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Descrizione
English: Opinion polling for the 2020 Croatian parliamentary election using local regressions (LOESS)
Code template: https://gitlab.com/gbuvn1/opinion-polling-graph
ggplot.R 
Sys.setlocale("LC_TIME", "English")
library(ggplot2)
library(anytime)
library(tidyverse)
library(svglite)

polls <- read.table("CAT.csv", header=T, sep=",", fileEncoding="UTF-8", stringsAsFactor=F)
polls$polldate <- as.Date(anydate(polls$polldate))

spansize <- 0.1            # general smoothing parameter for trend line
startdate <- '2016-09-11'   # date of previous election
enddate <- '2020-07-05'     # (latest) date of next election

# retrieve party names from CSV
party1 <- colnames(polls)[2]
party2 <- colnames(polls)[3]
party3 <- colnames(polls)[4]
party4 <- colnames(polls)[5]
party5 <- colnames(polls)[6]
party6 <- colnames(polls)[7]
party7 <- colnames(polls)[8]
party8 <- colnames(polls)[9]
party9 <- colnames(polls)[10]
party10 <- colnames(polls)[11]
party11 <- colnames(polls)[12]
party12 <- colnames(polls)[13]
party13 <- colnames(polls)[14]
party14 <- colnames(polls)[15]
party15 <- colnames(polls)[16]
party16 <- colnames(polls)[17]

# define party colors (taken from https://en.wikipedia.org/wiki/Category:Germany_political_party_colour_templates)
col1 <- '#295BA5'
col2 <- '#ED1C24'
col3 <- '#E95826'
col4 <- '#FFD10C'
col5 <- '#609F44'
col6 <- '#00A950'
col7 <- '#23274D'
col8 <- '#FF931E'
col9 <- '#0AAF4C'
col10 <- '#5BA5D6'
col11 <- '#0081C7'
col12 <- '#08457E'
col13 <- '#026399'
col14 <- '#202124'
col15 <- '#9370db'
col16 <- '#B01324'

transp <-'55'       # transparency level of points

graph <- ggplot(polls)+
  geom_vline(xintercept = as.Date(startdate), color='#aaaaaabb')+       # vertical line (last election)
  geom_vline(xintercept = as.Date(enddate), color='#aaaaaabb')+         # vertical line (next election)
  # add poll points
  geom_point(aes_string(x='polldate',y=party1),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col1,transp),fill=paste0(col1,transp))+
  geom_point(aes_string(x='polldate',y=party2),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col2,transp),fill=paste0(col2,transp))+
  geom_point(aes_string(x='polldate',y=party3),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col3,transp),fill=paste0(col3,transp))+
  geom_point(aes_string(x='polldate',y=party4),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col4,transp),fill=paste0(col4,transp))+
  geom_point(aes_string(x='polldate',y=party5),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col5,transp),fill=paste0(col5,transp))+
