Stata中数据日期格式问题
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编者按：在涉及日期的数据处理中，特别是在不同软件之间相互读取数据时，常常使我们焦头烂额，为什么总得不到我们所要的结果。我认为，需要将各种格式的日期类型好好总结一下，特别是一些重要的函数，一定要烂记于心，这样才能得心应手。
要点：1.字符、数字、日期类型的转化技巧；
&2.众多的日期函数；
&3.字符型的截取函数运用。
Stata中数据格式的转换问题一直让我很头疼。我有两个数据库，同一个yeartime变量，都显示为yyyymm的格式，例如200110.
但是在一个数据库中为long .0g,另一个数据库中为float %tmCCYYNN.我要用yeartime
这个变量对两个数据库进行合并。数据格式无论如何转化都不行。请高手教教我怎么处理呢？
假设时间变量名为v1，显示为yyyymmdd的形式
对于v1是数字格式的情况，可用如下代码转换为Stata时间日期格式
gen year=int(v1/10000)
gen month=int((v1-year*1)
gen day=int((v1-year*10000-month*100))
gen date=mdy(month,day,year)
format date %td
对于v1是字符串格式的情况，可使用如下代码：
gen date=date(v1,"YMD")
谢谢你回复啊！我被这个日期格式搞疯了要。我输入%td格式，为什么一转成月份数据就直接变样子了啊。例如
01nov1999在%td格式下面，但是一转成%tm的就变成3172m6。为什么会有这种问题出现啊，请你教教我吧！谢谢啦！
还有,如果将日期型数据转化为数值型或者字符型该怎么能保证显示跟之前的日期型数据是一致的。我用你提到的类似的方法将月份型数据2012022转化为字符型的，g
begin=string(year(yeartime)*10^2+month(yeartime,"%6.0f"),结果出来的是196109，不知道怎么回事啊！
你第一个问题，把日数据变成月度数据：
还是假设时间变量名为v1
gen ym=mofd(v1)
format ym %tm
如果变成年度数据；
gen Year=year(DateAnnounced)
如果变成季度数据：
yq=qofd(DateAnnounced)
对于你第二个问题，保证所有日期数据格式一直，最好的方法是吧各种格式的（字符串的，数字的）转变为Stata日期格式。
Re: st: RE: dates
From&& Nick Cox &&A href="mailto:"&&
Subject&& Re: st: RE: dates
Date&& Sun, 9 Oct :00 +0100
&As you say, and as I implied, "month" here& is in the sense of Stata
monthly date, as returmed by -mofd()-,& not month of year alone.
On Sun, Oct 9, 2011 at 1:48 PM, Steven Samuels &&A href="mailto:"&& wrote:
& The one-step solution is very neat! I wasn't even aware of& of -dofm- . But substituting the month for -mofd- won't do because information on year is missing& In the original one-step formula, substitute for "visdate"& any date in the visit month, e.g. the first:
& day(dofm(1 + mofd(mdy(vmonth,1,vyear)))-1)
& On Oct 7, 2011, at 8:01 AM, Nick Cox wrote:
& In this particular problem you don't have a daily date, but just use the month instead of the result of -mofd()-.
& Nick Cox
& Suppose -visdate- as here is a daily date variable.
& Then the length of the current month is given by the last day of the
& current month, which is given by the first day of the next month less
& day(dofm(1 + mofd(visdate)) - 1)
& In steps:
& 1. current month is mofd(visdate)
& 2. next month is 1 + mofd(visdate)
& 3. first day of next month is dofm(1 + mofd(visdate))
& 4. last day of this month is dofm(1 + mofd(visdate)) - 1
& 5. day of last day ... you got it long since.
& But I never remember most of the function names and always have to
& look them up.
& It's key _never_ to type in rules about 28/31 or leap years, because
& Stata already knows.
& On Thu, Oct 6, 2011 at 11:55 PM, Steven Samuels &&A href="mailto:"&& wrote:
&& Oops! The original algorithm assigned days only from 1 to 15. The correction is below.& A better version& would assign days according to whether the month has 28, 29, 30, or 31 days, but I'll leave that to others.
