I'm currently working in
Stata on a dataset by which the year and quarter are given as 'YYYY QQ' in a string. I am trying to split this into year and quarter using the year and quarter functions. However, I keep getting a type error and have no idea why.
Those functions require a numeric argument and in any case the numeric argument should be a Stata daily date. There are various better ways forward for you. One is to use the split command with the destring option.
clear
set obs 1
gen given = "2022 3"
split given, destring
rename (given?) (year quarter)
You likely need a quarterly date any way and the function for that is quarterly().
gen wanted = quarterly(given, "YQ")
format wanted %tq
list
+----------------------------------+
| given year quarter wanted |
|----------------------------------|
1. | 2022 3 2022 3 2022q3 |
+----------------------------------+
See help datetime for basic documentation.
Related
I have data with a start and end date e.g.
+---+----------+------------+
| id| start| end|
+---+----------+------------+
| 1|2021-05-01| 2022-02-01|
| 2|2021-10-01| 2021-12-01|
| 3|2021-11-01| 2022-01-01|
| 4|2021-06-01| 2021-10-01|
| 5|2022-01-01| 2022-02-01|
| 6|2021-08-01| 2021-12-01|
+---+----------+------------+
I want a count for each month on how many observations were "active" in order to display that in a plot. With active I mean I want a count on how many observations have a start and end date that includes the given month. The result for the example data should look like this:
Example of a plot for the active times
I have looked into the pyspark Window function, but I don't think that can help me with my problem. So far my only idea is to specify an extra column for each month in the data and indicate whether the observation is active in that month and work from there. But I feel like there must be a much more efficient way to do this.
You can use sequence SQL. sequence will create the date range with start, end and interval and return the list.
Then, you can use explode to flatten the list and then count.
from pyspark.sql import functions as F
# Make sure your spark session is set to UTC.
# This SQL won't work well with a month interval if timezone is set to a place that has a daylight saving.
spark = (SparkSession
.builder
.config('spark.sql.session.timeZone', 'UTC')
... # other config
.getOrCreate())
df = (df.withColumn('range', F.expr('sequence(to_date(`start`), to_date(`end`), interval 1 month) as date'))
.withColumn('observation', F.explode('range')))
df = df.groupby('observation').count()
In Stata I have a variable yearmonth which is formatted as 201201, 201202 etc. for the years 2012 - 2019, monthly with no gaps. When I format the variable as
format yearmonth %tm
The results look like: 2.0e+05 for all periods, with the exact same number each time. A Dickey-Fuller test tells me I have gaps in my data (I don't) and a tsfill command generates dozens of empty observations between each period.
How do I properly format my yearmonth variable so I can set it as a monthly date?
You do have gaps — between 201212 and 201301, for example. Consider a statement like
gen wanted = ym(floor(yearmonth/100), mod(yearmonth, 100))
which parses your integers like 201201 into year and month components. So floor(201201/100) is floor(2012.01) and so 2012 while mod(201201, 100) is 1. The two components are then the arguments of ym() which expects a year and a month argument.
Then and only then will your format statement do you want. That command won’t create date variables.
See help datetime in Stata for more information and Problem with displaying reformatted string into a four-digit year in Stata 17 for an explanation of the difference between a date value and a date display format.
I am starting with a date_of_survey variable that is a string formatted as YYYY-MM-DD. I then run the following commands to convert it to a date variable, and display that variable in a useful format:
gen date = date(date_of_survey, "YMD")
gen date_clean = date
format date_clean %dM_d,_CY
drop date_of_survey
That leaves me with a "date_clean" variable displayed as "September 3, 2020" and a corresponding "date" variable displayed as "22161" (equal to days since January 1, 1960).
I now need to create a variable that indicates the year and quarter of each observation, preferably in YYYY-QQ format. I assumed this shouldn't be difficult, but no matter how I have coded it, I wind up with years in the 7000s and inaccurate quarters. I must be misunderstanding how the dates are stored. My first instinct was to try a simple format date %tq command, but I'm still not getting the output I need. Any help is much appreciated. I read over the help files, and can't find the discrepancy that's causing this little problem.
ANSWER: I needed to put the date variable into quarters since January 1, 2021. a qofd() function call before the format %tq did the trick!
I have a data frame which is a time series of meteorological measurement with monthly resolution from 1961 till 2018. I am interested in the variable that measures the monthly average temperature since I need the multi-annual average temperature for the summers.
To do this I must filter from the "DateVaraible" column the fifth and sixth digit, which are the month.
The values in time column are formatted like this
"19610701". So I need the 07(Juli) after 1961.
I start coding for 1 month for other purposes, so I did not try anything worth to mention. I guess that .grepl could do the work, but I do not know how the "matching" operator works.
So I started with this code that works.
summersmonth<- Df[DateVariable %like% "19610101" I DateVariable %like% "19610201"]
I am expecting a code like this
summermonths <- Df[DateVariable %like% "**06**" I DateVariable%like% "**07**..]
