Python pandas.compat.next() Examples

def read(self, nrows=None):
        nrows = _validate_integer('nrows', nrows)
        ret = self._engine.read(nrows)

        # May alter columns / col_dict
        index, columns, col_dict = self._create_index(ret)

        if index is None:
            if col_dict:
                # Any column is actually fine:
                new_rows = len(compat.next(compat.itervalues(col_dict)))
                index = RangeIndex(self._currow, self._currow + new_rows)
            else:
                new_rows = 0
        else:
            new_rows = len(index)

        df = DataFrame(col_dict, columns=columns, index=index)

        self._currow += new_rows

        if self.squeeze and len(df.columns) == 1:
            return df[df.columns[0]].copy()
        return df 

def _check_file_or_buffer(self, f, engine):
        # see gh-16530
        if is_file_like(f):
            next_attr = "__next__" if PY3 else "next"

            # The C engine doesn't need the file-like to have the "next" or
            # "__next__" attribute. However, the Python engine explicitly calls
            # "next(...)" when iterating through such an object, meaning it
            # needs to have that attribute ("next" for Python 2.x, "__next__"
            # for Python 3.x)
            if engine != "c" and not hasattr(f, next_attr):
                msg = ("The 'python' engine cannot iterate "
                       "through this file buffer.")
                raise ValueError(msg)

        return engine 

def _check_file_or_buffer(self, f, engine):
        # see gh-16530
        if is_file_like(f):
            next_attr = "__next__" if PY3 else "next"

            # The C engine doesn't need the file-like to have the "next" or
            # "__next__" attribute. However, the Python engine explicitly calls
            # "next(...)" when iterating through such an object, meaning it
            # needs to have that attribute ("next" for Python 2.x, "__next__"
            # for Python 3.x)
            if engine != "c" and not hasattr(f, next_attr):
                msg = ("The 'python' engine cannot iterate "
                       "through this file buffer.")
                raise ValueError(msg)

        return engine 

def _check_file_or_buffer(self, f, engine):
        # see gh-16530
        if is_file_like(f):
            next_attr = "__next__" if PY3 else "next"

            # The C engine doesn't need the file-like to have the "next" or
            # "__next__" attribute. However, the Python engine explicitly calls
            # "next(...)" when iterating through such an object, meaning it
            # needs to have that attribute ("next" for Python 2.x, "__next__"
            # for Python 3.x)
            if engine != "c" and not hasattr(f, next_attr):
                msg = ("The 'python' engine cannot iterate "
                       "through this file buffer.")
                raise ValueError(msg)

        return engine 

def _check_file_or_buffer(self, f, engine):
        # see gh-16530
        if is_file_like(f):
            next_attr = "__next__" if PY3 else "next"

            # The C engine doesn't need the file-like to have the "next" or
            # "__next__" attribute. However, the Python engine explicitly calls
            # "next(...)" when iterating through such an object, meaning it
            # needs to have that attribute ("next" for Python 2.x, "__next__"
            # for Python 3.x)
            if engine != "c" and not hasattr(f, next_attr):
                msg = ("The 'python' engine cannot iterate "
                       "through this file buffer.")
                raise ValueError(msg)

        return engine 

def _check_file_or_buffer(self, f, engine):
        # see gh-16530
        if is_file_like(f):
            next_attr = "__next__" if PY3 else "next"

            # The C engine doesn't need the file-like to have the "next" or
            # "__next__" attribute. However, the Python engine explicitly calls
            # "next(...)" when iterating through such an object, meaning it
            # needs to have that attribute ("next" for Python 2.x, "__next__"
            # for Python 3.x)
            if engine != "c" and not hasattr(f, next_attr):
                msg = ("The 'python' engine cannot iterate "
                       "through this file buffer.")
                raise ValueError(msg)

        return engine 

def read(self, nrows=None):
        nrows = _validate_integer('nrows', nrows)
        ret = self._engine.read(nrows)

