1. 使用套件tidyquant, timetk，並讀入資料 https://github.com/swtzang/FinDB_2019/tree/master/data_wrangle_practice/tej_day_price_2017_2018.txt

library(tidyquant)
## Warning: package 'tidyquant' was built under R version 3.5.3
## Loading required package: lubridate
## Warning: package 'lubridate' was built under R version 3.5.3
## 
## Attaching package: 'lubridate'
## The following object is masked from 'package:base':
## 
##     date
## Loading required package: PerformanceAnalytics
## Warning: package 'PerformanceAnalytics' was built under R version 3.5.3
## Loading required package: xts
## Loading required package: zoo
## 
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric
## 
## Attaching package: 'PerformanceAnalytics'
## The following object is masked from 'package:graphics':
## 
##     legend
## Loading required package: quantmod
## Warning: package 'quantmod' was built under R version 3.5.3
## Loading required package: TTR
## Warning: package 'TTR' was built under R version 3.5.3
## Version 0.4-0 included new data defaults. See ?getSymbols.
## Loading required package: tidyverse
## Warning: package 'tidyverse' was built under R version 3.5.3
## -- Attaching packages ------------------------------------------------------ tidyverse 1.2.1 --
## √ ggplot2 3.1.0       √ purrr   0.3.1  
## √ tibble  2.0.1       √ dplyr   0.8.0.1
## √ tidyr   0.8.3       √ stringr 1.4.0  
## √ readr   1.3.1       √ forcats 0.4.0
## Warning: package 'ggplot2' was built under R version 3.5.3
## Warning: package 'readr' was built under R version 3.5.3
## Warning: package 'forcats' was built under R version 3.5.3
## -- Conflicts --------------------------------------------------------- tidyverse_conflicts() --
## x lubridate::as.difftime() masks base::as.difftime()
## x lubridate::date()        masks base::date()
## x dplyr::filter()          masks stats::filter()
## x dplyr::first()           masks xts::first()
## x lubridate::intersect()   masks base::intersect()
## x dplyr::lag()             masks stats::lag()
## x dplyr::last()            masks xts::last()
## x lubridate::setdiff()     masks base::setdiff()
## x lubridate::union()       masks base::union()
library(timetk)
## Warning: package 'timetk' was built under R version 3.5.3
stock_day <- read_tsv("C:/Users/Sarah/Desktop/FinDB2019_SalesAnalysis/FinDB_2019_Sales_Analysis/data_wrangle_practice/tej_day_price_2017_2018.txt")
## Parsed with column specification:
## cols(
##   證券代碼 = col_double(),
##   簡稱 = col_character(),
##   `TSE 產業別` = col_character(),
##   上市別 = col_character(),
##   年月日 = col_double(),
##   `開盤價(元)` = col_double(),
##   `最高價(元)` = col_double(),
##   `收盤價(元)` = col_double(),
##   `最低價(元)` = col_double(),
##   `成交值(千元)` = col_double(),
##   `市值(百萬元)` = col_double(),
##   `成交量(千股)` = col_double()
## )
glimpse(stock_day)
## Observations: 443,171
## Variables: 12
## $ 證券代碼       <dbl> 1101, 1102, 1103, 1104, 1108, 1109, 1110, 1201, 120...
## $ 簡稱           <chr> "台泥", "亞泥", "嘉泥", "環泥", "幸福", "信大", "東泥", "味全", "...
## $ `TSE 產業別`   <chr> "01", "01", "01", "01", "01", "01", "01", "02", "0...
## $ 上市別         <chr> "TSE", "TSE", "TSE", "TSE", "TSE", "TSE", "TSE", "...
## $ 年月日         <dbl> 20170103, 20170103, 20170103, 20170103, 20170103, ...
## $ `開盤價(元)`   <dbl> 29.90, 24.91, 8.27, 21.41, 8.56, 10.11, 15.58, 17.5...
## $ `最高價(元)`   <dbl> 29.90, 24.95, 8.27, 21.54, 8.57, 10.11, 15.63, 17.7...
## $ `收盤價(元)`   <dbl> 29.64, 24.95, 8.27, 21.50, 8.57, 10.11, 15.54, 17.6...
## $ `最低價(元)`   <dbl> 29.35, 24.76, 8.17, 21.37, 8.56, 10.11, 15.54, 17.5...
## $ `成交值(千元)` <dbl> 101450, 33550, 2411, 3705, 182, 42, 406, 11504, 171,...
## $ `市值(百萬元)` <dbl> 129779, 89078, 6748, 15610, 3703, 3789, 9009, 8931, ...
## $ `成交量(千股)` <dbl> 2890, 1271, 278, 150, 20, 4, 25, 653, 7, 2213, 19, 2...

2. 選取欄位“證券代碼”, “簡稱”, “年月日”, “收盤價(元)”, “市值(百萬元)”, 並將名稱改為“id”, “name”, “date”, “price”, “cap”。

price_day <- stock_day %>% 
  rename(id    = `證券代碼`, 
         name  = `簡稱`, 
         date  = `年月日`, 
         price = `收盤價(元)`,
         cap   = `市值(百萬元)`
  )

dim(price_day)
## [1] 443171     12
glimpse(price_day)
## Observations: 443,171
## Variables: 12
## $ id             <dbl> 1101, 1102, 1103, 1104, 1108, 1109, 1110, 1201,...
## $ name           <chr> "台泥", "亞泥", "嘉泥", "環泥", "幸福", "信大", "東泥", "味全",...
## $ `TSE 產業別`   <chr> "01", "01", "01", "01", "01", "01", "01", "02", "0...
## $ 上市別         <chr> "TSE", "TSE", "TSE", "TSE", "TSE", "TSE", "TSE", "...
## $ date           <dbl> 20170103, 20170103, 20170103, 20170103, 2017010...
## $ `開盤價(元)`   <dbl> 29.90, 24.91, 8.27, 21.41, 8.56, 10.11, 15.58, 17.5...
## $ `最高價(元)`   <dbl> 29.90, 24.95, 8.27, 21.54, 8.57, 10.11, 15.63, 17.7...
## $ price          <dbl> 29.64, 24.95, 8.27, 21.50, 8.57, 10.11, 15.54, ...
## $ `最低價(元)`   <dbl> 29.35, 24.76, 8.17, 21.37, 8.56, 10.11, 15.54, 17.5...
## $ `成交值(千元)` <dbl> 101450, 33550, 2411, 3705, 182, 42, 406, 11504, 171,...
## $ cap            <dbl> 129779, 89078, 6748, 15610, 3703, 3789, 9009, 8...
## $ `成交量(千股)` <dbl> 2890, 1271, 278, 150, 20, 4, 25, 653, 7, 2213, 19, 2...
price_day
## # A tibble: 443,171 x 12
##       id name  `TSE 產業別` 上市別   date `開盤價(元)` `最高價(元)` price
##    <dbl> <chr> <chr>        <chr>   <dbl>        <dbl>        <dbl> <dbl>
##  1  1101 台泥  01           TSE    2.02e7        29.9         29.9  29.6 
##  2  1102 亞泥  01           TSE    2.02e7        24.9         25.0  25.0 
##  3  1103 嘉泥  01           TSE    2.02e7         8.27         8.27  8.27
##  4  1104 環泥  01           TSE    2.02e7        21.4         21.5  21.5 
##  5  1108 幸福  01           TSE    2.02e7         8.56         8.57  8.57
##  6  1109 信大  01           TSE    2.02e7        10.1         10.1  10.1 
##  7  1110 東泥  01           TSE    2.02e7        15.6         15.6  15.5 
##  8  1201 味全  02           TSE    2.02e7        17.6         17.7  17.6 
##  9  1203 味王  02           TSE    2.02e7        21.4         21.4  20.8 
## 10  1210 大成  02           TSE    2.02e7        24.8         25.0  24.7 
## # ... with 443,161 more rows, and 4 more variables: `最低價(元)` <dbl>,
## #   `成交值(千元)` <dbl>, cap <dbl>, `成交量(千股)` <dbl>

3. 選取id, date, price, 並將id改為文字格式，date改為日期格式，並將資料格式改為寬資料。提示：使用spread()。

price_day1 <- stock_day %>% 
  rename(id    = `證券代碼`, 
         name  = `簡稱`, 
         date  = `年月日`, 
         price = `收盤價(元)`,
         cap   = `市值(百萬元)`
  ) %>% 
  mutate(id = as.character(id)) %>%
  mutate(date = as.Date(as.character(date), '%Y%m%d')) %>%
  select(id, date, price) %>% 
  spread(key = id, value = price) 

