Any help would be greatly appreciated!!
I'm trying to create a choropleth map in R that shows the counties of texas, color-coded by their population ranges.
My problem is that the range of populations is too large. The highest population is over 4 million, but most of the counties have a population under 50,000. The criteria for the fill is: (0-1mil), (1-2mil), (2-3mil), (3-4mil), (4-5mil) but almost all fall under 0-1mil.
How can I change the legend to account for different ranges of numbers? For example, maybe:
(0-1,000), (1,000-10,000), (10,000-100,000), (100,000-1mil), (1mil-5mil)
Here's the code I wrote to plot the data:
txplot <- ggplot(txczpop, aes(fill=pop2014)) + geom_map(txmap)
tm_shape(txmap) +
tm_fill("pop2014", title="TX County Population", palette = "PRGn") +
tm_borders(alpha=.5) +
tm_style_beaver()
Here's the result:
[![enter image description here][1]][1]
I'm using a census county shapefile and population also retrieved from a census file.
Here's the output of my population data:
txczpop <- structure(list(county_fips = c(48001L, 48003L, 48005L, 48007L,
48009L, 48011L, 48013L, 48015L, 48017L, 48019L, 48021L, 48023L,
48025L, 48027L, 48029L, 48031L, 48033L, 48035L, 48037L, 48039L,
48041L, 48043L, 48045L, 48047L, 48049L, 48051L, 48053L, 48055L,
48057L, 48059L, 48061L, 48063L, 48065L, 48067L, 48069L, 48071L,
48073L, 48075L, 48077L, 48079L, 48081L, 48083L, 48085L, 48087L,
48089L, 48091L, 48093L, 48095L, 48097L, 48099L, 48101L, 48103L,
48105L, 48107L, 48109L, 48111L, 48113L, 48115L, 48117L, 48119L,
48121L, 48123L, 48125L, 48127L, 48129L, 48131L, 48133L, 48135L,
48137L, 48141L, 48139L, 48143L, 48145L, 48147L, 48149L, 48151L,
48153L, 48155L, 48157L, 48159L, 48161L, 48163L, 48165L, 48167L,
48169L, 48171L, 48173L, 48175L, 48177L, 48179L, 48181L, 48183L,
48185L, 48187L, 48189L, 48191L, 48193L, 48195L, 48197L, 48199L,
48201L, 48203L, 48205L, 48207L, 48209L, 48211L, 48213L, 48215L,
48217L, 48219L, 48221L, 48223L, 48225L, 48227L, 48229L, 48231L,
48233L, 48235L, 48237L, 48239L, 48241L, 48243L, 48245L, 48247L,
48249L, 48251L, 48253L, 48255L, 48257L, 48259L, 48261L, 48263L,
48265L, 48267L, 48269L, 48271L, 48273L, 48275L, 48283L, 48277L,
48279L, 48281L, 48285L, 48287L, 48289L, 48291L, 48293L, 48295L,
48297L, 48299L, 48301L, 48303L, 48305L, 48313L, 48315L, 48317L,
48319L, 48321L, 48323L, 48307L, 48309L, 48311L, 48325L, 48327L,
48329L, 48331L, 48333L, 48335L, 48337L, 48339L, 48341L, 48343L,
48345L, 48347L, 48349L, 48351L, 48353L, 48355L, 48357L, 48359L,
48361L, 48363L, 48365L, 48367L, 48369L, 48371L, 48373L, 48375L,
48377L, 48379L, 48381L, 48383L, 48385L, 48387L, 48389L, 48391L,
48393L, 48395L, 48397L, 48399L, 48401L, 48403L, 48405L, 48407L,
48409L, 48411L, 48413L, 48415L, 48417L, 48419L, 48421L, 48423L,
48425L, 48427L, 48429L, 48431L, 48433L, 48435L, 48437L, 48439L,
48441L, 48443L, 48445L, 48447L, 48449L, 48451L, 48453L, 48455L,
48457L, 48459L, 48461L, 48463L, 48465L, 48467L, 48469L, 48471L,
48473L, 48475L, 48477L, 48479L, 48481L, 48483L, 48485L, 48487L,
48489L, 48491L, 48493L, 48495L, 48497L, 48499L, 48501L, 48503L,
48505L, 48507L), county_name = c("Anderson", "Andrews", "Angelina",
"Aransas", "Archer", "Armstrong", "Atascosa", "Austin", "Bailey",
"Bandera", "Bastrop", "Baylor", "Bee", "Bell", "Bexar", "Blanco",
"Borden", "Bosque", "Bowie", "Brazoria", "Brazos", "Brewster",
"Briscoe", "Brooks", "Brown", "Burleson", "Burnet", "Caldwell",
"Calhoun", "Callahan", "Cameron", "Camp", "Carson", "Cass", "Castro",
"Chambers", "Cherokee", "Childress", "Clay", "Cochran", "Coke",
"Coleman", "Collin", "Collingsworth", "Colorado", "Comal", "Comanche",
"Concho", "Cooke", "Coryell", "Cottle", "Crane", "Crockett",
"Crosby", "Culberson", "Dallam", "Dallas", "Dawson", "Deaf Smith",
"Delta", "Denton", "DeWitt", "Dickens", "Dimmit", "Donley", "Duval",
"Eastland", "Ector", "Edwards", "El Paso", "Ellis", "Erath",
"Falls", "Fannin", "Fayette", "Fisher", "Floyd", "Foard", "Fort Bend",
"Franklin", "Freestone", "Frio", "Gaines", "Galveston", "Garza",
"Gillespie", "Glasscock", "Goliad", "Gonzales", "Gray", "Grayson",
"Gregg", "Grimes", "Guadalupe", "Hale", "Hall", "Hamilton", "Hansford",
"Hardeman", "Hardin", "Harris", "Harrison", "Hartley", "Haskell",
"Hays", "Hemphill", "Henderson", "Hidalgo", "Hill", "Hockley",
"Hood", "Hopkins", "Houston", "Howard", "Hudspeth", "Hunt", "Hutchinson",
"Irion", "Jack", "Jackson", "Jasper", "Jeff Davis", "Jefferson",
"Jim Hogg", "Jim Wells", "Johnson", "Jones", "Karnes", "Kaufman",
"Kendall", "Kenedy", "Kent", "Kerr", "Kimble", "King", "Kinney",
"Kleberg", "Knox", "La Salle", "Lamar", "Lamb", "Lampasas", "Lavaca",
