From 45bf57b186b76b7876421604c9e7bff5d77d8671 Mon Sep 17 00:00:00 2001 From: Helene31 Date: Wed, 22 Apr 2020 14:44:33 +0200 Subject: [PATCH] maj --- module3/exercice3/ConcentrationCO2.Rmd | 133 +++ module3/exercice3/ConcentrationCO2.html | 584 +++++++++++++ module3/exercice3/monthly_in_situ_co2_mlo.csv | 813 ++++++++++++++++++ 3 files changed, 1530 insertions(+) create mode 100644 module3/exercice3/ConcentrationCO2.Rmd create mode 100644 module3/exercice3/ConcentrationCO2.html create mode 100644 module3/exercice3/monthly_in_situ_co2_mlo.csv diff --git a/module3/exercice3/ConcentrationCO2.Rmd b/module3/exercice3/ConcentrationCO2.Rmd new file mode 100644 index 0000000..2ea30ba --- /dev/null +++ b/module3/exercice3/ConcentrationCO2.Rmd @@ -0,0 +1,133 @@ +--- +title: "Concentration de CO2 dans l'atmosphère depuis 1958" +author: "Hélène Raynal" +date: "21 avril 2020" +output: html_document +--- + + +### Sujet + +En 1958, Charles David Keeling a initié une mesure de la concentration de CO2 dans l'atmosphère à l'observatoire de Mauna Loa, Hawaii, États-Unis qui continue jusqu'à aujourd'hui. L'objectif initial était d'étudier la variation saisonnière, mais l'intérêt s'est déplacé plus tard vers l'étude de la tendance croissante dans le contexte du changement climatique. En honneur à Keeling, ce jeu de données est souvent appelé "Keeling Curve" (voir (https://en.wikipedia.org/wiki/Keeling_Curve) pour l'histoire et l'importance de ces données). + +Les données sont disponibles sur le site Web de l'institut Scripps. Utilisez le fichier avec les observations hebdomadaires. Attention, ce fichier est mis à jour régulièrement avec de nouvelles observations. Notez donc bien la date du téléchargement, et gardez une copie locale de la version précise que vous analysez. Faites aussi attention aux données manquantes. + + +### Pré-requis +Traitement de suites chronologiques + +Quelques références: + +- [caschrono: Séries Temporelles Avec R] (https://cran.r-project.org/web/packages/caschrono/) - Yves Aragon - Université Toulouse Capitole - 28 janvier 2019 + + +### Create dataframe and load R libraries required for the different statistical treatments + +The data file below contains 10 columns. + +- Columns 1-4 give the dates in several redundant formats. +- Column 5 below gives monthly Mauna Loa CO2 concentrations in micro-mol CO2 per mole (ppm), reported on the 2008A SIO manometric mole fraction scale. This is thestandard version of the data most often sought. The monthly values have been adjusted to 24:00 hours on the 15th of each month. +- Column 6 gives the same data after a seasonal adjustment to remove the quasi-regular seasonal cycle. The adjustment involves subtracting from the data a 4-harmonic fit with a linear gain factor. +- Column 7 is a smoothed version of the data generated from a stiff cubic spline function plus 4-harmonic functions with linear gain. +- Column 8 is the same smoothed version with the seasonal cycle removed. +- Column 9 is identical to Column 5 except that the missing values from Column 5 have been filled with values from Column 7. +- Column 10 is identical to Column 6 except missing values have been filled with values from Column 8. + +Missing values are denoted by -99.99 + + CO2 concentrations are measured on the '08A' calibration scale + +```{r } +library(tidyverse) +library(forecast) +library(lubridate) +library(car) +library(scales) +library(patchwork) +library(kableExtra) + +dataCO2 <- read.csv("monthly_in_situ_co2_mlo.csv", sep="," ,skip = 57) +colnames(dataCO2) <- c("Year", "Month","Date1", "Date2", "ObsCO2", "SeasAdjCO2","SplineAdjCO2", "SplineAdjCO2Trend", "ObsCO2Comp", "SeasAdjCO2Comp") +summary(dataCO2) + +dataCO2$Date <- ymd(paste0(dataCO2$Year, " ", dataCO2$Month, " ", "15")) + +``` + + +** Remplacement dans la série des valeurs observées, des valeurs manquantes -99.99 par celles qui sont interpolées +** on enlève ensuite les observations manquantes +```{r } + + + +dataCO2 <- dataCO2[dataCO2$ObsCO2Comp != "-99.99", ] + +``` + +** Create a column Date with format YYYY MM DD +```{r } + + +dataCO2$Date <- ymd(paste0(dataCO2$Year, "-", dataCO2$Month, "-", "15")) + +``` + + +### Représentation des résultats + +```{r } +ggplot(dataCO2,aes(Date, dataCO2$ObsCO2Comp)) + + geom_line(color='orange') + + xlab("Year, Month") + + scale_x_date(date_labels = "%Y-%m", date_breaks = "5 year") + + theme(axis.text.x = element_text(face = "bold", color = "#993333", + size = 12, angle = 45, hjust = 1)) + + ylab("CO2 Concentration (ppm)") + + scale_y_continuous() + + theme(axis.text.y = element_text(face = "bold", color = "#993333", + size = 10, hjust = 1),axis.title.y = element_text(size = 10)) + + ggtitle("Graphique 1") + +``` + +```{r } + + library(viridis) + +dataCO2_by_year <- dataCO2 %>% group_by("Year") +ggplot(dataCO2_by_year, aes(dataCO2_by_year$Month,dataCO2_by_year$ObsCO2Comp )) + + geom_line(aes( group = dataCO2_by_year$Year , colour=dataCO2_by_year$Year)) + + xlab("Month")+ + ylab("CO2 Concentration (ppm)") + + ggtitle("Graphique saisonnier") +``` + + + +### Modélisation + +** Doc + +(https://github.com/Peymankor/Data-Science_Portfolio/blob/master/Time%20Series%20Analysis-Historical%20Co2/medium_post.Rmd) + +Série n'est pas stationnaire comme le montre le graphique + +Série montre une saisonnalité voir graphique 2 + +Now, knowing the the non-statinary and seasonality of the data, it suggest to use theseasons differencing to model the data. To answer, + + +* How is Autocorelation function and Partial Auto corellation? + +Here is the plot of ACF and PACF from the *forecast* package: + +```{r} +Co2_train <- ts(dataCO2_by_year$ObsCO2Comp, start = c(1958,3), frequency = 12) +Co2_train %>% ggtsdisplay() +``` + + +```{r} +Co2_train %>% diff(lag=12) %>% diff() %>% ggtsdisplay() +``` \ No newline at end of file diff --git a/module3/exercice3/ConcentrationCO2.html b/module3/exercice3/ConcentrationCO2.html new file mode 100644 index 0000000..d221aef --- /dev/null +++ b/module3/exercice3/ConcentrationCO2.html @@ -0,0 +1,584 @@ + + + + + + + + + + + + + + +Concentration de CO2 dans l’atmosphère depuis 1958 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
+ + + + + + + +
+

