R Under development (unstable) (2024-03-11 r86098 ucrt) -- "Unsuffered Consequences" Copyright (C) 2024 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > # Datastream User Created Timeseries > # ---------------------------------- > # > # Datastream permits users to create and manage custom items. One of these > # types is custom timeseries data. Clients can upload their own timeseries > # data to Datastream’s central systems. These can then be used in combination > # with Datastream maintained series in charts and data requests with the full > # power of the Datastream expressions language. > # > # DatastreamUserCreated_TimeSeries.R defines a TimeseriesClient class and > # ancillary classes that assist in creating and managing timeseries data. > # > # This simple test script demonstrates how to manage custom timeseries data > # using the DatastreamUserCreated_TimeSeries.R module. > # > # Prerequesites: > # > # Firstly, your Datastream credentials need to be permissioned to use the > # Datastream API services. To verify you have access, please access the API > # test page at https://product.datastream.com/dswsclient/Docs/TestUserCreatedItems.aspx. > # Selecting the "Get Token" service method, insert your Datastream credentials > # and press the Execute button. If your credentials are valid and are permissioned > # to access the API service, you will receive a token response. If you are not > # permissioned, you will receive below message > # "User 'Your ID' not entitled to ClientApi service.". > # Please contact your LSEG representative to get your ID permissioned. > # > # Once you have permissions to access the API service, you also need to be > # permissioned to specifically access the service that permits you to access > # and manage custom user created items such as timeseries. You can verify this > # by using the "Get All Items" service method on the above test page. Using the > # token returned from the GetToken method, copy the token into the Token field > # and then select Execute. If you are permissioned for the user created items > # service, you will get a response listing the timeseries available to you on > # Datastream. This may be an empty list if you are a new customer or have never created user created items before. If you > # are not permissioned, you will receive an error message: > # "ID 'Your ID' is not permissioned for user created items.". > # Please contact your LSEG representative to get your ID permissioned. > # > > library (DatastreamR) > library(logger) > > # You can set the threshold for log messages as given below > # logger::log_threshold(ERROR) > > # This is a simple support function for displaying the contents of an individual > # timeseries item. It's used frequently in the demos below. > ProcessTimeseriesResponse = function(tsResponse, tsName) + { + if (!is.null(tsResponse)) + { + # Any request dealing with a single user created item returns a DSUserObjectResponse. This has ResponseStatus property that indicates success or failure + if (tsResponse$ResponseStatus != DSUserObjectResponseStatus$UserObjectSuccess) + print(paste('Request failed for timeseries', tsName, 'with error ', names(DSUserObjectResponseStatus)[tsResponse$ResponseStatus + 1], ': ', tsResponse$ErrorMessage)) + else if (!is.null(tsResponse$UserObject)) # The timeseries item won't be returned if you set SkipItem true in CreateItem or UpdateItem + { + # Here we simply display the timeseries data using a dataframe. + tsItem = tsResponse$UserObject + metadata = c (Id = tsItem$Id, + Desc = tsItem$Description, + LastModified = as.character(tsItem$LastModified), + StartDate = ifelse (!is.null(tsItem$DateInfo), as.character(tsItem$DateInfo$StartDate), NULL), + EndDate = ifelse(!is.null(tsItem$DateInfo),as.character(tsItem$DateInfo$EndDate), NULL), + Frequency = ifelse(!is.null(tsItem$DateInfo), names(DSUserObjectFrequency)[tsItem$DateInfo$Frequency + 1], NULL), + NoOfValues = ifelse(!is.null(tsItem$DateRange), tsItem$DateRange$ValuesCount , 0)) + df = data.frame(metadata) + print(df) + + if (!is.null(tsItem$DateRange)) + { + df = data.frame(Dates = sapply(tsItem$DateRange$Dates, FUN = function(x) { return (as.character(x)) }), + Values = sapply(tsItem$DateRange$Values, FUN = function(x) { ifelse (is.null(x), return (NA_character_ ), return (x) )} )) + # Values if NULL, is printed as because, while converting list to vector + # either by using as.vector or sapply, the NULL values in the list are deleted. + # and thus there will be mismatch in no of rows and cannot be put in a dataframe + print(df) + } + } + } + else + print(paste('Timeseries ', tsName, ' successfully updated but item details not returned.')) + } > > > # > # To query and modify timeseries, you first need to create a TimeseriesClient > # object using your Datastream credentials. > # > # This can be done in two ways. The first method is simply to create the > # client passing your Datastream credentials in directly: > # > # timeseriesClient = TimeseriesClient(NULL, 'YourID', 'YourPwd') > # > # Alternatively, you can use a configuration file containing your > # credentials. The config file just needs your credentials in the following > # format: > # > # [credentials] > # username=YourID > # password=YourPwd > # > # Then create the TimeseriesClient object passing in the config file. > # > # timeseriesClient = TimeseriesClient('config.ini') > # > # > # Okay, let's start the demo by creating the TimeseriesClient. > > timeseriesClient = NULL > > # Assuming you have permissioned credentials, replace 'YourID' and 'YourPwd' > # with them and then let's logon and create the TimeseriesClient object. > # Note the basic error handling for DSUserObjectFault exceptions > > tryCatch({ + # First step is creating the client by replacing 'YourID' and + # 'YourPwd' with your own credentials. + print('Creating a TimeseriesClient object using your credentials.') + + timeseriesClient = TimeSeriesClient$new(NULL, "zdsm043", "horse485") + + #timeseriesClient = TimeSeriesClient('Config.ini') + + }, + error = function(e) + { + stop(message(e)) + } + ) [1] "Creating a TimeseriesClient object using your credentials." INFO [2024-03-13 10:17:18] DSConnect.R DSConnect$getToken :Getting Token and Token Expiry INFO [2024-03-13 10:17:18] DSConnect.R DSConnect$getJsonResponse Web response received > > if (!is.null(timeseriesClient) & timeseriesClient$IsValid()) + { + print(paste('Successfully created the TimeseriesClient.')) + # With a valid client connection, we can start to perfom some actions + # dealing with timeseries items. + + readline("Press Enter to continue...") + + + # You still need exception handling for possible network errors + tryCatch({ + # First step is to get a list of all the timeseries you + # currently have available. This list may be empty if you + # are a new user. + print('Requesting all timeseries available for your datastream + ID.') + itemsResp = timeseriesClient$GetAllItems() + + # DSUserObjectGetAllResponse has ResponseStatus property that + # indicates success or failure for the query + + if (!is.null(itemsResp)) + { + if (itemsResp$ResponseStatus != DSUserObjectResponseStatus$UserObjectSuccess) + { + # Your Datastream Id might not be permissioned for + # managing user created items on this API + print(paste('GetAllItems failed with error', + names(DSUserObjectResponseStatus)[itemsResp$ResponseStatus+1], + itemsResp$ErrorMessage)) + } + + else if ((is.null(itemsResp$UserObjects)) | (itemsResp$UserObjectsCount == 0)) + print(paste('GetAllItems returned zero timeseries items.')) + else + { + # You do have access to some timeseries + # Note, because you can