To stack 1-D arrays as columns into a 2-D array, use the ma.column_stack() method in Python Numpy. Take a sequence of 1-D arrays and stack them as columns to make a single 2-D array. 2-D arrays are stacked as-is, just like with hstack. 1-D arrays are turned into 2-D columns ... Read More

To stack arrays in sequence vertically (row wise), use the ma.row_stack() method in Python Numpy. This is equivalent to concatenation along the first axis after 1-D arrays of shape (N, ) have been reshaped to (1, N). Rebuilds arrays divided by vsplit. Returns the array formed by stacking the given ... Read More

To remove axes of length one, use the ma.MaskedArray.squeeze() method in Numpy. The axis is set using the "axis" parameter. The axis selects a subset of the entries of length one in the shape. If an axis is selected with shape entry greater than one, an error is raised.The function ... Read More

To convert inputs to arrays with at least two dimensions, use the ma.atleast_2d() method in Python Numpy. The parameters are One or more array-like sequences. Non-array inputs are converted to arrays. Arrays that already have two or more dimensions are preserved.The method returns an array, or list of arrays, each ... Read More

To convert inputs to arrays with at least one dimension, use the ma.atleast_1d() method in Python Numpy. Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional inputs are preserved. It returns an array, or list of arrays, each with a.ndim >= 1. Copies are made only if necessary. The function ... Read More

To get or set the mask of the array if it has no named fields, use the MaskedArray.recordmask  in Python Numpy. For structured arrays, returns a ndarray of booleans where entries are True if all the fields are masked, False otherwise.A masked array is the combination of a standard numpy.ndarray ... Read More

To display the current mask, use the ma.MaskedArray.mask in Python Numpy. A masked array is the combination of a standard numpy.ndarray and a mask. A mask is either nomask, indicating that no value of the associated array is invalid, or an array of booleans that determines for each element of ... Read More

To count the number of masked elements along specific axis, use the ma.MaskedArray.count_masked() method. The axis 0 is set using the "axis" parameter. The method returns the total number of masked elements (axis=None) or the number of masked elements along each slice of the given axis.The axis parameter is the ... Read More

To compute the differences between consecutive elements of a masked array, use the MaskedArray.ediff1d() method in Python Numpy.The "to_begin" parameter sets the array of number(s) to prepend at the start of the returned differences. The "to_end" parameter sets the array of number(s) to append at the end of the returned ... Read More

To count the number of masked elements along specific axis, use the ma.MaskedArray.count_masked() method. The axis is set using the "axis" parameter. The method returns the total number of masked elements (axis=None) or the number of masked elements along each slice of the given axis.The axis parameter is the axis ... Read More