basic ploting for skills

notes_tools/reports/filters.py

@@ -19,7 +19,7 @@ def includegraphics(fig_ax, document_path="./", fig_path="fig/",
     """
     try:
         fig, ax = fig_ax
-    except TypeError:
+    except (TypeError, ValueError):
         ax = fig_ax
         fig = ax.figure
 

notes_tools/reports/templates/tpl_reports_term.tex

@@ -18,6 +18,11 @@
 \Var{e["quest"] | radar_on("Competence") | includegraphics(document_path=directory, scale=0.6)}
 \Var{e["quest"] | radar_on("Domaine") | includegraphics(document_path=directory, scale=0.6)}
 
+\vfill
+\hspace{-2cm}
+\Var{e["quest"] | pies_skills_level("Competence") | includegraphics(document_path=directory, scale=0.3)}
+
+
 \vfill
 %#\Var{conn_df}
 %- if not conn_df.empty

notes_tools/reports/texenv.py

@@ -31,10 +31,12 @@ texenv = jinja2.Environment(
 from .filters import includegraphics
 texenv.filters['includegraphics'] = includegraphics
 
-from notes_tools.tools.marks_plottings import radar_on, marks_hist, parallele_on
+from notes_tools.tools.marks_plottings import *
 texenv.filters['radar_on'] = radar_on
 texenv.filters['marks_hist'] = marks_hist
 texenv.filters['parallele_on'] = parallele_on
+texenv.filters['pie_skill_evaluation'] = pie_skill_evaluation
+texenv.filters['pies_skills_level'] = pies_skills_level
 
 def feed_template(target, datas, template):
     """ Get the template and feed it to create reports

notes_tools/tools/marks_plottings.py

@@ -2,10 +2,17 @@
 # encoding: utf-8
 
 from .plottings import radar_graph
+from .skills_tools import count_levels, count_skill_evaluation
+import matplotlib.pyplot as plt
 import pandas as pd
 import numpy as np
 
-__all__ = ["radar_on", "marks_hist", "parallele_on"]
+__all__ = ["radar_on", 
+        "pie_skill_evaluation",
+        "pies_skills_level",
+        "marks_hist",
+        "parallele_on",
+        ]
 
 def radar_on(df, index, optimum = None):
     """ Plot the radar graph concerning index column of the df
@@ -26,6 +33,19 @@ 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 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
+
 def marks_hist(df):
     """ Return axe for the histogramme of the dataframe