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+++ b/README.md
@@ -32,7 +32,6 @@ Matplotlib可以说是python数据可视化最重要且常见的工具之一，
 
 - 使用前请将matplotlib升级到最新版本V3.3.3(2020年12月)，否则可能会出现报错！
 - 本教程独立网站已上线：[https://datawhalechina.github.io/fantastic-matplotlib/](https://datawhalechina.github.io/fantastic-matplotlib/)
-- 本教程pdf版本已在仓库更新：[https://github.com/datawhalechina/fantastic-matplotlib/blob/main/fantastic-matplotlib.pdf](https://github.com/datawhalechina/fantastic-matplotlib/blob/main/fantastic-matplotlib.pdf)
 - 使用时若发现任何问题，或是你对项目内容有好的建议，欢迎留言交流
 
 
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@@ -10,7 +10,6 @@ kernelspec:
 # 第三回：布局格式定方圆
 
 
-
 ```{code-cell} ipython3
 import numpy as np
 import pandas as pd
@@ -23,7 +22,7 @@ plt.rcParams['axes.unicode_minus'] = False   #用来正常显示负号
 
 ### 1. 使用 `plt.subplots` 绘制均匀状态下的子图
 
-返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列
+返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列，不传入时默认值都为1
 
 `figsize` 参数可以指定整个画布的大小
 
@@ -47,8 +46,34 @@ fig.tight_layout()
 ```
 
 
+​    
+​    
 
 
+`subplots`是基于OO模式的写法，显式创建一个或多个axes对象，然后在对应的子图对象上进行绘图操作。  
+还有种方式是使用`subplot`这样基于pyplot模式的写法，每次在指定位置新建一个子图，并且之后的绘图操作都会指向当前子图，本质上`subplot`也是`Figure.add_subplot`的一种封装。
+
+在调用`subplot`时一般需要传入三位数字，分别代表总行数，总列数，当前子图的index
+
+
+```{code-cell} ipython3
+plt.figure()
+# 子图1
+plt.subplot(2,2,1) 
+plt.plot([1,2], 'r')
+# 子图2
+plt.subplot(2,2,2)
+plt.plot([1,2], 'b')
+#子图3
+plt.subplot(224)  # 当三位数都小于10时，可以省略中间的逗号，这行命令等价于plt.subplot(2,2,4) 
+plt.plot([1,2], 'g');
+```
+
+
+​    
+
+​    
+
 
 除了常规的直角坐标系，也可以通过`projection`方法创建极坐标系下的图表
 
@@ -66,6 +91,11 @@ plt.scatter(theta, r, c=colors, s=area, cmap='hsv', alpha=0.75);
 ```
 
 
+```{admonition} 练一练
+<p>请思考如何用极坐标系画出类似的玫瑰图</p>
+<img src="http://www.hinews.cn/news/pic/003/205/569/00320556959_f01764d0.jpg" width="300" align="bottom" />
+
+```
 
 
 
@@ -92,7 +122,9 @@ fig.tight_layout()
 ```
 
 
+​    
 
+​    
 
 
 在上面的例子中出现了 `spec[i, j]` 的用法，事实上通过切片就可以实现子图的合并而达到跨图的共能
@@ -121,39 +153,14 @@ fig.tight_layout()
 ```
 
 
+​    
 
+​    
 
 
 ## 二、子图上的方法
 
-在 `ax` 对象上定义了和 `plt` 类似的图形绘制函数，常用的有： `plot, hist, scatter, bar, barh, pie`
-
-
-```{code-cell} ipython3
-fig, ax = plt.subplots(figsize=(4,3))
-ax.plot([1,2],[2,1]);
-```
-
-
-
-
-
-
-```{code-cell} ipython3
-fig, ax = plt.subplots(figsize=(4,3))
-ax.hist(np.random.randn(1000));
-```
-
-
-
-
-
-
-
-
-
-
-
+补充介绍一些子图上的方法
 
 常用直线的画法为： `axhline, axvline, axline` （水平、垂直、任意方向）
 
@@ -166,91 +173,64 @@ ax.axline([0.3,0.3],[0.7,0.7]);
 ```
 
 
+​    
 
-
+​    
 
 
 使用 `grid` 可以加灰色网格
 
+
 ```{code-cell} ipython3
 fig, ax = plt.subplots(figsize=(4,3))
 ax.grid(True)
 ```
 
 
+​    
+
+​    
 
 
-使用 `set_xscale, set_title, set_xlabel` 分别可以设置坐标轴的规度（指对数坐标等）、标题、轴名
+使用 `set_xscale` 可以设置坐标轴的规度（指对数坐标等）
+
 
 ```{code-cell} ipython3
 fig, axs = plt.subplots(1, 2, figsize=(10, 4))
-fig.suptitle('大标题', size=20)
 for j in range(2):
     axs[j].plot(list('abcd'), [10**i for i in range(4)])
     if j==0:
         axs[j].set_yscale('log')
-        axs[j].set_title('子标题1')
-        axs[j].set_ylabel('对数坐标')
     else:
-        axs[j].set_title('子标题1')
-        axs[j].set_ylabel('普通坐标')
+        pass
 fig.tight_layout()
 ```
 
 
+​    
+
+​    
+
+
+## 思考题
+
+- 墨尔本1981年至1990年的每月温度情况  
+
+数据集来自github仓库下data/layout_ex1.csv  
+请利用数据，画出如下的图：
+
+<img src="https://s1.ax1x.com/2020/11/01/BwvCse.png" width="800" align="bottom" />
 
 
 
-与一般的 `plt` 方法类似， `legend, annotate, arrow, text` 对象也可以进行相应的绘制
+-  画出数据的散点图和边际分布
 
+用 `np.random.randn(2, 150)` 生成一组二维数据，使用两种非均匀子图的分割方法，做出该数据对应的散点图和边际分布图
 
-```{code-cell} ipython3
-fig, ax = plt.subplots()
-ax.arrow(0, 0, 1, 1, head_width=0.03, head_length=0.05, facecolor='red', edgecolor='blue')
-ax.text(x=0, y=0,s='这是一段文字', fontsize=16, rotation=70, rotation_mode='anchor', color='green')
-ax.annotate('这是中点', xy=(0.5, 0.5), xytext=(0.8, 0.2), arrowprops=dict(facecolor='yellow', edgecolor='black'), fontsize=16);
-```
+<img src="https://s1.ax1x.com/2020/11/01/B0pEnS.png" width="400" height="400" align="bottom" />
 
 
 
 
 
