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{ | |
"cells": [ | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"# K-Means Clustering on Dog Sales" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 1, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"#importing various libraries needed\n", | |
"from pyspark.sql import SparkSession\n", | |
"from pyspark.sql.types import *\n", | |
"from pyspark.ml import PipelineModel\n", | |
"from pyspark.ml.classification import LogisticRegressionModel\n", | |
"import matplotlib.pyplot as plt\n", | |
"import seaborn as sns\n", | |
"from pyspark.sql.types import *\n", | |
"from pyspark.sql.functions import monotonically_increasing_id\n", | |
"from pyspark.ml.feature import VectorAssembler\n", | |
"import numpy as np\n", | |
"from pyspark.ml.clustering import KMeans\n", | |
"sns.set()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Connect to Spark" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 2, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"#I set this to local for testing. Change this to match your cluster.\n", | |
"spark = SparkSession.builder \\\n", | |
" .appName(\"Flight Predictor\") \\\n", | |
" .master(\"local[*]\") \\\n", | |
" .config(\"spark.driver.memory\",\"4g\")\\\n", | |
" .getOrCreate()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Since we know the schema, we can create the schema map ahead of time and save on time spent infering schema." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 3, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"schema = StructType(\n", | |
" [\n", | |
" StructField(\"region\", StringType(), True),\n", | |
" StructField(\"code\", StringType(), True), \n", | |
" StructField(\"state\", StringType(), True), \n", | |
" StructField(\"item_type\", StringType(), True), \n", | |
" StructField(\"item_sold\", StringType(), True), \n", | |
" StructField(\"units_sold\", DoubleType(), True),\n", | |
" StructField(\"unit_price\", DoubleType(), True), \n", | |
" StructField(\"total_revenue\", DoubleType(), True), \n", | |
" StructField(\"channel\", StringType(), True), \n", | |
" StructField(\"orderdate\", TimestampType(), True), \n", | |
" StructField(\"shipdate\", TimestampType(), True)\n", | |
" ]\n", | |
")" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Read in the DataFrame\n", | |
"_note: change this to your HDFS path_" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 4, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"dogsales_df = spark.read.csv(\n", | |
" path=\"file:///home/cdsw/dogsales.csv\",\n", | |
" header=False,\n", | |
" schema=schema\n", | |
")" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Basic Feature Engineering\n", | |
"Because something will *always* go wrong with the data, lets just remove the poential `null` row issues ahead of time." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 5, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"dogsales_df = dogsales_df.na.drop()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"Since this data is random generated, it doesn't have real clusters. The next cell creates some artificial data centers of gravity be doing to `groupby` opperations to exagerate some numerical values. This creates groups around `region | code | state | item_type | item_sold` and aggrates the total units sold and the average unit price." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 6, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"+--------+----+-----+----------------+-------------------+--------------+------------------+\n", | |
"| region|code|state| item_type| item_sold|all_units_sold| avg_unit_price|\n", | |
"+--------+----+-----+----------------+-------------------+--------------+------------------+\n", | |
"| Asia| CN|CN-AH|Collar & Leashes| Retractable Leash| 6.0| 24.63|\n", | |
"|Americas| US|US-NH| Toys| Squeak Toys| 30.0|2.6900000000000004|\n", | |
"| Europe| NL|NL-FL| Toys| Ball Launcher| 718.0|10.599999999999959|\n", | |
"| Asia| CN|CN-NM| Food|Royal Canin Dry 4kg| 140.0| 17.88999999999999|\n", | |
"| Europe| NL|NL-UT| Food|Royal Canin Dry 8kg| 103.0| 45.23000000000001|\n", | |
"+--------+----+-----+----------------+-------------------+--------------+------------------+\n", | |
"only showing top 5 rows\n", | |
"\n" | |
] | |
} | |
], | |
"source": [ | |
"dogsales_df\\\n", | |
" .groupby(\"region\",\"code\",\"state\",\"item_type\",\"item_sold\")\\\n", | |
" .agg({\"units_sold\":\"sum\",\"unit_price\":\"avg\"})\\\n", | |
" .withColumnRenamed(\"sum(units_sold)\", \"all_units_sold\")\\\n", | |
" .withColumnRenamed(\"avg(unit_price)\", \"avg_unit_price\")\\\n", | |
" .show(5)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"The data we've created is un-indexed, so we need to add one." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 7, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"agg_df = dogsales_df\\\n", | |
" .groupby(\"region\",\"code\",\"state\",\"item_type\",\"item_sold\")\\\n", | |
" .agg({\"units_sold\":\"sum\",\"unit_price\":\"avg\"})\\\n", | |
" .withColumnRenamed(\"sum(units_sold)\", \"all_units_sold\")\\\n", | |
" .withColumnRenamed(\"avg(unit_price)\", \"avg_unit_price\")\\\n", | |
" .withColumn(\"idx\",monotonically_increasing_id())" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 8, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"+--------+----+-----+----------------+-------------------+--------------+------------------+---+\n", | |
"| region|code|state| item_type| item_sold|all_units_sold| avg_unit_price|idx|\n", | |
"+--------+----+-----+----------------+-------------------+--------------+------------------+---+\n", | |
"| Asia| CN|CN-AH|Collar & Leashes| Retractable Leash| 6.0| 24.63| 0|\n", | |
"|Americas| US|US-NH| Toys| Squeak Toys| 30.0|2.6900000000000004| 1|\n", | |
"| Europe| NL|NL-FL| Toys| Ball Launcher| 718.0|10.599999999999959| 2|\n", | |
"| Asia| CN|CN-NM| Food|Royal Canin Dry 4kg| 140.0| 17.88999999999999| 3|\n", | |
"| Europe| NL|NL-UT| Food|Royal Canin Dry 8kg| 103.0| 45.23000000000001| 4|\n", | |
"+--------+----+-----+----------------+-------------------+--------------+------------------+---+\n", | |
"only showing top 5 rows\n", | |
"\n" | |
] | |
} | |
], | |
"source": [ | |
"agg_df.show(5)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"This first plot shows the distribution of the aggregation groups that was selected." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 9, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"<matplotlib.text.Text at 0x7f471c216b00>" | |
] | |
}, | |
"execution_count": 9, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f47387da160>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"dogsales_pdf = agg_df.toPandas()\n", | |
"plt.scatter(\n", | |
" x=dogsales_pdf['all_units_sold'],\n", | |
" y=dogsales_pdf['avg_unit_price'],\n", | |
" s=20, \n", | |
" edgecolor=\"black\"\n", | |
")\n", | |
"plt.xlabel(\"All Units Sold\")\n", | |
"plt.ylabel(\"Avg Unit Price\")" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Buildling the Pipeline\n", | |
"The next step is to create the K-Means pipeline in Spark" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 10, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"FEATURES_COL = ['all_units_sold','avg_unit_price']" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"We need to assemble the 2 numeric features we created into a Spark Vector using `Vector Assembler`." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 11, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"+---+--------------------+\n", | |
"|idx| features|\n", | |
"+---+--------------------+\n", | |
"| 0| [6.0,24.63]|\n", | |
"| 1|[30.0,2.690000000...|\n", | |
"| 2|[718.0,10.5999999...|\n", | |
"| 3|[140.0,17.8899999...|\n", | |
"| 4|[103.0,45.2300000...|\n", | |
"+---+--------------------+\n", | |
"only showing top 5 rows\n", | |
"\n" | |
] | |
} | |
], | |
"source": [ | |
"vecAssembler = VectorAssembler(inputCols=FEATURES_COL, outputCol=\"features\", handleInvalid=\"skip\")\n", | |
"df_kmeans = vecAssembler.transform(agg_df).select('idx','features')\n", | |
"df_kmeans.show(5)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Training the Model\n", | |
"K-Means does not automatically select the best number of centers, this is a decision you need to make. Plotting the cost fuction shows that after about k=5, there is little additional benefit to adding more centers." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 12, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"cost = np.zeros(10)\n", | |
"for k in range(2,10):\n", | |
" kmeans = KMeans().setK(k).setSeed(1).setFeaturesCol(\"features\")\n", | |
" model = kmeans.fit(df_kmeans.sample(False,0.1, seed=42))\n", | |
" cost[k] = model.computeCost(df_kmeans)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 13, | |
"metadata": { | |
"scrolled": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"text/plain": [ | |
"[<matplotlib.lines.Line2D at 0x7f4713ecd860>]" | |
] | |
}, | |
"execution_count": 13, | |
"metadata": {}, | |
"output_type": "execute_result" | |
}, | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f471c5cada0>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plt.plot(range(2,10),cost[2:10])" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"With a k=5, we can calculate the centers for the data." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 14, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"Cluster Centers: \n", | |
"[105.11719939 16.43004566]\n", | |
"[10.57334659 16.455818 ]\n", | |
"[1385.3 3.62]\n", | |
"[727.53571429 4.91107143]\n", | |
"[390.5 27.15722222]\n" | |
] | |
} | |
], | |
"source": [ | |
"k = 5\n", | |
"kmeans = KMeans().setK(k).setSeed(1).setFeaturesCol(\"features\")\n", | |
"model = kmeans.fit(df_kmeans)\n", | |
"centers = model.clusterCenters()\n", | |
"\n", | |
"print(\"Cluster Centers: \")\n", | |
"for center in centers:\n", | |
" print(center)" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Evaluating the Model\n", | |
