I'm getting tired of never getting the kind of charts I want out of Matplotlib. It's so damned fiddly. I put this together to do plotting in a way that I need for presentations and things. At the moment, it works on a set of csvs, but it could easily be copied into existing code.

There are two folders: data and output.

• Data: holds a set of csv files that you want plotted.
• Output: holds a set of pngs
• chart_details_lookup.py is a lookup table. It tells the script which csvs you want plotted and how you want them plotted (more details below).
• graphing.py is the script that produces the charts based on the details in the lookup table.
• requirements.txt holds the details of the libraries used by the scripts

Prepare for running Python:

1. If not already installed, install virtualenv:
   • pip install virtualenv
2. Create a project folder:
   • virtualenv -p <location of Python3 install directory> <name of project>
3. Activate the virtual environment:
   • source <name of project>/bin/activate
4. Install libraries:
   • pip install -r requirements.txt

chart_details_lookup.py holds all details about the plots you want.

1. At the top of the lookup are global_specs that specify the size of the charts, the resolution of the saved charts, and the font used in the charts. Change these to suit your preferences.
2. plot_details is set up as a dictionary of dictionaries. It contains all data about the charts you want. It's liable to change, but the current set up is as follows:

     '<name of chart>': {
            'filename': 'foo.csv',     # the name of the csv in the data directory
            'plot_type': 'bar',           # currently only does bar charts, but this will change in the future
            'y1_axis': 'percentage',      # Name of the column you want plotted
            'y2_axis': False,             # Name of a second column you want plotted (or False, if there isn't one)
            'x_title': False,             # A title for the x-axis, or False if you don't want a title
            'x_rot': 0,                   # Rotation of x-axis tick labels (0 is horizontal)
            'x_max_len': 15,              # Max length of x-axis tick labels before they start a new line
            'y_title': 'Percentage',      # Title for y axis, or use False if you don't want a title
            'chart_title': 'Which OS do you use at work?',     # Chart title, or use False if you don't want a title
            'show_values': True,          # If True, show value on bars, if False, nothing
            'skip_labels': False,         # If False, print all x-axis labels. If set to a number, print an x-tick label, then skip that number of labels before printing the next x-axis label. (Allows you to deal with having too many x-tick labels to show neatly).
            'bottom_size': 0.15,          # Fraction of chart dedicated to x-axis tick labels (must be in range 0 - 1)
            'title_font_size': 24,        # Size of title font
            'axis_font_size': 14,         # Size of axis fonts
            'value_font_size': 20         # Size of value label font
             },

1. If you want to see the charts as they are created, open python graphing.py and uncomment the following line:

• # plt.show()
• Note: you will now have to close each chart after it's opened by the script

1. Run the script:

• python graphing.py

1. Your charts will appear in the output folder as png files.

Once you're finished, you can archive your files by copying the chart_details_lookup.py file, and the data and output directories into the archived_presentations directory under an appriately named sub-directory.