 
-
-
-
-
-
-
-```{code-cell} ipython3
-fig, ax = plt.subplots()
-ax.plot([1,2],[2,1],label="line1")
-ax.plot([1,1],[1,2],label="line1")
-ax.legend(loc=1);
-```
-
-
-
-
-
-
-其中，图例的 `loc` 参数如下：
-
-|  string   | code  |
-|  ----  | ----  |
-| best  | 0 |
-| upper right  | 1 |
-| upper left  | 2 |
-| lower left  | 3 |
-| lower right  | 4 |
-| right  | 5 |
-| center left  | 6 |
-| center right  | 7 |
-| lower center  | 8 |
-| upper center  | 9 |
-| center  | 10 |
-
-
-## 参考资料
-
-[1.matplotlib官网布局使用指南](https://matplotlib.org/stable/tutorials/intermediate/gridspec.html#sphx-glr-tutorials-intermediate-gridspec-py)
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@@ -211,7 +211,7 @@
 <li class="toctree-l1"><a class="reference internal" href="%E7%AC%AC%E4%B8%89%E5%9B%9E%EF%BC%9A%E5%B8%83%E5%B1%80%E6%A0%BC%E5%BC%8F%E5%AE%9A%E6%96%B9%E5%9C%86/index.html">第三回：布局格式定方圆</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="%E7%AC%AC%E4%B8%89%E5%9B%9E%EF%BC%9A%E5%B8%83%E5%B1%80%E6%A0%BC%E5%BC%8F%E5%AE%9A%E6%96%B9%E5%9C%86/index.html#id2">一、子图</a></li>
 <li class="toctree-l2"><a class="reference internal" href="%E7%AC%AC%E4%B8%89%E5%9B%9E%EF%BC%9A%E5%B8%83%E5%B1%80%E6%A0%BC%E5%BC%8F%E5%AE%9A%E6%96%B9%E5%9C%86/index.html#id3">二、子图上的方法</a></li>
-<li class="toctree-l2"><a class="reference internal" href="%E7%AC%AC%E4%B8%89%E5%9B%9E%EF%BC%9A%E5%B8%83%E5%B1%80%E6%A0%BC%E5%BC%8F%E5%AE%9A%E6%96%B9%E5%9C%86/index.html#id4">参考资料</a></li>
+<li class="toctree-l2"><a class="reference internal" href="%E7%AC%AC%E4%B8%89%E5%9B%9E%EF%BC%9A%E5%B8%83%E5%B1%80%E6%A0%BC%E5%BC%8F%E5%AE%9A%E6%96%B9%E5%9C%86/index.html#id4">思考题</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="%E7%AC%AC%E5%9B%9B%E5%9B%9E%EF%BC%9A%E6%96%87%E5%AD%97%E5%9B%BE%E4%BE%8B%E5%B0%BD%E7%9C%89%E7%9B%AE/index.html">第四回：文字图例尽眉目</a><ul>
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diff --git a/docs/第三回：布局格式定方圆/index.html b/docs/第三回：布局格式定方圆/index.html
index 2d51a3c..90a3528 100644
--- a/docs/第三回：布局格式定方圆/index.html
+++ b/docs/第三回：布局格式定方圆/index.html
@@ -222,7 +222,7 @@
  </li>
  <li class="toc-h2 nav-item toc-entry">
   <a class="reference internal nav-link" href="#id4">
-   参考资料
+   思考题
   </a>
  </li>
 </ul>
@@ -253,7 +253,7 @@
 <h2>一、子图<a class="headerlink" href="#id2" title="永久链接至标题">¶</a></h2>
 <div class="section" id="plt-subplots">
 <h3>1. 使用 <code class="docutils literal notranslate"><span class="pre">plt.subplots</span></code> 绘制均匀状态下的子图<a class="headerlink" href="#plt-subplots" title="永久链接至标题">¶</a></h3>
-<p>返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列</p>
+<p>返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列，不传入时默认值都为1</p>
 <p><code class="docutils literal notranslate"><span class="pre">figsize</span></code> 参数可以指定整个画布的大小</p>
 <p><code class="docutils literal notranslate"><span class="pre">sharex</span></code> 和 <code class="docutils literal notranslate"><span class="pre">sharey</span></code> 分别表示是否共享横轴和纵轴刻度</p>
 <p><code class="docutils literal notranslate"><span class="pre">tight_layout</span></code> 函数可以调整子图的相对大小使字符不会重叠</p>
@@ -277,6 +277,32 @@
 <img alt="../_images/index_3_0.png" src="../_images/index_3_0.png" />
 </div>
 </div>
+<p>​<br />
+​</p>
+<p><code class="docutils literal notranslate"><span class="pre">subplots</span></code>是基于OO模式的写法，显式创建一个或多个axes对象，然后在对应的子图对象上进行绘图操作。<br />
+还有种方式是使用<code class="docutils literal notranslate"><span class="pre">subplot</span></code>这样基于pyplot模式的写法，每次在指定位置新建一个子图，并且之后的绘图操作都会指向当前子图，本质上<code class="docutils literal notranslate"><span class="pre">subplot</span></code>也是<code class="docutils literal notranslate"><span class="pre">Figure.add_subplot</span></code>的一种封装。</p>
+<p>在调用<code class="docutils literal notranslate"><span class="pre">subplot</span></code>时一般需要传入三位数字，分别代表总行数，总列数，当前子图的index</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">()</span>
+<span class="c1"># 子图1</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span> 
+<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">],</span> <span class="s1">&#39;r&#39;</span><span class="p">)</span>
+<span class="c1"># 子图2</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">2</span><span class="p">)</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">],</span> <span class="s1">&#39;b&#39;</span><span class="p">)</span>
+<span class="c1">#子图3</span>
+<span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="mi">224</span><span class="p">)</span>  <span class="c1"># 当三位数都小于10时，可以省略中间的逗号，这行命令等价于plt.subplot(2,2,4) </span>
+<span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">],</span> <span class="s1">&#39;g&#39;</span><span class="p">);</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<img alt="../_images/index_5_0.png" src="../_images/index_5_0.png" />
+</div>
+</div>
+<p>​</p>
+<p>​</p>
 <p>除了常规的直角坐标系，也可以通过<code class="docutils literal notranslate"><span class="pre">projection</span></code>方法创建极坐标系下的图表</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
@@ -293,9 +319,14 @@
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_5_0.png" src="../_images/index_5_0.png" />
+<img alt="../_images/index_7_0.png" src="../_images/index_7_0.png" />
 </div>
 </div>
+<div class="admonition- admonition">
+<p class="admonition-title">练一练</p>
+<p>请思考如何用极坐标系画出类似的玫瑰图</p>
+<img src="http://www.hinews.cn/news/pic/003/205/569/00320556959_f01764d0.jpg" width="300" align="bottom" />
+</div>
 </div>
 <div class="section" id="gridspec">
 <h3>2. 使用 <code class="docutils literal notranslate"><span class="pre">GridSpec</span></code> 绘制非均匀子图<a class="headerlink" href="#gridspec" title="永久链接至标题">¶</a></h3>
@@ -318,9 +349,11 @@
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_7_0.png" src="../_images/index_7_0.png" />
+<img alt="../_images/index_9_0.png" src="../_images/index_9_0.png" />
 </div>
 </div>
+<p>​</p>
+<p>​</p>
 <p>在上面的例子中出现了 <code class="docutils literal notranslate"><span class="pre">spec[i,</span> <span class="pre">j]</span></code> 的用法，事实上通过切片就可以实现子图的合并而达到跨图的共能</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
@@ -347,36 +380,16 @@
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_9_0.png" src="../_images/index_9_0.png" />
+<img alt="../_images/index_11_0.png" src="../_images/index_11_0.png" />
 </div>
 </div>
+<p>​</p>
+<p>​</p>
 </div>
 </div>
 <div class="section" id="id3">
 <h2>二、子图上的方法<a class="headerlink" href="#id3" title="永久链接至标题">¶</a></h2>
-<p>在 <code class="docutils literal notranslate"><span class="pre">ax</span></code> 对象上定义了和 <code class="docutils literal notranslate"><span class="pre">plt</span></code> 类似的图形绘制函数，常用的有： <code class="docutils literal notranslate"><span class="pre">plot,</span> <span class="pre">hist,</span> <span class="pre">scatter,</span> <span class="pre">bar,</span> <span class="pre">barh,</span> <span class="pre">pie</span></code></p>
-<div class="cell docutils container">
-<div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">],[</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">]);</span>
-</pre></div>
-</div>
-</div>
-<div class="cell_output docutils container">
-<img alt="../_images/index_11_0.png" src="../_images/index_11_0.png" />
-</div>
-</div>
-<div class="cell docutils container">
-<div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">4</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">randn</span><span class="p">(</span><span class="mi">1000</span><span class="p">));</span>
-</pre></div>
-</div>
-</div>
-<div class="cell_output docutils container">
-<img alt="../_images/index_12_0.png" src="../_images/index_12_0.png" />
-</div>
-</div>
+<p>补充介绍一些子图上的方法</p>
 <p>常用直线的画法为： <code class="docutils literal notranslate"><span class="pre">axhline,</span> <span class="pre">axvline,</span> <span class="pre">axline</span></code> （水平、垂直、任意方向）</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
@@ -388,9 +401,11 @@
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_14_0.png" src="../_images/index_14_0.png" />
+<img alt="../_images/index_13_0.png" src="../_images/index_13_0.png" />
 </div>
 </div>
+<p>​</p>
+<p>​</p>
 <p>使用 <code class="docutils literal notranslate"><span class="pre">grid</span></code> 可以加灰色网格</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
@@ -400,106 +415,45 @@
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_16_0.png" src="../_images/index_16_0.png" />
+<img alt="../_images/index_15_0.png" src="../_images/index_15_0.png" />
 </div>
 </div>
-<p>使用 <code class="docutils literal notranslate"><span class="pre">set_xscale,</span> <span class="pre">set_title,</span> <span class="pre">set_xlabel</span></code> 分别可以设置坐标轴的规度（指对数坐标等）、标题、轴名</p>
+<p>​</p>
+<p>​</p>
+<p>使用 <code class="docutils literal notranslate"><span class="pre">set_xscale</span></code> 可以设置坐标轴的规度（指对数坐标等）</p>
 <div class="cell docutils container">
 <div class="cell_input docutils container">
 <div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">axs</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
-<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s1">&#39;大标题&#39;</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="mi">20</span><span class="p">)</span>
 <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">2</span><span class="p">):</span>
     <span class="n">axs</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="s1">&#39;abcd&#39;</span><span class="p">),</span> <span class="p">[</span><span class="mi">10</span><span class="o">**</span><span class="n">i</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">4</span><span class="p">)])</span>
     <span class="k">if</span> <span class="n">j</span><span class="o">==</span><span class="mi">0</span><span class="p">:</span>
         <span class="n">axs</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">set_yscale</span><span class="p">(</span><span class="s1">&#39;log&#39;</span><span class="p">)</span>
-        <span class="n">axs</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;子标题1&#39;</span><span class="p">)</span>
-        <span class="n">axs</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;对数坐标&#39;</span><span class="p">)</span>
     <span class="k">else</span><span class="p">:</span>
-        <span class="n">axs</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;子标题1&#39;</span><span class="p">)</span>
-        <span class="n">axs</span><span class="p">[</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;普通坐标&#39;</span><span class="p">)</span>
+        <span class="k">pass</span>
 <span class="n">fig</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
 </pre></div>
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_18_0.png" src="../_images/index_18_0.png" />
+<img alt="../_images/index_17_0.png" src="../_images/index_17_0.png" />
 </div>
 </div>
-<p>与一般的 <code class="docutils literal notranslate"><span class="pre">plt</span></code> 方法类似， <code class="docutils literal notranslate"><span class="pre">legend,</span> <span class="pre">annotate,</span> <span class="pre">arrow,</span> <span class="pre">text</span></code> 对象也可以进行相应的绘制</p>
-<div class="cell docutils container">
-<div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">arrow</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">head_width</span><span class="o">=</span><span class="mf">0.03</span><span class="p">,</span> <span class="n">head_length</span><span class="o">=</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">facecolor</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s1">&#39;blue&#39;</span><span class="p">)</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">text</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span><span class="n">s</span><span class="o">=</span><span class="s1">&#39;这是一段文字&#39;</span><span class="p">,</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">16</span><span class="p">,</span> <span class="n">rotation</span><span class="o">=</span><span class="mi">70</span><span class="p">,</span> <span class="n">rotation_mode</span><span class="o">=</span><span class="s1">&#39;anchor&#39;</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;green&#39;</span><span class="p">)</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">annotate</span><span class="p">(</span><span class="s1">&#39;这是中点&#39;</span><span class="p">,</span> <span class="n">xy</span><span class="o">=</span><span class="p">(</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">),</span> <span class="n">xytext</span><span class="o">=</span><span class="p">(</span><span class="mf">0.8</span><span class="p">,</span> <span class="mf">0.2</span><span class="p">),</span> <span class="n">arrowprops</span><span class="o">=</span><span class="nb">dict</span><span class="p">(</span><span class="n">facecolor</span><span class="o">=</span><span class="s1">&#39;yellow&#39;</span><span class="p">,</span> <span class="n">edgecolor</span><span class="o">=</span><span class="s1">&#39;black&#39;</span><span class="p">),</span> <span class="n">fontsize</span><span class="o">=</span><span class="mi">16</span><span class="p">);</span>
-</pre></div>
-</div>
-</div>
-<div class="cell_output docutils container">
-<img alt="../_images/index_20_0.png" src="../_images/index_20_0.png" />
-</div>
-</div>
-<div class="cell docutils container">
-<div class="cell_input docutils container">
-<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">()</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">],[</span><span class="mi">2</span><span class="p">,</span><span class="mi">1</span><span class="p">],</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;line1&quot;</span><span class="p">)</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">1</span><span class="p">,</span><span class="mi">1</span><span class="p">],[</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">],</span><span class="n">label</span><span class="o">=</span><span class="s2">&quot;line1&quot;</span><span class="p">)</span>
-<span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">loc</span><span class="o">=</span><span class="mi">1</span><span class="p">);</span>
-</pre></div>
-</div>
-</div>
-<div class="cell_output docutils container">
-<img alt="../_images/index_21_0.png" src="../_images/index_21_0.png" />
-</div>
-</div>
-<p>其中，图例的 <code class="docutils literal notranslate"><span class="pre">loc</span></code> 参数如下：</p>
-<table class="colwidths-auto table">
-<thead>
-<tr class="row-odd"><th class="head"><p>string</p></th>
-<th class="head"><p>code</p></th>
-</tr>
-</thead>
-<tbody>
-<tr class="row-even"><td><p>best</p></td>
-<td><p>0</p></td>
-</tr>
-<tr class="row-odd"><td><p>upper right</p></td>
-<td><p>1</p></td>
-</tr>
-<tr class="row-even"><td><p>upper left</p></td>
-<td><p>2</p></td>
-</tr>
-<tr class="row-odd"><td><p>lower left</p></td>
-<td><p>3</p></td>
-</tr>
-<tr class="row-even"><td><p>lower right</p></td>
-<td><p>4</p></td>
-</tr>
-<tr class="row-odd"><td><p>right</p></td>
-<td><p>5</p></td>
-</tr>
-<tr class="row-even"><td><p>center left</p></td>
-<td><p>6</p></td>
-</tr>
-<tr class="row-odd"><td><p>center right</p></td>
-<td><p>7</p></td>
-</tr>
-<tr class="row-even"><td><p>lower center</p></td>
-<td><p>8</p></td>
-</tr>
-<tr class="row-odd"><td><p>upper center</p></td>
-<td><p>9</p></td>
-</tr>
-<tr class="row-even"><td><p>center</p></td>
-<td><p>10</p></td>
-</tr>
-</tbody>
-</table>
+<p>​</p>
+<p>​</p>
 </div>
 <div class="section" id="id4">
-<h2>参考资料<a class="headerlink" href="#id4" title="永久链接至标题">¶</a></h2>
-<p><a class="reference external" href="https://matplotlib.org/stable/tutorials/intermediate/gridspec.html#sphx-glr-tutorials-intermediate-gridspec-py">1.matplotlib官网布局使用指南</a></p>
-</div>
+<h2>思考题<a class="headerlink" href="#id4" title="永久链接至标题">¶</a></h2>
+<ul class="simple">
+<li><p>墨尔本1981年至1990年的每月温度情况</p></li>
+</ul>
+<p>数据集来自github仓库下data/layout_ex1.csv<br />
+请利用数据，画出如下的图：</p>
+<img src="https://s1.ax1x.com/2020/11/01/BwvCse.png" width="800" align="bottom" />
+<ul class="simple">
+<li><p>画出数据的散点图和边际分布</p></li>
+</ul>
+<p>用 <code class="docutils literal notranslate"><span class="pre">np.random.randn(2,</span> <span class="pre">150)</span></code> 生成一组二维数据，使用两种非均匀子图的分割方法，做出该数据对应的散点图和边际分布图</p>
+<img src="https://s1.ax1x.com/2020/11/01/B0pEnS.png" width="400" height="400" align="bottom" /></div>
 </div>
 
