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AnCaJuLu
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  1. library(ggplot2)

  2. I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)

  3. data = data.frame(I,II,III,IV,V,VI,VII)

  4. ggplot(data) + geom_point()

  5. ggplot(data[I]) + geom_point()

  6. ggplot(data[I],aes(x,y)) + geom_point()

  7. data

  8. mtcars

  9. data = rbind(I,II,III,IV,V,VI,VII)

  10. data

  11. ggplot(data,aes(x="I",y="[],1]")) + geom_point()

  12. plot(data)

  13. par(mfrow=c(3,3))

  14. "indigo"

  15. par(mfrow=c(1,1))

  16. plot(I, color="red",pch=21,xlab = "bins",ylab="frequency")

  17. plot(I, gcolor="red",pch=21,xlab = "bins",ylab="frequency")

  18. plot(I, gcolor="red",pch=21,xlab = "bins",ylab="frequency")

  19. plot(II, gcolor="orange",pch=21,xlab="bins",ylab="frequency")

  20. plot(III, gcolor="yellow",pch=21,xlab="bins",ylab="frequency")

  21. plot(IV, gcolor="green",pch=21,xlab="bins",ylab="frequency")

  22. plot(V, gcolor="blue",pch=21,xlab="bins",ylab="frequency")

  23. plot(VI, gcolor="indigo",pch=21,xlab="bins",ylab="frequency")

  24. plot(VII, gcolor="purple",pch=21,xlab="bins",ylab="frequency")

  25. plot(VII, gcolor="purple",pch=16,xlab="bins",ylab="frequency")

  26. plot(I, col="red",pch=16,xlab = "bins",ylab="frequency")

  27. par(bg="pink")

  28. plot(I, col="red",pch=16,xlab = "bins",ylab="frequency")

  29. points(II, col="orange",pch=16)

  30. plot(I, col="red",pch=16,xlab = "bins",ylab="frequency")

  31. points(II, col="orange",pch=16)

  32. points(III, col="yellow",pch=16)

  33. points(IV, col="green",pch=16)

  34. points(V, col="blue",pch=16)

  35. points(VI, col="indigo",pch=16)

  36. plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")

  37. points(II, col="orange",pch=8)

  38. points(III, col="yellow",pch=8)

  39. points(IV, col="green",pch=8)

  40. points(V, col="blue",pch=8)

  41. points(VI, col="indigo",pch=8)

  42. points(VII, col="purple",pch=8)

  43. plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")

  44. points(II, col="orange",pch=8)

  45. points(III, col="yellow",pch=8)

  46. points(IV, col="green",pch=8)

  47. points(V, col="blue",pch=8)

  48. points(VI, col="indigo",pch=8)

  49. legend(0,0,legend=c("I","II","III","IV","V","VI","VII")

  50. )

  51. legend(0,0,legend=c("I","II","III","IV","V","VI","VII"))

  52. legend(1,1,legend=c("I","II","III","IV","V","VI","VII"))

  53. plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")

  54. points(II, col="orange",pch=8)

  55. points(III, col="yellow",pch=8)

  56. points(IV, col="green",pch=8)

  57. points(V, col="blue",pch=8)

  58. points(VI, col="purple",pch=8)

  59. points(VII, col="black",pch=8)

  60. legend(1,1,legend=c("I","II","III","IV","V","VI","VII"))

  61. legend(0,1,legend=c("I","II","III","IV","V","VI","VII"))

  62. legend(1,95,legend=c("I","II","III","IV","V","VI","VII"))

  63. legend(1,1,legend=c("I","II","III","IV","V","VI","VII"))

  64. legend(1,1,legend=c("I","II","III","IV","V","VI","VII"),fill="white")

  65. legend(1,1,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  66. legend(legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  67. legend(0,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  68. legend(3,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  69. legend(x=0,y=1legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  70. legend(x=0,y=1,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  71. par(bg="pink")

  72. plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")

  73. points(II, col="orange",pch=8)

  74. points(III, col="yellow",pch=8)

  75. points(IV, col="green",pch=8)

  76. points(V, col="blue",pch=8)

  77. points(VI, col="purple",pch=8)

  78. points(VII, col="black",pch=8)

