NumPy strings.startswith()

The numpy.strings.startswith() function checks whether each string element in an array starts with a specified prefix. It returns a boolean array indicating which elements start with the given prefix.

Syntax

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numpy.strings.startswith(a, prefix, start=0, end=None)

Parameters

Parameter	Type	Description
`a`	array-like (StringDType, bytes_, or str_ dtype)	Input array of strings.
`prefix`	array-like (StringDType, bytes_, or str_ dtype)	Prefix to check at the start of each string.
`start`	array-like (integer dtype), optional	Specifies the position to start checking within the string.
`end`	array-like (integer dtype), optional	Specifies the position to stop checking.

Return Value

Returns an array of boolean values. Each element is True if the corresponding string starts with the given prefix, otherwise False.

Examples

1. Checking If Strings Start with a Given Prefix

Here, we check whether each string in the array starts with the specified prefix.

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import numpy as np

# Define an array of strings
strings = np.array(["apple", "banana", "apricot", "blueberry"], dtype="U")

# Define the prefix to check
prefix = "ap"

# Check if each string starts with the prefix
result = np.strings.startswith(strings, prefix)

# Print the result
print("Does each string start with 'ap'?:", result)

Output:

Does each string start with 'ap'?: [ True False  True False]

2. Using the `start` Parameter

We check whether the substring from a specific position starts with the given prefix.

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import numpy as np

# Define an array of strings
strings = np.array(["banana", "bandana", "banish", "banner"], dtype="U")

# Define the prefix to check
prefix = "na"

# Specify the starting position
start_position = 2

# Check if substring starting from index 2 matches the prefix
result = np.strings.startswith(strings, prefix, start=start_position)

# Print the result
print("Does each string start with 'na' from index 2?:", result)

Output:

Does each string start with 'na' from index 2?: [ True False False False]

3. Using the `end` Parameter

Here, we limit the substring check within a specified range using the end parameter.

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import numpy as np

# Define an array of strings
strings = np.array(["python", "pyramid", "pythonic", "pyrex"], dtype="U")

# Define the prefix
prefix = "py"

# Specify the range within which to check
start_position = 0
end_position = 3

# Check if strings start with the prefix within the given range
result = np.strings.startswith(strings, prefix, start=start_position, end=end_position)

# Print the result
print("Does each string start with 'py' within the range [0,3]?:", result)

Output:

Does each string start with 'py' within the range [0,3]?: [ True  True  True  True]

4. Checking Multiple Prefixes

We check if each string starts with one of multiple possible prefixes.

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import numpy as np

# Define an array of strings
strings = np.array(["hello", "world", "hi", "house"], dtype="U")

# Define an array of prefixes
prefixes = np.array(["he", "wo", "ha", "ho"], dtype="U")

# Check if each string starts with its corresponding prefix
result = np.strings.startswith(strings, prefixes)

# Print the result
print("Does each string start with the corresponding prefix?:", result)

Output:

Does each string start with the corresponding prefix?: [ True  True False  True]

Each element is checked against its corresponding prefix. The third string "hi" does not start with "ha", so it returns False.

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NumPy strings.startswith() – Check – Starts With Specific Prefix