = c(NA, NA, 1.87488, 0, 0), day_76 = c(NA,
> > NA, 0.26784, 0, 0), day_77 = c(NA, NA, 0, 0, 0), day_78 = c(NA,
> > NA, 0, 0, 2.81664), day_79 = c(NA, NA, 0, 0, 0), day_80 = c(NA,
> > NA, 0, 0, 0), day_81 = c(NA, NA, 0, 0, 0), day_82 = c(NA,
> > NA, 1.29276, 0, 0), day_83 = c(NA, NA, 0.18468, 0, 1.46124
> > ), day_84 = c(NA, NA, 0, 0, 0), day_85 = c(NA, NA, 0, 0,
> > 0), day_86 = c(NA, NA, 57.36528, 0, 0), day_87 = c(NA, NA,
> > 8.19504, 0, 0), day_88 = c(NA, NA, 0, 0, 0), day_89 = c(NA,
> > NA, 6.45732, 0, 0), day_90 = c(NA, NA, 0, 0, 0), day_91 = c(NA,
> > NA, 0, 0, 44.20332), day_92 = c(NA, NA, 0, 0, 6.31476), day_93 =
> c(NA,
> > NA, 0, 0, 0.35748), day_94 = c(NA, NA, 16.74972, 30.35988,
> > 5.0436), day_95 = c(NA, NA, 4.93992, 1.46556, 19.86768),
> > day_96 = c(NA, NA, 0, 0, 0.88128), day_97 = c(NA, NA, 5.751,
> > 19.02096, 0), day_98 = c(NA, NA, 11.5452, 13.37148, 0), day_99 =
> c(NA,
> > NA, 0, 0, 0), day_100 = c(NA, NA, 0, 0, 0), day_101 = c(NA,
> > NA, 4.70124, 23.80644, 7.61832), day_102 = c(NA, NA, 0, 1.02492,
> > 0), day_103 = c(NA, NA, 0, 0, 15.86304), day_104 = c(NA,
> > NA, 0, 0, 0.26352), day_105 = c(NA, NA, 0, 0, 21.60864),
> > day_106 = c(NA, NA, 56.93436, 0, 0.22464), day_107 = c(NA,
> > NA, 8.13348, 0, 0), day_108 = c(NA, NA, 6.83748, 0, 0), day_109 =
> c(NA,
> > NA, 0, 0, 0), day_110 = c(NA, NA, 14.36724, 0, 0), day_111 = c(NA,
> > NA, 0.63936, 2.43864, 4.0554), day_112 = c(NA, NA, 1.21392,
> > 1.15452, 0), day_113 = c(NA, NA, 0.7722, 0, 0), day_114 = c(NA,
> > NA, 0, 0, 1.08864), day_115 = c(NA, NA, 1.47528, 0, 0), day_116 =
> c(NA,
> > NA, 0, 1.73124, 0), day_117 = c(NA, NA, 0, 0, 0), day_118 = c(NA,
> > NA, 2.4516, 0, 0), day_119 = c(NA, NA, 0, 3.14388, 0), day_120 =
> c(NA,
> > NA, 1.81872, 0, 0), day_121 = c(NA, NA, 2.77236, 0, 0), day_122 =
> c(NA,
> > NA, 1.34028, 0.70632, 0), day_123 = c(NA, NA, 0, 0, 0), day_124 =
> c(NA,
> > NA, 0, 0, 0), day_125 = c(NA, NA, 0.56484, 0.74412, 0), day_126 =
> c(NA,
> > NA, 1.11888, 0.06264, 0), day_127 = c(NA, NA, 0, 0, 0), day_128 =
> c(NA,
> > NA, 1.05624, 0, 0), day_129 = c(NA, NA, 26.63928, 34.04268,
> > 0), day_130 = c(NA, NA, 6.89796, 0, 0), day_131 = c(NA, NA,
> > 1.91592, 2.241, 0), day_132 = c(NA, NA, 0, 2.23668, 45.23904
> > ), day_133 = c(NA, NA, 0, 0, 6.46272), day_134 = c(NA, NA,
> > 0, 0, 0), day_135 = c(NA, NA, 0, 0, 0), day_136 = c(NA, NA,
> > 0, 0, 0), day_137 = c(NA, NA, 0, 0, 0), day_138 = c(NA, NA,
> > 0, 0, 0), day_139 = c(NA, NA, 0, 0, 0), day_140 = c(NA, NA,
