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.gitignore

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.ipynb_checkpoints
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*.swp
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# 第1章 准备工作"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## 重要的Python库"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"1. NumPy\n",
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" - NumPy在数据分析方面有一个主要作用,即作为算法之间传递数据的容器,对于数值型数据,NumPy数组在存储和处理数据时要比内置的Python数据结构高效的多,此外,由低级语言(C、Fortran等)编写的库可以直接操作NumPy数组中的数据,无需进行任何数据复制工作\n",
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"2. pandas\n",
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" - 兼具NumPy高性能的数组计算功能以及电子表格和关系型数据库(SQL等)灵活的数据处理功能\n",
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"3. matplotlib\n",
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"4. IPython\n",
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"5. SciPy"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 2",
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"language": "python",
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"name": "python2"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 2
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython2",
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"version": "2.7.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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