将pandas数据框转换为numpy数组-首选哪种方法? [英] Convert pandas dataframe to numpy array - which approach to prefer?

问题描述

我需要将大数据帧转换为numpy数组. 仅保留数值和类型. 我知道有充分的记录方法.

I need to convert a large dataframe to a numpy array. Preserving only numerical values and types. I know there are well documented ways to do so.

那么，哪一个更受欢迎?

So, which one is to prefer?

df.values
df._as_matrix()
pd.to_numeric(df)
... others ...

决定因素:

• 效率

• efficiency

在nan，np.nans和其他可能的意外值上安全运行

safely operating on nan,np.nans, and other possible unexpected values

数值稳定

推荐答案

您提到的功能有不同的用途.

The functions you mention serve different purposes.

1. pd.to_numeric :如果当前数据不是以数字形式或存储，则可以使用它来转换数据框中的类型 通过downcast='float'强制转换为最佳类型 downcast='integer'.

1. pd.to_numeric: Use this to convert types in your dataframe if your data is not currently stored in numeric form or if you wish to cast as an optimal type via downcast='float' or downcast='integer'.

pd.DataFrame.to_numpy() (v0.24 +)或

pd.DataFrame.to_numpy() (v0.24+) or pd.DataFrame.values: Use this to retrieve numpy array representation of your dataframe.

pd.DataFrame.as_matrix :请勿使用此功能.仅包括它是为了向后兼容.

pd.DataFrame.as_matrix: Do not use this. It is included only for backwards compatibility.

这篇关于将pandas数据框转换为numpy数组-首选哪种方法?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！