  79. legend(x=0,y=1,legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  80. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),fill="white",col=c("red","orange","yellow","green","blue","purple","black"))

  81. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))

  82. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=1:7)

  83. plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")

  84. points(II, col="orange",pch=8)

  85. points(III, col="yellow",pch=8)

  86. points(IV, col="green",pch=8)

  87. points(V, col="blue",pch=8)

  88. points(VI, col="purple",pch=8)

  89. points(VII, col="black",pch=8)

  90. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=1:7)

  91. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))

  92. plot(I, col="red",pch=8,xlab = "bins",ylab="frequency")

  93. points(II, col="orange",pch=8)

  94. points(III, col="yellow",pch=8)

  95. points(IV, col="green",pch=8)

  96. points(V, col="blue",pch=8)

  97. points(VI, col="purple",pch=8)

  98. points(VII, col="black",pch=8)

  99. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))

  100. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),col=c("red","orange","yellow","green","blue","purple","black"))

  101. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),fill=c("red","orange","yellow","green","blue","purple","black"))

  102. plot(I, col="red",pch=8,xlab = "Bins",ylab="Frequency")

  103. points(II, col="orange",pch=8)

  104. points(III, col="yellow",pch=8)

  105. points(IV, col="green",pch=8)

  106. points(V, col="blue",pch=8)

  107. points(VI, col="purple",pch=8)

  108. points(VII, col="black",pch=8)

  109. legend("topleft",legend=c("I","II","III","IV","V","VI","VII"),fill=c("red","orange","yellow","green","blue","purple","black"))

  110. bins = rep(c(1:31),each=7)

  111. bins

  112. 1:31

  113. bins = rep(c((1:31)),each=7)

  114. 1:31

  115. bins

  116. bins = rep(c((1:31)),times=7)

  117. bins

  118. sample = rep(c("I","II","III","IV","V","VI","VII"), each =31)

  119. sample

  120. library(tidyverse)

  121. I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)

  122. II = c(0,0,.002,0,0,.004,.004,.011,.009,.015,.013,.017,.028,.028,.019,.026,.030,.043,.054,.054,.058,.078,.061,.061,.056,.082,.069,.078,.032,.030,.035)

  123. III = c(0,0,0,0,0,0,.012,.006,.014,.006,.017,.012,.038,.012,.003,.029,.049,.043,.078,.058,.064,.066,.052,.072,.069,.061,.081,.075,.026,.006,.052)

  124. IV = c(0,0,0,0,0,.003,.006,.009,.006,.009,.012,.006,.037,.018,.027,.040,.015,.046,.095,.073,.067,.064,.052,.043,.052,.061,.073,.076,.015,.027,.067)

  125. V = c(0,0,0,0,0,.010,.012,.012,.007,.022,.026,.014,.034,.026,.031,.022,.034,.043,.048,.058,.077,.046,.050,.050,.072,.063,.050,.072,.019,.026,.075)

  126. install.packages("assertthat")

  127. library(tidyverse)

  128. install.packages("Rcpp")

  129. library(tidyverse)

  130. I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)

  131. II = c(0,0,.002,0,0,.004,.004,.011,.009,.015,.013,.017,.028,.028,.019,.026,.030,.043,.054,.054,.058,.078,.061,.061,.056,.082,.069,.078,.032,.030,.035)

  132. III = c(0,0,0,0,0,0,.012,.006,.014,.006,.017,.012,.038,.012,.003,.029,.049,.043,.078,.058,.064,.066,.052,.072,.069,.061,.081,.075,.026,.006,.052)

  133. IV = c(0,0,0,0,0,.003,.006,.009,.006,.009,.012,.006,.037,.018,.027,.040,.015,.046,.095,.073,.067,.064,.052,.043,.052,.061,.073,.076,.015,.027,.067)

  134. V = c(0,0,0,0,0,.010,.012,.012,.007,.022,.026,.014,.034,.026,.031,.022,.034,.043,.048,.058,.077,.046,.050,.050,.072,.063,.050,.072,.019,.026,.075)

  135. VI = c(0,0,0,.002,0,.007,.005,.009,.009,.011,.014,.018,.043,.016,.027,.018,.043,.080,.062,.050,.084,.082,.062,.071,.050,.082,.057,.043,.005,.014,.034)

