Az adatok forrása: https://earthquake.usgs.gov/earthquakes/feed/v1.0/csv.php
Az all_month.csv állomány beolvasása:
X <- read.csv("https://earthquake.usgs.gov/earthquakes/feed/v1.0/summary/all_month.csv", row.names = "id", as.is = c("time", "updated"))
Vizsgáljuk meg az adatokat:
str(X)
## 'data.frame': 10622 obs. of 21 variables:
## $ time : chr "2019-06-17T05:31:45.640Z" "2019-06-17T05:31:01.170Z" "2019-06-17T05:26:22.367Z" "2019-06-17T05:06:04.990Z" ...
## $ latitude : num 36.7 37.6 66.4 34 34.9 ...
## $ longitude : num -121 -119 -157 -118 -118 ...
## $ depth : num 2.82 5.12 0.2 2.7 5.64 2.07 13.6 5.33 22.4 0.49 ...
## $ mag : num 1.34 1.08 1.2 1.14 1.67 0.96 1.4 0.95 1.3 1.87 ...
## $ magType : Factor w/ 10 levels "","mb","mb_lg",..: 4 4 6 6 6 4 6 6 6 4 ...
## $ nst : int 8 10 NA 41 5 19 NA 20 NA 47 ...
## $ gap : num 200 96 NA 28 145 81 NA 110 NA 58 ...
## $ dmin : num 0.0423 0.0155 NA 0.0447 0.4196 ...
## $ rms : num 0.13 0.02 1.36 0.21 0.23 0.04 0.79 0.29 0.93 0.36 ...
## $ net : Factor w/ 17 levels "ak","av","ci",..: 8 8 1 3 3 8 1 3 1 4 ...
## $ updated : chr "2019-06-17T05:33:22.016Z" "2019-06-17T05:38:03.241Z" "2019-06-17T05:31:25.989Z" "2019-06-17T05:09:54.665Z" ...
## $ place : Factor w/ 5596 levels "0km ESE of Manhattan, Montana",..: 810 5411 4182 3455 5166 4497 4734 960 4763 444 ...
## $ type : Factor w/ 5 levels "earthquake","explosion",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ horizontalError: num 1.17 0.7 NA 0.26 2.09 0.26 NA 0.6 NA 0.44 ...
## $ depthError : num 2.88 0.65 0.9 0.35 15.64 ...
## $ magError : num 0.45 0.22 NA 0.156 0.438 0.1 NA 0.176 NA 0.1 ...
## $ magNst : int 6 10 NA 28 14 4 NA 18 NA 18 ...
## $ status : Factor w/ 2 levels "automatic","reviewed": 1 1 1 1 1 1 1 1 1 1 ...
## $ locationSource : Factor w/ 17 levels "ak","av","ci",..: 8 8 1 3 3 8 1 3 1 4 ...
## $ magSource : Factor w/ 20 levels "ak","av","ci",..: 9 9 1 3 3 9 1 3 1 5 ...
summary(X)
## time latitude longitude depth
## Length:10622 Min. :-61.79 Min. :-179.9 Min. : -3.56
## Class :character 1st Qu.: 34.05 1st Qu.:-148.7 1st Qu.: 2.77
## Mode :character Median : 38.76 Median :-120.0 Median : 5.95
## Mean : 41.16 Mean :-118.2 Mean : 18.33
## 3rd Qu.: 58.09 3rd Qu.:-116.8 3rd Qu.: 13.40
## Max. : 85.39 Max. : 180.0 Max. :647.21
##
## mag magType nst gap
## Min. :-1.250 ml :7244 Min. : 2.00 Min. : 11.0
## 1st Qu.: 0.750 md :2704 1st Qu.: 9.00 1st Qu.: 66.0
## Median : 1.150 mb : 541 Median : 15.00 Median : 96.0
## Mean : 1.391 mww : 66 Mean : 20.88 Mean :117.2
## 3rd Qu.: 1.720 mwr : 27 3rd Qu.: 27.00 3rd Qu.:150.0
## Max. : 8.000 mb_lg : 19 Max. :191.00 Max. :360.0
## NA's :5 (Other): 21 NA's :3504 NA's :2754
## dmin rms net updated
## Min. : 0.0000 Min. :0.0000 ak :2751 Length:10622
## 1st Qu.: 0.0223 1st Qu.:0.0900 ci :2482 Class :character
## Median : 0.0487 Median :0.1800 nc :2096 Mode :character
## Mean : 0.4149 Mean :0.3139 nn : 871
## 3rd Qu.: 0.1502 3rd Qu.:0.5000 us : 753
## Max. :39.2640 Max. :6.6100 pr : 352
## NA's :2972 NA's :1 (Other):1317
## place type horizontalError
## 4km NNW of Glen Avon, CA : 431 earthquake :10378 Min. : 0.080
## 5km NNW of Glen Avon, CA : 318 explosion : 68 1st Qu.: 0.230
## 7km NW of The Geysers, CA : 185 ice quake : 45 Median : 0.350
## 4km NW of Glen Avon, CA : 152 other event : 33 Mean : 1.445
## 7km WNW of The Geysers, CA: 120 quarry blast: 98 3rd Qu.: 0.790
## 6km WNW of The Geysers, CA: 111 Max. :92.100
## (Other) :9305 NA's :3781
## depthError magError magNst status
## Min. : 0.000 Min. :0.000 Min. : 0.00 automatic:2506
## 1st Qu.: 0.370 1st Qu.:0.106 1st Qu.: 4.00 reviewed :8116
## Median : 0.630 Median :0.157 Median : 8.00
## Mean : 2.588 Mean :0.180 Mean : 15.85
## 3rd Qu.: 1.570 3rd Qu.:0.224 3rd Qu.: 18.00
## Max. :679.500 Max. :3.980 Max. :523.00
## NA's :2 NA's :3402 NA's :2841
## locationSource magSource
## ak :2753 ak :2762
## ci :2482 ci :2482
## nc :2096 nc :2096
## nn : 871 nn : 871
## us : 750 us : 734
## pr : 352 pr : 352
## (Other):1318 (Other):1325
A sztring típusú time
és updated
oszlopokat alakítsuk időbélyegekké:
library(lubridate)
##
## Attaching package: 'lubridate'
## The following object is masked from 'package:base':
##
## date
X <- transform(X, time = ymd_hms(time), updated = ymd_hms(updated))
summary(X)
## time latitude longitude
## Min. :2019-05-18 05:45:58 Min. :-61.79 Min. :-179.9
## 1st Qu.:2019-05-26 04:59:41 1st Qu.: 34.05 1st Qu.:-148.7
## Median :2019-06-02 05:01:24 Median : 38.76 Median :-120.0
## Mean :2019-06-02 01:06:26 Mean : 41.16 Mean :-118.2
## 3rd Qu.:2019-06-08 16:43:16 3rd Qu.: 58.09 3rd Qu.:-116.8
## Max. :2019-06-17 05:31:45 Max. : 85.39 Max. : 180.0
##
## depth mag magType nst
## Min. : -3.56 Min. :-1.250 ml :7244 Min. : 2.00
## 1st Qu.: 2.77 1st Qu.: 0.750 md :2704 1st Qu.: 9.00
## Median : 5.95 Median : 1.150 mb : 541 Median : 15.00
## Mean : 18.33 Mean : 1.391 mww : 66 Mean : 20.88
## 3rd Qu.: 13.40 3rd Qu.: 1.720 mwr : 27 3rd Qu.: 27.00
## Max. :647.21 Max. : 8.000 mb_lg : 19 Max. :191.00
## NA's :5 (Other): 21 NA's :3504
## gap dmin rms net
## Min. : 11.0 Min. : 0.0000 Min. :0.0000 ak :2751
## 1st Qu.: 66.0 1st Qu.: 0.0223 1st Qu.:0.0900 ci :2482
## Median : 96.0 Median : 0.0487 Median :0.1800 nc :2096
## Mean :117.2 Mean : 0.4149 Mean :0.3139 nn : 871
## 3rd Qu.:150.0 3rd Qu.: 0.1502 3rd Qu.:0.5000 us : 753
## Max. :360.0 Max. :39.2640 Max. :6.6100 pr : 352
## NA's :2754 NA's :2972 NA's :1 (Other):1317
## updated place
## Min. :2019-05-18 07:43:52 4km NNW of Glen Avon, CA : 431
## 1st Qu.:2019-05-31 04:48:55 5km NNW of Glen Avon, CA : 318
## Median :2019-06-06 01:22:33 7km NW of The Geysers, CA : 185
## Mean :2019-06-05 12:54:33 4km NW of Glen Avon, CA : 152
## 3rd Qu.:2019-06-11 23:45:32 7km WNW of The Geysers, CA: 120
## Max. :2019-06-17 05:38:03 6km WNW of The Geysers, CA: 111
## (Other) :9305
## type horizontalError depthError magError
## earthquake :10378 Min. : 0.080 Min. : 0.000 Min. :0.000
## explosion : 68 1st Qu.: 0.230 1st Qu.: 0.370 1st Qu.:0.106
## ice quake : 45 Median : 0.350 Median : 0.630 Median :0.157
## other event : 33 Mean : 1.445 Mean : 2.588 Mean :0.180
## quarry blast: 98 3rd Qu.: 0.790 3rd Qu.: 1.570 3rd Qu.:0.224
## Max. :92.100 Max. :679.500 Max. :3.980
## NA's :3781 NA's :2 NA's :3402
## magNst status locationSource magSource
## Min. : 0.00 automatic:2506 ak :2753 ak :2762
## 1st Qu.: 4.00 reviewed :8116 ci :2482 ci :2482
## Median : 8.00 nc :2096 nc :2096
## Mean : 15.85 nn : 871 nn : 871
## 3rd Qu.: 18.00 us : 750 us : 734
## Max. :523.00 pr : 352 pr : 352
## NA's :2841 (Other):1318 (Other):1325
str(X)
## 'data.frame': 10622 obs. of 21 variables:
## $ time : POSIXct, format: "2019-06-17 05:31:45" "2019-06-17 05:31:01" ...
## $ latitude : num 36.7 37.6 66.4 34 34.9 ...
## $ longitude : num -121 -119 -157 -118 -118 ...
## $ depth : num 2.82 5.12 0.2 2.7 5.64 2.07 13.6 5.33 22.4 0.49 ...
## $ mag : num 1.34 1.08 1.2 1.14 1.67 0.96 1.4 0.95 1.3 1.87 ...
## $ magType : Factor w/ 10 levels "","mb","mb_lg",..: 4 4 6 6 6 4 6 6 6 4 ...
## $ nst : int 8 10 NA 41 5 19 NA 20 NA 47 ...
## $ gap : num 200 96 NA 28 145 81 NA 110 NA 58 ...
## $ dmin : num 0.0423 0.0155 NA 0.0447 0.4196 ...
## $ rms : num 0.13 0.02 1.36 0.21 0.23 0.04 0.79 0.29 0.93 0.36 ...
## $ net : Factor w/ 17 levels "ak","av","ci",..: 8 8 1 3 3 8 1 3 1 4 ...
## $ updated : POSIXct, format: "2019-06-17 05:33:22" "2019-06-17 05:38:03" ...
## $ place : Factor w/ 5596 levels "0km ESE of Manhattan, Montana",..: 810 5411 4182 3455 5166 4497 4734 960 4763 444 ...
