Python pandas.core.dtypes.generic.ABCMultiIndex() Examples
The following are 17
code examples of pandas.core.dtypes.generic.ABCMultiIndex().
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Example #1
| Source File: excel.py From recruit with Apache License 2.0 | 6 votes |
|
def _format_header_regular(self):
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
if has_aliases or self.header:
coloffset = 0
if self.index:
coloffset = 1
if isinstance(self.df.index, ABCMultiIndex):
coloffset = len(self.df.index[0])
colnames = self.columns
if has_aliases:
if len(self.header) != len(self.columns):
raise ValueError('Writing {cols} cols but got {alias} '
'aliases'.format(cols=len(self.columns),
alias=len(self.header)))
else:
colnames = self.header
for colindex, colname in enumerate(colnames):
yield ExcelCell(self.rowcounter, colindex + coloffset, colname,
self.header_style)
Example #2
| Source File: excel.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
|
def _format_header_regular(self):
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
if has_aliases or self.header:
coloffset = 0
if self.index:
coloffset = 1
if isinstance(self.df.index, ABCMultiIndex):
coloffset = len(self.df.index[0])
colnames = self.columns
if has_aliases:
if len(self.header) != len(self.columns):
raise ValueError('Writing {cols} cols but got {alias} '
'aliases'.format(cols=len(self.columns),
alias=len(self.header)))
else:
colnames = self.header
for colindex, colname in enumerate(colnames):
yield ExcelCell(self.rowcounter, colindex + coloffset, colname,
self.header_style)
Example #3
| Source File: test_generic.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
simplefilter('ignore', FutureWarning)
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
assert isinstance(self.datetime_array, gt.ABCDatetimeArray)
assert not isinstance(self.datetime_index, gt.ABCDatetimeArray)
assert isinstance(self.timedelta_array, gt.ABCTimedeltaArray)
assert not isinstance(self.timedelta_index, gt.ABCTimedeltaArray)
Example #4
| Source File: test_generic.py From twitter-stock-recommendation with MIT License | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
Example #5
| Source File: test_generic.py From elasticintel with GNU General Public License v3.0 | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
Example #6
| Source File: excel.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def _format_regular_rows(self):
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
if has_aliases or self.header:
self.rowcounter += 1
# output index and index_label?
if self.index:
# check aliases
# if list only take first as this is not a MultiIndex
if (self.index_label and
isinstance(self.index_label, (list, tuple, np.ndarray,
Index))):
index_label = self.index_label[0]
# if string good to go
elif self.index_label and isinstance(self.index_label, str):
index_label = self.index_label
else:
index_label = self.df.index.names[0]
if isinstance(self.columns, ABCMultiIndex):
self.rowcounter += 1
if index_label and self.header is not False:
yield ExcelCell(self.rowcounter - 1, 0, index_label,
self.header_style)
# write index_values
index_values = self.df.index
if isinstance(self.df.index, ABCPeriodIndex):
index_values = self.df.index.to_timestamp()
for idx, idxval in enumerate(index_values):
yield ExcelCell(self.rowcounter + idx, 0, idxval,
self.header_style)
coloffset = 1
else:
coloffset = 0
for cell in self._generate_body(coloffset):
yield cell
Example #7
| Source File: excel.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def _format_body(self):
if isinstance(self.df.index, ABCMultiIndex):
return self._format_hierarchical_rows()
else:
return self._format_regular_rows()
Example #8
| Source File: html.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def write_style(self):
