From edda9f68409b9f0c159f2041a303cd5e4e4ad72c Mon Sep 17 00:00:00 2001 From: Devjeet Roy <42415129+devjeetroy98@users.noreply.github.com> Date: Thu, 25 Oct 2018 18:31:42 +0530 Subject: [PATCH] Created using Colaboratory --- assignment3.ipynb | 855 ++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 855 insertions(+) create mode 100644 assignment3.ipynb diff --git a/assignment3.ipynb b/assignment3.ipynb new file mode 100644 index 0000000..f9890bd --- /dev/null +++ b/assignment3.ipynb @@ -0,0 +1,855 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "name": "Untitled7.ipynb", + "version": "0.3.2", + "provenance": [], + "include_colab_link": true + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + } + }, + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "id": "view-in-github", + "colab_type": "text" + }, + "source": [ + "[View in Colaboratory](https://colab.research.google.com/github/devjeetroy98/Assignment-3/blob/devjeetroy98/assignment3.ipynb)" + ] + }, + { + "metadata": { + "id": "LWcsm3L8H4dr", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "LwZaCApSH-jp", + "colab_type": "text" + }, + "cell_type": "markdown", + "source": [ + "Assignment 3 Exercise" + ] + }, + { + "metadata": { + "id": "QVk2S0KmIBJf", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "import numpy as np\n", + "import pandas as pd" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "x8Meb7A1IGYV", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "wine_df=pd.read_csv('https://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data')" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "zSyjiE3lIfQ-", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 198 + }, + "outputId": "78e9d912-a168-4613-d6ad-60cf502743bc" + }, + "cell_type": "code", + "source": [ + "wine_df.head(5)" + ], + "execution_count": 105, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
114.231.712.4315.61272.83.06.282.295.641.043.921065
0113.201.782.1411.21002.652.760.261.284.381.053.401050
1113.162.362.6718.61012.803.240.302.815.681.033.171185
2114.371.952.5016.81133.853.490.242.187.800.863.451480
3113.242.592.8721.01182.802.690.391.824.321.042.93735
4114.201.762.4515.21123.273.390.341.976.751.052.851450
\n", + "
" + ], + "text/plain": [ + " 1 14.23 1.71 2.43 15.6 127 2.8 3.06 .28 2.29 5.64 1.04 3.92 \\\n", + "0 1 13.20 1.78 2.14 11.2 100 2.65 2.76 0.26 1.28 4.38 1.05 3.40 \n", + "1 1 13.16 2.36 2.67 18.6 101 2.80 3.24 0.30 2.81 5.68 1.03 3.17 \n", + "2 1 14.37 1.95 2.50 16.8 113 3.85 3.49 0.24 2.18 7.80 0.86 3.45 \n", + "3 1 13.24 2.59 2.87 21.0 118 2.80 2.69 0.39 1.82 4.32 1.04 2.93 \n", + "4 1 14.20 1.76 2.45 15.2 112 3.27 3.39 0.34 1.97 6.75 1.05 2.85 \n", + "\n", + " 1065 \n", + "0 1050 \n", + "1 1185 \n", + "2 1480 \n", + "3 735 \n", + "4 1450 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 105 + } + ] + }, + { + "metadata": { + "id": "oWTlLp4sInOG", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 198 + }, + "outputId": "6266a206-2a4f-43ec-edc8-94c6491f0af6" + }, + "cell_type": "code", + "source": [ + "wine_df_copy=wine_df.copy()\n", + "wine_df_copy=wine_df_copy.drop(wine_df_copy.index[1::2])\n", + "wine_df_copy.head(5)" + ], + "execution_count": 109, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
114.231.712.4315.61272.83.06.282.295.641.043.921065
0113.201.782.1411.21002.652.760.261.284.381.053.401050
2114.371.952.5016.81133.853.490.242.187.800.863.451480
4114.201.762.4515.21123.273.390.341.976.751.052.851450
6114.062.152.6117.61212.602.510.311.255.051.063.581295
8113.861.352.2716.0982.983.150.221.857.221.013.551045
\n", + "
" + ], + "text/plain": [ + " 1 14.23 1.71 2.43 15.6 127 2.8 3.06 .28 2.29 5.64 1.04 3.92 \\\n", + "0 1 13.20 1.78 2.14 11.2 100 2.65 2.76 0.26 1.28 4.38 1.05 3.40 \n", + "2 1 14.37 1.95 2.50 16.8 113 3.85 3.49 0.24 2.18 7.80 0.86 3.45 \n", + "4 1 14.20 1.76 2.45 15.2 112 3.27 3.39 0.34 1.97 6.75 1.05 2.85 \n", + "6 1 14.06 2.15 2.61 17.6 121 2.60 2.51 0.31 1.25 5.05 1.06 3.58 \n", + "8 1 13.86 1.35 2.27 16.0 98 2.98 3.15 0.22 1.85 7.22 1.01 3.55 \n", + "\n", + " 1065 \n", + "0 1050 \n", + "2 1480 \n", + "4 1450 \n", + "6 1295 \n", + "8 1045 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 109 + } + ] + }, + { + "metadata": { + "id": "Um9yuR6TJN00", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 233 + }, + "outputId": "b70e3bf4-feb1-4122-f9ac-03c10a753e1d" + }, + "cell_type": "code", + "source": [ + "wine_df_copy.columns=['','Alcohol','Malic Acid','Ash','Alcalinity of ash','Magnesium','Total phenols','Flavanoids','Nonflavanoid phenols','Proanthocyanins','Color Intensity','Hue','OD280/OD315 of diluted wines','Proline']\n", + "wine_df_copy.head(5)" + ], + "execution_count": 111, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
