Making Music with Pandas

This year I’ve started taking guitar lessons. While I’m anxious to jump into learning a bunch of songs, my instructor is keen on me developing foundational knowledge in music theory, scales, modes, and so forth–which I’m perfectly fine with, as well.

So far, we’ve covered several ways to play major scales, the pentatonic minor scale, and the natural minor scale. We also talked about scale “relatives:” how every major scale has a minor scale and every minor scale is a subset of a major scale, the two being relatives of each other.

My instructor then gave me this assignment: play any major scale from the low E string to the high E string, transition into the scale’s relative minor by dropping down three frets, and finish playing out the relative minor scale.

As I’ve been practicing this task, though, I often find myself off by a fret. I have to ask myself, “self, what major scale did you start in? C major? So why are you playing the G# natural minor scale?”

What would really help my practice is to have a handy cheatsheet to show me all the notes in each major scale and highlight the relative minor scale of each major. I could write it all out by hand, but why do that when I have Python and Pandas at my disposal! Here’s what I came up with:

Import my packages

I really only need pandas for this work:

import pandas as pd

Generate the twelve major scales

Here’s the code I came up with to calculate all the notes in each scale. Each scale consists of 15 notes spanning three octaves:

# make up my list of notes
chromatic_scale_ascending = ['C', 'C#', 'D', 'D#', 'E', 'F', 'F#', 'G', 'G#', 'A', 'A#', 'B']
# since I usually start on the low E string, rearrange the notes starting on E
scale_from_e = (chromatic_scale_ascending + chromatic_scale_ascending)[4:16]

# the scale pattern:
# root, whole step, whole step, half step, whole step, whole step, whole step, half step
key_steps = [2, 2, 1, 2, 2, 2]  # on the guitar, a whole step is two frets
major_keys = []
for root in scale_from_e:
    three_octaves = scale_from_e * 3
    steps_from_root = three_octaves.index(root)
    major_scale = [root]
    # construct the unique notes in the scale
    for step in key_steps:
        steps_from_root += step
        major_scale.append(three_octaves[steps_from_root])
        
    # span the scale across 3 octaves
    major_keys.append(major_scale * 2 + [root])

Drop the scales into Pandas for the looks

Writing my list of lists to a pandas dataframe and then writing that dataframe out in a jupyter notebook makes everything look nice. More importantly, I can use the style function in pandas to highlight the relative minor scales of each major scale:

df_major_keys = pd.DataFrame(major_keys)

# use this function to highlight the relative minor scales in orange
def highlight_natural_minor(data):
    df = data.copy()
    df.iloc[:,5:13] = 'background-color: orange'
    return df

df_major_keys.style.apply(highlight_natural_minor, axis=None)

…and here’s my handy major/minor scale cheatsheet:

Column 0 is the tonic/root of the major scale while columns 5 through 12 represent the relative minor scale of that major. So we can see that that the E major scale contains the C# minor scale. For example, Ozzy’s Crazy Train apparently moves between A major and F# minor scales which sound just great together–assuming you ignore Ozzy’s personal eccentricities.

So here’s a cool way to merge my interests in music and Python and Pandas into one large mash of goodness.