{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Iris" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Introduction:\n", "\n", "This exercise may seem a little bit strange, but keep doing it.\n", "\n", "### Step 1. Import the necessary libraries" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "collapsed": false }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 2. Import the dataset from this [address](https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data). " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 3. Assign it to a variable called iris" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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04.93.01.40.2Iris-setosa
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" ], "text/plain": [ " 5.1 3.5 1.4 0.2 Iris-setosa\n", "0 4.9 3.0 1.4 0.2 Iris-setosa\n", "1 4.7 3.2 1.3 0.2 Iris-setosa\n", "2 4.6 3.1 1.5 0.2 Iris-setosa\n", "3 5.0 3.6 1.4 0.2 Iris-setosa\n", "4 5.4 3.9 1.7 0.4 Iris-setosa" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 4. Create columns for the dataset" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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04.93.01.40.2Iris-setosa
14.73.21.30.2Iris-setosa
24.63.11.50.2Iris-setosa
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width class\n", "0 4.9 3.0 1.4 0.2 Iris-setosa\n", "1 4.7 3.2 1.3 0.2 Iris-setosa\n", "2 4.6 3.1 1.5 0.2 Iris-setosa\n", "3 5.0 3.6 1.4 0.2 Iris-setosa\n", "4 5.4 3.9 1.7 0.4 Iris-setosa" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# 1. sepal_length (in cm)\n", "# 2. sepal_width (in cm)\n", "# 3. petal_length (in cm)\n", "# 4. petal_width (in cm)\n", "# 5. class" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 5. Is there any missing value in the dataframe?" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/plain": [ "sepal_length 0\n", "sepal_width 0\n", "petal_length 0\n", "petal_width 0\n", "class 0\n", "dtype: int64" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 6. Lets set the values of the rows 10 to 29 of the column 'petal_length' to NaN" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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24.63.11.50.2Iris-setosa
35.03.61.40.2Iris-setosa
45.43.91.70.4Iris-setosa
54.63.41.40.3Iris-setosa
65.03.41.50.2Iris-setosa
74.42.91.40.2Iris-setosa
84.93.11.50.1Iris-setosa
95.43.71.50.2Iris-setosa
104.83.4NaN0.2Iris-setosa
114.83.0NaN0.1Iris-setosa
124.33.0NaN0.1Iris-setosa
135.84.0NaN0.2Iris-setosa
145.74.4NaN0.4Iris-setosa
155.43.9NaN0.4Iris-setosa
165.13.5NaN0.3Iris-setosa
175.73.8NaN0.3Iris-setosa
185.13.8NaN0.3Iris-setosa
195.43.4NaN0.2Iris-setosa
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width class\n", "0 4.9 3.0 1.4 0.2 Iris-setosa\n", "1 4.7 3.2 1.3 0.2 Iris-setosa\n", "2 4.6 3.1 1.5 0.2 Iris-setosa\n", "3 5.0 3.6 1.4 0.2 Iris-setosa\n", "4 5.4 3.9 1.7 0.4 Iris-setosa\n", "5 4.6 3.4 1.4 0.3 Iris-setosa\n", "6 5.0 3.4 1.5 0.2 Iris-setosa\n", "7 4.4 2.9 1.4 0.2 Iris-setosa\n", "8 4.9 3.1 1.5 0.1 Iris-setosa\n", "9 5.4 3.7 1.5 0.2 Iris-setosa\n", "10 4.8 3.4 NaN 0.2 Iris-setosa\n", "11 4.8 3.0 NaN 0.1 Iris-setosa\n", "12 4.3 3.0 NaN 0.1 Iris-setosa\n", "13 5.8 4.0 NaN 0.2 Iris-setosa\n", "14 5.7 4.4 NaN 0.4 Iris-setosa\n", "15 5.4 3.9 NaN 0.4 Iris-setosa\n", "16 5.1 3.5 NaN 0.3 Iris-setosa\n", "17 5.7 3.8 NaN 0.3 Iris-setosa\n", "18 5.1 3.8 NaN 0.3 Iris-setosa\n", "19 5.4 3.4 NaN 0.2 Iris-setosa" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 7. Good, now lets substitute the NaN values to 1.0" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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04.93.01.40.2Iris-setosa
14.73.21.30.2Iris-setosa
24.63.11.50.2Iris-setosa
35.03.61.40.2Iris-setosa
45.43.91.70.4Iris-setosa
54.63.41.40.3Iris-setosa
65.03.41.50.2Iris-setosa
74.42.91.40.2Iris-setosa
84.93.11.50.1Iris-setosa
95.43.71.50.2Iris-setosa
104.83.41.00.2Iris-setosa
114.83.01.00.1Iris-setosa
124.33.01.00.1Iris-setosa
135.84.01.00.2Iris-setosa
145.74.41.00.4Iris-setosa
155.43.91.00.4Iris-setosa
165.13.51.00.3Iris-setosa
175.73.81.00.3Iris-setosa
185.13.81.00.3Iris-setosa
195.43.41.00.2Iris-setosa
205.13.71.00.4Iris-setosa
214.63.61.00.2Iris-setosa
225.13.31.00.5Iris-setosa
234.83.41.00.2Iris-setosa
245.03.01.00.2Iris-setosa
255.03.41.00.4Iris-setosa
265.23.51.00.2Iris-setosa
275.23.41.00.2Iris-setosa
284.73.21.00.2Iris-setosa
294.83.11.00.2Iris-setosa
..................
