使用 R，我可以将这些月度目标拆分为每日目标吗？
Using R, can I take these monthly targets and split them into daily targets?
我想参加以下table：
并根据月份和年份将数据拆分为每日目标，以便使用 R 考虑闰年？
感谢您的帮助！！！
您可以使用 lubridate 中的 days_in_month 来获取每个月的正确天数，包括闰年。然后您可以将目标除以这个数字。
library(tidyverse)
library(lubridate)
df %>%
group_by(across(everything())) %>%
summarize(day = seq(days_in_month(
as.POSIXct(paste(year, match(month, month.name), 1, sep = "-")))),
.groups = "drop") %>%
group_by(year, month) %>%
mutate(daily_target = target_ticket_click / n()) %>%
ungroup() %>%
select(-target_ticket_click) %>%
as.data.frame()
#> month year day daily_target
#> 1 April 2023 1 278.9667
#> 2 April 2023 2 278.9667
#> 3 April 2023 3 278.9667
#> 4 April 2023 4 278.9667
#> 5 April 2023 5 278.9667
#> 6 April 2023 6 278.9667
#> 7 April 2023 7 278.9667
#> 8 April 2023 8 278.9667
#> 9 April 2023 9 278.9667
#> 10 April 2023 10 278.9667
#> 11 April 2023 11 278.9667
#> 12 April 2023 12 278.9667
#> 13 April 2023 13 278.9667
#> 14 April 2023 14 278.9667
#> 15 April 2023 15 278.9667
#> 16 April 2023 16 278.9667
#> 17 April 2023 17 278.9667
#> 18 April 2023 18 278.9667
#> 19 April 2023 19 278.9667
#> 20 April 2023 20 278.9667
#> 21 April 2023 21 278.9667
#> 22 April 2023 22 278.9667
#> 23 April 2023 23 278.9667
#> 24 April 2023 24 278.9667
#> 25 April 2023 25 278.9667
#> 26 April 2023 26 278.9667
#> 27 April 2023 27 278.9667
#> 28 April 2023 28 278.9667
#> 29 April 2023 29 278.9667
#> 30 April 2023 30 278.9667
#> 31 August 2022 1 256.9677
#> 32 August 2022 2 256.9677
#> 33 August 2022 3 256.9677
#> 34 August 2022 4 256.9677
#> 35 August 2022 5 256.9677
#> 36 August 2022 6 256.9677
#> 37 August 2022 7 256.9677
#> 38 August 2022 8 256.9677
#> 39 August 2022 9 256.9677
#> 40 August 2022 10 256.9677
#> 41 August 2022 11 256.9677
#> 42 August 2022 12 256.9677
#> 43 August 2022 13 256.9677
#> 44 August 2022 14 256.9677
#> 45 August 2022 15 256.9677
#> 46 August 2022 16 256.9677
#> 47 August 2022 17 256.9677
#> 48 August 2022 18 256.9677
#> 49 August 2022 19 256.9677
#> 50 August 2022 20 256.9677
#> 51 August 2022 21 256.9677
#> 52 August 2022 22 256.9677
#> 53 August 2022 23 256.9677
#> 54 August 2022 24 256.9677
#> 55 August 2022 25 256.9677
#> 56 August 2022 26 256.9677
#> 57 August 2022 27 256.9677
#> 58 August 2022 28 256.9677
#> 59 August 2022 29 256.9677
#> 60 August 2022 30 256.9677
#> 61 August 2022 31 256.9677
#> 62 December 2022 1 500.6452
#> 63 December 2022 2 500.6452
#> 64 December 2022 3 500.6452
#> 65 December 2022 4 500.6452
#> 66 December 2022 5 500.6452
#> 67 December 2022 6 500.6452
#> 68 December 2022 7 500.6452
#> 69 December 2022 8 500.6452
#> 70 December 2022 9 500.6452
#> 71 December 2022 10 500.6452
#> 72 December 2022 11 500.6452
#> 73 December 2022 12 500.6452
#> 74 December 2022 13 500.6452
#> 75 December 2022 14 500.6452
#> 76 December 2022 15 500.6452
#> 77 December 2022 16 500.6452
#> 78 December 2022 17 500.6452
#> 79 December 2022 18 500.6452
#> 80 December 2022 19 500.6452
#> 81 December 2022 20 500.6452
#> 82 December 2022 21 500.6452
#> 83 December 2022 22 500.6452
