The basetable timeline

Intermediate Predictive Analytics in Python

Nele Verbiest Ph. D.

Senior Data Scientist @PythonPredictions

The predictive modeling process

Foundations of predictive analytics I:

Build predictive models
Evaluate predictive models
Present predictive models to business stakeholders

Foundations of predictive analytics II:

Construct the basetable

The basetable (1)

The basetable (2)

The basetable (3)

The basetable (4)

The timeline (1)

The timeline (2)

The timeline (3)

The timeline (4)

Reconstructing history (1)

Reconstructing history (2)

Reconstructing history (3)

Selecting relevant data in Python

import pandas as pd
gifts = pd.read_csv("gifts.csv")
gifts["date"] = pd.to_datetime(gifts["date"])
print(gifts.head())

   id       date  amount
0   1 2015-10-16    75.0
1   1 2014-02-11   111.0
2   1 2012-03-28    93.0
3   1 2013-12-13   113.0
4   1 2012-01-10    93.0

start_target = datetime(year = 2018, month = 5, day = 1)
end_target = datetime(year = 2018, month = 8, day = 1)

gifts_target = gifts[(gifts["date"]>=start_target) & (gifts["date"]<end_target)]

gifts_pred_variables = gifts[(gifts["date"]<start_target]

Let's practice!

Intermediate Predictive Analytics in Python