Sujet

+

En 1958, Charles David Keeling a initié une mesure de la concentration de CO2 dans l’atmosphère à l’observatoire de Mauna Loa, Hawaii, États-Unis qui continue jusqu’à aujourd’hui. L’objectif initial était d’étudier la variation saisonnière, mais l’intérêt s’est déplacé plus tard vers l’étude de la tendance croissante dans le contexte du changement climatique. En honneur à Keeling, ce jeu de données est souvent appelé “Keeling Curve” (voir (https://en.wikipedia.org/wiki/Keeling_Curve) pour l’histoire et l’importance de ces données).

+

Les données sont disponibles sur le site Web de l’institut Scripps. Utilisez le fichier avec les observations hebdomadaires. Attention, ce fichier est mis à jour régulièrement avec de nouvelles observations. Notez donc bien la date du téléchargement, et gardez une copie locale de la version précise que vous analysez. Faites aussi attention aux données manquantes.

+
+
+

Pré-requis

+

Traitement de suites chronologiques

+

Quelques références:

+ +
+
+

Create dataframe and load R libraries required for the different statistical treatments

+

The data file below contains 10 columns.

+
    +
  • Columns 1-4 give the dates in several redundant formats.
  • +
  • Column 5 below gives monthly Mauna Loa CO2 concentrations in micro-mol CO2 per mole (ppm), reported on the 2008A SIO manometric mole fraction scale. This is thestandard version of the data most often sought. The monthly values have been adjusted to 24:00 hours on the 15th of each month.
    +
  • +
  • Column 6 gives the same data after a seasonal adjustment to remove the quasi-regular seasonal cycle. The adjustment involves subtracting from the data a 4-harmonic fit with a linear gain factor.
    +
  • +
  • Column 7 is a smoothed version of the data generated from a stiff cubic spline function plus 4-harmonic functions with linear gain.
    +
  • +
  • Column 8 is the same smoothed version with the seasonal cycle removed.
    +
  • +
  • Column 9 is identical to Column 5 except that the missing values from Column 5 have been filled with values from Column 7.
    +
  • +
  • Column 10 is identical to Column 6 except missing values have been filled with values from Column 8.
  • +
+

