def _is_shape_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
shape = _read_required_arg_or_kwarg(args, 0, kwargs, 'shape')
ret_specd['obj'] = "is_shape has no output object"
ret_specd['ndframe'] = "is_shape has no output ndframe"
ret_specd['bool'] = not dfcheck.shape == shape
return _ret_proper_objects(_ret, ret_specd)
def _is_shape_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
shape = _read_required_arg_or_kwarg(args, 0, kwargs, 'shape')
ret_specd['obj'] = "is_shape has no output object"
ret_specd['ndframe'] = "is_shape has no output ndframe"
ret_specd['bool'] = not dfcheck.shape == shape
return _ret_proper_objects(_ret, ret_specd)
def _has_dtypes_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
items = _read_required_arg_or_kwarg(args, 0, kwargs, 'items')
results = {}
dtypes = dfcheck.dtypes
for k, v in items.items():
results[k] = not dtypes[k] == v
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = any(list(results.values()))
return _ret_proper_objects(_ret, ret_specd)
def _within_range_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
items = _read_required_arg_or_kwarg(args, 0, kwargs, 'items')
results = {}
for k, (lower, upper) in items.items():
results[k] = (lower > dfcheck[k]).any() or (upper < dfcheck[k]).any()
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = any(list(results.values()))
return _ret_proper_objects(_ret, ret_specd)
def _within_set_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
items = _read_required_arg_or_kwarg(args, 0, kwargs, 'items')
results = {}
for k, v in items.items():
results[k] = not dfcheck[k].isin(v).all()
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = any(list(results.values()))
return _ret_proper_objects(_ret, ret_specd)
def _has_dtypes_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
items = _read_required_arg_or_kwarg(args, 0, kwargs, 'items')
results = {}
dtypes = dfcheck.dtypes
for k, v in items.items():
results[k] = not dtypes[k] == v
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = any(list(results.values()))
return _ret_proper_objects(_ret, ret_specd)
def _within_range_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
items = _read_required_arg_or_kwarg(args, 0, kwargs, 'items')
results = {}
for k, (lower, upper) in items.items():
results[k] = (lower > dfcheck[k]).any() or (upper < dfcheck[k]).any()
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = any(list(results.values()))
return _ret_proper_objects(_ret, ret_specd)
def _within_set_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
items = _read_required_arg_or_kwarg(args, 0, kwargs, 'items')
results = {}
for k, v in items.items():
results[k] = not dfcheck[k].isin(v).all()
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = any(list(results.values()))
return _ret_proper_objects(_ret, ret_specd)
def _has_in_index_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
orig_obj_to_check = _read_required_arg_or_kwarg(args, 0, kwargs, 'obj')
obj_to_check = orig_obj_to_check
try_ix = _read_arg_or_kwarg(args, 1, kwargs, 'try_ix', False)
try_strftime = _read_arg_or_kwarg(args, 2, kwargs, 'try_strftime', False)
check_na = _read_arg_or_kwarg(args, 3, kwargs, 'check_na', False)
ans = obj_to_check in dfcheck.index
if try_strftime:
try:
obj_to_check = obj_to_check.strftime(try_strftime)
except:
pass
# at this point, if it's in the index, ans will be True
if try_ix:
try:
ans = ans or (len(dfcheck.ix[obj_to_check]) > 0)
except:
pass
# at this point, if it's in the index, or if it's string representation
# is in the index, ans will be True
if check_na:
try:
isna = dfcheck.ix[obj_to_check].isnull()[0]
except:
isna = True
ans = not ((not ans) or isna)
results = {orig_obj_to_check : ans}
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = not ans
return _ret_proper_objects(_ret, ret_specd)
def _has_in_index_ret(dforig, dfcheck, dfderive, *args, **kwargs):
_ret, ret_specd = _pull_out_ret(kwargs, dforig)
orig_obj_to_check = _read_required_arg_or_kwarg(args, 0, kwargs, 'obj')
obj_to_check = orig_obj_to_check
try_ix = _read_arg_or_kwarg(args, 1, kwargs, 'try_ix', False)
try_strftime = _read_arg_or_kwarg(args, 2, kwargs, 'try_strftime', False)
check_na = _read_arg_or_kwarg(args, 3, kwargs, 'check_na', False)
ans = obj_to_check in dfcheck.index
if try_strftime:
try:
obj_to_check = obj_to_check.strftime(try_strftime)
except:
pass
# at this point, if it's in the index, ans will be True
if try_ix:
try:
ans = ans or (len(dfcheck.ix[obj_to_check]) > 0)
except:
pass
# at this point, if it's in the index, or if it's string representation
# is in the index, ans will be True
if check_na:
try:
isna = dfcheck.ix[obj_to_check].isnull()[0]
except:
isna = True
ans = not ((not ans) or isna)
results = {orig_obj_to_check: ans}
ret_specd['obj'] = results
ret_specd['ndframe'] = pd.Series(results)
ret_specd['bool'] = not ans
return _ret_proper_objects(_ret, ret_specd)
