1

I have data on earnings which looks like the following;

# A tibble: 6 x 24
  m_ticker ticker comp_name    comp_name_2       exchange currency_code per_end_date_fr0
  <chr>    <chr>  <chr>        <chr>             <chr>    <chr>         <date>          
1 AAPL     AAPL   APPLE INC    Apple Inc.        NSDQ     USD           2017-09-30      
2 AXP      AXP    AMER EXPRES~ American Express~ NYSE     USD           2017-12-31      
3 BA       BA     BOEING CO    The Boeing Compa~ NYSE     USD           2017-12-31      
4 CTR      CAT    CATERPILLAR~ Caterpillar Inc.  NYSE     USD           2017-12-31      
5 CSCO     CSCO   CISCO SYSTE~ Cisco Systems, I~ NSDQ     USD           2017-07-31      
6 SD       CVX    CHEVRON CORP Chevron Corporat~ NYSE     USD           2017-12-31      
# ... with 17 more variables: per_end_date_qr1 <date>, eps_mean_est_qr1 <dbl>,
#   street_mean_est_qr1 <dbl>, exp_rpt_date_qr1 <date>, exp_rpt_date_qr2 <date>,
#   exp_rpt_date_fr1 <date>, exp_rpt_date_fr2 <date>, late_last_flag <dbl>,
#   late_last_desc <chr>, source_flag <dbl>, source_desc <chr>, time_of_day_code <dbl>,
#   time_of_day_desc <chr>, per_end_date_qr0 <date>, eps_act_qr0 <dbl>,
#   per_end_date_qrm3 <date>, eps_act_qrm3 <dbl>

I also have a vector of ticker symbols called tickers.

tickers <- c("PYPL", "GOOG", "AAPL", "MSFT", "CSCO")

I am trying to create an ifelse statement which will print a small table of the following columns from the earnings data:

ticker | comp_name | exp_rpt_date_qr1 | exp_rpt_date_qr2 | time_of_day_desc

So, if ticker matches earnings$ticker then print the above columns.

I have tried using grepl to print a basic yes / no which reports a warning message.

ifelse(grepl(tickers, earnings$ticker), "yes", "no")

Data:

