更改日期的时间部分在图形上的显示方式 [英] Change how time portion of the date is displayed on graph
本文介绍了更改日期的时间部分在图形上的显示方式的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
这是dataex
* Example generated by -dataex-. To install: ssc install dataex
clear
input str23 eventname str10(eventdate scrapedate) byte pricepart float(thpercentile median v7 mean) str5 timestamp str19 datetime
"Home Team vs. Away Team" "2016-01-03" "2015-12-04" 1 117.02 153.635 215.135 178.74034 "07:59" "2015-12-04 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-04" 2 117.02 153.635 215.135 178.74034 "16:00" "2015-12-04 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-04" 3 117.02 153.635 215.135 178.74034 "23:59" "2015-12-04 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-05" 1 117.02 153.635 215.135 178.64935 "07:59" "2015-12-05 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-05" 2 110.335 150.62 210.775 175.1715 "16:00" "2015-12-05 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-05" 3 . . . . "23:59" "2015-12-05 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-06" 1 110.335 149.55 208.6575 174.38936 "07:59" "2015-12-06 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-06" 2 110.99 151.32 210 175.17485 "16:00" "2015-12-06 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-06" 3 . . . . "23:59" "2015-12-06 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-07" 1 110.77 151.5 214.98 176.9686 "07:59" "2015-12-07 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-07" 2 107.66 147.99 205.75 171.1186 "16:00" "2015-12-07 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-07" 3 104.97 145.01 205.2 169.3728 "23:59" "2015-12-07 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-08" 1 105.415 145.33 205.265 169.3202 "07:59" "2015-12-08 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-08" 2 104.97 145.65 205.54 169.6171 "16:00" "2015-12-08 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-08" 3 . . . . "23:59" "2015-12-08 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-09" 1 104.97 145.92 207.24 170.63264 "07:59" "2015-12-09 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-09" 2 104.97 147.16 205.435 169.48587 "16:00" "2015-12-09 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-09" 3 . . . . "23:59" "2015-12-09 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-10" 1 104.97 147.16 208.315 173.76367 "07:59" "2015-12-10 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-10" 2 104.99 147.99 210 176.39133 "16:00" "2015-12-10 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-10" 3 . . . . "23:59" "2015-12-10 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-11" 1 105.69 148.75 214.67 174.9753 "07:59" "2015-12-11 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-11" 2 105.69 148.75 214.2775 174.9714 "16:00" "2015-12-11 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-11" 3 105.69 148.965 214.825 182.88837 "23:59" "2015-12-11 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-12" 1 109.76 151.5 214.98 177.088 "07:59" "2015-12-12 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-12" 2 109.57 151.5 212.325 176.69136 "16:00" "2015-12-12 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-12" 3 110.1225 148.75 207.97 175.44093 "23:59" "2015-12-12 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-13" 1 110.55 148.75 210 175.927 "07:59" "2015-12-13 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-13" 2 110.55 148.75 209.995 176.09927 "16:00" "2015-12-13 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-13" 3 110.99 151.5 207.97 175.9855 "23:59" "2015-12-13 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-14" 1 110.99 151.5 207.97 176.13016 "07:59" "2015-12-14 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-14" 2 110.99 151.5 207.49 175.95207 "16:00" "2015-12-14 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-14" 3 113.65 151.32 207.25 176.1622 "23:59" "2015-12-14 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-15" 1 114.1825 151.41 207.49 176.63448 "07:59" "2015-12-15 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-15" 2 114.36 151.32 208.21 176.49957 "16:00" "2015-12-15 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-15" 3 112.24 150 210 174.69102 "23:59" "2015-12-15 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-16" 1 113.65 151.32 210.4 175.1356 "07:59" "2015-12-16 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-16" 2 113.065 151.32 211.775 176.25023 "16:00" "2015-12-16 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-16" 3 115.91 151.5 209.105 176.2387 "23:59" "2015-12-16 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-17" 1 114.36 150.545 207.25 173.55644 "07:59" "2015-12-17 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-17" 2 114.36 151.09 207.25 174.5637 "16:00" "2015-12-17 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-17" 3 112.135 148.75 207.25 172.02206 "23:59" "2015-12-17 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-18" 1 114.36 149.92 207.87 175.4566 "07:59" "2015-12-18 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-18" 2 113.65 148.75 207.25 173.69534 "16:00" "2015-12-18 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-18" 3 118.33 151.5 214.95 180.4201 "23:59" "2015-12-18 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-19" 1 118.56 152.99 215.71 180.30553 "07:59" "2015-12-19 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-19" 2 119.31 152.99 215.12 179.263 "16:00" "2015-12-19 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-19" 3 119.31 151.5 214.2325 178.78603 "23:59" "2015-12-19 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-20" 1 119.4925 152.99 215.71 181.24663 "07:59" "2015-12-20 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-20" 2 119.25 152.99 215.85 181.3266 "16:00" "2015-12-20 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-20" 3 119.5 154.05 216.61 181.498 "23:59" "2015-12-20 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-21" 1 120.2575 