April 2019
Intermediate to advanced
172 pages
4h 39m
Chinese
Content preview from 精通特征工程
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回到特征：建立学术论文推荐器
｜
141
说实话，我并不认为这次特征选择的效果有多么好。这些字段中有很多缺失值。下面继续
看一下能否找出一些信息更丰富的特征。
找到你的位置
在
Pandas
数据框和
NumPy
矩阵之间的转换中，索引会令人迷惑——索引的大小相同，
但其分配的位置却不一样。为了解决这个问题，
Pandas
提供了
.iloc
、
.loc
和
.get_
loc
三种方法，如例
9-11
所示。
b
.loc
返回基于初始
Pandas
数据框的索引，可以让我们引用具体的论文。
b
.iloc
使用整数位置，和
NumPy
数组的索引是一样的。
b
.get_loc
可以帮助我们在已知数据框索引时找出整数位置。
例
9-11
在转换时维护索引分配
>>> model_df.loc[21]
abstract A microprocessor includes hardware registers t...
authors [{'name': 'Mark John Ebersole'}]
fos [Embedded system, Parallel computing, Computer...
keywords NaN
title Microprocessor that enables ARM ISA program to...
year 2013
Name: 21, dtype: object
>>> model_df.iloc[21]
abstract NaN
authors [{'name': 'Nicola M. Heller'}, ...
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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.