帶有 stargazer() 的匯總表，qwraps2() 生成 \$\textbackslash pm\$

Question

我嘗試使用 stargazer() 和 qwraps2() package 獲取匯總表，但是我的代碼沒有生成預期的結果，而是像奇怪的表達式

1. \$\textbackslash pm\$ ,

2. 變量名不顯示並且

3. 大多數數字沒有逗號。 想知道我是否可以解決這三個問題。

我的數據是公司的財務報表，公司分為大公司和小公司。 我還將時間分為危機前和危機后兩個時期。 所以我的類別組是兩個：小公司與大公司以及危機前與危機后。 所以我的表有 4 列作為四個組合類別。

structure(list(firmid = structure(c("000020", "000020", "000020", 
"000020", "000020", "000020", "000020", "000020", "000020", "000020"
), label = "거래소코드", format.stata = "%9s"), year = structure(c(1991, 
1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000), format.stata = "%9.0g"), 
    postcrisis = structure(c(0, 0, 0, 0, 0, 0, 0, 1, 1, 1), format.stata = "%9.0g"), 
    firm_kor = structure(c("동화약품(주)", "동화약품(주)", 
    "동화약품(주)", "동화약품(주)", "동화약품(주)", 
    "동화약품(주)", "동화약품(주)", "동화약품(주)", 
    "동화약품(주)", "동화약품(주)"), label = "회사명", format.stata = "%44s"), 
    business_group = structure(c("동화약", "동화약", "동화약", 
    "동화약", "동화약", "동화약", "동화약", "동화약", 
    "동화약", "동화약"), label = "그룹사명", format.stata = "%33s"), 
    lbg30 = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g"), 
    lbg = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), label = "기업규모코드", format.stata = "%10.0gc"), 
    bg = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), format.stata = "%9.0g"), 
    size = structure(c("", "", "", "", "", "", "", "", "", ""
    ), label = "기업규모명", format.stata = "%12s"), assets = structure(c(12150840320, 
    15652244480, 16448676864, 19630718976, 29004148736, 28329910272, 
    27457734656, 62851514368, 59374006272, 50737635328), format.stata = "%9.0g"), 
    liability = structure(c(54948823040, 66054799360, 81120837632, 
    106961879040, 122920968192, 140161728512, 162787033088, 159752404992, 
    149670641664, 105075081216), format.stata = "%9.0g"), sales = structure(c(88381997056, 
    102572998656, 114394996736, 119775002624, 128408002560, 134840000512, 
    143815000064, 141186007040, 136299003904, 138230005760), format.stata = "%9.0g"), 
    profit = structure(c(44432998400, 50231001088, 55298998272, 
    58389999616, 63920001024, 62578999296, 67171000320, 69623996416, 
    59872002048, 53057998848), format.stata = "%9.0g"), ebit = structure(c(19534999552, 
    19583000576, 21048999936, 21987000320, 25397999616, 23047999488, 
    21745000448, 26130999296, 23641999360, 1.458e+09), label = "Earning before interest and taxes (million won)", format.stata = "%9.0g"), 
    va = structure(c(25720190976, 32258500608, 35595018240, 34623062016, 
    41200451584, 43741118464, 48058458112, 50603368448, 70541492224, 
    22522920960), format.stata = "%9.0g"), va_pw = structure(c(26930000, 
    32920000, 36430000, 34010000, 41870000, 45090000, 49540000, 
    55730000, 88180000, 30440000), format.stata = "%9.0g"), va_ratio = structure(c(29.1000003814697, 
    31.4500007629395, 31.1200008392334, 28.9099998474121, 32.0900001525879, 
    32.439998626709, 33.4199981689453, 35.8400001525879, 51.75, 
    16.2900009155273), format.stata = "%9.0g"), k_productivity = structure(c(819.200012207031, 
    588.530029296875, 744.309997558594, 608.419982910156, 702.099975585938, 
    779.320007324219, 911.700012207031, 991.530029296875, 1964.06994628906, 
    502.309997558594), format.stata = "%9.0g"), k_productivity_gross = structure(c(31.4400005340576, 
    33.1300010681152, 29.6599998474121, 23.4799995422363, 25.0900001525879, 
    23.0799999237061, 22.5599994659424, 19.7700004577637, 26.2700004577637, 
    9.72999954223633), format.stata = "%9.0g"), wb = structure(c(8572080128, 
    9890159616, 10399187968, 12745639936, 14407654400, 15426884608, 
    17462267904, 16719245312, 14328732672, 15299931136), format.stata = "%9.0g"), 
    deprec = structure(c(1540752000, 1781939968, 2044096000, 
    2322487040, 2697072896, 3057124096, 3395273984, 1194128000, 
    1957659008, 2335313920), format.stata = "%9.0g"), cogs = structure(c(43948998656, 
    52342001664, 59095998464, 61384998912, 64488001536, 72260001792, 
    76643999744, 71562002432, 76427001856, 85172002816), format.stata = "%9.0g"), 
    land = structure(c(3962739968, 4533998080, 4673968128, 5412840960, 
    15167494144, 15234676736, 15215484928, 44340424704, 43726028800, 
    34115977216), format.stata = "%9.0g"), facilities = structure(c(5593545216, 
    6132070912, 7142042112, 8962248704, 9655307264, 9766675456, 
    9834147840, 12669279232, 12533188608, 12470169600), format.stata = "%9.0g"), 
    structures = structure(c(428073984, 439003008, 453208992, 
    453208992, 462492992, 487492992, 493648000, 298323008, 309323008, 
    352156992), format.stata = "%9.0g"), machinery = structure(c(7848509952, 
    12346684416, 13176728576, 15883726848, 18024470528, 20001619968, 
    5274594816, 20351035392, 21328994304, 25123174400), format.stata = "%9.0g"), 
    mold_pattern = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g"), 
    machinery_heavy = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 
    0), format.stata = "%9.0g"), equipment = structure(c(0, 0, 
    0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g"), devices = structure(c(0, 
    0, 0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g")), row.names = c(NA, 
-10L), class = c("tbl_df", "tbl", "data.frame"))

