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This repository aims to extract an insight from your job statistics. For that purpose it uses Jupyter notebook to process data gathered in an Excel data sheet.

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JobAnalysis

This repository aims to extract an insight of your job statistics.

The idea is to have an easily readable Excel where you can update your work days, and use a Jupyter notebook (with common Python libraries for data science) to process this data and extract further insights.

The Excel is pretty straightforward. Each table corresponds to a week work where you can add:

  • Entry and Exit hours, which will automatically calculate your working hours and update the total weekly hours. This is particularly convenient when you have a flexible schedule as long as you respect the working hours.
  • Status, which contains the project you are working on and your location, with the format: Project (location). Notice that you should write "DAY OFF" or "BANK HOLIDAYS" on the Status column when you did not work on that day.
  • Comment, allowing you to remember that particular day (e.g. Discussed with XXX about ZZZ product).

captura de ecra 2019-02-08 as 23 28 24

Here are some examples of the type of insights that you can extract from the data.

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This repository aims to extract an insight from your job statistics. For that purpose it uses Jupyter notebook to process data gathered in an Excel data sheet.

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