  136. VII = c(0,.002,.002,.003,.002,.003,.013,.013,.018,.015,.020,.016,.031,.010,.042,.016,.021,.028,.056,.056,.090,.044,.044,.056,.065,.075,.083,.075,.025,.026,.051)

  137. bins = rep(c((1:31)),times=7)

  138. sample = rep(c("I","II","III","IV","V","VI","VII"), each =31)

  139. values = c(I,II,III,IV,V,VI,VII)

  140. length(values)

  141. length(bins)

  142. length(sample)

  143. data = data.frame(bins,sample,values)

  144. data

  145. ggplot(data) +

  146. geom_point(mapping=aes(x=bins,y=values,color=sample)) +

  147. theme_bw()

  148. ggplot(data) +

  149. geom_point(mapping=aes(x=bins,y=values,color=sample)) +

  150. theme_bw() + xlab("Bin") + ylab("Alelles") +

  151. scale_x_continuous(breaks=(1:31))

  152. library(tidyverse)

  153. ggplot(data) +

  154. geom_point(mapping=aes(x=bins,y=values,color=sample)) +

  155. theme_bw() + xlab("Bin") + ylab("Alelle Frecuency") +

  156. scale_x_continuous(breaks=(1:31))

  157. a = c(9.96,9.97,9.95)

  158. sd(a)

  159. b = sd(a)

  160. b

  161. help(sd)

  162. a = c(10.01,10.26,9.96)

  163. sd(a)

  164. a = c(9.63,9.74,9.76)

  165. sd(a)

  166. a = c(7.24,7.59,8.46)

  167. sd(a)

  168. a = c(1.027,1.029,1.026)

  169. sd(a)

  170. mean(a)

  171. 2,5/10.27

  172. 2.5/10.27

  173. 10.25/10

  174. density = c(0.99,1.006,1.027,1.045,1.067)

  175. concentration = (0.87,2.01,5.02,7.00,10.00)

  176. concentration = c(0.87,2.01,5.02,7.00,10.00)

  177. plot(density, concentration)

  178. library(tidyverse)

  179. I = c(0,0,0,0,.005,0,.002,.01,.012,.01,.012,.0,.022,.020,.017,.03,.015,.052,.072,.06,.062,.062,.052,.047,.065,.09,.082,.077,.037,.017,.067)

  180. II = c(0,0,.002,0,0,.004,.004,.011,.009,.015,.013,.017,.028,.028,.019,.026,.030,.043,.054,.054,.058,.078,.061,.061,.056,.082,.069,.078,.032,.030,.035)

  181. III = c(0,0,0,0,0,0,.012,.006,.014,.006,.017,.012,.038,.012,.003,.029,.049,.043,.078,.058,.064,.066,.052,.072,.069,.061,.081,.075,.026,.006,.052)

  182. IV = c(0,0,0,0,0,.003,.006,.009,.006,.009,.012,.006,.037,.018,.027,.040,.015,.046,.095,.073,.067,.064,.052,.043,.052,.061,.073,.076,.015,.027,.067)

  183. V = c(0,0,0,0,0,.010,.012,.012,.007,.022,.026,.014,.034,.026,.031,.022,.034,.043,.048,.058,.077,.046,.050,.050,.072,.063,.050,.072,.019,.026,.075)

  184. VI = c(0,0,0,.002,0,.007,.005,.009,.009,.011,.014,.018,.043,.016,.027,.018,.043,.080,.062,.050,.084,.082,.062,.071,.050,.082,.057,.043,.005,.014,.034)

  185. VII = c(0,.002,.002,.003,.002,.003,.013,.013,.018,.015,.020,.016,.031,.010,.042,.016,.021,.028,.056,.056,.090,.044,.044,.056,.065,.075,.083,.075,.025,.026,.051)

  186. bins = rep(c((1:31)),times=7)

  187. sample = rep(c("I","II","III","IV","V","VI","VII"), each =31)

  188. values = c(I,II,III,IV,V,VI,VII)

  189. data = data.frame(bins,sample,values)