#> 84 December 2022 23 500.6452
#> 85 December 2022 24 500.6452
#> 86 December 2022 25 500.6452
#> 87 December 2022 26 500.6452
#> 88 December 2022 27 500.6452
#> 89 December 2022 28 500.6452
#> 90 December 2022 29 500.6452
#> 91 December 2022 30 500.6452
#> 92 December 2022 31 500.6452
#> 93 February 2023 1 295.3929
#> 94 February 2023 2 295.3929
#> 95 February 2023 3 295.3929
#> 96 February 2023 4 295.3929
#> 97 February 2023 5 295.3929
#> 98 February 2023 6 295.3929
#> 99 February 2023 7 295.3929
#> 100 February 2023 8 295.3929
#> 101 February 2023 9 295.3929
#> 102 February 2023 10 295.3929
#> 103 February 2023 11 295.3929
#> 104 February 2023 12 295.3929
#> 105 February 2023 13 295.3929
#> 106 February 2023 14 295.3929
#> 107 February 2023 15 295.3929
#> 108 February 2023 16 295.3929
#> 109 February 2023 17 295.3929
#> 110 February 2023 18 295.3929
#> 111 February 2023 19 295.3929
#> 112 February 2023 20 295.3929
#> 113 February 2023 21 295.3929
#> 114 February 2023 22 295.3929
#> 115 February 2023 23 295.3929
#> 116 February 2023 24 295.3929
#> 117 February 2023 25 295.3929
#> 118 February 2023 26 295.3929
#> 119 February 2023 27 295.3929
#> 120 February 2023 28 295.3929
#> 121 January 2023 1 265.1613
#> 122 January 2023 2 265.1613
#> 123 January 2023 3 265.1613
#> 124 January 2023 4 265.1613
#> 125 January 2023 5 265.1613
#> 126 January 2023 6 265.1613
#> 127 January 2023 7 265.1613
#> 128 January 2023 8 265.1613
#> 129 January 2023 9 265.1613
#> 130 January 2023 10 265.1613
#> 131 January 2023 11 265.1613
#> 132 January 2023 12 265.1613
#> 133 January 2023 13 265.1613
#> 134 January 2023 14 265.1613
#> 135 January 2023 15 265.1613
#> 136 January 2023 16 265.1613
#> 137 January 2023 17 265.1613
#> 138 January 2023 18 265.1613
#> 139 January 2023 19 265.1613
#> 140 January 2023 20 265.1613
#> 141 January 2023 21 265.1613
#> 142 January 2023 22 265.1613
#> 143 January 2023 23 265.1613
#> 144 January 2023 24 265.1613
#> 145 January 2023 25 265.1613
#> 146 January 2023 26 265.1613
#> 147 January 2023 27 265.1613
#> 148 January 2023 28 265.1613
#> 149 January 2023 29 265.1613
#> 150 January 2023 30 265.1613
#> 151 January 2023 31 265.1613
#> 152 July 2022 1 255.2903
#> 153 July 2022 2 255.2903
#> 154 July 2022 3 255.2903
#> 155 July 2022 4 255.2903
#> 156 July 2022 5 255.2903
#> 157 July 2022 6 255.2903
#> 158 July 2022 7 255.2903
#> 159 July 2022 8 255.2903
#> 160 July 2022 9 255.2903
#> 161 July 2022 10 255.2903
#> 162 July 2022 11 255.2903
#> 163 July 2022 12 255.2903
#> 164 July 2022 13 255.2903
#> 165 July 2022 14 255.2903
#> 166 July 2022 15 255.2903
#> 167 July 2022 16 255.2903
#> 168 July 2022 17 255.2903
#> 169 July 2022 18 255.2903
#> 170 July 2022 19 255.2903
#> 171 July 2022 20 255.2903
#> 172 July 2022 21 255.2903
#> 173 July 2022 22 255.2903
#> 174 July 2022 23 255.2903
#> 175 July 2022 24 255.2903
#> 176 July 2022 25 255.2903
#> 177 July 2022 26 255.2903
#> 178 July 2022 27 255.2903
#> 179 July 2022 28 255.2903
#> 180 July 2022 29 255.2903
#> 181 July 2022 30 255.2903
#> 182 July 2022 31 255.2903