dim(price_day1)
## [1] 493 929
glimpse(price_day1)
## Observations: 493
## Variables: 929
## $ date   <date> 2017-01-03, 2017-01-04, 2017-01-05, 2017-01-06, 2017-0...
## $ `1101` <dbl> 29.64, 29.73, 29.73, 29.73, 29.43, 29.47, 30.19, 30.61,...
## $ `1102` <dbl> 24.95, 24.81, 24.95, 24.95, 24.76, 24.67, 25.09, 25.61,...
## $ `1103` <dbl> 8.27, 8.23, 8.24, 8.21, 8.31, 8.28, 8.33, 8.35, 8.40, 8...
## $ `1104` <dbl> 21.50, 21.50, 21.54, 21.41, 21.41, 21.37, 21.46, 21.46,...
## $ `1108` <dbl> 8.57, 8.56, 8.61, 8.57, 8.59, 8.59, 8.57, 8.60, 8.59, 8...
## $ `1109` <dbl> 10.11, 10.11, 10.09, 10.11, 10.11, 10.16, 10.21, 10.11,...
## $ `1110` <dbl> 15.54, 15.44, 15.44, 15.39, 15.29, 15.29, 15.14, 15.19,...
## $ `1201` <dbl> 17.65, 17.45, 17.50, 17.45, 17.55, 17.40, 18.00, 18.10,...
## $ `1203` <dbl> 20.83, 20.92, 20.92, 21.10, 21.06, 20.92, 20.87, 20.92,...
## $ `1210` <dbl> 24.73, 24.68, 24.60, 24.43, 24.09, 23.96, 24.18, 24.18,...
## $ `1213` <dbl> 16.80, 16.80, 16.80, 16.85, 16.80, 16.75, 16.80, 16.75,...
## $ `1215` <dbl> 42.14, 43.51, 43.60, 43.74, 43.37, 42.78, 43.19, 43.33,...
## $ `1216` <dbl> 47.81, 47.54, 48.53, 48.53, 48.62, 48.17, 48.44, 48.80,...
## $ `1217` <dbl> 7.33, 7.34, 7.34, 7.38, 7.35, 7.34, 7.40, 7.49, 7.43, 7...
## $ `1218` <dbl> 14.19, 14.28, 14.28, 14.23, 14.28, 14.23, 14.23, 14.37,...
## $ `1219` <dbl> 15.13, 15.09, 15.13, 15.09, 14.94, 15.13, 15.18, 15.18,...
## $ `1220` <dbl> 9.83, 9.60, 9.69, 9.78, 9.83, 9.78, 9.83, 9.83, 9.74, 9...
## $ `1225` <dbl> 46.42, 46.32, 46.47, 46.32, 46.37, 46.32, 45.94, 46.32,...
## $ `1227` <dbl> 69.38, 69.47, 69.65, 69.83, 69.01, 68.56, 69.56, 69.56,...
## $ `1229` <dbl> 17.28, 17.28, 17.36, 17.32, 17.32, 17.56, 17.67, 17.71,...
## $ `1231` <dbl> 26.72, 27.01, 27.10, 26.97, 27.18, 27.01, 27.18, 27.18,...
## $ `1232` <dbl> 75.77, 75.95, 76.13, 76.31, 76.31, 76.04, 76.04, 76.04,...
## $ `1233` <dbl> 33.08, 33.17, 33.21, 33.17, 33.35, 33.44, 33.39, 33.35,...
## $ `1234` <dbl> 28.77, 28.82, 28.77, 28.77, 28.91, 28.77, 28.82, 28.82,...
## $ `1235` <dbl> 20.31, 20.31, 20.34, 20.69, 20.76, 20.62, 20.58, 20.65,...
## $ `1236` <dbl> 17.87, 17.87, 17.97, 17.97, 18.02, 17.97, 17.97, 17.97,...
## $ `1256` <dbl> 112.48, 114.32, 114.32, 114.78, 114.78, 114.78, 114.78,...
## $ `1262` <dbl> 131.07, 130.62, 132.87, 131.97, 129.27, 135.12, 136.92,...
## $ `1301` <dbl> 81.28, 81.47, 81.56, 81.65, 81.38, 80.74, 80.56, 81.92,...
## $ `1303` <dbl> 63.17, 63.62, 65.12, 65.12, 65.48, 64.86, 64.24, 65.12,...
## $ `1304` <dbl> 14.66, 14.70, 14.57, 14.52, 14.25, 14.43, 14.43, 14.48,...
## $ `1305` <dbl> 20.28, 20.83, 20.58, 20.62, 19.69, 19.69, 19.90, 20.20,...
## $ `1307` <dbl> 31.29, 31.42, 31.51, 31.42, 31.37, 31.42, 31.42, 31.55,...
## $ `1308` <dbl> 16.63, 16.55, 16.46, 16.63, 16.37, 16.94, 16.94, 17.07,...
## $ `1309` <dbl> 10.45, 11.10, 10.85, 10.95, 10.65, 10.55, 10.70, 10.80,...
## $ `1310` <dbl> 16.71, 16.83, 16.92, 16.75, 16.58, 16.75, 16.79, 16.83,...
## $ `1312` <dbl> 19.18, 19.13, 19.04, 19.41, 19.08, 19.13, 19.18, 19.41,...
## $ `1313` <dbl> 10.43, 10.51, 10.51, 10.60, 10.27, 10.51, 10.56, 10.56,...
## $ `1314` <dbl> 10.05, 10.00, 10.05, 10.05, 10.05, 10.10, 10.15, 10.25,...
## $ `1315` <dbl> 23.08, 23.17, 23.17, 23.12, 23.03, 23.08, 23.17, 23.12,...
## $ `1316` <dbl> 13.55, 13.43, 13.43, 13.49, 13.99, 14.05, 14.11, 14.11,...
## $ `1319` <dbl> 57.95, 57.58, 57.67, 58.41, 57.21, 55.28, 52.34, 53.26,...
## $ `1321` <dbl> 24.60, 24.65, 24.75, 24.80, 24.80, 24.75, 24.65, 24.65,...
## $ `1323` <dbl> 30.53, 31.12, 31.12, 30.76, 30.76, 30.76, 30.39, 30.35,...
## $ `1324` <dbl> 12.41, 12.55, 12.45, 12.45, 12.50, 12.50, 12.55, 12.26,...
## $ `1325` <dbl> 19.84, 19.89, 19.89, 19.89, 19.89, 19.84, 19.84, 19.79,...
## $ `1326` <dbl> 86.58, 86.49, 87.20, 86.94, 86.49, 85.07, 85.16, 87.20,...
## $ `1337` <dbl> 17.31, 17.65, 17.65, 17.75, 17.41, 17.85, 17.75, 17.75,...
## $ `1338` <dbl> 85.75, 85.29, 85.93, 86.39, 85.29, 84.92, 84.10, 84.56,...
## $ `1339` <dbl> 35.91, 35.86, 37.10, 37.14, 37.46, 36.73, 36.14, 36.18,...
## $ `1340` <dbl> 44.08, 45.04, 45.12, 45.04, 44.40, 44.16, 44.80, 45.12,...
## $ `1341` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `1402` <dbl> 22.69, 22.64, 23.01, 23.11, 22.83, 23.01, 23.11, 23.39,...
## $ `1409` <dbl> 8.51, 8.54, 8.55, 8.55, 8.53, 8.50, 8.65, 8.80, 8.79, 8...
## $ `1410` <dbl> 21.56, 21.56, 21.65, 21.65, 21.61, 21.61, 21.56, 21.65,...
## $ `1413` <dbl> 5.55, 5.58, 5.60, 5.65, 5.65, 5.64, 5.50, 5.57, 5.57, 5...
## $ `1414` <dbl> 5.65, 5.65, 5.70, 5.70, 5.66, 5.67, 5.67, 5.68, 5.68, 5...
## $ `1416` <dbl> 22.50, 22.33, 22.37, 22.46, 22.50, 22.55, 23.51, 23.47,...
## $ `1417` <dbl> 5.16, 5.16, 5.15, 5.15, 5.16, 5.16, 5.17, 5.16, 5.17, 5...
## $ `1418` <dbl> 17.68, 17.60, 16.89, 16.89, 16.89, 15.79, 14.95, 16.44,...
## $ `1419` <dbl> 36.48, 36.43, 36.39, 36.75, 36.52, 36.52, 36.48, 36.43,...
## $ `1423` <dbl> 6.78, 6.76, 6.74, 6.73, 6.69, 6.69, 6.77, 6.83, 6.80, 6...
## $ `1432` <dbl> 16.35, 16.40, 16.50, 16.40, 16.30, 16.20, 16.00, 16.10,...
## $ `1434` <dbl> 26.65, 26.97, 26.97, 27.24, 27.06, 27.06, 27.15, 27.33,...
## $ `1435` <dbl> 4.20, 4.17, 4.17, 4.18, 4.18, 4.17, 4.19, 4.19, 4.19, 4...
## $ `1436` <dbl> 34.07, 34.15, 34.20, 34.20, 34.15, 34.11, 34.24, 34.28,...
## $ `1437` <dbl> 14.98, 15.07, 15.07, 15.30, 15.30, 15.39, 15.43, 15.39,...
## $ `1438` <dbl> 4.22, 4.35, 4.01, 4.40, 4.40, 4.52, 4.40, 4.20, 4.02, 4...
## $ `1439` <dbl> 15.45, 15.45, 15.55, 15.40, 15.11, 15.11, 14.96, 15.21,...
## $ `1440` <dbl> 11.64, 11.54, 11.69, 12.07, 12.11, 11.92, 12.02, 12.11,...
## $ `1441` <dbl> 9.06, 9.06, 9.19, 9.12, 9.03, 9.08, 9.09, 9.09, 9.09, 9...
## $ `1442` <dbl> 14.01, 14.09, 14.01, 14.09, 14.05, 14.01, 14.01, 13.97,...
## $ `1443` <dbl> 4.47, 4.39, 4.41, 4.58, 4.58, 4.65, 4.70, 4.73, 4.78, 4...
## $ `1444` <dbl> 7.84, 7.85, 7.86, 7.87, 7.81, 7.84, 7.90, 7.93, 7.91, 7...
## $ `1445` <dbl> 8.50, 8.41, 8.44, 8.46, 8.42, 8.39, 8.42, 8.42, 8.43, 8...
## $ `1446` <dbl> 17.60, 17.31, 17.36, 17.85, 17.50, 17.46, 17.16, 17.07,...
## $ `1447` <dbl> 8.10, 8.06, 8.12, 8.20, 8.23, 8.19, 8.31, 8.42, 8.35, 8...
## $ `1449` <dbl> 4.10, 4.17, 4.07, 4.10, 4.05, 4.06, 4.09, 4.13, 4.14, 4...
## $ `1451` <dbl> 34.01, 34.08, 34.22, 34.15, 34.08, 34.08, 34.22, 34.43,...
## $ `1452` <dbl> 18.02, 18.51, 18.46, 18.51, 18.33, 18.59, 18.37, 18.33,...
## $ `1453` <dbl> 7.97, 8.08, 7.93, 7.95, 7.97, 7.96, 7.99, 7.92, 7.82, 7...
## $ `1454` <dbl> 7.96, 8.00, 7.98, 7.97, 7.88, 7.88, 7.89, 7.98, 7.95, 7...
## $ `1455` <dbl> 8.69, 8.69, 8.75, 8.94, 9.00, 8.88, 8.90, 8.94, 8.93, 8...
## $ `1456` <dbl> 8.50, 8.47, 8.69, 8.80, 8.80, 8.80, 9.68, 10.60, 11.65,...
## $ `1457` <dbl> 9.34, 9.39, 9.48, 9.53, 9.48, 9.53, 9.48, 9.48, 9.43, 9...
## $ `1459` <dbl> 8.40, 8.42, 8.49, 8.44, 8.46, 8.31, 8.36, 8.35, 8.31, 8...
## $ `1460` <dbl> 15.66, 15.71, 15.75, 15.66, 15.43, 15.48, 15.52, 15.43,...
## $ `1463` <dbl> 16.39, 16.46, 16.39, 16.58, 16.27, 16.39, 16.31, 16.35,...
## $ `1464` <dbl> 20.66, 20.82, 20.82, 20.70, 20.42, 20.54, 20.66, 20.62,...
## $ `1465` <dbl> 11.70, 11.60, 11.65, 11.60, 11.65, 11.70, 11.74, 11.65,...
## $ `1466` <dbl> 13.50, 13.45, 13.60, 13.55, 13.40, 13.35, 13.35, 13.50,...
## $ `1467` <dbl> 10.30, 10.30, 10.40, 10.50, 10.65, 10.60, 10.40, 10.45,...
## $ `1468` <dbl> 9.98, 9.89, 9.89, 9.85, 9.88, 9.82, 9.85, 9.80, 9.69, 9...
## $ `1470` <dbl> 18.02, 18.02, 18.44, 18.44, 18.44, 18.49, 18.49, 18.53,...
## $ `1471` <dbl> 6.20, 6.23, 6.34, 6.39, 6.53, 6.57, 6.46, 6.45, 6.44, 6...
## $ `1472` <dbl> 20.55, 20.55, 20.81, 20.55, 20.37, 20.28, 20.20, 20.28,...
## $ `1473` <dbl> 27.66, 27.75, 27.80, 27.80, 27.66, 27.52, 27.43, 27.47,...
## $ `1474` <dbl> 10.32, 10.27, 10.18, 10.18, 10.23, 10.32, 10.32, 10.36,...
## $ `1475` <dbl> 25.41, 25.71, 25.71, 25.97, 25.51, 25.31, 25.31, 25.28,...
## $ `1476` <dbl> 312.98, 303.71, 299.54, 296.76, 287.48, 306.03, 303.25,...
## $ `1477` <dbl> 116.53, 116.07, 114.25, 111.52, 109.70, 111.52, 111.52,...
## $ `1503` <dbl> 38.03, 38.03, 38.08, 38.08, 37.61, 37.61, 37.98, 37.65,...
## $ `1504` <dbl> 25.88, 25.93, 26.11, 26.02, 26.02, 25.97, 26.07, 26.16,...
## $ `1506` <dbl> 14.55, 14.50, 14.45, 14.65, 14.70, 14.65, 14.75, 14.75,...
## $ `1507` <dbl> 40.80, 40.71, 40.71, 40.98, 40.80, 40.75, 40.84, 41.16,...
## $ `1512` <dbl> 6.00, 6.02, 5.88, 5.90, 5.98, 5.91, 5.90, 5.89, 5.94, 6...
## $ `1513` <dbl> 17.61, 17.61, 18.34, 18.66, 18.57, 18.66, 19.07, 19.02,...
## $ `1514` <dbl> 8.99, 8.98, 8.97, 8.90, 8.77, 8.81, 8.81, 9.14, 9.03, 8...
## $ `1515` <dbl> 14.20, 14.29, 14.29, 14.58, 14.68, 14.39, 14.20, 14.10,...
## $ `1516` <dbl> 15.10, 15.01, 16.49, 18.10, 17.97, 17.12, 16.85, 17.88,...
## $ `1517` <dbl> 10.03, 10.03, 10.03, 9.98, 9.98, 9.98, 10.03, 10.03, 9....
## $ `1519` <dbl> 16.67, 16.77, 16.81, 16.95, 16.86, 16.77, 16.77, 16.77,...
## $ `1521` <dbl> 71.81, 71.55, 71.64, 71.73, 72.69, 72.61, 71.29, 71.73,...
## $ `1522` <dbl> 31.85, 31.90, 31.94, 32.07, 31.67, 31.45, 31.85, 31.81,...
## $ `1524` <dbl> 10.23, 10.18, 10.28, 10.37, 10.37, 10.46, 10.37, 10.32,...
## $ `1525` <dbl> 106.57, 107.04, 108.46, 108.46, 109.41, 107.52, 105.62,...
## $ `1526` <dbl> 13.14, 13.23, 13.23, 13.23, 13.32, 13.32, 13.36, 13.36,...
## $ `1527` <dbl> 86.69, 84.82, 83.88, 85.85, 86.31, 85.85, 88.93, 86.03,...
## $ `1528` <dbl> 9.06, 9.09, 9.09, 9.37, 9.28, 9.23, 9.23, 9.28, 9.14, 9...
## $ `1529` <dbl> 32.72, 32.72, 29.08, 29.08, 29.08, 30.63, 33.36, 31.36,...
## $ `1530` <dbl> 26.94, 27.13, 27.22, 27.13, 26.94, 27.22, 27.41, 27.32,...
## $ `1531` <dbl> 14.77, 14.81, 14.81, 14.95, 15.00, 15.00, 15.14, 15.14,...
## $ `1532` <dbl> 28.48, 28.39, 28.43, 28.34, 27.89, 28.12, 28.07, 28.03,...
## $ `1533` <dbl> 42.21, 42.41, 43.39, 43.25, 42.51, 42.51, 42.21, 42.41,...
## $ `1535` <dbl> 43.82, 43.77, 45.58, 45.58, 45.03, 44.98, 44.65, 44.70,...
## $ `1536` <dbl> 118.75, 118.75, 121.55, 123.89, 121.55, 118.28, 114.54,...
## $ `1537` <dbl> 139.13, 140.02, 141.79, 143.56, 143.56, 142.68, 140.46,...
## $ `1538` <dbl> 8.62, 8.61, 8.64, 8.55, 8.56, 8.44, 8.50, 8.56, 8.52, 8...
## $ `1539` <dbl> 25.49, 25.49, 25.45, 25.31, 25.13, 25.22, 25.99, 25.58,...
## $ `1540` <dbl> 11.42, 11.56, 11.83, 11.83, 12.46, 12.37, 12.32, 12.28,...
## $ `1541` <dbl> 47.19, 50.24, 50.51, 51.05, 50.87, 51.95, 54.83, 54.56,...
## $ `1558` <dbl> 138.76, 139.64, 140.94, 142.25, 140.94, 141.82, 142.69,...
## $ `1560` <dbl> 58.18, 57.72, 59.46, 59.73, 58.18, 58.55, 57.82, 58.36,...
## $ `1568` <dbl> 30.97, 30.92, 32.48, 32.48, 32.20, 31.63, 31.35, 31.21,...
## $ `1582` <dbl> 68.03, 67.81, 69.32, 69.00, 69.00, 68.78, 65.98, 66.09,...
## $ `1583` <dbl> 52.33, 52.14, 52.43, 52.99, 53.47, 53.28, 54.79, 53.66,...
## $ `1587` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `1589` <dbl> 97.33, 98.73, 98.26, 99.67, 98.26, 98.26, 97.80, 96.39,...
## $ `1590` <dbl> 237.72, 232.51, 231.56, 238.66, 237.24, 237.72, 234.88,...
## $ `1592` <dbl> 49.05, 49.51, 50.61, 53.83, 52.36, 50.61, 46.56, 47.67,...
## $ `1598` <dbl> 37.34, 38.67, 38.17, 38.67, 38.30, 37.89, 36.79, 37.30,...
## $ `1603` <dbl> 21.65, 20.90, 20.85, 20.62, 19.96, 19.91, 19.91, 19.91,...
## $ `1604` <dbl> 17.79, 17.84, 17.69, 17.60, 17.45, 17.50, 17.45, 17.84,...
## $ `1605` <dbl> 10.57, 10.70, 10.84, 10.75, 10.75, 10.75, 11.07, 10.93,...
## $ `1608` <dbl> 7.73, 7.79, 7.89, 7.86, 7.80, 7.78, 7.80, 7.79, 7.79, 7...
## $ `1609` <dbl> 5.33, 5.39, 5.43, 5.45, 5.38, 5.36, 5.37, 5.41, 5.45, 5...
## $ `1611` <dbl> 6.82, 7.22, 7.14, 7.13, 7.11, 6.99, 7.02, 7.08, 7.08, 6...
## $ `1612` <dbl> 8.17, 8.17, 8.34, 8.33, 8.30, 8.29, 8.29, 8.30, 8.32, 8...
## $ `1614` <dbl> 22.51, 22.37, 22.51, 22.47, 22.51, 22.56, 22.56, 22.51,...
## $ `1615` <dbl> 9.12, 9.08, 9.12, 9.79, 9.70, 9.52, 9.57, 9.70, 9.57, 9...
## $ `1616` <dbl> 5.09, 5.06, 5.08, 5.10, 5.14, 5.12, 5.15, 5.27, 5.25, 5...
## $ `1617` <dbl> 6.99, 6.99, 7.03, 7.02, 7.02, 7.05, 7.14, 7.23, 7.49, 7...
## $ `1618` <dbl> 7.79, 7.75, 7.79, 7.83, 7.76, 7.93, 7.94, 7.96, 7.90, 7...
## $ `1626` <dbl> 24.96, 25.01, 24.92, 24.96, 25.30, 25.11, 24.96, 24.77,...
## $ `1701` <dbl> 17.09, 17.09, 17.09, 17.04, 17.04, 16.99, 16.99, 16.95,...
## $ `1702` <dbl> 55.96, 55.87, 57.15, 57.42, 56.96, 57.42, 57.60, 58.15,...
## $ `1707` <dbl> 158.27, 163.91, 172.36, 170.01, 161.56, 165.32, 159.68,...