&& With enough missing dates& it might be better to randomly assign a day of the month, or you risk distorting the distribution of inter-visit intervals.
&& *********************************
&& input str10 date
&& set seed 21932
&& gen visdate = date(date, "YMD")
&& tempvar day
&& gen str2 `day' = string(ceil(30*runiform())) if length(date)==6
&& replace `day' = "0"+`day' if real(`day')&10
&& gen fakeday = (length(date)==6)
&& replace visdate = date(date + `day', "YMD") if length(date)==6
&& format visdate %td
&& list date visdate fakeday
&& *****************************
&& On Oct 6, 2011, at 5:46 PM, Michael Eisenberg wrote:
&& Thanks so much.
&& On Thu, Oct 6, 2011 at 8:23 AM, Nick Cox &&A href="mailto:n.j.cox@durham.ac.uk"&n.j.cox@durham.ac.uk& wrote:
&&& You don't say what "without success" means precisely.
&&& "200801" does not match either date pattern. If there is no information on day of month, Stata can only return missing for a daily date.
&&& -date("200801" + "15", "YMD")- seems to be the most common fudge. I would always tag such guessed dates with an indicator variable.
&&& Michael Eisenberg
&&& I have a list of visit dates for patients.& Unfortunately, the format
&&& is not constant.
&&& Most are listed with the year, month, day such as
for Jan 5,
&&& 2008 but some are listed only with the year and month 200801 for Jan
&&& I attempted to convert them into stata dates with the commands below
&&& without success.
&&& gen ndate = date(dx_date, "YMD")
&&& gen ndate = date(dx_date, "CCYYNNDD")
&&& Can stata handle such inconsistent data?
代码示例：
input str10 date
set seed 21932
gen visdate = date(date, "YMD")
tempvar day
gen str2 `day' = string(ceil(30*runiform())) if length(date)==6
replace `day' = "0"+`day' if real(`day')&10
gen fakeday = (length(date)==6)
replace visdate = date(date + `day', "YMD") if length(date)==6
format visdate %td
list date visdate fakeday
gen ym=mofd(visdate)
format ym %tm
Stata has many tools for working with dates. This article will introduce you to some of the most useful and easy to use features.
A Stata date is simply a number, but with the&%td&format applied Stata will interpret that number as "number of days since January 1, 1960." You can then use that number in a variety of ways. Stata has similar tools that measure time in terms of milliseconds, months, quarters, years and more. This article will focus on days, but if you know how to work with days you can quickly learn the others.
Often the first task is to convert the data you've been given into official Stata dates.
Converting Strings to Dates
If you've been given a date in string form, such as "November 3, 2010", "11/3/2010" or " 08:35:12" it can be converted using the&date&function. The date function takes two arguments, the string to be converted, and a series of letters called a "mask" that tells Stata how the string is structured. In a date mask,&Y&means year,&M&means month,&D&means day and&#&means an element should be skipped.
Thus the mask&MDY&means "month, day, year" and can be used to convert both "November 3, 2010" and "11/3/2010". A date like " 08:35:12" requires the mask&YMD###&so that the last three numbers are skipped. If you are interested in tracking the time of day you need to switch to the&clock&function and the&%tc&format so time is measured in milliseconds rather than days, but they are very similar.
To see this in action, type (or copy and paste) the following into Stata:
use http://www.ssc.wisc.edu/sscc/pubs/files/dates.dta
This is an example data set containing the above dates as&dateString1,dateString2&and&dateString3. To convert them to Stata dates do the following:
gen date1=date(dateString1,"MDY")
gen date2=date(dateString2,"MDY")
gen date3=date(dateString3,"YMD###")
Note that the mask goes in quotes.
Converting Numbers to Dates
Another common scenario gives you dates as three separate numeric variables, one for the year, one for the month and one for the day. The&year,&month&and&day&variables in the example data set contain the same date as the others but in this format. To convert such dates to Stata dates, use the&mdy&function. It takes three numeric arguments: the month, day and year to be converted.
gen date4=mdy(month,day,year)
Formatting Date Variables
While the four date variables you've created are perfectly functional dates as far as Stata is concerned, they're difficult for humans to interpret. However, the&%td&format tells Stata to print them out as human readable dates:
format date1 %td
format date2 %td
format date3 %td
format date4 %td
This turns the&18569&now stored in all four variables into&03nov2010&(18,569 days since January 1, 1960) in all output. Try a&list&to see the result. If you remember your&, you can do them all at once with:
format date? %td
You can have Stata output dates in different formats as well. For instructions type&help dates&and then click on the link&Formatting date and time values.
