阿里彩票
彩种报告
雷欧 
2020-07-26
## 3210448065@qq.com
## leiou123
## 2849108450@qq.com
## leiou123
## https://rstudio.cloud/project/1198888
pkg <- c('plyr', 'tidyverse', 'magrittr', 'readr', 'readxl', 'tidyr',
'knitr', 'kableExtra', 'forecast', 'formattable', 'DT',
'lubridate', 'highcharter', 'htmltools', 'echarts4r')
plyr::l_ply(pkg, require, quietly = TRUE, character.only = TRUE, .print = FALSE)
1 数据
读取样本数据。
## 读取数据
fls <- suppressWarnings(list.files('data/彩种'))
smp <- fls %>% llply(., function(x) {
dtt <- x %>% str_replace_all('.xls', '') %>% ymd
smpp <- read_excel(paste0('data/彩种/', x)) %>%
.[-nrow(.),]
data.frame('日期' = dtt, smpp)
}) %>% bind_rows %>%
as_tibble %>%
mutate('彩种名称' = factor(彩种名称), '盈率' = as.numeric(percent(盈率))) %>%
mutate_if(is.character, as.numeric)
rm(fls)
smp %>% datatable(
caption = "彩种数据",
escape = FALSE, filter = 'top', rownames = FALSE,
extensions = list('ColReorder' = NULL, 'RowReorder' = NULL,
'Buttons' = NULL, 'Responsive' = NULL),
options = list(dom = 'BRrltpi', autoWidth = TRUE, scrollX = TRUE,
lengthMenu = list(c(10, 50, 100, 500, -1),
c('10', '50', '100', '500', 'All')),
ColReorder = TRUE, rowReorder = TRUE,
buttons = list('copy', 'print',
list(extend = 'collection',
buttons = c('csv', 'excel', 'pdf'),
text = 'Download'), I('colvis'))))上图显示从2020-05-27到2020-07-24的报表数据。
2 绘图
2.1 投注人数
pl1 <- smp %>%
highchart() %>%
hc_chart('line', hcaes(x = 日期, y = 投注人数, group = 彩种名称)) %>%
hc_title(text = '彩种') %>%
hc_subtitle(text = '投注人数')
tagList(pl1)smp %>%
group_by(彩种名称) %>%
e_charts(x = 日期) %>%
e_line(投注人数, smooth = TRUE) %>%
e_datazoom(
type = 'slider',
toolbox = FALSE,
bottom = -5) %>%
e_tooltip() %>%
e_title(text = '彩种', subtext = '投注人数', left = 'center') %>%
e_axis_labels(x = '日期', y = '投注人数') %>%
e_x_axis(日期, axisPointer = list(show = TRUE)) %>%
e_legend(
orient = 'vertical',
type = c('scroll'),
#selectedMode = 'multiple', #https://echarts.apache.org/en/option.html#legend
#selected = list('彩种'),
left = 0, top = 80) %>%
e_grid(left = 150, top = 90) %>%
#e_theme('shine') %>%
e_toolbox_feature('saveAsImage', title = '截图')上图显示从2020-05-27到2020-07-24的投注人数，默认设置显示所有彩种，可以点击彩种筛选焦点彩种。
2.2 投注金额
smp %>%
hchart('line', hcaes(x = 日期, y = 投注金额, group = 彩种名称)) %>%
hc_title(text = '彩种') %>%
hc_subtitle(text = '投注金额')smp %>%
group_by(彩种名称) %>%
e_charts(x = 日期) %>%
e_line(投注金额, smooth = TRUE) %>%
e_datazoom(
type = 'slider',
toolbox = FALSE,
bottom = -5) %>%
e_tooltip() %>%
e_title(text = '彩种', subtext = '投注金额', left = 'center') %>%
e_axis_labels(x = '日期', y = '投注金额') %>%
e_x_axis(日期, axisPointer = list(show = TRUE)) %>%
e_legend(
orient = 'vertical',
type = c('scroll'),
left = 0, top = 80) %>%
