Python Matplotlib.pyplot.table()用法及代码示例

Matplotlib.pyplot.table()是matplotlib库的子部分，其中使用绘制的图形进行分析以生成表格。由于表格比图形提供了更精确的详细信息，因此该方法使分析更容易，更高效。 matplotlib.pyplot.table创建的表通常挂在堆积的条形图下方，以使读者了解上图所生成的数据。

用法：matplotlib.pyplot.table(cellText=None, cellColours=None, cellLoc=’right’, colWidths=None,rowLabels=None, rowColours=None, rowLoc=’left’, colLabels=None, colColours=None, colLoc=’center’, loc=’bottom’, bbox=None, edges=’closed’, **kwargs)

范例1：考虑一个图表，分析了几个月中农裁剪价格的上涨。以下代码用于非线性图。

Python3

# importing necesarry packagess 
import numpy as np 
import matplotlib.pyplot as plt 
  
  
# input data values 
data = [[322862, 876296, 45261, 782372,  32451], 
        [58230, 113139,  78045,  99308, 516044], 
        [89135,  8552, 15258, 497981, 603535], 
        [24415,  73858, 150656, 19323,  69638], 
        [139361, 831509, 43164, 7380,  52269]] 
  
# preparing values for graph 
columns = ('Soya', 'Rice', 'Wheat', 'Bakri', 'Ragi') 
rows = ['%d months' % x for x in (50, 35, 20, 10, 5)] 
values = np.arange(0, 2500, 500) 
value_increment = 1000
  
# Adding pastel shades to graph 
colors = plt.cm.Oranges(np.linspace(22, 3, 12)) 
n_rows = len(data) 
index = np.arange(len(columns)) + 0.3
bar_width = 0.4
  
# Initialing vertical-offset for the graph. 
y_offset = np.zeros(len(columns)) 
  
# Plot bars and create text labels for the table 
cell_text = [] 
  
for row in range(n_rows):
    plt.plot(index, data[row], bar_width, color=colors[row]) 
    y_offset = y_offset + data[row] 
    cell_text.append(['%1.1f' % (x / 1000.0) for x in y_offset]) 
  
# Reverse colors and text labels to display table contents with 
# color. 
colors = colors[::-1] 
cell_text.reverse() 
  
# Add a table at the bottom 
the_table = plt.table(cellText=cell_text, 
                      rowLabels=rows, 
                      rowColours=colors, 
                      colLabels=columns, 
                      loc='bottom') 
  
# make space for the table:
plt.subplots_adjust(left=0.2, bottom=0.2) 
plt.ylabel("Price in Rs.{0}'s".format(value_increment)) 
plt.yticks(values * value_increment, ['%d' % val for val in values]) 
plt.xticks([]) 
plt.title('Cost price increase') 
  
# plt.show()-display graph 
# Create image. plt.savefig ignores figure edge and face color. 
fig = plt.gcf() 
plt.savefig('pyplot-table-original.png', 
            bbox_inches='tight', 
            dpi=150)

输出：

范例2：让我们考虑一下过去几年中不同品牌的牛奶价格上涨

Python3

# importing necesarry packagess 
import numpy as np 
import matplotlib.pyplot as plt 
  
  
# input data values 
data = [[322862, 876296, 45261, 782372,  32451], 
        [58230, 113139,  78045,  99308, 516044], 
        [89135,  8552, 15258, 497981, 603535], 
        [24415,  73858, 150656, 19323,  69638], 
        [139361, 831509, 43164, 7380,  52269]] 
  
# preparing values for graph 
columns = ('Gokul', 'Kwality', 'Bakhri', 'Arun', 'Amul') 
rows = ['%d months' % x for x in (50, 35, 20, 10, 5)] 
values = np.arange(0, 2500, 500) 
value_increment = 1000
  
# Adding pastel shades to graph 
colors = plt.cm.Oranges(np.linspace(22, 3, 12)) 
n_rows = len(data) 
index = np.arange(len(columns)) + 0.3
bar_width = 0.4
  
# Initialing vertical-offset for the graph. 
y_offset = np.zeros(len(columns)) 
  
# Plot bars and create text labels for the table 
cell_text = [] 
for row in range(n_rows):
    plt.bar(index, data[row], bar_width, bottom=y_offset, color=colors[row]) 
    y_offset = y_offset + data[row] 
    cell_text.append(['%1.1f' % (x / 1000.0) for x in y_offset]) 
  
# Reverse colors and text labels to display table contents with 
# color. 
colors = colors[::-1] 
cell_text.reverse() 
  
# Add a table at the bottom 
the_table = plt.table(cellText=cell_text, 
                      rowLabels=rows, 
                      rowColours=colors, 
                      colLabels=columns, 
                      loc='bottom') 
  
# make space for the table:
plt.subplots_adjust(left=0.2, bottom=0.2) 
plt.ylabel("Rise in Rs's".format(value_increment)) 
plt.yticks(values * value_increment, ['%d' % val for val in values]) 
plt.xticks([]) 
plt.title('Cost of Milk od diff. brands') 
  
# plt.show()-display graph 
# Create image. plt.savefig ignores figure edge and face color. 
fig = plt.gcf() 
plt.savefig('pyplot-table-original.png', 
            bbox_inches='tight', 
            dpi=150)

输出：

相关用法

注：本文由纯净天空筛选整理自tedious_wings大神的英文原创作品 Matplotlib.pyplot.table() function in Python。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。