如何在 pandas 中创建数据框视图? [英] How to create a view of dataframe in pandas?
问题描述
我有一个大数据框(10m行，40列，7GB内存).我想创建一个视图，以便为表达起来很复杂的视图取一个简写名称，而不会增加2-4 GB的内存使用量.换句话说，我宁愿输入:
I have a large dataframe (10m rows, 40 columns, 7GB in memory). I would like to create a view in order to have a shorthand name for a view that is complicated to express, without adding another 2-4 GB to memory usage. In other words, I would rather type:
df2
比:
df.loc[complicated_condition, some_columns]
The documentation states that, while using .loc ensures that setting values modifies the original dataframe, there is still no guarantee as to whether the object returned by .loc is a view or a copy.
我知道我可以将条件和列列表分配给变量(例如df.loc[cond, cols])，但是我通常很想知道是否可以创建数据框视图.
I know I could assign the condition and column list to variables (e.g. df.loc[cond, cols]), but I'm generally curious to know whether it is possible to create a view of a dataframe.
修改:相关问题:
- What rules does Pandas use to generate a view vs a copy?
- Pandas: Subindexing dataframes: Copies vs views
推荐答案
您通常无法返回视图.
您的答案在于pandas文档: returning-a-view-与复制.
Your answer lies in the pandas docs: returning-a-view-versus-a-copy.
只要标签数组或布尔向量涉及到 索引操作，结果将是副本.带单标签/ 标量索引和切片，例如df.ix [3:6]或df.ix [:,'A']，视图 将返回.
Whenever an array of labels or a boolean vector are involved in the indexing operation, the result will be a copy. With single label / scalar indexing and slicing, e.g. df.ix[3:6] or df.ix[:, 'A'], a view will be returned.
在以下帖子中找到了此答案:链接.
This answer was found in the following post: Link.
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