I am looking to do a CASE statement in a calculated field to identify dates as holidays, and have tried:
CASE
WHEN
FORMAT_DATETIME("%Y%M%D", date) BETWEEN 20190218 AND 20190219 OR
FORMAT_DATETIME("%Y%M%D", date) BETWEEN 20220220 AND 20220222
THEN 'presidents_day'
ELSE NULL
END
I am having trouble formatting the date correctly to use the BETWEEN statement and I am getting the error:
Invalid formula - Operator "BETWEEN" doesn't support TEXT BETWEEN NUMBER AND NUMBER. Operator "BETWEEN" supports ANY BETWEEN ANY AND ANY.
Data Set (Google Sheets):
date
17 Feb 2019
18 Feb 2019
19 Feb 2019
20 Feb 2019
19 Feb 2022
20 Feb 2022
21 Feb 2022
22 Feb 2022
23 Feb 2022
Expected output:
date
Date_CASE
Feb 17, 2019
Feb 18, 2019
presidents_day
Feb 19, 2019
presidents_day
Feb 20, 2019
Feb 19, 2022
Feb 20, 2022
presidents_day
Feb 21, 2022
presidents_day
Feb 22, 2022
presidents_day
Feb 23, 2022
Google Data Studio report
Using the BETWEEN operator in conjunction with the DATE function ("Creates a date" in the YYYY, MM, DD format) would create the required CASE statement (where date represents the date field):
CASE
WHEN
date BETWEEN DATE(2019, 02, 18) AND DATE(2019, 02, 19) OR
date BETWEEN DATE(2022, 02, 20) AND DATE(2022, 02, 22)
THEN "presidents_day"
ELSE NULL
END
Publicly editable Google Data Studio report (embedded Google Sheets data source) and a GIF to elaborate:
Related
let currentDate = moment();
let weekStart = currentDate.clone().startOf('week');
let weekEnd = currentDate.clone().endOf('week');
I want to know the start date and end date of every week for a given month.
expected output
In August month
In Array of object
1. 1 Aug 2021 - 7 Aug 2021
2. 8 Aug 2021 - 14 Aug 2021
3. 15 Aug 2021 - 21 Aug 2021
4. 22 Aug 2021 - 28 Aug 2021
5. 29 Aug 2021 - 31 Aug 2021
moment().startOf('week');
moment().endOf('week');
Refrence:
https://www.itsolutionstuff.com/post/moment-js-get-current-week-start-and-end-date-exampleexample.html
I'm trying to forecast an accumulated monthly time series (see data below) with the auto.arima function with exogenous regressors. I have two issues.
1) My first issue is that when I fit the model and use the forecast function to predict the second half of 2019 the forecast starts from zero as can be seen in this forecast plot.
This only happens when I include a matrix of exogenous regressors and not when I use a single time series as regressor as can be seen in this plot.
Why is that? My code is:
regnskab <- ts(data$Regnskab, frequency = 12, start = c(2014,1), end = c(2019,6))
budget <- ts(data$Budget, frequency = 12, start = c(2014,1), end = c(2019,6))
dagtilbud <- ts(data$Dagtilbud, frequency = 12, start = c(2014,1), end = c(2019,6))
skole <- ts(data$Skole, frequency = 12, start = c(2014,1), end = c(2019,6))
sundhed <- ts(data$Sundhed, frequency = 12, start = c(2014,1), end = c(2019,6))
miljø <- ts(data$Miljø, frequency = 12, start = c(2014,1), end = c(2019,6))
tsmatrix <- cbind(budget, dagtilbud, miljø, skole, sundhed)
fit <- auto.arima(regnskab, xreg = tsmatrix)
fcast <- forecast(fit, h = 6, xreg = tsmatrix)
autoplot(fcast)
summary(fcast)
2) My second issue is that I want a forecast for 6 months forward, but the h=6 option does not apply when including exogenous regressors. Can this be solved in any way? Again, it is not a problem without exogenous regressors.
I hope you can help and sorry for the data spamming!
