https://github.com/winvector/wvu
Win Vector LLC Python data science teaching tools (graphs and data manipulation)
https://github.com/winvector/wvu
Last synced: 4 months ago
JSON representation
Win Vector LLC Python data science teaching tools (graphs and data manipulation)
- Host: GitHub
- URL: https://github.com/winvector/wvu
- Owner: WinVector
- License: other
- Created: 2022-08-28T15:36:08.000Z (almost 4 years ago)
- Default Branch: main
- Last Pushed: 2023-02-23T21:42:45.000Z (over 3 years ago)
- Last Synced: 2025-01-27T07:02:19.304Z (over 1 year ago)
- Language: HTML
- Homepage: https://winvector.github.io/wvu/
- Size: 1.19 MB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.ipynb
- License: LICENSE
Awesome Lists containing this project
README
{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"[wvu](https://github.com/WinVector/wvu) is a simple \n",
"set of utilities for doing and teaching data science and machine learning methods.\n",
"They are not replacements for the standard methods in sklearn.\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'0.3.9'"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import numpy.random\n",
"import pandas\n",
"import wvu.util\n",
"\n",
"wvu.__version__"
]
},
{
"cell_type": "markdown",
"metadata": {
"pycharm": {
"name": "#%% md\n"
}
},
"source": [
"Illustration of cross-method plan."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false,
"jupyter": {
"outputs_hidden": false
},
"pycharm": {
"name": "#%%\n"
}
},
"outputs": [
{
"data": {
"text/plain": [
"[{'train': [0, 1, 2, 3, 8], 'test': [4, 5, 6, 7, 9]},\n",
" {'train': [4, 5, 6, 7, 9], 'test': [0, 1, 2, 3, 8]}]"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wvu.util.mk_cross_plan(10, 2)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Plotting example"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on function plot_roc in module wvu.util:\n",
"\n",
"plot_roc(prediction, istrue, title='Receiver operating characteristic plot', *, truth_target=True, ideal_line_color=None, extra_points=None, show=True)\n",
" Plot a ROC curve of numeric prediction against boolean istrue.\n",
" \n",
" :param prediction: column of numeric predictions\n",
" :param istrue: column of items to predict\n",
" :param title: plot title\n",
" :param truth_target: value to consider target or true.\n",
" :param ideal_line_color: if not None, color of ideal line\n",
" :param extra_points: data frame of additional point to annotate graph, columns fpr, tpr, label\n",
" :param show: logical, if True call matplotlib.pyplot.show()\n",
" :return: calculated area under the curve, plot produced by call.\n",
" \n",
" Example:\n",
" \n",
" import pandas\n",
" import wvu.util\n",
" \n",
" d = pandas.DataFrame({\n",
" 'x': [1, 2, 3, 4, 5],\n",
" 'y': [False, False, True, True, False]\n",
" })\n",
" \n",
" wvu.util.plot_roc(\n",
" prediction=d['x'],\n",
" istrue=d['y'],\n",
" ideal_line_color='lightgrey'\n",
" )\n",
" \n",
" wvu.util.plot_roc(\n",
" prediction=d['x'],\n",
" istrue=d['y'],\n",
" ideal_line_color='lightgrey',\n",
" extra_points=pandas.DataFrame({\n",
" 'tpr': [0, 1],\n",
" 'fpr': [0, 1],\n",
" 'label': ['AAA', 'BBB']\n",
" })\n",
" )\n",
"\n"
]
}
],
"source": [
"help(wvu.util.plot_roc)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"d = pandas.concat([\n",
" pandas.DataFrame({\n",
" 'x': numpy.random.normal(size=1000),\n",
" 'y': numpy.random.choice([True, False], \n",
" p=(0.02, 0.98), \n",
" size=1000, \n",
" replace=True)}),\n",
" pandas.DataFrame({\n",
" 'x': numpy.random.normal(size=200) + 5,\n",
" 'y': numpy.random.choice([True, False], \n",
" size=200, \n",
" replace=True)}),\n",
"])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": [
"0.8635570926073719"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"wvu.util.plot_roc(\n",
" prediction=d.x,\n",
" istrue=d.y,\n",
" ideal_line_color=\"DarkGrey\",\n",
" title='Example ROC plot')"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on function threshold_plot in module wvu.util:\n",
"\n",
"threshold_plot(d: pandas.core.frame.DataFrame, pred_var: str, truth_var: str, truth_target: bool = True, threshold_range: Iterable[float] = (-inf, inf), plotvars: Iterable[str] = ('precision', 'recall'), title: str = 'Measures as a function of threshold', *, show: bool = True) -> None\n",
" Produce multiple facet plot relating the performance of using a threshold greater than or equal to\n",
" different values at predicting a truth target.\n",
" \n",
" :param d: pandas.DataFrame to plot\n",
" :param pred_var: name of column of numeric predictions\n",
" :param truth_var: name of column with reference truth\n",
" :param truth_target: value considered true\n",
" :param threshold_range: x-axis range to plot\n",
" :param plotvars: list of metrics to plot, must come from ['threshold', 'count', 'fraction',\n",
" 'true_positive_rate', 'false_positive_rate', 'true_negative_rate', 'false_negative_rate',\n",
" 'precision', 'recall', 'sensitivity', 'specificity', 'accuracy']\n",
" :param title: title for plot\n",
" :param show: logical, if True call matplotlib.pyplot.show()\n",
" :return: None, plot produced as a side effect\n",
" \n",
" Example:\n",
" \n",
" import pandas\n",
" import wvu.util\n",
" \n",
" d = pandas.DataFrame({\n",
" 'x': [1, 2, 3, 4, 5],\n",
" 'y': [False, False, True, True, False]\n",
" })\n",
" \n",
" wvu.util.threshold_plot(\n",
" d,\n",
" pred_var='x',\n",
" truth_var='y',\n",
" plotvars=(\"sensitivity\", \"specificity\"),\n",
" )\n",
"\n"
]
}
],
"source": [
"help(wvu.util.threshold_plot)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"wvu.util.threshold_plot(\n",
" d,\n",
" pred_var='x',\n",
" truth_var='y',\n",
" plotvars=(\"sensitivity\", \"specificity\"),\n",
" title = \"example plot\"\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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