matplotlib & pandas

Python/matplotlab/gallery/statistics/histogram_multihist.md

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+# 使用多个数据集演示直方图(hist)函数
+
+绘制具有多个样本集的直方图并演示：
+
+- 使用带有多个样本集的图例
+- 堆积图
+- 没有填充的步进曲线
+- 不同样本量的数据集
+
+选择不同的存储量和大小会显著影响直方图的形状。Astropy文档有很多关于如何选择这些参数的部分: http://docs.astropy.org/en/stable/visualization/histogram.html
+
+
+![多个数据集演示直方图](https://matplotlib.org/_images/sphx_glr_histogram_multihist_001.png)
+
+```python
+import numpy as np
+import matplotlib.pyplot as plt
+
+np.random.seed(19680801)
+
+n_bins = 10
+x = np.random.randn(1000, 3)
+
+fig, axes = plt.subplots(nrows=2, ncols=2)
+ax0, ax1, ax2, ax3 = axes.flatten()
+
+colors = ['red', 'tan', 'lime']
+ax0.hist(x, n_bins, density=True, histtype='bar', color=colors, label=colors)
+ax0.legend(prop={'size': 10})
+ax0.set_title('bars with legend')
+
+ax1.hist(x, n_bins, density=True, histtype='bar', stacked=True)
+ax1.set_title('stacked bar')
+
+ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)
+ax2.set_title('stack step (unfilled)')
+
+# Make a multiple-histogram of data-sets with different length.
+x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]
+ax3.hist(x_multi, n_bins, histtype='bar')
+ax3.set_title('different sample sizes')
+
+fig.tight_layout()
+plt.show()
+```
+
+## 下载这个示例
+            
+- [下载python源码: histogram_multihist.py](https://matplotlib.org/_downloads/histogram_multihist.py)
+- [下载Jupyter notebook: histogram_multihist.ipynb](https://matplotlib.org/_downloads/histogram_multihist.ipynb)