Missing values are denoted by -99.99

+

CO2 concentrations are measured on the ‘08A’ calibration scale

+
library(tidyverse)
+
## Warning: package 'tidyverse' was built under R version 3.5.3
+
## -- Attaching packages -------------------------------------------------------------------------------------------------------------- tidyverse 1.2.1 --
+
## v ggplot2 3.1.0       v purrr   0.3.2  
+## v tibble  2.1.1       v dplyr   0.8.0.1
+## v tidyr   0.8.3       v stringr 1.4.0  
+## v readr   1.3.1       v forcats 0.4.0
+
## Warning: package 'tibble' was built under R version 3.5.3
+
## Warning: package 'tidyr' was built under R version 3.5.3
+
## Warning: package 'readr' was built under R version 3.5.3
+
## Warning: package 'purrr' was built under R version 3.5.3
+
## Warning: package 'dplyr' was built under R version 3.5.3
+
## Warning: package 'stringr' was built under R version 3.5.3
+
## Warning: package 'forcats' was built under R version 3.5.3
+
## -- Conflicts ----------------------------------------------------------------------------------------------------------------- tidyverse_conflicts() --
+## x dplyr::filter() masks stats::filter()
+## x dplyr::lag()    masks stats::lag()
+
library(forecast)
+
## Warning: package 'forecast' was built under R version 3.5.3
+
library(lubridate)
+
## Warning: package 'lubridate' was built under R version 3.5.3
+
## 
+## Attaching package: 'lubridate'
+
## The following object is masked from 'package:base':
+## 
+##     date
+
library(car)
+
## Warning: package 'car' was built under R version 3.5.3
+
## Loading required package: carData
+
## Warning: package 'carData' was built under R version 3.5.2
+
## 
+## Attaching package: 'car'
+
## The following object is masked from 'package:dplyr':
+## 
+##     recode
+
## The following object is masked from 'package:purrr':
+## 
+##     some
+
library(scales)
+
## 
+## Attaching package: 'scales'
+
## The following object is masked from 'package:purrr':
+## 
+##     discard
+
## The following object is masked from 'package:readr':
+## 
+##     col_factor
+
library(patchwork)
+
## Warning: package 'patchwork' was built under R version 3.5.3
+
library(kableExtra)
+
## Warning: package 'kableExtra' was built under R version 3.5.3
+
## 
+## Attaching package: 'kableExtra'
+
## The following object is masked from 'package:dplyr':
+## 
+##     group_rows
+
dataCO2 <- read.csv("monthly_in_situ_co2_mlo.csv", sep="," ,skip = 57)
+colnames(dataCO2) <- c("Year", "Month","Date1", "Date2", "ObsCO2", "SeasAdjCO2","SplineAdjCO2", "SplineAdjCO2Trend", "ObsCO2Comp", "SeasAdjCO2Comp")
+summary(dataCO2)
+
##       Year          Month            Date1           Date2     
+##  Min.   :1958   Min.   : 1.000   Min.   :21231   Min.   :1958  
+##  1st Qu.:1973   1st Qu.: 4.000   1st Qu.:26968   1st Qu.:1974  
+##  Median :1989   Median : 7.000   Median :32704   Median :1990  
+##  Mean   :1989   Mean   : 6.507   Mean   :32705   Mean   :1990  
+##  3rd Qu.:2005   3rd Qu.: 9.500   3rd Qu.:38442   3rd Qu.:2005  
+##  Max.   :2020   Max.   :12.000   Max.   :44180   Max.   :2021  
+##      ObsCO2         SeasAdjCO2      SplineAdjCO2    SplineAdjCO2Trend
+##  Min.   :-99.99   Min.   :-99.99   Min.   :-99.99   Min.   :-99.99   
+##  1st Qu.:328.40   1st Qu.:328.70   1st Qu.:328.46   1st Qu.:328.82   
+##  Median :351.34   Median :352.13   Median :351.33   Median :352.03   
+##  Mean   :346.18   Mean   :346.18   Mean   :348.95   Mean   :348.95   
+##  3rd Qu.:377.55   3rd Qu.:377.35   3rd Qu.:377.69   3rd Qu.:377.37   
+##  Max.   :414.83   Max.   :413.33   Max.   :414.94   Max.   :413.35   
+##    ObsCO2Comp     SeasAdjCO2Comp  
+##  Min.   :-99.99   Min.   :-99.99  
+##  1st Qu.:328.40   1st Qu.:328.70  
+##  Median :351.34   Median :352.13  
+##  Mean   :348.96   Mean   :348.95  
+##  3rd Qu.:377.55   3rd Qu.:377.35  
+##  Max.   :414.83   Max.   :413.33
+
dataCO2$Date <- ymd(paste0(dataCO2$Year, " ", dataCO2$Month, " ", "15"))
+

