<jupyter_start><jupyter_text>ReproducibilityAs a warm-up exercise, we're going to check what version of packages we're using and what system we're running on<jupyter_code>import pandas as pd<jupyter_output><empty_output><jupyter_text>As a convention, most (but not all) packages contain a special attribute `__version__`<jupyter_code>pd.__version__<jupyter_output><empty_output><jupyter_text>[PIP](https://pypi.org/project/pip), the [package installer for Python](https://packaging.python.org/guides/tool-recommendations/) has a `freeze` command to list all packages installed including their versions.This can be run in he terminal, or prefixed with `!` in the Notebook<jupyter_code>!pip freeze<jupyter_output><empty_output><jupyter_text>If using [Conda](https://docs.conda.io/en/latest/), a similar output is available as `conda list`<jupyter_code>!conda list<jupyter_output><empty_output><jupyter_text>The version of Python itself is also important and may be different in various environments, causing code to break or behave differently<jupyter_code>import sys
sys.version<jupyter_output><empty_output><jupyter_text>Finally, the operating system itself can play a role, especially when executing system commands or working with files or network<jupyter_code>import platform
platform.platform()<jupyter_output><empty_output><jupyter_text>Try `platform.processor()` and [other functions](https://docs.python.org/3/library/platform.html) to understand where your code is running<jupyter_code>platform.processor()
platform.architecture()<jupyter_output><empty_output>
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