## $ `1708` <dbl> 24.47, 24.60, 24.74, 25.19, 25.14, 24.69, 24.65, 24.65,...
## $ `1709` <dbl> 13.94, 13.94, 13.98, 13.94, 13.98, 13.98, 14.06, 14.06,...
## $ `1710` <dbl> 22.72, 22.67, 23.43, 23.24, 23.28, 23.00, 23.52, 23.47,...
## $ `1711` <dbl> 19.17, 19.17, 19.12, 19.22, 18.98, 19.03, 19.12, 19.17,...
## $ `1712` <dbl> 13.64, 13.68, 13.68, 13.68, 13.59, 13.59, 13.59, 13.64,...
## $ `1713` <dbl> 13.97, 13.97, 13.97, 14.16, 14.16, 14.16, 14.16, 14.25,...
## $ `1714` <dbl> 7.81, 7.81, 7.78, 7.78, 7.83, 7.81, 7.84, 8.04, 8.04, 7...
## $ `1717` <dbl> 27.75, 27.79, 28.00, 28.00, 28.08, 27.92, 27.79, 27.83,...
## $ `1718` <dbl> 8.05, 8.20, 8.28, 8.28, 8.20, 8.18, 8.15, 8.22, 8.22, 8...
## $ `1720` <dbl> 29.94, 29.99, 29.89, 29.85, 29.58, 29.58, 29.85, 29.67,...
## $ `1721` <dbl> 13.99, 14.08, 14.31, 14.13, 14.08, 14.04, 13.90, 13.94,...
## $ `1722` <dbl> 36.35, 36.67, 36.71, 36.80, 36.58, 36.53, 36.71, 36.85,...
## $ `1723` <dbl> 112.81, 113.74, 112.81, 111.41, 110.95, 111.88, 112.35,...
## $ `1724` <dbl> 15.00, 15.05, 15.00, 15.05, 14.69, 14.78, 14.78, 14.73,...
## $ `1725` <dbl> 12.57, 12.53, 12.62, 12.71, 12.62, 12.53, 12.43, 12.57,...
## $ `1726` <dbl> 72.87, 73.05, 72.87, 72.87, 72.78, 72.87, 73.23, 73.05,...
## $ `1727` <dbl> 11.94, 11.94, 11.85, 12.03, 12.08, 12.26, 12.26, 12.22,...
## $ `1730` <dbl> 34.56, 34.61, 34.79, 34.70, 34.75, 34.61, 34.61, 34.61,...
## $ `1731` <dbl> 12.59, 12.63, 12.63, 12.63, 12.72, 12.68, 12.77, 12.91,...
## $ `1732` <dbl> 13.55, 13.70, 13.65, 13.55, 13.55, 13.55, 13.50, 13.45,...
## $ `1733` <dbl> 37.55, 37.46, 37.33, 37.33, 37.51, 36.65, 36.42, 36.33,...
## $ `1734` <dbl> 23.77, 23.87, 24.11, 24.11, 23.97, 23.82, 23.82, 23.87,...
## $ `1735` <dbl> 11.58, 11.53, 11.63, 11.67, 11.63, 11.58, 11.53, 11.53,...
## $ `1736` <dbl> 44.26, 44.60, 44.89, 44.79, 44.65, 44.60, 44.60, 44.41,...
## $ `1737` <dbl> 26.64, 26.78, 26.73, 26.82, 26.73, 26.59, 26.59, 26.73,...
## $ `1760` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `1762` <dbl> 26.05, 26.15, 26.25, 26.29, 25.81, 26.63, 26.39, 26.25,...
## $ `1773` <dbl> 48.73, 48.91, 48.73, 48.91, 48.64, 49.18, 48.73, 49.09,...
## $ `1776` <dbl> 18.55, 18.63, 18.72, 18.76, 18.85, 18.76, 18.42, 18.33,...
## $ `1783` <dbl> 23.58, 23.48, 23.78, 23.63, 23.63, 24.13, 24.47, 24.47,...
## $ `1786` <dbl> 54.20, 54.39, 53.81, 54.39, 53.71, 53.62, 52.26, 52.55,...
## $ `1789` <dbl> 36.36, 36.41, 36.97, 37.11, 36.88, 37.02, 36.93, 36.60,...
## $ `1802` <dbl> 12.86, 12.82, 12.91, 12.77, 12.67, 12.43, 12.43, 12.52,...
## $ `1805` <dbl> 5.65, 5.53, 5.66, 5.63, 5.60, 5.60, 5.57, 5.64, 5.55, 5...
## $ `1806` <dbl> 7.04, 7.04, 7.03, 7.04, 7.02, 7.01, 7.01, 7.18, 7.23, 7...
## $ `1808` <dbl> 27.00, 27.00, 27.20, 27.29, 27.62, 27.54, 27.67, 28.13,...
## $ `1809` <dbl> 11.79, 11.83, 11.83, 11.83, 11.79, 11.74, 11.74, 11.74,...
## $ `1810` <dbl> 8.98, 8.93, 9.07, 9.14, 9.07, 9.04, 9.05, 9.00, 8.96, 8...
## $ `1817` <dbl> 32.93, 32.80, 32.80, 32.80, 32.71, 32.84, 32.62, 32.62,...
## $ `1902` <dbl> 11.10, 11.15, 11.69, 11.59, 11.44, 11.35, 11.10, 11.15,...
## $ `1903` <dbl> 32.50, 32.70, 33.00, 32.70, 32.60, 32.60, 32.60, 32.00,...
## $ `1904` <dbl> 12.28, 12.41, 13.62, 14.13, 13.57, 13.76, 13.48, 13.25,...
## $ `1905` <dbl> 8.46, 8.43, 9.03, 9.15, 8.95, 9.00, 8.98, 8.96, 8.95, 9...
## $ `1906` <dbl> 15.46, 15.41, 15.91, 17.48, 18.42, 18.69, 18.33, 18.11,...
## $ `1907` <dbl> 9.22, 9.29, 10.21, 10.68, 10.40, 10.21, 10.30, 10.11, 1...
## $ `1909` <dbl> 15.28, 15.55, 16.44, 18.04, 18.08, 19.33, 18.53, 18.35,...
## $ `2002` <dbl> 22.79, 23.03, 23.17, 23.03, 22.89, 22.89, 23.35, 23.40,...
## $ `2006` <dbl> 18.89, 19.07, 19.07, 18.80, 18.71, 18.53, 18.71, 18.89,...
## $ `2007` <dbl> 5.35, 5.41, 5.49, 5.51, 5.49, 5.40, 5.41, 5.42, 5.38, 5...
## $ `2008` <dbl> 10.55, 10.60, 10.65, 10.70, 10.85, 10.95, 10.95, 10.75,...
## $ `2009` <dbl> 7.34, 7.34, 7.59, 7.58, 7.45, 7.36, 7.53, 7.50, 7.45, 7...
## $ `2010` <dbl> 10.48, 10.53, 10.53, 10.53, 10.62, 10.53, 10.62, 10.71,...
## $ `2012` <dbl> 12.15, 12.10, 12.19, 12.15, 12.10, 12.15, 12.10, 12.10,...
## $ `2013` <dbl> 20.91, 20.91, 20.81, 20.91, 21.00, 21.10, 21.10, 21.15,...
## $ `2014` <dbl> 9.45, 9.85, 10.00, 9.99, 9.90, 10.10, 10.40, 10.30, 10....
## $ `2015` <dbl> 39.84, 39.75, 39.79, 40.10, 40.10, 40.28, 40.64, 40.77,...
## $ `2017` <dbl> 7.55, 7.50, 7.52, 7.69, 7.76, 7.76, 7.68, 7.54, 7.55, 7...
## $ `2020` <dbl> 11.66, 11.79, 11.79, 11.83, 11.83, 11.88, 11.71, 11.66,...
## $ `2022` <dbl> 6.74, 6.81, 6.75, 6.75, 6.70, 6.71, 6.80, 6.75, 6.75, 6...
## $ `2023` <dbl> 9.73, 9.81, 9.86, 9.81, 9.86, 9.90, 10.12, 10.16, 10.34...
## $ `2024` <dbl> 7.27, 7.35, 7.36, 7.38, 7.32, 7.27, 7.24, 7.51, 7.40, 7...
## $ `2025` <dbl> 2.81, 2.88, 2.94, 2.90, 2.90, 2.82, 2.89, 2.94, 2.88, 2...
## $ `2027` <dbl> 15.59, 15.68, 15.72, 15.77, 15.72, 15.68, 15.99, 15.90,...
## $ `2028` <dbl> 4.15, 4.00, 4.00, 3.90, 4.00, 3.98, 4.10, 3.90, 4.00, 4...
## $ `2029` <dbl> 29.85, 31.16, 31.55, 31.12, 30.59, 30.68, 31.12, 31.07,...
## $ `2030` <dbl> 9.56, 9.56, 9.61, 9.56, 9.43, 9.52, 9.56, 9.52, 9.52, 9...
## $ `2031` <dbl> 19.12, 19.43, 19.52, 19.70, 19.47, 19.43, 19.56, 19.39,...
## $ `2032` <dbl> 9.88, 9.88, 10.02, 9.98, 9.93, 9.93, 9.93, 9.88, 9.88, ...
## $ `2033` <dbl> 8.61, 8.66, 8.72, 8.65, 8.70, 8.69, 8.61, 8.61, 8.65, 8...
## $ `2034` <dbl> 23.53, 23.44, 23.83, 23.57, 23.31, 23.53, 23.53, 23.57,...
## $ `2038` <dbl> 6.58, 6.53, 6.51, 6.46, 6.46, 6.37, 6.36, 6.38, 6.35, 6...
## $ `2049` <dbl> 137.54, 142.19, 141.26, 142.19, 142.65, 142.19, 142.65,...
## $ `2059` <dbl> 398.66, 399.62, 396.72, 397.21, 391.88, 387.05, 407.37,...
## $ `2062` <dbl> 38.96, 38.96, 39.01, 39.01, 38.62, 39.30, 39.01, 39.15,...
## $ `2069` <dbl> 19.35, 19.39, 19.44, 20.09, 20.79, 21.01, 21.09, 21.05,...
## $ `2101` <dbl> 27.32, 27.46, 27.55, 27.69, 27.64, 27.36, 27.50, 27.46,...
## $ `2102` <dbl> 12.81, 12.91, 13.30, 13.25, 13.45, 13.40, 13.50, 13.45,...
## $ `2103` <dbl> 31.84, 32.17, 32.60, 32.31, 32.69, 32.93, 33.63, 33.96,...
## $ `2104` <dbl> 22.66, 22.70, 22.86, 22.82, 22.70, 22.89, 22.78, 22.66,...
## $ `2105` <dbl> 56.27, 56.54, 56.54, 57.37, 57.92, 57.09, 58.47, 58.47,...
## $ `2106` <dbl> 44.61, 44.47, 44.61, 45.21, 45.12, 44.93, 45.21, 45.02,...
## $ `2107` <dbl> 15.62, 15.57, 15.57, 15.52, 15.38, 15.38, 15.43, 15.52,...
## $ `2108` <dbl> 18.33, 18.42, 18.50, 18.46, 18.75, 18.63, 18.84, 18.75,...
## $ `2109` <dbl> 10.66, 10.56, 10.71, 10.61, 10.71, 10.71, 10.66, 10.95,...
## $ `2114` <dbl> 68.58, 68.76, 68.32, 67.96, 68.94, 68.85, 68.58, 68.58,...
## $ `2115` <dbl> 47.85, 47.94, 48.96, 49.47, 48.79, 48.79, 48.79, 48.79,...
## $ `2201` <dbl> 25.58, 25.58, 25.68, 25.77, 25.68, 25.68, 25.82, 25.63,...
## $ `2204` <dbl> 23.20, 23.64, 23.69, 23.69, 23.69, 23.91, 24.79, 24.88,...
## $ `2206` <dbl> 18.67, 18.67, 18.71, 18.67, 18.62, 18.62, 18.80, 18.62,...
## $ `2207` <dbl> 337.50, 338.89, 337.97, 338.43, 337.04, 338.89, 337.97,...
## $ `2208` <dbl> 32.16, 32.04, 31.81, 31.69, 31.46, 31.93, 31.93, 31.93,...
## $ `2227` <dbl> 168.16, 168.59, 169.01, 169.01, 167.74, 167.31, 166.04,...
## $ `2228` <dbl> 153.22, 158.23, 160.06, 159.60, 159.60, 157.32, 159.60,...
## $ `2231` <dbl> 198.71, 197.93, 197.93, 198.71, 195.62, 195.23, 191.37,...
## $ `2236` <dbl> 51.25, 50.54, 51.51, 51.25, 51.25, 52.04, 51.69, 51.69,...
## $ `2239` <dbl> 177.08, 176.14, 174.26, 174.26, 182.26, 179.44, 178.50,...
## $ `2243` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `2301` <dbl> 41.84, 43.14, 42.62, 42.66, 42.79, 42.40, 43.36, 42.58,...
## $ `2302` <dbl> 6.55, 6.50, 6.47, 6.54, 6.44, 6.40, 6.48, 6.46, 6.48, 6...
## $ `2303` <dbl> 10.56, 10.51, 10.56, 10.74, 10.74, 10.79, 10.79, 10.93,...
## $ `2305` <dbl> 8.05, 8.15, 8.35, 8.43, 8.27, 8.17, 8.22, 8.25, 8.25, 8...
## $ `2308` <dbl> 146.72, 145.79, 147.18, 149.50, 149.50, 148.57, 151.35,...
## $ `2312` <dbl> 11.26, 11.26, 11.45, 11.50, 11.50, 11.40, 11.54, 11.54,...
## $ `2313` <dbl> 14.64, 14.69, 14.78, 15.01, 15.06, 14.83, 15.11, 15.01,...
## $ `2314` <dbl> 24.61, 24.61, 24.22, 24.71, 25.01, 25.11, 25.21, 24.86,...
## $ `2316` <dbl> 19.58, 19.36, 19.42, 19.36, 19.20, 19.31, 19.25, 19.20,...
## $ `2317` <dbl> 96.08, 95.97, 95.74, 95.51, 95.17, 95.74, 95.97, 96.08,...
## $ `2321` <dbl> 5.34, 5.46, 5.50, 5.42, 5.54, 5.46, 5.50, 5.42, 5.40, 5...
## $ `2323` <dbl> 3.51, 3.51, 3.55, 3.56, 3.51, 3.51, 3.46, 3.48, 3.46, 3...
## $ `2324` <dbl> 16.50, 16.50, 16.64, 16.59, 16.50, 16.55, 16.50, 16.37,...
## $ `2327` <dbl> 66.13, 66.35, 67.24, 68.25, 68.81, 69.37, 71.50, 74.07,...
## $ `2328` <dbl> 23.56, 23.98, 23.60, 23.37, 23.42, 23.84, 23.70, 23.98,...
## $ `2329` <dbl> 16.34, 16.34, 16.48, 16.34, 16.19, 16.04, 15.97, 16.04,...
## $ `2330` <dbl> 170.87, 170.87, 171.34, 171.80, 171.80, 171.80, 169.94,...
## $ `2331` <dbl> 14.92, 14.92, 15.01, 16.19, 15.91, 16.05, 16.10, 16.38,...
## $ `2332` <dbl> 10.56, 10.51, 10.71, 10.76, 10.32, 10.37, 10.32, 10.42,...
## $ `2337` <dbl> 8.89, 8.85, 9.18, 9.74, 9.89, 10.51, 10.82, 10.98, 12.0...
## $ `2338` <dbl> 8.65, 8.71, 8.73, 8.80, 8.81, 8.93, 8.84, 8.85, 8.85, 8...
## $ `2340` <dbl> 14.07, 14.07, 14.32, 14.27, 14.17, 14.02, 13.61, 13.66,...
## $ `2342` <dbl> 13.70, 13.65, 13.46, 13.84, 13.55, 13.60, 13.41, 13.51,...
## $ `2344` <dbl> 9.05, 9.09, 9.18, 9.09, 9.00, 8.96, 9.05, 9.00, 9.00, 9...
## $ `2345` <dbl> 47.48, 49.13, 49.59, 50.42, 49.13, 50.97, 52.44, 51.89,...
## $ `2347` <dbl> 29.80, 29.57, 29.66, 29.85, 29.75, 29.71, 29.71, 30.21,...
## $ `2348` <dbl> 17.02, 17.02, 17.02, 17.02, 17.66, 17.66, 16.56, 17.71,...
## $ `2349` <dbl> 6.99, 6.99, 7.09, 7.04, 6.99, 6.92, 6.85, 6.95, 6.89, 6...
## $ `2351` <dbl> 38.54, 38.45, 38.68, 38.45, 39.61, 39.80, 39.89, 41.76,...
## $ `2352` <dbl> 13.71, 13.80, 13.94, 14.07, 14.07, 14.12, 14.34, 14.25,...
## $ `2353` <dbl> 12.31, 12.31, 12.54, 12.64, 12.50, 12.50, 12.59, 12.68,...
## $ `2354` <dbl> 78.40, 78.40, 78.22, 77.94, 78.50, 78.40, 78.50, 77.76,...
## $ `2355` <dbl> 54.56, 55.37, 55.19, 54.92, 55.37, 55.46, 55.19, 55.37,...
## $ `2356` <dbl> 19.40, 19.49, 19.80, 19.76, 20.64, 20.68, 20.73, 20.82,...
## $ `2357` <dbl> 237.04, 237.04, 238.81, 239.70, 238.81, 240.14, 241.92,...
## $ `2358` <dbl> 15.28, 15.28, 15.09, 14.85, 14.89, 14.70, 14.51, 14.36,...
## $ `2359` <dbl> 13.87, 13.83, 13.87, 13.69, 13.51, 13.46, 13.51, 13.46,...
## $ `2360` <dbl> 71.63, 72.01, 73.42, 75.77, 75.49, 77.56, 78.41, 79.16,...
## $ `2362` <dbl> 26.32, 26.41, 27.36, 27.03, 26.98, 26.89, 26.89, 26.89,...
## $ `2363` <dbl> 6.50, 6.49, 6.56, 6.54, 6.88, 6.82, 6.87, 6.77, 6.93, 6...
## $ `2364` <dbl> 2.49, 2.45, 2.45, 2.52, 2.45, 2.54, 2.53, 2.52, 2.47, 2...
## $ `2365` <dbl> 8.80, 8.79, 8.85, 8.86, 8.78, 8.75, 8.62, 8.65, 8.65, 8...
## $ `2367` <dbl> 8.84, 8.88, 8.99, 9.01, 9.11, 9.02, 9.05, 9.17, 9.08, 9...
## $ `2368` <dbl> 10.45, 10.55, 10.50, 10.60, 10.40, 10.30, 10.30, 10.30,...
## $ `2369` <dbl> 10.99, 10.99, 11.03, 11.12, 11.17, 11.08, 10.94, 10.89,...
## $ `2371` <dbl> 9.61, 9.60, 9.60, 9.65, 9.70, 10.65, 11.70, 12.30, 12.3...
## $ `2373` <dbl> 64.45, 64.81, 64.69, 64.81, 64.81, 64.93, 65.05, 65.17,...
## $ `2374` <dbl> 15.33, 15.28, 15.28, 15.28, 15.10, 14.79, 14.92, 14.79,...
## $ `2375` <dbl> 15.70, 15.70, 15.75, 15.89, 15.94, 15.70, 15.65, 15.65,...
## $ `2376` <dbl> 37.52, 37.35, 38.75, 38.23, 37.57, 37.61, 36.95, 36.82,...
## $ `2377` <dbl> 66.87, 67.05, 68.58, 68.31, 66.96, 68.84, 70.64, 70.64,...
## $ `2379` <dbl> 93.99, 92.61, 93.53, 93.07, 93.07, 93.53, 95.38, 96.76,...
## $ `2380` <dbl> 6.70, 6.70, 6.67, 6.64, 6.68, 6.68, 6.62, 6.62, 6.59, 6...
## $ `2382` <dbl> 53.78, 53.78, 53.78, 54.14, 55.21, 55.12, 56.47, 56.92,...
## $ `2383` <dbl> 81.89, 87.77, 90.43, 87.58, 87.22, 88.59, 87.86, 93.18,...
## $ `2385` <dbl> 65.72, 65.54, 65.72, 65.01, 64.75, 64.84, 64.48, 64.22,...
## $ `2387` <dbl> 18.25, 18.31, 18.47, 18.47, 18.20, 18.20, 18.15, 18.09,...
## $ `2388` <dbl> 10.05, 10.25, 10.30, 10.25, 11.25, 11.05, 11.10, 11.05,...
## $ `2390` <dbl> 16.87, 16.77, 16.82, 16.92, 16.67, 16.62, 16.52, 16.52,...
## $ `2392` <dbl> 33.40, 33.49, 33.63, 33.44, 33.40, 33.54, 33.54, 33.81,...
## $ `2393` <dbl> 39.95, 40.21, 41.30, 41.04, 41.34, 41.86, 41.86, 41.82,...
## $ `2395` <dbl> 215.96, 213.82, 216.39, 219.81, 220.24, 219.81, 220.67,...
