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杨韬的Python/Jupyter学习笔记

Python 安装库

安装Jupyter Notebook

安装numpy 数学包

到https://pypi.python.org/pypi/numpy#downloads 下载对应版本的numpy-1.14.0-cp36-none-win_amd64.whl 文件，复制到Scripts目录下安装
cmd运行 在K:\Jupyter Notebook Python\Python_3.6.4\Scripts>

pip install numpy-1.14.0-cp36-none-win_amd64.whl

安装绘图包matplotlib

安装pandas 数据输入输出库

安装seaborn绘图库

pip安装命令

安装指定版本 pip install jupyterthemes==0.18.3

若在线安装失败，如UnicodeDecodeError: ‘gbk‘ codec can‘t decode 这类问题。可能需要安装之前的指定版本

import math 

math.sin(3)

0.1411200080598672

words = ['cat', 'window', 'defenestrate']for w in words:    print("单词 "+w, "长度"+str(len(w)))

单词 cat 长度3单词 window 长度6单词 defenestrate 长度12

# 绘图包 matplotlib 的使用# https://liam0205.me/2014/09/11/matplotlib-tutorial-zh-cn/# http://codingpy.com/article/a-quick-intro-to-matplotlib/import matplotlib.pyplot as plt # 需要先包含绘图包 import numpy as npx = np.arange(20)y = x**2plt.plot(x, y)plt.show() # 显示图形#参考 http://codingpy.com/article/a-quick-intro-to-matplotlib/

$$ \int_0^{+\infty} x^2 dx $$

# 自定义曲线的外观x = np.linspace(0, 2 * np.pi, 50)plt.plot(x, np.sin(x), 'r-o',        x, np.cos(x), 'g--')   # r g 颜色   - 线型plt.show()

# 彩色映射散点图x = np.random.rand(1000)y = np.random.rand(1000)size = np.random.rand(1000) * 50colour = np.random.rand(1000)plt.scatter(x, y, size, colour) # 散点图plt.colorbar() #颜色栏plt.show()

 ![](http://images2017.cnblogs.com/blog/151822/201801/151822-20180113001655894-342726755.png)

import matplotlib.pyplot as pltimport numpy as npfrom mpl_toolkits.mplot3d import Axes3Dnp.random.seed(42)# 采样个数500n_samples = 500dim = 3# 先生成一组3维正态分布数据，数据方向完全随机samples = np.random.multivariate_normal(    np.zeros(dim),    np.eye(dim),    n_samples)# 通过把每个样本到原点距离和均匀分布吻合得到球体内均匀分布的样本for i in range(samples.shape[0]):    r = np.power(np.random.random(), 1.0/3.0)    samples[i] *= r / np.linalg.norm(samples[i])upper_samples = []lower_samples = []for x, y, z in samples:    # 3x+2y-z=1作为判别平面    if z > 3*x + 2*y - 1:        upper_samples.append((x, y, z))    else:        lower_samples.append((x, y, z))fig = plt.figure('3D scatter plot')ax = fig.add_subplot(111, projection='3d')uppers = np.array(upper_samples)lowers = np.array(lower_samples)# 用不同颜色不同形状的图标表示平面上下的样本# 判别平面上半部分为红色圆点，下半部分为绿色三角ax.scatter(uppers[:, 0], uppers[:, 1], uppers[:, 2], c='r', marker='o')ax.scatter(lowers[:, 0], lowers[:, 1], lowers[:, 2], c='g', marker='^')plt.show()# 参考 https://zhuanlan.zhihu.com/p/24309547

使用pandas数据输入输出库

参考 http://python.jobbole.com/80853/

import pandas as pd df = pd.DataFrame({  'A' : 1.,                                    'B' : pd.Timestamp('20130102'),                                    'C' : pd.Series(1, index=list(range(4)), dtype='float32'),                                    'D' : pd.Series([1, 2, 1, 2], dtype='int32'),                                    'E' : pd.Categorical(["test", "train", "test", "train"]),                                    'F' : 'foo' })df

df.B

0   2013-01-021   2013-01-022   2013-01-023   2013-01-02Name: B, dtype: datetime64[ns]

使用Seaborn绘图库

Seaborn本质上使用Matplotlib作为核心库，默认情况下就能创建赏心悦目的图

# http://python.jobbole.com/80853/import seaborn as sns # Load one of the data sets that come with seaborntips = sns.load_dataset("tips") sns.jointplot("total_bill", "tip", tips, kind='reg');

tips.head()

sns.lmplot("total_bill", "tip", tips, col="smoker");

其它参考

http://blog.csdn.net/qq_34264472/article/details/53814653

https://www.cnblogs.com/kylinlin/p/5236601.html

http://blog.csdn.net/u013082989/article/details/73278458

https://www.cnblogs.com/gczr/p/6767175.html

Python·Jupyter Notebook各种使用方法记录

http://blog.csdn.net/tina_ttl/article/details/51031113

Jupyter更换主题

https://github.com/dunovank/jupyter-themes

安装主题

# 嵌入视频from IPython.display import VimeoVideoVimeoVideo("63250251",with=600, height=400)

  File "<ipython-input-21-5e0fd48278da>", line 3    VimeoVideo("63250251",with=600, height=400)                             ^SyntaxError: invalid syntax

# 交互图表import ipywidgetsa=ipywidgets.IntSlider(value=5,min=0, max=10, step=1)a

ipywidgets.Text()

# 嵌入HTML页面from IPython.display import HTMLHTML('<iframe src="https://www.baidu.com" width=800 height=400></iframe>')

# 运行外部.py程序#    %run xxxx/xxxx.py

# Geo-Json