Compile usage statistics from bookings in a calendar exported to xls files

This notebook compiles statistics from a booking calendar exported to a set of excel xlsx files.

Step by step installation of python work environment (tested on Windows 10)

The following instruction are for people who never used python before.

Installing python

• Download miniconda from https://repo.anaconda.com/miniconda/Miniconda3-latest-Windows-x86_64.exe
• Run the installer, find a folder without spaces to install it C:\Software\Miniconda3 ### Installing Visual Studio code We can use Visual Studio code as an integrated environement for running the code. We could also use jupyter notebook or jupyter lab.
• Download Visual Studio Code https://code.visualstudio.com/sha/download?build=stable&os=win32-user
• Open Visual Code and on the start page, select clone repository. At the top, copy paste the link to this repository (https://github.com/jboulanger/UsageStats)
• Open the file 'Usage Stats Analytics.ipynb'
• Install python extension and select python interpreter in C:\System\Miniconda3\ when prompted. ### Create an environement The environement insures that you have all the necessary packages and isolate this configuration for the rest of the system. In Visual Code or in (conda) terminal:
• Press terminal > new terminal (select a cmd terminal not Powershell)
• Type C:\Software\Miniconda3\Scripts\activate C:\Software\Miniconda3\
• The terminal line should start by (base)
• Create the environment conda env create -f environment.yml
• Activate the environement conda activate usagestats, now the terminal should line should start with (usagestats).
• Register the kernel for notebooks: python -m ipykernel install --user --name usagestats

Configuration

The notebook should be at the same level than xlsx files, for simplicity copy the files next to the notebook.

Usage

• In visual code open the file 'Usage Stats Analytics.ipynb' as a jupyter notebook.
• Select the kernel 'usagestats' at the top right of the notebook.
• Configure the input in the first cell and run all the subsequent cells (Run all) to produce the graphs and csv files.
• If no file 'users.csv' and 'groups.csv' are present use they will be created with 'Unknown' values for groups and divisions. Check the files users.csv and groups.csv and fill out the missing values.
• Run again the notebook to update the graphs.

Note

The git repository configuration removes the output of the notebook when staging files using a .gitattibutes files and by having the following line in the file .git/config: [filter "strip-notebook-output"] clean = "jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to=notebook --stdin --stdout --log-level=ERROR"

The environment.yml file was created using: conda env export --no-builds --from-history | head -n -1 > environement.yml to remove the site specific prefix line.