 
diff --git a/docs/第二回：艺术画笔见乾坤/index.html b/docs/第二回：艺术画笔见乾坤/index.html
index 21fbe29..39237e6 100644
--- a/docs/第二回：艺术画笔见乾坤/index.html
+++ b/docs/第二回：艺术画笔见乾坤/index.html
@@ -574,7 +574,7 @@ Rectangle本身的主要比较简单，即xy控制锚点，width和height分别
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_12_01.png" src="../_images/index_12_01.png" />
+<img alt="../_images/index_12_0.png" src="../_images/index_12_0.png" />
 </div>
 </div>
 <p><code class="docutils literal notranslate"><span class="pre">Rectangle</span></code>矩形类绘制直方图</p>
@@ -610,7 +610,7 @@ Rectangle本身的主要比较简单，即xy控制锚点，width和height分别
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_14_01.png" src="../_images/index_14_01.png" />
+<img alt="../_images/index_14_0.png" src="../_images/index_14_0.png" />
 </div>
 </div>
 <p><strong>2) bar-柱状图</strong></p>
@@ -642,7 +642,7 @@ Rectangle本身的主要比较简单，即xy控制锚点，width和height分别
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_16_01.png" src="../_images/index_16_01.png" />
+<img alt="../_images/index_16_0.png" src="../_images/index_16_0.png" />
 </div>
 </div>
 <div class="cell docutils container">
@@ -662,7 +662,7 @@ Rectangle本身的主要比较简单，即xy控制锚点，width和height分别
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_17_0.png" src="../_images/index_17_0.png" />
+<img alt="../_images/index_17_01.png" src="../_images/index_17_01.png" />
 </div>
 </div>
 </div>
@@ -731,7 +731,7 @@ closed为True则指定多边形将起点和终点重合从而显式关闭多边
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_21_01.png" src="../_images/index_21_01.png" />
+<img alt="../_images/index_21_0.png" src="../_images/index_21_0.png" />
 </div>
 </div>
 <p>wedge绘制饼图</p>
diff --git a/docs/第五回：样式色彩秀芳华/index.html b/docs/第五回：样式色彩秀芳华/index.html
index 497c45f..7679d63 100644
--- a/docs/第五回：样式色彩秀芳华/index.html
+++ b/docs/第五回：样式色彩秀芳华/index.html
@@ -377,7 +377,7 @@ ytick.labelsize : 16</p>
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_12_02.png" src="../_images/index_12_02.png" />
+<img alt="../_images/index_12_01.png" src="../_images/index_12_01.png" />
 </div>
 </div>
 <p>另外matplotlib也还提供了了一种更便捷的修改样式方式，可以一次性修改多个样式。</p>
@@ -389,7 +389,7 @@ ytick.labelsize : 16</p>
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_14_02.png" src="../_images/index_14_02.png" />
+<img alt="../_images/index_14_01.png" src="../_images/index_14_01.png" />
 </div>
 </div>
 </div>
@@ -422,7 +422,7 @@ ytick.labelsize : 16</p>
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_17_01.png" src="../_images/index_17_01.png" />
+<img alt="../_images/index_17_02.png" src="../_images/index_17_02.png" />
 </div>
 </div>
 </div>
@@ -453,7 +453,7 @@ ytick.labelsize : 16</p>
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_21_02.png" src="../_images/index_21_02.png" />
+<img alt="../_images/index_21_01.png" src="../_images/index_21_01.png" />
 </div>
 </div>
 </div>
diff --git a/docs/第四回：文字图例尽眉目/index.html b/docs/第四回：文字图例尽眉目/index.html
index 9db30a4..9f9fc56 100644
--- a/docs/第四回：文字图例尽眉目/index.html
+++ b/docs/第四回：文字图例尽眉目/index.html
@@ -557,7 +557,7 @@ annotate的参数非常复杂，这里仅仅展示一个简单的例子，更多
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_14_03.png" src="../_images/index_14_03.png" />
+<img alt="../_images/index_14_02.png" src="../_images/index_14_02.png" />
 </div>
 </div>
 <p>​</p>
@@ -589,7 +589,7 @@ annotate的参数非常复杂，这里仅仅展示一个简单的例子，更多
 </div>
 </div>
 <div class="cell_output docutils container">
-<img alt="../_images/index_17_02.png" src="../_images/index_17_02.png" />
+<img alt="../_images/index_17_03.png" src="../_images/index_17_03.png" />
 </div>
 </div>
 <p>​</p>
diff --git a/fantastic-matplotlib.pdf b/fantastic-matplotlib.pdf
deleted file mode 100644
index b14d7fd..0000000
Binary files a/fantastic-matplotlib.pdf and /dev/null differ
diff --git a/notebook/.ipynb_checkpoints/第三回：布局格式定方圆-checkpoint.ipynb b/notebook/.ipynb_checkpoints/第三回：布局格式定方圆-checkpoint.ipynb
new file mode 100644
index 0000000..0ed9fd8
--- /dev/null
+++ b/notebook/.ipynb_checkpoints/第三回：布局格式定方圆-checkpoint.ipynb
@@ -0,0 +1,572 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 第三回：布局格式定方圆"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:25.798702Z",
+     "start_time": "2020-11-01T10:58:25.319113Z"
+    }
+   },
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "plt.rcParams['font.sans-serif'] = ['SimHei']   #用来正常显示中文标签\n",
+    "plt.rcParams['axes.unicode_minus'] = False   #用来正常显示负号"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 一、子图\n",
+    "\n",
+    "### 1. 使用 `plt.subplots` 绘制均匀状态下的子图\n",
+    "\n",
+    "返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列，不传入时默认值都为1\n",
+    "\n",
+    "`figsize` 参数可以指定整个画布的大小\n",
+    "\n",
+    "`sharex` 和 `sharey` 分别表示是否共享横轴和纵轴刻度\n",
+    "\n",
+    "`tight_layout` 函数可以调整子图的相对大小使字符不会重叠"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:26.423289Z",
+     "start_time": "2020-11-01T10:58:25.798702Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x288 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axs = plt.subplots(2, 5, figsize=(10, 4), sharex=True, sharey=True)\n",
+    "fig.suptitle('样例1', size=20)\n",
+    "for i in range(2):\n",
+    "    for j in range(5):\n",
+    "        axs[i][j].scatter(np.random.randn(10), np.random.randn(10))\n",
+    "        axs[i][j].set_title('第%d行，第%d列'%(i+1,j+1))\n",
+    "        axs[i][j].set_xlim(-5,5)\n",
+    "        axs[i][j].set_ylim(-5,5)\n",
+    "        if i==1: axs[i][j].set_xlabel('横坐标')\n",
+    "        if j==0: axs[i][j].set_ylabel('纵坐标')\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`subplots`是基于OO模式的写法，显式创建一个或多个axes对象，然后在对应的子图对象上进行绘图操作。  \n",
+    "还有种方式是使用`subplot`这样基于pyplot模式的写法，每次在指定位置新建一个子图，并且之后的绘图操作都会指向当前子图，本质上`subplot`也是`Figure.add_subplot`的一种封装。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "在调用`subplot`时一般需要传入三位数字，分别代表总行数，总列数，当前子图的index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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THX88fPmlv+pl6lT/dCORBLZmDVx2mW/cdfjhMHu2f166mnYJJPMa+9Kl/rKAmTN9Q4xhw+CII4JOJRIW5/zNRd27+8sZ+/Xz7/XhU/aUfDP23Fw/dWnUyF/r9cYb/qlGKuqS4H78Ec49988VxQUL4J57VNRlX8k1JObM8aN+4UK48krf3egvfwk6lUhY8vJgyBDfvqhMGb+i2LGj+rtI0ZJjaGzf7k+GnnYa5OT4SxnfeUdFXRLe0qX+mvQ774QWLXzTrttuU1GX4iX+8Pj8c9/ZqH9/f4vdkiXQrl3QqUTCkpvrr0PXiqKURuIW9s2bfRPpFi1g1y6YNAleegkOPjjoZCJhmTMH0tOhd2+45BI/a7/2WjXtktAlZmEfN84/d3TYMN/rZdEiOPvsoFOJhGX3imLjxn5F8aOP4O23taIo+y+xCvv69X7qcsEFcNBBMGMGPPUUVK4cdDKRsBS2ovjPfwadShJVYhR25/zJ0LQ0/+eDD8LcudCkSdDJRMJS2Iriiy9qRVHCE/+XO65e7S8DGD3aLzxOmgQnnBB0KpGwjRsHt94Kq1b5FcXHHtOHT4mM+J2xO+dPhqal+d6jTz7p7yJVUZcEt349XHedX1GsWlUrihJ58VnYf/gBWreGW27x13stWgR33aVb7CShOQfvvuvnKm+/rRVFiZ6QCruZ1TazacV8v5yZjTWzGWZ2c6nT5OXB00/7pl2zZ8MLL8CUKfD3v5d6lyLFidXYXr3aX7rYvr1/gPTcufDII1ChQmn3KFK0Egu7mVUHXgOK+6B4O5DtnGsGXGhmVUuV5pprfEejVq38ZQGZmbrFTqImVmN79Wo/S8/KggED/Ipiw4alDC0SglCqZh7QHthczDYtgXcL3s8A0vfewMwyzSzbzLJzcnIK30vHjvDWWzBmjO9FKhJdMRnbdev6Pi+LFkGPHlpRlOgrcYg55zYDWPG3vVUGfi54vxmoXch+hgPDAdLT012heznrrJLiiERMLMf2vfeGk1Rk/0RqnWMrULHgfZUI7lckaBrbknAiNUjnAGcUvD8RWB6h/YoETWNbEo45V/iqyD4bmk11zrU0s1ZAmnNu8B7fqweMAyYBzYAmzrm8YvaVA/xUxLdrAutDzB9t8ZIlXnJA/GQpLkc951ytUHeUgmM7XnJA/GSJlxwQgbEdcmEvcUdmdfEzmyzn3KYw9pPtnNvnBFUQ4iVLvOSA+MkSyxzJNrbjJQfET5Z4yQGRyRKx8/POudX8efWASNLQ2JZEoxNBIiJJJh4L+/CgA+whXrLESw6InyzxkmN/xEvmeMkB8ZMlXnJABLJEbI1dRETiQzzO2EVEJAwq7CIiSUaFXUQkycS0sJvZiIL2p733Z5tQfi7SWcysmpmNN7OJZvahmZU3swPMbIWZTS14RaRHXwhZCj2umT1iZrPNbHBhPxeFHLftkWG+mb0Qxd/JfrfTjVj76FLQ2C5VjpiM6xCzJNXYjllhN7NLgbIF7U/rmtnRoWwTys9FIwtwDfCUc64NsBZoC5wA/Mc517LgtShGWfY5rpml42+aOQ1YZWato53DOTd0dwZgGv7sfTR+J6VtpxuZ9tH7SWO71DmiPq5DzZJsYzuWM/aW/HmTxxT+7L9R0jah/FzEszjnnnfOTSz4x1rAOqAJcImZfWFmb5lZJG7wKjFLEcc9E3jf+cuaJgHNY5ADADM7DKjtnJtTRLZwlbadbmFfi4U9j6uxHWKOIo4Z6XEdahYgecZ2LAt7ie1Pi9gmlJ+LRhYAzKwpUN059yUwG2jhnDsD+A04P0ZZCjtupH8v+7O/zsDQYrKFxTm3OYRb92M1VkKhsV26HLEY16Fm2S0pxnYsC3so7U8L2yYabVND2qeZ1QAGAbvXtBY659YUvP8GCPujc4hZCjtupH8vof5OygBnOec+LSZbLMRqrJQ2SyjbJPPYjpdxHWqWpBrbsSzsobQ/LWybaLRNLXGfZlYe/9Hnfufc7m59b5jZiWZWFrgEWBCLLEUcN9K/l1D31xz4qoRssRCrsVLaLKFsk8xjO17GdahZIJnGtnMuJi/gIPwv5ilgaUG4PiVsU62wr8Uoy23ARmBqwas9cDywEFgE9I3h72Wf4+L/pzwdeBZYBhwZ7RwF2/0LuLS4bBEcM1ML/mwFdNnre/WAxQX//rOBsoV9TWM7mLEdL+M6Vcd2TFsKFJwRbgN87pxbG+o2ofxcNLLESmmzmFlF4AJgrnPuh6ByBMUKaadb2NdilEVjO0I5Ij2uw8kSlHDHtnrFiIgkGd15KiKSZFTYRUSSTMSeoCQiULNmTVe/fv2gY0iSmjNnznoXwjNPVdhFIqh+/fpkZ2cHHUOSlJkV9aD0/6GlGElJVkgjrCK2i3iTLpFoU2GXVFVYI6z/EY0mXSLFWbFpBVN+nBL2flTYJSW5whth7a0lITSPMrNMM8s2s+ycnJyIZ5Xkl+/yeX728xz3/HHcNOomcvNyw9qfCruktL0aYe0tpMZLzrnhzrl051x6rVolntcS+R/f/votLV9tSedxnWl6eFM+u/EzypUtF9Y+dfJUUtYejbAuK2KToJqKSQrYlb+LgTMG8tDUh6hYriKv/PMVbjjxBsws7H2