#> 183 June 2022 1 497.7000
#> 184 June 2022 2 497.7000
#> 185 June 2022 3 497.7000
#> 186 June 2022 4 497.7000
#> 187 June 2022 5 497.7000
#> 188 June 2022 6 497.7000
#> 189 June 2022 7 497.7000
#> 190 June 2022 8 497.7000
#> 191 June 2022 9 497.7000
#> 192 June 2022 10 497.7000
#> 193 June 2022 11 497.7000
#> 194 June 2022 12 497.7000
#> 195 June 2022 13 497.7000
#> 196 June 2022 14 497.7000
#> 197 June 2022 15 497.7000
#> 198 June 2022 16 497.7000
#> 199 June 2022 17 497.7000
#> 200 June 2022 18 497.7000
#> 201 June 2022 19 497.7000
#> 202 June 2022 20 497.7000
#> 203 June 2022 21 497.7000
#> 204 June 2022 22 497.7000
#> 205 June 2022 23 497.7000
#> 206 June 2022 24 497.7000
#> 207 June 2022 25 497.7000
#> 208 June 2022 26 497.7000
#> 209 June 2022 27 497.7000
#> 210 June 2022 28 497.7000
#> 211 June 2022 29 497.7000
#> 212 June 2022 30 497.7000
#> 213 March 2023 1 268.3226
#> 214 March 2023 2 268.3226
#> 215 March 2023 3 268.3226
#> 216 March 2023 4 268.3226
#> 217 March 2023 5 268.3226
#> 218 March 2023 6 268.3226
#> 219 March 2023 7 268.3226
#> 220 March 2023 8 268.3226
#> 221 March 2023 9 268.3226
#> 222 March 2023 10 268.3226
#> 223 March 2023 11 268.3226
#> 224 March 2023 12 268.3226
#> 225 March 2023 13 268.3226
#> 226 March 2023 14 268.3226
#> 227 March 2023 15 268.3226
#> 228 March 2023 16 268.3226
#> 229 March 2023 17 268.3226
#> 230 March 2023 18 268.3226
#> 231 March 2023 19 268.3226
#> 232 March 2023 20 268.3226
#> 233 March 2023 21 268.3226
#> 234 March 2023 22 268.3226
#> 235 March 2023 23 268.3226
#> 236 March 2023 24 268.3226
#> 237 March 2023 25 268.3226
#> 238 March 2023 26 268.3226
#> 239 March 2023 27 268.3226
#> 240 March 2023 28 268.3226
#> 241 March 2023 29 268.3226
#> 242 March 2023 30 268.3226
#> 243 March 2023 31 268.3226
#> 244 May 2022 1 478.5161
#> 245 May 2022 2 478.5161
#> 246 May 2022 3 478.5161
#> 247 May 2022 4 478.5161
#> 248 May 2022 5 478.5161
#> 249 May 2022 6 478.5161
#> 250 May 2022 7 478.5161
#> 251 May 2022 8 478.5161
#> 252 May 2022 9 478.5161
#> 253 May 2022 10 478.5161
#> 254 May 2022 11 478.5161
#> 255 May 2022 12 478.5161
#> 256 May 2022 13 478.5161
#> 257 May 2022 14 478.5161
#> 258 May 2022 15 478.5161
#> 259 May 2022 16 478.5161
#> 260 May 2022 17 478.5161
#> 261 May 2022 18 478.5161
#> 262 May 2022 19 478.5161
#> 263 May 2022 20 478.5161
#> 264 May 2022 21 478.5161
#> 265 May 2022 22 478.5161
#> 266 May 2022 23 478.5161
#> 267 May 2022 24 478.5161
#> 268 May 2022 25 478.5161
#> 269 May 2022 26 478.5161
#> 270 May 2022 27 478.5161
#> 271 May 2022 28 478.5161
#> 272 May 2022 29 478.5161
#> 273 May 2022 30 478.5161
#> 274 May 2022 31 478.5161
#> 275 November 2022 1 924.8333
#> 276 November 2022 2 924.8333
#> 277 November 2022 3 924.8333
#> 278 November 2022 4 924.8333
#> 279 November 2022 5 924.8333
#> 280 November 2022 6 924.8333
#> 281 November 2022 7 924.8333
#> 282 November 2022 8 924.8333
#> 283 November 2022 9 924.8333
#> 284 November 2022 10 924.8333
#> 285 November 2022 11 924.8333
#> 286 November 2022 12 924.8333
#> 287 November 2022 13 924.8333
