def __repr__(self):
arr_repr = ndarray.__repr__(self)
weights = self._weights
if weights is not None:
weights_repr = repr(weights)
arr_repr += '\nweights=\n{0}'.format(weights_repr)
return arr_repr
def __repr__(self):
"""Clean string representation of a Series"""
if len(self.index) > 500:
return self._make_repr(50)
elif len(self.index) > 0:
return _seriesRepr(self.index, self.values)
else:
return '%s' % ndarray.__repr__(self)
def __repr__(self):
"""Clean string representation of a Series"""
vals = self.values
index = self.index
if len(index) > 500:
head = _seriesRepr(index[:50], vals[:50])
tail = _seriesRepr(index[-50:], vals[-50:])
return head + '\n...\n' + tail + '\nlength: %d' % len(vals)
elif len(index) > 0:
return _seriesRepr(index, vals)
else:
return '%s' % ndarray.__repr__(self)
def __repr__(self):
"""Clean string representation of a Series"""
vals = self.values
index = self.index
if len(index) > 500:
head = _seriesRepr(index[:50], vals[:50])
tail = _seriesRepr(index[-50:], vals[-50:])
return head + '\n...\n' + tail + '\nlength: %d' % len(vals)
elif len(index) > 0:
return _seriesRepr(index, vals)
else:
return '%s' % ndarray.__repr__(self)
def __repr__(self):
return ndarray.__repr__(self)[:-1] + \
",\n freq='%s')" % self.freqstr
def __repr__(self): return "%s\n axis info: %s" % (ndarray.__repr__(self), str(self._info))
def __repr__(self):
return "%s\n axis info: %s" % (ndarray.__repr__(self), str(
self._info))
def __repr__(self):
return ndarray.__repr__(self)[:-1] + \
",\n freq='%s')" % self.freqstr
def __repr__(a):
s = ndarray.__repr__(a).replace(
'\n', '\n' + ' ' * (len(a.__class__.__name__) - len('array')) )
if a.units != dimensionless: s += ' * ' + a.dimensionality.string
return s.replace( 'nan', '...' )