So that all entries with month digit from 06 to 09 are saved in the new dataframe summermonths.
Thanks in advance for any reply or feedback regarding my question.
Update
Thank to your answers I got the first part, which is to convert the variable in a as.date with the format "month"(Class=char)
Now I need to select months from Juni to September .
A horrible way to get the result I wanted is to do several subset and a rbind afterward.
Sommer1<-subset(Df, MonthVar == "Mai")
Sommer2<-subset(Df, MonthVar == "Juli")
Sommer3<-subset(Df, MonthVar == "September")
SummerTotal<-rbind(Sommer1,Sommer2,Sommer3)
I would be very glad to see this written in a tidy way.
Update 2 - Solution
Here is the tidy way, as here Using multiple criteria in subset function and logical operators
Veg_Seas<-subset(Df, subset = MonthVar %in% c("Mai","Juni","Juli","August","September"))
You can convert your date variable as date (format) and take the month:
allmonths <- month(as.Date(Df$DateVariable, format="%Y%m%d"))
Note that of your column has been originally imported as factor you need to convert it to character first:
allmonths <- month(as.Date(as.character(Df$DateVariable), format="%Y%m%d"))
Then you can check whether it is a summermonth:
summersmonth <- Df[allmonths %in% 6:9, ]
Example:
as.Date("20190702", format="%Y%m%d")
[1] "2019-07-02"
month(as.Date("20190702", format="%Y%m%d"))
[1] 7
We can use anydate from anytime to convert to Date class and then extract the month
library(anytime)
month(anydate(as.character(Df$DateVariable)))
The %tw format in Stata has the form: 1960w1 which has no equivalent in R.
Therefore %tw dates must be post-processed.
Importing a .dta file into R, the date is an integer like 1304 (instead of 1985w5) or 1426 (instead of 1987w23). If it was a simple time series you could set a starting date as follows:
ts(df, start= c(1985,5), frequency=52)
Another possibility would be:
as.Date(Camp$date, format= "%Yw%W" , origin = "1985w5")
But if each row is not a single date, then you must convert it.
The package ISOweek is based on ISO-8601 with the form "1985-W05" and does not process the Stata %tw.
The Lubridate package does not work with this format. The week() returns the number of complete seven day periods that have occurred between the date and January 1st, plus one. week function
In Stata week 1 of any year starts on 1 January, whatever day of the week that is. Stata Documentation on Dates
In the format %W of Date in R the week starts as Monday as first day of the week.
From strptime %V is
the Week of the year as decimal number (00--53) as defined in ISO
8601. If the week (starting on Monday) containing 1 January has four or more days in the new year, then it is considered week 1. Otherwise,
it is the last week of the previous year, and the next week is week 1.
(Accepted but ignored on input.) Strptime
Larmarange noted on Github that Haven doesn't interpret dates properly:
months, week, quarter and halfyear are specific format from Stata,
respectively %tm, %tw, %tq and %th. I'm not sure that there are
corresponding formats available in R. So far they are imported as
integers.
Is there a way to convert Stata %tw to a date format R understands?
Here is an Stata file with dates
This won't be an answer in terms of R code, but it is commentary on Stata weeks that can't be fitted into a comment.
Strictly, dates in Stata are not defined by the display formats that make them intelligible to people. A date in Stata is always a numeric variable or scalar or macro defined with origin the first instance in 1960. Thus it is at best a shorthand to talk about %tw dates, etc. We can use display to see the effects of different date display formats:
. di %td 0
01jan1960
. di %tw 0
1960w1
. di %tq 0
1960q1
. di %td 42
12feb1960
. di %tw 42
1960w43
. di %tq 42
1970q3
A subtle point made explicit above is that changing the display format will not change what is stored, i.e. the numeric value.
Otherwise put, dates in Stata are not distinct data types; they are just integers made intelligible as dates by a pertinent display format.
The question presupposes that it was correct to describe some weekly dates in terms of Stata weeks. This seems unlikely, as I know no instance in which a body outside StataCorp uses the week rules of Stata, not only that week 1 always starts on 1 January, but also that week 52 always includes either 8 or 9 days and hence that there is never a week 53 in a calendar year.
So, you need to go upstream and find out what the data should have been. Failing some explanation, my best advice is to map the 52 weeks of each year to the days that start them, namely days 1(7)358 of each calendar year.
Stata weeks won't map one-to-one to any other scheme for defining weeks.
More in this article on Stata weeks
It's not completely clear what the question is but the year and week corresponding to 1304 are:
wk <- 1304
1960 + wk %/% 52
## [1] 1985
wk %% 52 + 1
## [1] 5
so assuming that the first week of the year is week 1 and starts on Jan 1st, the beginning of the above week is this date:
as.Date(paste(1960 + wk %/% 52, 1, 1, sep = "-")) + 7 * (wk %% 52)
## [1] "1985-01-29"