#> 288 November 2022 14 924.8333
#> 289 November 2022 15 924.8333
#> 290 November 2022 16 924.8333
#> 291 November 2022 17 924.8333
#> 292 November 2022 18 924.8333
#> 293 November 2022 19 924.8333
#> 294 November 2022 20 924.8333
#> 295 November 2022 21 924.8333
#> 296 November 2022 22 924.8333
#> 297 November 2022 23 924.8333
#> 298 November 2022 24 924.8333
#> 299 November 2022 25 924.8333
#> 300 November 2022 26 924.8333
#> 301 November 2022 27 924.8333
#> 302 November 2022 28 924.8333
#> 303 November 2022 29 924.8333
#> 304 November 2022 30 924.8333
#> 305 October 2022 1 338.2903
#> 306 October 2022 2 338.2903
#> 307 October 2022 3 338.2903
#> 308 October 2022 4 338.2903
#> 309 October 2022 5 338.2903
#> 310 October 2022 6 338.2903
#> 311 October 2022 7 338.2903
#> 312 October 2022 8 338.2903
#> 313 October 2022 9 338.2903
#> 314 October 2022 10 338.2903
#> 315 October 2022 11 338.2903
#> 316 October 2022 12 338.2903
#> 317 October 2022 13 338.2903
#> 318 October 2022 14 338.2903
#> 319 October 2022 15 338.2903
#> 320 October 2022 16 338.2903
#> 321 October 2022 17 338.2903
#> 322 October 2022 18 338.2903
#> 323 October 2022 19 338.2903
#> 324 October 2022 20 338.2903
#> 325 October 2022 21 338.2903
#> 326 October 2022 22 338.2903
#> 327 October 2022 23 338.2903
#> 328 October 2022 24 338.2903
#> 329 October 2022 25 338.2903
#> 330 October 2022 26 338.2903
#> 331 October 2022 27 338.2903
#> 332 October 2022 28 338.2903
#> 333 October 2022 29 338.2903
#> 334 October 2022 30 338.2903
#> 335 October 2022 31 338.2903
#> 336 September 2022 1 267.2333
#> 337 September 2022 2 267.2333
#> 338 September 2022 3 267.2333
#> 339 September 2022 4 267.2333
#> 340 September 2022 5 267.2333
#> 341 September 2022 6 267.2333
#> 342 September 2022 7 267.2333
#> 343 September 2022 8 267.2333
#> 344 September 2022 9 267.2333
#> 345 September 2022 10 267.2333
#> 346 September 2022 11 267.2333
#> 347 September 2022 12 267.2333
#> 348 September 2022 13 267.2333
#> 349 September 2022 14 267.2333
#> 350 September 2022 15 267.2333
#> 351 September 2022 16 267.2333
#> 352 September 2022 17 267.2333
#> 353 September 2022 18 267.2333
#> 354 September 2022 19 267.2333
#> 355 September 2022 20 267.2333
#> 356 September 2022 21 267.2333
#> 357 September 2022 22 267.2333
#> 358 September 2022 23 267.2333
#> 359 September 2022 24 267.2333
#> 360 September 2022 25 267.2333
#> 361 September 2022 26 267.2333
#> 362 September 2022 27 267.2333
#> 363 September 2022 28 267.2333
#> 364 September 2022 29 267.2333
#> 365 September 2022 30 267.2333
由 reprex package (v2.0.1)
创建于 2022-06-01
使用的数据 - 从相关图像转录
df <- data.frame(month = c(month.name[5:12], month.name[1:4]),
year = c(rep(2022, 8), rep(2023, 4)),
target_ticket_click = c(14834, 14931, 7914, 7966, 8017, 10487,
27745, 15520, 8220, 8271, 8318, 8369))
df
#> month year target_ticket_click
#> 1 May 2022 14834
#> 2 June 2022 14931
#> 3 July 2022 7914
#> 4 August 2022 7966
#> 5 September 2022 8017
#> 6 October 2022 10487
#> 7 November 2022 27745
#> 8 December 2022 15520
#> 9 January 2023 8220
#> 10 February 2023 8271