我嘗試了以下方法。

our_summary1 <-
  list("Assets" =
       list("min"       = ~ min(assets),
            "max"       = ~ max(assets),
            "mean (sd)" = ~ qwraps2::mean_sd(assets)),
       "Liability" =
       list("min"       = ~ min(liability),
            "max"       = ~ max(liability),
            "mean (sd)" = ~ qwraps2::mean_sd(liability)),
       "Sales" =
       list("min"       = ~ min(sales),
            "max"       = ~ max(sales),
            "mean (sd)" = ~ qwraps2::mean_sd(sales)),
       "Capital share" =
       list("min"       = ~ min(k_share),
            "max"       = ~ max(k_share),
            "mean (sd)" = ~ qwraps2::mean_sd(k_share)),
         "Profit share" =
       list("min"       = ~ min(p_share),
            "max"       = ~ max(p_share),
            "mean (sd)" = ~ qwraps2::mean_sd(p_share)),
       "Business groups" =   
       list("Non-chaebol" = ~ qwraps2::n_perc0(lbg30 == 0),
            "Chaebol"  = ~ qwraps2::n_perc0(lbg30 == 1))
       )



whole <- summary_table(group_by(mydata, lbg30, postcrisis), our_summary1)
stargazer(whole)

我的結果是：

\begin{table}[!htbp] \centering 
  \caption{} 
  \label{} 
\begin{tabular}{@{\extracolsep{5pt}} ccccc} 
\\[-1.8ex]\hline 
\hline \\[-1.8ex] 
 & 0.0 (N = 2054) & 1.0 (N = 437) & 0.1 (N = 4958) & 1.1 (N = 1168) \\ 
\hline \\[-1.8ex] 
min & 1007414016 & 899977024 & 757000 & 304087008 \\ 
max & 56125391110144 & 8132442980352 & 67875771514880 & 43761086234624 \\ 
mean..sd. & 228,103,462,058.69 \$\textbackslash pm\$ 2,076,523,086,502.10 & 682,061,149,448.64 \$\textbackslash pm\$ 1,089,056,976,546.76 & 297,431,169,357.71 \$\textbackslash pm\$ 2,243,936,148,407.28 & 1,810,008,717,207.01 \$\textbackslash pm\$ 3,754,383,893,471.53 \\ 
min.1 & 1794923008 & 7073050112 & 889158016 & 1544504960 \\ 
max.1 & 29608464351232 & 17235575832576 & 33819348434944 & 27211834851328 \\ 
mean..sd..1 & 216,957,295,600.30 \$\textbackslash pm\$ 1,082,760,576,132.28 & 1,142,211,747,943.10 \$\textbackslash pm\$ 1,758,492,729,183.62 & 300,653,298,256.94 \$\textbackslash pm\$ 1,525,315,964,497.17 & 2,069,977,052,675.29 \$\textbackslash pm\$ 3,148,813,746,977.57 \\ 
min.2 & 2.488e+09 & 2664999936 & 3.13e+08 & 11944999936 \\ 
max.2 & 13116184199168 & 25041351737344 & 39189663973376 & 112249473597440 \\ 
mean..sd..2 & 218,013,170,581.56 \$\textbackslash pm\$ 747,575,842,745.56 & 1,630,072,085,639.91 \$\textbackslash pm\$ 3,036,650,802,612.91 & 455,256,841,211.49 \$\textbackslash pm\$ 1,714,674,929,904.94 & 4,083,970,061,917.81 \$\textbackslash pm\$ 8,303,192,785,561.71 \\ 
