'''
箱型图

箱型图：又称为盒须图、盒式图、盒状图或箱线图，是一种用做显示一组数据分散状况资料的统计图
包含一组数据的：最大值、最小值、中位数、上四分位数（Q3）、下四分位数（Q1）、异常值
① 中位数 → 一组数据平均分红两份，中间的数
② 上四分位数Q1 → 是将序列平均分红四份，计算(n+1)/4与(n-1)/4两种，通常使用(n+1)/4
③ 下四分位数Q3 → 是将序列平均分红四份，计算(1+n)/4*3=6.75
④ 内限 → T形的盒须就是内限，最大值区间Q3+1.5IQR,最小值区间Q1-1.5IQR （IQR=Q3-Q1）
⑤ 外限 → T形的盒须就是内限，最大值区间Q3+3IQR,最小值区间Q1-3IQR （IQR=Q3-Q1）
⑥ 异常值 → 内限以外 - 中度异常，外限以外 - 极度异常

plt.plot.box(),plt.boxplot()
'''

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

# plt.plot.box()绘制

fig,axes = plt.subplots(2,1,figsize=(10,6))
df = pd.DataFrame(np.random.rand(10, 5), columns=['A', 'B', 'C', 'D', 'E'])
color = dict(boxes='DarkGreen', whiskers='DarkOrange', medians='DarkBlue', caps='Gray')
# 箱型图着色
# boxes → 箱线
# whiskers → 分位数与error bar横线之间竖线的颜色
# medians → 中位数线颜色
# caps → error bar横线颜色

df.plot.box(ylim=[0,1.2],
           grid = True,
           color = color,
           ax = axes[0])
# color：样式填充

# df.plot.box(vert=False, 
#             positions=[1, 4, 5, 6, 8],
#             ax = axes[1],
#             grid = True,
#            color = color)
# vert：是否垂直，默认True
# position：箱型图占位

<matplotlib.axes._subplots.AxesSubplot at 0x1eba85398d0>

# plt.boxplot()绘制
# pltboxplot(x, notch=None, sym=None, vert=None, whis=None, positions=None, widths=None, patch_artist=None, bootstrap=None, 
# usermedians=None, conf_intervals=None, meanline=None, showmeans=None, showcaps=None, showbox=None, showfliers=None, boxprops=None, 
# labels=None, flierprops=None, medianprops=None, meanprops=None, capprops=None, whiskerprops=None, manage_xticks=True, autorange=False, 
# zorder=None, hold=None, data=None)

df = pd.DataFrame(np.random.rand(10, 5), columns=['A', 'B', 'C', 'D', 'E'])
plt.figure(figsize=(10,4))
# 建立图表、数据

f = df.boxplot(sym = 'o',  # 异常点形状，参考marker
               vert = True,  # 是否垂直
               whis = 1.5,  # IQR，默认1.5，也能够设置区间好比[5,95]，表明强制上下边缘为数据95%和5%位置
               patch_artist = True,  # 上下四分位框内是否填充，True为填充
               meanline = False,showmeans=True,  # 是否有均值线及其形状
               showbox = True,  # 是否显示箱线
               showcaps = True,  # 是否显示边缘线
               showfliers = True,  # 是否显示异常值
               notch = False,  # 中间箱体是否缺口
               return_type='dict'  # 返回类型为字典
              ) 
plt.title('boxplot')
print(f)

for box in f['boxes']:
    box.set( color='b', linewidth=1)        # 箱体边框颜色
    box.set( facecolor = 'b' ,alpha=0.5)    # 箱体内部填充颜色
for whisker in f['whiskers']:
    whisker.set(color='k', linewidth=0.5,linestyle='-')
for cap in f['caps']:
    cap.set(color='gray', linewidth=2)
for median in f['medians']:
    median.set(color='DarkBlue', linewidth=2)
for flier in f['fliers']:
    flier.set(marker='o', color='y', alpha=0.5)
# boxes, 箱线
# medians, 中位值的横线,
# whiskers, 从box到error bar之间的竖线.
# fliers, 异常值
# caps, error bar横线
# means, 均值的横线,

