July 2017
Intermediate to advanced
398 pages
11h 54m
Chinese
Content preview from Python数据处理
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58
第 4 章
处理
Excel
文件
与上一章的数据不同，将本章和下一章的数据导入
Python
不会那么轻松，某些数据的导入
需要花点工夫。这是因为有些数据格式是用于机器读取的，而另一些数据格式是通过桌面
工具来交互的，比如我们即将看到的那些数据。在本章和下一章里，我们将研究两种文件
类型实例：
Excel
文件和
PDF
，并给出几条一般性说明，在遇到其他文件类型时可以参考。
目前为止，你在本书中学到的数据导入方法都是比较常规的方法。本章我们将开始学习一
些数据处理过程，每次处理过程之间都会有很大差异。虽然过程更加困难，但最终目标是
相同的：提取有用信息，并将其转换成
Python
可用的格式。
本章和下一章的例子中使用的数据来自于
UNICEF
（联合国儿童基金会）
2014
年的报告，
报告主题是“世界儿童状况”（
http://www.unicef.org/sowc2014/numbers/
）。数据有
PDF
和
Excel
两种格式。
当需要从这些更难处理的文件格式中提取数据时，你可以想象文件里面有一个很恨你的
人，因为过程可能很痛苦。我们向你保证，在大多数情况下，生成数据文件的人只是不知
道发布机器可读格式文件的重要性。
4.1
安装
Python
包
首先我们要学习如何安装
Python
外部包（或库）。目前为止，我们使用的
Python
库都是在
安装
Python
时默认安装的。还记得在第
3
章里我们导入的
csv
和
json
包吗？它们属于标
准库里的程序包，在安装
Python
时默认安装。
Python
默认安装了一些常用库。由于许多库并不常用，所以你需要手动指定安装 ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.