#> 11 March 2023 8318
#> 12 April 2023 8369
我想参加以下table：
并根据月份和年份将数据拆分为每日目标，以便使用 R 考虑闰年？
感谢您的帮助！！！
您可以使用 lubridate 中的 days_in_month 来获取每个月的正确天数，包括闰年。然后您可以将目标除以这个数字。
library(tidyverse)
library(lubridate)
df %>%
group_by(across(everything())) %>%
summarize(day = seq(days_in_month(
as.POSIXct(paste(year, match(month, month.name), 1, sep = "-")))),
.groups = "drop") %>%
group_by(year, month) %>%
mutate(daily_target = target_ticket_click / n()) %>%
ungroup() %>%
select(-target_ticket_click) %>%
as.data.frame()
#> month year day daily_target
#> 1 April 2023 1 278.9667
#> 2 April 2023 2 278.9667
#> 3 April 2023 3 278.9667
#> 4 April 2023 4 278.9667
#> 5 April 2023 5 278.9667
#> 6 April 2023 6 278.9667
#> 7 April 2023 7 278.9667
#> 8 April 2023 8 278.9667
#> 9 April 2023 9 278.9667
#> 10 April 2023 10 278.9667
#> 11 April 2023 11 278.9667
#> 12 April 2023 12 278.9667
#> 13 April 2023 13 278.9667
#> 14 April 2023 14 278.9667
#> 15 April 2023 15 278.9667
#> 16 April 2023 16 278.9667
#> 17 April 2023 17 278.9667
#> 18 April 2023 18 278.9667
#> 19 April 2023 19 278.9667
#> 20 April 2023 20 278.9667
#> 21 April 2023 21 278.9667
#> 22 April 2023 22 278.9667
#> 23 April 2023 23 278.9667
#> 24 April 2023 24 278.9667
#> 25 April 2023 25 278.9667
#> 26 April 2023 26 278.9667
#> 27 April 2023 27 278.9667
#> 28 April 2023 28 278.9667
#> 29 April 2023 29 278.9667
#> 30 April 2023 30 278.9667
#> 31 August 2022 1 256.9677
#> 32 August 2022 2 256.9677
#> 33 August 2022 3 256.9677
#> 34 August 2022 4 256.9677
#> 35 August 2022 5 256.9677
#> 36 August 2022 6 256.9677
#> 37 August 2022 7 256.9677
#> 38 August 2022 8 256.9677
#> 39 August 2022 9 256.9677
#> 40 August 2022 10 256.9677
#> 41 August 2022 11 256.9677
#> 42 August 2022 12 256.9677
#> 43 August 2022 13 256.9677
#> 44 August 2022 14 256.9677
#> 45 August 2022 15 256.9677
#> 46 August 2022 16 256.9677
#> 47 August 2022 17 256.9677
#> 48 August 2022 18 256.9677
#> 49 August 2022 19 256.9677
#> 50 August 2022 20 256.9677
#> 51 August 2022 21 256.9677
#> 52 August 2022 22 256.9677
#> 53 August 2022 23 256.9677
#> 54 August 2022 24 256.9677
#> 55 August 2022 25 256.9677
#> 56 August 2022 26 256.9677
#> 57 August 2022 27 256.9677
#> 58 August 2022 28 256.9677
#> 59 August 2022 29 256.9677
#> 60 August 2022 30 256.9677
#> 61 August 2022 31 256.9677
#> 62 December 2022 1 500.6452
#> 63 December 2022 2 500.6452
#> 64 December 2022 3 500.6452
#> 65 December 2022 4 500.6452
#> 66 December 2022 5 500.6452
#> 67 December 2022 6 500.6452
#> 68 December 2022 7 500.6452
#> 69 December 2022 8 500.6452
#> 70 December 2022 9 500.6452
#> 71 December 2022 10 500.6452
#> 72 December 2022 11 500.6452
#> 73 December 2022 12 500.6452
#> 74 December 2022 13 500.6452
#> 75 December 2022 14 500.6452
#> 76 December 2022 15 500.6452
#> 77 December 2022 16 500.6452
#> 78 December 2022 17 500.6452
#> 79 December 2022 18 500.6452
#> 80 December 2022 19 500.6452
#> 81 December 2022 20 500.6452
#> 82 December 2022 21 500.6452
#> 83 December 2022 22 500.6452
#> 84 December 2022 23 500.6452
#> 85 December 2022 24 500.6452