> > 0, 0, 0), day_141 = c(NA, NA, 0, 0, 0), day_142 = c(NA, NA,
> > 0, 0, 0), day_143 = c(NA, NA, 0, 0, 0), day_144 = c(NA, NA,
> > 2.943, 5.17536, 0), day_145 = c(NA, NA, 0, 0, 0), day_146 = c(NA,
> > NA, 0, 0, 0), day_147 = c(NA, NA, 0, 0, 0), day_148 = c(NA,
> > NA, 10.96308, 2.98188, 0), day_149 = c(NA, NA, 20.4822, 0.43632,
> > 0), day_150 = c(NA, NA, 1.5282, 0, 0), day_151 = c(NA, NA,
> > 0, 0, 0), day_152 = c(NA, NA, 0, 0, 0), day_153 = c(NA, NA,
> > 0, 0, 0), day_154 = c(NA, NA, 0, 0, 0), day_155 = c(NA, NA,
> > 0, 0, 0), day_156 = c(NA, NA, 0, 0, 0), day_157 = c(NA, NA,
> > 0, 0, 0), day_158 = c(NA, NA, 0, 0, 0), day_159 = c(NA, NA,
> > 0, 0, 0), day_160 = c(NA, NA, 0, 0, 0), day_161 = c(NA, NA,
> > 0, 0, 0), day_162 = c(NA, NA, 0, 0, 0), day_163 = c(NA, NA,
> > 0, 26.3412, 4.07376), day_164 = c(NA, NA, 0, 4.28328, 3.03156
> > ), day_165 = c(NA, NA, 0, 0, 0), day_166 = c(NA, NA, 0, 0,
> > 4.60404), day_167 = c(NA, NA, 0, 0, 0.70848), day_168 = c(NA,
> > NA, 0, 0, 0), day_169 = c(NA, NA, 0, 0, 0), day_170 = c(NA,
> > NA, 0, 0, 0), day_171 = c(NA, NA, 0, 0, 0), day_172 = c(NA,
> > NA, 0, 0, 0), day_173 = c(NA, NA, 0, 0, 3.7854), day_174 = c(NA,
> > NA, 0, 0, 0), day_175 = c(NA, NA, 0, 0, 0), day_176 = c(NA,
> > NA, 0, 0, 0), day_177 = c(NA, NA, 0, 0, 0), day_178 = c(NA,
> > NA, 0, 0, 0), day_179 = c(NA, NA, 0, 0, 0), day_180 = c(NA,
> > NA, 0, 0, 0), day_181 = c(NA, NA, 0, 0, 0), day_182 = c(NA,
> > NA, 0, 0, 0), day_183 = c(NA, NA, 0, 0, 0), day_184 = c(NA,
> > NA, 0, 0, 0), day_185 = c(NA, NA, 0, 0, 0), day_186 = c(NA,
> > NA, 0, 0, 0), day_187 = c(NA, NA, 7.30728, 4.1202, 0), day_188 =
> c(NA,
> > NA, 2.56608, 0.5886, 0), day_189 = c(NA, NA, 0, 0, 0), day_190 =
> c(NA,
> > NA, 21.93156, 8.0082, 11.4318), day_191 = c(NA, NA, 3.13308,
> > 0, 0), day_192 = c(NA, NA, 0, 0, 0.10692), day_193 = c(NA,
> > NA, 0, 0, 4.65912), day_194 = c(NA, NA, 0, 0, 0), day_195 = c(NA,
> > NA, 0, 0, 0), day_196 = c(NA, NA, 0, 0, 0), day_197 = c(NA,
> > NA, 0, 0, 0), day_198 = c(NA, NA, 0, 0, 0), day_199 = c(NA,
> > NA, 0, 0, 0), day_200 = c(NA, NA, 0, 0, 0), day_201 = c(NA,
> > NA, 0, 0, 0), day_202 = c(NA, NA, 0, 7.77276, 4.6602), day_203 =
> c(NA,
> > NA, 0, 0.86292, 0), day_204 = c(NA, NA, 0, 0, 0), day_205 = c(NA,
> > NA, 21.45528, 8.69616, 0), day_206 = c(NA, NA, 0, 0, 0),
> > day_207 = c(NA, NA, 0, 0, 0), day_208 = c(NA, NA, 0, 0, 0
> > ), day_209 = c(NA, NA, 0, 0, 0), day_210 = c(NA, NA, 0, 0,
> > 0), day_211 = c(NA, NA, 0, 0, 0), day_212 = c(NA, NA, 0,
