| { |
| "cells": [ |
| { |
| "cell_type": "markdown", |
| "metadata": { |
| "collapsed": false, |
| "jupyter": { |
| "outputs_hidden": false |
| } |
| }, |
| "source": [ |
| "# Hello World Example\n", |
| "This uses the jupyter magic commands to create a simple example of how to use Hamilton." |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": null, |
| "metadata": { |
| "collapsed": false, |
| "jupyter": { |
| "outputs_hidden": false |
| } |
| }, |
| "outputs": [], |
| "source": [ |
| "#! pip install pandas \"sf-hamilton[visualization]\"" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 10, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:39:54.379474Z", |
| "start_time": "2024-06-05T05:39:47.097691Z" |
| }, |
| "collapsed": false, |
| "jupyter": { |
| "outputs_hidden": false |
| } |
| }, |
| "outputs": [], |
| "source": [ |
| "# Cell 1 - import the things you need\n", |
| "import logging\n", |
| "import sys\n", |
| "from hamilton import driver\n", |
| "\n", |
| "%load_ext hamilton.plugins.jupyter_magic\n", |
| "logging.basicConfig(stream=sys.stdout)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 2, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:41:01.783934Z", |
| "start_time": "2024-06-05T05:41:01.152301Z" |
| } |
| }, |
| "outputs": [ |
| { |
| "data": { |
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| "<title>spend_std_dev</title>\n", |
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| "<title>function</title>\n", |
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| ], |
| "source": [ |
| "%%cell_to_module my_functions --display\n", |
| "# Cell 2 - Define your functions in a module.\n", |
| "import pandas as pd\n", |
| "\n", |
| "def avg_3wk_spend(spend: pd.Series) -> pd.Series:\n", |
| " \"\"\"Rolling 3 week average spend.\"\"\"\n", |
| " return spend.rolling(3).mean()\n", |
| "\n", |
| "def spend_per_signup(spend: pd.Series, signups: pd.Series) -> pd.Series:\n", |
| " \"\"\"The cost per signup in relation to spend.\"\"\"\n", |
| " return spend / signups\n", |
| "\n", |
| "def spend_mean(spend: pd.Series) -> float:\n", |
| " \"\"\"Shows function creating a scalar. In this case it computes the mean of the entire column.\"\"\"\n", |
| " return spend.mean()\n", |
| "\n", |
| "def spend_zero_mean(spend: pd.Series, spend_mean: float) -> pd.Series:\n", |
| " \"\"\"Shows function that takes a scalar. In this case to zero mean spend.\"\"\"\n", |
| " return spend - spend_mean\n", |
| "\n", |
| "def spend_std_dev(spend: pd.Series) -> float:\n", |
| " \"\"\"Function that computes the standard deviation of the spend column.\"\"\"\n", |
| " return spend.std()\n", |
| "\n", |
| "def spend_zero_mean_unit_variance(spend_zero_mean: pd.Series, spend_std_dev: float) -> pd.Series:\n", |
| " \"\"\"Function showing one way to make spend have zero mean and unit variance.\"\"\"\n", |
| " return spend_zero_mean / spend_std_dev\n" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 3, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2023-11-08T00:06:17.404504Z", |
| "start_time": "2023-11-08T00:06:17.343242Z" |
| }, |
| "pycharm": { |
| "name": "#%%\n" |
| } |
| }, |
| "outputs": [], |
| "source": [ |
| "# Cell 3 - Optional - if you have existing modules you can import them here.\n", |
| "# We use the autoreload extension that comes with ipython to automatically reload modules when\n", |
| "# the code in them changes.\n", |
| "\n", |
| "# import the jupyter extension\n", |
