{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "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": 20, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ " % Total % Received % Xferd Average Speed Time Time Time Current\n", " Dload Upload Total Spent Left Speed\n", "\r", " 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:-- 0\r", "100 16041 0 16041 0 0 66769 0 --:--:-- --:--:-- --:--:-- 66837\n" ] } ], "source": [ "%%bash\n", "curl https://openneuro.org/crn/datasets/ds000228/snapshots/1.0.0/files/participants.tsv -o /data/participants.tsv" ] }, { "cell_type": "code", "execution_count": 21, "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": 21, "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": 22, "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": 22, "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": 23, "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": 24, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 24, "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": 25, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages/seaborn/distributions.py:2551: 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", "/opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages/seaborn/distributions.py:2055: 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": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "
" ] }, "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": 26, "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": 27, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 27, "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": 28, "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": 29, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 29, "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": 30, "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": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Value counts of AgeGroup\n", "pheno['AgeGroup'].value_counts()" ] }, { "cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/miniconda-latest/envs/neuro/lib/python3.7/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": 31, "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": 32, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 32, "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": 33, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 33, "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": 34, "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": 35, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 35, "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": [ "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": 36, "metadata": {}, "outputs": [ { "data": { "image/png": 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\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": 37, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 37, "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": 38, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 0, 'Participant Age')" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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XZtR+5OSY6z+ACWdvhg3hZnq6w1zTFWZFc96BKVBeTZ9CsfTlLi+X+ZRfUg1qahqqBTYjMIzpmemDqpya/w/tHeAfdu4jlnAYnzRTWNkaYnu3m+l71vK8IexAZW0bC8XSF8plKLS83HyL+ZRfUg7FZgQFFYGIXFzsoHOVBbyYFMFCG3UYs0OlD6pMyeeR8aSbvVtkkJhIOew+OMhPevt5eN+xnHA/j0BDwMuZrQ3c8UcXF3yo+70eGgNemoK+imr63HTX40SGYzkx8mPxJAPD47S3BEteHm4Jcc8tl8/4vOUeZ7ap1DT0d+n3ELAJeBrXvHcB8HPgymoKaeSS/c+8tMFPZDjGx+9/lk+BKYM6pZKyBJUMBCYnETUG3IiiOx86kHf/eNLt9zsyTclnR5Vnjp5iZ2+EXfsGGJ7k9G0O+mgJ+WgKeEFgOJaYogQCPg9NAR+NQS9B38wKuh0+McbShtz2kZlchrV5YuwLLS83lr/Qeeciv6RaFFQEqnoNgIjcC9yiqr9Ofz4f+PDsiLd4Kfef2ZjflKvYZzIQKOVBlan5M1xCw5eDx0bZmS7vnO309Qi8bm0bA0PjpNShKWuEHE2kJnIHMgXdGoPVbeCypq1xysg8mkjRFHBnQaUuLzeWv9B55yK/pFqUcle6MkoAQFWfAS6qmUQGML+yWo2ZU0lZgkpLIBRLNkqkHAZH47w0OEZkKFZQCQwMj/OvTxzmln95knd/fQ/f2n14Qgmc19HCn209m3+95XI+e8MF/NnWs3Ey8fvp3IGUKrdsWc9Zy5s4c2kDSxr9Ve/iVSiW/uYr15e1vNxY/vmUX1ItSoka6hWRu4Fv4Oaw/CHQW1OpjAU56ljMlGtOmIn54dYtnXz8/mcZiycnfATjSYe3XbKaw4OF9x+JJXlo/wA7eiM8ffhkjt3/jCUherrDbO/uYO2y3N/g5s5l/Lls4Nt7jvDqUJQ1bY3cdvXZNZ+5bu0K8ynIG0tfKK+iGvkWxc5br0wbNSQiIeA9wJb0ooeAr6hqrPBetWOxOIvrNTLByE+5DsaZOiR39UX4yoMvcHhwjI7WEG/flL8cczzp8PODg+zs7eexA8dJZNV5WNLgZ+t5bk/fjWe0TrH3SzrMszndxGWhdu9aKMwoj0BVYyJyB/Cfqrq36tIZeVmIo47FTL5R+nRlCcrZPpvR8SRdZ7Tyt7+bv/y8o8qvj5xiR2+EB/cNMJLVFjLo8/D6s5dz7cYONp3VljeBqyEd6dMc8C2ovr2LmVJmBG8GPgsEVHW9iFwEfEpV3zwL8k1hscwIjPlDtZOQyilLUGj7yTK9+8p1XHLWsqLN3g8MjLCjN8IDfREiw7lO30vOamN7dwdXnrM8b8nikN99+DcFLLu3XqkojyB7Z2AbsEtVX5de9itVvaDqkpaAKQJjNpmPJrqMTD6PW+9/LJ4knjrdgCWbyFCMB/oi7OiLcGBgNGfdeStb3Ezf88IsawpMOU/Q76U54KMpaA//hcBMS0wkVfWU2f9qz3xMIPvCjn3c/chBRuNu+N3NV67nAz3nzqlMk5l83a7oXMZjBwZzriNQ05j8m+58lMcOnpj47PfApnXLa3IPv7zrBQTF5/WScpSgz4ujKe594jCbO90uYA/uG2BnXz9PHz6V4/Q9c2mInq4OtnWHpzh9obSHfzVagBrzi1JmBP8E7AQ+Bvwe8AHAr6q31V68qSzUGcF8HHl+Ycc+bn/geTzp6pCOuq8Pbjtn3iiDydft+Og4keE47c0BVjQHiSZSnIomENw2iOVe2ys/8wBLG/w5jlBV5VQ0wcMf3QZMVQIZgl7oWNJYlXuYSDkMx9ykr9+/81FaQz4kqwtBSh2Oj8Q5f9VSfn4w1+m7tMHPNemG7l0rW6Y4dcsZ+VejBagxNxSbEZQy33s/8BpgHLgHGAL+vGrSGcD8aouY4e5HDuIRtw6MRzzpd3f5fGHydRuKJvEIDMeSE9dxZDzJcKyyVo6lNADJpwQAxlPM6B6qKsOxBK+cinJ4cGyi1eMZrQ3EEs5EDPurQzEOHBvjZDTJI88fI5FSQj4P27vC/O3vns+3b72c9287h+6syJ+g38vypiBrljWyKh3nX4r5pxotQI35RylRQ2PAX6VfRo2Yj2nro/EUvknPBo+4y+cLk69bPOXgyWqfCG4Btckz35nE5JeTPFTJPYwlUgzHkoyOJ3HyzNivPncFdz9ykFjCbXCSwSOw6aw2ejZ28IazV9AQyE1IDPg8NAd9NAV9FSd3lfI7nY+/ZaM40yoCETkXt6TEuuztVXVb7cRafMzHBLJMSn52hKCj7vL5wuTrFvB6iKecifaJ4LYERHPNIaVe25mG8ZZ6nvFkipFYktHxVN6on/6M07c3wsFjuU7fxoCX7V1h/uQN62hrzHX6+r2nH/6ByVq9Akr5nc7H37JRnFKcxd8B7gDuBubPUHCBMdORZy24+cr13P7A8yQdJ8dHcPOV6+dMpslMvm6tDT4iw3FaQj5U3XIHzUEfAhVf261d4aIP/ivWtxX0ERQ7j+MoI3HXbDWep6/sUDQxken7qyOnctatWtqQzvQNT3nA+jwemoKVV/UsRim/0/n4WzaKU1L4qKpeMkvyTEu9OovLibSYTwlk9RQ1lLlumaih7OsIU0f1mWXViGwpJ2ooGk8xPJ5gbDw1xfQTTzo8duA4O3r7+fmBQZLO6fVtjX6uOc99+E92+tby4T+ZarQANWafSvsRZAKSPwBEgO/hOowBUNXBKstZEvWoCCyKYv4x2/ckU+p5dDw5pdFLylGePnKSHc9FeHj/QI4PJuT3cOU5K+jp7uCSs9pcM1ea2Xz4G/VPpXkET+IWmcv88j6StU4Bm+eViJWUnn/Mxj3JdPkaiU81/agqLwyMsiNd3vn4SHxinUfg0nXL6OkO8/pzVuRUofWI0Bj00hL0T3EGG0alFOtHMH8MwXXObEdRFDND5VsH8Okf9HLwuCtP54omPnpd14JWUuXek+lMe7v6Inz6B70cSDty1y5r5OarOtm8PjfT99WhGA+kG7ofOp57ro1ntNDT3cHW89pZmuX0zRR3awr6eOLAce56+KAlahlVpZSoofcC31TVk+nPbcBNqvrlGsu2YJjNKIpiDU2AKes+ct/TxBIpoglnIjpof2SEj9z3NJ+94cIF+5Ap555M1yRmV1+Ev/jOLzk5lpi4hgePjfKZH/bx0Td20XVGCw/uc52+vz6a6/Rd3dbAtd1upu+qpQ056zLF3ZoCPrweYVdfhE98/znrWmdUnVKihv5UVf8x80FVT4jInwKmCEpkNqMoipk8gCnrjp6IEk85+D2eiUqSospwbGGbrsq5J4Wu6R0PvsCFa5Zy+879DI8n8YhMXEN1HIaiCf7XD3oZi6dynL7LmgJcc147Pd0dnNvRnOP0Dfg8tAT9ebN8zcRo1IpSFIFHRETTXmUR8QJTK1QZBZnNktLFTB4KU9YlHQdHIbvqgAgkU86CTgAq555kX1NVxVHweYRDx0c5MRbn5VNRHEcRwHEgld4GYCjd17fB7+WqDSvY3h3m4rVTnb7NIbfEQ7E+vpaoZdSKUhTBj4Fvp3sSKHAb8MOaSrUAmS4WvVpMZ/KYvM7n8eCog2YpA1V3+UJPACr1nqxe2kD/UIyg3+uGe+rpnryqypKQn4Hh8fTDPzcKrzXk4/3bNvCGc5bnRPZ4Pe7IviVUesSPJWoZtaKUVMP/hlt07j3Ae9N/f6ToHsacUayfar51LSG3xnxKlZTjpF9KS8i3qBOAMtcnMhzjra9bRSzpMDqenEhSiyVThFuDvOtre9gXGSHL8oOkX0safPz367vZ3h0m5Hc7eDUHfXS0hli7rJH2lmBZYZ8LsVeuMT8oJaHsg6p6+3TLZot6zCOYbUppaDI5sWqxRQ0VIhpPMTKeZCyeJJX1dN99YJBvPP4iL50YI+XolHpL7c1BkimH4fEEIsKatkZuuaqTy85eToPf68b7V6GjlyVqGZUy08Y0T6nqxZOW/SLTpGa2MUVgVBN3ZJ1iNJ4kGk/lPPzBLQD32AvH2dEbYfehwZz1y5oCbOtynb4bwrlO36Df7eXbHPTl+AMMY66oKKFMRG4C3gGsF5H7s1a1AMerK6JhzB4Z887IeDJvmYeUo/zipRPs7Ivw8P5jjGWN/hsDaadvV5jXTXL6Zgq8NYcqr+5pGHNBMWfxo8ArwArg77KWDwO/qqVQhlELCpl9wFUO+/pH2NHbz0/3DjA4ejrT1+sRNq9bxrUbw1zRuZzgJKdvU3rkb2UejHqlWGbxi8CLwBWzJ051WSzt8nb1RfjMD/s4cGyUlOMQ8HppDHppbw6iqozEUxV///lcdC77/jYHXGfs8Hgy57vGskb++co7v3wyys50pu/hE9Gcda9d1cr27g6uPredJZPCNhsDPn7x0gm+/ughjpyMTmmRWUiean7nevhN15u8i5VSfASXA18EunHzB7zAqKq21l68qZTqI1gshd529UX4yH1Pc2IsgaqS6VAouDVrRIRVS0P4vJ6yv/98blWZfX+TKYejJ2MArFoawuMR4knlz7dv4JJ1bVP2PTWWYNe+CD95LsJzrwzlrDtreaNb3rmrg5VLQjnr/F4PLSF39P/I/mMFW2QGfZ4ceSq59tN953r4TdebvAudmTav/xJwI25fgk3AHwPnVE+82rBYsjDvfOgAw7EkXo9M9KkV3Gh2RyHgEY6NxOlsby77+2e3qgRXGSQdh7sfOTjniiD7/h4YGHHjoAUiw+OsaWskKSm++fOXJhRBLJHiZ88fZ2dfP08cOpFjGlreHGDbeWGu3djB2e1NOU5fj7imn8nx/pN/X9ktMocBrwgIFV/76b4zzP/fdL3Ju5gpRRGgqs+LiFdVU8A/i8ijpewnItcBt+POIu5W1U9PWr8E+AawNi3L51T1n8v5AoU4fGIMr8CBgZGJjlUrmgNzloVZqyny4RNjJB0Hn9fD5Mmd4iaJZdo2lpuFOp9bVR4+MUZryEcy5TCeTOFJP3gzJZ5Dfg+vnBrjiUOD7OiN8Mj+Yzm9h5sCXq7a0E5Pd5gL1yydEtnTEDgd9TO52Xvm/EVbZKqScmA86f4Gq/Hbq7fM4nqTdzFTiiIYE5EA8EsR+d+4DuSm6XZKl6L4R+Ba4AjwhIjcr6rPZW32XuA5Vf1tEWkH9orIN1U1nueQZdEc8PL8wCheEbwiJFPK0ZMxzmmfVvSqM13Rspmwpq2RY8PjE5nBOimxSZWJto3lZqHOx1aVsUSK0fEk7c1Bjo2M0+D34vd6SKZnQz6PEE2kODEWJ5Zw+Oi//XpiX59HuGz9MrZ3d3BF57Icp6+7Pm36KSHqp1iLzGTKYTytDwSq9turt8ziepN3MVNKjNsf4Y7o3weMAmuA3ythv83A86p6IP1gvxd4y6RtFGgRd8jVDAwCyRJlL8rEKE6yXtnLZ5HsKbJbUtiH3ysTheBmwq1bOmkJ+Uila93A6SYSHnHr3qxoDlSUhXrzletxNFOPyJmoSzSbrSpVlWg8xcDwOC8dH+Plk1FORRO8fdMako4bBtrW6CflKMmUknDg8IkoI+OnC729dtUS/mvPBu677Qr+5nfOZ+t57RNKIJPte8aSBtYub6StKVBS6OfkLN/WBh+OQkvIl1O4ye+Vqv326i2zuN7kXcxMOyNIRw8BRIH/p4xjrwIOZ30+Alw2aZsvAfcDL+PmJ7xdVaeEdojILcAtAGvXri3p5MPjSVYtDXFsJD4xUlvZGmRkvCp6pixqOUXe2hXmszdcOBE1JHmihkbjKcItobLNURk/wGxHDakqsYRTMNQTYHPnMt49vp5/fvQQAyNxMj+azLYdLUF++8Iz2dYVnuL0hXSVz5C/4oSvyUXr1i1v5qZL3aihgUODBL2CiJBSxe+Rqvz2ZrN4YTWoN3kXM8USyormCqjqBdMcO99/1+T/6DcCvwS2AWcDPxGRh1U1J5RDVe8C7gI3amia8wKnp6Wd7c0Ty8biScItUx8KtabWU+RaFrT7QM+5s+IYdhxlLJFibDzJWHxqkleGaCLFz54/xo7eCHsODebU+FnRHGB7V5ie7g46Jzl9obDjt1LyXfcPADfd9fiU+12t395sFS+sFvUm72Kl2IzAwX1wfwv4Pu6MoByO4JqRMqzGHfln8y7g0+kS18+LyEGgC9hd5rmmMJs9AOpJlvmEW7PHjfGPJlIUCmVOOcqeFwfZ2RvhkeePEUucnjQ2BbxsOdd1+l6weqrTFyDk906Efc6GadDut1FvFEsou0hEuoCbcJXBc+n3H6tqKXPcJ4ANIrIeOIobgvqOSdu8BGwHHhaRDuA8YOaGc+bXtLRWshRqO5kxEwGsX97Ix67vnjejsnjSYSzujvpjicLRR6pK36vD7OiNsGtvhBNjiYl1fq9w2frl9HSHubxzOYGs0KbdBwa594nDvDoUZXVbI7dt6aTnNStr+p0mM59+e4ZRCtMmlE1sKPJ23Cigz6jqZ0vc503A53GdzV9V1f8pIrcBqOodInIm8DXgDFxT0qdV9RvFjmlF51zyJeuciiZIpBxGx09H+jgKSxv9fG4O205mIn3G4qmJ8M5CHDkxls70jXD0ZO4k9ILVS+jp7uDqc1fQEvJP2Xf3gUG+8NP9BH0emgI+S2AyjCwqrj4qIqtwR/JvBU4A3wa+p6ojtRC0FEwRuOSzQ++PDDOecAj4PHhESDlKIuWguA1SvnDj62blgZjt7I3G85d2yGZwNM6uve7Dv+/V4Zx161c0sb0rzLbuMCtb89vYM8Xe3vONJxkYGc9rm7/nlstn/sUMo46ptProg7iRPN8G/gQ3tBMgICLLVHWw0L7zkYVW8yRfJFLK0YkksmwlADAWT9W00bmTDuXM2PwLOXszROMpHnn+GDt6+3nyxRM5Tt/25iDbu8Ns7w5zdpazP5t8jt8jJ6OWwGQYFVDMWXwWrrP4VtKhm5ATql43nq9aJnTNFfkikbweN3FO07H/GQQI+jwTuQvV+s4ZZ280nmIsXtjZmyGZctjz4gl29kb42fPHiCWznL5BL1ef69b2v2D1EjdTOA8NAS8tIT9N6aJu2VgCk2FURjFn8bpZlKOmLMSaJ/kiU5qDPoI+10eQ0zpRYEVzsCqj40TKYWzcHfkXc/ZmUFV6XxnmJ739PLh3gJPRXKfv5Z3L2d4d5vL1uU7fbLKLvfmKJHtZtI5hVEZJtYYyiMgnVfWTNZKlZizEmif5IlP+x29uBNyooYytPeAVVi5poLXBz1g8WdHoeDyZmnj4x5PF7f0ZXhocY2dvPzv7IrycrsQJ7uzkwjWu03fLhnaaQ/l/gpXE/Fu0jmFURlmKAHgz8MkayFFTFqrJoFCyztau8JSoonLT+8uJ9MkwOBrnp3sj7Hguwt7+XKdvZ3sTPd0dbO8K094SLHiMxoBb6yef6acULIHJMMqnXEVQl81XF6PJoNzRcSbSJ+PsnS7SJ8NYPMkjzx9nx3