From 600ebe34813a486a2e64875cb6be5ef14e210e7c Mon Sep 17 00:00:00 2001 From: barbara Date: Sat, 26 Jun 2021 13:42:28 -0300 Subject: [PATCH] first commit --- README.md | 4 +- img/kfold.png | Bin 0 -> 86053 bytes requirements.txt | 7 + src/hands_on_analyze_collaborators.ipynb | 1027 +++++ ...on_analyze_collaborators_with_answer.ipynb | 3850 +++++++++++++++++ 5 files changed, 4887 insertions(+), 1 deletion(-) create mode 100644 img/kfold.png create mode 100644 requirements.txt create mode 100644 src/hands_on_analyze_collaborators.ipynb create mode 100644 src/hands_on_analyze_collaborators_with_answer.ipynb diff --git a/README.md b/README.md index 003d847..623098c 100644 --- a/README.md +++ b/README.md @@ -1 +1,3 @@ -# wids2021 \ No newline at end of file +# Women in Data Science BH 2021 + +## Hands-on: Uso de Ciência de Dados para Analisar Colaboradores de uma Empresa diff --git a/img/kfold.png b/img/kfold.png new file mode 100644 index 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AgeAttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeCountEmployeeNumber...RelationshipSatisfactionStandardHoursStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceYearsAtCompanyYearsInCurrentRoleYearsSinceLastPromotionYearsWithCurrManager
041YesTravel_Rarely1102Sales12Life Sciences11...18008016405
149NoTravel_Frequently279Research & Development81Life Sciences12...4801103310717
237YesTravel_Rarely1373Research & Development22Other14...28007330000
333NoTravel_Frequently1392Research & Development34Life Sciences15...38008338730
427NoTravel_Rarely591Research & Development21Medical17...48016332222
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" + ], + "text/plain": [ + " Age Attrition BusinessTravel DailyRate Department \\\n", + "0 41 Yes Travel_Rarely 1102 Sales \n", + "1 49 No Travel_Frequently 279 Research & Development \n", + "2 37 Yes Travel_Rarely 1373 Research & Development \n", + "3 33 No Travel_Frequently 1392 Research & Development \n", + "4 27 No Travel_Rarely 591 Research & Development \n", + "\n", + " DistanceFromHome Education EducationField EmployeeCount EmployeeNumber \\\n", + "0 1 2 Life Sciences 1 1 \n", + "1 8 1 Life Sciences 1 2 \n", + "2 2 2 Other 1 4 \n", + "3 3 4 Life Sciences 1 5 \n", + "4 2 1 Medical 1 7 \n", + "\n", + " ... RelationshipSatisfaction StandardHours StockOptionLevel \\\n", + "0 ... 1 80 0 \n", + "1 ... 4 80 1 \n", + "2 ... 2 80 0 \n", + "3 ... 3 80 0 \n", + "4 ... 4 80 1 \n", + "\n", + " TotalWorkingYears TrainingTimesLastYear WorkLifeBalance YearsAtCompany \\\n", + "0 8 0 1 6 \n", + "1 10 3 3 10 \n", + "2 7 3 3 0 \n", + "3 8 3 3 8 \n", + "4 6 3 3 2 \n", + "\n", + " YearsInCurrentRole YearsSinceLastPromotion YearsWithCurrManager \n", + "0 4 0 5 \n", + "1 7 1 7 \n", + "2 0 0 0 \n", + "3 7 3 0 \n", + "4 2 2 2 \n", + "\n", + "[5 rows x 35 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "IQlK107wJRko", + "outputId": "4a86ce68-6a16-4dcd-a091-f883786008ef" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(1470, 35)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "alZZP9h0JRkt" + }, + "source": [ + "# Conhecendo os dados" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 208 + }, + "id": "X06erQ8zJRku", + "outputId": "53c6aaf8-ce44-42d9-8ddc-d01c91761624" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['Age', 'Attrition', 'BusinessTravel', 'DailyRate', 'Department',\n", + " 'DistanceFromHome', 'Education', 'EducationField', 'EmployeeCount',\n", + " 'EmployeeNumber', 'EnvironmentSatisfaction', 'Gender', 'HourlyRate',\n", + " 'JobInvolvement', 'JobLevel', 'JobRole', 'JobSatisfaction',\n", + " 'MaritalStatus', 'MonthlyIncome', 'MonthlyRate', 'NumCompaniesWorked',\n", + " 'Over18', 'OverTime', 'PercentSalaryHike', 'PerformanceRating',\n", + " 'RelationshipSatisfaction', 'StandardHours', 'StockOptionLevel',\n", + " 'TotalWorkingYears', 'TrainingTimesLastYear', 'WorkLifeBalance',\n", + " 'YearsAtCompany', 'YearsInCurrentRole', 'YearsSinceLastPromotion',\n", + " 'YearsWithCurrManager'],\n", + " dtype='object')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 644 + }, + "id": "8WAg3jIXJRky", + "outputId": "fef83fe5-0598-47b8-cd1c-2144f2803c78", + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Age 0\n", + "Attrition 0\n", + "BusinessTravel 0\n", + "DailyRate 0\n", + "Department 0\n", + "DistanceFromHome 0\n", + "Education 0\n", + "EducationField 0\n", + "EmployeeCount 0\n", + "EmployeeNumber 0\n", + "EnvironmentSatisfaction 0\n", + "Gender 0\n", + "HourlyRate 0\n", + "JobInvolvement 0\n", + "JobLevel 0\n", + "JobRole 0\n", + "JobSatisfaction 0\n", + "MaritalStatus 0\n", + "MonthlyIncome 0\n", + "MonthlyRate 0\n", + "NumCompaniesWorked 0\n", + "Over18 0\n", + "OverTime 0\n", + "PercentSalaryHike 0\n", + "PerformanceRating 0\n", + "RelationshipSatisfaction 0\n", + "StandardHours 0\n", + "StockOptionLevel 0\n", + "TotalWorkingYears 0\n", + "TrainingTimesLastYear 0\n", + "WorkLifeBalance 0\n", + "YearsAtCompany 0\n", + "YearsInCurrentRole 0\n", + "YearsSinceLastPromotion 0\n", + "YearsWithCurrManager 0\n", + "dtype: int64" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Check valores missing\n", + "df.isna().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 644 + }, + "id": "xQuZKmf2JRk7", + "outputId": "66a63f82-0351-4e15-e720-3923019f959c", + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Age int64\n", + "Attrition object\n", + "BusinessTravel object\n", + "DailyRate int64\n", + "Department object\n", + "DistanceFromHome int64\n", + "Education int64\n", + "EducationField object\n", + "EmployeeCount int64\n", + "EmployeeNumber int64\n", + "EnvironmentSatisfaction int64\n", + "Gender object\n", + "HourlyRate int64\n", + "JobInvolvement int64\n", + "JobLevel int64\n", + "JobRole object\n", + "JobSatisfaction int64\n", + "MaritalStatus object\n", + "MonthlyIncome int64\n", + "MonthlyRate int64\n", + "NumCompaniesWorked int64\n", + "Over18 object\n", + "OverTime object\n", + "PercentSalaryHike int64\n", + "PerformanceRating int64\n", + "RelationshipSatisfaction int64\n", + "StandardHours int64\n", + "StockOptionLevel int64\n", + "TotalWorkingYears int64\n", + "TrainingTimesLastYear int64\n", + "WorkLifeBalance int64\n", + "YearsAtCompany int64\n", + "YearsInCurrentRole int64\n", + "YearsSinceLastPromotion int64\n", + "YearsWithCurrManager int64\n", + "dtype: object" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Check tipo das colunas\n", + "df.dtypes" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 644 + }, + "id": "_d_Cssi9JRk_", + "outputId": "60b0413b-4198-4d01-c16e-366d27b91445", + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Over18 1\n", + "StandardHours 1\n", + "EmployeeCount 1\n", + "Gender 2\n", + "Attrition 2\n", + "PerformanceRating 2\n", + "OverTime 2\n", + "MaritalStatus 3\n", + "Department 3\n", + "BusinessTravel 3\n", + "StockOptionLevel 4\n", + "EnvironmentSatisfaction 4\n", + "JobInvolvement 4\n", + "JobSatisfaction 4\n", + "RelationshipSatisfaction 4\n", + "WorkLifeBalance 4\n", + "Education 5\n", + "JobLevel 5\n", + "EducationField 6\n", + "TrainingTimesLastYear 7\n", + "JobRole 9\n", + "NumCompaniesWorked 10\n", + "PercentSalaryHike 15\n", + "YearsSinceLastPromotion 16\n", + "YearsWithCurrManager 18\n", + "YearsInCurrentRole 19\n", + "DistanceFromHome 29\n", + "YearsAtCompany 37\n", + "TotalWorkingYears 40\n", + "Age 43\n", + "HourlyRate 71\n", + "DailyRate 886\n", + "MonthlyIncome 1349\n", + "MonthlyRate 1427\n", + "EmployeeNumber 1470\n", + "dtype: int64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Check colunas com apenas 1 valor\n", + "df.nunique().sort_values()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "id": "apLEdmuqJRlD" + }, + "outputs": [], + "source": [ + "#drop colunas com apenas 1 tipo de valor\n", + "columns_unique_value =[\"EmployeeCount\", \"Over18\", \"StandardHours\"]\n", + "df = df.drop(columns=columns_unique_value)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 774 + }, + "id": "a7acGKpNJRlL", + "outputId": 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Age1470.036.9238109.13537318.030.0036.043.0060.0