have thousands of timeseries + # per Datastream ID, and each of these can contain upto + # 130 years of daily data, the GetAllItems method returns + # just the summary data for each timeseries. Each of the + # DSTimeSeriesResponseObjects returned in the UserObjects + # collection will specify the number of datapoints available in + # the ValuesCount field of the DateRange property, however the Dates + # and Values fields will always be NULL or an empty list. To view + # the actual dates and values of a specific timeseries, you need to + # use the GetItem method. Here we just put the timeseries details into + # a dataframe and list them + + print(paste('GetAllItems returned', + itemsResp$UserObjectsCount, 'timeseries items.')) + colnames = c('Id', 'Desc', 'LastModified', 'startDate', 'endDate','Frequency', + 'NoOfValues') + df = data.frame() + for (tsItem in itemsResp$UserObjects) + { + coldata = NULL + if (!is.null(tsItem)) + { + rowdata = c (Id = tsItem$Id, + Desc = tsItem$Description, + LastModified = as.character(tsItem$LastModified), + StartDate = ifelse (!is.null(tsItem$DateInfo), as.character(tsItem$DateInfo$StartDate), NULL), + EndDate = ifelse(!is.null(tsItem$DateInfo),as.character(tsItem$DateInfo$EndDate), NULL), + Frequency = ifelse(!is.null(tsItem$DateInfo), names(DSUserObjectFrequency)[tsItem$DateInfo$Frequency + 1], NULL), + NoOfValues = ifelse(!is.null(tsItem$DateRange), tsItem$DateRange$ValuesCount , 0)) + df = rbind(df, rowdata) + } + } + colnames(df) = colnames + print(df) + } + + + readline("Press Enter to continue...") + + + # Let us request and display the full details for the first timeseries + # in your returned list (if there is one) + + if (!is.null(itemsResp) & + itemsResp$ResponseStatus == DSUserObjectResponseStatus$UserObjectSuccess & + itemsResp$UserObjectsCount > 0 & + !is.null(itemsResp$UserObjects)) + { + firstItem = itemsResp$UserObjects[[1]]$Id + print(paste('Requesting the first timeseries in your list: ', + firstItem )) + getItemResp = timeseriesClient$GetItem(firstItem) + + # Let's use ProcessTimeseriesResponse to perfom general processing + # of the DSUserObjectResponse as we will be handling a few timeseries + # responses. See the comments in ProcessTimeseriesResponse for a + # description of handling a response + ProcessTimeseriesResponse(getItemResp, firstItem) + + } + } + + + readline("Press Enter to continue...") + + + # Let's now start the process of creating a new timeseries. + # First of all, we need to know which dates are supported on Datastream. + # Datastream only stores the actual working weekdays for a given date + # range, sovwe need to provide values that match the dates supported. + + # The API supports a GetTimeseriesDateRange method which returns a list + # of supported dates for a given start date, end date and frequency. + + # We'll start off creating a timeseries with quarterly frequency, so let's + # retrieve the supported dates. + # This example intentionally shows two different date constructors, + # requesting quarterly dates between 2016 and 2022. + + startDate = as.Date.character('2016-1-1', format = "%Y-%m-%d") + endDate = as.Date('2022-04-01') + freq = DSUserObjectFrequency$Quarterly + print('Requesting GetTimeseriesDateRange to get supported dates from 2016-01-01 to 2022-04-01 at quarterly frequency.') + dateRangeResp = timeseriesClient$GetTimeseriesDateRange(startDate, endDate, freq) + + #process the returned dates + datesCount = 0 # we'll use this later in our example for creating an actual timeseries + if (is.null(dateRangeResp)) + { + if (dateRangeResp$ResponseStatus != DSUserObjectResponseStatus$UserObjectSuccess) + print('GetTimeseriesDateRange failed with error ', names(DSUserObjectResponseStatus)[dateRangeResp$ResponseStatus + 1],': ', dateRangeResp$ErrorMessage) + } + else if (!is.null(dateRangeResp$Dates)) + { + df = data.frame(Dates = sapply(dateRangeResp$Dates, + FUN = function(x) { return (as.character(x)) })) + print(df) + } + + # You would normally use the returned dates to populate the timeseries + # request's objects Values field with corresponding values. + # Here we are just going to track how many valid dates there were within + #the requested period. + datesCount = length(dateRangeResp$Dates) + + readline("Press Enter to continue...") + + + # With the list of supported dates returned from GetTimeseriesDateRange, + # you would then create an array of values associated + # with the given dates from your data source. + # For this example, we'll just populate an array of test values randomly + # between 10.00 and 200.00 with two decimal places + datesCount = ifelse (datesCount > 0, datesCount, 26) # safety: setting datesCount in case GetTimeseriesDateRange response processing was skipped over + + # We'll simply create an array of values datesCount long with random + # values between 10 and 200 with 2 decimal places to reflect data + # retrieved from some source + values = runif(datesCount, 10, 200) + + # We'll use a variable to store the test ID as we'll manipulate the + # timeseries a few times. + # Note Timeseries IDs must be 8 uppercase alphanumeric characters in + # length and start with TS. e.g. TSZZZ001 + # Feel free to change this ID to something you prefer. + testID = 'TSVVV023' + + # To now create the timeseries, we need a DSTimeSeriesRequestObject. + # The constructor for this requires you to provide only the mandatory + # properties. There are some key parameters you need to set in a timeseries + # request object: The ID, the start and end dates, the frequency of data + # and the data values for the given date range and frequency + + # You can construct the timeseries with the key data in two ways: + # First method is to use the optional parameters in the constructor to + # supply the key data + #testTs = DSTimeSeriesRequestObject$new(testID, startDate, endDate, + #DSUserObjectFrequency$Quarterly, values) + + # Or you can construct the basic object and populate the fields directly + testTs = DSTimeSeriesRequestObject$new() + testTs$Id = testID + testTs$DataInput = DSTimeSeriesDataInput$new() # or more directly testTs$DataInput = DSTimeSeriesDataInput$new(startDate, endDate, DSUserObjectFrequency$Quarterly, values) + testTs$DataInput$StartDate = startDate + testTs$DataInput$EndDate = endDate + testTs$DataInput$Frequency = DSUserObjectFrequency$Quarterly + testTs$DataInput$Values = values + + + #Set any other optional properties directly + testTs$DisplayName = 'My first test timeseries' # if you don't set the DisplayName it will be set to the same as the ID in the response + testTs$DecimalPlaces = 2 # we created our array of values with 2 decimal places. You can specify 0 to 8 decimal places + testTs$Units = "Billions" # Leave units blank or set with any custom text (max 12 chars) + testTs$DateAlignment = DSTimeSeriesDateAlignment$MidPeriod # when requested by users in data retrieval, you can specify the quarterly dates to be returned as start, middle or end of the select period (frequency) + + # Now we actually try and create the item. + # When you create an item, the create request will normally be rejected if the item already exists. However, there is an option to overwrite the existing + # item. We will use that option here in case the item was created in an earlier test and not subsequently deleted. + print(paste('Creating a new timeseries', testID)) + tsResp = timeseriesClient$CreateItem(testTs, overWrite = TRUE) + + # The timeseries should now be returned in the list of timeseries if you + # call timeseriesClient.GetAllItems() again. + # It should also, after a few minutes, appear in Datastream's Navigator