{'whiskers': [<matplotlib.lines.Line2D object at 0x000001EBA8329550>, <matplotlib.lines.Line2D object at 0x000001EBA83296A0>, <matplotlib.lines.Line2D object at 0x000001EBA833C5F8>, <matplotlib.lines.Line2D object at 0x000001EBA833C748>, <matplotlib.lines.Line2D object at 0x000001EBA834C630>, <matplotlib.lines.Line2D object at 0x000001EBA834C780>, <matplotlib.lines.Line2D object at 0x000001EBA835E668>, <matplotlib.lines.Line2D object at 0x000001EBA835E7B8>, <matplotlib.lines.Line2D object at 0x000001EBA83706A0>, <matplotlib.lines.Line2D object at 0x000001EBA83707F0>], 'caps': [<matplotlib.lines.Line2D object at 0x000001EBA8329B38>, <matplotlib.lines.Line2D object at 0x000001EBA8329F60>, <matplotlib.lines.Line2D object at 0x000001EBA833CB70>, <matplotlib.lines.Line2D object at 0x000001EBA833CF98>, <matplotlib.lines.Line2D object at 0x000001EBA834CBA8>, <matplotlib.lines.Line2D object at 0x000001EBA834CFD0>, <matplotlib.lines.Line2D object at 0x000001EBA835EBE0>, <matplotlib.lines.Line2D object at 0x000001EBA8367048>, <matplotlib.lines.Line2D object at 0x000001EBA8370C18>, <matplotlib.lines.Line2D object at 0x000001EBA8379080>], 'boxes': [<matplotlib.patches.PathPatch object at 0x000001EBA83292E8>, <matplotlib.patches.PathPatch object at 0x000001EBA833C358>, <matplotlib.patches.PathPatch object at 0x000001EBA834C3C8>, <matplotlib.patches.PathPatch object at 0x000001EBA835E400>, <matplotlib.patches.PathPatch object at 0x000001EBA8370438>], 'medians': [<matplotlib.lines.Line2D object at 0x000001EBA83323C8>, <matplotlib.lines.Line2D object at 0x000001EBA8343400>, <matplotlib.lines.Line2D object at 0x000001EBA8356438>, <matplotlib.lines.Line2D object at 0x000001EBA8367470>, <matplotlib.lines.Line2D object at 0x000001EBA83794A8>], 'fliers': [<matplotlib.lines.Line2D object at 0x000001EBA8332BE0>, <matplotlib.lines.Line2D object at 0x000001EBA8343C18>, <matplotlib.lines.Line2D object at 0x000001EBA8356C50>, <matplotlib.lines.Line2D object at 0x000001EBA8367C88>, <matplotlib.lines.Line2D object at 0x000001EBA8379CC0>], 'means': [<matplotlib.lines.Line2D object at 0x000001EBA83327F0>, <matplotlib.lines.Line2D object at 0x000001EBA8343828>, <matplotlib.lines.Line2D object at 0x000001EBA8356860>, <matplotlib.lines.Line2D object at 0x000001EBA8367898>, <matplotlib.lines.Line2D object at 0x000001EBA83798D0>]}

# plt.boxplot()绘制
# 分组汇总

df = pd.DataFrame(np.random.rand(10,2), columns=['Col1', 'Col2'] )
df['X'] = pd.Series(['A','A','A','A','A','B','B','B','B','B'])
df['Y'] = pd.Series(['A','B','A','B','A','B','A','B','A','B'])
print(df.head())
df.boxplot(by = 'X')
df.boxplot(column=['Col1','Col2'], by=['X','Y'])
# columns：按照数据的列分子图
# by：按照列分组作箱型图

       Col1      Col2  X  Y
0  0.275776  0.381310  A  A
1  0.446302  0.232518  A  B
2  0.723103  0.587340  A  A
3  0.397370  0.775876  A  B
4  0.382352  0.618421  A  A

array([<matplotlib.axes._subplots.AxesSubplot object at 0x000001EBA873A198>,
       <matplotlib.axes._subplots.AxesSubplot object at 0x000001EBA8761550>],
      dtype=object)

十二、箱型图