A summary of my model:
> summary(fcast)
Forecast method: Regression with ARIMA(1,0,0)(1,0,0)[12] errors
Model Information:
Series: regnskab
Regression with ARIMA(1,0,0)(1,0,0)[12] errors
Coefficients:
ar1 sar1 budget dagtilbud miljø skole sundhed
0.7466 0.6693 0.0101 2.0861 0.1037 2.5240 7.7623
s.e. 0.0935 0.1042 0.0077 0.6967 1.7672 0.7535 2.6611
sigma^2 estimated as 1.884: log likelihood=-114.84
AIC=245.68 AICc=248.21 BIC=263.2
Error measures:
ME RMSE MAE MPE MAPE MASE ACF1
Training set -0.01739231 1.297694 0.9002519 -0.1065542 0.9060671 0.3687968 -0.03222251
> regnskab
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2014 19.11281 36.68003 54.66383 74.93864 94.10328 113.36373 134.96638 152.75095 170.79800 189.55430 207.00803 227.82096
2015 18.90205 37.20079 55.73305 75.44689 94.74538 115.03997 136.79829 155.41164 173.69889 191.96484 210.42391 231.52982
2016 20.12939 38.51516 56.32522 78.04822 97.46681 116.58424 139.43255 157.83048 175.26727 195.06259 213.73833 234.45281
2017 20.43082 38.55219 57.50119 78.07558 97.50132 119.13735 141.71973 161.49281 180.32002 199.27769 216.92571 239.40683
2018 19.35194 37.40571 55.36897 76.33412 95.90922 117.41442 140.03545 159.10527 177.88068 194.43207 215.28905 245.85670
2019 20.85722 40.01691 59.97383 81.92719 103.15225 123.81454
> tsmatrix
budget dagtilbud miljø skole sundhed
Jan 2014 230.0605 2.616639 0.597125 3.193017 0.456470
Feb 2014 230.0605 5.025708 1.047983 6.402845 1.012468
Mar 2014 230.0605 7.548424 1.458105 9.816814 1.602384
Apr 2014 230.0605 10.350321 1.957022 13.446215 2.263646
May 2014 230.0605 12.913356 2.439587 17.100957 2.873934
Jun 2014 230.0605 15.380146 2.915020 20.791343 3.498350
Jul 2014 230.0605 17.931069 3.434464 23.701276 3.987042
Aug 2014 230.0605 20.441732 3.837721 27.319389 4.597127
Sep 2014 230.0605 22.839922 4.295486 30.859254 5.185271
Oct 2014 230.0605 25.234620 4.761740 34.350629 5.819948
Nov 2014 230.0605 27.554525 5.163576 37.688182 6.416112
Dec 2014 230.0605 30.109529 5.742699 42.095747 7.313195
Jan 2015 234.5089 2.404843 0.643976 3.185265 0.477921
Feb 2015 234.5089 5.090533 1.094641 6.654691 1.040235
Mar 2015 234.5089 7.319261 1.462134 10.168618 1.659232
Apr 2015 234.5089 10.040823 1.943120 14.082780 2.356247
May 2015 234.5089 12.470742 2.431818 17.827494 2.963360
Jun 2015 234.5089 14.846720 3.019969 21.612527 3.615607
Jul 2015 234.5089 17.543682 3.540084 24.702634 4.126374
Aug 2015 234.5089 19.786612 3.984587 28.330977 4.741392
Sep 2015 234.5089 22.037785 4.362497 31.942762 5.367815
Oct 2015 234.5089 24.347196 4.805391 35.423452 6.019133
Nov 2015 234.5089 26.751255 5.250481 38.964450 6.642436
Dec 2015 234.5089 29.276667 5.789919 43.428855 7.555361
Jan 2016 237.2361 2.538133 0.721184 3.352676 0.508847
Feb 2016 237.2361 4.906975 1.377086 6.804320 1.100914
Mar 2016 237.2361 7.184724 1.719629 10.290800 1.744743
Apr 2016 237.2361 9.895237 2.333842 14.223635 2.480869
May 2016 237.2361 12.316509 2.850905 17.957433 3.115473
Jun 2016 237.2361 14.578536 3.404785 21.759111 3.858713
Jul 2016 237.2361 17.215216 3.867858 24.949928 4.359129
Aug 2016 237.2361 19.399769 4.406750 28.503968 5.030926
Sep 2016 237.2361 21.702215 4.792190 32.112449 5.674259