> > 0, 0), day_213 = c(NA, NA, 0, 0, 0), day_214 = c(NA, NA,
> > 0, 0, 0), day_215 = c(NA, NA, 0, 0, 0), day_216 = c(NA, NA,
> > 0, 0, 0), day_217 = c(NA, NA, 0, 0, 0), day_218 = c(NA, NA,
> > 0, 0, 0), day_219 = c(NA, NA, 0, 0, 0), day_220 = c(NA, NA,
> > 6.10092, 10.85508, 13.22244), day_221 = c(NA, NA, 0.87156,
> > 0, 0), day_222 = c(NA, NA, 0, 0, 15.46452), day_223 = c(NA,
> > NA, 0, 0, 9.83664), day_224 = c(NA, NA, 0, 0, 0), day_225 = c(NA,
> > NA, 0, 0, 0), day_226 = c(NA, NA, 16.46028, 0, 0), day_227 = c(NA,
> > NA, 0, 0, 0), day_228 = c(NA, NA, 0, 0, 0), day_229 = c(NA,
> > NA, 0, 0, 0), day_230 = c(NA, NA, 0, 0, 0), day_231 = c(NA,
> > NA, 2.7108, 0, 0), day_232 = c(NA, NA, 0, 0, 0), day_233 = c(NA,
> > NA, 0, 0, 0), day_234 = c(NA, NA, 0, 0, 0), day_235 = c(NA,
> > NA, 0, 0, 0), day_236 = c(NA, NA, 0, 0, 3.5586), day_237 = c(NA,
> > NA, 0, 0, 0), day_238 = c(NA, NA, 0, 0, 0), day_239 = c(NA,
> > NA, 10.23192, 0, 0), day_240 = c(NA, NA, 0, 0, 0), day_241 = c(NA,
> > NA, 0, 0, 0), day_242 = c(NA, NA, 0, 0, 0), day_243 = c(NA,
> > NA, 0, 0, 0), day_244 = c(NA, NA, 0, 0, 0), day_245 = c(NA,
> > NA, 0, 0, 0), day_246 = c(NA, NA, 0, 0, 0), day_247 = c(NA,
> > NA, 0, 0, 0), day_248 = c(NA, NA, 0, 0, 0), day_249 = c(NA,
> > NA, 0.50544, 0, 0), day_250 = c(NA, NA, 0.12636, 0, 0), day_251 =
> c(NA,
> > NA, 7.02432, 0, 5.39784), day_252 = c(NA, NA, 3.33828, 8.00064,
> > 7.08372), day_253 = c(NA, NA, 0, 0, 0), day_254 = c(NA, NA,
> > 0, 0, 0), day_255 = c(NA, NA, 2.5704, 4.71636, 11.99772),
> > day_256 = c(NA, NA, 0.3672, 0.75384, 0), day_257 = c(NA,
> > NA, 0, 0, 0), day_258 = c(NA, NA, 0.50328, 0, 0), day_259 = c(NA,
> > NA, 6.78888, 0, 0), day_260 = c(NA, NA, 0.96984, 0, 0), day_261 =
> c(NA,
> > NA, 4.62672, 0, 0), day_262 = c(NA, NA, 0, 0, 0), day_263 = c(NA,
> > NA, 3.16224, 0.27864, 0), day_264 = c(NA, NA, 0, 1.31112,
> > 0), day_265 = c(NA, NA, 0.37692, 0, 0), day_266 = c(NA, NA,
> > 0, 0, 0), day_267 = c(NA, NA, 0.70524, 0.43524, 0), day_268 = c(NA,
> > NA, 0.18792, 0.12744, 0), day_269 = c(NA, NA, 0, 1.79064,
> > 0.96012), day_270 = c(NA, NA, 0, 0, 0.58644), day_271 = c(NA,
> > NA, 4.4982, 0, 0), day_272 = c(NA, NA, 0, 0, 0), day_273 = c(NA,
> > NA, 2.04552, 6.56964, 0), day_274 = c(NA, NA, 0.71712, 0.93852,
> > 0), day_275 = c(NA, NA, 0, 0, 0), day_276 = c(NA, NA, 0,
> > 0, 0), day_277 = c(NA, NA, 3.31452, 0, 0), day_278 = c(NA,
> > NA, 1.20204, 0, 0), day_279 = c(NA, NA, 0, 0, 0), day_280 = c(NA,
> > NA, 0, 0, 0), day_281 = c(NA, NA, 0, 0, 0), day_282 = c(NA,
