{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Lecture/Practice 9 - Visualization of different data types with python\n", "==========\n", "Here, will learn some of the most basic `plotting` functionalities with `Python`, to give you the tools you need to assess basic distributions and relationships within you dataset. We will focus on the [Seaborn library](https://seaborn.pydata.org/index.html), which is designed to make nice looking `plots` quickly and (mostly) intuitively." ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import os\n", "import pandas\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's first gather our dataset. We'll use participant related information from the [OpenNeuro dataset ds000228 \"MRI data of 3-12 year old children and adults during viewing of a short animated film\"](https://openneuro.org/datasets/ds000228/versions/1.0.0) ." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%%bash\n", "wget -O data/participants.tsv https://openneuro.org/crn/datasets/ds000228/snapshots/1.0.0/files/participants.tsv" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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participant_idAgeAgeGroupChild_AdultGenderHandednessToM Booklet-MatchedToM Booklet-Matched-NOFBFB_CompositeFB_GroupWPPSI BD rawWPPSI BD scaledKBIT_rawKBIT_standardDCCS SummaryScanlog: ScannerScanlog: CoilScanlog: Voxel slizeScanlog: Slice Gap
0sub-pixar0014.7748124yochildMR0.800.7368426.0pass22.013.0NaNNaN3.03T17-8yo 32ch3mm iso0.1
1sub-pixar0024.8569474yochildFR0.720.7368424.0inc18.09.0NaNNaN2.03T17-8yo 32ch3mm iso0.1
2sub-pixar0034.1533204yochildFR0.440.4210533.0inc15.09.0NaNNaN3.03T17-8yo 32ch3mm iso0.1
3sub-pixar0044.4736484yochildFR0.640.7368422.0fail17.010.0NaNNaN3.03T17-8yo 32ch3mm iso0.2
4sub-pixar0054.8377824yochildFR0.600.5789474.0inc13.05.0NaNNaN2.03T17-8yo 32ch3mm iso0.2
\n", "
" ], "text/plain": [ " participant_id Age AgeGroup Child_Adult Gender Handedness \\\n", "0 sub-pixar001 4.774812 4yo child M R \n", "1 sub-pixar002 4.856947 4yo child F R \n", "2 sub-pixar003 4.153320 4yo child F R \n", "3 sub-pixar004 4.473648 4yo child F R \n", "4 sub-pixar005 4.837782 4yo child F R \n", "\n", " ToM Booklet-Matched ToM Booklet-Matched-NOFB FB_Composite FB_Group \\\n", "0 0.80 0.736842 6.0 pass \n", "1 0.72 0.736842 4.0 inc \n", "2 0.44 0.421053 3.0 inc \n", "3 0.64 0.736842 2.0 fail \n", "4 0.60 0.578947 4.0 inc \n", "\n", " WPPSI BD raw WPPSI BD scaled KBIT_raw KBIT_standard DCCS Summary \\\n", "0 22.0 13.0 NaN NaN 3.0 \n", "1 18.0 9.0 NaN NaN 2.0 \n", "2 15.0 9.0 NaN NaN 3.0 \n", "3 17.0 10.0 NaN NaN 3.0 \n", "4 13.0 5.0 NaN NaN 2.0 \n", "\n", " Scanlog: Scanner Scanlog: Coil Scanlog: Voxel slize Scanlog: Slice Gap \n", "0 3T1 7-8yo 32ch 3mm iso 0.1 \n", "1 3T1 7-8yo 32ch 3mm iso 0.1 \n", "2 3T1 7-8yo 32ch 3mm iso 0.1 \n", "3 3T1 7-8yo 32ch 3mm iso 0.2 \n", "4 3T1 7-8yo 32ch 3mm iso 0.2 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pheno_file = ('data/participants.tsv')\n", "\n", "pheno = pandas.read_csv(pheno_file,sep='\\t')\n", "\n", "pheno.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What are our different variables?" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Index(['participant_id', 'Age', 'AgeGroup', 'Child_Adult', 'Gender',\n", " 'Handedness', 'ToM Booklet-Matched', 'ToM Booklet-Matched-NOFB',\n", " 'FB_Composite', 'FB_Group', 'WPPSI BD raw', 'WPPSI BD scaled',\n", " 'KBIT_raw', 'KBIT_standard', 'DCCS Summary', 'Scanlog: Scanner',\n", " 'Scanlog: Coil', 'Scanlog: Voxel slize', 'Scanlog: Slice Gap'],\n", " dtype='object')" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pheno.columns" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Univariate visualization" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's start by having a quick look at the `summary statistics` and `distribution` of `Age`:" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "count 155.000000\n", "mean 10.555189\n", "std 8.071957\n", "min 3.518138\n", "25% 5.300000\n", "50% 7.680000\n", "75% 10.975000\n", "max 39.000000\n", "Name: Age, dtype: float64\n" ] } ], "source": [ "print(pheno['Age'].describe())" ] }, { "cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# simple histogram with seaborn\n", "sns.displot(pheno['Age'],\n", " #bins=30, # increase \"resolution\"\n", " #color='red', # change color\n", " #kde=False, # get rid of KDE (y axis=N)\n", " #rug=True, # add \"rug\"\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What kind of distribution do we have here? \n", "\n", "Let's try log normalization as a solution. Here's one way to do that:" ] }, { "cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "c:\\program files\\python36\\lib\\site-packages\\seaborn\\distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", " warnings.warn(msg, FutureWarning)\n", "c:\\program files\\python36\\lib\\site-packages\\seaborn\\distributions.py:2056: FutureWarning: The `axis` variable is no longer used and will be removed. Instead, assign variables directly to `x` or `y`.\n", " warnings.warn(msg, FutureWarning)\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 18, "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": [ "import numpy as np\n", "\n", "log_age = np.log(pheno['Age'])\n", "sns.distplot(log_age,\n", " bins=30, \n", " color='black', \n", " kde=False, \n", " rug=True, \n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "There is another approach for log-transforming that is perhaps better practice, and generalizable to *nearly any* type of transformation. With [sklearn](https://scikit-learn.org/stable/index.html), you can great a custom transformation object, which can be applied to different datasets.\n", "\n", "_Advantages_ :\n", "* Can be easily reversed at any time\n", "* Perfect for basing transformation off one dataset and applying it to a different dataset\n", "\n", "_Distadvantages_ :\n", "* Expects 2D data (but that's okay)\n", "* More lines of code :(" ] }, { "cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "from sklearn.preprocessing import FunctionTransformer\n", "\n", "log_transformer = FunctionTransformer(np.log, validate=True)\n", "\n", "age2d = pheno['Age'].values.reshape(-1,1)\n", "log_transformer.fit(age2d)\n", "\n", "sk_log_Age = log_transformer.transform(age2d)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Are two log transformed datasets are equal?" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all(sk_log_Age[:,0] == log_age)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "And we can easily reverse this normalization to return to the original values for age." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "reverted_age = log_transformer.inverse_transform(age2d)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The inverse transform should be the same as our original values:" ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all(reverted_age == age2d)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Another strategy would be `categorization`. Two type of `categorization` have already been done for us in this dataset. We can visualize this with `pandas value_counts()` or with `seaborn countplot()`:" ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "5yo 34\n", "8-12yo 34\n", "Adult 33\n", "7yo 23\n", "3yo 17\n", "4yo 14\n", "Name: AgeGroup, dtype: int64" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Value counts of AgeGroup\n", "pheno['AgeGroup'].value_counts()" ] }, { "cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "c:\\program files\\python36\\lib\\site-packages\\seaborn\\_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n", " FutureWarning\n" ] }, { "data": { "text/plain": [ "" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Countplot of Child_Adult\n", "\n", "sns.countplot(pheno['Child_Adult'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Bivariate visualization: Linear x Linear" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Cool! Now let's play around a bit with `bivariate visualization`. \n", "\n", "For example, we could look at the association between `age` and a cognitive phenotype like `Theory of Mind` or `\"intelligence\"`. We can start with a `scatterplot`. A quick and easy `scatterplot` can be built with `regplot()`:" ] }, { "cell_type": "code", "execution_count": 25, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 25, "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": [ "sns.regplot(x=pheno['Age'], y=pheno['ToM Booklet-Matched'])" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`regplot()` will automatically drop missing values (`pairwise`). There are also a number of handy and very quick arguments to change the nature of the plot:" ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 43, "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": [ "## Try uncommenting these lines (one at a time) to see how\n", "## the plot changes.\n", "\n", "sns.regplot(x=pheno['Age'], y=pheno['ToM Booklet-Matched'],\n", " order=2, # fit a quadratic curve\n", " #lowess=True, # fit a lowess curve\n", " #fit_reg = False # no regression line\n", " #marker = '' # no points\n", " #marker = 'x', # xs instead of points\n", " )\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Take a minute to try plotting another set of variables. Don't forget -- you may have to change the data type!" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "#sns.regplot(x=, y=)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This would be as good a time as any to remind you that `seaborn` is built on top of `matplotlib`. Any `seaborn` object could be built from scratch from a `matplotlib` object. For example, `regplot()` is built on top of `plt.scatter`:" ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 41, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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lxaJH3X13w/OfB+6sPrwOeIO7j7TaZxILXKSx+EESx9AiDSKSlFYLXEReoZvZILAXeBeVBaOPmdlBdz9da+PuH69r/1FgTddRx5DGVVwSx9DVpoikIfIK3czeAexy93XVxzsB3P3hkPb/C3jA3Z9qtV8tQSci0r5ul6AbA87XPZ6pbgs60E3AcuBIyPNbzWzKzKbm5uZiHFpEROKKc1M0aBWFsMv6zcABd18IetLd9wH7oHKFHitC6XuaAkAknjgJfQZYVvd4KXAhpO1m4CPdBpWFLJJGt8ecnJ5l18FTXLxUWeDCDNwr0+cG7auIiVFTAIjEF6fL5RiwwsyWm9m1VJL2wcZGZrYSuAH4i2RD7L0s1hzt9piT07Nsf/LE1WQOlWROyL6Kuq5q0ZcPFElTZEJ398vANuAw8DzwhLufMrMHzWxDXdMtwOMeZxxkzmSRNLo95p7DZ5i/En6qG/dV1MSoKQBE4otVWOTuh4BDDdvub3i8K7mw0pVF0uj2mHHa1bcpamIsw/KBImkpdOl/UrKYN6TbY8ZpV9+mqHOjaAoAkfiU0MkmaXR7zO3rVjI0EDQAKXhfRU2MWi9VJL5Cz+WSlCwqObs9Zq1d3FEuRa5W1fKBIvHEmsulF1QpKiLSvm4rRUVEpACU0EVESqJv+9C7qZosYsWliJRfXyb0bsrJVYouInnVl10u3VRNFrXiUkTKry8TejdVk0WtuBSR8itcl0sS/dfdlJOrFF1E8qpQV+hJzRjYTdVkUSsuRaT8CpXQk+q/7qacXKXoIpJXhepySbL/uptycpWii0geFeoKvagzBoqIpKFQCV391yIi4WJ1uZjZeuARYBB41N13B7T5l8AuKgtIn3D3DyQYJ9DdjIFZVneqslRE0hA526KZDQLfBd5FZcHoY8AWdz9d12YF8ARwl7u/bGZvcPcXW+03zdkWG6s7oXJln8bNzCyPLSLl02q2xThX6LcCZ939XHVnjwMbgdN1bf4NsNfdXwaISuZpazU6ptdJtZNj167oZy9eYtCMBfemOc6TuurXrweR8oiT0MeA83WPZ4C1DW3+CYCZPUOlW2aXu/9p447MbCuwFWB8fLyTeDuSZXVnu8duvKJfqP6Cqp8zBkhkPhnNSyNSLnFuigatc9bYT3MNsAK4A9gCPGpmI00vct/n7hPuPjE6OtpurB3LcnRMu8cOuqKvqV3ZJzUeX/PSiJRLnIQ+Ayyre7wUuBDQ5o/dfd7dvw+coZLgcyHL0THtHjvqV8OFi5cS+8WheWlEyiVOQj8GrDCz5WZ2LbAZONjQZhK4E8DMllDpgjmXZKDdyLK6s91jR/1quHFkOLFfHBrXL1IukX3o7n7ZzLYBh6n0jz/m7qfM7EFgyt0PVp/752Z2GlgAtrv73/Uy8HZlWd3ZzrG3r1vZNCqmpv7KPmjkTLu/OIKOpXH9IsUVaxy6ux8CDjVsu7/ubwc+Uf1HulA/1r7VKJdam25Gp3Qzrl9E8idyHHqvpDkOXUSkLLodh9630hwPLiLSLSX0EGmOBxcRSYISeog448Frfwc9p4QuImlTQg8RZzx4p68VEekFJfQQYWuH1j8P9Hx90bA+evXdi0gjJfQQaY4HDxM218rUD17iK8dn1XcvIosooYdIczx4mLC5VvYfPX/1Jm39dvXdi/Q3JfQW4lR49rICNawvvjGZR7UXkf5QqCXo+k1YX/ygBU2AqTlYRPqdEnqOhc3UuGXtMq2tKiJNCtvlMjk9y6f/6CQ/frXSx2zAr9w2zkObVmcbWIJazbUycdPrNcpFRBYp5Fwuk9OzfPLJEyxcaY793pIldRGReq3mcilkl8uew2cCkznA/qPnA7eLiJRdIRN6q9EcYSNARETKrpAJvdVojrARICIiZRcroZvZejM7Y2ZnzWxHwPMfMrM5M/t29Z9/nXyor9m+biWDA8GJe8vaZYHbi2xyepbbdx9h+Y4/4fbdR5icns06JBHJochRLmY2COwF3kVlMehjZnbQ3U83NP1Dd9/Wgxib1EZzlH2UC4SX/4PK/EVksTjDFm8Fzrr7OQAzexzYCDQm9FRluUZomsLK/1XmLyKN4nS5jAH1Q0dmqtsavc/MnjOzA2YW2O9hZlvNbMrMpubm5joIt/+E3QBWmb+INIqT0IM6qxuHknwNuNnd3wr8GfCloB25+z53n3D3idHR0fYi7VNhN4BV5i8ijeIk9Bmg/op7KXChvoG7/527/3314e8Cb08mPAkr/1eZv4g0ipPQjwErzGy5mV0LbAYO1jcwszfWPdwAPJ9ciP1t05oxHn7vasZGhjFgbGSYh9+7Wv3nItIk8qaou182s23AYWAQeMzdT5nZg8CUux8EPmZmG4DLwEvAh3oYc9/plxvAItKdQs7lIiLSr0o3l4uIiDRTQhcRKQkldBGRkijsAhe9NDk9q8UjRKRwlNAbaO4UESkqdbk0aDV3iohInukKvarWzTKruVNEpKCU0GnuZgmiuVNEJO/U5UJwN0s9zZ0iIkXQd1foQSNYWnWnjGmUi4gURF8l9LARLD81PMTFS/NN7cdGhnlmx11phyki0pG+6nIJG8FihqaoFZHCK1xC72bB5LCulYuvzGuKWhEpvEJ1uXRb9HPjyHDgsMQbR4Y1Ra2IFF6hrtC7LfrR6j8iUmaFukLvdsHk2hW45mkRkTKKdYVuZuvN7IyZnTWzHS3a/ZKZuZkFTr7eLS2YLCISLjKhm9kgsBe4G1gFbDGzVQHtXgd8DDiadJA13XaZ1PrgZy9ewnmtD76dG6siInkV5wr9VuCsu59z91eBx4GNAe3+HfBZ4P8lGN8i3S6YrIm3RKTM4vShjwHn6x7PAGvrG5jZGmCZu3/dzD4VtiMz2wpsBRgfH28/WrpbMLnbPngRkTyLc4VuAduurixtZgPA54FPRu3I3fe5+4S7T4yOjsaPMiHqgxeRMouT0GeAZXWPlwIX6h6/DngL8C0z+2vgNuBgr26MdkPDFkWkzOJ0uRwDVpjZcmAW2Ax8oPaku/8IWFJ7bGbfAj7l7lPJhto