e_grid(left = 150, top = 90) %>%
#e_theme('shine') %>%
e_toolbox_feature('saveAsImage', title = '截图')上图显示从2020-05-27到2020-07-24的投注金额，默认设置显示所有彩种，可以点击彩种筛选焦点彩种。
2.3 中奖金额
smp %>%
hchart('line', hcaes(x = 日期, y = 投注金额, group = 彩种名称)) %>%
hc_title(text = '彩种') %>%
hc_subtitle(text = '中奖金额')smp %>%
group_by(彩种名称) %>%
e_charts(x = 日期) %>%
e_line(中奖金额, smooth = TRUE) %>%
e_datazoom(
type = 'slider',
toolbox = FALSE,
bottom = -5) %>%
e_tooltip() %>%
e_title(text = '彩种', subtext = '中奖金额', left = 'center') %>%
e_axis_labels(x = '日期', y = '中奖金额') %>%
e_x_axis(日期, axisPointer = list(show = TRUE)) %>%
e_legend(
orient = 'vertical',
type = c('scroll'),
left = 0, top = 80) %>%
e_grid(left = 150, top = 90) %>%
#e_theme('shine') %>%
e_toolbox_feature('saveAsImage', title = '截图')上图显示从2020-05-27到2020-07-24的中奖金额，默认设置显示所有彩种，可以点击彩种筛选焦点彩种。
2.4 撤单金额
smp %>%
hchart('line', hcaes(x = 日期, y = 投注金额, group = 彩种名称)) %>%
hc_title(text = '彩种') %>%
hc_subtitle(text = '撤单金额')smp %>%
group_by(彩种名称) %>%
e_charts(x = 日期) %>%
e_line(撤单金额, smooth = TRUE) %>%
e_datazoom(
type = 'slider',
toolbox = FALSE,
bottom = -5) %>%
e_tooltip() %>%
e_title(text = '彩种', subtext = '撤单金额', left = 'center') %>%
e_axis_labels(x = '日期', y = '撤单金额') %>%
e_x_axis(日期, axisPointer = list(show = TRUE)) %>%
e_legend(
orient = 'vertical',
type = c('scroll'),
left = 0, top = 80) %>%
e_grid(left = 150, top = 90) %>%
#e_theme('shine') %>%
e_toolbox_feature('saveAsImage', title = '截图')上图显示从2020-05-27到2020-07-24的撤单金额，默认设置显示所有彩种，可以点击彩种筛选焦点彩种。
2.5 返点金额
smp %>%
hchart('line', hcaes(x = 日期, y = 投注金额, group = 彩种名称)) %>%
hc_title(text = '彩种') %>%
hc_subtitle(text = '返点金额')smp %>%
group_by(彩种名称) %>%
e_charts(x = 日期) %>%
e_line(返点金额, smooth = TRUE) %>%
e_datazoom(
type = 'slider',
toolbox = FALSE,
bottom = -5) %>%
e_tooltip() %>%
e_title(text = '彩种', subtext = '返点金额', left = 'center') %>%
e_axis_labels(x = '日期', y = '返点金额') %>%
e_x_axis(日期, axisPointer = list(show = TRUE)) %>%
e_legend(
orient = 'vertical',
type = c('scroll'),
left = 0, top = 80) %>%
e_grid(left = 150, top = 90) %>%
#e_theme('shine') %>%
e_toolbox_feature('saveAsImage', title = '截图')上图显示从2020-05-27到2020-07-24的返点金额，默认设置显示所有彩种，可以点击彩种筛选焦点彩种。
2.6 盈利
smp %>%
hchart('line', hcaes(x = 日期, y = 投注金额, group = 彩种名称)) %>%
hc_title(text = '彩种') %>%
hc_subtitle(text = '盈利')smp %>%
group_by(彩种名称) %>%
e_charts(x = 日期) %>%
e_line(盈利, smooth = TRUE) %>%
e_datazoom(
type = 'slider',
toolbox = FALSE,
bottom = -5) %>%
e_tooltip() %>%
e_title(text = '彩种', subtext = '盈利', left = 'center') %>%
e_axis_labels(x = '日期', y = '盈利') %>%
e_x_axis(日期, axisPointer = list(show = TRUE)) %>%
e_legend(
orient = 'vertical',
type = c('scroll'),
left = 0, top = 80) %>%
