import pandas as pd
from matplotlib import pyplot as plt

SLO_PERIOD = 28
EBP = 2 # percent
ALERTING_WIN = 1

df = pd.read_csv('sav_2013_2017.csv', parse_dates=['date'])

# aviod divide by zero
df['hits'] += 1 

# add constant column for plotting
df['static burn rate'] = (24 * SLO_PERIOD) / ALERTING_WIN * (EBP / 100)

# calculate dynamic burn rate
df['total_hits_last_28_days']= df.hits.rolling(24 * SLO_PERIOD).sum()
df['dynamic burn rate'] = df['total_hits_last_28_days'] / (df['hits']) * (EBP / 100)

# sample
idx = 36984
df_sample = df[idx:idx+96] # 96 hours

# plot
fig, ax = plt.subplots(figsize=(16, 5))
df_sample.plot(x='date',y='hits', ax=ax, logy=True)
df_sample.plot(x='date',y='dynamic burn rate', ax=ax, logy=True)
df_sample.plot(x='date',y='static burn rate', ax=ax, logy=True, linestyle='--')
ax.grid()