| "%load_ext autoreload\n", |
| "# set it to only reload the modules imported\n", |
| "%autoreload 1\n", |
| "# import the function modules you want to reload when they change.\n", |
| "# i.e. these should be your modules you write your functions in. As you change them,\n", |
| "# they will be reimported without you having to do anything.\n", |
| "# %aimport NAME_OF_MODULE # uncomment and replace NAME_OF_MODULE with the name of your module" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 4, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:43:08.346466Z", |
| "start_time": "2024-06-05T05:43:07.937399Z" |
| }, |
| "pycharm": { |
| "name": "#%%\n" |
| } |
| }, |
| "outputs": [ |
| { |
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| "%%cell_to_module extra_functions --display\n", |
| "# Cell 4 - Define your new Hamilton functions \n", |
| "import numpy as np\n", |
| "import pandas as pd\n", |
| "# Look at `my_functions` to see how these functions connect.\n", |
| "def signups() -> pd.Series:\n", |
| " \"\"\"Returns sign up values\"\"\"\n", |
| " return pd.Series([1, 10, 50, 100, 200, 400])\n", |
| "\n", |
| "def spend() -> pd.Series:\n", |
| " \"\"\"Returns the spend values\"\"\"\n", |
| " return pd.Series([10, 10, 20, 40, 40, 50])\n", |
| "\n", |
| "def log_spend_per_signup(spend_per_signup: pd.Series) -> pd.Series:\n", |
| " \"\"\"Simple function taking the logarithm of spend over signups.\"\"\"\n", |
| " return np.log(spend_per_signup)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 5, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:43:42.229169Z", |
| "start_time": "2024-06-05T05:43:42.210553Z" |
| }, |
| "pycharm": { |
| "name": "#%%\n" |
| } |
| }, |
| "outputs": [], |
| "source": [ |
| "# Cell 5 - Instantiate the Hamilton driver and pass it the right things in.\n", |
| "initial_config = {}\n", |
| "# my_functions and extra_functions are the modules we created in cells 2 and 4.\n", |
| "dr = driver.Driver(initial_config, my_functions, extra_functions) # can pass in multiple modules\n", |
| "# we need to specify what we want in the final dataframe.\n", |
| "output_columns = [\n", |
| " \"spend\",\n", |
| " \"signups\",\n", |
| " \"avg_3wk_spend\",\n", |
| " \"spend_per_signup\",\n", |
| " \"spend_zero_mean_unit_variance\",\n", |
| "]" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 6, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:43:52.023683Z", |
| "start_time": "2024-06-05T05:43:51.626814Z" |
| } |
| }, |
| "outputs": [ |
| { |
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| "<path fill=\"none\" stroke=\"black\" d=\"M66.78,-205.7C78.22,-227.08 95.4,-254.88 116.1,-274.8 116.71,-275.38 117.33,-275.96 117.95,-276.54\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"115.47,-279.02 125.38,-282.75 119.96,-273.65 115.47,-279.02\"/>\n", |
| "</g>\n", |
| "<!-- spend_mean->spend_zero_mean -->\n", |
| "<g id=\"edge3\" class=\"edge\">\n", |
| "<title>spend_mean->spend_zero_mean</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M239.73,-60.67C245.91,-64.56 252.03,-68.65 257.7,-72.8 283.06,-91.32 309.3,-114.57 330.07,-134.09\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"327.57,-136.54 337.23,-140.88 332.38,-131.46 327.57,-136.54\"/>\n", |
| "</g>\n", |
| "<!-- spend_per_signup->log_spend_per_signup -->\n", |
| "<g id=\"edge4\" class=\"edge\">\n", |
