theosanderson

SELECT *, count_diff/time_diff AS rate FROM (SELECT petitions.action AS petitition, (countb2-count1) AS count_diff, t2-t1 AS time_diff FROM (SELECT * FROM (SELECT MIN(count) AS count1, petition_id AS pid1 FROM timeseries WHERE count>100000 GROUP BY petition_id) a INNER JOIN (SELECT time AS t1, petition_id AS pid2, count AS count2 FROM timeseries) b ON count1=count2 AND pid1=pid2) first  INNER JOIN (SELECT * FROM (SELECT MIN(count) AS countb1, petition_id AS pidb1 FROM timeseries WHERE count>150000 GROUP BY petition_id) a INNER JOIN (SELECT  time AS t2, petition_id AS pidb2, count AS countb2 FROM timeseries) b ON countb1=countb2 AND pidb1=pidb2) second ON pid1 = pidb1 AND count1 !=countb1 INNER JOIN petitions ON pid1=petitions.id ORDER BY time_diff) c ORDER BY rate DESC

theosanderson

string=[]; for (i in data){string.push(a.date.toString()+","+a.n+"\n")}; string.join("")

theosanderson

perl -0777 -pe 's/\\begin{figure[*]*}.*?\\end{figure[*]*}//gs' paper.tex  | perl -0777 -pe 's/\\begin{table[*]*}.*?\\end{table[*]*}//gs' |   perl -0777 -pe 's/\\%/&percnt;/gs' | perl -0777 -pe 's/%.*?\n//gs' | perl -0777 -pe 's/\n\n/§/gs' | perl -0777 -pe 's/[§\n]+/§\n/gs'  | perl -0777 -pe 's/§\n/<\/p>\n<p>/gs'   | perl -0777 -pe 's/\\textit{(.+?)}/<i>\1<\/i>/gs' | perl -0777 -pe 's/[ ]*\\cite[p]*{(.+?)}/<dt-cite key="\1"><\/dt-cite>/gs' | perl -0777 -pe 's/<p>\\section[*]*{(.+?)}<\/p>/<h2>\1<\/h2>/gs'   | perl -0777 -pe 's/<p>\\subsection[*]*{(.+?)}<\/p>/<h3>\1<\/h3>/gs' > out.html

theosanderson

I work on finding out how to tell your computer what your color is, and what its type, and how it works.

I work on finding out how very small things that don't die can make things we know turn in different ways. We look for things we can tell by looking at what the little things are saying to us.

I work on finding out more about whether it is possible that different animals come from the same place, or whether we have to look at lots and lots of different places to find the different animals.

I work on finding out how often our tiny star bodies are hit by stars outside the big group of stars in the sky.

I work on finding out what causes small cells to not form. We are trying out a new approach to find out which cells are important in the little cells in your blood, stomach, stomach, small heart and brain. We hope to know more about how the number of different kinds of cells can change how big, and if that also has an effect on how well the tiny tiny things stick together to form the big cell.

theosanderson

theosanderson

                                areaName  cases_added
91                              Liverpool        274.0
84                             Lancashire        261.0
85                                  Leeds        231.0
10                             Birmingham        212.0
17                               Bradford        124.0
135                             Sheffield        119.0
14                                 Bolton        101.0
103                   Newcastle upon Tyne         97.0
176                                Wirral         95.0

theosanderson

from uk_covid19 import Cov19API

cases = {
    "date": "date",

    "newCasesBySpecimenDate": "newCasesBySpecimenDate",

}

api = Cov19API(filters=['areaType=utla',f'areaCode=N09000011'], structure=cases)

theosanderson

library(tidyverse)
library(gganimate)
library(lubridate)
data <- read_csv("D:/cases_anim/cog_metadata_microreact_public.csv")

kent <- data %>% filter(latitude==.7334,longitude==51.2245)
data$sample_date = ymd(data$sample_date)

data$diff_days = data$sample_date - ymd("2020-09-01")
data_sub <- data %>% filter(sample_date>"2020-09-01")

theosanderson

library(tidyverse)
library(gganimate)
library(lubridate)
data <-
  read_csv("D:/cases_anim/cog_metadata_microreact_public.csv.txt")
data$sample_date = ymd(data$sample_date)
library(sp)
library('sf')
ltlas <-

theosanderson