• using R Under development (unstable) (2025-06-19 r88329)
• using platform: x86_64-pc-linux-gnu
• R was compiled by     clang version 20.1.7     flang version 20.1.7
• running under: Fedora Linux 42 (Workstation Edition)
• using session charset: UTF-8
• using option ‘--no-stop-on-test-error’
• checking for file ‘tidyquant/DESCRIPTION’ ... OK
• checking extension type ... Package
• this is package ‘tidyquant’ version ‘1.0.11’
• package encoding: UTF-8
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• checking package dependencies ... INFO Imports includes 24 non-default packages. Importing from so many packages makes the package vulnerable to any of them becoming unavailable. Move as many as possible to Suggests and use conditionally.
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• checking whether package ‘tidyquant’ can be installed ... [20s/62s] OK See the install log for details.
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• checking examples ... [19s/110s] ERROR Running examples in ‘tidyquant-Ex.R’ failed The error most likely occurred in: > ### Name: tq_mutate > ### Title: Mutates quantitative data > ### Aliases: tq_mutate tq_mutate_ tq_mutate_xy tq_mutate_xy_ > ### tq_mutate_fun_options tq_transmute tq_transmute_ tq_transmute_xy > ### tq_transmute_xy_ tq_transmute_fun_options > > ### ** Examples > > # Load libraries > library(dplyr) ######################### Warning from 'xts' package ########################## # # # The dplyr lag() function breaks how base R's lag() function is supposed to # # work, which breaks lag(my_xts). Calls to lag(my_xts) that you type or # # source() into this session won't work correctly. # # # # Use stats::lag() to make sure you're not using dplyr::lag(), or you can add # # conflictRules('dplyr', exclude = 'lag') to your .Rprofile to stop # # dplyr from breaking base R's lag() function. # # # # Code in packages is not affected. It's protected by R's namespace mechanism # # Set `options(xts.warn_dplyr_breaks_lag = FALSE)` to suppress this warning. # # # ############################################################################### Attaching package: ‘dplyr’ The following objects are masked from ‘package:xts’:     first, last The following objects are masked from ‘package:stats’:     filter, lag The following objects are masked from ‘package:base’:     intersect, setdiff, setequal, union > > ##### Basic Functionality > > fb_stock_prices <- tidyquant::FANG %>% + filter(symbol == "META") %>% + filter( + date >= "2016-01-01", + date <= "2016-12-31" + ) > > goog_stock_prices <- FANG %>% + filter(symbol == "GOOG") %>% + filter( + date >= "2016-01-01", + date <= "2016-12-31" + ) > > # Example 1: Return logarithmic daily returns using periodReturn() > fb_stock_prices %>% + tq_mutate(select = close, mutate_fun = periodReturn, + period = "daily", type = "log") # A tibble: 252 × 9    symbol date open high low close volume adjusted daily.returns    <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>  1 META 2016-01-04 102. 102. 99.8 102. 37912400 102. 0  2 META 2016-01-05 103. 104. 102. 103. 23258200 103. 0.00498  3 META 2016-01-06 101. 104. 101. 103. 25096200 103. 0.00233  4 META 2016-01-07 100. 101. 97.3 97.9 45172900 97.9 -0.0503  5 META 2016-01-08 99.9 100. 97.0 97.3 35402300 97.3 -0.00604  6 META 2016-01-11 97.9 98.6 95.4 97.5 29932400 97.5 0.00185  7 META 2016-01-12 99 100. 97.6 99.4 28395400 99.4 0.0189  8 META 2016-01-13 101. 101. 95.2 95.4 33410600 95.4 -0.0404  9 META 2016-01-14 95.8 98.9 92.4 98.4 48658600 98.4 0.0302 10 META 2016-01-15 94.0 96.4 93.5 95.0 45935600 95.0 -0.0352 # ℹ 242 more rows > > # Example 2: Use tq_mutate_xy to use functions with two columns required > fb_stock_prices %>% + tq_mutate_xy(x = close, y = volume, mutate_fun = EVWMA, + col_rename = "EVWMA") # A tibble: 252 × 9    symbol date open high low close volume adjusted EVWMA    <chr> <date> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>  1 META 2016-01-04 102. 102. 99.8 102. 37912400 102. NA  2 META 2016-01-05 103. 104. 102. 103. 23258200 103. NA  3 META 2016-01-06 101. 104. 101. 103. 25096200 103. NA  4 META 2016-01-07 100. 101. 97.3 97.9 45172900 97.9 NA  5 META 2016-01-08 99.9 100. 97.0 97.3 35402300 97.3 NA  6 META 2016-01-11 97.9 98.6 95.4 97.5 29932400 97.5 NA  7 META 2016-01-12 99 100. 97.6 99.4 28395400 99.4 NA  8 META 2016-01-13 101. 101. 95.2 95.4 33410600 95.4 NA  9 META 2016-01-14 95.8 98.9 92.4 98.4 48658600 98.4 NA 10 META 2016-01-15 94.0 96.4 93.5 95.0 45935600 95.0 95.0 # ℹ 242 more rows > > # Example 3: Using tq_mutate to work with non-OHLC data > tq_get("DCOILWTICO", get = "economic.data") %>% + tq_mutate(select = price, mutate_fun = lag.xts, k = 1, na.pad = TRUE) Warning: x = 'DCOILWTICO', get = 'economic.data': Error in getSymbols.FRED(Symbols = "DCOILWTICO", env = <environment>, : Unable to import “DCOILWTICO”. cannot open the connection Error in tq_mutate_.default(data = data, select = lazyeval::expr_text(select), :   data must be a tibble or data.frame object Calls: %>% -> tq_mutate -> tq_mutate_ -> tq_mutate_.default Execution halted
• checking for unstated dependencies in ‘tests’ ... OK
• checking tests ... [17s/48s] OK   Running ‘testthat.R’ [17s/48s]
• checking for unstated dependencies in vignettes ... OK
• checking package vignettes ... OK
• checking re-building of vignette outputs ... OK
• checking PDF version of manual ... [12s/24s] OK
• checking HTML version of manual ... OK
• checking for non-standard things in the check directory ... OK
• checking for detritus in the temp directory ... OK
• DONE

Status: 1 ERROR