  geom_point(aes_string(x='polldate',y=party6),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col6,transp),fill=paste0(col6,transp))+
  geom_point(aes_string(x='polldate',y=party7),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col7,transp),fill=paste0(col7,transp))+
  geom_point(aes_string(x='polldate',y=party8),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col8,transp),fill=paste0(col8,transp))+
  geom_point(aes_string(x='polldate',y=party9),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col9,transp),fill=paste0(col9,transp))+
  geom_point(aes_string(x='polldate',y=party10),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col10,transp),fill=paste0(col10,transp))+
  geom_point(aes_string(x='polldate',y=party11),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col11,transp),fill=paste0(col11,transp))+
  geom_point(aes_string(x='polldate',y=party12),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col12,transp),fill=paste0(col12,transp))+
  geom_point(aes_string(x='polldate',y=party13),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col13,transp),fill=paste0(col13,transp))+
  geom_point(aes_string(x='polldate',y=party14),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col14,transp),fill=paste0(col14,transp))+
  geom_point(aes_string(x='polldate',y=party15),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col15,transp),fill=paste0(col15,transp))+
  geom_point(aes_string(x='polldate',y=party16),size=ifelse(polls$polldate==startdate | polls$polldate==enddate,3,1.5),shape=ifelse(polls$polldate==startdate | polls$polldate==enddate,23,21),color=paste0(col16,transp),fill=paste0(col16,transp))+
  # add trend lines
  # the "span" (smoothing parameter) should be manually changed for individual parties that have less polling data
  geom_smooth(aes_string(x='polldate',y=party1,color=shQuote('col1')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party2,color=shQuote('col2')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party3,color=shQuote('col3')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party4,color=shQuote('col4')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party5,color=shQuote('col5')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party6,color=shQuote('col6')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party7,color=shQuote('col7')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party8,color=shQuote('col8')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party9,color=shQuote('col9')),span=spansize,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party10,color=shQuote('col10')),span=0.4,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party