pivot table pie plots

notes_tools/tools/marks_plottings.py

@@ -1,15 +1,16 @@
 #!/usr/bin/env python
 # encoding: utf-8
 
-from .plottings import radar_graph
+from .plottings import radar_graph, pivot_table_to_pie
 from .skills_tools import count_levels, count_skill_evaluation
 import matplotlib.pyplot as plt
 import pandas as pd
 import numpy as np
+import logging
+logger = logging.getLogger(__name__)
 
 __all__ = ["radar_on", 
-        "pie_skill_evaluation",
-        "pies_skills_level",
+        "pie_pivot_table",
         "marks_hist",
         "parallele_on",
         ]
@@ -33,18 +34,16 @@ def radar_on(df, index, optimum = None):
     fig, ax = radar_graph(labels, values, optimum)
     return fig, ax
 
-def pie_skill_evaluation(df, skill):
-    """ Plot a pie plot with the repartition of skill evaluations
-    """
-    ax = count_skill_evaluation(df, skill).plot.pie(autopct='%.0f')
-    return ax
+def pie_pivot_table(df, pies_per_lines = 3, **kwargs):
+    """ Plot a pie plot of the pivot_table of df
 
-def pies_skills_level(df, skill):
-    """ Plot series of pies (one by different skill) with level repartition """
-    levels_counts = count_levels(df, skill)
-    fig, ax = plt.subplots(nrows=1, ncols=len(levels_counts), figsize=(16,3))
-    plots = levels_counts.T.plot(ax=ax ,kind="pie", subplots=True, legend=False)
-    return fig, ax
+    :param df: the dataframe.
+    :param pies_per_lines: Number of pies per line.
+    :param kwargs:  arguments to pass to pd.pivot_table.
+    """
+    logger.debug(f"pie_pivot_table avec les arguments {kwargs}")
+    pv = pd.pivot_table(df, **kwargs)
+    return pivot_table_to_pie(pv, pies_per_lines)
 
 def marks_hist(df):
     """ Return axe for the histogramme of the dataframe