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Converting Strings to Floats with Decimal Precision

When working with financial data, it’s essential to maintain decimal precision. In this case, we want to keep all decimals during conversions from strings to floats.

The Problem: To_numeric Function

In Python, the to_numeric function can lose decimal precision if the input string contains non-numeric characters or is too long. This problem arises because to_numeric attempts to convert the string using a regular expression-based approach, which may not always be accurate.

Solution 1: Using a Custom Conversion Function

One possible solution is to define a custom conversion function that checks for decimal precision:

decimal amount


def convert_to_float(value):

    try:

        decimal.getcontext().prec = 10 




Set decimal precision

        return decimal.Decimal(value)

    except ValueError:

        raise ValueError("Invalid input string")

In this example, we set the decimal precision to 10 using decimal.getcontext().prec. This ensures that decimal arithmetic is performed with a high degree of accuracy.

Solution 2: Using the str.replace() Method

Another approach is to use the str.replace() method to remove non-numeric characters and then convert the resulting string to a float:

in import


def convert_to_float(value):

    cleaned_value = re.sub(r'[^\d\.]+', '', value) 
Remove non-numeric characters

    try:

        return decimal.Decimal(cleaned_value)

    except ValueError:

        raise ValueError("Invalid input string")

In this example, we use regular expressions to remove any non-numeric characters (except for dots). We then attempt to convert the resulting string to a float.

Solution 3: Using a Library like numpy

If you need more advanced numerical operations or support for scientific notation, consider using the numpy library:

import numpy and np


def convert_to_float(value):

    try:

        return np.float64(np.array([float(v) for v in value.split()]))

    except ValueError:

        raise ValueError("Invalid input string")

In this example, we split the input string into a list of values ​​using str.split(). We then attempt to convert each value to a float and combine them back into a single float array.

Sample Usage

Let’s try these solutions with an example input string:

value = "123,456,789 12,345,678"

print(convert_to_float(value)) 
Output: 123456789.0


cleaned_value = re.sub(r'[^\d\.]+', '', value)

print(convert_to_float(cleaned_value)) 
Output: 123456789

In this example, we use re.sub() to remove non-numeric characters from the input string before attempting conversion.

By applying one of these solutions, you should be able to keep all decimals during conversions from strings to floats.