## $ `2397` <dbl> 45.31, 45.14, 45.14, 45.66, 45.92, 45.48, 45.05, 44.70,...
## $ `2399` <dbl> 7.82, 7.83, 7.95, 7.86, 7.90, 8.13, 8.08, 8.06, 8.04, 7...
## $ `2401` <dbl> 10.44, 10.44, 10.62, 10.53, 10.48, 10.39, 10.35, 10.35,...
## $ `2402` <dbl> 16.05, 15.95, 16.05, 16.60, 16.55, 16.55, 16.85, 16.55,...
## $ `2404` <dbl> 50.10, 49.95, 50.10, 50.40, 50.10, 50.30, 51.10, 51.40,...
## $ `2405` <dbl> 8.16, 8.28, 8.25, 8.33, 8.62, 8.45, 8.52, 8.83, 8.73, 8...
## $ `2406` <dbl> 24.55, 24.80, 24.50, 24.35, 22.95, 23.35, 23.30, 23.60,...
## $ `2408` <dbl> 44.08, 44.46, 45.15, 45.48, 45.39, 44.55, 44.64, 43.99,...
## $ `2409` <dbl> 10.23, 10.18, 10.44, 10.70, 10.95, 10.91, 10.91, 10.99,...
## $ `2412` <dbl> 93.66, 94.58, 95.49, 94.12, 93.21, 93.21, 92.75, 93.21,...
## $ `2413` <dbl> 11.85, 11.80, 11.90, 11.80, 11.70, 11.50, 11.70, 11.70,...
## $ `2414` <dbl> 15.09, 15.05, 14.96, 15.01, 15.09, 15.09, 15.05, 15.05,...
## $ `2415` <dbl> 24.64, 25.49, 25.59, 25.54, 26.70, 26.80, 29.12, 28.62,...
## $ `2417` <dbl> 10.96, 11.10, 10.86, 10.86, 10.71, 10.42, 10.27, 10.22,...
## $ `2419` <dbl> 18.63, 18.82, 18.91, 18.68, 18.86, 19.28, 18.95, 18.82,...
## $ `2420` <dbl> 30.37, 30.42, 30.67, 30.97, 31.48, 31.36, 30.46, 30.46,...
## $ `2421` <dbl> 24.36, 24.90, 24.95, 24.81, 25.35, 24.41, 26.16, 25.89,...
## $ `2423` <dbl> 17.19, 17.19, 17.23, 17.28, 17.10, 17.54, 17.41, 17.46,...
## $ `2424` <dbl> 21.00, 21.00, 21.75, 21.75, 21.60, 21.60, 23.30, 22.15,...
## $ `2425` <dbl> 19.83, 19.83, 19.83, 19.73, 19.68, 19.53, 19.48, 19.73,...
## $ `2426` <dbl> 11.33, 11.37, 11.51, 11.42, 11.28, 11.28, 11.10, 11.05,...
## $ `2427` <dbl> 6.87, 6.83, 6.83, 6.88, 6.98, 7.54, 7.42, 7.33, 7.85, 8...
## $ `2428` <dbl> 59.07, 59.07, 59.90, 61.01, 61.20, 62.86, 62.21, 61.66,...
## $ `2429` <dbl> 22.62, 22.48, 22.34, 22.96, 22.96, 22.96, 22.14, 22.82,...
## $ `2430` <dbl> 24.87, 24.83, 24.70, 24.75, 24.53, 24.58, 24.53, 24.37,...
## $ `2431` <dbl> 13.64, 13.50, 13.40, 13.45, 13.55, 13.40, 13.17, 13.17,...
## $ `2433` <dbl> 34.42, 34.77, 35.03, 35.07, 34.94, 34.86, 34.99, 34.99,...
## $ `2434` <dbl> 8.72, 8.57, 8.57, 8.68, 8.62, 8.63, 8.51, 9.32, 8.93, 8...
## $ `2436` <dbl> 23.89, 24.17, 24.28, 24.17, 23.84, 23.78, 23.78, 23.78,...
## $ `2438` <dbl> 10.00, 9.77, 9.98, 10.20, 9.85, 9.93, 9.90, 9.56, 9.80,...
## $ `2439` <dbl> 105.85, 104.55, 103.69, 102.83, 101.53, 104.12, 104.12,...
## $ `2440` <dbl> 8.87, 8.68, 8.78, 9.65, 9.89, 9.53, 9.64, 9.45, 9.50, 9...
## $ `2441` <dbl> 34.63, 34.46, 34.72, 34.63, 35.17, 35.30, 35.26, 35.35,...
## $ `2442` <dbl> 6.78, 6.87, 6.92, 7.11, 7.09, 7.43, 7.31, 7.79, 7.77, 7...
## $ `2443` <dbl> 6.16, 6.16, 6.18, 6.15, 6.10, 6.02, 6.04, 6.06, 6.06, 6...
## $ `2444` <dbl> 11.11, 11.16, 11.25, 11.35, 11.30, 10.96, 10.91, 10.91,...
## $ `2448` <dbl> 22.56, 22.95, 24.28, 24.28, 23.84, 23.98, 23.49, 23.20,...
## $ `2449` <dbl> 23.23, 23.36, 23.71, 23.89, 23.54, 23.63, 23.76, 23.54,...
## $ `2450` <dbl> 46.16, 45.90, 45.64, 45.64, 45.99, 45.64, 45.81, 46.07,...
## $ `2451` <dbl> 74.82, 75.60, 75.87, 75.25, 75.60, 75.78, 75.69, 75.34,...
## $ `2453` <dbl> 9.72, 9.67, 9.76, 9.85, 9.76, 9.81, 9.85, 9.85, 9.85, 9...
## $ `2454` <dbl> 202.81, 200.95, 202.81, 204.67, 201.88, 199.55, 200.48,...
## $ `2455` <dbl> 45.33, 45.33, 45.75, 46.22, 45.85, 46.13, 46.64, 46.27,...
## $ `2456` <dbl> 88.56, 88.94, 89.06, 88.94, 88.69, 87.81, 88.69, 88.94,...
## $ `2457` <dbl> 12.81, 12.61, 12.56, 12.56, 11.49, 11.49, 11.44, 11.39,...
## $ `2458` <dbl> 42.58, 42.15, 41.85, 42.64, 42.88, 42.27, 42.09, 42.21,...
## $ `2459` <dbl> 31.01, 30.92, 31.05, 30.92, 30.84, 30.79, 30.71, 30.79,...
## $ `2460` <dbl> 10.25, 10.15, 10.30, 10.35, 10.30, 10.85, 10.90, 10.70,...
## $ `2461` <dbl> 17.72, 17.58, 17.49, 17.63, 15.94, 16.12, 16.30, 15.80,...
## $ `2462` <dbl> 20.35, 20.30, 20.25, 20.35, 20.30, 20.30, 20.35, 20.35,...
## $ `2464` <dbl> 34.91, 35.41, 35.63, 35.77, 35.68, 35.41, 35.05, 35.18,...
## $ `2465` <dbl> 16.00, 15.66, 15.94, 15.76, 15.84, 15.88, 15.64, 15.70,...
## $ `2466` <dbl> 35.15, 35.25, 35.40, 35.40, 35.40, 35.35, 35.40, 35.45,...
## $ `2467` <dbl> 19.39, 20.31, 19.85, 19.66, 19.20, 19.20, 19.02, 18.65,...
## $ `2468` <dbl> 9.74, 9.74, 9.74, 9.88, 9.84, 9.84, 9.79, 9.84, 9.79, 9...
## $ `2471` <dbl> 12.60, 12.60, 12.51, 12.64, 12.73, 12.99, 12.99, 13.12,...
## $ `2472` <dbl> 35.36, 35.95, 35.99, 36.27, 36.18, 35.95, 35.81, 35.45,...
## $ `2474` <dbl> 211.49, 210.08, 207.74, 209.14, 210.08, 209.14, 204.92,...
## $ `2475` <dbl> 1.29, 1.32, 1.34, 1.32, 1.33, 1.31, 1.33, 1.44, 1.42, 1...
## $ `2476` <dbl> 22.69, 22.69, 22.61, 22.87, 22.96, 22.96, 22.87, 22.74,...
## $ `2477` <dbl> 18.47, 18.41, 18.25, 18.31, 18.25, 18.41, 18.95, 18.79,...
## $ `2478` <dbl> 18.51, 18.56, 18.61, 18.61, 18.61, 18.66, 19.14, 19.53,...
## $ `2480` <dbl> 28.29, 28.75, 28.70, 28.70, 28.65, 28.65, 28.70, 28.70,...
## $ `2481` <dbl> 15.75, 15.84, 15.84, 15.84, 15.84, 15.70, 15.61, 15.70,...
## $ `2482` <dbl> 12.69, 12.69, 12.69, 12.74, 12.78, 12.88, 12.78, 12.83,...
## $ `2483` <dbl> 15.06, 15.06, 15.10, 15.24, 15.15, 15.06, 15.15, 15.06,...
## $ `2484` <dbl> 16.48, 16.66, 16.66, 17.60, 17.11, 17.51, 18.23, 17.87,...
## $ `2485` <dbl> 31.49, 31.54, 31.30, 31.30, 31.82, 31.58, 31.30, 31.11,...
## $ `2486` <dbl> 8.98, 8.97, 9.40, 9.45, 9.13, 9.19, 9.15, 9.20, 9.09, 9...
## $ `2488` <dbl> 37.40, 37.49, 37.53, 37.70, 35.90, 36.11, 36.24, 35.90,...
## $ `2489` <dbl> 20.41, 20.32, 20.45, 20.68, 20.86, 20.50, 20.59, 20.41,...
## $ `2491` <dbl> 7.56, 7.86, 7.51, 7.69, 7.99, 8.08, 7.80, 7.72, 7.80, 7...
## $ `2492` <dbl> 35.46, 35.21, 35.21, 35.56, 35.21, 35.15, 35.10, 35.15,...
## $ `2493` <dbl> 23.23, 23.27, 23.19, 23.23, 23.32, 23.32, 23.23, 23.15,...
## $ `2495` <dbl> 14.93, 14.89, 14.80, 14.89, 14.75, 14.89, 14.75, 14.75,...
## $ `2496` <dbl> 87.92, 86.21, 86.21, 86.21, 86.21, 86.21, 85.35, 85.35,...
## $ `2497` <dbl> 32.08, 32.42, 32.91, 32.86, 32.81, 32.62, 32.27, 32.03,...
## $ `2498` <dbl> 79.2, 81.8, 81.3, 81.2, 79.2, 78.6, 79.4, 79.5, 79.1, 7...
## $ `2499` <dbl> 13.00, 13.10, 13.55, 13.35, 13.15, 13.00, 12.95, 13.00,...
## $ `2501` <dbl> 15.49, 15.49, 15.49, 15.49, 15.45, 15.45, 15.62, 15.62,...
## $ `2504` <dbl> 6.40, 6.42, 6.39, 6.38, 6.62, 6.64, 6.63, 6.62, 6.62, 6...
## $ `2505` <dbl> 11.53, 11.34, 11.34, 11.44, 11.39, 11.29, 11.44, 11.49,...
## $ `2506` <dbl> 11.14, 10.90, 10.99, 10.95, 10.85, 10.80, 10.80, 10.75,...
## $ `2509` <dbl> 14.38, 14.22, 14.18, 13.97, 13.97, 13.89, 13.81, 13.81,...
## $ `2511` <dbl> 8.99, 8.99, 8.99, 9.07, 8.94, 8.94, 9.07, 9.03, 9.03, 8...
## $ `2514` <dbl> 15.71, 15.71, 15.80, 15.80, 15.85, 15.85, 15.66, 15.85,...
## $ `2515` <dbl> 5.85, 5.85, 5.89, 5.85, 5.80, 5.78, 5.78, 5.79, 5.78, 5...
## $ `2516` <dbl> 6.79, 6.76, 6.76, 6.75, 6.75, 6.81, 6.81, 6.84, 6.83, 6...
## $ `2520` <dbl> 18.07, 18.07, 18.30, 18.30, 18.39, 18.39, 18.12, 18.12,...
## $ `2524` <dbl> 19.41, 19.36, 19.41, 19.36, 19.54, 19.59, 19.54, 19.77,...
## $ `2527` <dbl> 17.76, 17.76, 17.72, 17.67, 17.67, 17.58, 17.76, 17.76,...
## $ `2528` <dbl> 5.83, 5.83, 5.74, 5.74, 6.00, 6.04, 6.04, 5.79, 5.82, 5...
## $ `2530` <dbl> 12.74, 12.65, 12.65, 12.74, 12.65, 12.60, 12.65, 12.56,...
## $ `2534` <dbl> 14.07, 13.96, 14.26, 14.37, 14.45, 14.41, 14.15, 14.30,...
## $ `2535` <dbl> 16.58, 16.93, 16.71, 16.75, 17.01, 16.97, 16.80, 16.75,...
## $ `2536` <dbl> 22.02, 22.02, 21.97, 21.93, 21.97, 22.14, 21.76, 21.76,...
## $ `2537` <dbl> 8.77, 8.76, 8.74, 8.79, 8.76, 8.62, 8.59, 8.57, 8.57, 8...
## $ `2538` <dbl> 8.24, 8.22, 8.20, 8.24, 8.17, 8.11, 8.03, 8.02, 7.94, 7...
## $ `2539` <dbl> 19.52, 19.22, 19.10, 19.10, 18.95, 19.37, 19.33, 19.10,...
## $ `2540` <dbl> 24.00, 24.00, 24.50, 24.05, 23.85, 23.85, 23.85, 24.00,...
## $ `2542` <dbl> 37.70, 37.90, 38.11, 38.36, 38.32, 38.20, 38.28, 38.99,...
## $ `2543` <dbl> 8.94, 8.90, 8.90, 8.90, 8.94, 8.93, 8.90, 8.89, 8.89, 8...
## $ `2545` <dbl> 33.65, 33.65, 33.35, 33.22, 33.22, 33.06, 32.76, 32.72,...
## $ `2546` <dbl> 14.52, 14.52, 14.56, 14.47, 14.43, 14.43, 14.69, 14.56,...
## $ `2547` <dbl> 9.25, 9.29, 9.30, 9.34, 9.37, 9.35, 9.37, 9.56, 9.66, 9...
## $ `2548` <dbl> 51.80, 51.72, 51.80, 51.80, 52.23, 52.06, 52.49, 52.57,...
## $ `2597` <dbl> 31.79, 32.14, 32.31, 32.09, 32.18, 32.14, 32.39, 32.31,...
## $ `2601` <dbl> 6.79, 6.82, 6.87, 6.86, 6.84, 6.81, 6.80, 6.81, 6.75, 6...
## $ `2603` <dbl> 10.66, 10.71, 10.61, 10.94, 11.03, 11.03, 11.49, 11.62,...
## $ `2605` <dbl> 18.17, 18.31, 18.50, 18.68, 18.45, 18.45, 18.92, 18.78,...
## $ `2606` <dbl> 23.63, 23.54, 23.35, 23.73, 23.58, 23.58, 24.20, 24.10,...
## $ `2607` <dbl> 12.25, 12.25, 12.34, 12.44, 12.44, 12.49, 12.58, 12.49,...
## $ `2608` <dbl> 41.04, 40.76, 40.71, 40.67, 40.62, 40.71, 40.71, 40.94,...
## $ `2609` <dbl> 10.32, 10.24, 10.39, 10.49, 10.43, 10.49, 10.85, 11.25,...
## $ `2610` <dbl> 9.07, 9.07, 9.09, 9.09, 9.12, 9.17, 9.31, 9.30, 9.21, 9...
## $ `2611` <dbl> 6.97, 6.82, 7.03, 7.15, 7.09, 7.05, 7.04, 6.97, 7.03, 7...
## $ `2612` <dbl> 25.82, 25.72, 26.06, 26.35, 26.01, 25.48, 26.06, 25.67,...
## $ `2613` <dbl> 12.05, 12.05, 12.14, 12.19, 12.14, 12.19, 12.14, 12.24,...
## $ `2614` <dbl> 7.58, 7.55, 7.67, 7.71, 7.60, 7.63, 7.55, 7.60, 7.57, 7...
## $ `2615` <dbl> 15.85, 15.75, 15.75, 15.75, 15.85, 16.09, 16.80, 16.66,...
## $ `2616` <dbl> 24.28, 24.36, 24.41, 24.36, 24.23, 25.02, 24.97, 25.02,...
## $ `2617` <dbl> 11.96, 11.91, 12.05, 12.10, 12.01, 12.05, 12.05, 12.15,...
## $ `2618` <dbl> 13.00, 13.00, 13.27, 13.18, 13.18, 13.22, 13.45, 13.40,...
## $ `2630` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `2633` <dbl> 17.87, 17.82, 18.20, 18.39, 18.24, 18.29, 18.24, 18.29,...
## $ `2634` <dbl> 34.85, 35.16, 35.16, 35.21, 34.76, 34.98, 34.98, 34.76,...
## $ `2636` <dbl> 19.88, 19.47, 19.79, 19.79, 19.88, 19.61, 19.65, 19.61,...
## $ `2637` <dbl> 27.02, 27.15, 27.15, 27.20, 27.24, 27.11, 27.29, 27.29,...
## $ `2642` <dbl> 23.63, 23.44, 23.53, 23.53, 23.39, 23.63, 23.58, 23.44,...
## $ `2701` <dbl> 11.98, 11.98, 12.07, 12.12, 12.03, 12.03, 12.03, 12.03,...
## $ `2702` <dbl> 15.28, 15.24, 15.24, 15.38, 15.24, 15.38, 15.43, 15.33,...
## $ `2704` <dbl> 22.20, 22.25, 22.44, 22.49, 22.30, 22.34, 22.34, 22.34,...
## $ `2705` <dbl> 8.16, 8.16, 8.18, 8.18, 8.15, 8.12, 8.15, 8.13, 8.04, 8...
## $ `2706` <dbl> 14.24, 14.24, 14.24, 14.24, 14.19, 14.24, 14.28, 14.32,...
## $ `2707` <dbl> 153.13, 153.13, 152.68, 152.23, 152.68, 152.68, 152.68,...
## $ `2712` <dbl> 25.58, 25.58, 24.94, 24.94, 24.89, 24.99, 24.99, 24.99,...
## $ `2722` <dbl> 36.67, 36.76, 36.67, 36.67, 36.45, 36.27, 36.27, 36.23,...
## $ `2723` <dbl> 195.04, 193.05, 203.02, 206.61, 204.22, 206.21, 199.43,...
## $ `2727` <dbl> 122.91, 126.64, 127.57, 129.43, 126.17, 126.64, 129.90,...
## $ `2731` <dbl> 76.12, 76.02, 75.93, 75.47, 77.04, 76.12, 75.29, 74.92,...
## $ `2739` <dbl> 28.96, 28.73, 28.87, 28.73, 28.91, 28.91, 28.91, 28.87,...
## $ `2748` <dbl> 44.83, 45.94, 45.85, 46.50, 46.87, 46.78, 47.43, 48.08,...
## $ `2801` <dbl> 14.93, 14.84, 14.93, 14.97, 14.93, 14.97, 15.06, 15.28,...
## $ `2809` <dbl> 25.60, 25.55, 26.23, 25.87, 25.64, 25.91, 25.96, 25.96,...
## $ `2812` <dbl> 7.98, 7.97, 7.96, 7.95, 7.97, 7.97, 8.02, 8.02, 8.00, 7...
## $ `2816` <dbl> 14.41, 14.31, 14.22, 14.07, 14.22, 14.12, 14.12, 14.22,...
## $ `2820` <dbl> 11.69, 11.65, 11.69, 11.74, 11.74, 11.78, 11.78, 11.87,...
## $ `2823` <dbl> 26.28, 26.28, 26.36, 25.91, 26.11, 26.16, 26.03, 25.50,...
## $ `2832` <dbl> 17.45, 17.45, 17.45, 17.45, 17.49, 17.49, 17.40, 17.31,...
## $ `2834` <dbl> 7.32, 7.31, 7.34, 7.33, 7.30, 7.34, 7.40, 7.40, 7.39, 7...
## $ `2836` <dbl> 8.14, 8.15, 8.14, 8.15, 8.15, 8.17, 8.23, 8.24, 8.23, 8...
## $ `2838` <dbl> 7.95, 7.97, 7.99, 7.98, 8.01, 7.99, 7.97, 8.00, 7.99, 7...
## $ `2841` <dbl> 10.15, 10.10, 10.15, 10.20, 10.10, 10.15, 10.10, 10.05,...
## $ `2845` <dbl> 7.97, 7.97, 7.97, 7.97, 7.96, 7.95, 7.97, 8.01, 8.00, 7...
## $ `2849` <dbl> 13.26, 12.75, 12.71, 12.66, 12.71, 12.52, 12.39, 12.39,...
## $ `2850` <dbl> 23.88, 23.83, 23.79, 23.70, 23.70, 23.61, 23.74, 23.83,...
## $ `2851` <dbl> 12.98, 12.98, 12.98, 13.07, 13.02, 13.02, 13.07, 13.07,...
## $ `2852` <dbl> 12.06, 12.06, 12.15, 12.02, 11.88, 11.97, 12.06, 12.15,...
## $ `2855` <dbl> 10.34, 10.16, 10.25, 10.16, 10.16, 10.16, 10.21, 10.34,...
