局部整体（八）利用python绘制华夫饼图

HsuHeinrich

发布于 2024-11-23 08:44:17

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局部整体（八）利用python绘制华夫饼图

华夫饼图（ Waffle chart）简介

华夫饼图是饼图的一种变体，一般由100个格子组成，一个格子代表1%。用不同颜色的格子区分不同的分类数据，以展示各部分在整体中的占比。尤其擅长展示部分在整体中的占比关系。

快速绘制

基于pywaffle

import matplotlib.pyplot as plt
from pywaffle import Waffle

# 自定义数据
data = {'Kevin': 10, 'Joseph': 7, 'Yan': 8}

# 基础华夫饼图
plt.figure(
    FigureClass=Waffle,
    rows=15,
    columns=20,
    values=data,
    legend={'loc': 'upper left', 'bbox_to_anchor': (1.05, 1)},
)
plt.show()

定制多样化的华夫饼图

自定义华夫饼图一般是结合使用场景对相关参数进行修改，并辅以其他的绘图知识。参数信息可以通过官网进行查看，其他的绘图知识则更多来源于实战经验，大家不妨将接下来的绘图作为一种学习经验，以便于日后总结。

更多用法可参考Basic Examples and Formats of Values[1]

修改参数 PyWaffle支持通过Font Awesome使用图标进行绘图，要搜索Font Awesome中可用的图标名称可访问 https://fontawesome.com/search import pandas as pd import matplotlib.pyplot as plt from pywaffle import Waffle import numpy as np # 自定义数据 data = {'Category 1': 15, 'Category 2': 30, 'Category 3': 10, 'Category 4': 25, 'Category 5': 20} # 计算方块数量 total_icons = sum(data.values()) # 自定义颜色图标 fig = plt.figure( FigureClass=Waffle, rows=10, values=data, icons='star', # 修改icon colors=["#FF5733", "#FFC300", "#900C3F", "#FF5733", "#C70039"], # 自定义颜色 legend={'loc': 'upper left', 'bbox_to_anchor': (1, 1)}, icon_legend=True, figsize=(8, 4), font_size = 18 ) plt.show()

自定义图例 # 自定义数据 data = {'Cat': 30, 'Dog': 16, 'Goat': 40} # 计算比例 repartition = [f"{k} ({int(v / sum(data.values()) * 100)}%)" for k, v in data.items()] # 自定义图例 fig = plt.figure( FigureClass=Waffle, rows=10, columns=15, values=data, title={ 'label': 'A graph with the distribution in the legend', 'loc': 'left', 'fontdict': { 'fontsize': 12 } }, labels=repartition, legend={ 'loc': 'lower left', 'bbox_to_anchor': (0, -0.15), 'ncol': len(data), 'fontsize': 12 } ) plt.show()

绘制多子图的分组华夫饼图 # 自定义数据 data = {'labels': ['Car', 'Truck', 'Motorcycle'], 'Factory A': [32384, 13354, 5245], 'Factory B': [22147, 6678, 2156], 'Factory C': [8932, 3879, 896], } df = pd.DataFrame(data).set_index('labels') # 图1-Factory A plot1 = {'values': [value/1000 for value in data['Factory A']], # 计算方块数 'labels': [f"{index} ({value})" for index, value in zip(df['Factory A'],df.index)], 'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.05, 1), 'fontsize': 8}, 'title': {'label': 'Vehicle Production of Factory A', 'loc': 'left', 'fontsize': 12} } # 图2-Factory B plot2 = {'values': [value/1000 for value in data['Factory B']], 'labels': [f"{index} ({value})" for index, value in zip(df['Factory B'],df.index)], 'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.2, 1), 'fontsize': 8}, 'title': {'label': 'Vehicle Production of Factory B', 'loc': 'left', 'fontsize': 12} } # 图3-Factory C plot3 = {'values': [value/1000 for value in data['Factory C']], 'labels': [f"{index} ({value})" for index, value in zip(df['Factory C'],df.index)], 'legend': {'loc': 'upper left', 'bbox_to_anchor': (1.3, 1), 'fontsize': 8}, 'title': {'label': 'Vehicle Production of Factory C', 'loc': 'left', 'fontsize': 12} } fig = plt.figure( FigureClass=Waffle, plots={ 311: plot1, 312: plot2, 313: plot3, }, rows=5, # 行数，应用于所有子图 cmap_name="Accent", # 颜色 rounding_rule='ceil', # 更改舍入规则（向上取整），因此小于1000的值也有一块 figsize=(8, 6) ) # 添加标题和注释信息 fig.suptitle('Vehicle Production by Vehicle Type', fontsize=14, fontweight='bold') fig.supxlabel('1 block = 1000 vehicles', fontsize=8, x=0.14, # 轴位置 ) fig.set_facecolor('#EEEDE7') plt.show()