earnings <- structure(list(m_ticker = c("AAPL", "AXP", "BA", "CTR", "CSCO", 
    "SD", "DIS", "GE", "GS&", "HOMD", "IBM", "ITL", "JNJ", "CHL", 
    "KO", "MCD", "MMM", "MRK", "MSFT", "NIKE", "PFE", "PG", "SPM", 
    "UNIH", "UA", "VISA", "BEL", "WMS", "J"), ticker = c("AAPL", 
    "AXP", "BA", "CAT", "CSCO", "CVX", "DIS", "GE", "GS", "HD", "IBM", 
    "INTC", "JNJ", "JPM", "KO", "MCD", "MMM", "MRK", "MSFT", "NKE", 
    "PFE", "PG", "TRV", "UNH", "UTX", "V", "VZ", "WMT", "XOM"), comp_name = c("APPLE INC", 
    "AMER EXPRESS CO", "BOEING CO", "CATERPILLAR INC", "CISCO SYSTEMS", 
    "CHEVRON CORP", "DISNEY WALT", "GENL ELECTRIC", "GOLDMAN SACHS", 
    "HOME DEPOT", "INTL BUS MACH", "INTEL CORP", "JOHNSON & JOHNS", 
    "JPMORGAN CHASE", "COCA COLA CO", "MCDONALDS CORP", "3M CO", 
    "MERCK & CO INC", "MICROSOFT CORP", "NIKE INC-B", "PFIZER INC", 
    "PROCTER & GAMBL", "TRAVELERS COS", "UNITEDHEALTH GP", "UTD TECHS CORP", 
    "VISA INC-A", "VERIZON COMM", "WALMART INC", "EXXON MOBIL CRP"
    ), comp_name_2 = c("Apple Inc.", "American Express Company", 
    "The Boeing Company", "Caterpillar Inc.", "Cisco Systems, Inc.", 
    "Chevron Corporation", "The Walt Disney Company", "General Electric Company", 
    "The Goldman Sachs Group, Inc.", "The Home Depot, Inc.", "International Business Machines Corporation", 
    "Intel Corporation", "Johnson & Johnson", "JPMorgan Chase & Co.", 
    "Coca-Cola Company (The)", "McDonald's Corporation", "3M Company", 
    "Merck & Co., Inc.", "Microsoft Corporation", "NIKE, Inc.", "Pfizer Inc.", 
    "Procter & Gamble Company (The)", "The Travelers Companies, Inc.", 
    "UnitedHealth Group Incorporated", "United Technologies Corporation", 
    "Visa Inc.", "Verizon Communications Inc.", "Walmart Inc.", "Exxon Mobil Corporation"
    ), exchange = c("NSDQ", "NYSE", "NYSE", "NYSE", "NSDQ", "NYSE", 
    "NYSE", "NYSE", "NYSE", "NYSE", "NYSE", "NSDQ", "NYSE", "NYSE", 
    "NYSE", "NYSE", "NYSE", "NYSE", "NSDQ", "NYSE", "NYSE", "NYSE", 
    "NYSE", "NYSE", "NYSE", "NYSE", "NYSE", "NYSE", "NYSE"), currency_code = c("USD", 
    "USD", "USD", "USD", "USD", "USD", "USD", "USD", "USD", "USD", 
    "USD", "USD", "USD", "USD", "USD", "USD", "USD", "USD", "USD", 
    "USD", "USD", "USD", "USD", "USD", "USD", "USD", "USD", "USD", 
    "USD"), per_end_date_fr0 = structure(c(17439, 17531, 17531, 17531, 
    17378, 17531, 17439, 17531, 17531, 17562, 17531, 17531, 17531, 
    17531, 17531, 17531, 17531, 17531, 17347, 17682, 17531, 17347, 
    17531, 17531, 17531, 17439, 17531, 17562, 17531), class = "Date"), 
        per_end_date_qr1 = structure(c(17712, 17712, 17712, 17712, 
        17743, 17712, 17712, 17712, 17712, 17743, 17712, 17712, 17712, 
        17804, 17712, 17712, 17712, 17712, 17712, 17774, 17712, 17712, 
        17712, 17712, 17712, 17712, 17712, 17743, 17712), class = "Date"), 
        eps_mean_est_qr1 = c(2.19, 1.83, 3.43, 2.66, 0.63, 2.1, 2.04, 
        0.18, 4.67, 2.85, 3.03, 0.99, 2.06, 2.27, 0.6, 1.93, 2.59, 
        1.03, 1.07, 0.61, 0.75, 0.91, 2.44, 3.03, 1.86, 1.09, 1.15, 
        1.21, 1.24), street_mean_est_qr1 = c(2.187, 1.83, 3.434, 
        2.658, 0.689, 2.098, 2.043, 0.178, 4.674, 2.847, 3.031, 0.99, 
        2.055, 2.27, 0.601, 1.929, 2.594, 1.03, 1.074, 0.609, 0.748, 
        0.906, 2.436, 3.031, 1.858, 1.089, 1.145, 1.212, 1.244), 
        exp_rpt_date_qr1 = structure(c(17743, 17730, 17737, 17742, 
        17758, 17739, 17750, 17732, 17729, 17764, 17730, 17738, 17729, 
        17815, 17737, 17738, 17736, 17739, 17731, 17799, 17743, 17743, 
        17731, 17729, 17736, 17737, 17736, 17759, 17739), class = "Date"), 
        exp_rpt_date_qr2 = structure(c(17836, 17821, 17828, 17827, 
        17856, 17830, 17843, 17823, 17820, 17848, 17820, 17829, 17820, 
        17907, 17828, 17827, 17827, 17830, 17829, 17885, 17834, 17823, 
        17822, 17820, 17827, 17828, 17822, 17850, 17830), class = "Date"), 
        exp_rpt_date_fr1 = structure(c(17836, 17913, 17926, 17920, 
        17758, 17928, 17843, 17919, 17912, 17946, 17913, 17920, 17918, 
        17907, 17942, 17925, 17920, 17928, 17731, 18074, 17925, 17743, 
        17918, 17911, 17919, 17828, 17918, 17946, 17928), class = "Date"), 
        exp_rpt_date_fr2 = structure(c(NA_real_, NA_real_, NA_real_, 
        NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
        NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
        NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
        NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, 
        NA_real_, NA_real_), class = "Date"), late_last_flag = c(0, 
