ImageMagick 在加入 2 个 PNG 时保留自定义调色板-6ren

ImageMagick 在加入 2 个 PNG 时保留自定义调色板

转载作者：行者123 更新时间：2023-12-04 20:39:21

我需要加入 2 张 PNG 图像，带有 16 个调色板，保持颜色编号和顺序为原件。

两种 PNG 都使用相同的 16 色调色板。

有没有一种方法可以创建具有所有颜色的 4 位索引 PNG，甚至在每个 PNG 中都没有使用？

编辑更清楚:

我有2张照片。
第一个是“level-000.png”:

它被识别为:

Image: level-000.png
  Format: PNG (Portable Network Graphics)
  Mime type: image/png
  Class: PseudoClass
  Geometry: 144x144+0+0
  Resolution: 28.35x28.35
  Print size: 5.07937x5.07937
  Units: PixelsPerCentimeter
  Type: Palette
  Endianess: Undefined
  Colorspace: sRGB
  Depth: 8-bit
  Channel depth:
    red: 8-bit
    green: 8-bit
    blue: 8-bit
  Channel statistics:
    Pixels: 20736
    Red:
      min: 0 (0)
      max: 184 (0.721569)
      mean: 88.6151 (0.34751)
      standard deviation: 27.9329 (0.109541)
      kurtosis: 1.7675
      skewness: 0.143857
    Green:
      min: 0 (0)
      max: 199 (0.780392)
      mean: 68.8957 (0.270179)
      standard deviation: 22.7411 (0.0891808)
      kurtosis: 18.2722
      skewness: 2.87959
    Blue:
      min: 0 (0)
      max: 111 (0.435294)
      mean: 19.4671 (0.0763416)
      standard deviation: 22.1775 (0.0869706)
      kurtosis: 2.80475
      skewness: 1.17593
  Image statistics:
    Overall:
      min: 0 (0)
      max: 199 (0.780392)
      mean: 58.9926 (0.231344)
      standard deviation: 24.4216 (0.095771)
      kurtosis: 17.5446
      skewness: 0.948025
  Colors: 4
  Histogram:
       390: (  0,  0,  0) #000000 black
     10196: ( 67, 57,  0) #433900 srgb(67,57,0)
      9770: (111, 79, 37) #6F4F25 srgb(111,79,37)
       380: (184,199,111) #B8C76F srgb(184,199,111)
  Colormap entries: 16
  Colormap:
         0: (  0,  0,  0) #000000 black
         1: (255,255,255) #FFFFFF white
         2: (104, 55, 43) #68372B srgb(104,55,43)
         3: (112,164,178) #70A4B2 srgb(112,164,178)
         4: (111, 61,134) #6F3D86 srgb(111,61,134)
         5: ( 88,141, 67) #588D43 srgb(88,141,67)
         6: ( 53, 40,121) #352879 srgb(53,40,121)
         7: (184,199,111) #B8C76F srgb(184,199,111)
         8: (111, 79, 37) #6F4F25 srgb(111,79,37)
         9: ( 67, 57,  0) #433900 srgb(67,57,0)
        10: (154,103, 89) #9A6759 srgb(154,103,89)
        11: ( 68, 68, 68) #444444 srgb(68,68,68)
        12: (108,108,108) #6C6C6C srgb(108,108,108)
        13: (154,210,132) #9AD284 srgb(154,210,132)
        14: (108, 94,181) #6C5EB5 srgb(108,94,181)
        15: (149,149,149) #959595 srgb(149,149,149)
  Rendering intent: Perceptual
  Gamma: 0.454545
  Chromaticity:
    red primary: (0.64,0.33)
    green primary: (0.3,0.6)
    blue primary: (0.15,0.06)
    white point: (0.3127,0.329)
  Background color: black
  Border color: srgb(223,223,223)
  Matte color: grey74
  Transparent color: black
  Interlace: None
  Intensity: Undefined
  Compose: Over
  Page geometry: 144x144+0+0
  Dispose: Undefined
  Iterations: 0
  Compression: Zip
  Orientation: Undefined
  Properties:
    date:create: 2015-04-10T12:24:18+02:00
    date:modify: 2015-04-09T22:33:29+02:00
    png:bKGD: chunk was found (see Background color, above)
    png:IHDR.bit-depth-orig: 4
    png:IHDR.bit_depth: 4
    png:IHDR.color-type-orig: 3
    png:IHDR.color_type: 3 (Indexed)
    png:IHDR.interlace_method: 0 (Not interlaced)
    png:IHDR.width,height: 144, 144
    png:pHYs: x_res=2835, y_res=2835, units=1
    png:PLTE.number_colors: 16
    png:sRGB: intent=0 (Perceptual Intent)
    signature: 00d9489d55480d588c3329ab0fa844ed2a67eea06fd4dfa793503a36f9c4b160
  Artifacts:
    filename: level-000.png
    verbose: true
  Tainted: False
  Filesize: 337B
  Number pixels: 20.7K
  Pixels per second: 0B
  User time: 0.000u
  Elapsed time: 0:01.000
  Version: ImageMagick 6.8.9-8 Q16 x86_64 2014-11-18