# We use the "scoped" attribute here so that the desired
# style properties for the data frame are not then applied
# throughout the entire notebook.
template_first = """\
<style scoped>"""
template_last = """\
</style>"""
template_select = """\
.dataframe %s {
%s: %s;
}"""
element_props = [('tbody tr th:only-of-type',
'vertical-align',
'middle'),
('tbody tr th',
'vertical-align',
'top')]
if isinstance(self.columns, ABCMultiIndex):
element_props.append(('thead tr th',
'text-align',
'left'))
if self.show_row_idx_names:
element_props.append(('thead tr:last-of-type th',
'text-align',
'right'))
else:
element_props.append(('thead th',
'text-align',
'right'))
template_mid = '\n\n'.join(map(lambda t: template_select % t,
element_props))
template = dedent('\n'.join((template_first,
template_mid,
template_last)))
self.write(template)
Example #9
| Source File: html.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
|
def _write_body(self, indent):
self.write('<tbody>', indent)
fmt_values = {i: self.fmt._format_col(i) for i in range(self.ncols)}
# write values
if self.fmt.index and isinstance(self.frame.index, ABCMultiIndex):
self._write_hierarchical_rows(
fmt_values, indent + self.indent_delta)
else:
self._write_regular_rows(
fmt_values, indent + self.indent_delta)
self.write('</tbody>', indent)
Example #10
| Source File: test_generic.py From recruit with Apache License 2.0 | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
simplefilter('ignore', FutureWarning)
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
assert isinstance(self.datetime_array, gt.ABCDatetimeArray)
assert not isinstance(self.datetime_index, gt.ABCDatetimeArray)
assert isinstance(self.timedelta_array, gt.ABCTimedeltaArray)
assert not isinstance(self.timedelta_index, gt.ABCTimedeltaArray)
Example #11
| Source File: test_generic.py From vnpy_crypto with MIT License | 5 votes |
|
def test_abc_types(self):
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndex)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCInt64Index)
assert isinstance(pd.UInt64Index([1, 2, 3]), gt.ABCUInt64Index)
assert isinstance(pd.Float64Index([1, 2, 3]), gt.ABCFloat64Index)
assert isinstance(self.multi_index, gt.ABCMultiIndex)
assert isinstance(self.datetime_index, gt.ABCDatetimeIndex)
assert isinstance(self.timedelta_index, gt.ABCTimedeltaIndex)
assert isinstance(self.period_index, gt.ABCPeriodIndex)
assert isinstance(self.categorical_df.index, gt.ABCCategoricalIndex)
assert isinstance(pd.Index(['a', 'b', 'c']), gt.ABCIndexClass)
assert isinstance(pd.Int64Index([1, 2, 3]), gt.ABCIndexClass)
assert isinstance(pd.Series([1, 2, 3]), gt.ABCSeries)
assert isinstance(self.df, gt.ABCDataFrame)
with catch_warnings(record=True):
assert isinstance(self.df.to_panel(), gt.ABCPanel)
assert isinstance(self.sparse_series, gt.ABCSparseSeries)
assert isinstance(self.sparse_array, gt.ABCSparseArray)
assert isinstance(self.sparse_frame, gt.ABCSparseDataFrame)
assert isinstance(self.categorical, gt.ABCCategorical)
assert isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCPeriod)
assert isinstance(pd.DateOffset(), gt.ABCDateOffset)
assert isinstance(pd.Period('2012', freq='A-DEC').freq,
gt.ABCDateOffset)
assert not isinstance(pd.Period('2012', freq='A-DEC'),
gt.ABCDateOffset)
assert isinstance(pd.Interval(0, 1.5), gt.ABCInterval)
assert not isinstance(pd.Period('2012', freq='A-DEC'), gt.ABCInterval)
Example #12
| Source File: excel.py From recruit with Apache License 2.0 | 5 votes |
|
def _format_regular_rows(self):
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
if has_aliases or self.header:
self.rowcounter += 1
# output index and index_label?
if self.index:
# check aliases
# if list only take first as this is not a MultiIndex
if (self.index_label and
isinstance(self.index_label, (list, tuple, np.ndarray,
Index))):
index_label = self.index_label[0]
# if string good to go
elif self.index_label and isinstance(self.index_label, str):
index_label = self.index_label
else:
index_label = self.df.index.names[0]
if isinstance(self.columns, ABCMultiIndex):
self.rowcounter += 1
if index_label and self.header is not False:
yield ExcelCell(self.rowcounter - 1, 0, index_label,
self.header_style)
# write index_values
index_values = self.df.index
if isinstance(self.df.index, ABCPeriodIndex):
index_values = self.df.index.to_timestamp()
for idx, idxval in enumerate(index_values):
yield ExcelCell(self.rowcounter + idx, 0, idxval,
self.header_style)
coloffset = 1
else:
coloffset = 0
for cell in self._generate_body(coloffset):
yield cell
Example #13
| Source File: excel.py From recruit with Apache License 2.0 | 5 votes |
|
def _format_body(self):
if isinstance(self.df.index, ABCMultiIndex):
return self._format_hierarchical_rows()
else:
return self._format_regular_rows()
Example #14
| Source File: html.py From recruit with Apache License 2.0 | 5 votes |
|
def write_style(self):