** Remplacement dans la série des valeurs observées, des valeurs manquantes -99.99 par celles qui sont interpolées ** on enlève ensuite les observations manquantes

+
dataCO2 <- dataCO2[dataCO2$ObsCO2Comp != "-99.99", ]
+

** Create a column Date with format YYYY MM DD

+
dataCO2$Date <- ymd(paste0(dataCO2$Year, "-", dataCO2$Month, "-", "15"))
+
+
+

Représentation des résultats

+
ggplot(dataCO2,aes(Date, dataCO2$ObsCO2Comp)) +
+    geom_line(color='orange') +
+    xlab("Year, Month") +
+    scale_x_date(date_labels = "%Y-%m", date_breaks = "5 year") +
+    theme(axis.text.x = element_text(face = "bold", color = "#993333", 
+                           size = 12, angle = 45, hjust = 1)) +
+    ylab("CO2 Concentration (ppm)") +
+    scale_y_continuous() +
+    theme(axis.text.y = element_text(face = "bold", color = "#993333", 
+                           size = 10, hjust = 1),axis.title.y = element_text(size = 10)) +
+  ggtitle("Graphique 1")
+

+
 library(viridis) 
+
## Loading required package: viridisLite
+
## 
+## Attaching package: 'viridis'
+
## The following object is masked from 'package:scales':
+## 
+##     viridis_pal
+
dataCO2_by_year <- dataCO2 %>% group_by("Year")
+ggplot(dataCO2_by_year, aes(dataCO2_by_year$Month,dataCO2_by_year$ObsCO2Comp )) +
+         geom_line(aes( group = dataCO2_by_year$Year , colour=dataCO2_by_year$Year)) +
+         xlab("Month")+
+         ylab("CO2 Concentration (ppm)") +
+         ggtitle("Graphique saisonnier")
+