min.3 & 2.488e+09 & 2664999936 & 3.13e+08 & 11944999936 \\ 
max.3 & 13116184199168 & 25041351737344 & 39189663973376 & 112249473597440 \\ 
mean..sd..3 & 218,013,170,581.56 \$\textbackslash pm\$ 747,575,842,745.56 & 1,630,072,085,639.91 \$\textbackslash pm\$ 3,036,650,802,612.91 & 455,256,841,211.49 \$\textbackslash pm\$ 1,714,674,929,904.94 & 4,083,970,061,917.81 \$\textbackslash pm\$ 8,303,192,785,561.71 \\ 
min.4 & 2070000 & 2950000 & 190000 & 130000 \\ 
max.4 & 912830016 & 440569984 & 53583810560 & 36381839360 \\ 
mean..sd..4 & 45,713,821.82 \$\textbackslash pm\$ 37,358,735.51 & 66,567,940.47 \$\textbackslash pm\$ 54,096,233.32 & 162,652,232.58 \$\textbackslash pm\$ 1,121,170,189.51 & 396,946,421.21 \$\textbackslash pm\$ 2,091,558,126.59 \\ 
min.5 & 0 & 0 & 0 & 0 \\ 
max.5 & 663556 & 205244.3125 & 8574273536 & 5692597248 \\ 
mean..sd..5 & 2,806.53 \$\textbackslash pm\$ 23,025.97 & 2,538.26 \$\textbackslash pm\$ 13,319.14 & 17,120,018.31 \$\textbackslash pm\$ 264,568,202.95 & 27,713,502.17 \$\textbackslash pm\$ 349,100,779.66 \\ 
min.6 & 0.0258530080318451 & 0.0198683179914951 & 0.00108905520755798 & 0.00175066222436726 \\ 
max.6 & 500.657531738281 & 6.69289970397949 & 219.152282714844 & 429.950073242188 \\ 
mean..sd..6 & 0.64 \$\textbackslash pm\$ 11.04 & 0.37 \$\textbackslash pm\$ 0.36 & 0.70 \$\textbackslash pm\$ 3.61 & 0.85 \$\textbackslash pm\$ 12.60 \\ 
min.7 & 0.0849330127239227 & 0.0952611565589905 & 0.000275577913271263 & 0.000365072424756363 \\ 
max.7 & 141.074615478516 & 49.3747863769531 & 588.954650878906 & 5605.19091796875 \\ 
mean..sd..7 & 2.72 \$\textbackslash pm\$ 4.77 & 2.88 \$\textbackslash pm\$ 3.06 & 5.68 \$\textbackslash pm\$ 18.21 & 8.99 \$\textbackslash pm\$ 164.60 \\ 
min.8 & -7.74467849731445 & -0.465335518121719 & -4.67534494400024 & -1.5767308473587 \\ 
max.8 & 12.6667022705078 & 9.40117931365967 & 528.178955078125 & 534.63623046875 \\ 
mean..sd..8 & 0.79 \$\textbackslash pm\$ 0.59 & 0.80 \$\textbackslash pm\$ 0.64 & 1.53 \$\textbackslash pm\$ 8.56 & 1.73 \$\textbackslash pm\$ 15.81 \\ 
Non.chaebol & 2,054 (100) & 0 (0) & 4,958 (100) & 0 (0) \\ 
Chaebol & 0 (0) & 437 (100) & 0 (0) & 1,168 (100) \\ 
\hline \\[-1.8ex] 
\end{tabular} 
\end{table} 

Answer 1

根據?summary_table

 'summary_table' can be used to generate good looking, simple tables in LaTeX or markdown.