#> 86 December 2022 25 500.6452
#> 87 December 2022 26 500.6452
#> 88 December 2022 27 500.6452
#> 89 December 2022 28 500.6452
#> 90 December 2022 29 500.6452
#> 91 December 2022 30 500.6452
#> 92 December 2022 31 500.6452
#> 93 February 2023 1 295.3929
#> 94 February 2023 2 295.3929
#> 95 February 2023 3 295.3929
#> 96 February 2023 4 295.3929
#> 97 February 2023 5 295.3929
#> 98 February 2023 6 295.3929
#> 99 February 2023 7 295.3929
#> 100 February 2023 8 295.3929
#> 101 February 2023 9 295.3929
#> 102 February 2023 10 295.3929
#> 103 February 2023 11 295.3929
#> 104 February 2023 12 295.3929
#> 105 February 2023 13 295.3929
#> 106 February 2023 14 295.3929
#> 107 February 2023 15 295.3929
#> 108 February 2023 16 295.3929
#> 109 February 2023 17 295.3929
#> 110 February 2023 18 295.3929
#> 111 February 2023 19 295.3929
#> 112 February 2023 20 295.3929
#> 113 February 2023 21 295.3929
#> 114 February 2023 22 295.3929
#> 115 February 2023 23 295.3929
#> 116 February 2023 24 295.3929
#> 117 February 2023 25 295.3929
#> 118 February 2023 26 295.3929
#> 119 February 2023 27 295.3929
#> 120 February 2023 28 295.3929
#> 121 January 2023 1 265.1613
#> 122 January 2023 2 265.1613
#> 123 January 2023 3 265.1613
#> 124 January 2023 4 265.1613
#> 125 January 2023 5 265.1613
#> 126 January 2023 6 265.1613
#> 127 January 2023 7 265.1613
#> 128 January 2023 8 265.1613
#> 129 January 2023 9 265.1613
#> 130 January 2023 10 265.1613
#> 131 January 2023 11 265.1613
#> 132 January 2023 12 265.1613
#> 133 January 2023 13 265.1613
#> 134 January 2023 14 265.1613
#> 135 January 2023 15 265.1613
#> 136 January 2023 16 265.1613
#> 137 January 2023 17 265.1613
#> 138 January 2023 18 265.1613
#> 139 January 2023 19 265.1613
#> 140 January 2023 20 265.1613
#> 141 January 2023 21 265.1613
#> 142 January 2023 22 265.1613
#> 143 January 2023 23 265.1613
#> 144 January 2023 24 265.1613
#> 145 January 2023 25 265.1613
#> 146 January 2023 26 265.1613
#> 147 January 2023 27 265.1613
#> 148 January 2023 28 265.1613
#> 149 January 2023 29 265.1613
#> 150 January 2023 30 265.1613
#> 151 January 2023 31 265.1613
#> 152 July 2022 1 255.2903
#> 153 July 2022 2 255.2903
#> 154 July 2022 3 255.2903
#> 155 July 2022 4 255.2903
#> 156 July 2022 5 255.2903
#> 157 July 2022 6 255.2903
#> 158 July 2022 7 255.2903
#> 159 July 2022 8 255.2903
#> 160 July 2022 9 255.2903
#> 161 July 2022 10 255.2903
#> 162 July 2022 11 255.2903
#> 163 July 2022 12 255.2903
#> 164 July 2022 13 255.2903
#> 165 July 2022 14 255.2903
#> 166 July 2022 15 255.2903
#> 167 July 2022 16 255.2903
#> 168 July 2022 17 255.2903
#> 169 July 2022 18 255.2903
#> 170 July 2022 19 255.2903
#> 171 July 2022 20 255.2903
#> 172 July 2022 21 255.2903
#> 173 July 2022 22 255.2903
#> 174 July 2022 23 255.2903
#> 175 July 2022 24 255.2903
#> 176 July 2022 25 255.2903
#> 177 July 2022 26 255.2903
#> 178 July 2022 27 255.2903
#> 179 July 2022 28 255.2903
#> 180 July 2022 29 255.2903
#> 181 July 2022 30 255.2903
#> 182 July 2022 31 255.2903
#> 183 June 2022 1 497.7000
#> 184 June 2022 2 497.7000