## $ `2867` <dbl> 13.30, 13.45, 13.57, 13.53, 13.45, 13.34, 13.42, 13.45,...
## $ `2880` <dbl> 13.84, 13.80, 13.92, 13.97, 14.01, 14.01, 14.05, 14.18,...
## $ `2881` <dbl> 47.15, 46.87, 47.15, 47.33, 47.42, 47.70, 47.42, 47.88,...
## $ `2882` <dbl> 44.01, 43.92, 44.38, 44.70, 44.93, 45.11, 44.93, 44.65,...
## $ `2883` <dbl> 7.20, 7.20, 7.23, 7.20, 7.18, 7.17, 7.18, 7.23, 7.20, 7...
## $ `2884` <dbl> 15.07, 15.07, 15.11, 15.15, 14.98, 14.94, 15.07, 15.19,...
## $ `2885` <dbl> 11.08, 11.08, 11.18, 11.18, 11.13, 11.18, 11.27, 11.55,...
## $ `2886` <dbl> 20.63, 20.94, 21.12, 21.16, 20.85, 21.07, 21.16, 21.34,...
## $ `2887` <dbl> 10.05, 10.05, 10.13, 10.17, 10.09, 10.00, 10.13, 10.17,...
## $ `2888` <dbl> 7.33, 7.37, 7.44, 7.44, 7.33, 7.33, 7.57, 7.49, 7.55, 7...
## $ `2889` <dbl> 7.15, 7.16, 7.16, 7.17, 7.15, 7.15, 7.23, 7.22, 7.21, 7...
## $ `2890` <dbl> 7.91, 7.89, 7.97, 8.00, 7.97, 7.93, 7.98, 8.01, 7.99, 7...
## $ `2891` <dbl> 16.00, 16.09, 16.27, 16.27, 16.27, 16.27, 16.27, 16.27,...
## $ `2892` <dbl> 15.01, 15.10, 15.23, 15.23, 15.19, 15.23, 15.28, 15.32,...
## $ `2897` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `2901` <dbl> 24.52, 24.47, 24.52, 24.42, 24.42, 24.37, 24.32, 24.47,...
## $ `2903` <dbl> 14.47, 14.42, 14.42, 14.42, 14.42, 14.42, 14.33, 14.47,...
## $ `2904` <dbl> 21.58, 21.67, 21.67, 21.72, 21.63, 21.50, 21.54, 21.54,...
## $ `2905` <dbl> 18.54, 18.54, 18.46, 18.42, 18.38, 18.13, 18.22, 18.87,...
## $ `2906` <dbl> 9.69, 9.78, 9.83, 9.87, 9.92, 10.06, 9.92, 10.15, 10.15...
## $ `2908` <dbl> 18.08, 17.76, 17.71, 17.76, 17.90, 17.85, 17.90, 17.99,...
## $ `2910` <dbl> 38.32, 36.45, 35.42, 35.07, 32.42, 29.42, 27.16, 26.62,...
## $ `2911` <dbl> 10.68, 10.58, 10.87, 10.87, 10.63, 10.82, 10.77, 10.63,...
## $ `2912` <dbl> 209.04, 205.00, 207.25, 203.66, 204.11, 205.00, 205.00,...
## $ `2913` <dbl> 13.29, 13.19, 13.33, 13.29, 13.24, 13.24, 13.29, 13.33,...
## $ `2915` <dbl> 76.27, 77.26, 77.26, 76.41, 80.10, 82.09, 80.25, 80.10,...
## $ `2923` <dbl> 20.02, 20.02, 19.78, 19.88, 19.98, 19.69, 19.59, 19.78,...
## $ `2929` <dbl> 83.93, 83.53, 84.73, 87.53, 86.73, 86.73, 87.53, 87.13,...
## $ `2936` <dbl> 41.59, 43.02, 45.81, 45.63, 44.24, 42.40, 40.69, 40.51,...
## $ `2939` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `3002` <dbl> 9.92, 9.97, 10.01, 10.06, 9.97, 9.83, 9.83, 9.87, 9.83,...
## $ `3003` <dbl> 35.89, 36.17, 36.59, 36.63, 36.54, 36.40, 36.49, 37.99,...
## $ `3004` <dbl> 46.03, 46.08, 46.22, 46.27, 46.27, 46.22, 45.89, 46.27,...
## $ `3005` <dbl> 34.42, 34.64, 35.17, 34.78, 36.18, 36.89, 38.91, 38.38,...
## $ `3006` <dbl> 30.24, 30.10, 30.92, 30.83, 30.10, 29.78, 29.65, 29.65,...
## $ `3008` <dbl> 3690.64, 3676.05, 3938.63, 4031.02, 3899.73, 4021.29, 4...
## $ `3010` <dbl> 40.99, 40.99, 40.86, 40.95, 40.95, 41.22, 41.57, 41.75,...
## $ `3011` <dbl> 7.46, 7.36, 7.30, 7.30, 7.18, 7.16, 7.19, 7.16, 7.16, 7...
## $ `3013` <dbl> 16.99, 16.90, 18.08, 17.84, 17.65, 17.23, 17.09, 16.80,...
## $ `3014` <dbl> 25.82, 26.00, 26.17, 26.12, 25.91, 25.31, 25.31, 25.22,...
## $ `3015` <dbl> 20.99, 21.13, 21.30, 21.43, 21.17, 20.95, 20.99, 21.08,...
## $ `3016` <dbl> 18.93, 20.80, 22.08, 22.18, 21.54, 22.28, 21.54, 20.80,...
## $ `3017` <dbl> 23.10, 22.92, 23.01, 23.01, 23.19, 22.83, 22.42, 22.42,...
## $ `3018` <dbl> 16.36, 16.50, 16.54, 16.45, 16.32, 16.23, 16.45, 16.50,...
## $ `3019` <dbl> 29.78, 29.88, 29.97, 31.42, 30.75, 30.70, 30.55, 31.08,...
## $ `3021` <dbl> 11.23, 11.28, 11.28, 11.28, 11.23, 11.23, 11.32, 11.37,...
## $ `3022` <dbl> 45.19, 45.79, 46.33, 46.13, 46.23, 46.53, 46.38, 46.53,...
## $ `3023` <dbl> 63.04, 63.22, 65.30, 65.21, 64.85, 65.12, 64.31, 64.49,...
## $ `3024` <dbl> 7.05, 7.03, 7.00, 7.00, 7.00, 6.99, 6.98, 7.16, 7.78, 7...
## $ `3025` <dbl> 11.44, 11.49, 11.54, 11.54, 11.29, 11.24, 11.10, 11.15,...
## $ `3026` <dbl> 39.50, 39.13, 39.25, 39.38, 39.25, 39.19, 39.38, 39.50,...
## $ `3027` <dbl> 12.20, 12.25, 12.35, 12.44, 12.49, 12.49, 12.54, 12.84,...
## $ `3028` <dbl> 14.55, 14.55, 14.51, 14.55, 14.51, 14.55, 14.89, 14.85,...
## $ `3029` <dbl> 15.83, 16.01, 16.14, 16.36, 16.28, 16.23, 16.32, 16.23,...
## $ `3030` <dbl> 33.90, 33.99, 34.30, 33.95, 33.77, 33.68, 33.37, 33.41,...
## $ `3031` <dbl> 11.47, 11.47, 11.70, 11.38, 11.51, 11.56, 11.11, 11.02,...
## $ `3032` <dbl> 33.91, 33.96, 34.23, 35.35, 34.45, 34.54, 37.99, 39.42,...
## $ `3033` <dbl> 14.43, 14.43, 14.51, 14.51, 14.47, 14.47, 14.60, 14.69,...
## $ `3034` <dbl> 95.74, 96.18, 97.53, 98.42, 95.74, 98.42, 98.42, 99.76,...
## $ `3035` <dbl> 28.74, 29.49, 29.39, 29.53, 29.77, 29.58, 29.91, 29.63,...
## $ `3036` <dbl> 37.76, 37.54, 37.54, 37.54, 37.23, 37.36, 37.63, 37.49,...
## $ `3037` <dbl> 11.80, 11.99, 12.08, 12.13, 11.94, 11.80, 11.89, 12.04,...
## $ `3038` <dbl> 9.00, 8.99, 9.11, 10.01, 10.06, 10.06, 10.06, 10.01, 10...
## $ `3040` <dbl> 28.94, 29.01, 30.92, 30.16, 30.27, 31.23, 30.54, 30.54,...
## $ `3041` <dbl> 15.75, 15.80, 16.10, 16.05, 16.10, 15.90, 16.00, 16.00,...
## $ `3042` <dbl> 35.53, 35.40, 35.48, 35.75, 35.44, 35.53, 35.75, 35.83,...
## $ `3043` <dbl> 2.18, 2.11, 2.16, 2.15, 2.11, 2.15, 2.29, 2.30, 2.30, 2...
## $ `3044` <dbl> 65.45, 66.26, 68.24, 67.61, 65.81, 66.98, 67.43, 67.52,...
## $ `3045` <dbl> 94.33, 96.14, 97.04, 95.69, 95.24, 95.24, 96.59, 96.14,...
## $ `3046` <dbl> 16.13, 16.17, 16.27, 16.13, 15.90, 16.00, 15.73, 17.30,...
## $ `3047` <dbl> 10.10, 9.96, 10.01, 9.96, 10.01, 9.96, 10.01, 10.29, 10...
## $ `3048` <dbl> 15.26, 15.35, 15.30, 15.21, 15.30, 15.21, 15.12, 15.21,...
## $ `3049` <dbl> 9.02, 8.97, 9.15, 9.13, 8.90, 9.10, 9.11, 10.00, 10.95,...
## $ `3050` <dbl> 10.10, 10.19, 10.33, 10.33, 10.33, 10.19, 9.83, 9.92, 9...
## $ `3051` <dbl> 4.62, 4.47, 4.45, 4.43, 4.23, 4.47, 4.32, 4.38, 4.66, 4...
## $ `3052` <dbl> 7.28, 7.26, 7.31, 7.28, 7.26, 7.23, 7.26, 7.26, 7.24, 7...
## $ `3054` <dbl> 24.60, 24.37, 24.54, 24.65, 24.48, 24.31, 23.80, 23.80,...
## $ `3055` <dbl> 15.95, 15.95, 15.95, 16.04, 16.23, 16.13, 16.13, 16.23,...
## $ `3056` <dbl> 15.09, 15.04, 14.96, 14.92, 14.79, 14.71, 14.75, 14.75,...
## $ `3057` <dbl> 15.60, 15.60, 15.60, 15.85, 15.30, 15.35, 15.45, 15.20,...
## $ `3058` <dbl> 10.13, 10.23, 10.32, 10.23, 9.94, 9.90, 9.94, 9.90, 9.9...
## $ `3059` <dbl> 21.87, 22.07, 22.27, 22.32, 22.22, 21.92, 22.07, 22.61,...
## $ `3060` <dbl> 32.95, 32.90, 32.74, 34.19, 35.10, 35.58, 34.89, 35.21,...
## $ `3062` <dbl> 18.23, 18.32, 18.32, 18.23, 17.90, 17.99, 18.04, 18.04,...
## $ `3090` <dbl> 20.63, 20.67, 20.67, 20.72, 20.55, 20.59, 20.55, 20.63,...
## $ `3094` <dbl> 19.62, 20.36, 20.22, 20.13, 20.03, 19.80, 19.67, 19.67,...
## $ `3130` <dbl> 123.57, 123.13, 123.57, 124.89, 124.45, 124.45, 122.69,...
## $ `3149` <dbl> 20.50, 20.75, 22.80, 22.05, 21.25, 21.35, 20.85, 20.90,...
## $ `3164` <dbl> 23.30, 23.00, 22.75, 22.80, 23.15, 22.70, 22.10, 22.00,...
## $ `3167` <dbl> 24.01, 24.01, 24.20, 23.92, 26.31, 25.85, 25.67, 25.39,...
## $ `3189` <dbl> 66.55, 66.83, 66.74, 66.27, 65.62, 66.27, 65.90, 66.46,...
## $ `3209` <dbl> 19.90, 20.27, 20.76, 21.05, 20.68, 20.52, 20.35, 20.39,...
## $ `3229` <dbl> 11.45, 11.45, 11.40, 11.50, 11.60, 11.50, 11.30, 11.40,...
## $ `3231` <dbl> 21.54, 21.33, 21.07, 21.63, 21.54, 21.41, 23.01, 23.05,...
## $ `3257` <dbl> 33.64, 33.45, 33.45, 33.77, 34.00, 33.73, 33.54, 33.64,...
## $ `3266` <dbl> 11.50, 11.50, 11.55, 11.60, 11.60, 11.50, 11.55, 11.50,...
## $ `3296` <dbl> 11.83, 11.87, 12.11, 12.48, 12.30, 12.25, 12.58, 12.77,...
## $ `3305` <dbl> 27.97, 28.28, 28.41, 30.85, 30.63, 31.07, 30.49, 30.27,...
## $ `3308` <dbl> 7.85, 7.79, 7.85, 7.72, 7.54, 7.60, 7.50, 7.72, 7.63, 7...
## $ `3311` <dbl> 15.10, 15.25, 15.25, 15.25, 15.00, 15.05, 14.90, 15.55,...
## $ `3312` <dbl> 9.34, 9.35, 9.63, 9.60, 9.55, 9.72, 9.99, 9.80, 9.78, 9...
## $ `3321` <dbl> 13.60, 13.79, 13.84, 13.65, 13.55, 13.41, 13.46, 14.03,...
## $ `3338` <dbl> 30.43, 30.74, 31.10, 30.74, 30.52, 29.58, 29.26, 29.76,...
## $ `3346` <dbl> 53.81, 54.35, 59.73, 64.22, 64.75, 68.97, 75.79, 75.70,...
## $ `3356` <dbl> 40.73, 40.22, 40.47, 40.00, 38.81, 38.64, 37.84, 37.41,...
## $ `3376` <dbl> 77.53, 77.53, 79.12, 78.84, 78.18, 78.65, 78.37, 78.18,...
## $ `3380` <dbl> 18.24, 18.42, 18.79, 18.70, 18.20, 18.47, 18.38, 18.38,...
## $ `3383` <dbl> 2.56, 2.60, 2.72, 2.61, 2.48, 2.47, 2.53, 2.52, 2.55, 2...
## $ `3406` <dbl> 108.68, 108.18, 110.67, 108.18, 104.71, 106.20, 104.21,...
## $ `3413` <dbl> 74.00, 74.09, 74.09, 74.18, 73.40, 73.75, 73.83, 73.75,...
## $ `3416` <dbl> 50.26, 49.62, 49.99, 49.71, 48.53, 48.53, 47.99, 47.99,...
## $ `3419` <dbl> 16.78, 16.54, 16.74, 16.74, 16.78, 16.64, 16.39, 16.25,...
## $ `3432` <dbl> 11.03, 10.94, 10.94, 10.76, 10.71, 10.80, 10.62, 10.54,...
## $ `3437` <dbl> 21.79, 21.88, 22.46, 22.32, 22.12, 22.17, 22.07, 21.98,...
## $ `3443` <dbl> 74.81, 75.85, 76.33, 76.80, 75.85, 75.76, 76.52, 75.66,...
## $ `3450` <dbl> 92.10, 91.75, 90.69, 88.58, 86.82, 89.29, 88.23, 88.23,...
## $ `3454` <dbl> 71.75, 71.50, 71.50, 70.21, 71.15, 70.98, 70.30, 70.30,...
## $ `3481` <dbl> 11.20, 11.25, 11.62, 11.99, 11.90, 11.85, 11.80, 11.90,...
## $ `3494` <dbl> 12.50, 12.50, 12.50, 12.55, 12.35, 12.30, 12.25, 12.35,...
## $ `3501` <dbl> 44.81, 44.90, 44.64, 44.72, 45.07, 44.29, 44.03, 44.20,...
## $ `3504` <dbl> 26.00, 26.20, 26.25, 26.60, 26.00, 25.50, 26.30, 26.00,...
## $ `3515` <dbl> 34.28, 34.78, 34.83, 35.11, 35.06, 34.92, 34.88, 35.47,...
## $ `3518` <dbl> 21.16, 21.16, 21.21, 21.74, 21.16, 21.06, 21.06, 21.11,...
## $ `3528` <dbl> 24.37, 24.54, 24.58, 25.17, 25.04, 24.96, 24.96, 24.87,...
## $ `3530` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `3532` <dbl> 119.75, 119.93, 119.93, 119.38, 115.34, 118.28, 115.53,...
## $ `3533` <dbl> 90.33, 90.05, 90.33, 91.74, 91.83, 89.87, 88.74, 88.74,...
## $ `3535` <dbl> 17.40, 17.35, 17.25, 17.40, 17.25, 17.15, 16.60, 16.80,...
## $ `3536` <dbl> 17.38, 17.43, 17.67, 17.72, 17.67, 17.57, 17.67, 17.53,...
## $ `3545` <dbl> 34.50, 33.93, 33.97, 33.59, 33.73, 34.17, 33.73, 33.54,...
## $ `3550` <dbl> 12.83, 12.83, 12.87, 13.05, 13.05, 13.09, 13.09, 13.09,...
## $ `3557` <dbl> 10.96, 11.11, 11.01, 11.01, 10.96, 11.20, 10.98, 11.03,...
## $ `3563` <dbl> 57.72, 56.97, 56.02, 55.54, 54.98, 54.50, 55.45, 55.07,...
## $ `3576` <dbl> 15.15, 15.45, 15.40, 15.40, 15.15, 15.10, 15.05, 15.10,...
## $ `3579` <dbl> 10.80, 11.85, 12.50, 12.10, 11.80, 11.80, 11.70, 12.85,...
## $ `3583` <dbl> 55.48, 55.86, 55.77, 55.77, 55.58, 55.48, 55.20, 55.39,...
## $ `3588` <dbl> 33.21, 33.07, 33.31, 32.84, 32.47, 31.36, 31.13, 30.89,...
## $ `3591` <dbl> 13.35, 13.40, 14.70, 14.60, 14.20, 14.40, 14.35, 14.30,...
## $ `3593` <dbl> 12.15, 12.40, 12.99, 12.83, 12.51, 12.33, 12.30, 12.51,...
## $ `3596` <dbl> 51.37, 52.00, 52.00, 51.55, 51.01, 53.26, 53.88, 54.06,...
## $ `3605` <dbl> 24.44, 24.39, 24.25, 24.15, 23.82, 23.82, 23.29, 23.19,...
## $ `3607` <dbl> 30.66, 30.80, 30.80, 30.71, 30.62, 30.80, 30.16, 29.42,...
## $ `3617` <dbl> 89.29, 89.83, 89.38, 89.92, 88.75, 86.33, 87.05, 88.93,...
## $ `3622` <dbl> 12.04, 11.99, 12.04, 12.14, 12.04, 11.79, 11.84, 11.89,...
## $ `3645` <dbl> 30.38, 30.28, 32.09, 31.85, 31.85, 31.66, 31.71, 31.57,...
## $ `3653` <dbl> 45.35, 45.87, 49.56, 48.61, 47.15, 47.29, 47.01, 47.38,...
## $ `3661` <dbl> 30.46, 29.96, 30.31, 30.21, 29.72, 30.11, 29.72, 29.77,...
## $ `3665` <dbl> 157.18, 158.11, 160.91, 163.71, 159.98, 160.91, 159.05,...
## $ `3669` <dbl> 18.86, 18.86, 19.38, 19.38, 19.33, 19.15, 19.10, 19.52,...
## $ `3673` <dbl> 54.96, 54.96, 55.15, 55.43, 55.72, 54.96, 53.72, 54.20,...
## $ `3679` <dbl> 71.46, 72.48, 74.52, 74.52, 73.09, 73.50, 72.89, 73.19,...
## $ `3682` <dbl> 10.40, 10.45, 10.35, 10.35, 10.25, 10.30, 10.30, 10.30,...
## $ `3686` <dbl> 7.22, 7.34, 7.28, 7.25, 7.03, 7.07, 7.03, 7.07, 7.07, 7...
## $ `3694` <dbl> 14.10, 14.50, 14.50, 14.35, 14.50, 14.30, 14.20, 14.10,...
## $ `3698` <dbl> 13.25, 13.30, 13.89, 13.79, 13.54, 13.35, 13.35, 13.64,...
## $ `3701` <dbl> 13.88, 13.78, 13.78, 13.72, 13.40, 12.62, 12.66, 12.52,...
## $ `3702` <dbl> 35.91, 36.15, 36.15, 36.20, 36.01, 35.91, 35.67, 36.06,...
## $ `3703` <dbl> 9.64, 9.64, 9.77, 9.77, 9.59, 9.59, 9.59, 9.68, 9.68, 9...
## $ `3704` <dbl> 14.29, 14.19, 14.39, 14.58, 14.39, 14.24, 14.14, 14.04,...