11,color=shQuote('col11')),span=0.3,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party12,color=shQuote('col12')),span=0.3,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party13,color=shQuote('col13')),span=0.5,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party14,color=shQuote('col14')),span=0.5,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party15,color=shQuote('col15')),span=0.7,se=FALSE)+
  geom_smooth(aes_string(x='polldate',y=party16,color=shQuote('col16')),span=0.7,se=FALSE)+
  scale_y_continuous(labels = function(x) paste0(x, "%"),limits=c(0,45))+    # add %, manual limits on y-axis
  scale_x_date(limits = as.Date(c(startdate,enddate)), date_minor_breaks = "1 months", date_breaks = "3 months", date_labels = "%b %Y")+    # grid: 1 month, labels: 3 months
  labs(x = "", y = "")+
  scale_color_manual(name="",
                     breaks = c('col1','col2','col3','col4','col5','col6','col7','col8','col9','col10','col11','col12','col13','col14','col15','col16'),
                     labels = c(party1,party2,party3,party4,party5,party6,party7,party8,party9,party10,party11,party12,party13,party14,party15,party16),
                     values = c('col1'=col1,'col2'=col2,'col3'=col3,'col4'=col4,'col5'=col5,'col6'=col6,'col7'=col7,'col8'=col8,'col9'=col9,'col10'=col10,'col11'=col11,'col12'=col12,'col13'=col13,'col14'=col14,'col15'=col15,'col16'=col16))+
  # legend appearance
  theme(
    axis.text.x = element_text(size = 11),
    axis.text.y = element_text(size = 12),
    axis.title.y = element_text(size = 16),
    legend.position="right",
    legend.key.width=unit(24, "pt"),
    legend.key.height=unit(24, "pt"),
    legend.text = element_text(size=16, margin = margin(b = 5, t = 5, unit = "pt")))

graph + theme()

ggsave(file="polls.svg", plot=graph, width=18, height=8)

# workaround since svglite doesn't properly work in Wikipedia
aaa=readLines("polls.svg",-1)
bbb <- gsub(".svglite ", "", aaa)
writeLines(bbb,"polls.svg")
CAT.csv 
polldate,HDZ,SDP,Most,ZZ,BM365,IDS,Pametno,HNS-LD,HSS,SSIP,GLAS,NHR,NLMK,Hrast-HS,DPMS,ZL
2020-07-05,37.26,24.87,7.39,2.26,0.59,,3.98,1.30,,,,0.44,,,10.89,6.99
2020-07-02,29.8,30,5.4,1.5,,,,,,,,,,,10.5,
2020-06-29,36.4,45,4.3,0,,,,,,,,,,,12.1,
2020-07-04,27.8,25.9,6.7,0.4,,,,,,,,,,,11.6,
2020-06-26,26.7,24.6,6.8,3.3,0.5,,4.1,0.6,,,,,,,11.1,4.5
2020-06-07,26.6,28.6,4.1,1.7,1,,1.8,1.1,,1.9,,,,,13.5,2.4
2020-05-25,28,24.9,4.8,1.9,0.7,1.8,2.4,0.7,,2.2,,,,,13.5,2.6
2020-05-20,29.7,32.8,4.3,0.8,1,1.6,1.7,1.7,,,,0.6,,,9.9,
2020-05-10,26.6,31.5,4,1.1,1.1,1.9,1,1.6,,0.5,,0.5,0.6,,10.7,
2020-04-24,27.9,23.2,5.1,1.3,1.1,2.6,2.8,1,1.1,,,,,1.6,10.5,
