bpm_mean_stdev

import music
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import plotly.express as px

#link between a song's genre and its key + bpm

m = music.get_music()
d = {}

for i in m:
    genre = i['artist']['terms']
    bpm = i['song']['tempo']

    if bpm == 0:
        continue
    elif genre in d:
        d[genre].append(bpm)
    else:
        d[genre] = [bpm]

new_d = {}

for g in d:
    if len(d[g]) >= 131:
        new_d[g] = d[g]

for g in new_d:
    # Currently, executing this code will create a graph of the mean BPM by genre.
    # To create a graph of St. Dev. of BPM by genre, use np.std instead of np.mean in line 32.
    new_d[g] = np.mean(new_d[g])

k = list(new_d.keys())
v = list(new_d.values())

print(len(new_d))

plt.bar(k, v, color = ['black', 'brown', 'purple', 'blue', 'cyan', 'orange', 'red', 'yellow', 'violet', 'green'])
plt.xticks(rotation = 60)
plt.show()