"Lee", "Leon", "Liberty", "Limestone", "Lipscomb", "Live Oak",
"Llano", "Loving", "Lubbock", "Lynn", "Madison", "Marion", "Martin",
"Mason", "Matagorda", "Maverick", "McCulloch", "McLennan", "McMullen",
"Medina", "Menard", "Midland", "Milam", "Mills", "Mitchell",
"Montague", "Montgomery", "Moore", "Morris", "Motley", "Nacogdoches",
"Navarro", "Newton", "Nolan", "Nueces", "Ochiltree", "Oldham",
"Orange", "Palo Pinto", "Panola", "Parker", "Parmer", "Pecos",
"Polk", "Potter", "Presidio", "Rains", "Randall", "Reagan", "Real",
"Red River", "Reeves", "Refugio", "Roberts", "Robertson", "Rockwall",
"Runnels", "Rusk", "Sabine", "San Augustine", "San Jacinto",
"San Patricio", "San Saba", "Schleicher", "Scurry", "Shackelford",
"Shelby", "Sherman", "Smith", "Somervell", "Starr", "Stephens",
"Sterling", "Stonewall", "Sutton", "Swisher", "Tarrant", "Taylor",
"Terrell", "Terry", "Throckmorton", "Titus", "Tom Green", "Travis",
"Trinity", "Tyler", "Upshur", "Upton", "Uvalde", "Val Verde",
"Van Zandt", "Victoria", "Walker", "Waller", "Ward", "Washington",
"Webb", "Wharton", "Wheeler", "Wichita", "Wilbarger", "Willacy",
"Williamson", "Wilson", "Winkler", "Wise", "Wood", "Yoakum",
"Young", "Zapata", "Zavala"), pop2014 = c(57627L, 17477L, 87750L,
24972L, 8811L, 1955L, 47774L, 29114L, 6910L, 20892L, 78069L,
3592L, 32863L, 329140L, 1855866L, 10812L, 652L, 17780L, 93275L,
338124L, 209152L, 9173L, 1536L, 7194L, 37653L, 17253L, 44943L,
39810L, 21797L, 13513L, 420392L, 12621L, 6013L, 30261L, 7781L,
38145L, 50902L, 7089L, 10370L, 2935L, 3254L, 8430L, 885241L,
3017L, 20719L, 123694L, 13550L, 4050L, 38761L, 75562L, 1415L,
4950L, 3812L, 5899L, 2266L, 7135L, 2518638L, 13372L, 19195L,
5238L, 753363L, 20684L, 2218L, 11089L, 3543L, 11533L, 18176L,
153904L, 1879L, 833487L, 159317L, 40147L, 16989L, 33752L, 24833L,
3831L, 5949L, 1275L, 685345L, 10600L, 19762L, 18531L, 19425L,
314198L, 6435L, 25520L, 1291L, 7549L, 20462L, 23044L, 123534L,
123204L, 27172L, 147250L, 34720L, 3147L, 8199L, 5509L, 3928L,
55621L, 4441370L, 67336L, 6089L, 5769L, 185025L, 4180L, 79290L,
831073L, 34848L, 23577L, 53921L, 35921L, 22741L, 36651L, 3211L,
88493L, 21773L, 1574L, 8855L, 14739L, 35552L, 2204L, 252235L,
5255L, 41353L, 157456L, 19936L, 14906L, 111236L, 38880L, 400L,
785L, 50562L, 4438L, 262L, 3526L, 32190L, 3858L, 7474L, 49523L,
13574L, 20156L, 19721L, 16742L, 16861L, 78117L, 23524L, 3553L,
12091L, 19510L, 86L, 293974L, 5771L, 13861L, 10149L, 5460L, 4071L,
36519L, 57023L, 8199L, 243441L, 805L, 47894L, 2147L, 155830L,
24256L, 4870L, 9076L, 19416L, 518947L, 22148L, 12743L, 1153L,
65301L, 48195L, 14138L, 15093L, 356221L, 10758L, 2070L, 83433L,
28096L, 23769L, 123164L, 9908L, 15893L, 46079L, 121627L, 6976L,
11032L, 128220L, 3755L, 3371L, 12446L, 14349L, 7302L, 928L, 16500L,
87809L, 10416L, 53923L, 10350L, 8610L, 27099L, 66915L, 5622L,
3162L, 17328L, 3343L, 25515L, 3084L, 218842L, 8694L, 62955L,
9405L, 1339L, 1403L, 3972L, 7581L, 1945360L, 135143L, 927L, 12739L,
1608L, 32506L, 116608L, 1151145L, 14224L, 21418L, 40354L, 3454L,
27117L, 48974L, 52910L, 91081L, 69789L, 46820L, 11625L, 34438L,
266673L, 41168L, 5714L, 132355L, 12973L, 21903L, 489250L, 46402L,
7821L, 61638L, 42852L, 8286L, 18350L, 14319L, 12267L)), .Names = c("county_fips",
"county_name", "pop2014"), row.names = c(5100L, 5101L, 5103L,
5106L, 5107L, 5109L, 5112L, 5114L, 5116L, 5118L, 5120L, 5121L,
5124L, 5126L, 5128L, 5129L, 5131L, 5133L, 5136L, 5137L, 5140L,
5141L, 5143L, 5146L, 5147L, 5150L, 5152L, 5153L, 5156L, 5158L,
5159L, 5161L, 5163L, 5166L, 5168L, 5170L, 5171L, 5174L, 5176L,
5178L, 5179L, 5182L, 5183L, 5185L, 5188L, 5190L, 5192L, 5194L,
5195L, 5198L, 5200L, 5201L, 5203L, 5205L, 5208L, 5209L, 5212L,
5214L, 5215L, 5218L, 5219L, 5221L, 5224L, 5226L, 5228L, 5230L,
5232L, 5233L, 5235L, 5239L, 5237L, 5242L, 5244L, 5245L, 5248L,
5249L, 5251L, 5254L, 5256L, 5257L, 5260L, 5261L, 5264L, 5265L,
5268L, 5270L, 5272L, 5274L, 5276L, 5278L, 5280L, 5281L, 5284L,
5286L, 5288L, 5290L, 5292L, 5293L, 5296L, 5298L, 5300L, 5301L,
5303L, 5306L, 5308L, 5309L, 5312L, 5314L, 5316L, 5317L, 5319L,
5321L, 5323L, 5326L, 5327L, 5330L, 5332L, 5334L, 5335L, 5337L,
5339L, 5341L, 5343L, 5346L, 5348L, 5349L, 5352L, 5354L, 5356L,
5357L, 5360L, 5362L, 5364L, 5365L, 5368L, 5369L, 5372L, 5374L,
5382L, 5376L, 5378L, 5379L, 5383L, 5385L, 5388L, 5390L, 5392L,
5394L, 5396L, 5398L, 5400L, 5401L, 5404L, 5412L, 5413L, 5416L,
5418L, 5419L, 5421L, 5406L, 5407L, 5409L, 5423L, 5425L, 5427L,
5429L, 5432L, 5434L, 5435L, 5438L, 5440L, 5442L, 5443L, 5446L,
5448L, 5449L, 5451L, 5453L, 5456L, 5457L, 5460L, 5461L, 5464L,
5465L, 5468L, 5470L, 5472L, 5474L, 5476L, 5477L, 5480L, 5482L,