## $ type : Factor w/ 5 levels "earthquake","explosion",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ horizontalError: num 1.17 0.7 NA 0.26 2.09 0.26 NA 0.6 NA 0.44 ...
## $ depthError : num 2.88 0.65 0.9 0.35 15.64 ...
## $ magError : num 0.45 0.22 NA 0.156 0.438 0.1 NA 0.176 NA 0.1 ...
## $ magNst : int 6 10 NA 28 14 4 NA 18 NA 18 ...
## $ status : Factor w/ 2 levels "automatic","reviewed": 1 1 1 1 1 1 1 1 1 1 ...
## $ locationSource : Factor w/ 17 levels "ak","av","ci",..: 8 8 1 3 3 8 1 3 1 4 ...
## $ magSource : Factor w/ 20 levels "ak","av","ci",..: 9 9 1 3 3 9 1 3 1 5 ...
Ábrázoljuk a földrengéseket a koordinátáik alapján:
library(ggplot2)
## Registered S3 methods overwritten by 'ggplot2':
## method from
## [.quosures rlang
## c.quosures rlang
## print.quosures rlang
qplot(longitude, latitude, data = X, color = type)
qplot(longitude, latitude, data = X, color = mag)
Az ábrázolásnál jelenítsünk meg térképet is:
library(ggspatial)
ggplot(X, aes(longitude, latitude, color = mag)) + annotation_map_tile(type = "osm") + geom_spatial_point()
## Assuming crs = 4326 in stat_spatial_identity()
## Zoom: 1
ggplot(X, aes(longitude, latitude, color = mag)) + annotation_map_tile(type = "osm") + geom_spatial_point() + scale_color_gradient(low = "yellow", high = "red")
## Assuming crs = 4326 in stat_spatial_identity()
## Zoom: 1
Az adatok forrása: https://data.worldbank.org/indicator/SP.POP.TOTL
Az adatokat CSV formátumban tartalmazó ZIP állomány letöltése:
tmp <- tempfile(fileext = ".zip")
tmp
## [1] "/tmp/RtmpLKNfbu/file900bab4c49.zip"
download.file("http://api.worldbank.org/v2/en/indicator/SP.POP.TOTL?downloadformat=csv", tmp)
A CSV állomány beolvasása a ZIP állományból:
X <- read.csv(unz(tmp, "API_SP.POP.TOTL_DS2_en_csv_v2_10576638.csv"), skip = 4)
Viszgáljuk meg az oszlopok neveit:
names(X)
## [1] "Country.Name" "Country.Code" "Indicator.Name" "Indicator.Code"
## [5] "X1960" "X1961" "X1962" "X1963"
## [9] "X1964" "X1965" "X1966" "X1967"
## [13] "X1968" "X1969" "X1970" "X1971"
## [17] "X1972" "X1973" "X1974" "X1975"
## [21] "X1976" "X1977" "X1978" "X1979"
## [25] "X1980" "X1981" "X1982" "X1983"
## [29] "X1984" "X1985" "X1986" "X1987"
## [33] "X1988" "X1989" "X1990" "X1991"
## [37] "X1992" "X1993" "X1994" "X1995"
## [41] "X1996" "X1997" "X1998" "X1999"
## [45] "X2000" "X2001" "X2002" "X2003"
## [49] "X2004" "X2005" "X2006" "X2007"
## [53] "X2008" "X2009" "X2010" "X2011"
## [57] "X2012" "X2013" "X2014" "X2015"
## [61] "X2016" "X2017" "X2018" "X"
Az alábbi paraméterezéssel olvassuk be a CSV állományt a ZIP állományból, majd vizsgáljuk meg az oszlopok neveit:
X <- read.csv(unz(tmp, "API_SP.POP.TOTL_DS2_en_csv_v2_10576638.csv"), skip = 4, check.names = FALSE)
names(X)
## [1] "Country Name" "Country Code" "Indicator Name" "Indicator Code"
## [5] "1960" "1961" "1962" "1963"
## [9] "1964" "1965" "1966" "1967"
## [13] "1968" "1969" "1970" "1971"
## [17] "1972" "1973" "1974" "1975"
## [21] "1976" "1977" "1978" "1979"
## [25] "1980" "1981" "1982" "1983"
## [29] "1984" "1985" "1986" "1987"
## [33] "1988" "1989" "1990" "1991"
## [37] "1992" "1993" "1994" "1995"
## [41] "1996" "1997" "1998" "1999"
## [45] "2000" "2001" "2002" "2003"
## [49] "2004" "2005" "2006" "2007"
## [53] "2008" "2009" "2010" "2011"
## [57] "2012" "2013" "2014" "2015"
## [61] "2016" "2017" "2018" ""
Vizsgáljuk meg az adatokat:
summary(X)
## Country Name Country Code Indicator Name
## Afghanistan : 1 ABW : 1 Population, total:264
## Albania : 1 AFG : 1
## Algeria : 1 AGO : 1
## American Samoa: 1 ALB : 1
## Andorra : 1 AND : 1
## Angola : 1 ARB : 1
## (Other) :258 (Other):258
## Indicator Code 1960 1961
## SP.POP.TOTL:264 Min. :4.279e+03 Min. :4.453e+03
## 1st Qu.:5.184e+05 1st Qu.:5.301e+05
## Median :3.670e+06 Median :3.734e+06
## Mean :1.178e+08 Mean :1.194e+08
## 3rd Qu.:2.533e+07 3rd Qu.:2.612e+07
## Max. :3.032e+09 Max. :3.073e+09
## NA's :4 NA's :4
## 1962 1963 1964
## Min. :4.566e+03 Min. :4.656e+03 Min. :4.748e+03
## 1st Qu.:5.427e+05 1st Qu.:5.560e+05 1st Qu.:5.684e+05
## Median :3.840e+06 Median :3.955e+06 Median :4.074e+06
## Mean :1.215e+08 Mean :1.241e+08 Mean :1.268e+08
## 3rd Qu.:2.691e+07 3rd Qu.:2.770e+07 3rd Qu.:2.848e+07
## Max. :3.127e+09 Max. :3.192e+09 Max. :3.257e+09
## NA's :4 NA's :4 NA's :4
## 1965 1966 1967
## Min. :4.841e+03 Min. :4.936e+03 Min. :5.033e+03
## 1st Qu.:5.728e+05 1st Qu.:5.786e+05 1st Qu.:5.882e+05
## Median :4.171e+06 Median :4.234e+06 Median :4.300e+06
## Mean :1.295e+08 Mean :1.324e+08 Mean :1.353e+08
## 3rd Qu.:2.925e+07 3rd Qu.:3.000e+07 3rd Qu.:3.060e+07
## Max. :3.325e+09 Max. :3.395e+09 Max. :3.464e+09
## NA's :4 NA's :4 NA's :4
## 1968 1969 1970
## Min. :5.161e+03 Min. :5.303e+03 Min. :5.450e+03
## 1st Qu.:6.258e+05 1st Qu.:6.568e+05 1st Qu.:6.751e+05
## Median :4.368e+06 Median :4.449e+06 Median :4.524e+06
## Mean :1.382e+08 Mean :1.412e+08 Mean :1.443e+08
## 3rd Qu.:3.120e+07 3rd Qu.:3.180e+07 3rd Qu.:3.235e+07
## Max. :3.535e+09 Max. :3.610e+09 Max. :3.686e+09
## NA's :4 NA's :4 NA's :4
## 1971 1972 1973
## Min. :5.601e+03 Min. :5.756e+03 Min. :5.915e+03
## 1st Qu.:6.905e+05 1st Qu.:7.011e+05 1st Qu.:7.110e+05
## Median :4.622e+06 Median :4.729e+06 Median :4.844e+06
## Mean :1.475e+08 Mean :1.506e+08 Mean :1.538e+08
## 3rd Qu.:3.281e+07 3rd Qu.:3.317e+07 3rd Qu.:3.354e+07
## Max. :3.763e+09 Max. :3.840e+09 Max. :3.916e+09
## NA's :4 NA's :4 NA's :4
## 1974 1975 1976
## Min. :6.078e+03 Min. :6.291e+03 Min. :6.530e+03
## 1st Qu.:7.194e+05 1st Qu.:7.256e+05 1st Qu.:7.315e+05
## Median :4.961e+06 Median :5.035e+06 Median :5.129e+06
## Mean :1.569e+08 Mean :1.600e+08 Mean :1.630e+08
## 3rd Qu.:3.393e+07 3rd Qu.:3.433e+07 3rd Qu.:3.473e+07
## Max. :3.993e+09 Max. :4.068e+09 Max. :4.141e+09
## NA's :4 NA's :4 NA's :4
## 1977 1978 1979
## Min. :6.778e+03 Min. :7.035e+03 Min. :7.264e+03
## 1st Qu.:7.588e+05 1st Qu.:7.839e+05 1st Qu.:7.884e+05
## Median :5.276e+06 Median :5.397e+06 Median :5.518e+06
## Mean :1.660e+08 Mean :1.691e+08 Mean :1.722e+08
## 3rd Qu.:3.521e+07 3rd Qu.:3.620e+07 3rd Qu.:3.721e+07
## Max. :4.213e+09 Max. :4.287e+09 Max. :4.363e+09
## NA's :4 NA's :4 NA's :4
## 1980 1981 1982
## Min. :7.488e+03 Min. :7.592e+03 Min. :7.717e+03
## 1st Qu.:7.957e+05 1st Qu.:8.063e+05 1st Qu.:8.198e+05
## Median :5.641e+06 Median :5.785e+06 Median :5.938e+06
## Mean :1.754e+08 Mean :1.786e+08 Mean :1.820e+08
## 3rd Qu.:3.765e+07 3rd Qu.:3.800e+07 3rd Qu.:3.832e+07
## Max. :4.439e+09 Max. :4.518e+09 Max. :4.599e+09
## NA's :4 NA's :4 NA's :4
## 1983 1984 1985
## Min. :7.854e+03 Min. :8.005e+03 Min. :8.173e+03
## 1st Qu.:8.373e+05 1st Qu.:8.597e+05 1st Qu.:8.822e+05
## Median :6.099e+06 Median :6.265e+06 Median :6.427e+06
## Mean :1.854e+08 Mean :1.889e+08 Mean :1.923e+08
## 3rd Qu.:3.869e+07 3rd Qu.:3.974e+07 3rd Qu.:4.080e+07
## Max. :4.681e+09 Max. :4.763e+09 Max. :4.846e+09
## NA's :4 NA's :4 NA's :4
## 1986 1987 1988
## Min. :8.353e+03 Min. :8.554e+03 Min. :8.755e+03
## 1st Qu.:9.045e+05 1st Qu.:9.269e+05 1st Qu.:9.497e+05
## Median :6.516e+06 Median :6.701e+06 Median :6.858e+06
## Mean :1.959e+08 Mean :1.996e+08 Mean :2.033e+08
## 3rd Qu.:4.144e+07 3rd Qu.:4.209e+07 3rd Qu.:4.276e+07
## Max. :4.932e+09 Max. :5.020e+09 Max. :5.109e+09
## NA's :4 NA's :4 NA's :4
## 1989 1990 1991
## Min. :8.947e+03 Min. :9.003e+03 Min. :9.053e+03
## 1st Qu.:9.730e+05 1st Qu.:1.024e+06 1st Qu.:1.045e+06
## Median :7.000e+06 Median :7.129e+06 Median :7.148e+06
## Mean :2.071e+08 Mean :2.092e+08 Mean :2.129e+08
## 3rd Qu.:4.345e+07 3rd Qu.:4.231e+07 3rd Qu.:4.277e+07
## Max. :5.198e+09 Max. :5.288e+09 Max. :5.376e+09
## NA's :4 NA's :2 NA's :2
## 1992 1993 1994
## Min. :9.109e+03 Min. :9.156e+03 Min. :9.190e+03
## 1st Qu.:1.063e+06 1st Qu.:1.089e+06 1st Qu.:1.113e+06
## Median :7.382e+06 Median :7.495e+06 Median :7.584e+06
## Mean :2.172e+08 Mean :2.208e+08 Mean :2.243e+08
## 3rd Qu.:4.375e+07 3rd Qu.:4.419e+07 3rd Qu.:4.464e+07
## Max. :5.460e+09 Max. :5.545e+09 Max. :5.629e+09
## NA's :3 NA's :3 NA's :3
## 1995 1996 1997
## Min. :9.230e+03 Min. :9.256e+03 Min. :9.277e+03
## 1st Qu.:1.126e+06 1st Qu.:1.140e+06 1st Qu.:1.156e+06
## Median :7.655e+06 Median :7.740e+06 Median :7.855e+06
## Mean :2.269e+08 Mean :2.304e+08 Mean :2.339e+08
## 3rd Qu.:4.463e+07 3rd Qu.:4.509e+07 3rd Qu.:4.556e+07
## Max. :5.714e+09 Max. :5.797e+09 Max. :5.879e+09
## NA's :2 NA's :2 NA's :2
## 1998 1999 2000
## Min. :9.306e+03 Min. :9.345e+03 Min. :9.420e+03
## 1st Qu.:1.166e+06 1st Qu.:1.198e+06 1st Qu.:1.231e+06
## Median :7.913e+06 Median :7.992e+06 Median :8.049e+06
## Mean :2.364e+08 Mean :2.397e+08 Mean :2.431e+08
## 3rd Qu.:4.562e+07 3rd Qu.:4.626e+07 3rd Qu.:4.704e+07
## Max. :5.961e+09 Max. :6.041e+09 Max. :6.121e+09
## NA's :1 NA's :1 NA's :1
## 2001 2002 2003
## Min. :9.512e+03 Min. :9.635e+03 Min. :9.767e+03
## 1st Qu.:1.265e+06 1st Qu.:1.286e+06 1st Qu.:1.303e+06
## Median :8.111e+06 Median :8.172e+06 Median :8.234e+06
## Mean :2.464e+08 Mean :2.497e+08 Mean :2.530e+08
## 3rd Qu.:4.788e+07 3rd Qu.:4.792e+07 3rd Qu.:4.785e+07
## Max. :6.201e+09 Max. :6.280e+09 Max. :6.359e+09
## NA's :1 NA's :1 NA's :1
## 2004 2005 2006
## Min. :9.894e+03 Min. :1.003e+04 Min. :1.007e+04
## 1st Qu.:1.320e+06 1st Qu.:1.326e+06 1st Qu.:1.325e+06
## Median :8.306e+06 Median :8.392e+06 Median :8.485e+06
## Mean :2.564e+08 Mean :2.598e+08 Mean :2.632e+08
## 3rd Qu.:4.816e+07 3rd Qu.:4.865e+07 3rd Qu.:4.911e+07
## Max. :6.439e+09 Max. :6.520e+09 Max. :6.601e+09
## NA's :1 NA's :1 NA's :1
## 2007 2008 2009
## Min. :1.000e+04 Min. :9.947e+03 Min. :9.945e+03
## 1st Qu.:1.325e+06 1st Qu.:1.363e+06 1st Qu.:1.426e+06
## Median :8.857e+06 Median :9.220e+06 Median :9.299e+06
## Mean :2.666e+08 Mean :2.701e+08 Mean :2.736e+08
## 3rd Qu.:4.953e+07 3rd Qu.:4.995e+07 3rd Qu.:5.039e+07
## Max. :6.683e+09 Max. :6.766e+09 Max. :6.849e+09
## NA's :1 NA's :1 NA's :1
## 2010 2011 2012
## Min. :1.002e+04 Min. :1.006e+04 Min. :1.028e+04
## 1st Qu.:1.444e+06 1st Qu.:1.465e+06 1st Qu.:1.416e+06
## Median :9.378e+06 Median :9.461e+06 Median :9.624e+06
## Mean :2.771e+08 Mean :2.807e+08 Mean :2.853e+08
## 3rd Qu.:5.087e+07 3rd Qu.:5.141e+07 3rd Qu.:5.250e+07
## Max. :6.933e+09 Max. :7.015e+09 Max. :7.099e+09
## NA's :1 NA's :1 NA's :2
## 2013 2014 2015
## Min. :1.082e+04 Min. :1.091e+04 Min. :1.100e+04
## 1st Qu.:1.432e+06 1st Qu.:1.447e+06 1st Qu.:1.472e+06
## Median :9.747e+06 Median :9.879e+06 Median :1.002e+07
## Mean :2.890e+08 Mean :2.927e+08 Mean :2.964e+08
## 3rd Qu.:5.319e+07 3rd Qu.:5.396e+07 3rd Qu.:5.494e+07
## Max. :7.185e+09 Max. :7.271e+09 Max. :7.357e+09
## NA's :2 NA's :2 NA's :2
## 2016 2017 2018
## Min. :1.110e+04 Min. :1.119e+04 Mode:logical Mode:logical
## 1st Qu.:1.523e+06 1st Qu.:1.577e+06 NA's:264 NA's:264
## Median :1.012e+07 Median :1.018e+07
## Mean :3.002e+08 Mean :3.039e+08
## 3rd Qu.:5.590e+07 3rd Qu.:5.716e+07
## Max. :7.444e+09 Max. :7.530e+09
## NA's :2 NA's :2
head(X)
## Country Name Country Code Indicator Name Indicator Code 1960
## 1 Aruba ABW Population, total SP.POP.TOTL 54211
## 2 Afghanistan AFG Population, total SP.POP.TOTL 8996351
## 3 Angola AGO Population, total SP.POP.TOTL 5643182
## 4 Albania ALB Population, total SP.POP.TOTL 1608800
## 5 Andorra AND Population, total SP.POP.TOTL 13411
## 6 Arab World ARB Population, total SP.POP.TOTL 92490932
## 1961 1962 1963 1964 1965 1966 1967
## 1 55438 56225 56695 57032 57360 57715 58055
## 2 9166764 9345868 9533954 9731361 9938414 10152331 10372630
## 3 5753024 5866061 5980417 6093321 6203299 6309770 6414995
## 4 1659800 1711319 1762621 1814135 1864791 1914573 1965598
## 5 14375 15370 16412 17469 18549 19647 20758
## 6 95044497 97682294 100411076 103239902 106174988 109230593 112406932
## 1968 1969 1970 1971 1972 1973 1974
## 1 58386 58726 59063 59440 59840 60243 60528
## 2 10604346 10854428 11126123 11417825 11721940 12027822 12321541
## 3 6523791 6642632 6776381 6927269 7094834 7277960 7474338
## 4 2022272 2081695 2135479 2187853 2243126 2296752 2350124
## 5 21890 23058 24276 25559 26892 28232 29520
## 6 115680165 119016542 122398374 125807419 129269375 132863416 136696761
## 1975 1976 1977 1978 1979 1980 1981
## 1 60657 60586 60366 60103 59980 60096 60567
## 2 12590286 12840299 13067538 13237734 13306695 13248370 13053954
## 3 7682479 7900997 8130988 8376147 8641521 8929900 9244507
## 4 2404831 2458526 2513546 2566266 2617832 2671997 2726056
## 5 30705 31777 32771 33737 34818 36067 37500
## 6 140843298 145332378 150133054 155183724 160392488 165689490 171051950
## 1982 1983 1984 1985 1986 1987 1988
## 1 61345 62201 62836 63026 62644 61833 61079
## 2 12749645 12389269 12047115 11783050 11601041 11502761 11540888
## 3 9582156 9931562 10277321 10609042 10921037 11218268 11513968
## 4 2784278 2843960 2904429 2964762 3022635 3083605 3142336
## 5 39114 40867 42706 44600 46517 48455 50434
## 6 176490084 182005827 187610756 193310301 199093767 204942549 210844771
## 1989 1990 1991 1992 1993 1994 1995
## 1 61032 62149 64622 68235 72504 76700 80324
## 2 11777609 12249114 12993657 13981231 15095099 16172719 17099541
## 3 11827237 12171441 12553446 12968345 13403734 13841301 14268994
## 4 3227943 3286542 3266790 3247039 3227287 3207536 3187784
## 5 52448 54509 56671 58888 60971 62677 63850
## 6 216787402 224735446 230829868 235037179 241286091 247435930 255029671
## 1996 1997 1998 1999 2000 2001 2002
## 1 83200 85451 87277 89005 90853 92898 94992
## 2 17822884 18381605 18863999 19403676 20093756 20966463 21979923
## 3 14682284 15088981 15504318 15949766 16440924 16983266 17572649
## 4 3168033 3148281 3128530 3108778 3089027 3060173 3051010
## 5 64360 64327 64142 64370 65390 67341 70049
## 6 260843462 266575075 272235146 277962869 283832016 289850357 296026575
## 2003 2004 2005 2006 2007 2008 2009
## 1 97017 98737 100031 100832 101220 101353 101453
## 2 23064851 24118979 25070798 25893450 26616792 27294031 28004331
## 3 18203369 18865716 19552542 20262399 20997687 21759420 22549547
## 4 3039616 3026939 3011487 2992547 2970017 2947314 2927519
## 5 73182 76244 78867 80991 82683 83861 84462
## 6 302434519 309162029 316264728 323773264 331653797 339825483 348145094
## 2010 2011 2012 2013 2014 2015 2016
## 1 101669 102053 102577 103187 103795 104341 104822
## 2 28803167 29708599 30696958 31731688 32758020 33736494 34656032
## 3 23369131 24218565 25096150 25998340 26920466 27859305 28813463
## 4 2913021 2905195 2900401 2895092 2889104 2880703 2876101
## 5 84449 83751 82431 80788 79223 78014 77281
## 6 356508908 364895878 373306993 381702086 390043028 398304960 406452690
## 2017 2018
## 1 105264 NA NA
## 2 35530081 NA NA
## 3 29784193 NA NA
## 4 2873457 NA NA
## 5 76965 NA NA
## 6 414491886 NA NA
Szabaduljunk meg a harmadik, a negyedik és az utolsó két oszloptól:
X[c(3, 4, 63, 64)] <- NULL
summary(X)
## Country Name Country Code 1960
## Afghanistan : 1 ABW : 1 Min. :4.279e+03
## Albania : 1 AFG : 1 1st Qu.:5.184e+05
## Algeria : 1 AGO : 1 Median :3.670e+06
## American Samoa: 1 ALB : 1 Mean :1.178e+08
## Andorra : 1 AND : 1 3rd Qu.:2.533e+07
## Angola : 1 ARB : 1 Max. :3.032e+09
## (Other) :258 (Other):258 NA's :4
## 1961 1962 1963
## Min. :4.453e+03 Min. :4.566e+03 Min. :4.656e+03
## 1st Qu.:5.301e+05 1st Qu.:5.427e+05 1st Qu.:5.560e+05
## Median :3.734e+06 Median :3.840e+06 Median :3.955e+06
## Mean :1.194e+08 Mean :1.215e+08 Mean :1.241e+08
## 3rd Qu.:2.612e+07 3rd Qu.:2.691e+07 3rd Qu.:2.770e+07
## Max. :3.073e+09 Max. :3.127e+09 Max. :3.192e+09
## NA's :4 NA's :4 NA's :4
## 1964 1965 1966
## Min. :4.748e+03 Min. :4.841e+03 Min. :4.936e+03
## 1st Qu.:5.684e+05 1st Qu.:5.728e+05 1st Qu.:5.786e+05
## Median :4.074e+06 Median :4.171e+06 Median :4.234e+06
## Mean :1.268e+08 Mean :1.295e+08 Mean :1.324e+08
## 3rd Qu.:2.848e+07 3rd Qu.:2.925e+07 3rd Qu.:3.000e+07
## Max. :3.257e+09 Max. :3.325e+09 Max. :3.395e+09
## NA's :4 NA's :4 NA's :4
## 1967 1968 1969
## Min. :5.033e+03 Min. :5.161e+03 Min. :5.303e+03
## 1st Qu.:5.882e+05 1st Qu.:6.258e+05 1st Qu.:6.568e+05
## Median :4.300e+06 Median :4.368e+06 Median :4.449e+06
## Mean :1.353e+08 Mean :1.382e+08 Mean :1.412e+08
## 3rd Qu.:3.060e+07 3rd Qu.:3.120e+07 3rd Qu.:3.180e+07
## Max. :3.464e+09 Max. :3.535e+09 Max. :3.610e+09
## NA's :4 NA's :4 NA's :4
## 1970 1971 1972
## Min. :5.450e+03 Min. :5.601e+03 Min. :5.756e+03
## 1st Qu.:6.751e+05 1st