[R] Better way of writing R code
arun
smartpink111 at yahoo.com
Fri Apr 5 19:13:10 CEST 2013
Hi,
You can preserve the order using join(). Though, in this case, merge would be easier.
library(plyr)
both<- join(currency_df,rate_df,type="left")
names(both)[14:15]<- paste0("currency_",names(both)[14:15])
names(rate_df)[2]<- "other_currency"
both2<- join(both,rate_df,type="left",by=c("other_currency","tenor"))
names(both2)[16:17]<- paste0("other_currency_",names(both2)[16:17])
A.K.
----- Original Message -----
From: "Adams, Jean" <jvadams at usgs.gov>
To: Katherine Gobin <katherine_gobin at yahoo.com>
Cc: R help <r-help at r-project.org>
Sent: Friday, April 5, 2013 9:40 AM
Subject: Re: [R] Better way of writing R code
Katherine,
To preserve the original order, you could create a new variable for the
currency data frame (BEFORE the merges), then use this variable to reorder
at the end.
currency_df$orig.order <- 1:dim(currency_df)[1]
You can do another merge for the other currency, you just need to specify
the columns that you want to merge by. The rate information will be called
rate.x for the first currency (from the first merge) and rate.y for the
other currency (from the second merge).
both2 <- merge(both, rate_df, by.x=c("other_currency", "tenor"),
by.y=c("currency", "tenor"), all.x=TRUE)
Then reorder.
both2 <- both2[order(both2$orig.order), ]
Jean
On Thu, Apr 4, 2013 at 3:19 AM, Katherine Gobin
<katherine_gobin at yahoo.com>wrote:
> Dear Mr Adams,
>
> I sincerely apologize for taking the liberty of writing to you. I
> wholeheartedly thank you for the wonderful solution you had provided me
> yesterday. I have customized the R code you had provided and it's yielding
> the results. I can't imagine me repeating the 10000 lines code after
> receving such a powerful solution from you. In future it will save lots of
> efforts from my side as I always deal with such situation.
>
> There is one small problem though -
>
> I am dealing with pair of currencies
>
> e.g. currency other_currency transaction
> USD EURO Buy
> USD CAD Buy
> GBP CHF Sell
> SEK USD Buy
>
>
> The R code gives me the currency rates (w.r.t. appropriate "tenor"),
> however, I need the corresponding rates pertaining to the other currency
> too i.e. in the first case, the maturity period applicable is one month so
> the R - code gives me one month LIBOR wr.t. USD, but I need the
> corresponding one month LIBOR w.r.t. the other currency i.e. EURO in this
> case.
>
> I tried to improve upon the merge statement and used "?merge", but
> couldn't. Another problem is the order of the original portfolio is not
> mainteained , but I think I can manage the order.
>
> With warm regards
>
>
> Katherine
>
>
>
>
>
>
>
>
> --- On *Wed, 3/4/13, Adams, Jean <jvadams at usgs.gov>* wrote:
>
>
> From: Adams, Jean <jvadams at usgs.gov>
> Subject: Re: [R] Better way of writing R code
> To: "Katherine Gobin" <katherine_gobin at yahoo.com>
> Cc: "R help" <r-help at r-project.org>
> Date: Wednesday, 3 April, 2013, 2:08 PM
>
> Katherine,
>
> You don't need to convert rate_df into tabular form. You just need to
> categorize each row in currency_df into a "tenor". Then you can merge the
> two data frames (by currency and tenor). For example ...