1196.93.25.72.3Iris-virginica
1205.62.84.92.0Iris-virginica
1217.72.86.72.0Iris-virginica
1226.32.74.91.8Iris-virginica
1236.73.35.72.1Iris-virginica
1247.23.26.01.8Iris-virginica
1256.22.84.81.8Iris-virginica
1266.13.04.91.8Iris-virginica
1276.42.85.62.1Iris-virginica
1287.23.05.81.6Iris-virginica
1297.42.86.11.9Iris-virginica
1307.93.86.42.0Iris-virginica
1316.42.85.62.2Iris-virginica
1326.32.85.11.5Iris-virginica
1336.12.65.61.4Iris-virginica
1347.73.06.12.3Iris-virginica
1356.33.45.62.4Iris-virginica
1366.43.15.51.8Iris-virginica
1376.03.04.81.8Iris-virginica
1386.93.15.42.1Iris-virginica
1396.73.15.62.4Iris-virginica
1406.93.15.12.3Iris-virginica
1415.82.75.11.9Iris-virginica
1426.83.25.92.3Iris-virginica
1436.73.35.72.5Iris-virginica
1446.73.05.22.3Iris-virginica
1456.32.55.01.9Iris-virginica
1466.53.05.22.0Iris-virginica
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width class\n", "0 4.9 3.0 1.4 0.2 Iris-setosa\n", "1 4.7 3.2 1.3 0.2 Iris-setosa\n", "2 4.6 3.1 1.5 0.2 Iris-setosa\n", "3 5.0 3.6 1.4 0.2 Iris-setosa\n", "4 5.4 3.9 1.7 0.4 Iris-setosa\n", "5 4.6 3.4 1.4 0.3 Iris-setosa\n", "6 5.0 3.4 1.5 0.2 Iris-setosa\n", "7 4.4 2.9 1.4 0.2 Iris-setosa\n", "8 4.9 3.1 1.5 0.1 Iris-setosa\n", "9 5.4 3.7 1.5 0.2 Iris-setosa\n", "10 4.8 3.4 1.0 0.2 Iris-setosa\n", "11 4.8 3.0 1.0 0.1 Iris-setosa\n", "12 4.3 3.0 1.0 0.1 Iris-setosa\n", "13 5.8 4.0 1.0 0.2 Iris-setosa\n", "14 5.7 4.4 1.0 0.4 Iris-setosa\n", "15 5.4 3.9 1.0 0.4 Iris-setosa\n", "16 5.1 3.5 1.0 0.3 Iris-setosa\n", "17 5.7 3.8 1.0 0.3 Iris-setosa\n", "18 5.1 3.8 1.0 0.3 Iris-setosa\n", "19 5.4 3.4 1.0 0.2 Iris-setosa\n", "20 5.1 3.7 1.0 0.4 Iris-setosa\n", "21 4.6 3.6 1.0 0.2 Iris-setosa\n", "22 5.1 3.3 1.0 0.5 Iris-setosa\n", "23 4.8 3.4 1.0 0.2 Iris-setosa\n", "24 5.0 3.0 1.0 0.2 Iris-setosa\n", "25 5.0 3.4 1.0 0.4 Iris-setosa\n", "26 5.2 3.5 1.0 0.2 Iris-setosa\n", "27 5.2 3.4 1.0 0.2 Iris-setosa\n", "28 4.7 3.2 1.0 0.2 Iris-setosa\n", "29 4.8 3.1 1.0 0.2 Iris-setosa\n", ".. ... ... ... ... ...\n", "119 6.9 3.2 5.7 2.3 Iris-virginica\n", "120 5.6 2.8 4.9 2.0 Iris-virginica\n", "121 7.7 2.8 6.7 2.0 Iris-virginica\n", "122 6.3 2.7 4.9 1.8 Iris-virginica\n", "123 6.7 3.3 5.7 2.1 Iris-virginica\n", "124 7.2 3.2 6.0 1.8 Iris-virginica\n", "125 6.2 2.8 4.8 1.8 Iris-virginica\n", "126 6.1 3.0 4.9 1.8 Iris-virginica\n", "127 6.4 2.8 5.6 2.1 Iris-virginica\n", "128 7.2 3.0 5.8 1.6 Iris-virginica\n", "129 7.4 2.8 6.1 1.9 Iris-virginica\n", "130 7.9 3.8 6.4 2.0 Iris-virginica\n", "131 6.4 2.8 5.6 2.2 Iris-virginica\n", "132 6.3 2.8 5.1 1.5 Iris-virginica\n", "133 6.1 2.6 5.6 1.4 Iris-virginica\n", "134 7.7 3.0 6.1 2.3 Iris-virginica\n", "135 6.3 3.4 5.6 2.4 Iris-virginica\n", "136 6.4 3.1 5.5 1.8 Iris-virginica\n", "137 6.0 3.0 4.8 1.8 Iris-virginica\n", "138 6.9 3.1 5.4 2.1 Iris-virginica\n", "139 6.7 3.1 5.6 2.4 Iris-virginica\n", "140 6.9 3.1 5.1 2.3 Iris-virginica\n", "141 