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本文整理汇总了Python中pandas.core.index.Index._verify_integrity方法的典型用法代码示例。如果您正苦于以下问题：Python Index._verify_integrity方法的具体用法？Python Index._verify_integrity怎么用？Python Index._verify_integrity使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pandas.core.index.Index的用法示例。 在下文中一共展示了Index._verify_integrity方法的8个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。 示例1: rename_axis # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] def rename_axis(self, mapper, axis=1): new_axis = Index([mapper(x) for x in self.axes[axis]]) new_axis._verify_integrity() new_axes = list(self.axes) new_axes[axis] = new_axis return BlockManager(self.blocks, new_axes)开发者ID:mattias-lundell，项目名称:pandas，代码行数:9，代码来源:internals.py 示例2: rename_items # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] def rename_items(self, mapper, copydata=True): new_items = Index([mapper(x) for x in self.items]) new_items._verify_integrity() new_blocks = [] for block in self.blocks: newb = block.copy(deep=copydata) newb.set_ref_items(new_items, maybe_rename=True) new_blocks.append(newb) new_axes = list(self.axes) new_axes[0] = new_items return BlockManager(new_blocks, new_axes)开发者ID:mattias-lundell，项目名称:pandas，代码行数:14，代码来源:internals.py 示例3: append # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] def append(self, other): """ Concatenate two Series. The indices should not overlap Parameters ---------- other : Series Returns ------- y : Series """ new_index = np.concatenate((self.index, other.index)) new_index = Index(new_index) new_index._verify_integrity() new_values = np.concatenate((self, other)) return Series(new_values, index=new_index)开发者ID:timClicks，项目名称:pandas，代码行数:20，代码来源:series.py 示例4: get_chunk # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] def get_chunk(self, rows=None): if rows is not None and self.skip_footer: print "skip_footer not supported for iteration" try: content = self._get_lines(rows) except StopIteration: if self._first_chunk: content = [] else: raise # done with first read, next time raise StopIteration self._first_chunk = False if len(content) == 0: # pragma: no cover if self.index_col is not None: if np.isscalar(self.index_col): index = Index([], name=self.index_name) else: index = MultiIndex.from_arrays([[]] * len(self.index_col), names=self.index_name) else: index = Index([]) return DataFrame(index=index, columns=self.columns) zipped_content = list(lib.to_object_array(content).T) # no index column specified, so infer that's what is wanted if self.index_col is not None: if np.isscalar(self.index_col): index = zipped_content.pop(self.index_col) else: # given a list of index index = [] for idx in self.index_col: index.append(zipped_content[idx]) # remove index items from content and columns, don't pop in loop for i in reversed(sorted(self.index_col)): zipped_content.pop(i) if np.isscalar(self.index_col): if self.parse_dates: index = lib.try_parse_dates(index, parser=self.date_parser) index = Index(_convert_types(index, self.na_values), name=self.index_name) else: arrays = [] for arr in index: if self.parse_dates: arr = lib.try_parse_dates(arr, parser=self.date_parser) arrays.append(_convert_types(arr, self.na_values)) index = MultiIndex.from_arrays(arrays, names=self.index_name) else: index = Index(np.arange(len(content))) if not index._verify_integrity(): dups = index._get_duplicates() raise Exception("Index has duplicates: %s" % str(dups)) if len(self.columns) != len(zipped_content): raise Exception("wrong number of columns") data = dict((k, v) for k, v in zip(self.columns, zipped_content)) # apply converters for col, f in self.converters.iteritems(): if isinstance(col, int) and col not in self.columns: col = self.columns[col] data[col] = np.vectorize(f)(data[col]) data = _convert_to_ndarrays(data, self.na_values) return DataFrame(data=data, columns=self.columns, index=index)开发者ID:ralphbean，项目名称:pandas，代码行数:74，代码来源:parsers.py 示例5: test_duplicates # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] def test_duplicates(self): idx = Index([0, 0, 0]) self.assert_(not idx._verify_integrity()) self.assertRaises(Exception, getattr, idx, 'indexMap')开发者ID:c0ldlimit，项目名称:pandas，代码行数:6，代码来源:test_index.py 示例6: get_chunk # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] def get_chunk(self, rows=None): if rows is not None and self.skip_footer: raise ValueError('skip_footer not supported for iteration') try: content = self._get_lines(rows) except StopIteration: if self._first_chunk: content = [] else: raise # done with first read, next time raise StopIteration self._first_chunk = False if len(content) == 0: # pragma: no cover if self.index_col is not None: if np.isscalar(self.index_col): index = Index([], name=self.index_name) else: index = MultiIndex.from_arrays([[]] * len(self.index_col), names=self.index_name) else: index = Index([]) return DataFrame(index=index, columns=self.columns) zipped_content = list(lib.to_object_array(content).T) # no index column specified, so infer that's what is wanted if self.index_col is not None: if np.isscalar(self.index_col): index = zipped_content.pop(self.index_col) else: # given a list of index index = [] for idx in self.index_col: index.append(zipped_content[idx]) # remove index items from content and columns, don't pop in loop for i in reversed(sorted(self.index_col)): zipped_content.pop(i) if np.isscalar(self.index_col): if self.parse_dates: index = lib.try_parse_dates(index, parser=self.date_parser) index, na_count = _convert_types(index, self.na_values) index = Index(index, name=self.index_name) if self.verbose and na_count: print 'Found %d NA values in the index' % na_count else: arrays = [] for arr in index: if self.parse_dates: arr = lib.try_parse_dates(arr, parser=self.date_parser) arr, _ = _convert_types(arr, self.na_values) arrays.append(arr) index = MultiIndex.from_arrays(arrays, names=self.index_name) else: index = Index(np.arange(len(content))) if not index._verify_integrity(): dups = index.get_duplicates() idx_str = 'Index' if not self.implicit_idx else 'Implicit index' err_msg = ('%s (columns %s) have duplicate values %s' % (idx_str, self.index_col, str(dups))) raise Exception(err_msg) if len(self.columns) != len(zipped_content): raise Exception('wrong number of columns') data = dict((k, v) for k, v in izip(self.columns, zipped_content)) # apply converters for col, f in self.converters.iteritems(): if isinstance(col, int) and col not in self.columns: col = self.columns[col] data[col] = lib.map_infer(data[col], f) data = _convert_to_ndarrays(data, self.na_values, self.verbose) return DataFrame(data=data, columns=self.columns, index=index)开发者ID:smc77，项目名称:pandas，代码行数:82，代码来源:parsers.py 示例7: _simple_parser # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] #.........这里部分代码省略......... columns.append('Unnamed: %d' % i) else: columns.append(c) content = lines[header+1:] counts = {} for i, col in enumerate(columns): cur_count = counts.get(col, 0) if cur_count > 0: columns[i] = '%s.%d' % (col, cur_count) counts[col] = cur_count + 1 else: ncols = len(lines[0]) if not colNames: columns = ['X.%d' % (i + 1) for i in range(ncols)] else: assert(len(colNames) == ncols) columns = colNames content = lines if len(content) == 0: # pragma: no cover if index_col is not None: if np.isscalar(index_col): index = Index([], name=columns.pop(index_col)) else: cp_cols = list(columns) names = [] for i in index_col: name = cp_cols[i] columns.remove(name) names.append(name) index = MultiIndex.fromarrays([[]] * len(index_col), names=names) else: index = Index([]) return DataFrame(index=index, columns=columns) # common NA values # no longer excluding inf representations # '1.#INF','-1.#INF', '1.#INF000000', NA_VALUES = set(['-1.#IND', '1.#QNAN', '1.#IND', '-1.#QNAN', '#N/A N/A', 'NA', '#NA', 'NULL', 'NaN', 'nan', '']) if na_values is None: na_values = NA_VALUES else: na_values = set(list(na_values)) | NA_VALUES zipped_content = list(lib.to_object_array(content).T) if index_col is None and len(content[0]) == len(columns) + 1: index_col = 0 # no index column specified, so infer that's what is wanted if index_col is not None: if np.isscalar(index_col): index = zipped_content.pop(index_col) if len(content[0]) == len(columns) + 1: name = None else: name = columns.pop(index_col) else: # given a list of index idx_names = [] index = [] for idx in index_col: idx_names.append(columns[idx]) index.append(zipped_content[idx]) #remove index items from content and columns, don't pop in loop for i in range(len(index_col)): columns.remove(idx_names[i]) zipped_content.remove(index[i]) if np.isscalar(index_col): if parse_dates: index = lib.try_parse_dates(index, parser=date_parser) index = Index(_convert_types(index, na_values), name=name) else: arrays = _maybe_convert_int_mindex(index, parse_dates, date_parser) index = MultiIndex.from_arrays(arrays, names=idx_names) else: index = Index(np.arange(len(content))) if not index._verify_integrity(): dups = index._get_duplicates() raise Exception('Index has duplicates: %s' % str(dups)) if len(columns) != len(zipped_content): raise Exception('wrong number of columns') data = dict((k, v) for k, v in zip(columns, zipped_content)) data = _convert_to_ndarrays(data, na_values) return DataFrame(data=data, columns=columns, index=index)开发者ID:ara818，项目名称:pandas，代码行数:104，代码来源:parsers.py 示例8: test_duplicates # 需要导入模块: from pandas.core.index import Index [as 别名] # 或者: from pandas.core.index.Index import _verify_integrity [as 别名] def test_duplicates(self): idx = Index([0, 0, 0]) self.assert_(not idx._verify_integrity())开发者ID:ara818，项目名称:pandas，代码行数:5，代码来源:test_index.py注：本文中的pandas.core.index.Index._verify_integrity方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台，相关代码片段筛选自各路编程大神贡献的开源项目，源码版权归原作者所有，传播和使用请参考对应项目的License；未经允许，请勿转载。 |
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