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),
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> > 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,
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> > day_361 = c(NA, NA, 0.13392, 4.941, 4.94424), day_362 = c(NA,
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> c(NA,
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> "day_2",
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"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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[[alternative HTML version deleted]]
If I do: as.data.frame(apply(df[,-(1:3)],1, mean, na.rm=T)) is it possible to sequentially name the variables as "mean_1960", "max_1960". "min_1960", "mean_1961", "max_1961". "min_1961", ...? On Fri, Nov 18, 2016 at 3:10 PM, Miluji Sb <milujisb at gmail.com> wrote:> 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]] >> > >> > ______________________________________________ >> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see >> > https://stat.ethz.ch/mailman/listinfo/r-help >> > PLEASE do read the posting guide http://www.R-project.org/posting- >> > guide.html >> > and provide commented, minimal, self-contained, reproducible code. >> >> ________________________________ >> Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou >> ur?eny pouze jeho adres?t?m. >> Jestli?e 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Delete the contents of this e-mail with all attachments and its >> copies from your system. >> If you are not the intended recipient of this e-mail, you are not >> authorized to use, disseminate, copy or disclose this e-mail in any manner. >> The sender of this e-mail shall not be liable for any possible damage >> caused by modifications of the e-mail or by delay with transfer of the >> email. >> >> In case that this e-mail forms part of business dealings: >> - the sender reserves the right to end negotiations about entering into a >> contract in any time, for any reason, and without stating any reasoning. >> - if the e-mail contains an offer, the recipient is entitled to >> immediately accept such offer; The sender of this e-mail (offer) excludes >> any acceptance of the offer on the part of the recipient containing any >> amendment or variation. >> - the sender insists on that the respective contract is concluded only >> upon an express mutual agreement on all its aspects. >> - the sender of this e-mail informs that he/she is not authorized to >> enter into any contracts on behalf of the company except for cases in which >> he/she is expressly authorized to do so in writing, and such authorization >> or power of attorney is submitted to the recipient or the person >> represented by the recipient, or the existence of such authorization is >> known to the recipient of the person represented by the recipient. >> > >[[alternative HTML version deleted]]
Hi
see in line
From: Miluji Sb [mailto:milujisb at gmail.com]
Sent: Friday, November 18, 2016 3:57 PM
To: PIKAL Petr <petr.pikal at precheza.cz>
Cc: r-help mailing list <r-help at r-project.org>
Subject: Re: [R] Melt and compute Max, Mean, Min
If I do:
as.data.frame(apply(df[,-(1:3)],1, mean, na.rm=T))
is it possible to sequentially name the variables as "mean_1960",
"max_1960". "min_1960", "mean_1961",
"max_1961". "min_1961", ...?
But here you have only mean. How do you want to add min or max?
On Fri, Nov 18, 2016 at 3:10 PM, Miluji Sb <milujisb at
gmail.com<mailto:milujisb at gmail.com>> wrote:
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")
Not exactly.
In this case I would use for cycle. It is quite easy to do something like:
for( i in 1:length(filelist)) {
temp<-read.csv(filelist[i]) #you need to read your file in R first
.mean <- apply(temp[,-(1:3)],1, mean, na.rm=T)
.max <- apply(temp[,-(1:3)],1, max, na.rm=T)
.min <- apply(temp[,-(1:3)],1, min, na.rm=T)
# now you can concatenate those results as you wish, name them or anything. It
is difficult to suggest any direct code as you did not disclose what do you want
to do with summaries further.
}
And BTW, please, do not post in HTML.
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<mailto: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<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<mailto: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,
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> [[alternative HTML version deleted]]
>
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[[alternative HTML version deleted]]
Hi
Well, thean you could try as I sugested.
.mean <- apply(temp[,-(1:3)],1, mean, na.rm=T)
.max <- apply(temp[,-(1:3)],1, max, na.rm=T)
.min <- apply(temp[,-(1:3)],1, min, na.rm=T)
temp2 <- data.frame(temp[,1:3], maxim = .max, minim = .min, aver = .mean)
You should construct a cycle, read the year file to temp, add above lines, add
year and rbind temp2 with previous result(s).
You could do it also manually but if I remember correctly you have plenty of
files.
Cheers
Petr
From: Miluji Sb [mailto:milujisb at gmail.com]
Sent: Monday, November 21, 2016 6:15 PM
To: PIKAL Petr <petr.pikal at precheza.cz>
Subject: Re: [R] Melt and compute Max, Mean, Min
Hello Petr,
Thank you so much for your reply. Apologies for the HTML posting, there's
something wrong with my email editor. My goal is to compute the maximum,
minimum, and mean for each observation by year and then merge them, so they look
like the following:
lat | lon | year | max | min | mean
Thanks again.
