def visualize():
my_util = Util()
df = my_util.load_df("../only_calculated_datasets/cleaned_df.pkl")
my_visu = Visualization()
my_visu.make_histograms(df, ["age", "race", "gender", "max_glu_serum", "A1Cresult", "num_lab_procedures",
"time_in_hospital", "change", "diabetesMed"], image_path="../outputs/attr_hist_plot.png") # all the attributes distributions
my_visu.make_histograms(df, ["readmitted"], cmap="spring",
image_path="../outputs/class_attr_hist_plot.png")
my_visu.build_scatter_2attr_plot(df, x_col="num_lab_procedures", y_col="num_medications",
image_path="../outputs/num_of_procedures_vs_medications_plot.png")
my_visu.build_3d_scatter_plot(df, x_axis_col="number_outpatient", y_axis_col="number_emergency", z_axis_col="number_inpatient",
class_col="readmitted", image_path="../outputs/outPt_emergencyPt_inPt_vs_readmitted_sctter_plot.png", is_show=False)
my_visu.build_3d_scatter_plot(df, x_axis_col="diag_1", y_axis_col="diag_2", z_axis_col="diag_3",
class_col="readmitted", image_path="../outputs/diag_1_2_3_vs_readmitted_sctter_plot.png", is_show=False)