#> 185 June 2022 3 497.7000
#> 186 June 2022 4 497.7000
#> 187 June 2022 5 497.7000
#> 188 June 2022 6 497.7000
#> 189 June 2022 7 497.7000
#> 190 June 2022 8 497.7000
#> 191 June 2022 9 497.7000
#> 192 June 2022 10 497.7000
#> 193 June 2022 11 497.7000
#> 194 June 2022 12 497.7000
#> 195 June 2022 13 497.7000
#> 196 June 2022 14 497.7000
#> 197 June 2022 15 497.7000
#> 198 June 2022 16 497.7000
#> 199 June 2022 17 497.7000
#> 200 June 2022 18 497.7000
#> 201 June 2022 19 497.7000
#> 202 June 2022 20 497.7000
#> 203 June 2022 21 497.7000
#> 204 June 2022 22 497.7000
#> 205 June 2022 23 497.7000
#> 206 June 2022 24 497.7000
#> 207 June 2022 25 497.7000
#> 208 June 2022 26 497.7000
#> 209 June 2022 27 497.7000
#> 210 June 2022 28 497.7000
#> 211 June 2022 29 497.7000
#> 212 June 2022 30 497.7000
#> 213 March 2023 1 268.3226
#> 214 March 2023 2 268.3226
#> 215 March 2023 3 268.3226
#> 216 March 2023 4 268.3226
#> 217 March 2023 5 268.3226
#> 218 March 2023 6 268.3226
#> 219 March 2023 7 268.3226
#> 220 March 2023 8 268.3226
#> 221 March 2023 9 268.3226
#> 222 March 2023 10 268.3226
#> 223 March 2023 11 268.3226
#> 224 March 2023 12 268.3226
#> 225 March 2023 13 268.3226
#> 226 March 2023 14 268.3226
#> 227 March 2023 15 268.3226
#> 228 March 2023 16 268.3226
#> 229 March 2023 17 268.3226
#> 230 March 2023 18 268.3226
#> 231 March 2023 19 268.3226
#> 232 March 2023 20 268.3226
#> 233 March 2023 21 268.3226
#> 234 March 2023 22 268.3226
#> 235 March 2023 23 268.3226
#> 236 March 2023 24 268.3226
#> 237 March 2023 25 268.3226
#> 238 March 2023 26 268.3226
#> 239 March 2023 27 268.3226
#> 240 March 2023 28 268.3226
#> 241 March 2023 29 268.3226
#> 242 March 2023 30 268.3226
#> 243 March 2023 31 268.3226
#> 244 May 2022 1 478.5161
#> 245 May 2022 2 478.5161
#> 246 May 2022 3 478.5161
#> 247 May 2022 4 478.5161
#> 248 May 2022 5 478.5161
#> 249 May 2022 6 478.5161
#> 250 May 2022 7 478.5161
#> 251 May 2022 8 478.5161
#> 252 May 2022 9 478.5161
#> 253 May 2022 10 478.5161
#> 254 May 2022 11 478.5161
#> 255 May 2022 12 478.5161
#> 256 May 2022 13 478.5161
#> 257 May 2022 14 478.5161
#> 258 May 2022 15 478.5161
#> 259 May 2022 16 478.5161
#> 260 May 2022 17 478.5161
#> 261 May 2022 18 478.5161
#> 262 May 2022 19 478.5161
#> 263 May 2022 20 478.5161
#> 264 May 2022 21 478.5161
#> 265 May 2022 22 478.5161
#> 266 May 2022 23 478.5161
#> 267 May 2022 24 478.5161
#> 268 May 2022 25 478.5161
#> 269 May 2022 26 478.5161
#> 270 May 2022 27 478.5161
#> 271 May 2022 28 478.5161
#> 272 May 2022 29 478.5161
#> 273 May 2022 30 478.5161
#> 274 May 2022 31 478.5161
#> 275 November 2022 1 924.8333
#> 276 November 2022 2 924.8333
#> 277 November 2022 3 924.8333
#> 278 November 2022 4 924.8333
#> 279 November 2022 5 924.8333
#> 280 November 2022 6 924.8333
#> 281 November 2022 7 924.8333
#> 282 November 2022 8 924.8333
#> 283 November 2022 9 924.8333
#> 284 November 2022 10 924.8333
#> 285 November 2022 11 924.8333
#> 286 November 2022 12 924.8333
#> 287 November 2022 13 924.8333
#> 288 November 2022 14 924.8333
#> 289 November 2022 15 924.8333
