You can handle outliers in a numeric column by filtering or transforming the data using techniques like Z-score or IQR (Interquartile Range).
Example Code (using Z-score for outlier removal):
from scipy import stats
# Calculate the Z-score for a numeric column
z_scores = stats.zscore(df['Numeric_Column'])
# Define a threshold for Z-score (e.g., 2)
threshold = 2
# Remove rows with Z-scores greater than the threshold
df = df[(z_scores < threshold) | (z_scores > -threshold)]
