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# coding: utf-8

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# # Lifelines examples
# ##### Divorce Rates

# In[1]:


from lifelines.estimation import AalenAdditiveFitter
import pandas as pd
import numpy as np
import patsy
get_ipython().run_line_magic('pylab', 'inline')


# In[18]:


data = pd.read_csv('../lifelines/datasets/divorce.dat', sep="\s{2,10}")


# In[19]:


data.head(10)


# In[20]:


df = patsy.dmatrix('heduc + heblack + heblack:mixed + years + mixed + div -1 ', data, return_type='dataframe')


# In[21]:


df.head()


# ## Aalen's Additive Model

# In[24]:


aaf = AalenAdditiveFitter(fit_intercept=True, coef_penalizer=0.5)


# In[25]:


timeline = np.linspace(0, 35, 1000)


# In[26]:


aaf.fit(df, 'years', event_col='div[T.Yes]', timeline=timeline)


# In[27]:


figsize(12.5, 8.5)
aaf.cumulative_hazards_.plot()
plt.legend(loc='upper left')


# ## Cox's Proportional Hazard Model

# In[28]:


from lifelines import CoxPHFitter


# In[37]:


cp = CoxPHFitter(penalizer=0.5)
cp.fit(df, 'years', event_col='div[T.Yes]')


# In[39]:


cp.plot()


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