5484L, 5486L, 5488L, 5489L, 5491L, 5494L, 5496L, 5498L, 5499L,
5501L, 5504L, 5505L, 5508L, 5510L, 5511L, 5514L, 5516L, 5518L,
5520L, 5522L, 5524L, 5526L, 5527L, 5530L, 5531L, 5533L, 5536L,
5537L, 5540L, 5542L, 5544L, 5546L, 5547L, 5550L, 5552L, 5554L,
5555L, 5558L, 5559L, 5562L, 5563L, 5566L, 5568L, 5569L, 5571L,
5574L, 5575L, 5578L, 5579L, 5582L, 5584L, 5585L, 5587L, 5590L,
5592L, 5594L, 5595L, 5598L, 5600L, 5602L, 5604L, 5606L), class = "data.frame")
I just created a new column in the population dataframe that summarizes the population based on the ranges that I want to use, and then use that as the criteria for the fill:
txczpop$poprange[txczpop$pop2014 >= 0 & txczpop < 1000] <- "0-1,000"
txczpop$poprange[txczpop$pop2014 >= 1000 & txczpop < 10000] <- "1-10,000"
txczpop$poprange[txczpop$pop2014 >= 10000 & txczpop$pop2014 < 100000] <- "10,000-100,000"
txczpop$poprange[txczpop$pop2014 >= 100000 & txczpop$pop2014 < 1000000] <- "100,000 - 1,000,000"
txczpop$poprange[txczpop$pop2014 >= 1000000 & txczpop$pop2014 <= 5000000] <- "1,000,000 - 5,000,000"
Related
My first data frame (df) contains Entrydate and ExitDate columns. Another dataframe (n1) has all trading dates. I need a new column in first dataframe calculated as number of days as calculated from the second dataframe. How do I call this dayCount function for each row of df. When I try to use mapply, I am unable to pass n1 as a parameter.
dayCount <- function (startDate, endDate, n1) {
return (nrow(subset(n1, Date >= startDate & Date <= endDate)))
}
df<- structure(list(EntryDate = structure(c(11355, 11418, 11436, 11449,
11520, 11523, 11548, 11620, 11768, 11773), class = "Date"), ExitDate = structure(c(11360,
11422, 11438, 11457, 11522, 11526, 11554, 11625, 11772, 11778
), class = "Date")), row.names = c(22L, 65L, 76L, 84L, 135L,
138L, 155L, 204L, 305L, 307L), class = "data.frame")
n1<- structure(c(11354, 11355, 11358, 11359, 11360, 11361, 11362,
11365, 11366, 11367, 11368, 11369, 11372, 11373, 11374, 11375,
11376, 11379, 11380, 11381, 11382, 11383, 11386, 11388, 11389,
11390, 11393, 11394, 11395, 11396, 11397, 11400, 11401, 11402,
11403, 11404, 11407, 11408, 11409, 11410, 11411, 11414, 11415,
11416, 11418, 11421, 11422, 11423, 11424, 11428, 11429, 11430,
11431, 11432, 11435, 11436, 11437, 11438, 11439, 11442, 11444,
11445, 11446, 11449, 11450, 11451, 11452, 11453, 11456, 11457,
11458, 11459, 11460, 11463, 11464, 11465, 11466, 11467, 11470,
11471, 11472, 11473, 11474, 11477, 11478, 11479, 11480, 11481,
11484, 11485, 11486, 11487, 11488, 11491, 11492, 11493, 11494,
11495, 11498, 11499, 11500, 11501, 11502, 11505, 11506, 11507,
11508, 11509, 11512, 11513, 11514, 11515, 11516, 11519, 11520,
11521, 11522, 11523, 11526, 11527, 11528, 11529, 11530, 11533,
11534, 11535, 11536, 11537, 11540, 11541, 11542, 11543, 11544,
11547, 11548, 11550, 11551, 11554, 11555, 11557, 11558, 11561,
11562, 11563, 11564, 11565, 11568, 11569, 11570, 11571, 11572,
11575, 11576, 11577, 11578, 11579, 11582, 11583, 11584, 11585,
11586, 11589, 11590, 11591, 11592, 11593, 11596, 11598, 11599,
11600, 11603, 11604, 11605, 11606, 11607, 11610, 11611, 11612,
11613, 11614, 11617, 11618, 11619, 11620, 11624, 11625, 11626,
11627, 11628, 11631, 11632, 11633, 11634, 11635, 11638, 11639,
11640, 11641, 11645, 11646, 11647, 11648, 11649, 11652, 11653,
11654, 11655, 11659, 11660, 11661, 11662, 11663, 11666, 11667,
11668, 11669, 11670, 11674, 11675, 11676, 11677, 11680, 11682,
11683, 11684, 11687, 11688, 11689, 11690, 11691, 11694, 11695,
11696, 11697, 11698, 11701, 11702, 11703, 11704, 11705, 11708,
11709, 11710, 11711, 11712, 11715, 11716, 11717, 11718, 11719,
11722, 11723, 11724, 11725, 11726, 11729, 11730, 11731, 11732,
11733, 11736, 11737, 11738, 11739, 11740, 11743, 11744, 11745,
11746, 11747, 11750, 11751, 11752, 11753, 11754, 11757, 11758,
11759, 11760, 11761, 11764, 11765, 11766, 11767, 11768, 11772,
11773, 11774, 11778), class = "Date")
You can use %in% to count number of days in n1 between each EntryDate and ExitDate.
df$dayCount <- colSums(mapply(function(x, y) n1 %in% seq(x, y, by = '1 day'),
df$EntryDate, df$ExitDate))
df
# EntryDate ExitDate dayCount
#22 2001-02-02 2001-02-07 4
#65 2001-04-06 2001-04-10 3
#76 2001-04-24 2001-04-26 3
#84 2001-05-07 2001-05-15 7
#135 2001-07-17 2001-07-19 3
#138 2001-07-20 2001-07-23 2
#155 2001-08-14 2001-08-20 4
#204 2001-10-25 2001-10-30 3
#305 2002-03-22 2002-03-26 2
#307 2002-03-27 2002-04-01 3
I want to write an algorithm that spits out the points highlighted by arrows. I've tried using a second derivative but it returns a similar plot to the one above and not sure how to use it.
