{"cells":[{"cell_type":"markdown","source":"# K-means","metadata":{"id":"E9z1zz9ImN5X","cell_id":"a1f082e702d3434389caf54bdf9018f7","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"import numpy as np\nimport pandas as pd\nfrom matplotlib import pyplot as plt\nfrom sklearn.datasets import make_blobs\nfrom sklearn.cluster import KMeans\nX, y = make_blobs(n_samples=300, centers=4, cluster_std=0.60, random_state=0)\nwcss = []\nfor i in range(1, 11):\n    kmeans = KMeans(n_clusters=i, init='k-means++', max_iter=300, n_init=10, random_state=0)\n    kmeans.fit(X)\n    wcss.append(kmeans.inertia_)\nplt.plot(range(1, 11), wcss)\nplt.title('Metodo del codo')\nplt.xlabel('Numero de clusters')\nplt.ylabel('Inercia')\nplt.show()","metadata":{"id":"coVXI8ZegYrb","colab":{"height":295,"base_uri":"https://localhost:8080/"},"cell_id":"1a9038149ff8478a87ee6a610ee7328a","outputId":"8f6a60e6-0ef5-4836-ad59-6662063ff93d","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":1837,"user_tz":300,"timestamp":1642264577468},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":"<Figure size 432x288 with 1 Axes>"},"metadata":{"needs_background":"light"}}],"execution_count":9},{"cell_type":"code","source":"kmeans = KMeans(n_clusters=4, init='k-means++', max_iter=300, n_init=10, random_state=0)\npred_y = kmeans.fit_predict(X)\nplt.scatter(X[:,0], X[:,1])\nplt.scatter(kmeans.cluster_centers_[:, 0], kmeans.cluster_centers_[:, 1], s=300, c='red')\nplt.show()","metadata":{"id":"uZkQW3KqmMNP","colab":{"height":265,"base_uri":"https://localhost:8080/"},"cell_id":"47ea5fa5b5c248bfa4260d62845bdc05","outputId":"e88c0320-23ee-48f2-f207-5ff563bb1fcf","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos 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\n","text/plain":"<Figure size 432x288 with 1 Axes>"},"metadata":{"needs_background":"light"}}],"execution_count":10},{"cell_type":"markdown","source":"# Agglomerative Clustering","metadata":{"id":"SgiDR3Lpn1Df","cell_id":"5756dca92de9467c9915da4f569bc816","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"from google.colab import drive\nimport os\ndrive.mount('/content/gdrive')\n%cd '/content/gdrive/MyDrive/'","metadata":{"id":"ulllZObwn26a","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"4b18382047e84006b0d1ab0515da2a09","outputId":"e3e3d5ca-f68b-41d8-b64b-c8d17dc3e00e","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":43954,"user_tz":300,"timestamp":1642265060951},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"Mounted at /content/gdrive\n/content/gdrive/MyDrive\n"}],"execution_count":11},{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nfrom matplotlib import pyplot as plt\nfrom sklearn.cluster import AgglomerativeClustering\nimport scipy.cluster.hierarchy as sch\ndataset = pd.read_csv('Mall_Customers.csv')\nX = dataset.iloc[:, [3, 4]].values\nplt.figure(figsize=(10,6))\ndendrogram = sch.dendrogram(sch.linkage(X, method='ward'))","metadata":{"id":"8cMr3-kWoLIZ","colab":{"height":374,"base_uri":"https://localhost:8080/"},"cell_id":"7b71d606b4d94501995e806432c5bf61","outputId":"8a0506a9-8d6b-4979-894b-8f70e5276c38","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":7270,"user_tz":300,"timestamp":1642265166806},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":"<Figure size 720x432 with 1 Axes>"},"metadata":{"needs_background":"light"}}],"execution_count":14},{"cell_type":"code","source":"model = AgglomerativeClustering(n_clusters=5, affinity='euclidean', linkage='ward')\nmodel.fit(X)\nlabels = model.labels_\nplt.scatter(X[labels==0, 0], X[labels==0, 1], s=50, marker='o', color='red')\nplt.scatter(X[labels==1, 0], X[labels==1, 1], s=50, marker='o', color='blue')\nplt.scatter(X[labels==2, 0], X[labels==2, 1], s=50, marker='o', color='green')\nplt.scatter(X[labels==3, 0], X[labels==3, 1], s=50, marker='o', color='purple')\nplt.scatter(X[labels==4, 0], X[labels==4, 1], s=50, marker='o', color='orange')\nplt.show()","metadata":{"id":"JuhlHT14oflN","colab":{"height":265,"base_uri":"https://localhost:8080/"},"cell_id":"d6986c2282ec4a0caa0d51273c3f3913","outputId":"778aeec1-e047-4f01-df18-b666799eb5a8","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":299,"user_tz":300,"timestamp":1642265198374},"deepnote_cell_type":"code"},"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":"<Figure size 432x288 with 1 Axes>"},"metadata":{"needs_background":"light"}}],"execution_count":16},{"cell_type":"markdown","source":"# DBSCAN","metadata":{"id":"XROPQr5VqVdq","cell_id":"753fdf23b9364f1a8345cd3a0ea436d2","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"from sklearn.datasets import make_blobs\nfrom sklearn.cluster import DBSCAN\n# Configuracion de datos y parametros\nnum_samples_total = 1000;cluster_centers = [(3,3), (7,7)]\nnum_classes = len(cluster_centers)\nepsilon = 1.0;min_samples = 13\n# Generacion de datos\nX, y = make_blobs(n_samples = num_samples_total, centers = cluster_centers, n_features = num_classes, center_box=(0, 1), cluster_std = 0.5)\n# DBSCAN\ndb = DBSCAN(eps=epsilon, min_samples=min_samples).fit(X)\nlabels = db.labels_\nno_clusters = len(np.unique(labels) )\nno_noise = np.sum(np.array(labels) == -1, axis=0) # Ruido (Outliers)\nprint('#. clusters estimado: %d' % no_clusters)\nprint('# puntos ruidosos: %d' % no_noise)\n# Generar figura de datos\ncolors = list(map(lambda x: '#3b4cc0' if x == 1 else '#b40426', labels))\nplt.scatter(X[:,0], X[:,1], c=colors, marker=\"o\", picker=True)\nplt.title('Clasificacion DBSCAN')\nplt.xlabel('Eje X[0]');plt.ylabel('Eje X[1]')\nplt.show()","metadata":{"id":"exC6zW2UqWeG","colab":{"height":330,"base_uri":"https://localhost:8080/"},"cell_id":"0cfae3c3f8fa454f9b0cc089a5c338c5","outputId":"5dadba0d-89ee-44fa-b8c8-bd55ae673466","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":534,"user_tz":300,"timestamp":1642266041231},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"#. clusters estimado: 2\n# puntos ruidosos: 0\n"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":"<Figure size 432x288 with 1 Axes>"},"metadata":{"needs_background":"light"}}],"execution_count":17},{"cell_type":"markdown","source":"# Actividad Colaborativa","metadata":{"id":"xg4ZnWNKyhtU","cell_id":"680bc62eb8334d47afc543c912ec118d","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"import pandas as pd\nurl = 'https://raw.githubusercontent.com/JJTorresDS/stocks-ds-edu/main/stocks.csv'\ndf = pd.read_csv(url, index_col=0)\ndf.head(5)","metadata":{"id":"K4KdEIiqyjrh","colab":{"height":302,"base_uri":"https://localhost:8080/"},"cell_id":"b38c89cc1c8642a9bd8a4305a1c23a03","outputId":"12fdd7e6-48cb-4a09-da44-dbdca798b975","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":372,"user_tz":300,"timestamp":1642276826125},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-aa279427-a17c-44f1-8f6d-2354a35bc557\">\n    <div class=\"colab-df-container\">\n      <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>MCD</th>\n      <th>SBUX</th>\n      <th>GOOG</th>\n      <th>AMZN</th>\n      <th>MSFT</th>\n      <th>JPM</th>\n      <th>BAC</th>\n      <th>C</th>\n      <th>MAR</th>\n      <th>HLT</th>\n      <th>RCL</th>\n      <th>V</th>\n      <th>MA</th>\n      <th>PYPL</th>\n    </tr>\n    <tr>\n      <th>formatted_date</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>2016-01-01</th>\n      <td>106.332146</td>\n      <td>54.353962</td>\n      <td>742.950012</td>\n      <td>587.000000</td>\n      <td>49.853489</td>\n      <td>50.424938</td>\n      <td>12.573010</td>\n      <td>36.897804</td>\n      <td>57.754189</td>\n      <td>35.192841</td>\n      <td>74.235298</td>\n      <td>71.574371</td>\n      <td>85.822624</td>\n      <td>36.139999</td>\n    </tr>\n    <tr>\n      <th>2016-02-01</th>\n      <td>100.671043</td>\n      <td>52.064243</td>\n      <td>697.770020</td>\n      <td>552.520020</td>\n      <td>46.043667</td>\n      <td>48.033066</td>\n      <td>11.132540</td>\n      <td>33.707108</td>\n      <td>64.228912</td>\n      <td>41.061607</td>\n      <td>67.360649</td>\n      <td>69.556580</td>\n      <td>83.956566</td>\n      <td>38.139999</td>\n    </tr>\n    <tr>\n      <th>2016-03-01</th>\n      <td>108.782211</td>\n      <td>53.571442</td>\n      <td>744.950012</td>\n      <td>593.640015</td>\n      <td>50.339031</td>\n      <td>50.524323</td>\n      <td>12.021718</td>\n      <td>36.223217</td>\n      <td>67.336624</td>\n      <td>44.499886</td>\n      <td>74.790009</td>\n      <td>73.631477</td>\n      <td>91.278160</td>\n      <td>38.599998</td>\n    </tr>\n    <tr>\n      <th>2016-04-01</th>\n      <td>109.483307</td>\n      <td>50.457645</td>\n      <td>693.010010</td>\n      <td>659.590027</td>\n      <td>45.453705</td>\n      <td>53.919910</td>\n      <td>12.995729</td>\n      <td>40.153545</td>\n      <td>66.305466</td>\n      <td>43.716049</td>\n      <td>70.465584</td>\n      <td>74.363144</td>\n      <td>93.683258</td>\n      <td>39.180000</td>\n    </tr>\n    <tr>\n      <th>2016-05-01</th>\n      <td>105.648926</td>\n      <td>49.255203</td>\n      <td>735.719971</td>\n      <td>722.789978</td>\n      <td>48.306515</td>\n      <td>56.098225</td>\n      <td>13.201019</td>\n      <td>40.447887</td>\n      <td>62.474155</td>\n      <td>41.198154</td>\n      <td>70.456474</td>\n      <td>75.999847</td>\n      <td>92.817329</td>\n      <td>37.790001</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-aa279427-a17c-44f1-8f6d-2354a35bc557')\"\n              title=\"Convert this dataframe to an interactive table.\"\n              style=\"display:none;\">\n        \n  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n       width=\"24px\">\n    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 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Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  ","text/plain":"                       MCD       SBUX  ...         MA       PYPL\nformatted_date                         ...                      \n2016-01-01      106.332146  54.353962  ...  85.822624  36.139999\n2016-02-01      100.671043  52.064243  ...  83.956566  38.139999\n2016-03-01      108.782211  53.571442  ...  91.278160  38.599998\n2016-04-01      109.483307  50.457645  ...  93.683258  39.180000\n2016-05-01      105.648926  49.255203  ...  