nalvared · October 31, 2017 17:41 · Oct 31, 2017
diff --git a/ExamplePlotHelper.md b/ExamplePlotHelper.md
@@ -0,0 +1,34 @@
+
+# PlotHelper
+
+## Import library
+The _plothelper.py_ file should be in the same folder
+
+```python
+import numpy as np
+import pandas as pd
+from plothelper import PlotHelper as PH
+%matplotlib inline
+```
+
+## Load dataset with pandas
+
+```python
+# load dataset
+dfHouses = pd.read_csv('kc_house_data.csv')
+```
+
+## Using PH.pairplot
+This is the same function that _seaborn.pairplot()_ but it has two new parameters:
+- max_per_row: maximum charts in the same row
+- reg_line_color: if the type of the chart is _kind='reg'_, this property paints the regression line in the color choosen
+
+```python
+PH().pairplot(data=dfHouses,
+              x_vars=dfHouses.columns.tolist(),
+              y_vars=['price'],
+              max_per_row=5,
+              kind='reg',
+              reg_line_color='red')
+```
+
diff --git a/plothelper.py b/plothelper.py
@@ -0,0 +1,45 @@
+import numpy as np
+import seaborn as sns
+class PlotHelper:
+
+    def splitVariables(self, x_vars=None, y_vars=None, max_per_row=10):
+        slices = []
+        for y in y_vars:
+            curr_y = y
+            l = []
+            if max_per_row > len(x_vars):
+                for x in x_vars:
+                    if y != x:
+                        l.append(x)
+                slices.append([curr_y, l])
+            else:
+                i = 0
+                for s in range(int(np.ceil(len(x_vars)/max_per_row))):
+                    l = []
+                    for x in x_vars[i:max_per_row+i]:
+                        if y != x:
+                            l.append(x)
+                    slices.append([l,curr_y])
+                    i += max_per_row
+        return slices
+
+    def pairplot(self, data=None, hue=None, hue_order=None, palette=None,
+                 vars=None, x_vars=None, y_vars=None, kind='scatter',
+                 diag_kind='hist', markers=None, size=2.5, aspect=1,
+                 dropna=True, plot_kws=None, diag_kws=None,
+                 grid_kws=None, wrap=True, max_per_row=None, reg_line_color=None):
+        if kind == 'reg' and reg_line_color != None:
+            plot_kws={'line_kws':{'color':reg_line_color}}
+        if max_per_row == None:
+            return sns.pairplot(data=data, hue=hue, hue_order=hue_order, palette=palette,
+                         vars=vars, x_vars=x_vars, y_vars=y_vars, kind=kind,
+                         diag_kind=diag_kind, markers=markers, size=size, aspect=aspect,
+                         dropna=dropna, plot_kws=plot_kws, diag_kws=diag_kws, grid_kws=grid_kws)
+        else:
+            slices = self.splitVariables(x_vars, y_vars, max_per_row)
+            for i in range(len(slices)):
+                sns.pairplot(data=data, hue=hue, hue_order=hue_order, palette=palette,
+                     vars=vars, x_vars=slices[i][0], y_vars=slices[i][1], kind=kind,
+                     diag_kind=diag_kind, markers=markers, size=size, aspect=aspect,
+                     dropna=dropna, plot_kws=plot_kws, diag_kws=diag_kws, grid_kws=grid_kws)
+
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