Qu.:6.905e+05 1st Qu.:7.011e+05
## Median :4.524e+06 Median :4.622e+06 Median :4.729e+06
## Mean :1.443e+08 Mean :1.475e+08 Mean :1.506e+08
## 3rd Qu.:3.235e+07 3rd Qu.:3.281e+07 3rd Qu.:3.317e+07
## Max. :3.686e+09 Max. :3.763e+09 Max. :3.840e+09
## NA's :4 NA's :4 NA's :4
## 1973 1974 1975
## Min. :5.915e+03 Min. :6.078e+03 Min. :6.291e+03
## 1st Qu.:7.110e+05 1st Qu.:7.194e+05 1st Qu.:7.256e+05
## Median :4.844e+06 Median :4.961e+06 Median :5.035e+06
## Mean :1.538e+08 Mean :1.569e+08 Mean :1.600e+08
## 3rd Qu.:3.354e+07 3rd Qu.:3.393e+07 3rd Qu.:3.433e+07
## Max. :3.916e+09 Max. :3.993e+09 Max. :4.068e+09
## NA's :4 NA's :4 NA's :4
## 1976 1977 1978
## Min. :6.530e+03 Min. :6.778e+03 Min. :7.035e+03
## 1st Qu.:7.315e+05 1st Qu.:7.588e+05 1st Qu.:7.839e+05
## Median :5.129e+06 Median :5.276e+06 Median :5.397e+06
## Mean :1.630e+08 Mean :1.660e+08 Mean :1.691e+08
## 3rd Qu.:3.473e+07 3rd Qu.:3.521e+07 3rd Qu.:3.620e+07
## Max. :4.141e+09 Max. :4.213e+09 Max. :4.287e+09
## NA's :4 NA's :4 NA's :4
## 1979 1980 1981
## Min. :7.264e+03 Min. :7.488e+03 Min. :7.592e+03
## 1st Qu.:7.884e+05 1st Qu.:7.957e+05 1st Qu.:8.063e+05
## Median :5.518e+06 Median :5.641e+06 Median :5.785e+06
## Mean :1.722e+08 Mean :1.754e+08 Mean :1.786e+08
## 3rd Qu.:3.721e+07 3rd Qu.:3.765e+07 3rd Qu.:3.800e+07
## Max. :4.363e+09 Max. :4.439e+09 Max. :4.518e+09
## NA's :4 NA's :4 NA's :4
## 1982 1983 1984
## Min. :7.717e+03 Min. :7.854e+03 Min. :8.005e+03
## 1st Qu.:8.198e+05 1st Qu.:8.373e+05 1st Qu.:8.597e+05
## Median :5.938e+06 Median :6.099e+06 Median :6.265e+06
## Mean :1.820e+08 Mean :1.854e+08 Mean :1.889e+08
## 3rd Qu.:3.832e+07 3rd Qu.:3.869e+07 3rd Qu.:3.974e+07
## Max. :4.599e+09 Max. :4.681e+09 Max. :4.763e+09
## NA's :4 NA's :4 NA's :4
## 1985 1986 1987
## Min. :8.173e+03 Min. :8.353e+03 Min. :8.554e+03
## 1st Qu.:8.822e+05 1st Qu.:9.045e+05 1st Qu.:9.269e+05
## Median :6.427e+06 Median :6.516e+06 Median :6.701e+06
## Mean :1.923e+08 Mean :1.959e+08 Mean :1.996e+08
## 3rd Qu.:4.080e+07 3rd Qu.:4.144e+07 3rd Qu.:4.209e+07
## Max. :4.846e+09 Max. :4.932e+09 Max. :5.020e+09
## NA's :4 NA's :4 NA's :4
## 1988 1989 1990
## Min. :8.755e+03 Min. :8.947e+03 Min. :9.003e+03
## 1st Qu.:9.497e+05 1st Qu.:9.730e+05 1st Qu.:1.024e+06
## Median :6.858e+06 Median :7.000e+06 Median :7.129e+06
## Mean :2.033e+08 Mean :2.071e+08 Mean :2.092e+08
## 3rd Qu.:4.276e+07 3rd Qu.:4.345e+07 3rd Qu.:4.231e+07
## Max. :5.109e+09 Max. :5.198e+09 Max. :5.288e+09
## NA's :4 NA's :4 NA's :2
## 1991 1992 1993
## Min. :9.053e+03 Min. :9.109e+03 Min. :9.156e+03
## 1st Qu.:1.045e+06 1st Qu.:1.063e+06 1st Qu.:1.089e+06
## Median :7.148e+06 Median :7.382e+06 Median :7.495e+06
## Mean :2.129e+08 Mean :2.172e+08 Mean :2.208e+08
## 3rd Qu.:4.277e+07 3rd Qu.:4.375e+07 3rd Qu.:4.419e+07
## Max. :5.376e+09 Max. :5.460e+09 Max. :5.545e+09
## NA's :2 NA's :3 NA's :3
## 1994 1995 1996
## Min. :9.190e+03 Min. :9.230e+03 Min. :9.256e+03
## 1st Qu.:1.113e+06 1st Qu.:1.126e+06 1st Qu.:1.140e+06
## Median :7.584e+06 Median :7.655e+06 Median :7.740e+06
## Mean :2.243e+08 Mean :2.269e+08 Mean :2.304e+08
## 3rd Qu.:4.464e+07 3rd Qu.:4.463e+07 3rd Qu.:4.509e+07
## Max. :5.629e+09 Max. :5.714e+09 Max. :5.797e+09
## NA's :3 NA's :2 NA's :2
## 1997 1998 1999
## Min. :9.277e+03 Min. :9.306e+03 Min. :9.345e+03
## 1st Qu.:1.156e+06 1st Qu.:1.166e+06 1st Qu.:1.198e+06
## Median :7.855e+06 Median :7.913e+06 Median :7.992e+06
## Mean :2.339e+08 Mean :2.364e+08 Mean :2.397e+08
## 3rd Qu.:4.556e+07 3rd Qu.:4.562e+07 3rd Qu.:4.626e+07
## Max. :5.879e+09 Max. :5.961e+09 Max. :6.041e+09
## NA's :2 NA's :1 NA's :1
## 2000 2001 2002
## Min. :9.420e+03 Min. :9.512e+03 Min. :9.635e+03
## 1st Qu.:1.231e+06 1st Qu.:1.265e+06 1st Qu.:1.286e+06
## Median :8.049e+06 Median :8.111e+06 Median :8.172e+06
## Mean :2.431e+08 Mean :2.464e+08 Mean :2.497e+08
## 3rd Qu.:4.704e+07 3rd Qu.:4.788e+07 3rd Qu.:4.792e+07
## Max. :6.121e+09 Max. :6.201e+09 Max. :6.280e+09
## NA's :1 NA's :1 NA's :1
## 2003 2004 2005
## Min. :9.767e+03 Min. :9.894e+03 Min. :1.003e+04
## 1st Qu.:1.303e+06 1st Qu.:1.320e+06 1st Qu.:1.326e+06
## Median :8.234e+06 Median :8.306e+06 Median :8.392e+06
## Mean :2.530e+08 Mean :2.564e+08 Mean :2.598e+08
## 3rd Qu.:4.785e+07 3rd Qu.:4.816e+07 3rd Qu.:4.865e+07
## Max. :6.359e+09 Max. :6.439e+09 Max. :6.520e+09
## NA's :1 NA's :1 NA's :1
## 2006 2007 2008
## Min. :1.007e+04 Min. :1.000e+04 Min. :9.947e+03
## 1st Qu.:1.325e+06 1st Qu.:1.325e+06 1st Qu.:1.363e+06
## Median :8.485e+06 Median :8.857e+06 Median :9.220e+06
## Mean :2.632e+08 Mean :2.666e+08 Mean :2.701e+08
## 3rd Qu.:4.911e+07 3rd Qu.:4.953e+07 3rd Qu.:4.995e+07
## Max. :6.601e+09 Max. :6.683e+09 Max. :6.766e+09
## NA's :1 NA's :1 NA's :1
## 2009 2010 2011
## Min. :9.945e+03 Min. :1.002e+04 Min. :1.006e+04
## 1st Qu.:1.426e+06 1st Qu.:1.444e+06 1st Qu.:1.465e+06
## Median :9.299e+06 Median :9.378e+06 Median :9.461e+06
## Mean :2.736e+08 Mean :2.771e+08 Mean :2.807e+08
## 3rd Qu.:5.039e+07 3rd Qu.:5.087e+07 3rd Qu.:5.141e+07
## Max. :6.849e+09 Max. :6.933e+09 Max. :7.015e+09
## NA's :1 NA's :1 NA's :1
## 2012 2013 2014
## Min. :1.028e+04 Min. :1.082e+04 Min. :1.091e+04
## 1st Qu.:1.416e+06 1st Qu.:1.432e+06 1st Qu.:1.447e+06
## Median :9.624e+06 Median :9.747e+06 Median :9.879e+06
## Mean :2.853e+08 Mean :2.890e+08 Mean :2.927e+08
## 3rd Qu.:5.250e+07 3rd Qu.:5.319e+07 3rd Qu.:5.396e+07
## Max. :7.099e+09 Max. :7.185e+09 Max. :7.271e+09
## NA's :2 NA's :2 NA's :2
## 2015 2016 2017
## Min. :1.100e+04 Min. :1.110e+04 Min. :1.119e+04
## 1st Qu.:1.472e+06 1st Qu.:1.523e+06 1st Qu.:1.577e+06
## Median :1.002e+07 Median :1.012e+07 Median :1.018e+07
## Mean :2.964e+08 Mean :3.002e+08 Mean :3.039e+08
## 3rd Qu.:5.494e+07 3rd Qu.:5.590e+07 3rd Qu.:5.716e+07
## Max. :7.357e+09 Max. :7.444e+09 Max. :7.530e+09
## NA's :2 NA's :2 NA's :2
head(X)
## Country Name Country Code 1960 1961 1962 1963 1964
## 1 Aruba ABW 54211 55438 56225 56695 57032
## 2 Afghanistan AFG 8996351 9166764 9345868 9533954 9731361
## 3 Angola AGO 5643182 5753024 5866061 5980417 6093321
## 4 Albania ALB 1608800 1659800 1711319 1762621 1814135
## 5 Andorra AND 13411 14375 15370 16412 17469
## 6 Arab World ARB 92490932 95044497 97682294 100411076 103239902
## 1965 1966 1967 1968 1969 1970 1971
## 1 57360 57715 58055 58386 58726 59063 59440
## 2 9938414 10152331 10372630 10604346 10854428 11126123 11417825
## 3 6203299 6309770 6414995 6523791 6642632 6776381 6927269
## 4 1864791 1914573 1965598 2022272 2081695 2135479 2187853
## 5 18549 19647 20758 21890 23058 24276 25559
## 6 106174988 109230593 112406932 115680165 119016542 122398374 125807419
## 1972 1973 1974 1975 1976 1977 1978
## 1 59840 60243 60528 60657 60586 60366 60103
## 2 11721940 12027822 12321541 12590286 12840299 13067538 13237734
## 3 7094834 7277960 7474338 7682479 7900997 8130988 8376147
## 4 2243126 2296752 2350124 2404831 2458526 2513546 2566266
## 5 26892 28232 29520 30705 31777 32771 33737
## 6 129269375 132863416 136696761 140843298 145332378 150133054 155183724
## 1979 1980 1981 1982 1983 1984 1985
## 1 59980 60096 60567 61345 62201 62836 63026
## 2 13306695 13248370 13053954 12749645 12389269 12047115 11783050
## 3 8641521 8929900 9244507 9582156 9931562 10277321 10609042
## 4 2617832 2671997 2726056 2784278 2843960 2904429 2964762
## 5 34818 36067 37500 39114 40867 42706 44600
## 6 160392488 165689490 171051950 176490084 182005827 187610756 193310301
## 1986 1987 1988 1989 1990 1991 1992
## 1 62644 61833 61079 61032 62149 64622 68235
## 2 11601041 11502761 11540888 11777609 12249114 12993657 13981231
## 3 10921037 11218268 11513968 11827237 12171441 12553446 12968345
## 4 3022635 3083605 3142336 3227943 3286542 3266790 3247039
## 5 46517 48455 50434 52448 54509 56671 58888
## 6 199093767 204942549 210844771 216787402 224735446 230829868 235037179
## 1993 1994 1995 1996 1997 1998 1999
## 1 72504 76700 80324 83200 85451 87277 89005
## 2 15095099 16172719 17099541 17822884 18381605 18863999 19403676
## 3 13403734 13841301 14268994 14682284 15088981 15504318 15949766
## 4 3227287 3207536 3187784 3168033 3148281 3128530 3108778
## 5 60971 62677 