RohitR_190121042_Week 8

edit_assignment.py

@@ -0,0 +1,33 @@
+import pandas as pd 
+
+from matplotlib import pyplot as plt
+
+df=pd.read_csv('data.txt',delimiter='\t')
+
+plt.rcParams['figure.figsize']=(20,10)
+
+fig,ax=plt.subplots(nrows=5,ncols=9)
+
+r=c=0
+
+list=[[0,0],[0,1],[0,2],[0,3],[0,4],[0,5],[0,6],[0,7],[0,8],[1,0],[1,1],[1,2],[1,3],[1,4],[1,5],[1,6],[1,7],[1,8],[2,0],[2,1],[2,2],[2,3],[2,4],[2,5],[2,6],[2,7],[2,8],[3,0],[3,1],[3,2],[3,3],[3,4],[3,5],[3,6],[3,7],[3,8],[4,0],[4,1],[4,2],[4,3],[4,4],[4,5],[4,6],[4,7],[4,8]]
+
+flag=-1
+
+for i in range(1,10):
+	for j in range(i+1,11):
+		flag=flag+1
+		r=list[flag][0]
+		c=list[flag][1]
+		for k in range(999):
+			if df['Label'][k]==1:
+				ax[r][c].scatter(df[str(i)][k],df[str(j)][k],color='r')
+			elif df['Label'][k]==2:
+				ax[r][c].scatter(df[str(i)][k],df[str(j)][k],color='b')
+
+		ax[r][c].set_xlabel('feature '+str(i))
+		ax[r][c].set_ylabel('feature '+str(j))
+        ax[0][4].set_title('My Plot')
+
+# print(plt.rcParams['figure.figsize'])
+plt.show()

introduction_to_matrix.ipynb

@@ -0,0 +1,102 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# used for manipulating directory paths\n",
+    "import os\n",
+    "\n",
+    "# Scientific and vector computation for python\n",
+    "import numpy as np\n",
+    "\n",
+    "# Plotting library\n",
+    "from matplotlib import pyplot\n",
+    "from mpl_toolkits.mplot3d import Axes3D  # needed to plot 3-D surfaces\n",
+    "\n",
+    "# library written for this exercise providing additional functions for assignment submission, and others\n",
+    "import utils \n",
+    "\n",
+    "# define the submission/grader object for this exercise\n",
+    "grader = utils.Grader()\n",
+    "\n",
+    "# tells matplotlib to embed plots within the notebook\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def warmUpExercise():\n",
+    "    \"\"\"\n",
+    "    Example function in Python which computes the identity matrix.\n",
+    "    \n",
+    "    Returns\n",
+    "    -------\n",
+    "    A : array_like\n",
+    "        The 5x5 identity matrix.\n",
+    "    \n",
+    "    Instructions\n",
+    "    ------------\n",
+    "    Return the 5x5 identity matrix.\n",
+    "    \"\"\"    \n",
+    "    # ======== YOUR CODE HERE ======\n",
+    "    A = []   # modify this line\n",
+    "    A=np.eye(5)\n",
+    "    \n",
+    "    # ==============================\n",
+    "    return A"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[1., 0., 0., 0., 0.],\n",
+       "       [0., 1., 0., 0., 0.],\n",
+       "       [0., 0., 1., 0., 0.],\n",
+       "       [0., 0., 0., 1., 0.],\n",
+       "       [0., 0., 0., 0., 1.]])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "warmUpExercise()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}