> > NA, 17.955, 5.7942, 9.93816), day_283 = c(NA, NA, 4.79304,
> > 4.8006, 0), day_284 = c(NA, NA, 3.9366, 0.78084, 0), day_285 = c(NA,
> > NA, 0, 0, 0), day_286 = c(NA, NA, 0, 0, 0), day_287 = c(NA,
> > NA, 0, 0, 0), day_288 = c(NA, NA, 0, 0, 0), day_289 = c(NA,
> > NA, 0, 0, 0), day_290 = c(NA, NA, 0, 0, 0), day_291 = c(NA,
> > NA, 0, 0, 0), day_292 = c(NA, NA, 0, 0, 0), day_293 = c(NA,
> > NA, 1.55736, 0, 0), day_294 = c(NA, NA, 4.28328, 0, 0), day_295 =
> c(NA,
> > NA, 0, 0, 0), day_296 = c(NA, NA, 0, 0, 0), day_297 = c(NA,
> > NA, 1.6362, 0, 0), day_298 = c(NA, NA, 1.28844, 0, 6.14088
> > ), day_299 = c(NA, NA, 0, 0, 0.50112), day_300 = c(NA, NA,
> > 0, 0, 0), day_301 = c(NA, NA, 0, 0.13824, 0.03456), day_302 = c(NA,
> > NA, 0, 2.92572, 9.24264), day_303 = c(NA, NA, 2.8188, 0.41796,
> > 0), day_304 = c(NA, NA, 2.04876, 11.28384, 0), day_305 = c(NA,
> > NA, 0, 0.3564, 0), day_306 = c(NA, NA, 0, 0, 0), day_307 = c(NA,
> > NA, 0, 2.36736, 0), day_308 = c(NA, NA, 0, 0, 0), day_309 = c(NA,
> > NA, 34.91856, 20.42604, 0), day_310 = c(NA, NA, 0, 0, 0),
> > day_311 = c(NA, NA, 0, 0, 0), day_312 = c(NA, NA, 0, 0.40392,
> > 0), day_313 = c(NA, NA, 0, 0.5292, 0), day_314 = c(NA, NA,
> > 0, 0, 5.21424), day_315 = c(NA, NA, 0, 0, 0), day_316 = c(NA,
> > NA, 0, 0, 0.4266), day_317 = c(NA, NA, 0, 0, 0), day_318 = c(NA,
> > NA, 0, 0, 0), day_319 = c(NA, NA, 0, 0, 0), day_320 = c(NA,
> > NA, 0.23436, 0.6048, 14.9256), day_321 = c(NA, NA, 0, 0.10908,
> > 0), day_322 = c(NA, NA, 7.68096, 6.66036, 4.53924), day_323 = c(NA,
> > NA, 1.09728, 1.59732, 8.51148), day_324 = c(NA, NA, 0, 0,
> > 0), day_325 = c(NA, NA, 1.46016, 0, 0), day_326 = c(NA, NA,
> > 0, 0, 8.70048), day_327 = c(NA, NA, 0, 0, 0), day_328 = c(NA,
> > NA, 0, 0, 0), day_329 = c(NA, NA, 0, 0, 0), day_330 = c(NA,
> > NA, 5.3082, 0, 0), day_331 = c(NA, NA, 2.5866, 0, 0), day_332 = c(NA,
> > NA, 8.03628, 6.3666, 4.3308), day_333 = c(NA, NA, 0, 0, 0
> > ), day_334 = c(NA, NA, 0, 0, 0), day_335 = c(NA, NA, 0, 0,
> > 0), day_336 = c(NA, NA, 0, 0, 5.29632), day_337 = c(NA, NA,
> > 0, 1.77444, 2.7216), day_338 = c(NA, NA, 0.40608, 0, 0.83052
> > ), day_339 = c(NA, NA, 0, 0, 0), day_340 = c(NA, NA, 0, 0,
> > 0), day_341 = c(NA, NA, 0, 0, 0), day_342 = c(NA, NA, 0,
> > 0, 0), day_343 = c(NA, NA, 0, 0, 0), day_344 = c(NA, NA,
> > 7.73388, 0, 0), day_345 = c(NA, NA, 4.80384, 0, 0), day_346 = c(NA,
> > NA, 4.374, 0.09288, 0), day_347 = c(NA, NA, 6.42924, 3.2022,
> > 0), day_348 = c(NA, NA, 0, 16.27668, 0), day_349 = c(NA,
