Formative

quantitative reasoning made simple (but not easy)

$pip install formative-ds

example.py

from formative.causal import DAG, IV2SLS
from formative.game import maximin
 
 
# ---- Causal estimation ----
 
dag = DAG()
dag.assume("proximity").causes("education")
dag.assume("ability").causes("education", "income")
dag.assume("education").causes("income")
 
result = IV2SLS(
    dag,
    treatment="education",
    outcome="income",
    instrument="proximity"
).fit(df)
print(result.summary())
 
 
# ---- Game theory ----
 
outcomes = {
    "stocks": {"recession": -20, "stagnation":  5, "growth": 30},
    "bonds":  {"recession":   5, "stagnation":  5, "growth":  7},
    "cash":   {"recession":   2, "stagnation":  2, "growth":  2},
}
result = maximin(outcomes).solve()
print(result)

Documentation PyPI GitHub

Find the right method

Answer a few questions to find the right approach for measuring cause and effect in your situation.

Methods

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