154.6 216.195 181.61243 "07:59" "2015-12-21 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-21" 2 119.705 154.05 216.46 181.6927 "16:00" "2015-12-21 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-21" 3 114.36 147.71 216.31 177.83945 "23:59" "2015-12-21 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-22" 1 114.36 148.75 217.78 179.7802 "07:59" "2015-12-22 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-22" 2 115.155 148.75 218.95 182.94615 "16:00" "2015-12-22 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-22" 3 114.12 147.85 214.8325 178.60695 "23:59" "2015-12-22 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-23" 1 114.36 148.44 215.1375 178.2195 "07:59" "2015-12-23 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-23" 2 114.36 147.71 214.28 176.39894 "16:00" "2015-12-23 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-23" 3 114.3 148.75 216.6775 181.7427 "23:59" "2015-12-23 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-24" 1 114.12 147.71 214.61 179.2775 "07:59" "2015-12-24 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-24" 2 113.885 147.71 214.445 177.577 "16:00" "2015-12-24 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-24" 3 118.4625 148.75 218.95 183.9876 "23:59" "2015-12-24 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-25" 1 118.33 148.75 217.78 182.2171 "07:59" "2015-12-25 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-25" 2 118.33 148.75 218.95 184.2348 "16:00" "2015-12-25 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-25" 3 118.33 148.75 218.95 184.0091 "23:59" "2015-12-25 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-26" 1 118.595 149.65 218.95 184.72743 "07:59" "2015-12-26 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-26" 2 116.575 148.75 218.95 183.86197 "16:00" "2015-12-26 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-26" 3 115.42 148.75 218.95 182.9738 "23:59" "2015-12-26 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-27" 1 115.5625 148.75 218.6575 183.38004 "07:59" "2015-12-27 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-27" 2 114.59 148.75 218.95 185.2042 "16:00" "2015-12-27 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-27" 3 119.5 149.93 218.95 186.70554 "23:59" "2015-12-27 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-28" 1 119.5 149.92 218.95 185.5134 "07:59" "2015-12-28 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-28" 2 119.5 151.195 219.345 188.6705 "16:00" "2015-12-28 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-28" 3 113.8275 141.56 202.37 170.03584 "23:59" "2015-12-28 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-29" 1 115.12 142.9 204.655 172.76167 "07:59" "2015-12-29 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-29" 2 115.42 142.9 204.655 171.8042 "16:00" "2015-12-29 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-29" 3 109.405 137.05 192.455 171.29094 "23:59" "2015-12-29 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-30" 1 108.86 131.96 181.35 161.5101 "07:59" "2015-12-30 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-30" 2 108.86 132.72 182.93 162.9379 "16:00" "2015-12-30 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-30" 3 103.32 128.86 180.84 163.9678 "23:59" "2015-12-30 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-31" 1 102.76 124.18 177.13 155.92645 "07:59" "2015-12-31 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-31" 2 103.12 125.35 176.13 156.4449 "16:00" "2015-12-31 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2015-12-31" 3 104.85 128.08 178 161.6073 "23:59" "2015-12-31 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-01" 1 104.86 130.025 177.985 161.02515 "07:59" "2016-01-01 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-01" 2 101.95 119.5 158.695 144.57149 "16:00" "2016-01-01 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-01" 3 104.86 127.885 177.12 163.0666 "23:59" "2016-01-01 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-02" 1 105.46 131.2 168.64 145.27736 "07:59" "2016-01-02 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-02" 2 105.46 131.19 166.3 144.06587 "16:00" "2016-01-02 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-02" 3 108.385 130.035 154.0075 138.77951 "23:59" "2016-01-02 23:59:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-03" 1 108.0925 129.74 148.7475 136.77663 "07:59" "2016-01-03 07:59:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-03" 2 109.55 125.35 145.57 134.23042 "16:00" "2016-01-03 16:00:00"
"Home Team vs. Away Team" "2016-01-03" "2016-01-03" 3 . . . . "23:59" "2016-01-03 23:59:00"
end
这些是我的do文件的内容，向您显示了我的努力:
These are the contents of my do file which shows you my effort:
gen double eventtime = clock(datetime, "YMDhms")
tsset eventtime, format(%tcNN/DD/CCYY_HH:MM:SS)
twoway (connected mean eventtime, msymbol(point) mfcolor(none)) ///
(connected median eventtime, msymbol(point) mfcolor(none)) ///
(connected thpercentile eventtime, msymbol(point) mfcolor(none)) ///
(connected v7 eventtime, msymbol(point) mfcolor(none)), ///
ytitle(Price in USD) ///
xtitle(Scrape Date) ///
xlabel(, angle(vertical) ///
format(%tcNN/DD/CCYY_HH:MM:SS)) xmtick(##10, angle(vertical))
我的努力结果是这样的:
The output of my efforts is this:
此输出的问题是我的csv文件中根本没有日期刻度标签的X轴HH:MM:SS部分！我的日期中代表日期的列具有3个模式"MM/DD/YYYY 07:59:00"，"MM/DD/YYYY 16:00:00"，"MM/DD/YYYY 23:59:00"..但是我的图形输出在轴标签中具有日期的这些HH:MM:SS位置，但在数据集.您在X轴标签中看到的所有HH:MM:SS部分(例如05:46:40，00:40:00，19:33:20等)都不存在于我的数据中！
My issue with this output is that none of the X-axis HH:MM:SS portion of date tick labels exist in my csv file at all! The column in my date that represents the date has the 3 patterns "MM/DD/YYYY 07:59:00", "MM/DD/YYYY 16:00:00", "MM/DD/YYYY 23:59:00".. But my graph output has these HH:MM:SS postions of the date in axis labels that are not present in the dataset. All of the HH:MM:SS portions that you see in the X-axis labels like 05:46:40, 00:40:00, 19:33:20 etc do not exist in my data!
