Visual Exploration

Plotly express, great idea:


Matplolib Cours:

I like this:

def plot_cloud_points(df):
    figure = plt.figure(figsize=(20, 5))
    my_cm  = ListedColormap(['#bb0000', '#00FF00'])
    axes = {p : ('age', 'income') if p != "Mortgage"else ('members_in_household', 'loan_accounts') for p in products}
    for product in products:
        ax = plt.subplot(1, len(products), products.index(product)+1)
        ax.set_title(product)
        axe = axes[product]
        plt.xlabel(axe[0])
        plt.ylabel(axe[1])
        ax.scatter(df[axe[0]], df[axe[1]], c=df[product], cmap=my_cm, alpha=0.5)

plot_cloud_points(known_behaviors)     
        

 



Employee Attrition Distribution Stats

linspace


Plotly Bubble 

compcol = "#66ff87"
compname = "IBM"
compdf = df[df['ParentCompany'] == compname] 
generate_all(compdf, compname, compcol)
bars()
createhmap1(compcol)



Plotly Poster

## Business Keywords - IBM
compcol = "#66ff87"