92.817329  37.790001\n\n[5 rows x 14 columns]"},"metadata":{},"execution_count":64}],"execution_count":64},{"cell_type":"code","source":"import numpy as np\nfrom scipy import stats\nfrom sklearn.preprocessing import MinMaxScaler\nX = df.values\nX_2= np.average(X,axis=0);X_3= np.std(X,axis=0)\ndf_n = pd.DataFrame();df_n['labels']=df.columns\ndf_n['Valores']=X_2;df_n['Sd']=X_3;df_n.index=df_n['labels']\ndf_n['Trim']=stats.trim_mean(X, 0.1)\ndf_n= df_n.drop(columns='labels')\ndf_n[['Valores', 'Sd','Trim']] = MinMaxScaler().fit_transform(df_n[['Valores', 'Sd','Trim']])\ndf_n","metadata":{"id":"dn-EIQdi6V1m","colab":{"height":520,"base_uri":"https://localhost:8080/"},"cell_id":"b726c4ecb08e4be2ac54e800e30aabd1","outputId":"24dca0b4-0c76-4745-a4e5-eeec7e4ad8e9","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":383,"user_tz":300,"timestamp":1642278903485},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-56be1b11-dd2d-4b18-bd6b-02bdc751dfa3\">\n    <div class=\"colab-df-container\">\n      <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>Valores</th>\n      <th>Sd</th>\n      <th>Trim</th>\n    </tr>\n    <tr>\n      <th>labels</th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>MCD</th>\n      <td>0.077086</td>\n      <td>0.037153</td>\n      <td>0.078899</td>\n    </tr>\n    <tr>\n      <th>SBUX</th>\n      <td>0.024480</td>\n      <td>0.014914</td>\n      <td>0.023919</td>\n    </tr>\n    <tr>\n      <th>GOOG</th>\n      <td>0.705615</td>\n      <td>0.614485</td>\n      <td>0.668251</td>\n    </tr>\n    <tr>\n      <th>AMZN</th>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>MSFT</th>\n      <td>0.058936</td>\n      <td>0.074416</td>\n      <td>0.055583</td>\n    </tr>\n    <tr>\n      <th>JPM</th>\n      <td>0.040301</td>\n      <td>0.023653</td>\n      <td>0.040679</td>\n    </tr>\n    <tr>\n      <th>BAC</th>\n      <td>0.000000</td>\n      <td>0.000000</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>C</th>\n      <td>0.016929</td>\n      <td>0.003106</td>\n      <td>0.017896</td>\n    </tr>\n    <tr>\n      <th>MAR</th>\n      <td>0.046938</td>\n      <td>0.021447</td>\n      <td>0.049068</td>\n    </tr>\n    <tr>\n      <th>HLT</th>\n      <td>0.030534</td>\n      <td>0.019685</td>\n      <td>0.030826</td>\n    </tr>\n    <tr>\n      <th>RCL</th>\n      <td>0.035688</td>\n      <td>0.015828</td>\n      <td>0.037564</td>\n    </tr>\n    <tr>\n      <th>V</th>\n      <td>0.065614</td>\n      <td>0.047340</td>\n      <td>0.066810</td>\n    </tr>\n    <tr>\n      <th>MA</th>\n      <td>0.105959</td>\n      <td>0.093324</td>\n      <td>0.107895</td>\n    </tr>\n    <tr>\n      <th>PYPL</th>\n      <td>0.049305</td>\n      <td>0.072439</td>\n      <td>0.045507</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button class=\"colab-df-convert\" 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Visit the ' +\n            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n            + ' to learn more about interactive tables.';\n          element.innerHTML = '';\n          dataTable['output_type'] = 'display_data';\n          await google.colab.output.renderOutput(dataTable, element);\n          const docLink = document.createElement('div');\n          docLink.innerHTML = docLinkHtml;\n          element.appendChild(docLink);\n        }\n      </script>\n    </div>\n  </div>\n  ","text/plain":"         Valores        Sd      Trim\nlabels                              \nMCD     0.077086  0.037153  0.078899\nSBUX    0.024480  0.014914  0.023919\nGOOG    0.705615  0.614485  0.668251\nAMZN    1.000000  1.000000  1.000000\nMSFT    0.058936  0.074416  0.055583\nJPM     0.040301  0.023653  0.040679\nBAC     0.000000  0.000000  0.000000\nC       0.016929  0.003106  0.017896\nMAR     0.046938  0.021447  0.049068\nHLT     0.030534  0.019685  0.030826\nRCL     0.035688  0.015828  