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abk, ?, grey | |
ara, day blind, lightyellow | |
aze, night bird, orange | |
bel, leather one, turquoise | |
bos, blind mouse, lightgreen | |
bre, blind mouse, lightblue | |
bul, sticking one, blue | |
cat, winged rat, yellow | |
cau, ?, grey | |
ces, night flyer, lightgreen |
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import matplotlib.pyplot as plt | |
unique = [] | |
check = [] | |
k = 50 #These need to be estimated for particular languages but this is a base estimate | |
b=0.4 # | |
for x in range(1, 100000, 100): | |
unique.append(k*(x**b)) | |
check.append(x) |
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import pdfplumber | |
def is_bold_font(char): | |
return "bold" in char['fontname'].lower() | |
def parse_pdf_to_dictionary(pdf_path): | |
term_definition_dict = {} | |
term = "" | |
next_term = "" | |
definition = "" |
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Year | Language | taxis | iso | |
---|---|---|---|---|
1505 | Latin | 1 | va | |
1543 | Italian | 1 | it | |
1557 | Latin | 1 | va | |
1558 | German | 1 | de | |
1562 | German | 1 | de | |
1562 | German | 1 | de | |
1564 | French | 1 | fr | |
1570 | English | 1 | gb | |
1572 | Latin | 1 | va |
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objects <-c('Truman','Eisenhower','Kennedy','Johnson','Nixon','Ford','Carter','Reagan','Bush','Clinton','G. W. Bush','Obama','Trump','Biden') | |
#'FDR', 0.796, | |
performance <- c(0.319,0.165,0.206,0.172,0.170,0.188,0.219,0.130,0.113,0.105,0.099,0.094,0.15,0.165) | |
color<-c('#0015BC', '#E9141D', '#0015BC', '#0015BC', '#E9141D', '#E9141D', '#0015BC', '#E9141D', '#E9141D', '#0015BC', '#E9141D', '#0015BC','#E9141D','#0015BC') | |
df<- data.frame(objects, performance, color) | |
#lock in order |
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library(dplyr) | |
library(lubridate) | |
library(tidyverse) | |
gridwatch <- | |
read_csv( | |
file = "gridwatch.csv") | |
#get date int data format |
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get data from https://www.met.ie/climate/available-data/historical-data | |
for Dublin airport | |
```{r} | |
dub<-read_csv('dly532.csv', skip=25, col_names = TRUE) | |
head(dub) | |
``` | |
date looks like 01-jan-1942 | |
separate it out into 3 columns |
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#choose or open the file directly | |
f <- file.choose() | |
library(dplyr) | |
trust <- read.csv(f) | |
#trust <- read.csv("HadCRUT.csv",header=TRUE) | |
head(trust) | |
#names(trust)[names(trust) == 'Anomaly..deg.C.'] <- "Anomaly..deg.C" | |
#if graphing all not filtering by year | |
vac<-trust | |
vac<-trust %>% |
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Year | Recorded | |
---|---|---|
1975 | 49293 | |
1980 | 52552 | |
1985 | 38637 | |
1988 | 35251 | |
1990 | 23484 | |
1993 | 10487 | |
1995 | 7035 | |
2000 | 719 | |
2005 | 1979 |
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Country | vaccinated | long | lat | |
---|---|---|---|---|
Denmark | 77.4 | 10.445 | 55.728 | |
Belgium | 75.2 | 4.39 | 50.86 | |
Austria | 66.5 | 15.3 | 47.97 | |
Croatia | 48.4 | 16.173 | 45.567 | |
Albania | 36.1 | 19.8 | 41.28 | |
Belarus | 29.2 | 27.56 | 53.9 | |
Bosnia | 24.4 | 18.41 | 43.86 | |
Iceland | 82.5 | -21.95 | 64.15 | |
Ireland | 76.8 | -7.063 | 53.208 |
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