  190. ggplot(data) +

  191. geom_point(mapping=aes(x=bins,y=values,color=sample)) +

  192. theme_bw() + xlab("Bin") + ylab("Alelle Frecuency") +

  193. scale_x_continuous(breaks=(1:31))

  194. library(tidyverse)

  195. density = c(0.99,1.006,1.027,1.045,1.067)

  196. concentration = c(0.87,2.01,5.02,7.00,10.00)

  197. data = data.frame(density,concentration)

  198. data

  199. ggplot(data) +

  200. geom_point(mapping=aes(x=density,y=concentration,color=sample)) +

  201. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")

  202. ggplot(data) +

  203. geom_point(mapping=aes(x=density,y=concentration)) +

  204. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")

  205. ggplot(data) +

  206. geom_point(mapping=aes(x=density,y=concentration)) +

  207. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")+

  208. geom_smooth(method='lm')

  209. ggplot(data) +

  210. geom_point(mapping=aes(x=density,y=concentration)) +

  211. geom_smooth(method='lm') +

  212. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")

  213. ggplot(data, aes(x=density,y=concentration)) +

  214. geom_point() +

  215. geom_smooth(method='lm') +

  216. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%")

  217. ggplot(data, aes(x=density,y=concentration)) +

  218. geom_point() +

  219. geom_smooth(method='lm') +

  220. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +

  221. ggtitle("Density vs Concentration of Prepared Solutions")

  222. data = data.frame(density,concentration)

  223. model <- lm(concentration~density, data=data)

  224. summary(model)

  225. ggplot(data, aes(x=density,y=concentration)) +

  226. geom_point() +

  227. geom_smooth(method='lm') +

  228. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +

  229. ggtitle("Density vs Concentration of Prepared Solutions") +

  230. geom_label(x = x_lab, y = y_lab, label = "avg rate")

  231. ggplot(data, aes(x=density,y=concentration)) +

  232. geom_point() +

  233. geom_smooth(method='lm') +

  234. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +

  235. ggtitle("Density vs Concentration of Prepared Solutions") +

  236. geom_label(x = 1, y = 5, label = "avg rate")

  237. summary(model)

  238. ggplot(data, aes(x=density,y=concentration)) +

  239. geom_point() +

  240. geom_smooth(method='lm') +

  241. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +

  242. ggtitle("Density vs Concentration of Prepared Solutions") +

  243. geom_label(x = 1, y = 5, label = "y = 120.94x - 119.23") +

  244. geom_label(x = 1, y = 4, label = "R-squared: 0.9931") +

  245. xx

  246. library(tidyverse)

  247. density = c(0.99,1.006,1.027,1.045,1.067)

  248. concentration = c(0.87,2.01,5.02,7.00,10.00)

  249. data = data.frame(density,concentration)

  250. model <- lm(concentration~density, data=data)

  251. summary(model)

  252. ggplot(data, aes(x=density,y=concentration)) +

  253. geom_point() +

  254. geom_smooth(method='lm') +

  255. theme_bw() + xlab("Density(g/mL)") + ylab("Concentration%") +

  256. ggtitle("Density vs Concentration of Prepared Solutions") +

  257. geom_label(x = 1, y = 5, label = "y = 120.94x - 119.23") +

  258. geom_label(x = 1, y = 4, label = "R-squared: 0.9931")

  259. p = c(5.10,5.25,5.16)

  260. v = c(4.86,5.01,4.94)

  261. mean(p)

  262. sd(p)

  263. mean(v)

  264. sd(v)

  265. A = c(0.335,0.199,0.0953,0.0278)

  266. concentration = c(0.60,0.30,0.12,0.06)

  267. data = data.frame(A,concentration)

  268. model <- lm(A~concentration, data=data)

  269. summary(model)

  270. data = data.frame(A,concentration)

  271. model <- lm((A-0.01674)~(concentration-0.01674), data=data)

  272. summary(model)

  273. data = data.frame(A,concentration)

  274. model <- lm((A-0.01674)~(concentration-0.01674), data=data)

  275. summary(model)

  276. data = data.frame(A,concentration)

  277. model <- lm(I(A-0.01674)~(concentration-0.01674), data=data)

  278. summary(model)

  279. c = c(5.10,5.26,5.17)

  280. sd(c)