+
+
+

Modélisation

+

Série n’est pas stationnaire comme le montre le graphique

+

Série montre une saisonnalité

+
+ + + + +
+ + + + + + + + + + + + + + + diff --git a/module3/exercice3/monthly_in_situ_co2_mlo.csv b/module3/exercice3/monthly_in_situ_co2_mlo.csv new file mode 100644 index 0000000..dff2f65 --- /dev/null +++ b/module3/exercice3/monthly_in_situ_co2_mlo.csv @@ -0,0 +1,813 @@ +------------------------------------------------------------------------------------------- + Atmospheric CO2 concentrations (ppm) derived from in situ air measurements + at Mauna Loa, Observatory, Hawaii: Latitude 19.5°N Longitude 155.6°W Elevation 3397m + + Source: R. F. Keeling, S. J. Walker, S. C. Piper and A. F. Bollenbacher + Scripps CO2 Program ( http://scrippsco2.ucsd.edu ) + Scripps Institution of Oceanography (SIO) + University of California + La Jolla, California USA 92093-0244 + + Status of data and correspondence: + + These data are subject to revision based on recalibration of standard gases. Questions + about the data should be directed to Dr. Ralph Keeling (rkeeling@ucsd.edu), Stephen Walker + (sjwalker@ucsd.edu) and Stephen Piper (scpiper@ucsd.edu), Scripps CO2 Program. + + Baseline data in this file through 17-Apr-2020 from archive dated 20-Apr-2020 08:06:03 + +------------------------------------------------------------------------------------------- + + Please cite as: + + C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and + H. A. Meijer, Exchanges of atmospheric CO2 and 13CO2 with the terrestrial biosphere and + oceans from 1978 to 2000. I. Global aspects, SIO Reference Series, No. 01-06, Scripps + Institution of Oceanography, San Diego, 88 pages, 2001. + + If it is necessary to cite a peer-reviewed article, please cite as: + + C. D. Keeling, S. C. Piper, R. B. Bacastow, M. Wahlen, T. P. Whorf, M. Heimann, and + H. A. Meijer, Atmospheric CO2 and 13CO2 exchange with the terrestrial biosphere and + oceans from 1978 to 2000: observations and carbon cycle implications, pages 83-113, +" in A History of Atmospheric CO2 and its effects on Plants, Animals, and Ecosystems"", """ + editors, Ehleringer, J.R., T. E. Cerling, M. D. Dearing, Springer Verlag, + New York, 2005. + +------------------------------------------------------------------------------------------- + + The data file below contains 10 columns. Columns 1-4 give the dates in several redundant + formats. Column 5 below gives monthly Mauna Loa CO2 concentrations in micro-mol CO2 per + mole (ppm), reported on the 2008A SIO manometric mole fraction scale. This is the + standard version of the data most often sought. The monthly values have been adjusted + to 24:00 hours on the 15th of each month. Column 6 gives the same data after a seasonal + adjustment to remove the quasi-regular seasonal cycle. The adjustment involves + subtracting from the data a 4-harmonic fit with a linear gain factor. Column 7 is a + smoothed version of the data generated from a stiff cubic spline function plus 4-harmonic + functions with linear gain. Column 8 is the same smoothed version with the seasonal + cycle removed. Column 9 is identical to Column 5 except that the missing values from + Column 5 have been filled with values from Column 7. Column 10 is identical to Column 6 + except missing values have been filled with values from Column 8. Missing values are + denoted by -99.99 + + CO2 concentrations are measured on the '08A' calibration scale + + Yr, Mn, Date, Date, CO2,seasonally, fit, seasonally, CO2, seasonally + , , , , , adjusted, ,adjusted fit, filled,adjusted filled + , , Excel, , [ppm], [ppm] , [ppm], [ppm], [ppm], [ppm] +1958, 01, 21200, 1958.0411, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +1958, 02, 21231, 1958.1260, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +1958, 03, 21259, 1958.2027, 