DailyRate1470.0802.485714403.509100102.0465.00802.01157.001499.0
DistanceFromHome1470.09.1925178.1068641.02.007.014.0029.0
Education1470.02.9129251.0241651.02.003.04.005.0
EmployeeNumber1470.01024.865306602.0243351.0491.251020.51555.752068.0
EnvironmentSatisfaction1470.02.7217691.0930821.02.003.04.004.0
HourlyRate1470.065.89115620.32942830.048.0066.083.75100.0
JobInvolvement1470.02.7299320.7115611.02.003.03.004.0
JobLevel1470.02.0639461.1069401.01.002.03.005.0
JobSatisfaction1470.02.7285711.1028461.02.003.04.004.0
MonthlyIncome1470.06502.9312934707.9567831009.02911.004919.08379.0019999.0
MonthlyRate1470.014313.1034017117.7860442094.08047.0014235.520461.5026999.0
NumCompaniesWorked1470.02.6931972.4980090.01.002.04.009.0
PercentSalaryHike1470.015.2095243.65993811.012.0014.018.0025.0
PerformanceRating1470.03.1537410.3608243.03.003.03.004.0
RelationshipSatisfaction1470.02.7122451.0812091.02.003.04.004.0
StockOptionLevel1470.00.7938780.8520770.00.001.01.003.0
TotalWorkingYears1470.011.2795927.7807820.06.0010.015.0040.0
TrainingTimesLastYear1470.02.7993201.2892710.02.003.03.006.0
WorkLifeBalance1470.02.7612240.7064761.02.003.03.004.0
YearsAtCompany1470.07.0081636.1265250.03.005.09.0040.0
YearsInCurrentRole1470.04.2292523.6231370.02.003.07.0018.0
YearsSinceLastPromotion1470.02.1877553.2224300.00.001.03.0015.0
YearsWithCurrManager1470.04.1231293.5681360.02.003.07.0017.0
\n", + "
" + ], + "text/plain": [ + " count mean std min 25% \\\n", + "Age 1470.0 36.923810 9.135373 18.0 30.00 \n", + "DailyRate 1470.0 802.485714 403.509100 102.0 465.00 \n", + "DistanceFromHome 1470.0 9.192517 8.106864 1.0 2.00 \n", + "Education 1470.0 2.912925 1.024165 1.0 2.00 \n", + "EmployeeNumber 1470.0 1024.865306 602.024335 1.0 491.25 \n", + "EnvironmentSatisfaction 1470.0 2.721769 1.093082 1.0 2.00 \n", + "HourlyRate 1470.0 65.891156 20.329428 30.0 48.00 \n", + "JobInvolvement 1470.0 2.729932 0.711561 1.0 2.00 \n", + "JobLevel 1470.0 2.063946 1.106940 1.0 1.00 \n", + "JobSatisfaction 1470.0 2.728571 1.102846 1.0 2.00 \n", + "MonthlyIncome 1470.0 6502.931293 4707.956783 1009.0 2911.00 \n", + "MonthlyRate 1470.0 14313.103401 7117.786044 2094.0 8047.00 \n", + "NumCompaniesWorked 1470.0 2.693197 2.498009 0.0 1.00 \n", + "PercentSalaryHike 1470.0 15.209524 3.659938 11.0 12.00 \n", + "PerformanceRating 1470.0 3.153741 0.360824 3.0 3.00 \n", + "RelationshipSatisfaction 1470.0 2.712245 1.081209 1.0 2.00 \n", + "StockOptionLevel 1470.0 0.793878 0.852077 0.0 0.00 \n", + "TotalWorkingYears 1470.0 11.279592 7.780782 0.0 6.00 \n", + "TrainingTimesLastYear 1470.0 2.799320 1.289271 0.0 2.00 \n", + "WorkLifeBalance 1470.0 2.761224 0.706476 1.0 2.00 \n", + "YearsAtCompany 1470.0 7.008163 6.126525 0.0 3.00 \n", + "YearsInCurrentRole 1470.0 4.229252 3.623137 0.0 2.00 \n", + "YearsSinceLastPromotion 1470.0 2.187755 3.222430 0.0 0.00 \n", + "YearsWithCurrManager 1470.0 4.123129 3.568136 0.0 2.00 \n", + "\n", + " 50% 75% max \n", + "Age 36.0 43.00 60.0 \n", + "DailyRate 802.0 1157.00 1499.0 \n", + "DistanceFromHome 7.0 14.00 29.0 \n", + "Education 3.0 4.00 5.0 \n", + "EmployeeNumber 1020.5 1555.75 2068.0 \n", + "EnvironmentSatisfaction 3.0 4.00 4.0 \n", + "HourlyRate 66.0 83.75 100.0 \n", + "JobInvolvement 3.0 3.00 4.0 \n", + "JobLevel 2.0 3.00 5.0 \n", + "JobSatisfaction 3.0 4.00 4.0 \n", + "MonthlyIncome 4919.0 8379.00 19999.0 \n", + "MonthlyRate 14235.5 20461.50 26999.0 \n", + "NumCompaniesWorked 2.0 4.00 9.0 \n", + "PercentSalaryHike 14.0 18.00 25.0 \n", + "PerformanceRating 3.0 3.00 4.0 \n", + "RelationshipSatisfaction 3.0 4.00 4.0 \n", + "StockOptionLevel 1.0 1.00 3.0 \n", + "TotalWorkingYears 10.0 15.00 40.0 \n", + "TrainingTimesLastYear 3.0 3.00 6.0 \n", + "WorkLifeBalance 3.0 3.00 4.0 \n", + "YearsAtCompany 5.0 9.00 40.0 \n", + "YearsInCurrentRole 3.0 7.00 18.0 \n", + "YearsSinceLastPromotion 1.0 3.00 15.0 \n", + "YearsWithCurrManager 3.0 7.00 17.0 " + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Análise descritiva" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pandas profiling" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "from pandas_profiling import ProfileReport" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "profile = ProfileReport(df, title=\"Pandas Profiling Report\")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9dc2a262489b4b1295efdbfe3aeb7a16", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(HTML(value='Summarize dataset'), FloatProgress(value=0.0, max=45.0), HTML(value='')))" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f4aa1371a09a41a58efb8f3cd04eb791", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(HTML(value='Generate report structure'), FloatProgress(value=0.0, max=1.0), HTML(value='')))" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ad283796389e4b0ca59b6b72b117696f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(HTML(value='Render HTML'), FloatProgress(value=0.0, max=1.0), HTML(value='')))" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "11cadd02f43248fe98d985a9add88b02", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(HTML(value='Export report to file'), FloatProgress(value=0.0, max=1.0), HTML(value='')))" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "CPU times: user 44.8 s, sys: 14.1 s, total: 58.9 s\n", + "Wall time: 45.3 s\n" + ] + } + ], + "source": [ + "%%time\n", + "profile.to_file(\"output/df_profile.html\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PJyCBk6_JRlP" + }, + "source": [ + "# Análise Exploratória" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hj5G-rqDJRlQ" + }, + "source": [ + "## Pessoas que sairam da empresa" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "No 1233\n", + "Yes 237\n", + "Name: Attrition, dtype: int64" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df[\"Attrition\"].value_counts()#.plot(kind=\"bar\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ADTBOeenJRlX" + }, + "source": [ + " Análise: \n", + " - A maior parte dos dados são de pessoas que não sairam da empresa." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vvBaSdw-JRlY" + }, + "source": [ + "## E qual a idade delas?" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "TZ2mJIf1JRlb", + "outputId": "ba506e18-d819-43ac-a79e-ea3b45c09b57" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x=\"Attrition\", y=\"Age\", data=df, hue=\"Gender\", order=[\"No\",\"Yes\"])\n", + "plt.legend(bbox_to_anchor=(1.25, 0.95))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "CSp2NNxYJRlh" + }, + "source": [ + " Análise: \n", + " - A médiana da idade das pessoas que saem da empresa é menor do que as que permanecem.\n", + " - Hipótese: pessoas mais novas saem mais da empresa que pessoas mais velhas." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FvaFHMHlJRlq" + }, + "source": [ + "## São casadas?" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "ZRzOa4Hvq9z9", + "outputId": "cf1c25e5-f48b-4b51-a519-f8bc25811e00" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"Attrition\")[\"MaritalStatus\"].value_counts(normalize=True).unstack().plot(kind=\"bar\")\n", + "plt.legend(loc=9)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "V5aGEtnBJRlz" + }, + "source": [ + " Análise: \n", + " - A maior parte das pessoas que saem são solteiras, o que fazer sentido, pois são pessoas mais novas." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YhZFvRZHJRmB" + }, + "source": [ + "## Como é o salário dessas pessoas?" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "8-QXqvpgJRmC", + "outputId": "e86874ea-0e6b-45f6-b806-09a08e9f2b86" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(df['Attrition'], df['MonthlyIncome'], hue=df[\"Gender\"], order=[\"No\",\"Yes\"]) \n", + "plt.legend(bbox_to_anchor=(1.25, 0.95))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "pNPfvBbxJRmG" + }, + "source": [ + " Análise: \n", + " - A mediana do salário de quem sai é menor do que as que não saem.\n", + " - As pessoas saem do trabalho pois estão insatisfeitas com o salário. (Hipótese)\n", + " - A diferença salarial entre homens e mulheres não é significativa, aparentemente." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_DOko6_kJRmH" + }, + "source": [ + "## E a satisfação com o ambiente de trabalho?\n", + "EnvironmentSatisfaction 1 'Low' 2 'Medium' 3 'High' 4 'Very High'" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "i2xSi55EsJPA", + "outputId": "44d089ca-04d4-468d-97d9-bc590632232f" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"Attrition\")[\"EnvironmentSatisfaction\"].value_counts(normalize=True).unstack().plot(kind=\"bar\")\n", + "plt.legend(loc=9)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ULlr7PUiJRmP" + }, + "source": [ + " Análise: \n", + " - Pessoas que estão insatisfeitas com o ambiente de trabalho são propensas a sairem do trabalho. (=1)\n", + " - Mais de 60% das pessoas que não saíram estão satisfeitas com ambiente de trabalho." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r6tOOyKDM-W0" + }, + "source": [ + "## E a satisfação com o trabalho?\n", + "\n", + "JobSatisfaction 1 'Low' 2 'Medium' 3 'High' 4 'Very High'" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "9A1NhIdwsPpA", + "outputId": "e0139b00-0c54-45e5-9a61-357e73701c87" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"Attrition\")[\"JobSatisfaction\"].value_counts(normalize=True).unstack().plot(kind=\"bar\")\n", + "plt.legend(loc=9)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2sRSY6AiylnM" + }, + "source": [ + " Análise \n", + "- Pessoas que estão insatifestas com o trabalho saem mais.\n", + "- Pessoas que estão totatalmente satifesitas com o trabalho saem menos." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_ojiN-ecJRmP" + }, + "source": [ + "## Elas trabalhavam na empresa há muito tempo?" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "VE5wa4LrJRmQ", + "outputId": "5a76c924-2433-4ea4-c002-bce3320a5a45" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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yceNGxowZw1tvvcVbb72Vaizr1q2r6t+RUkb1/IOZ/aOZ3QQcDXzL3e8p9QRm1gDcA3zV3TeZWd9jF8xs0BU+6+rqaG5uLvWUUkR9fT2APk/pp7m5mRkzZqQaQ28rf/HixanGUU0ymcyA9Tvs4zezv+29EbXUPwT8DijEdYMys3FESf8n7n5vXP2Kme0fP78/0aqfIiJSJsVa/NuvyPk7YFxcXwDufdc7+jCzGuCHQNbdr+7z1ANAK/Ct+P7+nYxZRESGodieuzPMrBaY5e7XDOHYxxKt3f+Mma2M6y4lSvg/M7NzgBeB04dwbBERGaKiffzu3mNmZwA7nfjd/XGiPXoHUnREkIiIJKeUUT2/NrPvE026eqO3UjN3RURGp1IS/5T4/vI+dYPO3BURkcpUynDO48sRiIiIlEcpWy/uAcwHPhZX/Stwubu/nmRgIiKSjFLW478N2Ew0+uZ0YBPwoySDEhGR5JTSx/8+d/9Mn/LCPsMzRURklCmlxb/VzD7aWzCzY4GtyYUkIiJJKqXFfwHQFvf11wAbiWbciojIKFRsB65rgd8Av3b3I81sdwB31367IiKjWLGung7gNKIJXJ3ATcDZZnaUmZXSRSQiIhWo2Fo93we+D2Bmfwl8JL7NAfYBdi9HgCIiMrKK9vHHK2weQZTwjwUOA54n2ktXRERGoWJ9/MuJWvUrgf8HXOXu1bsljYhIIIq1+FcD7wcmA13ABjP7k7tvKEtkI+j666+no6Mj7TAqQu/nkPaeppWiqamJmTNnph2GSFkV6+M/DyAezfMhou6er5jZPsCz7j5qhnR2dHSw8tksPfUT0w4ldTU90Y88s/qVlCNJX21uY9ohiKSilHH8eSBHNGkrDxwI7JJkUEnoqZ/I1kOnpx2GVJDxz7WnHYJIKor18V9D1MqfTLTt4r8TDelsdffXBjuwmd0GfBJY7+6Hx3ULgHOBP8Uvu9Td9dsnIlJGxVr8LwA/Bla6e88Qjr2EaDjo9iOArnH37w7heCIiMgKKJf7H4/sjzexdTw62A5e7P2ZmjUMPTUREklAs8X+vyHPD2YHrQjM7G3gSuNjdXx3sDfl8nmx26CNJc7nckN8r1S2Xyw3ruyUjp/f3VD+P5BUb1ZPEzls3AlcQ/eG4guiPyxcHe1NdXR3Nzc1DPml9fT3RlgIi/dXX1w/ruyUjJ/o9RT+PEZTJZAasL2VUD2Z2ONGs3V1769x9p2fvuvvbYwjN7FbgoZ09hoiIDM+gi62Z2Xzg+vh2PPCPwKeGcjIz279P8dPAs0M5joiIDF0pLf7PAkcCv3P3GWa2L9Fon6LM7KfAccDeZraGaN/e48xsClFXTydw3tDCFhGRoSol8W91921m1h3P4l0PHDTYm9z9jAGqf7izAYqIyMgqJfE/aWZ7ArcCGWAL0WQuEREZhQZN/O7+5fjhTWa2FNjd3VclG5aIiCSllIu7j/Q+dvdOd1/Vt05EREaXYmv17ArUE12c3Ytoo3WI1ug/oAyxiYhIAop19ZwHfBX4S6Dv8gybiLdkFBGR0afYzN3FwGIzm+nu15cxJhERSVApo3puNrNZwMfi8q+Am939rcSiEhGRxJSS+P8JGBffA5xFtObOl5IKSkREklPs4u5Yd+8G/trdj+zz1C/N7OnkQxMRkSQUG875H/F9j5m9r7fSzN4LDGVjFhERqQDFunp6h29+DXjUzFbH5UZgRpJBiYhIcool/n3M7KL48c1Abfy4BzgKeDTJwEREJBnFEn8t0MA7Lf++79ktsYhERCRRxRL/y+5+edkiERGRsih2cXf7lr6IiFSBYi3+jw/nwGZ2G/BJYL27Hx7XTQTuIrpA3AmcXspm6yIiMnJ22OJ3943DPPYSoGW7ukuAR9x9MvBIXBYRkTIqabP1oXD3x8yscbvqU4m2YwRoI1r+YW5SMfTauHEjtbkuxj/XnvSpZBSpzXWxceO4VGO4/vrr6ejoSDWGStH7OcyePTvlSCpDU1MTM2fOTOTYiSX+HdjX3V+OH/8R2LeUN+XzebLZ7JBP+uabbw75vVLd3nzzzWF9t4Zr1apVrH3BObhBcyJ3L0SXFfMvPplyJOl7aUstuVwuse9muRP/29y9YGaFUl5bV1dHc3PzkM+13377sTZXw9ZDpw/5GFJ9xj/Xzn777Tus79Zw1dfXc3BDD5d+YFNqMUjlueqp3amrrx/2dzOTyQxYP+gOXCPsFTPbHyC+X1/m84uIBK/cif8BoDV+3ArcX+bzi4gEL7GuHjP7KdGF3L3NbA0wH/gW8DMzOwd4ETg9qfOLiMjAkhzVc8YOnhrW/AARERmecnf1iIhIypT4RUQCo8QvIhIYJX4RkcAo8YuIBEaJX0QkMEr8IiKBUeIXEQlMaou0iUi0ZPiGzbVc9dTuaYciFeTFzbXsvXG4W6LsmFr8IiKBUYtfJEUTJ05kwubVWpZZ+rnqqd2pmzgxseOrxS8iEhglfhGRwATT1VOb26g9d4Gat7YCUBg3PuVI0leb20iJu3+KVJUgEn9TU1PaIVSM3g2tm96rhAf76rshQQoi8Se1U/1oNHv2bAAWL16cciQikpZUEr+ZdQKbgR6g290/mEYcIiIhSrPFf7y7b0jx/CIiQdKoHhGRwKTV4i8AvzCzAnCzu99S7MX5fJ5sNlueyKpcLpcD0OdZIXK5HLVpByEVKZfLJfZ7mlbi/6i7rzWzvwCWm9lz7v7Yjl5cV1dHc3NzGcOrXvX19QD6PCtEfX09+bSDkIpUX18/7N/TTCYzYH0qXT3uvja+Xw/cBxyTRhwiIiEqe+I3swlmtlvvY+ATwLPljkNEJFRpdPXsC9xnZr3nv8Pdl6YQh4hIkMqe+N19NXBkuc8rIiIRDecUEQmMEr+ISGCU+EVEAhPEIm0ileylLdpzF+D1N2sA2GOXQsqRpO+lLbVMTvD4SvwiKdKy0O/YFC8Z/heH6DOZTLLfDSV+kRRpyfB3aMnw8lEfv4hIYJT4RUQCo8QvIhIYJX4RkcAo8YuIBEaJX0QkMEr8IiKBUeIXEQmMEr+ISGCU+EVEApPKkg1m1gIsBmqBH7j7t9KIQ0QkRGnsuVsL3ACcBBwGnGFmh5U7DhGRUKXR4j8G6Ii3YMTM7gROBf4zhVjKZtmyZbS3t6cdBh3xCoi9C2KlZfr06UybNi3VGOQdlfD9rJTvJlT/9zONxH8A8Ic+5TXA/yj2hnw+TzabTTSopK1bt45cLpd2GDQ0NACkHsu6detG/c+0mlTC97NSvptQ/d/PUbEsc11dHc3NzWmHMSzNzc3MmDEj7TBEBqTvZ3XKZDID1qcxqmctcFCf8oFxnYiIlEEaLf4ngMlm9h6ihP954H+lEIeISJDK3uJ3927gQmAZkAV+5u6/L3ccIiKhSqWP393bgfSHuIiIBEgzd0VEAqPELyISGCV+EZHAKPGLiARmVEzgyuVyGzKZzItpxyEiMsocMlBlTaFQKHcgIiKSInX1iIgERolfRCQwSvwiIoFR4hcRCYwSv4hIYJT4RUQCo8RfxcysYGbf61P+mpktSDEkCZyZ1ZjZ42Z2Up+6vzOzpWnGFRol/uqWB/7WzPZOOxARAHcvAOcDV5vZrmbWAFwFfCXdyMIyKmbuypB1A7cAc4DL+j5hZo3AbcDewJ+AGe7+UrkDlPC4+7Nm9iAwF5gA/Bi4zMwOB8YBC9z9fjP7K+BHwC5EjdTPuPvzacVdTdTir343AGea2R7b1V8PtLn7+4GfANeVPTIJ2UKinfdOAnYFfunuxwDHA98xswlE/zNY7O5TgA8Ca1KKteoo8Vc5d98E3A7M2u6pDwN3xI//GfhoOeOSsLn7G8BdRN+9E4FLzGwl8CuiPwQHA/8OXGpmc4FD3H1rOtFWH3X1hOFa4Cmi/zaLVIpt8a2GqBvHt3s+a2a/BU4G2s3sPHf/ZbmDrEZq8QfA3TcCPwPO6VP9G6KN7gHOBP6t3HGJxJYBM82sBsDMjorv3wusdvfrgPuB96cXYnVR4g/H94gu5PaaCcwws1XAWcDsVKISgSuILuquMrPfx2WA04Fn4y6gw4m6LGUEaFlmEZHAqMUvIhIYJX4RkcAo8YuIBEaJX0QkMEr8IiKBUeKXIJnZafHqpYfG5SlmNr3P88eZ2UeKvP9TZnZJn2Md1ue5y81sapLxiwyHZu5KqM4AHo/v5wNTiNaDaY+fPw7YQjTRrR8zG+vuDwAPxFWnAQ8B/wng7t9MLmyR4dM4fglOvBSwEy0I9iBwBNABjAfWAj8lWtG0h2jl0plEs57/DBwF/BpYRfSH4g6ipP96fPsM8A/AQ+5+t5l9HPguUSPrCeACd8+bWSfQBpxCNHnp79z9uaT/7SKgrh4J06nAUnf//0AXUeL/JnCXu09x928DNwHXxOXe5SwOBD7i7hf1Hsjdf0PU8v96/Nr/6n3OzHYFlgCfc/cjiJL/BX3i2ODuHwBuBL6W0L9V5F2U+CVEZwB3xo/vjMul+Bd379mJ8xjwQvwHBqIW/sf6PH9vfJ8BGnfiuCLDoj5+CYqZTQROAI4wswJQCxSA35fw9jdGOJx8fN+DfheljNTil9B8Fvhndz/E3Rvd/SDgBaL133fr87rN25WL2dFrHWg0s6a4fBbwr0MLW2TkKPFLaM4A7tuu7h5gP+AwM1tpZp8juuj76bj8Pwc55p3A183sd2b2vt5Kd/8zMAP4FzN7hmjt+ZtG6h8iMlQa1SMiEhi1+EVEAqPELyISGCV+EZHAKPGLiARGiV9EJDBK/CIigVHiFxEJzH8DOsfmVETaE7AAAAAASUVORK5CYII=\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(df['Attrition'], df['TotalWorkingYears'], order=[\"No\",\"Yes\"]) " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Ae00yZaHJRmT" + }, + "source": [ + " Análise: \n", + " - As pessoas que saem do trabalho, em sua maioria, tem menos tempo de empresa" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LSZx09YmJRmU" + }, + "source": [ + "## Trabalham além da carga horária?" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "0NY-pF1QJRmV", + "outputId": "741e695f-444f-4163-a790-980657d25dd8" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"Attrition\")[\"OverTime\"].value_counts(normalize=True).unstack().plot(kind=\"bar\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "lvbubWt-2PFg" + }, + "source": [ + "- Análise: No grupo das pessoas que não sairam, a maior parte não faz hora extra. Diferente do grupo das que saem." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2k2UCEHROiby" + }, + "source": [ + "### Das pessoas que trabalham, além da carga horária. Como é o nível de satisfação com o nível de trabalho delas?" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "RdJpgZoFvb2o", + "outputId": "be07bfaa-1e95-4fd3-db5b-ba397c35e4fa" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df[df[\"OverTime\"] == \"Yes\"].groupby(\"Attrition\")[\"EnvironmentSatisfaction\"].value_counts(normalize=True).unstack().plot(kind=\"bar\")\n", + "plt.legend(bbox_to_anchor=(0.5,0.4))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "v1pmRHMI0OkJ" + }, + "source": [ + "Análise: \n", + "\n", + "- Das pessoas que fazem hora extra, a maioria está satisfeita com o ambiente de trabalho.\n", + "- O percentual das pessoas insatisfeitas é maior no grupo que faz hora extra." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZHKS6EzrJRmd" + }, + "source": [ + "## Moravam perto do trabalho?" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "GXHvF04UJRme", + "outputId": "710bf8b4-acf0-4685-dd3e-9c4acf2a69d0" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(x=\"Attrition\", y=\"DistanceFromHome\", data=df, order=[\"No\",\"Yes\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "naSYO9LUJRmj" + }, + "source": [ + " Análise: \n", + " - Pessoas que moram mais longe do trabalho, são mais propensas a deixarem do trabalho." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "N13aA8WeJRmr" + }, + "source": [ + "## E qual o nível dessas pessoas?" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "OofTpwKxwATB", + "outputId": "dfaa1393-54d0-4f70-e2d6-002b2f5278ad" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"Attrition\")[\"JobLevel\"].value_counts(normalize=True).unstack().plot(kind=\"bar\")\n", + "#plt.legend(bbox_to_anchor=(0.5,0.4))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "y5n7bEWrJRmy" + }, + "source": [ + " Análise: \n", + " - Pessoas mais \"junior\" são mais propensas a saírem do trabalho." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8hnQSmc8JRmy" + }, + "source": [ + "## E o papel delas?" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "M5oz4S9_wHgN", + "outputId": "29dfcfdb-29fa-4999-f1c9-bd05b6b8c8b6" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "df.groupby(\"Attrition\")[\"JobRole\"].value_counts(normalize=True).unstack().plot(kind=\"bar\")\n", + "plt.legend(bbox_to_anchor=(1.55,0.8))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Quais papéis tem os maiores salários?" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 411 + }, + "id": "gbz0pQKSJRnA", + "outputId": "4c905833-1a96-47b9-9025-ab542954e279" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([0, 1, 2, 3, 4, 5, 6, 7, 8]),\n", + " [Text(0, 0, 'Sales Executive'),\n", + " Text(1, 0, 'Research Scientist'),\n", + " Text(2, 0, 'Laboratory Technician'),\n", + " Text(3, 0, 'Manufacturing Director'),\n", + " Text(4, 0, 'Healthcare Representative'),\n", + " Text(5, 0, 'Manager'),\n", + " Text(6, 0, 'Sales Representative'),\n", + " Text(7, 0, 'Research Director'),\n", + " Text(8, 0, 'Human Resources')])" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "sns.boxplot(df['JobRole'], df['MonthlyIncome']) \n", + "plt.xticks(rotation=90)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "i1MbH3CEJRnE" + }, + "source": [ + " Análise: \n", + "\n", + " - Quem tem os maiores salários praticamente não saem do trabalho. \n", + " - Laboratory Tecnician e Research Scientist que tem mais saídas possuem salários baixos\n", + " - Paepeis relacionadas a vendas, são mais propensos a saírem. (Representante de Vendas e Executivo de Vendas)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tqQq1MuKJRnE" + }, + "source": [ + "# Seleção de Features e Feature enginering" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JtmZiaEcJRnF" + }, + "source": [ + "## Análise da correlação das features" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 749 + }, + "id": "xqDtifvjJRnG", + "outputId": "bf82bf60-8157-4d51-f8d7-f5deac292cbf" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 34, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(18, 10))\n", + "sns.heatmap(df.corr(), annot=True, cmap=\"Blues\")" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6YYy7TLZJRnT" + }, + "source": [ + "### Reduzir dimensionalidade" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "3gIwPPKmTIJ_", + "outputId": "0874ddb7-88a3-4e83-926e-d5e908bb8e6b" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(1470, 32)" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "id": "o7cb6YlAJRnU" + }, + "outputs": [], + "source": [ + "colunas_reduzir = ['YearsAtCompany', 'YearsInCurrentRole','YearsSinceLastPromotion', 'YearsWithCurrManager']" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "VNqRBiLWJRnW", + "outputId": "9155c5dc-4fba-4ede-8e11-927b619f6645" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "explained: [0.80556036]\n" + ] + } + ], + "source": [ + "pca = PCA(n_components=1)\n", + "pca.fit(df[colunas_reduzir].values)\n", + "print(\"explained: \"+ str(pca.explained_variance_ratio_))\n", + "df[\"years_pca\"] = pca.transform(df[colunas_reduzir].values)\n", + "df.drop(colunas_reduzir, axis=1, inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "-wDc272mJRnY", + "outputId": "3a00db62-2dd9-4c3e-8fab-51d1df923126" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(1470, 29)" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Ba4aR_k1JRnh" + }, + "source": [ + "## Criar grupos com uma feature" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 320 + }, + "id": "v5jL2fUdJRni", + "outputId": "af708b79-a156-46ea-dd75-214223c48d97" + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ 57., 105., 224., 265., 255., 217., 131., 92., 77., 47.]),\n", + " array([18. , 22.2, 26.4, 30.6, 34.8, 39. , 43.2, 47.4, 51.6, 55.8, 60. ]),\n", + " )" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#Agrupar as idades\n", + "plt.hist(df[\"Age\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "id": "uOl3XmjzJRnn" + }, + "outputs": [], + "source": [ + "# 18-24 = grupo1 , 25-45=grupo2 , >=46 grupo3\n", + "df['age_range'] = pd.cut(df['Age'], [17, 24, 45, 120], labels=['18-24', '25-45', '46-60'])\n", + "df.drop(['Age'],axis=1,inplace=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 199 + }, + "id": "YWuZ9axhTQv_", + "outputId": "37fb561d-f0b9-4785-e260-8248c065662e" + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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age_range
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AttritionBusinessTravelDailyRateDepartmentDistanceFromHomeEducationEducationFieldEmployeeNumberEnvironmentSatisfactionGender...OverTimePercentSalaryHikePerformanceRatingRelationshipSatisfactionStockOptionLevelTotalWorkingYearsTrainingTimesLastYearWorkLifeBalanceyears_pcaage_range
0YesTravel_Rarely1102Sales12Life Sciences12Female...Yes11310801-1.16487525-45
1NoTravel_Frequently279Research & Development81Life Sciences23Male...No2344110334.21262546-60
2YesTravel_Rarely1373Research & Development22Other44Male...Yes15320733-9.38181725-45
3NoTravel_Frequently1392Research & Development34Life Sciences54Female...Yes113308330.48773525-45
4NoTravel_Rarely591Research & Development21Medical71Male...No12341633-5.66029225-45
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5 rows × 29 columns

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" + ], + "text/plain": [ + " Attrition BusinessTravel DailyRate Department \\\n", + "0 Yes Travel_Rarely 1102 Sales \n", + "1 No Travel_Frequently 279 Research & Development \n", + "2 Yes Travel_Rarely 1373 Research & Development \n", + "3 No Travel_Frequently 1392 Research & Development \n", + "4 No Travel_Rarely 591 Research & Development \n", + "\n", + " DistanceFromHome Education EducationField EmployeeNumber \\\n", + "0 1 2 Life Sciences 1 \n", + "1 8 1 Life Sciences 2 \n", + "2 2 2 Other 4 \n", + "3 3 4 Life Sciences 5 \n", + "4 2 1 Medical 7 \n", + "\n", + " EnvironmentSatisfaction Gender ... OverTime PercentSalaryHike \\\n", + "0 2 Female ... Yes 11 \n", + "1 3 Male ... No 23 \n", + "2 4 Male ... Yes 15 \n", + "3 4 Female ... Yes 11 \n", + "4 1 Male ... No 12 \n", + "\n", + " PerformanceRating RelationshipSatisfaction StockOptionLevel \\\n", + "0 3 1 0 \n", + "1 4 4 1 \n", + "2 3 2 0 \n", + "3 3 3 0 \n", + "4 3 4 1 \n", + "\n", + " TotalWorkingYears TrainingTimesLastYear WorkLifeBalance years_pca \\\n", + "0 8 0 1 -1.164875 \n", + "1 10 3 3 4.212625 \n", + "2 7 3 3 -9.381817 \n", + "3 8 3 3 0.487735 \n", + "4 6 3 3 -5.660292 \n", + "\n", + " age_range \n", + "0 25-45 \n", + "1 46-60 \n", + "2 25-45 \n", + "3 25-45 \n", + "4 25-45 \n", + "\n", + "[5 rows x 29 columns]" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IMG9VCmPJRo7" + }, + "source": [ + "# Modelo - classificação com pycaret" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Pycaret\n", + "\n", + "Pycaret é uma biblioteca de Machine Learning (ML) que automatiza fluxos de trabalho. \n", + "\n", + "documentação: https://pycaret.org/classification/" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Data for Modeling: (1396, 29)\n", + "Unseen Data For Predictions: (74, 29)\n" + ] + } + ], + "source": [ + "data = df.sample(frac=0.95, random_state=786)\n", + "data_unseen = df.drop(data.index)\n", + "data.reset_index(inplace=True, drop=True)\n", + "data_unseen.reset_index(inplace=True, drop=True)\n", + "\n", + "print('Data for Modeling: ' + str(data.shape))\n", + "print('Unseen Data For Predictions: ' + str(data_unseen.shape))" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "No 1170\n", + "Yes 226\n", + "Name: Attrition, dtype: int64" + ] + }, + "execution_count": 45, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data[\"Attrition\"].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "No 63\n", + "Yes 11\n", + "Name: Attrition, dtype: int64" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_unseen[\"Attrition\"].value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [], + "source": [ + "from pycaret.classification import *" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "setup: Esta função inicializa o ambiente de treinamento e cria o pipeline de transformação. Ela deve ser chamada antes de executar qualquer outra função. Possui dois parâmetros obrigatórios: ``data`` e ``target``." + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Description Value
0session_id123
1TargetAttrition
2Target TypeBinary
3Label EncodedNo: 0, Yes: 1
4Original Data(1396, 29)
5Missing ValuesFalse
6Numeric Features8
7Categorical Features20
8Ordinal FeaturesFalse
9High Cardinality FeaturesFalse
10High Cardinality MethodNone
11Transformed Train Set(977, 104)
12Transformed Test Set(419, 104)
13Shuffle Train-TestTrue
14Stratify Train-TestFalse
15Fold GeneratorStratifiedKFold
16Fold Number10
17CPU Jobs-1
18Use GPUFalse
19Log ExperimentFalse
20Experiment Nameclf-default-name
21USI115a
22Imputation Typesimple
23Iterative Imputation IterationNone
24Numeric Imputermean
25Iterative Imputation Numeric ModelNone
26Categorical Imputerconstant
27Iterative Imputation Categorical ModelNone
28Unknown Categoricals Handlingleast_frequent
29NormalizeTrue
30Normalize Methodzscore
31TransformationFalse
32Transformation MethodNone
33PCAFalse
34PCA MethodNone
35PCA ComponentsNone
36Ignore Low VarianceFalse
37Combine Rare LevelsFalse
38Rare Level ThresholdNone
39Numeric BinningFalse
40Remove OutliersFalse
41Outliers ThresholdNone
42Remove MulticollinearityFalse
43Multicollinearity ThresholdNone
44ClusteringFalse
45Clustering IterationNone
46Polynomial FeaturesFalse
47Polynomial DegreeNone
48Trignometry FeaturesFalse
49Polynomial ThresholdNone
50Group FeaturesFalse
51Feature SelectionFalse
52Feature Selection Methodclassic
53Features Selection ThresholdNone
54Feature InteractionFalse
55Feature RatioFalse
56Interaction ThresholdNone
57Fix ImbalanceTrue
58Fix Imbalance MethodSMOTE
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pycaret_config = setup(data = data, \n", + " target = 'Attrition', \n", + " fix_imbalance=True,\n", + " fold=10,\n", + " normalize=True, \n", + " session_id=123)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " compare_models : Esta função treina e avalia o desempenho de todos os modelos disponíveis na biblioteca de modelos usando validação cruzada (Cross Validation)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Explicação Validação Cruzada\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Model Accuracy AUC Recall Prec. F1 Kappa MCC TT (Sec)
gbcGradient Boosting Classifier0.86290.82400.43530.67540.52250.44800.46590.2320
lightgbmLight Gradient Boosting Machine0.85980.82260.35980.69950.46910.39920.43110.2630
rfRandom Forest Classifier0.85670.80750.25490.82800.37690.32200.39720.1180
adaAda Boost Classifier0.85060.81140.60360.58080.58770.49720.50000.0850
etExtra Trees Classifier0.84850.82470.23790.70310.35020.28950.34540.1090
mlpMLP Classifier0.83520.81450.49350.55980.51180.41470.42290.7840
rbfsvmSVM - Radial Kernel0.81070.82620.67290.47610.55300.43830.45240.4830
lrLogistic Regression0.78710.82540.71990.43920.54330.41570.43910.5350
svmSVM - Linear Kernel0.78190.00000.67250.43980.52280.39360.41400.0260
dtDecision Tree Classifier0.77480.63390.41700.37960.39390.25730.25940.0230
ldaLinear Discriminant Analysis0.76660.82370.73760.41080.52620.38810.41870.0240
ridgeRidge Classifier0.76560.00000.73170.40880.52300.38410.41420.0160
nbNaive Bayes0.60700.70060.67320.26440.37760.16760.20570.0250
gpcGaussian Process Classifier0.45040.65430.85950.22400.35530.10550.18222.0530
knnK Neighbors Classifier0.43710.66430.86010.22040.35080.09770.16940.0390
qdaQuadratic Discriminant Analysis0.18830.50050.98240.17620.29870.00030.01070.0200
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 53.7 s, sys: 1min 27s, total: 2min 20s\n", + "Wall time: 55 s\n" + ] + } + ], + "source": [ + "%%time\n", + "#best_model = compare_models(exclude=[\"xgboost\"])\n", + "best_model = compare_models(include=[\"lr\",\"knn\",\"nb\",\"dt\",\"svm\",\"rbfsvm\",\"gpc\",\"mlp\",\"ridge\",\"rf\",\"qda\",\"ada\",\"gbc\",\"lda\",\"et\",\"lightgbm\"])" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "V2mEKChPhjxC" + }, + "source": [ + "### Qual métrica utilizar?\n", + "\n", + "Mini-curso sobre métricas:https://www.youtube.com/watch?v=7tGaa_ekXf4&t=216s&ab_channel=A3DataConsultoria" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rxHsBR_T9gvU" + }, + "source": [ + "Métricas Qual utilizar?\n", + "- VP: modelo diz que a pessoa vai sair e ela sai.\n", + "- VN: modelo diz que a pessoa não vai sair e ela não sai.\n", + "- FN: modelo diz que a pessoa não vai sair e ela sai. \n", + "- FP: modelo diz que a pessoa vai sair e ela não sai.\n", + "- F1 -> harmoniza recall e precision\n", + "\n", + "- Recall -> quanto mais alto o recall menos FN tenho.\n", + "- Precision -> quanto mais alto a precision menos FP tenho.\n", + "- Acurácia -> como meu problema é binário e desbalanceado, não será um modelo bom. Pois, na maior parte dos casos ele informa que todo mundo vai sair." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " create_model: Esta função treina e avalia o desempenho de um determinado modelo usando validação cruzada. " + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Accuracy AUC Recall Prec. F1 Kappa MCC
00.83670.83880.47060.53330.50000.40290.4040
10.84690.77630.70590.54550.61540.52180.5286
20.79590.79670.52940.42860.47370.34880.3518
30.90820.76180.64710.78570.70970.65570.6601
40.82650.73420.41180.50000.45160.34970.3521
50.88780.90560.77780.66670.71790.64840.6514
60.79590.79310.61110.45830.52380.39730.4040
70.84540.84040.58820.55560.57140.47720.4775
80.87630.83240.64710.64710.64710.57210.5721
90.88660.83460.64710.68750.66670.59840.5988
Mean0.85060.81140.60360.58080.58770.49720.5000
SD0.03670.04650.10330.10680.09270.11290.1127
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "model = create_model('ada')" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None, learning_rate=1.0,\n", + " n_estimators=50, random_state=123)\n" + ] + } + ], + "source": [ + "print(model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " tune_model: Essa função ajusta os hiperparâmetros de um determinado modelo. " + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Accuracy AUC Recall Prec. F1 Kappa MCC
00.86730.88530.52940.64290.58060.50270.5061
10.87760.76980.58820.66670.62500.55220.5537
20.81630.83300.41180.46670.43750.32830.3292
30.89800.77780.58820.76920.66670.60770.6153
40.82650.76540.47060.50000.48480.38070.3809
50.89800.94310.77780.70000.73680.67380.6752
60.80610.79580.55560.47620.51280.39270.3945
70.87630.86840.64710.64710.64710.57210.5721
80.87630.85660.64710.64710.64710.57210.5721
90.86600.78900.64710.61110.62860.54690.5472
Mean0.86080.82840.58630.61270.59670.51290.5146
SD0.03120.05600.09790.09540.08750.10520.1058
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tuned_model = tune_model(model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Avaliar o modelo" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "plot_model: Esta função analisa o desempenho de um modelo treinado no conjunto de validação}" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_model(tuned_model, plot = 'confusion_matrix')" + ] + }, + { + "cell_type": "code", + "execution_count": 97, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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\n", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_model(tuned_model, plot = 'class_report')" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_model(tuned_model, plot = 'feature')" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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Parameters
algorithmSAMME
base_estimatorNone
learning_rate0.4
n_estimators230
random_state123
\n", + "
" + ], + "text/plain": [ + " Parameters\n", + "algorithm SAMME\n", + "base_estimator None\n", + "learning_rate 0.4\n", + "n_estimators 230\n", + "random_state 123" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_model(tuned_model, plot = 'parameter')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "evaluate_model: Esta função exibe uma interface de usuário para analisar o desempenho de um treinado" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5faaa7f65c994b5491669667309420ce", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "interactive(children=(ToggleButtons(description='Plot Type:', icons=('',), options=(('Hyperparameters', 'param…" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "evaluate_model(tuned_model)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Salvar modelo" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " save_model: Esta função salva o pipeline de transformação e o objeto de modelo treinado no diretório de trabalho atual como um arquivo pickle para uso posterior." + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": { + "scrolled": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Transformation Pipeline and Model Succesfully Saved\n" + ] + }, + { + "data": { + "text/plain": [ + "(Pipeline(memory=None,\n", + " steps=[('dtypes',\n", + " DataTypes_Auto_infer(categorical_features=[],\n", + " display_types=True, features_todrop=[],\n", + " id_columns=[],\n", + " ml_usecase='classification',\n", + " numerical_features=[], target='Attrition',\n", + " time_features=[])),\n", + " ('imputer',\n", + " Simple_Imputer(categorical_strategy='not_available',\n", + " fill_value_categorical=None,\n", + " fill_value_numerical=None,\n", + " numeric_st...\n", + " ('dummy', Dummify(target='Attrition')),\n", + " ('fix_perfect', Remove_100(target='Attrition')),\n", + " ('clean_names', Clean_Colum_Names()),\n", + " ('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),\n", + " ('dfs', 'passthrough'), ('pca', 'passthrough'),\n", + " ['trained_model',\n", + " AdaBoostClassifier(algorithm='SAMME', base_estimator=None,\n", + " learning_rate=0.4, n_estimators=230,\n", + " random_state=123)]],\n", + " verbose=False),\n", + " 'output/model.pkl')" + ] + }, + "execution_count": 105, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "save_model(tuned_model,'output/model')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Dicas:" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Outras bibliotecas que facilitam o processo de treinamento:\n", + "\n", + "- AutoGluon: https://github.com/awslabs/autogluon\n", + "- Mljar: https://github.com/mljar\n", + "- TPOT: https://github.com/EpistasisLab/tpot\n", + "\n", + "Para facilitar a organização e deploy:\n", + "\n", + "- Hermione: https://github.com/A3Data/hermione\n" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [ + "YWUAzo5FJRpr" + ], + "name": "Análise RH.ipynb", + "provenance": [] + }, + "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": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +}

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+ "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "1CtXmkxhJRkN" + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt \n", + "from sklearn.decomposition import PCA\n", + "import numpy as np\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sns.set_style(\"whitegrid\")\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "B7cQkNQhJRkY" + }, + "source": [ + "# Leitura dos Dados" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "vk3HKCy4JRka" + }, + "outputs": [], + "source": [ + "df = pd.read_csv(\"HR-Employee-Attrition.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 316 + }, + "id": "vP7vlUINJRkg", + "outputId": "773faa14-d27d-414e-dc89-a2d03c2fcc85" + }, + "outputs": [], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "IQlK107wJRko", + "outputId": "4a86ce68-6a16-4dcd-a091-f883786008ef" + }, + "outputs": [], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "alZZP9h0JRkt" + }, + "source": [ + "# Conhecendo os dados" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 208 + }, + "id": "X06erQ8zJRku", + "outputId": "53c6aaf8-ce44-42d9-8ddc-d01c91761624" + }, + "outputs": [], + "source": [ + "#Liste as colunas do dado\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 644 + }, + "id": "8WAg3jIXJRky", + "outputId": "fef83fe5-0598-47b8-cd1c-2144f2803c78", + "scrolled": true + }, + "outputs": [], + "source": [ + "#Check valores missing\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 644 + }, + "id": "xQuZKmf2JRk7", + "outputId": "66a63f82-0351-4e15-e720-3923019f959c", + "scrolled": true + }, + "outputs": [], + "source": [ + "#Check tipo das colunas\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 644 + }, + "id": "_d_Cssi9JRk_", + "outputId": "60b0413b-4198-4d01-c16e-366d27b91445", + "scrolled": true + }, + "outputs": [], + "source": [ + "#Check colunas com apenas 1 valor\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "apLEdmuqJRlD" + }, + "outputs": [], + "source": [ + "#drop colunas com apenas 1 tipo de valor\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 774 + }, + "id": "a7acGKpNJRlL", + "outputId": "f3ee08b1-dadd-4479-9435-03346cb20e13", + "scrolled": true + }, + "outputs": [], + "source": [ + "df.describe().T" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Análise descritiva" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Pandas profiling" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pandas_profiling import ProfileReport" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Aplique o pandas_profiling no dado carregado " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "PJyCBk6_JRlP" + }, + "source": [ + "# Análise Exploratória" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "hj5G-rqDJRlQ" + }, + "source": [ + "## Pessoas que sairam da empresa\n", + "\n", + "são quantas?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "vvBaSdw-JRlY" + }, + "source": [ + "## E qual a idade delas?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "TZ2mJIf1JRlb", + "outputId": "ba506e18-d819-43ac-a79e-ea3b45c09b57" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "FvaFHMHlJRlq" + }, + "source": [ + "## São casadas?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "ZRzOa4Hvq9z9", + "outputId": "cf1c25e5-f48b-4b51-a519-f8bc25811e00" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "YhZFvRZHJRmB" + }, + "source": [ + "## Como é o salário dessas pessoas?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "8-QXqvpgJRmC", + "outputId": "e86874ea-0e6b-45f6-b806-09a08e9f2b86" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Tem diferença por gênero?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "6jBvT8CyLM4r", + "outputId": "a82a760f-a4cb-4b68-ad37-debfeed54f1d" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_DOko6_kJRmH" + }, + "source": [ + "## E a satisfação com o ambiente de trabalho?\n", + "EnvironmentSatisfaction 1 'Low' 2 'Medium' 3 'High' 4 'Very High'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "i2xSi55EsJPA", + "outputId": "44d089ca-04d4-468d-97d9-bc590632232f" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "r6tOOyKDM-W0" + }, + "source": [ + "## E a satisfação com o trabalho?\n", + "\n", + "JobSatisfaction 1 'Low' 2 'Medium' 3 'High' 4 'Very High'" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "9A1NhIdwsPpA", + "outputId": "e0139b00-0c54-45e5-9a61-357e73701c87" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "_ojiN-ecJRmP" + }, + "source": [ + "## Elas trabalhavam na empresa há muito tempo?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "VE5wa4LrJRmQ", + "outputId": "5a76c924-2433-4ea4-c002-bce3320a5a45" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "LSZx09YmJRmU" + }, + "source": [ + "## Trabalham além da carga horária?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "0NY-pF1QJRmV", + "outputId": "741e695f-444f-4163-a790-980657d25dd8" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "2k2UCEHROiby" + }, + "source": [ + "### Das pessoas que trabalham, além da carga horária. Como é o nível de satisfação com o nível de trabalho delas?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "RdJpgZoFvb2o", + "outputId": "be07bfaa-1e95-4fd3-db5b-ba397c35e4fa" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "ZHKS6EzrJRmd" + }, + "source": [ + "## Moravam perto do trabalho?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 300 + }, + "id": "GXHvF04UJRme", + "outputId": "710bf8b4-acf0-4685-dd3e-9c4acf2a69d0" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "N13aA8WeJRmr" + }, + "source": [ + "## E qual o nível dessas pessoas?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "OofTpwKxwATB", + "outputId": "dfaa1393-54d0-4f70-e2d6-002b2f5278ad" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "8hnQSmc8JRmy" + }, + "source": [ + "## E o papel delas?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 307 + }, + "id": "M5oz4S9_wHgN", + "outputId": "29dfcfdb-29fa-4999-f1c9-bd05b6b8c8b6" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Quais papéis tem os maiores salários?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 411 + }, + "id": "gbz0pQKSJRnA", + "outputId": "4c905833-1a96-47b9-9025-ab542954e279" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "tqQq1MuKJRnE" + }, + "source": [ + "# Seleção de Features e Feature enginering" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "JtmZiaEcJRnF" + }, + "source": [ + "## Análise da correlação das features" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 749 + }, + "id": "xqDtifvjJRnG", + "outputId": "bf82bf60-8157-4d51-f8d7-f5deac292cbf" + }, + "outputs": [], + "source": [ + "#Gere a correlação das variáveis do seu dataset" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "6YYy7TLZJRnT" + }, + "source": [ + "### Reduzir dimensionalidade\n", + "\n", + "Transforme as colunas ``YearsAtCompany``, ``YearsInCurrentRole``, ``YearsSinceLastPromotion``, ``YearsWithCurrManager`` em apenas uma." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "3gIwPPKmTIJ_", + "outputId": "0874ddb7-88a3-4e83-926e-d5e908bb8e6b" + }, + "outputs": [], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "o7cb6YlAJRnU" + }, + "outputs": [], + "source": [ + "colunas_reduzir = ['YearsAtCompany', 'YearsInCurrentRole','YearsSinceLastPromotion', 'YearsWithCurrManager']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "VNqRBiLWJRnW", + "outputId": "9155c5dc-4fba-4ede-8e11-927b619f6645" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 34 + }, + "id": "-wDc272mJRnY", + "outputId": "3a00db62-2dd9-4c3e-8fab-51d1df923126" + }, + "outputs": [], + "source": [ + "df.shape" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "Ba4aR_k1JRnh" + }, + "source": [ + "## Criar grupos com uma feature\n", + "\n", + "Crie grupos com a variável ``Age``\n", + "\n", + "- 18-24 = grupo1 , 25-45=grupo2 , >=46 grupo3" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 320 + }, + "id": "v5jL2fUdJRni", + "outputId": "af708b79-a156-46ea-dd75-214223c48d97" + }, + "outputs": [], + "source": [ + "#Agrupar as idades\n", + "plt.hist(df[\"Age\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#tranformação" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "uOl3XmjzJRnn" + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "IMG9VCmPJRo7" + }, + "source": [ + "# Modelo - classificação com pycaret" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Pycaret\n", + "\n", + "Pycaret é uma biblioteca de Machine Learning (ML) que automatiza fluxos de trabalho. \n", + "\n", + "documentação: https://pycaret.org/classification/" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data = df.sample(frac=0.95, random_state=786)\n", + "data_unseen = df.drop(data.index)\n", + "data.reset_index(inplace=True, drop=True)\n", + "data_unseen.reset_index(inplace=True, drop=True)\n", + "\n", + "print('Data for Modeling: ' + str(data.shape))\n", + "print('Unseen Data For Predictions: ' + str(data_unseen.shape))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "from pycaret.classification import *" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "setup: Esta função inicializa o ambiente de treinamento e cria o pipeline de transformação. Ela deve ser chamada antes de executar qualquer outra função. Possui dois parâmetros obrigatórios: ``data`` e ``target``." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#configue o setup do pycaret" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " compare_models : Esta função treina e avalia o desempenho de todos os modelos disponíveis na biblioteca de modelos usando validação cruzada (Cross Validation)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Explicação Validação Cruzada\n", + "" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#treine o modelo com os seguintes algortimos:\n", + "#\"lr\",\"knn\",\"nb\",\"dt\",\"svm\",\"rbfsvm\",\"gpc\",\"mlp\",\"ridge\",\"rf\",\"qda\",\"ada\",\"gbc\",\"lda\",\"et\",\"lightgbm\"]\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "V2mEKChPhjxC" + }, + "source": [ + "### Qual métrica utilizar?\n", + "\n", + "Mini-curso sobre métricas:https://www.youtube.com/watch?v=7tGaa_ekXf4&t=216s&ab_channel=A3DataConsultoria" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "rxHsBR_T9gvU" + }, + "source": [ + "Métricas Qual utilizar?\n", + "- VP: modelo diz que a pessoa vai sair e ela sai.\n", + "- VN: modelo diz que a pessoa não vai sair e ela não sai.\n", + "- FN: modelo diz que a pessoa não vai sair e ela sai. \n", + "- FP: modelo diz que a pessoa vai sair e ela não sai.\n", + "- F1 -> harmoniza recall e precision\n", + "\n", + "- Recall -> quanto mais alto o recall menos FN tenho.\n", + "- Precision -> quanto mais alto a precision menos FP tenho.\n", + "- Acurácia -> como meu problema é binário e desbalanceado, não será um modelo bom. Pois, na maior parte dos casos ele informa que todo mundo vai sair." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " create_model: Esta função treina e avalia o desempenho de um determinado modelo usando validação cruzada. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Crie o modelo com o algoritmo que deu a melhor métrica que você entenda que a melhor para o seu problema." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " tune_model: Essa função ajusta os hiperparâmetros de um determinado modelo. " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "#Tune o modelo criado" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Avaliar o modelo" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "plot_model: Esta função analisa o desempenho de um modelo treinado no conjunto de validação}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "plot_model?" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Gere Avalie a matriz de confusão" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Gere o gráficos dos erros " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Gere o gráfico do report das classes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Gere o gráfico das melhores features" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Quais são os parâmetros do seu modelo \"tunado\"\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "evaluate_model: Esta função exibe uma interface de usuário para analisar o desempenho de um treinado" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "#Gera o evaluete model" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Salvar modelo" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + " save_model: Esta função salva o pipeline de transformação e o objeto de modelo treinado no diretório de trabalho atual como um arquivo pickle para uso posterior." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "scrolled": false + }, + "outputs": [], + "source": [ + "#salve o modelo" + ] + } + ], + "metadata": { + "accelerator": "GPU", + "colab": { + "collapsed_sections": [ + "YWUAzo5FJRpr" + ], + "name": "Análise RH.ipynb", + "provenance": [] + }, + "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": "3.8.5" + } + }, + "nbformat": 4, + "nbformat_minor": 1 +} diff --git a/src/hands_on_analyze_collaborators_with_answer.ipynb b/src/hands_on_analyze_collaborators_with_answer.ipynb new file mode 100644 index 0000000..971af3c --- /dev/null +++ b/src/hands_on_analyze_collaborators_with_answer.ipynb @@ -0,0 +1,3850 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 107, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 333 + }, + "collapsed": true, + "id": "P-gLiEsSJYQB", + "outputId": "a7c3ccb6-039f-4da1-9c5d-6567404516e1" + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "--2021-06-26 11:11:15-- https://docs.google.com/uc?export=download&id=1KuesGYYqJ3DdPq1gvMc5Sbs2KcvYXYeE\n", + "Resolving docs.google.com (docs.google.com)... 2800:3f0:4004:802::200e, 142.250.218.110\n", + "Connecting to docs.google.com (docs.google.com)|2800:3f0:4004:802::200e|:443... connected.\n", + "HTTP request sent, awaiting response... 302 Moved Temporarily\n", + "Location: https://doc-0o-3k-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/5ktvmjbv5mjicv85vmjcq0tjfks389na/1624716675000/08155615283259294201/*/1KuesGYYqJ3DdPq1gvMc5Sbs2KcvYXYeE?e=download [following]\n", + "Warning: wildcards not supported in HTTP.\n", + "--2021-06-26 11:11:16-- https://doc-0o-3k-docs.googleusercontent.com/docs/securesc/ha0ro937gcuc7l7deffksulhg5h7mbp1/5ktvmjbv5mjicv85vmjcq0tjfks389na/1624716675000/08155615283259294201/*/1KuesGYYqJ3DdPq1gvMc5Sbs2KcvYXYeE?e=download\n", + "Resolving doc-0o-3k-docs.googleusercontent.com (doc-0o-3k-docs.googleusercontent.com)... 2800:3f0:4004:80e::2001, 142.250.218.97\n", + "Connecting to doc-0o-3k-docs.googleusercontent.com (doc-0o-3k-docs.googleusercontent.com)|2800:3f0:4004:80e::2001|:443... connected.\n", + "HTTP request sent, awaiting response... 200 OK\n", + "Length: 227977 (223K) [text/csv]\n", + "Saving to: ‘data/HR-Employee-Attrition.csv’\n", + "\n", + "data/HR-Employee-At 100%[===================>] 222,63K 1,14MB/s in 0,2s \n", + "\n", + "2021-06-26 11:11:17 (1,14 MB/s) - ‘data/HR-Employee-Attrition.csv’ saved [227977/227977]\n", + "\n" + ] + } + ], + "source": [ + "#Download dataset\n", + "!wget -O 'HR-Employee-Attrition.csv' 'https://docs.google.com/uc?export=download&id=1KuesGYYqJ3DdPq1gvMc5Sbs2KcvYXYeE'" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 577 + }, + "id": "yhMIBA19JaAT", + "outputId": "83a738be-c3d4-4e22-957f-988298dbcb53" + }, + "outputs": [], + "source": [ + "#!pip install -r requirements.txt\n", + "#!pip install pandas==1.2.5\n", + "#!pip install pandas_profiling==2.11.0\n", + "#!pip install matplotlib==3.3.4\n", + "#!pip install pycaret==2.3.1\n", + "#!pip install numpy==1.19.5\n", + "#!pip install seaborn==0.11.1\n", + "#!pip install scikit_learn==0.23.2\n", + "\n", + "#depois de instalar esses pacotes, reinicie o kernel.\n", + " #no jupyer notebook -> Kernel > Restart\n", + " #no colab -> Runtime > Runtime Restart" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "id": "1CtXmkxhJRkN" + }, + "outputs": [], + "source": [ + "import pandas as pd\n", + "import seaborn as sns\n", + "import matplotlib.pyplot as plt \n", + "from sklearn.decomposition import PCA\n", + "import numpy as np\n", + "import warnings\n", + "warnings.filterwarnings('ignore')\n", + "\n", + "sns.set_style(\"whitegrid\")\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "id": "B7cQkNQhJRkY" + }, + "source": [ + "# Leitura dos Dados" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "id": "vk3HKCy4JRka" + }, + "outputs": [], + "source": [ + "df = pd.read_csv(\"HR-Employee-Attrition.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 316 + }, + "id": "vP7vlUINJRkg", + "outputId": "773faa14-d27d-414e-dc89-a2d03c2fcc85" + }, + "outputs": [ + { + "data": { + "text/html": [ + "