Pandas - pandas.DataFrame.from_csv和pandas.read_csv [英] Pandas - pandas.DataFrame.from_csv vs pandas.read_csv

问题描述

之间有什么区别：

pandas.DataFrame.from_csv ，doc链接： http://pandas.pydata.org/pandas-docs/stable/generated/ pandas.DataFrame.from_csv.html

和

熊猫。 read_csv ，doc链接： http://pandas.pydata.org/pandas-docs/stable/generated/pandas.io.parsers.read_csv.html

推荐答案

没有真正的区别（两者都基于相同的底层函数），但是如注释中所述，他们有一些不同的默认值（对于 read_csv 和<$ c>，index_col 为0或无， parse_dates 分别为$ c> DataFrame.from_csv 和 read_csv 支持更多参数 / code>它们只是没有通过）。

There is no real difference (both are based on the same underlying function), but as noted in the comments, they have some different default values (index_col is 0 or None, parse_dates is True or False for read_csv and DataFrame.from_csv respectively) and read_csv supports more arguments (in from_csv they are just not passed through).

除此之外，它是建议使用 pd.read_csv 。

DataFrame.from_csv 仅仅因为历史原因而存在，并保持向后兼容性（计划是弃用它，请参见此处），但所有新功能仅添加到 read_csv （你可以在更长的关键字参数列表中看到）。实际上，这应该在文档中更清楚。

Apart from that, it is recommended to use pd.read_csv.
DataFrame.from_csv exists merely for historical reasons and to keep backwards compatibility (plans are to deprecate it, see here), but all new features are only added to read_csv (as you can see in the much longer list of keyword arguments). Actually, this should be made more clear in the docs.

这篇关于Pandas - pandas.DataFrame.from_csv和pandas.read_csv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！