#> 290 November 2022 16 924.8333
#> 291 November 2022 17 924.8333
#> 292 November 2022 18 924.8333
#> 293 November 2022 19 924.8333
#> 294 November 2022 20 924.8333
#> 295 November 2022 21 924.8333
#> 296 November 2022 22 924.8333
#> 297 November 2022 23 924.8333
#> 298 November 2022 24 924.8333
#> 299 November 2022 25 924.8333
#> 300 November 2022 26 924.8333
#> 301 November 2022 27 924.8333
#> 302 November 2022 28 924.8333
#> 303 November 2022 29 924.8333
#> 304 November 2022 30 924.8333
#> 305 October 2022 1 338.2903
#> 306 October 2022 2 338.2903
#> 307 October 2022 3 338.2903
#> 308 October 2022 4 338.2903
#> 309 October 2022 5 338.2903
#> 310 October 2022 6 338.2903
#> 311 October 2022 7 338.2903
#> 312 October 2022 8 338.2903
#> 313 October 2022 9 338.2903
#> 314 October 2022 10 338.2903
#> 315 October 2022 11 338.2903
#> 316 October 2022 12 338.2903
#> 317 October 2022 13 338.2903
#> 318 October 2022 14 338.2903
#> 319 October 2022 15 338.2903
#> 320 October 2022 16 338.2903
#> 321 October 2022 17 338.2903
#> 322 October 2022 18 338.2903
#> 323 October 2022 19 338.2903
#> 324 October 2022 20 338.2903
#> 325 October 2022 21 338.2903
#> 326 October 2022 22 338.2903
#> 327 October 2022 23 338.2903
#> 328 October 2022 24 338.2903
#> 329 October 2022 25 338.2903
#> 330 October 2022 26 338.2903
#> 331 October 2022 27 338.2903
#> 332 October 2022 28 338.2903
#> 333 October 2022 29 338.2903
#> 334 October 2022 30 338.2903
#> 335 October 2022 31 338.2903
#> 336 September 2022 1 267.2333
#> 337 September 2022 2 267.2333
#> 338 September 2022 3 267.2333
#> 339 September 2022 4 267.2333
#> 340 September 2022 5 267.2333
#> 341 September 2022 6 267.2333
#> 342 September 2022 7 267.2333
#> 343 September 2022 8 267.2333
#> 344 September 2022 9 267.2333
#> 345 September 2022 10 267.2333
#> 346 September 2022 11 267.2333
#> 347 September 2022 12 267.2333
#> 348 September 2022 13 267.2333
#> 349 September 2022 14 267.2333
#> 350 September 2022 15 267.2333
#> 351 September 2022 16 267.2333
#> 352 September 2022 17 267.2333
#> 353 September 2022 18 267.2333
#> 354 September 2022 19 267.2333
#> 355 September 2022 20 267.2333
#> 356 September 2022 21 267.2333
#> 357 September 2022 22 267.2333
#> 358 September 2022 23 267.2333
#> 359 September 2022 24 267.2333
#> 360 September 2022 25 267.2333
#> 361 September 2022 26 267.2333
#> 362 September 2022 27 267.2333
#> 363 September 2022 28 267.2333
#> 364 September 2022 29 267.2333
#> 365 September 2022 30 267.2333
由 reprex package (v2.0.1)
创建于 2022-06-01使用的数据 - 从相关图像转录
df <- data.frame(month = c(month.name[5:12], month.name[1:4]),
year = c(rep(2022, 8), rep(2023, 4)),
target_ticket_click = c(14834, 14931, 7914, 7966, 8017, 10487,
27745, 15520, 8220, 8271, 8318, 8369))
df
#> month year target_ticket_click
#> 1 May 2022 14834
#> 2 June 2022 14931
#> 3 July 2022 7914
#> 4 August 2022 7966
#> 5 September 2022 8017
#> 6 October 2022 10487
#> 7 November 2022 27745
#> 8 December 2022 15520
#> 9 January 2023 8220
#> 10 February 2023 8271
#> 11 March 2023 8318
#> 12 April 2023 8369