Using Dates
Often your goal in creating a Stata date will be to create a time variable that can be included in a statistical command. If so, you can probably use it with no further modification. However, there are some common data preparation tasks involving dates.
Date Constants
If you need to refer to a particular date in your code, then in principle you could refer to it by number. However, it's usually more convenient to use the same functions used to import date variables. For example, the following are all equivalent ways of referring to November 3, 2010:
date("November 3, 2010","MDY")
mdy(11,3,2010)
The&td&pseudofunction was designed for tasks like this and is somewhat more convenient to use. It takes a single argument (which cannot be a variable name) and converts it to a date on the assumption that the argument is a string containing a date in the format day, month, year. This matches the output of the&%td&format, e.g.&3nov2010. Thus the following is also equivalent:
td(3nov2010)
However, the following is not:
td(11/3/2010)
This will be interpreted as March 11, 2010, not November 3, 2010.
Extracting Date Components
Sometimes you need to pull out the components of a date. You can do so with the&year,month&and&day&functions:
gen year1=year(date1)
gen month1=month(date1)
gen day1=day(date1)
Before and After
Since dates are just numbers, before and after are equivalent to less than and greater than. Thus:
gen before2010=(date1
gen after2010=(date1&date("January 1 2010","MDY"))
Durations and Intervals
Durations in days can be found using simple subtraction. The
example data set contains the dates&beginning&and&ending,
and you can find out the duration of the interval between them
gen duration=ending-beginning
Durations in months are more difficult because months vary in
length. One common approach is to ignore days entirely and
calculate the duration solely from the year and month components of
the dates involved:
durationInMonths=(year(ending)-year(beginning))*12+month(ending)-month(beginning)
Just keep in mind that this approach says January 31 and February 1
are one month apart, while January 1 and January 31 are zero months
Date Arithmetic
If you need to add (or subtract) a period measured in days to a
date, it is straightforward to do so. Just remember to format all
new date variables as dates with&%td:
gen tenDaysLater=date1+10
gen yesterday=date1-1
format %td tenDaysLater yesterday
If the period is measured in weeks, just multiply by 7. Months are
again problematic since different months have different lengths.
Years have the same problem if you need to be precise enough to
care about leap years.
You can avoid this by building a new date based on the components
of the old one, modified as required. The only trick is that you
must handle year changes properly. For example, the following works
gen oneMonthLater=mdy(month(date1)+1,day(date1),year(date1))
format %td oneMonthLater
oneMonthLater&is now December 3, 2010.
But the following does not:
twoMonthsLaterBad=mdy(month(date1)+2,day(date1),year(date1))
format %td twoMonthsLaterBad
This tries to set the month component of the new date to 13, which
is invalid. It needs to be January of the next year instead. The
following code will do allow you to add or subtract any number of
months (just change the final number in the first line and the name
of the new variable):
gen newMonth=month(date1)+2
gen newYear=year(date1)+floor((newMonth-1)/12)
replace newMonth=mod((newMonth-1),12)+1
gen twoMonthsLater=mdy(newMonth,day(date1),newYear)
format %td twoMonthsLater
drop newMonth newYear
If you need to do such things frequently you might want to turn
this bit of code into a program, or even an ado file.
Learning More
To read the full documentation on Stata dates,
then click on thedates
and times&link at the
top (the PDF documentation is much easier to read in this case).