Sincerely,
Milu
On Mon, Nov 21, 2016 at 6:57 AM, PIKAL Petr <petr.pikal at
precheza.cz<mailto:petr.pikal at precheza.cz>> wrote:
Hi
see in line
From: Miluji Sb [mailto:milujisb at gmail.com<mailto:milujisb at
gmail.com>]
Sent: Friday, November 18, 2016 3:57 PM
To: PIKAL Petr <petr.pikal at precheza.cz<mailto:petr.pikal at
precheza.cz>>
Cc: r-help mailing list <r-help at r-project.org<mailto:r-help at
r-project.org>>
Subject: Re: [R] Melt and compute Max, Mean, Min
If I do:
as.data.frame(apply(df[,-(1:3)],1, mean, na.rm=T))
is it possible to sequentially name the variables as "mean_1960",
"max_1960". "min_1960", "mean_1961",
"max_1961". "min_1961", ...?
But here you have only mean. How do you want to add min or max?
On Fri, Nov 18, 2016 at 3:10 PM, Miluji Sb <milujisb at
gmail.com<mailto:milujisb at gmail.com>> wrote:
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")
Not exactly.
In this case I would use for cycle. It is quite easy to do something like:
for( i in 1:length(filelist)) {
temp<-read.csv(filelist[i]) #you need to read your file in R first
.mean <- apply(temp[,-(1:3)],1, mean, na.rm=T)
.max <- apply(temp[,-(1:3)],1, max, na.rm=T)
.min <- apply(temp[,-(1:3)],1, min, na.rm=T)
# now you can concatenate those results as you wish, name them or anything. It
is difficult to suggest any direct code as you did not disclose what do you want
to do with summaries further.
}
And BTW, please, do not post in HTML.
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<mailto: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<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<mailto: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,
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> [[alternative HTML version deleted]]
>
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Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou ur?eny
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zpo?d?n?m p?enosu e-mailu.
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to z jak?hokoliv d?vodu i bez uveden? d?vodu.
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Odes?latel tohoto e-mailu (nab?dky) vylu?uje p?ijet? nab?dky ze strany p??jemce
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- trv? odes?latel na tom, ?e p??slu?n? smlouva je uzav?ena teprve v?slovn?m
dosa?en?m shody na v?ech jej?ch n?le?itostech.
- odes?latel tohoto emailu informuje, ?e nen? opr?vn?n uzav?rat za spole?nost
??dn? smlouvy s v?jimkou p??pad?, kdy k tomu byl p?semn? zmocn?n nebo p?semn?
pov??en a takov? pov??en? nebo pln? moc byly adres?tovi tohoto emailu p??padn?
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This e-mail and any documents attached to it may be confidential and are
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Delete the contents of this e-mail with all attachments and its copies from your
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Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou ur?eny
pouze jeho adres?t?m.
Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? neprodlen? jeho
odes?latele. Obsah tohoto emailu i s p??lohami a jeho kopie vyma?te ze sv?ho
syst?mu.
Nejste-li zam??len?m adres?tem tohoto emailu, nejste opr?vn?ni tento email
jakkoliv u??vat, roz?i?ovat, kop?rovat ?i zve?ej?ovat.
Odes?latel e-mailu neodpov?d? za eventu?ln? ?kodu zp?sobenou modifikacemi ?i
zpo?d?n?m p?enosu e-mailu.
V p??pad?, ?e je tento e-mail sou??st? obchodn?ho jedn?n?:
- vyhrazuje si odes?latel pr?vo ukon?it kdykoliv jedn?n? o uzav?en? smlouvy, a
to z jak?hokoliv d?vodu i bez uveden? d?vodu.
- a obsahuje-li nab?dku, je adres?t opr?vn?n nab?dku bezodkladn? p?ijmout;
Odes?latel tohoto e-mailu (nab?dky) vylu?uje p?ijet? nab?dky ze strany p??jemce
s dodatkem ?i odchylkou.
- trv? odes?latel na tom, ?e p??slu?n? smlouva je uzav?ena teprve v?slovn?m
dosa?en?m shody na v?ech jej?ch n?le?itostech.