# We use the "scoped" attribute here so that the desired
# style properties for the data frame are not then applied
# throughout the entire notebook.
template_first = """\
<style scoped>"""
template_last = """\
</style>"""
template_select = """\
.dataframe %s {
%s: %s;
}"""
element_props = [('tbody tr th:only-of-type',
'vertical-align',
'middle'),
('tbody tr th',
'vertical-align',
'top')]
if isinstance(self.columns, ABCMultiIndex):
element_props.append(('thead tr th',
'text-align',
'left'))
if self.show_row_idx_names:
element_props.append(('thead tr:last-of-type th',
'text-align',
'right'))
else:
element_props.append(('thead th',
'text-align',
'right'))
template_mid = '\n\n'.join(map(lambda t: template_select % t,
element_props))
template = dedent('\n'.join((template_first,
template_mid,
template_last)))
self.write(template)
Example #15
| Source File: html.py From recruit with Apache License 2.0 | 5 votes |
|
def _write_body(self, indent):
self.write('<tbody>', indent)
fmt_values = {i: self.fmt._format_col(i) for i in range(self.ncols)}
# write values
if self.fmt.index and isinstance(self.frame.index, ABCMultiIndex):
self._write_hierarchical_rows(
fmt_values, indent + self.indent_delta)
else:
self._write_regular_rows(
fmt_values, indent + self.indent_delta)
self.write('</tbody>', indent)
Example #16
| Source File: excel.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 4 votes |
|
def _format_header_mi(self):
if self.columns.nlevels > 1:
if not self.index:
raise NotImplementedError("Writing to Excel with MultiIndex"
" columns and no index "
"('index'=False) is not yet "
"implemented.")
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
if not (has_aliases or self.header):
return
columns = self.columns
level_strs = columns.format(sparsify=self.merge_cells, adjoin=False,
names=False)
level_lengths = get_level_lengths(level_strs)
coloffset = 0
lnum = 0
if self.index and isinstance(self.df.index, ABCMultiIndex):
coloffset = len(self.df.index[0]) - 1
if self.merge_cells:
# Format multi-index as a merged cells.
for lnum in range(len(level_lengths)):
name = columns.names[lnum]
yield ExcelCell(lnum, coloffset, name, self.header_style)
for lnum, (spans, levels, level_codes) in enumerate(zip(
level_lengths, columns.levels, columns.codes)):
values = levels.take(level_codes)
for i in spans:
if spans[i] > 1:
yield ExcelCell(lnum, coloffset + i + 1, values[i],
self.header_style, lnum,
coloffset + i + spans[i])
else:
yield ExcelCell(lnum, coloffset + i + 1, values[i],
self.header_style)
else:
# Format in legacy format with dots to indicate levels.
for i, values in enumerate(zip(*level_strs)):
v = ".".join(map(pprint_thing, values))
yield ExcelCell(lnum, coloffset + i + 1, v, self.header_style)
self.rowcounter = lnum
Example #17
| Source File: excel.py From recruit with Apache License 2.0 | 4 votes |
|
def _format_header_mi(self):
if self.columns.nlevels > 1:
if not self.index:
raise NotImplementedError("Writing to Excel with MultiIndex"
" columns and no index "
"('index'=False) is not yet "
"implemented.")
has_aliases = isinstance(self.header, (tuple, list, np.ndarray, Index))
if not (has_aliases or self.header):
return
columns = self.columns
level_strs = columns.format(sparsify=self.merge_cells, adjoin=False,
names=False)
level_lengths = get_level_lengths(level_strs)
coloffset = 0
lnum = 0
if self.index and isinstance(self.df.index, ABCMultiIndex):
coloffset = len(self.df.index[0]) - 1
if self.merge_cells:
# Format multi-index as a merged cells.
for lnum in range(len(level_lengths)):
name = columns.names[lnum]
yield ExcelCell(lnum, coloffset, name, self.header_style)
for lnum, (spans, levels, level_codes) in enumerate(zip(
level_lengths, columns.levels, columns.codes)):
values = levels.take(level_codes)
for i in spans:
if spans[i] > 1:
yield ExcelCell(lnum, coloffset + i + 1, values[i],
self.header_style, lnum,
coloffset + i + spans[i])
else:
yield ExcelCell(lnum, coloffset + i + 1, values[i],
self.header_style)
else:
# Format in legacy format with dots to indicate levels.
for i, values in enumerate(zip(*level_strs)):
v = ".".join(map(pprint_thing, values))
yield ExcelCell(lnum, coloffset + i + 1, v, self.header_style)
self.rowcounter = lnum