        # May alter columns / col_dict
        index, columns, col_dict = self._create_index(ret)

        if index is None:
            if col_dict:
                # Any column is actually fine:
                new_rows = len(compat.next(compat.itervalues(col_dict)))
                index = RangeIndex(self._currow, self._currow + new_rows)
            else:
                new_rows = 0
        else:
            new_rows = len(index)

        df = DataFrame(col_dict, columns=columns, index=index)

        self._currow += new_rows

        if self.squeeze and len(df.columns) == 1:
            return df[df.columns[0]].copy()
        return df 

def _next_iter_line(self, row_num):
        """
        Wrapper around iterating through `self.data` (CSV source).

        When a CSV error is raised, we check for specific
        error messages that allow us to customize the
        error message displayed to the user.

        Parameters
        ----------
        row_num : The row number of the line being parsed.
        """

        try:
            return next(self.data)
        except csv.Error as e:
            if self.warn_bad_lines or self.error_bad_lines:
                msg = str(e)

                if 'NULL byte' in msg:
                    msg = ('NULL byte detected. This byte '
                           'cannot be processed in Python\'s '
                           'native csv library at the moment, '
                           'so please pass in engine=\'c\' instead')
                elif 'newline inside string' in msg:
                    msg = ('EOF inside string starting with '
                           'line ' + str(row_num))

                if self.skipfooter > 0:
                    reason = ('Error could possibly be due to '
                              'parsing errors in the skipped footer rows '
                              '(the skipfooter keyword is only applied '
                              'after Python\'s csv library has parsed '
                              'all rows).')
                    msg += '. ' + reason

                self._alert_malformed(msg, row_num)
            return None 

def read(self, nrows=None):
        if nrows is not None:
            if self.options.get('skipfooter'):
                raise ValueError('skipfooter not supported for iteration')

        ret = self._engine.read(nrows)

        if self.options.get('as_recarray'):
            return ret

        # May alter columns / col_dict
        index, columns, col_dict = self._create_index(ret)

        if index is None:
            if col_dict:
                # Any column is actually fine:
                new_rows = len(compat.next(compat.itervalues(col_dict)))
                index = RangeIndex(self._currow, self._currow + new_rows)
            else:
                new_rows = 0
        else:
            new_rows = len(index)

        df = DataFrame(col_dict, columns=columns, index=index)

        self._currow += new_rows

        if self.squeeze and len(df.columns) == 1:
            return df[df.columns[0]].copy()
        return df 

def _next_iter_line(self, row_num):
        """
        Wrapper around iterating through `self.data` (CSV source).

        When a CSV error is raised, we check for specific
        error messages that allow us to customize the
        error message displayed to the user.

        Parameters
        ----------
        row_num : The row number of the line being parsed.
        """

        try:
            return next(self.data)
        except csv.Error as e:
            if self.warn_bad_lines or self.error_bad_lines:
                msg = str(e)

                if 'NULL byte' in msg:
                    msg = ('NULL byte detected. This byte '
                           'cannot be processed in Python\'s '
                           'native csv library at the moment, '
                           'so please pass in engine=\'c\' instead')
                elif 'newline inside string' in msg:
                    msg = ('EOF inside string starting with '
                           'line ' + str(row_num))

                if self.skipfooter > 0:
                    reason = ('Error could possibly be due to '
                              'parsing errors in the skipped footer rows '
                              '(the skipfooter keyword is only applied '
                              'after Python\'s csv library has parsed '
                              'all rows).')
                    msg += '. ' + reason

                self._alert_malformed(msg, row_num)
            return None 

def read(self, nrows=None):
        if nrows is not None:
            if self.options.get('skipfooter'):
                raise ValueError('skipfooter not supported for iteration')

        ret = self._engine.read(nrows)