Oct 2016 237.2361 24.112579 5.238401 35.625806 6.328084
Nov 2016 237.2361 26.453919 5.677270 39.158270 6.977991
Dec 2016 237.2361 28.969565 6.098136 43.558768 7.974787
Jan 2017 241.9089 2.538901 0.917354 3.488151 0.535639
Feb 2017 241.9089 4.847981 1.450172 6.857674 1.138782
Mar 2017 241.9089 7.281994 1.899543 10.394615 1.808938
Apr 2017 241.9089 10.031959 2.388542 14.335895 2.554613
May 2017 241.9089 12.411935 2.893036 18.042788 3.206503
Jun 2017 241.9089 14.982942 3.282057 22.137085 3.959622
Jul 2017 241.9089 17.567382 3.770244 25.392706 4.540047
Aug 2017 241.9089 19.738993 4.484434 29.108498 5.196528
Sep 2017 241.9089 22.273634 5.051894 32.693173 5.870257
Oct 2017 241.9089 24.636583 5.456458 36.203329 6.544383
Nov 2017 241.9089 27.259158 5.793056 39.867875 7.249982
Dec 2017 241.9089 29.831986 6.079033 44.273697 8.269454
Jan 2018 246.0944 2.467981 0.985846 3.377469 0.544258
Feb 2018 246.0944 4.877189 1.383190 6.815726 1.167431
Mar 2018 246.0944 7.367918 1.738033 10.486250 1.848972
Apr 2018 246.0944 10.148353 2.249466 14.439246 2.614913
May 2018 246.0944 12.687311 2.844656 18.194669 3.328234
Jun 2018 246.0944 15.482606 3.616200 22.433048 4.108966
Jul 2018 246.0944 17.715938 3.982451 25.305411 4.689087
Aug 2018 246.0944 20.077201 4.696088 29.018017 5.396796
Sep 2018 246.0944 22.659831 5.158706 32.860215 6.087975
Oct 2018 246.0944 24.719623 5.586616 36.143198 6.713136
Nov 2018 246.0944 27.750904 6.069519 40.237747 7.501346
Dec 2018 246.0944 30.326036 6.308786 44.733470 8.564162
Jan 2019 251.9230 2.653607 0.932776 3.501389 0.595458
Feb 2019 251.9230 5.070721 1.445741 6.991538 1.243721
Mar 2019 251.9230 7.542256 1.825956 10.737607 1.941444
Apr 2019 251.9230 10.301781 2.330015 14.647082 2.733956
May 2019 251.9230 13.193286 2.999816 18.671285 3.455616
Jun 2019 251.9230 15.423716 3.516735 22.612031 4.145206
The xreg matrix in the forecast function should be for the future time periods. If you want h=6, then give a matrix of 6 rows corresponding to those 6 periods.
I am trying to create a rrule for my fullcalendar event, that occur on the 2nd Monday, Wednesday and Friday of the month for every month.
Here is the rrule I have tried
RRULE:FREQ=MONTHLY;COUNT=10;INTERVAL=1;WKST=SU;BYDAY=MO,WE,FR;BYSETPOS=2
events: [{
title: 'rrule event',
rrule: {
freq: RRule.MONTHLY,
count: 10,
interval: 1,
wkst: RRule.SU,
byweekday: [RRule.MO, RRule.WE, RRule.FR],
bysetpos: [2]
},
duration: '02:00',
rendering: 'inverse-background'
}
],
This is what I get
1 Fri, 03 May 2019 12:33:53 GMT
2 Wed, 05 Jun 2019 12:33:53 GMT
3 Wed, 03 Jul 2019 12:33:53 GMT
4 Mon, 05 Aug 2019 12:33:53 GMT
5 Wed, 04 Sep 2019 12:33:53 GMT
6 Fri, 04 Oct 2019 12:33:53 GMT
7 Mon, 04 Nov 2019 12:33:53 GMT
8 Wed, 04 Dec 2019 12:33:53 GMT
9 Fri, 03 Jan 2020 12:33:53 GMT
10 Wed, 05 Feb 2020 12:33:53 GMT
What is expected is
1 Mon, 08 Apr 2019
2 Wed, 10 Apr 2019
3 Fri, 12 Apr 2019
4 Mon, 13 May 2019
5 Wed, 08 May 2019
6 Fri, 10 May 2019.........
RFC 5545, section 3.3.10. states:
Each BYDAY value can also be preceded by a positive (+n) or
negative (-n) integer. If present, this indicates the nth
occurrence of a specific day within the MONTHLY or YEARLY "RRULE".