Hi, sorry about that, I don't want the peaks, I want the point where the graph starts to increase - ie I want the point where the gradient changes from ~0 to something larger, does that make sense
Example data is below.
df = structure(list(X1 = c("2729", "2730", "2731", "2732", "2733",
"2734", "2735", "2736", "2737", "2738", "2739", "2740", "2741",
"2742", "2743", "2744", "2745", "2746", "2747", "2748", "2749",
"2750", "2751", "2752", "2753", "2754", "2755", "2756", "2757",
"2758", "2759", "2760", "2761", "2762", "2763", "2764", "2765",
"2766", "2767", "2768", "2769", "2770", "2771", "2772", "2773",
"2774", "2775", "2776", "2777", "2778", "2779", "2780", "2781",
"2782", "2783", "2784", "2785", "2786", "2787", "2788", "2789",
"2790", "2791", "2792", "2793", "2794", "2795", "2796", "2797",
"2798", "2799", "2800", "2801", "2802", "2803", "2804", "2805",
"2806", "2807", "2808", "2809", "2810", "2811", "2812", "2813",
"2814", "2815", "2816", "2817", "2818", "2819", "2820", "2821",
"2822", "2823", "2824", "2825", "2826", "2827", "2828", "2829",
"2830", "2831", "2832", "2833", "2834", "2835", "2836", "2837",
"2838", "2839", "2840", "2841", "2842", "2843", "2844", "2845",
"2846", "2847", "2848", "2849", "2850", "2851", "2852", "2853",
"2854", "2855", "2856", "2857", "2858", "2859", "2860", "2861",
"2862", "2863", "2864", "2865", "2866", "2867", "2868", "2869",
"2870", "2871", "2872", "2873", "2874", "2875", "2876", "2877",
"2878", "2879", "2880", "2881", "2882", "2883", "2884", "2885",
"2886", "2887", "2888", "2889", "2890", "2891", "2892", "2893",
"2894", "2895", "2896", "2897", "2898", "2899", "2900", "2901",
"2902", "2903", "2904", "2905", "2906", "2907", "2908", "2909",
"2910", "2911", "2912", "2913", "2914", "2915", "2916", "2917",
"2918", "2919", "2920", "2921", "2922", "2923", "2924", "2925",
"2926", "2927", "2928", "2929", "2930", "2931", "2932", "2933",
"2934", "2935", "2936", "2937", "2938", "2939", "2940", "2941",
"2942", "2943", "2944", "2945", "2946", "2947", "2948", "2949",
"2950", "2951", "2952", "2953", "2954", "2955", "2956", "2957",
"2958", "2959", "2960", "2961", "2962", "2963", "2964", "2965",
"2966", "2967", "2968", "2969", "2970", "2971", "2972", "2973",
"2974", "2975", "2976", "2977", "2978", "2979", "2980", "2981",
"2982", "2983", "2984", "2985", "2986", "2987", "2988", "2989",
"2990", "2991", "2992", "2993", "2994", "2995", "2996", "2997",
"2998", "2999", "3000", "3001", "3002", "3003", "3004", "3005",
"3006", "3007", "3008", "3009", "3010", "3011", "3012", "3013",
"3014", "3015", "3016", "3017", "3018", "3019", "3020", "3021",
"3022", "3023", "3024", "3025", "3026", "3027", "3028", "3029",
"3030", "3031", "3032", "3033", "3034", "3035", "3036", "3037",
"3038", "3039", "3040", "3041", "3042", "3043", "3044", "3045",
"3046", "3047", "3048", "3049", "3050", "3051", "3052", "3053",
"3054", "3055", "3056", "3057", "3058", "3059", "3060", "3061",
"3062", "3063", "3064", "3065", "3066", "3067", "3068", "3069",
"3070", "3071", "3072", "3073", "3074", "3075", "3076", "3077",
"3078", "3079", "3080", "3081", "3082", "3083", "3084", "3085",
"3086", "3087", "3088", "3089", "3090", "3091", "3092", "3093",
"3094", "3095", "3096", "3097", "3098", "3099", "3100", "3101",
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"3438", "3439", "3440", "3441", "3442", "3443", "3444", "3445"
), X2 = c(-0.00385000000001254, -0.0154500000000484, -0.0277600000000007,
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-8.05101707233625e-15)), row.names = c(NA, -717L), class = "data.frame")
As others have said, it is not clear what you are looking for.
specifically, it's not clear how high above "baseline" is too high.
Here's a shot at it:
df_prime <- df$X2[-1] - df$X2[-length(df$X2)]
large_rise <- which(df_prime > sd(df_prime) & df$X2[-length(df$X2)] > -sd(df$X2))
df$X1[large_rise]
It's difficult to know from the question, but aren't you just looking for something like this?
spikes <- as.numeric(df$X1[df$X2 > 0.1])
spikes <- spikes[which(diff(c(0, spikes)) > 3)]
spikes
#> [1] 2738 2758 2984 2994 3126 3139 3190 3260 3273 3309 3316 3363 3377
So, for example if you did
plot(df$X1, df$X2, type = "l")
points(spikes, rep(1, length(spikes)), col="red")
You would get
I have the following format, please advise how to convert it to a list in R?