问题:
-
是否有可能，使用我的csv中的
"MM/DD/YYYY 07:59:00"，"MM/DD/YYYY 16:00:00"，"MM/DD/YYYY 23:59:00"模式显示12个特定日期，而不是Stata自行查看相对位置并在X轴标签上相应地设置HH:MM:SS?
Is it possible, to display 12 specific dates with
"MM/DD/YYYY 07:59:00","MM/DD/YYYY 16:00:00","MM/DD/YYYY 23:59:00"pattern FROM my csv, instead of Stata taking it upon itself to look at the relative position and accordingly setting a HH:MM:SS on the X axis label?
是否可以在这些特定X轴日期点的4个点添加4条参考线，并在顶部添加自定义文字标记?我遇到的问题是，我似乎无法理解如何选择X轴上的位置，因为它们都是日期时间值，以及如何在特定的Y坐标处添加带有文本标记的多条参考线.
Can I add 4 reference lines at 4 of those specific X-axis date points, with a custom text marker on top? The issue I'm having with this is, I cannot seem to understand how to pick the positions in X axis as they are all datetime values and how I add multiple reference lines with a text marker at a specific Y coordinate.
如何在图形内部而不是外部设置较小的图例?
How can I set a smaller legend inside the graph instead of outside?
我希望我的输出类似于以下内容.
I would like my output to be something like the one below.
交叉发布于统计学家.
推荐答案
以下代码段获取最小和最大原始日期/时间值，根据所需步骤(在本例中为12)找到两次观察之间的间隔，然后遍历观察以获取每一步的日期/时间值，并将所有内容插入列表:
The following code snippet gets the minimum and maximum raw date/time values, finds the interval between observations based on the desired steps (in this case 12), then loops over observations to get the date/time value at every step and inserts everything in a list:
sort eventtime
summarize eventtime
local min = r(min)
local max = r(max)
local plus = _N / 12
local total = _N / `plus'
local dtlist `dtlist' `min'
local counter = 0
forvalues i = 1 / `total' {
local counter = `counter' + `plus'
local dtlist `dtlist' `=eventtime[`counter']'
}
local dtlist `dtlist' `max'
然后使用生成的列表绘制图形:
You then draw the graph using the generated list:
twoway (connected mean eventtime, msymbol(point) mfcolor(none)) ///
(connected median eventtime, msymbol(point) mfcolor(none)) ///
(connected thpercentile eventtime, msymbol(point) mfcolor(none)) ///
(connected v7 eventtime, msymbol(point) mfcolor(none)), ///
ytitle(Price in USD) xtitle(Scrape Date) ///
xlabel(`dtlist', format(%tcNN/DD/CCYY_HH:MM:SS) angle(vertical))
此外，这是如何在选项xlines()中选择并插入参考线的值的方法:
In addition, this is how you can pick and insert the values for the reference lines in option xlines():
display %15.0f eventtime[3]
1764892740000
xline(1765238340000 1765670340000 1766102340000 1766534340000, lwidth(vthin) ///
lcolor(gray))
可以为每个参考线添加一个文本框，如下所示:
A textbox can be added for each reference line as follows:
text(240 1765238340000 "CUSTOM" "TEXT" "MARKER 1", ///
orientation(horizontal) size(vsmall) justification(left) lwidth(vthin) fcolor(white) box)
类似地，可以通过以下方式添加图例:
Similarly, the legend can be added in the following way:
legend(pos(1) ring(0) col(1) symxsize(small) size(vsmall) rowgap(zero))
显然，您必须使用各种文本框和图例选项的值才能获得所需的外观.
You will obviously have to play with the values of the various textbox and legend options to achieve the exact appearance you need.
这篇关于更改日期的时间部分在图形上的显示方式的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
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