P9PPVSrtM33OI6fXu6O1i/onDBtVJNP4Zh1IZpFYGIvEFVf5b+eEmeZfOexWoyyHy/TLRUpshdZrnjKD9+9lX+z8MHOXpyjJWtDdx46Ro2dy4retxkyuGJQyfY0dvPoy8cZzzLXNQc9LH1vHa2d4d57arCTt9ql3uAhRcZZhizRSkdyp5S1YunWzZbWB5B6eRLOosnHf7y+i4uPmsZu/ZGuH3nfnweIeT3EEs4JB3lg9s2TFEGqsqzLw+xszfCrn0DnJrk9L3i7OX0dHWwef2ygk5fmLnpp5zvaslkhnGaSvMIrgBeD7SLyIeyVrXiZgrPObM5AqzmuWZL7ky0VIPfi6Nuvf04Dnc9dJC/f3sr9+4+jM/jrgcmHqD3PnF4QhG8dHyMHX397OyN8MqpXKfvRWuX0tMV5qpz22kOFp5cBnweWoJ+moLempl+FmJkmGHMFsVMQwHcHgE+3MSyDEPADbUUqhRmMzegmueaLbnHkykOHR+lJejLifQJ+T28OuSWbnhlKErrpKidkN/D0ZNjfOfJI+zs7Wdff24S+TntzfRsDHPNecWdvl6PW+e/OeQj6Kv9uGEhRoYZxmxRLI/gQeBBEfmaqr4oIk2qOjqLshVlNkeA1TxXLeWeHOnT0RLi+Oj4xIjf3cZhZWsDAGe0NkysdxxleDzJyWiC8aTDV3a9MLFPR2uQ7V1htk/j9IXiCV+1ZKFGhhnGbFBK1NCZIvID3NnBWhG5ELhVVf+stqIVZzZHgNU8V7XljsZTBRu43HjpGm5/YD/RRCrHB3DjpW518BsuWcXf/WQfx0bixBKpnGYRLSHX6dvT1cFrVrUWdPrC/Ij6WYyRYYZRLUpRBJ/HbSBzP4CqPi0iW2opVCnM5giwmuea6bFU3Zo+mYJu+bp3ZdjcuYwPsmGiLPPK1gbevmk1DQEv/7BjHw/uHWAodrqiuADnr1rC2zatZvP6ZUVbNtYi6mcmLNbIMMOoBiXlEajq4UnT/OlrC9SY2RwBVvNclRwr5ehEDf9oke5d+djcuYzNncs4dHyUnb0RPv/AfvqHxifWC3Dx2qVs7+7gqg0raCri9AXX8dva4Kc54MNTQYvHWmLJZIZRGaUogsMi8npARSSA242vt7ZiTc9sjgCrea5Sj5VMOYzGU4yli7pVwrGRcR7oc8s7Px/JdfpuCDfT0x3mmq4wK5oLO31h/o3+DcOoLqXkEawAbgd6cAeQPwY+qKrHay/eVBZyHkGp3buKMTKe5OH9x9jZ288vXjqZY/df2RpKZ/qGOWt5cacvQDDT4nEejv4LYUllhpGfivIIMqjqMeAPqi7VPGQuHiLZkT4/23+Me584zCtDUc4oMcsX3Iqguw8OsiNd3jk5yW/g8wghn4eOliCvPXNJXiWQ3eJx1VL3u//G+bPb4nGmLMRy44YxGxScEYjIF4GC0wVV/UCthCpGrWYEs5WZqqqMxVMTdfwzzt7dBwa5/YHSsnwBHFWeOXpqItN3OJbbRjq7cYQH8HhgaYMfv8875Zi7DwzyhQf2E/B5aAp4iSWduszKzde1zTqUGYZLpTOChWl/KUAt4/tLcfbe+8T0Wb4Ah46PsuM5t7xzttPXI9AU8OH3SjqUlImZgQKCMBpPsSLgmzimiNAU9PK9XxylIeDN+u6euszKtaQyw6iMYgllXwcQkXWqeih7nYhcWmO5Zp1qP0TKbeBSKMv31aEoA8Pj7OyLsLO3nxcGcnP6zu1oZnt3B9vOa+d99/yC1pCPoWMJPCIT07lM+8pEyiHk99A/FGV5c5CWoGv7P3pqYbR4tKQyw6iMUqKG/k1E3qyqRwFE5GrgS8BrayrZLFONh0gs4bZsHB1PllzDP0N2li+4s4jBsTiJlHLjXY/n2OjOWBKipzvM9q4O1i5vnHIMv9dDMqUImdkAqLqJX0lHWbeimSVZD/6F8gC1pDLDqIxS0kBvA/6viKwUkTfhRhC9qbZizT63bukkkXJNOK4df/pGLo6jjIwniQzHePH4KC+fjHJyLF62EgA3CziRcjg+GuflU1FeODbKibEEI+NJFGgN+XjLRWfyxZsu4hvv3sy73rA+RwlkjpF0lKaAF0XJpH64CkFZ0uAn5TDlO1Xy3ecjW7vCfOrNryHcEuJUNEG4JVR3fg7DmAumDR+FiUqkdwIx4DdVdaDWghWiluGjmaihUuL7o/EU0cT0Ddunw1Hl10dOsaM3ws6+fmKJ00rE7xWu2tBOT3eYTWe1lVS+IRP98+LxEZKOTtT7CXiFDR2tBSOhSvnuhmHUL8WcxcWihr5PbtTQRuAV4ASAqr65ynKWxFzkEcQS7oO/nJ6903Hw2Cg/ea6fB/oiRIZznb6XnNXG9u4OrjxneY65Zjq8HqEl5Kcl5CtaHsIwjMVHpVFDn6uRPPOGQnkDmXo+o+OuAijUtjEz+i417j8yFHMzffsiHJjk9D1vZQvXdofZel6YZU2Bsr5HyO+ltWH2K34ahrEwKNU01AFkIoV2q2qkplIVoVozgnzN3eNJ5S+uPZeLzmqb1uRTatz/SCzJg/sG2NnXz9OHT+VMsc5cGqKnq4Pt3WHWLCvPMSvi1vtvbZidev+GYdQ3M8osFpG3AZ8FduH6Hb8oIh9R1fuqKuUsc+dDB/B53CJqiZTi83hISIqvP/YiF65dOu3+xeL+L1q7lMcPHmdnb4THDxwnkTr9+F/a4Gfree1cu7GDrpUtZY/gfR4PrQ0+WkJ+vHVS9sEwjPlNKQbovwIuzcwCRKQd2AHUpSLIhHgePDZCS8hHKushnd29azomx/2rKo4qe/uH+L07HmV0/HTuQMjn4Q3nrKBnY5hL1pbm9J1MQ8BLa8hPo5l/DMOoMqUoAs8kU9BxSgs7rQkHBka58jMPlFwLKNven928ZeWkuH3I7d41HZmYfY/AUCzJcCyZU+PHI7DprDZ6NnbwhrNX0BAo33zjEaE55KM15C/aEN4wDGMmlKIIfigiPwLuSX9+O/CftROpOEnHmbagWCklHabr3lWM/qEYK1uDPPPyqSkF3ta0NfCWi1ZxTVc7bY3lOX0zZKp+tgR9Nvo3DKPmlFJ99CMi8rvAlbg+grtU9Xs1l6wAHhFEZEotoOySDuNJZ1pnb77uXcWifoZjCR7cN8CO3gi/OnIqZ53XI7Q3B/nDy9bypgvOqPh7NYfcmv/m/DUMYzYpNUj9Z0ACN69gd+3EKY+gz8OLx0c5cmKsovj+TPeuQsSTDo8dOM6O3n5+fmAwZ/Tf1ujnmvPC9GwMc15H+U7fDKFMzX8b/RuGMUfUXdSQ4mb3Onq6xHC1krzANSs9feQkO56L8PD+AUazuoOF/B6uPGcFPd0dXHJWW8VROzb6NwxjPlHTqCERuQ63NpEXuFtVP51nm63A5wE/cExVry52TMdRko5Tlk0fiid/qSovDKQzffdGOD4Sn9jPI7Bp3TKu7Q7z+nNW5DiXyyXo99Ia8rHn4CB3PXzQumgZhjEvqFnUkIh4gX8ErgWOAE+IyP2q+lzWNkuBLwPXqepLIjLt09DnEYZjyWlt+tlkJ3+1hnwcHx3n9gf288djZ3F8NM6O3n4OHc8tubzxjBa2d3ew9bzKnb5wut9vJvFrV1+ET3z/OeuiZRjGvKGWUUObgedV9QCAiNwLvAV4LmubdwDfVdWXAErJWF6zvJFv/Wl53aayk79SjjKedDgZTfCZH+3N2W51W4Nb3rm7g1VLSwsjLUTA53Hr/gRz+/1W2gBnV1+ET/+gl4NphdW5oomPXteVs08tWm1aD2DDWPjUMmpoFXA46/MR4LJJ25wL+EVkF9AC3K6q/zL5QCJyC3ALwKrVpZmCsnn51BgeEQZH4zk2f0g7fbvCXNvdwbkdzTNy2IoITQG37k+ogAmpkgY4u/oifPi+pzk5liCjU/ZHRvjIfU/z2RsuZGtXuCb9eq0HsGEsDkqKGlLV7wLfFZEVuKahUsj3RJ0c0+kDLgG2Aw3AYyLyuKrum3T+u4C7AC543cUl1X1OOcrTh0+yozfCsZE42eH+Iu7Dd2VriDv/6JIZl2rwez1u3H8JZR8qaQJz50MHGBlP4hWZmF2IKsOx0zOJWrTarGX7TsMw5g8FFYGIXA58GhgE/gb4f4EVgEdE/lhVfzjNsY8A2cP31cDLebY5pqqjwKiIPARcCOyjAlSV/ZERdvZGpjh9wY36WdrgPqwdhVuu6pyREmgMuLb/ckpFV9JF6/CJMVKO4s2arYi40VOZmUQt+vVaD2DDWBwUe4J9CfjvwBLgAeB6VX1cRLpw/QXTKYIngA0ish44CtyI6xPI5t+BL4mIDwjgmo7+odwv8cqpKDt7I+zsjfDi4GSnbyvXbgzTEvTzH796hVeHorQ3h0p2NE9mpjX/t3aF+RSU1QRmTVsjx0bGUYeJrmOqbgG6zEyiFu0mF0oLS8MwilNMEfhU9ccAIvIpVX0cQFX7SrGjq2pSRN4H/Ag3fPSrqvqsiNyWXn+HqvaKyA+BXwEObojpM6UIfiqaYNfeAXb29vPMy0M569a0NdCzsYPtXWHOzHL6buuu3JzREPDSEqpOzf+tXeGyTCu3bumc8BFo2sblqOvfyMwkatGv13oAG8bioFiHsqdU9eLJf+f7PJus77pAL//QXew+NDhRQA5gWVOAbV3t9HR3sCE8M6dvBo8Ivzpykm/+/CVeGBghnnTwe4VzC7R8rGWETTlRQ9VsN2ktLA1jYVBpq8oUMIrr9G0AMjYXAUKq6s+7Y40JnrFBz3jn5wHXXr3l3BVs7wrzurWVZ/pOOUe67MOTBwf5xPefI5FKcWw4PuH+Xt4UIODz5jRGn9zoJjN6tubphmHMBypqTKOq87b2wRWdy+npDnPF2csLhmmWi4jQFHRr/meOedfDB/F7heMjSTwewSOC47jROiuX+HKiZyzCxjCMeqX0cJd5wjnhZv7nW8+v2vH8Xg+tIT/NId+UGUUmaiaecibWiUA85UyJnpnNCJtCJihL/jIMoxLqThFUw/yTSfxqCfmLNozJRM0EvB6SjiLiRusEvJ4p0TOzFWFTKMnrhiMnue+po5b8ZRhG2Syqtlc+j4dlTQHWtDUQbg1N2zXs1i2dJFJKa4Nvotidg9IS8k2JnslsOxZPouq+1yLCJtsElenL4PcKdz9yMO/yOx86UNXzG4ax8Ki7GUElNAbcks9NwfK+bnbMfyI1TDzpEPAK61c0TzG7VJIfUAmFTFCj8RRrJ/lLLPnLMIxSKJZZPExuSQhJfxZAVbW1xrLNiJkmfmUoJ+a/3PyASihkgmoKuJFKlvxlGEa5FBsi7wRWAt8F7s1UCJ0P7D4wyOd37uPVoXEAgj7hHZeu5Y9ev27Bd/wqlOR185Xrue+po5b8ZRhG2RTMIwAQkSXA7+KWhwgB/4qrFAZnR7ypnL3xAm34/f/NyHhqyroPbDubD/1G1xxINbsUSvKy5C/DMApRUULZpAN4cPsQfBH4X6r699UVsXTa1nbpknf83ZTlArSEfPzqk2+cfaEMwzDmORUllKV3fD1wE3AV8AjwVlV9uPoilk7COd2fOLsAm8KUXgOGYRjG9BRzFh8CTgL34jaFSaaXXwygqk/VXrypBLzevI0OBGiaJhx0IWHJY4ZhVItiM4JDuAPtN6Zf2SiwrUYyFaW9JUiowcepaHJKm5ubr1w/FyLNOtY5zDCMalKs1tDWWZSjZFpCPj739tfxP/79GY6ciKJAg9/De64+mw/0nDvX4s0KVtfIMIxqMm2GlYj4gfcAW9KLdgF3qmqihnIVZWtXmIe75mRCMi+wzmGGYVSTUjKtvoLbV/jL6dcl6WXGHLGmrZFoItcxbsljhmFUSkFFkG4fCXCpqr5TVR9Iv94FXDo74hn5mK26RoZhLA6KzQh2p99TInJ2ZqGIdAIWpzmHbO0K86k3v4ZwS4hT0QThlpA1wDEMo2KK+QgyUZofBn4qIpkyluuAd9VSKGN6ZqOukWEYi4NiiqBdRD6U/vtO3Ab0o7ilJl4H/LTGshmGYRizQDFF4AWaISd/qzn93lIziQzDMIxZpZgieEVVPzVrkswzLHPXMIzFQjFn8cKr4VwimczdyHAsJ3N3V19krkUzDMOoOsUUwfZZk2KeUagdpLV9NAxjIVKsxMSc9RyYC7JNQQPD46xsDeast8xdwzAWKouqeX0hJpuCRODoyRjDsdNVNCxz1zCMhcqiaF6fTT4n8OQibh0tIY6ejPLqqRjNQZ+1fTQMY0GzqBRBofLNo+MJzljSMLFda4MfUF4dGudUNGFtHw3DWNDUnSLoe3WYm+56vKIHc6HyzYmUEk2kJpYD+LweLl7bxj23XF5V+Q3DMOYbdecj8Hmk4nDOwyfGaPDndjFr8HsJ+DxWxM0wjEVL3SkCoOJwzkLlmzeEW6yIm2EYi5a6Mw1lqCSc89YtnXz8/mcZiydp8HtznMBWxM0wjMVKTWcEInKdiOwVkedF5GNFtrtURFIickOpx64knHNrV5gbLl7FwPA4va8OMzA8zg0XrzIFYBjGoqZmikBEvMA/AtcDG4GbRGRjge0+A/yo1GNXasPf1RfhvqeO0t4SpHtlC+0tQe576qiVjjAMY1FTyxnBZuB5VT2gqnHgXuAtebZ7P/BvQElP45SjFdvwrXSEYRjGVGrpI1gFHM76fAS4LHsDEVkFvBXYRpH2lyJyC3ALwNq1aysO6bSm74ZhGFOp5YwgX/VSnfT588BHVbVo60tVvUtVN6nqpvb29ooFsqbvhmEYU6mlIjgCrMn6vBp4edI2m4B7ReQQcAPwZRH5nVoJZE3fDcMwplJL09ATwAYRWQ8cBW4E3pG9gaquz/wtIl8D/kNV/2+tBNraFeZTuL6CIyfGrHSEYRgGNVQEqpoUkffhRgN5ga+q6rMiclt6/R21Oncx6i1fwDqlGYZRa0R1stl+frNp0ybds2dPwfWZB+e+/iESKSXg87Ah3FKXD9DsInnZCXCW9WwYRrmIyJOquinfurosMVGIzIPz4LERhmJJookUp8YSHDo+UpetJi3c1TCM2WBBKYLMg3M4lsSD4PN48HiEoWiyLh+ghYrkWbirYRjVpG5rDeWznWfyBOIpB6+40asiEE85NPi97I+4Jazrxd6+pq2RyHAspzy2hbsahlFt6nJGMLm1ZKYsdXPAtaMHvB4yrg9VCHg9HB8dZziWnLLPfDYXWbirYRizQV0qgkK2cxEhkVJaQj4clKTj4DhKa4OPwdEEbY3+urK3b+0KW3lswzBqTl2ahgqVijgVTfA3bzmfOx86QDI1RDwdNbRueTPx5BArmoNT9pnv9vZ6C3c1DKP+qEtFUMx2XujBedNdj5u93TAMIw91aRqqxHZu9nbDMIz81OWMoJJSEQuxvIRlHRuGUQ0WXGbxYsGyjg3DKIdFk1m8mLCsY8MwqoUpgjrFso4Nw6gWpgjqFGuyYxhGtVj0imBXX4Sb7nqcKz/zADfd9fi8zjTOxqKgDMOoFotaERQqVVEPysCyjg3DqBZ1GT5aLbIdrgCNAR9j8SR3PnSgLh6olnVsGEY1WNQzAnO4GoZhLHJFYA5XwzCMRa4IzOFqGIaxyBWBOVwNwzAWubMYzOFqGIaxqGcEhmEYhikCwzCMRY8pAsMwjEVO3SmCAwOjdVcOwjAMYz5Td4og6Th1Vw7CMAxjPlN3isAjYvX3DcMwqkjdKYJsrByEYRjGzKlrRWDlIAzDMGZO3SWUOaqo6kSPXisHYRiGMTPqThH4PB5ORROsbmvk1i2dlhVsGIYxQ+pOEXS2N/HwR7fNtRiGYRgLhpr6CETkOhHZKyLPi8jH8qz/AxH5Vfr1qIhcWEt5DMMwjKnUTBGIiBf4R+B6YCNwk4hsnLTZQeBqVb0A+BvgrlrJYxiGYeSnljOCzcDzqnpAVePAvcBbsjdQ1UdV9UT64+PA6hrKYxiGYeShlopgFXA46/OR9LJCvBv4Qb4VInKLiOwRkT0DAwNVFNEwDMOopSKQPMs074Yi1+Aqgo/mW6+qd6nqJlXd1N7eXkURDcMwjFpGDR0B1mR9Xg28PHkjEbkAuBu4XlWPT3fQJ5988piIvFglGVcAx6p0rGpicpWHyVUeJld5zFe5oDzZziq0QlTzDtJnjIj4gH3AduAo8ATwDlV9NmubtcADwB+r6qM1EaS4jHtUddNsn3c6TK7yMLnKw+Qqj/kqF1RPtprNCFQ1KSLvA34EeIGvquqzInJbev0dwMeB5cCXRQQgOV8vuGEYxkKlpgllqvqfwH9OWnZH1t83AzfXUgbDMAyjOHVddK4KzNe8BZOrPEyu8jC5ymO+ygVVkq1mPgLDMAyjPljsMwLDMIxFjykCwzCMRc6iVQQi4hWRX4jIf8y1LBlE5JCI/FpEfikie+ZangwislRE7hORPhHpFZEr5lomABE5L32tMq8hEfnzuZYLQET+q4g8KyLPiMg9IhKaa5kAROSDaZmenctrJSJfFZGIiDyTtWyZiPxERPan39vmiVy/n75ejojMSVRjAbk+m/6f/JWIfE9EllZ6/EWrCIAPAr1zLUQerlHVi+ZZGO3twA9VtQu4kHly3VR1b/paXQRcAowB35tbqUBEVgEfADap6vm44dM3zq1UICLnA3+KWwfsQuC3RGTDHInzNeC6Scs+BuxU1Q3AzvTn2eZrTJXrGeB3gYdmXZrTfI2pcv0EOD9dtHMf8JeVHnxRKgIRWQ38Jm5Gs1EEEWkFtgD/BKCqcVU9OadC5Wc78IKqVivrfKb4gIZ0YmUjebLq54Bu4HFVHVPVJPAg8Na5EERVHwIGJy1+C/D19N9fB35nNmWC/HKpaq+q7p1tWSbJkE+uH6fvI8ywaOeiVATA54H/BjhzLMdkFPixiDwpIrfMtTBpOoEB4J/TprS7RaRproXKw43APXMtBICqHgU+B7wEvAKcUtUfz61UgDuy3SIiy0WkEXgTuWVg5poOVX0FIP1u7QdL579QoGhnKSw6RSAivwVEVPXJuZYlD29Q1Ytxezi8V0S2zLVAuCPbi4GvqOrrgFHmZspeEBEJAG8GvjPXsgCkbdtvAdYDZwJNIvKHcyuVO7IFPoNrUvgh8DSQLLqTMe8Rkb/CvY/frPQYi04RAG8A3iwih3B7JGwTkW/MrUguqvpy+j2Ca+vePLcSAW7xwCOq+vP05/twFcN84nrgKVXtn2tB0vQAB1V1QFUTwHeB18+xTACo6j+p6sWqugXX1LB/rmXKol9EzgBIv0fmWJ55j4i8E/gt4A90Bklhi04RqOpfqupqVV2Ha054QFXnfLQmIk0i0pL5G/gN3Kn8nKKqrwKHReS89KLtwHNzKFI+bmKemIXSvARcLiKN4hbR2s48cbCLSDj9vhbXATqfrtv9wDvTf78T+Pc5lGXeIyLX4Zbuf7Oqjs3kWHXXvH4B0wF8L118zwd8S1V/OLciTfB+4JtpE8wB4F1zLM8EaVv3tcCtcy1LBlX9uYjcBzyFO2X/BfOnTMG/ichyIAG8N6tD4KwiIvcAW4EVInIE+ATwaeDbIvJuXGX6+/NErkHgi0A78P+JyC9V9Y3zQK6/BILAT9LPjcdV9baKjm8lJgzDMBY3i840ZBiGYeRiisAwDGORY4rAMAxjkWOKwDAMY5FjisAwDGORY4rAqFtEJJWuOvqMiHwnHUpa6r4Xicibsj6/WUSKZkyLyKMzkbfAMbeKSNFkMxH5dxF5rNrnNowMpgiMeiaarj56PhAHSoqhTheCuwi31g4Aqnq/qn662H6qWovs4K0UyTpOlxa+GFgqIutrcH7DsDwCo34RkRFVbU7/fRtwAW7hrb8GAsBx3NT7fhH5JG7dn3XAMeBKoAE4Cvxt+u9Nqvo+EekA7sAtuAfwHlV9NHM+EdkKfCp9/PNwyxP/mao6IvIV4NL08e5T1U+k5TuEW1HztwE/brJUDLdqZAq3sN/7VfXhSd/x3bgltvuBuKr+bXr52bi1Zbzp7/yhrGvxEeBtuMlG38vIYBiFsBmBUfekR/jXA78GHgEuTxfIuxe3ymyGS4C3qOo7gI8D/5qeUfzrpEN+AXhQVS/EHY0/m+e0m4G/AF4LnI1brgHgr9K9JC4ArhaRC7L2OZYuKvgV4MOqeghX4fxDWo4cJZAmUz7jnvTfGW4HblfVS8kqcS0ivwFsSMt3EXDJPCleaMxjTBEY9UyDiPwS2INbkuCfcGuy/0hEfg18BHhN1vb3q2q0hONuw31Yo6opVT2VZ5vdqnpAVVO4D+kr08vfJiJP4ZaVeA2wMWuf76bfn8SdmRQlPTM5B3hEVfcByXRzGYArOF1t9VtZu/1G+vUL3BIXXbiKwTAKYrWGjHommu5ONoGIfBH4e1W9P23C+WTW6tEqnnuyTVXTNvwPA5eq6gkR+RqQ3aJyPP2eorT/vbcDbcDBdC2ZVtxCiX9dZB8B/lZV7yzh+IYB2IzAWHgswbX7w+lKlvkYBloKrNsJvAcmelu35tlms4isFxEP7gP7EdwH9ShwKj2av74EeYvJcRNwnaquS1fLvYTTLS8fB34v/Xd2G8wfAf9FRDL+glWZiqOGUQhTBMZC45PAd0TkYVyncCF+CmxMh5++fdK6DwLXpM1LT5JrXsrwGG61zGeAg7hO2adxTTLPAl8FflaCvN8H3pqW46rMQhFZB6zFfeADoKoHgSERuQz4c+BDIrIbOAM4ld7mx7imosfS8t9HYUVjGIBFDRlG2aRNTh9W1d+aQxkacU1jKiI3Ajep6lvmSh6jvjEfgWHUJ5cAX0o3vjmJ27PWMCrCZgSGYRiLHPMRGIZhLHJMERiGYSxyTBEYhmEsckwRGIZhLHJMERiGYSxy/n/AzzwZ0bz6MgAAAABJRU5ErkJggg==\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": 39, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 32.99999999999995, 'Participant Age')" ] }, "execution_count": 39, "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": 40, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 40, "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": 42, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "['3yo', '4yo', '5yo', '7yo', '8-12yo']" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "order = sorted(pheno.AgeGroup.unique())[:-1]\n", "order" ] }, { "cell_type": "code", "execution_count": 43, "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": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 44, "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." ] }, { "cell_type": "code", "execution_count": 48, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting ptitprince\n", " Downloading ptitprince-0.2.5.tar.gz (9.2 kB)\n", "Requirement already satisfied: seaborn>=0.10 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from ptitprince) (0.11.0)\n", "Requirement already satisfied: matplotlib in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from ptitprince) (3.3.2)\n", "Requirement already satisfied: numpy>=1.13 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from ptitprince) (1.18.5)\n", "Requirement already satisfied: scipy in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from ptitprince) (1.4.1)\n", "Collecting PyHamcrest>=1.9.0\n", " Downloading PyHamcrest-2.0.2-py3-none-any.whl (52 kB)\n", "Requirement already satisfied: cython in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from ptitprince) (0.29.21)\n", "Requirement already satisfied: pandas>=0.23 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from seaborn>=0.10->ptitprince) (1.1.4)\n", "Requirement already satisfied: cycler>=0.10 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from matplotlib->ptitprince) (0.10.0)\n", "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from matplotlib->ptitprince) (2.4.7)\n", "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from matplotlib->ptitprince) (1.3.1)\n", "Requirement already satisfied: certifi>=2020.06.20 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from matplotlib->ptitprince) (2020.6.20)\n", "Requirement already satisfied: python-dateutil>=2.1 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from matplotlib->ptitprince) (2.8.1)\n", "Requirement already satisfied: pillow>=6.2.0 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from matplotlib->ptitprince) (8.0.1)\n", "Requirement already satisfied: pytz>=2017.2 in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from pandas>=0.23->seaborn>=0.10->ptitprince) (2020.4)\n", "Requirement already satisfied: six in /opt/miniconda-latest/envs/neuro/lib/python3.7/site-packages (from cycler>=0.10->matplotlib->ptitprince) (1.15.0)\n", "Building wheels for collected packages: ptitprince\n", " Building wheel for ptitprince (setup.py): started\n", " Building wheel for ptitprince (setup.py): finished with status 'done'\n", " Created wheel for ptitprince: filename=ptitprince-0.2.5-py3-none-any.whl size=8428 sha256=b233423b170924d0614d65d9166e74f70961972a4506ae798d248d5ed0897163\n", " Stored in directory: /home/neuro/.cache/pip/wheels/58/a5/f2/55920bbc5d0e6fb74b2370e1e52e07c236ba7b621236ea5a81\n", "Successfully built ptitprince\n", "Installing collected packages: PyHamcrest, ptitprince\n", "Successfully installed PyHamcrest-2.0.2 ptitprince-0.2.5\n" ] } ], "source": [ "%%bash\n", "pip install ptitprince" ] }, { "cell_type": "code", "execution_count": 49, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 49, "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": 50, "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": 50, "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": 51, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "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": [ "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": 52, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 52, "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": 53, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "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": [ "## 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": 54, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 54, "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": 55, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 55, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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TQJ06ddiwYQPR0dHs3r2bJ598koyMDLp27cq6desqI24hhBBVICYmhszMTAAyMzM5fPiwhSMynqpHlFFRUWg0Gl5//XUaNmxYYhlvb28WLVqEjY0NS5cuxc/Pj549e5olWCHKUxP3xlu6dClnz56t1DZ0zpw5A/y120Rla9mypeq2koDPqfxF3DP//79Old5S0WeqWwXtmGLOnDkG3//nP/9R/f+YpahKcOfPn0ej0dCtWzeD4wUFBcXKvvTSS2zevJl169ZJghPVmm51dFMSXFU4e/YsR+KOVM1vwP9/pnPkypHKb+uW+iotW7Y0exilSf3/ZN+wVatKb6suVfvZ1ND13kr7vjpTleDu3LmDs7Mztra2+mP29vZkZWUVK+vl5YWLiwvx8fEVj1III9XYvfHqgvYxraWjMCurn9TPUqqqnuXdbVXrn4sq4OTkZJDUnJyqok9rHqp+wtzd3cnIyDDosbm7u1NQUMDly5cNyubn55OVlUVGRoZ5IhVCCFHl/v6I8p133rFMICZQleAaNWqEoihcu3ZNf6xt27YAbN261aDsli1bKCwsxMvLywxhCiGEsITmzZsbfN+0aVPLBGICVQmuR48eKIrC3r179cdGjBiBoiisWLGCuXPn8vXXXzN//nzefvttNBoN/fv3N3vQQgghqsaaNWuwtrYGwNrauuZueNqnTx/8/f1JTEzUH+vatSujR4+moKCAr776irfffpsNGzZQUFDAww8/zL///W+zBy2EEKJq7Ny5k8LCQgAKCwtrzoanf9eoUSO+++67Ysdnz55Njx49iIqKIjk5GScnJ7p168bQoUMNBqQIIYS4t9TYDU/V6NGjBz169DDX5YQQQlQD9/KGp7KbgBBCiFLpNjzVjamoMRueCiGEEDVyw1PdWpMVJbsJCCHEvete3fC0zAQ3c+ZMNBpNhRrQaDQVSnBbt25l06ZNJCQkoNVqadasGcOHD2fkyJFYWRn3hPXgwYMEBwcbVXbPnj14e3vrv585cybh4eGllm/WrBlRUVFGXVsIIUTVMeoRpYuLC/b29pUdSzFz585l48aN1KpVi8DAQGxsbDhw4ADz5s3jwIEDLFmyRD8/oyz16tVj6NChpZ4/fvw4586do3HjxqVOTO/QoQNNmjQpdtzd3d34DySECdLS0uCWaUtbVWu3IM0hzdJRiBrMqARXUFBA165dGTJkCJ07d67smACIjo5m48aNuLu7s379ev3s+evXrxMcHMzOnTtZv369Uc+EW7RoQWhoaKnnn3zySQCGDx9eao/16aefZtiwYeo/iBBCCIsoM8EtX76czZs389NPPxEeHk5ERAReXl4MHDiQIUOG0KxZs0oLbOXKlQDMmDHDYGmYevXqMWfOHMaMGUNYWBhjxowx+lFlSY4cOcLZs2extrYus5cnhKW4urpyMedijVxsubru4CBqhjIzQ+/evVm2bBn79u3jP//5D23btuXq1ausXLmSAQMG8PTTT7NhwwZu3bpl1qCSkpKIi4vD1ta2xJXhAwIC8PDwIDU1laNHj1aoLd3E9e7du+Ph4VGhawkhhKg+jHpEWadOHUaNGsWoUaO4cOEC4eHhbN26lRMnTnDy5ElCQ0Pp2bMngwYN4vHHH6/w6iW6LXZatWpV6ru/tm3bkpyczKlTp+jQoYNJ7eTk5Og37hsxYkSZZQ8ePEhCQgLZ2dm4ubnRsWNHunXrVqHeoxBCiMqjeh5c06ZNefnll3n55ZeJiYkhPDycnTt3smvXLnbv3o2LiwtvvvkmgwcPNjmoP//8E8BgNOPf6QaD6MqaIioqiqysLNzc3HjsscfKLFvSlImWLVuyePFifH19TY5BCCFE5ajQRO+AgAACAgKYM2cO69ev58MPPyQ9PZ2EhIQKBZWdnQ2Ag4NDqWVq164NUOJmq8bSPZ4cPHhwqb3O1q1bM3v2bAIDA/H29iYzM5P4+Hg+/PBDTp8+zbhx4wgPDzfp8ebJkydNjr2idPv0HT582GIxVBfV/V7U5D0VMzIyqv19r67xifJVKMHl5uYSHR3Nli1b+O233/QrTuuSj6kURQGo8By8sly8eJFDhw4BZT+eHDt2rMH3jo6O1K9fn65duzJmzBiOHj3KypUreeutt1TH0KZNG2rVqqW6njk4OzsD0LFjR4u0X51U93vh7OwM6ZaOonI4OztX7/tO9f25uB/duXNHVcfApAR34MABNm/ezI4dO8jJyUFRFNzc3BgwYABDhgzB39/flMvq6RKkridXEl3PzdRkquu9tW/fnhYtWqiub2dnx8SJE5k8ebLB/nhCCCGqB6MT3Llz54iIiGDr1q0kJyejKAq1atWiX79+DBkyhO7duxs16doYDRo0AODq1aullklKSjIoq0ZhYaH+ndrw4cPVB/j/dDvdJicnm3wNIYQQlaPMBJeWlsa2bduIiIjg1KlT+keHHTp0YMiQIfTv31/fjTcnPz8/AM6cOUNubm6JIylPnDgBwIMPPqj6+vv27SM5ORlHR0cGDBhgcpy66REVfSQrhBDC/MpMcD169KCwsBBFUWjcuDGDBw9m0KBBNGrUqFKD8vLywt/fn7i4OKKiooqtZRkTE0NSUhLu7u60b99e9fW//fZbAPr371+h5KTbI6lNmzYmX0MIIUTlKDPBFRQUoNFo8Pb2pm3btpw/f56PPvpIdSOLFi1SXWfixIlMmzaNDz74gPbt2+vXgbxx4wZz584FYMKECQbz0BYtWsTOnTvp06cPr7zySonXTUtLY8+ePUD5c99OnTpFUlISPXr0MHj8WlBQwLp161i3bh1QfCCKEEIIyyv3HZyiKFy9epVr167pv1dDo9GYlOCCgoIYOXIkmzZtYuDAgXTt2lW/2HJmZia9e/dm9OjRBnVSU1P5448/SE1NLfW6W7ZsIT8/n+bNm5c7QfzKlStMmTKFunXr0rRpUzw8PMjKyiIxMZGUlBSsrKyYMWMG3bt3V/35hBBCVK4yE5yl12acM2cOHTt2ZMOGDcTExKDVamnevLnq7XLuphs9aczgEl9fX4KDgzlx4gRXrlwhPj4ejUaDp6cnw4YNY9SoUfJ4UgghqqkyE9zChQurKo5SDRw4kIEDBxpVNjQ0tMxdA6BofzljNWrUiFmzZhldvqKWLl3K2bNnq6StM2fOAPDiiy9WSXstW7assraEEAIqONFbmNfZs2c5ciIerWPlr7CuKSz6qz98LqnS27LKlj2/hBBVTxJcNaN1dCXX7ylLh2FW9vHbLB2CEOI+ZJal8EeMGEHv3r3NcSkhhBDCLMzSg0tKSuLGjRvmuJQQQghhFrKZmRBCiBpJEpwQQogaSQaZCCFqvKioKCIjI1XVMXUqzYABAwgKClJVR1QOsyQ4taubCCFEdefm5mbpEEQFmSXBjR8/vsy924QQwpKCgoKkV3UfMkuC++c//2mOywghhBBmo2qQSXBwsKrn0dOnTyckJER1UEIIIURFqerBxcTEUK9ePaPLHz16VL8LgRBCCFGVKnWagFarRaPRVGYTQgghRIkqLcHl5eVx48YNnJycKqsJIYQQolRlPqK8evUqV65cMTiWn59PbGxsqVMDFEUhPT2dH374gfz8fNq3b2++aIUQQggjlZngvv/+ez7++GODY+np6YwZM6bcC+sSoAwyEUIIYQllJjhnZ2e8vLz031+9ehUrKys8PDxKrWNlZYWTkxMtW7ZkxIgRdOnSxXzRCiGEEEYqM8GFhIQY9MBat27NAw88wI8//ljpgQkhhBAVoWqawAsvvICjo2NlxSKEEEKYjeoEJ4QQQtwLTF6qKy4ujl9//ZWkpCRyc3P573//qz+Xl5fH9evX0Wg0Bu/whBBCiKqiOsGlpaXx2muv8euvvwJFoyU1Go1BglMUhWeffZYbN27www8/0KxZM/NFLO4LS5cu5ezZs1XSlqnbopiqZcuWVdaWEPczVQkuJyeHsWPHkpiYSP369enRowc//PADubm5BuVq1arFyJEjWbp0KdHR0Tz//PNmDVrUfGfPniXx5O80diqs9LZclKLVdnIvHKr0ti5lWld6G0KIIqoS3Pr160lMTKRdu3aEhYXh7OzMTz/9VCzBAfTt25elS5fy888/S4IzUlpaGlbZN7CP32bpUMzKKvsGaWl2qus1dipkdqfMSojIcubHyso+QlQVVQlu+/btaDQa3nzzTZydncss26JFC2xsbPjjjz8qFKAQArgFVj9V6tKxRXT/VrWv/Ka4BTSognbEfUtVgrtw4QK2tra0bdu23LIajQYnJycyMjJMDu5+4+rqyh8388j1e8rSoZiVffw2XF1dLR3GPatly5ZV1pbufWSrBq0qv7EGVfvZxP1HVYLTarVYW1sbtUNAYWEhWVlZODg4mBycEKLqBr/c3dbSpUurrE0hKouqZx6enp7k5uaSlJRUbtmYmBjy8/Np3LixycEJIYQQplKV4Lp16wbApk2byiyXm5vL+++/j0ajoWfPnqZHJ4QQQphIVYL75z//iZ2dHZ9//jlr164lLy/P4LxWq+Xnn3/mmWeeIT4+HmdnZ0aPHm3WgIUQQghjqEpwDRo04P333wdg4cKFdO7cmVu3bgEwbNgwHnnkESZNmkRiYiJ2dnYsWrRIBhcIIYSwCNXjjvv27cvGjRtp164dOTk5FBQUoCgK8fHxZGVloSgK7dq1Y+PGjXTv3r0yYhZCCCHKZdJalA899BCbNm3i8uXL/P7776SmpqLVaqlXrx7t2rWjefPm5o5TCCGEUMXkxZYBGjVqRKNGjcwVixBCCGE2VbA0ghBCCFH1JMEJIYSokUp9RPnEE0+YpQGNRsOuXbvMci0hhBDCWKUmuCtXrpilAWOW9RJCCCHMrdQEt3bt2qqMQ/w/q+y0KtkuR5OfA4BiW/lrhVplpwGeld6OEELcrdQEFxAQUJVxCCy0anyLqkg8nrJqvBCiyqneTcDKSt24lKSkJDw95V/vxpBV44UQwnxUZauZM2equvjly5cZNWqUqjpCCCGEOahKcFu2bOGdd94xquylS5cYM2YMV69eNSkwIYQQoiJUJThXV1c2btzIhx9+WGa58+fPM3r0aJKSkujQoUOFAhRCCCFMoSrBffHFFzg5ObFq1SrCwsJKLJOYmEhwcDApKSkEBASUWk4IIYSoTKoSXOvWrVm5ciX29vYsXryYr776yuD8qVOnCAkJ4fr163Tt2pVVq1bh6Oho1oCFEEIIY6heqqtDhw4sW7YMGxsb5s2bx7ZtRXO2jh8/ztixY7l58yY9e/bk008/xd7e3uwBCyGEEMYwaS3KRx99lEWLFqHRaJg5cyaffPIJ48eP5/bt2/Tq1Yvly5djZ2dn7liFEEIIo5m8XU7fvn2ZN28es2fPZunSpSiKQt++fVm8eDE2NhXahcfA1q1b2bRpEwkJCWi1Wpo1a8bw4cMZOXKkqjl5M2fOJDw8vNTzzZo1IyoqqtLjEEIIUTUqlImGDx9OVlYW//3vf3nyySd5//33zfrLfu7cuWzcuJFatWoRGBiIjY0NBw4cYN68eRw4cIAlS5ZgbW2t6podOnSgSZMmxY67u7tXaRyibGlpaaRmWDM/1snSoZjVxQxr3NPSLB2GEPeFUhPcgw8+aPRFNBoNkZGRREZGlnguPj5edWDR0dFs3LgRd3d31q9fT9OmTQG4fv06wcHB7Ny5k/Xr1xMSEqLquk8//TTDhg2zeBxCCCEqV6kJTlEUszRg6nVWrlwJwIwZM/RJBaBevXrMmTOHMWPGEBYWxpgxYyr1EWF1ieN+4+rqimP6OWZ3yrR0KGY1P9YJe1dXS4chxH2h1AS3e/fuqozDQFJSEnFxcdja2hIUFFTsfEBAAB4eHiQnJ3P06NFKm0xeXeIQQgihXqkJrkGDBlUZhwHdI81WrVqVOtWgbdu2JCcnc+rUKVWJ5eDBgyQkJJCdnY2bmxsdO3akW7duJfa+KjMOIYQQlct8wx3N6M8//wTA29u71DJeXl4GZY0VERFR7FjLli1ZvHgxvr6+VRaHEEKIylWhBHfjxg3i4uJI+/9RYa6urvj7++Pm5lahoLKzswFwcCh9M87atWsDkJWVZdQ1W7duzezZswkMDMTb25vMzEzi4+P58MMPOX36NOPGjSM8PBwPD49KjeNuJ0+eVF3HXDIyMgA4fPiwxWIoS0ZGBraWDqKSZGRkVOv7DtX350IINUxKcLGxsSxZsoTY2NgSz3fq1ImXXnqJjh07mhSUbmCKRqMxqX5Jxo4da/C9o6Mj9evXp2vXrowZM4ajR4+ycuVK3nrrrUqN425t2rShVq1alXLt8jg7OwOY/HdU2Zydncm9YekoKoezs3O1vu9QfX8uxP3tzp07qjoGqof9bdq0iZCQEGJjY1EUBWtra9zc3HBzc8Pa2hpFUTh06BDBwcHF1qo0lq5XpOtBlUTXY9KVNZWdnR0TJ04EYO/evRaLQwghhHmp6sHFx8fzzjvvoNVq6dixI5MnT+aRRx7RL8uVl5dHTEwMK1as4Pfff+edd97hoYcews/PT1VQugEuZe0ll5SUZFC2Ipo3bw5AcnKyReMQQghhPqq3y9FqtfTv359169bRrVs3gzUn7ezsePTRR1m/fj39+vWjsLCQ1atXqw5KlxDPnDlDbm5uiWVOnDgBqJuQXppbt24BxXthVR2HEEII81GV4A4dOoRGo+GNN94oc1KzlZUVb775JhqNhpiYGNVBeXl54e/vT35+fonrQ8bExJCUlIS7uzvt27dXff2/2759O1D0TsyScQghhDAfVQkuLS0NFxcX6tevX25ZDw8PXFxc9CMs1dK9F/vggw+4ePGi/viNGzeYO3cuABMmTDBItIsWLSIoKIhFixYZXOvUqVPs2bOHwsJCg+MFBQWsXr2adevWAcUHopgahxBCCMtT9Q7OycmJjIwMsrOzy93INDs7m8zMTFxcXEwKLCgoiJEjR7Jp0yYGDhxI165d9YscZ2Zm0rt3b0aPHm1QJzU1lT/++IPU1FSD41euXGHKlCnUrVuXpk2b4uHhQVZWFomJiaSkpGBlZcWMGTPo3r27WeIQQghheaoSnJ+fH/v372fdunVMmjSpzLJr166lsLAQf39/k4ObM2cOHTt2ZMOGDcTExKDVamnevLnqbWp8fX0JDg7mxIkTXLlyhfj4eDQaDZ6engwbNoxRo0YVezxZGXEIIYSoOqoS3LPPPsuvv/7KkiVLyM7O5l//+pd+3oxOSkoKn3/+OevWrUOj0fDss89WKMCBAwcycOBAo8qGhoYSGhpa7HijRo2YNWtWlcUhhBDC8lQluL59+zJ48GA2b97MqlWrWL16Na1bt8bDw4O8vDyuXr3KhQsXKCgoQFEUhg4dSp8+fSordiGEEKJUqlcyCQ0NpUWLFqxatYrMzEyOHz9erIyTkxOTJk1i/PjxZglSCCGEUEt1gtNoNEycOJExY8bw66+/lrgWZbdu3cpcv1EIIYSobCYvtuzg4EDv3r3p3bu3OeMRQgghzKJabpcj1ImKiiIyMlJVnTNnzgDw4osvqm5vwIABJW4AK4QQ1YnJCS4rK4u9e/cSHx9v8IjSz8+Pnj17yuLD1VxFtzQSQojqTnWCUxSFlStXEhYWVuoq+46OjkyaNIkJEyZU2lYz4i9BQUHSoxJCiL9RneBmzpzJli1bUBSFWrVq4e/vj6enJ1C0sn5cXBxZWVl8+OGHnDt3jnfffdfsQQshhBDlUZXgduzYwebNm9FoNPoempOTk0GZzMxMVq1aRVhYGFu2bKF3794yF04IIUSVU7XG1P/+9z80Gg0vv/wyL7/8crHkBkVz4KZPn860adNQFIX//e9/ZgtWCCGEMJaqBBcXF4e1tTVjxowpt2xwcDDW1taqthcXQgghzEVVgsvKyqJ27dpGTeJ2dHTEycmJrKwsk4MTQgghTKUqwbm5uZGenk5ycnK5ZZOTk0lPT8fV1dXk4IQQQghTqUpwnTp1AorWo1QUpcyyCxcuBCAgIMDE0IQQQgjTqUpw48ePR6PREBUVxZgxY/j555/JycnRn7958yZRUVEMHz6c6OhorKys+Oc//2n2oIUQQojyqJom8OCDD/L2228zd+5cDh8+zKRJk9BoNDg7O5OXl0dubi5QNBncysqKt956iwcffLBSAhdCCCHKonor6meffZb169frHz1qtVpu375NTk6O/rFlly5d2LBhQ4U3OxVCCCFMZdJalB06dGDNmjXcvn2b+Ph4bt68CcADDzyAn58fderUMWuQQgghhFoV2k2gTp06BAYGmisWIYQQwmxUP6IUQggh7gVm2Q8uKyuLAwcOcPnyZWxsbPDz86Njx47muLQQQghhEqMS3JYtW9izZw85OTk0btyY5557jqZNmwIQERFBaGgot2/fNqjj5+fHkiVLaNiwodmDFkIIIcpTboKbPn0627dvB4qG/2s0Gr7++mvWrl3LzZs3efPNN9FqtcXqxcXFMX78eCIiIoxa2ksIIYQwpzITXFRUFJGRkQA0b96cli1bcu7cOc6dO8eyZctIT0/HysqKf/3rXwwdOhRvb2+Sk5OJjIzkk08+4dKlS/zvf/9j7NixVfFZhBBCCL0yE1xERAQajYYhQ4bw3//+F41Gg6IozJo1i82bN6PVahk3bhzTp0/X12ncuDHPP/88dnZ2vPfee+zatUsSnBBCiCpXZoKLi4sD4MUXX0Sj0QCg0WiYOnUq33//PRqNhuHDh5dYd8SIEbz33nucOXPGzCGL+8WlTGvmxxbfc9DcbucV/WzXsSt7fVVzuJRpjU+ltyKEgHIS3M2bN7G3t8fLy8vguJeXFw4ODuTm5tKoUaMS67q4uODs7ExmZqb5ohX3jZYtW1ZZW5f//x9hHk1bVXpbPlTtZxPiflZmgisoKKBu3bolnqtduza5ubnY2dmVWr9WrVqS4IRJXnzxxSpva+nSpVXWphCi8slEbyGEEDWSJDghhBA1Urnz4LKzs1m+fHmx41lZWQAlnvt7GSGEEKKqlZvgcnJy+Pjjj0s9X9Y53cRwIYQQoqqVmeC8vb2rKg4hhBDCrMpMcD/++GNVxSGEEEKYlQwyEUIIUSNJghNCCFEjmWU/OCFE9XP3YunG0i2tp3ai/YABAwgKClJVR4jKJglOCKHn5uZm6RCEMBtJcELUUEFBQdKrEvc1eQcnhBCiRpIEd5+6fv06U6dO5caNG5YORQghKoUkuPvUmjVrOH78OGvWrLF0KEIIUSkkwd2Hrl+/zvbt21EUhe3bt0svTghRI0mCuw+tWbMGRSnavVqr1UovTghRI0mCuw/t3LmT/Px8APLz89mxY4eFIxJCCPMrc5pAcHBwhRvQaDTSQ6hm+vTpQ2RkJPn5+dja2tK3b19LhySEEGZXZoKLiYlBo9HoH2eZQrbLqX5CQkLYvn07AFZWVoSEhFg4IiGEMD+jJno3aNCA3r174+DgUNnxiCpQr149+vfvz5YtW+jfv7+sXiGEqJHKTHAPPPAAN2/e5MqVK3zzzTf07duXwYMHExgYWFXxsXXrVjZt2kRCQgJarZZmzZoxfPhwRo4ciZWVca8Q8/PziY2NZe/evfz+++9cvXqVW7du8cADD9C+fXtGjRpF586dS6w7c+ZMwsPDS712s2bNiIqKMumzWVJISAgXLlyQ3psQosYqM8Ht27ePvXv3EhERwU8//URERASbN2/G09OTgQMHMnjwYFq0aFFpwc2dO5eNGzdSq1YtAgMDsbGx4cCBA8ybN48DBw6wZMkSrK2ty73OoUOHGDduHADu7u74+/vj4ODAuXPniI6OJjo6msmTJzNt2rRSr9GhQweaNGlS7Li7u7vpH9CC6tWrx7JlyywdhhBCVJoyE5y1tTW9evWiV69eZGRksG3bNjZv3szRo0dZtWoVYWFh+Pv7M2TIEAYMGICrq6vZAouOjmbjxo24u7uzfv16mjZtChTN4QoODmbnzp2sX7/eqB6IRqOhX79+BAcH06lTJ4NzkZGRzJgxgxUrVtC5c2e6dOlS4jWefvpphg0bVuHPJYQQomoYPU3A2dmZkSNH8tVXX7Fjxw7+/e9/4+3tzcmTJ1mwYAE9evTg+eefJyoqiry8vAoHtnLlSgBmzJihT25Q1POYM2cOAGFhYWi12nKvFRgYyNKlS4slNyja5mPo0KEAbNmypcJxCyGEqB5MmgfXuHFjpk2bxu7du1m3bh3Dhg3DwcGBn376iZdffpklS5ZUKKikpCTi4uKwtbUtcTX0gIAAPDw8SE1N5ejRoxVqC8DPzw+A5OTkCl9LCCFE9VDh7XIeeeQRGjdujKenJytXrqSwsLBC0woA4uPjAWjVqhX29vYllmnbti3JycmcOnWKDh06VKi9CxcuAGW/Tzt48CAJCQlkZ2fj5uZGx44d6datm9EDXYQQQlQtkxNcTk4O0dHRREREEBMTg6IoKIqCj49PqSMSjfXnn38C4O3tXWoZLy8vg7KmSk1N1Y+SLGvCc0RERLFjLVu2ZPHixfj6+lYoBiGEEOanKsEpisL+/fvZvHkzO3fuJDc3F0VRqFevHk899RSDBw/mwQcfrHBQ2dnZAGXOu6tduzYAWVlZJrdTUFDAq6++SkZGBoGBgfTq1atYmdatWzN79mwCAwPx9vYmMzOT+Ph4PvzwQ06fPs24ceMIDw/Hw8NDdfsnT540OXZhPhkZGQAcPnzYwpEIIczJqASXmJjI5s2b2bp1K6mpqSiKgr29Pf3792fw4MF0797drI/qdI84K3sVlLfffpsDBw7g5eXF+++/X2KZsWPHGnzv6OhI/fr16dq1K2PGjOHo0aOsXLmSt956S3X7bdq0oVatWqaELkoRFRVFZGSkqjpJSUkAJi0pN2DAANk1W4gqcufOHVUdgzIT3JdffsnmzZs5ffo0iqKg0Wjo2LEjgwcPpn///jg5OVU44JLoeme6nlxJdD03XVm15s+fz7fffou7uztffvml6vlsdnZ2TJw4kcmTJ7N3716TYhDVg6zkIkTNVGaCCw0NRaPR4OXlxaBBgxg8eDANGjTQnzd2OoCdnZ2qoHRtXL16tdQyun913x2PsUJDQ1m3bh2urq58+eWXBtMQ1GjevDkgoy+rk6CgIOlRCSEAIx9RXrt2jZUrV+rnpqmh0Wj0oyKNpRu2f+bMGXJzc0scSXnixAkA1e/83nvvPVavXk3dunVZvXo1LVu2VFX/brdu3QJM70UKIYSoPOW+ONONjqzIl1peXl74+/uTn59f4jqPMTExJCUl4e7uTvv27Y2+7gcffMDnn39OnTp1WL16Na1bt1Yd2910K/K3adOmQtcRQghhfmX24NauXVtVcRQzceJEpk2bxgcffED79u3160DeuHGDuXPnAjBhwgSDwS2LFi1i586d9OnTh1deecXgeh999BFhYWG4uLjwxRdf6HuJZTl16hRJSUn06NHDYM3LgoIC1q1bx7p164DiA1GEEEJYXpkJLiAgoKriKCYoKIiRI0eyadMmBg4cSNeuXfWLLWdmZtK7d29Gjx5tUCc1NZU//viD1NRUg+O7d+/mk08+AYpWYVm/fn2JbTZv3pyJEyfqv79y5QpTpkyhbt26NG3aFA8PD7KyskhMTCQlJQUrKytmzJhB9+7dzfzphRBCVFSFVzKpTHPmzKFjx45s2LCBmJgYtFotzZs3V71dzu3bt/V/PnnyZKnDTAMCAgwSnK+vL8HBwZw4cYIrV64QHx+PRqPB09OTYcOGMWrUKHk8KYQQ1ZRGqei6WkI13VwOmQcnhBDGU/u706QeXH5+Plu3bmX79u3Ex8frRxPWrVsXPz8/BgwYwFNPPYWtra0plxdCCCEqTHUP7tKlS0yZMoWzZ8+WOkJSo9HQqlUrli9fTuPGjc0SaE2Sm5tLXFwcPj4+qucICiHE/SovL4/ExET8/f1LXYj/bqoSXGZmJoMGDeLq1avY2NjQr18/unTpgqenJ1A0+fq3334jOjqagoICGjRowObNmyttxZN7VUZGBomJiZYOQwgh7kk+Pj44OzuXW05Vglu2bBkff/wx3t7erFq1qtRJ0mfOnGHSpElcu3aNKVOm8MILLxgf+X1Aq9WSlZWFra1tpa+3KYQQNYWiKOTn51O7dm2jBhmqSnCDBg3izJkzrF69mi5dupRZ9sCBA4wbNw4fHx/ZKVsIIUSVU7UFwOXLl7G3ty83uQEEBgbi4ODA5cuXTQ5OCCGEMJVsRy2EEKJGUpXgGjduTG5uLgcOHCi37IEDB8jJyaFRo0YmByeEEEKYSlWC6927N4qiMGvWLM6dO1dqudOnTzNr1iw0Gg19+/atcJBCCCGEWmUOMgkODqZu3bosXboUKD5NoHfv3nTu3BkPDw/y8vK4evUqBw8e5Oeff0ZRFJkmIIQQwmLKTHCtW7emXr167Nu3T3/s4sWLTJ06lcTExBKHuOsu5+vry7Jly2SitxBCCItQvVRXkyZN+O6774iMjCQ6Opr4+HjS0tIAcHV1xc/Pj379+jFgwABZqksIIYTFqO7BCSGEEPeCar1djjDe4sWLWblyJQCvvfYa48ePt3BEVWfdunXExsaSmJhIWloamZmZODs707p1a4YOHcqgQYPumxVjZs6cSXh4eKnnmzVrRlRUVBVGZBkHDx4kODjYqLJ79uzB29u7kiMyTVJSEmFhYezbt49r166hKApeXl506dKFCRMmqB6lfv78eX755RdOnDjByZMnuXDhAoqisGTJEoKCgkqsk5+fT2xsLHv37uX333/n6tWr3Lp1iwceeID27dszatQoOnfubI6Pa3aS4GqA48eP89lnn6HRaEpdALsmCwsLIy0tjVatWtG+fXscHBy4evUqv/32GwcOHCA6Oprly5cbvX9gTdChQweaNGlS7Li7u7sFoql69erVY+jQoaWeP378OOfOnaNx48Z4eXlVYWTGi4+PJyQkhPT0dDw9PXn00UeBoj0t//e//7F161Y+//xzOnToYPQ1N23axNq1a1XFcejQIcaNGwcU/fz4+/vj4ODAuXPniI6OJjo6msmTJzNt2jRV160K5Sa4zMxM3njjDZMb0Gg0/Pe//zW5vihbXl4eb7zxBm5ubjz00EPs2rXL0iFVucWLF+Pn54ejo6PB8TNnzjB27Fh2795NeHg4w4cPt1CEVe/pp59m2LBhlg7DYlq0aEFoaGip55988kkAhg8fXm179/PmzSM9PZ1nnnmGt956Sz+mIT8/n7fffpvvvvuOOXPmqFoK0cfHh/Hjx9OmTRvatGnDrFmziImJKbOORqOhX79+BAcH06lTJ4NzkZGRzJgxgxUrVtC5c2ejVrmqSuUmuDt37hAREWHSxRVFkQRXyZYsWcLZs2f55JNP2LFjh6XDsYi//0+n06pVK5577jmWLl3K/v3776sEJ0p35MgRzp49i7W1dZm9PEu6c+cOR44cAeDFF180GLBna2vLtGnT+O6770hISCAnJwcHBwejrvv000+rjiUwMJDAwMASzw0YMIBff/2Vb7/9li1bttx7Cc7GxoZ27dpVQShCrWPHjrF69WqeeuopevXqVWKC+/PPP+nTpw/Ozs78/PPPJe6hlJ+fz+OPP05qaio//PCDwS4RV65cISwsjF9++YXk5GQcHBxo3bo1zzzzDAMHDqzUz2cONjZFP+K6fffu9/txt/v1Xnz33XcAdO/eHQ8PD6D63QsrKytsbGwoKCgo8bWDrtfp6Oho1L5olcnPzw+A5ORk/bHqcj/LTXB16tRh3bp1Rl9QVI07d+7w+uuvU6dOHWbNmlVquYYNG/L444+ze/dutm3bxogRI4qV2bFjB6mpqQQEBBj8kB07dox//etfpKen07BhQ/r06cOtW7c4dOgQMTEx/PLLL7z77rvV9hHP5cuX+eqrrwDo1asXcP/cj4MHD5KQkEB2djZubm507NiRbt26GbyHvF/uxd1ycnKIjIwEMPi81e1e2Nra0qVLF/bt28eyZcuKPaL86KOPgOrxiPXChQuA4fvdanM/lTL4+voq3bp1K6uIsJCFCxcqPj4+yg8//KA/9vrrrys+Pj7KZ599ZlB2//79io+PjzJ06NASr/Xcc88pPj4+yvbt2/XHcnNzlZ49eyo+Pj7KggULlIKCAv25hIQEJTAwUPHx8VE2bdpk5k9mum+//VZ5/fXXlenTpyujRo1S/Pz8lNatWyuLFi0yKFeT74fuZ6CkrwEDBiinT582KF+T70VJvv/+e8XHx0cJDAxU8vLyDM5Vt3tx6dIlpW/fvoqPj4/So0cPZfLkycrkyZOV7t27Kw8//LAyf/78Yp9BrdGjRxf7TGqkpKQoHTt2VHx8fJTdu3cbnKsO91MS3D3o8OHDSuvWrZXJkycbHC8twSmKogwYMEDx8fFRjh07ZnA8ISFB8fHxUR599FElPz9ffzw8PFzx8fFRHn/88RL/J9qwYYPi4+Oj9OnTx0yfquLefPNNg1/ofn5+yieffKLk5uYWK1tT78fq1auVtWvXKmfOnFGysrKU5ORkZc+ePcqgQYP0v9iTkpIM6tTUe1GSUaNGKT4+PkpoaGiJ56vbvbhx44byr3/9q9g/VoYNG6ZER0ebdM27VSTB5efnKyEhIYqPj48SEhJSYhlL38/7Z9x0DZGbm8sbb7yBk5MTb7/9ttH1Ro0aBcDGjRsNjm/YsAGAZ599Vv++CoqGBgMMHDiwxBVpdI9GLl68aPDs3ZIWLFhAQkICx44d44cffiA4OJjly5fzzDPPFIuxpt6PsWPHMmbMGFq2bImjoyP169fnscce45tvvqFdu3bcuHFDP19Sp6bei7+7ePGiPvaSHplB9boXv//+OwMHDuTSpUusWLFCP+3l448/Jj09nalTp7J8+XJV1zSnt99+mwMHDuDl5cX7779fYhlL309JcPeYxYsXc+HCBWbOnEn9+vWNrjdkyBCcnZ2JjIzk1q1bQNEUkC1btmBjY8MzzzxjUF73w9OwYcMSr1erVi19+9XplxiAvb09LVu25PXXX2f69OmcPn2ad955x6DM/XQ/oGiQzcSJEwHYu3evwbn75V7oBpe0b9+eFi1alFimutyL9PR0pkyZQlZWFp999hlPPPEEDzzwAK6urvTu3ZvPPvsMe3t7PvnkE/07sHfffZeZM2cafL377rtGt6nG/Pnz+fbbb3F3d+fLL78sdX6lpe+nJLh7zK5du7CysiIiIoIxY8YYfP3yyy9A0WTOMWPGGAw+cXR0ZPjw4dy5c0f/P3pERATZ2dn07t27WLJUjJgwbkwZS9PNBduzZw/5+fn64/fj/WjevDlQ/BfD/XAvCgsL9dOdypouUl3uxU8//URaWhoPP/xwiauVNGnShIceeoiCggL9PLbo6GjCw8MNvqKjo1W3XZ7Q0FDWrVuHq6srX375JU2bNi21rKXvZ5kJ7vTp07IOZTWk1WqJiYkp9nX9+nWgaPRgTEwMJ0+eNKg3atQorKys+Oqrr9BqtWzatEl//O88PT2BouG+Jblz5w6pqakA+qHW1ZGLi4t+uPXt27cNzt1v90P3L+jatWsXO1fT78W+fftITk7G0dGRAQMGlFm2OtyLa9euAeDs7FxqGRcXF+Cvv9cff/yRhIQEg68ff/zR6DaN8d5777F69Wrq1q3L6tWrDUY/lsaS91N6cPeYkn6IdV+6SauvvfYaCQkJbN682aBu48aN6dGjB5cuXWLx4sWcPXuWVq1aERAQUKydRx55BIBt27ZRUFBQ7Hx4eDiKotCkSZNq80usJIcOHaKgoAAXFxceeOABg3P32/3Yvn07AG3atCl2rqbfi2+//RaA/v37l5jg71Yd7oWuZxMXF2fw5EEnPz+fuLg4oPTHeeb2wQcf8Pnnn1OnTh1Wr15N69atjapnyfspCe4+M3r0aKBo/UaAkSNHlliuf//+eHl58eeff7Jo0SK0Wq3+3NmzZ1m2bBkA//znPys54rLFxsayZcsW8vLyip07fPiw/jHtiBEjsLa2LlamJt2PU6dOsWfPHgoLCw2OFxQUsHr1av181rFjx5ZYvybdi7ulpaWxZ88eoPTBJX9n6XvRo0cP/ZqqCxcuNPj5zsvLY/78+Vy7do06derQvXt3Vdc2xUcffURYWBguLi588cUX+sndxrLU/Sxzuxxxb9GtJF/WbgKKotC/f3/++OMPateuzc8//1zqjutHjx5lwoQJpKen07hxY9q2bcvt27c5ePAg+fn5DB482OKTeb///nveeOMNXFxc8PPzo169emRlZXH58mXOnj0LwGOPPcaSJUtKXE2hJt2PXbt2MWXKFOrWrUvTpk3x8PAgKyuLxMREUlJSsLKyYvr06UyYMKHE+jXpXtztyy+/ZOHChTRv3lzfiy1PdbgX4eHhzJo1i8LCQurXr4+/vz9QtNhyamoqdnZ2fPjhh/Tu3dvoa8bFxTF37lz992