There you'll learn to:
Work with times
Use intervals other than days, such as months, quarters or
Create your own date format for output (e.g.&November
3rd, 2010&rather
than3nov2010)
Track leap seconds, in case you need to be extremely
precise--you'll also find an explanation of why such things
Last Revised:&11/9/2010
Time Series Data in Stata
Time series data and tsset
To use Stata's time-series functions and analyses, you must first
make sure that your data are, indeed, time-series. First, you must
have a date variable that is in Stata date format. Secondly, you
must make sure that your data are sorted by this date variable. If
you have panel data, then your data must be sorted by the date
variable within the variable that identifies the panel. Finally,
you must use the&tsset&command
to tell Stata that your data are time-series:
sort datevar
tsset datevar
sort panelvar datevar
tsset panelvar datevar
The first example tells Stata that you have simple time-series
data, and the second tells Stata that you have panel data.
Stata Date Format
Stata stores dates as the number of elapsed days since January 1,
1960. There are different ways to create elapsed Stata dates that
depend on how dates are represented in your data. If your original
dataset already contains a single date variable, then use the
date() function or one of the other string-date commands. If you
have separate variables storing different parts of the date (month,
year and quarter, etc.) then you will need to use the
partial date variable functions.
Date functions for a single string date variable
Sometimes, your data will have the dates in string format. (A
string variable is simply a variable containing anything other than
just numbers.) Stata provides a way to convert these to time-series
dates. The first thing you need to know is that the string must be
easily separated into its components. In other words, strings like
"01feb1990" "February 1, 1990" "02/01/90" are acceptable, but
"020190" is not.
For example, let's say that you have a string variable "sdate" with
values like "01feb1990" and you need to convert it to a daily
time-series date:
gen daily=date(sdate,"DMY")
Note that in this function, as with the other functions to convert
strings to time-series dates, the "DMY" portion indicates the order
of the day, month and year in the variable. Had the values been
coded as "February 1, 1990" we would have used "MDY" instead. What
if the original date only has two digits for the year? Then we
would use:
gen daily=date(sdate,"DM19Y")
Whenever you have two digit years, simply place the century before
the "Y." If you have the last two digit years mixed, such as 1/2/98
and 1/2/00, use:
gen daily=date(sdate,"DMY",2020)
where 2020 is the largest year you have in your data set. Here are
the other functions:
weekly(stringvar,"wy")
monthly(stringvar,"my")
quarterly(stringvar,"qy")
halfyearly(stringvar,"hy")
yearly(stringvar,"y")
Note: Stata 10 uses upper case letters as DMY whereas earlier
version of Stata uses lower case, dmy.
Date functions for partial date variables
Often you will have separate variables for the various components
you need to put them together before you can designate
them as proper time-series dates. Stata provides an easy way to do
this with numeric variables. If you have separate variables for
month, day and year then use the mdy() function to create an
elapsed date variable. Once you have created an elapsed date
variable, you will probably want to format it, as described
Use the mdy() function to create an elapsed Stata date variable
when your original data contains separate variables for month, day
and year. The month, day and year variables must be numeric. For
example, suppose you are working with these data:
Use the following Stata command to generate a new variable named
gen mydate = mdy(month,day,year)
where mydate is an elapsed date varible, mdy() is the Stata
function, and month, day, and year are the names of the variables
that contain data for month, day and year, respectively.
If you have two variables, "year" and "quarter" use the "yq()"
gen qtr=yq(year,quarter)
gen qtr=yq(1990,3)
The other functions are:
mdy(month,day,year)
for daily data
yw(year, week)
for weekly data
ym(year,month)
for monthly data
yq(year,quarter)
for quarterly data
yh(year,half-year)
for half-yearly data
Converting a date variable stored as a single number
If you have a date variable where the date is stored as a single
number of the form yyyymmdd (for example,
for December 31,
2004) the following set of functions will convert it into a Stata
elapsed date.
gen year = int(date/10000)
gen month = int((date-year*1)
gen day = int((date-year*10000-month*100))
gen mydate = mdy(month,day,year)
format mydate %d
Time series date formats
Use the format command to display elapsed Stata dates as calendar
dates. In the example given above, the elapsed date variable,
mydate, has the following values, which represent the number of
days before or after January 1, 1960.
You can use the format command to display elapsed dates in a more
customary way. For example:
format mydate %d
where mydate is an elapsed date variable and %d is the format which
will be used to display values for that variable.
