我已经使用python学习数据科学大约一年了。我已经对语法和模型创建非常满意。我之所以专门使用Google Colab，是因为它非常方便，而且我喜欢笔记本电脑的风格。但是，我不了解的一件事就是环境问题。尽管我使用Colab，但我的机器上确实装有python和anaconda，并使用以下完全相同的格式安装了各种软件包：ag <- structure(list(mat.agr = structure(c(0, 0, 0, 0, 0, 0, 0, 0,
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1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), .Dim = c(83L, 41L))), header = list(
description = "MATLAB 5.0 MAT-file, Platform: PCWIN64, Created on: Tue Aug 11 11:44:30 2020 ",
version = "5", endian = "little"))
。当我打开终端时，第一行以pip install (package name)开头，当我在anaconda导航器中检查(base)标签时，好像我将所有这些软件包都安装到名为{{1 }}？是对的吗？如果是这样，那么我的环境的名字是什么？与venv相比，什么是基本环境？
我问的原因是因为如果将来我决定使用IDE，我需要将环境设置为能够运行软件包，对吗？
仅出于乐趣，我想尝试使用R及其允许在R中使用python的reticulate软件包。如对this question的回答所述，我需要先设置虚拟环境，然后才能使用R中使用python。我的虚拟环境是否为Environments？
我对所有这些环境知识都完全陌生。同样，我刚刚打开终端，并为已安装的所有软件包键入base (root)。感谢您的任何事先帮助。
答案 0 :(得分：2)
因此，根据您的描述，听起来您的计算机上的默认Python安装是通过Anaconda实现的。如果真是这样，base实际上就是您所使用的conda虚拟环境的名称。
虚拟环境可能很棘手，所以我将带您逐步了解这里的工作。
首先，您始终可以通过在Mac / Linux上使用which命令来检查当前正在使用 的Python安装，或者如果您使用的是Windows，则该命令可能是where（如果您使用的是Windows，此答案可能会有所帮助：equivalent of 'which' in Windows。）
(base) ➜ ~ which python
/Users/steven/miniconda3/bin/python
从上面可以看到，我的默认Python是通过Miniconda进行的，Miniconda只是Anaconda的小版本。
这意味着当您使用pip安装软件包时，这些软件包将被安装到此base conda环境中。而且，顺便说一句，您也可以将which命令与pip一起使用，只是要仔细检查您使用的是当前环境中的pip版本：
(base) ➜ ~ which pip
/Users/steven/miniconda3/bin/pip
如果要查看当前安装的软件包列表，可以执行pip freeze或conda env export。 pip和conda都是软件包管理器，如果您正在使用Anaconda Python安装，则可以（通常）使用其中一个将软件包安装到虚拟环境中。
（简要说明：“虚拟环境”是可以以不同方式实现的一般概念。conda和virtualenv都是在Python中使用虚拟环境的方式。我也是数据科学家，而我在所有虚拟环境中都使用conda。
如果要使用conda创建新的虚拟环境，这非常简单。首先，您可以创建环境并立即安装一些软件包，例如pandas和matplotlib。然后，您可以激活该环境，检查您的python版本，然后将其停用。
(base) ➜ ~ conda create -n my-new-environment pandas matplotlib
(base) ➜ ~ which python
/Users/steven/miniconda3/bin/python
(base) ➜ ~ conda activate my-new-environment
(my-new-environment) ➜ ~ which python
/Users/steven/miniconda3/envs/my-new-environment/bin/python
(my-new-environment) ➜ ~ conda deactivate
(base) ➜ ~ which python
/Users/steven/miniconda3/bin/python
而且，如果要查看当前可用的conda虚拟环境，可以运行conda env list。
以下是有关conda环境的文档，我一直都在引用它们：https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html
我希望这会有所帮助！