tool. + # You should also be able to chart it using the DSChart tool in Eikon or + # LSEG Workstation. The raw data should also be retrievable with + # requests via the standard Datastream API or via Datastream. + # For Office (DSGrid queries). + # Here, we will just display the response returned from the mainframe. + ProcessTimeseriesResponse(tsResp, testID) + + # You can pause here and test the new item in DFO, Navigator or DSCharting. + readline("Press Enter to continue...") + + print("Re-creating the same Timeseries") + values = runif(30, 20, 200) + testTs = DSTimeSeriesRequestObject$new(testID, as.Date("2024-01-01"), as.Date("2024-02-01"), + DSUserObjectFrequency$Daily, values) + tsResp = timeseriesClient$CreateItem(testTs, overWrite = TRUE) + ProcessTimeseriesResponse(tsResp, testID) + readline("Press Enter to continue...") + + + # Now we can try updating an existing item. + # Let's modify it to be a daily frequency series with data from 2000 + # until 2020. + # Again, we'll get the list of supported dates between the start and + # end date. + startDate = as.Date('2000-01-01') + endDate = as.Date('2020-12-31') + freq = DSUserObjectFrequency$Daily + print('Requesting GetTimeseriesDateRange to get supported dates from 2001-01-01 to 2020-12-31 at daily frequency.') + dateRangeResp = timeseriesClient$GetTimeseriesDateRange(startDate, endDate, freq) + print('') + + # With the list of supported dates returned from GetTimeseriesDateRange, + # you would then create an array of values associated with the given dates + # from your data source + # Again, for this example, we'll just populate an array of test values + # randomly between 10.00 and 200.00 with two decimal places + if (!(is.null(dateRangeResp)) & + dateRangeResp$ResponseStatus == DSUserObjectResponseStatus$UserObjectSuccess & + !(is.null(dateRangeResp$Dates))) + { + # We'll just take the count of the number of dates and generate random + # data to simulate us retrieving corresponding values from your data source. + datesCount = length(dateRangeResp$Dates) + values = runif(datesCount, 10, 200) # an array datesCount long with random values between 10 and 200 with 2 decimal places + } + + # set the new dates, frequency and values on our existing timeseries object + + # Note: Datastream takes the StartDate, Frequency and Values and creates + # the timeseries based only using these parameters. The EndDate is not + # actually used internally other than for logging purposes. The true end + # date is calculated based on the start date, frequency and list of values. Supply too few or too many values + # and the mainframe will accept them and set the end date accordingly + # based on the given frequency for the item. + # To demonstrate this, we deliberately set the enddate to be a date other + # than 2020-12-31. The response item will give the true end date as + # calculated (2020-12-31) + testTs$DataInput = DSTimeSeriesDataInput$new(startDate, as.Date('2005-12-31'), + freq, values) + testTs$DisplayName = 'Modifying timeseries to be daily frequency' + testTs$DataInput$Frequency = DSUserObjectFrequency$Daily + + # and finally call UpdateItem + print(paste('Updating our timeseries', testID, 'to have daily frequency.')) + tsResp = timeseriesClient$UpdateItem(testTs) + # Again, we will just display the updated timeseries object returned + # from the mainframe. + ProcessTimeseriesResponse(tsResp, testID) + + # You can pause here and test the updated item in DFO, Navigator or + # DSCharting. + readline("Press Enter to continue...") + + + # Now we can create and modify timeseries, let's look at how we handle + # non-trading days. On Datastream non-trading days are stored as float NaN + # values. R supports NaN values and JSON (used to communicate with + # API server) also support NaN values. + # The client can provide NULL input values for Non-trading days, similar to + # python code, which internally are converted to NaN Values. + + # However, the JSON response received from API server will be NULL values + # for non-trading days. By default, the client expects non-trading values + # to be represented by NULL value. An option has been provided for the + # client to choose values to be returned for non-trading days to be NaN. + # We'll now demonstrate both modes of operation. + + + # First of all, let's demo the default mode where trading days are accepted + # and returned only as NULL values. + # Again, we'll modify the same test item. We'll keep all previous settings + # the same but simply modify the values to include some NULL values + testTs$DataInput$Values = list (30.01, 50.02, NULL, 70.04, 80.05, NULL, 100.07) + + # You can provide NaN in place of NULL, as shown below + # testTs$DataInput$Values = list (30.01, 50.02, NaN, 70.04, 80.05, NaN, 100.07) + + # One modification we have to do is set the CarryIndicator to 'No' to stop + # the mainframe replacing the NaNs with the prior values (padding) + testTs$CarryIndicator = DSTimeSeriesCarryIndicator$No + + # And apply the update + print(paste('Updating our timeseries', testID, + 'to have some non-trading values represented by NULL.')) + tsResp = timeseriesClient$UpdateItem(testTs, skipItemReturn = TRUE) + # Again, we will just display the updated timeseries object returned from + # the mainframe. + # The returned Values for non-trading days should be set to NULL. + ProcessTimeseriesResponse(tsResp, testID) + + # You can pause here and test the updated item in DFO, Navigator or + # DSCharting. + readline("Press Enter to continue...") + + + + # We can now demonstrate the alternative option of using float NaN to + # retrieve non-trading values as NaNs. + # To do this we set useNaNforNotANumber to be True + timeseriesClient$useNaNforNotANumber = TRUE + + # In the following we just demonstrate providing floating NaN values and + # NULL when creating or updating a timeseries. + testTs$DataInput$Values = list (50.01, 60.02, NaN, 80.04, NaN, 90.05, NULL, 100.07, NULL, 120.23) + + # And apply the update + print(paste('Updating our timeseries', testID, + 'to have some non-trading values represented by NaNs.')) + tsResp = timeseriesClient$UpdateItem(testTs) + # Again, we will just display the updated timeseries object returned from + # the mainframe. + # The returned Values for non-trading days should be set to NaN values. + ProcessTimeseriesResponse(tsResp, testID) + + # You can pause here and test the updated item in DFO, Navigator or + # DSCharting. + readline("Press Enter to continue...") + + + # We are now done testing. Let's clean up the example by deleting it + print(paste('Deleting our timeseries', testID)) + delResp = timeseriesClient$DeleteItem(testID) + if (!is.null(delResp)) + { + if (delResp$ResponseStatus != DSUserObjectResponseStatus$UserObjectSuccess) + print(paste('Timeseries DeleteItem failed on', delResp.UserObjectId, ' with error', names(DSUserObjectResponseStatus)[delResp$ResponseStatus + 1], ':', delResp$ErrorMessage)) + else + print(paste('Timeseries', delResp$UserObjectId,'successfully deleted.')) + } + + # You can pause here and test the deleted item in DFO, Navigator or + # DSCharting. + readline("Press Enter to continue...") + + + # let's try that again and see an example of the error handling as + # DeleteItem will fail + print(paste('Deleting our timeseries', testID, 'again to demonstrate the API server returning an error response.')) + delResp = timeseriesClient$DeleteItem(testID) + if (!is.null(delResp)) + { + if (delResp$ResponseStatus != DSUserObjectResponseStatus$UserObjectSuccess) + print(paste('Timeseries DeleteItem failed on', delResp$UserObjectId, + 'with error', + names(DSUserObjectResponseStatus)[delResp$ResponseStatus + 1], + ':', delResp$ErrorMessage)) + else # delResp.UserObject won't be set on DeleteItem if successful + print(paste('Timeseries', delResp$UserObjectId,'successfully deleted.')) + } + }, + error = function(e) + { + print(paste('TimeseriesClient request failed with error message:', message(e))) + stop(message(e)) + }) + } [1] "Successfully created the TimeseriesClient." Press Enter to continue... [1] "Requesting all timeseries available for your datastream\n ID." INFO [2024-03-13 10:17:18] DatastreamUserCreated_TimeSeries.R TimeseriesClient$GetAllItems GetAllItems requested INFO [2024-03-13 10:17:19] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$GetAllItems GetAllItems returned [1] "GetAllItems returned 25 timeseries items." Id Desc LastModified 1 TS000001 Cross-section average of OECD countries inflation 2023-03-01 2 TS00000A JohnS testing frequency conversion actual 2024-02-08 3 TS0001JS TS0001JS 2022-08-08 4 TSABCPKK TSABC.PK 2020-10-12 5 TSBETA13 JOHN LOWERCASE 2019-04-12 6 TSDAYS03 SP500 number of days outside small gains fixed up 2023-03-02 7 TSJS0001 TSJS0001 2014-06-30 8 TSTEST04 JS4 2017-01-03 9 TSTEST06 TS06 2017-01-03 10 TSTEST07 JS07 2017-01-03 11 TSTEST99 TSTEST99 2020-10-15 12 TSTR6000 2 2020-11-20 13 TSUSA831 TSUSA831 2020-04-28 14 TSVDV021 TSVDV021 2023-01-13 15 TSVDVD04 TSVDVD04 2022-02-01 16 TSVDVD18 TSVDVD18 2023-01-09 17 TSVID022 VID 2020-11-12 18 TSVID830 TSVID830 2020-04-28 19 TSVV0001 My Test series : TSVV0001 2022-03-25 20 TSVVV001 My first test timeseries 2023-02-08 21 TSVVV002 TSVVV002 2022-04-12 22 TSVVV010 TSVVV010 2022-04-13 23 TSVVVD04 TSVVVD04 2022-04-12 24 TSXYZPKK Strange 16/02/20 name 2020-10-19 25 TSZZZ002 My first test timeseries 2023-06-14 startDate endDate Frequency NoOfValues 1 1980-12-15 2022-04-15 Monthly 497 2 2023-02-01 2023-02-16 Daily 12 3 2016-06-30 2020-06-30 Yearly 5 4 2010-01-31 2010-05-31 Monthly 5 5 2019-01-01 2019-01-04 Daily 4 6 1964-01-02 2023-03-01 Daily 15435 7 2014-01-31 2014-06-27 Daily 106 8 2016-12-02 2016-12-30 Weekly 5 9 2010-03-31 2016-12-31 Quarterly 28 10 2016-01-31 2016-12-31 Monthly 12 11 2019-01-01 2019-01-04 Daily 4 12 2000-01-31 2002-01-31 Monthly 25 13 2010-01-31 2010-05-31 Monthly 5 14 2016-01-01 2016-02-05 Daily 26 15 2021-01-31 2021-06-30 Monthly 6 16 2021-01-31 2021-02-08 Daily 7 17 1950-12-02 1950-12-29 Weekly 5 18 2020-04-28 2020-04-28 Daily 1 19 2016-01-02 2016-02-01 Daily 22 20 2016-02-15 2022-05-15 Quarterly 26 21 2000-01-01 2000-01-05 Daily 4 22 2000-01-01 2000-01-20 Daily 15 23 2012-04-23 2012-04-26 Daily 4 24 2010-01-31 2010-05-31 Monthly 5 25 2016-03-31 2022-06-30 Quarterly 26 Press Enter to continue... [1] "Requesting the first timeseries in your list: TS000001" INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$GetItem Requesting TS000001 INFO [2024-03-13 10:17:19] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$GetItem TS000001 returned a response metadata Id TS000001 Desc Cross-section average of OECD countries inflation LastModified 2023-03-01 StartDate 1980-12-15 EndDate 2022-04-15 Frequency Monthly NoOfValues 497 Dates Values 1 1980-12-01 2 1981-01-01 3 1981-02-01 4 1981-03-01 5 1981-04-01 6 1981-05-01 7 1981-06-01 8 1981-07-01 9 1981-08-01 10 1981-09-01 11 1981-10-01 12 1981-11-01 13 1981-12-01 14 1982-01-01 15 1982-02-01 16 1982-03-01 17 1982-04-01 18 1982-05-01 19 1982-06-01 20 1982-07-01 21 1982-08-01 22 1982-09-01 23 1982-10-01 24 1982-11-01 25 1982-12-01 26 1983-01-01 27 1983-02-01 28 1983-03-01 29 1983-04-01 30 1983-05-01 31 1983-06-01 32 1983-07-01 33 1983-08-01 34 1983-09-01 35 1983-10-01 36 1983-11-01 37 1983-12-01 38 1984-01-01 39 1984-02-01 40 1984-03-01 41 1984-04-01 42 1984-05-01 43 1984-06-01 44 1984-07-01 45 1984-08-01 46 1984-09-01 47 1984-10-01 48 1984-11-01 49 1984-12-01 50 1985-01-01 51 1985-02-01 52 1985-03-01 53 1985-04-01 54 1985-05-01 55 1985-06-01 56 1985-07-01 57 1985-08-01 58 1985-09-01 59 1985-10-01 60 1985-11-01 -0.254 61 1985-12-01 -0.281 62 1986-01-01 -0.308 63 1986-02-01 -0.337 64 1986-03-01 -0.367 65 1986-04-01 -0.398 66 1986-05-01 -0.428 67 1986-06-01 -0.458 68 1986-07-01 -0.489 69 1986-08-01 -0.519 70 1986-09-01 -0.546 71 1986-10-01 -0.574 72 1986-11-01 -0.6 73 1986-12-01 -0.626 74 1987-01-01 -0.652 75 1987-02-01 -0.674 76 1987-03-01 -0.694 77 1987-04-01 -0.711 78 1987-05-01 -0.726 79 1987-06-01 -0.739 80 1987-07-01 -0.749 81 1987-08-01 -0.755 82 1987-09-01 -0.761 83 1987-10-01 -0.765 84 1987-11-01 -0.768 85 1987-12-01 -0.769 86 1988-01-01 -0.768 87 1988-02-01 -0.766 88 1988-03-01 -0.761 89 1988-04-01 -0.757 90 1988-05-01 -0.752 91 1988-06-01 -0.744 92 1988-07-01 -0.734 93 1988-08-01 -0.725 94 1988-09-01 -0.715 95 1988-10-01 -0.703 96 1988-11-01 -0.692 97 1988-12-01 -0.681 98 1989-01-01 -0.668 99 1989-02-01 -0.655 100 1989-03-01 -0.643 101 1989-04-01 -0.626 102 1989-05-01 -0.606 103 1989-06-01 -0.586 104 1989-07-01 -0.565 105 1989-08-01 -0.543 106 1989-09-01 -0.519 107 1989-10-01 -0.494 108 1989-11-01 -0.469 109 1989-12-01 -0.443 110 1990-01-01 -0.414 111 1990-02-01 -0.386 112 1990-03-01 -0.358 113 1990-04-01 -0.334 114 1990-05-01 -0.311 115 1990-06-01 -0.288 116 1990-07-01 -0.264 117 1990-08-01 -0.237 118 1990-09-01 -0.208 119 1990-10-01 -0.175 120 1990-11-01 -0.145 121 1990-12-01 -0.119 122 1991-01-01 -0.091 123 1991-02-01 -0.062 124 1991-03-01 -0.034 125 1991-04-01 -0.005 126 1991-05-01 0.025 127 1991-06-01 0.056 128 1991-07-01 0.088 129 1991-08-01 0.116 130 1991-09-01 0.137 131 1991-10-01 0.156 132 1991-11-01 0.176 133 1991-12-01 0.195 134 1992-01-01 0.211 135 1992-02-01 0.225 136 1992-03-01 0.238 137 1992-04-01 0.248 138 1992-05-01 0.253 139 1992-06-01 0.255 140 1992-07-01 0.25 141 1992-08-01 0.242 142 1992-09-01 0.233 143 1992-10-01 0.221 144 1992-11-01 0.206 145 1992-12-01 0.191 146 1993-01-01 0.178 147 1993-02-01 0.164 148 1993-03-01 0.15 149 1993-04-01 0.137 150 1993-05-01 0.122 151 1993-06-01 0.107 152 1993-07-01 0.092 153 1993-08-01 0.078 154 1993-09-01 0.063 155 1993-10-01 0.048 156 1993-11-01 0.032 157 1993-12-01 0.016 158 1994-01-01 -0.004 159 1994-02-01 -0.025 160 1994-03-01 -0.046 161 1994-04-01 -0.07 162 1994-05-01 -0.095 163 1994-06-01 -0.118 164 1994-07-01 -0.141 165 1994-08-01 -0.162 166 1994-09-01 -0.184 167 1994-10-01 -0.208 168 1994-11-01 -0.232 169 1994-12-01 -0.255 170 1995-01-01 -0.28 171 1995-02-01 -0.305 172 1995-03-01 -0.33 173 1995-04-01 -0.351 174 1995-05-01 -0.37 175 1995-06-01 -0.389 176 1995-07-01 -0.412 177 1995-08-01 -0.437 178 1995-09-01 -0.465 179 1995-10-01 -0.495 180 1995-11-01 -0.524 181 1995-12-01 -0.551 182 1996-01-01 -0.58 183 1996-02-01 -0.608 184 1996-03-01 -0.633 185 1996-04-01 -0.657 186 1996-05-01 -0.68 187 1996-06-01 -0.705 188 1996-07-01 -0.73 189 1996-08-01 -0.753 190 1996-09-01 -0.772 191 1996-10-01 -0.785 192 1996-11-01 -0.799 193 1996-12-01 -0.811 194 1997-01-01 -0.819 195 1997-02-01 -0.828 196 1997-03-01 -0.842 197 1997-04-01 -0.857 198 1997-05-01 -0.87 199 1997-06-01 -0.879 200 1997-07-01 -0.884 201 1997-08-01 -0.884 202 1997-09-01 -0.884 203 1997-10-01 -0.881 204 1997-11-01 -0.876 205 1997-12-01 -0.871 206 1998-01-01 -0.869 207 1998-02-01 -0.864 208 1998-03-01 -0.859 209 1998-04-01 -0.852 210 1998-05-01 -0.843 211 1998-06-01 -0.835 212 1998-07-01 -0.829 213 1998-08-01 -0.827 214 1998-09-01 -0.824 215 1998-10-01 -0.822 216 1998-11-01 -0.819 217 1998-12-01 -0.82 218 1999-01-01 -0.819 219 1999-02-01 -0.818 220 1999-03-01 -0.814 221 1999-04-01 -0.808 222 1999-05-01 -0.805 223 1999-06-01 -0.802 224 1999-07-01 -0.801 225 1999-08-01 -0.797 226 1999-09-01 -0.793 227 1999-10-01 -0.786 228 1999-11-01 -0.779 229 1999-12-01 -0.768 230 2000-01-01 -0.757 231 2000-02-01 -0.746 232 2000-03-01 -0.734 