杨韬的Python/Jupyter学习笔记

2022-11-29 15:50:31

Python语法学习 https://zhuanlan.zhihu.com/p/24162430

Python 安装库

安装Jupyter Notebook

先安装Python
cmd 进入K:\Jupyter Notebook Python\Python_3.6.4\Scripts目录
cmd 输入 pip install jupyter 开始安装
运行 Python_3.6.4\Scripts下的 jupyter-notebook.exe

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

cmd 输入 pip install matplotlib

安装pandas 数据输入输出库

cmd 输入 pip install pandas

安装seaborn绘图库

cmd 输入 pip install seaborn

pip安装命令

安装 pip install jupyterthemes
安装最新版本 pip install --upgrade jupyterthemes
安装指定版本 pip install jupyterthemes==0.18.3
实际上pip instal 既可以安装本地.whl 也可以在线安装
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 np

x = np.arange(20)

y = x**2

plt.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) * 50

colour = 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 plt

import numpy as np

from mpl_toolkits.mplot3d import Axes3D

np.random.seed(42)

# 采样个数500

n_samples = 500

dim = 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

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	A	B	C	D	E	F
0	1.0	2013-01-02	1.0	1	test	foo
1	1.0	2013-01-02	1.0	2	train	foo
2	1.0	2013-01-02	1.0	1	test	foo
3	1.0	2013-01-02	1.0	2	train	foo

df.B

0   2013-01-02

1   2013-01-02

2   2013-01-02

3   2013-01-02

Name: 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 seaborn

tips = sns.load_dataset("tips")

sns.jointplot("total_bill", "tip", tips, kind='reg');

tips.head()

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	total_bill	tip	sex	smoker	day	time	size
0	16.99	1.01	Female	No	Sun	Dinner	2
1	10.34	1.66	Male	No	Sun	Dinner	3
2	21.01	3.50	Male	No	Sun	Dinner	3
3	23.68	3.31	Male	No	Sun	Dinner	2
4	24.59	3.61	Female	No	Sun	Dinner	4

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

pip install jupyterthemes

若出现UnicodeDecodeError: 'gbk' 中文问题，可安装之前的版本

pip install jupyterthemes==0.18.3

查看已安装带主题

命令行 jt -l

应用主题

命令行 jt -t onedork -f fira -fs 13

-fs 13 字体

回复原始状态

jt -r

# 嵌入视频

from IPython.display import VimeoVideo

VimeoVideo("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 ipywidgets

a=ipywidgets.IntSlider(value=5,min=0, max=10, step=1)

a

ipywidgets.Text()

# 嵌入HTML页面

from IPython.display import HTML

HTML('<iframe src="https://www.baidu.com" width=800 height=400></iframe>')

# 运行外部.py程序

#    %run xxxx/xxxx.py

# Geo-Json

安装jupyter lab Python IDE

pip install jupyterlab

执行 jupyter lab

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