第二张图片是“scacchiera.png”。

它被识别为:

Image: scacchiera.png
  Format: PNG (Portable Network Graphics)
  Mime type: image/png
  Class: PseudoClass
  Geometry: 144x144+0+0
  Resolution: 28.35x28.35
  Print size: 5.07937x5.07937
  Units: PixelsPerCentimeter
  Type: Palette
  Endianess: Undefined
  Colorspace: sRGB
  Depth: 8-bit
  Channel depth:
    red: 8-bit
    green: 8-bit
    blue: 8-bit
  Channel statistics:
    Pixels: 20736
    Red:
      min: 67 (0.262745)
      max: 111 (0.435294)
      mean: 89 (0.34902)
      standard deviation: 22 (0.0862745)
      kurtosis: -2
      skewness: -1.18433e-11
    Green:
      min: 57 (0.223529)
      max: 79 (0.309804)
      mean: 68 (0.266667)
      standard deviation: 11 (0.0431373)
      kurtosis: -2
      skewness: 7.03683e-11
    Blue:
      min: 0 (0)
      max: 37 (0.145098)
      mean: 18.5 (0.072549)
      standard deviation: 18.5 (0.072549)
      kurtosis: -2
      skewness: 0
  Image statistics:
    Overall:
      min: 0 (0)
      max: 111 (0.435294)
      mean: 58.5 (0.229412)
      standard deviation: 17.7694 (0.0696837)
      kurtosis: 29.9398
      skewness: -1.66976
  Colors: 2
  Histogram:
     10368: ( 67, 57,  0) #433900 srgb(67,57,0)
     10368: (111, 79, 37) #6F4F25 srgb(111,79,37)
  Colormap entries: 16
  Colormap:
         0: (  0,  0,  0) #000000 black
         1: (255,255,255) #FFFFFF white
         2: (104, 55, 43) #68372B srgb(104,55,43)
         3: (112,164,178) #70A4B2 srgb(112,164,178)
         4: (111, 61,134) #6F3D86 srgb(111,61,134)
         5: ( 88,141, 67) #588D43 srgb(88,141,67)
         6: ( 53, 40,121) #352879 srgb(53,40,121)
         7: (184,199,111) #B8C76F srgb(184,199,111)
         8: (111, 79, 37) #6F4F25 srgb(111,79,37)
         9: ( 67, 57,  0) #433900 srgb(67,57,0)
        10: (154,103, 89) #9A6759 srgb(154,103,89)
        11: ( 68, 68, 68) #444444 srgb(68,68,68)
        12: (108,108,108) #6C6C6C srgb(108,108,108)
        13: (154,210,132) #9AD284 srgb(154,210,132)
        14: (108, 94,181) #6C5EB5 srgb(108,94,181)
        15: (149,149,149) #959595 srgb(149,149,149)
  Rendering intent: Perceptual
  Gamma: 0.454545
  Chromaticity:
    red primary: (0.64,0.33)
    green primary: (0.3,0.6)
    blue primary: (0.15,0.06)
    white point: (0.3127,0.329)
  Background color: white
  Border color: srgb(223,223,223)
  Matte color: grey74
  Transparent color: black
  Interlace: None
  Intensity: Undefined
  Compose: Over
  Page geometry: 144x144+0+0
  Dispose: Undefined
  Iterations: 0
  Compression: Zip
  Orientation: Undefined
  Properties:
    date:create: 2015-04-10T20:46:55+02:00
    date:modify: 2015-04-10T20:46:55+02:00
    png:IHDR.bit-depth-orig: 4
    png:IHDR.bit_depth: 4
    png:IHDR.color-type-orig: 3
    png:IHDR.color_type: 3 (Indexed)
    png:IHDR.interlace_method: 0 (Not interlaced)
    png:IHDR.width,height: 144, 144
    png:pHYs: x_res=2835, y_res=2835, units=1
    png:PLTE.number_colors: 16
    png:sRGB: intent=0 (Perceptual Intent)
    signature: 8a0ca53e6e6f8e8fc4b141c7194b399ed1fc32473b174b6240addbb3f98864e5
  Artifacts:
    filename: scacchiera.png
    verbose: true
  Tainted: False
  Filesize: 241B
  Number pixels: 20.7K
  Pixels per second: 0B
  User time: 0.000u
  Elapsed time: 0:01.000
  Version: ImageMagick 6.8.9-8 Q16 x86_64 2014-11-18