63850 64360 64327 64142 64370
## 6 241286091 247435930 255029671 260843462 266575075 272235146 277962869
## 2000 2001 2002 2003 2004 2005 2006
## 1 90853 92898 94992 97017 98737 100031 100832
## 2 20093756 20966463 21979923 23064851 24118979 25070798 25893450
## 3 16440924 16983266 17572649 18203369 18865716 19552542 20262399
## 4 3089027 3060173 3051010 3039616 3026939 3011487 2992547
## 5 65390 67341 70049 73182 76244 78867 80991
## 6 283832016 289850357 296026575 302434519 309162029 316264728 323773264
## 2007 2008 2009 2010 2011 2012 2013
## 1 101220 101353 101453 101669 102053 102577 103187
## 2 26616792 27294031 28004331 28803167 29708599 30696958 31731688
## 3 20997687 21759420 22549547 23369131 24218565 25096150 25998340
## 4 2970017 2947314 2927519 2913021 2905195 2900401 2895092
## 5 82683 83861 84462 84449 83751 82431 80788
## 6 331653797 339825483 348145094 356508908 364895878 373306993 381702086
## 2014 2015 2016 2017
## 1 103795 104341 104822 105264
## 2 32758020 33736494 34656032 35530081
## 3 26920466 27859305 28813463 29784193
## 4 2889104 2880703 2876101 2873457
## 5 79223 78014 77281 76965
## 6 390043028 398304960 406452690 414491886
Alakítsuk át az adatokat és vizsgáljuk meg az eredményt:
library(reshape2)
Y <- melt(X)
## Using Country Name, Country Code as id variables
summary(Y)
## Country Name Country Code variable
## Afghanistan : 58 ABW : 58 1960 : 264
## Albania : 58 AFG : 58 1961 : 264
## Algeria : 58 AGO : 58 1962 : 264
## American Samoa: 58 ALB : 58 1963 : 264
## Andorra : 58 AND : 58 1964 : 264
## Angola : 58 ARB : 58 1965 : 264
## (Other) :14964 (Other):14964 (Other):13728
## value
## Min. :4.279e+03
## 1st Qu.:9.251e+05
## Median :6.345e+06
## Mean :2.060e+08
## 3rd Qu.:4.220e+07
## Max. :7.530e+09
## NA's :165
head(Y)
## Country Name Country Code variable value
## 1 Aruba ABW 1960 54211
## 2 Afghanistan AFG 1960 8996351
## 3 Angola AGO 1960 5643182
## 4 Albania ALB 1960 1608800
## 5 Andorra AND 1960 13411
## 6 Arab World ARB 1960 92490932
Az alábbi módon paraméterezzük a melt
függvényt, hogy a megfelelő oszlopneveket kapjuk:
Y <- melt(X, variable.name = "Year", value.name = "Population")
## Using Country Name, Country Code as id variables
summary(Y)
## Country Name Country Code Year
## Afghanistan : 58 ABW : 58 1960 : 264
## Albania : 58 AFG : 58 1961 : 264
## Algeria : 58 AGO : 58 1962 : 264
## American Samoa: 58 ALB : 58 1963 : 264
## Andorra : 58 AND : 58 1964 : 264
## Angola : 58 ARB : 58 1965 : 264
## (Other) :14964 (Other):14964 (Other):13728
## Population
## Min. :4.279e+03
## 1st Qu.:9.251e+05
## Median :6.345e+06
## Mean :2.060e+08
## 3rd Qu.:4.220e+07
## Max. :7.530e+09
## NA's :165
head(Y)
## Country Name Country Code Year Population
## 1 Aruba ABW 1960 54211
## 2 Afghanistan AFG 1960 8996351
## 3 Angola AGO 1960 5643182
## 4 Albania ALB 1960 1608800
## 5 Andorra AND 1960 13411
## 6 Arab World ARB 1960 92490932
A nominális Year
oszlopot alakítsuk numerikussá:
Y$Year <- as.numeric(as.character(Y$Year))
summary(Y)
## Country Name Country Code Year Population
## Afghanistan : 58 ABW : 58 Min. :1960 Min. :4.279e+03
## Albania : 58 AFG : 58 1st Qu.:1974 1st Qu.:9.251e+05
## Algeria : 58 AGO : 58 Median :1988 Median :6.345e+06
## American Samoa: 58 ALB : 58 Mean :1988 Mean :2.060e+08
## Andorra : 58 AND : 58 3rd Qu.:2003 3rd Qu.:4.220e+07
## Angola : 58 ARB : 58 Max. :2017 Max. :7.530e+09
## (Other) :14964 (Other):14964 NA's :165
Végül rendezzük a sorokat országkód szerint növekvő sorrendbe:
Y.sorted <- Y[order(Y$"Country Code"),]
head(Y.sorted)
## Country Name Country Code Year Population
## 1 Aruba ABW 1960 54211
## 265 Aruba ABW 1961 55438
## 529 Aruba ABW 1962 56225
## 793 Aruba ABW 1963 56695
## 1057 Aruba ABW 1964 57032
## 1321 Aruba ABW 1965 57360
Az adatok forrása: https://datasets.imdbws.com/
Az adatokat TSV formátumban tartalmazó tömörített állomány letöltése:
tmp <- tempfile(fileext = ".gz")
download.file("https://datasets.imdbws.com/title.basics.tsv.gz", tmp)
Az állomány túl nagy ahhoz, hogy read.delim
függvénnyel olvassuk be, a data.table
csomag fread
függvényét használjuk helyette:
library(data.table)
## data.table 1.12.2 using 4 threads (see ?getDTthreads). Latest news: r-datatable.com
##
## Attaching package: 'data.table'
## The following objects are masked from 'package:reshape2':
##
## dcast, melt
## The following objects are masked from 'package:lubridate':
##
## hour, isoweek, mday, minute, month, quarter, second, wday,
## week, yday, year
X <- fread(tmp, sep = "\t", na.strings = "\\N", quote = "", verbose = TRUE)
## omp_get_num_procs()==8
## R_DATATABLE_NUM_PROCS_PERCENT=="" (default 50)
## R_DATATABLE_NUM_THREADS==""
## omp_get_thread_limit()==2147483647
## omp_get_max_threads()==8
## OMP_THREAD_LIMIT==""
## OMP_NUM_THREADS==""
## data.table is using 4 threads. This is set on startup, and by setDTthreads(). See ?setDTthreads.
## RestoreAfterFork==true
## Registered S3 method overwritten by 'R.oo':
## method from
## throw.default R.methodsS3
## Input contains no \n. Taking this to be a filename to open
## [01] Check arguments
## Using 4 threads (omp_get_max_threads()=8, nth=4)
## NAstrings = [<<\N>>]
## None of the NAstrings look like numbers.
## show progress = 1
## 0/1 column will be read as integer
## [02] Opening the file
## Opening file /tmp/RtmpLKNfbu/file90041986e1f
## File opened, size = 480.3MB (503679513 bytes).
## Memory mapped ok
## [03] Detect and skip BOM
## [04] Arrange mmap to be \0 terminated
## \n has been found in the input and different lines can end with different line endings (e.g. mixed \n and \r\n in one file). This is common and ideal.
## [05] Skipping initial rows if needed
## Positioned on line 1 starting: <<tconst titleType primaryTitle >>
## [06] Detect separator, quoting rule, and ncolumns
## Using supplied sep '\t'
## sep=0x9 with 100 lines of 9 fields using quote rule 0
## Detected 9 columns on line 1. This line is either column names or first data row. Line starts as: <<tconst titleType primaryTitle >>
## Quote rule picked = 0
## fill=false and the most number of columns found is 9
## [07] Detect column types, good nrow estimate and whether first row is column names
## Number of sampling jump points = 100 because (503679512 bytes from row 1 to eof) / (2 * 9100 jump0size) == 27674
## Type codes (jump 000) : AAAA5525A Quote rule 0
## Type codes (jump 001) : AAAA5555A Quote rule 0
## Type codes (jump 100) : AAAA5555A Quote rule 0
## 'header' determined to be true due to column 5 containing a string on row 1 and a lower type (int32) in the rest of the 10053 sample rows
## =====
## Sampled 10053 rows (handled \n inside quoted fields) at 101 jump points
## Bytes from first data row on line 2 to the end of last row: 503679420
## Line length: mean=84.08 sd=23.29 min=39 max=343
## Estimated number of rows: 503679420 / 84.08 = 5990530
## Initial alloc = 11981060 rows (5990530 + 100%) using bytes/max(mean-2*sd,min) clamped between [1.1*estn, 2.0*estn]
## =====
## [08] Assign column names
## [09] Apply user overrides on column types
## After 0 type and 0 drop user overrides : AAAA5555A
## [10] Allocate memory for the datatable
## Allocating 9 column slots (9 - 0 dropped) with 11981060 rows
## [11] Read the data
## jumps=[0..480), chunk_size=1049332, total_size=503679420
## Read 5937358 rows x 9 columns from 480.3MB (503679513 bytes) file in 00:12.029 wall clock time
## [12] Finalizing the datatable
## Type counts:
## 4 : int32 '5'
## 5 : string 'A'
## =============================
## 0.000s ( 0%) Memory map 0.469GB file
## 0.002s ( 0%) sep='\t' ncol=9 and header detection
## 0.000s ( 0%) Column type detection using 10053 sample rows
## 1.017s ( 8%) Allocation of 11981060 rows x 9 cols (0.625GB) of which 5937358 ( 50%) rows used
## 11.010s ( 92%) Reading 480 chunks (0 swept) of 1.001MB (each chunk 12369 rows) using 4 threads
## + 0.669s ( 6%) Parse to row-major thread buffers (grown 0 times)
## + 9.071s ( 75%) Transpose
## + 1.270s ( 11%) Waiting
## 0.000s ( 0%) Rereading 0 columns due to out-of-sample type exceptions
## 12.029s Total
Vizsgáljuk meg az adatokat:
str(X)
