Add data label to grouped bar chart in MatPlotLib
我设法找到并自定义了一些matplotlib代码以创建分组的条形图。但是，该代码的顶部没有标签。我已经尝试了几种方法，但是我只是做得不好。
我的最终目标将是：
任何帮助(尤其是#1帮助)都将不胜感激！
代码：
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 | #Code adapted from: #https://chrisalbon.com/python/matplotlib_grouped_bar_plot.html #matplotlib online import pandas as pd import matplotlib.pyplot as plt import numpy as np raw_data = {'plan_type': ['A1', 'A2', 'A3', 'A4', 'A5', 'A6'], 'Group A': [100, 0, 0, 0, 0, 0], 'Group B': [48, 16, 9, 22, 5, 0], 'Group C': [18, 28, 84, 34, 11, 0], 'Group D': [49, 13, 7, 23, 6, 0], 'Group E': [57, 16, 9, 26, 3, 0] } df = pd.DataFrame(raw_data, columns = ['plan_type', 'Group B', 'Group C', 'Group D', 'Group E']) df2 =pd.DataFrame(raw_data, columns = ['plan_type', 'Group A']) # Setting the positions and width for the bars pos = list(range(len(df['Group B']))) width = 0.2 # Plotting the bars fig, ax = plt.subplots(figsize=(7, 2)) #This creates another y-axis that shares the same x-axis # Create a bar with Group A data, # in position pos + some width buffer, plt.bar(pos, #using df['Group E'] data, df2['Group A'], # of width width*8, # with alpha 0.5 alpha=1, # with color color='#E6E9ED', # with label the fourth value in plan_type label=df2['plan_type'][0]) # Create a bar with Group B data, # in position pos, plt.bar(pos, #using df['Group B'] data, df['Group B'], # of width width, # with alpha 1 alpha=1, # with color color='#900C3F', # with label the first value in plan_type label=df['plan_type'][0]) # Create a bar with Group C data, # in position pos + some width buffer, plt.bar([p + width for p in pos], #using df['Group C'] data, df['Group C'], # of width width, # with alpha 1 alpha=1.0, # with color color='#C70039', # with label the second value in plan_type label=df['plan_type'][1]) # Create a bar with Group D data, # in position pos + some width buffer, plt.bar([p + width*2 for p in pos], #using df['Group D'] data, df['Group D'], # of width width, # with alpha 1 alpha=1, # with color color='#FF5733', # with label the third value in plan_type label=df['plan_type'][2]) # Create a bar with Group E data, # in position pos + some width buffer, plt.bar([p + width*3 for p in pos], #using df['Group E'] data, df['Group E'], # of width width, # with alpha 1 alpha=1, # with color color='#FFC300', # with label the fourth value in plan_type label=df['plan_type'][3]) # Set the y axis label ax.set_ylabel('Percent') # Set the chart's title ax.set_title('A GRAPH - YAY!', fontweight ="bold") # Set the position of the x ticks ax.set_xticks([p + 1.5 * width for p in pos]) # Set the labels for the x ticks ax.set_xticklabels(df['plan_type']) # Setting the x-axis and y-axis limits plt.xlim(min(pos)-width, max(pos)+width*5) plt.ylim([0, 100] ) #plt.ylim([0, max(df['Group B'] + df['Group C'] + df['Group D'] + df['Group E'])] ) # Adding the legend and showing the plot. Upper center location, 5 columns, Expanded to fit on one line. plt.legend(['Group A','Group B', 'Group C', 'Group D', 'Group E'], loc='upper center', ncol=5, mode='expand', fontsize ='x-small') #plt.grid() --> This would add a Grid, but I don't want that. plt.show() plt.savefig("PlanOffered.jpg") |
解决方案与此问题中的解决方案类似：
在matplotlib条形图上添加值标签
但是，我为您提供了一个示例，该示例使用了您自己的绘图类型，因此更易于理解。
为了在条形图的顶部获得标签，通常的想法是遍历轴内的斑块，并用其相应的高度标注它们。
我简化了代码。
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | import pandas as pd import matplotlib.pyplot as plt import numpy as np raw_data = {'plan_type': ['A1', 'A2', 'A3', 'A4', 'A5', 'A6'], 'Group A': [100, 0, 0, 0, 0, 0], 'Group B': [48, 16, 9, 22, 5, 0], 'Group C': [18, 28, 84, 34, 11, 0], 'Group D': [49, 13, 7, 23, 6, 0], 'Group E': [57, 16, 9, 26, 3, 0] } df2 =pd.DataFrame(raw_data, columns = ['plan_type', 'Group A']) df = pd.DataFrame(raw_data, columns = ['plan_type', 'Group B', 'Group C', 'Group D', 'Group E']) ax = df2.plot.bar(rot=0,color='#E6E9ED',width=1) ax = df.plot.bar(rot=0, ax=ax, color=["#900C3F", '#C70039', '#FF5733', '#FFC300'], width = 0.8 ) for p in ax.patches[1:]: h = p.get_height() x = p.get_x()+p.get_width()/2. if h != 0: ax.annotate("%g" % p.get_height(), xy=(x,h), xytext=(0,4), rotation=90, textcoords="offset points", ha="center", va="bottom") ax.set_xlim(-0.5, None) ax.margins(y=0) ax.legend(ncol=len(df.columns), loc="lower left", bbox_to_anchor=(0,1.02,1,0.08), borderaxespad=0, mode="expand") ax.set_xticklabels(df["plan_type"]) plt.show() |