        0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
        0, 0, 0, 0, 0, 0, 0, 0, 0), late_last_desc = c("Not late", 
        "Not late", "Not late", "Not late", "Not late", "Not late", 
        "Not late", "Not late", "Not late", "Not late", "Not late", 
        "Not late", "Not late", "Not late", "Not late", "Not late", 
        "Not late", "Not late", "Not late", "Not late", "Not late", 
        "Not late", "Not late", "Not late", "Not late", "Not late", 
        "Not late", "Not late", "Not late"), source_flag = c(1, 1, 
        1, 1, 2, 1, 1, 1, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 2, 1, 
        1, 1, 1, 1, 1, 1, 2, 1), source_desc = c("Company", "Company", 
        "Company", "Company", "Estimated", "Company", "Company", 
        "Company", "Company", "Estimated", "Company", "Company", 
        "Company", "Estimated", "Company", "Company", "Company", 
        "Company", "Company", "Estimated", "Company", "Company", 
        "Company", "Company", "Company", "Company", "Company", "Estimated", 
        "Company"), time_of_day_code = c(1, 1, 2, 2, 4, 2, 1, 2, 
        2, 4, 1, 1, 2, 4, 2, 2, 2, 2, 1, 4, 2, 2, 2, 2, 2, 1, 2, 
        4, 2), time_of_day_desc = c("After market close", "After market close", 
        "Before the open", "Before the open", "Unknown", "Before the open", 
        "After market close", "Before the open", "Before the open", 
        "Unknown", "After market close", "After market close", "Before the open", 
        "Unknown", "Before the open", "Before the open", "Before the open", 
        "Before the open", "After market close", "Unknown", "Before the open", 
        "Before the open", "Before the open", "Before the open", 
        "Before the open", "After market close", "Before the open", 
        "Unknown", "Before the open"), per_end_date_qr0 = structure(c(17621, 
        17621, 17621, 17621, 17651, 17621, 17621, 17621, 17621, 17651, 
        17621, 17621, 17621, 17712, 17621, 17621, 17621, 17621, 17621, 
        17682, 17621, 17621, 17621, 17621, 17621, 17621, 17621, 17651, 
        17621), class = "Date"), eps_act_qr0 = c(2.73, 1.86, 3.64, 
        2.82, 0.6, 1.9, 1.84, 0.16, 6.95, 2.08, 2.45, 0.87, 2.06, 
        2.29, 0.47, 1.79, 2.5, 1.05, 0.95, 0.69, 0.77, 1, 2.46, 3.04, 
        1.77, 1.11, 1.17, 1.14, 1.09), per_end_date_qrm3 = structure(c(17347, 
        17347, 17347, 17347, 17378, 17347, 17347, 17347, 17347, 17378, 
        17347, 17347, 17347, 17439, 17347, 17347, 17347, 17347, 17347, 
        17409, 17347, 17347, 17347, 17347, 17347, 17347, 17347, 17378, 
        17347), class = "Date"), eps_act_qrm3 = c(1.67, 1.47, 2.55, 
        1.49, 0.55, 0.91, 1.58, 0.28, 3.95, 2.25, 2.97, 0.72, 1.83, 
        1.76, 0.59, 1.73, 2.58, 1.01, 0.98, 0.57, 0.67, 0.85, 1.92, 
        2.46, 1.85, 0.86, 0.96, 1.08, 0.78)), .Names = c("m_ticker", 
    "ticker", "comp_name", "comp_name_2", "exchange", "currency_code", 
    "per_end_date_fr0", "per_end_date_qr1", "eps_mean_est_qr1", "street_mean_est_qr1", 
    "exp_rpt_date_qr1", "exp_rpt_date_qr2", "exp_rpt_date_fr1", "exp_rpt_date_fr2", 
    "late_last_flag", "late_last_desc", "source_flag", "source_desc", 
    "time_of_day_code", "time_of_day_desc", "per_end_date_qr0", "eps_act_qr0", 
    "per_end_date_qrm3", "eps_act_qrm3"), row.names = c(NA, -29L), class = c("tbl_df", 
    "tbl", "data.frame"))
Improve this question
3
  • You need to use "PYPL|GOOG|AAPL|MSFT|CSCO" in the grepl statement where you have tickers. Commented Jul 16, 2018 at 18:46
  • The tickers vector will change depending on which stock I choose to analyse. It is not possible to pass a vector through grepl? Commented Jul 16, 2018 at 18:47
  • 1
    you can use paste(tickers, collapse = "|") Commented Jul 16, 2018 at 18:53

1 Answer 1

Reset to default
3

Instead of grepl you can use %in%. Furthermore, if all you're doing is choosing specific rows and columns to print, you could use subset.

> keepcols = c('ticker','comp_name','exp_rpt_date_qr1','exp_rpt_date_qr2','time_of_day_desc')
> subset(earnings, ticker %in% tickers, select = keepcols)
   ticker      comp_name exp_rpt_date_qr1 exp_rpt_date_qr2   time_of_day_desc
1    AAPL      APPLE INC       2018-07-31       2018-11-01 After market close
5    CSCO  CISCO SYSTEMS       2018-08-15       2018-11-21            Unknown
19   MSFT MICROSOFT CORP       2018-07-19       2018-10-25 After market close
Improve this answer
Sign up to request clarification or add additional context in comments.

Comments

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.