| "<title>spend_per_signup->log_spend_per_signup</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M258.19,-315.8C263.82,-315.8 269.56,-315.8 275.32,-315.8\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"274.89,-319.3 284.89,-315.8 274.89,-312.3 274.89,-319.3\"/>\n", |
| "</g>\n", |
| "<!-- function -->\n", |
| "<g id=\"node10\" class=\"node\">\n", |
| "<title>function</title>\n", |
| "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M72.85,-402.1C72.85,-402.1 28,-402.1 28,-402.1 22,-402.1 16,-396.1 16,-390.1 16,-390.1 16,-377.5 16,-377.5 16,-371.5 22,-365.5 28,-365.5 28,-365.5 72.85,-365.5 72.85,-365.5 78.85,-365.5 84.85,-371.5 84.85,-377.5 84.85,-377.5 84.85,-390.1 84.85,-390.1 84.85,-396.1 78.85,-402.1 72.85,-402.1\"/>\n", |
| "<text text-anchor=\"middle\" x=\"50.42\" y=\"-378\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">function</text>\n", |
| "</g>\n", |
| "</g>\n", |
| "</svg>\n" |
| ], |
| "text/plain": [ |
| "<graphviz.graphs.Digraph at 0x14cca3fa0>" |
| ] |
| }, |
| "execution_count": 6, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "# Cell 5 - visualize execution\n", |
| "# To visualize do `pip install \"sf-hamilton[visualization]\"` if you want these to work\n", |
| "\n", |
| "# visualize all possible functions\n", |
| "dr.display_all_functions() # no args needed for jupyter" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 7, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:43:52.549992Z", |
| "start_time": "2024-06-05T05:43:52.259829Z" |
| }, |
| "pycharm": { |
| "name": "#%%\n" |
| } |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "image/svg+xml": [ |
| "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n", |
| "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", |
| " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", |
| "<!-- Generated by graphviz version 10.0.1 (20240210.2158)\n", |
| " -->\n", |
| "<!-- Pages: 1 -->\n", |
| "<svg width=\"698pt\" height=\"504pt\"\n", |
| " viewBox=\"0.00 0.00 698.40 503.80\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", |
| "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 499.8)\">\n", |
| "<polygon fill=\"white\" stroke=\"none\" points=\"-4,4 -4,-499.8 694.4,-499.8 694.4,4 -4,4\"/>\n", |
| "<g id=\"clust1\" class=\"cluster\">\n", |
| "<title>cluster__legend</title>\n", |
| "<polygon fill=\"#ffffff\" stroke=\"black\" points=\"8,-357.8 8,-487.8 92.85,-487.8 92.85,-357.8 8,-357.8\"/>\n", |
| "<text text-anchor=\"middle\" x=\"50.42\" y=\"-470.5\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">Legend</text>\n", |
| "</g>\n", |
| "<!-- signups -->\n", |
| "<g id=\"node1\" class=\"node\">\n", |
| "<title>signups</title>\n", |
| "<path fill=\"#ffc857\" stroke=\"black\" d=\"M75.1,-347.6C75.1,-347.6 25.75,-347.6 25.75,-347.6 19.75,-347.6 13.75,-341.6 13.75,-335.6 13.75,-335.6 13.75,-296 13.75,-296 13.75,-290 19.75,-284 25.75,-284 25.75,-284 75.1,-284 75.1,-284 81.1,-284 87.1,-290 87.1,-296 87.1,-296 87.1,-335.6 87.1,-335.6 87.1,-341.6 81.1,-347.6 75.1,-347.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"24.55\" y=\"-324.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">signups</text>\n", |
| "<text text-anchor=\"start\" x=\"31.3\" y=\"-296.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">Series</text>\n", |
| "</g>\n", |
| "<!-- spend_per_signup -->\n", |
| "<g id=\"node7\" class=\"node\">\n", |
| "<title>spend_per_signup</title>\n", |
