CODEWITHSUNDEEP
rfunctionlapply
Anders
Anders

Reputation: 73

R - Define several step function for lapply

Hi I have a list SPX400

I have already used lapply to subset: SPX400<- lapply(ALL400, function(x) x[x$ticker=="SPX",])

However I now want to filter my dataset even more and have tried to set up the following, defining a function to be used by lapply:

    Usedfilter <- function(x) {
  mutate(fifteen = x[x$expirDate-x$trade_date-15]) %>% #making new vairable
  filter(fifteen >=0) %>% # filter on fifteen
  mutate(Stockandexpricedif = x[x$stkPx-x$strike]) %>% #making new variable
  filter(Stockandexpricedif < 10 & Stockandexpricedif > -10) # filter on Stockandexpricedif
}

SPXfilter <- lapply(SPX400, Usedfilter)

I get the following error:

 Error in is.data.frame(.data) : 
  argument ".data" is missing, with no default

Hope you can help me out.

This is the structure of SPX400:

$ : tibble [2,498 × 37] (S3: tbl_df/tbl/data.frame)
  ..$ ticker          : chr [1:2498] "SPX" "SPX" "SPX" "SPX" ...
  ..$ stkPx           : num [1:2498] 1923 1923 1923 1923 1923 ...
  ..$ expirDate       : Date[1:2498], format: "2014-08-01" "2014-08-01" "2014-08-01" "2014-08-01" ...
  ..$ yte             : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ strike          : num [1:2498] 1350 1375 1400 1425 1450 ...
  ..$ cVolu           : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ cOi             : num [1:2498] 0 0 0 0 30 0 0 0 0 0 ...
  ..$ pVolu           : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ pOi             : num [1:2498] 770 3573 2246 7984 20967 ...
  ..$ cBidPx          : num [1:2498] 569 544 519 494 469 ...
  ..$ cValue          : num [1:2498] 574 549 524 499 474 ...
  ..$ cAskPx          : num [1:2498] 581 556 531 506 481 ...
  ..$ pBidPx          : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ pValue          : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ pAskPx          : num [1:2498] 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 ...
  ..$ cBidIv          : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ cMidIv          : num [1:2498] 0.00542 0.00567 0.00567 0 0.00567 0.00564 0.00567 0.00567 0.00567 0.00567 ...
  ..$ cAskIv          : num [1:2498] 0.0108 0.0113 0.0113 0 0.0113 ...
  ..$ smoothSmvVol    : num [1:2498] 0.321 0.327 0.333 0.333 0.235 ...
  ..$ pBidIv          : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ pMidIv          : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ pAskIv          : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ iRate           : num [1:2498] 1e-04 1e-04 1e-04 1e-04 1e-04 1e-04 1e-04 1e-04 1e-04 1e-04 ...
  ..$ divRate         : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ residualRateData: num [1:2498] -10 -10 -10 -10 -10 ...
  ..$ delta           : num [1:2498] 1 1 1 1 1 1 1 1 1 1 ...
  ..$ gamma           : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ theta           : num [1:2498] -138 -141 -143 -146 -148 ...
  ..$ vega            : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ rho             : num [1:2498] 0.000257 0.000261 0.000266 0.000271 0.000276 ...
  ..$ phi             : num [1:2498] -0.000366 -0.000366 -0.000366 -0.000366 -0.000366 ...
  ..$ driftlessTheta  : num [1:2498] -0.000975 -0.000993 -0.001011 -0.00103 -0.001047 ...
  ..$ extVol          : num [1:2498] 0.102 0.102 0.271 0.271 0.102 ...
  ..$ extCTheo        : num [1:2498] 593 568 543 518 493 ...
  ..$ extPTheo        : num [1:2498] 0 0 0 0 0 0 0 0 0 0 ...
  ..$ spot_px         : logi [1:2498] NA NA NA NA NA NA ...
  ..$ trade_date      : Date[1:2498], format: "2014-08-01" "2014-08-01" "2014-08-01" "2014-08-01" ...
  ..- attr(*, "problems")= tibble [9,071 × 5] (S3: tbl_df/tbl/data.frame)
  .. ..$ row     : int [1:9071] 39322 39323 39324 39325 39326 39327 39328 39329 39330 39331 ...
  .. ..$ col     : chr [1:9071] "spot_px" "spot_px" "spot_px" "spot_px" ...
  .. ..$ expected: chr [1:9071] "1/0/T/F/TRUE/FALSE" "1/0/T/F/TRUE/FALSE" "1/0/T/F/TRUE/FALSE" "1/0/T/F/TRUE/FALSE" ...
  .. ..$ actual  : chr [1:9071] "68.38" "68.38" "68.38" "68.38" ...
  .. ..$ file    : chr [1:9071] "'OSMV-20140801.csv'" "'OSMV-20140801.csv'" "'OSMV-20140801.csv'" "'OSMV-20140801.csv'" ...

Upvotes: 0

Views: 194

Answers (2)

linog
linog

Reputation: 6226

Since your datasets are "big", I recommend you to use data.table. The solution below is untested.

First, convert all your tables to data.table format:

library(data.table)
lapply(SPX400, setDT)

Then, define a generic function

Usedfilter <- function(df){
    df2 <- data.table::copy(df)
    df2[,fifteen := get('expirDate') - get('trade_date') - 15]
    df2 <- df[get('fifteen') > 0]
    df2[, ('Stockandexpricedif')  := get('stkPx') - get('strike')]
    #return(
    #  df2[between(get('Stockandexpricedif') , -10, 10, incbounds=FALSE)]
    #)
    return(df2[which.min(fifteen)])
}

And then, apply on all your dataframes:

SPX400_filtered <- lapply(SPX400, Usedfilter)

Upvotes: 1

Ronak Shah
Ronak Shah

Reputation: 388817

Try using : 

new_data <- Filter(length, SPX400)

SPXfilter <- lapply(new_data, function(df) subset(df, 
                  abs(expirDate - trade_date) >= 15 & abs(stkPx - strike) < 10))

This selects rows where the absolute difference between expirDate and trade_date is greater than equal to 15 days and absolute difference between stkPx and strike is less than 10.

Upvotes: 0

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