"""Pandas DataFrame↔Table conversion helpers"""
import numpy as np
import pandas as pd
from pandas.api.types import (
is_categorical_dtype, is_object_dtype,
is_datetime64_any_dtype, is_numeric_dtype,
)
from Orange.data import (
Table, Domain, DiscreteVariable, StringVariable, TimeVariable,
ContinuousVariable,
)
__all__ = ['table_from_frame', 'table_to_frame']
def table_from_frame(df,class_name, *, force_nominal=False):
"""
Convert pandas.DataFrame to Orange.data.Table
Parameters
----------
df : pandas.DataFrame
force_nominal : boolean
If True, interpret ALL string columns as nominal (DiscreteVariable).
Returns
-------
Table
"""
def _is_discrete(s):
return (is_categorical_dtype(s) or
is_object_dtype(s) and (force_nominal or
s.nunique() < s.size**.666))
def _is_datetime(s):
if is_datetime64_any_dtype(s):
return True
try:
if is_object_dtype(s):
pd.to_datetime(s, infer_datetime_format=True)
return True
except Exception:
pass
return False
if not (df.index.is_integer() and (df.index.is_monotonic_increasing or
df.index.is_monotonic_decreasing)):
df = df.reset_index()
attrs, metas,calss_vars = [], [],[]
X, M = [], []
for name, s in df.items():
name = str(name)
if name == class_name:
discrete = s.astype('category').cat
calss_vars.append(DiscreteVariable(name, discrete.categories.astype(str).tolist()))
X.append(discrete.codes.replace(-1, np.nan).values)
elif _is_discrete(s):
discrete = s.astype('category').cat
attrs.append(DiscreteVariable(name, discrete.categories.astype(str).tolist()))
X.append(discrete.codes.replace(-1, np.nan).values)
elif _is_datetime(s):
tvar = TimeVariable(name)
attrs.append(tvar)
s = pd.to_datetime(s, infer_datetime_format=True)
X.append(s.astype('str').replace('NaT', np.nan).map(tvar.parse).values)
elif is_numeric_dtype(s):
attrs.append(ContinuousVariable(name))
X.append(s.values)
else:
metas.append(StringVariable(name))
M.append(s.values.astype(object))
return Table.from_numpy(Domain(attrs, calss_vars, metas),
np.column_stack(X) if X else np.empty((df.shape[0], 0)),
None,
np.column_stack(M) if M else None)
