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https://github.com/huangcongqing/python-libraries
python库(numpy,pandas...)学习
https://github.com/huangcongqing/python-libraries
matplotlib numpy pandas python3 xgboost
Last synced: 19 days ago
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python库(numpy,pandas...)学习
- Host: GitHub
- URL: https://github.com/huangcongqing/python-libraries
- Owner: HuangCongQing
- License: mit
- Created: 2019-03-07T14:23:01.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-10-09T06:20:23.000Z (about 1 month ago)
- Last Synced: 2024-10-13T17:52:49.512Z (about 1 month ago)
- Topics: matplotlib, numpy, pandas, python3, xgboost
- Language: Jupyter Notebook
- Size: 18 MB
- Stars: 0
- Watchers: 4
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# python-libraries
python库(numpy,pandas...)学习
总结文档：https://www.yuque.com/huangzhongqing/lang/vl43ut
加载github jupyter文件网址：https://nbviewer.jupyter.org/
注：开始用py文件写的，后面用的jupyter写的，可以写文档，更方便日后看，更容易看懂！
**环境： win7 python35**
* python基础：https://github.com/HuangCongQing/Python
# libraries
* 虚拟环境安装 ： [anaconda_environments](anaconda_environments)
* tensorflow=1.11.0
* torch==1.4.0
#### [01Numpy](./01Numpy)
* 矩阵运算
1. [学习莫凡讲解视频](https://www.bilibili.com/video/av16378934/)
```
C =np.concatenate((A,B,B,A),axis=0) #行操作，纵向合并
print(C)
C =np.concatenate((A,B,B,A), axis=1) #列操作，横向合并
```
#### [02Pandas](./02Pandas)
* 数据分析处理库Pandas，基于Numpy
#### [03Matplotlib](./03Matplotlib)
画图-可视化工具
笔记：ttps://www.yuque.com/huangzhongqing/lang/gv9n6f
菊安酱和菜菜的Python可视化
中文版[数据分析最有用的 Top 50 Matplotlib 图（附完整的Python代码](https://cloud.tencent.com/developer/article/1535159#:~:text=%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90%E6%9C%80%E6%9C%89%E7%94%A8%E7%9A%84%20Top%2050%20Matplotlib%20%E5%9B%BE%EF%BC%88%E9%99%84%E5%AE%8C%E6%95%B4%E7%9A%84Python%E4%BB%A3%E7%A0%81%EF%BC%89%20%28%E4%B8%8A%29%201%201.%E5%85%B3%E8%81%94,6%206.%E5%8F%98%E5%8C%96%207%207.%E5%88%86%E7%BB%84%208%201.%E6%95%A3%E7%82%B9%E5%9B%BE%209%202.%E5%B8%A6%E8%BE%B9%E7%95%8C%E7%9A%84%E6%B0%94%E6%B3%A1%E5%9B%BE.)
英文原版：[https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/](https://www.machinelearningplus.com/plots/top-50-matplotlib-visualizations-the-master-plots-python/)
* 代码目录： [03Matplotlib/Python可视化Top50Matplotlib](03Matplotlib/Python可视化Top50Matplotlib)
#### [04Seaborn](./04Seaborn)
* Seaborn基于Matplotlib
* 更简洁的语法
* 了解df，更轻松从CSV绘制数据
* 将包含许多行数据的Pandas DataFrames汇总到聚合图表中
#### [05Scikit-learn](./05Scikit-learn)
---
学习素材：[给深度学习入门者的Python快速教程 - numpy和Matplotlib篇](https://zhuanlan.zhihu.com/p/24309547)
...
### Install
```
# cv2(镜像下载)
pip install -i https://pypi.tuna.tsinghua.edu.cn/simple opencv-python
````
---
# 2 Python-module Download
python直接install安装不了一些python包，下载的whl文件集合
### whl文件集合
下载whl链接：https://www.lfd.uci.edu/~gohlke/pythonlibs/
#### python35
* [numpy](./python3/numpy-1.13.3+mkl-cp35-cp35m-win_amd64.whl)
* [scipy](./python3/scipy-1.0.0rc1-cp35-cp35m-win_amd64.whl)
* [xgboost](./python3/xgboost-0.6-cp35-cp35m-win_amd64.whl)
* [matplotlib](./python3/matplotlib-1.5.0-cp35-none-win_amd64.whl)
* [wordcloud](./python3/wordcloud-1.4.1-cp35-cp35m-win_amd64.whl)
### 下载库文件
如果是python2(python2.exe)
`python2 -m pip install 库名`
如果是python3（python3.exe）
`python3 -m pip install 库名`
如果不能下载报错，尝试下面两种方式
### 其他下载库文件两种方式
#### 一、下载whl文件方式
1. 命令行执行
`pip install wheel `
2. 下载相应版本的lxml后缀为.whl的文件
https://www.lfd.uci.edu/~gohlke/pythonlibs/
3. 安装
到包含`.whl`的文件夹下，打开命令行窗口
命令行执行
`pip install 文件名.whl`
完成
#### 二、下载库文件安装压缩包
1. 下载对应库文件的压缩包
2. 将压缩包解压到对应位置
3. 安装（解压文件夹里有setup.py）
执行
`python setup.py install`
安装完成
### License
Copyright (c) [ChungKing](https://github.com/HuangCongQing). All rights reserved.
Licensed under the MIT License.