## Classes 'data.table' and 'data.frame': 5937358 obs. of 9 variables:
## $ tconst : chr "tt0000001" "tt0000002" "tt0000003" "tt0000004" ...
## $ titleType : chr "short" "short" "short" "short" ...
## $ primaryTitle : chr "Carmencita" "Le clown et ses chiens" "Pauvre Pierrot" "Un bon bock" ...
## $ originalTitle : chr "Carmencita" "Le clown et ses chiens" "Pauvre Pierrot" "Un bon bock" ...
## $ isAdult : int 0 0 0 0 0 0 0 0 0 0 ...
## $ startYear : int 1894 1892 1892 1892 1893 1894 1894 1894 1894 1895 ...
## $ endYear : int NA NA NA NA NA NA NA NA NA NA ...
## $ runtimeMinutes: int 1 5 4 NA 1 1 1 1 45 1 ...
## $ genres : chr "Documentary,Short" "Animation,Short" "Animation,Comedy,Romance" "Animation,Short" ...
## - attr(*, ".internal.selfref")=<externalptr>
summary(X)
## tconst titleType primaryTitle
## Length:5937358 Length:5937358 Length:5937358
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## originalTitle isAdult startYear endYear
## Length:5937358 Min. :0.00000 Min. :1874 Min. :1924
## Class :character 1st Qu.:0.00000 1st Qu.:1996 1st Qu.:1992
## Mode :character Median :0.00000 Median :2009 Median :2007
## Mean :0.02993 Mean :2001 Mean :2001
## 3rd Qu.:0.00000 3rd Qu.:2014 3rd Qu.:2015
## Max. :1.00000 Max. :2115 Max. :2027
## NA's :334946 NA's :5887267
## runtimeMinutes genres
## Min. : 0 Length:5937358
## 1st Qu.: 15 Class :character
## Median : 30 Mode :character
## Mean : 45
## 3rd Qu.: 61
## Max. :125156
## NA's :4157753
X
## tconst titleType primaryTitle
## 1: tt0000001 short Carmencita
## 2: tt0000002 short Le clown et ses chiens
## 3: tt0000003 short Pauvre Pierrot
## 4: tt0000004 short Un bon bock
## 5: tt0000005 short Blacksmith Scene
## ---
## 5937354: tt9916848 tvEpisode Episode #3.17
## 5937355: tt9916850 tvEpisode Episode #3.19
## 5937356: tt9916852 tvEpisode Episode #3.20
## 5937357: tt9916856 short The Wind
## 5937358: tt9916880 tvEpisode Horrid Henry Knows It All
## originalTitle isAdult startYear endYear
## 1: Carmencita 0 1894 NA
## 2: Le clown et ses chiens 0 1892 NA
## 3: Pauvre Pierrot 0 1892 NA
## 4: Un bon bock 0 1892 NA
## 5: Blacksmith Scene 0 1893 NA
## ---
## 5937354: Episode #3.17 0 2010 NA
## 5937355: Episode #3.19 0 2010 NA
## 5937356: Episode #3.20 0 2010 NA
## 5937357: The Wind 0 2015 NA
## 5937358: Horrid Henry Knows It All 0 2014 NA
## runtimeMinutes genres
## 1: 1 Documentary,Short
## 2: 5 Animation,Short
## 3: 4 Animation,Comedy,Romance
## 4: NA Animation,Short
## 5: 1 Comedy,Short
## ---
## 5937354: NA Action,Drama,Family
## 5937355: NA Action,Drama,Family
## 5937356: NA Action,Drama,Family
## 5937357: 27 Short
## 5937358: NA Animation,Comedy,Family
Készítsünk hisztogramot:
library(ggplot2)
qplot(startYear, data = X, geom = "histogram", binwidth = 1, xlab = "Year")
## Warning: Removed 334946 rows containing non-finite values (stat_bin).
Az adatok forrása: https://data.worldbank.org/indicator/SP.POP.TOTL
Az adatokat tartalmazó MS Excel állomány letöltése:
tmp <- tempfile(fileext = ".xls")
tmp
## [1] "/tmp/RtmpLKNfbu/file90074d9d480.xls"
download.file("https://api.worldbank.org/v2/en/indicator/SP.POP.TOTL?downloadformat=excel", tmp)
Az adatok beolvasása a letöltött állományból:
library(readxl)
X <- read_excel(tmp, skip = 3)
Vizsgáljuk meg az adatokat:
str(X)