?stargazer ，另一方面：

'stargazer' 命令為格式良好的表格生成 LaTeX 代碼、HTML 代碼和 ASCII 文本，這些表格並排保存來自多個模型的回歸分析結果。

也就是說，這兩個函數都用於從 R 數據幀生成 latex 表。

如果你只是跑

mydata <- structure(list(firmid = structure(c("000020", "000020", "000020",
"000020", "000020", "000020", "000020", "000020", "000020", "000020"
), label = "거래소코드", format.stata = "%9s"), year = structure(c(1991,
1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000), format.stata = "%9.0g"),
    postcrisis = structure(c(0, 0, 0, 0, 0, 0, 0, 1, 1, 1), format.stata = "%9.0g"),
    firm_kor = structure(c("동화약품(주)", "동화약품(주)",
    "동화약품(주)", "동화약품(주)", "동화약품(주)",
    "동화약품(주)", "동화약품(주)", "동화약품(주)",
    "동화약품(주)", "동화약품(주)"), label = "회사명", format.stata = "%44s"),
    business_group = structure(c("동화약", "동화약", "동화약",
    "동화약", "동화약", "동화약", "동화약", "동화약",
    "동화약", "동화약"), label = "그룹사명", format.stata = "%33s"),
    lbg30 = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g"),
    lbg = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), label = "기업규모코드", format.stata = "%10.0gc"),
    bg = structure(c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1), format.stata = "%9.0g"),
    size = structure(c("", "", "", "", "", "", "", "", "", ""
    ), label = "기업규모명", format.stata = "%12s"), assets = structure(c(12150840320,
    15652244480, 16448676864, 19630718976, 29004148736, 28329910272,
    27457734656, 62851514368, 59374006272, 50737635328), format.stata = "%9.0g"),
    liability = structure(c(54948823040, 66054799360, 81120837632,
    106961879040, 122920968192, 140161728512, 162787033088, 159752404992,
    149670641664, 105075081216), format.stata = "%9.0g"), sales = structure(c(88381997056,
    102572998656, 114394996736, 119775002624, 128408002560, 134840000512,
    143815000064, 141186007040, 136299003904, 138230005760), format.stata = "%9.0g"),
    profit = structure(c(44432998400, 50231001088, 55298998272,
    58389999616, 63920001024, 62578999296, 67171000320, 69623996416,
    59872002048, 53057998848), format.stata = "%9.0g"), ebit = structure(c(19534999552,
    19583000576, 21048999936, 21987000320, 25397999616, 23047999488,
    21745000448, 26130999296, 23641999360, 1.458e+09), label = "Earning before interest and taxes (million won)", format.stata = "%9.0g"),
    va = structure(c(25720190976, 32258500608, 35595018240, 34623062016,
    41200451584, 43741118464, 48058458112, 50603368448, 70541492224,
    22522920960), format.stata = "%9.0g"), va_pw = structure(c(26930000,
    32920000, 36430000, 34010000, 41870000, 45090000, 49540000,
    55730000, 88180000, 30440000), format.stata = "%9.0g"), va_ratio = structure(c(29.1000003814697,
    31.4500007629395, 31.1200008392334, 28.9099998474121, 32.0900001525879,
    32.439998626709, 33.4199981689453, 35.8400001525879, 51.75,
    16.2900009155273), format.stata = "%9.0g"), k_productivity = structure(c(819.200012207031,
    588.530029296875, 744.309997558594, 608.419982910156, 702.099975585938,
    779.320007324219, 911.700012207031, 991.530029296875, 1964.06994628906,
    502.309997558594), format.stata = "%9.0g"), k_productivity_gross = structure(c(31.4400005340576,
    33.1300010681152, 29.6599998474121, 23.4799995422363, 25.0900001525879,
    23.0799999237061, 22.5599994659424, 19.7700004577637, 26.2700004577637,
    9.72999954223633), format.stata = "%9.0g"), wb = structure(c(8572080128,
    9890159616, 10399187968, 12745639936, 14407654400, 15426884608,
    17462267904, 16719245312, 14328732672, 15299931136), format.stata = "%9.0g"),
    deprec = structure(c(1540752000, 1781939968, 2044096000,
    2322487040, 2697072896, 3057124096, 3395273984, 1194128000,
    1957659008, 2335313920), format.stata = "%9.0g"), cogs = structure(c(43948998656,
    52342001664, 59095998464, 61384998912, 64488001536, 72260001792,
    76643999744, 71562002432, 76427001856, 85172002816), format.stata = "%9.0g"),
    land = structure(c(3962739968, 4533998080, 4673968128, 5412840960,
    15167494144, 15234676736, 15215484928, 44340424704, 43726028800,
    34115977216), format.stata = "%9.0g"), facilities = structure(c(5593545216,
    6132070912, 7142042112, 8962248704, 9655307264, 9766675456,
    9834147840, 12669279232, 12533188608, 12470169600), format.stata = "%9.0g"),
    structures = structure(c(428073984, 439003008, 453208992,
    453208992, 462492992, 487492992, 493648000, 298323008, 309323008,
    352156992), format.stata = "%9.0g"), machinery = structure(c(7848509952,
    12346684416, 13176728576, 15883726848, 18024470528, 20001619968,
    5274594816, 20351035392, 21328994304, 25123174400), format.stata = "%9.0g"),
    mold_pattern = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g"),
    machinery_heavy = structure(c(0, 0, 0, 0, 0, 0, 0, 0, 0,
    0), format.stata = "%9.0g"), equipment = structure(c(0, 0,
    0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g"), devices = structure(c(0,
    0, 0, 0, 0, 0, 0, 0, 0, 0), format.stata = "%9.0g")), row.names = c(NA,
-10L), class = c("tbl_df", "tbl", "data.frame"))