        if self.options.get('as_recarray'):
            return ret

        # May alter columns / col_dict
        index, columns, col_dict = self._create_index(ret)

        if index is None:
            if col_dict:
                # Any column is actually fine:
                new_rows = len(compat.next(compat.itervalues(col_dict)))
                index = RangeIndex(self._currow, self._currow + new_rows)
            else:
                new_rows = 0
        else:
            new_rows = len(index)

        df = DataFrame(col_dict, columns=columns, index=index)

        self._currow += new_rows

        if self.squeeze and len(df.columns) == 1:
            return df[df.columns[0]].copy()
        return df 

def _next_iter_line(self, row_num):
        """
        Wrapper around iterating through `self.data` (CSV source).

        When a CSV error is raised, we check for specific
        error messages that allow us to customize the
        error message displayed to the user.

        Parameters
        ----------
        row_num : The row number of the line being parsed.
        """

        try:
            return next(self.data)
        except csv.Error as e:
            if self.warn_bad_lines or self.error_bad_lines:
                msg = str(e)

                if 'NULL byte' in msg:
                    msg = ('NULL byte detected. This byte '
                           'cannot be processed in Python\'s '
                           'native csv library at the moment, '
                           'so please pass in engine=\'c\' instead')

                if self.skipfooter > 0:
                    reason = ('Error could possibly be due to '
                              'parsing errors in the skipped footer rows '
                              '(the skipfooter keyword is only applied '
                              'after Python\'s csv library has parsed '
                              'all rows).')
                    msg += '. ' + reason

                self._alert_malformed(msg, row_num)
            return None 

def read(self, rows=None):
        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

        columns = list(self.orig_names)
        if not len(content):  # pragma: no cover
            # DataFrame with the right metadata, even though it's length 0
            names = self._maybe_dedup_names(self.orig_names)
            index, columns, col_dict = _get_empty_meta(
                names, self.index_col, self.index_names, self.dtype)
            columns = self._maybe_make_multi_index_columns(
                columns, self.col_names)
            return index, columns, col_dict

        # handle new style for names in index
        count_empty_content_vals = count_empty_vals(content[0])
        indexnamerow = None
        if self.has_index_names and count_empty_content_vals == len(columns):
            indexnamerow = content[0]
            content = content[1:]

        alldata = self._rows_to_cols(content)
        data = self._exclude_implicit_index(alldata)

        columns = self._maybe_dedup_names(self.columns)
        columns, data = self._do_date_conversions(columns, data)

        data = self._convert_data(data)
        index, columns = self._make_index(data, alldata, columns, indexnamerow)

        return index, columns, data 

def _next_iter_line(self, row_num):
        """
        Wrapper around iterating through `self.data` (CSV source).

        When a CSV error is raised, we check for specific
        error messages that allow us to customize the
        error message displayed to the user.

        Parameters
        ----------
        row_num : The row number of the line being parsed.
        """

        try:
            return next(self.data)
        except csv.Error as e:
            if self.warn_bad_lines or self.error_bad_lines:
                msg = str(e)

                if 'NULL byte' in msg:
                    msg = ('NULL byte detected. This byte '
                           'cannot be processed in Python\'s '
                           'native csv library at the moment, '
                           'so please pass in engine=\'c\' instead')
                elif 'newline inside string' in msg:
                    msg = ('EOF inside string starting with '
                           'line ' + str(row_num))

                if self.skipfooter > 0:
                    reason = ('Error could possibly be due to '
                              'parsing errors in the skipped footer rows '
                              '(the skipfooter keyword is only applied '
                              'after Python\'s csv library has parsed '
                              'all rows).')
                    msg += '. ' + reason

                self._alert_malformed(msg, row_num)
            return None 

def read(self, rows=None):
        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

        columns = list(self.orig_names)
        if not len(content):  # pragma: no cover
            # DataFrame with the right metadata, even though it's length 0
            names = self._maybe_dedup_names(self.orig_names)
            index, columns, col_dict = _get_empty_meta(
                names, self.index_col, self.index_names, self.dtype)
            columns = self._maybe_make_multi_index_columns(
                columns, self.col_names)
            return index, columns, col_dict