rsEtKKqIR1t52N176Et9fZFmM4kmSm792PhmjM5i7Zi6XNriUIecPoU6VOhHbvwq7pKoM4BSgl5n1Aj4Fyjnn9rz65SNgWkGPjvPwD14QKbUdu3bw2GeP0W96P2pWqsnIK0ZyWVpRHxhLT4VdUpJzbih/PlChqG02m1lLfPOo/rFsKibJZ8bKGWSMzuCb9d9ww4k38NS5T1GjYo2oHEuFXaQYzrmN/HlljMh+2/rHVnpO7sngWYP5a7W/8sk1n3Du38+N6jFV2EVEomTCfyeQOSaTFZtW0OW0LvRt1ZeqFaL/jHUVdhGRCNu4fSPdJ3Tn1fmvcswhxzDtpmmcfsTpMTu+CruISAR9sPQDOo/rTM7vOfQ8oycPtHiAAw84MKYZVNhFRCJg7da1dBnXhfeXvs9JdU5i/DXjaVSnUSBZVNhFRMLgnOO1Ba/RPas723K38fjZj9OjaY+w7x4Nhwq7iEgpLf9tOR3HdmTCfydwxhFn8NJFL3FMzWOCjqXCLiKyv/JdPkNmDeH+yfdjZgw5fwi3pt9KGYuPrhMq7CIi++Gb9d/QYXQHpq+cTtu/t2XYBcOod3C9oGP9DxV2EZEQ5Obl8uSMJ3nks0eoUr4Kr7d7nWtPuDYiTbsiTYVdRKQEc9fMJWN0BvPXzueKtCsYdN4galcptItzXFBhFxEpwvbc7Tz62aM8OeNJalWuxQdXfsAlDS4JOlaJVNhFRArxxYovyBidwbe/fsvNjW5mwDkDqF6xetCxQqLCLiKyhy07t3D/5PsZMnsI9Q+uz8TrJtL6qNZBx9ovKuwiIgXGfzeejmM7smrzKro27kqfVn2oXL5y0LH2mwq7iKS8X7f9Sresbryx8A0a1GzA9Jun0/SvTYOOVWoq7CKSspxzjFwyki7ju7Bh+wYeOPMBejXvRYUDKgQdLSwq7CKSktZsWUOncZ346JuPOOXQU5hw7QROrHNi0LEiQoVdRFKKc45X5r9C96zu7MzbSf/W/enWtBsHlEmecpg8/yYiIiX4ceOPZI7NZNIPkziz3pm8dNFLHH3I0UHHijgVdhFJenn5eQyeNZieU3pS1soy9IKhZJ6SGTdNuyJNhV1EktqSnCVkjM7gy1Vfcv7R5zPsgmH8tdpfg44VVSrsIpKU/sj7g35f9KPPtD5ULV+VNy95k6sbXh2XTbsiTYVdRJJO9upsMkZnsPCXhVx1/FU82/ZZ/lL5L0HHihkVdhFJGttzt/PQ1IcYOHMgdarUYdRVo7j4mIuDjhVzKuwikhQ+W/4ZHcZ04PsN33PLybfwZJsnqXZgtaBjBUKFXUQS2uadm7l34r0MmzOMo6ofxeTrJ9PqyFZBxwqUCruIJKyPv/2YWz++ldVbVtO9SXcea/UYlcpVCjpW4FTYRSThrN+2nq6fdOWtRW9xXK3jGHnFSBof3jjoWHFDhV1EEoZzjncWv8Pt429n045NPNTiIXo270n5suWDjhZXVNhFJCH8vPlnOo3rxOhlozm17qmMuHgEDWs3DDpWXFJhF5G45pzjpbkvcdfEu8jNy2XgOQO5s/GdlC1TNuhocUuFXUTi1n83/JdbxtzCp8s/5az6Z/HiRS/ytxp/CzpW3FNhF5G4k5efx7NfPUvvKb0pV7Ycwy8cToeTO6REO4BIUGEXkbjy9bqvyRidwayfZ3HRPy5i6AVDOeygw4KOlVBU2EUkLvyR9wePT3ucvtP6Uu3Aavznsv/Q/rj2mqWXggq7iARu1s+zyBidwdfrvuaahtfwTNtnqFmpZtCxElZydpkXCZGZ1TazacV8/zAzW2VmUwtetWKZL9lty91Gj6weNB3RlN92/MbY/zeWNy99U0U9TJqxS8oys+rAa0DlYjZrDPR1zg2NTarU8emPn9JhTAd+2PgDt55yK/3a9OOgCgcFHSspaMYuqSwPaA9sLmabJkAnM5tpZk8XtoGZZZpZtpll5+TkRCNnUtm0YxOZYzJp9XorylgZpt4wlaEXDlVRjyAVdklZzrnNzrlNJWw2HmjmnGsK/MPMTihkP8Odc+nOufRatbRSU5wxy8aQ9nwaI+aN4O5md7Pg1gW0qN8i6FhJR0sxIsWb4ZzbWfD+G+BoYGGAeRJSzu853PHJHbz99ds0/EtDRl01ivS66UHHSlqasYsUL8vMDjWzSsC5wNdBB0okzjn+vejfNBjSgPeXvM+jLR8lOzNbRT3KNGMXKWBmrYA059zgPb78CPAp8AcwzDm3LJBwCWjlppXc9vFtfPzdxzQ5vAkjLh5BWq20oGOlBBV2SXnOuZYFf04Bpuz1vU+BYwOIlbDyXT7D5wznnon3kOfyeObcZ+hyWhc17YohFXYRiZjvfv2OW8bcwmc/fcbZR57N8IuGc1T1o4KOlXJU2EUkbLvyd/H0zKd5cOqDVChbgREXj+CmRjepHUBAVNhFJCwLf1lIxugMsldn0+7Ydgw5fwh1q9YNOlZKU2EXkVLZuWsnfaf15fEvHqdGxRq8e/m7XJ52uWbpcUCFXUT228yVM8kYncHS9Uu5/sTreeqcpzik0iFBx5ICKuwiErLf//idXlN68dxXz3H4QYcz7upxnHf0eUHHkr2osItISCb9MIlbxtzC8t+W0/nUzjx+9uNUrVA16FhSCBV2ESnWbzt+o0dWD16e/zJH1ziaz2/8nOb1mgcdS4qhwi4iRfrom4/o9HEn1v2+jvtOv48HWzxIxXIVg44lJVBhF5F9/LL1F24ffzvvLXmPRnUaMfbqsZx86MlBx5IQqbCLyP9xzvHGwjfo+klXfs/9nb6t+nJ3s7spV7Zc0NFkP6iwiwgAKzatoOPYjnzy/Sc0+2szRlw8gmNrqk1OIlJhF0lx+S6fobOHct/k+3DO8Vzb5+h8WmfKmLp6JyoVdpEUtmz9MjqM6cAXK76gzVFtGH7RcOofXD/oWBImFXaRFLQrfxcDZgzg4akPU6lcJV7956tcf+L1ageQJFTYRVLM/LXzyRidwdw1c7mswWUMPn8wdarUCTqWRJAKu0iK2LFrB4999hj9pvejZqWajLxiJJelXRZ0LIkCFXaRFDB9xXQyRmew7Ndl3NjoRgaeM5AaFWsEHUuiRIVdJIlt/WMrPSf3ZPCswRxR7Qiyrs3inL+dE3QsiTIVdpEkNeG/E8gck8mKTSu4/bTb6Xt2X6qUrxJ0LIkBFXaRJLNh+wZ6TOjBq/Nf5diaxzLtpmmcfsTpQceSGFJhF0ki7y95n87jOrN+23p6Ne9F7zN7c+ABBwYdS2JMhV0kCazZsoYu47vwwdIPOKnOSXxy7Sc0qtMo6FgSEBV2kQTmnOO1Ba/RLasb23O388TZT9CjWQ8OKKO/2qlM//VFEtTy35aTOSaTiT9M5IwjzuCli17imJrHBB1L4oAKu0iCyXf5DJk1hPsn34+ZMeT8Idyafquadsn/UWEXSSBLc5bSYUwHZqycQdu/t+WFC1/giGpHBB1L4owKu0gCyM3Lpf/0/jz6+aNUKV+F19u9zrUnXKumXVIoFXaRODd3zVxuHnUzC35ZwJXHXclzbZ+jdpXaQceSOKbCLhKntudu55HPHmHAjAHUqlyLD9t/SLtj2wUdSxKACrtIHJr20zQ6jOnAt79+S8ZJGTzZ5kmqV6wedCxJECrsInFky84t3DfpPp7Pfp4jDz6SiddNpPVRrYOOJQlGhV0kToz/bjwdx3Zk1eZVdG3clT6t+lC5fOWgY0kCUmEXCdiv236lW1Y33lj4Bmm10piRMYMmhzcJOpYkMBV2kYA453hvyXt0GdeFjTs28sCZD9CreS8qHFAh6GiS4FTYRQKwestqOo/rzEfffMQph57CpOsncULtE4KOJUlChV0khpxzvDzvZXpM6MHOvJ30b92fbk27qWmXRJRGk6Q0M6sNjHTONS/i++WAD4EawEvOuZdLe6wfNv5A5phMJv84mRb1WvDiRS9y9CFHl3Z3IkVS1yBJWWZWHXgNKO7Sk9uBbOdcM+BCM6u6v8fJy8/jmS+foeHQhsz6eRbDLhjGlBumqKhL1KiwSyrLA9oDm4vZpiXwbsH7GUD63huYWaaZZZtZdk5Ozj47yNmWw8NTH+as+mexpPMSOqZ3VCdGiSotxUjKcs5tBkpqpFUZ+Lng/WZgnyYtzrnhwHCA9PR0t/f361Spw7yO86h/cH017ZKY0LRBpHhbgYoF76tQyr8zR1Y/UkVdYkaFXaR4c4AzCt6fCCwPLopIaLQUI1LAzFoBac65wXt8+TVgnJk1B9KArwIJJ7IfzLl9lgRFZA9mVhc/a89yzm0qYdsc4Kcivl0TWB/heKURLzkgfrLESw4oPks951ytknagwi4SI2aW7Zzb56qaVM0B8ZMlXnJAZLJojV1EJMmosIuIJBkVdpHYGR50gALxkgPiJ0u85IAIZNEau4hIktGMXUQkyaiwi4gkGRV2kQgwsxFmNsPMeu/PNqH8XKSzmFk1MxtvZhPN7EMzK29mB5jZCjObWvBqGIMchR7TzB4xs9lmNriwn4tSltv2yDHfzF6Ixu+k4Fi1zWxaMd8vZ2ZjC/LeXNTXiqPCLhImM7sUKFvQ2reume3Tj7ewbUL5uWhkAa4BnnLOtQHWAm2BE4D/OOdaFrwWxSDHPsc0s3T8zWCnAavMrHU4OULN4pwbujsHMA1/AjOiv5OCLKVtFb1f7aNV2EXC15I/W/tO4c/eMiVtE8rPRTyLc+5559zEgn+sBawDmgCXmNkXZvaWmYXbbqTEHEUc80zgfeev6pgEFPoAlChkAcDMDgNqO+fmFJEvXKVtFV3Y14qkwi4SvhJb+xaxTSg/F40sAJhZU6C6c+5LYDbQwjl3BvAbcH4MchR2zEB/J0BnYGgx+cLinNtcUlsKIjBWVNhFwhdKa9/CtolIS+BSZMHMagCDgN3rtQudc2sK3n8DhLssFEqOwo4Z5O+kDHCWc+7TYvLFQthjRYVdJHyhtPYtbJtotAQucZ9mVh7/sf5+59zuhmVvmNmJZlYWuARYEO0cRRwzkN9Jgeb8b/fOSP9OQhX+WHHO6aWXXmG8gIPwf+mfApYW/MXrU8I21Qr7Woyy3AZsBKYWvNoDxwMLgUVA3xjl2OeY+MnmdOBZYBlwZCyyFGz3L+DS4vJFcMxMLfizFdBlr+/VAxYX/A5mA2UL+1px+9edpyIRUHC1Qxvgc+fc2lC3CeXnopElFkqbw8wqAhcAc51zPwSZJSiFtYrer/bRKuwiIslFa+wiIklGhV1EJMmosIuIJBkVdhGRJKPCLiKSZP4/sGa13b9k/O0AAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 432x288 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure()\n",
+    "# 子图1\n",
+    "plt.subplot(2,2,1) \n",
+    "plt.plot([1,2], 'r')\n",
+    "# 子图2\n",
+    "plt.subplot(2,2,2)\n",
+    "plt.plot([1,2], 'b')\n",
+    "#子图3\n",
+    "plt.subplot(224)  # 当三位数都小于10时，可以省略中间的逗号，这行命令等价于plt.subplot(2,2,4) \n",
+    "plt.plot([1,2], 'g');"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "除了常规的直角坐标系，也可以通过`projection`方法创建极坐标系下的图表"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "N = 150\n",
+    "r = 2 * np.random.rand(N)\n",
+    "theta = 2 * np.pi * np.random.rand(N)\n",
+    "area = 200 * r**2\n",
+    "colors = theta\n",
+    "\n",
+    "\n",
+    "plt.subplot(projection='polar')\n",
+    "plt.scatter(theta, r, c=colors, s=area, cmap='hsv', alpha=0.75);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "> 练一练  \n",
+    "\n",
+    "请思考如何用极坐标系画出类似的玫瑰图\n",
+    "<img src=\"http://www.hinews.cn/news/pic/003/205/569/00320556959_f01764d0.jpg\" width=\"300\" align=\"bottom\" />\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2. 使用 `GridSpec` 绘制非均匀子图\n",
+    "\n",
+    "所谓非均匀包含两层含义，第一是指图的比例大小不同但没有跨行或跨列，第二是指图为跨列或跨行状态\n",
+    "\n",
+    "利用 `add_gridspec` 可以指定相对宽度比例 `width_ratios` 和相对高度比例参数 `height_ratios`"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:27.018425Z",
+     "start_time": "2020-11-01T10:58:26.425522Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x288 with 10 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 4))\n",
+    "spec = fig.add_gridspec(nrows=2, ncols=5, width_ratios=[1,2,3,4,5], height_ratios=[1,3])\n",
+    "fig.suptitle('样例2', size=20)\n",
+    "for i in range(2):\n",
+    "    for j in range(5):\n",
+    "        ax = fig.add_subplot(spec[i, j])\n",
+    "        ax.scatter(np.random.randn(10), np.random.randn(10))\n",
+    "        ax.set_title('第%d行，第%d列'%(i+1,j+1))\n",
+    "        if i==1: ax.set_xlabel('横坐标')\n",
+    "        if j==0: ax.set_ylabel('纵坐标')\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "在上面的例子中出现了 `spec[i, j]` 的用法，事实上通过切片就可以实现子图的合并而达到跨图的共能"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:27.397245Z",
+     "start_time": "2020-11-01T10:58:27.020418Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 720x288 with 5 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig = plt.figure(figsize=(10, 4))\n",
+    "spec = fig.add_gridspec(nrows=2, ncols=6, width_ratios=[2,2.5,3,1,1.5,2], height_ratios=[1,2])\n",
+    "fig.suptitle('样例3', size=20)\n",
+    "# sub1\n",
+    "ax = fig.add_subplot(spec[0, :3])\n",
+    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
+    "# sub2\n",
+    "ax = fig.add_subplot(spec[0, 3:5])\n",
+    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
+    "# sub3\n",
+    "ax = fig.add_subplot(spec[:, 5])\n",
+    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
+    "# sub4\n",
+    "ax = fig.add_subplot(spec[1, 0])\n",
+    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
+    "# sub5\n",
+    "ax = fig.add_subplot(spec[1, 1:5])\n",
+    "ax.scatter(np.random.randn(10), np.random.randn(10))\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 二、子图上的方法\n",
+    "\n",
