3190edaefb7b5973a73d19593045df83fd8923df,pymc/examples/ARM12_6.py,,,#,7

Before Change

import pkgutil
from StringIO import StringIO
data = pd.read_csv(StringIO(pkgutil.get_data("pymc.examples", "data/srrs2.dat")))

cty_data = pd.read_csv(StringIO(pkgutil.get_data("pymc.examples", "data/cty.dat")))

data = data[data.state == "MN"]

data["fips"] = data.stfips * 1000 + data.cntyfips
cty_data["fips"] = cty_data.stfips * 1000 + cty_data.ctfips


data["lradon"] = np.log(np.where(data.activity == 0, .1, data.activity))


data = data.merge(cty_data, "inner", on="fips")

unique = data[["fips"]].drop_duplicates()
unique["group"] = np.arange(len(unique))
unique.set_index("fips")
data = data.merge(unique, "inner", on="fips")

obs_means = data.groupby("fips").lradon.mean()
n = len(obs_means)

lradon = np.array(data.lradon)
floor = np.array(data.floor)
group = np.array(data.group)


model = Model()

After Change

from pymc import *
import pandas as pd

data = pd.read_csv(get_data_file("pymc.examples", "data/srrs2.dat"))

cty_data = pd.read_csv(get_data_file("pymc.examples", "data/cty.dat"))

data = data[data.state == "MN"]

data["fips"] = data.stfips * 1000 + data.cntyfips
cty_data["fips"] = cty_data.stfips * 1000 + cty_data.ctfips


data["lradon"] = np.log(np.where(data.activity == 0, .1, data.activity))


data = data.merge(cty_data, "inner", on="fips")

unique = data[["fips"]].drop_duplicates()
unique["group"] = np.arange(len(unique))
unique.set_index("fips")
data = data.merge(unique, "inner", on="fips")

obs_means = data.groupby("fips").lradon.mean()
n = len(obs_means)

lradon = np.array(data.lradon)
floor = np.array(data.floor)
group = np.array(data.group)


model = Model()

Instances