"{1948, 2507, 2510, 7030, 7110, 9009, 00027, 00206, 00399, 00717, 00814, 00828, 00848, 00917, 01050, 01105, 01144, 02130, 02768, 03037, 03752, 03754, 04070, 04110, 05050, 05255, 05289, 05564, 05595, 06100, 06330, 06671, 07041, 07119, 07137, 07273, 07313, 07454, 07871, 08104, 08714, 08726, 08995, 09059, 09073, 09525, 09949, 09981, 10092, 10439, 10782, 11185, 11507, 11712, 11806, 11858, 11980, 12067, 12113, 12139, 12643, 13820, 14534, 15007, 15014, 15549, 15953, 16151, 16174, 16634, 16733, 16888, 17111, 17207, 17377, 17721, 17900, 18118, 18400, 18686, 18880, 19080, 19342, 19444, 19772, 19790, 19891, 20091, 20245, 20402, 20811, 21114, 21345, 21811, 21881, 22222, 22311, 22320, 22831, 22969, 23251, 23572, 23734, 23862, 23889, 24034, 24463, 25172, 25688, 26143, 26221, 26803, 26850, 26898, 27497, 28291, 28343, 29411, 29419, 30024, 30561, 30923, 31345, 31351, 31555, 31927, 32198, 32861, 33020, 33040, 33095, 33188, 33311, 33368, 33377, 33475, 33519, 33574, 33592, 34207, 34235, 34272, 34484, 34854, 34872, 34875, 34876, 34880, 35222, 35292, 35344, 36177, 36266, 37038, 37060, 37548, 37686, 37700, 38139, 39368, 39369, 39633, 40132, 40698, 40704, 40744, 40819, 41311, 41971, 42102, 42616, 43055, 43211, 43234, 43428, 43494, 43934, 44117, 44252, 44272, 44301, 44336, 44619, 44866, 44888, 45049, 45197, 45412, 45718, 46694, 46736, 47000, 48046, 48540, 49078, 49109, 49216, 49388, 49464, 50056, 50155, 50217, 50477, 50692, 51122, 51445, 51946, 52475, 52537, 52982, 54011, 54031, 54160, 54963, 55000, 55537, 56080, 56163, 56282, 56760, 56787, 57102, 57727, 57871, 58101, 58558, 58882, 59902, 60225, 60397, 60501, 60619, 60703, 60890, 61075, 61894, 61944, 62322, 62337, 62380, 62413, 62729, 62766, 62923, 63010, 63234, 63977, 64127, 65359, 65428, 65542, 65750, 65863, 66184, 66636, 66712, 67201, 67439, 67953, 68133, 68854, 69251, 69959, 70107, 70725, 70768, 71081, 71099, 71948, 72013, 72377, 72400, 72420, 72735, 73000, 73015, 73142, 73223, 73455, 73717, 74049, 74492, 74854, 74941, 75142, 75399, 75464, 75587, 75618, 75642, 75887, 76357, 76651, 77199, 77302, 77456, 77579, 77601, 77649, 77668, 77694, 77745, 78006, 78010, 78178, 78335, 78656, 78729, 78808, 78824, 78844, 78945, 79416, 79471, 79915, 80077, 80111, 80189, 80262, 80409, 80470, 80529, 80539, 80838, 81272, 81513, 81658, 81740, 81743, 81762, 81843, 82001, 82070, 82106, 82342, 82472, 82719, 83670, 84009, 84151, 84299, 84430, 84450, 84460, 84945, 86411, 86443, 86446, 86668, 86942, 87286, 87317, 87624, 87785, 88023, 88517, 88696, 88787, 88868, 88977, 89206, 90108, 90440, 90734, 90802, 90849, 90920, 90931, 91011, 91031, 91133, 91777, 91949, 92162, 92494, 93012, 93172, 94300, 94517, 95142, 95410, 95559, 95859, 96112, 97255, 97787, 97986, 98240, 98817, 99050, 99198, 99222, 99241, 99295, 99326, 99335, 99503, 99603, 99643, 99803, 99968}"
THIS IS NOT A DUPLICATE OF convert json to list in a vectorized way in R
IT'S COMPLETELY DIFFERENT BECAUSE THE FORMAT IS ABSOLUTELY DIFFERENT.
Try this one line code:
as.numeric(sapply(strsplit(substr(j,2,nchar(j)-1),split = ","),trimws))
[1] 1948 2507 2510 7030 7110 9009 27 206 399 717 814 828 848 917 1050 1105 1144
[18] 2130 2768 3037 3752 3754 4070 4110 5050 5255 5289 5564 5595 6100 6330 6671 7041 7119
[35] 7137 7273 7313 7454 7871 8104 8714 8726 8995 9059 9073 9525 9949 9981 10092 10439 10782
[52] 11185 11507 11712 11806 11858 11980 12067 12113 1213 ..
Your input:
j<-"{1948, 2507, 2510, 7030, 7110, 9009, 00027, 00206, 00399, 00717, 00814, 00828, 00848, 00917, 01050, 01105, 01144, 02130, 02768, 03037, 03752, 03754, 04070, 04110, 05050, 05255, 05289, 05564, 05595, 06100, 06330, 06671, 07041, 07119, 07137, 07273, 07313, 07454, 07871, 08104, 08714, 08726, 08995, 09059, 09073, 09525, 09949, 09981, 10092, 10439, 10782, 11185, 11507, 11712, 11806, 11858, 11980, 12067, 12113, 12139, 12643, 13820, 14534, 15007, 15014, 15549, 15953, 16151, 16174, 16634, 16733, 16888, 17111, 17207, 17377, 17721, 17900, 18118, 18400, 18686, 18880, 19080, 19342, 19444, 19772, 19790, 19891, 20091, 20245, 20402, 20811, 21114, 21345, 21811, 21881, 22222, 22311, 22320, 22831, 22969, 23251, 23572, 23734, 23862, 23889, 24034, 24463, 25172, 25688, 26143, 26221, 26803, 26850, 26898, 27497, 28291, 28343, 29411, 29419, 30024, 30561, 30923, 31345, 31351, 31555, 31927, 32198, 32861, 33020, 33040, 33095, 33188, 33311, 33368, 33377, 33475, 33519, 33574, 33592, 34207, 34235, 34272, 34484, 34854, 34872, 34875, 34876, 34880, 35222, 35292, 35344, 36177, 36266, 37038, 37060, 37548, 37686, 37700, 38139, 39368, 39369, 39633, 40132, 40698, 40704, 40744, 40819, 41311, 41971, 42102, 42616, 43055, 43211, 43234, 43428, 43494, 43934, 44117, 44252, 44272, 44301, 44336, 44619, 44866, 44888, 45049, 45197, 45412, 45718, 46694, 46736, 47000, 48046, 48540, 49078, 49109, 49216, 49388, 49464, 50056, 50155, 50217, 50477, 50692, 51122, 51445, 51946, 52475, 52537, 52982, 54011, 54031, 54160, 54963, 55000, 55537, 56080, 56163, 56282, 56760, 56787, 57102, 57727, 57871, 58101, 58558, 58882, 59902, 60225, 60397, 60501, 60619, 60703, 60890, 61075, 61894, 61944, 62322, 62337, 62380, 62413, 62729, 62766, 62923, 63010, 63234, 63977, 64127, 65359, 65428, 65542, 65750, 65863, 66184, 66636, 66712, 67201, 67439, 67953, 68133, 68854, 69251, 69959, 70107, 70725, 70768, 71081, 71099, 71948, 72013, 72377, 72400, 72420, 72735, 73000, 73015, 73142, 73223, 73455, 73717, 74049, 74492, 74854, 74941, 75142, 75399, 75464, 75587, 75618, 75642, 75887, 76357, 76651, 77199, 77302, 77456, 77579, 77601, 77649, 77668, 77694, 77745, 78006, 78010, 78178, 78335, 78656, 78729, 78808, 78824, 78844, 78945, 79416, 79471, 79915, 80077, 80111, 80189, 80262, 80409, 80470, 80529, 80539, 80838, 81272, 81513, 81658, 81740, 81743, 81762, 81843, 82001, 82070, 82106, 82342, 82472, 82719, 83670, 84009, 84151, 84299, 84430, 84450, 84460, 84945, 86411, 86443, 86446, 86668, 86942, 87286, 87317, 87624, 87785, 88023, 88517, 88696, 88787, 88868, 88977, 89206, 90108, 90440, 90734, 90802, 90849, 90920, 90931, 91011, 91031, 91133, 91777, 91949, 92162, 92494, 93012, 93172, 94300, 94517, 95142, 95410, 95559, 95859, 96112, 97255, 97787, 97986, 98240, 98817, 99050, 99198, 99222, 99241, 99295, 99326, 99335, 99503, 99603, 99643, 99803, 99968}"
This code removes first and last character of the string ("{" and "}" characters), splits values by "," and removes whitespaces using trimws. After that it moves the format to number.