## $ `3705` <dbl> 42.04, 42.13, 42.00, 41.81, 41.77, 41.68, 41.77, 41.81,...
## $ `3706` <dbl> 24.17, 24.95, 24.99, 24.99, 24.91, 25.62, 25.89, 25.81,...
## $ `3708` <dbl> 71.33, 71.24, 71.43, 73.74, 71.33, 72.20, 70.37, 70.18,...
## $ `3711` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `3712` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4104` <dbl> 40.98, 40.89, 40.94, 40.98, 40.67, 40.45, 40.22, 40.18,...
## $ `4106` <dbl> 32.09, 32.00, 31.86, 31.86, 31.43, 31.24, 31.19, 31.01,...
## $ `4108` <dbl> 30.80, 30.70, 30.65, 30.60, 30.15, 30.20, 30.00, 29.95,...
## $ `4119` <dbl> 68.99, 68.90, 68.99, 69.35, 68.08, 66.81, 66.72, 66.35,...
## $ `4133` <dbl> 34.27, 34.45, 34.36, 34.41, 33.89, 33.37, 33.61, 33.28,...
## $ `4137` <dbl> 139.00, 144.52, 145.44, 143.60, 138.08, 139.92, 136.24,...
## $ `4141` <dbl> 31.87, 31.73, 31.87, 32.11, 31.77, 31.77, 31.44, 31.39,...
## $ `4142` <dbl> 21.40, 21.54, 21.50, 21.45, 21.40, 21.36, 21.17, 21.17,...
## $ `4144` <dbl> 47.01, 46.82, 47.34, 47.16, 46.59, 46.87, 47.34, 47.25,...
## $ `4148` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4155` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4164` <dbl> 41.94, 41.61, 41.66, 42.13, 41.94, 41.71, 40.81, 40.29,...
## $ `4190` <dbl> 78.14, 78.52, 80.01, 79.45, 78.42, 79.82, 79.07, 78.52,...
## $ `4306` <dbl> 11.55, 11.65, 11.69, 11.69, 11.74, 11.84, 11.93, 12.17,...
## $ `4414` <dbl> 17.40, 17.45, 17.40, 17.55, 18.20, 18.29, 18.54, 18.79,...
## $ `4426` <dbl> 80.10, 79.73, 78.98, 78.98, 79.35, 81.23, 73.14, 69.77,...
## $ `4438` <dbl> 135.38, 133.52, 133.05, 132.12, 130.26, 129.80, 128.40,...
## $ `4526` <dbl> 20.84, 20.74, 20.74, 20.84, 20.74, 20.84, 20.94, 20.94,...
## $ `4532` <dbl> 28.56, 28.43, 28.83, 28.52, 28.61, 29.09, 29.22, 29.22,...
## $ `4536` <dbl> 91.51, 92.42, 91.96, 91.51, 92.42, 94.24, 94.24, 94.24,...
## $ `4540` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4545` <dbl> 38.97, 39.01, 38.97, 39.47, 40.02, 39.70, 39.61, 43.57,...
## $ `4551` <dbl> 121.40, 122.79, 126.48, 125.09, 123.71, 123.71, 123.25,...
## $ `4552` <dbl> 94.57, 93.72, 95.42, 99.68, 100.11, 99.25, 97.55, 97.98...
## $ `4555` <dbl> 56.50, 56.97, 57.82, 57.73, 59.51, 60.17, 59.89, 59.42,...
## $ `4557` <dbl> 64.52, 64.34, 65.39, 65.57, 65.48, 65.39, 65.66, 68.02,...
## $ `4560` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4562` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4566` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4720` <dbl> 14.07, 14.17, 14.22, 14.17, 14.22, 14.26, 14.17, 14.12,...
## $ `4722` <dbl> 28.57, 28.91, 28.95, 29.33, 29.54, 29.41, 29.24, 29.16,...
## $ `4725` <dbl> 23.95, 24.20, 23.75, 24.25, 23.50, 23.20, 22.90, 22.90,...
## $ `4737` <dbl> 48.81, 51.07, 51.07, 51.25, 50.55, 49.94, 49.07, 49.33,...
## $ `4739` <dbl> 38.06, 38.80, 39.03, 38.85, 38.53, 38.90, 38.62, 38.76,...
## $ `4746` <dbl> 90.71, 90.52, 90.34, 90.89, 90.80, 90.62, 90.52, 90.06,...
## $ `4755` <dbl> 27.92, 28.19, 27.92, 27.83, 27.11, 27.01, 26.92, 26.79,...
## $ `4763` <dbl> 111.18, 111.65, 115.39, 114.45, 116.32, 121.46, 122.86,...
## $ `4764` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4766` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4807` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4904` <dbl> 65.01, 66.01, 66.46, 66.46, 66.37, 66.28, 66.37, 66.37,...
## $ `4906` <dbl> 21.89, 22.12, 22.62, 22.26, 22.30, 22.58, 22.17, 22.12,...
## $ `4912` <dbl> 75.42, 75.61, 79.20, 79.97, 81.23, 81.72, 82.20, 83.27,...
## $ `4915` <dbl> 39.69, 39.05, 38.96, 39.51, 40.05, 39.69, 39.64, 40.05,...
## $ `4916` <dbl> 28.11, 28.11, 28.28, 28.11, 28.88, 28.41, 28.37, 27.98,...
## $ `4919` <dbl> 35.45, 35.91, 36.05, 36.37, 35.91, 35.73, 35.91, 35.86,...
## $ `4927` <dbl> 27.89, 27.98, 27.98, 27.93, 27.98, 27.89, 27.93, 27.84,...
## $ `4930` <dbl> 12.81, 12.86, 13.10, 13.10, 13.10, 12.95, 13.00, 13.10,...
## $ `4934` <dbl> 14.45, 14.65, 14.65, 14.60, 14.35, 14.90, 14.70, 14.70,...
## $ `4935` <dbl> 62.57, 62.47, 62.11, 63.21, 61.19, 61.01, 60.64, 60.55,...
## $ `4938` <dbl> 70.17, 70.89, 69.82, 69.82, 69.73, 70.53, 66.24, 65.07,...
## $ `4942` <dbl> 23.62, 23.66, 23.57, 23.26, 23.39, 23.57, 23.80, 23.71,...
## $ `4943` <dbl> 52.66, 51.56, 50.63, 53.25, 51.56, 55.78, 60.01, 62.12,...
## $ `4952` <dbl> 31.84, 32.26, 32.73, 33.15, 32.56, 32.43, 32.73, 32.48,...
## $ `4956` <dbl> 21.57, 21.81, 21.71, 21.57, 20.20, 20.20, 19.66, 19.95,...
## $ `4958` <dbl> 58.83, 58.83, 59.10, 59.47, 59.10, 59.47, 60.21, 61.50,...
## $ `4960` <dbl> 13.75, 14.10, 14.85, 14.80, 14.25, 14.00, 14.20, 14.00,...
## $ `4961` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4968` <dbl> 51.03, 51.82, 52.80, 52.09, 51.47, 51.73, 51.65, 54.04,...
## $ `4976` <dbl> 23.14, 24.12, 25.14, 24.75, 24.75, 24.41, 23.48, 23.29,...
## $ `4977` <dbl> 78.42, 77.71, 79.31, 83.29, 80.19, 80.37, 77.98, 78.51,...
## $ `4989` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `4994` <dbl> 69.2, 68.9, 68.7, 67.5, 67.7, 66.4, 65.6, 67.3, 67.0, 6...
## $ `4999` <dbl> 46.98, 47.25, 47.25, 47.78, 47.69, 47.69, 47.87, 48.05,...
## $ `5007` <dbl> 49.48, 48.48, 48.30, 48.94, 48.48, 48.57, 48.57, 48.30,...
## $ `5203` <dbl> 70.09, 69.81, 69.52, 68.38, 67.62, 67.71, 66.76, 66.95,...
## $ `5215` <dbl> 24.58, 24.18, 24.36, 24.36, 24.71, 24.84, 24.88, 24.66,...
## $ `5225` <dbl> 29.37, 29.37, 29.37, 29.37, 29.32, 29.37, 29.70, 29.37,...
## $ `5234` <dbl> 29.71, 29.88, 30.08, 33.07, 32.25, 31.92, 31.88, 31.64,...
## $ `5243` <dbl> 35.45, 35.72, 35.72, 35.95, 35.31, 35.36, 35.40, 35.45,...
## $ `5258` <dbl> 35.94, 36.03, 35.67, 35.76, 36.03, 35.05, 34.06, 37.47,...
## $ `5259` <dbl> 9.38, 9.76, 9.54, 10.08, 10.00, 10.00, 9.80, 10.20, 10....
## $ `5264` <dbl> 77.32, 77.32, 77.05, 77.77, 78.13, 78.04, 79.94, 78.86,...
## $ `5269` <dbl> 254.36, 251.58, 276.55, 282.10, 273.32, 269.15, 277.94,...
## $ `5284` <dbl> 51.81, 51.27, 51.63, 51.72, 51.81, 51.90, 51.90, 51.45,...
## $ `5285` <dbl> 32.27, 32.46, 32.92, 32.74, 32.23, 32.27, 32.09, 32.37,...
## $ `5288` <dbl> 73.98, 73.43, 73.52, 73.52, 71.23, 70.04, 69.58, 69.67,...
## $ `5305` <dbl> 22.01, 22.06, 22.94, 22.66, 22.94, 23.03, 23.45, 23.40,...
## $ `5388` <dbl> 70.00, 70.72, 72.33, 72.33, 71.70, 71.97, 71.79, 72.06,...
## $ `5434` <dbl> 76.33, 76.07, 76.33, 76.69, 77.13, 76.25, 77.49, 77.93,...
## $ `5469` <dbl> 16.62, 16.67, 16.81, 16.76, 16.20, 16.11, 16.90, 17.46,...
## $ `5471` <dbl> 28.94, 28.81, 28.90, 28.90, 30.02, 29.53, 29.30, 29.12,...
## $ `5484` <dbl> 6.55, 6.56, 6.46, 6.49, 6.57, 6.50, 6.12, 6.16, 6.21, 6...
## $ `5515` <dbl> 7.85, 7.85, 7.84, 7.84, 7.84, 7.82, 7.78, 7.79, 7.75, 7...
## $ `5519` <dbl> 9.77, 9.68, 9.63, 9.68, 9.68, 9.63, 9.63, 9.68, 9.68, 9...
## $ `5521` <dbl> 9.18, 9.19, 9.13, 9.14, 9.14, 9.11, 9.18, 9.18, 9.18, 9...
## $ `5522` <dbl> 31.03, 31.07, 30.94, 30.90, 30.94, 30.90, 30.94, 31.11,...
## $ `5525` <dbl> 13.65, 13.65, 13.65, 13.60, 13.60, 13.55, 13.55, 13.55,...
## $ `5531` <dbl> 9.25, 9.29, 9.29, 9.38, 9.34, 9.34, 9.52, 9.52, 9.52, 9...
## $ `5533` <dbl> 14.50, 14.36, 14.31, 14.40, 14.45, 14.31, 14.45, 14.36,...
## $ `5534` <dbl> 54.55, 54.55, 54.30, 54.30, 54.30, 55.15, 54.72, 54.64,...
## $ `5538` <dbl> 25.14, 25.71, 25.71, 25.49, 25.45, 25.36, 24.92, 25.54,...
## $ `5607` <dbl> 14.13, 14.18, 14.33, 14.38, 14.28, 14.28, 14.53, 14.62,...
## $ `5608` <dbl> 13.43, 13.48, 13.67, 13.72, 13.67, 13.61, 13.64, 13.58,...
## $ `5706` <dbl> 29.83, 29.91, 30.26, 30.13, 29.91, 29.83, 29.87, 29.96,...
## $ `5871` <dbl> 50.22, 50.49, 50.67, 50.67, 50.67, 50.40, 50.49, 50.76,...
## $ `5876` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `5880` <dbl> 12.13, 12.13, 12.22, 12.22, 12.22, 12.26, 12.31, 12.35,...
## $ `5906` <dbl> 12.00, 12.00, 12.00, 12.00, 12.00, 12.52, 13.16, 12.58,...
## $ `5907` <dbl> 20.00, 20.19, 20.37, 20.79, 20.93, 20.83, 21.06, 21.06,...
## $ `6005` <dbl> 8.35, 8.20, 8.21, 8.21, 8.20, 8.10, 7.99, 8.12, 8.00, 7...
## $ `6024` <dbl> 29.86, 29.90, 30.06, 30.10, 30.10, 29.98, 29.73, 29.73,...
## $ `6108` <dbl> 24.90, 24.81, 25.21, 25.16, 24.72, 25.07, 24.28, 23.97,...
## $ `6112` <dbl> 21.12, 21.16, 21.20, 21.39, 21.43, 21.59, 21.59, 21.43,...
## $ `6115` <dbl> 38.15, 37.98, 38.10, 38.15, 38.06, 37.93, 37.93, 37.89,...
## $ `6116` <dbl> 7.18, 7.19, 7.31, 7.31, 7.51, 7.38, 7.39, 7.38, 7.32, 7...
## $ `6117` <dbl> 12.31, 12.36, 12.22, 12.36, 12.27, 12.27, 12.31, 12.50,...
## $ `6120` <dbl> 12.31, 12.41, 12.36, 12.65, 12.50, 12.50, 12.45, 12.50,...
## $ `6128` <dbl> 36.62, 36.70, 36.70, 36.70, 36.97, 37.14, 36.88, 36.88,...
## $ `6131` <dbl> 12.99, 12.89, 12.69, 12.54, 12.54, 12.49, 12.54, 12.54,...
## $ `6133` <dbl> 8.69, 8.63, 8.65, 8.69, 8.69, 8.61, 8.98, 8.92, 8.93, 8...
## $ `6136` <dbl> 20.31, 20.31, 20.40, 20.44, 20.40, 20.40, 20.53, 20.61,...
## $ `6139` <dbl> 33.49, 34.08, 33.62, 33.53, 32.75, 33.85, 34.77, 33.67,...
## $ `6141` <dbl> 10.00, 10.24, 10.20, 10.05, 10.39, 11.40, 11.30, 11.06,...
## $ `6142` <dbl> 5.82, 5.82, 5.86, 5.83, 6.00, 5.95, 5.96, 5.94, 5.82, 5...
## $ `6152` <dbl> 9.97, 10.10, 10.15, 10.15, 10.05, 9.90, 9.86, 9.91, 9.9...
## $ `6153` <dbl> 17.23, 17.13, 17.37, 17.27, 17.08, 17.13, 17.03, 16.94,...
## $ `6155` <dbl> 17.37, 17.37, 17.47, 17.52, 17.52, 17.32, 17.32, 17.67,...
## $ `6164` <dbl> 13.36, 13.32, 13.22, 13.00, 12.72, 12.68, 12.50, 12.63,...
## $ `6165` <dbl> 15.70, 15.25, 15.50, 15.40, 13.90, 14.00, 14.00, 13.90,...
## $ `6166` <dbl> 58.16, 58.91, 57.88, 57.41, 56.93, 58.35, 57.50, 57.59,...
## $ `6168` <dbl> 10.51, 10.46, 10.74, 10.65, 10.60, 10.51, 10.27, 10.37,...
## $ `6172` <dbl> 11.45, 11.60, 11.50, 10.75, 10.75, 10.95, 10.70, 9.90, ...
## $ `6176` <dbl> 48.43, 49.04, 49.21, 50.16, 48.95, 49.12, 49.12, 49.12,...
## $ `6177` <dbl> 15.38, 15.61, 15.69, 15.69, 15.61, 15.69, 15.65, 15.61,...
## $ `6183` <dbl> 23.65, 23.60, 23.93, 24.06, 24.02, 23.83, 24.02, 24.02,...
## $ `6184` <dbl> 30.31, 30.26, 30.31, 30.35, 30.35, 30.45, 31.37, 30.91,...
## $ `6189` <dbl> 26.55, 26.64, 26.64, 26.73, 26.51, 26.47, 26.60, 26.68,...
## $ `6191` <dbl> 11.58, 11.49, 11.58, 11.58, 11.58, 11.21, 11.16, 11.30,...
## $ `6192` <dbl> 52.12, 52.62, 52.82, 52.62, 52.42, 51.82, 50.83, 51.33,...
## $ `6196` <dbl> 26.07, 26.76, 26.67, 26.90, 26.62, 26.34, 26.80, 26.90,...
## $ `6197` <dbl> 30.23, 30.23, 30.55, 30.50, 30.08, 30.02, 30.29, 30.45,...
## $ `6201` <dbl> 26.37, 26.63, 26.42, 26.50, 26.33, 26.54, 26.50, 26.46,...
## $ `6202` <dbl> 44.27, 44.09, 44.31, 44.49, 44.45, 44.14, 44.89, 44.49,...
## $ `6205` <dbl> 26.55, 26.95, 27.18, 27.45, 27.18, 27.13, 26.77, 26.86,...
## $ `6206` <dbl> 85.63, 86.34, 85.72, 85.98, 86.43, 86.52, 86.52, 87.15,...
## $ `6209` <dbl> 20.10, 20.15, 20.35, 20.59, 20.35, 19.95, 19.81, 19.86,...
## $ `6213` <dbl> 30.32, 30.96, 33.99, 34.30, 33.62, 33.99, 33.71, 34.44,...
## $ `6214` <dbl> 49.89, 49.63, 49.97, 51.16, 51.08, 50.57, 51.25, 50.74,...
## $ `6215` <dbl> 11.44, 11.44, 11.90, 11.95, 11.90, 11.72, 11.72, 11.30,...
## $ `6216` <dbl> 25.67, 25.62, 25.80, 25.84, 25.92, 25.92, 26.22, 26.52,...
## $ `6224` <dbl> 51.99, 51.99, 51.99, 52.08, 52.17, 52.08, 51.90, 51.81,...
## $ `6225` <dbl> 3.68, 3.80, 3.80, 3.99, 3.60, 3.75, 3.75, 3.60, 3.60, 3...
## $ `6226` <dbl> 6.58, 6.48, 6.73, 6.75, 6.71, 6.66, 6.80, 6.86, 6.86, 6...
## $ `6230` <dbl> 118.88, 120.23, 119.78, 122.93, 131.48, 135.09, 132.38,...
## $ `6235` <dbl> 18.58, 18.58, 18.23, 18.27, 18.00, 17.91, 17.78, 17.74,...
## $ `6239` <dbl> 78.96, 79.05, 78.42, 78.42, 79.33, 78.05, 78.14, 78.96,...
## $ `6243` <dbl> 14.15, 14.15, 14.40, 14.15, 14.05, 14.10, 14.15, 14.15,...
## $ `6251` <dbl> 8.87, 9.08, 9.15, 9.06, 9.03, 9.06, 9.01, 9.04, 8.92, 8...
## $ `6257` <dbl> 21.00, 21.00, 21.35, 21.35, 21.35, 21.31, 21.44, 21.49,...
## $ `6269` <dbl> 75.37, 75.81, 75.90, 76.70, 77.40, 77.84, 78.55, 78.19,...
## $ `6271` <dbl> 97.78, 100.49, 98.68, 98.68, 96.43, 98.68, 106.79, 105....
## $ `6277` <dbl> 70.44, 70.44, 70.44, 70.00, 69.91, 69.91, 69.91, 70.00,...
## $ `6278` <dbl> 24.12, 24.31, 24.35, 24.17, 23.99, 23.85, 23.85, 23.99,...
## $ `6281` <dbl> 55.36, 55.36, 55.36, 55.27, 55.18, 54.48, 54.83, 54.65,...
## $ `6282` <dbl> 21.47, 21.47, 21.38, 21.38, 21.02, 20.93, 21.34, 21.52,...
## $ `6283` <dbl> 26.11, 26.59, 27.48, 28.05, 28.33, 27.91, 28.24, 28.62,...
