The basetable timeline

Gevorderde voorspellende analyse 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
Gevorderde voorspellende analyse in Python

The basetable (1)

Gevorderde voorspellende analyse in Python

The basetable (2)

Gevorderde voorspellende analyse in Python

The basetable (3)

Gevorderde voorspellende analyse in Python

The basetable (4)

Gevorderde voorspellende analyse in Python

The timeline (1)

Gevorderde voorspellende analyse in Python

The timeline (2)

Gevorderde voorspellende analyse in Python

The timeline (3)

Gevorderde voorspellende analyse in Python

The timeline (4)

Gevorderde voorspellende analyse in Python

Reconstructing history (1)

Gevorderde voorspellende analyse in Python

Reconstructing history (2)

Gevorderde voorspellende analyse in Python

Reconstructing history (3)

Gevorderde voorspellende analyse in Python

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]
Gevorderde voorspellende analyse in Python

Let's practice!

Gevorderde voorspellende analyse in Python

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