+    "补充介绍一些子图上的方法"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T09:23:21.140175Z",
+     "start_time": "2020-11-01T09:23:21.137223Z"
+    }
+   },
+   "source": [
+    "常用直线的画法为： `axhline, axvline, axline` （水平、垂直、任意方向）"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:27.686055Z",
+     "start_time": "2020-11-01T10:58:27.583390Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 288x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(4,3))\n",
+    "ax.axhline(0.5,0.2,0.8)\n",
+    "ax.axvline(0.5,0.2,0.8)\n",
+    "ax.axline([0.3,0.3],[0.7,0.7]);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "使用 `grid` 可以加灰色网格"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:27.774748Z",
+     "start_time": "2020-11-01T10:58:27.688043Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": "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\n",
+      "text/plain": [
+       "<Figure size 288x216 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(4,3))\n",
+    "ax.grid(True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T09:35:34.166136Z",
+     "start_time": "2020-11-01T09:35:34.161109Z"
+    }
+   },
+   "source": [
+    "使用 `set_xscale` 可以设置坐标轴的规度（指对数坐标等）"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:28.239217Z",
+     "start_time": "2020-11-01T10:58:27.775747Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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8vJu7n33FJ/jD9X2djnLBVJBFBIB/bjjIT15bS7OwEObcPYQRXds4HUlERPyM2103Ra9nuxaM6+G/u3SqIIsEOZfb8pePt/LMojzSk+OYcccgkuKizv2JIiIip/n35kNsP1zOE7cO8Ot3IFWQRYJY0fFqHpqfw5LtR7htSAq//U5vmoWFOh1LRET8kLWWZxblkRwfxTX92jsd56KoIIsEqQ37Spg2J5vCsir+PLEftw5JcTqSiIj4sS92FZFbUMzvr+9LWKhXF0rzOBVkkSD02uoCHn57A21iIngtczjpyXFORxIRET83Y1EebZpHcPPgjk5HuWgqyCJBpLrWze/e20jWyj2M6Nqap24bSOvmzZyOJSIifm7DvhIWbyvkp1f1IDLc/6fqqSCLBImDJZVMn5tNzp5ipo3pwk+v6uH3b4GJiIhvmLk4jxbNwpgyvJPTUTxCBVkkCHyx8yg/eGUNFdUunr59ENf09++bJ0RExHfkHznOB+sPMHVMV1pGhjsdxyNUkEUCmLWWF5bl88cPNtMpPpp59w6jW2ILp2OJiEgAmbVkJ2GhIdw1MtXpKB6jgiwSoCqqa/nFG+t5d+1+ruydyOO3pAfMb/YiIuIbDpdW8vrqvdyU0ZG2LSOdjuMxKsgiASj/yHEys7LZeqiMn17Vg+ljuxIS4r8LtouIiG+avWwXtW4308Z0cTqKR6kgiwSYT7cc4qH5uYSGGF7+/hDGdPffrT5FRMR3lZyoYe7KPVzTP4lOrWOcjuNRKsgiAcLttjz56Xb+9u/t9ElqyczJg0mOj3Y6loiIBKislbspr6olc2xgXT0GFWSRgFBSUcN/Lcjl0y2HuXFQRx69oW9ArEMpIiK+qbLGxQtLdzG2ewJ9kmKdjuNxKsgifm7zgVIys7LZX3yC31/fl8lDUzBG841FRKTpvLa6gKPHq7lvXFenozQJFWQRP/ZO7j5+/sY6WkaGM3/qMAZ3inc6koiIBLhal5tnP9/JoJQ4hnQOzJ87KsgifqjG5eaPH2zmxWX5DEmN5+93DKRti8BZXkdERHzXe+sOsPfYCX4zoU/AvmPpsYJsjLkbiAHSrLUPeup1ReTrDpdVcv/cHFblF/H9kan86tu9CNeW0SIi4gXWWmYsyqNb2+Zc1rOt03GaTKN+qhpjEo0xS04bm22MWW6MeaR+aI619kmguadDikid7N3HmPDUUtbtK+aJWwfwmwl9VI5FRMRrPtt6mK2Hypg+LrDX1z/nT1ZjTCvgZequDn81NhEItdaOAJKMMd2stdXGmB8CT5/ldaYaY1YbY1YXFhZ6Jr1IkLDWMmflbm6dtYJmYaG8dd9IrhvQwelYIiISZJ75LI8OcVFMSE9yOkqTasylJxcwCShtMDYOWFD/+FNglDHmQWAkcKkx5huLr1prZ1lrM6y1GQkJ2rhApLEqa1z85LV1/PrtDYxKa8PC+0fRq31Lp2OJiEiQ+TK/iNW7j3Hv6M4B/+7lOecgW2tLgdMnYccA++ofl1I37/jPwJOeDigSzAqKKsjMymbj/lIeuqwbD13WLaDf0hIREd81Y1Ee8TERTLokxekoTe5Cb9IrB6LqHzen8XOZJwAT0tLSLvCwIsHj822FPDg/B5fbMvt7GVzWK9HpSCIiEqQ2Hyjl0y2H+fEV3YmKCPyNqC70+ng2MKr+cTqQ35hPstYutNZOjY0NvB1XRDzFWsvTn+3gey+uIrFFJAvvH6VyLCIijpq5OI+YiFC+OzzV6ShecaFXkN8GlhhjkoDxwDCPJRIJYmWVNfx4wVo+3nSI76Qn8ecb+xEdoeXKRUTEOXuOVrBw7X7uHtWZ2Ohwp+N4RaN/8lprxzV4XGqMGQdcATxmrS3xeDKRILP9UBnTsrLZfbSCX1/bm7tGpgbsAuwiIuI/nluyk7CQEO4Z3cXpKF5zwZemrLXHOLWSRaNoDrLImX24/gA/eW0tURGhzL1nKMO6tHY6koiICIVlVSxYXcDEQR1IbBk8O7Z6dY0OzUEW+bpal5s/fbiZ6XPX0L1dC957YLTKsYiI+IwXl+2i2uVm6pjguXoMHtxqWkTOz9HyKh6cn8OyHUeZPCyFX1/bm2ZhgX9nsIiI+IfSyhrmrNjN+L7t6JIQXBslqyCLOGDd3mIy52Rz5Hg1/3dTf27OSHY6koiIyNe88sUeyqpqmT42+KbGqiCLeNmCLwt45J0NJDRvxhuZI+jXUVOORETEt1TWuJi9dBeju7UJyp9TXi3IuklPgllVrYvfvruJeav2MCqtDU/eNpD4mAinY4mIiHzDG2v2UlhWxROTBjgdxRG6SU/ECw6UnOCWZ1cyb9Ue7hvXlZfvGqJyLBfFGPNM/UUHjDGzjTHLjTGPNHj+G2MiIo1R63Lz7OKdpCfHMbxrcN447tWCLBKMlucd4donl7LjUBkzJw/iZ1f3JDRE6xvLhTPGjAbaWWsXGmMmAqHW2hFAkjGm25nGHA0sIn7lww0H2VNUwfSxXYN2PX4VZJEmYq3luc93MmX2KuKiw3nn/lFc3be907HEzxljwoHngHxjzHXAOE6tSf8pMOosY6e/zlRjzGpjzOrCwsKmji0ifsJayzOL8uiSEMOVvROdjuMYFWSRJnC8qpb75+Xw6AebuaJXIu/cP4q0tsG1RI40me8Cm4DHgCHAD4B99c+VAolAzBnGvsZaO8tam2GtzUhISGjy0CLiHxZvK2TzgVIyx3YlJIjf7dRNeiIetrOwnMysbHYcLufnV/ckc2yXoH2LSprEQGCWtfagMSYLGAFE1T/XnLoLH+VnGBMROacZi/JoHxvJ9QM6OB3FUbpJT8SD/rXpENf9fRmFZVX8466hTB8XvPO3pMnsAL7a0ioDSOXUFIp0IB/IPsOYiMh/lL37GF/sKuKe0V2ICAvu36u1DrKIB7jclr/9extPfbqDfh1imTF5EB1bRTsdSwLTbOAFY8ytQDh1843fNcYkAeOBYYAFlpw2JiLyH81YlEdcdDi3XqLNq1SQRS5ScUU1D83PZfG2Qm4e3JHfX9+XyHBtGS1Nw1pbBtzccMwYMw64AnjMWltytjERkbPZdqiMf28+xEOXdSOmmeqhvgIiF2Hj/hIys7I5WFLJozf05fYhKZpSIV5nrT3GqVUrzjomInI2MxfnERUeyp0jUp2O4hNUkEUu0Fs5e/nFG+tpFR3Bq9OGMyilldORREREztveYxW8m7uf7w5PpZU2sQK0ioXIeauudfPHDzbz0vJ8hnaO5++3DyKhRTOnY4mIiFyQ55fswhi4Z3Rnp6P4DK1iIXIeDpdWcvtzK3lpeT73jOrM3HuGqhyLiIjfOlpexfwv93D9gA4kxUWd+xOChKZYiDTS6vwips9dQ3llLU/dNpAJ6UlORxIREbkoLy/Pp6rWzbSxXc79wUFEBVnkHKy1/GPFbn7/3iY6tooi6+6h9GjXwulYIiIiF6W8qpaXludzZe9E0trq51pDKsgi/8GJahcPv7WeN3P2cXmvtvzllgHERoU7HUtEROSizftiD6WVtUwfp3vDTqeCLHIWe45WMC0rmy0HS/nRFd25/9K0oN6XXkREAkdVrYvnl+5kRNfWDEiOczqOz1FBFjmDRVsP89D8XKy1vHDnJVzao63TkURERDzm7Zx9HCqt4vGb052O4pO0zJtIA2635enPdvDXf2+jR2ILnp0ymE6tY5yOJSIi4jEut2Xm4p307dCSUWltnI7jk7TMm0i90soaps7J5i//2sZ16Um8dd9IlWMREQk4H208yK4jx5k+Nk27v56FpliIAFsPlpGZlU1BUQW/ndCb741I1UlDREQCjrWWGYvy6Nwmhqv7tnM6js9SQZag9966/fzs9XXENAtj3tRhXJIa73QkERGRJrF0xxHW7yvhzxP7Eaobz89KBVmCVq3Lzf/+cwvPLdnF4E6teOaOQSS2jHQ6loiISJOZsSiPxJbNuGFQB6ej+DQVZAlKR8qruP+VNazcWcR3h3fikWt6ExHm1Sn5IiIiXpVbUMzyvKM8/O1eNAsLdTqOT1NBlqCTs+cY981dQ9Hxav5yczo3Du7odCQREZEmN3NRHi0jw7htaIrTUXyeCrIElXmr9vCbdzbStmUz3pg+gr4dtKKKiIgEvh2Hy/lo00HuvzSN5s1U/85FXyEJCpU1Ln7zzkZeXV3AmO4JPDFpAK1iIpyOJSIi4hXPLs6jWVgId45IdTqKX1BBloC3r/gE07OyWbe3hPsvTeO/ruiuO3dFRCRo7C8+wdu5+7hjaCdaN2/mdBy/oJ30JKAt23GEB+blUFPrZtaUwVzZR2s+iohIcJm9dBduC/eM7ux0FL+hnfQkIFlreXZxHlNmf0HrmAjeuX+kyrGIiASdY8ermbdqD9elJ9GxVbTTcfyGplhIwCmvquVnr6/lg/UHuaZfex67qT8xuiFBRESC0Msr8qmodpE5rqvTUfyKWoMElLzCcqbNyWZnYTkPf7sX94zurC2jRUQkKFVU1/LS8nwu75VI98QWTsfxKyrIEjA+2niQHy9YS0RYCFl3D2VEWhunI4mIiDhm3qoCiitqmK6rx+dNBVn8nstt+eu/tvL0Z3mkd4xlxuTBJMVFOR1LRETEMdW1bp5fspMhneMZ3KmV03H8jgqy+LVjx6t5cH4OS7Yf4bYhyfxmQh8iw7V9poiIBLd3cvdxoKSSP03s53QUv6SCLH5rw74SMrOyOVxaxZ8n9uPWIdo6U0RExO22zFycR6/2LRnbPcHpOH5JBVn80uvZe3n4rfXEx0SwIHM4A5LjnI4kIiLiEz7edIi8wuM8edtA3ah+gVSQxa9U17r5/XubmLNyN8O7tOap2wfSRrsCiYiIAHX7AMxYnEdKfDTf7qv1/y+UCrL4jYMlldw3N5s1e4qZNqYLP72qB2GhXt3rRkRExKet2HmUtQXFPHpDX/2MvAgqyOIXvth5lB+8kkNFdS1P3z6Ia/q3dzqSiIiIz5mxKI82zZtx46COTkfxayrI4tOstby4LJ9HP9hMp/hoXrl3qBY7FxEROYP1e0tYsv0IP7+6p1Z0ukheLcjGmAnAhLS0NG8eVvxURXUtv3xzPe/k7ueK3on85ZZ0WkaGOx1LRETEJ81cnEeLZmHcMUyrOl0sr05OsdYutNZOjY2N9eZhxQ/tPnqcic8s5921+/nJld15dvJglWMREZGz2HXkOB9sOMCU4Z3089IDNMVCfM5nWw7z0PwcjDG89P0hWsNRRETkHJ5dnEd4aAjfH9nZ6SgBQQVZfIbbbXny0+088cl2erVrybNTBpMcH+10LBEREZ92sKSSN9bsZdIlySS00NKnnqCCLD6h5EQNP3o1l0+2HGbioA48en0/oiJ0g4GIiMi5vLBsF24L08Z0dTpKwFBBFsdtOVjKtDnZ7Dt2gt9f14fJwzpp5x8REZFGKKmoYe7K3Vzbv73edfUgrSAtjnondx83PL2cE9UuXp02jCnDU1WORc7BGJNojMmpfzzbGLPcGPNIg+e/MSYigekfK/I5Xu0ic6yuHnuSCrI4osZVt2X0Q/Nz6duhJe89OIrBneKdjiXiLx4HoowxE4FQa+0IIMkY0+1MY44mFZEmc6LaxYvL87m0RwK92rd0Ok5A0RQL8brCsip+8MoaVu0q4s4RqTx8TS/CtR2mSKMYY74FHAcOAuOABfVPfQqMAgaeYWz7GV5nKjAVICVFa6aK+KMFqwsoOl7NfZdqfwlPU0EWr1qz5xjTs7IpOVHD3yYN4PqBHZyOJOI3jDERwH8D1wNvAzHAvvqnS4G0s4x9g7V2FjALICMjwzZVZhFpGjUuN7M+30lGp1Zckqp3YD1Nl+3EK6y1ZK3czaRnV9AsLJQ3p49UORY5f78AnrbWFtf/vRyIqn/cnLpz+pnGRCTALFy7n33FJ5g+TnOPm4KuIEuTq6xx8eu3N/Ba9l7G9UjgiUkDiY3WLj8iF+By4FvGmB8AA4AUoABYCaQDW4G91E2raDgmIgHE7bbMXJxHj8QWXNqjrdNxApIKsjSpvccqyMzKZsO+Uh68rBs/vKwbISFapULkQlhrx3z12BizCPgOsMQYkwSMB4YB9gxjIhJAPt1ymG2HyvnbpAH6mdpEVJClySzZXsiD83KodVue/24Gl/dOdDqSSMCw1o4DMMaMA64AHrPWlpxtTEQCg7WWZxbtoGOrKK7t397pOAFLBVk8zlrLjMV5PP7RVrq1bcHMKYPp3CbG6VgiAclae4xTq1acdUxEAsOqXUWs2VPM767rQ5hWgGoyKsjiUWWVNfzktbV8tPEQE9KT+N8b+xEdof/NREREPGHG4jxax0Rw8+Bkp6MENDUX8Zgdh8uYOieb3UcreOSaXtw9qrN2xRMREfGQTftLWbS1kJ9e1YOoiFCn4wQ0FWTxiA/XH+Anr60lKiKUrLuHMrxra6cjiYiIBJQZi/No3iyMycM6OR0l4Kkgy0Wpdbl5/ONtzFycx4DkOGZMHkT72Khzf6KIiIg02u6jx3l/3X7uHd2F2CgtldrUVJDlghUdr+aBeWtYtuMotw9N4TcTetMsTG/5iIiIeNqsz3cSFhLC3aM6Ox0lKKggywVZt7eY6VlrKCyv4rEb+3PLJbpZQEREpCkcLqvktey93Di4I21bRjodJyh4dH0QY0wbY8x7xpiOnnxd8S0LvizgppkrAHg9c7jKsYiISBN6YWk+tS4308Z0cTpK0Gh0QTbGJBpjlpw2NtsYs9wY80j9UDiwxpMBxXdU1br41Vvr+dkb6xiSGs/CB0bRv2Oc07FEREQCVmllDXNX7mZ8v/akak8Br2nUFAtjTCvgZSCmwdhEINRaO8IY84wxppu1drsxxn2W15gKTAVISUm5+OTiVQdKTjA9aw25BcVkju3KT6/qQai2txQREWlSWSt3U1ZVy/SxXZ2OElQaewXZBUwCShuMjePUTk2fAqP+0wtYa2dZazOstRkJCQnnm1MctCLvKBOeWsr2Q2XMnDyIX4zvqXIsIiLSxCprXLywdBdjuifQt0Os03GCSqOuIFtrS4HTN32IAfbVPy4F0uo/9reeiydOstYye+ku/vThFlJbRzN/6jDS2rZwOpaIiEhQeC17L0fKq3X12AEXs4pFOfDVgrfN8fANf+Ksiupafvb6Ot5bd4Cr+iTy+M3ptIjUuosiIiLeUOtyM+vzuj0GhnWJdzpO0LmYgpxN3bSKlUA6sPVcn2CMmQBMSEtLu4jDSlPbdeQ4mXOy2X64jJ9f3ZPMsV20ZbSIiIgXvb/+AAVFJ/j1Nb31M9gBF1OQ3waWGGOSgPHAsHN9grV2IbAwIyPj3os4rjShTzYf4oev5hIWYnj5riGM7qb54iIiIt5krWXGojzS2jbn8l6JTscJSuc1LcJaO67B41LqbtRbCVxqrS3xaDLxKpfb8tePt3L3y6vp1DqahQ+MUjkWERFxwKKthWw5WEbm2K6E6KZ4R1zUTnrW2mOcWslC/FRxRTU/fDWXRVsLuWlwR/5wfV8iw7VltIiIiBNmLMojKTaS6wYkOR0laHl1q2nNQfY9m/aXMi1rNQdLKvnD9X25Y2iK5jqJiIg4ZHV+Eavyi/jNhN6Eh2r9A6d49StvrV1orZ0aG6u1/HzBWzl7mThjGdW1bl6dNpzJwzqpHIuIiDhoxqI8WkWHM+mSZKejBDWvXkEW31DjcvPo+5t5aXk+QzrH8/Ttg0ho0czpWCIiIkFty8FSPtlymP+6vDvREapoTtJXP8gcLq3kB6+s4cv8Y9w9qjO/GN9Tb+GIiIj4gGcX7yQ6IpTvjejkdJSgpznIQSR7dxHTs9ZQVlnLE7cO4LoBHZyOJCIiIkBBUQXvrt3P90ekEhcd4XScoKc5yEHAWss/VuQz6dmVREWE8tYPRqgci4iI+JDnluwkxMDdozs7HUXQFIuAV1nj4ldvrefNNfu4rGdb/jppALFR2jJaRETEVxwpr+LVLwu4YWAH2sdGOR1HUEEOaAVFFUybk83mg6X81+XdeeBbaVpwXERExMe8tCyfapebaWO7Oh1F6qkgB6jF2wp5cF4O1lpe+N4lXNqzrdORRERE5DRllTW8vCKfq/u0o2tCc6fjSD3dpBdg3G7LM4t28Jd/baNHYguenTKYTq1jnI4lIiIiZ/DKF3soq6xl+jhdPfYlukkvgJRW1jAtK5vHP97Gd9KTeOu+kSrHIiIiPqqyxsXzS3cxKq0N/TvGOR1HGtAUiwCx/VAZ0+Zks6eogt9M6M2dI1K1K56IiIgPeytnH4VlVfxt0gCno8hpVJADwPvrDvDT19cSHRHGK/cOY0jneKcjiYiIyH/gclueXZxH/46xjOja2uk4choVZD9W63Lz2EdbmfX5TgalxDFj8mASW0Y6HUtERETO4cMNB8g/WsGMOwbpHV8fpILsp46UV/HAKzms2HmUKcM68etrexMRpi2jRUREfJ21lhmL8uiSEMNVfdo5HUfOQKtY+KHcgmKmZ2VTdLyax29O56bBHZ2OJCIiIo30+fYjbNxfymM39tf+BD5Kq1j4mXmr9nDLzBWEhhjemD5C5VhERMTPzFi0g3YtI7luYJLTUeQsNMXCT1TWuPjtuxuZ/2UBo7u14clbB9IqJsLpWCIiInIe1uw5xsqdRTxyTS+ahYU6HUfOQgXZD+wvPsH0rGzW7i3hB5d25UdX9CBUb8mIiIj4nZmL8oiNCue2ISlOR5H/QAXZxy3fcYT75+VQXevm2SmDNZlfRETET20/VMbHmw7x4GXdiGmmCubL9N3xUdZanluykz9/uIWuCc2ZOWWw9mgXERHxYzMX7yQqPJQ7R6Q6HUXOQQXZB5VX1fLz19fx/voDfLtfOx67KZ3m+k1TRABjTCwwn7rzdzkwCZgB9AI+sNb+of7jZp8+JiLO2Vd8gndy9zFleCfidQ+Rz9PCuT4mr7CcG55exocbDvCrb/fk6dsHqRyLSEN3AH+11l4BHARuBUKttSOAJGNMN2PMxNPHHMwrIsDzS3YCcM/oLg4nkcbQOsg+5KONB/nxgrVEhIWQdfdQRqS1cTqSiPgYa+0zDf6aAEwG/lb/90+BUcBAYMFpY9sbvo4xZiowFSAlRTcLiTSlouPVzF9VwHUDOtAhLsrpONIIWgfZB7jclsc/2sq0Odl0TYhh4QOjVI5F5D8yxgwHWgEFwL764VIgEYg5w9jXWGtnWWszrLUZCQkJXkgsErxeWp7PiRoXmWN19dhf6L17hx07Xs1Dr+by+bZCbr0kmd9+pw+R4VoXUUTOzhgTDzwF3Aj8CPjqklRz6i58lJ9hTEQccLyqlpeX53Nl70S6JbZwOo40kgqygzbsKyEzK5vDpVX8aWI/rYkoIudkjImgbvrEL621u40x2dRNoVgJpANbgb1nGBMRB8xbtYeSEzVkjuvqdBQ5DyrIDnk9ey8Pv7We+JgIFmQOZ0BynNORRMQ/3A0MBh42xjwMvAhMMcYkAeOBYYAFlpw2JiJeVlXr4rklOxnWJZ5BKa2cjiPnQQXZy6pr3fz+vU3MWbmb4V1a89TtA2nTvJnTsUTET1hrZ1C3rNtJxph3gSuAx6y1JfVj404fExHveidnP4dKq3jspnSno8h5UkH2okOllUzPymbNnmKmjunCz67qQViopgaKyMWx1h7j1KoVZx0TEe9xuS0zP8+jT1JLxnTTjff+RgXZS1btKuK+uWuoqK7l77cP5Nr+SU5HEhERkSby8caD7Cw8zt9vH4gxxuk4cp5UkJuYtZaXlufz6PubSY6P5pV7h9Jdd7GKiIgELGstMxbnkdo6mvF92zsdRy6ANgppQieqXfzizXW8k7ufy3sl8tdJ6bSMDHc6loiIiDSh5XlHWbe3hD9N7EdoiK4e+yNtFNJEdh89zg3PLOPdtfv5yZXdmTVlsMqxiIhIEHhm0Q7atmjGxEEdnI4iF0hTLJrAZ1sO89D8HIwxvPT9IYztrl2qREREgsHagmKW7TjKL8f3pFmYNv7yVyrIHuR2W576dAd/+2Qbvdq15Nkpg0mOj3Y6loiIiHjJzMV5tIwM4/ah2vzLn6kge0jJiRp+9Goun2w5zMSBHXj0hn5EReg3RxERkWCRV1jOPzce5Afj0mihaZV+TQXZA7YcLCVzTjZ7j53gd9f1YcqwTlrSRUREJMg8uziPiNAQ7hyZ6nQUuUgqyBfp3bX7+fnr62gRGcb8qcPISI13OpKIiIh42YGSE7yVs4/bhqRoh9wAoIJ8gWpcbv784RZmL93FJamtePr2QbRtGel0LBEREXHA7CW7cFu4d3QXp6OIB6ggX4DCsiruf2UNX+wq4s4RqTx8TS/CtWW0iIhIUCquqOaVVXv4TnqSbs4PECrI52nNnmNMz8qm5EQN/29SOjcM7Oh0JBEREXHQy8t3U1HtYtpYXT0OFCrIjWStZe4Xe/ifhRtpFxvJm9NH0juppdOxRERExEEV1bW8tHwXl/VsS8926gWBQgW5ESprXPz67Q28lr2Xsd0TeOLWAcRFRzgdS0RERBz26pcFHKuo4b5LuzodRTxIBfkc9h6rIDMrmw37SnnwW2k8dHl37asuIiIiVNe6ee7znQxJjWdwJ61iFUi8WpCNMROACWlpad487AVbsr2QB+flUOuyPP/dDC7vneh0JBEREXFIZY2LjftLyC0oIbegmJw9x9hfUsmjN/RzOpp4mFcLsrV2IbAwIyPjXm8e93xZa5mxOI/HP9pKt7YtmDllMJ3bxDgdS0RERLzE7bbkFZaTW1BMbkExa/cWs+VAGbVuC0BSbCTpyXHcf2ka43okOJxWPE1TLE5TVlnDT19bxz83HmRCehL/e2M/oiP0ZRIREQlkh0srySkoZm19IV6/t4SyqloAWjQLo39yLFPHdGFAchwDkuO090GAU/NrYMfhcqbNWU3+0QoeuaYXd4/qrC2jRUREAszxqlrW76ubJvFVIT5QUglAWIihZ/sWXDcwifSOcQxMiaNLm+aE6P6joKKCXO+fGw7w4wVriYoIJevuoQzv2trpSCIiInKRal1uth0qZ+3eYnL31E2V2HaojPqZEqTER5ORGl9/ZTiWPkmxRIaHOhtaHBf0Bdnltjz+8VZmLMpjQHIcMyYPon1slNOxRERE5DxZa9lfUnmyCOfuKWb9vhJO1LgAiIsOJ71jHFf2acfA5Dj6d4yldfNmDqcWXxTUBbnoeDUPzsth6Y4j3D40hd9M6E2zMP3WKCIi4g9KTtSwfm8JuQXHTq4scaS8CoCI0BB6J7Vk0iXJJ+cNd2odramT0ihBW5DX7y0hMyubwvIqHruxP7dckux0JBERETmL6lo3Ww6Wsrag+OTNdHmFx08+3yUhhjHd2zAgOY70jnH0at+SiLAQBxOLPwvKgrxgdQGPvL2BhObNeD1zOP07xjkdSUREROpZa9lTVHFyibXcgmI27i+lutYNQJvmEQxIjuOGgR1IT46jf8c4YqPCHU4tgSSoCnJVrYv/WbiJV77Yw8i01jx12yDiY7RltIiIiJOKjld/7Sa6tQXFHKuoASAyPIT+HeL43vBODEhuRXpyLB3iojRVQppU0BTkAyUnmJ61htyCYjLHduUnV3YnLFRvvYiIiHhT3W50pSeXV1u7t5jdRysAMAa6t23Blb3bkV4/b7h7YnP9vBavC4qCvCLvKA/MW8OJahcz7hjE+H7tnY4kIiIS8Nxuy84jx7+23vDmA6Und6NrHxtJesc4bhuSQnrHOPp1jKV5s6CoJuLjAvr/Qmsts5fu4k8fbqFT62jmTx1GWtsWTscSEREJSIfLKllbULeqxNqCEtbuLaassm43uubNwujfMZZ7G+xGl6jd6MRHBWxBrqiu5Wevr+O9dQe4qk8ij9+cTotITeAXERHxhIrqWtbvrSvBdVeIS9hXfAKA0BBDz3Yt+E56EunJcQxMjqNLQnNCtRud+ImALMi7jhwnc0422w+X8bOrezB9bFdN5hcREblALrdl++GykzfR5ez5+m50yfFRDEyJ4/sjUxmQHEefpFiiIrSvgPivgCvIn2w+xA9fzSUsxPDyXUMY3S3B6UgiIiJ+w1rLgZLKk3OGcwvqdqOrqK7bjS42Kpz05Diu7J3IgJS6JdbaaDc6CTABU5DdbsvfPtnOk59sp2+HlsycPJiOraKdjiUiIuLTyiprWLe35GQZXltQzOGyU7vR9UpqyS0ZyaQnxzIguRWp2o1OgkBAFOSSihp++GoOn20t5KbBHfnD9X2JDNdbOyIiIg3VuNxsPVh2cie63IJi8grLsfVTJbq0iWFkWv1udMlx9GrfgmZh+nkqwcfvC/Km/aVkZmVzoOQEf7i+L3cMTdFvtiIiEvSstRQUnSC3wQYcG/aVUFW/G13rmLrd6K6rv5EuvWMcsdG6mV0E/Lwgv52zj1+8uY7YqHBenTacQSmtnI4kIiLiiOKK6pOrSeQWHGPt3hKKjlcDdbvR9esQy5RhnRiQUleGO7bSbnQiZ+OXBbnG5ebR9zfz0vJ8hnSO5+nbB5HQQjcIiIiIb3O5LTUuN7VuS02tmxq3mxqXpdblpsZV97jhn7UuW/cxtfWf87Xn3FRUu9h8oJTcgmLyG+xG161tcy7v1bbBbnQtCNdudCKN5rGCbIy5ErgO2Gmt/YunXvd0h8squX9uDqvyi7h7VGd+Mb6n/tGLiJyBMWY20Av4wFr7B6fzeIrbbak+R8msddV/zFeF8gwl8/RSWuu2VNe6qXU3LKr1JfXkx7iprrX1H3Nakf3q40/mOvXcV1m+WhbNk9q1jCQ9OZZJl6SQnhxL/45x2o1O5CI16l+QMSYReN1aO7rB2Okn3tuAu4AfG2MirbWVng6bvbuI6VlrKKus5YlbB3DdgA6ePoSISEAwxkwEQq21I4wxzxhjullrt3vyGB+uP0DJiZqzlsxTxfC0K59nKJm1rtNK6RlK5lfPNUXJbCgsxBAeGkJYqCGi/s+wkBAiwkJOPhceeupjmjcLOzkWFhpC+MnPDyHiq7HTPic85NTHf3WMr39M/et87Zinnj+ZLyyEltoES8TjzlmQjTGtgJeBmAZj3zjxAtXWWmuMKQdaAQdOe52pwFSAlJSU8w7qdlv++52NREWE8o+7h9CzXcvzfg0RkSAyDlhQ//hTYBTg0YL8pw+3sKeo4ozPnW/JjHGwZIaHhBAeVpcvPNRoXq6INOoKsguYBLzTYGwc3zzx5hljLgEGALNPfxFr7SxgFkBGRsZ5//4fEmKYOXkwLaPCiY3Sb8siIucQA+yrf1wKpDV88mIvWgC8Om0YBqOSKSIB55wF2VpbCpx+sjvTifdx4FbgGWttjWdj1kmO18YfIiKNVA5E1T9uDnztZo2LvWgB0D426twfJCLihy707rZvnHittbXW2ixr7TrPRBMRkYuQTd27ewDpQL5zUURE/MuF3ub61Yl3JXUn3q2N+SRjzARgQlpa2jk/VkRELsrbwBJjTBIwHhjmbBwREf9xoVeQ3wamGGP+CtwCvN+YT7LWLrTWTo2Njb3Aw4qISGPUT48bR92FjEuttSXOJhIR8R+NLsjW2nENHuvEKyLi46y1x6y1C6y1B53OIiLiTy54JXFr7TFOrWQhIiIiIhIQvLoFnTFmgjFmVkmJLjiLiIiIiG/yakHWHGQRERER8XVeLcgiIiIiIr5OBVlEREREpAFj7QVtoHRxBzWmENh9gZ/eBjjiwThy/vQ9cJa+/s67mO9BJ2ttgifDXCydk/2evgfO0tffeR4/JztSkC+GMWa1tTbD6RzBTN8DZ+nr7zx9D07R18J5+h44S19/5zXF90BTLEREREREGlBBFhERERFpwB8L8iynA4i+Bw7T1995+h6coq+F8/Q9cJa+/s7z+PfA7+Ygi4iIiIg0JX+8giwiIiIi0mRUkEVEREREGlBBlkYzxvzWGDPO6RwivkD/HsRp+n9Q5BRP/3tQQRYRERERacBvCrIxprkx5gNjzKfGmBedzhPEfmSMWWyMmW+MCXU6TDAxxkTWf92XGmPeM8ZEO50p2BhjWhlj/m2M+QwY53QeJ+mc7DN0TnaIzsnOa8pzst8UZKA98DQwHkg1xiQ6nCdYrbbWjgVKgAlOhwkyU4G11tpRwBtAX4fzBKOpwHvW2kuBGqfDOEznZN+gc7JzdE52XpOdk/2pINcA9wBzgXggytk4QeuL+j/XAF2dDBKEegKr6h+/BHzpXJSg1RlYV/94tZNBfIDOyb5B52Tn6JzsvCY7J/tTQb4beB24DTjucJZgNrj+z/5AvoM5gtEW4JL6x7+irpyId+0Getc/HuBgDl+gc7Jv0DnZOTonO6/Jzsn+VJD/BfwS+LT+7x0czBLMRhtjFgOJwDtOhwkys4BBxphFwCBgjrNxgtJzwI3134OWDmdxms7JvkHnZOfonOy8Jjsnayc9EREREZEG/OkKsoiIiIhIk1NBFhERERFpQAVZRERERKQBFWQRERERkQZUkEVEREREGlBBFhERERFp4P8D7nmb4k8kqqQAAAAASUVORK5CYII=\n",
+      "text/plain": [
+       "<Figure size 720x288 with 2 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, axs = plt.subplots(1, 2, figsize=(10, 4))\n",
+    "for j in range(2):\n",
+    "    axs[j].plot(list('abcd'), [10**i for i in range(4)])\n",
+    "    if j==0:\n",
+    "        axs[j].set_yscale('log')\n",
+    "    else:\n",
+    "        pass\n",
+    "fig.tight_layout()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 思考题\n",
+    "\n",
+    "- 墨尔本1981年至1990年的每月温度情况"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:58:28.482772Z",
+     "start_time": "2020-11-01T10:58:28.472757Z"
+    }
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Time</th>\n",
+       "      <th>Temperature</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1981-01</td>\n",
+       "      <td>17.712903</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1981-02</td>\n",
+       "      <td>17.678571</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1981-03</td>\n",
+       "      <td>13.500000</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1981-04</td>\n",