So the rule you're looking for literally specifies the 2nd Monday (2MO), Wednesday (2WE) and Friday (2FR) of each month.
FREQ=MONTHLY;COUNT=10;BYDAY=2MO,2WE,2FR
(click to see the results)
Note that INTERVAL=1 is the default and WKST=SU is meaningless in this case, so you can just as well omit them.
Btw, your rule basically says, of all Mondays, Wednesdays and Fridays of a month, take the second instance in that month.
I need to create a new data frame from my original whose format given below.
MonthFrom MonthTo
Jan 2010 May 2010
Mar 2010 Jan 2012
Jan 2011 Jun 2011
Mar 2010 Jun 2010
Feb 2012 Mar 2012
Feb 2013 Feb 2013 #please note that these two months same.
The example data set above is from my data. I want to create a data frame as below.
Month NumberofMonth
Jan 5
Jan 12
Feb 1
Feb 2
Mar 16
Mar 4
So Generally,the function will count the number of months between two dates (whose class yearmon), and will assign this number to corresponding date. For example, If the number of months in first row is 5 and the MonthFrom in the first row is January, the function will assign the 5 to january. Can anyone help me please?
Given that the zoo type yearmon you're using allows for basic math manipulation and month name extraction with format(), the following should work for you (unless I've missed something in your requirements):
library(zoo)
my.df <- data.frame(
MonthFrom=as.yearmon(c("Jan 2010", "Mar 2010", "Jan 2011", "Mar 2010", "Feb 2012", "Feb 2013")),
MonthTo=as.yearmon(c("May 2010", "Jan 2012", "Jun 2011", "Jun 2010", "Mar 2012", "Feb 2013")))
print(my.df)
## MonthFrom MonthTo
## 1 Jan 2010 May 2010
## 2 Mar 2010 Jan 2012
## 3 Jan 2011 Jun 2011
## 4 Mar 2010 Jun 2010
## 5 Feb 2012 Mar 2012
## 6 Feb 2013 Feb 2013
new.df <- data.frame(
Month=format(my.df$MonthFrom, "%b"),
NumberOfMonth= (my.df$MonthTo - my.df$MonthFrom) * 12 + 1)
print(new.df)
## Month NumberOfMonth
## 1 Jan 5
## 2 Mar 23
## 3 Jan 6
## 4 Mar 4
## 5 Feb 2
## 6 Feb 1
I am trying to sort the multi dimensional array on a date column. The first date in each row is start date and second one is end date. I want to sort the rows in ascending order based on start date.
The datastructure is:
data = [["p1aprd", "Monthly", "PRD", "Date {Wed Nov 06 2013 01:27:00 GMT-0800 (Pacific Daylight Time)}", "Date {Thu Nov 07 2013 01:28:00 GMT-0800 (Pacific Daylight Time)}", "2"],
["p1aprd", "Monthly", "PRD", "Date {Tue Nov 05 2013 01:29:00 GMT-0800 (Pacific Daylight Time)}", "Date {Wed Nov 06 2013 01:29:00 GMT-0800 (Pacific Daylight Time)}", "2"],
["p1aprd", "Monthly", "PRD", "Date {Mon Nov 04 2013 01:31:00 GMT-0800 (Pacific Daylight Time)}", "Date {Thu Nov 14 2013 01:31:00 GMT-0800 (Pacific Daylight Time)}", "2"],
["p1aprd", "Monthly", "PRD", "Date {Mon Nov 04 2013 01:00:00 GMT-0800 (Pacific Daylight Time)}", "Date {Thu Nov 14 2013 01:38:00 GMT-0800 (Pacific Daylight Time)}", "2"]];
I am trying the function:
data.sort((function(index){
return function(a, b){
return (a[index] === b[index] ? 0 : (a[index] < b[index] ? -1 : 1));
};})(4));
alert(data);
I tried all possible solutions suggested here but no luck. I might be overlooking some simple error here. Any help is really appreciated.
2 problems with your code:
1. you are comparing date string and not date.
2. you are passing 4 whereas index of start date is 3.
Try this:
function getDateFromString(str){ return new Date(str.match(/\{(.*) \(/)[1]); }
data.sort((function(index){
return function(a, b){
a = getDateFromString(a[index]);
b = getDateFromString(b[index]);
return a - b;
};
})(3));
alert(data);