## Classes 'tbl_df', 'tbl' and 'data.frame': 264 obs. of 63 variables:
## $ Country Name : chr "Aruba" "Afghanistan" "Angola" "Albania" ...
## $ Country Code : chr "ABW" "AFG" "AGO" "ALB" ...
## $ Indicator Name: chr "Population, total" "Population, total" "Population, total" "Population, total" ...
## $ Indicator Code: chr "SP.POP.TOTL" "SP.POP.TOTL" "SP.POP.TOTL" "SP.POP.TOTL" ...
## $ 1960 : num 54211 8996351 5643182 1608800 13411 ...
## $ 1961 : num 55438 9166764 5753024 1659800 14375 ...
## $ 1962 : num 56225 9345868 5866061 1711319 15370 ...
## $ 1963 : num 56695 9533954 5980417 1762621 16412 ...
## $ 1964 : num 57032 9731361 6093321 1814135 17469 ...
## $ 1965 : num 57360 9938414 6203299 1864791 18549 ...
## $ 1966 : num 57715 10152331 6309770 1914573 19647 ...
## $ 1967 : num 58055 10372630 6414995 1965598 20758 ...
## $ 1968 : num 58386 10604346 6523791 2022272 21890 ...
## $ 1969 : num 58726 10854428 6642632 2081695 23058 ...
## $ 1970 : num 59063 11126123 6776381 2135479 24276 ...
## $ 1971 : num 59440 11417825 6927269 2187853 25559 ...
## $ 1972 : num 59840 11721940 7094834 2243126 26892 ...
## $ 1973 : num 60243 12027822 7277960 2296752 28232 ...
## $ 1974 : num 60528 12321541 7474338 2350124 29520 ...
## $ 1975 : num 60657 12590286 7682479 2404831 30705 ...
## $ 1976 : num 60586 12840299 7900997 2458526 31777 ...
## $ 1977 : num 60366 13067538 8130988 2513546 32771 ...
## $ 1978 : num 60103 13237734 8376147 2566266 33737 ...
## $ 1979 : num 59980 13306695 8641521 2617832 34818 ...
## $ 1980 : num 60096 13248370 8929900 2671997 36067 ...
## $ 1981 : num 60567 13053954 9244507 2726056 37500 ...
## $ 1982 : num 61345 12749645 9582156 2784278 39114 ...
## $ 1983 : num 62201 12389269 9931562 2843960 40867 ...
## $ 1984 : num 62836 12047115 10277321 2904429 42706 ...
## $ 1985 : num 63026 11783050 10609042 2964762 44600 ...
## $ 1986 : num 62644 11601041 10921037 3022635 46517 ...
## $ 1987 : num 61833 11502761 11218268 3083605 48455 ...
## $ 1988 : num 61079 11540888 11513968 3142336 50434 ...
## $ 1989 : num 61032 11777609 11827237 3227943 52448 ...
## $ 1990 : num 62149 12249114 12171441 3286542 54509 ...
## $ 1991 : num 64622 12993657 12553446 3266790 56671 ...
## $ 1992 : num 68235 13981231 12968345 3247039 58888 ...
## $ 1993 : num 72504 15095099 13403734 3227287 60971 ...
## $ 1994 : num 76700 16172719 13841301 3207536 62677 ...
## $ 1995 : num 80324 17099541 14268994 3187784 63850 ...
## $ 1996 : num 83200 17822884 14682284 3168033 64360 ...
## $ 1997 : num 85451 18381605 15088981 3148281 64327 ...
## $ 1998 : num 87277 18863999 15504318 3128530 64142 ...
## $ 1999 : num 89005 19403676 15949766 3108778 64370 ...
## $ 2000 : num 90853 20093756 16440924 3089027 65390 ...
## $ 2001 : num 92898 20966463 16983266 3060173 67341 ...
## $ 2002 : num 94992 21979923 17572649 3051010 70049 ...
## $ 2003 : num 97017 23064851 18203369 3039616 73182 ...
## $ 2004 : num 98737 24118979 18865716 3026939 76244 ...
## $ 2005 : num 100031 25070798 19552542 3011487 78867 ...
## $ 2006 : num 100832 25893450 20262399 2992547 80991 ...
## $ 2007 : num 101220 26616792 20997687 2970017 82683 ...
## $ 2008 : num 101353 27294031 21759420 2947314 83861 ...
## $ 2009 : num 101453 28004331 22549547 2927519 84462 ...
## $ 2010 : num 101669 28803167 23369131 2913021 84449 ...
## $ 2011 : num 102053 29708599 24218565 2905195 83751 ...
## $ 2012 : num 102577 30696958 25096150 2900401 82431 ...
## $ 2013 : num 103187 31731688 25998340 2895092 80788 ...
## $ 2014 : num 103795 32758020 26920466 2889104 79223 ...
## $ 2015 : num 104341 33736494 27859305 2880703 78014 ...
## $ 2016 : num 104822 34656032 28813463 2876101 77281 ...
## $ 2017 : num 105264 35530081 29784193 2873457 76965 ...
## $ 2018 : logi NA NA NA NA NA NA ...
summary(X)
## Country Name Country Code Indicator Name
## Length:264 Length:264 Length:264
## Class :character Class :character Class :character
## Mode :character Mode :character Mode :character
##
##
##
##
## Indicator Code 1960 1961
## Length:264 Min. :4.279e+03 Min. :4.453e+03
## Class :character 1st Qu.:5.184e+05 1st Qu.:5.301e+05
## Mode :character Median :3.670e+06 Median :3.734e+06
## Mean :1.178e+08 Mean :1.194e+08
## 3rd Qu.:2.533e+07 3rd Qu.:2.612e+07
## Max. :3.032e+09 Max. :3.073e+09
## NA's :4 NA's :4
## 1962 1963 1964
## Min. :4.566e+03 Min. :4.656e+03 Min. :4.748e+03
## 1st Qu.:5.427e+05 1st Qu.:5.560e+05 1st Qu.:5.684e+05
## Median :3.840e+06 Median :3.955e+06 Median :4.074e+06
## Mean :1.215e+08 Mean :1.241e+08 Mean :1.268e+08
## 3rd Qu.:2.691e+07 3rd Qu.:2.770e+07 3rd Qu.:2.848e+07
## Max. :3.127e+09 Max. :3.192e+09 Max. :3.257e+09
## NA's :4 NA's :4 NA's :4
## 1965 1966 1967
## Min. :4.841e+03 Min. :4.936e+03 Min. :5.033e+03
## 1st Qu.:5.728e+05 1st Qu.:5.786e+05 1st Qu.:5.882e+05
## Median :4.171e+06 Median :4.234e+06 Median :4.300e+06
## Mean :1.295e+08 Mean :1.324e+08 Mean :1.353e+08
## 3rd Qu.:2.925e+07 3rd Qu.:3.000e+07 3rd Qu.:3.060e+07
## Max. :3.325e+09 Max. :3.395e+09 Max. :3.464e+09
## NA's :4 NA's :4 NA's :4
## 1968 1969 1970
## Min. :5.161e+03 Min. :5.303e+03 Min. :5.450e+03
## 1st Qu.:6.258e+05 1st Qu.:6.568e+05 1st Qu.:6.751e+05
## Median :4.368e+06 Median :4.449e+06 Median :4.524e+06
## Mean :1.382e+08 Mean :1.412e+08 Mean :1.443e+08
## 3rd Qu.:3.120e+07 3rd Qu.:3.180e+07 3rd Qu.:3.235e+07
## Max. :3.535e+09 Max. :3.610e+09 Max. :3.686e+09
## NA's :4 NA's :4 NA's :4
## 1971 1972 1973
## Min. :5.601e+03 Min. :5.756e+03 Min. :5.915e+03
## 1st Qu.:6.905e+05 1st Qu.:7.011e+05 1st Qu.:7.110e+05
## Median :4.622e+06 Median :4.729e+06 Median :4.844e+06
## Mean :1.475e+08 Mean :1.506e+08 Mean :1.538e+08
## 3rd Qu.:3.281e+07 3rd Qu.:3.317e+07 3rd Qu.:3.354e+07
## Max. :3.763e+09 Max. :3.840e+09 Max. :3.916e+09
## NA's :4 NA's :4 NA's :4
## 1974 1975 1976
## Min. :6.078e+03 Min. :6.291e+03 Min. :6.530e+03
## 1st Qu.:7.194e+05 1st Qu.:7.256e+05 1st Qu.:7.315e+05
## Median :4.961e+06 Median :5.035e+06 Median :5.129e+06
## Mean :1.569e+08 Mean :1.600e+08 Mean :1.630e+08
## 3rd Qu.:3.393e+07 3rd Qu.:3.433e+07 3rd Qu.:3.473e+07
## Max. :3.993e+09 Max. :4.068e+09 Max. :4.141e+09
## NA's :4 NA's :4 NA's :4
## 1977 1978 1979
## Min. :6.778e+03 Min. :7.035e+03 Min. :7.264e+03
## 1st Qu.:7.588e+05 1st Qu.:7.839e+05 1st Qu.:7.884e+05
## Median :5.276e+06 Median :5.397e+06 Median :5.518e+06
## Mean :1.660e+08 Mean :1.691e+08 Mean :1.722e+08
## 3rd Qu.:3.521e+07 3rd Qu.:3.620e+07 3rd Qu.:3.721e+07
## Max. :4.213e+09 Max. :4.287e+09 Max. :4.363e+09
## NA's :4 NA's :4 NA's :4
## 1980 1981 1982
## Min. :7.488e+03 Min. :7.592e+03 Min. :7.717e+03
## 1st Qu.:7.957e+05 1st Qu.:8.063e+05 1st Qu.:8.198e+05
## Median :5.641e+06 Median :5.785e+06 Median :5.938e+06
## Mean :1.754e+08 Mean :1.786e+08 Mean :1.820e+08
## 3rd Qu.:3.765e+07 3rd Qu.:3.800e+07 3rd Qu.:3.832e+07
## Max. :4.439e+09 Max. :4.518e+09 Max. :4.599e+09
## NA's :4 NA's :4 NA's :4
## 1983 1984 1985
## Min. :7.854e+03 Min. :8.005e+03 Min. :8.173e+03
## 1st Qu.:8.373e+05 1st Qu.:8.597e+05 1st Qu.:8.822e+05
## Median :6.099e+06 Median :6.265e+06 Median :6.427e+06
## Mean :1.854e+08 Mean :1.889e+08 Mean :1.923e+08
## 3rd Qu.:3.869e+07 3rd Qu.:3.974e+07 3rd Qu.:4.080e+07
## Max. :4.681e+09 Max. :4.763e+09 Max. :4.846e+09
## NA's :4 NA's :4 NA's :4
## 1986 1987 1988
## Min. :8.353e+03 Min. :8.554e+03 Min. :8.755e+03
## 1st Qu.:9.045e+05 1st Qu.:9.269e+05 1st Qu.:9.497e+05
## Median :6.516e+06 Median :6.701e+06 Median :6.858e+06
## Mean :1.959e+08 Mean :1.996e+08 Mean :2.033e+08
## 3rd Qu.:4.144e+07 3rd Qu.:4.209e+07 3rd Qu.:4.276e+07
## Max. :4.932e+09 Max. :5.020e+09 Max. :5.109e+09
## NA's :4 NA's :4 NA's :4
## 1989 1990 1991
## Min. :8.947e+03 Min. :9.003e+03 Min. :9.053e+03
## 1st Qu.:9.730e+05 1st Qu.:1.024e+06 1st Qu.:1.045e+06
## Median :7.000e+06 Median :7.129e+06 Median :7.148e+06
## Mean :2.071e+08 Mean :2.092e+08 Mean :2.129e+08
## 3rd Qu.:4.345e+07 3rd Qu.:4.231e+07 3rd Qu.:4.277e+07
## Max. :5.198e+09 Max. :5.288e+09 Max. :5.376e+09
## NA's :4 NA's :2 NA's :2
## 1992 1993 1994
## Min. :9.109e+03 Min. :9.156e+03 Min. :9.190e+03
## 1st Qu.:1.063e+06 1st Qu.:1.089e+06 1st Qu.:1.113e+06
## Median :7.382e+06 Median :7.495e+06 Median :7.584e+06
## Mean :2.172e+08 Mean :2.208e+08 Mean :2.243e+08
## 3rd Qu.:4.375e+07 3rd Qu.:4.419e+07 3rd Qu.:4.464e+07
## Max. :5.460e+09 Max. :5.545e+09 Max. :5.629e+09
## NA's :3 NA's :3 NA's :3
## 1995 1996 1997
## Min. :9.230e+03 Min. :9.256e+03 Min. :9.277e+03
## 1st Qu.:1.126e+06 1st Qu.:1.140e+06 1st Qu.:1.156e+06
## Median :7.655e+06 Median :7.740e+06 Median :7.855e+06
## Mean :2.269e+08 Mean :2.304e+08 Mean :2.339e+08
## 3rd Qu.:4.463e+07 3rd Qu.:4.509e+07 3rd Qu.:4.556e+07
## Max. :5.714e+09 Max. :5.797e+09 Max. :5.879e+09
## NA's :2 NA's :2 NA's :2
## 1998 1999 2000
## Min. :9.306e+03 Min. :9.345e+03 Min. :9.420e+03
## 1st Qu.:1.166e+06 1st Qu.:1.198e+06 1st Qu.:1.231e+06
## Median :7.913e+06 Median :7.992e+06 Median :8.049e+06
## Mean :2.364e+08 Mean :2.397e+08 Mean :2.431e+08
## 3rd Qu.:4.562e+07 3rd Qu.:4.626e+07 3rd Qu.:4.704e+07
## Max. :5.961e+09 Max. :6.041e+09 Max. :6.121e+09
## NA's :1 NA's :1 NA's :1
## 2001 2002 2003
## Min. :9.512e+03 Min. :9.635e+03 Min. :9.767e+03
## 1st Qu.:1.265e+06 1st Qu.:1.286e+06 1st Qu.:1.303e+06
## Median :8.111e+06 Median :8.172e+06 Median :8.234e+06
## Mean :2.464e+08 Mean :2.497e+08 Mean :2.530e+08
## 3rd Qu.:4.788e+07 3rd Qu.:4.792e+07 3rd Qu.:4.785e+07
## Max. :6.201e+09 Max. :6.280e+09 Max. :6.359e+09
## NA's :1 NA's :1 NA's :1
## 2004 2005 2006
## Min. :9.894e+03 Min. :1.003e+04 Min. :1.007e+04
## 1st Qu.:1.320e+06 1st Qu.:1.326e+06 1st Qu.:1.325e+06
## Median :8.306e+06 Median :8.392e+06 Median :8.485e+06
## Mean :2.564e+08 Mean :2.598e+08 Mean :2.632e+08
## 3rd Qu.:4.816e+07 3rd Qu.:4.865e+07 3rd Qu.:4.911e+07
## Max. :6.439e+09 Max. :6.520e+09 Max. :6.601e+09
## NA's :1 NA's :1 NA's :1
## 2007 2008 2009
## Min. :1.000e+04 Min. :9.947e+03 Min. :9.945e+03
## 1st Qu.:1.325e+06 1st Qu.:1.363e+06 1st Qu.:1.426e+06
## Median :8.857e+06 Median :9.220e+06 Median :9.299e+06
## Mean :2.666e+08 Mean :2.701e+08 Mean :2.736e+08
## 3rd Qu.:4.953e+07 3rd Qu.:4.995e+07 3rd Qu.:5.039e+07
## Max. :6.683e+09 Max. :6.766e+09 Max. :6.849e+09
## NA's :1 NA's :1 NA's :1
## 2010 2011 2012
## Min. :1.002e+04 Min. :1.006e+04 Min. :1.028e+04
## 1st Qu.:1.444e+06 1st Qu.:1.465e+06 1st Qu.:1.416e+06
## Median :9.378e+06 Median :9.461e+06 Median :9.624e+06
## Mean :2.771e+08 Mean :2.807e+08 Mean :2.853e+08
## 3rd Qu.:5.087e+07 3rd Qu.:5.141e+07 3rd Qu.:5.250e+07
## Max. :6.933e+09 Max. :7.015e+09 Max. :7.099e+09
## NA's :1 NA's :1 NA's :2
## 2013 2014 2015
## Min. :1.082e+04 Min. :1.091e+04 Min. :1.100e+04
## 1st Qu.:1.432e+06 1st Qu.:1.447e+06 1st Qu.:1.472e+06
## Median :9.747e+06 Median :9.879e+06 Median :1.002e+07
## Mean :2.890e+08 Mean :2.927e+08 Mean :2.964e+08
## 3rd Qu.:5.319e+07 3rd Qu.:5.396e+07 3rd Qu.:5.494e+07
## Max. :7.185e+09 Max. :7.271e+09 Max. :7.357e+09
## NA's :2 NA's :2 NA's :2
## 2016 2017 2018
## Min. :1.110e+04 Min. :1.119e+04 Mode:logical
## 1st Qu.:1.523e+06 1st Qu.:1.577e+06 NA's:264
## Median :1.012e+07 Median :1.018e+07
## Mean :3.002e+08 Mean :3.039e+08
## 3rd Qu.:5.590e+07 3rd Qu.:5.716e+07
## Max. :7.444e+09 Max. :7.530e+09
## NA's :2 NA's :2