While NumPy provides the computational foundation for these operations, you will likely want to use pandas as your basis for most kinds of data analysis (especially for structured or tabular data) as it provides
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string_) In [45]: numeric_strings.astype(float) Out[45]: array([ 1.25, -9.6 , 42. ]) Caution It’s important to be cautious when using the numpy.string_ type, as string data in NumPy is fixed size and may truncate input without warning. pandas has more intuitive out-of-the-box ...