233 2000-04-01 -0.726 234 2000-05-01 -0.717 235 2000-06-01 -0.703 236 2000-07-01 -0.685 237 2000-08-01 -0.669 238 2000-09-01 -0.65 239 2000-10-01 -0.632 240 2000-11-01 -0.612 241 2000-12-01 -0.596 242 2001-01-01 -0.579 243 2001-02-01 -0.562 244 2001-03-01 -0.546 245 2001-04-01 -0.525 246 2001-05-01 -0.501 247 2001-06-01 -0.479 248 2001-07-01 -0.462 249 2001-08-01 -0.445 250 2001-09-01 -0.43 251 2001-10-01 -0.419 252 2001-11-01 -0.414 253 2001-12-01 -0.408 254 2002-01-01 -0.397 255 2002-02-01 -0.387 256 2002-03-01 -0.373 257 2002-04-01 -0.358 258 2002-05-01 -0.347 259 2002-06-01 -0.34 260 2002-07-01 -0.33 261 2002-08-01 -0.32 262 2002-09-01 -0.311 263 2002-10-01 -0.297 264 2002-11-01 -0.282 265 2002-12-01 -0.267 266 2003-01-01 -0.253 267 2003-02-01 -0.237 268 2003-03-01 -0.222 269 2003-04-01 -0.214 270 2003-05-01 -0.21 271 2003-06-01 -0.205 272 2003-07-01 -0.201 273 2003-08-01 -0.194 274 2003-09-01 -0.188 275 2003-10-01 -0.184 276 2003-11-01 -0.179 277 2003-12-01 -0.173 278 2004-01-01 -0.165 279 2004-02-01 -0.161 280 2004-03-01 -0.159 281 2004-04-01 -0.154 282 2004-05-01 -0.142 283 2004-06-01 -0.128 284 2004-07-01 -0.112 285 2004-08-01 -0.101 286 2004-09-01 -0.092 287 2004-10-01 -0.08 288 2004-11-01 -0.071 289 2004-12-01 -0.067 290 2005-01-01 -0.067 291 2005-02-01 -0.069 292 2005-03-01 -0.07 293 2005-04-01 -0.068 294 2005-05-01 -0.072 295 2005-06-01 -0.082 296 2005-07-01 -0.088 297 2005-08-01 -0.092 298 2005-09-01 -0.094 299 2005-10-01 -0.096 300 2005-11-01 -0.103 301 2005-12-01 -0.106 302 2006-01-01 -0.106 303 2006-02-01 -0.107 304 2006-03-01 -0.111 305 2006-04-01 -0.116 306 2006-05-01 -0.121 307 2006-06-01 -0.122 308 2006-07-01 -0.12 309 2006-08-01 -0.118 310 2006-09-01 -0.121 311 2006-10-01 -0.127 312 2006-11-01 -0.126 313 2006-12-01 -0.123 314 2007-01-01 -0.125 315 2007-02-01 -0.126 316 2007-03-01 -0.124 317 2007-04-01 -0.121 318 2007-05-01 -0.115 319 2007-06-01 -0.107 320 2007-07-01 -0.102 321 2007-08-01 -0.1 322 2007-09-01 -0.092 323 2007-10-01 -0.08 324 2007-11-01 -0.06 325 2007-12-01 -0.039 326 2008-01-01 -0.014 327 2008-02-01 0.009 328 2008-03-01 0.035 329 2008-04-01 0.064 330 2008-05-01 0.103 331 2008-06-01 0.145 332 2008-07-01 0.19 333 2008-08-01 0.231 334 2008-09-01 0.269 335 2008-10-01 0.302 336 2008-11-01 0.321 337 2008-12-01 0.33 338 2009-01-01 0.336 339 2009-02-01 0.343 340 2009-03-01 0.345 341 2009-04-01 0.341 342 2009-05-01 0.324 343 2009-06-01 0.303 344 2009-07-01 0.278 345 2009-08-01 0.256 346 2009-09-01 0.236 347 2009-10-01 0.211 348 2009-11-01 0.194 349 2009-12-01 0.183 350 2010-01-01 0.178 351 2010-02-01 0.171 352 2010-03-01 0.165 353 2010-04-01 0.16 354 2010-05-01 0.159 355 2010-06-01 0.156 356 2010-07-01 0.151 357 2010-08-01 0.145 358 2010-09-01 0.136 359 2010-10-01 0.13 360 2010-11-01 0.128 361 2010-12-01 0.128 362 2011-01-01 0.127 363 2011-02-01 0.127 364 2011-03-01 0.132 365 2011-04-01 0.135 366 2011-05-01 0.134 367 2011-06-01 0.131 368 2011-07-01 0.129 369 2011-08-01 0.127 370 2011-09-01 0.134 371 2011-10-01 0.144 372 2011-11-01 0.151 373 2011-12-01 0.152 374 2012-01-01 0.153 375 2012-02-01 0.154 376 2012-03-01 0.15 377 2012-04-01 0.146 378 2012-05-01 0.141 379 2012-06-01 0.135 380 2012-07-01 0.129 381 2012-08-01 0.126 382 2012-09-01 0.119 383 2012-10-01 0.102 384 2012-11-01 0.073 385 2012-12-01 0.044 386 2013-01-01 0.009 387 2013-02-01 -0.028 388 2013-03-01 -0.068 389 2013-04-01 -0.108 390 2013-05-01 -0.152 391 2013-06-01 -0.197 392 2013-07-01 -0.242 393 2013-08-01 -0.285 394 2013-09-01 -0.326 395 2013-10-01 -0.361 396 2013-11-01 -0.381 397 2013-12-01 -0.389 398 2014-01-01 -0.394 399 2014-02-01 -0.4 400 2014-03-01 -0.399 401 2014-04-01 -0.394 402 2014-05-01 -0.382 403 2014-06-01 -0.369 404 2014-07-01 -0.353 405 2014-08-01 -0.34 406 2014-09-01 -0.328 407 2014-10-01 -0.316 408 2014-11-01 -0.311 409 2014-12-01 -0.312 410 2015-01-01 -0.32 411 2015-02-01 -0.326 412 2015-03-01 -0.333 413 2015-04-01 -0.342 414 2015-05-01 -0.348 415 2015-06-01 -0.351 416 2015-07-01 -0.357 417 2015-08-01 -0.362 418 2015-09-01 -0.37 419 2015-10-01 -0.378 420 2015-11-01 -0.387 421 2015-12-01 -0.398 422 2016-01-01 -0.407 423 2016-02-01 -0.418 424 2016-03-01 -0.433 425 2016-04-01 -0.447 426 2016-05-01 -0.462 427 2016-06-01 -0.475 428 2016-07-01 -0.486 429 2016-08-01 -0.498 430 2016-09-01 -0.509 431 2016-10-01 -0.517 432 2016-11-01 -0.523 433 2016-12-01 -0.522 434 2017-01-01 -0.514 435 2017-02-01 -0.504 436 2017-03-01 -0.494 437 2017-04-01 -0.482 438 2017-05-01 -0.472 439 2017-06-01 -0.464 440 2017-07-01 -0.454 441 2017-08-01 -0.443 442 2017-09-01 -0.432 443 2017-10-01 -0.421 444 2017-11-01 -0.407 445 2017-12-01 -0.394 446 2018-01-01 -0.381 447 2018-02-01 -0.367 448 2018-03-01 -0.353 449 2018-04-01 -0.337 450 2018-05-01 -0.317 451 2018-06-01 -0.297 452 2018-07-01 -0.276 453 2018-08-01 -0.254 454 2018-09-01 -0.23 455 2018-10-01 -0.203 456 2018-11-01 -0.18 457 2018-12-01 -0.163 458 2019-01-01 -0.149 459 2019-02-01 -0.132 460 2019-03-01 -0.113 461 2019-04-01 -0.094 462 2019-05-01 -0.077 463 2019-06-01 -0.064 464 2019-07-01 -0.052 465 2019-08-01 -0.04 466 2019-09-01 -0.03 467 2019-10-01 -0.02 468 2019-11-01 -0.008 469 2019-12-01 0.011 470 2020-01-01 0.036 471 2020-02-01 0.056 472 2020-03-01 0.067 473 2020-04-01 0.066 474 2020-05-01 0.059 475 2020-06-01 0.056 476 2020-07-01 0.057 477 2020-08-01 0.056 478 2020-09-01 0.056 479 2020-10-01 0.053 480 2020-11-01 0.048 481 2020-12-01 0.044 482 2021-01-01 0.044 483 2021-02-01 0.046 484 2021-03-01 0.059 485 2021-04-01 0.081 486 2021-05-01 0.109 487 2021-06-01 0.135 488 2021-07-01 0.164 489 2021-08-01 0.199 490 2021-09-01 0.237 491 2021-10-01 0.281 492 2021-11-01 0.33 493 2021-12-01 0.373 494 2022-01-01 0.41 495 2022-02-01 0.448 496 2022-03-01 0.494 497 2022-04-01 0.536 Press Enter to continue... [1] "Requesting GetTimeseriesDateRange to get supported dates from 2016-01-01 to 2022-04-01 at quarterly frequency." INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.RTimeSeriesClient$GetTimeseriesDateRangeRequesting date range INFO [2024-03-13 10:17:19] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$GetTimeseriesDateRange GetTimeseriesDateRange returned a response Dates 1 2016-01-01 2 2016-04-01 3 2016-07-01 4 2016-10-01 5 2017-01-01 6 2017-04-01 7 2017-07-01 8 2017-10-01 9 2018-01-01 10 2018-04-01 11 2018-07-01 12 2018-10-01 13 2019-01-01 14 2019-04-01 15 2019-07-01 16 2019-10-01 17 2020-01-01 18 2020-04-01 19 2020-07-01 20 2020-10-01 21 2021-01-01 22 2021-04-01 23 2021-07-01 24 2021-10-01 25 2022-01-01 26 2022-04-01 Press Enter to continue... [1] "Creating a new timeseries TSVVV023" INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$CreateItem Creating TSVVV023 INFO [2024-03-13 10:17:19] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$CreateItem TSVVV023 returned a response metadata Id TSVVV023 Desc My first test timeseries LastModified 2024-03-13 StartDate 2016-02-15 EndDate 2022-05-15 Frequency Quarterly NoOfValues 26 Dates Values 1 2016-01-01 169.65 2 2016-04-01 125.48 3 2016-07-01 66.96 4 2016-10-01 157.02 5 2017-01-01 199.83 6 2017-04-01 86.85 7 2017-07-01 106.25 8 2017-10-01 28.65 9 2018-01-01 11.08 10 2018-04-01 106.91 11 2018-07-01 105.66 12 2018-10-01 78.71 13 2019-01-01 138.51 14 2019-04-01 141.23 15 2019-07-01 180.80 16 2019-10-01 119.66 17 2020-01-01 174.88 18 2020-04-01 116.17 19 2020-07-01 104.92 20 2020-10-01 186.59 21 2021-01-01 191.04 22 2021-04-01 93.99 23 2021-07-01 179.43 24 2021-10-01 50.30 25 2022-01-01 70.44 26 2022-04-01 60.24 Press Enter to continue... [1] "Re-creating the same Timeseries" INFO [2024-03-13 10:17:19] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$CreateItem Creating TSVVV023 INFO [2024-03-13 