如您所见，两张图片具有相同的颜色:

  Colormap entries: 16
  Colormap:
         0: (  0,  0,  0) #000000 black
         1: (255,255,255) #FFFFFF white
         2: (104, 55, 43) #68372B srgb(104,55,43)
         3: (112,164,178) #70A4B2 srgb(112,164,178)
         4: (111, 61,134) #6F3D86 srgb(111,61,134)
         5: ( 88,141, 67) #588D43 srgb(88,141,67)
         6: ( 53, 40,121) #352879 srgb(53,40,121)
         7: (184,199,111) #B8C76F srgb(184,199,111)
         8: (111, 79, 37) #6F4F25 srgb(111,79,37)
         9: ( 67, 57,  0) #433900 srgb(67,57,0)
        10: (154,103, 89) #9A6759 srgb(154,103,89)
        11: ( 68, 68, 68) #444444 srgb(68,68,68)
        12: (108,108,108) #6C6C6C srgb(108,108,108)
        13: (154,210,132) #9AD284 srgb(154,210,132)
        14: (108, 94,181) #6C5EB5 srgb(108,94,181)
        15: (149,149,149) #959595 srgb(149,149,149)

如果我加入他们

convert -page 312x144+0+0 "scacchiera.png" -page +168+0 \
   "level-000.png" -background black -layers flatten "joined.png"

那么“joined.png”图片是:

它被识别为:

Image: joined.png
  Format: PNG (Portable Network Graphics)
  Mime type: image/png
  Class: PseudoClass
  Geometry: 312x144+0+0
  Resolution: 28.35x28.35
  Print size: 11.0053x5.07937
  Units: PixelsPerCentimeter
  Type: Palette
  Endianess: Undefined
  Colorspace: sRGB
  Depth: 8-bit
  Channel depth:
    red: 8-bit
    green: 8-bit
    blue: 8-bit
  Channel statistics:
    Pixels: 44928
    Red:
      min: 0 (0)
      max: 184 (0.721569)
      mean: 81.9762 (0.321475)
      standard deviation: 33.8163 (0.132613)
      kurtosis: 0.917842
      skewness: -0.743586
    Green:
      min: 0 (0)
      max: 199 (0.780392)
      mean: 63.1826 (0.247775)
      standard deviation: 25.0478 (0.0982265)
      kurtosis: 7.85041
      skewness: 0.0804364
    Blue:
      min: 0 (0)
      max: 111 (0.435294)
      mean: 17.5233 (0.0687188)
      standard deviation: 20.2675 (0.0794802)
      kurtosis: 1.51309
      skewness: 0.876441
  Image statistics:
    Overall:
      min: 0 (0)
      max: 199 (0.780392)
      mean: 54.2274 (0.212656)
      standard deviation: 26.9673 (0.105754)
      kurtosis: 7.87712
      skewness: 0.327418
  Colors: 4
  Histogram:
      3846: (  0,  0,  0) #000000 black
     20564: ( 67, 57,  0) #433900 srgb(67,57,0)
     20138: (111, 79, 37) #6F4F25 srgb(111,79,37)
       380: (184,199,111) #B8C76F srgb(184,199,111)
  Colormap entries: 4
  Colormap:
         0: ( 67, 57,  0) #433900 srgb(67,57,0)
         1: (111, 79, 37) #6F4F25 srgb(111,79,37)
         2: (  0,  0,  0) #000000 black
         3: (184,199,111) #B8C76F srgb(184,199,111)
  Rendering intent: Perceptual
  Gamma: 0.45455
  Chromaticity:
    red primary: (0.64,0.33)
    green primary: (0.3,0.6)
    blue primary: (0.15,0.06)
    white point: (0.3127,0.329)
  Background color: black
  Border color: srgb(223,223,223)
  Matte color: grey74
  Transparent color: black
  Interlace: None
  Intensity: Undefined
  Compose: Over
  Page geometry: 312x144+0+0
  Dispose: Undefined
  Iterations: 0
  Compression: Zip
  Orientation: Undefined
  Properties:
    date:create: 2015-04-12T15:13:11+02:00
    date:modify: 2015-04-12T15:13:11+02:00
    png:bKGD: chunk was found (see Background color, above)
    png:cHRM: chunk was found (see Chromaticity, above)
    png:gAMA: gamma=0.45454544 (See Gamma, above)
    png:IHDR.bit-depth-orig: 2
    png:IHDR.bit_depth: 2
    png:IHDR.color-type-orig: 3
    png:IHDR.color_type: 3 (Indexed)
    png:IHDR.interlace_method: 0 (Not interlaced)
    png:IHDR.width,height: 312, 144
    png:pHYs: x_res=2835, y_res=2835, units=1
    png:PLTE.number_colors: 4
    png:sRGB: intent=0 (Perceptual Intent)
    png:text: 2 tEXt/zTXt/iTXt chunks were found
    signature: 2049a10c0a2a73f864125d0ba93ccfc604a750667e3ba1d0fe8fe3be38a1cbea
  Artifacts:
    filename: joined.png
    verbose: true
  Tainted: False
  Filesize: 487B
  Number pixels: 44.9K
  Pixels per second: 4.493MB
  User time: 0.000u
  Elapsed time: 0:01.009
  Version: ImageMagick 6.8.9-8 Q16 x86_64 2014-11-18

