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r - `ifelse` 语句根据匹配的字符串返回多列

问题描述

我的数据earnings如下所示；

# 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>

我还有一个ticker符号向量，称为tickers.

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

我正在尝试创建一个ifelse语句，它将从数据中打印一个包含以下列的小表earnings：

ticker | comp_name | exp_rpt_date_qr1 | exp_rpt_date_qr2 | time_of_day_desc

因此，如果ticker匹配，earnings$ticker则打印上述列。

我曾尝试使用grepl打印一个基本yes / no的报告警告消息。

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

数据：

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"))

标签： r

解决方案

而不是grepl你可以使用%in%. 此外，如果您所做的只是选择要打印的特定行和列，则可以使用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

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