Add a data vectors column.
337495
def append_vector(self, name, vector, _left=False):
        """"""
        if np.issubdtype(vector.dtype, np.integer):
            # determine the length we need
            largest = str(max(vector.max(), vector.min(), key=abs))
            length = max(len(largest), min(7, len(name)))  # how many spaces we need to represent

            if len(name) > length:
                header = name[:length-1] + '.'
            else:
                header = name.rjust(length)

            def f(datum):
                return str(getattr(datum, name)).rjust(length)
        elif np.issubdtype(vector.dtype, np.floating):
            largest = np.format_float_positional(max(vector.max(), vector.min(), key=abs),
                                                 precision=6, trim='0')
            length = max(len(largest), min(7, len(name)))  # how many spaces we need to represent
            if len(name) > length:
                header = name[:length-1] + '.'
            else:
                header = name.rjust(length)

            def f(datum):
                return np.format_float_positional(getattr(datum, name),
                                                  precision=6, trim='0',
                                                  ).rjust(length)
        else:
            length = 7
            if len(name) > length:
                header = name[:length-1] + '.'
            else:
                header = name.rjust(length)

            def f(datum):
                r = repr(getattr(datum, name))
                if len(r) > length:
                    r = r[:length-3] + '...'
                return r.rjust(length)

        self.append(header, f, _left=_left)
459456
def addColumn(self, col, index=None):
        ''
        if col:
            if index is None:
                index = len(self.columns)
            col.sheet = self
            self.columns.insert(index, col)
            return col
714839
function _Vector(dimension, data) {
  if (!dimension || !Number.isInteger(dimension))
    throw new TypeError('Dimension of the array must be an integer.');

  var _values;
  if (!data || data === undefined)
    _values = [];
  else if (!util.isNumberArray(data))
    throw new TypeError('Invalid values for vector.');
  else
    _values = data;

  if (_values.length < dimension) {
    var zeros = Array(dimension - _values.length).fill(0);
    _values = _values.concat(zeros);
  } else if (_values.length > dimension) {
    _values = _values.slice(0, dimension);
  }

  readonly(this, "dimension", dimension);
  readonly(this, "values", _values);
  readonly(this, "magnitude", _magnitudeOf(_values));
}
72954
def append_column(table, col_name, default_value=None):
    '''
    
    '''
    table[0].append(col_name.strip())
    for row in table[1:]:
        row.append(default_value)
686498
def add_row(self, data: list):
        
        # validation
        if self.headers:
            if len(self.headers) != len(data):
                raise ValueError

        if len(data) != self.num_of_columns:
            raise ValueError

        offset = 0 if not self.headers else 1
        row = list()
        for i, element in enumerate(data):
            label = ttk.Label(self, text=str(element), relief=tk.GROOVE,
                              padding=self.padding)
            label.grid(row=len(self._rows) + offset, column=i, sticky='E,W')
            row.append(label)

        self._rows.append(row)
414052
def add_cell(self, row="unknown", col="unknown",
                 val="unknown", type="int32", meta=""):
        
        if self.arr is None:
            self.arr = np.array(
                [(row, val)], dtype=[ (self.name, "S50"), (col, type)])
            self.meta = np.array(
                [(row, val)], dtype=[ (self.name, TYPE_META), (col, type)])
            self.irt[row] = 0

        if not row in self._get_row_hdrs():
            self._expand_row(row)

        if not col in self._get_col_hdrs():
            self._expand_col(col, type)

        try:
            self._add_cell(val, row, col, meta)
        except ValueError:
            logging.error("unable to add val %s to [%s,%s]: "
                          "not a compatible data type" % (val, row, col))
            return False

        return True
1348723
def add_column(self, name, *, index=0, values=None):
        
        if name is None:
            return None

        params = {
            'name': name,
            'index': index
        }
        if values is not None:
            params['values'] = values

        url = self.build_url(self._endpoints.get('add_column'))
        response = self.session.post(url, data=params)
        if not response:
            return None

        data = response.json()

        return self.column_constructor(parent=self, **{self._cloud_data_key: data})
630574
def set_columns(self, columns):
        """"""
        if isinstance(columns, tuple):
            self.columns = columns
        elif is_text_string(columns):
            self.columns = tuple(int(e) for e in columns.split(','))

        self.update()
346395
def insert_data_frame(col, df, int_col=None, binary_col=None, minimal_size=5):
    
    data = transform.to_dict_list_generic_type(df,
                                               int_col=int_col,
                                               binary_col=binary_col)
    smart_insert(col, data, minimal_size)
620003
public void add(int index, DoubleVector v) {
        boolean added = indices.add(index);
        assert added : "Adding duplicate indices to candidate facility";
        if (sumVector == null) {
            sumVector = (v instanceof SparseVector)
                ? new SparseHashDoubleVector(v)
                : new DenseVector(v);
        }
        else {
            VectorMath.add(sumVector, v);
            centroid = null;
        }           
    }
413208
def combineColumns(cols):
    ''
    return Column("+".join(c.name for c in cols),
                  getter=lambda col,row,cols=cols,ch=' ': ch.join(c.getDisplayValue(row) for c in cols))
476684
def _add_row(self, index):
        
        self._index.append(index)
        for c, _ in enumerate(self._columns):
            self._data[c].append(None)
143690
function addCol($col_data, $col_id = 0, $row_id = 0) {
        foreach ($col_data as $col_cell) {
            $this->_data[$row_id++][$col_id] = $col_cell;
        }

        $this->_updateRowsCols();
        $this->_max_cols = max($this->_max_cols, $col_id + 1);
    }
1019401
public void add(IntFloatVector other) {
        if (other instanceof IntFloatUnsortedVector) {
            IntFloatUnsortedVector vec = (IntFloatUnsortedVector) other;
            for (int i=0; i<vec.top; i++) {
                this.add(vec.idx[i], vec.vals[i]);
            }
        } else {
            //  TODO: Add special case for IntFloatDenseVector.
            other.iterate(new SparseBinaryOpApplier(this, new Lambda.FloatAdd()));
        }
    }
1340263
def add_column(self, name, type_name, options=None):
        
        column = Column(name, type_name, options)

        self._add_column(column)

        return column
1047967
def AddTableColumns(self, table, columns):
    """"""
    table_columns = self._table_columns.setdefault(table, [])
    for attr in columns:
      if attr not in table_columns:
        table_columns.append(attr)
562752
void addColumn(String columnName)
    {
        data.add(new ArrayList<String>());
        columnNames.add(columnName);
    }