If it happens your data actually is json, stick with the rjson package. This answer is assuming your data is not json (since rjson::fromjson throws an error on your data)
Try:
string <- "{1948, 2507, 2510, 7030, 7110, 9009, 00027, 00206, 00399, 00717, 00814, 00828, 00848, 00917, 01050, 01105, 01144, 02130, 02768, 03037, 03752, 03754, 04070, 04110, 05050, 05255, 05289, 05564, 05595, 06100, 06330, 06671, 07041, 07119, 07137, 07273, 07313, 07454, 07871, 08104, 08714, 08726, 08995, 09059, 09073, 09525, 09949, 09981, 10092, 10439, 10782, 11185, 11507, 11712, 11806, 11858, 11980, 12067, 12113, 12139, 12643, 13820, 14534, 15007, 15014, 15549, 15953, 16151, 16174, 16634, 16733, 16888, 17111, 17207, 17377, 17721, 17900, 18118, 18400, 18686, 18880, 19080, 19342, 19444, 19772, 19790, 19891, 20091, 20245, 20402, 20811, 21114, 21345, 21811, 21881, 22222, 22311, 22320, 22831, 22969, 23251, 23572, 23734, 23862, 23889, 24034, 24463, 25172, 25688, 26143, 26221, 26803, 26850, 26898, 27497, 28291, 28343, 29411, 29419, 30024, 30561, 30923, 31345, 31351, 31555, 31927, 32198, 32861, 33020, 33040, 33095, 33188, 33311, 33368, 33377, 33475, 33519, 33574, 33592, 34207, 34235, 34272, 34484, 34854, 34872, 34875, 34876, 34880, 35222, 35292, 35344, 36177, 36266, 37038, 37060, 37548, 37686, 37700, 38139, 39368, 39369, 39633, 40132, 40698, 40704, 40744, 40819, 41311, 41971, 42102, 42616, 43055, 43211, 43234, 43428, 43494, 43934, 44117, 44252, 44272, 44301, 44336, 44619, 44866, 44888, 45049, 45197, 45412, 45718, 46694, 46736, 47000, 48046, 48540, 49078, 49109, 49216, 49388, 49464, 50056, 50155, 50217, 50477, 50692, 51122, 51445, 51946, 52475, 52537, 52982, 54011, 54031, 54160, 54963, 55000, 55537, 56080, 56163, 56282, 56760, 56787, 57102, 57727, 57871, 58101, 58558, 58882, 59902, 60225, 60397, 60501, 60619, 60703, 60890, 61075, 61894, 61944, 62322, 62337, 62380, 62413, 62729, 62766, 62923, 63010, 63234, 63977, 64127, 65359, 65428, 65542, 65750, 65863, 66184, 66636, 66712, 67201, 67439, 67953, 68133, 68854, 69251, 69959, 70107, 70725, 70768, 71081, 71099, 71948, 72013, 72377, 72400, 72420, 72735, 73000, 73015, 73142, 73223, 73455, 73717, 74049, 74492, 74854, 74941, 75142, 75399, 75464, 75587, 75618, 75642, 75887, 76357, 76651, 77199, 77302, 77456, 77579, 77601, 77649, 77668, 77694, 77745, 78006, 78010, 78178, 78335, 78656, 78729, 78808, 78824, 78844, 78945, 79416, 79471, 79915, 80077, 80111, 80189, 80262, 80409, 80470, 80529, 80539, 80838, 81272, 81513, 81658, 81740, 81743, 81762, 81843, 82001, 82070, 82106, 82342, 82472, 82719, 83670, 84009, 84151, 84299, 84430, 84450, 84460, 84945, 86411, 86443, 86446, 86668, 86942, 87286, 87317, 87624, 87785, 88023, 88517, 88696, 88787, 88868, 88977, 89206, 90108, 90440, 90734, 90802, 90849, 90920, 90931, 91011, 91031, 91133, 91777, 91949, 92162, 92494, 93012, 93172, 94300, 94517, 95142, 95410, 95559, 95859, 96112, 97255, 97787, 97986, 98240, 98817, 99050, 99198, 99222, 99241, 99295, 99326, 99335, 99503, 99603, 99643, 99803, 99968}"
string as list of characters:
string_as_list_char <- as.list(strsplit(gsub('\\{|\\}', '', string), ", "))[[1]]
or converted to numeric:
string_as_list_num <- as.list(as.numeric(strsplit(gsub('\\{|\\}', '', string), ", ")[[1]]))
I'm trying to fit some curves from the data below with a mono-exponential "decay". Graphical display is not as important as is pulling out the time constant. the y-axis is pA and the x is time in seconds.