  281. mean(c)

  282. library(tidycensus)

  283. library(tidyverse)

  284. install.package("tidycensus")

  285. install.packages("tidycensus")

  286. library(tidyverse)

  287. library(tidycensus)

  288. library(tidycensus)

  289. library(tidyverse)

  290. library("writexl")

  291. census_api_key("7a853acf81fd5758228680556ac831138c40b83e")

  292. variables = load_variables(2019,"acs5")

  293. variables

  294. variables$name

  295. match("DP02",variables)

  296. variables$name[2000]

  297. variables$name[3000]

  298. variables$name[5000]

  299. variables$name[10000]

  300. variables$name[600000]

  301. variables$name[60000]

  302. variables$name[50000]

  303. variables$name[40000]

  304. variables$name[30000]

  305. variables$name[20000]

  306. variables = load_variables(2019,"acs5/profile")

  307. variables

  308. View(variables)

  309. length(variables)

  310. length(variables[1])

  311. variables = load_variables(2021,"acs5/profile")

  312. variables = load_variables(2020,"pl/profile")

  313. variables = load_variables(2020,"acs5/profile")

  314. variables

  315. View(variables)

  316. test = get_acs(geography = "county",

  317. state = "PR",

  318. year = 2020,

  319. variables = "DP02_0001")

  320. test

  321. View(test)

  322. test = get_acs(geography = "region",

  323. state = "PR",

  324. year = 2020,

  325. variables = "DP02_0001")

  326. test = get_acs(geography = "block",

  327. state = "PR",

  328. year = 2020,

  329. variables = "DP02_0001")

  330. test = get_acs(geography = "county",

  331. state = "PR",

  332. year = 2020,

  333. variables = "DP02_0001")

  334. View(test)

  335. variables$name

  336. codes = variables$name

  337. test = get_acs(geography = "county",

  338. state = "PR",

  339. year = 2020,

  340. variables = codes)

  341. view(test)

  342. noNA = na.omit(test)

  343. noNA

  344. view(noNA)

  345. view(variables)

  346. DP02table = noNA %>% filter(startsWith(variable,"DP02"))

  347. DP02table

  348. view(DP02table)

  349. DP02table = noNA %>% filter(startsWith(variable,"DP02"))

  350. DP03table = noNA %>% filter(startsWith(variable,"DP03"))

  351. DP04table = noNA %>% filter(startsWith(variable,"DP04"))

  352. DP05table = noNA %>% filter(startsWith(variable,"DP05"))

  353. view(DP04table)

  354. variables$name

  355. variables$label

  356. noNA$GEOID

  357. table(noNA$GEOID)

  358. length(table(noNA$GEOID))

  359. view(test)

  360. #amount of GEOIDS

  361. for (x in 1:78){

  362. labelCol = c(labelCol, labels)

  363. }

  364. #add label column

  365. #create empty vector

  366. labelCol = c()

  367. #amount of GEOIDS

  368. for (x in 1:78){

  369. labelCol = c(labelCol, labels)

  370. }

  371. #combine test and cols

  372. test["label"] = labelCol

  373. labelCol

  374. #amount of GEOIDS

  375. for (x in 1:78){

  376. labelCol = c(labelCol, labels)

  377. }

  378. labels()

  379. labels()

  380. labels

  381. variables

  382. variables$label

  383. label

  384. labels

  385. label0 = variables$label

  386. label0

  387. #add label column

  388. #create empty vector

  389. labelCol = c()

  390. #amount of GEOIDS

  391. for (x in 1:78){

  392. labelCol = c(labelCol, label0)

  393. }

  394. #combine test and cols

  395. test["label"] = labelCol

  396. view(test)

  397. #omit NA rows

  398. noNA = na.omit(test)

  399. DP02table = noNA %>% filter(startsWith(variable,"DP02"))

  400. DP03table = noNA %>% filter(startsWith(variable,"DP03"))

  401. DP04table = noNA %>% filter(startsWith(variable,"DP04"))

  402. DP05table = noNA %>% filter(startsWith(variable,"DP05"))

  403. view(DP02table)

  404. GEOIDS = table(test$GEOID)

  405. GEOIDS

  406. #rearrange cols

  407. test = test[c("NAME","label","variable","estimate","moe","GEOID")]