9DVsUkTKLTOjuftnMtgGHgUHgMXc/ZWYPAlPufrDXQSZJFaEiUlaxCovc/RBwqGHb/SFt7+g+LBERaVehKkXLLmiudv2aEJG4SpnQJ6dn2XXw1NU5zm+4bogHfvHNuU6O3U48JiJSqMm54picnmX7kycWLVjx8ivzbD9wItcVoSp6EpFulS6h7zl8hvkr3rR9fsFznRxV9CQi3Sp0l0u764POXrzE7buP5LKPutVc7SIicRT2Cj1soq2fGh4KfY1V2+VxYi4VPYlItwqb0FutDzo0EDRbQd18BXXt89IN0+3EYyIihe1yabU+6Od/+W1No1xefmU+sH2e+qhV9CQi3ShsQm93fdDbdx9RH7WIlFphu1za7XNWH7WIlF1hr9DbnWhLE3OJSNmZe/OY7TRMTEz41FTuJmQUEck1Mzvu7oHTkxf2Cr3faJ4XEYmihF4AmudFROIo7E3RfqJ5XkQkDiX0AtA8LyISR6yEbmbrzeyMmZ01sx0Bz/+amZ00s2+b2f80s1XJh9q/tLi1iMQRmdDNbBDYC9wNrAK2BCTs/+7uq939bcBngc8lHmkf0xh6EYkjzk3RW4Gz7n4OwMweBzYCp2sN3P3/1LW/nuZpU3KpKCNHNIZeROKIk9DHgPN1j2eAtY2NzOwjwCeAa4G7gnZkZluBrQDj4+Ptxpqooo0c0TwvIhIlTh960NSFTVfg7r7X3f8x8JvAfUE7cvd97j7h7hOjo6PtRZowjRwRkbKJk9BngGV1j5cCF1q0fxzY1E1QadDIEREpmzgJ/RiwwsyWm9m1wGbgYH0DM1tR9/DdwPeSC7E3NHJERMomMqG7+2VgG3AYeB54wt1PmdmDZrah2mybmZ0ys29T6Uf/YM8iTohGjohI2cQq/Xf3Q8Chhm331/396wnH1XMaOSIiZdPXc7lo5IiIlIlK/0VESkIJXUSkJJTQRURKQgldRKQklNBFREqicKNcijKhlohI2gqV0Is2oZaISJoK1eWiCbVERMIVKqFrQi0RkXCFSuiaUEtEJFyhErom1BIRCVeom6KaUEtEJFyhEjpoQi0RkTCF6nIREZFwSugiIiURK6Gb2XozO2NmZ81sR8DznzCz02b2nJl908xuSj5UERFpJTKhm9kgsBe4G1gFbDGzVQ3NpoEJd38rcAD4bNKBiohIa3Gu0G8Fzrr7OXd/FXgc2FjfwN2fdvdXqg+fBZYmG6aIiESJk9DHgPN1j2eq28J8GPgfQU+Y2VYzmzKzqbm5ufhRiohIpDgJ3QK2eWBDs3uBCWBP0PPuvs/dJ9x9YnR0NH6UIiISKc449BlgWd3jpcCFxkZm9gvAp4F3uvvfJxOeiIjEFecK/RiwwsyWm9m1wGbgYH0DM1sD/A6wwd1fTD5MERGJYu6BvSeLG5ndA3wBGAQec/fPmNmDwJS7HzSzPwNWAz+svuQFd98Qsc854AddRd+dJcDfZnj8PNI5Cabz0kznpFla5+Qmdw/ss46V0MvIzKbcfSLrOPJE5ySYzksznZNmeTgnqhQVESkJJXQRkZLo54S+L+sAckjnJJjOSzOdk2aZn5O+7UMXESmbfr5CFxEpFSV0EZGS6NuEbmaDZjZtZl/POpY8MLMRMztgZt8xs+fN7B1Zx5Q1M/u4mZ0ys78ys/1m9hNZx5QFM3vMzF40s7+q2/Z6M3vKzL5X/fcNWcaYtpBzsqf6389zZvZHZjaSdlx9m9CBXweezzqIHHkE+FN3fxNwC31+bsxsDPgYlWmh30KlqG5ztlFl5ovA+oZtO4BvuvsK4JvVx/3kizSfk6eAt1SnEf8usDPtoPoyoZvZUuDdwKNZx5IHZvYPgZ8Dfg/A3V9194vZRpUL1wDDZnYNcB0Bcxj1A3f/c+Clhs0bgS9V//4SsCnVoDIWdE7c/Rvufrn6MJNpxPsyoVOZxuA3gCtZB5ITPwPMAf+12g31qJldn3VQWXL3WeC3gReoTGnxI3f/RrZR5cpPu/sPAar/fkPG8eTNvyJkGvFe6ruEbmbvAV509+NZx5Ij1wD/DPjP7r4G+DH99xN6kWqf8EZgOXAjcH11emiRlszs08Bl4A/SPnbfJXTgdmCDmf01ldWX7jKzL2cbUuZmgBl3P1p9fIBKgu9nvwB8393n3H0e+CrwsxnHlCd/Y2ZvBKj+W7OsAmb2QeA9wK94BkU+fZfQ3X2nuy9195up3OQ64u59feXl7v8bOG9mK6ubfh44nWFIefACcJuZXWdmRuWc9PWN4gYHgQ9W//4g8McZxpILZrYe+E0q04i/EtW+F+IscCH94aPAH1TnvD8H/GrG8WTK3Y+a2QHgL6n8fJ4mB6XdWTCz/cAdwBIzmwEeAHYDT5jZh6n8z+/92UWYvpBzshP4B8BTlWsAnnX3X0s1LpX+i4iUQ991uYiIlJUSuohISSihi4iUhBK6iEhJKKGLiJSEErqISEkooYuIlMT/BzsrrKgDUejKAAAAAElFTkSuQmCC\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.scatter(x=pheno['Age'], y=pheno['ToM Booklet-Matched'])\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "If you want to get really funky/fancy, you can play around with `jointplot()` and change the `\"kind\"` argument.\n", "\n", "However, note that `jointplot` is a different `type` of `object` and therefore follows different rules when it comes to editing. More on this later ..." ] }, { "cell_type": "code", "execution_count": 45, "metadata": {}, "outputs": [ { "data": { "image/png": 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URr6LiAykBJUU1LA1Hnc2bDnA9kMdPPiDX/VV4911TSOvH+7gnQum501ScyfV8R/7j/OBR1/qNw9qbcur3LmkkRsvmcEPtxxUtZ+ISAYt8eWwo62Dja3tfckJEoUODz27la0HT/TNgcp3jMxqvlUbtnLDopnc88QmNu5tV7WfiEgAJagcDhzrJO7B85jiTt8cqHzHCHp9as7TflX7iYgEUoLKYer4WqqMwGq8mNE3ByrfMYJe7574c7qq/UREAilB5TB3Uh2XzJrA3dee368a765rGmmcMrZvDlS+Y2RW861c0shTG/dw/9KFXDJjgqr9REQChDZuIyzFHrdxtlV8mcdIVelVV8U43tnFxLrRfbOk8s2gEpERT+M2AqiKL49YzJg7eSxzJ4/Nv3OOY2RWCA5mu4hIJdISn4iIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRFJFdZIY7GDAnp44Ww4c48jJbjpO9zBjwjmcXz+WLYeOs6+9k+kTzukbOpj+ms372gdsj8ed1w93sLf9JKOrqujo6qFhYh1zJo5h19GTeWPSUEMRqTQVk6DicefpzfsLHgzY0xPnXzbvo/XoKR56dmvfa/7ypoV84bmt7Gw7RW11jPuXLmTpG2cyalSMnp44T7yyh3ue2NS3//1LF/YNJXzg6de4ramBVRsSx5sz6RzuXNLYb/+gmAYbu4jISFAxS3xBgwNzDQbcvK+drQdP9CWn1Gv+4nubuGHRzL7H9zyxqW9w4eZ97X3JJn17aijhDYtm9iUnoG9oYb6YBhu7iMhIUDEJKtvgwGyDAfe1Zx9WaNb/cWpw4b724PdIDSVMDSlMyXycLabBxi4iMhJUTILKNjgw22DA6RPOyTqsML0DfW11rG9w4fQJ5wTuPy3tvYO254tpsLGLiIwEFZOgggYH5hoMuGD6eH5ryljuuqax32v+8qaFPLVxT9/j+5cu7BtcuGD6eO5furDf/vcvXcii5FDCJ1/Zw8olZ4735Ct7BuwfFNNgYxcRGQkqamDhYAcDZlbxTZ9QywX149hy6Dj72zuZNqG2b+hg+ms272sfsD1Vxbev/SQ1AVV8+WLSUEOREa2wgYWxmFOk7+wZs2azZ/euorwXWf7+oSYoM2sGHgKqgC+7++cytjcAXwPOTe7zCXdfn+uYw5Gggkq1i1XGrXJxEQlQtIm6RZ6UW6jiTtQ1syrgYeBaoBV4yczWufurabvdAzzu7l80s4uB9cDcMOLJVaoNFKWMW+XiIiKFC/Ma1BXANnff7u5dwGPATRn7ODA++fsEYG9YweQq1S5WGbfKxUVEChdmgpoJ7E573Jp8Lt2ngfeaWSuJs6c7gw5kZsvNrMXMWg4dOnRWweQq1S5WGbfKxUVksNK//0odS7GFmaCC1qwyFz6XAY+6+yzgeuAbZjYgJndf4+5N7t5UX19/VsHkKtUuVhm3ysVFZLDSv/9KHUuxhZmgWoHZaY9nMXAJ74PA4wDu/hOgFpgcRjC5SrWLVcatcnERkcKF2YvvJaDRzOYBe4Dbgfdk7LMLuAZ41MwuIpGgzm4NL49YzGheMI0LVy4OLNXOta1YMYiIyBmhJSh37zGzO4BnSJSQP+Lum83sPqDF3dcBHwG+ZGZ/RmL57/0eYv1jLGbMrx/L/Pqxg9pWrBhEROSMULuZJ+9pWp/x3L1pv78KvC3MGEREpDxVTKsjEREpLxUzD2qwUh0f2jpOYxhHOk4zdfzAAYW5XqtuESIiZ08JKkCq40PmgMHMAYW5XqtuESIiQ6MlvgCpjg+ZAwYzBxTmeq26RYiIDI0SVIADWQYMQv8Bhblem/kadYsQERmcilviK+T60NSMAYPpCSd9QGGQ1GszX6NuESIig1NRZ1Cp60PXr3qeZV96ketXPc/Tm/cTj/e/9SrV8SFzwGBtdYz7blrIRVPHBx2+32vVLUJEZGgq6gwq2/WhC1cu7nfjbKrjw8xza/n5zqOsft+bOHT8NDWjqvj6C9tpmnNe1htt1S1CRGR4ZE1QZnaUgc1d+7j7xFAiClGu60OZCScWM0529fKZp14bcJyg/TNfq24RIiJDk+sMajKJjuSfItEf7xvJx38EjAk/tOE32OtDup4kIlI6Wa9BuXuvu/cA17n7Knc/6u5H3P3zwB8WL8ThM9jrQ7qeJCJSOoVcg3Izu43EaPbU72VpsNeHdD1JRKR0CklQ7wE+D3zRzOLAT0ks85WlwV4f0vUkEZHSyJug3H078PtFiEVERKRP3vugzOy3zOwZM3sl+XiRmX0y/NBERKSSFXKj7peBzwCpUrZfAu8NLSIREREKS1B17v5C6kFy4m13eCGJiIgUViTRZmbzSN60a2ZLgf2hRhUh6b37xtSMoqu3l0l1o3NW82kelIjI0BWSoO4AvgJcaGY7gX3AslCjioig2U4rlzSytmUXH2++KHDGk+ZBiYgMj7xLfO6+zd2XANOBN7r7le7+evihlV5Q775VG7Zyw6KZWWc8aR6UiMjwyHsGZWY1wFJgLjDKLHEW4O6fDTWyYZRtyS3z+YbzxrDr6Mm+x9l696XmRAX15BtMvz8REcmukCW+/wN0Aj8DesMNZ/hlW3K77qKpfP+1A/2ev3/pQj6/YSs7205RWx3jS+9rCuzF5569J5/694mIDI9CqvjmuPvN7v5Zd38g9RN6ZMMk25Lb5n3tA56/54lN3LBo5pnH3/slD9y8qF8vvpVLGnlq456sPfnUv09EZHgUcgb1UzO72N1fDT2aEGRbctvXnn35LmVn2ylmnlvL+pWLk1V8VXT3xmleOC1rZZ7694mIDI9c86B+QaK0vBp42cy2AqdJjNxwd7+8OCEOTbYlt+kTgp/3tAlYtdUxJtaNHnQvPvXvExEZulxnUO8uWhQhSi25ZV6DWjB9woDnU9egQEtzIhJBZqxdcdWQDjFj1uxhCiZ85p51aG5iB7M3A6+5+4nk43HABe7eUoT4BmhqavKWlsG9dapaL3PJLfP5VBWfluZEpMgK+qIxM79t9Qv5d0xau+Iq8n3HR0Tg37+Qa1BrgDelPe4AVmc8F/yOZs3AQ0AV8GV3/1zG9r8Hfjf5cAwwxd3PLSCmQcm25Bb0vJbmRESioZAEFXP3vgs17h43s+p8LzKzKuBh4FqgFXjJzNalF1u4+5+l7X8ncNlgghcRkZGrkDLz183sv5hZlZnFzOzDwI4CXncFsM3dt7t7F/AYcFOO/ZcB3yzguCIiUgEKSVArgGuAA8mf3wH+tIDXzQR2pz1uTT43gJnNAeYBG7JsX25mLWbWcujQoQLeWkRkZEj//it1LMVWyBLfPHfvV9FnZlcCB/O8LuiiV7ardbcD33b3wE4V7r6GxLUwmpqayuKKn4jIcEj//jOzivr+K+QM6h8Cnnu4gNe1Aun1jLOAvVn2vR0t74mISJpcN+peAbwVqDezlWmbxpO4eTefl4DG5CypPSSS0HsC3ucC4DzgJ4OIO9I0D0pEZOhyLfHVAZOT+9SnPX8cuCXfgd29x8zuAJ4hUWb+iLtvNrP7gBZ3X5fcdRnwmEekWD8zucwYV8um/cfYf6yTqeNGM7o6xtjR1VmTjuZBiYgMj6wJyt2fA54zs6+6+/azObi7rwfWZzx3b8bjT5/NsYci1/iN9OTSNGcCtzbN4d51m/qSzWduXMCzr+1j6WUNgUknW3PaC1cu1v1VIiKDUEiRxDEz+5/AAqBvZoS7XxdaVCHKdYaTmVz++Kr5/Pdvv9Iv2Xxq3WZWv+9NrPjGzwKTjuZBiYgMj0KKJP43ifuezgceAPYDL4cYU6hyTbzNTC6nTvcEJpvfnOzuSzqZUs1p02kelIjI4BWSoOrdfTXQ5e7PAn9C4ibcspTrDCczuYwZPSow2Zw7pjpr0tE8KBGR4VHIEl938s/9ZvZ7JErFy6cdboZcE28zO59/7YXt3HfjwgHXoP7pp69nTTqaByUiMjwKSVCfNbMJwEdJ3P80HvhYqFGFKNv4jVQSyUwuM8bVMr++rq+Kr7Y6xpvnTsyZdDQPSkRk6PImqLRy8I3A4nDDCV++M5yg5NI0d2KpwhURqVi5btR9MNcL3f3u4Q+nOHSGIyISfbnOoO4Efgl8i0STWF1EERGRosmVoGYCtyZ/OoC1wHfd/VgxAhMRkcqWtczc3Q+6+xfc/e3Ah4CpwGtm9kdFi05ERCpW3iIJM1tEol9eM/BD4JWwgxIREclVJPEXwI3Ar0lMw/1UcjKuiIhI6HKdQX0G2AZcAHwKuNfsTJ2Eu18ebmgiIlLJciWoxqJFUWTp3cynjKulKgb72jW7SUQkSnKN2/h15nNm1uzuT4cbUriCupnfdU0jX//JTo6e7NLsJhGRiCikWWy6z4YSRREFdTN/6NmtvOvyWf06m4uISGkNNkGV/WlFtm7mqctr2cZoiIhIceVNUGaWvgz4XwOeKyvZ5jWlBs5rdpOISDQUcgb176lf3P0nmc+Vm6B5TXdd08h3f96q2U0iIhGS6z6oKcB04Bwzu4Qzy3vjgTFFiG1YpFfspar00ruZ149NVPFd1nCuZjeJiERIrqW63wf+EzAL+Ie0548BfxFmUMMlqGIvVaWX2c187mR1NhcRiZJcZeZfBb5qZre6++NFjGnYBFXs3f34y1y4crFGbYiIRFwh16B+ZGarzewpADO72MzeH25YwyNbxZ6q9EREoq+QBPVV4F+B2cnHW4GPhBbRMMpWsacqPRGR6CukXHyKu/+zmX0MwN27zaw35LiGRapiL/MalKr0RKQsmbF2xVWF7x8bxczZDezZvSu8mEJUSILqMLOJgAOY2ZuB46FGNUxiMetXsacqPREpa+7ctvqFQb1kUAktYgpJUB8FngTmm9m/kpi0++5QoxpGsZgNqNgTEZHoy5ug3L3FzH4XuIjEvVCvai6UiIiELdeNujdm2dRgZrj7unwHN7Nm4CGgCviyu38uYJ9bgU+TWEJ8xd3fU0jgZyvoxt3Ukl+ubSIiUly5zqBuybHNgZwJysyqgIeBa4FW4CUzW+fur6bt0wh8Enibux9Ndq8ITa4bd4Gs25SkRESKL9eNuu8DMLOazCU9Mzu3gGNfAWxz9+3J1zwG3AS8mrbPfwYedvejyfc8OLjwByfXjbuAbuoVEYmQQookvmNmS929F/p69P1f4M15XjcT2J32uBV4S8Y+5yeP+f9ILAN+OmggopktB5YDNDQ0FBBysFw37rrTt236hFr++K1zaJg4hq0Hj3P4xGmmjBtNw8REebqWAUWkWNK//ypNIQlqPfC4md1Coi/fk8AnCnhd0Le2B7x/I3B18tjPm9lCd/9Nvxe5rwHWADQ1NWUeo2CpG3fTk1T6jbu11THOG1PDh94+n5PdvXzkW6/0Lffdfe35XDBtLB2n41oGFJGiSf/+M7Oz/v4rR3k7Sbj7F4EfA98FngLucPd/KeDYrZzpPgGJBLQ3YJ/vuXu3u78ObCGRsEIRNGojdeNuatstTbNoO9nFQ89u7bfc9+APfsXxU72By4CawCsiMvxyVfGtzHhqLvAycJmZXebuq/Ic+yWg0czmAXuA24HMCr0ngGXAo2Y2mcSS3/bCwx+cfDfuNi+YRm11jJ/v+k3gUmBHV0/WJUJdpxIRGV65lvjqMx4/meX5QO7eY2Z3AM+QuL70iLtvNrP7gJZkmfozwHVm9irQC3zM3dsG9TcYpFw37sZixtxJdbyy+zeBS4F1NaNyLhGKiMjwMffCljTN7BwAdz8VakR5NDU1eUtLS2jHj8edDVsOsPXAib5lPl2DEpGQFfQFYmZ+Nq2OCv2eL6HAv3/eIgkzuxj4GonpumZmrcD73f214Y0vGmIxY8kFU/mt+rFc3nAexzq7OfecaurTqvjU209EJHyFVPGtAf7c3X8AYGbvAL4E/HaYgZVSLGbMnTw265Rd9fYTEQlfIfOgxqWSE4C7/xAYF15IIiIihSWoHWb2STOblfz5BLAz7MBERKSyFZKg/hOJ+5nWA/+S/P0DYQYlIiJSyLiNNuC/mtmYxMPSVvGJiEhlKKSKbwHwKP2r+D6Q3pW8HMXjzuuHO9h5pIO6mlHUja7iVHcvk+pGqzJPRCQCCstY7b0AABNkSURBVKniW83AKr41lHEVX9DYjbuuaWRMdRWPvPA6H2++SPc2iYiUWEVW8QWN3Xjo2a20nezihkUz1V9PRCQCKrKKL9vYjbiD2Zn+eiIiUjpnU8U3izKv4kuN3UhXWx0jZuCu/noiIlFQcBVfEWIpmtRojWzXoB689VIazhvDjsMnOHDsNB1dPcyZWMe8ySqeEBEpllzjNiYBHwKOkqji+xzwduDXJLqOhzYWI2ypsRsX3LmYXUc6GJOs4uvs7uWr77+ChvPG8KOtBwc0jFVjWBGR4sl1BvVPwEYSo9tfBL4JvBdYDHwF+N3QowtRLGa8YcpY3jBlYE+97YdOsLG1nTU/3j5gOOGFKxerD5+ISBHkSlDT3b3ZzAzY5e6fTT6/ycxWFCG2kjlwrJO4o+GEIiIllKtIohcSrSOAQxnb4gN3Hzmmjq+lyggspFDxhIhIceQ6g5pvZt8lMUgq9TvJx/NCj6yE5k6q45JZE7jrmsYB16DmTqordXgiIhUhV4K6Oe33L2Rsy3w8omQOLTzZ1UODqvhERIoqa4Jy92eLGUjU5BtaKCIi4SrkRl0REZGiK6RZbNnr6upl49529h/rZPr4Wi6ZMYGamqpShyUiIjmM+ATV1dXLExv3cu/3NvUVO9x300KWLpqhJCUi5cWMtSuuGtRLZsyaHVIw4cvVSeK72bYBuPu7hj+c4bdxb3tfcoLEvUz3fm8T8yfX0TR3YomjExEZBHduW/1C4Ka1K64icVfQyJHrDOpqYAeJDhI/I1FeXnb2Z+lcfuCYupWLiERZrgQ1Ffg9YFnyZx3wTXffUozAhsv0ZOfy9CRVWx1j6njdcCsiEmVZq/jcvdvdn3L3PwLeBuwC/s3Myqqz+SUzJnDfTQv7ukKkrkEtmjGhxJGJiEguOYskzKwaeCeJM6jzgX8AnixCXMOmpqaKpYtmMH9yHQeOdTJ1fC2LVMUnIhJ5uYokvgJcDjwDPODuLw/24GbWDDwEVAFfdvfPZWx/P/A3wJ7kU19w9y8P9n3yqampUkGEiEiZyXUG9QHgGLACWGFmqfIQI9FDNuc3vplVAQ8D1wKtwEtmts7dX83Yda2733FW0YcoHnd2tHX0nXXNnaQ2RyIixZQrQVUP8dhXANtSgw3N7DHgJiAzQUVOPO48vXl/v4m7GlYoIlJcuYokelM/wEXAf07+XJB8Lp+ZwO60x63J5zLdbGYbzezbZhaJO8p2tHX0JSc4M6xwR1tHiSMTEakceXvxmdkdwONAQ/LnWwVW8gWdamTeRfYkMNfdFwE/BL6WJYblZtZiZi2HDmWOphp+B7LcO3XwuO6dEpHiSv/+K3UsxVZIs9jlwBXu/ufu/ufAW4APFfC6ViD9jGgWsDd9B3dvc/fTyYdfAt4UdCB3X+PuTe7eVF9fX8BbD83U5L1T6TSsUERKIf37r9SxFFshCcqA7rTH3RTWVeIloNHM5plZDXA7iZt9zxzYbHrawxuB1wo4bujmTqrjwVsv7XfvlIYViogUV64y81Hu3gN8A/ipmX0nuekPybIUl87de5LLg8+QKDN/xN03m9l9QIu7rwNWmtmNQA9wBHj/kP42wyQWM5oXTOPClYs5eLyTKeNUxSciUmyWrbmgmf3c3S9P/v5mYDGJM6cfu/tLxQuxv6amJm9pqbilWBEZ2Qr616+Z+QhtFhv4989VZt73gmRCKllSEhGRypMrQdWb2d3ZNrr7gyHEIyIiAuROUFXAWMp0zIaIiJS3XAlqn7vfV7RIRERE0uQqM9eZk4iIlEyuBHVN0aIQERHJkKsX35FiBiIiIpKukE4SIiIiRZdzou5IpnlPIiLRVpEJSvOeRESiryKX+DTvSUQk+ioyQWnek4hI9FVkgtK8JxGR6KvIBNVw3hgeuHmR5j2JiERYxRVJxOPO9187wIM/2MIHf3s+VTFomjORq+ZPUoGEiEiEVFyCSi+QePi5bUDiDGr9ysXMrx9b4uhERCSl4pb4VCAhIlIeKi5BqUBCRKQ8VNwSX8N5Y1jzviZadh4h7vDkK3v4ePNFKpAQEYmYikpQqQKJ9A4SD9y8iOsumqoCCRGRiDF3L3UMg9LU1OQtLS1n9drth05w/arn+12DUoGEiERAQf9CtljMyfadHRsF8R5mzJrNnt27hjO2Ygj8+1fUGVSuAgklKBGJPHduW/1Czl3WrriqSMGEb8QnqPSu5WNqRlFbHRtwBqUCCRGR6BnRCSqza/mcSedw/9KF3PPEpn5dzFUgISISPSM6QWV2Ld/ZdorPb9jK2uVXcqq7lynjNAdKRCSqRnSCCrrmtLPtFKe6e7ly/uQSRSUiIoUY0Tfq6qZcEZHyNaIT1NxJdTx466XqWi4iUoZCXeIzs2bgIaAK+LK7fy7Lfu8GvgW82d3P7ianALGY0bxgGheuXMzB451MGVdLw3lj+qr6po7XNSgRkagKLUGZWRXwMHAt0Aq8ZGbr3P3VjP3GASuBF8OIIxYz5tePZX792AFVfakzquYF05SkREQiJswlviuAbe6+3d27gMeAmwL2+0vgr4HQ24lnVvV1dse5+/GX2dHWEfZbi4jIIIWZoGYCu9Metyaf62NmlwGz3f2pXAcys+Vm1mJmLYcOHTrrgDRqQ0TKTfr3X6ljKbYwE1TQmllfEykziwF/D3wk34HcfY27N7l7U319/VkHpKo+ESk36d9/pY6l2MJMUK3A7LTHs4C9aY/HAQuBH5nZDuBKYJ2ZhfYfQVV9IiLlI8wqvpeARjObB+wBbgfek9ro7u1A392yZvYj4KPDWcWXKaiqT1V8IiLRFFqCcvceM7sDeIZEmfkj7r7ZzO4DWtx9XVjvnUt6VZ+IiERXqPdBuft6YH3Gc/dm2ffqMGMREZHyMqI7SYiISPlSghIRkUhSghIRkUhSghIRkUga0fOgzlb6mHg1lBURKQ0lqAxqKCsiEg0Vs8QXjzs7Dp/gxe1tbPiPA/z64AnicR+wnxrKiohEQ0WcQcXjzoYtB9h64AQPPbs155lRroayurlXRKR4KuIMakdbBxtb2/uSE2Q/M1JDWRGRaKiIBHXgWCdxp6BRG2ooKyISDRWxxDd9Qi0XThtHbXWsX5KqrY5RP7b/mZEayoqIRMOIP4OKx51X9x3nb575D/7sHef3OzO665pGXm8bWCyRaih75fzJzK8fq+QkIlICI/4MKr0qL+7O8rfPJ+7gDl//yU6Onuxi/crFKoAQEYmYEZ+g0qvyOrp6+cKGbQP2UYWeiEj0jPglvsyqPFXoiYiUhxGfoNKr8r7zs1buuqZRFXoiImVgxC/xZVblTRtfy3UXT+PQCVXoiYhE2YhPUBA85v0NU3TNSUQkyioiQYmIjAhmrF1xVc5dZsyaXaRgwqcEJSJSLty5bfULfQ/XrrgK94FNr0eKEV8kISIi5UlnUDlocKGISOkoQWWhwYUiIqWlJb4sNLhQRKS0lKCyyDW4UEREwqcElYUGF4qIlJYSVBYaXCgiUloqkshCgwtFREor1DMoM2s2sy1mts3MPhGw/UNm9ksze9nM/s3MLg4znsHS4EIRkdIJLUGZWRXwMPBO4GJgWUAC+md3v8TdLwX+GngwrHhERKS8hHkGdQWwzd23u3sX8BhwU/oO7n4s7WEdMHJ7doiIyKCEeQ1qJrA77XEr8JbMnczsw8DdQA2wJOhAZrYcWA7Q0NAw5MDUIUJEykX691+lCfMMKugbf8AZkrs/7O5vAD4O3BN0IHdf4+5N7t5UX18/pKBSHSKuX/U8y770Itevep6nN+8nHtfJm4hET/r3X6ljKbYwE1QrkN73fRawN8f+jwFLQ4wHUIcIEZFyEWaCegloNLN5ZlYD3A6sS9/BzBrTHv4+sDXEeAB1iBARKRehXYNy9x4zuwN4BqgCHnH3zWZ2H9Di7uuAO8zsHUA3cBT4k7DiSUl1iEhPUuoQISISPaHeqOvu64H1Gc/dm/b7XWG+f5BUh4jMLuXqECEiEi0V10lCHSJERMpDxSUoONMhYn792FKHIiIiWahZrIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRJISlIiIRNKI78Wn8e4iIuVpRCeo1Hj3zNEazQumKUmJiETciF7i03h3EZHyNaLPoHKNd9eoDREpN9XV1axdcVXf4xmzZpcwmvCN6DOo1Hj3dBrvLiLlatGiRbh738+e3btKHVKoRnSCSo13TyUpjXcXESkfI3qJT+PdRUTK14hOUKDx7iIi5WpEL/GJiEj5UoISEZFIUoISEZFIUoISEZFIUoISEZFIUoISEZFICjVBmVmzmW0xs21m9omA7Xeb2atmttHMnjWzOWHGIyIi5SO0BGVmVcDDwDuBi4FlZnZxxm6/AJrcfRHwbeCvw4pHRETKS5hnUFcA29x9u7t3AY8BN6Xv4O7PufvJ5MOfArNCjEdERMpImAlqJrA77XFr8rlsPgj8S9AGM1tuZi1m1nLo0KFhDFFEJNoq+fsvzAQV1PDOA3c0ey/QBPxN0HZ3X+PuTe7eVF9fP4whiohEWyV//4XZi68VSB9WMgvYm7mTmb0D+B/A77j76RDjERGRMhLmGdRLQKOZzTOzGuB2YF36DmZ2GbAauNHdD4YYi4iIlBlzD1x1G56Dm10P/C+gCnjE3f/KzO4DWtx9nZn9ELgE2Jd8yS53vzHPMQ8BO0ML+ozJwOEivM/ZinJ8UY4NFN9QRDk2iHZ8uWI77O7N+Q5gZk8Xst9IEWqCKmdm1uLuTaWOI5soxxfl2EDxDUWUY4Noxxfl2KJKnSRERCSSlKBERCSSlKCyW1PqAPKIcnxRjg0U31BEOTaIdnxRji2SdA1KREQiSWdQIiISSUpQIiISSUpQAcxsh5n90sxeNrOWEsfyiJkdNLNNac9NNLMfmNnW5J/nRSy+T5vZnuTn93LyfrhSxDbbzJ4zs9fMbLOZ3ZV8PhKfX474ovL51ZrZv5vZK8n4PpN8fp6ZvZj8/NYmb8SPSmyPmtnraZ/dpcWOLSPOKjP7hZk9lXxc8s+unChBZfe77n5pBO5beBTIvDHvE8Cz7t4IPJt8XCqPMjA+gL9Pfn6Xuvv6IseU0gN8xN0vAq4EPpwc+RKVzy9bfBCNz+80sMTd3whcCjSb2ZXAA8n4GoGjJBo9RyU2gI+lfXYvlyC2dHcBr6U9jsJnVzaUoCLO3X8MHMl4+ibga8nfvwYsLWpQabLEFwnuvs/df578/TiJL4qZROTzyxFfJHjCieTD6uSPA0tIzG+DEn1+OWKLDDObBfw+8OXkYyMCn105UYIK5sD3zexnZra81MEEmOru+yDxJQdMKXE8Qe5ITkp+pJRLkClmNhe4DHiRCH5+GfFBRD6/5BLVy8BB4AfAr4HfuHtPcpd8Y3SKFpu7pz67v0p+dn9vZqNLEVvS/wL+OxBPPp5ERD67cqEEFext7n45iWnAHzazt5c6oDLzReANJJZe9gF/V8pgzGws8B3gv7n7sVLGEiQgvsh8fu7e6+6XkphGcAVwUdBuxY0q+aYZsZnZQuCTwIXAm4GJwMdLEZuZ3QAcdPefpT8dsGukzvqiRgkqgLvvTf55EPg/JP7HjJIDZjYdIPlnpDrBu/uB5JdHHPgSJfz8zKyaxJf/P7n7d5NPR+bzC4ovSp9firv/BvgRiWtl55pZalRP4BidYkqLrTm5bOrJ0T1fpXSf3duAG81sB4lp4ktInFFF6rOLOiWoDGZWZ2bjUr8D1wGbcr+q6NYBf5L8/U+A75UwlgFSX/5Jf0iJPr/kmv9XgNfc/cG0TZH4/LLFF6HPr97Mzk3+fg7wDhLXyZ4D3p3crSSfX5bY/iPtHx5G4vpOST47d/+ku89y97kkRg1tcPc/IgKfXTlRJ4kMZjafxFkTJAY6/rO7/1UJ4/kmcDWJVv0HgE8BTwCPAw3ALuAWdy9JoUKW+K4msTzlwA5gReqaT5Fj+23geeCXnLkO8OckrvOU/PPLEd8yovH5LSJxIb+KxD9mH3f3+5L/jzxGYgntF8B7iz1sNEdsG4B6EstpLwMfSiumKAkzuxr4qLvfEIXPrpwoQYmISCRpiU9ERCJJCUpERCJJCUpERCJJCUpERCJJCUpERCJJCUoqlpn9oZm5mV1Y6lhEZCAlKKlky4B/I3EjpYhEjBKUVKRk/7u3kRh3cHvyuZiZ/UNyvtBTZrbezN6d3PYmM/vXZAPhZzK6PYhICJSgpFItBZ52918BR8zscuBdwFzgEuBPgbdCX7+8zwPvdvc3AY8AJesuIlIpRuXfRWREWkaieSckWs8sIzFT6FvJJq37zey55PYLgIXADxIt3qgi0WVcREKkBCUVx8wmkeguvdDMnETCcc70YBzwEmCzu7+1SCGKCFrik8r0buDr7j7H3ee6+2zgdeAwcHPyWtRUEk1vAbYA9WbWt+RnZgtKEbhIJVGCkkq0jIFnS98BZpCYcroJWE2i63m7u3eRSGoPmNkrJLpkX1W8cEUqk7qZi6Qxs7HufiK5DPjvJKYr7y91XCKVSNegRPp7KjkIrwb4SyUnkdLRGZSIiESSrkGJiEgkKUGJiEgkKUGJiEgkKUGJiEgkKUGJiEgk/X94C/dMv8HIvwAAAABJRU5ErkJggg==\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for kind in ['scatter','hex']: #kde\n", " sns.jointplot(x=pheno['Age'], y=pheno['ToM Booklet-Matched'],\n", " kind=kind)\n", "\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That last one was a bit weird, eh? These `hexplots` are really built for larger sample sizes. Just to showcase this, let's plot a `hexplot` 1000 samples of some `random data`. Observe how the `hexplot` deals with `density` in a way that the `scatterplot` cannot." ] }, { "cell_type": "code", "execution_count": 46, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "mean, cov = [0, 1], [(1, .5), (.5, 1)]\n", "x, y = np.random.multivariate_normal(mean, cov, 1000).T\n", "sns.jointplot(x=x, y=y, kind=\"scatter\")\n", "sns.jointplot(x=x, y=y, kind=\"hex\")\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "More on dealing with \"overplotting\" here: https://python-graph-gallery.com/134-how-to-avoid-overplotting-with-python/." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "However, note that `jointplot` is a different type of object and therefore follows different rules when it comes to editing. This is perhaps one of the biggest drawbacks of `seaborn`.\n", "\n", "For example, look at how the same change requires different syntax between `regplot` and `jointplot`:" ] }, { "cell_type": "code", "execution_count": 51, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 0, 'Participant Age')" ] }, "execution_count": 51, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.regplot(x=pheno['Age'], y=pheno['ToM Booklet-Matched'])\n", "plt.xlabel('Participant Age')" ] }, { "cell_type": "code", "execution_count": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 32.99999999999995, 'Participant Age')" ] }, "execution_count": 53, "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": [ "g = sns.jointplot(x=pheno['Age'], y=pheno['ToM Booklet-Matched'],\n", " kind='scatter')\n", "g.ax_joint.set_xlabel('Participant Age')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, `lmplot()` is another nice `scatterplot` option for observing `multivariate interactions`.\n", "\n", "However, `lmplot()` cannot simply take two `arrays` as input. Rather (much like `R`), you must pass `lmplot` some data (in the form of a `pandas DataFrame` for example) and `variable` names. Luckily for us, we already have our data in a `pandas DataFrame`, so this should be easy.\n", "\n", "Let's look at how the relationship between `Age` and `Theory of Mind` varies by `Gender`. We can do this using the `\"hue\"`, `\"col\"` or `\"row\"` arguments: " ] }, { "cell_type": "code", "execution_count": 56, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.lmplot(x='Age', y = 'ToM Booklet-Matched', \n", " data = pheno, hue='Gender')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Unfortunately, these plots can be a bit sub-optimal at times. The `regplot` is perhaps more flexible. You can read more about this type of plotting here: https://seaborn.pydata.org/tutorial/distributions.html." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Bivariate visualization: Linear x Categorical" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's take a quick look at how to look at `bivariate relationships` when one `variable` is `categorical` and the other is `scalar`.\n", "\n", "For consistency can continue to look at the same relationship, but look at `\"AgeGroup\"` instead of `age`.\n", "\n", "There are many ways to visualize such relationships. While there are some advantages and disadvantes of each type of plot, much of the choice will come down to personal preference." ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "sns." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Here are several ways of visualizing the same relationship. Note that adults to not have cognitive tests, so we won't\n", "include adults in any of these plots. Note also that we explicitly pass the order of x:\n" ] }, { "cell_type": "code", "execution_count": 57, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['3yo', '4yo', '5yo', '7yo', '8-12yo']" ] }, "execution_count": 57, "metadata": {}, "output_type": "execute_result" } ], "source": [ "order = sorted(pheno.AgeGroup.unique())[:-1]\n", "order" ] }, { "cell_type": "code", "execution_count": 58, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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\n", 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\n", 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\n", 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "order = sorted(pheno.AgeGroup.unique())[:-1]\n", "\n", "sns.barplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'])\n", "plt.show()\n", "\n", "sns.boxplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'])\n", "plt.show()\n", "\n", "sns.boxenplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'],\n", " order = order)\n", "plt.show()\n", "\n", "sns.violinplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'])\n", "plt.show()\n", "\n", "sns.stripplot(x='AgeGroup', jitter=True,\n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'])\n", "plt.show()\n", "\n", "sns.pointplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'])\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Generally, `lineplots` and `barplots` are frowned upon because they do not show the actual data, and therefore can mask troublesome distributions and outliers. \n", "\n", "But perhaps you're really into `barplots`? No problem! One nice thing about many `seaborn plots` is that they can be overlaid very easily. Just call two plots at once before doing `plt.show()` (or in this case, before running the cell). Just overlay a `stripplot` on top!" ] }, { "cell_type": "code", "execution_count": 63, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 63, "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": [ "sns.barplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'],\n", " order = order, palette='Blues')\n", "\n", "sns.stripplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'],\n", " jitter=True,\n", " order = order, color = 'black')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can find more info on these types of plots here: https://seaborn.pydata.org/tutorial/categorical.html.\n", "\n", "Having trouble deciding which type of plot you want to use? Checkout the raincloud plot, which combines multiple types of plots to achieve a highly empirical visualization. \n", "\n", "Read more about it here:\n", "https://wellcomeopenresearch.org/articles/4-63/v1?src=rss.\n", "\n" ] }, { "cell_type": "code", "execution_count": 64, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 64, "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": [ "import ptitprince as pt\n", "\n", "dx = \"AgeGroup\"; dy = \"ToM Booklet-Matched\"; ort = \"v\"; pal = \"Set2\"; sigma = .2\n", "f, ax = plt.subplots(figsize=(7, 5))\n", "\n", "pt.RainCloud(x = dx, y = dy, data = pheno[pheno.AgeGroup!='Adult'], palette = pal, bw = sigma,\n", " width_viol = .6, ax = ax, orient = ort)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Bivariate visualization: Categorical x Categorical" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "What if we want to observe the relationship between two `categorical variables`? Since we are usually just looking at `counts` or `percentages`, a simple `barplot` is fine in this case.\n", "\n", "Let's look at `AgeGroup` x `Gender`. `Pandas.crosstab` helps sort the data in an intuitive way. " ] }, { "cell_type": "code", "execution_count": 65, "metadata": {}, "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", "
GenderFM
AgeGroup
3yo107
4yo86
5yo1618
7yo1112
8-12yo1915
Adult2013
\n", "
" ], "text/plain": [ "Gender F M\n", "AgeGroup \n", "3yo 10 7\n", "4yo 8 6\n", "5yo 16 18\n", "7yo 11 12\n", "8-12yo 19 15\n", "Adult 20 13" ] }, "execution_count": 65, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pandas.crosstab(index=pheno['AgeGroup'],\n", " columns=pheno['Gender'],)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can actually plot this directly from `pandas`." ] }, { "cell_type": "code", "execution_count": 66, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "pandas.crosstab(index=pheno['AgeGroup'],\n", " columns=pheno['Gender'],).plot.bar()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The above plot gives us absolute `counts`. Perhaps we'd rather visualize differences in `proportion` across `age groups`. Unfortunately we must do this manually." ] }, { "cell_type": "code", "execution_count": 67, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 67, "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": [ "crosstab = pandas.crosstab(index=pheno['AgeGroup'],\n", " columns=pheno['Gender'],)\n", "\n", "crosstab.apply(lambda r: r/r.sum(), axis=1).plot.bar()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Style points" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You will be surprised to find out exactly how customizable your `python plots` are. Its not so important when you're first `exploring` your data, but `aesthetic value` can add a lot to `visualizations` you are communicating in the form of `manuscripts`, `posters` and `talks`.\n", "\n", "Once you know the relationships you want to `plot`, spend time adjusting the `colors`, `layout`, and fine details of your `plot` to `maximize interpretability`, `transparency`, and if you can spare it, `beauty`!\n", "\n", "You can easily edit `colors` using many `matplotlib` and `python arguments`, often listed as `col`, `color`, or `palette`. " ] }, { "cell_type": "code", "execution_count": 72, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 72, "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": [ "## try uncommenting one of these lines at a time to see how the \n", "## graph changes\n", "\n", "sns.boxplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'],\n", " #palette = 'Greens_d'\n", " #palette = 'spectral',\n", " #color = 'black'\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can find more about your palette choices here: https://matplotlib.org/3.1.0/tutorials/colors/colormaps.html.\n", "\n", "More about your color choices here:\n", "https://matplotlib.org/3.1.0/gallery/color/named_colors.html." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "You can also easily change the style of the plots by setting `\"style\"` or `\"context\"`:" ] }, { "cell_type": "code", "execution_count": 73, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 73, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set_style('whitegrid')\n", "sns.boxplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'],\n", " )" ] }, { "cell_type": "code", "execution_count": 74, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 74, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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3atWKZs2a5dkmhBBClAVVw9p//PHH0opDCCGEKFSx38O6d+8eqamp+WZvz8rKIj09ndjYWH7//Xc+++yzEgcphBCidB0/fpypU6eyZMkS2rdvX97hFEh1wtq0aROrVq0iISGhSPUlYQkhRMU3e/ZscnJymDVrVrFWhygLqt7DOnjwIAsXLiQ+Ph5FUQr9U7t2bUaOHFlacQshhDCT48ePk5SUBEBSUhKnTp0q54gKpqqF9cMPPwC5s4dPnjwZGxsbPD09GTRoEJ988gl37txhx44dbNq0CSsrKz744INSCVo8vZ7UtcGWLVtGeHh4qZ8HMK4EbpjNv7S5ubmpPlcM8B1FWyy2JJL++7dDKZ8nBqjIY6Znz56d5+eK2spSlbDOnz+PnZ0d8+fPx8Eh95+4cePG/Pnnnzg4OODg4MAnn3yCg4MDK1asYPPmzfzjH/8olcCFUMOwxo/ahFVWwsPDORN6pmy+1f77XOVM9JnSP9d99buU5fyjcf9N3vVKecJuJ8r2utQytK5M/VxRqEpYiYmJuLq6GpMVgF6vZ9++fSQmJlKlShUA/v73v/Pdd99x4MABSVjCrJ7otcGcIKd3zuPrVSLaQFW9DkDZtfwePVeFvi/KgIODQ54k9eh3fEWi6m6ys7PDwsIiz7b69esDuVM5PVqvYcOG3LhxwwwhCiGEKE1/fSQ4b9688gnkMVQlrPr16xMVFUVqaqpx27PPPgvAxYsX89RNT08nIyPDDCEKIYQoTY0aNcrzc8OGDcsnkMdQlbC6detGcnIyc+fONSatli1boigK/+///T/jeiphYWFERkZSp04d80cshBDCrDZu3Gh8emZhYcHGjRvLOaKCqUpYI0eOpGrVqvzyyy/06NGDjIwM3Nzc6NChA6GhoQwZMoQpU6YwatQoFEWhW7dupRW3EEIIM/H39yc7OxuA7Oxs/Pz8yjmigqlKWDVq1GDNmjU0btwYCwsLrK2tAZgxYwb29vaEhYWxd+9eEhMTqVmzJuPHjy+VoIUQQphPZVnAUfVMF61atWLv3r1cv37duM3Dw4O9e/fy448/Eh0dTcOGDXnjjTeoVq2aWYMVQghhfqNGjWL//v1AJV3A8XEMgy0MatWqVabDUYUQQphHpV/AUQghxNOjUi/g+Ndx+cWh0Whk8lshhKgEKvUCjj/88AMajcb481+XESmMRqNBUZQSJayjR4+yatUqLl26RGZmJs2bN2fs2LFFWjxyxIgRHD9+/LH1JkyYwPvvv2/8uW/fvkRFRZmsHxoaiqWlNEqFEKI8FOnbt1mzZrRp0yZPAitNO3fuZPr06VhbW9O5c2dycnI4duwYPj4+zJ07l6FDhxa6f9euXalZs2aBZSkpKfz2229A7nUZPHz4kJs3b+Li4kKXLl0K3FerVT/NjBBFER8fD/eLN5VRhXYf4u3iyzsK8YQwmbBef/11fvvtNxISEggLC+PevXv079+fAQMG0K5du1ILKDY2ls8++wxHR0e2bduGXq8HIDg4mDFjxrBgwQJ69+5tMiEBjBs3zmTZ1KlTARgzZgx9+/Y1bg8LC0NRFDw9PZk/f76ZrkYIIYS5mExY8+fPZ+7cuRw7dgxfX19+++03Nm3axObNm3nmmWdKLXlt2bKFjIwM/vGPfxiTFeQOp/fx8WHp0qVs3769WCMS9+zZw65du9Dr9UyePDlP2YULFwBo3rx5yS5AiGJwdnbmeur1J3Ly24o6Q76ofAp9/qDVaunSpQtz5szhyJEjbNy4kTfffJOcnBw2bdrE8OHD6dmzJwsWLODkyZNmCejIkSMAeVo/Bv369QPg8OHDqo+bnJzM4sWLgdwBJYaXng3CwsIASVhCCFFRFXkEgUajoVOnTnTq1IlZs2Zx6tQpfH19CQgIYPPmzWzZsgUXFxdjy6tDhw6qg1EUhfDwcLRabb7JGCF3QkatVkt4eLhxUEdRrVq1iri4OLy9vWnfvn2+8gsXLmBhYcG1a9dYvHgxly5dQqPR0L59e9577z1atWql+nqEEEKYT7F6eDUaDR06dGDmzJkEBgby/fffM2rUKKysrNiyZQsjRoyge/fuqqeof/DgARkZGTg5OeVrAQFYWlpSrVo1UlNTSU5OLvJx79+/z+bNm9FoNAVOF5WRkcHVq1fJzs5m6tSppKen06lTJ6pVq8bvv//OsGHD8PX1VXUtQgghzMssY7Tbtm1L27Zt+fjjj9m8eTPLli3j7t27bNu2jVmzZhX5OIYZ4O3s7EzWsbW1BXIf8RV1kbHvv/+e1NRU+vTpU+Cqn5cuXSIrKwt7e3tWrFiRZ5Tghg0bWLRoEdOnT6d9+/bUqFGjyNdz/vz5ItctDQ8fPgTg1KlT5RpHRVDRPwtDfE+ihw8fVvjPvaLGJ/IqccLKyMjg6NGj+Pn5ERgYSEJCgvGdrRYtWqg6VlGGjat5HwxyZx7eunUrAD4+PgXWadmyJf/5z3/IyMigbt26ecpGjx7NiRMnCAgI4Oeff2bs2LFFPneLFi2wsbFRFa85OTo6AhT4CPRpU9E/C0dHR0gs7yhKh6OjY8X+3Km498XTJj09vdBf9IuVsFJSUjh06BD+/v4cOnSIlJQUFEVBq9XSrl07vLy88PLyonbt2qqOq9PpjEGbYigrrBX2qBMnThAXF0e9evUKvSkLazl5enoSEBBQ7i0mIYR4mhU5YT148IDffvsNPz8//vjjDzIyMlAUBQsLCzp16oSXlxf9+vVT9cjsrxwcHNDpdCQkJJCVlZVvVomsrCwSEhKwsbGhSpUqRTqmv78/AN7e3sWOy3BNaWlpxT6GEEKIkik0YcXGxuLv74+/vz8nT54kOzsbRVGwtLSke/fueHl50bdvX7MtI6LRaHBzcyM4OJjIyMh8/U3Xrl0jJycnz/tZj3Po0CHgf0PiC7Jv3z5+++03evfuzUsvvZSv/ObNm0DujPRCCCHKh8mE9cYbbxAcHIyiKCiKgo2NDT179qR///706dPH+OzX3Hr06EFwcDABAQH5ElZAQAAAvXr1KtKxEhISiIqKws7ODg8PD5P17t27x969e7l9+3a+hKUoCrt37wage/fuai5FCCGEGZlMWGfPns2tYGlJp06d6NWrFzqdjszMTA4cOFDkE7z++uuqAho0aBBr165lzZo1dO/e3ThwIyQkhLVr12Jra8uwYcOM9W/cuEFmZibPPPNMviQaEhIC5M4ZWNiktS+88AJLly7l1KlTbNiwgdGjRwO5yWrFihWcPXsWvV5Pnz59VF2LEEII8yn0kaBGoyErK4ujR49y9OjRYp1AbcKqV68e06ZNY+7cubzxxht07twZRVE4duwYWVlZLF68OM/iYqNHjyY6OppFixYxaNCgPMcyPMqrX79+oed0dnZm4cKFfPTRRyxatIiffvqJRo0acenSJSIjI6lRowbffPONzNQuhBDlyOQ3cKtWrcpsdva/Gj58OHXq1GHt2rWcOnUKa2tr2rVrx7hx40zOpF6Q+PjcWaKL0vfUv39/6taty+rVqzlx4gSRkZE888wzjBgxgvfee0/mQxNCiHJmMmH9+OOPZRlHPp6ennh6ej623sGDB02WTZgwgQkTJhT5nC1atCj1BcyWLVtGeHh4qZ7D4MqVKwDFmii4ONzc3MrsXEKIp4884ypj4eHhnAm5QI6u9Ftsmuzcf95TETGlfi5tiqx5JIQoXWZJWIsXLyYiIoJvv/3WHId74uXonEnzeLG8wzAr2wt7yzsEIcQTziwJ69y5c5w5c8YchxJCCCEK9IStxy2EEOJJJQlLCCFEpSAJSwghRKUgowSFEJWer68v+/btU71fcV/98Pb2ZsCAAarPJ0rGLAnLzc2N7OxscxxKCCHKzKOz5oiKzywJa+7cufm2paenExUVVeAKv0IIYU4DBgyQFs9TQFUfVuvWrXn77beLVPfNN980TiIrhBBClJSqhJWenl7oasAGKSkpxMXFkZj4hK75LYQQosyZfCQYERHBO++8Q05OTp7tISEh9O7d2+QBFUUhMTGRtLQ0GjdubLZAhRBCPN1MJqzGjRvTrVs3duzYYdym0WjIyMggJubxc9NZW1vz4YcfmidKIYQQT71CB11MnToVLy8vILflNHbsWNzd3Zk6darJfbRaLTqdDldXV5ycnMwbrRBCiKdWoQnL0dGRHj16GH9u1aoVzZo1y7NNCCGEKAuqhrWX9xpZQgghnl7Ffg8rKCiIw4cPc+3aNZKSkti2bRsPHz5k27ZtDBkyhGrVqpkzTiGEEE851QkrJiaGDz/8kHPnzgG5fVsajQaAGzdu8NVXX/Hdd9+xYsUKOnbsaN5ohRBCPLVUvYeVnJzM6NGjOXv2LC4uLgwZMoS6desay21sbKhTpw6JiYn4+PgQERFh9oCFEEI8nVQlrPXr1xMZGYmnpyd+fn7MmTOHmjVrGsvd3Nw4cOAAffv2JT09nbVr15o9YCGEEE8nVQnrwIEDWFlZsXDhQuzs7AqsY2Vlxfz587G1teXPP/80S5BCCCGEqj6sGzdu4O7u/tgBFU5OTri6uhqn7heiIMuWLSM8PLxMzlXcZSSKy83NrczOJcTTQlXCsrKyKvL8gGlpaSZbYUIAhIeHc/n8aRo4lP7SNFWU3IFBaZEnSv1cN5IsSv0cQjyNVCUsd3d3zp07x5UrV3B3dzdZ79KlS1y7do127dqVOMAnTXx8PNqUe9he2FveoZiVNuUe8fHWqvdr4JDNzA5JpRBR+Zl/0qG8QxDiiaQqYQ0aNIgzZ87w8ccfs3z5curVq5evzs2bN5k0aRIajYaXXnrJbIEK8cS7D9pAVd3KxZP2379tS/9U3AfqPraWEEWiKmG99tpr+Pr6EhQUxEsvvUTLli2JjIwE4F//+hcREREEBQWRmZlJ27ZtGTx4cGnEXKk5OztzLSGDNI8XyzsUs7K9sBdnZ+fyDqPSKsuFTg39ee51TT8lMZu6ZXtt4smmKmFptVpWrFjBggUL2LlzJ8ePHzeWrVu3DkVRgNzVP+fNm4elpVkWNBbiiVeWAzQM51q2bFmZnVMIc1CdUWxtbZk3bx7vvvsugYGBREREkJSUhJ2dHQ0bNqRnz56yDpYQQgizK3YTqG7dugwfPtycsQghhBAmlUEPrxBCCFFyJltY5mg9aTQatmzZUuLjCCGEECYT1qlTp0p8cMMs7kIIIURJmUxYs2fPLsMwhBBCiMKZTFhvvPFGWcYhhBBCFErVoIuYmJgi101ISGDKlCmqAxJCCCEKoiphvfXWW9y+ffux9Xbt2oW3tze//vprsQMTQgghHqUqYd28eZO33nqL6OjoAstv3bqFj48Pn3zyCQkJCTzzzDNmCVIIIYRQlbB69+5NdHQ0I0aMICoqyrhdURQ2bNjAiy++SFBQEFqtlrfeektaWEIIIcxG1UwXy5cvZ+rUqezbt48RI0awceNG0tPTmTlzJiEhISiKQvPmzZk7dy7NmzcvrZgrPW1KfJksL6LJTAVAsSr9dcm0KfFArVI/jxDi6aUqYVlaWrJkyRJ0Oh0//fQTQ4cOJSkpiaysLBwcHPjwww8ZPny4vH9ViHKZlbtxWSSSWjIrtxCiVKmeS1Cj0TB//nwcHBzYsGEDAJ07d+bzzz+XPqsikFm5hRCieIo9l+Ann3zChAkTgNwVhu/fv2+2oIQQQoi/KvFcgra2tty/f58RI0bkeyQkcwkKIYQwF7PNJfjgwYN8+0hflhBCCHORuQSFEEJUCjKXoBBCiEqh2CsOGzx48IDk5GR0Oh1OTk7miEkIIYTIp1gJ6/r166xatYrAwMA8owMdHR3p3r0748ePp3HjxmYLUgghhFCdsAIDA5k0aRJpaWkoipKnLDExkX379nHw4EG++OIL+vbtW+zAjh49yqpVq7h06RKZmZk0b96csWPH0qNHjyLtf/v2bXr37m2yvF27dnz//fd5tt25c4cVK1YQFBREXFwctWvX5uWXX+add97B2tq62NcihBCi5FQlrKioKCZNmkRqaio9evTgrbfeonnz5uh0Oh4+fEhoaChbt24lKCiIadOm8csvv1C/fn3VQe3cuZPp06djbW1N586dycnJ4dixY/j4+DB37lyGDh362GNcuHABgCZNmqDX6/OVu7q65paf7zEAACAASURBVPk5JiaGoUOHEhMTg4eHB82bN+f06dMsW7aMP//8k3Xr1mFlZaX6WoRp8fHxxD20YP5Jh/IOxayuP7SgRnx8eYchxBNHVcJas2YNqampDB8+nFmzZuUp0+l01KxZkz59+jBnzhy+//57Nm/ezIwZM1QFFBsby2effYajoyPbtm0zJpvg4GDGjBnDggUL6N27NzVr1iz0OGFhYQD4+Pjw8ssvP/a8s2fPJiYmhg8++ID33nsPgJSUFMaPH8/Ro0fZvHkzb7/9tqprEUIIYT6qElZQUBD29vZMnTq10HrTpk1j165dHDp0SHXC2rJlCxkZGfzjH//I0zJq1aoVPj4+LF26lO3btz92iiNDC6sok/BevXqVwMBAGjRowLvvvmvcrtPpWLBgAX379mXLli2SsMzM2dkZXWIEMzsklXcoZjX/pAO2zs7lHYYQTxxVUzPFxsbSqFEjbGxsCq1na2tL48aNuXPnjuqAjhw5AlBg/1e/fv0AOHz48GOPExYWhk6ny/foryD/+c9/UBQFT09PtNq8H0mdOnXw8PAgOjqa8PDwolyCEEKIUqAqYel0OuKL+Gw+Pj7+sYntrxRFITw8HK1WS6NGjfKVN2zYEK1WS3h4eL4BH4+6f/8+t27dwtXVlfXr1/Pyyy/TunVrunfvzqxZs/IlUkMicnd3L/B4hlguX76s6nqEEEKYj6qE5eHhwa1btzh69Gih9YKCgoiOjqZZs2aqgnnw4AEZGRk4OTkVOCrP0tKSatWqkZqaSnJyssnjGPqvQkND+eqrr6hevTqdOnUiOzubH3/8kddee42rV68a68fGxgKYnG2+Ro0aANy9e1fV9QghhDAfVX1YgwcP5o8//mDy5MksWrQIT0/PfHUOHjzI9OnT0Wg0DB48WFUwqam5Cw7a2ZlecNDW1haA5ORkHBwKHl1m6L9yd3dn5cqVxpGKKSkpzJo1i7179zJlyhR27tyZ57yGY5s6Z0pKiqrrOX/+vKr65vbw4UNA/byQZeXhw4c8qeMuHz58WKE/d6i494UQpqhKWN7e3vj6+uLn58d7771HzZo1adq0Kfb29iQnJxMWFkZsbCyKouDl5cULL7ygKpi/9h8VpLBHgQajR4/Gy8sLe3t7nB/p/NbpdMyfP58TJ04QGhrK2bNnadOmjfG8pibrNZyzKOd+VIsWLVQ/FjUnR0dHANq3b19uMRTG0dGRtHvlHUXpcHR0rNCfO1Tc+0I8vdLT0wv9RV/1i8NLly5l6dKlbN68mZiYGGJiYvKU29nZMXLkyGItVKjT6YDcoE0xlBXWCrOwsDD5/pednR2dO3dm165dhIaG0qZNG+N509LSin1OIYQQpUt1wtJqtUyePJmxY8fy559/EhkZaZxL0NXVlU6dOhl/g1PLwcEBnU5HQkICWVlZWFrmDS8rK4uEhARsbGyoUqVKsc4B4OLiAvzvUaCh78pUH1VcXFyeekIIIcpesSe/dXBwKNHUSwXRaDS4ubkRHBxMZGRkvgUhr127Rk5OToEzVzxq+fLlXL58mfHjx9OkSZN85Tdv3gSgVq1awP9GB5oath4REQHw2PMKIYQoPcVKWFlZWezZs4fff/89Twvr2WefpVu3bgwaNKjYfTc9evQgODiYgICAfAkrICAAgF69ehV6jEuXLuHn50ejRo3yJax79+4RFBSElZUVnTp1Mp4TcgeMTJkyJU9f2q1btwgLC6Nu3br54hFCCFF2VA1rh9z5BF999VVmzJiBn58fly9fJjo6mitXrhAQEMDcuXMZNGhQnmHjahiS3Zo1a/J0voWEhLB27VpsbW0ZNmyYcfuNGzeIiIgwjnwCjHMNrl+/Ps9IqOTkZGbMmEFSUhKvv/66cbh6/fr16dGjB9euXePrr7821k9JSWHmzJlkZ2czZsyYYl2PEEII81DVwkpKSuLtt98mKioKFxcX/va3v+Wb/HbPnj1EREQwbtw4du7cib29vaqA6tWrx7Rp05g7dy5vvPEGnTt3RlEUjh07RlZWFosXL6Z69erG+qNHjyY6OppFixYxaNAgALp3786YMWNYv349b731Fu3ataNatWqcPHmShIQEOnTowLRp0/Kc97PPPuPNN99k1apVHDx4EFdXV06fPk1cXBw9e/bkzTffVHUdQgghzEtVwtqwYQNRUVF07NiRf//73/kGV7z00kuMHz+ed999l9OnT7Nt2zbeeecd1UENHz6cOnXqsHbtWk6dOoW1tTXt2rVj3LhxdOnSpUjH+OSTT2jdujVbtmzhwoUL5OTk0KBBA3x8fBg1alS+mdfr16/Pjh07WLZsGYcPH+b69evUr1+fkSNHMmrUqHwDQIQQQpQtVd/Cfn5+WFpa8sUXX5gcCejo6GhcC2v//v3FSlgAnp6eBb6Y/FcHDx40WTZw4EAGDhxY5HPWrl2bRYsWFbm+EEKIsqOqD+vGjRu4u7s/dmmP2rVr4+7uzo0bN0oUnBBCCGGgKmFpNBqysrKKVDc7O5ucnJxiBSWEEEL8laqE1ahRIyIiIh7bcrp+/Trh4eE0bNiwJLEJIYQQRqoS1sCBA8nJyWHSpEnG2R/+KjY2lkmTJhnrCyGEEOagatDFiBEj2LlzJ6GhofTv35/nn38eDw8P7O3tSUpK4sKFCxw8eJCUlBTc3NwYMWJEacX9VPH19WXfvn2q97ty5QqA6nkdvb29GTBggOrzCSFEaVKVsGxsbNi0aRMTJkzg7Nmz7Nmzh7179xrLDbOZt23blqVLl5pcrkOUjUffVxNCiMpO9ctFLi4u/PDDDxw9epTAwMB8k9/27t2brl27lkasT60BAwZIi0cI8dQr9tuwXbt2lcQkhBCizJhl+obs7Gxu3rxpnE3CwsLCHIcVQgghjIqUsKKiorh69So6nY7WrVtjbW1tLFu3bh2rV68mMTERgCpVqvDmm2/y3nvv5aknhBBClEShCev27dvMmDGDP//807itSpUqTJkyhcGDB7N8+XJWrFiRZ+n4Bw8esHr1akJCQvjuu+9KL3IhhBBPFZMJ68GDBwwdOpTY2Fi0Wi21atUiKyuL2NhYPv30Ux4+fMiaNWuwsLDAx8cHT09PNBoNhw4d4rvvvuPo0aPs27cPb2/vsrweIYQQTyiTCWvdunXExsbSrVs35s+fT+3atQE4f/48EydO5F//+hcACxcu5NVXXzXu16pVKxo3bszkyZP59ddfJWEJIYQwC5MzXRw6dAgrKyuWLFliTFYALVq0YMaMGSiKgq2tLa+88kq+fb29vXF2diYsLKx0ohZCCPHUMZmwbt++Tf369XFycspX1rFjRwAaNGiARqMpcP969eoRHx9vpjCFEEI87UwmrMTERKpUqVJgmWEtLJ1OZ/LAlpaWpKenlzA8IYQQIpfJhKUoisn3qbRabZ6/hRBCiNImGUcIIUSlIAlLCCFEpVDoi8MxMTGsWbOmWOUxMTEli0wIIYR4RKEJ69atW3z55ZfFKlcUxeQIQiGEEEItkwmrVatWknCEEEJUGCYT1o8//liWcQghhBCFkkEXQgghKgVJWEIIISoFsyzgKERx3UiyYP5Jh1I/z4OM3P7YqtbKY2qW3I0kC/SlfhYhnj6SsES5cXNzK7NzRV25AkDNhu6lfi49ZXttQjwtJGGJcjNx4sQyP9eyZcvK7JxCCPOSPiwhhBCVgiQsIYQQlYIkLCGEEJWCJCwhhBCVgslBF61bty7xwTUaDWfPni3xcYQQQgiTCSs9PR2NRoOiFP+9FZmLUAghhLkUOqzdMON6s2bNGDBgAJ07d5ZVhoUQQpQLkwlr27ZtHDhwAH9/fy5cuEBYWBhVq1bFy8uLAQMG0KlTJywsLMoyViGEEE8xjVKEZ37BwcHs378fPz8/oqOj0Wg0VK1alX79+hlbXpK8/ic9PZ3z58/TokULbGxsyjscwZP54rCvry/79u1Tvd+V/8764e6ubtYPb29vBgwYoPp8QhTV4747izTTRatWrWjVqhXTpk3j/Pnz+Pr64ufnx44dO/jpp5+oUqWKMXl16dJFkpcQFVj16tXLOwQhiqVILSxTwsLCjMnr2rVraDQaqlSpwvPPP8+AAQPo2rUrlpZP3+xP0sKqeJ7EFpYQTxqztLBMadasGc2aNWPSpElcunQJPz8//Pz8+Pnnn/n555+pUqUKx44dK8kphBBCCMCMLw67urrSvHlzWrZsiZ2dHYqikJiYaK7Di2K4e/cu77//Pvfu3SvvUIQQosRK1MJKSkoiMDAQPz8/jhw5QlpaGoqiYGFhQefOnfHy8jJXnKIYNm7cSHBwMBs3bmTy5MnlHY4QQpSI6oQVHx/Pb7/9hr+/P3/++SeZmZkoioKlpSXdu3enf//+PP/881SrVq004hVFdPfuXfbv34+iKOzfv59Ro0ZJZ7sQolIrUsKKiYnBz88Pf39/Tp8+TU5ODoqiYGNjQ58+ffDy8qJPnz44OjqWdryiiDZu3GicpSQnJ0daWUKISs9kwrp27Rr+/v74+fkRGhoK5M58YWdnR69evfDy8qJ3797odLoyC1YUnb+/P5mZmQBkZmbi5+cnCUsIUamZTFgDBw40ziXo6OiIp6cnXl5e9OzZE2tr67KMURRDv3792LdvH5mZmVhZWUl/ohCi0nvsI0FLS0tcXV2Jjo5m/fr1rF+/vsgH12g0bNmypUQBiuIZNWoU+/fvB0Cr1TJq1KhyjkgIIUrmsZPfZmVlERwcXKyDy2zt5cfFxYWBAweye/duBg4cKAMuhBCVnsmENXv27DIMI7+jR4+yatUqLl26RGZmJs2bN2fs2LH06NGjyMc4dOgQmzZtIiQkhJSUFGrUqEGPHj147733qFWrVp66WVlZtG3bloyMjAKPVbNmTQ4fPlyiaypro0aNIjIyUlpXQogngsmE9cYbb5RlHHns3LmT6dOnY21tTefOncnJyeHYsWP4+Pgwd+5chg4d+thjfPvttyxZsgStVkurVq2oXr06YWFhbN++HX9/f7Zs2ULjxo2N9cPDw8nIyKBBgwYFLl7p5ORk1mssCy4uLnzzzTflHYYQQphFhZvoLzY2ls8++wxHR0e2bduGXq8HcmeMHzNmDAsWLKB3797UrFnT5DHCw8NZunQpOp2OdevW0bZtWyB3tNzChQvZtm0bM2bMYPv27cZ9wsLCABg0aBDjxo0rxSsUQghRHMWamunBgwcsX76c1157jfbt29OsWTPatWvHq6++ypIlS0o0FdCWLVvIyMhg9OjRxmQFuTPG+/j4kJ6enifRFGTXrl1kZ2czZswYY7ICsLKyYsaMGTg7O3P27Fmio6ONZRcuXACgefPmxY5dCCFE6VGdsEJCQnjxxRdZsWIFoaGhJCcnoygKKSkphIWFsXbtWv72t79x+vTpYgV05MgRAPr27ZuvrF+/fgCP7UuysrKiSZMmdOzYscCyevXqAbmtOQNDC0sSlhBCVEyqHgnevXuXsWPHkpCQgF6v54033qB58+bodDoePnxIaGgoP/74I1euXGHixIns2rVL1eg0RVEIDw9Hq9XSqFGjfOUNGzZEq9USHh6OoigmRyFOnDjRuJzEX6WkpBAeHg5gHHihKAphYWHUqFGDgwcPsn37diIiIrCxsaFr165MmDChwHiEEEKUHVUtrO+++46EhAS8vLzYuXMnw4YNo3Xr1ri7u9OuXTtGjBjBzz//TL9+/bh3757qd7AePHhARkYGTk5OBb6cbGlpSbVq1UhNTSU5OVnVsQ3WrFlDSkoKLVu2pHbt2gBERUWRlJREXFwcn376KTY2NnTq1AkbGxt+/fVXXn/9dU6dOlWs8wkhhDAPVS2s33//HRsbG+bPn29yYUZLS0vmz5/PoUOHCAgI4IMPPijy8VNTUwGws7MzWcfW1haA5ORkHBwcVESfO8x99erVaLVaPv74Y+N2Q/9VzZo1Wb16Nc2aNQNyh7ovWbKEdevWMWnSJPz9/VUtyHj+/HlV8YnS8/DhQwD5xUOISkxVwrp16xbu7u5UqVKl0HpVq1bF3d2dq1evqgpGq318g6+4CyQHBgYyceJEsrOz+eijj+jUqZOxrH///gQGBqLVavOMPrS0tOTjjz/m2LFjhIaGEhAQwAsvvFDkc8qKw+bn6+vLvn37VO8XExMD5E4KrIa3tzcDBgxQfT4hhHqGFYdNUfVI0MrKqsiP4pKTk7GwsFBzeONEuunp6SbrGMoKa4X91U8//cT48eNJT09n/PjxjB07Nk+5RqOhdu3aBQ6V12q19OrVC5AWU2VWvXp1me1DiEpOVQtLr9dz9uxZLly4gIeHh8l658+fJzIyMs+Q8qJwcHBAp9ORkJBAVlZWvseOWVlZJCQkYGNj89hWnsHSpUtZuXIlGo2G6dOnM3r0aFUxQe4LuABpaWmq9xXmNWDAAGnxCPGUUtXCeuWVV1AUhYkTJ3Lp0qUC61y8eJEPPvgAjUbD3/72N1XBaDQa3NzcyM7OJjIyMl/5tWvXyMnJyfN+limKovDPf/6TlStXYm1tzZdffmkyWW3dupUPP/yQo0ePFlh+8+ZNgHzTOQkhhCg7qlpYgwcPZvfu3Zw6dYpXX32VNm3a4OHhgb29PUlJSVy4cIFz586Rk5NDhw4dGDx4sOqAevToQXBwMAEBAbi5ueUpCwgIADA+oivM//3f//HTTz/h4ODAypUree6550zWjYqKYv/+/VhZWdG1a9c8Zenp6Rw4cACAbt26qb0cIYQQZqKqhaXValmzZg0vvPACiqJw+vRptmzZwrfffsu2bds4c+YMiqLwwgsvsGrVKtV9WJA7NZKNjQ1r1qzJ02cUEhLC2rVrsbW1ZdiwYcbtN27cICIiwjgKDHJfLN6wYQOWlpasXr260GQF8Prrr2NhYcGePXuMyQlyp3KaN28e0dHR9OzZkxYtWqi+HiGEEOahUYo57O7atWscPnyYyMhIkpOT0el0uLq60qtXLxo2bFiioLZu3crcuXOxsrKic+fOKIrCsWPHyMrKYvHixXkeNfbp04fo6GgWLVrEoEGDABgyZAjnzp2jZs2ahSarcePGGSfA3bRpEwsXLkRRFFq2bEmdOnU4d+4cMTExNGrUiC1bthS5094w0kVGCQohRNE97rvT5CPBW7duYWNjY/JL2tXVFVdXV/NF+ojhw4dTp04d1q5dy6lTp7C2tqZdu3aMGzeOLl26FLpvamoqISEhANy5c4c9e/aYrDt48GBjwho5ciTu7u6sXbuW4OBgLl26RJ06dXj33XcZO3Ys9vb25rtAIYQQqplsYTVt2pQOHTrIisHFIC0sIYRQ73HfnYX2YRX3JV0hhBDC3CrcelhPAkOiN7V6sRBCiPwM35mmGkuSsEpBZmYmAJcvXy7nSIQQovLJzMw0zhv7KElYpcDe3h69Xo+VlZXJJVCEEELkpSgKmZmZJge5FZqw7t27xy+//FKiAF555ZUS7V8ZabVaHB0dyzsMIYSodApqWRkUOkqwpK0DjUZjXLpDCCGEKIlCW1jW1tYyw7UQQogKodCE1aJFC7Zu3VpWsQghhBAmqZpLUAghhCgvkrCEEEJUCpKwhBBCVAqSsIQQQlQKJgddTJgwgdq1a5dlLEIIIYRJxV4PS5SP+/fv8+KLLxIXF8elS5fKO5wyl52dzdatW/npp5+4du0adnZ2tGjRgpEjR9K7d+/yDq9M/fLLL0ybNs1k+bvvvsukSZPKMKKy16RJkyLV27RpE506dSrlaMxn165dbN26lcuXL5OTk4OrqyuDBg3irbfeKtbCuAaffPIJu3fvNvl+bHZ2Nt9//z0///wzV69eJTs7m/r16+Pt7Y2Pj0+5rz4hUzNVMnPmzCEuLq68wyg306dPZ9euXTg4ONClSxcyMzM5fvw4QUFBTJw4kfHjx5d3iGUmLCwMgG7duuHs7JyvvFmzZmUdUpl76aWXTJZFRUVx9uxZHBwcqF+/fhlGVTKff/453333HdbW1nTs2BELCwtOnjzJwoULOX78OMuXLy/WpA5btmzh559/NpnwsrOzee+99wgMDESn09G6dWssLS05d+4cy5Yt49ChQ2zcuBE7O7uSXmLxKaLS2LNnj6LX641/nja//vqrotfrlf79+ytxcXHG7ZcvX1bat2+vNG3aVLl27Vr5BVjG3nrrLUWv1ysxMTHlHUqFk5KSogwcOFDR6/VKQEBAeYdTZBcvXlSaNGmidO7cWbl69apxe0xMjOLp6ano9XrF19dX1TGzs7OVr776SmnSpImi1+uVZs2aFVjv+++/V/R6vfLSSy/luafu3bunDB06VNHr9coXX3xRvAszExl0UUncuXOHefPm0bZt2xI9EqjMdu/eDcCUKVNwcXExbnd3d+ell14iJyeHoKCg8gqvzF28eBEXFxdq1qxZ3qFUOAsXLiQiIoIhQ4bw/PPPl3c4RXb06FEUReHll1/Os6J7zZo1GTZsGAAnTpwo8vHOnTvHsGHDWLlyJXXr1i207s8//wzAjBkz8txTzs7OzJ49G4Bff/21yOcuDZKwKol//vOfpKens3jx4nxlISEhNGnShH79+hW4b3x8PC1atOD555/Ps87M6dOnGT9+PJ07d6ZFixb06dOH2bNnExMTU2rXURLLli1jz5499OzZM19ZcnIyABYWFk/F5xEVFUViYiLNmzcvtJ6vry9NmjRh1KhRBZZfvHiRJk2aMGLEiDzbDx06xN///nc6duxIy5Yt6d+/P1988QUPHjww2zWUluDgYHbs2EH16tX5+OOPjdsrw31heNR3586dfGUJCQkAODk5Ffl4kyZN4syZM7z44ov89NNPhdatVq0ajRo1olWrVvnKGjZsCEBsbCxQfveVJKxKYNu2bRw5coQpU6bw7LPP5itv2bIlTZo04caNG5w+fTpf+d69e8nMzOTVV181/ofYunUrw4cPJyAggGeffZY+ffpgaWnJ999/zyuvvEJoaGipX5da1tbW6PV6rK2t82z//fff8fX1RafT0bdv36fi8zD0X1WvXp158+bRr18/4xfAihUrSE9PB6BPnz5Uq1aN48ePF/gFa/itetCgQcZtX3zxBWPHjuWPP/6gadOmeHp6kpqaypo1axg0aBA3b94sgyssvoULF6IoCu+//z5VqlQxbq8M90WPHj3QaDT4+vry7bffEh8fT2JiIj/99BObNm2iatWqvPbaa0U+XpcuXdi6dStLliyhWrVqhdZdtWoV+/fvR6fT5SsLCQkBoFatWkA53lfl+kBSPNb169eVNm3aKCNHjlRycnIURVGUZs2a5evDWr9+vaLX65VPP/003zFeffVVpUmTJsqNGzcURVGU0NBQpWnTpkrr1q2VoKAgY73s7Gzlm2++UfR6veLp6amkp6eX4pWVTGpqqvL+++8b+yl69+6tHD9+3Fj+pH8eX331lbEvs2PHjsq7776rDB8+XGndurWi1+uVoUOHKqmpqYqiKMr8+fMVvV6vrF69Os8xsrKylK5duypt2rRRkpOTFUVRlICAAEWv1ytdunRRLly4YKybnp6u/POf/1T0er0yZMiQsrtQlQIDAxW9Xq/07NlTycjIyFdeGe6LH3/80fjv+OifoUOH5unXKo7C+rBMycnJMfaXLl682Li9PO4raWFVYNnZ2UydOhWNRsOiRYsKHRn08ssvY2Vlha+vr3GZaYDw8HBCQ0Pp2LGjcaTU5s2bycnJYdy4cXTt2tVYV6vVMmHCBJ577jmio6PZt29f6V1cCd26dYsDBw4QERFh3PboMP8n/fMwtLAGDhxIYGAgK1euZMuWLezdu5emTZty5swZli5dCmD8jXzPnj15jnHkyBHu3r3LgAEDjL9Vb9iwAcjtx3h0lKG1tTWzZ8+mYcOGnD17lpMnT5b2JRaLIf4xY8ZgZWWVr7wy3Bft2rWjS5cu6HQ6OnfuTNeuXbG3tyckJIRt27aZXD6+tHz55ZccP34cFxcXfHx8jNvL476ShFWBrV27ljNnzjB9+nTq1KlTaF1nZ2c8PT25f/8+hw8fNm4vqGlu6LQdOHBggcd64YUX8tSriGrVqsWff/7J8ePHWbp0KZmZmcybN49vv/0WePI/j2XLlvHrr7/y+eef53mEU69ePf7v//4PjUbD9u3byczMpGnTpjRv3pzLly8bEx1gXJz11VdfBSArK4szZ85gaWlZYD+PpaUlXl5eABw/frw0L69YwsPDOXr0KI6OjgwZMqTAOhX9vjh79iyDBw/m5s2b7Nmzh40bN7J+/Xr279+Ph4cHmzZtYtmyZWY73+N8/fXXfPvtt1hbW7N06dI8r0+Ux30lCauCunjxIt988w29evVi8ODBRdrH8J9t165dAOTk5LBnzx50Oh39+/c31jN0nJoaNVSvXj0A7t69W+z4S5tOp6NatWpUrVqVgQMHGt9NWb16tbH/5kn+PGxsbHBzc8vXnwe571/VqlWLlJQUIiMjgfyfxcOHDzl48CD16tWjY8eOQO5L6ZmZmbi4uJh8QbQifhYGhpZOv379CuyHMajI98XChQtJTk5mwYIFxuND7ijBL7/8EktLSzZs2EBqaipTpkwp8I85ZGVl8emnn/Lvf/8bGxsbli9fbrxPHlXW95W8OFxBffXVV2RmZpKVlZXvJszJyQEwbp8xYwbOzs707NmTGjVqEBgYSGJiIufPn+fOnTsMGjQoz3/gxz1SyM7OBijwy7CiatOmDQ0aNOD69etERUXh5ub2VH8eLi4u3L59m9TUVCD3BdvFixezd+9epk6diq+vL+np6XkGGBg+h8IePVfkz8Lf3x8Ab2/vQutV1PsiLS2N4OBgHB0dCxypV79+fVxdXbly5QrXr1/P9yjO4IsvvihRHMnJyXzwwQccOXKEKlWq8O9//7vAZAVlf19JC6uCSklJASAoKIg9e/bk+WO4AQw/G+paWFjwt7/9jYyMDAIDAzlw4ADwv6a5wTPPPANgclSOztHtNgAAEQxJREFUYXtFWm1aURQ+//xzJk2aRFZWVoF1DDe7ofxJ/TySkpKYNWsWEydONPlZGGI2vE9TtWpVnn/+eeLi4jhz5gwHDhxAo9HwyiuvGPdxcnLCysqKuLg4Yyv1r6KiooCK81kY3L59m8uXL+Po6EiXLl0KrVtR74uHDx+iKEqh71kayjIzM7l06VKBf0riwYMHjBgxgiNHjlC7dm22bt1qMllB2d9XkrAqqM2bN5u8IQ03reHnRx8dGDpC/f39+f333/M0zQ0MP/v6+hZ47v379wPw3HPPmf26ikuj0fDbb7+xb9++Al8OjoqK4tq1a+h0ujwvXD6Jn4e9vT3+/v4cOHCgwP6Tw4cPk5CQgF6vz/MCqOGz2LVrF8eOHaNjx4557h0rKyvatm1LVlaWsbXyqKysLAICAgAq3Lx8586dA6BVq1ZYWj7+wVFFvC+qV6+Ok5MT9+/fJzg4OF/5nTt3iIiIwMrKikaNGpnlnI/KyMhg7NixhIaG4ubmxg8//IBer3/sfmV5X0nCesI0atSItm3bEhAQwJ07d/I0zQ0ME2iuXLmSP/74w7hdURSWL1/OiRMnqFu3Lp6enmUdfqEMHenz58/P8+7HnTt3mDx5MllZWQwbNizPc/In8fPQaDTGz2LevHl5XjK9ceMGc+bMAWDcuHF59uvWrRu1atVix44dZGRk5BlgYGB4EXThwoV5OtIzMzOZM2cON27coGXLlgU+sipP58+fB3LftSqKinhfaLVaXn/9dSB3ooBH/13j4+OZMmUKmZmZvPbaa9jb25vlnI9atmwZZ8+epXbt2mzevNn4ztXjlOV9JbO1V0IeHh5kZ2ebbP7v2LGDmTNnotFoCAgIyPPbjsHmzZtZsGABiqLQtm1batasycWLF4mMjMTZ2ZnVq1dXuC+lzMxMxo8fz6FDh9DpdLRr147s7GzOnTtHSkoKvXr1Yvny5fmegz+Jn0daWhpvv/02p06dQqfT0b59ewCOHTtGRkYGY8aM4ZNPPsm331dffcWqVavQ6XQEBQUVODhh8eLFrFu3DgsLCzp06ICTkxPnzp0jJiaGevXqsX79eho0aFDq16jGhx9+yP79+1mwYIHxS/9xKuJ9kZ6ejo+PD8ePH8fGxoaOHTui0Wg4d+4ciYmJtGnThvXr1xc6qKQwTZo0wcLCIt9s7ffv36dXr16kpaXRvHnzQltwBfWRldV9JYMunkDt2rUDyNc0f9SIESNo1qyZceh8aGgotWvXZvTo0bz99tsVcn46KysrVq5cybZt29i5cycnTpxAq9Wi1+sZNGgQQ4YMQavN/9DgSfw8bG1t2bBhAxs2bGDPnj0cO3YMa2tr2rRpw4gRI4zDhP/K8Fk8+o7MX02bNo327duzZcsWzp8/T2ZmJvXq1WP8+PGMHj06z+wRFUV8fDxAkVsFUDHvCxsbG9atW8e2bdvYtWsXp06dIicnh4YNG/LOO+8wevToUhnwEhwcTFpaGgChoaGFzuBRUMIqs/tK1SvPolJYvny5otfrlV27dpV3KBWCfB7/M336dEWv1ysnT54s71DKndwX5lNW95X0YT0hDL8dnT9/nk2bNlG9enUGDBhQzlGVH/k8/sfwWRw5coQ9e/bQpEkT4yPEp43cF+ZTHveVPBJ8QqxYsYKNGzcah43Onj27Qr4rU1bk8/iff/7zn/j7+xs/i48++qicIyo/cl+YT3ncV5KwnhDN/n979x5TZf0HcPzNzUC0uJOCyUU9CjE9W4oIy7K7wiY6IdxiihhIWpY50i5r5cpw2ayGlyCJsdECSREKTEAuw1kuN9oRSLlIHEVQUw6HiyeOvz/YefL8OFz8ZUP8fV4bG3yf5/s83+fA+Oz5Pp/n+5kzBwcHByZPnkxsbCwxMTFjPaQxJZ/H34KCgjhx4gRubm688sorLF68eKyHNGbk7+LuGYu/K8kSFEIIMS7IMywhhBDjggQsIYQQ44IELCGEEOOCJF0I8T/Ytm0beXl5wMCKCffSKhgmf/zxB7m5uZw8eZLm5mb0ej2TJk3C29ubsLAwoqKihiydIcS9SJIuhLhDPT09hIaGotfrAYiOjuaDDz4Y41H9zWAw8Omnn5KZmUl/fz9WVlZ4eXnh7OyMTqejpaUFo9HIhAkTeOONN1i7du1YD1mIUZEpQSHu0E8//YRerycsLAyAgoICpcTLWDMajWzatImDBw9iY2NDYmIi5eXllJSUkJubS3FxMZWVlaxfv56//vqLnTt38u233471sIUYFQlYQtwhU3XV559/njlz5qDX65VSE2MtLS2NsrIy7Ozs+Oqrr3j99dcHrXfn5ubGm2++yTvvvAMMrA1348aNsRiuEHdEApYQd6C9vV0pNREaGsozzzwDDDzHGms6nY59+/YBsHHjRhYuXDjs/qtXr2bWrFnodLp7JuAKMRwJWELcgaNHj9Lf38/s2bOZOnWqsg7dmTNnaGhoGLLfyZMniY+PZ9GiRajVamJiYigpKeHUqVOoVCpeeumlQX1u3rxJRkYGK1euRK1WM2/ePCIjI0lPT7dYubWgoAC9Xo+DgwOxsbEjXouVlRUJCQls2bKF0NBQpb21tRWVSkV4eDjnz58nOjqaoKAgwsLCyMrKUvbr7Ozkiy++ICIigrlz56JWq1mxYgVpaWnKOnO3W7JkCSqVirKyMovjCQ4ORqVScerUKaUtLy8PlUrFe++9x+XLl9myZQsLFy5UzvXdd99hNBpHvFZxf5AsQSHugGk68IUXXgDA39+f2bNnU1dXR05OjsUaVF9//TWffPIJMFB23dfXF41GQ1JSEk899ZTF81y/fp3169dTU1ODtbU106ZNw97envr6es6ePUthYSHp6ek4OzsrfcrLy4GBCrijrZcUHh4+5DadTse6devo7OxkxowZNDY24u/vD0BzczNr167l4sWL2NjYMHPmTIxGI2fPnkWj0ZCfn096ejru7u6jGsdIOjo6iIqKoq2tDX9/f4xGIxqNhnfffZeqqip27949qkrDYnyTOywhRqm2tlYpmrls2TKl3fT94cOHuXnzplmfmpoaUlJSsLa25v3336eiooK8vDzKy8tZvHgxJSUlFs/11ltvUVNTg1qtpri4mGPHjpGfn09JSQmPPfYYGo2Gt99+26yPaWyjrbo7kra2Nuzt7Tl+/Djff/895eXlLFy4EIPBQGJiIhcvXmTBggWUlpZy5MgRjh49yo8//ohKpaK+vp7NmzfflXEAlJaW0tvbS1ZWFj/88ANFRUVkZGQwadIkiouLyc7OvmvnEvcuCVhCjNLhw4cBmDt3LtOmTVPaly1bhpWVFX/++eegALR3715u3bqlLLRqKsPu7OzMnj17mDp16qDz/Pbbb5SVleHk5ERqaqpZFdYpU6bw+eef4+joSElJCXV1dcq2jo4OAFxcXO7aNcfFxeHq6gqAk5MTVlZWFBYW0tTUhJubG6mpqWZFE319fTlw4AATJ07k9OnTyl3f3fDRRx8xf/585eeQkBC2b98OwIEDB5A3dO5/ErCEGIX+/n4KCwsBWLp0qdk2Ly8v5s2bB0Bubq7S3tfXR3V1NQBRUVGDjung4MDy5csHtZuC3qJFiywGH1dXVyWhoqKiYtTXUFhYiEqlsvi1ZMkSi31M13U7UxCKiIhg8uTJg7Y//PDDSjLKiRMnRj2+4Xh5eVmcPo2IiMDBwYH29vZBZd/F/UcmfYUYhaqqKjo6OrC2tlaeX90uPDycM2fOUF1djVarxcvLC61WS29vL3Z2dvj5+Vk8bkBAwKA2U/LG6dOnhyx/0draCkBTU5PS5uTkREdHB1evXrXYx8XFRSllbtLZ2cn58+ct7g9YfAbV3NwMDJTqGEpAQABHjhxR9v2nHn30UYvtEyZMYPr06dTV1XHhwgUCAwPvyvnEvUkClhCjYEq2MBqNPP7440PuZzQaOXToEK+++irXr18HBu6kTFOB/83R0XFQW1dXFzCQQt/e3j7suHQ6nfL9zJkz6ejoGDIAhYSEEBISYtZWVlZGYmLikMd/4IEHBrWZVviwNHYT0zbTvv/Ugw8+OOK5TJ+buH9JwBJiBF1dXco0nYuLC3Z2dkPup9frycvLY+PGjUqmXk9PD0ajEWvrwTPwlv6hOzg4AJCcnExcXNyoxxkWFkZ1dTWVlZX09fVZDDZ3g+m6hgsQpkBqKVtxqGdNllLhTXp6eobcZhrH7RmT4v4kz7CEGEFRURG9vb1MmDCBoqIiKioqLH6lpKQAcOnSJSorK/Hx8cHOzg6DwWA2dXe733//fVDb9OnTAYZ9r+vs2bPU1taaBY3IyEgcHBzo7u7m4MGD/+SSh+Xr6wsMZE0ORaPRAJgljNjY2AAMyqSEganJ4QLWUJ9FX1+fMu1oSrkX9y8JWEKMwDQd+OSTT/LQQw8Nud8TTzyhPPPJzc3F3t5emYI7dOjQoP0NBgP5+fkWjwNw7Ngxrl27Nmi7TqdjzZo1LF++3GyFChcXF+U9sC+//HLEDD2DwcDx48eH3ccSUyn0goICsylJk7a2NuWO1LTeIvw9rWcpeJeWlg57ztraWrOMSJP8/Hz6+vrw8/Mb8jmhuH9IwBJiGFqtll9++QUYuIMZjq2trbJPWVkZV69eZcOGDVhZWfHNN9+YZRB2dXWRnJxsMSkhODiY+fPn09nZSUJCAhcuXFC2Xb58maSkJG7cuIG7uzsRERFmfV988UVWrFiBwWAgISGBDz/8cNDdiU6n49ChQ4SHhytjupO7k6VLl+Lr68uVK1dISkqira1N2dbU1MTLL79MT08ParXaLLNPrVYDkJWVZTam6upqPv744xHPu3nzZrNgV1FRofR77bXXRj1+MX5JeREhhpGamsqePXtwdXWloqJixNUUWlpaePbZZ7l16xZbt24lPj6e/fv3s3v3bgA8PT1xd3ensbGRnp4eAgIC0Gg0hISEkJGRoRzn8uXLrFu3jnPnzmFlZcWMGTOwtramsbERg8HApEmTyMrKGjJTLzs7m507dyrTbO7u7nh4eKDX69FqtRgMBmU8iYmJZu+Itba2KoHm119/tZhc0dDQQHx8PBcvXsTW1pYZM2ZgNBo5d+4ct27dQqVSsX//fqZMmaL0aW1tZeXKlVy/fl3p09XVRWtrK2q1GkdHR6qqqsjMzCQ4OBgYWJpp27ZtuLu7c/PmTXQ6HbNmzaK3t1cJ9nFxcSQnJ4/0qxT3AbnDEmIYpim78PDwUS3988gjj7BgwQLg73eyEhIS2Lt3LwsWLECv19PQ0EBAQABpaWk899xzANjb25sdx9PTk5ycHLZu3UpgYCBarZbGxkY8PDyIjo7myJEjw6aVx8TEUFpaypYtWwgODqa/v5/6+nquXLmCt7c3kZGRfPbZZ5SUlLB69eohsxiH4u/vz+HDh9mwYQO+vr40Nzdz6dIlgoKC2L59Ozk5OWbBCsDb25vc3FwiIyNxdnamoaEBW1tbNm3aRGZm5rBJIh4eHuTk5PD000+j1Wq5du0aISEh7Nu3T4LV/xG5wxJiDO3atYu0tDRWrVrFjh07xno49xzTHVZgYKBS4Vn8/5I7LCH+RWvWrGHVqlXU1NRY3F5VVQUM/xKuEGKABCwh/kV+fn7U1NSwa9cusxUouru72bFjB3V1dTg5OVlcPUMIYU5eHBbiX5SQkEBpaSk///wzixcvxsfHBxsbG1paWuju7mbixImkpKTc1QVrhbhfScAS4l/k6elJfn4+2dnZFBcXo9Vq6evrw9PTk9DQUGJjY/Hx8RnrYQoxLkjShRBCiHFBnmEJIYQYFyRgCSGEGBckYAkhhBgXJGAJIYQYFyRgCSGEGBf+A2ODPRDH73u4AAAAAElFTkSuQmCC\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.set_context('notebook',font_scale=2)\n", "sns.boxplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " data = pheno[pheno.AgeGroup!='Adult'],\n", " )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Notice these changes do not reset after the `plot` is shown. To learn more about controlling `figure aesthetics`, as well as how to produce temporary style changes, visit here: https://seaborn.pydata.org/tutorial/aesthetics.html." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Finally, remember that these `plots` are `extremely customizable`. Literally every aspect can be changed. Once you know the relationship you want to `plot`, don't be afraid to spend a good chunk of time `tweaking` your `plot` to perfection:" ] }, { "cell_type": "code", "execution_count": 83, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 83, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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uAcXExODp06c4deoUzMzMMHr06ArX5efnV9iz4uTkhClTpiA4OBgxMTGwt7eHVCqt8KRZQ2Btba1KQjS9d2VlZTh9+jRu376tWvJR7pmp6qDZq1evAkCFDfg10bdvX3Tq1An3799HcnKyao9VTZfjno+vqlkzZXzKn526JBaLMWTIEMhkMpw8ebLWT8dpQ/kepKSkqK29JZfL63w5kqipYsJEOqNcjvP09ESLFi00Xufh4aHaz/Lbb7/BzMwMAwcOBFC+gfqvZDKZaj/LX+8DlBcFfH6jrdLTp08xbdo0+Pr6CjqSpVevXnB0dMTVq1exd+9eyGQyjBgxotJSzwcffIApU6ZU2MCu1Lp1a9V+rOf3mDQUyk3Ev/zyi9r2sLAw+Pv7w9fXVzVboewTHh6udonz/v37qhlGTQUaq/J8ovr777/DysoKnp6eNe6vjG/fvn0VClQqJScnq54oGzx4sOD4akKZVMfGxiI6OrpOluOE6NevH1q0aIG8vDy1pTiOHj2KgoKCeouHqDFjwkQ6kZ2djT/++AMA8Nprr1V5rZGRkeqaY8eOIS8vD7Nnz4ZIJMIPP/xQIQGRSCRYsmSJ2t+K+/fvj1deeQUFBQWYOXOmasMrADx48ABz5szBkydPYG9vX2Gzdk1MmDABCoUCwcHBqj//lfKemzdvxqlTpyq0RUZG4sKFCzAwMNDZh3NtBAQEwNTUFGFhYfj2228rVEQ/deoUVq5cCQB48803VU/EjR07Fk5OTsjNzcWcOXMqlF7IyMjAjBkzUFRUhN69e2ssNFqViRMnQiQSYdeuXXj69Cm8vb0FLWVNnjwZNjY2uHnzJj744IMKTwUmJSVh3rx5UCgUGDNmDLp37y44vpoYPnw4jI2NERcXh+TkZHh6etbrU2nGxsaYPXs2AGDZsmW4ePGiqu3SpUuqGlREVL1GsYcpJCQES5cuxZ49e9CvX78a97t06RK2bt2KxMREFBQUoGXLlqojBDQ9NUJ14+DBg1AoFLC1ta3Rb9Rvvvkmtm7dCplMhgMHDiAgIADvvfcevvnmG3z00UdYv3497O3tkZ6ejqKiIlVFaENDwwr3+frrrzF9+nQkJSVh9OjRcHZ2hoGBAdLT0yGTyWBpaYmtW7cK/tCaMGECNmzYAKlUChsbG7UzJhMnTkRcXByioqIwffp0tGnTBnZ2dhU2of/rX/9qkD97zs7OWLt2LRYvXowtW7Zg165dcHJyQn5+PrKzswGUl2v44IMPVH1MTEwQHByMgIAAnDt3DiNGjICzszPkcjlSU1OhUCjg6uqKb7/9ttL3qSaU1dYvXLgAQNhyHFC+b27jxo2YPXs2IiMjERsbq6r0rUy4+/fvrzoKRRcsLS0xaNAgVYkDfZwd98477+DKlSuIiIjA5MmT4ezsDABIS0tD586d0bJlS70c20PU2DT4GabExESt/kI7dOgQpkyZgqNHj6J169Zwd3eHhYUFwsPD8frrr6tmP0g3lEtmPj4+amvg/FWnTp3w6quvAvhfTaaZM2di8+bNePXVV1FYWIhbt27Bzc0N27ZtUy11/DXxad26Nfbt24dFixahe/fuyM7ORnp6OhwcHPD3v/8dBw8erPIxc02UH95AeU0idV+TSCTC119/jY8++gi9evWCRCLBjRs3oFAoMGrUKOzcuRMzZ84UPHZ98fb2RmhoKN544w20bNkSKSkpyM/Px0svvYR///vf+O677yo9ede1a1eEhoZi9uzZcHJyQmZmJu7du6fqo6yorS1lktS+fXutni7s27cvwsLC8M4776Bt27ZITU3F48eP8corr+Dzzz/Hzp07df6UmLKIpVgsrvJJUV0xNDTE119/jVWrVqFHjx64e/cu8vLy4Ovri59++qnKpwiJ6H9ECk2ncDYA0dHR+PDDD1VPRNV0hunRo0eqoyg2bNiAkSNHAgAUCgW+++47fPPNN2jXrh2io6Nr/HguNSxffvkltm3bhjfffBOfffaZvsMhHdmwYQM2btyIOXPmYMGCBfoOh4iasQY5w3T//n0sXrwY8+bNg1wuh52dnaD+0dHRKCwsxIQJE1TJElA+AzBz5ky4ubnh7t27SExMrOvQqY5MmzYNb775JpKSktS2K/cIaTNbRI2DXC5HaGgoRCIR/Pz89B0OETVzDTJhCgoKwsGDB9GjRw/s3btXY7VnTeRyOdzc3FTHYPyV8hHi6oobkv506dIFSUlJ+PLLL5GXl6d6XSqV4rPPPsONGzfQsmXLWldMpoalpKQEN27cwO3bt/HRRx/hzp078PDwqHAGIRGRPjTITd9dunTB2rVrMWHCBLVFC6szZcoUTJkyRW2bXC5X1V55vkozNSwzZ85EXFwczp07B3d3dzg6OsLQ0BBZWVmQSqUQi8X44osvalzEkBoHuVxeYXO3mZkZFi9erMeIiIjKNciESXnqti6EhIQgKysLDg4OGg///Ktnz54hOTkZ9vb2Wj3tQ9rZsmULDh06hPj4eNy7dw8ymQy2trYYNWoU/Pz80KFDB9XZcNR0uLq6Ij09HY6OjpgzZw5MTEz4faYGqaysDA8fPkSPHj14iHEz0CATJl1JTk7GqlWrAADvv/9+jZ7eUvabOnWqLkOjGsrOzkZ2draqKCY1XampqXjvvff0HQZRtYSWvKmKQqHA06dPUVBQAKlU2iAL3TY1hoaGEIvFsLa2hpWVlcYzTJtNwpSUlIR//vOfkEqlmDRpEnx9fWvcV1mFes+ePVzGIyIiAOUPKE2dOlX1GVFbCoUCOTk5KCwshI2NDdq0aQNDQ0ONH+BUewqFAmVlZarzHouKiuDg4KD2PW8WCdOJEyewcOFCSKVS+Pn5Yfny5YL6K5fh2rRpgw4dOugiRCIiaqTqaqvG06dPUVhYiM6dO3P7Rz0RiUQwMjJCy5YtYWVlhdu3b+Pp06dq67M1yKfk6tIvv/yC2bNnQyqVwt/fH59//rlWG8mJiIh0qaCgADY2NkyW9MTQ0BA2NjYaz1ds0jNMGzduxIYNG2BgYIClS5di2rRp+g6JiIhILalUym0femZpaamx5FCTTZh27dqFDRs2wNjYGF988QXGjh2r75CIiIg0Kisr4+ySnhkaGmrcaN/oE6a7d++iqKgIrVq1UtXkSUlJwdq1awEAa9euZbJERESNAjd461dV73+jT5iWLFmCc+fOYe7cuZg3bx6A8vo9MpkM1tbWOHbsGI4dO6a276RJk+rsUVAiIiJquhp9wqTOuXPnAJRvoAsLC9N43aBBg5gwERERUbUaRcK0a9cuQW2///67LsMhIiKiZqZRJExEREQEzJ67AA9yc/UdRo21trPD5o3r6uReISEhWLp0KYDygtInT56sskzQkSNHsGDBAgDAa6+9hjVr1tRqfCZMRFQrFy5cwJQpU/D111/Dx8dH3+EQNWkPcnPxsMUL+g6j5nJv6OS2Dx8+xIULF/DKK69ovCYyMrJOx2QFRyLSilQqBQC0bNkSQHn9kudfJyLSBWUV7qioKI3XSKVSnDhxAsbGxnU2LhMmIhKsrKwMo0aNwqxZs5CWlgYAyM3Nxfvvv4+BAwfi/v37eo6QiJqqIUOGwNTUFNHR0VAoFGqvOXbsGIqKijB06NA6G5cJExEJlpubi+7duyMxMRHz588HAHz00Uc4fPgwunbtqrFSLhFRbYnFYgwbNgwPHjxAYmKi2msOHz4MsVgMDw+POhuXCRMRCda6dWt89913OH36NPr16weRSIROnTrh999/R0hICHr27KnvEImoCfP29gagfllOIpEgPj4ew4cPh5mZWZ2NyYSJiLT25Zdf4vz581izZg3u37+PRYsWaTxWgIiornh4eMDMzAzR0dGV2o4ePYri4mJVUlVXmDARkVYePHiA/fv3w9vbG76+vggICMDZs2fxxx9/6Ds0ImriLCwsMGzYMNy9exdJSUkV2iIjI2FlZYVhw4bV6ZgsK0BEWmndujVCQkJgbm4OAJg9ezZGjhyJ7t276zkyImoOvL29ER0djSNHjqi2ATx58gS///47fHx8YGJiUqfjcYaJiLTWsWNH2NnZAQBMTEyYLBFRvVG3LBcTEwOZTIaxY8fW+XhMmIiIiKjREYvFcHd3x59//omrV68CKF+Oa9myJQYNGlTn4zFhIiIiokZpzJgxAIDo6Gjk5+fj7NmzGD16NIyM6n7HEfcwNTPjxo3D4cOH9R0GETVjY8eORUREhL7DoCbA09MT5ubmiIqKQseOHVFaWlrnT8cpcYaJiIiIGiVzc3MMGzYMGRkZ2L59O+zs7NC/f3+djMUZpmaGv9UREVFT4u3tjaioKKSnp+Ott96CgYFu5oKYMBERETUSre3sgNwb+g6jxlr//1O0uuTh4QGxWAypVKqTp+OUmDARERE1Eps3rtN3CHrj5+cHPz+/Sq+bm5trPFNu4sSJmDhxYp2Mzz1MRERERNVgwkRERERUDSZMRERERNVgwkRERERUDSZMRERERNVgwkRERERUDSZMRERERNVgwkRERERUDSZMRERERNVgwkRERERUDSZMRERERNVoFAlTSEgIXF1dcf78eUH9Hjx4gI8//hgjRoxAz549MXr0aAQHB6OkpERHkRIREVFT1OATpsTERHz66aeC+92/fx9/+9vfsHfvXlhbW8PDwwOFhYVYv349pk+fDplMpoNoiYiIqClq0AlTdHQ0pk+fDqlUKrjvihUrcP/+fSxYsAAHDhzA+vXrER0djUGDBuHcuXPYtWuXDiImIiKipshI3wGoc//+fXzzzTc4ePAgzM3NYWdnh9zc3Br3T09Px/Hjx9GpUyfMmjVL9bpYLMaqVaswcuRI7N69G++++64uwiciItKJOe/Nx4P8mn8e6lvrVnbY9O36OrlXQkIC3nnnnRpdu3r1avj5+dXJuEoNMmEKCgrCwYMH0aNHD3z++ef47LPPBCVMp06dgkKhgKenJwwMKk6itWvXDm5ubrhy5QrS0tLg7Oxc1+ETERHpxIP8XDwd01nfYdTckdt1fkuxWIwRI0ZUeU2nTp3qfNwGmTB16dIFa9euxYQJEyolPDWRlpYGAHBxcdF4/ytXruDmzZtMmIiIiBqRVq1a4auvvqr3cRtkwjRjxoxa9c/JyQEAODg4qG23t7cHAEGzVkRERNR8NciEqbaKiooAAGZmZmrbla9rs5mciJqGyMhIhIeHq2179OgRAMDGxkZtu4+PD7y9vRvFmNUJCgpCamqq2ra8vDxVXELZ2NjA1ta20utpaWl49uwZTE1N1faTyWRaP8VsbGwMY2NjtW1ubm4ICgrS6r5EQBNNmJTLeCKRSG27QqGo8G8ioufl5eUB0Jy8NJUxASA1NRWJl68A5taVG2XFQGmxVveVlOQhK09SuaHwKSACZCK5+o5yBaDQ0FaN4jIZihWllRtkZbh//75W9yRSapIJk1gsBgA8e/ZMbXtxcflfAObm5vUWExE1LN7e3hpnbAIDAwEAwcHBjX7MGjG3hmGX/vUyVNnVGBi0tYD49V71Mh4ASPdfUjvbRSREk0yYlHuXNO1RevjwYYXriIiIqHHIzs6Gq6urxvYff/wR/fvX/S8ATTJhUj4dp3xa7q9u3boFAOjWrVu9xURERES1V11ZATs7O52M2yQTpqFDhwIA4uLi8MEHH1QoTXD37l1cv34d7du3Z0kBIiKiRkZfZQUa9NEoNXH37l3cunWrwpMcHTt2xNChQ5GRkYF169apXpdKpVi2bBnKysrg7++vj3CJiIioEWr0CdOSJUswduxY7Nmzp8Lry5cvh729PbZs2YLx48dj/vz58PLywu+//45hw4Zh8uTJeoqYiIiIGptGnzBp0rFjR+zbtw9+fn549OgRjh8/jhYtWuD999/Hxo0bYWTUJFcjiYiISAcaRdawa9curdratm2L1atX6yIkIqImIS8vDygqQFl6Qv0MKC+F/H4BpPsvCe6qkJYAAERiE2FDPpQAfCiaaqlRJExE1Dg0xErW1NCIYGpkAjeHLoJ7KiuSuwjt66D5bFGimmLCRET1Ql+VrKlqtra2yMqT1F/hyvQEuHXrrFWBTr0W92wgWreyA47c1ncYNda6lW4e8dcHJkxEVGcabCVroiZi07fr9R2C3vTv3/i+jdMAACAASURBVB8pKSl6G7/JbvomIiIiqisaZ5j++OOPOhnglVdeqZP7EBEREemLxoTp7bffhkgkqtXNRSIRrl27Vqt7EBGRjmnzlJys/BBzGJsKHouoMdKYMLVo0UJtwiSTyVBYWAgAMDMzg6OjI6ysrFBcXIzMzEwUFBRAJBKhS5cusLS01F3kRERUa9o+PaZ6Ys2lc72NSaRPGhOmhITKv21IJBK89dZbyM7OxtKlS+Hj4wMTk//Vw1AoFIiJicEnn3yC0tJSbN68WTdRExFRnVi4cKFW/biJn5obQZu+169fj5SUFGzYsAF+fn4VkiWgfAnOy8sLwcHBuH37Nr788ss6DZaIiIhIHwQlTEeOHEHnzp0xYMCAKq/r1asXnJ2dceLEiVoFR0RE1JwoFAp9h9CsVfX+C6rD9PTpU0FF5549eybk9kRUh1h1GwgKClLttRFC2Ue57CREWloanj17BlNTYZuhpVIpAMDLy0vwmG5ubggKChLcrzpV/QxV9x5p+zOkjzEbCkNDQ5SVlfGsUz0qKyuDoaGh2jZB35UOHTogNTUVt27dQteuXTVel5iYiLS0NLz00kvCIiWietFcqm6npqYi8fIVwNxaWEdZ+W+ZiTe1qKhc+BQQATKRXFi//5/vl5QUCesnK8P9+/eF9akDtra2zWLM+iQWiyGRSNCyZUt9h9JsSSQSiMVitW2CEqbXX38da9aswcyZM7FmzRr069ev0jVxcXFYtmwZRCIRJk+erF3ERFRrrLr9/8yt6+3YDwAouxoDg7YWEL/eq17Gk+6/pLNEoqqfIV3Rx5gNhbW1NXJzc2FlZaVxloN0p6ysDI8ePYKdnfrjXAQlTFOmTEFcXBzOnTuHt99+G23atEGXLl0gFoshlUqRkpKCvLw8KBQKjBs3Dn5+fnXyRRARETV1VlZWKCoqwu3bt2FjYwNLS0sYGhrWuiYiaaZQKFBWVgaJRIJHjx7BwsICVlZWaq8VlDCZmJjgv//9L4KDg7Fnzx7cu3cP9+7dq3BNixYtMHv2bLzzzjvafwVERETNjEgkgoODA54+fYqCggLk5OSgrKxM32E1eYaGhhCLxbCzs4OVlZXGBFXwzjJzc3N88MEHmD9/Pv744w9kZmZCIpHA2toaTk5O6NevHzesERERaUEkEsHa2hrW1gL33ZHOaZ3ZmJiYYPDgwRg8eHBdxkNERETU4HAqiFT4GDoRNWS5ubn4+OOP8emnnzb5J+ao4RGcMCUlJWHTpk1ITExEYWFhleurPHy36Wguj6ETUcO1Y8cOXL58GTt27MAHH3yg73ComRGUMCUnJ+Ptt99GSUlJjaqRsmJp48LH0KmpycvLA4oKUJZe+WxMnZGXQiEtqb/xmonc3FxERERAoVAgIiIC/v7+nGWieiUoYdq8eTOKi4vh7OyMGTNmwMnJCWZmZrqKjYiICED57JLyl3C5XM5ZJqp3ghKm8+fPw9TUFDt37tRY2ImIqKGwtbVFVp6k3gtXisQm1V9IgkRHR0MmkwEAZDIZoqKimDBRvRJ0+O6zZ8/QtWtXJktERFSvvLy8YGxsDAAwNjbG6NGj9RwRNTeCEqZOnTohJydHV7EQERGp5e/vryooaGBgAH9/fz1HRM2NoIRpwoQJyM3NxZEjR3QVDxERUSV2dnYYN24cRCIRxo0bxw3fVO8E7WF69913kZCQgH//+9/Izs7GsGHD0Lp1a9U0qTrm5ua1DpKIiMjf3x8ZGRmcXSK9EJQw+fr6oqysDFKpFF999RW++uqrKq9nHSYiao7kDyWQ7r8kqI+yFIHQDePyhxLAQVCXRsvOzg6bNm3SdxjUTAlKmFJTU1X/zTpMRERqGBjC0sQYLg5dBHVT/v0qtB8cABcXF2F9iEgwQQlTbGysruIgokYiKCiowi9PNaXsoyyCKoSLiwsWLlwouJ9emFrAxaWz4CKvja04rD6OKbl58yYCAwOxefNmODs718uYREqCEqb27dvrKo5KTp8+jS1btiAlJQUymQzdu3fHjBkzMHTo0Brf49KlS9i8eTMSExMhlUrRpk0bDB8+HIGBgWjRooUOoydqulJTU5F4NQkG9paC+imMy49RupyTLqif/KFE0PVUP/RxTMknn3yCwsJCLF++HHv27KmXMYmUGuThuyEhIVi6dClMTEwwYMAAyOVyJCQkICAgACtXrsTf//73au9x9OhRLFiwAKWlpejZsyfs7e1x5coV/PDDDzh+/Dh++eUXnotGpCUDe0uIX+9VL2MJ3QtEuqePY0pu3ryJjIwMAEBGRgbS0tI4y0T1SmPCtGDBAohEInz00Uewt7dXvSaESCRCUFCQoD45OTlYvnw5rKys8NNPP6Fbt24Ayg/99ff3x6pVq+Dh4YHWrVtrvEdpaSmWL18OuVyODRs2wMvLCwBQXFyMBQsW4NixYwgODsZ//vMfQbFRwxIZGYnw8HC1bY8ePQKg+bBgHx8fjefmNSb6WB67c+cO0JgKWWtzlpysuPzfxqZajdfU6eOYkk8++aTCnznLRPVNY8IUFRUFkUiEBQsWqBKmqKgoQTdXFhkTYvfu3SgpKcHMmTNVyRIA9OzZEwEBAQgKCsLevXsxf/58jfdISUlBbm4u3NzcVMkSAJiammLOnDk4duwY/vjjD8GxUeORl5cHQHPC1FSkpqYi8fIVwNxaWEdZ+Ydd4s3bwvoVFcBSbAaYGArrpyfaboZWbcB26Vyv4zYW+jimRDm7pOnPRLqmMWEKDAyESCRCq1atVK/NnTtX5wHFx8cDAEaOHFmpbdSoUQgKCsLJkyerTJgMDMrrcebl5aG0tBRGRv/7MvPz8wGAe5iaAG9vb42zRI1tA22tmFvX21lp5TM1JfUyVl3QdqN4s/r50YKXlxdCQ0OhUCggEonq5ZgSJyenCkmSk5OTzsckep7GhGnevHmVXtN1wqRQKJCWlgYDAwN06VL50VpHR0cYGBggLS1N9T+qOs7Ozmjbti3u3buHxYsXY+HChbC3t8elS5fwySefsKw+EVEtTJw4EQcOHABQ/ve2r6+vzsdcvnw5pk2bpvrzX5foiHStQW36fvLkCUpKSmBjYwMTk8qbJIyMjNCqVSvk5eWhsLAQlpbqn9IxNjbG+vXrMXfuXERERCAiIkLV5uDggK1bt2LIkCE6+zrqAvfnNEz8vhABBw8ehIGBAeRyOQwMDBAaGqrzJblu3bqpZpmcnJy44ZvqXYNKmIqKigBUfZyKmZkZAFSZMAHlBwWPHz8eO3bsQPfu3WFra4vk5GTk5ORg+/bt6NGjB1q2bFm3X0A9aS77cxobfXxf8vLytNvUrK2iAsiMDQE0jj1MpBvR0dGQy+UAyjd918ceJqB8likwMJCzS6QXGhOmF198sdY3F3o0inLvUVVqUj08Pz8fU6ZMwYMHD7Bjxw7071++v6OkpAQrV67Evn37EBgY2KCfsOD+nIaJ3xei8j1M4eHhkMlkMDY2rpc9TED5LFNMTEy9jEX0VxoTJuUeodocbyK0r1gsBlD++L8myraqZqG2b9+O9PR0LFq0SJUsAYCJiQmWL1+O8+fPq/7p16+foBiJGhJbW1tk5UnqddO3sagEsnoZjRoqf39/1VYH7gml5qLKJTll0vTiiy9izJgxGDJkCIyNjXUWjKWlJcRiMfLz8ys93QaU11fKz8+HqakprK01P0Z97tw5AMDgwYMrtRkbG2PQoEHIyMjAtWvXmDAREQlkZ2eHcePGITQ0FOPGjau3o1GI9EljwrR//35ERUUhKioK165dw/Xr1/Hdd99hxIgRGDNmDAYPHqx2Y3ZtiEQiODs7IykpCZmZmZU29WVkZEAul1eoz6ROQUF54ThDQ/X7LJSvK+uIEBGRMP7+/sjIyODsEjUbGhOm7t27o3v37vjXv/6FGzduIDIyEjExMTh48CAOHToECwsLDB8+XDXzVFfJ09ChQ5GUlISjR49WSpiOHj0KAHB3d6/yHl26dEFGRgZOnDhRKbkqKyvD2bNnAQAvvPBCncRMRFQTVT1lWV319Yb2lKWdnR02bdqk7zCI6k31u6xRnli89957OHz4MMLCwjBnzhy0bt0ahw4dQmBgIAYOHIhFixYhNjYWJSW1K2rn5+cHU1NTbN26FcnJyarXr1y5gm3btsHMzAxTpkxRvZ6VlYVbt27h6dOnqteUZ81t2bIFFy5cUL1eWlqKL774Ajdv3oSLiwsGDBhQq1iJiOqKra0tl7aIGjDBZQVcXFzg4uKCefPmIT09HZGRkYiKikJYWBjCw8MhFovh4eEBb29vDBs2TPDMU4cOHbBkyRKsXLkSkyZNwoABA6BQKJCQkIDS0lKsXbu2wl8q06ZNQ3Z2NlavXg0/Pz8A5TNQM2bMwHfffYepU6eiV69esLGxwfXr13H37l3Y2dkhKChI45IdEZEuVPWUJRE1bLWqw9SlSxcEBgYiMDAQmZmZiI6ORnR0NA4fPozDhw9DLBZXmOGpqalTp6Jdu3bYtm0bLly4ABMTE/Tp0wezZ8/GwIEDa3SP999/H3369MGuXbtw5coVJCcnw8HBAW+99RZmzpwJBwcHwXERERFR81RnhSvt7e3RsWNHdO7cGbdu3UJRURGkUqnW9/P09ISnp2e118XFxdX6HkRERERVqVXC9PjxY8TGxiImJganT5+GTCaDQqGAsbEx3N3d4eXlVVdxEhEREemN4ITpwYMHiImJQUxMDC5cuICysjIoFAqYmZlhxIgRGD16NDw9Pas8toSIiIioMalRwnT79m1ER0cjJiYGycnJUCgUUCgUqg3eXl5ecHd3r7L6NhEREVFjpTFhunHjBmJiYhAdHY20tDQA5ZW/ra2t4enpCS8vLwwdOrTOi1cSERERNTQaEyZfX1/VWXKtWrXCyJEj4eXlhUGDBvFxfCIiImpWql2SMzIyQtu2bXH9+nVcv34d69atq/HNRSIR9u3bV6sAiYiIiPSt2sN3S0tLce3aNa1uLhKJtOpHRERE1JBoTJhWr15dn3EQERERNVgaE6bXXnutPuMgIiIiarBqdPguERERUXNWZ0ejEFHzIJPJIH9YBOn+S/UynvyhBHmGefUyFhGRJkyY9CgoKAipqamC+yn7BAYGajWui4sLFi5cqFVfIiKi5ogJkx6lpqYi8fIVwNxaWEeZAgCQePO28EGLCoT3IXqOsbExZC3MIH69V72MJ91/Cba2tvUyFhGRJkyY9M3cGoZd+tfbcGXpCfU2FhERUVPBhKm5KS5Eamqq4OW82iwDcgmQiIgaO40Jk5+fHzp16oSgoCDVa3fv3oWpqSmnxxszeRkkJaW4nJMuqJvCuAwABPeTP5QIup6ovkRGRiI8PFxtW3W/IPj4+MDb21tnsRFRw6MxYcrIyKh0Ztzw4cPRr18/7N69W+eBke4Y2FvW6/4TosaGvxQS0V9pTJgMDQ2RlZWFgoICWFv/b1OyQqGol8CIiHTJ29ubs0REVGMaE6YePXogISEBI0aMQNeuXWFiYgIAuHnzJt55550a3VwkEuGHH36om0iJiIiI9ERjwrR48WL4+/vjyZMnuHTpf8sqT58+xblz52p0cx6+S0RERE2BxoTJzc0NR48exZkzZ/Do0SOUlpbis88+Q6dOnfCPf/yjPmMkIiIi0qsqywpYWVnBy8tL9efPPvsM9vb2mDp1qs4DI6KGS/5QInhDv0JaAgAQiU0EjwUHQV2IiOqcoDpMP/74I6ysrHQVCxE1Aubm5nBxcRHcT/movotDF2EdHaDVeEREdUlQwvTqq6+q/vvWrVs4ceIEMjMzUVhYCLFYjE6dOmHIkCF48cUX6zxQImoYOnTogODgYMH9lDWNtOlLRKRvgit9FxUVYcWKFQgLC4NCoahQZkAkEuGbb76Bt7c3Vq5cCUtLyzoNloiIiEgfBCVMZWVlmD17NhISys8j69u3L9zc3CAWiyGRSJCcnIzLly8jMjIS+fn52LFjh06CJiIiIqpPghKmkJAQnD17Fu3atUNwcLDapbfk5GTMmzcPZ8+eRWhoKHx9fessWCIiIiJ9MBBy8YEDByASibB+/XqN+5R69OiBdevWQaFQICQkpE6CJCIiItInQTNMN2/ehKOjI3r06FHldT179oSjo6PqqRhtnD59Glu2bEFKSgpkMhm6d++OGTNmYOjQoTW+h1QqxbZt2xAZGYk7d+7A3Nwcffr0QWBgIF566SWtYyMiIqLmRdAMU0lJCcRicY2utbCwgFQq1SqokJAQ+Pv7IzExET179kTv3r2RmJiIgIAA7N27t0b3ePz4MSZNmoTg4GAUFhbC3d0dbdq0wbFjxzBlyhQkJSVpFRsRERE1P4JmmNq1a4e0tLRKB/L+1ZMnT5Camoq2bdsKDignJwfLly+HlZUVfvrpJ3Tr1g0AkJSUBH9/f6xatQoeHh5o3bp1lfdZvXo1UlJSMG7cOKxZs0Z1Ft727dvxxRdfYNmyZTh06JDg+Bo9hVyrooPakj+UIM8wT+v+QUFBWs1UKvsoH2WvqTt37gAof3S+vsYEyusMLVy4UHA/IiKqH4ISJg8PD+zcuRMrVqzAV199BQODyhNUcrkcK1asgEwmg4eHh+CAdu/ejZKSEsycOVOVLAHly3wBAQEICgrC3r17MX/+fI33uHv3Lg4ePIiOHTtWSJYAYPr06YiIiMDTp0/x6NEj2NjYCI6R6k9qaioSL18BzDUn6GrJystdJN68Laxf4SPAxBB5JiXC+gFQGJcBAC7npAvqJ38oETxWBUUFKEtPENZHVlz+b2NTwWMRETVHghKm6dOn48CBA4iMjER6ejrefPNNvPjii7CwsIBEIsH169exb98+3Lx5E9bW1pg+fbrggOLj4wEAI0eOrNQ2atQoBAUF4eTJk1UmTNHR0VAoFJg6dWqFZEmpWW9GFxnAwN4C4td71ctw0v2XYGtrW7ubmFvDsEv/ugmoGmVXY+r1/QFQq9k+bStgq6puu3SutzGJiBozQQmTvb09tmzZglmzZuHGjRv47LPPKl2jUChgY2ODjRs3wsFB2AFQCoUCaWlpMDAwQJculY9PcHR0hIGBAdLS0qBQKCASidTe59q1awCAl156CYWFhTh8+DCSk5NhZGSEgQMHYsSIERr7EjUm2i7jseo2EZEwgit99+7dGzExMdi1axdOnjxZ4WgUJycnuLu7Y/LkyWjVqpXgYJ48eYKSkhLY2NionRkyMjJCq1atkJeXh8LCQo2VxLOysgCUb/weP348srOzVW27d+/GwIEDsXHjRr1XIs/Ly9NuOaU25KWqQ1CJiIioZgQnTABgbW2NwMBArTa3VqWoqAhA+eGempiZmQFAlQnT06dPAQBLly5Fx44d8fXXX8PFxQUpKSn45JNPcObMGSxfvhxff/11ncZPRERETZNWCZOuqNtE/lfPn12nSXFx+YZWY2Nj7Ny5U/VEX9++fbF9+3aMHj0a4eHhmDt3LpycnGoXdC3Y2toiK09Sb/tzgPI9OiJx5dk7IiIi0kxQHSZdU9Z4UiY86ijbqpqFUrb5+PhUKn9gb2+P4cOHAwD++OOPWsVLREREzUODSpgsLS0hFouRn5+P0tLSSu2lpaXIz8+HqalplXWglKUC2rdvr7Zd+Xp+fn4dRE1ERERNXYNKmEQiEZydnVFWVobMzMxK7RkZGZDL5RXqM6mjbM/JyVHb/vDhQwBgDSYiIiKqkQaVMAFQnRV39OjRSm3K19zd3au8x7Bhw1TX/3WmqqSkBAkJ5U+l9e3bt9bxEhERUdPX4BImPz8/mJqaYuvWrUhOTla9fuXKFWzbtg1mZmaYMmWK6vWsrCzcunVL9WQcAAwaNAgvvPACMjMz8fnnn6OsrLwCs1wuxxdffIE7d+5g8ODBams9EREREf2VoKfkLl68iD59+ugqFgDlZ3gtWbIEK1euxKRJkzBgwAAoFAokJCSgtLQUa9eurVA5etq0acjOzsbq1avh5+cHADA0NMQ333yDf/zjH9izZw+OHz+OF198ETdv3kRWVhbatm2LlStX6vTrICIioqZDUMI0ZcoUdOrUCRMmTMD48ePRubPwYxVqYurUqWjXrh22bduGCxcuwMTEBH369MHs2bMxcODAGt2ja9euCA0NxZYtWxAXF4cTJ07A3t4eU6dOxezZs2Fvb6+T2AWrz3PAAEBeeTM9ERERVU1QwtShQwdkZWUhODgYwcHBePnllzFx4kR4e3ujZcuWdRqYp6cnPD09q70uLi5OY5udnR2WLVuGZcuW1WVodUYf54ClppZAqtWoREREzZeghOno0aNITEzEoUOHcOTIEVy6dAmXL1/G559/Dnd3d0ycOBHu7u5qjzWhyvRxDlhgYCAu56RrNS4REVFzpdVZcr1798ZHH32EU6dO4eDBgzh27BiOHj2K2NhYWFlZwdvbGxMmTOBTaERERNQkaH00ipGRETw8PODh4YHCwkLExMTg2LFjOH36NH799Vf8+uuvaN++PXx9feHr64sOHTrUZdxE1ABFRkYiPDxcbZtyKVnTGZQ+Pj7w9vbWWWxERLVRJ2UFLCws4OvrixkzZmDKlCkwMzODQqHAnTt3sHHjRnh5eSEwMFBtMUoiah5sbW0rPOFKRNSY1Prw3WvXriEsLAxHjhzB/fv3Va/37dsXEydOxIMHDxAaGorY2FicPn0a27Zt41IdURPl7e3NWSIiapK0SpgyMzMRHh6OiIgI1ayRQqFQlRz46xLc3Llz8e9//xsHDhzA6tWr8dtvv9VJ8KQd+UMJpPsvCeqjkJYAAERiYRv65Q8lgIOgLkRERA2OoIRpx44dCA8Px7Vr1wCUJ0nW1tYYM2YMfH19NRa1FIlEmD17Ng4cOKDax0D6UetSBg4Cq6M7aD8mERFRQyEoYVq7dm15JyMjDBkyBL6+vhg+fHiNyghIpeXVf6o7OJd0Sx+lDGojLy9Pu+Ke2pKXqmbTiIiIlAQlTG5ubnjttdcwbtw42NjYCBqoS5cuuHz5MkxNtahOTURERKRHghImFxcX5Ofna5X0sJglacPW1hZZeRIYdulfL+OVXY0RvE+LiIiaPkFlBY4dO4ZffvkFZmZmuoqHiIiIqMERlDDJZDK0adMGhoaGuoqHiIiIqMERlDB5eHjg5s2bSEpK0lU8RERERA2OoD1M//rXv3Dv3j28/fbbGDVqFHr37g17e/sq9zS5u7vXOkgiIiIifRKUMHl5eQEor78UERGBiIiIKq8XiUSqmk1EREREjZWghKlt27a6ioOIiIiowRKUMMXFxekqDiIiIqIGS9CmbyIiIqLmSKvDdwEgPj4ex48fR2ZmJgoLCyEWi9GpUycMGTIEI0aMgEgkqss4ieqHQq7V4cS1IX8oQZ5hXr2NR0REwglOmPLy8rBw4UKcP38eQPkGcKUzZ85g79696N27N7799lu0bt267iIlIiIi0hNBCVNxcTHeffddpKSkwNzcHF5eXnBzc4NYLIZEIkFycjLi4uJw8eJFzJo1C3v37uWRKNS4iAxgYG8B8eu96m1I6f5LsLW1rbfxiIhIOEEJ0+7du5GSkoIXXngB//3vf9XOIN2/fx8zZszAjRs38Ouvv+Ktt96qs2CJiIiI9EFQwhQREQEDAwOsW7dO43JbmzZtsG7dOowdOxZhYWFMmLQUGRmJ8PBwtW2pqakAgMDAQLXtPj4+8Pb21llsREREzY2ghCkjIwPOzs7o3Llzldc5OTnB2dkZGRkZtQqO1OPyDRERUf0SlDApFIoaH7xraGgImUymVVAEeHt7c5aIiIiogRBUh6lTp05ITU1FTk5Oldc9ePAAaWlp6NChQ62CIyIiImoIBCVMo0aNQmlpKRYtWgSJRKL2GolEgkWLFqGsrAyjRo2qkyCJiIiI9EnQkty0adMQEhKCc+fOYcyYMRg/fjzc3NxgYWEBiUSC69evIywsDLm5uWjXrh38/f11FTcRERFRvRGUMFlZWWHHjh2YNWsWMjMzsXPnzkrXKBQKODk5ITg4GFZWVloHdvr0aWzZsgUpKSmQyWTo3r07ZsyYgaFDh2p9z4CAAMTHx+PHH39E//79tb4PERERNS+CK307OjoiPDwcEREROHHiRIWjUZycnODu7o6xY8fC2NhY66BCQkKwdOlSmJiYYMCAAZDL5UhISEBAQABWrlyJv//974Lv+dNPPyE+Pl7rmIiIiKj50uosOSMjI0ycOBETJ06s63iQk5OD5cuXw8rKCj/99BO6desGAEhKSoK/vz9WrVoFDw8PQceuZGVl4csvv6zzWImIiKh5ELTp+69yc3Nx/vx5HDt2DED5cpymzeA1tXv3bpSUlGDatGmqZAkAevbsiYCAABQXF2Pv3r01vp9cLsfixYthbGwMFxeXWsVGREREzZNWCVNsbCz8/PwwdOhQvP3226qK03/++SeGDRuGtWvXorS0VKuAlMtmI0eOrNSmfOru5MmTNb7f1q1bkZiYiP/85z+ws7PTKiYiIiJq3gQnTBs3bsTcuXNx7do1AOUFKhUKBQAgOzsbUqkUO3fuxMyZM1FWVibo3gqFAmlpaTAwMECXLl0qtTs6OsLAwABpaWmqMaty48YNbNiwAaNHj8b48eMFxUJERESkJChhOnPmDDZu3AgLCwusWLECCQkJ6Nmzp6q9f//+WLNmDcRiMU6fPo2ff/5ZUDBPnjxBSUkJWrZsCRMTk0rtRkZGaNWqFYqKilBYWFjlvUpKSrB48WJYW1tjxYoVguIgIiIiep6ghOmHH36ASCTCl19+iUmTJsHa2rrizQwM4Ovri3Xr1kGhUODQoUOCgikqKgIAmJuba7zGzMwMAKpNmNatW4eUlBSsXLkSNjY2guIgIiIiep6ghOnSpUto06YNPD09q7xuyJAhaNeuHdLS0oQFY1B9ODVZirtw4QK+//57TJgwQe1eKCIiIiIhBCVMhYWFaNWqVY2utbGxEbzxWywWAwCKp6MoFAAAIABJREFUi4s1XqNs0zQLJZVK8eGHH8Le3h7/+c9/BI1PREREpI6gOkwODg7IyMhAaWkpjIw0dy0pKUFGRgbs7e0FBWNpaQmxWIz8/Hy1Y5SWliI/Px+mpqaVlgOVfv75Z2RlZcHV1RUrV66s0Kac8dqyZQv27duHSZMmoV+/foJiJD0oKkBZeoKwPrL/T7qNTYX1k2v3dCcRETVtghKmwYMHY9++fdiyZQvmzp2r8brg4GAUFhZi7NixgoIRiURwdnZGUlISMjMz4ezsXKE9IyMDcrm8Qn2mv5JKpQCAlJQUpKSkqL3m9OnTAIBBgwYxYWrgtK2dlZqa+v/9OwvsVwKpViMSEVFTJihhmjFjBsLCwhAcHIzs7GyMGzcOz549AwAUFBQgLS0Nv/zyC8LCwmBqaop3331XcEBDhw5FUlISjh49WilhOnr0KADA3d1dY/958+Zh3rx5atumTZuGM2fO8Cy5RmThwoVa9VPWBgsODhbc73JOulZjUtVyc3Px8ccf49NPP4Wtra2+wyEiEkRQwtShQwesX78e7733Hg4cOIDQ0FBVmzIBUSgUMDU1xdq1a+Hk5CQ4ID8/P2zbtg1bt27FkCFD0KNHDwDAlStXsG3bNpiZmWHKlCmq67OysiCTyeDg4FCrw36JlOQPJZDuvyS4n0JaAgAQiSuXxKhuPDgIHq7R2bFjBy5fvowdO3bggw8+0Hc4RESCCD5LbujQoTh48CC2bduG48eP4969e6o2GxsbuLu7IyAgAF27dtUqoA4dOmDJkiVYuXIlJk2ahAEDBkChUCAhIQGlpaVYu3Zthd9Op02bhuzsbKxevRp+fn5ajUmkVJvjc1TLgA6Vi65WyaF24zYGubm5iIiIgEKhQEREBPz9/TnLRESNilaH77Zv3x7Lly/H8uXLUVhYCIlEArFYXGczPFOnTkW7du2wbds2XLhwASYmJujTpw9mz56NgQMH1skYROpouwQIaL8M2Bzs2LFDVRJELpdzlomIGh2tEqbnWVhYwMLCoi5iqcDT07Paek8AEBcXV+N77ty5sxYREZG2oqOjIZPJAAAymQxRUVFMmIioUdEqYcrNzcWlS5fw+PHjKmsmAeWzRUTUvHl5eSE8PBwymQzGxsYYPXq0vkMiIhJEcMK0atUq7Nmzp0YVtwEmTNS0REZGIjw8XG2bcg+Tcmnur3x8fODt7a2z2Boyf39/REREACiv6O/v76/niIiIhBGUMP3yyy/YtWsXAMDa2hodO3ZUVecmau64iVkzOzs7jBs3DqGhoRg3bhzfKyJqdAQlTL/++itEIhHeffddLFy4EMbGxrqKi6hB8vb2brazRLXl7++PjIwMzi4RUaMkKGHKyMiAra0tFi1apKt4iKiJsrOzw6ZNm/QdBhGRVgQdvmtsbAwHh2ZQYY+IiIjoOYISppdffhkZGRmQSCS6ioeIiIiowRGUMM2cORPFxcX49NNPIZfLdRUTERERUYOicQ/Tnj171L7es2dPHDp0CElJSfDw8EDr1q2r3PzNsgJE+sESCEREdUdjwvTpp59CJBKpbVMoFMjIyEBmZma1AzBhImp4+Fg/EZEwGhOmV155pT7jIKI6xhIIRER1R2PCpCxQSURE9H/t3Xt8zvX/x/HHNdts5qyFYWPYtVmSc/gip28OURHCL1FKRVS+Cp18FcL3G0VC9PNF5LQcSyFtpMhxbDPMGLMZm80O7Hj9/vDb9W1tu65h2zXb8367ud26Pp/35/N5fV6Zva735/15v0XKunwHfV++fJnY2NjijEVERESkRMq3YOratSvjx48vzlhERERESiSLM30XdIFdKR30VpWIiEje7mhpFCm79FaViIiUZSqYxExvVYmIiOTtjmb6FhERESmLLPYwxcbGsmnTpnu6wFNPPXVPx4uIiIjYmsWC6cKFC0yePPmuT24wGFQwiUixMRqNBW47fPhw3n333SKMJm/z589nwYIFPP7443z++efFfn1bOnXqFE8++SRDhw7lww8/NG9/7rnnOHLkCIcPH8bJycmGEYrkz2LB5OjoqMG+InLf8fLyomLFihbb1KtXr5iikWwnTpwA4KGHHjJvM5lMhISE0LBhQxVLUqJZLJgeeuihfBfhFREpqd577z3atm1r6zDkL06ePAnkLJjCw8NJTEzMsU2kJNKgbxERKRYnT57E2dmZRo0a5dgGqGCSEk8Fk4iIFLn09HROnz6Nt7c35cqVM28PCgoCVDBJyad5mERE8uHn53dHL76Ehobe0/UuXrzIihUr+P3334mMjCQtLY2qVavSrFkznnvuOR599NEc7Z977jkOHjzImjVr2Lp1K5s3bwbg4Ycf5uuvv8bOzo7MzEz8/PxYu3Yt586dw97enjZt2jB+/Hh27NjBggULGDt2LK+//nqOc8fGxrJ06VJ+/vlnoqKiKF++PE2aNGHIkCH07NmzQPczadIkvvvuuxzbjh49mufg/IEDBwKwe/du6tatW+CciRQXFUwiIvmoUaMGLVq0KJZr7du3jzFjxnDr1i0qVaqEu7s7qampXLx4kV27drF7927+9a9/8cQTT+Q6dtasWRw7dgwvLy/i4+NxdXXFzs6O9PR0JkyYwI8//giAp6cn9vb27Nq1i71799KyZcs8YwkKCuKll14iNjYWR0dHGjRowM2bN/n999/5/fff6d+/PzNmzMBgMFi8p/r165vzd+XKFSIjI2nUqBGVK1cGbg/4Pnr0KJUrVzY/pitfvvxd51CkKOVbMI0dO5batWsXZywid0Rr30lR69y5M507dy7y66SlpTF58mRu3brFiBEjmDBhAo6OjgBcu3aNiRMnsn//fhYuXJhnwXTs2DEWLFhAjx49yMrK4saNGwCsWLGCH3/8kWrVqvHFF1+YC6TTp08zZswYfv3111znSkxMZMyYMcTGxjJw4EAmTZpkfuPw8OHDvPHGG/j5+WE0GhkxYoTF+3rllVd45ZVXAJg2bRrffPMN8+bNo3HjxgCcP3+exx9/nMcff5yPP/747pInUkzyHcM0duxYBgwYUJyxiBSaGjVqaEqMMmz48OEYjcZ8/+zatcvWIeZw8uRJUlJSqFmzJm+//ba5WAJ44IEHzIV/eHg4WVlZuY5v3rw5PXr0AMDOzo6qVauSkZHBkiVLAJg+fXqO3iQvLy/mz5+fZw/R2rVriYqKok2bNnz00Uc5pmdo2bKlubBZsmQJ6enpBb7H4OBgnJyc8PT0zHHfAL6+vgU+j4it6JGc3Le09p3kx9o8TFWrVi3GaKxr0aIFhw8f5tatWzkGRGdzdnYGICsri9TUVPPnbI888kiuY44ePWp+PNe1a9dc+729vWnZsiWHDh3Ksf3nn38GoHfv3nkWVJ06daJKlSrExsYSFBSU57X/Kisri9DQUIxGY54DvlUwyf2gxBZM+/fvZ9GiRYSGhpKeno6vry8vv/wyHTt2LPA5/P39WbFiBSdOnCAlJQVXV1c6duzIa6+9Rq1atYowehGxpcKah8nf359FixYVuP2aNWvu6XpOTk4EBQURHBxMREQEERERnD59mvDwcHObvHqYXF1dc20LCwsDbheP+Y018vHxyVUwZR+3cuVKtmzZkudx2T1L4eHhBSqYwsPDSUlJwcfHJ8f2kydPYm9vf0cztIvYSoksmLLfTHF0dOTRRx8lKyuLAwcOMGrUKKZNm8bgwYOtnmPJkiX8+9//xs7OjocffpgaNWoQEhLC2rVr2blzJ6tWraJhw4bFcDcicr+KjY3lyJEjxXKtP/74g5kzZ5p7XeD28lIeHh707ds33+IF8h4oHR8fD5CrN+rPXFxccm1LSkoC/ls4WZKYmGhx/6JFi/D39ze327t3L0OGDDHvP3nyJAaDIcdYqM8//zzPAlDE1kpcwRQTE8OHH35IpUqVWL16NV5eXgAEBgYycuRIpk+fzmOPPUbNmjXzPcfZs2eZN28eFSpU4Ouvv6Z58+bA7W9FM2bMYPXq1UyZMoW1a9cWyz2JyP2pf//+9O/fv8ivc/r0aV544QXS0tJo1aoVTz75JEajkYYNG1KxYkXCw8MtFkx5yS6UkpOT822T1z5nZ2cSExPZuHHjPc+NdP78+RwFZ2RkJJGRkbna/blNamrqPV1TpKiUuIkrV61aRVpaGiNGjDAXS3B7XpFRo0aRmppqtdDZvHkzmZmZjBw50lwsATg4ODBlyhSqV6/OsWPH8vzBFREpbitXriQtLY127dqxYsUKBg0aRLNmzczjsKKjo+/4nNmv6Z85cwaTyZRnm+y3Sf/Mw8MDsNzDdODAAcLCwkhLS7MYwyeffEJoaCgtW7bE0dGRkydPEhoaSmhoKHPnzgVuPz7N3hYaGqo5mKTEKnEF0969ewHo3r17rn3Zb4EEBARYPIeDgwNGo5HWrVvnuS/7BzImJuZewxURuWfZX97+Oig624YNG8z/nZmZWaBztmrViqpVq3Lt2rU8/82MiIjgjz/+yLX9scceA2DdunV5FlqHDh1i+PDh9OnTh8uXL1uNIysri5CQELy9vXFwcDBv1wzfcr8pUQWTyWTi7Nmz2NnZ5Xj1NFv9+vWxs7Pj7Nmz+X5jAhg3bhxbtmyhXbt2ufalpKRw9uxZAA38FpESoX79+gB8//33XLhwwbw9ISGBGTNm5JhvrKCPrMqXL8+LL74IwLvvvsvx48fN+yIiIhgzZkyexdfQoUOpVq0ahw4dYsqUKTnGKZ04cYI333wTgG7dupnjtiQsLIyUlJRchVFQUBD29va5BoKLlFQlagxTQkICaWlpVK9ePcc8JNns7e2pVq0asbGxJCcnW3xtOD9fffUVKSkpNG3aVBNzikiJMHLkSLZu3UpMTAy9e/c2f2E8f/48aWlpeHt7Ex0dTXx8PDExMQUeFP3CCy9w6NAh/P39GTRoEA0bNsTBwYEzZ85QoUIFPDw8uHDhQo5erRo1ajB//nxee+01/Pz82L59O40aNSIpKclczBmNRmbOnFmgGPJbXDc4OJiGDRvi5ORUoPOI2FqJ6mG6efMmYPmtjuwfLksDGfPj7+/P4sWLsbOzY+LEiXcXpIhIIatXrx6bNm3i6aefpnbt2oSHhxMVFYW3tzeTJ09m/fr1dOjQAYA9e/YU+Lz29vYsXLiQyZMnYzQaiYyMJCoqih49erBhwwbq1asHkKtoad26NVu3bmX48OHUrl2bs2fPEh0djZeXF6+//jpr1qwxL29iTV6P3i5evEhCQoIex8l9xWCy9GyrmF25coVOnTpRp04d8+Rpf9WlSxcuX75MQECAxTfl/uqXX35h3LhxpKamMmHCBF5++eUCH3vp0iW6deumRSFFpFQZOHAggYGBzJkzh379+tk6nPuOfjeULSWqh6lChQqA5Wf02fss9UL91YYNGxgzZgypqamMGTPmjoolEZH7UXJyMh07duS5554z997/2dWrVwkJCQGgSZMmxR2eyH2nRBVMFStWpEKFCly/fp2MjIxc+zMyMrh+/Trly5cvcHfwvHnzePfdd8nMzGTy5MmMGzeusMMWESlxXFxcqFKlCgcPHmTevHk5vohGR0fz5ptvkp6eTqtWrcxTEIhI/krUoG+DwUCjRo0IDAzk/PnzuX6Isxee/PP8TPkxmUy89957bNiwAUdHR2bNmkXv3r2LKnQRkRJnypQpjB49muXLl7Nx40bc3d25efMmERERZGRk4OHhwaxZs2wdpsh9oUT1MAHmteLyWk08e1vnzp2tnueTTz5hw4YNVKxYkWXLlqlYEpEyp3379mzfvp0hQ4ZQs2ZNwsPDuXr1Ko0bN2b8+PFs3LhRY29ECqhE9TDB7aUIli5dyldffcXf/vY381sUJ06cYOnSpTg5OTF06FBz+4iICNLT03nwwQepVKkScHtiy+XLl2Nvb8/ixYtp1aqVTe5FRMTW3N3dmTp1qq3DELnvlbiCqW7durzzzjtMmzaNZ599lkcffRSTycSBAwfIyMhg1qxZ1KhRw9x+xIgRREZGMnPmTPOaTwsWLABuzyfy7bff8u233+Z5rVdffVUL8IqIiIhVJa5gAhg2bBhubm4sXbqUw4cP4+joSIsWLXj11VfznL37z27evMmJEyeA29MUbN26Nd+2AwcOVMEkIiIiVpXIggluz7fUpUsXq+3+Ol+Ts7Oz+VVZERERkcJQ4gZ9i4iIiJQ0KphERERErFDBJCIiImKFCiYRERERK1QwiYiIiFihgklERETEChVMIiIiIlaoYBIRkXwdOHAAo9FI27Ztc2zv2rUrRqORPXv23PE5x4wZg9FoJC4uzrzt4MGDGI1G5s6de88xixQFFUwiIlKsTp48iZubG9WrV8+xDTCvHypS0qhgEhGRYhMbG0t0dHSuwkgFk5R0KphERKTYZK/1mVfBVKNGDWrXrm2LsESsUsEkIiLFJq+epMTERCIiItS7JCVaiV18V0TkTvj5+TF58mQGDx7MmDFjmD17Nr/++iupqak0aNCAZ599lmeeeQY7u4J9T5w0aRLfffddgdq2adOGlStXFqjtgQMHWLFiBaGhoURHR1OpUiWaNGnCgAED6N27d54xfPHFF9SsWZMvvviCI0eOkJ6ejre3N2PGjOFvf/sbKSkpfPHFF/zwww/ExMTw4IMP0rdvX8aOHYuDg0OOc2ZmZrJt2za2b99OcHAw8fHxODo6Uq9ePbp168bIkSOpVKlSge6lIC5dukS3bt1ybX/hhRdybfP398doNPL000/zySefFFoMIoVBBZOIlCpXr15l0KBBREdH07BhQ7KysggKCuL9999n3759fPrpp9jbW/+nr379+rRo0aJA1/Ty8ipQu61bt/L222+TlZVFrVq1MBqNXLt2jX379rFv3z5OnDjBO++8k+u4X375hU2bNuHg4ED9+vW5ePEiR44c4eWXX+bLL7/k3//+N2fOnMHd3Z3atWsTERHBokWLuHbtGtOnTzefJz09nVdffZW9e/cC4O7uTs2aNYmOjubUqVOcOnWKXbt2sWHDBhwdHQt0T9aUL18+Rx6PHTuGk5MT3t7e5m2XL18mOjoao9GIi4sL9evXL5RrixQqk1h18eJFk5eXl+nixYu2DkVE8rFx40aTl5eXycvLy9SmTRvTwYMHzfv2799vatGihcnLy8u0YsUKm8SXmZlpat++vcnLy8u0ffv2HPu+++47k9FoNHl7e+f4d+add94x39Prr79uSkxMNJlMJlNiYqLpqaeeMnl5eZm8vb1NXbp0MQUFBZmPW7ZsmcnLy8vk4+Njun79unn7ihUrTF5eXqb27dubQkJCcsTw/fffm3x8fHLF9/vvv5tz+mddunQxeXl5mX7++ecC5yA2NtZ8L3/21ltvmby8vEzR0dEFPldJoN8NZYvGMIlIqTNjxgxat25t/tyuXTumTJkCwJIlSzCZTMUeU2xsLNeuXaNKlSr06tUrx76nnnqKQYMG0adPH5KSknIdW6VKFWbMmEHFihUBqFixIkOGDAEgKyuLqVOn0qRJE3P74cOH4+joSGZmJmfOnDFv//333ylXrhyvv/56jh4egF69etGmTRsAwsLCCuem/yI4OBggR6xwe1zTAw88QM2aNYvkuiKFQQWTiJQqderUyXPMTN++fXF2diYmJsb8i7s4VatWjUqVKpGQkMCUKVNyFDIA06ZN41//+leuQgagRYsW5mIpm5ubGwD29vY8+uijOfbZ29tTtWpVAJKTk83bv/jiC44fP84zzzyT6xqZmZm4uLgAcPPmzbu4Q+vyKpiSkpK4cOFCriJKpKTRGCYRKVXye9PK0dERDw8PTp06xYULF/D19bV4nkWLFuHv71+gazZp0oT333/fYht7e3vGjRvH9OnT8fPzw8/Pj9q1a9OhQwc6d+5Mx44dcXZ2zvPYvHpesgdzV6xYMc/xRtn7/9qb5uDgQEJCAocOHeLcuXNcunSJc+fOERwcbO7dKqoeuJCQECBnwRQcHIzJZFLBJCWeCiYRKVUqV66c777sHpS8Hnv91fnz5zly5EiBrlmQQeRw+1GZh4cHy5cv5+DBg0RFRbFhwwY2bNiAi4sLo0aN4rXXXst1XIUKFQp0fmtSU1P59NNPWbt2bY5eJBcXF5o3b861a9c4depUoVwr29WrVxk3bhwAoaGhGAwGXn/9dfP+7OVRfvjhBw4ePAhA586deeWVVwo1DpF7pYJJREoVS4+TsgulatWqWT3PJ598UiSvtnfu3JnOnTuTmJjIgQMH2L9/P3v27OHy5ct89tlnuLi48Pzzzxf6dQGmTJnCtm3bqFChAqNHj6Z58+Y0bNiQunXrYmdnx4QJEwq9YEpNTc1VeOZViF64cIELFy4A4OHhUagxiBQGFUwiUqrkN2A5NTWV8+fPA9CwYcNijOi2tLQ0zp8/T2ZmJj4+PlSqVInu3bvTvXt33nvvPaZMmcJ3333Hli1biqRgunLlCtu3bwdg8eLF5gHefxYdHV3o161bty6hoaH89ttvjBgxgnHjxjFmzBjz/t69exMbG8uBAwcK/doihUmDvkWkVAkJCcmzl2TLli2kpqbi6emJp6dnsce1c+dO+vbty4QJE3KNEbKzszMP3M7KyiqS60dGRpqvm9d4obCwMI4dOwZARkZGoV8/ryVRUlJSCA8P1wzfcl9QwSQipc4bb7xBeHi4+XNAQAAzZ84EYPz48TaJ6bHHHsPFxYWwsDBmzJiR49Hh5cuXWbZsGQCdOnUqkut7eHiYZzlfvHgxmZmZ5n0HDhzgpZdeMhdKqamphX797CVRmjZtat4WHBxMVlaWCia5L+iRnIiUKq6ursTFxdG7d2+8vLy4deuW+VHcCy+8QM+ePW0Sl4uLC7Nnz2bs2LGsWLGCjRs34u7uTlpaGhcuXCAjIwNfX19eeumlIrl+jRo1GDZsGCtXrmTJkiVs3LiR2rVrExMTQ0xMDPb29rRu3Zo//viDmJiYQr/+yZMncXNzo3r16uZtQUFBQP5vNoqUJOphEpFS5cEHH2T9+vV0796dyMhI4uLiaNeuHYsWLcpz2ZHi1L17d1atWsXf//53XFxcOHPmDFeuXKFJkya88847fPvtt7nmWypM7777LrNmzeLhhx8mIyOD0NBQHBwc6Nu3L+vWrWPatGkA/PHHHwV6k7Cg4uPjiYyMzFUYqWCS+4nBZIspb+8z2YtH7t69m7p169o6HBHJQ/biu76+vvj5+dk6HCkD9LuhbFEPk4iIiIgVKphERERErCixg77379/PokWLCA0NJT09HV9fX15++WU6duxY4HOEh4czf/58Dh8+THx8PO7u7gwePJihQ4ea3xYRERERsaZEVg1+fn6MHDmSo0eP8vDDD9O8eXOOHj3KqFGjWLt2bYHOcerUKZ555hm2b9+Om5sbHTt2JDo6mo8++oi33367iO9ARERESpMS18MUExPDhx9+SKVKlVi9ejVeXl4ABAYGMnLkSKZPn85jjz2W52KU2UwmE2+//TZJSUnMnj2bJ598Eri9ZtGIESPYunUrPXr04PHHHy+WexKRote/f3/69+9v6zBEpJQqcT1Mq1atIi0tjREjRpiLJYCHH36YUaNGkZqaarWX6ddffyU0NJQ2bdqYiyWA6tWr8+GHHwKwcuXKorkBERERKXVKXMG0d+9e4PZ8JX/Vo0cP4PasvXd7jpYtW1KjRg0OHz5cqPOMiIiISOlVogomk8nE2bNnsbOzy3Otp/r162NnZ8fZs2dzrcX0Z2fPngXI0UP1Zw0aNCArKyvfRTpFRERE/qxEjWFKSEggLS2N6tWr4+jomGu/vb091apVIzY2luTk5HxnxM2e1t/V1TXP/dnbr127VqC4stdcKoqVvEVE5P6U/Tvhz+vySelVogqm7MUonZ2d823j5OQEYLFgyj5Pdtv8zpGSklKguK5evQrAsGHDCtReRETKjqtXr+Lh4WHrMKSIlaiCqSBzIxVkJZfs8xgMBovnKOiqMA899BDffPMNrq6ulCtXrkDHiIhI6ZaZmcnVq1e1Fl4ZUaIKpgoVKgCQmpqab5vsfZZ6obLPc+vWLYvnyG5njZOTE61atSpQWxERKTvUs1R2lKhB3xUrVqRChQpcv36djIyMXPszMjK4fv065cuXp3Llyvme58EHHwTyH6OU/YgtvzFOIiIiIn9Wogomg8FAo0aNyMzM5Pz587n2h4eHk5WVle/bb9kaN24M/PdtuT8zmUycO3eOcuXK0bBhw0KJW0REREq3ElUwAea14nbt2pVrX/a2zp07F+gcu3fvzrXvyJEjxMXF0bJly3wHjYuIiIj8WYkrmPr370/58uX56quvOHnypHn7iRMnWLp0KU5OTgwdOtS8PSIigrCwMBITE83b2rRpQ+PGjfn1119Zt26deXtcXBz//Oc/ARg5cmQx3I2IiIiUBgZTQV8VK0bffPMN06ZNw8HBgUcffRSTycSBAwfIyMhg1qxZOZY76dq1K5GRkcycOTPHOlKBgYE8//zzpKSk0KxZMx588EEOHjxIQkICgwYN4qOPPrLFrYmIiMh9qES9JZdt2LBhuLm5sXTpUg4fPoyjoyMtWrTg1VdfpV27dgU6x8MPP8z69ev5/PPPOXDgAGfOnMHDw4O33nqLgQMHFvEdiIiISGlSInuYREREREqSEjeGSURERKSkUcEkIiIiYkWJHMMkRefcuXPExsbSunVrW4dS4ly5coXQ0FAyMjLw9fWlZs2atg6pxLh27RpBQUHcunWLWrVq4evri7192frnY9OmTTRq1EjLYBRAeno6CQkJVKtWzepyUvHx8aSkpODm5lZM0YncHY1hKmMmTpzItm3bCAkJsXUoNvH777+zd+9e7O3t6d27N0ajkaysLD766CPWr1+fY9Xx3r17889//rNMzNf19ttv06JFC5599tkc269fv86HH37Irl27cqy9WLVqVV566SVGjhyZ75qNpY23tzcODg6QaLiwAAAc2ElEQVRMmjRJC3HnIy4ujunTp7Nr1y7S0tIoX748Xbt25fXXX6dBgwZ5HjNx4kS2b99OcHBwMUcrcmfK1lfEUuzy5csFanfz5k0AoqKicvwCLAvf7t5//302bNhgvu9ly5Yxd+5cQkNDWbNmDc7OzrRp0wZHR0eOHTvG9u3buXjxIqtWrcLR0dHG0RetLVu2AOQomBITExk6dCjnz5/HyckJX19fHnjgAS5dukRISAhz5swhKCiIf//737YKu9ilp6fz8ccf88svvzB16lTq1Klj65BKjBs3bjBkyBAiIiIwGAxUr16d2NhYvv/+e/bs2cOMGTPo1atXnsfqe7vcD1QwlRJdu3a9o2/6Xbt2Nf+3wWAo9d/uNm/ezPr163Fzc2PYsGEkJSWxevVqPvjgA+zs7GjQoAFfffUVdevWBW4XCxMnTsTf359Vq1bxwgsv2PgOit/ChQsJDw+nffv2fPLJJ+Y1GgFOnz7N5MmT+f7772nfvj0DBgywYaTFp0OHDmRkZLB371569+7NiBEjGDlyJFWrVrV1aDa3aNEiLly4QI8ePZg+fTqVK1cmKiqKuXPnsmXLFiZMmMDNmzdzzJcncj/RoO9SwsvLy/wtzdXVlXr16uX5x9nZGSDHtuwioTRbu3YtLi4ufPvtt7z44ouMHz+eJUuWcP36deLi4njvvfdy5KFSpUrMmTOHypUrm3tfypqffvqJypUr8+mnn+YoluD237evvvqKChUq5JhNv7SrUaMGy5cv54033sBgMLBkyRK6dOnCzJkziY6OtnV4NrV7924eeOAB888NQO3atZk9e7Z5hYX333+fn376yZZhitw1FUylxMaNG3nxxRcxGAw4OzvzySef8NNPP+X6061bN4Bc20u70NBQWrVqleMXf7NmzWjSpAkAzZs3z3VMpUqVaNasWZ4LQZcF165do2nTpvn2nlSvXp22bdty5syZYo7MtgwGA6+88go7duygV69e3Lp1ixUrVtCtWzdGjhzJ+vXriYuLs3WYxe7y5cs0bdoUJyenXPsGDx7M1KlTyczMZOLEiRw6dMgGEYrcGxVMpYSDgwMTJ05k5cqVmEwmnnvuOebMmUNaWpqtQysRsrKyyMjIyLXdaDQC/x3b9VdpaWllZlDzX9WpUwcHBweLbW7evFlmx5/UqlWLTz/9lG3btjFgwADs7e357bff+OCDD+jQoQM9e/bk7bffZv78+axfv97W4Ra58uXLk5SUlO/+QYMGMXbsWFJTUxkzZgxhYWHFGJ3IvVPBVMq0bNmSzZs3M2DAAJYtW8aAAQNK/fikgmjcuDGHDh3i4sWLObbPnDmT48ePU6VKlVzHnD17lkOHDuHj41NcYdrUpUuXOHbsGLdu3QLg73//OwcPHiQ+Pj7P9ufOnePQoUM0atSoOMMscRo2bMjHH39MQEAAM2bMoHPnzjg6OnL+/Hm2bNnCF198wQcffGDrMIuc0WgkMDCQ8PDwfNuMHTuWp59+moSEBF588UUuXLhQjBGK3BsVTKWQs7Mz06ZNY/HixVy/fp1BgwYxf/78HK/MlzXDhg0jNTWVZ599lpUrV+b4Juzo6JhjTqG4uDjWrFnD//zP/5CZmcmQIUNsEXKxO3LkCEOGDKFly5b07duXU6dOkZKSwvjx40lJSTG3i4uLY+PGjQwfPpyMjAytzfj/qlSpQv/+/Vm0aBGHDh1iw4YNTJ06lVGjRvH000/bOrwiN3jwYFJTU3nhhRfYtGlTvo+yP/74Yzp27Eh0dDTPPPMMQUFBxRuoyF3SPEylXEJCAlOnTuWHH36gSZMmODo6cvz48TI5D9O8efNYtGgRBoOBH374gfr16+fZ7s0332THjh2YTCYGDRrEtGnTijdQGzh06BAhISEEBwcTEhLC2bNnzY8wDQYDO3bswMPDA7jdS7B7925MJhM9e/Zk3rx5tgy92Hh7e9OvXz9mz55t61BKrA8//JC1a9diMBho1KgRW7duzbNdWloaEyZMYOfOncDtv2Nl8d8kub9oWoFSrkqVKsydO5du3brx0UcfkZCQUGbH5Lzxxht06dKFrVu34u7unm87Hx8fbty4waBBg3j88ceLMULbadWqFa1atTJ/Tk9P58yZM+YC6s9vENaqVQsfHx+effbZMtW75ObmRvXq1W0dRon2z3/+k+7du7Np0yZcXFzybefo6Mj8+fNZs2YNCxcu5Nq1a8UYpcjdUQ9TGRITE8OiRYu4efMmM2fOtHU4IiKYTCbCw8Px9PS0dSgiFqlgEhEREbFCg75FRERErFDBJCIiImKFBn2LiMg9u3Llyj0dX7NmzUKKRKRoaAyTiIjcM29v77t+A7csLAAu9z/1MImIyD0bM2YMixcvJiMjAxcXlzxnzxe5n6mHqYwwmUzEx8djMBjyXUy1LFN+LFN+rFOOYNeuXbzxxhtUrlwZPz8/atWqZeuQRAqNBn2Xcvv372fUqFG0aNGC9u3bm+dfGjduHLNmzTKvG1ZWKT+WKT/WKUf/1b17dyZPnkxcXBzvvfeercMRKVR6JFeKzZs3j8WLF2MymbC3t8dkMplXlg8JCWHnzp0cO3aM5cuXU758eRtHW/yUH8uUH+uUo9yGDRuGv78/e/fuxd/fn86dO9s6JJFCoR6mUmrnzp0sWrSIevXqsXjxYg4fPpxj/4IFC/Dx8eHYsWOsWbPGRlHajvJjmfJjnXKUv0mTJtGqVSsOHjxo61BECo0KplJqxYoVODk5sXz5cjp37pzr263RaGTZsmVUqFCBLVu22ChK21F+LFN+rFOO8ufp6cnKlSuZOHGirUMRKTQqmEqp4OBgWrdujZubW75tqlWrRqtWrbh48WIxRlYyKD+WKT/WKUciZYsKplIqKyurQHOiZGRkkJGRUQwRlSzKj2XKj3XK0Z2Lj4/n8uXLtg5D5K6oYCqlPD09OX78ODdu3Mi3TXx8PIGBgWVylXDlxzLlxzrl6M5Nnz6d7t272zoMkbuigqmU6t+/PwkJCbz11lvExcXl2n/9+nUmTpxIUlIS/fr1s0GEtqX8WKb8WKcc3R1N/Sf3K01cWUplZmYyevRo9u3bh5OTEw0bNiQoKIh69epRr149Tpw4QWJiIi1btmT58uU4ODjYOuRipfxYpvxYpxzduYkTJ7Jt2zZCQkJsHYrIHVPBVIplZGSwYMECvvnmGxITE3Psc3Jy4plnnuEf//gHTk5ONorQtpQfy5Qf65SjO6OCSe5nKpjKgLS0NIKDg4mKiiIrKwtXV1eaNm2Ks7OzrUMrEZQfy5Qf65SjglHBJPczFUwiIlIsZsyYwa5du/j5559tHYrIHVPBVEpt2rSpQO0cHByoWLEi7u7uNGjQoIijKjmUH8uUH+uUI5GyRQVTKeXt7V2gOWL+rFGjRsyYMYOmTZsWUVQlh/JjmfJjnXJ056Kiojh16hTp6el4e3vj7u5u65BECkwFUym1efNmVq9ezfHjx2nQoAE9evSgTp06mEwmoqKi+OWXXwgNDcXd3Z2uXbty4cIFAgICcHFxwc/Pj7p169r6FoqU8mOZ8mOdcpRbWloaq1ev5o8//qBq1aoMHToUX19f0tLS+OCDD9i6dStZWVnm9p06dWLGjBnUqFHDhlGLFJBJSqVt27aZjEajafr06abMzMw823z++ecmb29v086dO00mk8nk7+9vMhqNpqlTpxZnqDah/Fim/FinHOV069Yt0+DBg03e3t4mo9FoMhqNpkceecR04sQJ04QJE0xGo9HUtm1b0+jRo02vvfaaqUOHDiaj0Wjq2bOnKTEx0dbhi1ilHqZSqn///iQnJ7Njxw6Ljw369OmDs7MzGzZsMB+XmJjIzp07iytUm1B+LFN+rFOOclqwYAELFiygadOmvPjii8TFxfHZZ5/h6urKuXPn6NSpE7Nnz6Zy5coApKSk8O6777Jjxw5eeeUVxo8fb+M7ELFMM32XUmFhYfj4+FgdY9G4cWPOnDlj/lyvXj1iYmKKOjybU34sU36sU45y+v7776lWrRr/+7//S8+ePRk6dCgff/wxZ8+epUqVKvzrX/8yF0sAFSpUYObMmdSoUYMdO3bYMHKRglHBVEpVr16ds2fPWm0XFhaGi4uL+fPNmzdzfC6tlB/LlB/rlKOcLl26RPPmzalYsaJ5W4cOHQB4+OGHc2zP5uTkxEMPPURkZGSxxSlyt1QwlVLt27cnLCyM+fPn59vmyy+/5MyZM7Rr1w6ApKQkjhw5goeHR3GFaTPKj2XKj3XKUU4ODg4kJSXl2JY9+3lycnK+x928eRNHR8cijU2kMNjbOgApGmPGjOGXX35h4cKF/PLLL3Tt2hU3NzeysrKIiopiz549BAcHU6VKFd544w2Sk5N55plnSE5O5qmnnrJ1+EVO+bFM+bFOOcrJ19eXw4cPc/z4cZo1awbAsmXLAAgMDOTMmTM0btw4xzFhYWEcPnyYRx55pNjjFblTGvRdip07d47333+fw4cPA5jHWmT/L/f19WXmzJl4eXlx+vRp+vXrR5cuXZg/fz729qW/llZ+LFN+rFOO/svf35/Ro0fj7OxMx44duXLlCoGBgVSuXJlu3bqxf/9+pkyZQvv27SlXrhz+/v7MmjWL6OhoPvnkE5588klb34KIRSqYyoCQkBD2799PVFQU6enp1KpVi7Zt29KiRQuuXLnC+vXrGTFiBDExMXh6eto63GKn/Fim/FinHN32zTffMHv2bFJTUwFwdnZm3rx5eHt7M2DAAGJjY3O0N5lM9O3blzlz5tgiXJE7ooKpjAoICGDt2rX4+/uTmZmpxTD/QvmxTPmxrqzmKC4ujsOHD2MwGGjVqhVVq1YFICIigrlz5/LHH39w48YNPD09GTx4MEOGDLFxxCIFU7r6hMWiq1evsnHjRtatW0dUVJT5sUFpHIB6N5Qfy5Qf65Sj228P9ujRI9d2d3d35s6da4OIRAqHCqYy4Ndff2Xt2rX8/PPPZGZmYjKZqFKlCr179+bJJ58s8wMulR/LlB/rlCOR0k8FUykVGxvLxo0bWb9+PZcuXTJ/0zUYDMyfP5/HHnsMBwcHG0dpO8qPZcqPdcqRSNmiMUylzG+//cbatWvZvXs3GRkZmEwmfHx86N+/P5s2bSI4OLjMjKXIi/JjmfJjnXIkUjaph6mUWLZsGevWrSMiIsL8OOCJJ55gwIABNGnSBICffvrJxlHajvJjmfJjnXIkUrapYCol5syZg5OTE3379qVnz5506tSp1M3zci+UH8uUH+uUI5GyTT/tpUhqairHjx+ncuXKODo60r59e+zstPpNNuXHMuXHOuVIpOzST3opsXXrVp5//nmSkpJYtWoVL730Ep06dWL27NkFWiC0tFN+LFN+rFOO7o3JZOL69evEx8fbOhSRu6JB36VMZmYme/bswc/Pj4CAADIyMjAYDPj6+nL16lViYmLK9IBU5ccy5cc65ejO7N+/n6+//prDhw9z69Yt+vXrx6xZsxg3bhx16tRh/PjxODk52TpMEavKTZ06daqtg5DCY2dnh6enJ3369OHZZ5/F1dXV/A94cnIyBoOBo0ePkpmZSd26dSlfvrytQy5Wyo9lyo91ylHBzZs3jw8++ICIiAgAsrKyMBqN9OjRg08//ZSAgAAOHDhA3759NR5MSjz1MJURQUFB+Pn5sW3bNhISEjAYDNjb29OxY0f69OlDnz59bB2iTSk/lik/1ilHOe3cuZPXX38dd3d33n33XR599FGaNWtGv379mD17NqGhoUyePJmQkBDeeecdRowYYeuQRSxSwVTGpKens2vXLvz8/Ni/fz+ZmZkYDAY9Qvh/yo9lyo91ytFtzz33HCdOnOD777/Hzc0NAG9vb3PBBHD9+nW6d++Oh4cHfn5+tgxXxCr1gZYxDg4O9OrVi169enH16lW+++47Nm3aZOuwSgzlxzLlxzrl6Lbg4GBat25tLpbyUq1aNVq1asWRI0eKMTKRu6MeJhERKXTNmzendevWLFmyxLztrz1MAC+++CJHjhzh6NGjtghTpMA0rYCIiBQ6T09Pjh8/zo0bN/JtEx8fT2BgIJ6ensUYmcjdUcEkIiKFrn///iQkJPDWW28RFxeXa//169eZOHEiSUlJ9OvXzwYRitwZPZITEZFCl5mZyejRo9m3bx9OTk40bNiQoKAg6tWrR7169Thx4gSJiYm0bNmS5cuX4+DgYOuQRSxSwSQiIkUiIyODBQsW8M0335CYmJhjn5OTE8888wz/+Mc/NHGl3BdUMImISJFKS0sjODiYqKgosrKycHV1pWnTpjg7O9s6NJECU8EkIiIiYoXmYRIRkUJX0LmnHBwcqFixIu7u7jRo0KCIoxK5e+phEhGRQuft7Y3BYLijYxo1asSMGTNo2rRpEUUlcvdUMImISKHbvHkzq1ev5vjx4zRo0IAePXpQp04dTCYTUVFR/PLLL4SGhuLu7k7Xrl25cOECAQEBuLi44OfnR926dW19CyI56JGciIgUOnt7e44fP87w4cOZNGkSdnY5p/178803mT9/PgsXLqRVq1ZMmjSJgIAAXn75ZZYtW8aHH35oo8hF8qYeJhERKXT9+/cnOTmZHTt2WHw016dPH5ydndmwYYP5uMTERHbu3FlcoYoUiGb6FhGRQhcWFoaPj4/VcUyNGzfmzJkz5s/16tUjJiamqMMTuWMqmEREpNBVr16ds2fPWm0XFhaGi4uL+fPNmzdzfBYpKVQwiYhIoWvfvj1hYWHMnz8/3zZffvklZ86coV27dgAkJSVx5MgRPDw8iitMkQLTGCYRESl0ly9fZuDAgcTFxdGkSRO6du2Km5sbWVlZREVFsWfPHoKDg6lcuTIbNmygevXqDBgwgAsXLjB16lQGDx5s61sQyUEFk4iIFIlz587x/vvvc/jwYQDzeKbsXzu+vr7MnDkTLy8vTp8+Tb9+/ejSpQvz58/H3l4vcUvJooJJRESKVEhICPv37ycqKor09HRq1apF27ZtadGiBVeuXGH9+vWMGDGCmJgYPD09bR2uSJ5UMImISLELCAhg7dq1+Pv7k5mZSUhIiK1DErFIfZ4iIlIsrl69ysaNG1m3bh1RUVHmR3Ma5C33AxVMIiJSpH799VfWrl3Lzz//TGZmJiaTiSpVqtC7d2+efPJJHnnkEVuHKGKVCiYRESl0sbGxbNy4kfXr13Pp0iVzb5LBYGD+/Pk89thjODg42DhKkYLTGCYRESk0v/32G2vXrmX37t1kZGRgMpnw8fGhf//+bNq0ieDgYI1XkvuSephEROSeLVu2jHXr1hEREWF+5PbEE08wYMAAmjRpAsBPP/1k4yhF7p4KJhERuWdz5szBycmJvn370rNnTzp16qS5lKRU0d9mEREpFKmpqRw/fpzKlSvj6OhI+/btsbPTClxSOuhvsoiI3LOtW7fy/PPPk5SUxKpVq3jppZfo1KkTs2fPLtAivCIlnQZ9i4hIocnMzGTPnj34+fkREBBARkYGBoMBX19frl69SkxMjAZ9y31JBZOIiBSJuLg4tmzZgp+fH6dPnwZuTyvQvn17+vTpQ48ePahUqZKNoxQpGBVMIiJS5IKCgvDz82Pbtm0kJCRgMBiwt7enY8eO9OnThz59+tg6RBGLVDCJiEixSU9PZ9euXfj5+bF//34yMzMxGAx6TCclngomERGxiatXr/Ldd9+xadMmvv/+e1uHI2KRCiYRERERKzStgIiIiIgVKphERERErFDBJCIiImKFCiaRMmry5MkYjUaMRiOBgYG2DkdEpERTwSRSBt28eZMff/zR/HnDhg02jEZEpORTwSRSBu3cuZPk5GT+9re/AbBt2zZSUlJsHJWISMmlgkmkDNq8eTMAPXv2xMfHh+TkZH744QcbRyUiUnKpYBIpY2JiYvjtt98A6NChAz169ABg/fr1tgxLRKREU8EkUsZs3bqVzMxMvL29cXNzo2fPngAcPXqUsLCwfI/77bffGDVqFO3bt6d58+YMGTKE3bt3c+DAAYxGI88991yuY9LS0li+fDkDBgygefPmPPLIIzz99NMsW7aM1NTUIrtHEZHCpoJJpIzJfhzXq1cvABo2bIi3tzeQfy/T119/zYgRI9i7dy/lypWjQYMGBAUF8dprr/Gf//wnz2Pi4+MZNmwYM2fOJDg4GFdXV9zd3QkNDWX27NkMGTKE69evF8EdiogUPhVMImVISEgIoaGhADlWh8/+702bNpGWlpbjmMDAQGbPno2dnR1Tp04lICAAPz8//P396dy5M7t3787zWpMmTSIwMJDmzZvz448/8tNPP7FlyxZ2795Nq1atCAoK4t133y2iOxURKVwqmETKkE2bNgHQrFkz6tWrZ97ep08fDAYD169fz1UAffnll5hMJoYPH86QIUMwGAwAVKtWjc8++ww3N7dc1zlx4gR79uyhatWqLFy4EHd3d/O+2rVr8/nnn+Pi4sLu3bs5depUUdyqiEihUsEkUkZkZmayfft2AHr37p1jX506dXjkkUeAnHMypaamsn//fgAGDRqU65zOzs489dRTubZnF13t27enevXqufbXqFGDRx99FICAgIC7uR0RkWJlb+sARKR47Nu3j6tXr2JnZ2cev/RnTzzxBEePHmX//v1ERkZSp04dIiMjuXXrFg4ODnh6euZ53iZNmuTalj14/NChQwwZMiTP4y5dugRAeHj43d6SiEixUcEkUkZkD/bOysqiU6dO+bbLyspi48aNjBs3jvj4eOB2T1L2o7i/cnFxybUtKSkJuD2FQUxMjMW4EhMTCxS/iIgtqWASKQOSkpLMj8mqV6+Og4NDvu2Sk5Px8/Nj7NixVKhQAbi9lEpWVhZ2drmf4icnJ+fa5uzsDMA777zDCy+8UFi3ISJiMyqYRMqAHTt2cOvWLRwdHdmxYwdVqlTJs92uXbsYM2YMUVFR7N27l7Zt2+Lg4EB6ejrh4eE0bNgw1zGnT5/Otc3DwwPA4rxOwcHBGAwG6tWrR8WKFe/yzkREiocGfYuUAdmP47p06ZJvsQTw2GOP4erqCtwe/O3k5ES7du0A2LhxY6726enpbNmyJc/zAPz000/ExcXl2p+YmMiIESN46qmntCSLiNwXVDCJlHKRkZH88ccfADz99NMW29rb25vb7Nmzh9jYWF599VUMBgP/+c9/crxBl5SUxDvvvMP58+dznadt27a0bt2aGzduMHr0aC5cuGDed+XKFV577TUSEhJwdXWlb9++hXCXIiJFy2AymUy2DkJEis7ChQv57LPPqFGjBgEBAdjbW34SHxERwd///ndMJhMTJ05k1KhRLF68mE8//RSAmjVr4urqyrlz57h58yZNmjQhKCiIdu3asXz5cvN5rly5wosvvsiZM2cwGAw0atQIOzs7zp07R3p6OhUrVmTVqlX4+PgU5e2LiBQK9TCJlHLZj8yeeOIJq8USgLu7O23atAH+OyfT6NGj+fLLL2nTpg3JycmEhYXRpEkTli5dyuOPPw6Ak5NTjvPUrFmT9evXM3HiRHx9fYmMjOTcuXM8+OCDDB48mM2bN6tYEpH7hnqYROSezJkzh6VLlzJw4EA+/vhjW4cjIlIk1MMkIhaNGDGCgQMHEhgYmOf+ffv2Aai3SERKNRVMImKRp6cngYGBzJkzh9jYWPP2lJQUPv74Y06dOkXVqlXznD1cRKS00CM5EbHoypUrDB48mKioKBwcHKhfvz7lypUjIiKClJQUKlSowLx58+jcubOtQxURKTIqmETEqhs3brBmzRp+/PFHIiMjSU1NpWbNmnTo0IHhw4dTv359W4coIlKkVDCJiIiIWKExTCIiIiJWqGASERERsUIFk4iIiIgVKphERERErFDBJCIiImLF/wEhvYCbN4+EOQAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# set style\n", "sns.set_style('white')\n", "sns.set_context('notebook',font_scale=2)\n", "\n", "# set figure size\n", "plt.subplots(figsize=(7,5))\n", "\n", "g = sns.boxplot(x='AgeGroup', \n", " y = 'ToM Booklet-Matched',\n", " hue = 'Gender',\n", " data = pheno[pheno.AgeGroup!='Adult'],\n", " palette = 'viridis')\n", "\n", "# Change X axis\n", "new_xtics = ['Age 4','Age 3','Age 5', 'Age 7', 'Age 8-12']\n", "g.set_xticklabels(new_xtics, rotation=90)\n", "g.set_xlabel('Age')\n", "\n", "# Change Y axis\n", "g.set_ylabel('Theory of Mind')\n", "g.set_yticks([0,.2,.4,.6,.8,1,1.2])\n", "g.set_ylim(0,1.2)\n", "\n", "# Title\n", "g.set_title('Age vs Theory of Mind')\n", "\n", "# Add some text\n", "g.text(2.5,0.2,'F = large #')\n", "g.text(2.5,0.05,'p = small #')\n", "\n", "# Add significance bars and asterisks\n", "plt.plot([0,0, 4, 4], \n", " [1.1, 1.1, 1.1, 1.1], \n", " linewidth=2, color='k')\n", "plt.text(2,1.08,'*')\n", "\n", "# Move figure legend outside of plot\n", "\n", "plt.legend(bbox_to_anchor=(1.05, 1), loc=2, borderaxespad=0.)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "That's all for now. There's so much more to visualization, but this should at least get you started." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### Recommended reading:\n", "\n", "multidimensional plotting with seaborn: https://jovianlin.io/data-visualization-seaborn-part-3/\n", "\n", "Great resource for complicated plots, creative ideas, and data!: https://python-graph-gallery.com/\n", "\n", "A few don'ts of plotting: https://www.data-to-viz.com/caveats.html" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "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": "3.6.8" } }, "nbformat": 4, "nbformat_minor": 4 }