> > NA, 0, 0.90072, 9.36684), day_350 = c(NA, NA, 0.135, 1.87272,
> > 2.49048), day_351 = c(NA, NA, 0, 0, 0), day_352 = c(NA, NA,
> > 0, 0, 0), day_353 = c(NA, NA, 0, 0, 0), day_354 = c(NA, NA,
> > 0, 0, 0), day_355 = c(NA, NA, 0, 0, 0), day_356 = c(NA, NA,
> > 0, 0, 0), day_357 = c(NA, NA, 2.82636, 39.45348, 26.08848
> > ), day_358 = c(NA, NA, 0, 0, 22.8582), day_359 = c(NA, NA,
> > 0, 0, 1.34028), day_360 = c(NA, NA, 30.03804, 0, 3.49704),
> > day_361 = c(NA, NA, 0.13392, 4.941, 4.94424), day_362 = c(NA,
> > NA, 0.92016, 0, 0.70632), day_363 = c(NA, NA, 0, 0, 0), day_364 =
> c(NA,
> > NA, 0, 0, 0), day_365 = c(NA, NA, 0, 0, 0), day_366 = c(NA,
> > NA, 21.42072, 0, 0)), .Names = c("ISO3", "lon", "lat", "day_1",
> "day_2",
> > "day_3", "day_4", "day_5", "day_6", "day_7", "day_8", "day_9", "day_10",
> > "day_11", "day_12", "day_13", "day_14", "day_15", "day_16", "day_17",
> > "day_18", "day_19", "day_20", "day_21", "day_22", "day_23", "day_24",
> > "day_25", "day_26", "day_27", "day_28", "day_29", "day_30", "day_31",
> > "day_32", "day_33", "day_34", "day_35", "day_36", "day_37", "day_38",
> > "day_39", "day_40", "day_41", "day_42", "day_43", "day_44", "day_45",
> > "day_46", "day_47", "day_48", "day_49", "day_50", "day_51", "day_52",
> > "day_53", "day_54", "day_55", "day_56", "day_57", "day_58", "day_59",
> > "day_60", "day_61", "day_62", "day_63", "day_64", "day_65", "day_66",
> > "day_67", "day_68", "day_69", "day_70", "day_71", "day_72", "day_73",
> > "day_74", "day_75", "day_76", "day_77", "day_78", "day_79", "day_80",
> > "day_81", "day_82", "day_83", "day_84", "day_85", "day_86", "day_87",
> > "day_88", "day_89", "day_90", "day_91", "day_92", "day_93", "day_94",
> > "day_95", "day_96", "day_97", "day_98", "day_99", "day_100", "day_101",
> > "day_102", "day_103", "day_104", "day_105", "day_106", "day_107",
> > "day_108", "day_109", "day_110", "day_111", "day_112", "day_113",
> > "day_114", "day_115", "day_116", "day_117", "day_118", "day_119",
> > "day_120", "day_121", "day_122", "day_123", "day_124", "day_125",
> > "day_126", "day_127", "day_128", "day_129", "day_130", "day_131",
> > "day_132", "day_133", "day_134", "day_135", "day_136", "day_137",
> > "day_138", "day_139", "day_140", "day_141", "day_142", "day_143",
> > "day_144", "day_145", "day_146", "day_147", "day_148", "day_149",
> > "day_150", "day_151", "day_152", "day_153", "day_154", "day_155",
> > "day_156", "day_157", "day_158", "day_159", "day_160", "day_161",
> > "day_162", "day_163", "day_164", "day_165", "day_166", "day_167",