+       "      <td>12.356667</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1981-05</td>\n",
+       "      <td>9.490323</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "      Time  Temperature\n",
+       "0  1981-01    17.712903\n",
+       "1  1981-02    17.678571\n",
+       "2  1981-03    13.500000\n",
+       "3  1981-04    12.356667\n",
+       "4  1981-05     9.490323"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ex1 = pd.read_csv('data/layout_ex1.csv')\n",
+    "ex1.head()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "ExecuteTime": {
+     "end_time": "2020-11-01T10:21:13.743892Z",
+     "start_time": "2020-11-01T10:21:13.738905Z"
+    }
+   },
+   "source": [
+    "请利用数据，画出如下的图：\n",
+    "\n",
+    "<img src=\"https://s1.ax1x.com/2020/11/01/BwvCse.png\" width=\"800\" align=\"bottom\" />"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "-  画出数据的散点图和边际分布\n",
+    "\n",
+    "用 `np.random.randn(2, 150)` 生成一组二维数据，使用两种非均匀子图的分割方法，做出该数据对应的散点图和边际分布图\n",
+    "\n",
+    "<img src=\"https://s1.ax1x.com/2020/11/01/B0pEnS.png\" width=\"400\" height=\"400\" align=\"bottom\" />"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.4"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": false,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {
+    "height": "calc(100% - 180px)",
+    "left": "10px",
+    "top": "150px",
+    "width": "288.661px"
+   },
+   "toc_section_display": true,
+   "toc_window_display": true
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebook/第三回：布局格式定方圆.ipynb b/notebook/第三回：布局格式定方圆.ipynb
index f9b7574..0ed9fd8 100644
--- a/notebook/第三回：布局格式定方圆.ipynb
+++ b/notebook/第三回：布局格式定方圆.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2020-11-01T10:58:25.798702Z",
@@ -33,7 +33,7 @@
     "\n",
     "### 1. 使用 `plt.subplots` 绘制均匀状态下的子图\n",
     "\n",
-    "返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列\n",
+    "返回元素分别是画布和子图构成的列表，第一个数字为行，第二个为列，不传入时默认值都为1\n",
     "\n",
     "`figsize` 参数可以指定整个画布的大小\n",
     "\n",
@@ -79,6 +79,52 @@
     "fig.tight_layout()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "`subplots`是基于OO模式的写法，显式创建一个或多个axes对象，然后在对应的子图对象上进行绘图操作。  \n",
+    "还有种方式是使用`subplot`这样基于pyplot模式的写法，每次在指定位置新建一个子图，并且之后的绘图操作都会指向当前子图，本质上`subplot`也是`Figure.add_subplot`的一种封装。"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "在调用`subplot`时一般需要传入三位数字，分别代表总行数，总列数，当前子图的index"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 3 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plt.figure()\n",
+    "# 子图1\n",
+    "plt.subplot(2,2,1) \n",
+    "plt.plot([1,2], 'r')\n",
+    "# 子图2\n",
+    "plt.subplot(2,2,2)\n",
+    "plt.plot([1,2], 'b')\n",
+    "#子图3\n",
+    "plt.subplot(224)  # 当三位数都小于10时，可以省略中间的逗号，这行命令等价于plt.subplot(2,2,4) \n",
+    "plt.plot([1,2], 'g');"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -88,22 +134,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "text/plain": [
-       "<matplotlib.collections.PathCollection at 0x140cd96b988>"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -123,7 +159,17 @@
     "\n",
     "\n",
     "plt.subplot(projection='polar')\n",
-    "plt.scatter(theta, r, c=colors, s=area, cmap='hsv', alpha=0.75)"
+    "plt.scatter(theta, r, c=colors, s=area, cmap='hsv', alpha=0.75);"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "> 练一练  \n",
+    "\n",
+    "请思考如何用极坐标系画出类似的玫瑰图\n",
+    "<img src=\"http://www.hinews.cn/news/pic/003/205/569/00320556959_f01764d0.jpg\" width=\"300\" align=\"bottom\" />\n"
    ]
   },
   {
@@ -232,87 +278,7 @@
    "source": [
     "## 二、子图上的方法\n",
     "\n",
-    "在 `ax` 对象上定义了和 `plt` 类似的图形绘制函数，常用的有： `plot, hist, scatter, bar, barh, pie`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-11-01T10:58:27.489701Z",
-     "start_time": "2020-11-01T10:58:27.398224Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x120c03070c8>]"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 288x216 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots(figsize=(4,3))\n",
-    "ax.plot([1,2],[2,1])"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-11-01T10:58:27.582392Z",
-     "start_time": "2020-11-01T10:58:27.490700Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "(array([  4.,  21.,  53., 157., 210., 255., 178.,  83.,  32.,   7.]),\n",
-       " array([-3.21675023, -2.5967257 , -1.97670118, -1.35667665, -0.73665212,\n",
-       "        -0.1166276 ,  0.50339693,  1.12342145,  1.74344598,  2.3634705 ,\n",
-       "         2.98349503]),\n",
-       " <BarContainer object of 10 artists>)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": "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\n",
-      "text/plain": [
-       "<Figure size 288x216 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots(figsize=(4,3))\n",
-    "ax.hist(np.random.randn(1000))"
+    "补充介绍一些子图上的方法"
    ]
   },
   {
@@ -329,7 +295,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 17,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2020-11-01T10:58:27.686055Z",
@@ -339,17 +305,7 @@
    "outputs": [
     {
      "data": {
-      "text/plain": [
-       "<matplotlib.lines._AxLine at 0x120c042b6c8>"
-      ]
-     },
-     "execution_count": 7,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 288x216 with 1 Axes>"
       ]
@@ -364,7 +320,7 @@
     "fig, ax = plt.subplots(figsize=(4,3))\n",
     "ax.axhline(0.5,0.2,0.8)\n",
     "ax.axvline(0.5,0.2,0.8)\n",
-    "ax.axline([0.3,0.3],[0.7,0.7])"
+    "ax.axline([0.3,0.3],[0.7,0.7]);"
    ]
   },
   {
@@ -376,7 +332,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 18,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2020-11-01T10:58:27.774748Z",
@@ -386,7 +342,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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\n",
+      "image/png": "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\n",
       "text/plain": [
        "<Figure size 288x216 with 1 Axes>"
       ]
@@ -411,12 +367,12 @@
     }
    },
    "source": [
-    "使用 `set_xscale, set_title, set_xlabel` 分别可以设置坐标轴的规度（指对数坐标等）、标题、轴名"
+    "使用 `set_xscale` 可以设置坐标轴的规度（指对数坐标等）"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 21,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2020-11-01T10:58:28.239217Z",
@@ -426,7 +382,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 720x288 with 2 Axes>"
       ]
@@ -439,16 +395,12 @@
    ],
    "source": [
     "fig, axs = plt.subplots(1, 2, figsize=(10, 4))\n",
-    "fig.suptitle('大标题', size=20)\n",
     "for j in range(2):\n",
     "    axs[j].plot(list('abcd'), [10**i for i in range(4)])\n",
     "    if j==0:\n",
     "        axs[j].set_yscale('log')\n",
-    "        axs[j].set_title('子标题1')\n",
-    "        axs[j].set_ylabel('对数坐标')\n",
     "    else:\n",
-    "        axs[j].set_title('子标题1')\n",
-    "        axs[j].set_ylabel('普通坐标')\n",
+    "        pass\n",
     "fig.tight_layout()"
    ]
   },
@@ -456,117 +408,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "与一般的 `plt` 方法类似， `legend, annotate, arrow, text` 对象也可以进行相应的绘制"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-11-01T10:58:28.362171Z",
-     "start_time": "2020-11-01T10:58:28.240214Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "Text(0.8, 0.2, '这是中点')"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots()\n",
-    "ax.arrow(0, 0, 1, 1, head_width=0.03, head_length=0.05, facecolor='red', edgecolor='blue')\n",
-    "ax.text(x=0, y=0,s='这是一段文字', fontsize=16, rotation=70, rotation_mode='anchor', color='green')\n",
-    "ax.annotate('这是中点', xy=(0.5, 0.5), xytext=(0.8, 0.2), arrowprops=dict(facecolor='yellow', edgecolor='black'), fontsize=16)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "metadata": {
-    "ExecuteTime": {
-     "end_time": "2020-11-01T10:58:28.469816Z",
-     "start_time": "2020-11-01T10:58:28.364168Z"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<matplotlib.legend.Legend at 0x120bef078c8>"
-      ]
-     },
-     "execution_count": 11,
-     "metadata": {},
-     "output_type": "execute_result"
-    },
-    {
-     "data": {
