图例颜色与图色不匹配

Question

我无法获得图表图例颜色与实际绘图颜色匹配。它们全都关闭了，有些关闭了。我将在下面发布代码，并介绍采取最终步骤的步骤。

这就是我最终得到的：

import pandas as pd
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches # needed for waffle Charts
%matplotlib inline

#The Data Frame:
borough3_df=borough_df.loc[['BRONX','BROOKLYN','MANHATTAN']]
borough3_df.head()

Borough已设置为索引，另一列为“总计”

步骤1。我首先要做的是确定每个类别相对于总数的比例。

# compute the proportion of each category with respect to the total
total_values = sum(borough3_df['Total'])
category_proportions = [(float(value) / total_values) for value in borough3_df['Total']]

# print out proportions
for i, proportion in enumerate(category_proportions):
    print (borough3_df.index.values[i] + ': ' + str(proportion))

BRONX: 0.3771366608264604
BROOKLYN: 0.35929220439297466
MANHATTAN: 0.26357113478056493

步骤2。第二步是定义华夫饼图的总体大小。

width = 30 # width of chart
height = 10 # height of chart

total_num_tiles = width * height # total number of tiles

步骤3。第三步是使用每个类别的比例来确定其各自的图块数量

# compute the number of tiles for each catagory
tiles_per_category = [round(proportion * total_num_tiles) for proportion in category_proportions]

# print out number of tiles per category
for i, tiles in enumerate(tiles_per_category):
    print (borough3_df.index.values[i] + ': ' + str(tiles))

布朗克斯：113 布鲁克林：108 曼哈顿：79

步骤4。第四步是创建一个类似于华夫饼图的矩阵并将其填充。

# initialize the waffle chart as an empty matrix
waffle_chart = np.zeros((height, width))

# define indices to loop through waffle chart
category_index = 0
tile_index = 0

# populate the waffle chart
for col in range(width):
    for row in range(height):
        tile_index += 1

        # if the number of tiles populated for the current category is equal to its corresponding allocated tiles...
        if tile_index > sum(tiles_per_category[0:category_index]):
            # ...proceed to the next category
            category_index += 1       

        # set the class value to an integer, which increases with class
        waffle_chart[row, col] = category_index

第5步。将华夫饼图矩阵映射到视觉图像中。

# instantiate a new figure object
fig = plt.figure()

# use matshow to display the waffle chart
colormap = plt.cm.coolwarm
plt.matshow(waffle_chart, cmap=colormap)
plt.colorbar()

# get the axis
ax = plt.gca()

# set minor ticks
ax.set_xticks(np.arange(-.5, (width), 1), minor=True)
ax.set_yticks(np.arange(-.5, (height), 1), minor=True)

# add gridlines based on minor ticks
ax.grid(which='minor', color='w', linestyle='-', linewidth=2)

plt.xticks([])
plt.yticks([])

#ADDITIONS

# compute cumulative sum of individual categories to match color schemes between chart and legend
values_cumsum = np.cumsum(borough3_df['Total'])
total_values = values_cumsum[len(values_cumsum) - 1]

# create legend
legend_handles = []
for i, category in enumerate(borough3_df.index.values):
    label_str = category + ' (' + str(borough3_df['Total'][i]) + ')'
    color_val = colormap(float(values_cumsum[i])/total_values)
    legend_handles.append(mpatches.Patch(color=color_val, label=label_str))


# add legend to chart
plt.legend(handles=legend_handles,
           loc='lower center', 
           ncol=len(borough3_df.index.values),
           bbox_to_anchor=(0., -0.2, 0.95, .1)
          )

布朗克斯应该是更深的蓝色 布鲁克林应该更浅蓝色 曼哈顿似乎一切正常。

这是图片：