你可以看到调色板与最初的完全不同。

图片在这里:

www.dropbox.com/s/jdftk03rizeqcub/scacchiera.png

www.dropbox.com/s/9c1fmav5qni8u2m/level-000.png

www.dropbox.com/s/8hhd1zyzb31c4me/joined.png

问题是: 有没有办法始终拥有这个调色板:

  Colormap entries: 16
  Colormap:
         0: (  0,  0,  0) #000000 black
         1: (255,255,255) #FFFFFF white
         2: (104, 55, 43) #68372B srgb(104,55,43)
         3: (112,164,178) #70A4B2 srgb(112,164,178)
         4: (111, 61,134) #6F3D86 srgb(111,61,134)
         5: ( 88,141, 67) #588D43 srgb(88,141,67)
         6: ( 53, 40,121) #352879 srgb(53,40,121)
         7: (184,199,111) #B8C76F srgb(184,199,111)
         8: (111, 79, 37) #6F4F25 srgb(111,79,37)
         9: ( 67, 57,  0) #433900 srgb(67,57,0)
        10: (154,103, 89) #9A6759 srgb(154,103,89)
        11: ( 68, 68, 68) #444444 srgb(68,68,68)
        12: (108,108,108) #6C6C6C srgb(108,108,108)
        13: (154,210,132) #9AD284 srgb(154,210,132)
        14: (108, 94,181) #6C5EB5 srgb(108,94,181)
        15: (149,149,149) #959595 srgb(149,149,149)

完全使用这 16 种颜色，并按每个重新调整的 PNG 的顺序？

最佳答案

我已经做了更多的工作，并且相信我可以实现你想要的......基本上，我允许 ImageMagick 完全按照你的方式对图像进行重新分页和连接，但随后我让 ImageMagick 输出一个 NetPBM 文件可移植任意 map PNM格式。然后我对 PNM 进行编码使用我编写的 Perl 编码器将文件格式化为 PNG，以满足您对调色板的非常具体的需求。因此，对于我从 PNM 读入的每个真彩色 24 位 RGB 像素文件，我通过计算平方误差的总和来计算它最接近哪个调色板条目，然后输出单个调色板索引。
NetPBM描述 here .
PNM格式非常易于解析，这就是我选择它的原因。说明here .