        # handle new style for names in index
        count_empty_content_vals = count_empty_vals(content[0])
        indexnamerow = None
        if self.has_index_names and count_empty_content_vals == len(columns):
            indexnamerow = content[0]
            content = content[1:]

        alldata = self._rows_to_cols(content)
        data = self._exclude_implicit_index(alldata)

        columns = self._maybe_dedup_names(self.columns)
        columns, data = self._do_date_conversions(columns, data)

        data = self._convert_data(data)
        index, columns = self._make_index(data, alldata, columns, indexnamerow)

        return index, columns, data 

def read(self, nrows=None):
        nrows = _validate_integer('nrows', nrows)

        if nrows is not None:
            if self.options.get('skipfooter'):
                raise ValueError('skipfooter not supported for iteration')

        ret = self._engine.read(nrows)

        # May alter columns / col_dict
        index, columns, col_dict = self._create_index(ret)

        if index is None:
            if col_dict:
                # Any column is actually fine:
                new_rows = len(compat.next(compat.itervalues(col_dict)))
                index = RangeIndex(self._currow, self._currow + new_rows)
            else:
                new_rows = 0
        else:
            new_rows = len(index)

        df = DataFrame(col_dict, columns=columns, index=index)

        self._currow += new_rows

        if self.squeeze and len(df.columns) == 1:
            return df[df.columns[0]].copy()
        return df 

def _next_iter_line(self, row_num):
        """
        Wrapper around iterating through `self.data` (CSV source).

        When a CSV error is raised, we check for specific
        error messages that allow us to customize the
        error message displayed to the user.

        Parameters
        ----------
        row_num : The row number of the line being parsed.
        """

        try:
            return next(self.data)
        except csv.Error as e:
            if self.warn_bad_lines or self.error_bad_lines:
                msg = str(e)

                if 'NULL byte' in msg:
                    msg = ('NULL byte detected. This byte '
                           'cannot be processed in Python\'s '
                           'native csv library at the moment, '
                           'so please pass in engine=\'c\' instead')

                if self.skipfooter > 0:
                    reason = ('Error could possibly be due to '
                              'parsing errors in the skipped footer rows '
                              '(the skipfooter keyword is only applied '
                              'after Python\'s csv library has parsed '
                              'all rows).')
                    msg += '. ' + reason

                self._alert_malformed(msg, row_num)
            return None 

def read(self, rows=None):
        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

        columns = list(self.orig_names)
        if not len(content):  # pragma: no cover
            # DataFrame with the right metadata, even though it's length 0
            names = self._maybe_dedup_names(self.orig_names)
            index, columns, col_dict = _get_empty_meta(
                names, self.index_col, self.index_names, self.dtype)
            columns = self._maybe_make_multi_index_columns(
                columns, self.col_names)
            return index, columns, col_dict

        # handle new style for names in index
        count_empty_content_vals = count_empty_vals(content[0])
        indexnamerow = None
        if self.has_index_names and count_empty_content_vals == len(columns):
            indexnamerow = content[0]
            content = content[1:]

        alldata = self._rows_to_cols(content)
        data = self._exclude_implicit_index(alldata)

        columns = self._maybe_dedup_names(self.columns)
        columns, data = self._do_date_conversions(columns, data)

        data = self._convert_data(data)
        index, columns = self._make_index(data, alldata, columns, indexnamerow)

        return index, columns, data 

def _next_line(self):
        if isinstance(self.data, list):
            while self.skipfunc(self.pos):
                self.pos += 1

            while True:
                try:
                    line = self._check_comments([self.data[self.pos]])[0]
                    self.pos += 1
                    # either uncommented or blank to begin with
                    if (not self.skip_blank_lines and
                            (self._is_line_empty(
                                self.data[self.pos - 1]) or line)):
                        break
                    elif self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])
                        if ret:
                            line = ret[0]
                            break
                except IndexError:
                    raise StopIteration
        else:
            while self.skipfunc(self.pos):
                self.pos += 1
                next(self.data)

            while True:
                orig_line = self._next_iter_line(row_num=self.pos + 1)
                self.pos += 1

                if orig_line is not None:
                    line = self._check_comments([orig_line])[0]

                    if self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])

