Return Addition of series and other, element-wise (binary operator `add`). Equivalent to ``series + other``, but with support to substitute a fill_value for missing data in either one of the inputs. Parameters ---------- other : Series or scalar val
(self, other, level=None, fill_value=None, axis: Axis = 0)
| 7108 | ) |
| 7109 | |
| 7110 | def add(self, other, level=None, fill_value=None, axis: Axis = 0) -> Series: |
| 7111 | """ |
| 7112 | Return Addition of series and other, element-wise (binary operator `add`). |
| 7113 | |
| 7114 | Equivalent to ``series + other``, but with support to substitute a fill_value |
| 7115 | for missing data in either one of the inputs. |
| 7116 | |
| 7117 | Parameters |
| 7118 | ---------- |
| 7119 | other : Series or scalar value |
| 7120 | With which to compute the addition. |
| 7121 | level : int or name |
| 7122 | Broadcast across a level, matching Index values on the |
| 7123 | passed MultiIndex level. |
| 7124 | fill_value : None or float value, default None (NaN) |
| 7125 | Fill existing missing (NaN) values, and any new element needed for |
| 7126 | successful Series alignment, with this value before computation. |
| 7127 | If data in both corresponding Series locations is missing |
| 7128 | the result of filling (at that location) will be missing. |
| 7129 | axis : {0 or 'index'} |
| 7130 | Unused. Parameter needed for compatibility with DataFrame. |
| 7131 | |
| 7132 | Returns |
| 7133 | ------- |
| 7134 | Series |
| 7135 | The result of the operation. |
| 7136 | |
| 7137 | See Also |
| 7138 | -------- |
| 7139 | Series.radd : Reverse of the Addition operator, see |
| 7140 | `Python documentation |
| 7141 | <https://docs.python.org/3/reference/datamodel.html#emulating-numeric-types>`_ |
| 7142 | for more details. |
| 7143 | |
| 7144 | Examples |
| 7145 | -------- |
| 7146 | >>> a = pd.Series([1, 1, 1, np.nan], index=["a", "b", "c", "d"]) |
| 7147 | >>> a |
| 7148 | a 1.0 |
| 7149 | b 1.0 |
| 7150 | c 1.0 |
| 7151 | d NaN |
| 7152 | dtype: float64 |
| 7153 | >>> b = pd.Series([1, np.nan, 1, np.nan], index=["a", "b", "d", "e"]) |
| 7154 | >>> b |
| 7155 | a 1.0 |
| 7156 | b NaN |
| 7157 | d 1.0 |
| 7158 | e NaN |
| 7159 | dtype: float64 |
| 7160 | >>> a.add(b, fill_value=0) |
| 7161 | a 2.0 |
| 7162 | b 1.0 |
| 7163 | c 1.0 |
| 7164 | d 1.0 |
| 7165 | e NaN |
| 7166 | dtype: float64 |
| 7167 | """ |