ValueError: Could Not Convert String to Float

Why This Happens

The float() function cannot parse text, empty strings, or strings with non-numeric characters. This is common when reading CSV data where missing values are 'N/A' or empty.

The Problem

values = ['1.5', '2.3', 'N/A', '4.1']
floats = [float(v) for v in values]

The Fix

def safe_float(v, default=0.0):
    try:
        return float(v)
    except ValueError:
        return default

floats = [safe_float(v) for v in values]

Step-by-Step Fix

1. 1

   Handle non-numeric values

   Wrap float() in try/except ValueError.

2. 2

   Clean the data

   Remove currency symbols and commas: float(s.strip().replace(',', '')).

3. 3

   Use pandas

   pd.to_numeric(series, errors='coerce') converts and replaces failures with NaN.