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stoneyv/plotnine_geom_polygon_test.ipynb

Created May 22, 2017 17:08
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python plotnine geom_polygon test adapted from ggplot2 documentation
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plotnine_geom_polygon_test.ipynb
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## plotnine geom_polygon test\n",
"https://plotnine.readthedocs.io/en/stable/generated/plotnine.geoms.geom_polygon.html#plotnine.geoms.geom_polygon"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"python version 3.6.0\n",
"numpy version 1.11.3\n",
"pandas version 0.20.1\n"
]
}
],
"source": [
"import pandas as pd\n",
"import numpy as np\n",
"import sys\n",
"\n",
"version = \".\".join(map(str, sys.version_info[:3]))\n",
"print('python version ', version)\n",
"print('numpy version ', np.__version__)\n",
"print('pandas version ',pd.__version__)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/stoney/anaconda3/lib/python3.6/site-packages/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.\n",
" from pandas.core import datetools\n"
]
}
],
"source": [
"from plotnine import *\n",
"from plotnine.layer import Layers\n",
"\n",
"%matplotlib inline"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## geom_polygon example adapted from ggplot2 documentation\n",
"http://ggplot2.tidyverse.org/reference/geom_polygon.html"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"ids = ['1.1','2.1','1.2','2.2','1.3','2.3']\n",
"\n",
"values = { 'iid': ids,\n",
" 'value':(3, 3.1, 3.1, 3.2, 3.15, 3.5)}\n",
"\n",
"positions = { 'iid': ids*4,\n",
" 'x':(2, 1, 1.1, 2.2, 1, 0, 0.3, 1.1, 2.2, 1.1, 1.2, 2.5, 1.1, 0.3,\n",
" 0.5, 1.2, 2.5, 1.2, 1.3, 2.7, 1.2, 0.5, 0.6, 1.3),\n",
" 'y':(-0.5, 0, 1, 0.5, 0, 0.5, 1.5, 1, 0.5, 1, 2.1, 1.7, 1, 1.5,\n",
" 2.2, 2.1, 1.7, 2.1, 3.2, 2.8, 2.1, 2.2, 3.3, 3.2)}\n",
"\n",
"positions_df = pd.DataFrame(positions)\n",
"values_df = pd.DataFrame(values)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"datapoly_df shape as rows,columns (24, 4)\n"
]
},
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>iid</th>\n",
" <th>x</th>\n",
" <th>y</th>\n",
" <th>value</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>1.1</td>\n",
" <td>2.0</td>\n",
" <td>-0.5</td>\n",
" <td>3.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>2.1</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>1.2</td>\n",
" <td>1.1</td>\n",
" <td>1.0</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>2.2</td>\n",
" <td>2.2</td>\n",
" <td>0.5</td>\n",
" <td>3.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>1.3</td>\n",
" <td>1.0</td>\n",
" <td>0.0</td>\n",
" <td>3.15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>2.3</td>\n",
" <td>0.0</td>\n",
" <td>0.5</td>\n",
" <td>3.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>1.1</td>\n",
" <td>0.3</td>\n",
" <td>1.5</td>\n",
" <td>3.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>7</th>\n",
" <td>2.1</td>\n",
" <td>1.1</td>\n",
" <td>1.0</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>1.2</td>\n",
" <td>2.2</td>\n",
" <td>0.5</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>9</th>\n",
" <td>2.2</td>\n",
" <td>1.1</td>\n",
" <td>1.0</td>\n",
" <td>3.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>10</th>\n",
" <td>1.3</td>\n",
" <td>1.2</td>\n",
" <td>2.1</td>\n",
" <td>3.15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>11</th>\n",
" <td>2.3</td>\n",
" <td>2.5</td>\n",
" <td>1.7</td>\n",
" <td>3.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>12</th>\n",
" <td>1.1</td>\n",
" <td>1.1</td>\n",
" <td>1.0</td>\n",
" <td>3.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>13</th>\n",
" <td>2.1</td>\n",
" <td>0.3</td>\n",
" <td>1.5</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>14</th>\n",
" <td>1.2</td>\n",
" <td>0.5</td>\n",
" <td>2.2</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>2.2</td>\n",
" <td>1.2</td>\n",
" <td>2.1</td>\n",
" <td>3.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>16</th>\n",
" <td>1.3</td>\n",
" <td>2.5</td>\n",
" <td>1.7</td>\n",
" <td>3.15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>17</th>\n",
" <td>2.3</td>\n",
" <td>1.2</td>\n",
" <td>2.1</td>\n",
" <td>3.50</td>\n",
" </tr>\n",
" <tr>\n",
" <th>18</th>\n",
" <td>1.1</td>\n",
" <td>1.3</td>\n",
" <td>3.2</td>\n",
" <td>3.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>19</th>\n",
" <td>2.1</td>\n",
" <td>2.7</td>\n",
" <td>2.8</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>20</th>\n",
" <td>1.2</td>\n",
" <td>1.2</td>\n",
" <td>2.1</td>\n",
" <td>3.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th>21</th>\n",
" <td>2.2</td>\n",
" <td>0.5</td>\n",
" <td>2.2</td>\n",
" <td>3.20</td>\n",
" </tr>\n",
" <tr>\n",
" <th>22</th>\n",
" <td>1.3</td>\n",
" <td>0.6</td>\n",
" <td>3.3</td>\n",
" <td>3.15</td>\n",
" </tr>\n",
" <tr>\n",
" <th>23</th>\n",
" <td>2.3</td>\n",
" <td>1.3</td>\n",
" <td>3.2</td>\n",
" <td>3.50</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" iid x y value\n",
"0 1.1 2.0 -0.5 3.00\n",
"1 2.1 1.0 0.0 3.10\n",
"2 1.2 1.1 1.0 3.10\n",
"3 2.2 2.2 0.5 3.20\n",
"4 1.3 1.0 0.0 3.15\n",
"5 2.3 0.0 0.5 3.50\n",
"6 1.1 0.3 1.5 3.00\n",
"7 2.1 1.1 1.0 3.10\n",
"8 1.2 2.2 0.5 3.10\n",
"9 2.2 1.1 1.0 3.20\n",
"10 1.3 1.2 2.1 3.15\n",
"11 2.3 2.5 1.7 3.50\n",
"12 1.1 1.1 1.0 3.00\n",
"13 2.1 0.3 1.5 3.10\n",
"14 1.2 0.5 2.2 3.10\n",
"15 2.2 1.2 2.1 3.20\n",
"16 1.3 2.5 1.7 3.15\n",
"17 2.3 1.2 2.1 3.50\n",
"18 1.1 1.3 3.2 3.00\n",
"19 2.1 2.7 2.8 3.10\n",
"20 1.2 1.2 2.1 3.10\n",
"21 2.2 0.5 2.2 3.20\n",
"22 1.3 0.6 3.3 3.15\n",
"23 2.3 1.3 3.2 3.50"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"datapoly_df = pd.merge(positions_df, values_df, how='left', on='iid' )\n",
"print('datapoly_df shape as rows,columns ', datapoly_df.shape)\n",
"datapoly_df.head(24)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## From ggplot2 geom_plot example\n",
"```\n",
"p <- ggplot(datapoly, aes(x = x, y = y)) +\n",
" geom_polygon(aes(fill = value, group = id))\n",
"p\n",
"```"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"p = (ggplot(aes('x', 'y' )) +\n",
" geom_polygon(datapoly_df, aes(fill = '#333333')))"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"ename": "PlotnineError",
"evalue": "\"Could not evaluate the 'fill' mapping: '#333333' (original error: unexpected EOF while parsing (<string>, line 1))\"",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mSyntaxError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/home/stoney/plotnine/plotnine/layer.py\u001b[0m in \u001b[0;36mcompute_aesthetics\u001b[0;34m(self, plot)\u001b[0m\n\u001b[1;32m 318\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 319\u001b[0;31m \u001b[0mnew_val\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0menv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0meval\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minner_namespace\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mdata\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 320\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/stoney/anaconda3/lib/python3.6/site-packages/patsy/eval.py\u001b[0m in \u001b[0;36meval\u001b[0;34m(self, expr, source_name, inner_namespace)\u001b[0m\n\u001b[1;32m 163\u001b[0m \"\"\"\n\u001b[0;32m--> 164\u001b[0;31m \u001b[0mcode\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompile\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexpr\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msource_name\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"eval\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mflags\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 165\u001b[0m return eval(code, {}, VarLookupDict([inner_namespace]\n",
"\u001b[0;31mSyntaxError\u001b[0m: unexpected EOF while parsing (<string>, line 1)",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[0;31mPlotnineError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m<ipython-input-15-568c012e485d>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/home/stoney/plotnine/plotnine/ggplot.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 138\u001b[0m \u001b[0;31m# assign a default theme\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 139\u001b[0m \u001b[0mself\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdeepcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 140\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_build\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 141\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 142\u001b[0m \u001b[0;31m# If no theme we use the default\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/stoney/plotnine/plotnine/ggplot.py\u001b[0m in \u001b[0;36m_build\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 223\u001b[0m \u001b[0;31m# Compute aesthetics to produce data with generalised\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 224\u001b[0m \u001b[0;31m# variable names\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 225\u001b[0;31m \u001b[0mlayers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute_aesthetics\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 226\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 227\u001b[0m \u001b[0;31m# Transform data using all scales\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/stoney/plotnine/plotnine/layer.py\u001b[0m in \u001b[0;36mcompute_aesthetics\u001b[0;34m(self, plot)\u001b[0m\n\u001b[1;32m 88\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompute_aesthetics\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mplot\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 89\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0ml\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 90\u001b[0;31m \u001b[0ml\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcompute_aesthetics\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mplot\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 91\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 92\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompute_statistic\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlayout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/stoney/plotnine/plotnine/layer.py\u001b[0m in \u001b[0;36mcompute_aesthetics\u001b[0;34m(self, plot)\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 321\u001b[0m raise PlotnineError(\n\u001b[0;32m--> 322\u001b[0;31m _TPL_EVAL_FAIL.format(ae, col, str(e)))\n\u001b[0m\u001b[1;32m 323\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 324\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mPlotnineError\u001b[0m: \"Could not evaluate the 'fill' mapping: '#333333' (original error: unexpected EOF while parsing (<string>, line 1))\""
]
}
],
"source": [
"p.draw()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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