七、柱狀圖、堆疊圖

 

 

In [ ]:

'''
柱狀圖、堆疊圖

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

'''

In [2]:

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

In [8]:

# 柱狀圖與堆疊圖

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參數 → 選擇第幾個子圖
# 單系列柱狀圖方法一：plt.plot(kind='bar/barh')

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


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



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]:

# 柱狀圖 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參數：x，y值
# width：寬度比例
# facecolor柱狀圖裏填充的顏色、edgecolor是邊框的顏色
# left-每一個柱x軸左邊界,bottom-每一個柱y軸下邊界 → bottom擴展便可化爲甘特圖 Gantt Chart
# align：決定整個bar圖分佈，默認left表示默認從左邊界開始繪製,center會將圖繪製在中間位置
# 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')
# 給圖添加text
# zip() 函數用於將可迭代的對象做爲參數，將對象中對應的元素打包成一個個元組，而後返回由這些元組組成的列表。

 

In [25]:

# 外嵌圖表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))
# 建立堆疊圖

plt.table(cellText = data,
          cellLoc='center',
          cellColours = None,
          rowLabels = rows,
          rowColours = plt.cm.BuPu(np.linspace(0, 0.5,5))[::-1],  # BuPu可替換成其餘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內文本對齊位置
# rowLabels：行標籤
# colLabels：列標籤
# rowLoc：行標籤對齊位置
# loc：表格位置 → left，right，top，bottom

plt.xticks([])
# 不顯示x軸標註

 

          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>)

 

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