315.70, 314.44, 316.18, 314.91, 315.70, 314.44 +1958, 04, 21290, 1958.2877, 317.46, 315.16, 317.30, 314.99, 317.46, 315.16 +1958, 05, 21320, 1958.3699, 317.51, 314.71, 317.86, 315.06, 317.51, 314.71 +1958, 06, 21351, 1958.4548, -99.99, -99.99, 317.24, 315.14, 317.24, 315.14 +1958, 07, 21381, 1958.5370, 315.86, 315.19, 315.86, 315.22, 315.86, 315.19 +1958, 08, 21412, 1958.6219, 314.93, 316.19, 314.00, 315.29, 314.93, 316.19 +1958, 09, 21443, 1958.7068, 313.21, 316.08, 312.46, 315.35, 313.21, 316.08 +1958, 10, 21473, 1958.7890, -99.99, -99.99, 312.44, 315.41, 312.44, 315.41 +1958, 11, 21504, 1958.8740, 313.33, 315.20, 313.61, 315.46, 313.33, 315.20 +1958, 12, 21534, 1958.9562, 314.67, 315.43, 314.77, 315.51, 314.67, 315.43 +1959, 01, 21565, 1959.0411, 315.58, 315.54, 315.62, 315.57, 315.58, 315.54 +1959, 02, 21596, 1959.1260, 316.49, 315.86, 316.27, 315.63, 316.49, 315.86 +1959, 03, 21624, 1959.2027, 316.65, 315.38, 316.98, 315.69, 316.65, 315.38 +1959, 04, 21655, 1959.2877, 317.72, 315.42, 318.09, 315.77, 317.72, 315.42 +1959, 05, 21685, 1959.3699, 318.29, 315.49, 318.65, 315.85, 318.29, 315.49 +1959, 06, 21716, 1959.4548, 318.15, 316.03, 318.04, 315.94, 318.15, 316.03 +1959, 07, 21746, 1959.5370, 316.54, 315.86, 316.68, 316.03, 316.54, 315.86 +1959, 08, 21777, 1959.6219, 314.80, 316.06, 314.83, 316.12, 314.80, 316.06 +1959, 09, 21808, 1959.7068, 313.84, 316.73, 313.31, 316.22, 313.84, 316.73 +1959, 10, 21838, 1959.7890, 313.33, 316.33, 313.33, 316.31, 313.33, 316.33 +1959, 11, 21869, 1959.8740, 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389.34, 389.73, 388.98, 390.08, 389.34 +2010, 03, 40252, 2010.2027, 391.01, 389.51, 390.70, 389.18, 391.01, 389.51 +2010, 04, 40283, 2010.2877, 392.38, 389.66, 392.13, 389.39, 392.38, 389.66 +2010, 05, 40313, 2010.3699, 393.22, 389.90, 392.90, 389.58, 393.22, 389.90 +2010, 06, 40344, 2010.4548, 392.24, 389.73, 392.25, 389.76, 392.24, 389.73 +2010, 07, 40374, 2010.5370, 390.33, 389.53, 390.70, 389.94, 390.33, 389.53 +2010, 08, 40405, 2010.6219, 388.52, 390.01, 388.58, 390.11, 388.52, 390.01 +2010, 09, 40436, 2010.7068, 386.84, 390.25, 386.84, 390.27, 386.84, 390.25 +2010, 10, 40466, 2010.7890, 387.16, 390.70, 386.91, 390.43, 387.16, 390.70 +2010, 11, 40497, 2010.8740, 388.67, 390.88, 388.39, 390.58, 388.67, 390.88 +2010, 12, 40527, 2010.9562, 389.81, 390.71, 389.82, 390.71, 389.81, 390.71 +2011, 01, 40558, 2011.0411, 391.30, 391.25, 390.91, 390.84, 391.30, 391.25 +2011, 02, 40589, 2011.1260, 391.92, 391.18, 391.73, 390.97, 391.92, 391.18 +2011, 03, 40617, 2011.2027, 392.45, 390.95, 392.61, 391.09, 392.45, 390.95 +2011, 04, 40648, 2011.2877, 393.37, 390.63, 393.98, 391.23, 393.37, 390.63 +2011, 05, 40678, 2011.3699, 394.28, 390.95, 394.69, 391.37, 394.28, 390.95 +2011, 06, 40709, 2011.4548, 393.69, 391.18, 394.02, 391.53, 393.69, 391.18 +2011, 07, 40739, 2011.5370, 392.59, 391.79, 392.46, 391.69, 392.59, 391.79 +2011, 08, 40770, 2011.6219, 390.21, 391.71, 390.33, 391.87, 390.21, 391.71 +2011, 09, 40801, 2011.7068, 389.00, 392.43, 388.60, 392.05, 389.00, 392.43 +2011, 10, 40831, 2011.7890, 388.93, 392.48, 388.69, 392.22, 388.93, 392.48 +2011, 11, 40862, 2011.8740, 390.24, 392.46, 390.21, 392.41, 390.24, 392.46 +2011, 12, 40892, 2011.9562, 391.80, 392.71, 391.69, 392.58, 391.80, 392.71 +2012, 01, 40923, 2012.0410, 393.07, 393.02, 392.83, 392.77, 393.07, 393.02 +2012, 02, 40954, 2012.1257, 393.35, 392.61, 393.71, 392.96, 393.35, 392.61 +2012, 03, 40983, 2012.2049, 394.36, 392.82, 394.69, 393.14, 394.36, 392.82 +2012, 04, 41014, 2012.2896, 396.43, 393.66, 396.12, 393.34, 396.43, 393.66 +2012, 05, 41044, 2012.3716, 396.87, 393.53, 396.87, 393.54, 396.87, 393.53 +2012, 06, 41075, 2012.4563, 395.88, 393.38, 396.23, 393.76, 395.88, 393.38 +2012, 07, 41105, 2012.5383, 394.52, 393.75, 394.71, 393.98, 394.52, 393.75 +2012, 08, 41136, 