基本堆积华夫饼条形图 import matplotlib.pyplot as plt import matplotlib.patches as mpatches from pywaffle import Waffle import pandas as pd # 自定义数据 data = { 2018: [3032, 2892, 804], 2019: [4537, 3379, 1096], 2020: [8932, 3879, 896], 2021: [22147, 6678, 2156], 2022: [32384, 13354, 5245] } df = pd.DataFrame(data, index=['car', 'truck', 'motorcycle']) number_of_bars = len(df.columns) # 每年一个bar # 初始化布局1*n的子图 fig, axs = plt.subplots(nrows=1, ncols=number_of_bars, figsize=(8,6),) # 迭代每个bar for i,ax in enumerate(axs): col_name = df.columns[i] values = df[col_name] Waffle.make_waffle( ax=ax, # 传参指定的ax rows=20, columns=5, values=values, ) plt.show()

垂直堆积华夫饼条形图 import matplotlib.pyplot as plt import matplotlib.patches as mpatches from pywaffle import Waffle import pandas as pd # 自定义数据 data = { 2018: [3032, 2892, 804], 2019: [4537, 3379, 1096], 2020: [8932, 3879, 896], 2021: [22147, 6678, 2156], 2022: [32384, 13354, 5245] } df = pd.DataFrame(data, index=['car', 'truck', 'motorcycle']) number_of_bars = len(df.columns) # 每年一个bar # 初始化布局1*n的子图 fig, axs = plt.subplots(nrows=1, ncols=number_of_bars, figsize=(8,6),) # 迭代每个bar for i,ax in enumerate(axs): col_name = df.columns[i] values = df[col_name] Waffle.make_waffle( ax=ax, rows=20, columns=5, values=values, vertical=True, # 垂直堆叠 ) plt.show()

自定义华夫饼风格 import matplotlib.pyplot as plt import matplotlib.patches as mpatches from pywaffle import Waffle import pandas as pd # 自定义数据 data = { 2018: [3032, 2892, 804], 2019: [4537, 3379, 1096], 2020: [8932, 3879, 896], 2021: [22147, 6678, 2156], 2022: [32384, 13354, 5245] } df = pd.DataFrame(data, index=['car', 'truck', 'motorcycle']) number_of_bars = len(df.columns) # 每年一个bar # 颜色 colors = ["darkred", "red", "darkorange"] # 初始化布局1*n的子图 fig, axs = plt.subplots(nrows=1, ncols=number_of_bars, figsize=(8,6),) # 迭代每个bar for i,ax in enumerate(axs): col_name = df.columns[i] values = df[col_name]/1000 Waffle.make_waffle( ax=ax, rows=20, columns=5, values=values, title={"label": col_name, "loc": "left"}, colors=colors, vertical=True, icons=['car-side', 'truck', 'motorcycle'], # 设置icon font_size=12, icon_legend=True, legend={'loc': 'upper left', 'bbox_to_anchor': (1, 1)}, ) # 添加标题 fig.suptitle('Vehicle Production by Year and Vehicle Type', fontsize=14, fontweight='bold') # 添加图例 legend_labels = df.index legend_elements = [mpatches.Patch(color=colors[i], label=legend_labels[i]) for i in range(len(colors))] fig.legend(handles=legend_elements, loc="upper right", title="Vehicle Types", bbox_to_anchor=(1.04, 0.9)) plt.subplots_adjust(right=0.85) plt.show()

利用华夫饼绘制象形柱图 import matplotlib.pyplot as plt import matplotlib.patches as mpatches from pywaffle import Waffle import pandas as pd # 自定义数据 data = { 2018: [3032, 2892, 804], 2019: [4537, 3379, 1096], 2020: [8932, 3879, 896], } df = pd.DataFrame(data, index=['car', 'truck', 'motorcycle']) # 颜色 colors = ["darkred", "red", "darkorange"] # 水平条形图：初始化布局1*n的子图（柱形图可以改一下布局，并改变下面的columns为rows） fig, axs = plt.subplots(nrows=3,ncols=1,figsize=(12,8),) # 迭代每个bar for i,ax in enumerate(axs): col_name = df.columns[i] values = df[col_name]/1000 Waffle.make_waffle( ax=ax, columns=10, # 这里的数值设置为所有数据中最大的，避免华夫饼图自动堆叠 values=values, title={"label": col_name, "loc": "left"}, icons=['car-side', 'truck', 'motorcycle'], # 设置icon colors=colors, rounding_rule='ceil', # 更改舍入规则（向上取整），因此小于1000的值也有一块 block_arranging_style='new-line', # 每一类从下一行开始绘制 vertical=True, # 垂直方向 interval_ratio_x=0.1, # 调整水平的格子间距比率 interval_ratio_y=0.1, # 调整垂直的格子间距比率 starting_location='NW', # 从左上角开始绘制 ) # 添加标题 fig.suptitle('Vehicle Production by Year and Vehicle Type', fontsize=14, fontweight='bold') # 添加图例 legend_labels = df.index legend_elements = [mpatches.Patch(color=colors[i], label=legend_labels[i]) for i in range(len(colors))] fig.legend(handles=legend_elements, loc="upper right", title="Vehicle Types", bbox_to_anchor=(1.04, 0.9)) plt.subplots_adjust(right=0.85) plt.show()