>
> # convert dates to R dates, to calculate the number of days to maturity
> # I am assuming this is the number of days from the current date to the
> maturity date
> currency_df$maturity <- as.Date(currency_df$maturity_date, "%d/%m/%Y")
> currency_df$current <- as.Date(currency_df$current_date, "%d/%m/%Y")
> currency_df$days2mature <- as.numeric(currency_df$maturity -
> currency_df$current)
>
> # categorize the number of days to maturity as you wish
> # you may need to change the breaks= option to suit your needs
> # read about the cut function to make sure you get the cut points included
> in the proper category, ?cut
> currency_df$tenor <- cut(currency_df$days2mature, breaks=c(0, 1, 7, 14,
> seq(from=30.5, length=12, by=30.5)),
> labels=c("1 day", "1 week", "2 weeks", "1 month", paste(2:12, "months")))
>
> # merge the currency_df and rate_df
> # this will work better with real data, since the example data you
> provided didn't have matching tenors
> both <- merge(currency_df, rate_df, all.x=TRUE)
>
> Jean
>
>
>
> On Wed, Apr 3, 2013 at 5:21 AM, Katherine Gobin <katherine_gobin at yahoo.com<http://mc/compose?to=katherine_gobin@yahoo.com>
> > wrote:
>
> Dear R forum,
>
> (Pl note this is not a finance problem)
>
> I have two data.frames as
>
> currency_df = data.frame(current_date = c("3/4/2013", "3/4/2013",
> "3/4/2013", "3/4/2013"), issue_date = c("27/11/2012", "9/12/2012",
> "14/01/2013", "28/02/2013"), maturity_date = c("27/04/2013", "3/5/2013",
> "14/6/2013", "28/06/2013"), currency = c("USD", "USD", "GBP", "SEK"),
> other_currency = c("EURO", "CAD", "CHF", "USD"), transaction = c("Buy",
> "Buy", "Sell", "Buy"), units_currency = c(100000, 25000, 150000, 40000),
> units_other_currency = c(78000, 25350, 99200, 6150))
>
> rate_df =
> data.frame(date =
> c("28/3/2013","27/3/2013","26/3/2013","25/3/2013","28/3/2013","27/3/2013","26/3/2013",
> "25/3/2013","28/3/2013","27/3/2013","26/3/2013","25/3/2013","28/3/2013","27/3/2013","26/3/2013",
> "25/3/2013","28/3/2013","27/3/2013","26/3/2013","25/3/2013","28/3/2013","27/3/2013","26/3/2013",
> "25/3/2013","28/3/2013","27/3/2013","26/3/2013","25/3/2013","28/3/2013","27/3/2013","26/3/2013",
> "25/3/2013","28/3/2013","27/3/2013","26/3/2013","25/3/2013"),
>
> currency = c("USD","USD","USD","USD", "USD", "USD",
> "USD","USD","USD","USD", "USD","USD",
> "GBP","GBP","GBP","GBP","GBP","GBP","GBP","GBP", "GBP","GBP", "GBP","GBP",
> "EURO","EURO","EURO","EURO","EURO","EURO","EURO", "EURO", "EURO","EURO",
> "EURO","EURO"),
>
> tenor = c("1 day","1 day","1 day","1 day","1 week","1 week","1 week","1
> week","2 weeks","2 weeks","2 weeks","2 weeks","1 day","1 day","1 day","1
> day","1 week","1 week","1 week","1 week","2 weeks","2 weeks","2 weeks","2
> weeks","1 day","1 day","1 day","1 day","1 week","1 week","1 week","1
> week","2 weeks","2 weeks","2 weeks","2 weeks"),
>
> rate =
> c(0.156,0.157,0.157,0.155,0.1752,0.1752,0.1752,0.1752,0.1752,0.1752,0.1752,
> 0.1752,0.48625,
> 0.485,0.48625,0.4825,0.49,0.49125,0.4925,0.49,0.49375,0.49125,0.4925,
> 0.49125,0.02643,0.02214,
> 0.02214,0.01929,0.034,0.034,0.034125,0.034,0.044,0.044, 0.041,0.045))
>
> # _______________________________________________________
>
> # 1st data.frame
>
> > currency_df
> current_date issue_date maturity_date currency
> 1 3/4/2013 27/11/2012 27/04/2013 USD
> 2 3/4/2013 9/12/2012 3/5/2013 USD
> 3 3/4/2013 14/01/2013 14/6/2013 GBP
> 4 3/4/2013 28/02/2013 28/06/2013 SEK
> other_currency transaction units_currency
> 1
> EURO Buy 100000
> 2 CAD Buy 25000
> 3 CHF Sell 150000
> 4 USD Buy 40000
> units_other_currency
> 1 78000
> 2
> 25350
> 3 99200
> 4 6150
>
> #
> .......................................................................................
