fillna() function

Addressing missing data is perhaps the most critical initial phase in the data preprocessing pipeline, essential for any analytical task or machine learning model training. The presence of NaN (Not a Number) values introduces statistical bias, compromises the integrity of results, and can halt model execution. Fortunately, the widely utilized Pandas library in Python provides […]