                        if ret:
                            line = ret[0]
                            break
                    elif self._is_line_empty(orig_line) or line:
                        break

        # This was the first line of the file,
        # which could contain the BOM at the
        # beginning of it.
        if self.pos == 1:
            line = self._check_for_bom(line)

        self.line_pos += 1
        self.buf.append(line)
        return line 

def _next_line(self):
        if isinstance(self.data, list):
            while self.skipfunc(self.pos):
                self.pos += 1

            while True:
                try:
                    line = self._check_comments([self.data[self.pos]])[0]
                    self.pos += 1
                    # either uncommented or blank to begin with
                    if (not self.skip_blank_lines and
                            (self._is_line_empty(
                                self.data[self.pos - 1]) or line)):
                        break
                    elif self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])
                        if ret:
                            line = ret[0]
                            break
                except IndexError:
                    raise StopIteration
        else:
            while self.skipfunc(self.pos):
                self.pos += 1
                next(self.data)

            while True:
                orig_line = self._next_iter_line(row_num=self.pos + 1)
                self.pos += 1

                if orig_line is not None:
                    line = self._check_comments([orig_line])[0]

                    if self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])

                        if ret:
                            line = ret[0]
                            break
                    elif self._is_line_empty(orig_line) or line:
                        break

        # This was the first line of the file,
        # which could contain the BOM at the
        # beginning of it.
        if self.pos == 1:
            line = self._check_for_bom(line)

        self.line_pos += 1
        self.buf.append(line)
        return line 

def read(self, rows=None):
        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

        columns = list(self.orig_names)
        if not len(content):  # pragma: no cover
            # DataFrame with the right metadata, even though it's length 0
            names = self._maybe_dedup_names(self.orig_names)
            index, columns, col_dict = _get_empty_meta(
                names, self.index_col, self.index_names, self.dtype)
            columns = self._maybe_make_multi_index_columns(
                columns, self.col_names)
            return index, columns, col_dict

        # handle new style for names in index
        count_empty_content_vals = count_empty_vals(content[0])
        indexnamerow = None
        if self.has_index_names and count_empty_content_vals == len(columns):
            indexnamerow = content[0]
            content = content[1:]

        alldata = self._rows_to_cols(content)
        data = self._exclude_implicit_index(alldata)

        columns = self._maybe_dedup_names(self.columns)
        columns, data = self._do_date_conversions(columns, data)

        data = self._convert_data(data)
        if self.as_recarray:
            return self._to_recarray(data, columns)

        index, columns = self._make_index(data, alldata, columns, indexnamerow)

        return index, columns, data 

def _next_line(self):
        if isinstance(self.data, list):
            while self.skipfunc(self.pos):
                self.pos += 1

            while True:
                try:
                    line = self._check_comments([self.data[self.pos]])[0]
                    self.pos += 1
                    # either uncommented or blank to begin with
                    if (not self.skip_blank_lines and
                            (self._is_line_empty(
                                self.data[self.pos - 1]) or line)):
                        break
                    elif self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])
                        if ret:
                            line = ret[0]
                            break
                except IndexError:
                    raise StopIteration
        else:
            while self.skipfunc(self.pos):
                self.pos += 1
                next(self.data)

            while True:
                orig_line = self._next_iter_line(row_num=self.pos + 1)
                self.pos += 1

                if orig_line is not None:
                    line = self._check_comments([orig_line])[0]

                    if self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])