>
> # 2nd data.frame
>
> > rate_df
> date currency tenor rate
> 1 28/3/2013 USD 1 day 0.156000
> 2 27/3/2013 USD 1 day 0.157000
> 3 26/3/2013 USD 1 day 0.157000
> 4 25/3/2013 USD 1 day 0.155000
> 5 28/3/2013 USD 1 week 0.175200
> 6 27/3/2013 USD 1 week
> 0.175200
> 7 26/3/2013 USD 1 week 0.175200
> 8 25/3/2013 USD 1 week 0.175200
> 9 28/3/2013 USD 2 weeks 0.175200
> 10 27/3/2013 USD 2 weeks 0.175200
> 11 26/3/2013 USD 2 weeks 0.175200
> 12 25/3/2013 USD 2 weeks 0.175200
> 13 28/3/2013 GBP 1 day 0.486250
> 14 27/3/2013 GBP 1 day 0.485000
> 15 26/3/2013 GBP 1 day 0.486250
> 16 25/3/2013 GBP 1 day 0.482500
> 17 28/3/2013 GBP 1 week 0.490000
> 18 27/3/2013 GBP 1 week 0.491250
> 19 26/3/2013 GBP 1 week 0.492500
> 20
> 25/3/2013 GBP 1 week 0.490000
> 21 28/3/2013 GBP 2 weeks 0.493750
> 22 27/3/2013 GBP 2 weeks 0.491250
> 23 26/3/2013 GBP 2 weeks 0.492500
> 24 25/3/2013 GBP 2 weeks 0.491250
> 25 28/3/2013 EURO 1 day 0.026430
> 26 27/3/2013 EURO 1 day 0.022140
> 27 26/3/2013 EURO 1 day 0.022140
> 28 25/3/2013 EURO 1 day 0.019290
> 29 28/3/2013 EURO 1 week 0.034000
> 30 27/3/2013 EURO 1 week 0.034000
> 31 26/3/2013 EURO 1 week 0.034125
> 32 25/3/2013 EURO 1 week 0.034000
> 33 28/3/2013 EURO 2 weeks 0.044000
> 34
> 27/3/2013 EURO 2 weeks 0.044000
> 35 26/3/2013 EURO 2 weeks 0.041000
> 36 25/3/2013 EURO 2 weeks 0.045000
>
> # ___________________________________________________
>
> Using plyr and reshape libraries, I have converted the rate_df into
> tabular form as
>
> date USD_1 day USD_1 week USD_2 weeks GBP_1 day
> 1 25/3/2013 0.155 0.1752 0.1752 0.48250
> 2 26/3/2013 0.157 0.1752 0.1752 0.48625
> 3 27/3/2013 0.157 0.1752 0.1752 0.48500
> 4 28/3/2013 0.156 0.1752 0.1752 0.48625
>
> GBP_1 week GBP_2 weeks EURO_1 day EURO_1 week
> 1 0.49000 0.49125 0.01929 0.034000
> 2 0.49250 0.49250 0.02214 0.034125
> 3 0.49125 0.49125 0.02214 0.034000
> 4 0.49000 0.49375 0.02643 0.034000
> EURO_2 weeks
> 1 0.045
> 2 0.041
> 3 0.044
> 4 0.044
>
> # __________________________________________________________
>
> Depending on the maturity period, I have defined discount rates as
>
> # FOR USD
>
>
> if
> (as.character(currency) ==
> "USD")
> {
> if
> (as.character(other_currency) == "GBP" & days_to_maturity <= 1)
>
> {
> libor_rate1 = df_LIBOR_rates$USD_o_n
> libor_rate2 = df_LIBOR_rates$GBP_o_n
> }
>
> else if (as.character(other_currency) == "EURO" & days_to_maturity <= 1)
>
> {
> libor_rate1 = df_LIBOR_rates$USD_o_n
> libor_rate2 = df_LIBOR_rates$EUR_o_n
> }
>
> ......................
> ......................
>
>
> if
> (as.character(other_currency) == "GBP" & (days_to_maturity > 1 &
> days_to_maturity <= 7))
>
> {
> libor_rate1 = df_LIBOR_rates$USD_1w
> libor_rate2 = df_LIBOR_rates$GBP_1w
> }
>
> else if (as.character(other_currency) == "EURO" & (days_to_maturity > 1
> & days_to_maturity <= 7))
>
> {
> libor_rate1 = df_LIBOR_rates$USD_1w
>
> libor_rate2 = df_LIBOR_rates$EUR_1w
> }
>
> ............................
> ............................
>
>
>
> Similarly for other currencies too ...
>
> # __________________________________________________
>
> # My PROBLEM
>
> In reality, I am dealing with at least (for the time being and will only
> increase in future) 10 currencies (LIBORs) only and each currency has about
> 15 tenors. So effectively, I have ended up writing 45*15*15 = 10125 such
> "if statements" only for assigning the rates depending on the tenor.
> (Tenors are overnight, 1 week, 2 weeks, 1 month, 2 months, 3 months, 4
> months, 5 months, 6 months, 7 months, 8 months, 9 months, 10 months, 11
> months, 12 months).
>
> The code is working and I am able to achieve what I need to. But, I think
> this is a foolish method of assigning the rates and each time a new
> currency is added, I will have to rewrite the whole code again. Also, the
> processing time is tremendous as it's taking me at least 10+ minutes.
>
> I am not a professional and hence this is my earnest request -
>
> Is it possible or is there any other way to assign the rates depending on
> the currency, other currency and tenor and also
> depending on the maturity period where maturity period is the difference
> in days between the maturity_date and current_date?
>
> Kindly guide
>
> Katherine
>
>
>
>
>
> [[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help at r-project.org <http://mc/compose?to=R-help@r-project.org> mailing
> list
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>
>
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