Other formats are available to control the display of elapsed
Time-series dates in Stata have their own formats similar to
regular date formats. The main difference is that for a regular
date format a "unit" or single "time period" is one day. For time
series formats, a unit or single time period can be a day, week,
month, quarter, half-year or year. There is a format for each of
these time periods:
Description
week 1, 1960
week 2, 1960
week 3, 1960
week 4, 1960
1st qtr, 1960
2nd qtr, 1960
3rd qtr, 1960
4th qtr, 1961
half-yearly
1st half, 1960
2nd half, 1960
1st half, 1961
2nd half, 1961
You should note that in the weekly format, the year is divided into
52 weeks. The first week is defined as the first seven days,
regardless of what day of the week it may be. Also, the last week,
week 52, may have 8 or 9 days. For the quarterly format, the first
quarter is January through March. For the half-yearly format, the
first half of the year is January through June.
It's even more important to note that you cannot jump from one
format to another by simply re-issuing the format command because
the units are different in each format. Here are the corresponding
results for January 1, 1999, which is an elapsed date of 14245:
These dates are so different because the elapsed date is actually
the number of weeks, quarters, etc., from the first week, quarter,
etc of 1960. The value for %ty is missing because it would be equal
to the year 14,245 which is beyond what Stata can accept.
Any of these time units can be translated to any of the others.
Stata provides functions to translate any time unit to and from %td
daily units, so all that is needed is to combine these
functions.
These functions translate to %td dates:
weekly to daily
monthly to daily
quarterly to daily
yearly to daily
These functions translate from %td dates:
daily to weekly
daily to monthly
daily to quarterly
daily to yearly
For more information see the Stata User's Guide, chapter 27.
Specifying dates
Often we need to consuct a particular analysis only on observations
that fall on a certain date. To do this, we have to use something
called a date literal. A date literal is simply a way of entering a
date in words and have Stata automatically convert it to an elapsed
date. As with the d() literal to specify a regular date, there are
the w(), m(), q(), h(), and y() literals for entering weekly,
monthly, quarterly, half-yearly, and yearly dates, respectively.
Here are some examples:
reg x y if w(1995w9)
sum income if q(1988-3)
tab gender if y(1999)
If you want to specify a range of dates, you can use the tin() and
twithin() functions:
reg y x if tin(01feb1990,01jun1990)
sum income if twithin(8-3)
The difference between tin() and twithin() is that tin() includes
the beginning and end dates, whereas twithin() excludes them.
Always enter the beginning date first, and write them out as you
would for any of the d(), w(), etc. functions.
Time Series Variable Lists
Often in time-series analyses we need to "lag" or "lead" the values
of a variable from one observation to the next. If we have many
variables, this can be cumbersome, especially if we need to lag a
variable more than once. In Stata, we can specify which variables
are to be lagged and how many times without having to create new
variables, thus saving alot of disk space and memory. You should
note that the tsset command must have been issued before any of the
"tricks" in this section will work. Also, if you have defined your
data as panel data, Stata will automatically re-start the
calculations as it comes to the beginning of a panel so you need
not worry about values from one panel being carried over to the
L.varname and F.varname
If you need to lag or lead a variable for an analysis, you can do
so by using the L.varname (to lag) and F.varname (to lead). Both
work the same way, so we'll just show some examples with L.varname.
Let's say you want to regress this year's income on last year's
reg income L.income
would accomplish this. The "L." tells Stata to lag income by one
time period. If you wanted to lag income by more than one time
period, you would simply change the L. to something like "L2." or
"L3." to lag it by 2 and 3 time periods, respectively. The
following two commands will produce the same results:
reg income L.income L2.income L3.income
reg income L(1/3).income
Another useful shortcut is D.varname, which takes the difference of
income in time 1 and income in time 2. For example, let's say a
person earned $20 yesterday and $30 today.
So, you can see that D.=(income-incomet-1) and
D2=(income-incomet-1)-(incomet-1-incomet-2)
S.varname refers to seasonal differences and works like D.varname,
except that the difference is always taken from the current
observation to the nthobservation:
In other words: S.income=income-incomet-1&and
S2.income=income-incomet-2
For more on lags, leads, differences and seasonal check
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