2020-04-20,29.9,27.4,4.1,1.6,1.4,1.5,1.5,1.3,2.1,0.9,0.8,0.9,1,1.1,9.2,
2020-04-10,26.1,30.7,3.9,1.2,0.9,2,,,,,0.9,1.1,,1.1,12.5,
2020-04-05,28.4,27,3.8,1.9,1.1,1.8,1.2,1.3,2.7,,,,,1,10.9,
2020-03-25,25.2,23.7,4.4,3,1.7,1.6,2.3,1.3,1.3,,,,,,12.5,
2020-03-20,27.3,29.3,3.8,1.1,1.4,1.3,1.3,1.1,2.5,0.8,0.8,0.9,2,1.1,10.5,
2020-03-13,21.4,31,3,1.7,,1.8,,0.6,1.1,,2,2,,,14,
2020-03-08,26.7,29.3,4.8,1.2,1.4,1.3,1.1,1.2,2.3,0.9,0.7,0.9,2,0.9,11.5,
2020-02-25,24.8,25.4,4.4,1.7,2,2.9,2.1,0.7,2.5,1.3,,0.1,,1.4,10.1,
2020-02-21,26.9,29.1,3.9,1.1,1.3,1.1,1.3,1.2,2.4,0.8,0.8,1.1,2.5,2.1,9.9,
2020-02-14,21.7,30.3,3.8,1.1,,2,,,1.2,,1.8,1.8,,,11.6,
2020-02-06,26.8,28.9,5.1,1,1.4,1.3,1.3,1.3,2.3,0.9,0.6,0.9,2.5,2.2,9.4,
2020-01-24,25.6,27.1,3,2,,0.9,2.1,0.1,1.3,1,1.4,,,1.7,16.6,
2020-01-17,22,28.9,4,3.7,,1.4,,,1.7,,,1.6,,1.3,10.9,
2020-01-12,26.9,27.8,5.6,2.1,1.4,1.3,1.3,1.7,3,0.7,0.5,0.7,3,3.9,,
2019-12-25,25.2,21.5,3.7,4.7,2.5,1.5,2.9,1.4,2.4,2.5,1.1,,5.7,2.5,,
2019-12-20,27,24.8,4.4,,,,,,3.1,,,,5.7,4.7,,
2019-12-11,27.3,25.2,6.2,1.5,1.7,1.4,1.1,2,3.1,0.6,0.6,0.7,6.6,3.2,,
2019-11-26,27.1,20.7,3.4,3.9,4.2,1.9,2,1.3,2.3,1,,1.6,6.9,,,
2019-11-20,27.5,25.4,5.8,1.8,2,1.4,1,1.7,3.5,0.9,0.8,1.4,7.6,3.5,,
2019-11-17,25.7,26.9,4.8,2.8,,1.3,1.3,,,,,2.4,5,,,
2019-11-10,27.9,24.8,5.7,2.8,2,1.3,,2.1,3.4,,,1.3,6.2,1.5,,
2019-10-28,24.8,28.2,4.9,2.9,,1.8,,0.5,,,,2.1,2.8,,,
2019-10-25,28.1,21.5,5,4.9,3.6,2.1,1.8,1.3,2.4,1.3,0.2,1.1,5.3,1.2,,
2019-10-20,27.4,24.6,5.6,1.8,1.9,1.3,0.7,1.7,3.3,1.1,0.9,2.2,6,1.4,,
2019-10-06,27.4,24.3,5.5,1.9,2,,,1.7,3.5,,,2.2,6.1,,,
2019-09-26,27.1,20.3,5.7,4,4.2,2.3,2,1.6,2.6,1.2,0.1,1.5,6.1,1.6,,
2019-09-20,27.6,24.8,5.1,2.2,,,,,3.1,,,2.3,6,,,
2019-09-20,24.9,28.1,3.4,2.2,,1.7,1.1,,,,,2.2,3.2,,,
2019-09-08,27,24.4,5,1.9,1.9,,,1.9,3.3,,,2.6,5.9,,,
2019-08-24,27.4,21,6,3.6,4,2.2,1.9,1.7,2.2,1,,1.5,6.1,1.8,,
2019-08-24,20.9,23.8,3.4,4,,1.7,,1.9,,,,2.9,4,,,
2019-08-04,26.4,22.6,4.7,2.5,1.9,,,2.2,3.4,,1.4,3.4,5.6,,,
2019-07-25,24.2,21.4,5,3.2,3.6,1.8,2.4,0.8,3.4,0.6,1.6,2,6.7,1.6,,
2019-07-15,21.2,23.3,1.9,2.8,,0.9,,,,,0.9,2.7,2.9,,,
2019-07-07,25.5,21.5,4.7,4.3,1.7,,,3.2,3.3,,,4.3,7.2,1.9,,
2019-06-26,24.9,18.3,6.1,6,2.4,2.6,1,2.3,3,0.5,0.4,1.8,10.9,0.6,,
2019-06-17,21,20.5,3.8,5.1,0.7,2,1,0.9,1.3,0.8,2.2,4.2,4.8,0.5,,
2019-06-09,26.5,20.4,4,5.4,2,,2.2,2.9,3.1,0.9,0.9,4.3,7,,,
2019-06-01,19.5,17.4,4.7,5.7,1.4,1.7,,,1.3,1,,4.2,6,5.9,,
2019-05-23,25,13,7.2,11.6,4.7,1.8,3,2.1,2.9,3.8,1.4,3.9,,1.3,,
2019-05-20,27.2,18.1,4.8,7.8,2.9,1.3,1.6,2.8,3.1,2.9,1.9,3.4,3.8,1.6,,
2019-05-08,27.3,17.4,6.6,9.6,3,,,2.8,3.3,2.6,,3.8,2.8,,,
2019-04-25,25.5,13.3,6.5,11.9,3.5,1.7,2.5,2.1,2.8,4.9,2.1,3.1,,,,
