diff --git a/README.md b/README.md index 44a0013..1788a62 100644 --- a/README.md +++ b/README.md @@ -205,25 +205,39 @@ B站视频在[这里](https://space.bilibili.com/88461692/#/channel/detail?cid=2 得到JK VanderPlas写的书《Python数据科学手册（Python Data Science HandBook）》，Jupyter notebooks在[这里](https://github.com/jakevdp/PythonDataScienceHandbook)。
**[高清中文版pdf](https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Other%20Docs/Python%E6%95%B0%E6%8D%AE%E7%A7%91%E5%AD%A6%E6%89%8B%E5%86%8C.zip)**
第2章：NumPy介绍，包括数据类型、数组和数组计算。 -br>代码如下： -
[NumPy介绍](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.00-Introduction-to-NumPy.ipynb) -
[理解Python中的数据类型](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.01-Understanding-Data-Types.ipynb) -
[NumPy数组基础](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.02-The-Basics-Of-NumPy-Arrays.ipynb) -
[NumPy数组的计算：通用函数](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.03-Computation-on-arrays-ufuncs.ipynb) +
代码如下： +
[2. NumPy入门](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.00-Introduction-to-NumPy.ipynb) +
[2.1 理解Python中的数据类型](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.01-Understanding-Data-Types.ipynb) +
[2.2 NumPy数组基础](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.02-The-Basics-Of-NumPy-Arrays.ipynb) +
[2.3 NumPy数组的计算：通用函数](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.03-Computation-on-arrays-ufuncs.ipynb) ## 深入研究 | NUMPY | 第46天 第2章： 聚合, 比较运算符和广播。
代码如下： -
[聚合：最小值、最大值和其他值](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.04-Computation-on-arrays-aggregates.ipynb) -
[数组的计算：广播](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.05-Computation-on-arrays-broadcasting.ipynb) -
[比较、掩码和布尔运算](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.06-Boolean-Arrays-and-Masks.ipynb) +
[2.4 聚合：最小值、最大值和其他值](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.04-Computation-on-arrays-aggregates.ipynb) +
[2.5 数组的计算：广播](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.05-Computation-on-arrays-broadcasting.ipynb) +
[2.6 比较、掩码和布尔运算](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.06-Boolean-Arrays-and-Masks.ipynb) ## 深入研究 | NUMPY | 第47天 第2章： 花哨的索引，数组排序，结构化数据。
代码如下： -
[花哨的索引](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.07-Fancy-Indexing.ipynb) -
[数组的排序](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.08-Sorting.ipynb) -
[结构化数据：NumPy的结构化数组](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.09-
Structured-Data-NumPy.ipynb) +
[2.7 花哨的索引](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.07-Fancy-Indexing.ipynb) +
[2.8 数组的排序](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.08-Sorting.ipynb) +
[2.9 结构化数据：NumPy的结构化数组](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/02.09-
Structured-Data-NumPy.ipynb) + +## 深入研究 | PANDAS | 第48天 +第3章：Pandas数据处理 +
包含Pandas对象，数据取值与选择，数值运算方法，处理缺失值，层级索引，合并数据集。 +
代码如下： +
[3 Pandas数据处理](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.00-Introduction-to-Pandas.ipynb) +
[3.1 Pandas对象简介](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.01-Introducing-Pandas-Objects.ipynb) +
[3.2 数据取值与选择](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.02-Data-Indexing-and-Selection.ipynb) +
[3.3 Pandas数值运算方法](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.03-Operations-in-Pandas.ipynb) +
[3.4 处理缺失值](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.04-Missing-Values.ipynb) +
[3.5 层级索引](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.05-Hierarchical-Indexing.ipynb) +
[3.6 合并数据集：ConCat和Append方法](https://github.com/jakevdp/PythonDataScienceHandbook/blob/master/notebooks/03.06-Concat-And-Append.ipynb) + + ## 层次聚类 | 第54天 [动画演示](https://github.com/MachineLearning100/100-Days-Of-ML-Code/blob/master/Other%20Docs/%E5%B1%82%E6%AC%A1%E8%81%9A%E7%B1%BB.gif)