5.8 2.7 5.1 1.9 Iris-virginica\n", "142 6.8 3.2 5.9 2.3 Iris-virginica\n", "143 6.7 3.3 5.7 2.5 Iris-virginica\n", "144 6.7 3.0 5.2 2.3 Iris-virginica\n", "145 6.3 2.5 5.0 1.9 Iris-virginica\n", "146 6.5 3.0 5.2 2.0 Iris-virginica\n", "147 6.2 3.4 5.4 2.3 Iris-virginica\n", "148 5.9 3.0 5.1 1.8 Iris-virginica\n", "\n", "[149 rows x 5 columns]" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 8. Now let's delete the column class" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "collapsed": false }, "outputs": [ { "data": { "text/html": [ "
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45.43.91.70.4
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "0 4.9 3.0 1.4 0.2\n", "1 4.7 3.2 1.3 0.2\n", "2 4.6 3.1 1.5 0.2\n", "3 5.0 3.6 1.4 0.2\n", "4 5.4 3.9 1.7 0.4" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 9. Set the first 3 rows as NaN" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "collapsed": false }, "outputs": [ { "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", "
sepal_lengthsepal_widthpetal_lengthpetal_width
0NaNNaNNaNNaN
1NaNNaNNaNNaN
2NaNNaNNaNNaN
35.03.41.50.2
44.42.91.40.2
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" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "0 NaN NaN NaN NaN\n", "1 NaN NaN NaN NaN\n", "2 NaN NaN NaN NaN\n", "3 5.0 3.4 1.5 0.2\n", "4 4.4 2.9 1.4 0.2" ] }, "execution_count": 52, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 10. Delete the rows that have NaN" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "collapsed": false }, "outputs": [ { "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", "
sepal_lengthsepal_widthpetal_lengthpetal_width
35.03.41.50.2
44.42.91.40.2
54.93.11.50.1
65.43.71.50.2
74.83.41.00.2
\n", "
" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "3 5.0 3.4 1.5 0.2\n", "4 4.4 2.9 1.4 0.2\n", "5 4.9 3.1 1.5 0.1\n", "6 5.4 3.7 1.5 0.2\n", "7 4.8 3.4 1.0 0.2" ] }, "execution_count": 53, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Step 11. Reset the index so it begins with 0 again" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "collapsed": false }, "outputs": [ { "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", "
sepal_lengthsepal_widthpetal_lengthpetal_width
05.03.41.50.2
14.42.91.40.2
24.93.11.50.1
35.43.71.50.2
44.83.41.00.2
\n", "
" ], "text/plain": [ " sepal_length sepal_width petal_length petal_width\n", "0 5.0 3.4 1.5 0.2\n", "1 4.4 2.9 1.4 0.2\n", "2 4.9 3.1 1.5 0.1\n", "3 5.4 3.7 1.5 0.2\n", "4 4.8 3.4 1.0 0.2" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### BONUS: Create your own question and answer it." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 2", "language": "python", "name": "python2" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 2 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython2", "version": "2.7.11" } }, "nbformat": 4, "nbformat_minor": 0 }