From 1beb50ef75a7db236a5ab3fdf88faf4c55f7c19d Mon Sep 17 00:00:00 2001
From: Camil Staps
Date: Sun, 11 Oct 2015 21:14:28 +0200
Subject: Assignment 2 finished

---
 Assignment2/ex21.py | 62 -----------------------------------------------------
 1 file changed, 62 deletions(-)
 delete mode 100644 Assignment2/ex21.py

(limited to 'Assignment2/ex21.py')

diff --git a/Assignment2/ex21.py b/Assignment2/ex21.py
deleted file mode 100644
index 87d68cd..0000000
--- a/Assignment2/ex21.py
+++ /dev/null
@@ -1,62 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Created on Sat Oct 10 21:28:45 2015
-
-@author: camilstaps
-"""
-
-import matplotlib.pyplot as plt
-from scipy import io as sciio, stats
-import numpy as np
-
-# 2.1.1
-wine = sciio.loadmat('./Data/wine.mat')
-data = wine['X']
-atts = [str(s[0]) for s in wine['attributeNames'][0]]
-
-# Initial boxplots & histograms
-plt.figure(figsize=(20,10))
-plt.boxplot(stats.zscore(data))
-plt.xticks(range(len(atts) + 1), [''] + atts, rotation=45, ha='right')
-plt.show()
-
-plt.figure(figsize=(20,10))
-for i in range(len(data[0])):
-    plt.subplot(3, 4, i + 1)
-    plt.hist(data[:,i])
-    plt.xlabel(atts[i])
-plt.show()
-
-# Removing known outliers
-data = np.array([d for d in data if d[1] < 20 and           # Volatide acidity
-                           0.01 < d[7] and d[7] < 10 and    # Density
-                           0.5 < d[10] and d[10] < 200])    # Alcohol
-
-# Clean boxplots & histograms
-plt.figure(figsize=(20,10))
-plt.boxplot(stats.zscore(data))
-plt.xticks(range(len(atts) + 1), [''] + atts, rotation=45, ha='right')
-plt.show()
-
-plt.figure(figsize=(20,10))
-for i in range(len(data[0])):
-    plt.subplot(3, 4, i + 1)
-    plt.hist(data[:,i])
-    plt.xlabel(atts[i])
-plt.show()
-
-# 2.1.2
-data = np.transpose(data)
-plt.figure(figsize=(20,10))
-for i in range(len(data) - 1):
-    plt.subplot(3, 4, i + 1)
-    plt.scatter(data[i], data[11], marker='.', alpha=0.2)
-    plt.xlabel(atts[i])
-plt.show()
-
-fig, ax = plt.subplots(figsize=(10,5))
-it = np.arange(len(data) - 1)
-ax.bar(it, [stats.pearsonr(data[i], data[11])[0] for i in it])
-ax.set_xticks(it + 0.5)
-ax.set_xticklabels(atts, rotation=90, ha='center')
-plt.show()
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