test(live): add live_test_plotgen for interactive plotgen usage and custom plot generation examples

Author: DYung26

test/live/live_test_plotgen.py

@@ -0,0 +1,64 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+
+from plotsense.plot_generator.generator import plotgen
+
+df = pd.DataFrame({
+    "a": range(10),
+    "b": range(10, 20)
+})
+
+suggestions_df = pd.DataFrame([
+    {"plot_type": "scatter", "variables": "a,b"}
+])
+
+# Standard plot
+fig1 = plotgen(df, 0, suggestions_df, generator="smart")
+
+# ---------
+
+# Custom plot
+def my_custom_plot(df, vars, **kwargs):
+    fig, ax = plt.subplots()
+    ax.plot(df[vars[0]], df[vars[1]], color="red")
+    return fig
+
+fig2 = plotgen(
+    df, 0, suggestions_df,
+    generator="smart",
+    plot_function=my_custom_plot,
+    plot_type="my_line"
+)
+
+# ---------
+
+# Create sample DataFrame
+df = pd.DataFrame({
+    "height": [165, 170, 175, 160, 172, 168, 180, 177, 169, 174]
+})
+
+# Simulate a recommendation DataFrame (just like your usual `suggestions_df`)
+suggestions_df = pd.DataFrame([
+    {"plot_type": "kde", "variables": "height"}
+])
+
+# Generate KDE Plot
+fig_kde = plotgen(df, 0, suggestions_df, generator="smart")
+
+# ---------
+
+# Create sample DataFrame
+df = pd.DataFrame({
+    "scores": [60, 72, 85, 90, 66, 75, 88, 93, 70, 80]
+})
+
+# Simulate recommendation DataFrame
+suggestions_df = pd.DataFrame([
+    {"plot_type": "ecdf", "variables": "scores"}
+])
+
+# Generate ECDF Plot
+fig_ecdf = plotgen(df, 0, suggestions_df, generator="smart")
+
+plt.show()
+