| "<path fill=\"#ffc857\" stroke=\"black\" d=\"M245.7,-347.6C245.7,-347.6 128.1,-347.6 128.1,-347.6 122.1,-347.6 116.1,-341.6 116.1,-335.6 116.1,-335.6 116.1,-296 116.1,-296 116.1,-290 122.1,-284 128.1,-284 128.1,-284 245.7,-284 245.7,-284 251.7,-284 257.7,-290 257.7,-296 257.7,-296 257.7,-335.6 257.7,-335.6 257.7,-341.6 251.7,-347.6 245.7,-347.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"126.9\" y=\"-324.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">spend_per_signup</text>\n", |
| "<text text-anchor=\"start\" x=\"167.77\" y=\"-296.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">Series</text>\n", |
| "</g>\n", |
| "<!-- signups->spend_per_signup -->\n", |
| "<g id=\"edge7\" class=\"edge\">\n", |
| "<title>signups->spend_per_signup</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M87.46,-315.8C92.82,-315.8 98.52,-315.8 104.36,-315.8\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"104.23,-319.3 114.23,-315.8 104.23,-312.3 104.23,-319.3\"/>\n", |
| "</g>\n", |
| "<!-- spend_std_dev -->\n", |
| "<g id=\"node2\" class=\"node\">\n", |
| "<title>spend_std_dev</title>\n", |
| "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M234.82,-265.6C234.82,-265.6 138.97,-265.6 138.97,-265.6 132.97,-265.6 126.97,-259.6 126.97,-253.6 126.97,-253.6 126.97,-214 126.97,-214 126.97,-208 132.97,-202 138.97,-202 138.97,-202 234.82,-202 234.82,-202 240.82,-202 246.82,-208 246.82,-214 246.82,-214 246.82,-253.6 246.82,-253.6 246.82,-259.6 240.82,-265.6 234.82,-265.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"137.77\" y=\"-242.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">spend_std_dev</text>\n", |
| "<text text-anchor=\"start\" x=\"174.15\" y=\"-214.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">float</text>\n", |
| "</g>\n", |
| "<!-- spend_zero_mean_unit_variance -->\n", |
| "<g id=\"node8\" class=\"node\">\n", |
| "<title>spend_zero_mean_unit_variance</title>\n", |
| "<path fill=\"#ffc857\" stroke=\"black\" d=\"M678.4,-235.6C678.4,-235.6 467.8,-235.6 467.8,-235.6 461.8,-235.6 455.8,-229.6 455.8,-223.6 455.8,-223.6 455.8,-184 455.8,-184 455.8,-178 461.8,-172 467.8,-172 467.8,-172 678.4,-172 678.4,-172 684.4,-172 690.4,-178 690.4,-184 690.4,-184 690.4,-223.6 690.4,-223.6 690.4,-229.6 684.4,-235.6 678.4,-235.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"466.6\" y=\"-212.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">spend_zero_mean_unit_variance</text>\n", |
| "<text text-anchor=\"start\" x=\"553.97\" y=\"-184.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">Series</text>\n", |
| "</g>\n", |
| "<!-- spend_std_dev->spend_zero_mean_unit_variance -->\n", |
| "<g id=\"edge9\" class=\"edge\">\n", |
| "<title>spend_std_dev->spend_zero_mean_unit_variance</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M247.09,-229.18C299.42,-225.09 377.56,-218.99 444.11,-213.79\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"444.33,-217.29 454.03,-213.02 443.79,-210.31 444.33,-217.29\"/>\n", |
| "</g>\n", |
| "<!-- spend_zero_mean -->\n", |
| "<g id=\"node3\" class=\"node\">\n", |
| "<title>spend_zero_mean</title>\n", |
| "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M414.8,-205.6C414.8,-205.6 298.7,-205.6 298.7,-205.6 292.7,-205.6 286.7,-199.6 286.7,-193.6 286.7,-193.6 286.7,-154 286.7,-154 286.7,-148 292.7,-142 298.7,-142 298.7,-142 414.8,-142 414.8,-142 420.8,-142 426.8,-148 426.8,-154 426.8,-154 426.8,-193.6 426.8,-193.6 426.8,-199.6 420.8,-205.6 414.8,-205.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"297.5\" y=\"-182.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">spend_zero_mean</text>\n", |