2019-04-20,27.6,17.8,7,8.1,2.4,1.1,2.2,2.3,3.2,3.6,2.1,4,3.1,,,
2019-04-07,28,16.9,6.8,8.5,2.6,,,,3.4,3.7,,3.6,2.8,,,
2019-03-25,27,14,6,11.8,4.5,1.7,1.4,1.2,3.2,5.1,1.5,2.2,,,,
2019-03-20,27.8,16.5,6.4,10.6,2.5,1.3,2.4,2.3,3.8,3.2,2.5,3.5,,,,
2019-03-06,28.1,17,6.8,10.4,2.7,,,2.5,3.6,3.4,2.9,3.6,,,,
2019-02-28,26.4,18.1,7.9,10.5,,1.4,1.4,1.2,1.5,4.1,5,5.4,,,,
2019-02-25,28.4,13.7,6.3,12.4,4.2,1.8,1.8,1.8,3.7,5.6,1.5,2,,,,
2019-02-06,28.4,15.8,6.5,10.9,2,1.6,1.6,1.6,3.2,4.6,3.8,3.3,,,,
2019-02-02,27,18.4,6.1,10.9,0.4,1.4,1.5,1.1,1.4,2.4,5.2,6.8,,,,
2019-01-25,28.8,14.3,6.8,13.8,4,1.6,2.6,1.8,3.9,,1.4,1.8,,,,
2019-01-09,29.1,16.1,7.2,13.7,1.9,1.4,1.7,1.7,2.6,,1.5,2.9,,,,
2018-12-28,23.4,17.1,4.8,8.3,1.8,1.7,,0.7,0.9,,2.9,3.2,,,,
2018-12-27,28.4,18.3,6.2,11.1,0.8,1.4,1.4,1.1,0.9,,3.7,5.2,,,,
2018-12-24,28.9,14.8,6.3,14.9,3,1.6,2.5,1.8,3.6,,1.1,1,,,,
2018-12-08,28.1,17,7.3,12.4,2.7,1.5,1.9,2.1,3.1,,1.7,2.7,,,,
2018-11-23,29.3,14.6,6,13.5,3.8,1.5,2.9,2.3,3.6,,,2.1,,,,
2018-11-23,27.2,19.9,6.1,9.2,0.9,1.7,1.9,0.9,0.9,,3,5.5,,,,
2018-11-08,28.4,17.4,6.3,12.1,2.1,1.9,1.9,1.7,3.2,,,,,,,
2018-10-27,26.6,19.8,6.7,9.2,0.5,1.1,1.4,0.9,1.4,,2.5,5.1,,,,
2018-10-25,29.1,16.3,6.6,13.2,3.9,1.8,3.2,1.5,3.3,,,,,,,
2018-10-06,27.5,17.7,6,12.4,2.9,1.7,2.8,1.7,3.5,,,,,,,
2018-09-25,29.2,17.2,8.3,12.6,3.3,2,2.9,1,3.7,,,,,,,
2018-09-21,27.3,20.4,7.3,9.9,0.6,1.1,1.4,0.9,0.6,,3.9,5,,,,
2018-09-08,27.2,18.1,6.8,12.7,3.6,1.4,2.5,1.8,3.3,,,,,,,
2018-08-24,28.9,17.3,7.3,13.4,3.8,2.4,3.1,1.1,4.5,,,,,,,
2018-08-24,24.5,19.7,7.5,9,1.4,1.3,1.7,1,0.9,,2.6,3.2,,,,
2018-08-05,26,18,7.5,13.2,3.1,1.7,2.4,1.9,2.6,,,,,,,
2018-07-26,27.1,18.3,7.8,12.3,3.7,2.7,3.1,1,3,,,,,,,
2018-07-21,25,19.4,6.1,9.6,0.7,1.6,,0.8,0.7,,1.6,4.8,,,,
2018-07-07,25,18.7,7.3,13.4,2.5,1.7,2.3,2,2.1,,,,,,,
2018-06-22,27.6,18.5,7.7,13.8,3.2,2.2,3.2,1.8,2.7,,,,,,,
2018-06-15,23.8,18.5,6.1,10.7,,1.7,1.4,,,,1.8,3.2,,,,
2018-06-07,24.8,19.1,7.8,13.1,2,1.5,1.5,1.9,3,,,,,,,
2018-05-25,26.6,18.2,7.7,14.5,3.5,2.1,3.7,1.4,3.6,,,,,,,
2018-05-24,24.7,20.7,6.9,11.1,,2,,0.4,1.2,,2.5,3.9,,,,
2018-05-06,26.4,20.7,7.6,12.7,2.2,1.7,1.7,2.2,2.4,,,,,,,
2018-04-25,27.6,18,7.1,13.8,3,2.6,2.9,1,4.6,,,,,,,
2018-04-24,25.1,21.2,9.9,12.9,,2,1,1.1,1.3,,1.1,4.6,,,,
2018-04-08,26.8,21.1,8.1,11.2,2,1.6,1.6,1.9,2.1,,,,,,,
2018-03-23,29.5,19.3,7.1,12.9,4.1,2.6,3,2,2.9,,,,,,,
2018-03-17,26.4,22.1,7.9,11.1,1.1,1.5,,0.9,,,2,4,,,,
2018-03-04,28.9,20.8,7.1,10.9,2.2,1.6,1.4,2,2.5,,,,,,,
2018-02-23,29.8,19.8,6.6,12.3,3,2.6,3.3,2.1,2.4,,,,,,,
2018-02-21,28.2,21.9,7.8,12.4,1.5,1.7,,1.8,1,,2.3,3.3,,,,
2018-02-04,29.3,21.1,6.1,11.8,2.2,1.1,1,2,2.9,,,,,,,
2018-01-27,32.7,19,5,9,,1.2,,,,,,1.3,,,,
2018-01-25,30.1,20.9,6.8,13,3.4,2.5,2.4,2.4,2.1,,,,,,,
