1. Data type conversion and filteringTransform the data types of columns required for data analysis.For example, POS can be converted to integer and QUAL to float.# Data type conversiondf['POS'] = df['POS'].astype(int)df['QUAL'] = df['QUAL'].astype(float)df['AF'] = df['AF'].apply(lambda x: float(x.split(',')[0]))# Filtering only high-quality variationshigh_quality_variants = df[df['QUAL'] >= 30]..