| "<text text-anchor=\"start\" x=\"337.62\" y=\"-154.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">Series</text>\n", |
| "</g>\n", |
| "<!-- spend_zero_mean->spend_zero_mean_unit_variance -->\n", |
| "<g id=\"edge8\" class=\"edge\">\n", |
| "<title>spend_zero_mean->spend_zero_mean_unit_variance</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M427.05,-183.5C432.64,-184.28 438.39,-185.09 444.22,-185.9\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"443.63,-189.35 454.02,-187.27 444.6,-182.42 443.63,-189.35\"/>\n", |
| "</g>\n", |
| "<!-- spend -->\n", |
| "<g id=\"node4\" class=\"node\">\n", |
| "<title>spend</title>\n", |
| "<path fill=\"#ffc857\" stroke=\"black\" d=\"M69.1,-205.6C69.1,-205.6 31.75,-205.6 31.75,-205.6 25.75,-205.6 19.75,-199.6 19.75,-193.6 19.75,-193.6 19.75,-154 19.75,-154 19.75,-148 25.75,-142 31.75,-142 31.75,-142 69.1,-142 69.1,-142 75.1,-142 81.1,-148 81.1,-154 81.1,-154 81.1,-193.6 81.1,-193.6 81.1,-199.6 75.1,-205.6 69.1,-205.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"30.55\" y=\"-182.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">spend</text>\n", |
| "<text text-anchor=\"start\" x=\"31.3\" y=\"-154.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">Series</text>\n", |
| "</g>\n", |
| "<!-- spend->spend_std_dev -->\n", |
| "<g id=\"edge1\" class=\"edge\">\n", |
| "<title>spend->spend_std_dev</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M81.27,-187.12C91.73,-191.78 103.96,-197.24 116.29,-202.74\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"114.7,-205.86 125.26,-206.74 117.55,-199.47 114.7,-205.86\"/>\n", |
| "</g>\n", |
| "<!-- spend->spend_zero_mean -->\n", |
| "<g id=\"edge2\" class=\"edge\">\n", |
| "<title>spend->spend_zero_mean</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M81.44,-173.8C126.07,-173.8 211.51,-173.8 275.23,-173.8\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"274.94,-177.3 284.94,-173.8 274.94,-170.3 274.94,-177.3\"/>\n", |
| "</g>\n", |
| "<!-- avg_3wk_spend -->\n", |
| "<g id=\"node5\" class=\"node\">\n", |
| "<title>avg_3wk_spend</title>\n", |
| "<path fill=\"#ffc857\" stroke=\"black\" d=\"M237.82,-145.6C237.82,-145.6 135.97,-145.6 135.97,-145.6 129.97,-145.6 123.97,-139.6 123.97,-133.6 123.97,-133.6 123.97,-94 123.97,-94 123.97,-88 129.97,-82 135.97,-82 135.97,-82 237.82,-82 237.82,-82 243.82,-82 249.82,-88 249.82,-94 249.82,-94 249.82,-133.6 249.82,-133.6 249.82,-139.6 243.82,-145.6 237.82,-145.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"134.77\" y=\"-122.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">avg_3wk_spend</text>\n", |
| "<text text-anchor=\"start\" x=\"167.77\" y=\"-94.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">Series</text>\n", |
| "</g>\n", |
| "<!-- spend->avg_3wk_spend -->\n", |
| "<g id=\"edge4\" class=\"edge\">\n", |
| "<title>spend->avg_3wk_spend</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M81.27,-160.48C90.87,-156.2 101.95,-151.25 113.25,-146.22\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"114.55,-149.47 122.26,-142.2 111.7,-143.07 114.55,-149.47\"/>\n", |
| "</g>\n", |
| "<!-- spend_mean -->\n", |
| "<g id=\"node6\" class=\"node\">\n", |
| "<title>spend_mean</title>\n", |