  408. view(test)

  409. pnorm(1.25)

  410. pnorm(1.25) - pnorm(-1.25)

  411. pnorm(1.875) - pnorm(-1.25)

  412. pnorm(0.75) - pnorm(-1.25)

  413. pnorm(1.25) - pnorm(-2.5)

  414. pnorm(2.7) - pnorm(2)

  415. pnorm(1.54)

  416. pnorm(1.54) - pnorm(-1.54)

  417. qnorm(0.4564)

  418. qnorm(0.9564)

  419. qnorm(0.05)

  420. qnorm(0.07)

  421. qnorm(0.94)

  422. qnorm(0.43)

  423. pnorm(-0.18)

  424. qnorm(0.43)

  425. pnorm(-0.17)

  426. pnorm(-1.30)

  427. qnorm(0.70,400,80)

  428. (106 - qnorm(0.70,106,21))/21

  429. (qnorm(0.70,106,21)-106)/21

  430. (qnorm(0.87,106,28)

  431. )

  432. qnorm(0.77)

  433. 0.74 * 17 + 108

  434. pnorm(252,369,59)

  435. pnorm(140,120,18) - pnorm(110,120,18)

  436. qnorm(0.87,100,10)

  437. 1- pnorm(96,100,20)

  438. pnorm(180,159,10) - pnorm(150,159,10)

  439. (pnorm(180,159,10) - pnorm(150,159,10))*425

  440. x = c(-40,0,260,460,960)

  441. px = c(0.99510,1/200,1/500,1/1000,1/2000)

  442. len(px)

  443. length(px)

  444. Ex = sum(x*px)

  445. Vx = sum(((x-Ex)^2)*px)

  446. Ex

  447. Vx

  448. library(tidycensus)

  449. library(tidyverse)

  450. tableYear = 2020

  451. #log on with API

  452. census_api_key("7a853acf81fd5758228680556ac831138c40b83e")

  453. #load variables

  454. pueblos = 78

  455. variables = load_variables(2020,"acs5/profile")

  456. codes = variables$name

  457. codess

  458. codes

  459. startsWith(codes,"DP02")

  460. callData = function(year,table,municipality) {

  461. #year is between 2000 and 2020

  462. #table is dp02pr, dp03, dp04, dp05

  463. #load variables

  464. variables = load_variables(year,"acs5/profile")

  465. #load variable vectors

  466. codes = variables$name

  467. codesBool = startsWith(codes,table)

  468. codes = codes[codesBool]

  469. labels = variables$label[codesBool]

  470. #pull table

  471. bigTable = get_acs(geography = "county",

  472. state = "PR",

  473. year = year,

  474. county = municipality,

  475. variables = codes)

  476. bigTable$Label = labels

  477. return(bigTable)

  478. }

  479. table = callData(2020,"DP05","Aguada")

  480. table

  481. view(table)

  482. view(table)

  483. callData = function(year,table,municipality) {

  484. #year is between 2000 and 2020

  485. #table is dp02pr, dp03, dp04, dp05

  486. #load variables

  487. variables = load_variables(year,"acs5/profile")

  488. #load variable vectors

  489. codes = variables$name

  490. codesBool = startsWith(codes,table)

  491. codes = codes[codesBool]

  492. labels = variables$label[codesBool]

  493. #pull table

  494. bigTable = get_acs(geography = "county",

  495. state = "PR",

  496. year = year,

  497. county = municipality,

  498. variables = codes)

  499. bigTable$Label = labels

  500. bigTable = bigTable[c("Label","estimate","moe")]

  501. return(bigTable)

  502. }

  503. table = callData(2020,"DP05","Aguada")

  504. view(table)

  505. plumber::plumb(file='C:/Users/kashi/Desktop/R.R')$run()

  506. plumb(file='C:/Users/kashi/Desktop/R.R')$run()

  507. setwd("C:/Users/kashi/Desktop")

  508. plumb(file='R.R')$run()

  509. setwd("C:/Users/kashi/Desktop/censusproject")

  510. plumb(file='R.R')$run()

  511. plumb(file='R.R')$run()

  512. plumb(file='R.R')$run()