dput(stackover_data)
structure(list(Time = c(0.09990001, 0.19990001, 0.29990001, 0.39990001,
0.49990001, 0.59990001, 0.69990001, 0.79990001, 0.89990001, 0.99990001,
1.09990001, 1.19990001, 1.29990001, 1.39990001, 1.49990001, 1.59990001,
1.69990001, 1.79990001, 1.89990001, 1.99990001, 2.09990001, 2.19990001,
2.29990001, 2.39990001, 2.49990001, 2.59990001, 2.69990001, 2.79990001,
2.89990001, 2.99990001, 3.09990001, 3.19990001, 3.29990001, 3.39990001,
3.49990001, 3.59990001, 3.69990001, 3.79990001, 3.89990001, 3.99990001,
4.09990001, 4.19990001, 4.29990001, 4.39990001, 4.49990001, 4.59990001,
4.69990001, 4.79990001, 4.89990001, 4.99990001, 5.09990001, 5.19990001,
5.29990001, 5.39990001, 5.49990001, 5.59990001, 5.69990001, 5.79990001,
5.89990001, 5.99990001, 6.09990001, 6.19990001, 6.29990001, 6.39990001,
6.49990001, 6.59990001, 6.69990001, 6.79990001, 6.89990001, 6.99990001,
7.09990001, 7.19990001, 7.29990001, 7.39990001, 7.49990001, 7.59990001,
7.69990001, 7.79990001, 7.89990001, 7.99990001, 8.09990001, 8.19990001,
8.29990001, 8.39990001, 8.49990001, 8.59990001, 8.69990001, 8.79990001,
8.89990001, 8.99990001, 9.09990001, 9.19990001, 9.29990001, 9.39990001,
9.49990001, 9.59990001, 9.69990001, 9.79990001, 9.89990001, 9.99990001,
10.09990001, 10.19990001, 10.29990001, 10.39990001, 10.49990001,
10.59990001, 10.69990001, 10.79990001, 10.89990001, 10.99990001,
11.09990001, 11.19990001, 11.29990001, 11.39990001, 11.49990001,
11.59990001, 11.69990001, 11.79990001, 11.89990001, 11.99990001,
12.09990001, 12.19990001, 12.29990001, 12.39990001, 12.49990001,
12.59990001, 12.69990001, 12.79990001, 12.89990001, 12.99990001,
13.09990001, 13.19990001, 13.29990001, 13.39990001, 13.49990001,
13.59990001, 13.69990001, 13.79990001, 13.89990001, 13.99990001,
14.09990001, 14.19990001, 14.29990001, 14.39990001, 14.49990001,
14.59990001, 14.69990001, 14.79990001, 14.89990001, 14.99990001,
15.09990001, 15.19990001, 15.29990001, 15.39990001, 15.49990001,
15.59990001, 15.69990001, 15.79990001, 15.89990001, 15.99990001,
16.09990001, 16.19990001, 16.29990001, 16.39990001, 16.49990001,
16.59990001, 16.69990001, 16.79990001, 16.89990001, 16.99990001,
17.09990001, 17.19990001, 17.29990001, 17.39990001, 17.49990001,
17.59990001, 17.69990001, 17.79990001, 17.89990001, 17.99990001,
18.09990001, 18.19990001, 18.29990001, 18.39990001, 18.49990001,
18.59990001, 18.69990001, 18.79990001, 18.89990001, 18.99990001,
19.09990001, 19.19990001, 19.29990001, 19.39990001, 19.49990001,
19.59990001, 19.69990001, 19.79990001, 19.89990001, 19.99990001
), `Trace 1` = c(-3.08656892325052, 9.36821982641837, 8.13806079083122,
10.7039590839898, 7.25670468903547, 4.31122291688919, 1.77905971163193,
-6.27606834721828, -8.65955381985049, -10.1445673910916, -10.6649772153892,
-6.52301948183154, -11.9757817854835, -0.976254254762154, 0.237467076202677,
-11.8114896779541, -11.0022757370468, -16.1845427042923, 2.70565927469852,
-18.9048281652216, -22.153682283437, -4363.32044948884, -3470.59111611883,
-2877.51064886248, -2253.51505229908, -1876.62974792002, -1541.14546478629,
-1288.26617158403, -1232.52313999354, -1042.98549163259, -938.795146277054,
-810.913567086442, -736.390770574588, -682.044521632168, -638.575324886466,
-596.587948389699, -629.282103146111, -569.200610245336, -587.387817942122,
-521.939307772762, -533.776693538631, -514.782451411908, -445.949395199026,
-451.026618716539, -461.669600651513, -442.372477296489, -426.132547857502,
-452.471101919398, -449.377497412324, -436.817659066873, -487.464805660851,
-442.915455035179, -458.666741489705, -454.990437793055, -455.173154690614,
-426.885702219019, -456.985443835707, -408.869318611773, -442.418742303429,
-407.42593099033, -414.538253423006, -316.036755461507, -248.395118743017,
-198.708015370115, -183.88480278352, -160.041754268138, -139.020785864805,
-123.701641615743, -137.253323547789, -124.240619047461, -121.512859107349,
-113.719386521321, -102.98429740535, -118.721098087137, -109.789471870234,
-122.145399997255, -109.542467905009, -96.6725326170008, -108.16233877188,
-94.1092968366083, -88.0987495250118, -89.2245425850472, -96.3495439993499,
-110.340434956898, -98.8777265479938, -88.0674013452629, -102.755317774957,
-91.0752842494157, -107.959830375198, -78.8424385901398, -93.7743443479161,
-98.3591889757604, -72.3214090579355, -85.6296201608712, -112.596656084088,
-115.518068650615, -110.973655632476, -78.8021307215932, -85.6443070182152,
-93.1744356389988, -100.483987323044, -87.6672104421484, -83.6481077757535,
-82.1465876740715, -86.7838666454595, -75.9066755520263, -86.6416980998645,
-88.9405806921788, -74.0592581080291, -86.3433338300531, -93.5114839187431,
-91.1875849041866, -82.7018083540351, -102.859075734953, -82.1494206590809,
-79.2197323780198, -78.1558787387238, -86.2649418863144, -93.5271994290692,
-84.6678528566242, -71.4828270654073, -69.5618263581887, -67.2920558863641,
-58.1490330439793, -59.8163238740351, -73.6957797622946, -61.7673947702343,
-63.6492255747164, -64.043638367468, -73.8301991524909, -69.3055992018769,
-65.9342860783478, -74.9891521715357, -74.5779808619617, -69.9029875902787,
-69.746935396023, -71.35455530782, -73.5279471991205, -77.8000626250279,
-74.6065254864801, -64.0834786591292, -45.1346212136811, -43.1615385011179,
-42.554841323715, -50.276566542849, -56.1940469314277, -49.6368473019083,
-53.9842269565738, -54.1480156577708, -48.2160751112714, -43.2902743874793,
-46.4358385791469, -58.4459814967147, -49.0443619038303, -56.8007684056415,
-56.3345802020277, -40.1704617527471, -38.2624410086947, -39.9339279963857,
-27.7637250414188, -40.8686520798649, -30.9246406597275, -32.70021580322,
-28.7536071219405, -32.4403271637661, -30.3389870650563, -23.2866770834185,