| "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M227.32,-63.6C227.32,-63.6 146.47,-63.6 146.47,-63.6 140.47,-63.6 134.47,-57.6 134.47,-51.6 134.47,-51.6 134.47,-12 134.47,-12 134.47,-6 140.47,0 146.47,0 146.47,0 227.32,0 227.32,0 233.32,0 239.32,-6 239.32,-12 239.32,-12 239.32,-51.6 239.32,-51.6 239.32,-57.6 233.32,-63.6 227.32,-63.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"145.27\" y=\"-40.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">spend_mean</text>\n", |
| "<text text-anchor=\"start\" x=\"174.15\" y=\"-12.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">float</text>\n", |
| "</g>\n", |
| "<!-- spend->spend_mean -->\n", |
| "<g id=\"edge5\" class=\"edge\">\n", |
| "<title>spend->spend_mean</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M66.78,-141.9C78.22,-120.52 95.4,-92.72 116.1,-72.8 118.92,-70.09 121.95,-67.48 125.12,-64.98\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"127.08,-67.88 133.1,-59.16 122.96,-62.23 127.08,-67.88\"/>\n", |
| "</g>\n", |
| "<!-- spend->spend_per_signup -->\n", |
| "<g id=\"edge6\" class=\"edge\">\n", |
| "<title>spend->spend_per_signup</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M66.78,-205.7C78.22,-227.08 95.4,-254.88 116.1,-274.8 116.71,-275.38 117.33,-275.96 117.95,-276.54\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"115.47,-279.02 125.38,-282.75 119.96,-273.65 115.47,-279.02\"/>\n", |
| "</g>\n", |
| "<!-- spend_mean->spend_zero_mean -->\n", |
| "<g id=\"edge3\" class=\"edge\">\n", |
| "<title>spend_mean->spend_zero_mean</title>\n", |
| "<path fill=\"none\" stroke=\"black\" d=\"M239.65,-60.05C245.9,-64.08 252.06,-68.37 257.7,-72.8 280.47,-90.68 303.16,-113.64 320.98,-133.15\"/>\n", |
| "<polygon fill=\"black\" stroke=\"black\" points=\"318.24,-135.34 327.53,-140.43 323.44,-130.66 318.24,-135.34\"/>\n", |
| "</g>\n", |
| "<!-- function -->\n", |
| "<g id=\"node9\" class=\"node\">\n", |
| "<title>function</title>\n", |
| "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M72.85,-402.1C72.85,-402.1 28,-402.1 28,-402.1 22,-402.1 16,-396.1 16,-390.1 16,-390.1 16,-377.5 16,-377.5 16,-371.5 22,-365.5 28,-365.5 28,-365.5 72.85,-365.5 72.85,-365.5 78.85,-365.5 84.85,-371.5 84.85,-377.5 84.85,-377.5 84.85,-390.1 84.85,-390.1 84.85,-396.1 78.85,-402.1 72.85,-402.1\"/>\n", |
| "<text text-anchor=\"middle\" x=\"50.42\" y=\"-378\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">function</text>\n", |
| "</g>\n", |
| "<!-- output -->\n", |
| "<g id=\"node10\" class=\"node\">\n", |
| "<title>output</title>\n", |
| "<path fill=\"#ffc857\" stroke=\"black\" d=\"M67.97,-457.1C67.97,-457.1 32.87,-457.1 32.87,-457.1 26.87,-457.1 20.87,-451.1 20.87,-445.1 20.87,-445.1 20.87,-432.5 20.87,-432.5 20.87,-426.5 26.87,-420.5 32.87,-420.5 32.87,-420.5 67.97,-420.5 67.97,-420.5 73.97,-420.5 79.97,-426.5 79.97,-432.5 79.97,-432.5 79.97,-445.1 79.97,-445.1 79.97,-451.1 73.97,-457.1 67.97,-457.1\"/>\n", |
| "<text text-anchor=\"middle\" x=\"50.42\" y=\"-433\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">output</text>\n", |
| "</g>\n", |
| "</g>\n", |
| "</svg>\n" |
| ], |
| "text/plain": [ |
| "<graphviz.graphs.Digraph at 0x14cca3a90>" |
| ] |
| }, |
| "execution_count": 7, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "# visualize just the execution path\n", |
| "dr.visualize_execution(output_columns) # no other args needed for jupyter" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 8, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:43:54.899373Z", |
| "start_time": "2024-06-05T05:43:54.609411Z" |
| }, |
| "collapsed": false, |
| "jupyter": { |
| "outputs_hidden": false |
| } |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "image/svg+xml": [ |
| "<?xml version=\"1.0\" encoding=\"UTF-8\" standalone=\"no\"?>\n", |
| "<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\n", |
| " \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\n", |
| "<!-- Generated by graphviz version 10.0.1 (20240210.2158)\n", |
| " -->\n", |
| "<!-- Pages: 1 -->\n", |
| "<svg width=\"674pt\" height=\"225pt\"\n", |
| " viewBox=\"0.00 0.00 674.40 224.80\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\n", |
| "<g id=\"graph0\" class=\"graph\" transform=\"scale(1 1) rotate(0) translate(4 220.8)\">\n", |
| "<polygon fill=\"white\" stroke=\"none\" points=\"-4,4 -4,-220.8 670.4,-220.8 670.4,4 -4,4\"/>\n", |
| "<g id=\"clust1\" class=\"cluster\">\n", |
| "<title>cluster__legend</title>\n", |
| "<polygon fill=\"#ffffff\" stroke=\"black\" points=\"8,-133.8 8,-208.8 92.85,-208.8 92.85,-133.8 8,-133.8\"/>\n", |
| "<text text-anchor=\"middle\" x=\"50.42\" y=\"-191.5\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">Legend</text>\n", |
| "</g>\n", |
| "<!-- spend_std_dev -->\n", |
| "<g id=\"node1\" class=\"node\">\n", |
| "<title>spend_std_dev</title>\n", |
| "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M221.7,-183.6C221.7,-183.6 125.85,-183.6 125.85,-183.6 119.85,-183.6 113.85,-177.6 113.85,-171.6 113.85,-171.6 113.85,-132 113.85,-132 113.85,-126 119.85,-120 125.85,-120 125.85,-120 221.7,-120 221.7,-120 227.7,-120 233.7,-126 233.7,-132 233.7,-132 233.7,-171.6 233.7,-171.6 233.7,-177.6 227.7,-183.6 221.7,-183.6\"/>\n", |
| "<text text-anchor=\"start\" x=\"124.65\" y=\"-160.5\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">spend_std_dev</text>\n", |
| "<text text-anchor=\"start\" x=\"161.02\" y=\"-132.5\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">float</text>\n", |
| "</g>\n", |
| "<!-- spend_zero_mean_unit_variance -->\n", |
| "<g id=\"node5\" class=\"node\">\n", |
| "<title>spend_zero_mean_unit_variance</title>\n", |
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| "<!-- spend_std_dev->spend_zero_mean_unit_variance -->\n", |
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| "<title>spend_zero_mean</title>\n", |
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| "<!-- spend -->\n", |
| "<g id=\"node3\" class=\"node\">\n", |
| "<title>spend</title>\n", |
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| "<!-- spend->spend_std_dev -->\n", |
| "<g id=\"edge1\" class=\"edge\">\n", |
| "<title>spend->spend_std_dev</title>\n", |
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| "<title>spend_mean</title>\n", |
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| "<title>spend->spend_mean</title>\n", |
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| "</g>\n", |
| "<!-- function -->\n", |
| "<g id=\"node6\" class=\"node\">\n", |
| "<title>function</title>\n", |
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| "</svg>\n" |
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| "text/plain": [ |
| "<graphviz.graphs.Digraph at 0x14cca3c70>" |
| ] |
| }, |
| "execution_count": 8, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "# visualize the path of execution between two functions\n", |
| "dr.visualize_path_between(\"spend_mean\", \"spend_zero_mean_unit_variance\",\n", |
| " strict_path_visualization=False)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 9, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2024-06-05T05:43:57.619299Z", |