10:17:20] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:20] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$CreateItem TSVVV023 returned a response metadata Id TSVVV023 Desc TSVVV023 LastModified 2024-03-13 StartDate 2024-01-01 EndDate 2024-02-09 Frequency Daily NoOfValues 30 Dates Values 1 2024-01-01 163 2 2024-01-02 89 3 2024-01-03 128 4 2024-01-04 53 5 2024-01-05 104 6 2024-01-08 23 7 2024-01-09 39 8 2024-01-10 32 9 2024-01-11 156 10 2024-01-12 100 11 2024-01-15 148 12 2024-01-16 60 13 2024-01-17 37 14 2024-01-18 165 15 2024-01-19 96 16 2024-01-22 26 17 2024-01-23 99 18 2024-01-24 30 19 2024-01-25 140 20 2024-01-26 89 21 2024-01-29 63 22 2024-01-30 125 23 2024-01-31 50 24 2024-02-01 58 25 2024-02-02 176 26 2024-02-05 40 27 2024-02-06 132 28 2024-02-07 197 29 2024-02-08 94 30 2024-02-09 132 Press Enter to continue... [1] "Requesting GetTimeseriesDateRange to get supported dates from 2001-01-01 to 2020-12-31 at daily frequency." INFO [2024-03-13 10:17:20] DatastreamUserCreated_TimeSeries.RTimeSeriesClient$GetTimeseriesDateRangeRequesting date range INFO [2024-03-13 10:17:20] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:22] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$GetTimeseriesDateRange GetTimeseriesDateRange returned a response [1] "" [1] "Updating our timeseries TSVVV023 to have daily frequency." INFO [2024-03-13 10:17:22] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$UpdateItem Updating TSVVV023 INFO [2024-03-13 10:17:23] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$UpdateItem TSVVV023 returned a response metadata Id TSVVV023 Desc Modifying timeseries to be daily frequency LastModified 2024-03-13 StartDate 2000-01-01 EndDate 2020-12-31 Frequency Daily NoOfValues 5480 Dates Values 1 1999-12-31 110 2 2000-01-03 12 3 2000-01-04 78 4 2000-01-05 82 5 2000-01-06 154 6 2000-01-07 137 7 2000-01-10 23 8 2000-01-11 124 9 2000-01-12 65 10 2000-01-13 181 11 2000-01-14 28 12 2000-01-17 137 13 2000-01-18 193 14 2000-01-19 178 15 2000-01-20 150 16 2000-01-21 153 17 2000-01-24 164 18 2000-01-25 74 19 2000-01-26 16 20 2000-01-27 81 21 2000-01-28 54 22 2000-01-31 96 23 2000-02-01 121 24 2000-02-02 98 25 2000-02-03 12 26 2000-02-04 59 27 2000-02-07 179 28 2000-02-08 28 29 2000-02-09 95 30 2000-02-10 127 31 2000-02-11 20 32 2000-02-14 15 33 2000-02-15 178 34 2000-02-16 110 35 2000-02-17 141 36 2000-02-18 13 37 2000-02-21 166 38 2000-02-22 125 39 2000-02-23 32 40 2000-02-24 31 41 2000-02-25 56 42 2000-02-28 150 43 2000-02-29 193 44 2000-03-01 123 45 2000-03-02 144 46 2000-03-03 122 47 2000-03-06 47 48 2000-03-07 194 49 2000-03-08 176 50 2000-03-09 114 51 2000-03-10 35 52 2000-03-13 101 53 2000-03-14 190 54 2000-03-15 29 55 2000-03-16 139 56 2000-03-17 28 57 2000-03-20 160 58 2000-03-21 147 59 2000-03-22 189 60 2000-03-23 124 61 2000-03-24 28 62 2000-03-27 150 63 2000-03-28 62 64 2000-03-29 61 65 2000-03-30 101 66 2000-03-31 66 67 2000-04-03 82 68 2000-04-04 138 69 2000-04-05 78 70 2000-04-06 47 71 2000-04-07 61 72 2000-04-10 130 73 2000-04-11 178 74 2000-04-12 82 75 2000-04-13 33 76 2000-04-14 181 77 2000-04-17 199 78 2000-04-18 170 79 2000-04-19 63 80 2000-04-20 57 81 2000-04-21 172 82 2000-04-24 55 83 2000-04-25 194 84 2000-04-26 170 85 2000-04-27 184 86 2000-04-28 19 87 2000-05-01 39 88 2000-05-02 108 89 2000-05-03 136 90 2000-05-04 22 91 2000-05-05 85 92 2000-05-08 138 93 2000-05-09 110 94 2000-05-10 73 95 2000-05-11 136 96 2000-05-12 46 97 2000-05-15 101 98 2000-05-16 80 99 2000-05-17 69 100 2000-05-18 59 101 2000-05-19 91 102 2000-05-22 170 103 2000-05-23 53 104 2000-05-24 102 105 2000-05-25 49 106 2000-05-26 87 107 2000-05-29 160 108 2000-05-30 103 109 2000-05-31 60 110 2000-06-01 140 111 2000-06-02 159 112 2000-06-05 55 113 2000-06-06 86 114 2000-06-07 132 115 2000-06-08 79 116 2000-06-09 175 117 2000-06-12 129 118 2000-06-13 108 119 2000-06-14 177 120 2000-06-15 52 121 2000-06-16 37 122 2000-06-19 43 123 2000-06-20 56 124 2000-06-21 147 125 2000-06-22 136 126 2000-06-23 130 127 2000-06-26 69 128 2000-06-27 107 129 2000-06-28 141 130 2000-06-29 94 131 2000-06-30 90 132 2000-07-03 136 133 2000-07-04 63 134 2000-07-05 170 135 2000-07-06 161 136 2000-07-07 75 137 2000-07-10 68 138 2000-07-11 144 139 2000-07-12 83 140 2000-07-13 180 141 2000-07-14 165 142 2000-07-17 89 143 2000-07-18 87 144 2000-07-19 97 145 2000-07-20 173 146 2000-07-21 89 147 2000-07-24 147 148 2000-07-25 40 149 2000-07-26 160 150 2000-07-27 160 151 2000-07-28 57 152 2000-07-31 196 153 2000-08-01 24 154 2000-08-02 84 155 2000-08-03 17 156 2000-08-04 141 157 2000-08-07 29 158 2000-08-08 142 159 2000-08-09 82 160 2000-08-10 162 161 2000-08-11 41 162 2000-08-14 84 163 2000-08-15 112 164 2000-08-16 172 165 2000-08-17 70 166 2000-08-18 121 167 2000-08-21 176 168 2000-08-22 133 169 2000-08-23 118 170 2000-08-24 95 171 2000-08-25 28 172 2000-08-28 64 173 2000-08-29 173 174 2000-08-30 176 175 2000-08-31 181 176 2000-09-01 183 177 2000-09-04 71 178 2000-09-05 160 179 2000-09-06 16 180 2000-09-07 74 181 2000-09-08 20 182 2000-09-11 87 183 2000-09-12 91 184 2000-09-13 28 185 2000-09-14 106 186 2000-09-15 185 187 2000-09-18 171 188 2000-09-19 103 189 2000-09-20 109 190 2000-09-21 187 191 2000-09-22 42 192 2000-09-25 74 193 2000-09-26 47 194 2000-09-27 176 195 2000-09-28 134 196 2000-09-29 87 197 2000-10-02 55 198 2000-10-03 187 199 2000-10-04 111 200 2000-10-05 68 201 2000-10-06 85 202 2000-10-09 50 203 2000-10-10 172 204 2000-10-11 27 205 2000-10-12 92 206 2000-10-13 189 207 2000-10-16 22 208 2000-10-17 23 209 2000-10-18 88 210 2000-10-19 50 211 2000-10-20 21 212 2000-10-23 84 213 2000-10-24 166 214 2000-10-25 26 215 2000-10-26 109 216 2000-10-27 33 217 2000-10-30 24 218 2000-10-31 70 219 2000-11-01 199 220 2000-11-02 14 221 2000-11-03 112 222 2000-11-06 194 223 2000-11-07 179 224 2000-11-08 117 225 2000-11-09 73 226 2000-11-10 99 227 2000-11-13 54 228 2000-11-14 157 229 2000-11-15 122 230 2000-11-16 84 231 2000-11-17 95 232 2000-11-20 63 233 2000-11-21 36 234 2000-11-22 135 235 2000-11-23 38 236 2000-11-24 167 237 2000-11-27 78 238 2000-11-28 123 239 2000-11-29 199 240 2000-11-30 125 241 2000-12-01 55 242 2000-12-04 97 243 2000-12-05 92 244 2000-12-06 92 245 2000-12-07 55 246 2000-12-08 84 247 2000-12-11 122 248 2000-12-12 55 249 2000-12-13 21 250 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2018-02-15 30 4731 2018-02-16 196 4732 2018-02-19 37 4733 2018-02-20 17 4734 2018-02-21 33 4735 2018-02-22 27 4736 2018-02-23 57 4737 2018-02-26 18 4738 2018-02-27 182 4739 2018-02-28 165 4740 2018-03-01 47 4741 2018-03-02 168 4742 2018-03-05 40 4743 2018-03-06 173 4744 2018-03-07 104 4745 2018-03-08 78 4746 2018-03-09 84 4747 2018-03-12 56 4748 2018-03-13 34 4749 2018-03-14 188 4750 2018-03-15 55 4751 2018-03-16 136 4752 2018-03-19 116 4753 2018-03-20 195 4754 2018-03-21 40 4755 2018-03-22 139 4756 2018-03-23 136 4757 2018-03-26 158 4758 2018-03-27 147 4759 2018-03-28 167 4760 2018-03-29 124 4761 2018-03-30 34 4762 2018-04-02 176 4763 2018-04-03 22 4764 2018-04-04 72 4765 2018-04-05 142 4766 2018-04-06 119 4767 2018-04-09 19 4768 2018-04-10 163 4769 2018-04-11 125 4770 2018-04-12 35 4771 2018-04-13 118 4772 2018-04-16 65 4773 2018-04-17 88 4774 2018-04-18 70 4775 2018-04-19 73 4776 2018-04-20 185 4777 2018-04-23 167 4778 2018-04-24 94 4779 2018-04-25 85 4780 2018-04-26 74 4781 2018-04-27 61 4782 2018-04-30 84 4783 2018-05-01 75 4784 2018-05-02 50 4785 2018-05-03 17 4786 2018-05-04 149 4787 2018-05-07 128 4788 2018-05-08 48 4789 2018-05-09 19 4790 2018-05-10 187 4791 2018-05-11 58 4792 2018-05-14 72 4793 2018-05-15 32 4794 2018-05-16 44 4795 2018-05-17 146 4796 2018-05-18 136 4797 2018-05-21 65 4798 2018-05-22 197 4799 2018-05-23 65 4800 2018-05-24 