                        if ret:
                            line = ret[0]
                            break
                    elif self._is_line_empty(orig_line) or line:
                        break

        # This was the first line of the file,
        # which could contain the BOM at the
        # beginning of it.
        if self.pos == 1:
            line = self._check_for_bom(line)

        self.line_pos += 1
        self.buf.append(line)
        return line 

def _next_line(self):
        if isinstance(self.data, list):
            while self.skipfunc(self.pos):
                self.pos += 1

            while True:
                try:
                    line = self._check_comments([self.data[self.pos]])[0]
                    self.pos += 1
                    # either uncommented or blank to begin with
                    if (not self.skip_blank_lines and
                            (self._is_line_empty(
                                self.data[self.pos - 1]) or line)):
                        break
                    elif self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])
                        if ret:
                            line = ret[0]
                            break
                except IndexError:
                    raise StopIteration
        else:
            while self.skipfunc(self.pos):
                self.pos += 1
                next(self.data)

            while True:
                orig_line = self._next_iter_line(row_num=self.pos + 1)
                self.pos += 1

                if orig_line is not None:
                    line = self._check_comments([orig_line])[0]

                    if self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])

                        if ret:
                            line = ret[0]
                            break
                    elif self._is_line_empty(orig_line) or line:
                        break

        # This was the first line of the file,
        # which could contain the BOM at the
        # beginning of it.
        if self.pos == 1:
            line = self._check_for_bom(line)

        self.line_pos += 1
        self.buf.append(line)
        return line 

def read(self, rows=None):
        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

        columns = list(self.orig_names)
        if not len(content):  # pragma: no cover
            # DataFrame with the right metadata, even though it's length 0
            names = self._maybe_dedup_names(self.orig_names)
            index, columns, col_dict = _get_empty_meta(
                names, self.index_col, self.index_names, self.dtype)
            columns = self._maybe_make_multi_index_columns(
                columns, self.col_names)
            return index, columns, col_dict

        # handle new style for names in index
        count_empty_content_vals = count_empty_vals(content[0])
        indexnamerow = None
        if self.has_index_names and count_empty_content_vals == len(columns):
            indexnamerow = content[0]
            content = content[1:]

        alldata = self._rows_to_cols(content)
        data = self._exclude_implicit_index(alldata)

        columns = self._maybe_dedup_names(self.columns)
        columns, data = self._do_date_conversions(columns, data)

        data = self._convert_data(data)
        if self.as_recarray:
            return self._to_recarray(data, columns)

        index, columns = self._make_index(data, alldata, columns, indexnamerow)

        return index, columns, data 

def _next_line(self):
        if isinstance(self.data, list):
            while self.skipfunc(self.pos):
                self.pos += 1

            while True:
                try:
                    line = self._check_comments([self.data[self.pos]])[0]
                    self.pos += 1
                    # either uncommented or blank to begin with
                    if (not self.skip_blank_lines and
                            (self._is_line_empty(
                                self.data[self.pos - 1]) or line)):
                        break
                    elif self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])
                        if ret:
                            line = ret[0]
                            break
                except IndexError:
                    raise StopIteration
        else:
            while self.skipfunc(self.pos):
                self.pos += 1
                next(self.data)

            while True:
                orig_line = self._next_iter_line(row_num=self.pos + 1)
                self.pos += 1

                if orig_line is not None:
                    line = self._check_comments([orig_line])[0]

                    if self.skip_blank_lines:
                        ret = self._remove_empty_lines([line])

                        if ret:
                            line = ret[0]
                            break
                    elif self._is_line_empty(orig_line) or line:
                        break

        # This was the first line of the file,
        # which could contain the BOM at the
        # beginning of it.
        if self.pos == 1:
            line = self._check_for_bom(line)

        self.line_pos += 1
        self.buf.append(line)
        return line