"Spark uses [silhouette](https://en.wikipedia.org/wiki/Silhouette_(clustering)) to evaluate clustering model performance\n" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 15, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"Silhouette with squared euclidean distance = 0.855068432319465\n" | |
] | |
} | |
], | |
"source": [ | |
"from pyspark.ml.evaluation import ClusteringEvaluator\n", | |
"evaluator = ClusteringEvaluator()\n", | |
"predictions = model.transform(df_kmeans)\n", | |
"silhouette = evaluator.evaluate(predictions)\n", | |
"print(\"Silhouette with squared euclidean distance = \" + str(silhouette))" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"## Using the Predictions from the Model\n", | |
"Now that the model values have been calculater, we can add it back to the original data set and see what clusters where discovered." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 16, | |
"metadata": {}, | |
"outputs": [], | |
"source": [ | |
"transformed = model.transform(df_kmeans).select('idx', 'prediction')\n", | |
"rows = transformed.collect()\n", | |
"df_pred = spark.createDataFrame(rows)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 17, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"+---+----------+--------+----+-----+----------------+-------------------+--------------+------------------+\n", | |
"|idx|prediction| region|code|state| item_type| item_sold|all_units_sold| avg_unit_price|\n", | |
"+---+----------+--------+----+-----+----------------+-------------------+--------------+------------------+\n", | |
"| 0| 1| Asia| CN|CN-AH|Collar & Leashes| Retractable Leash| 6.0| 24.63|\n", | |
"| 1| 1|Americas| US|US-NH| Toys| Squeak Toys| 30.0|2.6900000000000004|\n", | |
"| 2| 3| Europe| NL|NL-FL| Toys| Ball Launcher| 718.0|10.599999999999959|\n", | |
"| 3| 0| Asia| CN|CN-NM| Food|Royal Canin Dry 4kg| 140.0| 17.88999999999999|\n", | |
"| 4| 0| Europe| NL|NL-UT| Food|Royal Canin Dry 8kg| 103.0| 45.23000000000001|\n", | |
"+---+----------+--------+----+-----+----------------+-------------------+--------------+------------------+\n", | |
"only showing top 5 rows\n", | |
"\n" | |
] | |
} | |
], | |
"source": [ | |
"df_pred = df_pred.join(agg_df, 'idx')\n", | |
"df_pred.show(5)" | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 18, | |
"metadata": {}, | |
"outputs": [ | |
{ | |
"name": "stdout", | |
"output_type": "stream", | |
"text": [ | |
"+----------+-------------------+-------------------+-----------------+\n", | |
"|prediction|avg(avg_unit_price)|avg(all_units_sold)|count(prediction)|\n", | |
"+----------+-------------------+-------------------+-----------------+\n", | |
"| 0| 16.430045662100454| 105.117199391172| 657|\n", | |
"| 1| 16.455818000994537| 10.57334659373446| 2011|\n", | |
"| 3| 4.911071428571418| 727.5357142857143| 28|\n", | |
"| 2| 3.6199999999999632| 1385.3| 10|\n", | |
"| 4| 27.15722222222221| 390.5| 36|\n", | |
"+----------+-------------------+-------------------+-----------------+\n", | |
"\n" | |
] | |
} | |
], | |
"source": [ | |
"df_pred\\\n", | |
" .groupby(\"prediction\")\\\n", | |
" .agg(\n", | |
" {\n", | |
" \"prediction\":\"count\",\n", | |
" \"avg_unit_price\":\"avg\",\n", | |
" \"all_units_sold\":\"avg\"\n", | |
" }\n", | |
" )\\\n", | |
" .show()" | |
] | |
}, | |
{ | |
"cell_type": "markdown", | |
"metadata": {}, | |
"source": [ | |
"### Ploting the Final Result\n", | |
"This plot show the clusters that were calculated, and where there centers are." | |
] | |
}, | |
{ | |
"cell_type": "code", | |
"execution_count": 19, | |
"metadata": { | |
"scrolled": false | |
}, | |
"outputs": [ | |
{ | |
"data": { | |
"image/png": 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\n", | |
"text/plain": [ | |
"<matplotlib.figure.Figure at 0x7f4713de1518>" | |
] | |
}, | |
"metadata": { | |
"needs_background": "light" | |
}, | |
"output_type": "display_data" | |
} | |
], | |
"source": [ | |
"plot_df = df_pred.toPandas()\n", | |
"def plotter():\n", | |
" plt.scatter(\n", | |
" x=plot_df['all_units_sold'],\n", | |
" y=plot_df['avg_unit_price'],\n", | |
" c=plot_df['prediction'],\n", | |
" s=20, \n", | |
" cmap='viridis',\n", | |
" edgecolor=\"black\"\n", | |
" )\n", | |
" plt.scatter(np.array(centers)[:, 0], np.array(centers)[:, 1], c='black', s=100, alpha=0.5);\n", | |
" \n", | |
" for number in range(0,np.array(centers).shape[0]):\n", | |
" plt.text(np.array(centers)[:, 0][number]-15, \n", | |
" np.array(centers)[:, 1][number]-1, \n", | |
" number, \n", | |
" horizontalalignment='left', \n", | |
" size='medium', \n", | |
" color='white', \n", | |
" weight='normal')\n", | |
"plotter()" | |
] | |
} | |
], | |
"metadata": { | |
"kernelspec": { | |
"display_name": "Python 3", | |
"language": "python", | |
"name": "python3" | |
}, | |
"language_info": { | |
"codemirror_mode": { | |
"name": "ipython", | |
"version": 3 | |
}, | |
"file_extension": ".py", | |
"mimetype": "text/x-python", | |
"name": "python", | |
"nbconvert_exporter": "python", | |
"pygments_lexer": "ipython3", | |
"version": "3.6.8" | |
} | |
}, | |
"nbformat": 4, | |
"nbformat_minor": 2 | |
} |
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