## $ `6285` <dbl> 75.99, 76.42, 77.82, 78.08, 78.60, 78.60, 78.78, 77.91,...
## $ `6288` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6289` <dbl> 1.91, 1.96, 1.96, 1.96, 1.92, 1.88, 1.82, 1.78, 1.78, 1...
## $ `6405` <dbl> 15.70, 15.65, 15.65, 15.70, 15.46, 15.27, 15.36, 15.12,...
## $ `6409` <dbl> 412.93, 418.48, 430.52, 430.52, 424.04, 418.48, 418.02,...
## $ `6412` <dbl> 44.02, 43.80, 43.89, 42.73, 42.64, 42.19, 42.73, 42.82,...
## $ `6414` <dbl> 401.54, 395.42, 398.72, 395.42, 402.96, 409.55, 415.20,...
## $ `6415` <dbl> 454.51, 472.21, 478.12, 480.08, 468.77, 467.30, 474.18,...
## $ `6416` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6431` <dbl> 8.14, 8.14, 8.14, 8.07, 8.10, 8.08, 8.11, 8.12, 8.18, 8...
## $ `6442` <dbl> 41.87, 42.45, 43.16, 42.89, 41.96, 42.01, 41.43, 41.39,...
## $ `6443` <dbl> 10.24, 10.58, 10.48, 10.43, 10.09, 10.09, 10.04, 10.04,...
## $ `6449` <dbl> 27.57, 28.61, 28.52, 28.56, 28.83, 28.65, 28.83, 29.01,...
## $ `6451` <dbl> 94.90, 94.05, 94.90, 95.84, 91.22, 91.69, 89.23, 89.61,...
## $ `6452` <dbl> 350.26, 350.26, 361.53, 357.35, 351.51, 355.68, 351.09,...
## $ `6456` <dbl> 85.40, 86.71, 86.15, 86.05, 86.05, 85.49, 83.24, 84.74,...
## $ `6464` <dbl> 112.22, 112.22, 111.77, 112.22, 111.77, 111.77, 111.77,...
## $ `6477` <dbl> 17.53, 17.77, 17.87, 17.87, 17.82, 17.96, 17.68, 18.06,...
## $ `6504` <dbl> 142.64, 142.17, 142.17, 141.70, 140.29, 140.76, 140.29,...
## $ `6505` <dbl> 98.59, 98.59, 99.94, 98.14, 98.14, 97.69, 96.79, 97.24,...
## $ `6525` <dbl> 43.18, 42.93, 42.76, 42.85, 42.68, 42.60, 42.43, 42.52,...
## $ `6531` <dbl> 66.35, 66.26, 66.26, 66.08, 65.54, 66.81, 66.54, 66.44,...
## $ `6533` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6541` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6552` <dbl> NA, NA, NA, NA, NA, 32.26, 32.16, 30.61, 30.27, 29.88, ...
## $ `6558` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6573` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6579` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6581` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6582` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6591` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6605` <dbl> 79.75, 79.56, 79.28, 78.91, 79.00, 79.00, 78.54, 78.44,...
## $ `6625` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6641` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6655` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6666` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6668` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6670` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6671` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `6674` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8011` <dbl> 20.33, 20.38, 20.72, 20.53, 19.84, 19.89, 20.09, 20.28,...
## $ `8016` <dbl> 90.95, 88.63, 88.63, 89.16, 82.03, 84.26, 84.88, 84.88,...
## $ `8021` <dbl> 19.51, 19.91, 19.96, 19.96, 19.86, 19.91, 19.91, 20.01,...
## $ `8028` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8033` <dbl> 10.05, 10.05, 10.09, 10.02, 10.16, 10.07, 9.98, 10.03, ...
## $ `8039` <dbl> 31.30, 31.94, 31.89, 32.71, 33.16, 32.84, 33.03, 33.30,...
## $ `8046` <dbl> 23.39, 23.63, 23.96, 23.96, 23.72, 23.72, 23.53, 23.77,...
## $ `8070` <dbl> 112.42, 112.42, 113.72, 113.29, 111.55, 111.99, 111.99,...
## $ `8072` <dbl> 23.81, 23.65, 23.65, 23.54, 23.43, 23.32, 23.05, 23.11,...
## $ `8081` <dbl> 60.67, 61.28, 60.67, 59.98, 59.54, 59.63, 59.20, 59.46,...
## $ `8101` <dbl> 10.28, 10.34, 10.40, 10.32, 10.28, 10.26, 10.22, 10.48,...
## $ `8103` <dbl> 25.43, 25.25, 25.66, 25.66, 25.66, 25.70, 25.98, 25.75,...
## $ `8105` <dbl> 15.74, 15.70, 15.99, 16.43, 16.43, 16.72, 16.82, 16.62,...
## $ `8110` <dbl> 10.87, 10.91, 11.01, 11.10, 11.15, 11.10, 11.01, 11.10,...
## $ `8112` <dbl> 21.86, 22.16, 22.46, 22.50, 22.75, 22.24, 22.33, 22.20,...
## $ `8114` <dbl> 153.61, 154.49, 154.05, 159.77, 161.97, 158.45, 156.25,...
## $ `8131` <dbl> 20.28, 20.33, 20.41, 20.37, 19.89, 20.02, 20.07, 19.94,...
## $ `8150` <dbl> 25.71, 25.29, 26.18, 27.22, 26.85, 26.44, 27.74, 27.53,...
## $ `8163` <dbl> 19.10, 19.28, 19.46, 18.87, 18.42, 18.47, 18.15, 18.28,...
## $ `8201` <dbl> 8.19, 8.07, 8.08, 8.09, 8.11, 8.11, 8.24, 8.20, 8.18, 8...
## $ `8210` <dbl> 45.00, 45.08, 45.00, 45.26, 44.91, 44.30, 44.12, 43.95,...
## $ `8213` <dbl> 27.13, 27.27, 27.72, 27.67, 27.18, 27.31, 26.82, 26.86,...
## $ `8215` <dbl> 14.35, 14.11, 14.30, 14.83, 14.45, 14.07, 13.92, 13.97,...
## $ `8222` <dbl> 23.08, 23.56, 23.51, 24.41, 24.46, 24.03, 23.46, 23.27,...
## $ `8249` <dbl> 18.22, 18.22, 18.26, 18.39, 18.22, 18.52, 18.56, 19.04,...
## $ `8261` <dbl> 20.90, 21.19, 21.52, 21.67, 21.81, 21.77, 21.67, 21.77,...
## $ `8271` <dbl> 29.00, 28.95, 29.04, 29.04, 29.04, 29.00, 29.00, 29.00,...
## $ `8341` <dbl> 109.58, 109.11, 111.00, 113.36, 116.20, 115.72, 113.36,...
## $ `8367` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8374` <dbl> 19.44, 19.39, 19.24, 19.00, 18.80, 18.46, 18.07, 18.27,...
## $ `8404` <dbl> 30.89, 30.97, 31.56, 31.39, 31.06, 30.97, 31.10, 31.01,...
## $ `8411` <dbl> 29.95, 29.99, 29.55, 29.81, 29.51, 29.73, 29.60, 29.55,...
## $ `8422` <dbl> 144.04, 143.60, 143.60, 143.60, 141.84, 142.72, 143.16,...
## $ `8427` <dbl> 60.29, 60.02, 60.48, 60.20, 62.23, 61.67, 60.29, 60.11,...
## $ `8429` <dbl> 32.83, 32.93, 33.95, 33.72, 33.16, 32.42, 32.51, 32.60,...
## $ `8442` <dbl> 46.18, 46.08, 46.28, 46.08, 46.08, 46.08, 45.99, 45.99,...
## $ `8443` <dbl> 16.86, 16.96, 17.01, 17.01, 17.01, 17.15, 17.01, 17.01,...
## $ `8454` <dbl> 180.97, 179.10, 179.10, 179.10, 177.70, 178.17, 177.70,...
## $ `8462` <dbl> 55.68, 55.68, 56.08, 55.68, 55.61, 55.88, 55.75, 55.54,...
## $ `8463` <dbl> 15.65, 15.65, 15.78, 15.78, 15.78, 15.51, 15.60, 15.55,...
## $ `8464` <dbl> 300.02, 294.88, 297.68, 281.79, 269.64, 275.25, 264.50,...
## $ `8466` <dbl> 102.93, 101.64, 100.36, 100.36, 99.50, 99.50, 100.79, 1...
## $ `8467` <dbl> 29.99, 29.81, 29.72, 29.62, 29.62, 28.99, 29.17, 29.62,...
## $ `8473` <dbl> 47.26, 46.90, 47.26, 47.71, 47.35, 47.35, 47.81, 48.90,...
## $ `8478` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8480` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 91.63, 90.78, 9...
## $ `8481` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8482` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8488` <dbl> 39.14, 39.50, 40.40, 40.22, 40.22, 40.04, 40.13, 40.18,...
## $ `8497` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8499` <dbl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,...
## $ `8926` <dbl> 20.14, 20.05, 20.10, 20.14, 20.05, 20.05, 20.10, 20.28,...
## $ `8940` <dbl> 14.60, 14.30, 14.10, 14.30, 14.40, 14.20, 14.25, 14.20,...
## $ `8996` <dbl> 51.21, 51.85, 51.49, 51.21, 51.03, 51.03, 50.94, 50.94,...
## $ `9802` <dbl> 57.57, 57.30, 57.30, 57.57, 57.48, 57.66, 56.86, 56.50,...
## $ `9902` <dbl> 9.52, 9.51, 9.71, 9.85, 9.86, 9.82, 9.61, 9.63, 9.70, 9...
## $ `9904` <dbl> 36.75, 37.20, 37.34, 37.47, 35.97, 36.24, 36.47, 36.20,...
## $ `9905` <dbl> 21.41, 21.32, 21.32, 21.36, 21.45, 21.50, 21.54, 21.54,...
## $ `9906` <dbl> 17.41, 17.29, 17.29, 17.20, 16.91, 16.91, 16.66, 16.66,...
## $ `9907` <dbl> 12.94, 12.89, 12.94, 12.99, 12.94, 12.94, 12.94, 13.08,...
## $ `9908` <dbl> 22.52, 22.47, 22.52, 22.61, 22.61, 22.52, 22.38, 22.38,...
## $ `9910` <dbl> 114.35, 118.08, 120.88, 120.88, 120.88, 121.35, 121.35,...
## $ `9911` <dbl> 28.81, 28.38, 28.72, 29.11, 27.94, 27.68, 27.50, 27.68,...
## $ `9912` <dbl> 7.73, 7.76, 7.79, 7.81, 7.83, 7.85, 7.88, 7.75, 7.66, 7...
## $ `9914` <dbl> 139.17, 140.13, 140.61, 154.05, 160.29, 156.93, 154.05,...
## $ `9917` <dbl> 80.63, 80.36, 80.73, 80.45, 80.54, 80.73, 81.09, 81.09,...
## $ `9918` <dbl> 29.57, 29.47, 29.47, 29.47, 29.47, 29.47, 29.47, 29.47,...
## $ `9919` <dbl> 10.26, 10.21, 10.35, 10.40, 10.45, 10.49, 10.45, 10.40,...
## $ `9921` <dbl> 171.80, 172.74, 180.27, 184.04, 185.45, 184.51, 184.04,...
## $ `9924` <dbl> 37.16, 37.08, 36.86, 37.08, 36.72, 36.72, 36.90, 36.77,...
## $ `9925` <dbl> 35.87, 35.83, 35.83, 35.74, 35.78, 35.60, 35.65, 35.65,...
## $ `9926` <dbl> 38.20, 38.20, 38.20, 38.34, 38.34, 38.20, 38.20, 38.15,...
## $ `9927` <dbl> 29.74, 30.44, 30.48, 30.18, 30.09, 30.35, 30.82, 30.52,...
## $ `9928` <dbl> 8.35, 8.35, 8.35, 8.35, 8.35, 8.35, 8.35, 8.35, 8.35, 7...
## $ `9929` <dbl> 11.00, 11.05, 11.40, 11.35, 11.10, 11.30, 11.30, 11.30,...
## $ `9930` <dbl> 44.99, 44.99, 45.33, 45.16, 44.99, 45.07, 44.73, 44.82,...
## $ `9931` <dbl> 29.19, 29.19, 29.23, 28.91, 28.91, 29.00, 29.05, 28.82,...
## $ `9933` <dbl> 43.46, 43.42, 43.20, 43.55, 43.02, 43.95, 42.97, 43.29,...
## $ `9934` <dbl> 14.58, 14.71, 14.71, 14.54, 14.71, 14.27, 14.14, 14.18,...
## $ `9935` <dbl> 9.13, 9.08, 9.05, 9.05, 9.09, 9.08, 9.00, 9.05, 9.04, 9...
## $ `9937` <dbl> 35.96, 35.87, 36.14, 36.09, 36.09, 35.87, 35.64, 36.00,...
## $ `9938` <dbl> 89.14, 90.54, 89.89, 90.26, 88.30, 88.21, 87.65, 88.02,...
## $ `9939` <dbl> 48.50, 48.87, 49.23, 49.60, 49.05, 49.51, 50.05, 49.78,...
## $ `9940` <dbl> 25.21, 25.21, 25.29, 25.21, 25.25, 25.25, 25.84, 25.88,...
## $ `9941` <dbl> 70.22, 70.50, 71.32, 70.86, 70.95, 71.95, 72.14, 72.23,...
## $ `9942` <dbl> 75.24, 74.78, 74.24, 75.60, 75.96, 75.69, 75.42, 75.42,...
## $ `9943` <dbl> 44.06, 44.15, 44.06, 43.89, 44.06, 43.89, 44.06, 43.89,...
## $ `9944` <dbl> 20.28, 20.09, 20.28, 20.09, 20.19, 19.99, 19.99, 19.99,...
## $ `9945` <dbl> 42.71, 42.83, 42.89, 43.12, 43.59, 43.70, 43.94, 44.17,...
## $ `9946` <dbl> 9.12, 9.20, 9.24, 9.24, 9.20, 9.20, 9.16, 9.16, 9.16, 9...
## $ `9955` <dbl> 15.90, 15.90, 16.10, 16.30, 16.25, 16.25, 16.10, 16.55,...
## $ `9958` <dbl> 9.21, 9.20, 9.25, 9.19, 9.16, 9.12, 9.15, 9.14, 9.15, 9...
price_day1
## # A tibble: 493 x 929
##    date       `1101` `1102` `1103` `1104` `1108` `1109` `1110` `1201`
##    <date>      <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
##  1 2017-01-03   29.6   25.0   8.27   21.5   8.57   10.1   15.5   17.6
##  2 2017-01-04   29.7   24.8   8.23   21.5   8.56   10.1   15.4   17.4
##  3 2017-01-05   29.7   25.0   8.24   21.5   8.61   10.1   15.4   17.5
##  4 2017-01-06   29.7   25.0   8.21   21.4   8.57   10.1   15.4   17.4
##  5 2017-01-09   29.4   24.8   8.31   21.4   8.59   10.1   15.3   17.6
##  6 2017-01-10   29.5   24.7   8.28   21.4   8.59   10.2   15.3   17.4
##  7 2017-01-11   30.2   25.1   8.33   21.5   8.57   10.2   15.1   18  
##  8 2017-01-12   30.6   25.6   8.35   21.5   8.6    10.1   15.2   18.1
##  9 2017-01-13   30.4   25.7   8.4    21.4   8.59   10.2   15.3   17.8
## 10 2017-01-16   30.2   25.3   8.43   21.4   8.58   10.1   15.3   17.6
## # ... with 483 more rows, and 920 more variables: `1203` <dbl>,
## #   `1210` <dbl>, `1213` <dbl>, `1215` <dbl>, `1216` <dbl>, `1217` <dbl>,
## #   `1218` <dbl>, `1219` <dbl>, `1220` <dbl>, `1225` <dbl>, `1227` <dbl>,
## #   `1229` <dbl>, `1231` <dbl>, `1232` <dbl>, `1233` <dbl>, `1234` <dbl>,
## #   `1235` <dbl>, `1236` <dbl>, `1256` <dbl>, `1262` <dbl>, `1301` <dbl>,
## #   `1303` <dbl>, `1304` <dbl>, `1305` <dbl>, `1307` <dbl>, `1308` <dbl>,
## #   `1309` <dbl>, `1310` <dbl>, `1312` <dbl>, `1313` <dbl>, `1314` <dbl>,
## #   `1315` <dbl>, `1316` <dbl>, `1319` <dbl>, `1321` <dbl>, `1323` <dbl>,
## #   `1324` <dbl>, `1325` <dbl>, `1326` <dbl>, `1337` <dbl>, `1338` <dbl>,
## #   `1339` <dbl>, `1340` <dbl>, `1341` <dbl>, `1402` <dbl>, `1409` <dbl>,
## #   `1410` <dbl>, `1413` <dbl>, `1414` <dbl>, `1416` <dbl>, `1417` <dbl>,
## #   `1418` <dbl>, `1419` <dbl>, `1423` <dbl>, `1432` <dbl>, `1434` <dbl>,
## #   `1435` <dbl>, `1436` <dbl>, `1437` <dbl>, `1438` <dbl>, `1439` <dbl>,
## #   `1440` <dbl>, `1441` <dbl>, `1442` <dbl>, `1443` <dbl>, `1444` <dbl>,
## #   `1445` <dbl>, `1446` <dbl>, `1447` <dbl>, `1449` <dbl>, `1451` <dbl>,
## #   `1452` <dbl>, `1453` <dbl>, `1454` <dbl>, `1455` <dbl>, `1456` <dbl>,
## #   `1457` <dbl>, `1459` <dbl>, `1460` <dbl>, `1463` <dbl>, `1464` <dbl>,
## #   `1465` <dbl>, `1466` <dbl>, `1467` <dbl>, `1468` <dbl>, `1470` <dbl>,
## #   `1471` <dbl>, `1472` <dbl>, `1473` <dbl>, `1474` <dbl>, `1475` <dbl>,
## #   `1476` <dbl>, `1477` <dbl>, `1503` <dbl>, `1504` <dbl>, `1506` <dbl>,
## #   `1507` <dbl>, `1512` <dbl>, `1513` <dbl>, `1514` <dbl>, ...