-      "image/png": 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Tx4LNx5weS8RjuRTmxpiCxpilLqybZYypff9jiS8IDvTnpdaVmPFCE/LlzEa/T9cw4PO1JP2q4i6RtEo1zI0xeYApQEgq67oBe6y169w0m/iI6sVCmTWwCX9uVZGFW47TIiaO6WsOqbhLJA1cOTO/AXQB7vqqD2NMXuAD4Iwx5sG7rOlrjEk0xiQmJSWla1jxXoH+fgx4sBxzBzelXIGc/PGb9Tw7eTWHVdwl4pJUw9xam2ytPZfKsqHAN8AEoIcxpsMdtjPRWhturQ0PCwtL37Ti9coVyMU3/RrxZvsqrN53mpYxcUxdsU/FXSKpcNcDoLWBMdbaY8DXQHM3bVd8kJ+f4dkmt4q76pTMw99mbqbLxBXsTjrv9GgiWZa7wnwXUCbl83Bgv5u2Kz6seN4cTO1Vn/c712D7sV9pM2IpY5fs4pqKu0R+J81hbox5yBgz8LZvvwcMNMYsAyKAj90xnIgxhsfDi7Poj5E8VLEA783fziNjlrHpcGpX/kR8i8thbq1tnvJxsbV29G23HbHWtrXWNrHWRllrf3XznOLjCuQKZnz3uozrVofjyVfoOGYZ7y/YxuVrKu4SAb1oSDxMm+qFWRQdwaO1izLmp920HbmUxH2nnR5LxHEKc/E4D+QI4t+P12Rqr/pcuXaTxyes4M1Zm7lwRcVd4rsU5uKxIiqEETs0gmcalWLKilvFXfE79BoG8U0Kc/FoIdkCeLNDVb7p14hsgX70+Phn/vTNes5evOr0aCKZSmEuXiG8VF7mDmrGgAfL8v26w7SIiWfexqNOjyWSaRTm4jWCA/35c6tKzBrYhIK5s9H/87U8/+kaTiRfdno0kQynMBevU7VIKDMHNOGl1pVYvP0ELWLi+CbxoIq7xKspzMUrBfj70b95WeYNbkbFQrn487cb6PHxzxw8fdHp0UQyhMJcvFrZsJxM69uIf3asytr9Z2g1PJ5Plu1VcZd4HYW5eD0/P0P3RqVYMDSCeqXy8ubsLTw+YQW7TuiFyuI9FObiM4rlycEnPesR80RNdiedp+2IBEYv3qniLvEKCnPxKcYYOtUpxsKhkURVLci/Y3fQYbSKu8TzKczFJ4XlysaYrnWY0L0uJ8/fKu56Z56Ku8RzKczFp7WqWohFQyPpXKcY4+N203bEUn7eq+Iu8TwKc/F5oTkCebdzDT57rgFXb9zkiQkreH3GJn69fM3p0URcpjAXSdG0fH5ih0bQq0lpPlu1n1bD4vlp+wmnxxJxicJc5DdyBAXwt/ZV+Pb5xoRkC6Dn5NVET/uFMxdU3CVZm8Jc5A7qlszDnEFNGfRQOWatP0KLmDjmbDiiSgDJshTmIneRLcCf6JYVmf1iU4o8kJ2BX6yj36drOK7iLsmCFOYiqahcODffv9CYV9pUIm5HEi1i4pi2+oDO0iVLUZiLuCDA349+kWWZPySCyoVz89L0jTw9aRUHTqm4S7IGhblIGpTOH8JXfRry1iPVWH/wHK2GxzMpYS83VNwlDlOYi6SRn5/h6YYliR0aQaOy+fjnnC08Nm45O46ruEucozAXSaciD2Rn0jPhjHiyFvtPXaDdyKWM/HEnV6+ruEsyn8Jc5D4YY+hYqyiLoiNpXa0wMQt30GF0AusPnnV6NPExCnMRN8iXMxujnqrNhz3COXPxKo+OXcbbc7dy6aqKuyRzKMxF3CiqSkEWRkfSpV5xJsTvoc2IeFbsPuX0WOIDFOYibpY7OJC3O9Xgi94NuGnhqQ9X8tfvN5Ks4i7JQApzkQzSuFx+FgyJoE+z0nz18wFaxsSzeNtxp8cSL6UwF8lA2YP8ebVdFb57oQmh2QPp9Ukig79ax6nzV5weTbyMwlwkE9Qq/gCzX2zKkBblmbvxKFHD4pm1XsVd4j4uhbkxpqAxZqkL66oZY2LvfywR7xMU4MeQFhWY82IziufNwaAv19FnaiLHzqm4S+5fqmFujMkDTAFCUllngBggyD2jiXinioVy8V3/xrzWrjIJu04SFRPHF6sOcFOVAHIfXDkzvwF0AZJTWdcT+Om+JxLxAf5+ht7NyrBgSATVioby1+830vWjlew7ecHp0cRDpRrm1tpka+25e60xxuQDngb+fY81fY0xicaYxKSkpLRPKuKFSuYL4Ys+DXinU3U2H06m9Yh4Pozfo+IuSTN3PQD6DvCKtfauT6S11k601oZba8PDwsLctFsRz2eM4cn6JVgYHUnTcvn5v7lb6TR2GduPqbhLXOeuMI8E3jXGLAFqGWPectN2RXxGodBgPuwRzqinanPozCUeHrWUYQt3qLhLXJLmMDfGPGSMGfjb71lrK1hrm1trmwO/WGtfc9eAIr7EGEP7mkVYGB1Ju+qFGfHjTh4etZR1B844PZpkcS6HeUpQY61dbK0dndo6EUm/vCFBDH+yNh8/G86vl6/Tadxy/jlnCxevXnd6NMmi9KIhkSzsoUoFiR0aQbcGJZiUsJfWw5eyfNdJp8eSLEhhLpLF5QoO5K1HqvNV34b4Gej60Spenr6Bc5dU3CX/pTAX8RANy+Rj/pAI+kWW4evEg7QcFsfCLSruklsU5iIeJDjQn1faVGbGgCbkyRFEn6mJDPxiLSdV3OXzFOYiHqhGsQeYNbApf4yqQOzm40TFxDFj3WEVd/kwhbmIhwoK8OPFP5Tnh0FNKZU/hCHTfqHXJ6s5cvaS06OJAxTmIh6ufMFcfPt8Y/72cBVW7jlNy2HxfLpyv4q7fIzCXMQL+PsZejUtTezQCGoVf4DXZ2ziyQ9XslfFXT5DYS7iRYrnzcGnz9XnvcdqsPVoMq2HxzM+bjfXb6gSwNspzEW8jDGGJ+oVZ1F0JJEVwnhn3jYeHbucLUdSa7EWT6YwF/FSBXMHM6F7XcZ0rcPRc5foMDqBD2K3c+X6DadHkwygMBfxYsYY2tUozMKhkXSoVYRRi3fRbmQCa/aruMvbKMxFfECekCBinqjFJz3rcenqDTqPX87fZ2/mwhUVd3kLhbmID2lesQALhkbQvWFJJi/bR6vh8SzdqXf+8gYKcxEfkzNbAP/oWI2v+zUiyN+P7pN+5i/frufcRRV3eTKFuYiPql86L3MHN6N/87JMX3uYFsPimL/pmNNjSTopzEV8WHCgPy+1rsTMAU0Iy5mN5z9bw4DP15L0q4q7PI3CXESoVjSUmQOb8OdWFVm49TgtYuKYvuaQirs8iMJcRAAI9PdjwIPlmDuoGeUK5OSP36znmcmrOXTmotOjiQsU5iLyP8oVyMk3/Rrx9w5VSdx3mlbD4pm6Yp+Ku7I4hbmI/I6fn+GZxqVYMCSCOiXz8LeZm+kycQW7k847PZrchcJcRO6qeN4cTO1Vn38/XpMdx8/TZsRSxi7ZxTUVd2U5CnMRuSdjDJ3rFmNhdAQtKhfgvfnbeWTMMjYdPuf0aPIbCnMRcUmBXMGM7VaX8U/X4XjyFTqOWcZ787dx+ZqKu7IChbmIpEnraoX5MTqSTrWLMnbJbtqOXErivtNOj+XzFOYikmahOQJ5//GaTO1VnyvXbvL4hBW8MXMT51Xc5RiFuYikW0SFMGKHRvBMo1JMXbmfVsPiiduh4i4nKMxF5L6EZAvgzQ5V+fb5RgQH+vHMxz/zx6/Xc/biVadH8ykKcxFxi7ol8/LDoGYMfLAcM385TIuYOOZuPOr0WD5DYS4ibhMc6M+fWlVk5sAmFAoN5oXP1/L8p2s4kXzZ6dG8nsJcRNyuapFQZrzQhJdaV2Lx9hO0iInj68SDKu7KQApzEckQAf5+9G9elvmDm1GpUG7+8u0Genz8MwdPq7grI7gU5saYgsaYpfe4vYQxZokxZrExZqIxxrhvRBHxZGXCcvJV34b8s2NV1u4/Q6vh8UxetpcbKu5yq1TD3BiTB5gChNxjWT+gv7X2IaA4UN0944mIN/DzM3RvVIrY6Ejql87L32dv4fHxy9l14lenR/MarpyZ3wC6AMl3W2CtfdVauzXly3zAydvXGGP6GmMSjTGJSUl6HqqILyr6QHYmP1uPYV1qsufkBdqOSGD04p0q7nKDVMPcWptsrXWpUccY0wXYbK09coftTLTWhltrw8PCwtIxqoh4A2MMj9YuxqLoSKKqFuTfsTtoPyqBjYdU3HU/3PYAqDGmDPAnYIi7tiki3it/zmyM6VqHCd3rcvrCVR4Zu4x35qm4K73cEuYp19W/BHq5ehYvIgLQqmohFkZH0rlOMcbH7abNiKWs2nPK6bE8TprD3BjzkDFm4G3ffhkoAYxKeVZLpFumExGfEJo9kHc71+Dz3g24fvMmXSau5PUZm/j18jWnR/MYxokn8YeHh9vExMS033Fyu1sfe/7g3oFEJMu4ePU6H8Tu4ONleymcO5j/e7Q6D1Yq4PRYWYIxZo21NvxOt+lFQyKSpeQICuD1h6swvX9jQrIF0POT1Qyd9gunL6i4614U5iKSJdUpkYc5g5oy6A/lmb3+CFExcczZcESVAHehMBeRLCtbgD/RURWY/WJTiubJzsAv1tH30zUcV3HX7yjMRSTLq1w4N9/1b8xf21YifkcSLWLimLb6gM7Sf0NhLiIeIcDfj74RZVkwJIIqhXPz0vSNdPtoFQdOqbgLFOYi4mFK5Q/hyz4N+dej1dlw6Bwth8fx0dI9Pl/cpTAXEY/j52fo2qAEC6MjaFw2P2/9sJXHxi1nx3HfLe5SmIuIxyocmp1Jz4Qz4slaHDh9kXYjlzJi0U6uXve94i6FuYh4NGMMHWsVZeHQCNpUK8ywRTvoMDqB9QfPOj1aplKYi4hXyJczGyOfqs1HPcI5e/Eaj45dxr/mbuXSVd8o7lKYi4hXaVGlILHRETxZvwQT4/fQekQ8K3Z7f3GXwlxEvE7u4ED+9Wh1vujTAICnPlzJK99tJNmLi7sU5iLitRqXzc/8wRH0jSjDtNUHaBkTz49bjzs9VoZQmIuIV8se5M9f21bmuxeaEJo9kOemJDLoy3WcOn/F6dHcSmEuIj6hVvEHmP1iU4a2qMC8TUeJGhbPzF8Oe00lgMJcRHxGUIAfg1uU54dBzSiRNweDv/qF3lMSOXruktOj3TeFuYj4nAoFczG9f2Nea1eZZbtP0jImni9WHeCmB1cCKMxFxCf5+xl6NytD7JBIqhcL5a/fb6TrRyvZd/KC06Oli8JcRHxaiXw5+Lx3A97pVJ3Nh5NpNTyeifG7uX7DsyoBFOYi4vOMMTxZvwQLoyNpVj6Mf83dxmPjlrPtWLLTo7lMYS4ikqJQaDAf9qjLqKdqc+jMJR4emUDMwh1cuZ71KwEU5iIiv2GMoX3NIiyMjqR9zSKM/HEn7UclsO7AGadHuyeFuYjIHeQNCWJYl1pMfrYev16+Tqdxy/nnnC1cvHrd6dHuSGEuInIPD1YqQOzQCLo1KMGkhL20Gh7Psl0nnR7rdxTmIiKpyBUcyFuPVGda34YE+PnR7aNVvDx9A+cuZZ3iLoW5iIiLGpTJx7zBzegXWYavEw8SFRNH7OZjTo8FKMxFRNIkONCfV9pUZsaAJuQNCaLvp2sY+MVaTjpc3KUwFxFJhxrFbhV3/allBWI3H6dFTBzfrzvkWHGXwlxEJJ0C/f0Y+FB55g5uSpn8IQydtp6en6zm8NnML+5SmIuI3KdyBXLxzfONeaN9FVbtOU3LmDg+Xbk/U4u7FOYiIm7g72fo2aQ0sUMjqF0iD6/P2MSTE1eyJ+l8puxfYS4i4kbF8+bg0+fq817nGmw7lkybEUsZH5fxxV0uhbkxpqAxZuk9bg80xswxxiw3xvRy33giIp7HGMMT4cVZFB1J84phvDNvG4+MXcaWIxlX3JVqmBtj8gBTgJB7LHsRSLTWNgYeNsbkctN8IiIeq0DuYCZ0D2dctzocO3eFDqMTmJSwN0P25cqZ+Q2gC3Cvf1KaA1+nfL4cCL99gTGmrzEm0RiTmJSUlNY5bylU/dZ/IiIepE31wiyKjqBjraKUzJsjQ/YRkNoCa20y3Pq14R5CgMMpnycDBe+wnYnARIDw8PD0PcTb5p103U1ExGkP5AjigydqZtj23fUA6Hkge8rnOd24XRERcYG7QncN0DTl85rAPjdtV0REXJDqZZbbGWMeAqpYa0f/5ttTgLnGmGZAFWCVm+YTEREXuHxmbq1tnvJx8W1BjrV2PxAFLANaWGuz/nssiYh4kTSfmd+NtfYI/31Gi4iIZCI9UCki4gUU5iIiXkBhLiLiBYwTRerGmCRgfzrvnh/Ieu+mmrF0zL5Bx+wb7ueYS1prw+50gyNhfj+MMYnW2t/VBXgzHbNv0DH7how6Zl1mERHxAgpzEREv4IlhPtHpARygY/YNOmbfkCHH7HHXzEVE5Pc88cxcRERuozAXEfECWTrMffG9R1045hLGmCXGmMXGmIkmlXcN8QSpHfNv1lUzxsRmxkwZKQ3HO8sYUzszZspoLvy5LmOM+dEYs8IY83pmzpYRjDGhxph5xpiFxpjvjTFBd1k3KSW/XrvffWbZMPfF9x518Zj7Af2ttQ8BxQGPfh89F4+ZlH+0YoA7/qXwFGk43m7AHmvtukwZLAO5eMwDgdettY2AVsaYO74wxoN0A2KstVHAMaD17QuMMZ0A/5T8KmKMKX8/O8yyYY6b3nvUw6R6zNbaV621W1O+zIfnv3rOlZ8zQE/gp4wfJ8OlerzGmLzAB8AZY8yDmTVYBnLlZ3wKqGyMKcitf7DPZsJcGcZaO9ZauzDlyzDgxB2WNee/+bWY/77BT7q4rQLX3dz13qOexMVjJmVNF2BzSvWwx3LlmI0x+YCngVYp/3ksF3/GQ4FvgAnA28aYXNbaWZkwXoZw8ZjnA4OAMtz6R/t6xk+W8YwxjYA81tqVd7j59vwqdz/7yspn5q7wyfceNcaUAf4EDHF4lMzyDvCKtfaa04NkktrAGGvtMW6duTV3dpxM8QbwrLX2VW79nY5yeJ77lvIb1ijgbo/nuTW/PD38fO69R1OuP34J9LLWnnN6nkwSCbxrjFkC1DLGvOXwPBltF7fOUOHWpcP0ltJ5kiJAcWNMMFAH8OgXwKQ84Pk1t05C7vbzc2t+ZdnLLLfzxfcevcsxvwyUAEal/Nr6hrU2zon5MsKdjtlaW+E3ty+x1t73I/9ZxV1+xu8BHxljXgUuAp0cGS6D3OWY3wCWcOv68hxuXUP2ZM8BdYFXU36OPwGBt/3ZnQEsNcYUAdoADe9nhx7/CtCU/xFNgQU+dKYqIl4g5TftKCA+5bJa+rfl6WEuIiKef81cRERQmIuIeAWFuYiIF1CYi4h4AYW5iIgX+H9xstDSyd1PJAAAAABJRU5ErkJggg==\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "fig, ax = plt.subplots()\n",
-    "ax.plot([1,2],[2,1],label=\"line1\")\n",
-    "ax.plot([1,1],[1,2],label=\"line1\")\n",
-    "ax.legend(loc=1)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "其中，图例的 `loc` 参数如下：\n",
+    "## 思考题\n",
     "\n",
-    "|  string   | code  |\n",
-    "|  ----  | ----  |\n",
-    "| best  | 0 |\n",
-    "| upper right  | 1 |\n",
-    "| upper left  | 2 |\n",
-    "| lower left  | 3 |\n",
-    "| lower right  | 4 |\n",
-    "| right  | 5 |\n",
-    "| center left  | 6 |\n",
-    "| center right  | 7 |\n",
-    "| lower center  | 8 |\n",
-    "| upper center  | 9 |\n",
-    "| center  | 10 |"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## 作业\n",
-    "\n",
-    "### 1. 墨尔本1981年至1990年的每月温度情况"
+    "- 墨尔本1981年至1990年的每月温度情况"
    ]
   },
   {
@@ -662,7 +506,7 @@
     }
    },
    "source": [
-    "- 请利用数据，画出如下的图：\n",
+    "请利用数据，画出如下的图：\n",
     "\n",
     "<img src=\"https://s1.ax1x.com/2020/11/01/BwvCse.png\" width=\"800\" align=\"bottom\" />"
    ]
@@ -671,12 +515,19 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### 2. 画出数据的散点图和边际分布\n",
+    "-  画出数据的散点图和边际分布\n",
     "\n",
-    "- 用 `np.random.randn(2, 150)` 生成一组二维数据，使用两种非均匀子图的分割方法，做出该数据对应的散点图和边际分布图\n",
+    "用 `np.random.randn(2, 150)` 生成一组二维数据，使用两种非均匀子图的分割方法，做出该数据对应的散点图和边际分布图\n",
     "\n",
     "<img src=\"https://s1.ax1x.com/2020/11/01/B0pEnS.png\" width=\"400\" height=\"400\" align=\"bottom\" />"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {