{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Data Frames\n", "\n", "By Alex Jermakov\n", "\n", "We will start, as usual, by importing all the libraries we need." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "\n", "# Fancy plots\n", "plt.style.use('fivethirtyeight')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we are going to need some data. Go ahead and download\n", "[iris.csv]({{ site.baseurl }}/data/iris.csv) and import it as\n", "a dataframe (save the file to the same directory from which you\n", "are running this notebook to make your life easier)." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "iris = pd.read_csv('iris.csv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "At this moment we have no clue about what data are contained\n", "inside this dataframe. First thing we can do is simply print\n", "out the whole dataframe." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SepalLengthSepalWidthPetalLengthPetalWidthName
05.13.51.40.2Iris-setosa
14.93.01.40.2Iris-setosa
24.73.21.30.2Iris-setosa
34.63.11.50.2Iris-setosa
45.03.61.40.2Iris-setosa
55.43.91.70.4Iris-setosa
64.63.41.40.3Iris-setosa
75.03.41.50.2Iris-setosa
84.42.91.40.2Iris-setosa
94.93.11.50.1Iris-setosa
105.43.71.50.2Iris-setosa
114.83.41.60.2Iris-setosa
124.83.01.40.1Iris-setosa
134.33.01.10.1Iris-setosa
145.84.01.20.2Iris-setosa
155.74.41.50.4Iris-setosa
165.43.91.30.4Iris-setosa
175.13.51.40.3Iris-setosa
185.73.81.70.3Iris-setosa
195.13.81.50.3Iris-setosa
205.43.41.70.2Iris-setosa
215.13.71.50.4Iris-setosa
224.63.61.00.2Iris-setosa
235.13.31.70.5Iris-setosa
244.83.41.90.2Iris-setosa
255.03.01.60.2Iris-setosa
265.03.41.60.4Iris-setosa
275.23.51.50.2Iris-setosa
285.23.41.40.2Iris-setosa
294.73.21.60.2Iris-setosa
..................
1206.93.25.72.3Iris-virginica
1215.62.84.92.0Iris-virginica
1227.72.86.72.0Iris-virginica
1236.32.74.91.8Iris-virginica
1246.73.35.72.1Iris-virginica
1257.23.26.01.8Iris-virginica
1266.22.84.81.8Iris-virginica
1276.13.04.91.8Iris-virginica
1286.42.85.62.1Iris-virginica
1297.23.05.81.6Iris-virginica
1307.42.86.11.9Iris-virginica
1317.93.86.42.0Iris-virginica
1326.42.85.62.2Iris-virginica
1336.32.85.11.5Iris-virginica
1346.12.65.61.4Iris-virginica
1357.73.06.12.3Iris-virginica
1366.33.45.62.4Iris-virginica
1376.43.15.51.8Iris-virginica
1386.03.04.81.8Iris-virginica
1396.93.15.42.1Iris-virginica
1406.73.15.62.4Iris-virginica
1416.93.15.12.3Iris-virginica
1425.82.75.11.9Iris-virginica
1436.83.25.92.3Iris-virginica
1446.73.35.72.5Iris-virginica
1456.73.05.22.3Iris-virginica
1466.32.55.01.9Iris-virginica
1476.53.05.22.0Iris-virginica
1486.23.45.42.3Iris-virginica
1495.93.05.11.8Iris-virginica
\n", "

150 rows × 5 columns

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" ], "text/plain": [ " SepalLength SepalWidth PetalLength PetalWidth Name\n", "0 5.1 3.5 1.4 0.2 Iris-setosa\n", "1 4.9 3.0 1.4 0.2 Iris-setosa\n", "2 4.7 3.2 1.3 0.2 Iris-setosa\n", "3 4.6 3.1 1.5 0.2 Iris-setosa\n", "4 5.0 3.6 1.4 0.2 Iris-setosa\n", "5 5.4 3.9 1.7 0.4 Iris-setosa\n", "6 4.6 3.4 1.4 0.3 Iris-setosa\n", "7 5.0 3.4 1.5 0.2 Iris-setosa\n", "8 4.4 2.9 1.4 0.2 Iris-setosa\n", "9 4.9 3.1 1.5 0.1 Iris-setosa\n", "10 5.4 3.7 1.5 0.2 Iris-setosa\n", "11 4.8 3.4 1.6 0.2 Iris-setosa\n", "12 4.8 3.0 1.4 0.1 Iris-setosa\n", "13 4.3 3.0 1.1 0.1 Iris-setosa\n", "14 5.8 4.0 1.2 0.2 Iris-setosa\n", "15 5.7 4.4 1.5 0.4 Iris-setosa\n", "16 5.4 3.9 1.3 0.4 Iris-setosa\n", "17 5.1 3.5 1.4 0.3 Iris-setosa\n", "18 5.7 3.8 1.7 0.3 Iris-setosa\n", "19 5.1 3.8 1.5 0.3 Iris-setosa\n", "20 5.4 3.4 1.7 0.2 Iris-setosa\n", "21 5.1 3.7 1.5 0.4 Iris-setosa\n", "22 4.6 3.6 1.0 0.2 Iris-setosa\n", "23 5.1 3.3 1.7 0.5 Iris-setosa\n", "24 4.8 3.4 1.9 0.2 Iris-setosa\n", "25 5.0 3.0 1.6 0.2 Iris-setosa\n", "26 5.0 3.4 1.6 0.4 Iris-setosa\n", "27 5.2 3.5 1.5 0.2 Iris-setosa\n", "28 5.2 3.4 1.4 0.2 Iris-setosa\n", "29 4.7 3.2 1.6 0.2 Iris-setosa\n", ".. ... ... ... ... ...\n", "120 6.9 3.2 5.7 2.3 Iris-virginica\n", "121 5.6 2.8 4.9 2.0 Iris-virginica\n", "122 7.7 2.8 6.7 2.0 Iris-virginica\n", "123 6.3 2.7 4.9 1.8 Iris-virginica\n", "124 6.7 3.3 5.7 2.1 Iris-virginica\n", "125 7.2 3.2 6.0 1.8 Iris-virginica\n", "126 6.2 2.8 4.8 1.8 Iris-virginica\n", "127 6.1 3.0 4.9 1.8 Iris-virginica\n", "128 6.4 2.8 5.6 2.1 Iris-virginica\n", "129 7.2 3.0 5.8 1.6 Iris-virginica\n", "130 7.4 2.8 6.1 1.9 Iris-virginica\n", "131 7.9 3.8 6.4 2.0 Iris-virginica\n", "132 6.4 2.8 5.6 2.2 Iris-virginica\n", "133 6.3 2.8 5.1 1.5 Iris-virginica\n", "134 6.1 2.6 5.6 1.4 Iris-virginica\n", "135 7.7 3.0 6.1 2.3 Iris-virginica\n", "136 6.3 3.4 5.6 2.4 Iris-virginica\n", "137 6.4 3.1 5.5 1.8 Iris-virginica\n", "138 6.0 3.0 4.8 1.8 Iris-virginica\n", "139 6.9 3.1 5.4 2.1 Iris-virginica\n", "140 6.7 3.1 5.6 2.4 Iris-virginica\n", "141 6.9 3.1 5.1 2.3 Iris-virginica\n", "142 5.8 2.7 5.1 1.9 Iris-virginica\n", "143 6.8 3.2 5.9 2.3 Iris-virginica\n", "144 6.7 3.3 5.7 2.5 Iris-virginica\n", "145 6.7 3.0 5.2 2.3 Iris-virginica\n", "146 6.3 2.5 5.0 1.9 Iris-virginica\n", "147 6.5 3.0 5.2 2.0 Iris-virginica\n", "148 6.2 3.4 5.4 2.3 Iris-virginica\n", "149 5.9 3.0 5.1 1.8 Iris-virginica\n", "\n", "[150 rows x 5 columns]" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "But more often than not we don't need to see ~60 entires to get\n", "the idea of what we are looking at. All we want is the column\n", "names and some examples to understand the format the data are\n", "in. For these purposes we can use `head` method of the data\n", "frame." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SepalLengthSepalWidthPetalLengthPetalWidthName
05.13.51.40.2Iris-setosa
14.93.01.40.2Iris-setosa
24.73.21.30.2Iris-setosa
34.63.11.50.2Iris-setosa
45.03.61.40.2Iris-setosa
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" ], "text/plain": [ " SepalLength SepalWidth PetalLength PetalWidth Name\n", "0 5.1 3.5 1.4 0.2 Iris-setosa\n", "1 4.9 3.0 1.4 0.2 Iris-setosa\n", "2 4.7 3.2 1.3 0.2 Iris-setosa\n", "3 4.6 3.1 1.5 0.2 Iris-setosa\n", "4 5.0 3.6 1.4 0.2 Iris-setosa" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "By default, `head()` displays the first five rows, but we have the\n", "option to pass it a specific number of rows we want to see." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SepalLengthSepalWidthPetalLengthPetalWidthName
05.13.51.40.2Iris-setosa
14.93.01.40.2Iris-setosa
24.73.21.30.2Iris-setosa
34.63.11.50.2Iris-setosa
45.03.61.40.2Iris-setosa
55.43.91.70.4Iris-setosa
64.63.41.40.3Iris-setosa
75.03.41.50.2Iris-setosa
84.42.91.40.2Iris-setosa
94.93.11.50.1Iris-setosa
\n", "
" ], "text/plain": [ " SepalLength SepalWidth PetalLength PetalWidth Name\n", "0 5.1 3.5 1.4 0.2 Iris-setosa\n", "1 4.9 3.0 1.4 0.2 Iris-setosa\n", "2 4.7 3.2 1.3 0.2 Iris-setosa\n", "3 4.6 3.1 1.5 0.2 Iris-setosa\n", "4 5.0 3.6 1.4 0.2 Iris-setosa\n", "5 5.4 3.9 1.7 0.4 Iris-setosa\n", "6 4.6 3.4 1.4 0.3 Iris-setosa\n", "7 5.0 3.4 1.5 0.2 Iris-setosa\n", "8 4.4 2.9 1.4 0.2 Iris-setosa\n", "9 4.9 3.1 1.5 0.1 Iris-setosa" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris.head(10)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Okay, now we know that our dataframe has five columns, that describe\n", "the properties of different species of irises. _But wait!_, you may\n", "ask, _there are [260–300 species of iris\n", "genus](https://www.pacificbulbsociety.org/pbswiki/index.php/Iris) and\n", "there is no way they can all be represented in our 150 row dataframe!_.\n", "Well, my educated friend, you are absolutely right. It might be a good\n", "idea to take a look at all the _unique_ values we have in our `Name`\n", "column. To do that we extract our `Name` column as a Series." ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "0 Iris-setosa\n", "1 Iris-setosa\n", "2 Iris-setosa\n", "3 Iris-setosa\n", "4 Iris-setosa\n", "5 Iris-setosa\n", "6 Iris-setosa\n", "7 Iris-setosa\n", "8 Iris-setosa\n", "9 Iris-setosa\n", "10 Iris-setosa\n", "11 Iris-setosa\n", "12 Iris-setosa\n", "13 Iris-setosa\n", "14 Iris-setosa\n", "15 Iris-setosa\n", "16 Iris-setosa\n", "17 Iris-setosa\n", "18 Iris-setosa\n", "19 Iris-setosa\n", "20 Iris-setosa\n", "21 Iris-setosa\n", "22 Iris-setosa\n", "23 Iris-setosa\n", "24 Iris-setosa\n", "25 Iris-setosa\n", "26 Iris-setosa\n", "27 Iris-setosa\n", "28 Iris-setosa\n", "29 Iris-setosa\n", " ... \n", "120 Iris-virginica\n", "121 Iris-virginica\n", "122 Iris-virginica\n", "123 Iris-virginica\n", "124 Iris-virginica\n", "125 Iris-virginica\n", "126 Iris-virginica\n", "127 Iris-virginica\n", "128 Iris-virginica\n", "129 Iris-virginica\n", "130 Iris-virginica\n", "131 Iris-virginica\n", "132 Iris-virginica\n", "133 Iris-virginica\n", "134 Iris-virginica\n", "135 Iris-virginica\n", "136 Iris-virginica\n", "137 Iris-virginica\n", "138 Iris-virginica\n", "139 Iris-virginica\n", "140 Iris-virginica\n", "141 Iris-virginica\n", "142 Iris-virginica\n", "143 Iris-virginica\n", "144 Iris-virginica\n", "145 Iris-virginica\n", "146 Iris-virginica\n", "147 Iris-virginica\n", "148 Iris-virginica\n", "149 Iris-virginica\n", "Name: Name, Length: 150, dtype: object" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris_names = iris[\"Name\"]\n", "iris_names" ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "pandas.core.series.Series" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "type(iris_names)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we can use the `unique` method of the `Series`:" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array(['Iris-setosa', 'Iris-versicolor', 'Iris-virginica'], dtype=object)" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "iris_names.unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We see above that our dataset deals with only three species of iris:\n", "[Iris\n", "Setosa](https://apps.rhs.org.uk/plantselectorimages/detail/RHS_PUB0001482_1050.JPG),\n", "[Iris\n", "Versicolor](https://gardengoodsdirect.com/wp-content/uploads/2017/03/Iris_versicolor_3.jpg)\n", "and [Iris\n", "Virginica](https://plants.ces.ncsu.edu/media/images/Iris-virginica--Justin-Meissen--CC-BY-SA.jpg)\n", "\n", "We are going to look at the similarities and differences between the\n", "species later, but first, let's get familiar with each of them\n", "separately. For that, we can create a separate dataframe for each of\n", "the species." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We need to select the rows that correspond to each species. Let's start by selecting the rows that correspond to `'Iris-setosa'`.\n", "\n", "To select rows, we generally use the `loc` attribute of the data frame.\n", "\n", "Read `loc` as \"locate\". The attribute allows us to locate rows of interest. Here we use `loc` to select the `'Iris-setosa'` rows." ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "setosa = iris.loc[iris[\"Name\"]=='Iris-setosa']" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Make sure you understand the line above. In order to do that, dissect\n", "it bit by bit.\n", "\n", "* What does `iris[\"Name\"]` return?\n", "* What does `iris[\"Name\"]=='Iris-setosa'` return? Why? Is this familiar\n", " behaviour?\n", "* What is going to happen when you type `setosa`?\n", "\n", "Now you can go ahead and create dataframes for the other two species." ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "# Put code here to create dataframes for other two species\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If we want to take a closer look at any one of the species-specific\n", "dataframes that we now have, a good starting point is the `describe`\n", "method of Data Frames (or Series)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SepalLengthSepalWidthPetalLengthPetalWidth
count50.0000050.00000050.00000050.00000
mean5.006003.4180001.4640000.24400
std0.352490.3810240.1735110.10721
min4.300002.3000001.0000000.10000
25%4.800003.1250001.4000000.20000
50%5.000003.4000001.5000000.20000
75%5.200003.6750001.5750000.30000
max5.800004.4000001.9000000.60000
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" ], "text/plain": [ " SepalLength SepalWidth PetalLength PetalWidth\n", "count 50.00000 50.000000 50.000000 50.00000\n", "mean 5.00600 3.418000 1.464000 0.24400\n", "std 0.35249 0.381024 0.173511 0.10721\n", "min 4.30000 2.300000 1.000000 0.10000\n", "25% 4.80000 3.125000 1.400000 0.20000\n", "50% 5.00000 3.400000 1.500000 0.20000\n", "75% 5.20000 3.675000 1.575000 0.30000\n", "max 5.80000 4.400000 1.900000 0.60000" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "setosa.describe()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The first thing to note is that `describe()` does not include the\n", "`Name` column. It shows only the _numerical_ data. From this we can see\n", "that Iris Setosa is not a very versatile flower: deviations from the\n", "mean are quite small and the vast majority of flowers are quite similar\n", "in every way with the exception of _Petal Width_, which has outliers\n", "about six times the mean width.\n", "\n", "Use `describe` on the dataframes for the other two species. Can you\n", "spot anything interesting?" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "# Use describe on the other two species.\n", "# See if you can spot any patterns in the differences.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Okay, numbers are cool and all, but let's create some _graphs_. Since\n", "we mentioned that the _Petal Width_ of Iris Setosa might be interesting\n", "to look at, let's look at the histogram." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Hint**: In order to save yourself **A LOT** of time, please start\n", "using TAB autocompletion if you haven't already: Instead of typing\n", "`setosa[\"PetalWidth\"]`, then correcting typos, then realising it's\n", "case-sensitive and redoing everything, just do `seto`, `[\"P`,\n", "selecting the column you want, and press Enter." ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "setosa[\"PetalWidth\"].hist()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Something is clearly wrong with our histogram. It shows the\n", "information, sure. But what are those gaps? If you press `SHIFT+TAB`\n", "while being inside the parentheses of `hist()`, you can see all the\n", "arguments you can provide to it. Note that one of the arguments is\n", "called `bins`. It has a default value of `10`, so our default\n", "histogram above tries to split the data into ten bins." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Have a look at the unique values in `setosa[\"PetalWidth\"]`:" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "array([0.2, 0.4, 0.3, 0.1, 0.5, 0.6])" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "setosa[\"PetalWidth\"].unique()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "As you see, all the values are one of `0.1, 0.2, 0.3, 0.4, 0.5, 0.6`, so splitting the values into ten bins is going to leave some empty bins, which is what you see above." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Try using the `bin` argument to `hist`, to adjust the number of bins.\n", "You want a number of bins that makes the histogram more readable. What\n", "number makes more sense than `10` in our case? Why?" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "# Make a histogram of the setosa PetalWidth with a suitable number of\n", "# bins.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Replace this text to say why your chosen bin number above is the\n", "right one in this case.**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If there are any other histograms you think are worth looking at, feel\n", "free to plot them, too.\n", "\n", "But histograms describe the properties of one particular column of a\n", "dataframe. And the real power of data science is in seeing\n", "relationships between different properties.\n", "\n", "Is there a relationship between Sepal Length and Petal Length? Let's\n", "find out!" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "setosa.plot.scatter('SepalLength', 'PetalLength')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Hmm, doesn't look that related. Is that the case for all three\n", "species?)\n" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [], "source": [ "# Code here to do SepalLength vs PetalLength plots for the other two\n", "# species.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What about Sepal Length and Sepal Width?" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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VV9I/j6p5/Rjgq+nzAHyV2MzM2qaV29NbukPQyqGMHVGzzPyDX23inKUb2UFyXnzhO6dx8kG9bdm2mY1Py8VH0hxJh2cRxvJXxo6oWWauFCmAHcBZS30J1qzTWrk9fX9JdwO/BG5NXztF0mVZhbPslbEjapaZdzRYNrP8tdKi+jbwI6AX2J6+dgvwJ+0OZfkpY0fULDPX/kD4fLdZ57Xyc3gY8A8RsYPkpgkiYhDoyyKY5aOMHVGzzLzwndN2/lBUrlGZWWe1ctff8yRTeuwcLV3SG0kmT7SSKmNH1Cwzn3xQr2+eMCuYVlpU/wdYIukMYLKkDwKL8BBKZmaWoVZuT/8XSS8C5wCrSKb3+JuIuCGrcGZmZg1bVJLeImk+QFqUTieZRHE/4ARJezexjW5JD0j6RTry+t+Nss5USYskPSPpfkkHtPh3MTOzCaiZU3+XAq+uWv5nkmtV3wb+EPhSE9vYChwdEW8GDgaOH6Uv1pnA+oh4LXAJGZ1SXLlxO8ctWcshP/wtxy1Zy7Obtjf+UIvbft/y7rZv23ZZNrCF2Vet4fBlPcy+ag13D2xp27azOj58bJiNXzOF6g0kU88jaTrwbuC0iPg68EHgzxptIBKb08W90kftLHrvAa5Mn18LHJPFXFeVzqIrNo60vbNoGTvPllFl5uAR1PaZg7M6PnxsmI1fM9eoJgPb0ueHAwMR8TRARKxKi1dDkrqAB0laY1+PiPtrVtmP5NoXETEsaRB4JbButO319/c387W/Z2BTN9X1eWDT0Li3lee281CWrFuGewBVLe8o/L9h2Y8NKM/xUc2Z89GOzPPmzRvzvWYK1ePA+4FrgFNJR6UAkLQfMNhMiIgYAQ5OC9v1kuZHxGPNfHY09f5S9cx6ai2rhrbtWu7tbtstzlluO2vJrd7j26d567lvDZuHdzXIeyZPalv2rP4Ny3xsQLmOjwpnzkcemZs59fc54NuSXiI57Vd97egDwN2tfGFEbAB+Bhxf89ZzJFOHIGkySUfiF1vZdjMqnUUPnNbV/s6iJew8W0aVmYO7iLbPHJzV8eFjw2z8GraoImKZpP2B1wFPR0T15Ik/Aq5utA1JM4HtEbFBUg/JsEu1N0ssBj4C3AucAtweEbXXsXZbpbNoFsrYebaMKjMHZ/GbXFbHh48Ns/Frqh9VWpweHOX1p5r8nlnAlel1qknANRGxRNJFwPKIWAxcDlwl6RngJZLTjGZmtodrZQilcYuIR4A/HuX1C6qeD5FcCzMzM9vJg0ObmVmhuVCZmVmhuVC1kUcfMDNrPxeqNvLoA2Zm7edC1UZlnNbdzKzoXKjaqIzTupuZFZ0LVRt59AEzs/bLpR/VnsKjD5iZtZ9bVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmguVGZmVmi5FCpJcyT9TNITkh6XdN4o6xwpaVDSw+njgjyymZlZsU3O6XuGgU9FxEOSeoEHJd0SEU/UrHdXRJyYUyYzMyuBXFpUETEQEQ+lzzcBTwL75fHdZmZWboqIfL9QOgBYCsyPiI1Vrx8J/BBYDawBPh0Rj1d/dnBwcGfY/v7+HNKamVke5s2bt/N5X1+fqt/L69QfAJL2JilGf1FdpFIPAXMjYrOkE4D/C8yr3UZF9V+qaPr7+wudbzTOnI8yZoZy5nbmfOSRObe7/iTtRVKkvhcR19W+HxEbI2Jz+vzHwF6SZuSVz8zMiimvu/4EXA48GRH/NMY6r07XQ9JhabYX88hnZmbFldepvyOADwGPSno4fe2vgP0BIuJbwCnAxyUNA1uAUyPvC2hmZlY4uRSqiFgGqME6XwO+lkceMzMrD49MYWZmheZCZWZmheZCZWZmheZCZWZmheZCZWZmheZCZWZmheZCZWZmheZCZWZmheZCZWZmheZCZWZmhZbrNB82Pis3bufspRtYt3WEGVO7WLhgOnN79+p0LDOzXLhFVQJnL93AA2u3sWLjCA+s3cZZd27odCQzs9y4UJXAuq0jdZfNzCYyF6oSmDG1q+6ymdlE5kJVAgsXTOewmVM4cFoXh82cwsIF0zsdycwsN76ZogTm9u7FzSfO7HQMM7OOcIvKzMwKzYXKzMwKzYXKzMwKzYXKzMwKzYXKzMwKzYXKzMwKTRHR6QxNGxwcLE9YMzMbl76+PlUvu0VlZmaF5kJlZmaFVqpTf2Zmtudxi8rMzArNhcrMzArNhWo3SOqS9HNJS+qsc7KkkHRontnG0iizpD+X9ISkxyX9W975xlIvt6T9Jf0sff8RSSd0ImNNppWSHpX0sKTlo7wvSV+V9Eya+ZBO5KzJ1Cjzf0+zPirpHklv7kTOWo1yV633VknDkk7JM98YWRpmlnRk+v7jku7MO+MoeRodH32SbpT0izTzGe36bo+evnvOA54Epo32pqTedJ378wzVwJiZJc0DzgeOiIj1kv5j3uHqqLev/wa4JiK+KemNwI+BA3LMNpajImLdGO+9C5iXPt4GfDP9s9PqZf41sCA9Nt4F/DPFyAz1cyOpC7gYuDm/SA2NmVnSdOAbwPER8ZsC/SzW28//E3giIv5M0kzgKUnfi4htu/ulblGNk6TZwLuBy+qs9nmSH46hXEI10ETms4CvR8R6gIh4Ia9s9TSRO9hVwPqANXnk2k3vAb4TifuA6ZJmdTpUPRFxT+XYAO4DZncyT4s+CfwQKMQx3YT/BlwXEb+B4vwsNhBAryQBewMvAcPt2LAL1fhdCnwW2DHam+mpnDkR8aNcU9VXNzPwOuB1ku6WdJ+k4/OLVlej3BcCp0laTdKa+mROueoJ4GZJD0o6e5T39wNWVS2vTl/rpEaZq50J/CSHTM2om1vSfsB7SVqtRdFoX78O2EfSHek6H84532gaZf4a8AaSXxQfBc6LiLF+ZlviU3/jIOlE4IWIeFDSkaO8Pwn4J+D0nKONqVHm1GSSU1FHkvy2vFTSH0XEhnxS/r4mc38QuCIi/lHSfwaukjS/XT8k4/T2iHguPWVzi6RfRsTSDuZpRlOZJR1FUqjennvC0TXKfSnwuYjYkfyyXwiNMk8G3gIcA/QA90q6LyKe7kTYVKPMfwo8DBwNHJSuc1dEbNzdL3aLanyOAE6StBK4Gjha0ner3u8F5gN3pOscDizu8A0VjTJD8lv94ojYHhG/Bp4mKVyd1EzuM4FrACLiXqAbmJFnyFoR8Vz65wvA9cBhNas8B8ypWp6dvtYxTWRG0ptITsG+JyJezDfh6JrIfShwdXoMnQJ8Q9J/zTVkjSYyrwZ+GhG/S68JLQU6evNKE5nPIDldGRHxDMk1zde368v92I0HSetjSYN17gAO7XTWRpmB44Er0+czSE5NvbLTeZvI/RPg9PR55dSDOpjzFUBv1fN7SC6KV6/z7jS3SH6ReaDD+7aZzPsDzwD/pdPHQiu5a9a/Ajil6JnT4/g2kpbVfwAeA+YXPPM3gQvT568i+cVrRju+36f+2kjSRcDyiFjc6SzNqsn8U+A4SU8AI8BnoiC/Ndeqyf0pYKGkvyQ5j356pD8tHfIq4Pr0NNNk4N8i4iZJHwOIiG+RXEs7geQ//n8n+W20k5rJfAHwSpIWCcBwRHS620UzuYumYeaIeFLSTcAjJNdmL4uIxzqWuLn9/HngCkmPkvwC9rmocydmKzyEkpmZFZqvUZmZWaG5UJmZWaG5UJmZWaG5UJmZWaG5UJmZWaG5UJl1WDoq9bGdzlFN0oWjdKw26wgXKrMqkt6eTmExKOmldNzDt+b4/bkXiHQ6idV5fqdZK9zh1ywlaRqwBPg4yZBMU4B3AFs7mctsT+cWldkurwOIiO9HxEhEbImImyPiEQBJH5X0pKT1kn4qaW7lg0omxzxX0gpJ6yR9OR2cGEkHSbpd0ovpe99L5xtqiaR9Jf1Q0lpJv5Z0btV7F0q6RtJ3JG1SMnHdoVXvH6JkYslNkn4gaZGkv5f0CpKhnPaVtDl97Jt+bMpY2zPLkwuV2S5PAyOSrpT0Lkn7VN6Q9B7gr4D3ATOBu4Dv13z+vSQDoB5CMt/URysfB74I7EsyhtsckqlJmpYWvRuBX5BMB3IM8BeS/rRqtZNIBu6dDiwmmXYBSVNIBhG9AviDNPd7ASLidySTOK6JiL3Tx5p62zPLmwuVWSqS6QjeTjJe4EJgraTFkl4FfAz4YkQ8GRHDwBeAg6tbVcDFEfFSJJPdXUoy/QgR8UxE3BIRWyNiLckUMAtajPdWYGZEXBQR2yJiRZrx1Kp1lkXEjyNiBLiKXaNtH05ymv+rkYyMfx3wQBPfOdb2zHLla1RmVSLiSdJ5xCS9HvguSdGZC3xF0j9WrS6S1s2z6XL1RIjPkrSgSAvdV0iud/WS/IK4ntbMJTk9Vz03WBdJy67it1XP/x3oljQ5zfFczUC91VnHMur20kJtlhu3qMzGEBG/JDldNp/kP/ZzImJ61aMnIu6p+kj1/FL7k0w3AknrK4A/iohpwGkkRa4Vq4Bf13x/b0Sc0MRnB4D99PJZA6uzemRqKzQXKrOUpNdL+pSk2enyHJLTd/cB3wLOl/SH6Xt9kt5fs4nPSNon/dx5wKL09V5gMzCoZFr0zzSIMklSd9VjKsmpuk2SPiepR1KXpPlN3jp/L8m0LZ+QNDm93lY96d3zwCsl9TWxLbPcuVCZ7bIJeBtwv6TfkRSox4BPRcT1wMUkM8VuTF9/V83nbwAeJJmO+0fA5enrf0dyg8Vg+vp1DXJ8ENhS9fhVep3oROBgkplT15HMtNuwuETENpKbQM4ENpC06JaQ3nafthy/D6yQtKHqrj+zQvB8VGZtICmAeZFMwV14ku4HvhUR/9rpLGaNuEVltgeQtEDSq9NTfx8B3gTc1OlcZs3wXX9me4b/RDLaxiuAFcApETHQ2UhmzfGpPzMzKzSf+jMzs0JzoTIzs0JzoTIzs0JzoTIzs0JzoTIzs0L7/7JSofmoNEMiAAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "setosa.plot.scatter('SepalLength', 'SepalWidth')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now we are starting to see some relationship! What other variable pairs\n", "do you think might be related? Test out your hypotheses." ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "# Use scatter plots to look for relationships between other columns in\n", "# the \"setosa\" dataframe.\n" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "# See if the same relationships hold for the other species.\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "**Replace this text to describe the relationships you see**" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Now that we have played around with three species separately, let's\n", "take a look at the whole dataset again." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "iris.plot.scatter('SepalLength', 'PetalLength')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can see a linear relationship between Sepal Length and Petal Length\n", "that we couldn't see on the `setosa` graph. All of the `setosa` data\n", "points are in that bottom-left island of the graph.\n", "\n", "We can also squeeze more information into this graph by using colour:" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "iris.plot.scatter('SepalLength', 'PetalLength', c='PetalWidth', colormap='hsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "_(super-extra-cool points if you figure out how to colorise points by\n", "species name)_ - if you want to try, add that cell below." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "But wait! There's more!" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "iris.plot.scatter('SepalLength', 'PetalLength', s=iris[\"SepalWidth\"]**4, c='PetalWidth', colormap='hsv')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What is happening in the above cell? Make sure to utilize `SHIFT+TAB`\n", "in order to examine what arguments `plot.scatter()` can take. Why is\n", "there `**4` all of a sudden? What is going to happen if you change that\n", "value?" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "But what if we want to take a look at _every possible variable pair_? Surely that can't be done in one line, right?" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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