revenue_growth.py

from collections import Counter, defaultdict
from pandas import DataFrame, Series
import json
import seaborn
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import FuncFormatter, MaxNLocator
from sklearn.linear_model import LinearRegression

from sklearn.preprocessing import PolynomialFeatures
from sklearn.pipeline import Pipeline


fontsize = 14
fig = plt.figure(figsize=(12,8))
fig.suptitle('Revenue Growth', fontsize=fontsize)


quarters = [18, 20, 24, 28, 33, 38, 44, 51, 59, 65, 72, 82, 87, 96, 101]
guidance = 105
projected = 112

labels = [
    '2014Q2', '2014Q3', '2015Q1', '2015Q3', 
    '2016Q1', '2016Q3', '2017Q1', '2017Q3', 
    '2018Q1', '2018Q3', '2019Q1', '2019Q3'
]

periods = len(quarters) + 3
active_quarters = len(quarters) - 4


growth = (Series(quarters) / Series(quarters).shift(4) - 1) * 100


def plot_growth():
    return growth.plot(kind='line', 
                       label='Actual',
                       alpha=.8,
                       fontsize=fontsize,
                       xlim=[0, periods],
                       ylim=[20, 100])


def plot_trend_line():
    
    X = np.arange(active_quarters).reshape(-1, 1)
    y = growth.dropna().values
    
    model = LinearRegression()
    model.fit(X, y)
    
    nans = growth.values.tolist()[0:4]
    x = nans + list(range(4, periods + 6))
    X_test = [x for x in range(0, periods + 2)]
    X_test = np.array(X_test).reshape(-1, 1)

    y_test = model.predict(X_test).tolist()    
    y = nans + y_test
    plt.plot(x, y,
             alpha=.4,
             label='Trend', 
             color='purple')
    
    


def plot_next_quarter(value, title, color):
    most_recent_revenue = growth.values.tolist()[-1]
    indices = growth.index.tolist()
    nans = growth.values.tolist()[0:4]
    nas = np.repeat(nans[0], len(indices)).tolist()
    projection = (value / quarters[-4] - 1) * 100
    gx = indices + [indices[-1], indices[-1] + 1]
    gy = nas + [most_recent_revenue, projection]
    plt.plot(gx, gy, label=title, alpha=.4, color=color)
    

ax = plot_growth()
plot_trend_line()
plot_next_quarter(guidance, 'Guidance', '#fc0000')
plot_next_quarter(projected, 'Projected', '#3b9626')


## aesthetics
plt.xticks(rotation=45, fontsize=fontsize)
ax.xaxis.set_major_formatter(FuncFormatter(lambda x,y: labels[int(y)]))
ax.xaxis.set_major_locator(MaxNLocator(integer=True))
ax.set_ylabel('Year Over Year (Percent)', fontsize=fontsize)
plt.legend(prop={'size': fontsize})

plt.show()