七、柱状图、堆叠图

 

 

In [ ]:

'''
柱状图、堆叠图

plt.plot(kind='bar/barh') , plt.bar()

'''

In [2]:

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

In [8]:

# 柱状图与堆叠图

fig,axes = plt.subplots(4,1,figsize = (10,10))
s = pd.Series(np.random.randint(0,10,16),index = list('abcdefghijklmnop'))  
df = pd.DataFrame(np.random.rand(10,3), columns=['a','b','c'])

s.plot(kind='bar',ax = axes[0],color = 'k',grid = True,alpha = 0.5)  # ax参数 → 选择第几个子图
# 单系列柱状图方法一：plt.plot(kind='bar/barh')

df.plot(kind='bar',ax = axes[1],grid = True  )
# 多系列柱状图


df.plot.bar(ax = axes[2],grid = True ,stacked=True) 
# df.plot(kind='bar',ax = axes[2],grid = True ,stacked=True) 
# 多系列堆叠图
# stacked → 堆叠



df.plot.barh(ax = axes[3],grid = True,stacked=True,colormap = 'BuGn_r')
# 新版本plt.plot.<kind>

Out[8]:

<matplotlib.axes._subplots.AxesSubplot at 0x19feffea518>

 

In [17]:

# 柱状图 plt.bar()

plt.figure(figsize=(10,4))
x = np.arange(10)
y1 = np.random.rand(10)
y2 = -np.random.rand(10)

plt.bar(x,y1,width = 1,facecolor = 'yellowgreen',edgecolor = 'white',yerr = y1*0.1)
plt.bar(x,y2,width = 1,facecolor = 'lightskyblue',edgecolor = 'white',yerr = y2*0.1)
# x,y参数：x，y值
# width：宽度比例
# facecolor柱状图里填充的颜色、edgecolor是边框的颜色
# left-每一个柱x轴左边界,bottom-每一个柱y轴下边界 → bottom扩展便可化为甘特图 Gantt Chart
# align：决定整个bar图分布，默认left表示默认从左边界开始绘制,center会将图绘制在中间位置
# xerr/yerr ：wx/y方向error bar

for i,j in zip(x,y1):
    plt.text(i-0.2,j-0.15,'%.2f' % j, color = 'white')
for i,j in zip(x,y2):
    plt.text(i-0.2,j-0.15,'%.2f' % -j, color = 'black')
# 给图添加text
# zip() 函数用于将可迭代的对象做为参数，将对象中对应的元素打包成一个个元组，而后返回由这些元组组成的列表。

 

In [25]:

# 外嵌图表plt.table()
# 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)

data = [[ 66386, 174296,  75131, 577908,  32015],
        [ 58230, 381139,  78045,  99308, 160454],
        [ 89135,  80552, 152558, 497981, 603535],
        [ 78415,  81858, 150656, 193263,  69638],
        [139361, 331509, 343164, 781380,  52269]]
columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail')
rows = ['%d year' % x for x in (100, 50, 20, 10, 5)]
df = pd.DataFrame(data,
                  columns = ('Freeze', 'Wind', 'Flood', 'Quake', 'Hail'),
                  index = ['%d year' % x for x in (100, 50, 20, 10, 5)]
                 )
print(df)

df.plot(kind='bar',grid = True,colormap='Blues_r',stacked=True,figsize=(8,3))
# 建立堆叠图

plt.table(cellText = data,
          cellLoc='center',
          cellColours = None,
          rowLabels = rows,
          rowColours = plt.cm.BuPu(np.linspace(0, 0.5,5))[::-1],  # BuPu可替换成其余colormap
          colLabels = columns,
          colColours = plt.cm.Reds(np.linspace(0, 0.5,5))[::-1], 
          rowLoc='right',
          loc='bottom')
# cellText：表格文本
# cellLoc：cell内文本对齐位置
# rowLabels：行标签
# colLabels：列标签
# rowLoc：行标签对齐位置
# loc：表格位置 → left，right，top，bottom

plt.xticks([])
# 不显示x轴标注

 

          Freeze    Wind   Flood   Quake    Hail
100 year   66386  174296   75131  577908   32015
50 year    58230  381139   78045   99308  160454
20 year    89135   80552  152558  497981  603535
10 year    78415   81858  150656  193263   69638
5 year    139361  331509  343164  781380   52269

Out[25]:

([], <a list of 0 Text xticklabel objects>)

 

In [ ]: