Data Science Essentials-Correlation Analysis and Data Transformations.ipynb

{"cells":[{"cell_type":"code","execution_count":3,"metadata":{"executionInfo":{"elapsed":215,"status":"ok","timestamp":1691526507070,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"},"user_tz":420},"id":"UX-k6OPHnsuM"},"outputs":[],"source":["#Import relevant libraries\n","import math\n","import matplotlib.pyplot as plt\n","import numpy as np, pandas as pd\n","import seaborn as sns"]},{"cell_type":"code","execution_count":5,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":16547,"status":"ok","timestamp":1691526577900,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"},"user_tz":420},"id":"jNFArpWBvlAt","outputId":"7cc69c36-60cb-4009-b169-22b16d39da3a"},"outputs":[{"output_type":"stream","name":"stdout","text":["Mounted at /content/drive\n"]}],"source":["from google.colab import drive\n","drive.mount('/content/drive')"]},{"cell_type":"markdown","source":["## 1. Parametric Correlation Analysis: Pearson Correlation\n","\n","\n","*   Uncover linear relationships between variables\n","*   Can't be used to rule out possible nonlinear relationships\n","\n"],"metadata":{"id":"-0VqBreLRwmL"}},{"cell_type":"code","source":["#Load housing price dataset\n","data = pd.read_excel(\"/content/drive/MyDrive/Grad School-Files/Job Search/Data Science Basics/HousePricePrediction.xlsx\")\n","data = data.dropna() #drop null columns\n","data.info()\n","#Find Null Values\n","data.isnull().sum(axis=0)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"P5Wwkmrtfcjb","executionInfo":{"status":"ok","timestamp":1691532420411,"user_tz":420,"elapsed":732,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"36958b16-55bc-4111-9c8f-0539fa8c808d"},"execution_count":32,"outputs":[{"output_type":"stream","name":"stdout","text":["<class 'pandas.core.frame.DataFrame'>\n","Int64Index: 1460 entries, 0 to 1459\n","Data columns (total 13 columns):\n"," #   Column        Non-Null Count  Dtype  \n","---  ------        --------------  -----  \n"," 0   Id            1460 non-null   int64  \n"," 1   MSSubClass    1460 non-null   int64  \n"," 2   MSZoning      1460 non-null   object \n"," 3   LotArea       1460 non-null   int64  \n"," 4   LotConfig     1460 non-null   object \n"," 5   BldgType      1460 non-null   object \n"," 6   OverallCond   1460 non-null   int64  \n"," 7   YearBuilt     1460 non-null   int64  \n"," 8   YearRemodAdd  1460 non-null   int64  \n"," 9   Exterior1st   1460 non-null   object \n"," 10  BsmtFinSF2    1460 non-null   float64\n"," 11  TotalBsmtSF   1460 non-null   float64\n"," 12  SalePrice     1460 non-null   float64\n","dtypes: float64(3), int64(6), object(4)\n","memory usage: 159.7+ KB\n"]},{"output_type":"execute_result","data":{"text/plain":["Id              0\n","MSSubClass      0\n","MSZoning        0\n","LotArea         0\n","LotConfig       0\n","BldgType        0\n","OverallCond     0\n","YearBuilt       0\n","YearRemodAdd    0\n","Exterior1st     0\n","BsmtFinSF2      0\n","TotalBsmtSF     0\n","SalePrice       0\n","dtype: int64"]},"metadata":{},"execution_count":32}]},{"cell_type":"code","source":["cont_columns = data.select_dtypes(include=[np.float, 'int64'])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"4sACvt5R2VBr","executionInfo":{"status":"ok","timestamp":1691526788706,"user_tz":420,"elapsed":152,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"041d2d83-6917-4dfe-dea4-0d32f90a68dd"},"execution_count":12,"outputs":[{"output_type":"stream","name":"stderr","text":["<ipython-input-12-67ad77724ec3>:1: DeprecationWarning: `np.float` is a deprecated alias for the builtin `float`. To silence this warning, use `float` by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use `np.float64` here.\n","Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations\n","  cont_columns = data.select_dtypes(include=[np.float, 'int64'])\n"]}]},{"cell_type":"code","source":["cont_columns.corr()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":332},"id":"a6mqGGzL3l57","executionInfo":{"status":"ok","timestamp":1691527048793,"user_tz":420,"elapsed":162,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"cee667e3-c67a-4cee-c63f-a1544e36768a"},"execution_count":21,"outputs":[{"output_type":"execute_result","data":{"text/plain":["                    Id  MSSubClass   LotArea  OverallCond  YearBuilt  \\\n","Id            1.000000    0.011156 -0.033226     0.012609  -0.012713   \n","MSSubClass    0.011156    1.000000 -0.139781    -0.059316   0.027850   \n","LotArea      -0.033226   -0.139781  1.000000    -0.005636   0.014228   \n","OverallCond   0.012609   -0.059316 -0.005636     1.000000  -0.375983   \n","YearBuilt    -0.012713    0.027850  0.014228    -0.375983   1.000000   \n","YearRemodAdd -0.021998    0.040581  0.013788     0.073741   0.592855   \n","BsmtFinSF2   -0.005968   -0.065649  0.111170     0.040229  -0.049107   \n","TotalBsmtSF  -0.015415   -0.238518  0.260833    -0.171098   0.391452   \n","SalePrice    -0.021917   -0.084284  0.263843    -0.077856   0.522897   \n","\n","              YearRemodAdd  BsmtFinSF2  TotalBsmtSF  SalePrice  \n","Id               -0.021998   -0.005968    -0.015415  -0.021917  \n","MSSubClass        0.040581   -0.065649    -0.238518  -0.084284  \n","LotArea           0.013788    0.111170     0.260833   0.263843  \n","OverallCond       0.073741    0.040229    -0.171098  -0.077856  \n","YearBuilt         0.592855   -0.049107     0.391452   0.522897  \n","YearRemodAdd      1.000000   -0.067759     0.291066   0.507101  \n","BsmtFinSF2       -0.067759    1.000000     0.104810  -0.011378  \n","TotalBsmtSF       0.291066    0.104810     1.000000   0.613581  \n","SalePrice         0.507101   -0.011378     0.613581   1.000000  "],"text/html":["\n","\n","  <div id=\"df-226763d2-8812-47e4-b5d5-d4840e7bc076\">\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>Id</th>\n","      <th>MSSubClass</th>\n","      <th>LotArea</th>\n","      <th>OverallCond</th>\n","      <th>YearBuilt</th>\n","      <th>YearRemodAdd</th>\n","      <th>BsmtFinSF2</th>\n","      <th>TotalBsmtSF</th>\n","      <th>SalePrice</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <th>Id</th>\n","      <td>1.000000</td>\n","      <td>0.011156</td>\n","      <td>-0.033226</td>\n","      <td>0.012609</td>\n","      <td>-0.012713</td>\n","      <td>-0.021998</td>\n","      <td>-0.005968</td>\n","      <td>-0.015415</td>\n","      <td>-0.021917</td>\n","    </tr>\n","    <tr>\n","      <th>MSSubClass</th>\n","      <td>0.011156</td>\n","      <td>1.000000</td>\n","      <td>-0.139781</td>\n","      <td>-0.059316</td>\n","      <td>0.027850</td>\n","      <td>0.040581</td>\n","      <td>-0.065649</td>\n","      <td>-0.238518</td>\n","      <td>-0.084284</td>\n","    </tr>\n","    <tr>\n","      <th>LotArea</th>\n","      <td>-0.033226</td>\n","      <td>-0.139781</td>\n","      <td>1.000000</td>\n","      <td>-0.005636</td>\n","      <td>0.014228</td>\n","      <td>0.013788</td>\n","      <td>0.111170</td>\n","      <td>0.260833</td>\n","      <td>0.263843</td>\n","    </tr>\n","    <tr>\n","      <th>OverallCond</th>\n","      <td>0.012609</td>\n","      <td>-0.059316</td>\n","      <td>-0.005636</td>\n","      <td>1.000000</td>\n","      <td>-0.375983</td>\n","      <td>0.073741</td>\n","      <td>0.040229</td>\n","      <td>-0.171098</td>\n","      <td>-0.077856</td>\n","    </tr>\n","    <tr>\n","      <th>YearBuilt</th>\n","      <td>-0.012713</td>\n","      <td>0.027850</td>\n","      <td>0.014228</td>\n","      <td>-0.375983</td>\n","      <td>1.000000</td>\n","      <td>0.592855</td>\n","      <td>-0.049107</td>\n","      <td>0.391452</td>\n","      <td>0.522897</td>\n","    </tr>\n","    <tr>\n","      <th>YearRemodAdd</th>\n","      <td>-0.021998</td>\n","      <td>0.040581</td>\n","      <td>0.013788</td>\n","      <td>0.073741</td>\n","      <td>0.592855</td>\n","      <td>1.000000</td>\n","      <td>-0.067759</td>\n","      <td>0.291066</td>\n","      <td>0.507101</td>\n","    </tr>\n","    <tr>\n","      <th>BsmtFinSF2</th>\n","      <td>-0.005968</td>\n","      <td>-0.065649</td>\n","      <td>0.111170</td>\n","      <td>0.040229</td>\n","      <td>-0.049107</td>\n","      <td>-0.067759</td>\n","      <td>1.000000</td>\n","      <td>0.104810</td>\n","      <td>-0.011378</td>\n","    </tr>\n","    <tr>\n","      <th>TotalBsmtSF</th>\n","      <td>-0.015415</td>\n","      <td>-0.238518</td>\n","      <td>0.260833</td>\n","      <td>-0.171098</td>\n","      <td>0.391452</td>\n","      <td>0.291066</td>\n","      <td>0.104810</td>\n","      <td>1.000000</td>\n","      <td>0.613581</td>\n","    </tr>\n","    <tr>\n","      <th>SalePrice</th>\n","      <td>-0.021917</td>\n","      <td>-0.084284</td>\n","      <td>0.263843</td>\n","      <td>-0.077856</td>\n","      <td>0.522897</td>\n","      <td>0.507101</td>\n","      <td>-0.011378</td>\n","      <td>0.613581</td>\n","      <td>1.000000</td>\n","    </tr>\n","  </tbody>\n","</table>\n","</div>\n","      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-226763d2-8812-47e4-b5d5-d4840e7bc076')\"\n","         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Misra","userId":"11216241389951476389"}},"outputId":"26285a98-b813-499e-c19e-7a752c643341"},"execution_count":20,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<Axes: >"]},"metadata":{},"execution_count":20},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 2 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["We see that:\n","\n","*  YearBuilt variable is correlated with SalePrice, TotalBsmtSF and negatively correlated with OverallCond\n","*  YearRemodAdd is positively correlated with SalePrice, TotalBsmtSF, YearBuilt\n","*  LotArea is somewhat correlated with SalePrice and TotalBsmtSF\n","* SalePrice is correlated with TotalBsmtSF, YearRemodAdd, YearBuilt, LotArea"],"metadata":{"id":"E6Yx6lxyN0bW"}},{"cell_type":"markdown","source":[],"metadata":{"id":"axa2fqHd5wYI"}},{"cell_type":"markdown","source":["## 1. Non-Parametric Correlation Analysis\n","\n","\n","*   Find relationships between categorical, nonlinearly related, non-normally distributed variables"],"metadata":{"id":"sB1gMGdD5EsV"}},{"cell_type":"markdown","source":["### 1.a Spearman's rank correlation\n","\n","\n","\n","*   Converts ordinal variables into variable pairs and finds the R (similar to Pearson's correlation) correlation between the pairs\n","*   The pairs are then ranked according to the strength of correlation between them\n","\n","Assumptions:\n","\n","* Variables are ordinal\n","* Variables related nonlinearly\n","* Variables not distributed normally\n"],"metadata":{"id":"kJPT9H4q5b1i"}},{"cell_type":"code","source":["#Compute spearman rank correlation using scipy\n","from scipy.stats import spearmanr\n","r, p = spearmanr(data[\"MSZoning\"], data[\"SalePrice\"])\n","print('Spearman Rank Correlation between MSZoning and SalePrice is %0.3f and p-value is %0.3f' % (r,p))\n","\n","r, p = spearmanr(data[\"BldgType\"], data[\"SalePrice\"])\n","print('Spearman Rank Correlation between BldgType and SalePrice is %0.3f and p-value is %0.3f' % (r,p))\n","\n","r, p = spearmanr(data[\"LotConfig\"], data[\"SalePrice\"])\n","print('Spearman Rank Correlation between LotConfig and SalePrice is %0.3f and p-value is %0.3f' % (r,p))\n","\n","r, p = spearmanr(data[\"Exterior1st\"], data[\"SalePrice\"])\n","print('Spearman Rank Correlation between Exterior1st and SalePrice is %0.3f and p-value is %0.3f' % (r,p))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"YKTCHUe0Lx9L","executionInfo":{"status":"ok","timestamp":1691532618603,"user_tz":420,"elapsed":336,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"3bed0117-1921-4e73-805d-062b1cfef0f8"},"execution_count":41,"outputs":[{"output_type":"stream","name":"stdout","text":["Spearman Rank Correlation between MSZoning and SalePrice is -0.335 and p-value is 0.000\n","Spearman Rank Correlation between BldgType and SalePrice is -0.120 and p-value is 0.000\n","Spearman Rank Correlation between LotConfig and SalePrice is -0.074 and p-value is 0.005\n","Spearman Rank Correlation between Exterior1st and SalePrice is 0.068 and p-value is 0.009\n"]}]},{"cell_type":"markdown","source":["### 1.b Chi-square tables\n","\n","* Checks whether variables are not independent of each other. p < 0.05 -> reject null hypothesis and concludes that the variables are related\n","\n","Assumptions\n","\n","* Variables are categorical or numeric\n","* Categorical variables are binned\n"],"metadata":{"id":"lv9MJJou5ezr"}},{"cell_type":"code","source":["from scipy.stats import chi2_contingency\n","\n","#Create crosstab\n","table = pd.crosstab(data[\"MSZoning\"], data[\"SalePrice\"])\n","chi2, p, dof, expected = chi2_contingency(table.values)\n","print('Chi-squared statistic for MSZoning and SalePrice %0.3f and p-value is %0.3f' % (chi2, p))\n","\n","table = pd.crosstab(data[\"BldgType\"], data[\"SalePrice\"])\n","chi2, p, dof, expected = chi2_contingency(table.values)\n","print('Chi-squared statistic for BldgType and SalePrice %0.3f and p-value is %0.3f' % (chi2, p))\n","\n","table = pd.crosstab(data[\"LotConfig\"], data[\"SalePrice\"])\n","chi2, p, dof, expected = chi2_contingency(table.values)\n","print('Chi-squared statistic for LotConfig and SalePrice %0.3f and p-value is %0.3f' % (chi2, p))\n","\n","table = pd.crosstab(data[\"Exterior1st\"], data[\"SalePrice\"])\n","chi2, p, dof, expected = chi2_contingency(table.values)\n","print('Chi-squared statistic for Exterior1st and SalePrice %0.3f and p-value is %0.3f' % (chi2, p))\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bKDfwdd-5EN6","executionInfo":{"status":"ok","timestamp":1691532852432,"user_tz":420,"elapsed":996,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"6e2a5335-7873-4950-f7c6-57e5aee2de9f"},"execution_count":45,"outputs":[{"output_type":"stream","name":"stdout","text":["Chi-squared statistic for MSZoninf and SalePrice 3147.891 and p-value is 0.000\n","Chi-squared statistic for BldgType and SalePrice 2354.025 and p-value is 1.000\n","Chi-squared statistic for LotConfig and SalePrice 2771.985 and p-value is 0.046\n","Chi-squared statistic for Exterior1st and SalePrice 8712.733 and p-value is 1.000\n"]}]},{"cell_type":"markdown","source":["# 2. Data Transformations\n","\n","There are two main ways to prepare data for analysis\n","\n","* Normalization: value of obervation/sum of all observations\n","* Standardization: rescale data to have 0 mean and unit variance"],"metadata":{"id":"EdqKIgsPOdt3"}},{"cell_type":"code","source":["#Let's look at sale price and reshape it as a 1 column matrix\n","sale_price = data['SalePrice'].values.reshape(-1,1)"],"metadata":{"id":"yrXhER9dOzLq","executionInfo":{"status":"ok","timestamp":1691533856071,"user_tz":420,"elapsed":169,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}}},"execution_count":55,"outputs":[]},{"cell_type":"markdown","source":["### 2.a Normalization"],"metadata":{"id":"-erp9LByRmUr"}},{"cell_type":"code","source":["from sklearn import preprocessing\n","from sklearn.preprocessing import scale\n","\n","#Use min max to scale the variable to a defined range by default that range is 0 to 1\n","scaled = preprocessing.MinMaxScaler()\n","scaled_sale_price = scaled.fit_transform(sale_price)\n","\n","#Plot to take a look at the scaled data and check that the values range between 0 and 1\n","plt.plot(scaled_sale_price)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":447},"id":"AoJDiungQG4b","executionInfo":{"status":"ok","timestamp":1691533684691,"user_tz":420,"elapsed":1145,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"5d8ff523-4afc-4150-e696-dd855a8e55e2"},"execution_count":54,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[<matplotlib.lines.Line2D at 0x7c86ec6cc1f0>]"]},"metadata":{},"execution_count":54},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["### 2.b Standardization"],"metadata":{"id":"9dwRVrh0Rrjj"}},{"cell_type":"code","source":["#Let's look at sale price and reshape it as a 1 column matrix\n","sale_price = data['SalePrice'].values.reshape(-1,1)"],"metadata":{"id":"trJkJtqWRlIV","executionInfo":{"status":"ok","timestamp":1691533944344,"user_tz":420,"elapsed":147,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}}},"execution_count":56,"outputs":[]},{"cell_type":"code","source":["from sklearn import preprocessing\n","from sklearn.preprocessing import scale\n","\n","#Use scale function to scale the variable\n","standard_sale_price = scale(sale_price, axis=0, with_mean=False, with_std=False)\n","\n","#Plot to take a look at the scaled data and check that the values range between 0 and 1\n","plt.plot(standard_sale_price)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":447},"id":"FR-pWQnwR6e8","executionInfo":{"status":"ok","timestamp":1691534117411,"user_tz":420,"elapsed":779,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"7306a591-6a40-4631-a0a4-7994a2b4a2b5"},"execution_count":57,"outputs":[{"output_type":"execute_result","data":{"text/plain":["[<matplotlib.lines.Line2D at 0x7c86ec326ad0>]"]},"metadata":{},"execution_count":57},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["# 3. Outlier Detection"],"metadata":{"id":"nplmeqZpTIZm"}},{"cell_type":"markdown","source":["### 3.a Univariate Detection\n","\n","* Tukey Method: Uses boxplots to detect outliers. Points outside the 1.5IQR are considered to be outliers and are the dots above or below the boxplots\n","\n","* Tukey outlier labeling: Calculate outliers mathematically using the above and label them"],"metadata":{"id":"tvDDVqhMTM79"}},{"cell_type":"code","source":["#Create boxplots\n","sns.boxplot(data['SalePrice']).set_title('Boxplot of the sale price')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":469},"id":"xpNhcHBKTKBT","executionInfo":{"status":"ok","timestamp":1691534717208,"user_tz":420,"elapsed":737,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"59bf6b04-24ab-457f-e118-c1df1e8e8193"},"execution_count":69,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Boxplot of the sale price')"]},"metadata":{},"execution_count":69},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["#Calculate the interquartile range to find outliers\n","Q1 = data['SalePrice'].quantile(0.25)\n","Q3 = data['SalePrice'].quantile(0.75)\n","IQR = Q3 - Q1\n","lower = Q1 - 1.5 * IQR\n","upper = Q3 + 1.5 * IQR"],"metadata":{"id":"PsSa4JMrU3jL","executionInfo":{"status":"ok","timestamp":1691534921841,"user_tz":420,"elapsed":153,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}}},"execution_count":72,"outputs":[]},{"cell_type":"code","source":["sale_price_outliers = data[data['SalePrice'] > upper]['SalePrice']"],"metadata":{"id":"4fVKRnRUVqFG","executionInfo":{"status":"ok","timestamp":1691535010826,"user_tz":420,"elapsed":146,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}}},"execution_count":76,"outputs":[]},{"cell_type":"code","source":["sale_price_outliers"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"WSwogdEVV-_k","executionInfo":{"status":"ok","timestamp":1691535015210,"user_tz":420,"elapsed":147,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"01bb4785-004e-4d37-d80d-63ba1b40ada5"},"execution_count":77,"outputs":[{"output_type":"execute_result","data":{"text/plain":["11      345000.0\n","53      385000.0\n","58      438780.0\n","112     383970.0\n","151     372402.0\n","          ...   \n","1268    381000.0\n","1353    410000.0\n","1373    466500.0\n","1388    377500.0\n","1437    394617.0\n","Name: SalePrice, Length: 61, dtype: float64"]},"metadata":{},"execution_count":77}]},{"cell_type":"markdown","source":["### 3.b Multivariate Detection\n","\n","* Tukey Method: Uses boxplots to detect outliers. Points outside the 1.5IQR are considered to be outliers and are the dots above or below the boxplots.\n","\n"],"metadata":{"id":"2g19nHsVWqyg"}},{"cell_type":"code","source":["#Create boxplots with two variables. From out Non-parametric correlation analysis we found that SalePrice and MSZoning were significantly correlated\n","sns.boxplot(x=data[\"MSZoning\"], y=data['SalePrice']).set_title('Boxplot of the sale price')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":489},"id":"r35qzo90XkR5","executionInfo":{"status":"ok","timestamp":1691535471871,"user_tz":420,"elapsed":683,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"3b4e4db7-5dd1-45fc-e136-23d00d72ab9a"},"execution_count":78,"outputs":[{"output_type":"execute_result","data":{"text/plain":["Text(0.5, 1.0, 'Boxplot of the sale price')"]},"metadata":{},"execution_count":78},{"output_type":"display_data","data":{"text/plain":["<Figure size 640x480 with 1 Axes>"],"image/png":"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\n"},"metadata":{}}]},{"cell_type":"code","source":["data = pd.read_csv(\"/content/drive/MyDrive/Grad School-Files/Job Search/Data Science Basics/mtcars.csv\")"],"metadata":{"id":"CdChPCuUYVMJ","executionInfo":{"status":"ok","timestamp":1691535640688,"user_tz":420,"elapsed":607,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}}},"execution_count":79,"outputs":[]},{"cell_type":"code","source":["IQR = -(1.714 -1.936)\n","lower = 1.714 - 1.5 * IQR\n","upper = 1.936 + 1.5 * IQR"],"metadata":{"id":"lBgXAWIoYYst","executionInfo":{"status":"ok","timestamp":1691536002126,"user_tz":420,"elapsed":174,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}}},"execution_count":95,"outputs":[]},{"cell_type":"code","source":["lower"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"91bXnNglZqLZ","executionInfo":{"status":"ok","timestamp":1691536003362,"user_tz":420,"elapsed":159,"user":{"displayName":"Shruti Misra","userId":"11216241389951476389"}},"outputId":"0bf6d84d-c811-423e-87a2-35d7a64bda13"},"execution_count":96,"outputs":[{"output_type":"execute_result","data":{"text/plain":["1.381"]},"metadata":{},"execution_count":96}]}],"metadata":{"colab":{"provenance":[],"authorship_tag":"ABX9TyPcuWv1mzaBgCiz38NN4FkB"},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"}},"nbformat":4,"nbformat_minor":0}