| "start_time": "2024-06-05T05:43:57.580545Z" |
| } |
| }, |
| "outputs": [ |
| { |
| "data": { |
| "text/html": [ |
| "<div>\n", |
| "<style scoped>\n", |
| " .dataframe tbody tr th:only-of-type {\n", |
| " vertical-align: middle;\n", |
| " }\n", |
| "\n", |
| " .dataframe tbody tr th {\n", |
| " vertical-align: top;\n", |
| " }\n", |
| "\n", |
| " .dataframe thead th {\n", |
| " text-align: right;\n", |
| " }\n", |
| "</style>\n", |
| "<table border=\"1\" class=\"dataframe\">\n", |
| " <thead>\n", |
| " <tr style=\"text-align: right;\">\n", |
| " <th></th>\n", |
| " <th>spend</th>\n", |
| " <th>signups</th>\n", |
| " <th>avg_3wk_spend</th>\n", |
| " <th>spend_per_signup</th>\n", |
| " <th>spend_zero_mean_unit_variance</th>\n", |
| " </tr>\n", |
| " </thead>\n", |
| " <tbody>\n", |
| " <tr>\n", |
| " <th>0</th>\n", |
| " <td>10</td>\n", |
| " <td>1</td>\n", |
| " <td>NaN</td>\n", |
| " <td>10.000</td>\n", |
| " <td>-1.064405</td>\n", |
| " </tr>\n", |
| " <tr>\n", |
| " <th>1</th>\n", |
| " <td>10</td>\n", |
| " <td>10</td>\n", |
| " <td>NaN</td>\n", |
| " <td>1.000</td>\n", |
| " <td>-1.064405</td>\n", |
| " </tr>\n", |
| " <tr>\n", |
| " <th>2</th>\n", |
| " <td>20</td>\n", |
| " <td>50</td>\n", |
| " <td>13.333333</td>\n", |
| " <td>0.400</td>\n", |
| " <td>-0.483821</td>\n", |
| " </tr>\n", |
| " <tr>\n", |
| " <th>3</th>\n", |
| " <td>40</td>\n", |
| " <td>100</td>\n", |
| " <td>23.333333</td>\n", |
| " <td>0.400</td>\n", |
| " <td>0.677349</td>\n", |
| " </tr>\n", |
| " <tr>\n", |
| " <th>4</th>\n", |
| " <td>40</td>\n", |
| " <td>200</td>\n", |
| " <td>33.333333</td>\n", |
| " <td>0.200</td>\n", |
| " <td>0.677349</td>\n", |
| " </tr>\n", |
| " <tr>\n", |
| " <th>5</th>\n", |
| " <td>50</td>\n", |
| " <td>400</td>\n", |
| " <td>43.333333</td>\n", |
| " <td>0.125</td>\n", |
| " <td>1.257934</td>\n", |
| " </tr>\n", |
| " </tbody>\n", |
| "</table>\n", |
| "</div>" |
| ], |
| "text/plain": [ |
| " spend signups avg_3wk_spend spend_per_signup \\\n", |
| "0 10 1 NaN 10.000 \n", |
| "1 10 10 NaN 1.000 \n", |
| "2 20 50 13.333333 0.400 \n", |
| "3 40 100 23.333333 0.400 \n", |
| "4 40 200 33.333333 0.200 \n", |
| "5 50 400 43.333333 0.125 \n", |
| "\n", |
| " spend_zero_mean_unit_variance \n", |
| "0 -1.064405 \n", |
| "1 -1.064405 \n", |
| "2 -0.483821 \n", |
| "3 0.677349 \n", |
| "4 0.677349 \n", |
| "5 1.257934 " |
| ] |
| }, |
| "execution_count": 9, |
| "metadata": {}, |
| "output_type": "execute_result" |
| } |
| ], |
| "source": [ |
| "# let's create the dataframe!\n", |
| "dr.execute(output_columns)" |
| ] |
| }, |
| { |
| "cell_type": "code", |
| "execution_count": 8, |
| "metadata": { |
| "ExecuteTime": { |
| "end_time": "2023-05-22T22:27:18.053784Z", |
| "start_time": "2023-05-22T22:27:18.046215Z" |
| } |
| }, |
| "outputs": [], |
| "source": [] |
| } |
| ], |
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| "kernelspec": { |
| "display_name": "Python 3 (ipykernel)", |
| "language": "python", |
| "name": "python3" |
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| "codemirror_mode": { |
| "name": "ipython", |
| "version": 3 |
| }, |
| "file_extension": ".py", |
| "mimetype": "text/x-python", |
| "name": "python", |
| "nbconvert_exporter": "python", |
| "pygments_lexer": "ipython3", |
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| } |
| }, |
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| "nbformat_minor": 4 |
| } |