e_grid(left = 150, top = 90) %>%
#e_theme('shine') %>%
e_toolbox_feature('saveAsImage', title = '截图')上图显示从2020-05-27到2020-07-24的盈利，默认设置显示所有彩种，可以点击彩种筛选焦点彩种。
2.7 盈率
smp %>%
hchart('line', hcaes(x = 日期, y = 投注金额, group = 彩种名称)) %>%
hc_title(text = '彩种') %>%
hc_subtitle(text = '盈率')smp %>%
group_by(彩种名称) %>%
e_charts(x = 日期) %>%
e_line(盈率, smooth = TRUE) %>%
e_datazoom(
type = 'slider',
toolbox = FALSE,
bottom = -5) %>%
e_tooltip() %>%
e_title(text = '彩种', subtext = '盈率', left = 'center') %>%
e_axis_labels(x = '日期', y = '盈率') %>%
e_x_axis(日期, axisPointer = list(show = TRUE)) %>%
e_legend(
orient = 'vertical',
type = c('scroll'),
left = 0, top = 80) %>%
e_grid(left = 150, top = 90) %>%
#e_theme('shine') %>%
e_toolbox_feature('saveAsImage', title = '截图')上图显示从2020-05-27到2020-07-24的盈率，默认设置显示所有彩种，可以点击彩种筛选焦点彩种。
3 结论
3.2 附录
suppressMessages(require('dplyr', quietly = TRUE))
suppressMessages(require('formattable', quietly = TRUE))
suppressMessages(require('knitr', quietly = TRUE))
suppressMessages(require('kableExtra', quietly = TRUE))
sys1 <- devtools::session_info()$platform %>%
unlist %>% data.frame(Category = names(.), session_info = .)
rownames(sys1) <- NULL
#sys1 %<>% rbind(., data.frame(
# Category = 'Current time',
# session_info = paste(as.character(lubridate::now('Asia/Tokyo')), 'JST'))) %>%
# dplyr::filter(Category != 'os')
sys2 <- data.frame(Sys.info()) %>% mutate(Category = rownames(.)) %>% .[2:1]
names(sys2)[2] <- c('Sys.info')
rownames(sys2) <- NULL
if (nrow(sys1) == 7 & nrow(sys2) == 8) {
sys1 %<>% rbind(., data.frame(
Category = 'Current time',
session_info = paste(as.character(lubridate::now('Asia/Tokyo')), 'JST')))
} else {
sys2 %<>% rbind(., data.frame(
Category = 'Current time',
Sys.info = paste(as.character(lubridate::now('Asia/Tokyo')), 'JST')))
}
cbind(sys1, sys2) %>%
kable(caption = 'Additional session information:') %>%
kable_styling(bootstrap_options = c('striped', 'hover', 'condensed', 'responsive'))| Category | session_info | Category | Sys.info |
|---|---|---|---|
| version | R version 4.0.2 (2020-06-22) | sysname | Linux |
| os | Ubuntu 16.04.6 LTS | release | 5.3.0-1017-aws |
| system | x86_64, linux-gnu | version | #18~18.04.1-Ubuntu SMP Wed Apr 8 15:12:16 UTC 2020 |
| ui | X11 | nodename | application-2613621-deployment-6783693-jlfct |
| language | (EN) | machine | x86_64 |
| collate | C.UTF-8 | login | unknown |
| ctype | C.UTF-8 | user | rstudio-user |
| tz | Etc/UTC | effective_user | rstudio-user |
| date | 2020-07-26 | Current time | 2020-07-26 23:17:18 JST |
rm(sys1, sys2)binary.com Interview Question I (Extention)尝试分别使用
3个月、6个月、12个月、18个月和24个月的数据，结果12个月的数据最为精准。↩︎