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# NumPy | place method

schedule Aug 12, 2023
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NumPy's `place(~)` method sets the specified values given a boolean mask.

# Parameters

1. `arr` | `Numpy array`

The input array. All arrays are treated as a flattened array.

2. `mask` | `array-like`

An array of booleans that indicate whether or not to set the value. The shape must be the same as that of a.

3. `values` | `array-like`

A 1D array that contains the values to set. If v is shorter than a, then v will be repeated to ensure the shape matches up.

# Return value

None - the setting is done in-place.

# Examples

## Basic usage

``` a = np.array([5,6,7,8])np.place(a, [True, False, False, True], 9)a array([9, 6, 7, 9]) ```

Notice how only values that had a corresponding value of True in the mask were set.

## 2D arrays

Consider the following 2D array:

``` a = np.array([[5,6],[7,8]])a array([[5, 6],       [7, 8]]) ```

### Setting a single value

``` a = np.array([[5,6],[7,8]])np.place(a, [True, False, False, True], 9)a array([[9, 6],       [7, 9]]) ```

### Setting multiple values

``` a = np.array([[5,6],[7,8]])np.place(a, [True, False, False, True], [9,10])a array([[ 9, 6],       [ 7, 10]]) ```
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