fPniUrK4umTZtSp04d/fGvv/5a/+fdu3czefJkoKj336pVqxKv3bx5c/1Apr+z1P2U3QTuMxqNhq5du/LHH38wZMiQUn/IANq1a0dERASrVq3il19+YceOHdjb29OuXTv9kjmW/gX2yCOPMHnyZGJjY7lw4QJHjhxBURTc3d3p168fgwYNKvMXQE26H76+vgQHB3PixAmuXLlCfHw8Go0GT09Phg0bxqhRo0p8PKlTk+7F3XSDG9SsRVod7sXQoUPx8fFhzZo1xMbG8uuvvwJF755GjBjBuHHjjHoHdrfMzEyOHTtW7LhuJGZJ7n53ffLkyWLv9nUCAgJKTXCWup/Sg7vP5OXl8fjjj3P9+vVi67/dj+R+/EXuxV/kXpiXpe6nvIO7z2zcuJHr16/TvXt3+Z8WuR93k3vxF7kX5mWp+ymPKO8D58+f5/PPPyclJYV9+/Zha2vLjBkzLB2Wxcj9+Ivci7/IvTCv6nA/JcHdB1JTU/n222+xs7OjdevWvPTSS0YP8a2J5H78Re7FX+RemFd1uJ/yDk4IIUSNJO/ghBBC1EiS4IQQQtRIkuCEEELUSJLghBBC1EgyilKICtAtjwXQrVs3vvjiCwtHVL5Dhw6xfft2Dh06REpKCpmZmTg6OuLl5UWbNm3o1asXPXr0wM7OztKhClEhMopSiAqYMmUKu3btAsDKyoo9e/bot/yoblJTU3nttdfYv3+//pi1tTXOzs5kZ2cbLOjr6enJvHnz6NmzpyVCFcIs5BGlECa6efMme/fuxcHBgaeeegqtVsuWLVssHVaJrl27xogRI9i/fz8ODg6MHz+e8PBwTp48ycGDBzlx4gQ///wz7733HgEBASQlJclekOKeJwlOCBNt27aN/Px8nnjiCf7xj38ARSvAVzdarZZp06aRlJSEm5sbX331Fa+99hp+fn5YWf31K8DDw4PBgwezbt06Vq9eTYMGDSwYtRAVJwlOCBPpktnAgQPp1KkT3t7enD9/nuPHj5dZ7/Dhw0ycOJGAgADatWvHoEGD+PLLL9FqtcycORNfX1/9vld/p9VqiYiIYNy4cXTp0oU2bdrw6KOP8tJLL5W4SjxAVFSU/tyCBQuMWk2ia9euJe4b16tXL3x9fTl48CDJycnMmTOHJ554gjZt2jB48GCDspcuXeKtt97iiSeeoG3btjzyyCOMGjWKb775ptiedSVdvzS+vr74+voW2/X57nt3584dli5dSlBQEA899BCBgYFMnz6dP/74o9zPLmoOGWQihAnOnDlDXFwcdevWpVu3bmg0Gp588knCwsIIDw/noYceKrFeREQEb7zxhn4jRxcXF86dO8fChQuJjY0tcxuRzMxMpk6dqn+HptFoqF27NqmpqWzfvp3o6GhmzZql31xSR7e3l6+vL48//rg5Pj4XLlxg2rRp3Lx5EwcHB2xtbQ3O79mzh2nTpnHnzh0AnJ2dycnJITY2ltjYWCIjI/n4449xdHQ0Szx3y8vLIzg4mKNHj2Jra0utWrVIS0vjhx9+4McffyQsLEy/c7So2aQHJ4QJdL23/v3763+5Dxw4EIDIyMgSdxg/d+4cs2fPRqvV0rNnT3bv3s2hQ4c4fPgws2fPZs+ePezevbvUNl9//XX279+Pr68vq1at4ujRoxw+fJhDhw4xffp0rK2tWbBgAYcPH9bXycvL48iRI0DRxq/mEhoairu7O5s2beLo0aMcOXKEpUuXAkU9t+nTp3Pnzh0CAgLYvn07sbGx/P7778ybNw87Ozv279/PggULzBbP3TZt2kRCQgLvvvsuR44c4fDhw0RERODv709OTg4vvfSSwR5nouaSBCeESoWFhfrBJE899ZT+uK+vLz4+Pty6dYs9e/YUq7dq1Sry8/Px8fFh+fLlNGzYEAB7e3vGjBnDSy+9RHp6eolt7t+/n127dtGgQQPWrl1Lz5499TuUu7i4MGnSJKZNm4ZWq2XVqlX6elevXiU3N1cfn7nY2NiwevVqOnTooD/WpEkTAD799FOys7Np3Lgxq1atonnz5gDY2dnx7LPPMnv2bKBoI9KLFy+aLSadjIwM5s2bx5AhQ/T/+HjwwQf57LPPqFu3LtevX2fDhg1mb1dUP5LghFBp3759pKam0qBBAzp27GhwTteL+/tgE61Wq59OEBwcXOIcs9GjR5f6yE53vWHDhlG3bt0Sy+jaPnjwoP4d1909FRcXlxLrXbx4kW7dupX4VZrBgwdTr169YscVRWHHjh0AjB07FgcHh2Jlnn76aTw8PFAUhejo6FLbMFWDBg309+Jurq6u+sFAldGuqH7kHZwQKkVERADw5JNPotFoDM499dRTLF68mF9++YW0tDRcXV0BuHz5MpmZmQDFkqKOg4MD/v7+HDp0qNg53WPGL7/8kk2bNpUZX05ODrdu3cLNzc2oz1NQUMD169eNKqvTvn37Eo9fvnyZjIwMADp37lxiGSsrKwICAti6dStxcXGq2jXGI488Uuzv5e5zn376KWfOnCEvL08ms9dw0oMTQoWMjAz9e7K7H0/qeHt706lTJwoKCti6dav++M2bN/V/rl+/fqnXL+1camqqvv3r16+X+qWTk5MDQJ06dfTHSnv82aJFCxISEvRfq1evLjU+HV3i/ru0tDT9nz08PEqtr5sMf3d5cymrXd25wsLCUu+HqDmkByeECpGRkfqRgYMGDSqzbEREBCEhIUDRo7uK0I26XLFiBU888YTR9by9vbG3tyc3N5eEhASefPLJCsWhc/f8udKUNNDG0mThpvuL9OCEUEHNRO74+HgSEhIAwx5PSkpKqXV0PbW/073vOnfunNHtQ9HADt3jxJ9++klVXVPc/TmvXLlSarmkpKRi5aFo6TBA/4+Iv9M9/iyLMffX2tq61HeSouaQBCeEkS5evKh/F7Z582YOHTpU6pduvpnufV2jRo30c9zuHsZ/t9zcXE6ePFniuXbt2gGmDY545plnAEhISChxdKc5NWrUSJ84SpusrdVqiYmJAcDf39/gnLOzMwDJyckl1j1x4kS5MeiuXda5Vq1ayfu3+4AkOCGMpOu9tW7dmtatW+Pi4lLqV1BQEABbt26lsLAQKysr/aPFtWvXkp+fX+z6GzduJDs7u8S2hw4dCsDJkyf1SbM0f5/jFRQUxMMPPwzArFmzOH36tPEfWiWNRkOfPn2Aos+pexd4t2+++Ybk5GQ0Gg39+vUzOKebylDSfEBFUQgLCys3hitXrrBt27Zix2/duqWf9K77+xE1myQ4IYygKIp+7pvuF3hZevXqha2tLampqfpFiydNmoStrS2JiYlMnTpV/wjvzp07bNiwgcWLF5f62KxHjx707dsXgDfffJOlS5caPIq7ffs2u3bt4t///jehoaEGda2srFiyZAmenp7cuHGDf/zjH7z33nvEx8fr3+3dfY3Slgkz1vPPP4+joyMpKSlMnDiR8+fPA0Xv5L7++mvmz58PwIgRI/Rz53R0ieenn35i1apV+oT/559/Mn369FJ7uHdzdnbmP//5D5s3b6agoACA06dPM378eNLS0nBzc+O5556r0GcU9wbZLkcII/z222/6ASPbtm2jVatW5dYZP348+/bto3///nz00UdA0eTmWbNm6Qc71KlTh+zsbPLz8wkKCsLe3p6IiAimT5/OpEmTDK6XnZ3Nq6++qp9PB0W/zBVF0U9BgKK5cgsXLiwWT1nb5RQUFBhcw8vLi+nTpxcbSNOrVy+uXLnC2rVrS50GAPDjjz/y0ksv6d+lubi4kJOTo++5BgYGsmLFihLn/U2dOlU/l87KygonJyfS09OpVasWK1asYPz48UBRL083WR6K1qIMDw9n4sSJxMTEcPToUezs7LCzs9N/NgcHB1mq6z4ioyiFMILusWDTpk2NSm4A/fr1Y9++fezevZv09HRcXFwYPnw4TZo04dNPP+Xo0aPk5eXRokULhg8fzujRo3nhhReAv95F3c3R0ZGPP/6Yn376ie+++45jx46RlpaGlZUVTZo0oW3btvTt27fUPdzc3d1ZvXo1hw4dIjIyktjYWP2Gp7Vr18bHx4c2bdrwxBNP8Nhjj2FjY/qvh169erF161Y+++wzfv31V1JSUrC3t+ehhx5iyJAhDB8+XD+g5O8WLVrEF198QUREBH/++Sc2Njb069ePyZMnG7VQtJ2dHWvXrmXlypX88MMPXLt2DVdXVwIDA3nhhRf0K6uImk96cEJUE4qi8Pjjj3Pt2rVye0iiOF0P7oUXXmDq1KmWDkdUA/IOTohqQtfbcHJyKnU3AiGE8eQRpRBV6NNPP6V27dr07t0bDw8PrKysuH37NhERESxevBiA5557rsQ1HIUQ6kiCE6IKnT17lq1btzJ//nxsbW1xdHQkPT1dP+ika9eu+vdwQoiKkQQnRBV67rnncHJy4vDhw6SmppKRkUGdOnXw9fVl0KBBDBkypEKDO4QQf5FBJkIIIWokGWQihBCiRpIEJ4QQokaSBCeEEKJGkgQnhBCiRpIEJ4QQokb6P9EHHtspLdabAAAAAElFTkSuQmCC\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": 56, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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8KF+3dPjwYcTGxir99dprrwGouBFh69at5Yu2lW1dUFRUhOvXryu8J1tX8+IbR7Vl0KBBsLGxQW5uLs6cOYPU1FR5nKqSqRd16NABX375pTxeXU33VZebm5t8TdMff/yhVl3ZaN3Dhw+RlpamsExsbKx8+qhLly4ax+nl5QUrKyvcu3cPV65ckSdVmoxKGRsbo2PHjgDKX1ZQRnavJnGrY8iQIbCxsZGvYZOtFdMV2ee+ePGi0jKqtrwgasyYTJFGZKNSnTp1QqdOnWBlZaX0l5eXF4DyV71lC7oNDAzk03O7d+9W+Jr7vn37UFBQoLD9cePGAShfMK1st2iZ5xdYV5dQKJQvYpZN90mlUnTt2lXhHj9VTQ/J1qHUl2kkZSwtLeWH7G7ZsqXCmqQXlZaWIj8/X/7ngQMHwtLSEmKxGD/99FOl8mVlZdi8eTOA8lfpFb01V10mJibyqeXAwEDcunULQqFQ4zVFsv/Xhw4dUjjyEhUVJf/hYcSIERpGrR5jY2N88sknePfddzFr1iz5dg26Ivt3HB8frzBpSkpK0tku/0S6xmSK1CaVSuV7S73++utVlh86dCiEQiFEIhGioqLk199//30IhULcvXsXc+bMkU+xFBcXY+/evVi7di2srKwUPnPw4MHyb/qffPIJvv/++wrfBLOzsxEREYEPPvgAgYGBGn1O2dYKZ86ckY98KBuV2r9/P6ZNm4ajR49WiCMnJwc//vijfETq+R3T66sFCxbI30x86623Kkx1AuUjT7t27cLIkSMrjByam5vLX7ffs2cPtmzZIk+20tLS8NFHHyEuLg4GBgaYP39+jeOULUS/dOkSAOBf//qXfJpSXf7+/nBwcEBRURHee+89XLt2DUB5AhgWFoaPPvoIADBgwAD079+/xrFX15gxY7Bo0aIqTwPQhl69esnXD86dOxenT5+Wr12Mi4vDe++9p3CLEyJ9UG8XoD948AB//vknrl27huvXr+Off/6BVCrFhg0b5D8hVZdYLMbFixdx9uxZXLp0CSkpKcjKyoKtrS169OiBt99+W/7aM1XtwoUL8sSnOq+gW1lZoW/fvoiKisKhQ4fki2hffvllrFixAkuXLsXp06dx+vRpWFtbo6CgAGKxGF5eXjA1NUVISIjCL9LffvutfL+qTZs2YdOmTWjSpAmkUqn8bTMAVZ7lpkyvXr3g5OSEJ0+e4P79+zAwMFC6j45UKkVUVJQ8WTQ3N4eRkVGF18vffPPNer+AGABatWqF7du3Y9asWUhKSsLs2bNhZGQES0tLFBQUVEisXtwOY9q0abh//z5CQkKwfv16/PDDD7C0tEROTg6kUikMDAywbNmyWnmFvlOnTnBzc5MndDVZeG5tbY3Nmzfjvffew507dzBhwgRYWFigtLRU/pKFi4sLVq9eXeO4G7LAwED4+/vj4cOH+Pe//w1TU1MYGBigoKAATZs2xaJFi7Bs2TJdh0mkdfU2mdq/fz92795dK8+KjY2Vb0Do4OAAV1dXmJmZ4f79+wgLC0NYWBhmzpyJefPm1Up7jZ1sWq1t27bytSZV8fT0RFRUFCIjI5GTkyMfcfL19UWbNm3w448/4vLlyygpKcHLL78MX19f+Pv7Y/bs2QDKF3a/yNzcHJs2bcKZM2cQHByMK1euIDMzEwYGBmjTpg26du2K4cOHa5zAyM4YlE1Z9e3bV+lr4aNGjYKFhQXOnz+PO3fuQCQSoaCgAA4ODujatSsmTJhQ628d1qVu3brhxIkT2L9/PyIjI/HgwQPk5ubCwsICzs7O6N+/Pzw9PSvtY2VoaCg/BPe3337D9evXkZ+fDwcHB/Tp0wcBAQFwc3OrtTiHDx+O69evw8HBAYMHD67Rs7p164bQ0FD89NNPOHPmDJ48eQJDQ0O4ublh5MiR8Pf3l0/X6qtmzZrhwIED2Lx5M/744w88ffoU1tbWGDlyJObMmYOHDx/qOkQinRBI6+m7rL///jsSExPh5uYGNzc3LF26FDExMRqNTEVHR2P//v2YMmUKevXqVeHe8ePHsXDhQpSVleGXX35RuWkfaZdUKsVrr72GJ0+eYPfu3Rw9pEoCAgJw/vx5TJ8+vcK5eURE2lRvR6Zk6yFqQ//+/ZWucxg5cqT8sNIjR44wmapHQkND8eTJE1haWup88S3VPw8fPkR0dDQEAkGtfr0gIlJXvU2mtEn2yq+y17mp7vz444+wsLCAh4cHHB0dYWBggOzsbISEhMgPl500aZJaO1pT45efn48vv/xSPnqp6PxBIiJtYTIF4J9//gGAGr2qTZq5d+8ejh49iq+++gpCoRDm5ubyxcpA+dtTsnVTRLt27cLu3bshEolQUlICExMTTu8Rkc7pfTIlEonkeybJXrUn7Zk0aRIsLS0RFxcHkUiE3NxcWFtbw8XFBaNHj8bYsWPlm0gS5ebmIjk5GWZmZujRowcWLlyIDh066DosItJz9XYB+osmT56s8QJ0ZUpLS/Hee+8hOjoa/fv3x65du9SqL9uh28HBocrzxIiIqPErKyuDSCSCm5sbTE1NdR0OaYle/8j/+eefIzo6Gk5OTvjuu+/Urn/9+nW8/fbbdRAZERE1ZHv37q309nhNFBcXIzMzE7m5ufKTJKjuGRoaokmTJmjatKnKrVH0Npn66quvcODAATg4OGDXrl0arZeS1dm7dy+aN29e2yESEVEDk5qairfffrtW1+AWFxfj0aNHsLW1Rdu2bSEUCittmEu1TyqVQiwWIycnB48ePcJLL72kNKHSy2QqMDAQe/bsQdOmTbFr1y6FZ61Vh2xqr3nz5mjVqlUtRkhERA1ZbS79yMzMhK2tLezt7WvtmVQ1gUAAY2Njeb9nZmbCyclJYVm9O5tv1apV2LlzJ2xsbLBz504uXiUionotNzdX6TmlpB1WVlbIzc1Vel+vkqnVq1fj559/hrW1NXbu3IlOnTrpOiQiIiKVysrKIBQKdR2GXhMKhSrXqjWqZGrNmjXw8vLCmjVrKt1bv349tm/fDisrK+zYsUO+UScREVF9xzVSulVV/9fbNVM3btzAihUr5H++d+8eAGDdunXYsWOH/Ppvv/0m/71IJEJiYiJEIlGFZ0VGRmLLli0AgJdeeglBQUEK22zfvj1mzJhRa5+BiIiIGr96m0zl5eXhypUrla7LditXR3Z2tvz3169fx/Xr1xWW69OnD5MpIiIiUku9Tab69u2LO3fuqFUnMDAQgYGBla6PHz8e48ePr63QiIiIiOTqbTJFRI3D4sWLkZycjD179ug6FKJG64PZ85CWnq7rMKrN0d4eWzZuqJVnDR06FMnJyQCAGTNmYMGCBUrLLliwAMeOHQNQPhtVW1+XmEwRERE1cGnp6RBZN6A31NNv18ljQ0JCMH/+fIX7fOXl5SEiIqJO2m1Ub/MRkW5JJBLMnDkTkZGRSstcvHgR06ZNQ15enhYjI6LGzs3NDU+fPsVff/2l8H5oaCiKiorQtWvXWm+byRQR1ZqCggJYW1tj9uzZ+Pe//43Hjx/L72VmZmLJkiXw9/eHsbEx8vPzdRgpETU2srXRhw4dUnj/0KFDMDQ0xJgxY2q9bSZTRFRrLC0tsXLlShw+fBhSqRTe3t6IiYnBgwcP4OXlhcTEROzduxdbtmyBo6OjrsMlokakW7du6NChAyIjI5GTk1Ph3oMHDxAfH49BgwbV6rmJMkymiKjWOTs7Y+vWrZgxYwaSk5ORnp4ODw8P/Prrr3B3d9d1eETUSI0bNw7FxcXyReYystGqunqzn8kUEdW6+/fv49///je2bduGFi1awN7eHhEREfDz80N8fLyuwyOiRmrMmDEwNDSsMNVXVlaGkJAQ2NjYYOjQoXXSLpMpIqo1+fn5+PTTTzFq1CgAwLFjx9C3b1+0b98eJ06cQJs2beDn54c5c+YgLS1Nx9ESUWPj4OCAV199FVevXsX9+/cBAFFRUXj69Cl8fHxgbGxcJ+0ymSKiWmNqaor09HR8//33+PHHH9G6dWv5PTs7OwQGBiIoKAj5+fmwsLDQYaRE1FiNGzcOAHDw4EEA/5vik12vC0ymiKjWGBoaYsuWLfDw8FBaplevXtixYwcsLS21GBkR6YuhQ4fCxsYGhw8fRmZmJiIjI+Hs7Aw3N7c6a5PJFBERETUaxsbGGDVqFEQiET755BOUlJTA19e3TttkMkVEdSowMJBHyRCRVsmm9E6fPg0jIyP5Os66wmSKiIiIGhVXV1e4u7vDxsYGXl5esLOzq9P2eDYfwdvbG8ePH9d1GESk50aOHInQ0FBdh0GNxL59+7TWFkemiIiIiGqAI1PEnwSJiIhqgMkUERFRA+dobw+k39Z1GNXmaG9fa886deqUWuW9vLxw586dWmsfYDJFRETU4G3ZuEHXIeg1rpkiIiIiqgEmU0REREQ1wGSKiIiIqAaYTBERERHVAJMpIiIiohpgMkVERERUA0ymiIiIiGqAyRQRERFRDTCZIiIiIqoBJlNERERENVBvj5N58OAB/vzzT1y7dg3Xr1/HP//8A6lUig0bNsDLy0vj5x49ehT79+/HnTt3IJFI0K5dO/j6+sLPzw8GBswtiYiISD31Npnav38/du/eXavPXLFiBfbt2wcTExP0798fRkZGiI6OxhdffIHo6Ghs2LABhoaGtdomERERNW71NplydnbGtGnT4ObmBjc3NyxduhQxMTEaPy8sLAz79u2Dg4MDgoKC0LZtWwBAeno6pkyZgvDwcAQFBWHq1Km19AmIiIhIH9TbZGrixIm1+rytW7cCABYuXChPpADA3t4ey5cvx+TJk7F9+3ZMnjyZ031ERNSgzPxwLtKepes6jGpztLXH5nXf18qzhg4diuTkZJVlNm3aBA8Pj1ppT5F6m0zVptTUVNy4cQNCoVDheqs+ffrA0dERaWlpuHz5Mnr27KmDKImIiDST9iwduV5tdB1G9Z18WOuPHDRoEBwcHBTec3JyqvX2nqcXydTNmzcBAB07doSpqanCMl27dkVaWhpu3brFZIqIiKiBmTFjBvr27auTtvViPuvx48cAgBYtWigtI8taZWWJiIiIqkMvRqYKCgoAAGZmZkrLWFhYAADy8/O1EhMR1U8nTpzAsWPHFN7LzMwEADRt2lThfR8fH4wYMaJBtKnK+vXrkZCQoPBeRkaGPCZ1NW3aFHZ2dgrvpaSkKP36KxaLIRaLNWpTKBRCKBQqvNelSxesX79eo+cSPU8vkimpVAoAEAgEOo6EiBqyjIwMAMoTm8bSZkJCAuKvXAPMrCrfFBcDpcUaPTevJAOPMvIq3yjMgYnQEMUlxYBQwfY0EikglWjUZnGZGMXS0so3xGVITU3V6JlEL9KLZEo26iQboVJE9hORrCwR6acRI0YoHemZNWsWgPI3gxp6m1Uys4Jhe+2sPyl7cAFCQQnE9qYw9+2ulTYLgi8rHSUjUpdeJFMtW7YEUD6MrIzsJxRZWSIiImo4pkyZovD6uHHjEBgYWKdt60Uy1aVLFwDlQ9dFRUUK3+i7du0aAKBz585ajY2IiIhqTtnWCO7u7nXettJkauPGjbXWyOzZs2vtWZpwcnKCq6srbty4gZMnT2Ls2LEV7sfExCA1NRUODg7o0aOHboIkIiIijelyawSVyVRNF2xLpVIIBAKtJVNr1qxBeHg4Xn/9dSxYsKDCvRkzZmDevHlYvXo1evTogTZtyjc3y8jIwIoVKwAA06dP5+7nREREpBalydTYsWMVJlNSqRSRkZHIzc2FmZkZXF1d4ejoCKlUCpFIhOvXr6OwsBBWVlYYOnSoxgnZjRs35EkOANy7dw8AsG7dOuzYsUN+/bfffpP/XiQSITExESKRqNLzvLy84Ofnh/3792PUqFEYMGCA/KDjvLw8eHh4wN/fX6NYiYiISH8pTaYULdaSSqWYN28eCgoKMH/+fEyZMgXm5uYVyhQWFmL37t34/vvvUVBQgO+/1+zsnby8PFy5cqXS9X/++Uej5wHA8uXL4e7ujr179yImJgYSiQTt27eHr68v/Pz8OCpFREREalNrAfqePXsQHh6ORYsW4Z133lFYxszMDO+//z5MTEzw7bffIigoSKMRn759++LOnTtq1QkMDKxyxf6oUaMwatQoteMhItIXGRkZQGEOyh5c0E6DhTkQCw0BKNhjiqgBUCuZOnjwIAwNDeHn51dlWT8/P6xevRoHDhzg9BkREVVJIspDQfBltepIC0oAAAJzY7XbQjO1qhAppVYy9fDhQ1hYWMDExKTKsiYmJjA3N8fDh7V/MjQRNRw1OSoFqJvjUkg1Ozs7PMrI0+qmnVbmhmjVqpXadWXH3nRs1l69is2Ajh07qt0ekSJqJVPGxsbIyclBcnJylZtbPn78GDk5ObC2tq5RgETUeOniqBSqn1q1aqXRLu862yG+nnG0tQdONpzBC0db+1p71qlTp2rtWZpSK5nq0aMHzp49i+XLl2PTpk0wNlY8rCoWi7FixQoIBALu20Sk5+rlUSlEjczmdZq97EW1Q63X1z744AMYGBggKioKY8eOxe+//47ExETk5+cjPz8fiYmJ+P333zFu3DhERUXB0NAQM2fOrKvYiYiIiHROrZGpV155BatWrcInn3yCBw8e4LPPPlNYTiqVwsTEBCtXrkS3bt1qJVAiIiKi+kjts/m8vb3RrVs3bNmyBREREcjJyalw38rKCsOHD8f777+P1q1b11qgRESkRZpsjSAuLv+vsOqXlF5si6gh0+ig49atW+Obb77BN998g6SkpApv5DCBIiJq2DR9y03+Zl3HNlprk6g+0CiZel7r1q2ZQBERNSLz58/XqB5fKCB9xfNTiIiIiGpA45GpJ0+eICEhATk5OSgtLVVZduzYsZo2Q0REpPekUikEAoGuw9BbUqlU5X21k6krV67g66+/xrVr16pdh8kUUf2gajdyoOodyRvLbuTr16+Xr+9Rh6yObDpLHSkpKcjPz1e7XkFBAQBg+PDhatft0qUL1q9fr3Y9VVT9HaqqfzT9+6OLNusTAwMDSCQSGBry7EJdkUgkMDBQPpmnVjJ1/fp1TJ06FcXFxZBKpWjevDkcHR2Vbt5JRA2LvuxInpCQgPgr1wAzK/Uqist/Oo2/q+ZO04U5MBEaorikGBCq+Q3x/79+55UUqldPXIbU1FT16tSQnZ2dVtvTVZvaZmpqioKCAjRp0kTXoeitgoICmJmZKb2vVjK1ceNGFBUVwdnZGStXroSrq2uNAyQi7VG1GzmgZwuIzay0evacUFACsb0pzH27a6XNguDLdZJoVPV3qC7oos36xNLSEllZWbC0tORUnw5IpVJkZWXBwsJCaRm1FqDHx8dDIBBg9erVTKSIiIi0wNbWFqWlpXjy5Il8ZojqnlQqRXFxMZ48eYLS0lLY2toqLavWyFRxcTHMzc3h7Oxc4yCJiIioagYGBmjdujUyMzPx6NGjKl/6otpjZGQEa2trNGvWrPbWTL300ktITExEaWkpjIxqvEUVERERVYORkRGaNWuGZs2a6ToUUkCtjGj8+PEIDAxEZGQkPD096yomqmdUvUmjL29/ERERKaPWmqkpU6Zg0KBB+PzzzxEfH19XMVEDkpGRIX8DjIhI29LT0zFz5kx+HSKdUmtkavPmzejatSuuXr2KSZMmoVevXnBzc1O5wh0AZs+eXaMgSbdUvUmjV29/UaORkZGh2UG+mirMgVhoCID7BNW2nTt34sqVK9i5cycWLlyo63BIT6m9NYJAIJC/SRAbG4uLFy8qLS/bsZXJFBER1bb09HSEhoZCKpUiNDQUAQEBerHvFNU/aiVTY8eO5R4XRNTg2dnZ4VFGnvb3mdJKa/pj586d8h/uJRIJR6dIZ9RKpgIDA+sqDiIiIrX88ccfEIvLU1SxWIywsDAmU6QTai1AJyIiqi+GDx8OoVAIABAKhXzLnHSGyRQRETVIAQEB8qUnBgYGCAgI0HFEpK+YTBERUYNkb28Pb29vCAQCeHt7c/E56YzSNVOdO3cGALRv3x6hoaEVrqlDIBDg5s2bGoZHRNR4SER5KAi+rFYdaUEJAEBgbqx2W9CDzbIDAgKQmJjIUSnSKaXJlOwNiecPVNTkcEUeyEhEBJiZmaFjx45q10tISAAAdGzWXr2KzaBRew2Nvb09Nm/erOswSM8pTaYiIyPLCzx3Bp/sGhERqadVq1YabW7bkDbGTU9Px2effYYvv/xSa1Nud+/exaxZs7BlyxZ06NBBK20SvUhpMtWyZctqXatrR48exf79+3Hnzh1IJBK0a9cOvr6+8PPzU3mCsyKpqanYvn07oqKi8OTJE0ilUjg5OaFfv36YPn06WrduXUefgqhxW79+vXwERR2yOrKEQV0dO3bE/PnzNapLtU8Xu5GvWLEC+fn5+Pzzz7F3716ttEn0IrX2mdK2FStWYN++fTAxMUH//v1hZGSE6OhofPHFF4iOjsaGDRtgaFi94xlu3ryJqVOnIicnB82bN8egQYMAANevX8d///tfHD16FD///DN69uxZlx+JqFFKSEhA/I2rMHCwVKueVFgGALjy9IHabUpEeWrXobqji93I7969i8TERABAYmIi7t27x9Ep0ol6m0yFhYVh3759cHBwQFBQENq2bQug/B/slClTEB4ejqCgIEydOrVaz/viiy+Qk5ODN954A5999pl8bxKxWIzPP/8cwcHBWL58OY4cOVJXH4m04MSJEzh27JjCe5mZmQCApk2bKrzv4+Oj9AzChkTTUSJA85GihIQEGDhYwty3u0btakLdhdyVaHI2n7i4/L9CE7Xbaux0sRv5ihUrKvyZo1OkKyqTqdjY2FpppHfv3mrX2bp1KwBg4cKF8kQKKF9suHz5ckyePBnbt2/H5MmTq5zuKy4uRnx8PABg7ty58kQKKN/obd68eQgODsadO3dQWFgIMzMzteOl+k92qryyZKqxSEhIQPyVa4CZlfqVxeXfDOPvPlSvXn4eDKyt1W9PRzRdmC1fDN6xjdbabCh0sRu5bFRK2Z+JtEVlMjV58uQan8WnydYIqampuHHjBoRCIby8vCrd79OnDxwdHZGWlobLly9XOTVnYGAAIyMjlJaWKny7UPYZzc3NYWpqqlasVL+MGDFC6ehSQ1rIW2NmVlo7dw4Aym6Ea62t2qDpOiu9+jukpuHDh+Po0aMoLS2FkZGRVnYjb9euXYUEql27dnXeJpEi1VrBLZVKNf4lkUjUDkqWfHXs2FFpctO1a1cAwK1bt6p8nlAoRL9+/QAAP/zwg/ynJ6D8J6j169cDAHx9fXmQMxGRBgICAuRf7yUSiVb2ffr8888r/PnFaT8ibanWmqmWLVti9OjRGDNmjFbeeHv8+DEAoEWLFkrLODk5VShbleXLl+O9997Db7/9hnPnzsHNzQ0AcO3aNeTk5GDKlCn4z3/+U8PIiYhIW5ydneWjU+3atePic9IZlcnU4sWLceTIEdy8eRM//vgjfvzxR/Ts2RNjx47FiBEjYGmp3ps71VVQUAAAKtcuWVhYAADy8/Or9czWrVtj//79WLRoEc6dO4fU1FT5PTc3N/Tu3bvCWqr6igus6x/+PyEqX4BuYGAAiUQCAwMDrW2P8Pnnn2PWrFkclSKdUplMvfPOO3jnnXdw7949HDx4EMeOHUNcXBwuXbqEr776CkOHDsWYMWMwePBgtfd8UkW2rqk2p9wuXbqEOXPmwNLSEps3b0bPnj0hlUpx6dIlfPvtt5gzZw7mzJmD2bNn11qb2qYvC6wbEl38P8nIyNDsTbWakJTKjz0h/fTHH3+gtLQUAFBaWqqVBehA+ehUeHjDWrNHjU+1pvk6dOiA//znP/j4449x/vx5HDp0CJGRkThx4gROnjyJpk2bwsfHB6NHj4arq2uNg5KNOslGqBSRjUjJyqqSk5ODWbNmobCwEL/++muFqUoPDw907NgRo0ePxpYtW+Dj41Ph7cH6hgus6x/+PyEqX4B+7NgxiMViCIVCrSxAJ6ov1NpnSiAQYODAgRg4cCAKCgpw8uRJhISE4OLFi/jll1+we/dudOjQAQsWLMC//vUvjYOS7bSekpKitIxsmq46u7KfOXMGmZmZ6Nevn8I1X23atEG3bt0QExODmJiYep1MEVXFzs4OjzLytP42n7oH8VLjEhAQgNDQUADlb1Dz4GHSJxrPzZmbm2P8+PHYvXs3Tp06hZkzZ8LQ0BD37t1DTExMjYLq0qULgPI9XYqKihSWuXbtGgCgc+fOVT7vyZMnAIAmTZooLWNlVb4nT1ZWljqhEhERyvcA9Pb2hkAggLe3t9bO5iOqD2q80OnixYvYvHkzgoKC5Ps41XT9lJOTE1xdXSEWi3Hy5MlK92NiYpCamgoHBwf06NGjyuc1a9YMAHDjxo0K2yLIiMVi3LhxA0D5YaRERKS+gIAAvPLKKxyVIr2j0XEyjx49wuHDh3HkyBE8fvwYUqkURkZGGDp0KMaOHYvXXnutxoHNmDED8+bNw+rVq9GjRw+0aVO+43BGRob8rY3p06dXSNzWrFmD8PBwvP7661iwYIH8+uDBg2FmZoaUlBSsXLkSixcvhrFx+ZRESUkJvv76azx58gTW1tZ49dVXaxw7EZE6VL0RWtURP/XpjVB7e3ts3rxZ12EQaV21k6mcnBwcP34cISEhuHLlCoDyt+66du2KsWPHwtvbGzY2NrUWmJeXF/z8/LB//36MGjUKAwYMkB90nJeXBw8PD/j7+1eoIxKJkJiYCJFIVOG6nZ0dPv/8cyxduhR79+5FeHi4fKH89evXIRKJYGxsjG+++UblVCARkbZxuoyo/lOZTJWVleHMmTM4fPgwzpw5A7FYDKlUihYtWmDUqFEYM2YM2rdvX2fBLV++HO7u7ti7dy9iYmIgkUjQvn17+Pr6ws/PT63pxHHjxsHZ2Rm//PILLl68iL/++gsA4OjoiAkTJiAgIIAbvhGRTqh6I5SI6j+VydSgQYOQlZUFqVQKCwsLeHt7Y8yYMfKjWbRh1KhRGDVqVLXKBgYGIjAwUOl9V1dXrFq1qrZCIyIiIlKdTD179gwCgQAtWrTAsGHDYGZmhvPnz+P8+fNqNfLRRx/VKEgiIiKi+qpaa6aePHmCoKAgtR8ulUohEAiYTBEREVGjpTKZ6t27t7biICIiImqQVCZTe/bs0VYcRERERA1S7Z1OTERERKSHmEwRERER1QCTKSIiIqIaYDJFREREVANMpoiIiIhqgMkUERERUQ0wmSIiIiKqgWrtgE5EpJJUAokoDwXBl7XWpESUhwzDDK21R0SkjNJkasqUKbCxscH3338vv5aSkgJDQ0M4OjpqJTh9tX79eiQkJKhdT1Zn1qxZatft2LEj5s+fr3Y9IiIifac0mYqJiYG9vX2Fa0OHDoWDgwP+/PPPOg9MnyUkJCD+yjXAzEq9imIpACD+7kP16hXmqFee6EUCAxg4WMDct7vWmiwIvgw7OzuttUdEpIzSZMrIyAhisbjSdalUWqcB0f8zs4Jh+75aaarswQWttENERNQYKU2m7O3tkZaWhqSkJLRu3VqbMZEOPH78WKPpQU4tEhGRvlOaTA0cOBDBwcGYOHEi+vbtC3NzcwBAXl4elixZUu0GBAIBvvnmm5pHSnWqsLAQ8TeuwsDBUq16UmEZAODK0wdq1ZOI8tQqT6QtJ06cwLFjxxTeq+qHBx8fH4wYMaLOYiOi+klpMvXhhx8iPj4eDx48QFhYmPx6UVERDh06VO0GmEw1HAYOllpb86LNt76IagvXaBGRIiqn+Y4ePYqoqCgkJCSgqKgIGzduhLm5Od59911txkhEpDUjRozg6BIRqUXlPlOGhoYYMmQIhgwZAgDyZGr27NlaCY6IiIiovlNr086xY8eiSZMmdRULERERUYOjVjIVGBhYV3EQERERNUg1Ok7m6tWruHHjBjIzMwEATZs2haurK7p161YrwRFRw6HJcTLSghIAgMDcWKP20EztakREtU6jZOro0aNYv349UlJSFN5v1aoV5s+fD29v7xoFR0QNhIEhLI2F6NisvVrVZFsNqFsPANCsfK8yIiJdUzuZWrduHbZt2ybfCd3R0RHNmzcHAKSmpso3+ly4cCHu3r2LDz/8sHYjJqL6x8QCHTu2waZNm9SqJtuvSd16RET1iVrJ1N9//42tW7cCALy9vTF79my0a9euQpl//vkHP/zwA0JDQ7Ft2zYMGDAAfftq51gUIiIiIm0zUKdwUFAQBAIBJk+ejDVr1lRKpACgbdu2WLNmDfz9/SGVSrFnz55aC5aIiIiovlErmbp8+TIEAkG19pmaPXs2DAwMEB8fr3FwRERERPWdWtN8WVlZaNKkCaytrassa2NjgyZNmiAnJ0fj4IDyxe779+/HnTt3IJFI0K5dO/j6+sLPzw8GBmrlggDKj8PZs2cPTp48iYcPH0IsFsPOzg5ubm6YOnUq3N3daxQvERER6Re1kikbGxtkZmYiKysLNjY2KstmZWUhNzcXTZs21Ti4FStWYN++fTAxMUH//v1hZGSE6OhofPHFF4iOjsaGDRtgaGhY7eclJSVh2rRpePjwIezs7NC7d28YGxsjOTkZp06dQqdOnZhMERERkVrUSqa6d++OyMhIbNq0CUuXLlVZduPGjZBIJOjevbtGgYWFhWHfvn1wcHBAUFAQ2rZtCwBIT0/HlClTEB4ejqCgIEydOrVazysoKMC7776LR48eYebMmZg5cyaEQqH8/rNnz5CVlaVRrI2BWCyGRFSotQOIJaI8ZBhmaFR3/fr18lfq1SGrI3uDTB0dO3bE/Pnz1a5HRESNn1rJlL+/PyIiIhAUFIRnz57hgw8+wMsvv1yhzLVr17B161ZERkbKF6trQvbW4MKFC+WJFFB+APPy5csxefJkbN++HZMnT67WdN+WLVvw6NEjjB07FvPmzat039bWFra2thrFStqVkJCA+CvXADMr9SqKy7fziL/7UL16hTl4/PgxEzgiIlJIrWSqX79+eP/997F161aEhoYiNDQUTZs2haOjI0pKSpCSkoLCwkIAgFQqxQcffKDRtgipqam4ceMGhEIhvLy8Kt3v06cPHB0dkZaWhsuXL6Nnz54qn1dSUoLffvsNADBjxgy149EHQqEQYmtTmPt210p7BcGXYWdnp/kDzKxg2F47W26UPbiAwsJCxN+4CgMHS7XqSoVlAIArTx+oVU8iylOrfCWFOSh7cEH9euLi8v8KTdRuj4hIX6m9aeeHH34IZ2dnbNiwAY8ePUJGRgYyMipO17Rp0wbz5s3DyJEjNQrq5s2bAMp/Mjc1NVVYpmvXrkhLS8OtW7eqTKZu3LiBrKwsODk54eWXX8alS5dw5swZZGVlwd7eHq+++ip69OihUaykPwwcLLWabGqqJruCy3ck79hGq+0SETVkGh0n4+3tDW9vb9y6dUvh2XydO3euUVCPHz8GALRo0UJpGScnpwplVbl79y6A8iRv8eLFOHToUIX7mzZtgqenJ1atWqU0eSNqKGoyNcgdyYmI1Fejg447d+5c48RJkYKCAgCAmZmZ0jIWFhYAgPz8/Cqfl52dDQC4ePEiysrK8O6778LPzw82NjaIjY3FihUrEBYWBgsLC6xcubIWPkHNZGRkaD5No4nCHIiFhgCq/2YkERERlVN/oyYtkJ37JxAIauV5EokEAFBaWooJEyZg0aJFeOmll2BlZYVhw4Zh06ZNEAgECAkJQVJSUq20SURERPqhRiNTdUU26iQboVJENiIlK1ud5wHAG2+8Uel+165d4erqiuvXr+PChQto3bq1uiHXKjs7OzzKyNPqAmuhoARirbRGRETUuNTLkamWLVsCAFJSUpSWSU1NrVC2Os8DgFatWiksI7uenp5e7TiJiIiI6mUy1aVLFwDlbxYVFRUpLHPt2jUAqNaaLVdXV/nvnz17prCM7Lq5ublasRIREZF+q5fJlJOTE1xdXSEWi3Hy5MlK92NiYpCamgoHB4dqbWng6OiIV155BQDw999/V7qfnZ0t347Bzc2thtETERGRPqmXyRTwv801V69ejYcP/7djdUZGBlasWAEAmD59eoXdz9esWQMvLy+sWbOm0vP+/e9/Ayh/5fvWrVvy68XFxVi+fDlyc3Ph6urK/aaIiIhILfVyAToAeHl5wc/PD/v378eoUaMwYMAA+UHHeXl58PDwgL+/f4U6IpEIiYmJEIlElZ43dOhQvPvuu9ixYwcmTpyIV155BTY2Nrh69SqePn0KR0dHrF27ttbeICQiIiL9UG+TKQBYvnw53N3dsXfvXsTExEAikaB9+/bw9fWFn59ftc7ke96iRYvQs2dP7NmzB7du3UJhYSFatGiBgIAAzJgxA02bNq2jT0JERESNlVrJ1Lp16zBhwgStbh0watQojBo1qlplAwMDERgYqLLM66+/jtdff702QqtbmmzaWZNz1cy58zsREZEm1Eqmtm7dim3btqFXr17w9fWFl5cXj1+pA5qecVaTc9UeP36MApRo1C4REZE+UyuZ6tWrF+Li4hAbG4uLFy/iq6++wsiRI+Hr6yt/W45qTtOz1WpyrtqsWbOQ8fSBRu0SERHpM7WSqaCgICQlJeHAgQM4cuQInjx5gt9//x2///472rdvjwkTJmDMmDFce0REcidOnMCxY8cU3pONpsp+EFDEx8cHI0aMqJPYiIhqg9pbI7Ru3RoffvghTp06hZ9++gmenp4QCoW4f/8+Vq1ahcGDB2POnDk4ffq0/Ew8IiJF7OzsYGdnp+swiIhqROO3+QQCAQYNGoRBgwYhOzsbR48eRXBwMG7duoXw8HBERETAzs4O48aNw/jx49GuXbvajJuIGogRI0ZwZImIGrVa2bTT2toa/v7+OHToEEJCQtCzZ09IpVJkZGTgp59+wsiRIzF58mRERETURnNERERE9Uat7TOVkZGBw4cP4+DBg7h//z4AQCqVom3btnj06JF80Xrv3r3xww8/wNrauraaploiEeWhIPiyWnWkBeVvAArMjdVuC83UqkJERFQv1SiZKisrw+nTpxEcHIw///wTZWVlkEqlsLGxwZgxYzBx4kR06NABqamp+PXXX7Fnzx7ExsZizZo1+OKLL2rrM1AtqPF2DM3aq1exmeZtEhER1ScaJVN3797FwYMHceTIETx79gxSqRQCgQD9+vXDxIkT4eHhAWPj/41UNG/eHPPnz8fw4cPh6+uLU6dOMZmqZ3SxHYOmMjIyNNvUVFOFORALDQEYaqc9IiJqUNRKpvbu3YuDBw/i5s2bAMqn8Zo1a4Zx48ZVa2f0Ll26wN7eHunp6ZpHTERERFSPqJVMffnllwAAQ0NDDBkyBBMnTsSQIUPUOiOvVatWEAqF6kVJ9Bw7Ozs8ysiDYfu+Wmmv7MEFCAUlEGulNSIiamjUSqZat26NCRMmYPz48XBwcNCowf3792tUj4iIiKg+UiuZ+v777yEQCGBubl5X8RARERE1KGolU+PGjYOBgQGioqJgYWFRVzERERERNRhqJVNNmjSBgYEBz94jIiIi+n9q7YDetm1b5Ofno7i4uK7iISIiImpQ1EqmxowZg9LSUoSEhNRROEREREQNi1rTfG+//Taio6PxzTffwMDAAL6+vmpti0BERETU2KiVTH3yySewsrKCoaEhPvvsM6xduxZubm5o2rSp0qRKIBDgm2++qZVgiXRFLBZDIipU++xCTUlEecgwzNBKW0REVDNqJVOHDh2CQCCAVCoFADx79gx//vmnyjpMpoiIiKgxUyuZmj17dl3FQVSvCYVCiK1NYe7bXSvtFQRfhp2dnVbaIiKimmEyRURERFQDXD1OREREVANqjUyR7p04cQLHjh1TeC8hIQEAMGvWLIX3fXx8MGLEiDqLjYiISB9plEyJxWIcPXoUJ06cwM2bN5GVlQUAsLGxQZcuXTBy5Ej4+PhAKBTWZqxUBa6xISIi0j61k6lHjx5h1qxZuHfvnvytPpmMjAz8+eefiIqKws6dO7Fx40a89NJLtRYsASNGjODoEhERUT2iVjKVl5eHd955BykpKTAyMoKnpyf69euH5s2bAwBSU1Px999/IywsDHfv3kVAQAAOHz4MS0vLOgmeiIiISNfUSqZ27tyJlJQUtGjRAtu2bUOHDh0qlZk4cSL+/e9/4/3330dKSgp27drFtwCJiIio0VLrbb7w8HD5JpyKEimZjh074uuvv4ZUKsUff/xRowCPHj2KSZMmwd3dHT169MD48eOxd+9eSCSSGj0XANauXQsXFxe4uLjg559/rvHziIiISP+oNTKVlJQEU1NT9OvXr8qy/fv3h5mZGZKSkjQObsWKFdi3bx9MTEzQv39/GBkZITo6Gl988QWio6OxYcMGGBoaavTsq1ev4qeffqqwozsRERGRuurt1ghhYWHYt28fHBwcEBQUhLZt2wIA0tPTMWXKFISHhyMoKAhTp05V+9klJSVYsmQJ7Ozs0K1bN0RERNRy9ERERKQv1Jrme+mll1BUVITo6Ogqy0ZHR6OwsBCtW7fWKLCtW7cCABYuXChPpADA3t4ey5cvBwBs375do+m+DRs24N69e1ixYgWaNGmiUXxEREREgJrJlIeHB6RSKZYuXYr79+8rLXf79m0sXboUAoEAw4cPVzuo1NRU3LhxA0KhEF5eXpXu9+nTB46OjhCJRLh8+bJaz75y5Qp27twJHx8fDB06VO3YiIiIiJ6n1jRfQEAADh06hJSUFIwZMwYeHh7o27cvHB0dUVJSgpSUFFy4cAHnzp2DVCpFy5Yt8c4776gd1M2bNwGUL2Q3NTVVWKZr165IS0vDrVu30LNnz2o9t7i4GIsWLYK1tTWWLl2qdlxEREREL1IrmbK0tMTOnTsxZ84c3L17F2FhYQgLC6tQRraY28XFBT/88INGe0w9fvwYANCiRQulZZycnCqUrY5169YhMTER69atQ9OmTdWOi4iIiOhFai9Ab9OmDYKDg3H8+HGEhYXh5s2byMzMBAA0bdoUXbp0gaenJ0aOHKnxcTIFBQUAADMzM6VlLCwsAAD5+fnVeualS5fwyy+/wMPDAyNHjtQoLiIiIqIXafQ2n1AoxJgxYzBmzJjajgfA/0a3BAJBrTyvqKgIS5YsgaWlJT7//PNaeSYRERERoOYCdG2RjTrJRqgUkY1IycqqsnbtWvzzzz9YvHgxmjVrVjtBEhEREaEG+0yVlpbixo0bePLkCYqKijB27NhaC6ply5YAgJSUFKVlUlNTK5RVJSIiAgYGBggJCUFISEiFew8ePAAA7N+/H2fOnMFLL72Er7/+WsPIiYiISN9olExt27YNP//8M3JycuTXnk+mcnJy4Ofnh5KSEvz3v/9Ve7F3ly5dAAAJCQkoKipS+EbftWvXAACdO3eu1jMlEgliYmKU3k9KSkJSUlKFz0T1WGEOyh5cUK+OuLj8v0ITtduCueK3SomIiNROphYsWIDjx48DAFq3bo2UlBSUlZVVKGNlZYU+ffrg119/RUREBN544w212nBycoKrqytu3LiBkydPVhr1iomJQWpqKhwcHNCjR48qn3fq1Cml9xYvXoxDhw7hP//5D6ZNm6ZWnKQbHTt21KheQkLC/9dvo3bdx48fowAlGrVLyqWnp+Ozzz7Dl19+CTs7O12HQ0SkEbWSqdDQUISGhqJZs2bYuHEjunXrhkGDBiEjI6NSWR8fH+zfvx+RkZFqJ1MAMGPGDMybNw+rV69Gjx490KZN+TfAjIwMrFixAgAwffp0GBj8b9nXmjVrEB4ejtdffx0LFixQu01qGObPn69RvVmzZgEANm3apFHdjKcPNGqXlNu5c6d8I92FCxfqOhwiIo2olUwdOHAAAoEAS5cuRbdu3VSW7dq1KwwMDHDnzh2NAvPy8oKfnx/279+PUaNGYcCAAfKDjvPy8uDh4QF/f/8KdUQiERITEyESiTRqk0gViSgPBcGX1aojLSgfzRKYG6vdFhr5uxLp6ekIDQ2FVCpFaGgoAgICODpFRA2SWsnUzZs3YWBggNdee63KssbGxmjSpIl8DypNLF++HO7u7ti7dy9iYmIgkUjQvn17+Pr6ws/Pr8KoFFFdqvHUYrP26lVspnmbDcXOnTvl26BIJBKOThFRg6VWMlVQUAAzMzMYG1fvp+ySkhIYGhpqFJjMqFGjMGrUqGqVDQwMRGBgoFrP16QO6R9dTC02dn/88QfEYjEAQCwWIywsjMkUETVIag3tNG3aFPn5+cjLy6uybEJCAgoLC+Ho6KhxcETUeA0fPlx+SoJQKISnp6eOIyIi0oxayZTsQOHQ0NAqy27atAkCgQB9+/bVLDIiatQCAgLkpxwYGBggICBAxxEREWlGrWk+f39/nDhxAt9//z1cXV3h5uZWqUx2djZWrVqFkydPwsDAoNIicaLG5sSJEzh27JjCe7I1U7Lpvhf5+PhgxIgRdRZbfWZvbw9vb2+EhITA29ubi8+JqMFSK5lyd3fHtGnT8PPPP+Ott96Cu7u7fMrv22+/xb179xAbG4vi4vLNEefOndvoF9ESqcIEQbWAgAAkJiZyVIqIGjS1N+38+OOP0axZM2zYsAEXLvxvB+pdu3bJ38wxMzPDggULOCpFemHEiBF6O7pUU/b29ti8ebOuwyAiqhGNjpOZOnUqxo8fj7CwMMTHx0MkEkEikcDe3h7du3eHl5cXbGxsajlUIiIiovpH44OOmzRpggkTJmDChAm1GQ8RERFRg8JdL4mIiIhqgMkUERERUQ1oNM137tw5hIWFISEhAdnZ2SgtLVVaViAQICIiQuMAiaj2qNrGAeBWDkREmlArmRKLxfjwww8RGRkJAPK391SRbcpHRPUft3IgIlKfWsnU9u3bERERAYFAgCFDhsDDwwOOjo4wMTGpq/iIqBZxGwciotqnVjJ19OhRCAQCfPTRR5g+fXpdxURERETUYKi1AD05ORkGBgaYPHlyXcVDRERE1KCoNTJlZWWFkpISmJqa1lU8RERERA2KWslU7969cfLkSTx58gROTk51FRPVMzzIl4iISDm1pvk++OADmJiYYPXq1XUVDzUwdnZ2fAOMiIj0mlojU87Ozti0aRM+/PBDvPfee5g+fTq6du0Kc3PzuoqP6gG+AUZERKSc0mSqc+fOKiv+9ddf+Ouvv6psQCAQ4ObNm+pHRkREAIDFixfj0KFDmD17NubMmaPrcIjoBUqn+aRSaa38kkgk2vw8REQVLF68GC4uLlX+2rVrl65DpVowduxYuLi4IDMzU35ty5YtcHFxwW+//abDyKgxUzoyJdvlnIioMRAKhbC2tlZ6n8sVGr68vDzcvXsX7dq1Q9OmTeXX4+LiAADu7u66Co0aOaXJVMuWLbUZBxFRnerRowf27Nmj6zCoDsXHx6OsrAy9evWSX5NIJIiPj4eNjQ3at2+vw+ioMVP5Nt+UKVMwd+5cbcVCRESkMdkI1PPJ1O3bt5GXl4eePXvyrFiqMyrf5ouJiYG9vb22YiEiIjUlJSUhPDwcZ8+eRVJSEkQiEUxMTNC+fXt4eXlh0qRJCjdaPnjwIJYsWYI+ffpgz549OHLkCH777TckJCQgKysLmzZtgoeHBwCgrKwMe/bsQXBwMB4+fAhzc3O88sormDFjBtzd3eHi4gKgfHlIq1atKrWVmZmJnTt34syZM3j8+DGkUilatWqFYcOGISAgADY2NrXSF4qm8y5evFjpGlFtU2trBCIiql/mzZuHGzduACh/e7pJkybIzc3FlStXcOXKFYSGhuKXX36BpaWl0md89dVX2LNnDwwMDNCkSRMYGPxv0kIsFmPmzJk4d+4cAMDIyAhlZWU4c+YMoqKisHbtWpXxXbx4EbNmzUJWVhaA8rVrhoaGSEhIQEJCAg4fPowdO3aoPQWXmpqKSZMmVboGAFOnTpVfk7X7888/Y9++ffLrp06dUqs9IlWYTBERNWBdunTBmDFj8Nprr6F58+YwNjZGSUkJoqKi8O233+L69etYs2YNPv/8c4X1r1+/jtjYWMyZMwdTpkyBlZUV8vLyUFxcDKD8Tbhz587B0NAQixYtwptvvglTU1MkJyfjyy+/xLJly5TGlpycjA8++AA5OTmYOHEi3n33XbRt2xYCgQD37t3Dt99+iz///BNz5szBkSNHYGhoWO3PXVpaiuTkZKXtvuj5t/uIahuTKWpUePQNKRMfH4+BAwcqvDd48GCsXLlSrefJprY0cefOHY3rvuirr76qdM3Y2BhDhw5Fx44d4eXlhUOHDuE///kPzMzMKpUtKCjA+++/j9mzZ8uvWVpawtLSEvn5+di5cycAYO7cuRVGfFq2bIkffvgBEyZMQE5OjsLY1q1bh5ycHEyePLlS0tWxY0ds3rwZEydOxO3btxEeHg4vL69qf+5WrVpV6Mdt27ZhzZo1+PTTT+Hv7w8AePDgAUaMGIF+/frhl19+qfazidTFZIr0Bo+90W9isRjp6ekK72VnZ6v9vIawnrR169bo0KEDbt++jVu3bqFnz56VyhgaGuKdd95RWD8qKgoFBQUwMTHB5MmTK90XCoUICAjAokWLKt0rKirCyZMnAQABAQEKn29sbAxPT0/cvn0b58+fVyuZepFsbdTzi88VLUgnqgtVJlN5eXlYsmSJxg0IBAJ88803GtcnUgePviFlZAuta0t1ToDQlr/++gvBwcG4evUqRCIRioqKKpV5+vSpwrovvfRShT2Znic7vaJz586wsLBQWEbZwu7r169DLBYDAN544w2lsctiffLkidIyVZFtf2BlZQVnZ2f5de4vRdpSZTJVXFyMkJAQjR4ulUprnEwdPXoU+/fvx507dyCRSNCuXTv4+vrCz8+vwiJJVcRiMS5evIizZ8/i0qVLSElJQVZWFmxtbdGjRw+8/fbb6Nu3r8YxEhHpimzxuIxQKISNjQ2MjMq/vGdnZ0MsFqOwsFBhfWWJFAA8e/YMAODg4KC0jKOjo8LrzydvykYEn6coAayuO3fuICcnB//6178qfF+Ii4uDkZERXnnlFY2fTVQdVSZTRkZG6N69uxZCqWzFihXYt28fTExM0L9/fxgZGSE6OhpffPEFoqOjsWHDhmotWIyNjZUPMzs4OMDV1RVmZma4f/8+wsLCEBYWhpkzZ2LevHl1/ZGIiGrN2bNnsWfPHhgaGmLmzJkYPXo0WrduXWE/pUmTJiEuLg5SqVThM9RZ9K0OWXvW1taIiYmp1Wf//PPP2LFjh/zPJSUlAIALFy5UWBeXnp4OAwMDDB8+XH5txIgRKhfNE2miymTK2tpaJ7sGh4WFYd++fXBwcEBQUBDatm0LoPwfx5QpUxAeHo6goKAKCyKVEQgE8PT0xJQpUyrNnR8/fhwLFy7E5s2b0bdvX/Tr168uPg4RNTLKFrNXR21NEcrWJE2YMKHCAvLnZWRkaPx8W1tbAIBIJFJaRtn0oWyNYnZ2NkQikcrRLXUVFBQoHO0qLCysNAInkUgqlM3Ly6u1OIhk6u0C9K1btwIAFi5cKE+kgPJFn8uXL8fkyZOxfft2TJ48ucrpvv79+6N///4K740cORJ//fUXDhw4gCNHjjCZIqJqqc7UVV1LS0sDUL49giLJycl4+PChxs+XPffWrVvIz89XuG5KtvD7RW5ubjAyMkJpaSn++OMPvP322xrH8aI5c+Zgzpw58j8PGTIEWVlZiI2NhbGxMQDgyy+/RFBQUIXNR4nqSr1MplJTU3Hjxg0IhUKFb3f06dMHjo6OSEtLw+XLlxW+oaIO2RcM2RcmIqKq1Ob2BpqSbcR59+5dhffXrl2rdHqvOgYOHAhzc3MUFBRg7969mDFjRoX7paWlSrccsLS0xPDhw3H8+HFs2bIFnp6eSt+ALC0tRXFxsdJF7qokJSUhNTUVffr0kSdSQPnyDoFAwMXnpBXVW8GtZbI3SDp27KjwGAQA6Nq1K4Dyn5hq6p9//gGgepElEVF9I5tq/O9//4sDBw7I1w6lpKRg0aJFCA0NhbW1tcbPt7S0lC+l2LBhA/bs2SNfKJ6SkoK5c+fi8ePHSusvWLAANjY2EIlEeOuttxAeHi6PEQAePnyIXbt2YeTIkbh+/bpGMcbGxgIAevfuLb+Wk5ODhIQEdOzYUT5VSVSX6uXIlOwfZ4sWLZSWcXJyqlBWUyKRCIcOHQKACosUiYjqu3HjxuHgwYO4fPkyli5dis8++wwWFhbyTTTnzp2Lv//+u0YLwGfOnIlr164hKioKX331Fb799luYm5sjOzsbQqEQ69atk6/Xen5kCCjfWHP79u2YNWsWkpKSMHv2bBgZGcHS0hIFBQUVEitNDyGWJVMv7i8lkUi4vxRpTb0cmSooKAAAhbv1ysiGg/Pz8zVup7S0FB9//DFyc3PRv39/DB06VONnERFpm7GxMXbu3IkZM2agdevWMDAwgKGhIQYOHIgff/xR6W7/6raxdetWLF68GM7OzhAIBDAwMMBrr72GoKCgCtvKWFlZVarfrVs3nDhxAgsXLkSPHj1gYWGB3NxcmJqaws3NDdOnT8eBAwfQp08fjeKLjY2t9Na5bB3X86NVRHVJIK3JhHod2bJlC9avX4/Ro0fju+++U1hm3bp1+PHHH/Hmm2/iiy++0KidpUuX4sCBA3BycsLvv/+u9jTf48ePMWzYMKUnpRMRNXbR0dF455130LJlSx4eDH5f0Ff1cmRKNuokG6FSRDYipcmCRaB8o7sDBw7AwcEBu3bt4nopIiIN/PTTTwCAAQMG6DgSIt2pl8lUy5YtAZQvcFQmNTW1Qll1BAYGYs+ePWjatCl27dpVYesFIiL6n7KyMsydOxfnzp1Dbm6u/HpCQgLmzp2LqKgoCIVChWf3EemLerkAXbZVQUJCAoqKihS+0Xft2jUA5WdGqWPVqlXYuXMnbGxssHPnTnTo0KHmARMRNVJSqVR+UgRQ/oZfWVmZfHNMAwMDfPrpp3BxcdFlmEQ6VS9HppycnODq6gqxWCzf4fd5MTExSE1NhYODA3r06FHt565evRo///wzrK2tsXPnTnTq1Kk2wyYianQMDQ3x+eefY9iwYWjdujUkEgnKysrQsmVLjBkzBgcOHMCbb76p6zCJdKpejkwBwIwZMzBv3jysXr0aPXr0QJs2bQCUH42wYsUKAMD06dMr7H6+Zs0ahIeH4/XXX8eCBQsqPG/9+vXYvn07rKyssGPHDqU7BhMR0f8IBAJMmjQJkyZN0nUoRPVWvU2mvLy84Ofnh/3792PUqFEYMGCA/KDjvLw8eHh4wN/fv0IdkUiExMTESudIRUZGYsuWLQCAl156CUFBQQrbbN++faUdfomIiIhUqbfJFAAsX74c7u7u2Lt3L2JiYiCRSNC+fXv4+vrCz8+vyjP5ZLKzs+W/v379utKddvv06cNkioiIiNRSL/eZaii4nwgRET2P3xf0U71cgE5ERETUUDCZIiIiIqoBJlNERERENcBkioiIiKgGmEwRERER1QCTKSIiIqIaYDJFRERaNXnyZLi4uODgwYMVrj9+/BguLi48548aHCZTRETUaH3zzTdwcXHBiRMn5Nfi4uLg4uJS6dgxIk0xmSIiokYrLi4OANCrV69K19zd3XUSEzU+TKaIiKhRKigowO3bt9GmTRs4ODjIrzOZotrGZIqIiBqlK1euoLS0tELSJJFIcOnSJVhZWcHZ2VmH0VFjUq8POiYiqqmhQ4ciOTkZu3fvRuvWrbFp0yZERUUhMzMTDg4O8PT0xMyZM9GkSRNdh1ql27dvY8eOHbh48SKePn0KoVCIpk2bom3btnj11Vfx5ptvwszMTF7++c/erl07bNy4EWfPnsWzZ8/QsmVLvPnmm5gyZYr80PgTJ05gz549uHv3LiQSCXr16oWFCxcqTDpKSkpw/vx5RERE4OrVq0hLS0NBQQHs7e3Rs2dPBAQEwM3NTWt9o4iiKb67d+8iJycHQ4YMgUAg0FVo1MgwmSIivfDo0SPMnz8fmZmZMDc3h0AgQHJyMnbs2IHIyEgEBQWhWbNmug5TqbNnz2LWrFkQi8UAAGNjYxgYGODx48d4/PgxoqKi8Oqrr+Lll1+uVPfx48dYsGABRCIRLC0tUVpaigcPHmDlypVISkrCp59+itWrV2P79u0wNDSEqakp8vPzcfbsWcTHx+P3339H27ZtKzzzr7/+wr///W/5n83MzCAQCJCSkoKUlBScPHkSX3/9NcaOHVuX3VKBn58f0tLS5H9+9uwZAGDdunXYtGkTAKCwsBAAcPHiRQwdOlRedu3atejevbvWYqXGhckUEemFb7/9Fk2bNsUPP/yAXr16QSKR4NSpU1i2bBkePnyIxYsXY8eOHboOU6kvv/wSYrEYr732GhYtWoR27doBAPLy8nD79m0cPnwYJiYmCuuuXLkSHTp0wE8//YROnTqhsLAQO3fuxIYNG7B37144ODhg165d+OSTTzBx4kSYm5vj7t27mDt3LhITE7Fu3Tps2LChwjPNzc0xfvx4jB49Gp06dYKtrS0AICUlBbt27cIvv/yCzz77DH369EGLFi3qtnP+X1paGpKTkytdF4lEla7l5+cjPz9f/ufi4uI6jY0aNyZTRKQXSkpKsH37drRp0wYAYGBgAA8PD1haWmLq1Kn466+/cPHixQpTQlVZvHgxDh06pFE8K1euxPjx46tVNiMjA0lJSQCAr776Cvb29vJ7lpaW6NWrl8q4DQwMsG3bNlhZWQEoH0WaOXMmLly4gL///hvr1q3DnDlzMHXqVHkdZ2dnfPXVV3j77bdx6tQplJSUwNjYWH6/b9++6Nu3b6W2WrRogU8++QR5eXkIDg7GwYMHMXv27Gp9zpo6deqU/PdXrlzBG2+8AU9PT3z//ffy64MGDUJOTg4uXrxY4fMQ1QQXoBORXhgxYoQ8kXpev3790KNHDwBAWFiYWs+0tLSEvb29Rr9MTU2r3Y6FhYV8XZOiUZaqvPXWW/JE6nkDBgwAAAiFQgQEBFS637NnT5iYmKCkpASPHj1Sq03ZFNqlS5fUjrc2xMbGAqj4xt6jR48gEonwyiuvMJGiWsWRKSLSC3369FF5Lz4+Hjdv3lTrmcuWLcOyZctqGlqVTE1N0bt3b1y4cAHTpk2Dv78/XnvtNTg7O8PQ0LDK+sreWmvatCkAoGXLlrCwsKh038DAALa2tkhNTUV2dnal+1lZWdi7dy/+/PNPJCYmIjc3F2VlZRXKPH36tDofsdZdvHgRANC7d+9K13r27KmTmKjxYjJFRHrB0dGxynuZmZnaCkdtX3/9Nd5//33cv38fGzZswIYNG2Bubo7evXvD29sb3t7eMDJS/CX9+T2WnidLxFQtvJeVKS0trXD93r17mDp1KtLT0+XXLCwsYGpqCoFAALFYjOzsbBQUFKj1OWuDVCpFfHw8LC0tKxxNo+jtPqLawGSKiPSeVCrVdQhVat26NY4cOYIzZ87g3LlzuHjxIu7fv4+zZ8/i7Nmz+OWXX7Bnzx6FI0x1YcmSJUhPT4erqys+/PBD9OzZs0Lb0dHReOedd7QSy6VLlzBnzhz5n6VSKbKysmBkZITBgwfLr8tG1z7++GN5kti8eXMEBwdrJU5qvJhMEZFeUDXdJFuHJJv2qq6vvvqqwplv6li6dClGjhypVh0jIyN4eHjAw8MDQHncR44cwYYNG3Djxg1s3LgRixYt0igedaSkpODq1aswNDTEli1bFI76PT9iVdfEYrHC9kpLSxVel22ZAEDpG5BE6mAyRUR6ITY2VunbczExMQCALl26qPXMvLw8jZOGoqIijeo9z8HBAdOmTUNWVha2bdsmX3Rd11JTUwGUJ5/Kpk/Pnz+vlViA8jcL79y5I//zwoULcfToUezdu1c+pRcWFoa5c+diypQpWLp0qdZiI/3AZIqI9MLx48cxc+ZMtG7dusL12NhY+RtnXl5eaj0zMDAQgYGBtRajMmKxGEZGRkp37JaNrpSUlNR5LADku8Wnp6cjIyMDdnZ2Fe7fuXMHx44d00osisTFxcHExATdunWTX5Mlms8vSCeqLdwagYj0glAoxHvvvSdPnGSbds6dOxcAMHDgwHp78O29e/fg4+ODXbt2ITExUb7GSywWIywsDLt27QJQvoeSNrz88sto3rw5pFIp5s+fj4cPH8rj+eOPP/Duu+/C3NxcK7G86PHjx0hJSUG3bt0qbH8QFxcHgUDAxedUJzgyRUR6YdGiRVi7di38/Pxgbm4OiUQin2pr06aNVkaYauLevXtYuXIlVq5cCWNjY5ibmyMnJwcSiQQA4ObmhpkzZ2olFgMDAyxbtgxz585FTEwMhg8fDgsLC5SUlEAsFqNFixb4z3/+g//85z9aied5ivaXku0S//LLL6u9Lo6oOjgyRUR64aWXXkJwcDB8fX3RpEkTlJWVoWXLlnj33XcRHBxcr8/le/nll/H999/jrbfeQpcuXWBlZYW8vDxYWlrC3d0dn376Kfbv3w9LS0utxfT666/jl19+wcCBA2FhYYHS0lJ5fx46dAjNmzfXWizPUzSdFxcXJz+4maguCKQN4Z3geurx48cYNmwYIiMj0apVK12HQ0QKDB06FMnJydi9e7fC40+IahO/L+gnjkwRERER1QCTKSIiIqIaqPcL0I8ePYr9+/fjzp07kEgkaNeuHXx9feHn5yc/+FOXzyMiIiL9Vq+TqRUrVmDfvn0wMTFB//79YWRkhOjoaHzxxReIjo7Ghg0bqnXIZ109j4iIiKjeJlNhYWHYt28fHBwcEBQUhLZt2wIo3yRuypQpCA8PR1BQEKZOnaqT5xFRw3Dq1Cldh0BEjVy9ndfaunUrgPJjAWSJDwDY29tj+fLlAIDt27fL91jR9vOIiIiIgHqaTKWmpuLGjRsQCoUKj3fo06cPHB0dIRKJcPnyZa0/j4iIiEimXiZTN2/eBAB07NgRpqamCst07doVAHDr1i2tP4+IiIhIpl4mU48fPwYAtGjRQmkZJyenCmW1+TwiIiIimXq5AL2goAAAYGZmprSMhYUFACA/P1/rz5MpKysDUD6NSEREJPt+IPv+QPqhXiZTshNuBAJBvXyejEgkAgC8/fbbtfpcIiJq2EQiEdq0aaPrMEhL6mUyJRslko0oKSIbQZKV1ebzZNzc3LB37144ODhwfyoiIkJZWRlEIhHc3Nx0HQppUb1Mplq2bAkASElJUVpGNpQqK6vN58mYmpryFHIiIqqAI1L6p14uQO/SpQsAICEhAUVFRQrLXLt2DQDQuXNnrT+PiIiISKZeJlNOTk5wdXWFWCzGyZMnK92PiYlBamoqHBwc0KNHD60/j4iIiEimXiZTADBjxgwAwOrVq/Hw4UP59YyMDKxYsQIAMH369AqHE69ZswZeXl5Ys2ZNrTyPiIiIqCr1cs0UAHh5ecHPzw/79+/HqFGjMGDAAPnBxHl5efDw8IC/v3+FOiKRCImJifK37Gr6PCIiIqKq1NtkCgCWL18Od3d37N27FzExMZBIJGjfvj18fX3h5+en9ihSbT+PiIiISCCVbcJERERERGrjUAwRERFRDTCZIiIiIqoBJlOES5cuITIyUtdhEBERNUhcM0WYPHkyLl68iFu3buk6FJ16+PAhTExM0Lx58wrXb9++jYiICGRkZKBNmzbw9vaGg4ODjqKsX0QiEc6fP4+0tDRYWFiga9eu6Natm67D0pqlS5eiX79+8PT0hLGxsa7DqffS0tLke/q1aNFCZdnExESkp6ejd+/eWoqOSHNMpkjvk6mLFy9i8eLFSE5OBlC+C/6aNWvQrl077NmzB4GBgZBIJJBKpRAIBLCwsMC6devw6quv6jjyunf8+HG0atVKYYK0YcMG/PTTTygtLa1wvUePHli3bh0cHR21FabOdOrUCQKBAE2aNIGPjw98fX3h6uqq67DqneTkZCxevBgXL16UX3N1dcXixYuVHsm1ZMkShISE6O3XJWpYmEw1Yj179qxWueLiYkgkEpiZmcmvCQQCxMXF1VVo9UZycjJ8fHxQWFgIExMTGBgYoLCwEO3atcP69esxfvx4ODo6YujQobC1tcXff/+N2NhYWFpa4sSJE41+hKpTp04YN24cVq5cWeH6unXrsG3bNkilUnTp0gXt2rVDVlYW4uLiUFRUhA4dOuDgwYONfrSmU6dO8t8LBAIAgIuLCyZOnAgfHx9YW1vrKrR6Iy8vD2PGjJH/sGJra4ucnByUlZXB0NAQ8+bNk2+q/DwmU9SQcM1UI1ZQUIDCwkIUFBSo/FVWVgapVFrhWn5+vq7D14odO3agsLAQAQEBiIuLQ1xcHGbNmoXExEQsWbIEHTp0QEhICJYtW4ZZs2Zhz549ePfdd5GXl4f9+/frOnydSEtLw88//wyhUIgtW7bg4MGDWLNmDX7++WeEh4fDzc0N9+/fx2+//abrULXCx8cH69atw4ABAyAQCHD79m189dVXGDx4MBYsWIDz58/rOkSd+uWXX5CcnIy+ffvi7NmziI6ORlRUFN577z0A5Yn5d999p+MoiWqmXm/aSTVjbW2N3NxcvP3225g6darSTUk/+ugjXL16FREREVqOUPfOnz8PBwcHLFy4EIaGhgCA2bNn49ChQ7h16xY2bdoEKyurCnVmzpyJ3377DVFRUZg7d64uwtapyMhIlJaWYsaMGXjttdcq3HNwcEBgYCDGjh2LsLAwvThVQCgUYsSIERgxYgRSU1MRHByMkJAQJCUlITQ0FMePH4eTkxN8fX0xfvx4ODk56TpkrYqMjESTJk2wfv162NraAigfnVq4cCEGDBiAefPmYceOHSguLsayZct0HC2RZjgy1YiFhoZiyJAhCAoKwscff4yioiK0bNmy0i/ZVMyL1/XBkydP4OrqKk+kgPLpGtn0jaK1QpaWlujcuXOFMx71yYMHDyAQCDB69GiF9zt06IBOnTohISFBy5HpXvPmzTFr1iyEh4fjl19+gY+PD0xMTJCSkoKNGzdi2LBheO+993Dy5EmIxWJdh6sV//zzD7p16yZPpJ43YMAABAUFwdbWFnv37sXnn3+ugwiJao7JVCNmb2+PLVu2IDAwEImJiRg3bhy2bNmCsrIyXYdWb0ilUlhYWFS6LlvrYm9vr7Bes2bN9GYq9EUlJSUAgNatWyst07p1a+Tl5WkrpHqpb9++WL16NaKiovD555/D1dUVEokEUVFR+PDDDzF48GBdh6gVEokENjY2Su+7uLhgz549sLOzw2+//cbRKWqQmEzpgbFjx+Lo0aPo378/NmzYgAkTJnBR5/+ztbVVeDC2VCqFqnczxGIxLC0t6zK0eqtVq1YAgJycHKVlcnNzFSap+sjS0hJ+fn44cOAAjh49iilTpsDa2hpZWVm6Dk0rnJyckJSUpLLMyy+/jD179sDe3h7BwcFYsmQJJBKJliIkqjkmU3qiWbNm2Lp1K77++ms8fvwYEydOxLp16+SjDPqqZcuW+Oeffypd/+STT3D27Fml9R48eNDo3+STCQsLw7Bhw+S/du3aBQC4d++e0jpPnjxB06ZNtRRhw9GxY0d88skniIqKwoYNG3Qdjla8/PLLuHnzJrKzs1WWk21F4uDggJCQEJw8eVJLERLVHJMpPePr64tjx46hX79+2Lp1K8aOHYsnT57oOiyd6dKlC0QiUaWEysrKSuk+SQ8ePMC9e/fg5uamhQh1r6CgAMnJyfJfmZmZkEqlSr/ZpaWl4cGDB3B2dtZypA2HkZERhg8fruswtGLgwIEoLS3FkSNHqizbtm1bBAUFwdHREcXFxVqIjqh28G0+PeTo6IiffvoJv//+O7799lvk5eXJ98jRN2+99RacnZ3V2g8pIiICLVq0wKBBg+owsvpB1TFDyvrs3LlzcHFx0Ys1Qb1790b79u11HUa99q9//QtHjhxBfHw8Jk+eXGX5l156CXv27MHcuXOrHM0iqi+4aaeeS01NRXR0NABg3LhxOo6GiIio4WEyRURERFQDXDNFREREVANMpoiIqN45cOAANm7cqOswiKqF03xERFTvvPnmm7h69Sr3xKMGgSNTRERERDXAZIqIiIioBrjPFBER1ZlRo0ZpVK+qI2iI6hMmU0REVGcSEhIgEAhUnnWpjL5uJkwND5MpPZWbm4tr164hMzMTLVq0QM+ePXUdUr3DPlKN/aMa+6ecpaUl8vPzsXXrVpiZmVW73ooVK/DgwYM6jIyo9jCZ0jO5ubn45ptvcPToUZSVlQEAxo4dK/9Cv3fvXmzZsgUbN25E9+7ddRip7rCPVGP/qMb+qcjV1RUxMTFo0qSJWgmlpaVlHUZFVLu4AF2PFBQUYPLkyTh06BCsra0xePDgSkPvgwcPRnp6OiIiInQUpW6xj1Rj/6jG/qmsa9euAIDr16/rOBKiusORKT2yY8cO3L59G6NHj8aKFStgZmaGTp06VSjTunVrtG3bFn///beOotQt9pFq7B/V2D+Vubm5QSqV4saNG2rV69y5s1oHkBPpEpMpPXLy5Ek0a9YMX331lcovUi1atEBCQoIWI6s/2EeqsX9UY/9UNnz4cMTGxsLISL1vN8uXL6+bgIjqAKf59EhSUhK6du1a5U97tra2yMrK0k5Q9Qz7SDX2j2rsn8oMDAzQpEkTtRafEzU0TKb0iJGREYqLi6ssl5qaCnNzcy1EVP+wj1Rj/6jG/iHST0ym9Ei7du1w69YtlV/ss7Ozcfv2bTg7O2sxsvqDfaQa+0c19o9mLl26hJCQEF2HQaQxJlN6xNPTExkZGVi9erXSMmvXrkVBQQFGjBihxcjqD/aRauwf1dg/mvn999+xZMkSXYdBpDEuQNcj/v7+CAkJQVBQEK5fv47hw4cDAJKTk7Fv3z6cPHkSsbGxcHZ2xoQJE3QcrW6wj1Rj/6jG/iHSTwKpJnv8U4OVlpaGefPm4fLly/IjHmRHNkilUri6umLz5s1wdHTUcaS6wz5Sjf2jGvtHfUuWLEFISAhu3bql61CINMJkSk+dO3cO586dQ1JSEsrKyuDk5ITBgwfDw8OD52H9P/aRauwf1dg/1cdkiho6JlNERKRTTKaooeOaKSIi0qkJEyagT58+ug6DSGMcmSIiIiKqAY5M6ZHOnTtXq5yRkRFsbW3h5uaG8ePHw8PDo44jqz/YR6qxf1Rj/xDpJ45M6ZEXD1ytDoFAgLFjx2LlypV1EFH9wz5Sjf2jGvtHuYiICFy+fBm2trbw8fGRv82YlpaG9evX4/z588jOzkarVq3g7e2NadOm8aBjajCYTOmZVatW4ddff8WkSZPg4+ODli1bQiAQIDk5GceOHcO+ffvwxhtvYOrUqfj777/x3XffITMzE6tWrcKoUaN0Hb5WsI9UY/+oxv6pSCqVYt68eQgPD5dfMzc3x86dO9GyZUu88cYbSE5OrlBHIBCgT58+2LlzJwwMuLc0NQBS0hsHDhyQurq6SuPj45WWuXz5stTV1VX622+/SaVSqTQ+Pl7q4uIiDQgI0FKUusU+Uo39oxr7p7Lg4GCpi4uL1N3dXfrpp59KP/30U6m7u7t09OjR0pUrV0pdXFykn376qTQmJkZ669Yt6b59+6T9+vWTdurUSfrrr7/qOnyiauHIlB4ZP348mjRpgl9++UVlualTpyI3NxcHDx6U10tJScHff/+tjTB1in2kGvtHNfZPZZMnT8alS5cQHBwsnwa9efMmJkyYAGNjY0yYMAHLli2rUOf69et444034O7ujj179ugibCK1cPxUjyQmJsLe3r7Kcvb29khMTJT/uVWrVsjLy6vL0OoN9pFq7B/V2D+V3b17Fz179qywnqxLly7o2bMniouL4e/vX6mOm5sbunXrhrt372ozVCKNMZnSI8bGxrh9+3aV5W7fvl1h4adYLIaFhUVdhlZvsI9UY/+oxv6pLD8/H82aNat0XbYA3cnJSWE9Jycn5Ofn12lsRLWFyZQe6dmzJx48eICNGzcqLbN582bcv38f7u7u8muPHz9W+MWwMWIfqcb+UY39U5mlpSWePn1a6brs2pMnTxTWe/LkCczNzes0NqLawn2m9Mi8efNw/vx5bNq0CaGhoRg5ciRatGgBgUCAlJQUnDhxAg8ePICJiQnmzJkDAEhJSUFCQgImTZqk4+i1g32kGvtHNfZPZZ06dUJsbCzu3r0LZ2dnAOUjc3FxcTA3N8f+/fuxZMmSCnVu3bqFq1evonv37jqImEh9XICuZ6Kjo/Hxxx8jPT290mGrUqkU9vb2WLVqFQYMGAAAyMzMxJ07d9C+fXu9OeWefaQa+0c19k9FoaGhWLBgAaysrDBy5EgAwPHjx5GXl4fvvvsOCxcuxFtvvQUfHx80adIEV65cwfr165GZmYnFixdj6tSpOv4ERFVjMqWHioqKcPLkScTGxiItLQ0A0KxZM/Tu3RteXl4wMzPTcYS6xz5Sjf2jGvunosWLFyMkJKTCtXnz5uGDDz7AJ598goMHD1ZIPKVSKdzc3LB//34IhUItR0ukPiZTRERU5/766y9cuHABxsbGGDRokHwKr7S0FNu3b0dISAhSUlLQrFkzeHp6YubMmbC0tNRt0ETVxGSKKpBKpTh37hyCg4Px/fff6zqceol9pBr7RzX2D1HjwwXoBAB4+PAhgoODERISApFIpOtw6iX2kWrsH9XYP0SNF5MpPVZYWIgTJ04gODgYly5dAlD+U7OtrS28vb11HF39wD5Sjf2jGvuHSD8wmdJDsqMdTp48iYKCAkilUggEAnh6emLMmDF49dVXYWSk33812EeqsX9UY/8Q6ReumdITIpEIISEhOHjwIP755x/I/rd37twZ6enpSE9Px61bt3QcpW6xj1Rj/6jG/iHSX/zRqBErKyvD6dOnceDAAURFRaGsrAxSqRQ2Njbw8fGBr68vOnfujEmTJiE9PV3X4eoE+0g19o9q7B8iAphMNWqDBw9GZmYmpFIpDA0N8eqrr2L8+PEYNmwY9275f+wj1dg/qrF/iAhgMtWoZWRkQCAQoHnz5li7di169uyp65DqHfaRauwf1dg/RATwoONGrXnz5pBKpUhNTYW/vz8CAgJw5MgRFBcX6zq0eoN9pBr7RzX2DxEBXIDeqEmlUkRFReHAgQM4ffo0SkpKIBAIYGFhgZEjR2L8+PHo3r07Jk2ahPj4eL1cHMs+Uo39oxr7p2Zyc3Nx7do1ZGZmokWLFhzZowaLyZSeyM7OxuHDh3Hw4EHcvn0bACAQCNCmTRvk5uYiMzNT77/Qs49UY/+oxv6pvtzcXHzzzTc4evQoysrKAABjx47FypUrAQB79+7Fli1bsHHjRvmxM0T1GZMpPXTr1i38/vvvCA0NRXZ2NoDyL/oDBgzA6NGj8frrr8Pc3FzHUeoW+0g19o9q7B/lCgoKMGnSJNy+fRt2dnZwc3PD2bNnMW7cOHkylZSUhNdffx3vvfceFi5cqOOIiarGZEqPlZSUIDw8HAcPHkR0dDQkEgkEAgFMTU3h4eGB7777Ttch6hz7SDX2j2rsn8o2btyIjRs3YvTo0VixYgXMzMzQqVOnCskUAHh5ecHS0hIHDhzQYbRE1cNkigAAqampOHDgAA4fPoykpCQIBAJOSbyAfaQa+0c19k85Hx8f5OTkICIiAsbGxgCgMJl69913kZCQgD///FNXoRJVG9/mIwDlbyXNnj0b4eHh2LlzJ0aNGqXrkOod9pFq7B/V2D/lkpKS0LVrV3kipYytrS2ysrK0ExRRDXGfKaqkf//+6N+/v67DqNfYR6qxf1TT5/4xMjKq1tYRqamperuujBoejkwREZHWtGvXDrdu3VKZUGVnZ+P27dtwdnbWYmREmmMyRUREWuPp6YmMjAysXr1aaZm1a9eioKAAI0aM0GJkRJrjNB8REWmNv78/QkJCEBQUhOvXr2P48OEAgOTkZOzbtw8nT55EbGwsnJ2dMWHCBB1HS1Q9fJuPiIi0Ki0tDfPmzcPly5chEAgglUohEAgAlO8q7+rqis2bN8PR0VHHkRJVD5MpIiLSiXPnzuHcuXNISkpCWVkZnJycMHjwYHh4eMiTK6KGgMkUERERUQ1wAToRERFRDTCZIiIiIqoBvs1HRERa07lz52qVMzIygq2tLdzc3DB+/Hh4eHjUcWREmuOaKSIi0ppOnTqpXUcgEGDs2LEVzu4jqk84zUdERFpz+/ZtvPvuuzA3N8d7772HkJAQxMbG4uLFizh8+DCmT58OCwsLBAQE4MyZMwgMDETTpk0REhKCo0eP6jp8IoU4zUdERFoTHByM3bt3IygoCN27d69wz8XFBS4uLvDw8MDbb7+N9u3bY+LEiWjbti3eeustHDp0SG8PiKb6jSNTRESkNXv37oW7u3ulROp5r7zyCtzd3bF//34AQPfu3dGlSxfcvHlTS1ESqYfJFBERaU1iYiLs7e2rLGdvb4/ExET5n1u1aoW8vLy6DI1IY0ymiIhIa4yNjXH79u0qy92+fRvGxsbyP4vFYlhYWNRlaEQaYzJFRERa07NnTzx48AAbN25UWmbz5s24f/8+3N3d5dceP36MZs2aaSNEIrVxawQiItKa27dv480330RJSQnatm2LkSNHokWLFhAIBEhJScGJEyfw4MEDGBsb49dff0Xnzp2RkpKCoUOHYtKkSfjss890/RGIKmEyRUREWhUdHY2PP/4Y6enplQ40lkqlsLe3x6pVqzBgwAAAQGZmJu7cuYP27dvD0dFRFyETqcRkioiItK6oqAgnT55EbGws0tLSAADNmjVD79694eXlBTMzMx1HSFR9TKaIiIiIaoAL0ImIqF6RSqU4e/Ys5s6dq+tQiKqFO6ATEVG98PDhQwQHByMkJAQikUjX4RBVG5MpIiLSmcLCQpw4cQLBwcG4dOkSgPKRKVtbW3h7e+s4OqLqYTJFRERad+nSJQQHB+PkyZMoKCiAVCqFQCCAp6cnxowZg1dffRVGRvwWRQ0DF6ATEZFWiEQihISE4ODBg/jnn38g+/bTuXNnpKenIz09Hbdu3dJxlETqY9pPRER1pqysDKdPn8aBAwcQFRWFsrIySKVS2NjYwMfHB76+vujcuTMmTZqE9PR0XYdLpBEmU0REVGcGDx6MzMxMSKVSGBoa4tVXX8X48eMxbNgwCIVCXYdHVCuYTBERUZ3JyMiAQCBA8+bNsXbtWvTs2VPXIRHVOu4zRUREdaZ58+aQSqVITU2Fv78/AgICcOTIERQXF+s6NKJawwXoRERUZ6RSKaKionDgwAGcPn0aJSUlEAgEsLCwwMiRIzF+/Hh0794dkyZNQnx8PBegU4PEZIqIiLQiOzsbhw8fxsGDB3H79m0AgEAgQJs2bZCbm4vMzEwmU9QgMZkiIiKtu3XrFn7//XeEhoYiOzsbQHliNWDAAIwePRqvv/46zM3NdRwlUfUwmSIiIp0pKSlBeHg4Dh48iOjoaEgkEggEApiamsLDwwPfffedrkMkqhKTKSIiqhdSU1Nx4MABHD58GElJSRAIBJz2owaByRQREdU70dHROHToEFatWqXrUIiqxGSKiIiIqAa4zxQRERFRDTCZIiIiIqoBJlNERERENcBkiogQEREBFxcXuLi44N1339V1OEREDQqTKSLCoUOH5L+Pjo5GamqqDqMhImpYmEwR6blnz57h7NmzMDMzg4+PDyQSCY4cOaLrsIiIGgwmU0R67tixYxCLxRg2bBjeeustABVHqoiISDUmU0R6TpY4jRo1Cr169UKLFi3w4MEDXL16VWW9uLg4zJgxA3369EH37t0xevRo7Nq1CxKJBIsXL4aLiwt++OEHhXUlEglCQkIQEBCAfv36wc3NDYMGDcL8+fNx5cqVWv+MRER1ickUkR5LSEjAjRs3YGNjg4EDB0IgEMDb2xuA6tGpkJAQ+Pv74+zZs8jOzoZQKMT9+/excuVKzJ07V2WbeXl5mDZtGhYtWoTz588jKysLJiYmEIlEOHHiBN566y0EBQXV6uckIqpLTKaI9JgsYRoxYgSEQiGA8hEqADh+/DhKSkoq1bl//z6WLVsGiUSCIUOGIDIyErGxsYiLi8OyZctw+vRpREZGKm1TlkS5uLhg27ZtuHz5MuLi4hAbG4uPPvoIhoaG+PrrrxEXF1cHn5iIqPYxmSLSU2VlZfKF5j4+PvLrLi4ucHZ2RlZWFk6fPl2p3rZt2yAWi+Hs7IyNGzeiVatWAABTU1NMnjwZ8+fPR05OjsI2z58/j4iICLRs2RK7d+/GkCFDYGpqCgCwsrLC+++/j3nz5kEikWDbtm21/ZGJiOoEkykiPRUVFQWRSISWLVvC3d29wj3Z6NSLU30SiQQREREAgClTpsDY2LjSc/39/WFubq6wTdnzxo8fDxsbG4VlZG1fuHABZWVl1f9AREQ6YqTrAIhIN0JCQgAA3t7eEAgEFe75+Phg7dq1+PPPP5GZmYmmTZsCAJKSkpCXlwcAlRIwGTMzM7i6uiI2NrbSvfj4eADArl27sH//fpXxFRYWIisrC3Z2dmp9LiIibePIFJEeys3Nla9ren6KT6ZFixbo1asXSktLcfToUfn1Z8+eyX/frFkzpc9Xdk8kEsnbT09PV/pLprCwUL0PRkSkAxyZItJDx48fR3FxMQBg9OjRKsuGhIRg6tSpAACpVFqjdiUSCQBg8+bNGDZsWI2eRURUX3BkikgPqbMp582bN3Hnzh0AkE/3AcDTp0+V1pGNQL3I3t4eQPkbgUREjQWTKSI98/DhQ/napcOHDyM2Nlbpr9deew3A/9ZXtW7dGpaWlgCgdOuCoqIiXL9+XeG97t27AwDCwsJq8RMREekWkykiPSMblerUqRM6deoEKysrpb+8vLwAAEePHkVZWRkMDAzk03O7d++GWCyu9Px9+/ahoKBAYdvjxo0DAFy/fl2eoCmTnZ2t6UckItIqJlNEekQqlcr3lnr99derLD906FAIhUKIRCJERUUBAN5//30IhULcvXsXc+bMQXJyMgCguLgYe/fuxdq1a2FlZaXweYMHD8bw4cMBAJ988gm+//77CtOF2dnZiIiIwAcffIDAwMAafVYiIm3hAnQiPXLhwgV58uPp6VlleSsrK/Tt2xdRUVE4dOgQhgwZgpdffhkrVqzA0qVLcfr0aZw+fRrW1tYoKCiAWCyGl5cXTE1NERISonAfqm+//Va+X9WmTZuwadMmNGnSBFKpVL7tAlC+FxURUUPAZIpIj8im1tq2bYuOHTtWq46npyeioqIQGRmJnJwcWFlZwdfXF23atMGPP/6Iy5cvo6SkBC+//DJ8fX3h7++P2bNnAwCaNGlS6Xnm5ubYtGkTzpw5g+DgYFy5cgWZmZkwMDBAmzZt0LVrVwwfPhxDhgyptc9NRFSXBNKavutMRPQcqVSK1157DU+ePMHu3bvRt29fXYdERFSnuGaKiGpVaGgonjx5AktLS3Tr1k3X4RAR1TlO8xGR2n788UdYWFjAw8MDjo6OMDAwQHZ2NkJCQrB27VoAwKRJk2BmZqbjSImI6h6n+YhIbQsXLpQfMyMUCmFubo6cnBz5DukDBgzAjz/+CBMTE12GSUSkFRyZIiK1TZo0CZaWloiLi4NIJEJubi6sra3h4uKC0aNHY+zYsTAy4pcXItIPHJkiIiIiqgEuQCciIiKqASZTRERERDXAZIqIiIioBphMEREREdUAkykiIiKiGmAyRURERFQD/wcFyGJCVO2TJgAAAABJRU5ErkJggg==\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" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.8" } }, "nbformat": 4, "nbformat_minor": 4 }