> > "day_168", "day_169", "day_170", "day_171", "day_172", "day_173",
> > "day_174", "day_175", "day_176", "day_177", "day_178", "day_179",
> > "day_180", "day_181", "day_182", "day_183", "day_184", "day_185",
> > "day_186", "day_187", "day_188", "day_189", "day_190", "day_191",
> > "day_192", "day_193", "day_194", "day_195", "day_196", "day_197",
> > "day_198", "day_199", "day_200", "day_201", "day_202", "day_203",
> > "day_204", "day_205", "day_206", "day_207", "day_208", "day_209",
> > "day_210", "day_211", "day_212", "day_213", "day_214", "day_215",
> > "day_216", "day_217", "day_218", "day_219", "day_220", "day_221",
> > "day_222", "day_223", "day_224", "day_225", "day_226", "day_227",
> > "day_228", "day_229", "day_230", "day_231", "day_232", "day_233",
> > "day_234", "day_235", "day_236", "day_237", "day_238", "day_239",
> > "day_240", "day_241", "day_242", "day_243", "day_244", "day_245",
> > "day_246", "day_247", "day_248", "day_249", "day_250", "day_251",
> > "day_252", "day_253", "day_254", "day_255", "day_256", "day_257",
> > "day_258", "day_259", "day_260", "day_261", "day_262", "day_263",
> > "day_264", "day_265", "day_266", "day_267", "day_268", "day_269",
> > "day_270", "day_271", "day_272", "day_273", "day_274", "day_275",
> > "day_276", "day_277", "day_278", "day_279", "day_280", "day_281",
> > "day_282", "day_283", "day_284", "day_285", "day_286", "day_287",
> > "day_288", "day_289", "day_290", "day_291", "day_292", "day_293",
> > "day_294", "day_295", "day_296", "day_297", "day_298", "day_299",
> > "day_300", "day_301", "day_302", "day_303", "day_304", "day_305",
> > "day_306", "day_307", "day_308", "day_309", "day_310", "day_311",
> > "day_312", "day_313", "day_314", "day_315", "day_316", "day_317",
> > "day_318", "day_319", "day_320", "day_321", "day_322", "day_323",
> > "day_324", "day_325", "day_326", "day_327", "day_328", "day_329",
> > "day_330", "day_331", "day_332", "day_333", "day_334", "day_335",
> > "day_336", "day_337", "day_338", "day_339", "day_340", "day_341",
> > "day_342", "day_343", "day_344", "day_345", "day_346", "day_347",
> > "day_348", "day_349", "day_350", "day_351", "day_352", "day_353",
> > "day_354", "day_355", "day_356", "day_357", "day_358", "day_359",
> > "day_360", "day_361", "day_362", "day_363", "day_364", "day_365",
> > "day_366"), row.names = c(NA, 5L), class =
> > "data.frame")
> >
> > [[alternative HTML version deleted]]
> >
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