Now that we have the cuisine averages computed, we can display them in a histogram to get an idea of their spread. We first convert the dictionary to a data frame. Then plot the Rating column of the data frame into a histogram:
import pandas as pdimport numpy as npdf = pd.DataFrame(columns=['Cuisine', 'Rating'])for cuisine in cuisines: df.loc[len(df)]=[cuisine, cuisines[cuisine]]hist, bin_edges = np.histogram(df['Rating'], bins=range(5))import matplotlib.pyplot as pltplt.bar(bin_edges[:-1], hist, width = 1)plt.xlim(min(bin_edges), max(bin_edges))plt.show()
Again, we see a clear mark towards high average values. I had tried to get a better gradient on the data display to no avail.