Machine Learning, Deep Learning, Cryptocurrency Investment, Algorithmic Trading, Neural Networks.
DataFrame (df.replace([np.inf, -np.inf], np.nan, inplace=True)). This is necessary because some mathematical operations cannot handle infinities. It then removes rows with missing values (NaN) from the DataFrame (df.dropna(axis=0, inplace=True)) to ensure clean data for further analysis. 3.