AlcoholMalic AcidAshAlcalinity of ashMagnesiumTotal phenolsFlavanoidsNonflavanoid phenolsProanthocyaninsColor IntensityHueOD280/OD315 of diluted winesProline
0113.201.782.1411.21002.652.760.261.284.381.053.401050
2114.371.952.5016.81133.853.490.242.187.800.863.451480
4114.201.762.4515.21123.273.390.341.976.751.052.851450
6114.062.152.6117.61212.602.510.311.255.051.063.581295
8113.861.352.2716.0982.983.150.221.857.221.013.551045
\n", + "
" + ], + "text/plain": [ + " Alcohol Malic Acid Ash Alcalinity of ash Magnesium Total phenols \\\n", + "0 1 13.20 1.78 2.14 11.2 100 2.65 \n", + "2 1 14.37 1.95 2.50 16.8 113 3.85 \n", + "4 1 14.20 1.76 2.45 15.2 112 3.27 \n", + "6 1 14.06 2.15 2.61 17.6 121 2.60 \n", + "8 1 13.86 1.35 2.27 16.0 98 2.98 \n", + "\n", + " Flavanoids Nonflavanoid phenols Proanthocyanins Color Intensity Hue \\\n", + "0 2.76 0.26 1.28 4.38 1.05 \n", + "2 3.49 0.24 2.18 7.80 0.86 \n", + "4 3.39 0.34 1.97 6.75 1.05 \n", + "6 2.51 0.31 1.25 5.05 1.06 \n", + "8 3.15 0.22 1.85 7.22 1.01 \n", + "\n", + " OD280/OD315 of diluted wines Proline \n", + "0 3.40 1050 \n", + "2 3.45 1480 \n", + "4 2.85 1450 \n", + "6 3.58 1295 \n", + "8 3.55 1045 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 111 + } + ] + }, + { + "metadata": { + "id": "iEg-rjhvK2qU", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 198 + }, + "outputId": "bb4993d7-43c5-4a39-adf4-c021f6309be7" + }, + "cell_type": "code", + "source": [ + "for i in range(3):\n", + " wine_df.iloc[i,0]='NaN'\n", + "wine_df.head(5)" + ], + "execution_count": 112, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
114.231.712.4315.61272.83.06.282.295.641.043.921065
0NaN13.201.782.1411.21002.652.760.261.284.381.053.401050
1NaN13.162.362.6718.61012.803.240.302.815.681.033.171185
2NaN14.371.952.5016.81133.853.490.242.187.800.863.451480
3113.242.592.8721.01182.802.690.391.824.321.042.93735
4114.201.762.4515.21123.273.390.341.976.751.052.851450
\n", + "
" + ], + "text/plain": [ + " 1 14.23 1.71 2.43 15.6 127 2.8 3.06 .28 2.29 5.64 1.04 \\\n", + "0 NaN 13.20 1.78 2.14 11.2 100 2.65 2.76 0.26 1.28 4.38 1.05 \n", + "1 NaN 13.16 2.36 2.67 18.6 101 2.80 3.24 0.30 2.81 5.68 1.03 \n", + "2 NaN 14.37 1.95 2.50 16.8 113 3.85 3.49 0.24 2.18 7.80 0.86 \n", + "3 1 13.24 2.59 2.87 21.0 118 2.80 2.69 0.39 1.82 4.32 1.04 \n", + "4 1 14.20 1.76 2.45 15.2 112 3.27 3.39 0.34 1.97 6.75 1.05 \n", + "\n", + " 3.92 1065 \n", + "0 3.40 1050 \n", + "1 3.17 1185 \n", + "2 3.45 1480 \n", + "3 2.93 735 \n", + "4 2.85 1450 " + ] + }, + "metadata": { + "tags": [] + }, + "execution_count": 112 + } + ] + }, + { + "metadata": { + "id": "1--qiJgyLqs1", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 35 + }, + "outputId": "3d62e208-3024-4efc-daaf-7fe1b7cb396d" + }, + "cell_type": "code", + "source": [ + "import random\n", + "num=[]\n", + "for i in range(10):\n", + " num.append(random.randrange(1,160))\n", + "random=num\n", + "print(random)" + ], + "execution_count": 113, + "outputs": [ + { + "output_type": "stream", + "text": [ + "[11, 75, 124, 7, 159, 90, 147, 56, 12, 104]\n" + ], + "name": "stdout" + } + ] + }, + { + "metadata": { + "id": "GB84HdtVMJ5w", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "for i in range(10):\n", + " wine_df.iloc[random[i],0]='nan'" + ], + "execution_count": 0, + "outputs": [] + }, + { + "metadata": { + "id": "iaUiKgLOLqr8", + "colab_type": "code", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 290 + }, + "outputId": "9fa0064d-d064-4df6-8ad1-b2e9cfe16039" + }, + "cell_type": "code", + "source": [ + "null=wine_df.isnull().sum()\n", + "print(null)" + ], + "execution_count": 116, + "outputs": [ + { + "output_type": "stream", + "text": [ + "1 0\n", + "14.23 0\n", + "1.71 0\n", + "2.43 0\n", + "15.6 0\n", + "127 0\n", + "2.8 0\n", + "3.06 0\n", + ".28 0\n", + "2.29 0\n", + "5.64 0\n", + "1.04 0\n", + "3.92 0\n", + "1065 0\n", + "dtype: int64\n" + ], + "name": "stdout" + } + ] + }, + { + "metadata": { + "id": "eg2hevEdLqq3", + "colab_type": "code", + "colab": {} + }, + "cell_type": "code", + "source": [ + "wine_df=wine_df.notnull()" + ], + "execution_count": 0, + "outputs": [] + } + ] +} \ No newline at end of file