0.037564\nV       0.065614  0.047340  0.066810\nMA      0.105959  0.093324  0.107895\nPYPL    0.049305  0.072439  0.045507"},"metadata":{},"execution_count":127}],"execution_count":127},{"cell_type":"code","source":"feature_mtx=df_n.values\nfeature_mtx\nimport scipy\nleng = feature_mtx.shape[0]\nD = scipy.zeros([leng,leng])\nfor i in range(leng):\n    for j in range(leng):\n        D[i,j] = scipy.spatial.distance.euclidean(feature_mtx[i], feature_mtx[j])\nimport pylab\nimport scipy.cluster.hierarchy\n\nZ = scipy.cluster.hierarchy.linkage(D, 'complete')\nZ","metadata":{"id":"eNtTY1NlZeLB","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"6aefd33199814675a4ebe374dab85a7c","outputId":"1b18bbab-53d1-42df-be82-6d5bf376a6c5","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":257,"user_tz":300,"timestamp":1642278906827},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stderr","text":"/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: DeprecationWarning:\n\nscipy.zeros is deprecated and will be removed in SciPy 2.0.0, use numpy.zeros instead\n\n/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:12: ClusterWarning:\n\nscipy.cluster: The symmetric non-negative hollow observation matrix looks suspiciously like an uncondensed distance matrix\n\n"},{"output_type":"execute_result","data":{"text/plain":"array([[9.00000000e+00, 1.00000000e+01, 2.26894708e-02, 2.00000000e+00],\n       [5.00000000e+00, 8.00000000e+00, 3.08200009e-02, 2.00000000e+00],\n       [4.00000000e+00, 1.30000000e+01, 3.88833638e-02, 2.00000000e+00],\n       [0.00000000e+00, 1.10000000e+01, 4.89040408e-02, 2.00000000e+00],\n       [1.00000000e+00, 7.00000000e+00, 5.30273136e-02, 2.00000000e+00],\n       [1.40000000e+01, 1.50000000e+01, 7.35171368e-02, 4.00000000e+00],\n       [1.60000000e+01, 1.70000000e+01, 9.64486055e-02, 4.00000000e+00],\n       [6.00000000e+00, 1.80000000e+01, 1.31912776e-01, 3.00000000e+00],\n       [1.90000000e+01, 2.00000000e+01, 2.05829402e-01, 8.00000000e+00],\n       [2.10000000e+01, 2.20000000e+01, 2.90559137e-01, 1.10000000e+01],\n       [1.20000000e+01, 2.30000000e+01, 4.18556906e-01, 1.20000000e+01],\n       [2.00000000e+00, 3.00000000e+00, 2.18246642e+00, 2.00000000e+00],\n       [2.40000000e+01, 2.50000000e+01, 5.87672395e+00, 1.40000000e+01]])"},"metadata":{},"execution_count":128}],"execution_count":128},{"cell_type":"code","source":"fig = pylab.figure(figsize=(12,6))\ndef llf(id):\n    return '[%s]' % (df_n.index[id] )\n    \ndendro = scipy.cluster.hierarchy.dendrogram(Z,  leaf_label_func=llf, leaf_rotation=0, leaf_font_size =12, orientation = 'top')","metadata":{"id":"rxcLKn-XZzvJ","colab":{"height":377,"base_uri":"https://localhost:8080/"},"cell_id":"cc37a5b9013a4c838f259b3f26681d3b","outputId":"bca7dc49-8a19-4c4d-8ce6-b98dc22131c8","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos 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\n","text/plain":"<Figure size 864x432 with 1 Axes>"},"metadata":{}}],"execution_count":129},{"cell_type":"code","source":"agglom = AgglomerativeClustering(n_clusters = 4, linkage = 'complete')\nagglom.fit(feature_mtx)\nagglom.labels_","metadata":{"id":"aVqtuDDDVl3w","colab":{"base_uri":"https://localhost:8080/"},"cell_id":"468f31a5996f4c3492e74314220e15c9","outputId":"26dfe119-8b7a-4acf-a2ba-0c02110e275c","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":296,"user_tz":300,"timestamp":1642278913396},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"array([0, 0, 2, 3, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0])"},"metadata":{},"execution_count":130}],"execution_count":130},{"cell_type":"code","source":"df_n['cluster_'] = agglom.labels_\ndf_n.head()","metadata":{"id":"BBpg7aLhypBn","colab":{"height":238,"base_uri":"https://localhost:8080/"},"cell_id":"1a36e0428a9043bb86ee32e8b5345c9c","outputId":"9a48c004-9d68-4aba-f159-dfff75048e4d","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":266,"user_tz":300,"timestamp":1642278914921},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/html":"\n  <div id=\"df-3314095d-6664-4619-a459-1883f4f55e10\">\n    <div class=\"colab-df-container\">\n      <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>Valores</th>\n      <th>Sd</th>\n      <th>Trim</th>\n      <th>cluster_</th>\n    </tr>\n    <tr>\n      <th>labels</th>\n      <th></th>\n      <th></th>\n      <th></th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>MCD</th>\n      <td>0.077086</td>\n      <td>0.037153</td>\n      <td>0.078899</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>SBUX</th>\n      <td>0.024480</td>\n      <td>0.014914</td>\n      <td>0.023919</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>GOOG</th>\n      <td>0.705615</td>\n      <td>0.614485</td>\n      <td>0.668251</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>AMZN</th>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>MSFT</th>\n      <td>0.058936</td>\n      <td>0.074416</td>\n      <td>0.055583</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>\n      <button 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0"},"metadata":{},"execution_count":131}],"execution_count":131},{"cell_type":"code","source":"fig, ax = plt.subplots(figsize=(12,6))\nax.scatter(np.log(df_n.Valores), np.log(df_n.Sd))\n\nfor i, txt in enumerate(df_n.index):\n  ax.annotate(txt, (np.log(df_n.Valores[i]), np.log(df_n.Sd[i])))","metadata":{"id":"6TbLOy3layRW","colab":{"height":513,"base_uri":"https://localhost:8080/"},"cell_id":"a926d5c801d340249bc5e109ee487233","outputId":"45dc5c21-479b-4b81-a840-7dbef44497dd","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":741,"user_tz":300,"timestamp":1642278919092},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stderr","text":"/usr/local/lib/python3.7/dist-packages/pandas/core/series.py:726: RuntimeWarning:\n\ndivide by zero encountered in log\n\n/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: RuntimeWarning:\n\ndivide by zero encountered in log\n\n"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":"<Figure size 864x432 with 1 Axes>"},"metadata":{}}],"execution_count":132},{"cell_type":"markdown","source":"# PCA","metadata":{"id":"pQTIK1Potgpw","cell_id":"dc94c3010c804c4397ba3c57f5ebe555","deepnote_cell_type":"markdown"}},{"cell_type":"code","source":"# Preprocesado y modelado\nfrom sklearn.decomposition import PCA\nfrom sklearn.pipeline import make_pipeline\nfrom sklearn.preprocessing import StandardScaler\nfrom sklearn.preprocessing import scale\nimport statsmodels.api as sm\nUSArrests = sm.datasets.get_rdataset(\"USArrests\", \"datasets\")\ndatos = USArrests.data\n# Entrenamiento modelo PCA con escalado de los datos\npca_pipe = make_pipeline(StandardScaler(), PCA())\npca_pipe.fit(datos)\n# Se extrae el modelo entrenado del pipeline\nmodelo_pca = pca_pipe.named_steps['pca']\n# Porcentaje de varianza explicada por cada componente\nprint('Porcentaje de varianza explicada por cada componente')\nprint(modelo_pca.explained_variance_ratio_)\nimport seaborn as sns;sns.set_style(\"whitegrid\")\nfig, ax = plt.subplots(nrows=1, ncols=1, figsize=(10, 5))\nax.bar(x= np.arange(modelo_pca.n_components_) + 1,height = modelo_pca.explained_variance_ratio_)\nfor x, y in zip(np.arange(len(datos.columns)) + 1, modelo_pca.explained_variance_ratio_):\n    label = round(y, 2)\n    ax.annotate(label,(x,y),textcoords=\"offset points\",xytext=(0,10),ha='center')\nax.set_xticks(np.arange(modelo_pca.n_components_) + 1);ax.set_ylim(0, 1.1)\nax.set_title('Porcentaje de varianza explicada por cada componente')\nax.set_xlabel('Componente principal')\nax.set_ylabel('Por. varianza explicada');","metadata":{"id":"u-xSHssNthfX","colab":{"height":385,"base_uri":"https://localhost:8080/"},"cell_id":"e13fb3499d6c4a588da3e00b0601bd6a","outputId":"024afdb5-203e-418a-8ece-faeb48b8a604","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":804,"user_tz":300,"timestamp":1642267027712},"deepnote_cell_type":"code"},"outputs":[{"output_type":"stream","name":"stdout","text":"Porcentaje de varianza explicada por cada componente\n[0.62006039 0.24744129 0.0891408  0.04335752]\n"},{"output_type":"display_data","data":{"image/png":"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\n","text/plain":"<Figure size 720x360 with 1 Axes>"},"metadata":{}}],"execution_count":20},{"cell_type":"code","source":"# Proyección de las observaciones de entrenamiento\n# ==============================================================================\nproyecciones = pca_pipe.transform(X=datos)\nproyecciones = pd.DataFrame(\n    proyecciones,\n    columns = ['PC1', 'PC2', 'PC3', 'PC4'],\n    index   = datos.index\n)\nproyecciones = np.dot(modelo_pca.components_, scale(datos).T)\nproyecciones = pd.DataFrame(proyecciones, index = ['PC1', 'PC2', 'PC3', 'PC4'])\nproyecciones = proyecciones.transpose().set_index(datos.index)\nplt.figure(figsize=(15,6))\nproyecciones['val']=proyecciones.index\nax = proyecciones.set_index('PC1')['PC2'].plot(style='o')\ndef label_point(x, y, val, ax):\n  a = pd.concat({'x': x, 'y': y, 'val': val}, axis=1)\n  for i, point in a.iterrows():\n    ax.text(point['x'], point['y'], str(point['val']))\nlabel_point(proyecciones.PC1, proyecciones.PC2, proyecciones.val, ax)\nplt.axvline(x=0,color='black');plt.axhline(y=0,color='black')\nplt.title('PC1 vs PC2 estados EU');plt.xlabel('PC1',color='k')\nplt.ylabel('PC2',color='black')","metadata":{"id":"XBR_dAtLwVIP","colab":{"height":421,"base_uri":"https://localhost:8080/"},"cell_id":"2a232d7d39a14043893f9b07ad6feee3","outputId":"e82cba9d-226a-4b35-b799-e421c7944fab","executionInfo":{"user":{"userId":"04741209928239412574","photoUrl":"https://lh3.googleusercontent.com/a-/AOh14Gi4e7mWJaOA2l-1KUn-omyigRGSrm83lG6XLzS5=s64","displayName":"david francisco bustos usta"},"status":"ok","elapsed":1006,"user_tz":300,"timestamp":1642267299466},"deepnote_cell_type":"code"},"outputs":[{"output_type":"execute_result","data":{"text/plain":"Text(0, 0.5, 'PC2')"},"metadata":{},"execution_count":21},{"output_type":"display_data","data":{"image/png":"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size 1080x432 with 1 Axes>"},"metadata":{}}],"execution_count":21},{"cell_type":"markdown","source":"<a style='text-decoration:none;line-height:16px;display:flex;color:#5B5B62;padding:10px;justify-content:end;' href='https://deepnote.com?utm_source=created-in-deepnote-cell&projectId=4f9037d8-f2e9-4683-9ce3-67576f784ec7' target=\"_blank\">\n<img alt='Created in deepnote.com' style='display:inline;max-height:16px;margin:0px;margin-right:7.5px;' 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