2018-01-07,29,20.6,7,11.4,2.3,1.2,1.2,1.4,3.2,,,,,,,
2017-12-24,31.9,18.9,7.3,12.4,2.3,1.9,3,2.5,2.7,,,,,,,
2017-12-13,30,21,8.6,11.8,0.7,1.3,,0.7,0.7,,0.7,2,,,,
2017-12-07,30.8,22.3,7.5,11,2.1,1.1,0.5,1.3,3.5,,,,,,,
2017-11-25,24.7,20.2,6.1,4.1,,1.3,,,,,,1.6,,,,
2017-11-24,30.2,21.2,7.5,11.7,3.4,2.4,1.8,2,2.2,,,,,,,
2017-11-05,31.3,22.9,8.7,7.5,2.3,1.8,0.8,1.2,3.1,,,,,,,
2017-11-02,25.4,20,5.3,4.3,,,,,1.2,,,1.1,,,,
2017-10-29,32.5,23.4,6.9,10.5,4.2,2.3,,1,1.9,,,,,,,
2017-10-07,33.5,22.1,7.8,6.6,2.3,1.3,1.5,1.3,2.9,,,,,,,
2017-09-26,31.7,21.7,7.3,8.8,3.9,2.4,1.6,1.1,2.7,,,,,,,
2017-09-23,27.5,19.9,3.8,2.8,,1.1,,,,,1,1.3,,,,
2017-09-06,34,23.1,7.7,6.1,2.3,1.2,1.5,1.6,2.7,,,,,,,
2017-08-26,33.7,23.3,6.7,7.1,4.5,2,1.4,1.3,3,,,,,,,
2017-08-20,28.5,23,,,,,,,,,,,,,,
2017-08-06,34.2,22.1,7.8,6.8,2.6,1.7,1.1,2.2,2.5,,,,,,,
2017-07-25,33.6,22.4,6.2,7.6,4.7,1.7,1.6,1.9,2.7,,,,,,,
2017-07-25,24.3,20.1,3.6,3.3,,1.2,,,,,1.9,2.3,,,,
2017-07-05,34.3,23.8,6.4,6.1,2.2,1.2,1.9,2.5,2.4,,,,,,,
2017-06-26,34.8,22.2,7.4,7.3,3.6,2.6,2,2.4,3.3,,,,,,,
2017-06-25,24.5,20.8,6.6,3.7,1.3,1.8,0.1,0.5,,,,3.2,,,,
2017-06-06,34,24.8,7.2,6.1,1.7,1.8,2,3,2.9,,,,,,,
2017-05-24,33.7,21.7,9.2,7.6,3.3,2.6,2.4,2.8,2.1,,,,,,,
2017-05-20,23.5,19.8,,,,,,,,,,,,,,
2017-05-06,30.8,24.1,10.2,7.6,1.3,1.7,2,3.6,2.3,,,,,,,
2017-04-25,25.4,19,6.4,2.7,1.4,1.8,,2.3,,,,,,,,
2017-04-24,32.2,22.7,7.7,7.9,3,3.2,2.3,2.3,2.4,,,,,,,
2017-04-05,31.3,22.8,9.6,7.1,1.3,1.4,1.9,3.6,2,,,,,,,
2017-03-25,26.2,19.9,6,2.9,1.8,1.9,,2.1,,,,,,,,
2017-03-24,33.3,23,8.6,7.3,3.2,3.1,2.1,2.8,2.3,,,,,,,
2017-03-06,32.8,21.6,8,7.7,1.6,1.6,1.7,3.9,1.9,,,,,,,
2017-02-26,28,19.4,6.5,4.9,,1.2,,2,,,,,,,,
2017-02-24,35.1,21.9,8.6,9,3,2.2,2.1,1.7,3.1,,,,,,,
2017-02-05,34,22.3,7.2,5.8,1.6,1.7,1.4,3.9,2.3,,,,,,,
2017-01-25,33.6,22.4,8.8,9.5,3.7,2,2.1,1.7,3.2,,,,,,,
2017-01-25,37.1,20,7.9,3,,,,,,,,,,,,
2017-01-06,32.5,24.7,8.8,4.7,1.8,1.4,2,3.5,2.1,,,,,,,
2017-01-06,27.7,21,6.3,3,,1.2,0.1,1,,,,,,,,
2016-12-24,33.2,23.2,9.6,7.5,2.3,2.1,1.7,1.7,1.9,,,,,,,
2016-12-06,30.7,19.2,7.8,3.4,,1.1,,,,,,,,,,
2016-12-04,31.3,25.2,8.7,4.5,2,1.7,1.9,3.7,2.4,,,,,,,
2016-11-26,31.3,19.1,7.8,3.6,,1.1,,0.8,0.7,,,,,,,
2016-11-25,33.9,24.2,10.8,7.5,1.4,2.3,2.5,1.4,1.4,,,,,,,
2016-11-06,31.5,25.3,10.1,4.3,2.1,1.6,2,3.1,2.2,,,,,,,
2016-11-05,37.6,18.3,8.3,2.4,,1,,0.4,,,,,,,,
2016-10-25,35.3,25.4,9.9,5.1,4.1,2.6,2.4,2.9,,,,,,,,
2016-10-06,30.6,27,10.8,5.4,1.7,1.4,1.4,2.8,2,,,,,,,
2016-10-05,28.5,19.7,10.2,1.4,,1.4,,1.3,,,,,,,,
2016-09-26,27.8,20.8,10.9,2.3,1.1,1.5,,1.3,0.8,,,,,,,
2016-09-11,36.27,33.45,9.84,6.16,4.05,2.27,2.06,,,,,,,,,
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