Closed iampatgrady closed 4 years ago
Hi @iampatgrady, thanks for your question.
The type of data in your index should not influence the way you use the library. Suppose you have a pandas data frame df
that looks like this:
df.head()
x1 | x2 | y | |
---|---|---|---|
2018-01-01 | 100.804725 | 110.186868 | 145.878537 |
2018-01-02 | 101.252369 | 110.137887 | 146.963141 |
2018-01-03 | 101.949742 | 110.583246 | 147.882362 |
2018-01-04 | 101.974369 | 111.326806 | 146.473423 |
2018-01-05 | 101.069765 | 111.446466 | 146.067800 |
You can simply use the constructor with a datetime
date object:
from datetime import date
from causal_impact.causal_impact import CausalImpact
ci = CausalImpact(df, date(2018, 10, 28))
ci.run(max_iter=500)
ci.plot()
Let me know if you run into any issues, good luck!
As a user of causal-impact who is unfamiliar with reading code as documentation, is there a way to demonstrate how to run the library using a pandas data frame with a DateTime index?