2012.6230, 392.54, 394.07, 392.64, 394.21, 392.54, 394.07 +2012, 09, 41167, 2012.7077, 391.13, 394.57, 390.99, 394.45, 391.13, 394.57 +2012, 10, 41197, 2012.7896, 391.01, 394.56, 391.15, 394.69, 391.01, 394.56 +2012, 11, 41228, 2012.8743, 392.95, 395.17, 392.74, 394.93, 392.95, 395.17 +2012, 12, 41258, 2012.9563, 394.33, 395.24, 394.27, 395.16, 394.33, 395.24 +2013, 01, 41289, 2013.0411, 395.61, 395.55, 395.46, 395.40, 395.61, 395.55 +2013, 02, 41320, 2013.1260, 396.85, 396.10, 396.38, 395.62, 396.85, 396.10 +2013, 03, 41348, 2013.2027, 397.26, 395.75, 397.35, 395.82, 397.26, 395.75 +2013, 04, 41379, 2013.2877, 398.35, 395.60, 398.80, 396.04, 398.35, 395.60 +2013, 05, 41409, 2013.3699, 399.98, 396.63, 399.58, 396.24, 399.98, 396.63 +2013, 06, 41440, 2013.4548, 398.87, 396.34, 398.95, 396.44, 398.87, 396.34 +2013, 07, 41470, 2013.5370, 397.37, 396.56, 397.40, 396.63, 397.37, 396.56 +2013, 08, 41501, 2013.6219, 395.41, 396.92, 395.28, 396.82, 395.41, 396.92 +2013, 09, 41532, 2013.7068, 393.39, 396.84, 393.55, 397.01, 393.39, 396.84 +2013, 10, 41562, 2013.7890, 393.70, 397.26, 393.64, 397.19, 393.70, 397.26 +2013, 11, 41593, 2013.8740, 395.19, 397.43, 395.16, 397.37, 395.19, 397.43 +2013, 12, 41623, 2013.9562, 396.82, 397.73, 396.65, 397.54, 396.82, 397.73 +2014, 01, 41654, 2014.0411, 397.93, 397.87, 397.78, 397.71, 397.93, 397.87 +2014, 02, 41685, 2014.1260, 398.10, 397.35, 398.64, 397.88, 398.10, 397.35 +2014, 03, 41713, 2014.2027, 399.47, 397.95, 399.57, 398.03, 399.47, 397.95 +2014, 04, 41744, 2014.2877, 401.33, 398.57, 400.97, 398.20, 401.33, 398.57 +2014, 05, 41774, 2014.3699, 401.88, 398.52, 401.71, 398.36, 401.88, 398.52 +2014, 06, 41805, 2014.4548, 401.31, 398.77, 401.03, 398.52, 401.31, 398.77 +2014, 07, 41835, 2014.5370, 399.07, 398.26, 399.45, 398.67, 399.07, 398.26 +2014, 08, 41866, 2014.6219, 397.21, 398.72, 397.29, 398.84, 397.21, 398.72 +2014, 09, 41897, 2014.7068, 395.40, 398.86, 395.53, 399.00, 395.40, 398.86 +2014, 10, 41927, 2014.7890, 395.65, 399.23, 395.61, 399.17, 395.65, 399.23 +2014, 11, 41958, 2014.8740, 397.23, 399.46, 397.13, 399.34, 397.23, 399.46 +2014, 12, 41988, 2014.9562, 398.79, 399.70, 398.62, 399.52, 398.79, 399.70 +2015, 01, 42019, 2015.0411, 399.85, 399.80, 399.77, 399.70, 399.85, 399.80 +2015, 02, 42050, 2015.1260, 400.31, 399.56, 400.65, 399.89, 400.31, 399.56 +2015, 03, 42078, 2015.2027, 401.51, 399.99, 401.61, 400.07, 401.51, 399.99 +2015, 04, 42109, 2015.2877, 403.45, 400.69, 403.06, 400.28, 403.45, 400.69 +2015, 05, 42139, 2015.3699, 404.10, 400.73, 403.86, 400.49, 404.10, 400.73 +2015, 06, 42170, 2015.4548, 402.88, 400.33, 403.25, 400.73, 402.88, 400.33 +2015, 07, 42200, 2015.5370, 401.61, 400.80, 401.75, 400.97, 401.61, 400.80 +2015, 08, 42231, 2015.6219, 399.00, 400.52, 399.69, 401.25, 399.00, 400.52 +2015, 09, 42262, 2015.7068, 397.50, 400.96, 398.06, 401.55, 397.50, 400.96 +2015, 10, 42292, 2015.7890, 398.28, 401.87, 398.27, 401.85, 398.28, 401.87 +2015, 11, 42323, 2015.8740, 400.24, 402.49, 399.95, 402.17, 400.24, 402.49 +2015, 12, 42353, 2015.9562, 401.89, 402.81, 401.58, 402.48, 401.89, 402.81 +2016, 01, 42384, 2016.0410, 402.65, 402.60, 402.87, 402.80, 402.65, 402.60 +2016, 02, 42415, 2016.1257, 404.16, 403.41, 403.87, 403.11, 404.16, 403.41 +2016, 03, 42444, 2016.2049, 404.85, 403.30, 404.96, 403.39, 404.85, 403.30 +2016, 04, 42475, 2016.2896, 407.57, 404.77, 406.49, 403.67, 407.57, 404.77 +2016, 05, 42505, 2016.3716, 407.66, 404.28, 407.30, 403.92, 407.66, 404.28 +2016, 06, 42536, 2016.4563, 407.00, 404.48, 406.67, 404.16, 407.00, 404.48 +2016, 07, 42566, 2016.5383, 404.50, 403.72, 405.13, 404.38, 404.50, 403.72 +2016, 08, 42597, 2016.6230, 402.24, 403.79, 403.01, 404.60, 402.24, 403.79 +2016, 09, 42628, 2016.7077, 401.01, 404.50, 401.32, 404.83, 401.01, 404.50 +2016, 10, 42658, 2016.7896, 401.50, 405.09, 401.46, 