134 4801 2018-05-25 135 4802 2018-05-28 105 4803 2018-05-29 113 4804 2018-05-30 16 4805 2018-05-31 168 4806 2018-06-01 18 4807 2018-06-04 198 4808 2018-06-05 198 4809 2018-06-06 71 4810 2018-06-07 28 4811 2018-06-08 87 4812 2018-06-11 144 4813 2018-06-12 57 4814 2018-06-13 57 4815 2018-06-14 186 4816 2018-06-15 83 4817 2018-06-18 94 4818 2018-06-19 22 4819 2018-06-20 53 4820 2018-06-21 74 4821 2018-06-22 98 4822 2018-06-25 102 4823 2018-06-26 168 4824 2018-06-27 69 4825 2018-06-28 74 4826 2018-06-29 113 4827 2018-07-02 49 4828 2018-07-03 73 4829 2018-07-04 13 4830 2018-07-05 159 4831 2018-07-06 42 4832 2018-07-09 167 4833 2018-07-10 58 4834 2018-07-11 84 4835 2018-07-12 104 4836 2018-07-13 78 4837 2018-07-16 196 4838 2018-07-17 12 4839 2018-07-18 61 4840 2018-07-19 109 4841 2018-07-20 130 4842 2018-07-23 40 4843 2018-07-24 170 4844 2018-07-25 121 4845 2018-07-26 134 4846 2018-07-27 69 4847 2018-07-30 61 4848 2018-07-31 28 4849 2018-08-01 78 4850 2018-08-02 161 4851 2018-08-03 90 4852 2018-08-06 27 4853 2018-08-07 35 4854 2018-08-08 178 4855 2018-08-09 139 4856 2018-08-10 162 4857 2018-08-13 50 4858 2018-08-14 188 4859 2018-08-15 157 4860 2018-08-16 158 4861 2018-08-17 133 4862 2018-08-20 143 4863 2018-08-21 85 4864 2018-08-22 58 4865 2018-08-23 180 4866 2018-08-24 13 4867 2018-08-27 61 4868 2018-08-28 42 4869 2018-08-29 77 4870 2018-08-30 140 4871 2018-08-31 88 4872 2018-09-03 39 4873 2018-09-04 199 4874 2018-09-05 102 4875 2018-09-06 25 4876 2018-09-07 179 4877 2018-09-10 13 4878 2018-09-11 126 4879 2018-09-12 143 4880 2018-09-13 159 4881 2018-09-14 124 4882 2018-09-17 186 4883 2018-09-18 131 4884 2018-09-19 144 4885 2018-09-20 51 4886 2018-09-21 172 4887 2018-09-24 35 4888 2018-09-25 194 4889 2018-09-26 31 4890 2018-09-27 193 4891 2018-09-28 164 4892 2018-10-01 56 4893 2018-10-02 82 4894 2018-10-03 135 4895 2018-10-04 137 4896 2018-10-05 188 4897 2018-10-08 111 4898 2018-10-09 121 4899 2018-10-10 28 4900 2018-10-11 172 4901 2018-10-12 44 4902 2018-10-15 198 4903 2018-10-16 110 4904 2018-10-17 172 4905 2018-10-18 115 4906 2018-10-19 95 4907 2018-10-22 154 4908 2018-10-23 64 4909 2018-10-24 100 4910 2018-10-25 42 4911 2018-10-26 111 4912 2018-10-29 48 4913 2018-10-30 155 4914 2018-10-31 119 4915 2018-11-01 144 4916 2018-11-02 188 4917 2018-11-05 68 4918 2018-11-06 166 4919 2018-11-07 81 4920 2018-11-08 136 4921 2018-11-09 124 4922 2018-11-12 62 4923 2018-11-13 196 4924 2018-11-14 41 4925 2018-11-15 29 4926 2018-11-16 11 4927 2018-11-19 99 4928 2018-11-20 112 4929 2018-11-21 130 4930 2018-11-22 110 4931 2018-11-23 32 4932 2018-11-26 44 4933 2018-11-27 73 4934 2018-11-28 106 4935 2018-11-29 34 4936 2018-11-30 43 4937 2018-12-03 118 4938 2018-12-04 108 4939 2018-12-05 25 4940 2018-12-06 154 4941 2018-12-07 28 4942 2018-12-10 93 4943 2018-12-11 35 4944 2018-12-12 111 4945 2018-12-13 17 4946 2018-12-14 186 4947 2018-12-17 163 4948 2018-12-18 192 4949 2018-12-19 27 4950 2018-12-20 192 4951 2018-12-21 119 4952 2018-12-24 56 4953 2018-12-25 171 4954 2018-12-26 32 4955 2018-12-27 73 4956 2018-12-28 192 4957 2018-12-31 181 4958 2019-01-01 85 4959 2019-01-02 130 4960 2019-01-03 112 4961 2019-01-04 142 4962 2019-01-07 127 4963 2019-01-08 43 4964 2019-01-09 78 4965 2019-01-10 113 4966 2019-01-11 54 4967 2019-01-14 114 4968 2019-01-15 133 4969 2019-01-16 40 4970 2019-01-17 156 4971 2019-01-18 12 4972 2019-01-21 97 4973 2019-01-22 108 4974 2019-01-23 38 4975 2019-01-24 160 4976 2019-01-25 63 4977 2019-01-28 155 4978 2019-01-29 137 4979 2019-01-30 143 4980 2019-01-31 14 4981 2019-02-01 188 4982 2019-02-04 146 4983 2019-02-05 131 4984 2019-02-06 130 4985 2019-02-07 117 4986 2019-02-08 118 4987 2019-02-11 98 4988 2019-02-12 111 4989 2019-02-13 190 4990 2019-02-14 51 4991 2019-02-15 33 4992 2019-02-18 200 4993 2019-02-19 154 4994 2019-02-20 31 4995 2019-02-21 26 4996 2019-02-22 183 4997 2019-02-25 75 4998 2019-02-26 195 4999 2019-02-27 177 5000 2019-02-28 133 5001 2019-03-01 135 5002 2019-03-04 94 5003 2019-03-05 106 5004 2019-03-06 61 5005 2019-03-07 114 5006 2019-03-08 181 5007 2019-03-11 35 5008 2019-03-12 55 5009 2019-03-13 64 5010 2019-03-14 191 5011 2019-03-15 55 5012 2019-03-18 46 5013 2019-03-19 120 5014 2019-03-20 102 5015 2019-03-21 50 5016 2019-03-22 197 5017 2019-03-25 192 5018 2019-03-26 69 5019 2019-03-27 91 5020 2019-03-28 18 5021 2019-03-29 69 5022 2019-04-01 59 5023 2019-04-02 49 5024 2019-04-03 139 5025 2019-04-04 42 5026 2019-04-05 177 5027 2019-04-08 160 5028 2019-04-09 86 5029 2019-04-10 50 5030 2019-04-11 32 5031 2019-04-12 177 5032 2019-04-15 85 5033 2019-04-16 176 5034 2019-04-17 130 5035 2019-04-18 167 5036 2019-04-19 11 5037 2019-04-22 103 5038 2019-04-23 160 5039 2019-04-24 117 5040 2019-04-25 107 5041 2019-04-26 84 5042 2019-04-29 157 5043 2019-04-30 86 5044 2019-05-01 63 5045 2019-05-02 71 5046 2019-05-03 112 5047 2019-05-06 42 5048 2019-05-07 190 5049 2019-05-08 150 5050 2019-05-09 167 5051 2019-05-10 139 5052 2019-05-13 158 5053 2019-05-14 131 5054 2019-05-15 139 5055 2019-05-16 33 5056 2019-05-17 51 5057 2019-05-20 122 5058 2019-05-21 83 5059 2019-05-22 103 5060 2019-05-23 18 5061 2019-05-24 96 5062 2019-05-27 150 5063 2019-05-28 17 5064 2019-05-29 72 5065 2019-05-30 36 5066 2019-05-31 32 5067 2019-06-03 18 5068 2019-06-04 124 5069 2019-06-05 152 5070 2019-06-06 158 5071 2019-06-07 160 5072 2019-06-10 172 5073 2019-06-11 197 5074 2019-06-12 72 5075 2019-06-13 55 5076 2019-06-14 183 5077 2019-06-17 97 5078 2019-06-18 48 5079 2019-06-19 82 5080 2019-06-20 20 5081 2019-06-21 24 5082 2019-06-24 144 5083 2019-06-25 84 5084 2019-06-26 59 5085 2019-06-27 174 5086 2019-06-28 124 5087 2019-07-01 122 5088 2019-07-02 66 5089 2019-07-03 87 5090 2019-07-04 187 5091 2019-07-05 73 5092 2019-07-08 19 5093 2019-07-09 13 5094 2019-07-10 50 5095 2019-07-11 82 5096 2019-07-12 43 5097 2019-07-15 19 5098 2019-07-16 106 5099 2019-07-17 76 5100 2019-07-18 194 5101 2019-07-19 121 5102 2019-07-22 165 5103 2019-07-23 182 5104 2019-07-24 195 5105 2019-07-25 88 5106 2019-07-26 87 5107 2019-07-29 111 5108 2019-07-30 166 5109 2019-07-31 83 5110 2019-08-01 90 5111 2019-08-02 31 5112 2019-08-05 22 5113 2019-08-06 142 5114 2019-08-07 64 5115 2019-08-08 160 5116 2019-08-09 62 5117 2019-08-12 164 5118 2019-08-13 15 5119 2019-08-14 148 5120 2019-08-15 159 5121 2019-08-16 154 5122 2019-08-19 181 5123 2019-08-20 133 5124 2019-08-21 41 5125 2019-08-22 92 5126 2019-08-23 86 5127 2019-08-26 153 5128 2019-08-27 163 5129 2019-08-28 33 5130 2019-08-29 51 5131 2019-08-30 122 5132 2019-09-02 160 5133 2019-09-03 160 5134 2019-09-04 142 5135 2019-09-05 105 5136 2019-09-06 148 5137 2019-09-09 88 5138 2019-09-10 164 5139 2019-09-11 194 5140 2019-09-12 185 5141 2019-09-13 20 5142 2019-09-16 138 5143 2019-09-17 44 5144 2019-09-18 10 5145 2019-09-19 131 5146 2019-09-20 63 5147 2019-09-23 25 5148 2019-09-24 106 5149 2019-09-25 84 5150 2019-09-26 29 5151 2019-09-27 107 5152 2019-09-30 95 5153 2019-10-01 50 5154 2019-10-02 24 5155 2019-10-03 175 5156 2019-10-04 23 5157 2019-10-07 81 5158 2019-10-08 194 5159 2019-10-09 90 5160 2019-10-10 113 5161 2019-10-11 38 5162 2019-10-14 177 5163 2019-10-15 41 5164 2019-10-16 193 5165 2019-10-17 62 5166 2019-10-18 104 5167 2019-10-21 184 5168 2019-10-22 156 5169 2019-10-23 88 5170 2019-10-24 46 5171 2019-10-25 32 5172 2019-10-28 116 5173 2019-10-29 41 5174 2019-10-30 39 5175 2019-10-31 52 5176 2019-11-01 59 5177 2019-11-04 47 5178 2019-11-05 172 5179 2019-11-06 55 5180 2019-11-07 155 5181 2019-11-08 53 5182 2019-11-11 174 5183 2019-11-12 176 5184 2019-11-13 76 5185 2019-11-14 42 5186 2019-11-15 99 5187 2019-11-18 47 5188 2019-11-19 19 5189 2019-11-20 54 5190 2019-11-21 112 5191 2019-11-22 140 5192 2019-11-25 35 