Eda, Exploratory Data Analysis, Pandas, Python.
the independent variables for ivars in cols[~cols.isin([target])]: print("Processing variable:", ivars) if (data[ivars].dtype.kind in 'bifc') and (len(np.unique(data[ivars]))>10): binned_x = pd.qcut(data[ivars], bins, duplicates='drop') d0 = pd.DataFrame({'x': binned_x, 'y': data[target]}) else: d0