405.04, 401.50, 405.09 +2016, 11, 42689, 2016.8743, 403.64, 405.88, 403.02, 405.25, 403.64, 405.88 +2016, 12, 42719, 2016.9563, 404.55, 405.47, 404.54, 405.44, 404.55, 405.47 +2017, 01, 42750, 2017.0411, 406.07, 406.02, 405.69, 405.63, 406.07, 406.02 +2017, 02, 42781, 2017.1260, 406.64, 405.89, 406.57, 405.81, 406.64, 405.89 +2017, 03, 42809, 2017.2027, 407.05, 405.52, 407.51, 405.97, 407.05, 405.52 +2017, 04, 42840, 2017.2877, 408.95, 406.17, 408.93, 406.13, 408.95, 406.17 +2017, 05, 42870, 2017.3699, 409.91, 406.52, 409.68, 406.29, 409.91, 406.52 +2017, 06, 42901, 2017.4548, 409.12, 406.55, 408.99, 406.45, 409.12, 406.55 +2017, 07, 42931, 2017.5370, 407.20, 406.38, 407.39, 406.61, 407.20, 406.38 +2017, 08, 42962, 2017.6219, 405.24, 406.76, 405.20, 406.76, 405.24, 406.76 +2017, 09, 42993, 2017.7068, 403.27, 406.75, 403.41, 406.92, 403.27, 406.75 +2017, 10, 43023, 2017.7890, 403.64, 407.25, 403.47, 407.07, 403.64, 407.25 +2017, 11, 43054, 2017.8740, 405.17, 407.43, 404.99, 407.22, 405.17, 407.43 +2017, 12, 43084, 2017.9562, 406.75, 407.68, 406.46, 407.37, 406.75, 407.68 +2018, 01, 43115, 2018.0411, 408.05, 408.00, 407.58, 407.52, 408.05, 408.00 +2018, 02, 43146, 2018.1260, 408.34, 407.59, 408.44, 407.68, 408.34, 407.59 +2018, 03, 43174, 2018.2027, 409.25, 407.72, 409.38, 407.82, 409.25, 407.72 +2018, 04, 43205, 2018.2877, 410.30, 407.51, 410.81, 408.00, 410.30, 407.51 +2018, 05, 43235, 2018.3699, 411.30, 407.90, 411.60, 408.20, 411.30, 407.90 +2018, 06, 43266, 2018.4548, 410.88, 408.31, 410.96, 408.42, 410.88, 408.31 +2018, 07, 43296, 2018.5370, 408.90, 408.08, 409.43, 408.65, 408.90, 408.08 +2018, 08, 43327, 2018.6219, 407.10, 408.63, 407.34, 408.91, 407.10, 408.63 +2018, 09, 43358, 2018.7068, 405.59, 409.09, 405.67, 409.18, 405.59, 409.09 +2018, 10, 43388, 2018.7890, 405.99, 409.62, 405.84, 409.45, 405.99, 409.62 +2018, 11, 43419, 2018.8740, 408.12, 410.38, 407.48, 409.72, 408.12, 410.38 +2018, 12, 43449, 2018.9562, 409.23, 410.15, 409.08, 409.98, 409.23, 410.15 +2019, 01, 43480, 2019.0411, 410.92, 410.87, 410.30, 410.24, 410.92, 410.87 +2019, 02, 43511, 2019.1260, 411.66, 410.90, 411.25, 410.48, 411.66, 410.90 +2019, 03, 43539, 2019.2027, 412.00, 410.46, 412.25, 410.70, 412.00, 410.46 +2019, 04, 43570, 2019.2877, 413.52, 410.72, 413.74, 410.92, 413.52, 410.72 +2019, 05, 43600, 2019.3699, 414.83, 411.42, 414.55, 411.14, 414.83, 411.42 +2019, 06, 43631, 2019.4548, 413.96, 411.38, 413.91, 411.36, 413.96, 411.38 +2019, 07, 43661, 2019.5370, 411.85, 411.03, 412.36, 411.57, 411.85, 411.03 +2019, 08, 43692, 2019.6219, 410.08, 411.62, 410.22, 411.80, 410.08, 411.62 +2019, 09, 43723, 2019.7068, 408.55, 412.06, 408.50, 412.03, 408.55, 412.06 +2019, 10, 43753, 2019.7890, 408.43, 412.06, 408.63, 412.25, 408.43, 412.06 +2019, 11, 43784, 2019.8740, 410.28, 412.56, 410.23, 412.48, 410.28, 412.56 +2019, 12, 43814, 2019.9562, 411.85, 412.78, 411.79, 412.70, 411.85, 412.78 +2020, 01, 43845, 2020.0410, 413.37, 413.32, 412.98, 412.92, 413.37, 413.32 +2020, 02, 43876, 2020.1257, 414.09, 413.33, 413.91, 413.14, 414.09, 413.33 +2020, 03, 43905, 2020.2049, 414.51, 412.94, 414.94, 413.35, 414.51, 412.94 +2020, 04, 43936, 2020.2896, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 05, 43966, 2020.3716, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 06, 43997, 2020.4563, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 07, 44027, 2020.5383, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 08, 44058, 2020.6230, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 09, 44089, 2020.7077, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 10, 44119, 2020.7896, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 11, 44150, 2020.8743, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 +2020, 12, 44180, 2020.9563, -99.99, -99.99, -99.99, -99.99, -99.99, -99.99 -- 2.18.1