our_summary1 <-
  list("Assets" =
       list("min"       = ~ min(assets),
            "max"       = ~ max(assets),
            "mean (sd)" = ~ qwraps2::mean_sd(assets)),
       "Liability" =
       list("min"       = ~ min(liability),
            "max"       = ~ max(liability),
            "mean (sd)" = ~ qwraps2::mean_sd(liability)),
       "Sales" =
       list("min"       = ~ min(sales),
            "max"       = ~ max(sales),
            "mean (sd)" = ~ qwraps2::mean_sd(sales)),
       "Business groups" =   
       list("Non-chaebol" = ~ qwraps2::n_perc0(lbg30 == 0),
            "Chaebol"  = ~ qwraps2::n_perc0(lbg30 == 1))
       )

（請注意，您的數據不包括p_share和k_share所以我刪除了這些）

如果你運行：

library(tidyverse); library(qwraps2)
whole <- summary_table(group_by(mydata, lbg30, postcrisis), our_summary1)

您將獲得 LaTeX 表格環境。

\begin{tabular}{l|l|l}
\hline
 & 0.0 (N = 7) & 0.1 (N = 3)\\
\hline
\bf{Assets} & ~ & ~\\
\hline
~~ min & 12150840320 & 50737635328\\
\hline
~~ max & 29004148736 & 62851514368\\
\hline
~~ mean (sd) & 21,239,182,043.43 $\pm$ 6,935,313,632.37 & 57,654,385,322.67 $\pm$ 6,237,334,246.77\\
\hline
\bf{Liability} & ~ & ~\\
\hline
~~ min & 54948823040 & 105075081216\\
\hline
~~ max & 162787033088 & 159752404992\\
\hline
~~ mean (sd) & 104,993,724,123.43 $\pm$ 39,775,959,035.23 & 138,166,042,624.00 $\pm$ 29,097,582,083.91\\
\hline
\bf{Sales} & ~ & ~\\
\hline
~~ min & 88381997056 & 136299003904\\
\hline
~~ max & 143815000064 & 141186007040\\
\hline
~~ mean (sd) & 118,883,999,744.00 $\pm$ 19,079,750,722.14 & 138,571,672,234.67 $\pm$ 2,461,351,640.41\\
\hline
\bf{Business groups} & ~ & ~\\
\hline
~~ Non-chaebol & 7 (100) & 3 (100)\\
\hline
~~ Chaebol & 0 (0) & 0 (0)\\
\hline
\end{tabular}

要使其成為 latex 表，您需要在\begin{table}和 append 前面加上 \ \end{table} 。 渲染到 pdf 后，您會得到一個如下所示的表：