因此，您的原始命令几乎相同，除了 PNM文件在 stdout 上输出并读入 Perl 脚本 pnmtopng然后使 PNG你想要的文件:

convert -page 312x144+0+0 scacchiera.png -page +168+0 \
   level-000.png -background black -layers flatten pnm:- |  ./pnmtopng > out.png

Perl 脚本在这里:

#!/usr/bin/perl
use strict;
use warnings;
use Digest::CRC qw(crc32);
use IO::Compress::Deflate qw(deflate $DeflateError) ;

# Our beloved fixed palette
my @palette=(
      [0,0,0],
      [255,255,255],
      [104,55,43],
      [112,164,178],
      [111,61,134],
      [88,141,67],
      [53,40,121],
      [184,199,111],
      [111,79,37],
      [67,57,0],
      [154,103,89],
      [68,68,68],
      [108,108,108],
      [154,210,132],
      [108,94,181],
      [149,149,149]
   );

################################################################################
# Take chunk of PNG data as parameter, calculate its length & CRC, and output it
################################################################################
sub PNGoutputChunk()
{
   my $len=length($_[0])-4;
   my $crc = Digest::CRC->new(type=>"crc32");
   $crc->add($_[0]);
   print pack('N',$len),$_[0],pack('N',$crc->digest);
}

################################################################################
# Main
################################################################################

   # Read P6 PNM file from STDIN
   my $line = <STDIN>;
   chomp($line);
   if ($line ne "P6"){die "Expected P6 format PNM file"}

   # Read width and height from STDIN
   $line = <STDIN>;
   my ($width,$height) = ($line =~ /(\d+)\s+(\d+)/); 
   print STDERR "DEBUG: width=$width, height=$height\n";

   # Read MAX PNM value and ignore
   $line = <STDIN>;

   # Read entire remainder of PNM file
   my $expectedsize=$width * $height * 3;
   my $PNMdata;
   my $bytesRead = read(STDIN,$PNMdata,$expectedsize);
   if($bytesRead != $expectedsize){die "Unable to read PNM data"}

   # Output PNG header chunk
   printf "\x89PNG\x0d\x0a\x1a\x0a";

   my $bitdepth=8;
   my $colortype=3;
   my $compressiontype=0;
   my $filtertype=0;
   my $interlacetype=0;

   # Output PNG IHDR chunk
   my $IHDR='IHDR';
   $IHDR .= pack 'N',$width;
   $IHDR .= pack 'N',$height;
   $IHDR .= pack 'c',$bitdepth;
   $IHDR .= pack 'c',$colortype;
   $IHDR .= pack 'c',$compressiontype;
   $IHDR .= pack 'c',$filtertype;
   $IHDR .= pack 'c',$interlacetype;
   &PNGoutputChunk($IHDR);

   # Output PNG PLTE (palette)
   my $PLTE='PLTE';
   for(my $i=0;$i<scalar @palette;$i++){
      $PLTE .= sprintf('%c',$palette[$i][0]); # Red
      $PLTE .= sprintf('%c',$palette[$i][1]); # Green
      $PLTE .= sprintf('%c',$palette[$i][2]); # Blue
   }
   &PNGoutputChunk($PLTE);

   # Output PNG IDAT chunk
   # RFC-1950 zlib compression
   my $raw;
   # Go through PNM data, and for each RGB pixel, find nearest palette entry
   my @PNMvalues = unpack("C*",$PNMdata);
   print STDERR "Unpacked ",scalar @PNMvalues," from raw\n";
   for(my $pixel=0;$pixel<(scalar @PNMvalues)/3;$pixel++){

      # Output filter type byte (0) at start of each scanline
      if($pixel%$width==0){$raw .= "\x00";}

      my $r=$PNMvalues[(3*$pixel)];   # Red PNM value
      my $g=$PNMvalues[(3*$pixel)+1]; # Green PNM value
      my $b=$PNMvalues[(3*$pixel)+2]; # Blue PNM value
      my $nearest=0;
      my $distmin=(255*255)+(255*255)+(255*255); # Couldn't get further
      # Go through all palette entries to find nearest to this RGB
      for(my $pe=0;$pe<scalar @palette;$pe++){
         my $pr=$palette[$pe][0];   # Red palette value
         my $pg=$palette[$pe][1]; # Green palette value
         my $pb=$palette[$pe][2]; # Blue palette value
         my $dist = ($pr-$r)*($pr-$r) + ($pg-$g)*($pg-$g) + ($pb-$b)*($pb-$b);
         if($dist<$distmin){
            $distmin=$dist;
            $nearest=$pe;
         }
      }
      $raw .= sprintf "%c",$nearest;
      print STDERR "Pixel: $pixel, r=$r, g=$g, b=$b. Chose palette entry $nearest\n";
   }
   print STDERR "Length of raw: ",length($raw);

   my $deflated;
   my $status = deflate \$raw => \$deflated
        or die "deflate failed: $DeflateError\n";

   my $IDAT="IDAT" . $deflated;
   &PNGoutputChunk($IDAT);

