From f6763f5a077c361cae81b56db7dfc07561c4c154 Mon Sep 17 00:00:00 2001
From: maxhelskens <max.helskens@telenet.be>
Date: Thu, 12 Apr 2018 09:38:58 +0200
Subject: [PATCH] finished boxplot

---
 .gitignore                   |  3 +-
 opengrid/library/plotting.py | 54 ++++++++++++++++++++++++++++++++++++
 2 files changed, 56 insertions(+), 1 deletion(-)

diff --git a/.gitignore b/.gitignore
index 1324af9..6ad77c4 100644
--- a/.gitignore
+++ b/.gitignore
@@ -5,4 +5,5 @@
 opengrid/notebooks/index.html
 dist/
 build/
-opengrid.egg-info/
\ No newline at end of file
+opengrid.egg-info/
+.DS_Store
diff --git a/opengrid/library/plotting.py b/opengrid/library/plotting.py
index 722d65c..ac32d6b 100644
--- a/opengrid/library/plotting.py
+++ b/opengrid/library/plotting.py
@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import matplotlib
+import pandas as pd
 
 
 def plot_style():
@@ -13,4 +14,57 @@ def plot_style():
     matplotlib.style.use('seaborn-deep')
 
     plt.rcParams['figure.figsize'] = 16, 6
+
+    # To overrule the legend style
+    plt.rcParams['legend.facecolor'] = "#ffffff"
+    plt.rcParams['legend.frameon'] = True
+    plt.rcParams['legend.framealpha'] = 1
+
     return plt
+
+
+def boxplot(df, plot_mean=False, plot_ids=None):
+    """
+        Plot boxplots
+
+        Plot the boxplots of a dataframe in time
+
+        Parameters
+        ----------
+        df: Pandas Dataframe
+            Every collumn is a timeseries
+        plot_mean: bool
+            Wether or not to plot the means
+        plot_ids: [str]
+            List of id's to plot
+
+        Returns
+        -------
+        matplotlib figure
+        """
+    description = df.apply(pd.DataFrame.describe, axis=1)
+
+    # plot
+    plt = plot_style()
+
+    df.index = df.index.map(lambda x: x.strftime('%b'))
+
+    df = df.T
+
+    fig, ax = plt.subplots()
+    axes, bp = df.boxplot(ax=ax, return_type='both')
+    plt.setp(bp['boxes'], color='black')
+    plt.setp(bp['whiskers'], color='black')
+
+    for id in plot_ids:
+        ax.scatter(x=axes.get_xticks(), y=df.loc[id], label=str(id))
+
+    if plot_mean:
+        ax.scatter(x=axes.get_xticks(), y=description['mean'], label="Mean", color='k', s=30, marker='+')
+
+    plt.xticks(rotation=45)
+
+    ax.legend()
+
+    return fig
+