- odes?latel tohoto emailu informuje, ?e nen? opr?vn?n uzav?rat za spole?nost
??dn? smlouvy s v?jimkou p??pad?, kdy k tomu byl p?semn? zmocn?n nebo p?semn?
pov??en a takov? pov??en? nebo pln? moc byly adres?tovi tohoto emailu p??padn?
osob?, kterou adres?t zastupuje, p?edlo?eny nebo jejich existence je adres?tovi
?i osob? j?m zastoupen? zn?m?.
This e-mail and any documents attached to it may be confidential and are
intended only for its intended recipients.
If you received this e-mail by mistake, please immediately inform its sender.
Delete the contents of this e-mail with all attachments and its copies from your
system.
If you are not the intended recipient of this e-mail, you are not authorized to
use, disseminate, copy or disclose this e-mail in any manner.
The sender of this e-mail shall not be liable for any possible damage caused by
modifications of the e-mail or by delay with transfer of the email.
In case that this e-mail forms part of business dealings:
- the sender reserves the right to end negotiations about entering into a
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- if the e-mail contains an offer, the recipient is entitled to immediately
accept such offer; The sender of this e-mail (offer) excludes any acceptance of
the offer on the part of the recipient containing any amendment or variation.
- the sender insists on that the respective contract is concluded only upon an
express mutual agreement on all its aspects.
- the sender of this e-mail informs that he/she is not authorized to enter into
any contracts on behalf of the company except for cases in which he/she is
expressly authorized to do so in writing, and such authorization or power of
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the person represented by the recipient.
________________________________
Tento e-mail a jak?koliv k n?mu p?ipojen? dokumenty jsou d?v?rn? a jsou ur?eny
pouze jeho adres?t?m.
Jestli?e jste obdr?el(a) tento e-mail omylem, informujte laskav? neprodlen? jeho
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Nejste-li zam??len?m adres?tem tohoto emailu, nejste opr?vn?ni tento email
jakkoliv u??vat, roz?i?ovat, kop?rovat ?i zve?ej?ovat.
Odes?latel e-mailu neodpov?d? za eventu?ln? ?kodu zp?sobenou modifikacemi ?i
zpo?d?n?m p?enosu e-mailu.
V p??pad?, ?e je tento e-mail sou??st? obchodn?ho jedn?n?:
- vyhrazuje si odes?latel pr?vo ukon?it kdykoliv jedn?n? o uzav?en? smlouvy, a
to z jak?hokoliv d?vodu i bez uveden? d?vodu.
- a obsahuje-li nab?dku, je adres?t opr?vn?n nab?dku bezodkladn? p?ijmout;
Odes?latel tohoto e-mailu (nab?dky) vylu?uje p?ijet? nab?dky ze strany p??jemce
s dodatkem ?i odchylkou.
- trv? odes?latel na tom, ?e p??slu?n? smlouva je uzav?ena teprve v?slovn?m
dosa?en?m shody na v?ech jej?ch n?le?itostech.
- odes?latel tohoto emailu informuje, ?e nen? opr?vn?n uzav?rat za spole?nost
??dn? smlouvy s v?jimkou p??pad?, kdy k tomu byl p?semn? zmocn?n nebo p?semn?
pov??en a takov? pov??en? nebo pln? moc byly adres?tovi tohoto emailu p??padn?
osob?, kterou adres?t zastupuje, p?edlo?eny nebo jejich existence je adres?tovi
?i osob? j?m zastoupen? zn?m?.
This e-mail and any documents attached to it may be confidential and are
intended only for its intended recipients.
If you received this e-mail by mistake, please immediately inform its sender.
Delete the contents of this e-mail with all attachments and its copies from your
system.
If you are not the intended recipient of this e-mail, you are not authorized to
use, disseminate, copy or disclose this e-mail in any manner.
The sender of this e-mail shall not be liable for any possible damage caused by
modifications of the e-mail or by delay with transfer of the email.
In case that this e-mail forms part of business dealings:
- the sender reserves the right to end negotiations about entering into a
contract in any time, for any reason, and without stating any reasoning.
- if the e-mail contains an offer, the recipient is entitled to immediately
accept such offer; The sender of this e-mail (offer) excludes any acceptance of
the offer on the part of the recipient containing any amendment or variation.
- the sender insists on that the respective contract is concluded only upon an
express mutual agreement on all its aspects.
- the sender of this e-mail informs that he/she is not authorized to enter into
any contracts on behalf of the company except for cases in which he/she is
expressly authorized to do so in writing, and such authorization or power of
attorney is submitted to the recipient or the person represented by the
recipient, or the existence of such authorization is known to the recipient of
the person represented by the recipient.
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