基于行值的seaborn热图配色方案 [英] seaborn heatmap color scheme based on row values

问题描述

我有一个数据帧，部分复制如下:

I have a dataframe, reproduced partly as such:

import pandas as pd
import numpy as np
tab = pd.DataFrame(np.array([[ 46,  39,  25,  29,  21,  12,  33,  32,  70, 109, 144, 158, 161,
    184, 163, 113, 117,  82,  76,  88,  77,  76,  64,  35],
   [ 39,  33,  29,  29,  26,  14,  25,  33,  60,  83, 126, 117, 111,
    148, 141, 104,  92,  75,  78,  74,  63,  67,  52,  39],
   [ 30,  27,  14,  11,  20,  17,  21,  31,  48,  62,  83,  78,  88,
     90,  80,  67,  53,  61,  47,  54,  50,  48,  35,  26],
   [ 30,  24,  19,  15,  17,  10,  12,  18,  34,  69,  88,  79, 109,
     95,  89,  82,  53,  46,  53,  57,  39,  41,  26,  29],
   [ 37,  31,  18,  12,  30,  13,  15,  19,  51,  61,  74,  81,  77,
    100,  96,  74,  60,  57,  42,  48,  43,  40,  29,  25],
   [ 14,   8,  14,  11,  13,   7,   9,  15,  42,  49,  50,  44,  53,
     42,  31,  31,  30,  27,  33,  25,  27,  17,  20,  17],
   [ 10,  15,   6,  10,  15,  11,   7,  18,  28,  43,  49,  37,  41,
     33,  37,  32,  26,  28,  19,  24,  19,  19,  13,  18],
   [  9,   9,   8,  12,   7,  11,   4,   8,  14,  15,  23,  30,  29,
     34,  25,  39,  22,  20,  15,  23,  12,  19,  14,  13],
   [  0,   3,   4,   1,   1,   0,   3,   4,   4,   5,   3,   5,   6,
      7,   3,   3,   6,   4,   2,   3,   3,   2,   2,   2],
   [  3,   0,   1,   0,   0,   0,   1,   1,   4,   8,   2,   4,   7,
      2,   2,   9,   3,   5,   1,   5,   2,   0,   4,   1]]), index = 
        ['Stadsdeel Zuid', 'Stadsdeel West', 'Stadsdeel Nieuw-West',
   'Stadsdeel Centrum', 'Stadsdeel Oost', 'Stadsdeel Noord',
   'Wijk 00 Amstelveen', 'Stadsdeel Zuidoost', 'Wijk 00',
   'Wijk 00 Aalsmeer'])

我就这样创建了一个热图

and I created a heatmap as such

ax = sns.heatmap(tab, linewidths=.5 ,robust=True ,annot_kws = {'size':14})
ax.tick_params(labelsize=14)
ax.figure.set_size_inches((12, 10))

我希望锚定颜色图的值基于每行的最小值-最大值，以便具有较低值的行也能清晰可见. (实际上，该表包含更多的低值行，而热图几乎无法按颜色显示)

I would like though that values to anchor the colormap are based on min-max values per row so that also rows with lower values are well visible. (in reality the table contains many more rows with low values that the heatmap barely shows color-wise)

如何实现这一目标?

推荐答案

我将使用每行中的最大值将tab行归一化:

I would normalize the tab rows by the maximum value in each row with:

tab_n = tab.div(tab.max(axis=1), axis=0)

其中，tab_n是规格化的制表符，其值在[0,1]范围内.希望能有所帮助.绘制tab_n应该返回如下的热图:

where tab_n is the normalized tab having values in the range [0,1]. Hope that helps. Plotting tab_n should return an heatmap like this:

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