Split ploting in 2

notes_tools/tools/marks_plottings.py

@@ -0,0 +1,53 @@
+#!/usr/bin/env python
+# encoding: utf-8
+
+from .plottings import radar_graph
+import pandas as pd
+import numpy as np
+
+def comp_radar(df, optimum = None):
+    """ Plot the radar graph concerning "Competence" column of the df
+
+    :param df: DataFrame with "Competence", "Normalized"
+    :returns: exes with radar plot
+
+    """
+    comp_pt = pd.pivot_table(df,
+            index = ["Competence"],
+            values = ["Normalized"],
+            aggfunc=np.mean,
+            )
+    labels = list(comp_pt.index)
+    values = [i[0] for i in comp_pt.values]
+    if optimum is None:
+        optimum = [1]*len(values)
+    fig, ax = radar_graph(labels, values, optimum)
+    return fig, ax
+
+def marks_hist(df):
+    """ Return axe for the histogramme of the dataframe  
+
+    :param df: Dataframe with "Mark" and "Bareme" columns. If it has "Nom" column, it is use in title.
+    """
+    bareme = df["Bareme"].max()
+    bins = bareme*2
+
+    ax = df["Mark"].hist(bins = bins, range=(0,bareme))
+
+    try:
+        nom = df["Nom"].unique()
+    except KeyError:
+        title="Histogramme"
+    else:
+        title="Histogramme pour {}".format(" ".join(nom))
+
+    ax.set_title(title)
+
+    return ax
+
+
+
+# -----------------------------
+# Reglages pour 'vim'
+# vim:set autoindent expandtab tabstop=4 shiftwidth=4:
+# cursor: 16 del

notes_tools/tools/plottings.py

@@ -7,6 +7,7 @@ from matplotlib.path import Path
 from matplotlib.spines import Spine
 from matplotlib.projections.polar import PolarAxes
 from matplotlib.projections import register_projection
+plt.style.use('ggplot')
 
 def _radar_factory(num_vars):
     theta = 2*np.pi * np.linspace(0, 1-1./num_vars, num_vars)
@@ -69,9 +70,6 @@ def radar_graph(labels = [], values = [], optimum = []):
     ax.plot(theta, optimum, color='r')
     ax.set_varlabels(labels)
     return fig, ax
-    #plt.show()
-    #plt.savefig("radar.png", dpi=100)
-
 
 
 # -----------------------------