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R - XTS: get the first dates and values ​​for each month from a daily time series with missing rows

I have a daily time series as myxts xts object in R , the date format is d / m / y. Now I want to reduce the original time series to those that take only the first date and value for each month in the series.

myxts[.indexmday(myxts) == 1] returns a series containing d / m / y with d = 1.

My problem is that I need 1 data for each month, and my problem is that my original series contains several months without date and data for the date of the 1st calendar day.

How can I tell R if there is no such date, then it takes the 2nd day for this particular month, and if the latter is not available, take the third and so on ...

For example, in the examples below, there is no February 1, 2014. Also not on January 1st.

 dates <- c('14/02/2014', '13/02/2014', '12/02/2014', '11/02/2014', '10/02/2014', '07/02/2014', '06/02/2014', '05/02/2014', '04/02/2014', '03/02/2014', '31/01/2014', '30/01/2014', '29/01/2014', '28/01/2014', '27/01/2014', '24/01/2014', '23/01/2014', '22/01/2014', '21/01/2014', '20/01/2014', '17/01/2014', '16/01/2014', '15/01/2014', '14/01/2014', '13/01/2014', '10/01/2014', '09/01/2014', '08/01/2014', '07/01/2014', '06/01/2014', '03/01/2014', '02/01/2014', '31/12/2013', '30/12/2013', '27/12/2013', '26/12/2013', '24/12/2013', '23/12/2013', '20/12/2013', '19/12/2013', '18/12/2013', '17/12/2013', '16/12/2013', '13/12/2013', '12/12/2013', '11/12/2013', '10/12/2013', '09/12/2013', '06/12/2013', '05/12/2013', '04/12/2013', '03/12/2013', '02/12/2013', '29/11/2013', '28/11/2013', '27/11/2013', '26/11/2013', '25/11/2013', '22/11/2013', '21/11/2013', '20/11/2013', '19/11/2013', '18/11/2013', '15/11/2013', '14/11/2013', '13/11/2013', '12/11/2013', '11/11/2013', '08/11/2013', '07/11/2013', '06/11/2013', '05/11/2013', '04/11/2013', '01/11/2013', '31/10/2013', '30/10/2013', '29/10/2013', '28/10/2013', '25/10/2013', '24/10/2013', '23/10/2013', '22/10/2013', '21/10/2013', '18/10/2013', '17/10/2013', '16/10/2013', '15/10/2013', '14/10/2013', '11/10/2013', '10/10/2013', '09/10/2013', '08/10/2013', '07/10/2013', '04/10/2013', '03/10/2013', '02/10/2013', '01/10/2013', '30/09/2013', '27/09/2013', '26/09/2013', '25/09/2013', '24/09/2013', '23/09/2013', '20/09/2013', '19/09/2013', '18/09/2013', '17/09/2013', '16/09/2013', '13/09/2013', '12/09/2013', '11/09/2013', '10/09/2013', '09/09/2013', '06/09/2013', '05/09/2013', '04/09/2013', '03/09/2013', '02/09/2013', '30/08/2013', '29/08/2013', '28/08/2013', '27/08/2013', '26/08/2013', '23/08/2013', '22/08/2013', '21/08/2013', '20/08/2013', '19/08/2013', '16/08/2013', '15/08/2013', '14/08/2013', '13/08/2013', '12/08/2013', '09/08/2013', '08/08/2013', '07/08/2013', '06/08/2013', '05/08/2013', '02/08/2013', '01/08/2013', '31/07/2013', '30/07/2013', '29/07/2013', '26/07/2013', '25/07/2013', '24/07/2013', '23/07/2013', '22/07/2013', '19/07/2013', '18/07/2013', '17/07/2013', '16/07/2013', '15/07/2013', '12/07/2013', '11/07/2013', '10/07/2013', '09/07/2013', '08/07/2013', '05/07/2013', '04/07/2013', '03/07/2013', '02/07/2013', '01/07/2013', '28/06/2013') values <- c(920.25, 918.5, 921.5, 921.5, 921, 919, 906.25, 899, 906.25, 903, 917, 924, 923.75, 917.5, 914.5, 921.75, 922.5, 919, 919, 907.75, 916.25, 907.5, 913.75, 900.25, 907, 907.25, 907.25, 912.25, 910.5, 910.25, 910.25, 923.5, 944.25, 945.5, 955.75, 950, 944.25, 945.75, 945.25, 935.25, 929, 919.5, 931.5, 917.75, 932, 932, 928, 934.25, 940.75, 943.75, 947.25, 945.75, 942.75, 943, 942, 941, 944.5, 934.75, 937.75, 923.25, 911, 910.75, 910.25, 911.25, 908.75, 901.25, 903.25, 903.25, 893, 888.5, 905, 903, 904, 915, 932.5, 937.25, 930.5, 925.75, 909.75, 911.5, 920, 936.5, 941.5, 939.25, 931.5, 945, 940.25, 931.5, 933.5, 925.25, 925.25, 935.5, 926.25, 922.5, 926.5, 922.5, 905.25, 913, 927.25, 920.5, 919, 906, 913, 925.25, 934.5, 924.25, 925.75, 944.25, 949.75, 943.5, 943.5, 938.75, 960, 971, 963.75, 960.75, 960.25, 958.5, 969.5, 978.75, 970, 961.75, 940.25, 941.75, 936.25, 938.75, 938.75, 942.25, 941.25, 937.25, 926, 927.75, 903.75, 903.75, 896, 906, 909.25, 920.25, 923.75, 927, 910.5, 908, 913.75, 910.5, 913.75, 914.25, 919.75, 918.5, 925.75, 928.75, 923.75, 919.75, 916.5, 916.25, 913.75, 913.75, 909.25, 913.25, 911.75, 902.25, 903.25, 879.75, 883.25, 883.25) myxts <- as.xts(values, order.by = as.Date(dates, format = '%d/%m/%Y'))
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2 answers

There is an startof function that may be useful here

 myxts[xts:::startof(myxts, "months")] [,1] 2013-06-28 883.25 2013-07-01 883.25 2013-08-01 927.00 2013-09-02 958.50 2013-10-01 905.25 2013-11-01 915.00 2013-12-02 942.75 2014-01-02 923.50 2014-02-03 903.00
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You can use period.apply or a monthly wrapper:

 apply.monthly(myxts,head,1) [,1] 2013-06-28 883.25 2013-07-31 883.25 2013-08-30 927.00 2013-09-30 958.50 2013-10-31 905.25 2013-11-29 915.00 2013-12-31 942.75 2014-01-31 923.50 2014-02-14 903.00

EDIT with endpoints (this is basically a startof code function introduced in another solution)

  myxts[head(endpoints(myxts, "months") + 1, -1)] ## edited as Gsee comment [,1] 2013-06-28 883.25 2013-07-01 883.25 2013-08-01 927.00 2013-09-02 958.50 2013-10-01 905.25 2013-11-01 915.00 2013-12-02 942.75 2014-01-02 923.50 2014-02-03 903.00
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Source: https://habr.com/ru/post/1202380/

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