   # Output PNG IEND chunk
   &PNGoutputChunk('IEND');

结果是这样的:

关于ImageMagick 在加入 2 个 PNG 时保留自定义调色板，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/29587679/

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我有两个表 tbl_user 和 tbl_lastchangepassword，如下所示表 tbl_user id| name --------- 1 | user1 2 | user2 3 |
MySQL查询优化[加入]
我有下一个问题 SELECT i.*, gu.* vs.* FROM common.global_users gu LEFT JOIN common.global_users_perms gup ON
mysql新手——加入
我有一个电影表和一个投票表。用户为他们喜欢的电影投票。我需要显示按电影总票数降序排列的电影列表。我现在所拥有的有点作品。唯一的问题是它不显示 0 票的电影。 SELECT m.name, m.imdb
MySql 加入 BETWEEN
我有一个由这样的表组成的 mySql 数据库: 我如何(如果可能的话)使用 JOINS 从名称/周期表中获取结果？简单来说，它是如何工作的？我向菜鸟问题道歉。我对此很陌生。任何帮助将不胜感激。最佳答
SQL 自引用查询。加入
我需要查询单元先决条件的自引用关系。我知道您需要使用两个联接，我是否选择我的列然后将其联接到自身？ SELECT u.unit_code, u.name + ' is a prerequisi
LINQ - 加入 OR 条件
我有两个实体，用户和友谊，它们看起来像: public class User { public int UserId { get; set; } (..
sql - 加入 OR 的性能
假设我有两个表: Table A ProdID | PartNumber | Data... 1 | ABC-a | "Data A" 2 | (null) |
r - 加入/合并数据框内的两列
说我有这个数据， (df <- data.frame( col1 = c('My','Your','His','Thir'), col2 = c('Cat','Dog','Fish','Dog')))
php - 加入/合并两个数组
我有两个这样的数组，实际上这是从两个不同的服务器检索的 mysql 数据: $array1 = array ( 0 => array ( 'id' => 1, 'n
sqlite - 从不同的表中获取结果 - 加入
我的数据库中有以下表格 CREATE TABLE [author_details] ( [_id] INTEGER PRIMARY KEY AUTOINCREMENT NOT NULL, [name
LINQ 加入 Where 子句
我正在努力使用一个相当简单的 sql select 语句的 join/where 子句。我正在尝试从 tb1 中检索产品信息列表，其中 where 条件位于 tbl2 中，但这必须由三个不同的列连接
haskell - “加入”申请？
我正在寻找以下功能: Applicative f => f (f a) -> f a Hoogle给我看join : >:t join join :: Monad m => m (m a) -> m
javascript - 加入 Firebase
我有两个“表”，分别是 USER 和 CONGE。在表“CONGE”中，我插入了用户的 ID。但是我不知道如何根据用户的id显示用户的休假。我想根据id发布“Congé”。 { "conge"
elasticsearch - 加入/合并Elasticsearch结果
我们有一个具有(简化)结构的文档，如Elasticsearch所示: { _id: ..., patientId: 4711, text: "blue" } { _id: ..., patientId
sql - 加入/哪里概念
这两个sql语句有什么区别 a) 从 T1,T2 中选择 *，其中 T1.A=T2.A ； b) 从 T1,T2 中选择 *，其中 T2.A=T1.A ；在这两种情况下我得到相同的输出，这两种语句之
NHibernate HQL - 加入
我想做一个简单的连接，只是比较两个表中的 ID.. 我有我的组表，包含；身份证姓名等.. 我的 GroupMap 表包含；身份证组号元素编号我的查询采用 GroupMap.ItemID
python - 加入/合并具有相同列名的数据框的微妙问题
所以我有一组主要数据，如下所示: value_num code value_letter 1 CDX A 2 DEF B

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