4. 檢查含有NA的股票代碼及其NA的個數。

price_day1_na <- price_day1 %>% 
  map_df(~sum(is.na(.))) %>% 
  gather() %>% 
  filter(value!=0)
price_day1_na
## # A tibble: 51 x 2
##    key   value
##    <chr> <int>
##  1 1341    488
##  2 1587    311
##  3 1760    261
##  4 2025     77
##  5 2243    180
##  6 2630    277
##  7 2897     78
##  8 2939    253
##  9 3530    374
## 10 3711    321
## # ... with 41 more rows
price_day1_na1 <- price_day1 %>% 
  # last observation carried forward
  map_df(~sum(is.na(.))) %>% 
  gather() %>% 
  filter(value!=0)

price_day1_na1
## # A tibble: 51 x 2
##    key   value
##    <chr> <int>
##  1 1341    488
##  2 1587    311
##  3 1760    261
##  4 2025     77
##  5 2243    180
##  6 2630    277
##  7 2897     78
##  8 2939    253
##  9 3530    374
## 10 3711    321
## # ... with 41 more rows

5. 將NA值以最近的股價取代。提示：使用na.locf()

price_day_clear <-  price_day1 %>% 
  na.locf(fromLast = TRUE, na.rm=FALSE) %>%
  select(-c("2025", "6131"))

price_day_clear
## # A tibble: 493 x 927
##    date       `1101` `1102` `1103` `1104` `1108` `1109` `1110` `1201`
##    <date>      <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>  <dbl>
##  1 2017-01-03   29.6   25.0   8.27   21.5   8.57   10.1   15.5   17.6
##  2 2017-01-04   29.7   24.8   8.23   21.5   8.56   10.1   15.4   17.4
##  3 2017-01-05   29.7   25.0   8.24   21.5   8.61   10.1   15.4   17.5
##  4 2017-01-06   29.7   25.0   8.21   21.4   8.57   10.1   15.4   17.4
##  5 2017-01-09   29.4   24.8   8.31   21.4   8.59   10.1   15.3   17.6
##  6 2017-01-10   29.5   24.7   8.28   21.4   8.59   10.2   15.3   17.4
##  7 2017-01-11   30.2   25.1   8.33   21.5   8.57   10.2   15.1   18  
##  8 2017-01-12   30.6   25.6   8.35   21.5   8.6    10.1   15.2   18.1
##  9 2017-01-13   30.4   25.7   8.4    21.4   8.59   10.2   15.3   17.8
## 10 2017-01-16   30.2   25.3   8.43   21.4   8.58   10.1   15.3   17.6
## # ... with 483 more rows, and 918 more variables: `1203` <dbl>,
## #   `1210` <dbl>, `1213` <dbl>, `1215` <dbl>, `1216` <dbl>, `1217` <dbl>,
## #   `1218` <dbl>, `1219` <dbl>, `1220` <dbl>, `1225` <dbl>, `1227` <dbl>,
## #   `1229` <dbl>, `1231` <dbl>, `1232` <dbl>, `1233` <dbl>, `1234` <dbl>,
## #   `1235` <dbl>, `1236` <dbl>, `1256` <dbl>, `1262` <dbl>, `1301` <dbl>,
## #   `1303` <dbl>, `1304` <dbl>, `1305` <dbl>, `1307` <dbl>, `1308` <dbl>,
## #   `1309` <dbl>, `1310` <dbl>, `1312` <dbl>, `1313` <dbl>, `1314` <dbl>,
## #   `1315` <dbl>, `1316` <dbl>, `1319` <dbl>, `1321` <dbl>, `1323` <dbl>,
## #   `1324` <dbl>, `1325` <dbl>, `1326` <dbl>, `1337` <dbl>, `1338` <dbl>,
## #   `1339` <dbl>, `1340` <dbl>, `1341` <dbl>, `1402` <dbl>, `1409` <dbl>,
## #   `1410` <dbl>, `1413` <dbl>, `1414` <dbl>, `1416` <dbl>, `1417` <dbl>,
## #   `1418` <dbl>, `1419` <dbl>, `1423` <dbl>, `1432` <dbl>, `1434` <dbl>,
## #   `1435` <dbl>, `1436` <dbl>, `1437` <dbl>, `1438` <dbl>, `1439` <dbl>,
## #   `1440` <dbl>, `1441` <dbl>, `1442` <dbl>, `1443` <dbl>, `1444` <dbl>,
## #   `1445` <dbl>, `1446` <dbl>, `1447` <dbl>, `1449` <dbl>, `1451` <dbl>,
## #   `1452` <dbl>, `1453` <dbl>, `1454` <dbl>, `1455` <dbl>, `1456` <dbl>,
## #   `1457` <dbl>, `1459` <dbl>, `1460` <dbl>, `1463` <dbl>, `1464` <dbl>,
## #   `1465` <dbl>, `1466` <dbl>, `1467` <dbl>, `1468` <dbl>, `1470` <dbl>,
## #   `1471` <dbl>, `1472` <dbl>, `1473` <dbl>, `1474` <dbl>, `1475` <dbl>,
## #   `1476` <dbl>, `1477` <dbl>, `1503` <dbl>, `1504` <dbl>, `1506` <dbl>,
## #   `1507` <dbl>, `1512` <dbl>, `1513` <dbl>, `1514` <dbl>, ...

6. 刪除上題中仍含有NA值的股票, 並確認股票數量及筆數。

dim(price_day_clear)
## [1] 493 927

7. 將資料轉為xts(提示：可用tk_xts()), 計算日報酬率(以log計算)(提示：可用Return.calculate()), 並刪除第一筆沒有報酬率的資料。請顯示前五檔股票第1-5天的報酬率。

ret_day <- price_day_clear %>% 
  select(1:6)  %>% 
  tk_xts(select = -date, date_var = date) %>% 
  Return.calculate(method = "log")  %>%
  na.omit()

dim(ret_day)
## [1] 492   5
head(ret_day,5)
##                    1101         1102         1103         1104
## 2017-01-04  0.003031837 -0.005627024 -0.004848494  0.000000000
## 2017-01-05  0.000000000  0.005627024  0.001214329  0.001858737
## 2017-01-06  0.000000000  0.000000000 -0.003647420 -0.006053569
## 2017-01-09 -0.010142075 -0.007644374  0.012106685  0.000000000
## 2017-01-10  0.001358235 -0.003641517 -0.003616640 -0.001870033
##                    1108
## 2017-01-04 -0.001167542
## 2017-01-05  0.005824128
## 2017-01-06 -0.004656586
## 2017-01-09  0.002331003
## 2017-01-10  0.000000000

8. 計算月報酬率(以log計算)(提示：可用Return.calculate()), 並刪除第一筆沒有報酬率的資料。請顯示前五檔股票第1-5天的報酬率。

price_day.xts <- price_day_clear %>%
                 select(1:6)  %>%
  tk_xts(select = -date, date_var = date)  

ret_mon.xts <- price_day.xts %>% 
  to.period(period = "months", 
            indexAt = "lastof", 
            OHLC= FALSE) %>% 
  Return.calculate(method = "log") %>%
  na.omit()
  
dim(ret_mon.xts)
## [1] 23  5
ret_mon.xts
##                    1101         1102        1103         1104         1108
## 2017-02-28  0.061707886  0.127658684  0.19286519  0.068744779  0.102909963
## 2017-03-31 -0.036565972  0.006616775 -0.05291257  0.013370913 -0.020181248
## 2017-04-30 -0.033552392 -0.026377474 -0.02314472 -0.022969591 -0.031610261
## 2017-05-31 -0.020133763 -0.067822596 -0.01871054  0.003937874 -0.010016778
## 2017-06-30  0.022832820 -0.064589374  0.02357673 -0.042825456 -0.007860793
## 2017-07-31  0.035416576  0.022527099 -0.01368545 -0.026323386  0.001126761
## 2017-08-31 -0.004236604  0.057578197  0.13684774  0.017165812 -0.007914117
## 2017-09-30 -0.030506344 -0.018571692  0.02876679  0.008701681 -0.012564414
## 2017-10-31 -0.008792752  0.001910950 -0.02448413  0.006816659  0.001148765
## 2017-11-30  0.001357773  0.034525005  0.03691694 -0.019666767 -0.022055450
## 2017-12-31  0.082960896  0.012463504  0.06149642  0.002306806 -0.017762456
## 2018-01-31  0.032255907  0.063855228  0.01461003 -0.004618946  0.014235116
## 2018-02-28 -0.017381136 -0.056595668 -0.06872028 -0.017749182 -0.023839031
## 2018-03-31 -0.012068845  0.005410293 -0.08174762 -0.006619410 -0.063493631
## 2018-04-30  0.111258406  0.106043735  0.02540654 -0.013371737 -0.020779968
## 2018-05-31  0.064973663  0.040265385  0.10657086 -0.041723843  0.063553784
## 2018-06-30 -0.029133416  0.013273848 -0.03400881 -0.048790164 -0.022416879
## 2018-07-31  0.055918433  0.197235849  0.13734551  0.048790164  0.001258653
## 2018-08-31  0.073472446  0.052236958  0.01669023  0.027195743 -0.012658397
## 2018-09-30 -0.029960300 -0.008398370 -0.04225981 -0.014742282  0.003814372
## 2018-10-31 -0.169268435 -0.236790465 -0.18954180 -0.074488852 -0.094422249
## 2018-11-30 -0.005780363  0.028594875  0.20382776  0.010610179  0.031574346
## 2018-12-31  0.031386314  0.007391017 -0.03610500 -0.002642009 -0.008141158
head(ret_mon.xts,5)
##                   1101         1102        1103         1104         1108
## 2017-02-28  0.06170789  0.127658684  0.19286519  0.068744779  0.102909963
## 2017-03-31 -0.03656597  0.006616775 -0.05291257  0.013370913 -0.020181248
## 2017-04-30 -0.03355239 -0.026377474 -0.02314472 -0.022969591 -0.031610261
## 2017-05-31 -0.02013376 -0.067822596 -0.01871054  0.003937874 -0.010016778
## 2017-06-30  0.02283282 -0.064589374  0.02357673 -0.042825456 -0.007860793

9. 找出2017及2018年年底市值最大的前20家公司代碼, 簡稱, 並修改資本額格式，計算每家公司市值佔20家總市值的百分比。提示：使用filter(), arrange(), slice(), sum()。

tej20 <- read_tsv("C:/Users/Sarah/Desktop/FinDB2019_SalesAnalysis/FinDB_2019_Sales_Analysis/data_wrangle_practice/tej_day_price_2017_2018.txt", col_names = TRUE)
## Parsed with column specification:
## cols(
##   證券代碼 = col_double(),
##   簡稱 = col_character(),
##   `TSE 產業別` = col_character(),
##   上市別 = col_character(),
##   年月日 = col_double(),
##   `開盤價(元)` = col_double(),
##   `最高價(元)` = col_double(),
##   `收盤價(元)` = col_double(),
##   `最低價(元)` = col_double(),
##   `成交值(千元)` = col_double(),
##   `市值(百萬元)` = col_double(),
##   `成交量(千股)` = col_double()
## )
glimpse(tej20)
## Observations: 443,171
## Variables: 12
## $ 證券代碼       <dbl> 1101, 1102, 1103, 1104, 1108, 1109, 1110, 1201, 120...
## $ 簡稱           <chr> "台泥", "亞泥", "嘉泥", "環泥", "幸福", "信大", "東泥", "味全", "...
## $ `TSE 產業別`   <chr> "01", "01", "01", "01", "01", "01", "01", "02", "0...
## $ 上市別         <chr> "TSE", "TSE", "TSE", "TSE", "TSE", "TSE", "TSE", "...
## $ 年月日         <dbl> 20170103, 20170103, 20170103, 20170103, 20170103, ...
## $ `開盤價(元)`   <dbl> 29.90, 24.91, 8.27, 21.41, 8.56, 10.11, 15.58, 17.5...
## $ `最高價(元)`   <dbl> 29.90, 24.95, 8.27, 21.54, 8.57, 10.11, 15.63, 17.7...
## $ `收盤價(元)`   <dbl> 29.64, 24.95, 8.27, 21.50, 8.57, 10.11, 15.54, 17.6...
## $ `最低價(元)`   <dbl> 29.35, 24.76, 8.17, 21.37, 8.56, 10.11, 15.54, 17.5...
## $ `成交值(千元)` <dbl> 101450, 33550, 2411, 3705, 182, 42, 406, 11504, 171,...
## $ `市值(百萬元)` <dbl> 129779, 89078, 6748, 15610, 3703, 3789, 9009, 8931, ...
## $ `成交量(千股)` <dbl> 2890, 1271, 278, 150, 20, 4, 25, 653, 7, 2213, 19, 2...
tej1<-tej20 %>% select('證券代碼', '簡稱', '年月日', '市值(百萬元)') %>% 
  rename(id = '證券代碼', name = '簡稱', date = '年月日', cap = '市值(百萬元)') %>%      
  mutate(date = date %>% as.character %>% as.Date('%Y%m%d')) %>% 
  mutate(id = id %>% as.character) %>% 
  arrange(desc(date), desc(cap)) %>%  
  select(3,4,1,2) %>%
  slice(1:20, 224877:224896)

10. 將2017年前20大公司市值以圖形表示如下。注意：市值由大小排列順序。

tej2<-tej20 %>% select('證券代碼', '簡稱', '年月日', '市值(百萬元)') %>% 
  rename(id = '證券代碼', name = '簡稱', date = '年月日', cap = '市值(百萬元)') %>%      
  mutate(date = date %>% as.character %>% as.Date('%Y%m%d')) %>% 
  mutate(id = id %>% as.character) %>% 
  arrange(desc(date), desc(cap)) %>%  
  select(3,4,1,2) %>%
  slice(224877:224896)

tej2
## # A tibble: 20 x 4
##    date           cap id    name  
##    <date>       <dbl> <chr> <chr> 
##  1 2017-12-29 5951022 2330  台積電
##  2 2017-12-29 1649695 2317  鴻海  
##  3 2017-12-29 1100248 6505  台塑化
##  4 2017-12-29  822289 2412  中華電
##  5 2017-12-29  672131 2882  國泰金
##  6 2017-12-29  628298 1301  台塑  
##  7 2017-12-29  617810 1303  南亞  
##  8 2017-12-29  603702 1326  台化  
##  9 2017-12-29  539242 3008  大立光
## 10 2017-12-29  518843 2881  富邦金
## 11 2017-12-29  464955 2454  聯發科
## 12 2017-12-29  399688 2891  中信金
## 13 2017-12-29  389437 2002  中鋼  
## 14 2017-12-29  375012 1216  統一  
## 15 2017-12-29  372747 2308  台達電
## 16 2017-12-29  367739 3045  台灣大
## 17 2017-12-29  327075 2886  兆豐金
## 18 2017-12-29  295252 2912  統一超
## 19 2017-12-29  252688 2474  可成  
## 20 2017-12-29  239499 4904  遠傳

11. 將題7的日報酬格式由寬格式改為長格式(如下),並只選取2018年的資料。提示：可用tk_tbl()將資料xts轉為tibble格式。並用gather()將寬資料轉為長資料。

tej_day_price_2017_2018.tbl = ret_day %>% 
  tk_tbl(select = -date, date_var = date) %>%
  select(2:6) %>%
  gather(key = id, value = ret)

tej_day_price_2017_2018.tbl
## # A tibble: 2,460 x 2
##    id         ret
##    <chr>    <dbl>
##  1 1101   0.00303
##  2 1101   0      
##  3 1101   0      
##  4 1101  -0.0101 
##  5 1101   0.00136
##  6 1101   0.0241 
##  7 1101   0.0138 
##  8 1101  -0.00820
##  9 1101  -0.00562
## 10 1101  -0.00698
## # ... with 2,450 more rows

12. 利用題9的20檔股票代碼，找出相對應20檔股票在2018年的日報酬率。提示：利用filter()。

13. 依前題，計算20檔股票每月報酬率。提示：將每月中的每天報酬率加總，即可以得每月報酬率。利用as.yearmon()將日期轉為年月，並利用group_by(), summarize()計算分組報酬率總和。

老師不好意思，我盡我所能將會做的完成，有些只做到一半還是做不出來，有些則做不出來，不好意思再麻煩了