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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from collections import OrderedDict
from numpy import linspace, isnan
from numpy.testing import assert_equal
from pandas import DataFrame, Series
from json_tricks import dumps, loads
from tests.test_bare import nonpdata
COLUMNS = OrderedDict((
('name', ('Alfa', 'Bravo', 'Charlie', 'Delta', 'Echo', 'Foxtrot', 'Golf',
'Hotel', 'India', 'Juliett',)),
('count', linspace(0, 10, 10, dtype=int)),
('real', linspace(0, 7.5, 10, dtype=float)),
('special', (float('NaN'), float('+inf'), float('-inf'), float('+0'),
float('-0'), 1, 2, 3, 4, 5)),
#todo: other types?
))
def test_pandas_dataframe():
df = DataFrame(COLUMNS, columns=tuple(COLUMNS.keys()))
txt = dumps(df, allow_nan=True)
back = loads(txt)
assert isnan(back.iloc[0, -1])
assert (df.equals(back))
assert (df.dtypes == back.dtypes).all()
df = DataFrame(COLUMNS, columns=tuple(COLUMNS.keys()))
txt = dumps(df, primitives=True, allow_nan=True)
back = loads(txt)
assert isinstance(back, dict)
assert isnan(back['special'][0])
assert all(df.index.values == tuple(back.pop('index')))
for name, col in back.items():
assert name in COLUMNS
assert_equal(list(COLUMNS[name]), col)
def test_pandas_series():
for name, col in COLUMNS.items():
ds = Series(data=col, name=name)
txt = dumps(ds, allow_nan=True)
back = loads(txt)
assert (ds.equals(back))
assert ds.dtype == back.dtype
for name, col in COLUMNS.items():
ds = Series(data=col, name=name)
txt = dumps(ds, primitives=True, allow_nan=True)
back = loads(txt)
assert isinstance(back, dict)
assert_equal(ds.index.values, back['index'])
assert_equal(ds.values, back['data'])
def test_pandas_mixed_with_other_types():
df = DataFrame(COLUMNS, columns=tuple(COLUMNS.keys()))
mixed = dict(
complex=1+42j,
frames=[df, df],
**nonpdata
)
txt = dumps(mixed, allow_nan=True)
back = loads(txt)
assert mixed['frames'][0].equals(back['frames'][0]) and mixed['frames'][1].equals(back['frames'][1])
del mixed['frames'], back['frames'] # cannot compare dataframes with '=='
assert mixed == back
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