5193 2019-11-26 190 5194 2019-11-27 19 5195 2019-11-28 48 5196 2019-11-29 62 5197 2019-12-02 48 5198 2019-12-03 129 5199 2019-12-04 103 5200 2019-12-05 19 5201 2019-12-06 77 5202 2019-12-09 21 5203 2019-12-10 33 5204 2019-12-11 146 5205 2019-12-12 59 5206 2019-12-13 27 5207 2019-12-16 51 5208 2019-12-17 94 5209 2019-12-18 13 5210 2019-12-19 105 5211 2019-12-20 39 5212 2019-12-23 60 5213 2019-12-24 154 5214 2019-12-25 195 5215 2019-12-26 34 5216 2019-12-27 153 5217 2019-12-30 170 5218 2019-12-31 146 5219 2020-01-01 118 5220 2020-01-02 77 5221 2020-01-03 38 5222 2020-01-06 20 5223 2020-01-07 138 5224 2020-01-08 192 5225 2020-01-09 186 5226 2020-01-10 48 5227 2020-01-13 60 5228 2020-01-14 197 5229 2020-01-15 17 5230 2020-01-16 148 5231 2020-01-17 56 5232 2020-01-20 46 5233 2020-01-21 27 5234 2020-01-22 77 5235 2020-01-23 115 5236 2020-01-24 18 5237 2020-01-27 129 5238 2020-01-28 68 5239 2020-01-29 14 5240 2020-01-30 163 5241 2020-01-31 55 5242 2020-02-03 91 5243 2020-02-04 22 5244 2020-02-05 147 5245 2020-02-06 153 5246 2020-02-07 29 5247 2020-02-10 144 5248 2020-02-11 85 5249 2020-02-12 23 5250 2020-02-13 118 5251 2020-02-14 112 5252 2020-02-17 100 5253 2020-02-18 135 5254 2020-02-19 152 5255 2020-02-20 110 5256 2020-02-21 105 5257 2020-02-24 178 5258 2020-02-25 57 5259 2020-02-26 43 5260 2020-02-27 39 5261 2020-02-28 91 5262 2020-03-02 135 5263 2020-03-03 125 5264 2020-03-04 200 5265 2020-03-05 120 5266 2020-03-06 99 5267 2020-03-09 63 5268 2020-03-10 83 5269 2020-03-11 153 5270 2020-03-12 19 5271 2020-03-13 114 5272 2020-03-16 146 5273 2020-03-17 80 5274 2020-03-18 126 5275 2020-03-19 99 5276 2020-03-20 174 5277 2020-03-23 88 5278 2020-03-24 155 5279 2020-03-25 112 5280 2020-03-26 22 5281 2020-03-27 152 5282 2020-03-30 18 5283 2020-03-31 42 5284 2020-04-01 151 5285 2020-04-02 73 5286 2020-04-03 179 5287 2020-04-06 152 5288 2020-04-07 126 5289 2020-04-08 159 5290 2020-04-09 142 5291 2020-04-10 59 5292 2020-04-13 142 5293 2020-04-14 80 5294 2020-04-15 94 5295 2020-04-16 108 5296 2020-04-17 25 5297 2020-04-20 145 5298 2020-04-21 123 5299 2020-04-22 37 5300 2020-04-23 184 5301 2020-04-24 54 5302 2020-04-27 148 5303 2020-04-28 116 5304 2020-04-29 185 5305 2020-04-30 139 5306 2020-05-01 188 5307 2020-05-04 55 5308 2020-05-05 33 5309 2020-05-06 38 5310 2020-05-07 85 5311 2020-05-08 38 5312 2020-05-11 52 5313 2020-05-12 196 5314 2020-05-13 145 5315 2020-05-14 113 5316 2020-05-15 165 5317 2020-05-18 59 5318 2020-05-19 118 5319 2020-05-20 151 5320 2020-05-21 121 5321 2020-05-22 99 5322 2020-05-25 99 5323 2020-05-26 113 5324 2020-05-27 124 5325 2020-05-28 109 5326 2020-05-29 121 5327 2020-06-01 24 5328 2020-06-02 23 5329 2020-06-03 38 5330 2020-06-04 111 5331 2020-06-05 97 5332 2020-06-08 40 5333 2020-06-09 97 5334 2020-06-10 22 5335 2020-06-11 186 5336 2020-06-12 17 5337 2020-06-15 138 5338 2020-06-16 198 5339 2020-06-17 49 5340 2020-06-18 79 5341 2020-06-19 115 5342 2020-06-22 157 5343 2020-06-23 96 5344 2020-06-24 35 5345 2020-06-25 157 5346 2020-06-26 192 5347 2020-06-29 43 5348 2020-06-30 96 5349 2020-07-01 120 5350 2020-07-02 153 5351 2020-07-03 105 5352 2020-07-06 102 5353 2020-07-07 92 5354 2020-07-08 62 5355 2020-07-09 114 5356 2020-07-10 76 5357 2020-07-13 60 5358 2020-07-14 151 5359 2020-07-15 22 5360 2020-07-16 155 5361 2020-07-17 18 5362 2020-07-20 40 5363 2020-07-21 190 5364 2020-07-22 152 5365 2020-07-23 114 5366 2020-07-24 141 5367 2020-07-27 143 5368 2020-07-28 101 5369 2020-07-29 185 5370 2020-07-30 76 5371 2020-07-31 36 5372 2020-08-03 72 5373 2020-08-04 42 5374 2020-08-05 82 5375 2020-08-06 143 5376 2020-08-07 159 5377 2020-08-10 162 5378 2020-08-11 48 5379 2020-08-12 49 5380 2020-08-13 198 5381 2020-08-14 30 5382 2020-08-17 51 5383 2020-08-18 72 5384 2020-08-19 70 5385 2020-08-20 83 5386 2020-08-21 47 5387 2020-08-24 183 5388 2020-08-25 198 5389 2020-08-26 72 5390 2020-08-27 25 5391 2020-08-28 167 5392 2020-08-31 41 5393 2020-09-01 69 5394 2020-09-02 70 5395 2020-09-03 38 5396 2020-09-04 26 5397 2020-09-07 126 5398 2020-09-08 107 5399 2020-09-09 124 5400 2020-09-10 23 5401 2020-09-11 182 5402 2020-09-14 120 5403 2020-09-15 79 5404 2020-09-16 34 5405 2020-09-17 40 5406 2020-09-18 125 5407 2020-09-21 182 5408 2020-09-22 57 5409 2020-09-23 54 5410 2020-09-24 111 5411 2020-09-25 109 5412 2020-09-28 195 5413 2020-09-29 68 5414 2020-09-30 183 5415 2020-10-01 111 5416 2020-10-02 55 5417 2020-10-05 96 5418 2020-10-06 45 5419 2020-10-07 162 5420 2020-10-08 139 5421 2020-10-09 85 5422 2020-10-12 31 5423 2020-10-13 76 5424 2020-10-14 92 5425 2020-10-15 184 5426 2020-10-16 77 5427 2020-10-19 197 5428 2020-10-20 149 5429 2020-10-21 168 5430 2020-10-22 196 5431 2020-10-23 106 5432 2020-10-26 33 5433 2020-10-27 91 5434 2020-10-28 37 5435 2020-10-29 121 5436 2020-10-30 54 5437 2020-11-02 134 5438 2020-11-03 90 5439 2020-11-04 20 5440 2020-11-05 58 5441 2020-11-06 149 5442 2020-11-09 138 5443 2020-11-10 69 5444 2020-11-11 77 5445 2020-11-12 181 5446 2020-11-13 195 5447 2020-11-16 44 5448 2020-11-17 174 5449 2020-11-18 126 5450 2020-11-19 175 5451 2020-11-20 168 5452 2020-11-23 106 5453 2020-11-24 137 5454 2020-11-25 163 5455 2020-11-26 68 5456 2020-11-27 164 5457 2020-11-30 188 5458 2020-12-01 79 5459 2020-12-02 24 5460 2020-12-03 194 5461 2020-12-04 96 5462 2020-12-07 91 5463 2020-12-08 189 5464 2020-12-09 66 5465 2020-12-10 50 5466 2020-12-11 62 5467 2020-12-14 57 5468 2020-12-15 48 5469 2020-12-16 159 5470 2020-12-17 152 5471 2020-12-18 49 5472 2020-12-21 141 5473 2020-12-22 197 5474 2020-12-23 157 5475 2020-12-24 104 5476 2020-12-25 18 5477 2020-12-28 82 5478 2020-12-29 86 5479 2020-12-30 46 5480 2020-12-31 120 Press Enter to continue... [1] "Updating our timeseries TSVVV023 to have some non-trading values represented by NULL." INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$UpdateItem Updating TSVVV023 INFO [2024-03-13 10:17:25] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$UpdateItem TSVVV023 returned a response Press Enter to continue... [1] "Updating our timeseries TSVVV023 to have some non-trading values represented by NaNs." INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$UpdateItem Updating TSVVV023 INFO [2024-03-13 10:17:25] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$UpdateItem TSVVV023 returned a response metadata Id TSVVV023 Desc Modifying timeseries to be daily frequency LastModified 2024-03-13 StartDate 2000-01-01 EndDate 2000-01-13 Frequency Daily NoOfValues 10 Dates Values 1 1999-12-31 50 2 2000-01-03 60 3 2000-01-04 NaN 4 2000-01-05 80 5 2000-01-06 NaN 6 2000-01-07 90 7 2000-01-10 NaN 8 2000-01-11 100 9 2000-01-12 NaN 10 2000-01-13 120 Press Enter to continue... [1] "Deleting our timeseries TSVVV023" INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$DeleteItem Deleting TSVVV023 INFO [2024-03-13 10:17:25] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$DeleteItem TSVVV023 returned a response [1] "Timeseries TSVVV023 successfully deleted." Press Enter to continue... [1] "Deleting our timeseries TSVVV023 again to demonstrate the API server returning an error response." INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$DeleteItem Deleting TSVVV023 INFO [2024-03-13 10:17:25] DSConnect.R DSConnect$getJsonResponse Web response received INFO [2024-03-13 10:17:25] DatastreamUserCreated_TimeSeries.R TimeSeriesClient$DeleteItem TSVVV023 returned a response [1] "Timeseries DeleteItem failed on TSVVV023 with error UserObjectError : UNABLE TO RETRIEVE TIME SERIES" > # The demo has now finished. > > print(exp) function (x) .Primitive("exp") > > print('The demo has now finished.') [1] "The demo has now finished." > > > > proc.time() user system elapsed 6.71 0.43 8.03