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",
+        "pie_pivot_table",
-        "pies_skills_level",
         "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):
+def pie_pivot_table(df, pies_per_lines = 3, **kwargs):
-    """ Plot a pie plot with the repartition of skill evaluations
+    """ Plot a pie plot of the pivot_table of df
-    """
-    ax = count_skill_evaluation(df, skill).plot.pie(autopct='%.0f')
-    return ax
 
-def pies_skills_level(df, skill):
+    :param df: the dataframe.
-    """ Plot series of pies (one by different skill) with level repartition """
+    :param pies_per_lines: Number of pies per line.
-    levels_counts = count_levels(df, skill)
+    :param kwargs:  arguments to pass to pd.pivot_table.
-    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)
+    logger.debug(f"pie_pivot_table avec les arguments {kwargs}")
-    return fig, ax
+    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  

notes_tools/tools/plottings.py

@@ -71,6 +71,33 @@ def radar_graph(labels = [], values = [], optimum = []):
     ax.set_varlabels(labels)
     return fig, ax
 
+def my_autopct(values):
+    def my_autopct(pct):
+        total = sum(values)
+        val = int(round(pct*total/100.0))
+        return f'{val}'
+    return my_autopct
+
+def pivot_table_to_pie(pv, pies_per_lines = 3):
+    nbr_pies = len(pv.columns)
+    nbr_cols = min(pies_per_lines, nbr_pies)
+    nbr_rows = max(nbr_pies % nbr_cols,1)
+    f, axs = plt.subplots(nbr_rows, nbr_cols, figsize = (4*nbr_cols,4*nbr_rows))
+    for (c, ax) in zip(pv, axs.flatten()):
+        datas = pv[c]
+        explode = [0.1]*len(datas)
+        pv[c].plot(kind="pie",
+                             ax=ax,
+                             use_index = False,
+                             title = f"{c} (total={datas.sum()})",
+                             legend = False,
+                             autopct=my_autopct(datas),
+                             explode = explode,
+                            )
+        ax.set_ylabel("")
+    for i in range(nbr_pies//nbr_cols, nbr_cols*nbr_rows):
+        axs.flat[i].axis("off")
+    return (f, axs)
 
 # -----------------------------
 # Reglages pour 'vim'