numpy.trim_zeros() in Python

numpy.trim_zeros() removes the leading and trailing zeros from a 1-D array. It is often used to clean up data by trimming unnecessary zeros from the beginning or end of the array. Example:

[3 4 0 5]

Explanation: np.trim_zeros(a) removes both leading and trailing zeros by default (trim='fb'). Zeros in the middle remain unchanged.

Syntax

numpy.trim_zeros(filt, trim='fb')

Parameter:

• filt (array_like): A 1-D array of numeric values from which zeros will be trimmed.
• trim (str, optional): Indicates which zeros to remove, 'f' for leading (front), 'b' for trailing (back) and 'fb' (default) for both.

Returns: A new 1-D NumPy array with the specified zeros removed.

Examples

Example 1: In this example, we use the parameter trim='f' to remove the leading zeros from the beginning of the array, while keeping the zeros at the end unchanged.

[1 2 3 0]

Explanation: np.trim_zeros(a, trim='f') removes only the leading zeros from the beginning of the array. Trailing zeros are preserved, resulting in [1, 2, 3, 0].

Example 2: In this example, we use the parameter trim='b' to remove the trailing zeros from the end of the array, while keeping the leading zeros at the beginning unchanged.

[0 1 2]

Explanation: np.trim_zeros(a, trim='b') removes only the trailing zeros from the end of the array. Leading zeros are kept intact, resulting in [0, 1, 2].

Example 3: In this example, all elements are zeros. Since np.trim_zeros() removes zeros from both ends by default, the result is an empty array.

[]

Explanation: np.trim_zeros(a) removes zeros from both ends by default (trim='fb'). Since the array contains only zeros, the result is an empty array.