-40.349370835336, -39.7478049410975, -38.4648592612063, -37.4191914226093,
-52.1259539643142, -38.0993644763616, -37.5493511061199, -25.0794144286873,
-32.6165749053184, -17.2616237291667, -32.1515419380766, -27.0814392288745,
-26.2440551871993, -17.5882979851251, -19.852012057918, -22.1408312947152,
-21.3395092026716, -28.0789344732281, -19.6443281019371, -26.6585778398899,
-24.2994817465722, -27.847437388783, -22.0565059455712, -24.8747905836351,
-30.7544250721296, -29.9924061105416, -22.5728855329732, -24.9767037068316,
-18.8208568928653, -10.7306087216159, -16.4281210876173, -19.3057174287183,
-15.9745523586581), `Trace 2` = c(5.94927992143286, 1.42121402161905,
6.78788136514507, 3.33970424403748, -3.73956433922802, -7.3097330836793,
-9.18242380095097, 3.29952017048882, 5.17208246028, 1.53238537592179,
6.90832098860733, 3.16748380079213, 5.49988319742749, 3.86758484926656,
11.981378748128, -0.208159377585758, -7.2781503569274, 1.71389537416221,
-4.77614396689646, -0.561115871778583, -14.5385068323377, -4944.63006397872,
-3891.23141079918, -3065.66300899921, -2527.61853791531, -2060.05223709386,
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-38.5815843253789, -45.001677748311, -43.0547862406721)), .Names = c("Time",
"Trace 1", "Trace 2", "Trace 3"), row.names = c(1000L, 2000L,
3000L, 4000L, 5000L, 6000L, 7000L, 8000L, 9000L, 10000L, 11000L,
12000L, 13000L, 14000L, 15000L, 16000L, 17000L, 18000L, 19000L,
20000L, 21000L, 22000L, 23000L, 24000L, 25000L, 26000L, 27000L,
28000L, 29000L, 30000L, 31000L, 32000L, 33000L, 34000L, 35000L,
36000L, 37000L, 38000L, 39000L, 40000L, 41000L, 42000L, 43000L,
44000L, 45000L, 46000L, 47000L, 48000L, 49000L, 50000L, 51000L,
52000L, 53000L, 54000L, 55000L, 56000L, 57000L, 58000L, 59000L,
60000L, 61000L, 62000L, 63000L, 64000L, 65000L, 66000L, 67000L,
68000L, 69000L, 70000L, 71000L, 72000L, 73000L, 74000L, 75000L,
76000L, 77000L, 78000L, 79000L, 80000L, 81000L, 82000L, 83000L,
84000L, 85000L, 86000L, 87000L, 88000L, 89000L, 90000L, 91000L,
92000L, 93000L, 94000L, 95000L, 96000L, 97000L, 98000L, 99000L,
100000L, 101000L, 102000L, 103000L, 104000L, 105000L, 106000L,
107000L, 108000L, 109000L, 110000L, 111000L, 112000L, 113000L,
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156000L, 157000L, 158000L, 159000L, 160000L, 161000L, 162000L,
163000L, 164000L, 165000L, 166000L, 167000L, 168000L, 169000L,
170000L, 171000L, 172000L, 173000L, 174000L, 175000L, 176000L,
177000L, 178000L, 179000L, 180000L, 181000L, 182000L, 183000L,
184000L, 185000L, 186000L, 187000L, 188000L, 189000L, 190000L,
191000L, 192000L, 193000L, 194000L, 195000L, 196000L, 197000L,
198000L, 199000L, 200000L), class = "data.frame")
I've tried doing lm(y~x)but it doesn't seem to get the right answer (verified the right answer in Igor) and obviously this is because its a linear model and not a exponential. Any all suggestions are welcomed. I'm struggling on this!
Thanks all!
names(DF) <- make.names(names(DF))
plot(Trace.1 ~ Time, data = DF)
#remove the initial values that clearly don't follow the model
DF1 <- DF[-seq_len(which((diff(DF$Trace.1) < -1e3))),]
plot(Trace.1 ~ Time, data = DF1)
fit <- nls(Trace.1 ~ SSasymp(Time, Asym, R0, lrc), data = DF1)
summary(fit)
coef(fit)
help("SSasymp") #for an explanation of the parameters
lines(DF1$Time, predict(fit))
Is there an R function or library that will give me the monthly (or any other specified timeframe) time weighted rate of return (twrr) for my portfolio?
I am including a dput dump of sample data below of the date and portfolio ending balance below. Not sure why the dates were dput'ed the way they were, but the first date 12053 is '2003-01-01' and the last date 12195 is '2003-05-23'.
portfolio.df <- structure(
list(
Date = structure(c(12053, 12054, 12055, 12058,
12059, 12060, 12061, 12062, 12065, 12066, 12067, 12068, 12069,
12073, 12074, 12075, 12076, 12079, 12080, 12081, 12082, 12083,
12086, 12087, 12088, 12089, 12090, 12093, 12094, 12095, 12096,
12097, 12101, 12102, 12103, 12104, 12107, 12108, 12109, 12110,
12111, 12114, 12115, 12116, 12117, 12118, 12121, 12122, 12123,
12124, 12125, 12128, 12129, 12130, 12131, 12132, 12135, 12136,
12137, 12138, 12139, 12142, 12143, 12144, 12145, 12146, 12149,
12150, 12151, 12152, 12153, 12156, 12157, 12158, 12159, 12163,
12164, 12165, 12166, 12167, 12170, 12171, 12172, 12173, 12174,
12177, 12178, 12179, 12180, 12181, 12184, 12185, 12186, 12187,
12188, 12191, 12192, 12193, 12194, 12195),
class = "Date"),
Ending_Balance = c(56250000L,
56852500L, 57080000L, 57355000L, 57477500L, 56817500L, 57885000L,
57810000L, 57732500L, 57670000L, 57520000L, 57285000L, 57270000L,
56655000L, 55802500L, 56337500L, 55642500L, 54510000L, 54987500L,
55802500L, 56065000L, 56865000L, 56635000L, 56497500L, 56640000L,
56155000L, 55757500L, 55972500L, 55865000L, 55535000L, 55885000L,
56840000L, 56902500L, 56945000L, 56622500L, 57012500L, 57200000L,
58072500L, 57612500L, 57447500L, 57157500L, 57032500L, 57405000L,
57502500L, 56785000L, 57007500L, 56342500L, 55697500L, 56655000L,
56900000L, 57002500L, 57465000L, 57467500L, 57382500L, 57982500L,
56562500L, 58065000L, 58935000L, 58502500L, 58200000L, 57767500L,
57757500L, 58055000L, 58305000L, 58277500L, 58295000L, 59047500L,
58907500L, 59125000L, 59072500L, 59107500L, 59315000L, 59690000L,
58957500L, 59407500L, 59385000L, 59965000L, 60297500L, 59890000L,
59822500L, 60367500L, 60407500L, 60380000L, 60815000L, 61155000L,
61080000L, 61132500L, 61265000L, 60912500L, 61107500L, 61445000L,
61345000L, 61137500L, 61035000L, 60707500L, 61340000L, 61365000L,
61402500L, 61640000L, 61675000L)),
.Names = c("Date", "Ending_Balance"),
row.names = c(NA, 100L),
class = "data.frame")