Farmer-Adoption-Prediction-and-Clusteringfarmer-adoption-prediction-and-clustering-final.ipynb

{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2022-06-25T18:10:31.970534Z","iopub.execute_input":"2022-06-25T18:10:31.970973Z","iopub.status.idle":"2022-06-25T18:10:31.985054Z","shell.execute_reply.started":"2022-06-25T18:10:31.970938Z","shell.execute_reply":"2022-06-25T18:10:31.983745Z"},"trusted":true},"execution_count":148,"outputs":[{"name":"stdout","text":"/kaggle/input/farmers-adoption-data/Farmers Adoption Data Plateau State - Sheet1 (1).csv\n","output_type":"stream"}]},{"cell_type":"markdown","source":"# FARMERS TECHNOLOGY ADOPTION ANALYSIS\nThis is a personal project with objectives of:\n1. **Investigating the factors influencing adoption of innovation among farmers(hopefully generalizable).**\nThis will be achieved through Exploratory Data Analysis\n2. **Predicting Farmers' likelihood to adopt innovation.**\nA model will be trained with the available data to achieve this.\n3. **Assign individual farmers to various adoption clusters(Innovators....Laggards).**\nClustering will come into play, here.\n","metadata":{}},{"cell_type":"markdown","source":"This project is intended to be revisited quarterly, as more data becomes available, or better still deployed in order to make use of dynamic data.\n\nThe data for this work was extracted from various data sets collected primarily by students and staff of the Agricultural Extension and Management department of Federal College of Forestry, Jos, Plateau state, Nigeria, in their academic researches in various fields. It is also important to note at this point that, some of these data(definitely, more than one source) was not geared towards innovation adoption, hence, additional but non-intrusive work had to be done on the data to make it usable and relevant.","metadata":{}},{"cell_type":"markdown","source":"## Overall Approach/ Strategy\nThe war will be fought proceeding thus(read that in your inner villain voice):\n* **Data Examination**\n* **Data Exploration**\n* **Data Cleaning/wrangling**\n* **Data Visualization**\n* **Feature Engineering**\n* **Modelling**\n* **Evaluating the Model**\n* **Extraction for Deployment**\n\n*Nick Renotte, the above has you written all over, in my book anyways*\n\nCheck link for raw(mischievious wink file). [Rough Outline](https://github.com/maranatha443/My-ML-Projects/blob/352436cb0f3fc56f6f654ff0af8364e8a6f4d8d4/WhatsApp%20Image%202022-06-24%20at%2012.12.23%20PM.jpeg?raw=true)","metadata":{}},{"cell_type":"markdown","source":"### Data Examination, Exploration, Cleaning, and Visualization.\nLet's check our data mate.","metadata":{}},{"cell_type":"code","source":"abs# import relevant libraries, yeah I'm spoilt for choice, blame Nicholas @ world quaint uni.\nimport pandas as pd\nimport numpy as np\nfrom matplotlib import pyplot as plt\nimport seaborn as sns\nimport plotly_express as px\nprint(\"Set-up complete\")","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:31.987607Z","iopub.execute_input":"2022-06-25T18:10:31.988311Z","iopub.status.idle":"2022-06-25T18:10:31.996748Z","shell.execute_reply.started":"2022-06-25T18:10:31.988258Z","shell.execute_reply":"2022-06-25T18:10:31.995660Z"},"trusted":true},"execution_count":149,"outputs":[{"name":"stdout","text":"Set-up complete\n","output_type":"stream"}]},{"cell_type":"code","source":"# Load the dataset.\ndf = pd.read_csv(\"../input/farmers-adoption-data/Farmers Adoption Data Plateau State - Sheet1 (1).csv\")\ndf.head()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.003842Z","iopub.execute_input":"2022-06-25T18:10:32.004658Z","iopub.status.idle":"2022-06-25T18:10:32.026377Z","shell.execute_reply.started":"2022-06-25T18:10:32.004621Z","shell.execute_reply":"2022-06-25T18:10:32.025283Z"},"trusted":true},"execution_count":150,"outputs":[{"execution_count":150,"output_type":"execute_result","data":{"text/plain":"   AGE     SEX  EDUCATN STATUS HH/SIZE  F/EXP  F/SIZE  EXT TRAINING  INCOME  \\\n0   32    MALE               6       5      4       3             0   30000   \n1   32  FEMALE              12       4      5       4             1   31000   \n2   55    MALE               0       5      7       5             0   29000   \n3   56  FEMALE              12       6      8       3             0   26000   \n4   26    MALE              12       5      4       5             3   23000   \n\n   ADOPTION STATUS  \n0                1  \n1                1  \n2                1  \n3                1  \n4                0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>AGE</th>\n      <th>SEX</th>\n      <th>EDUCATN STATUS</th>\n      <th>HH/SIZE</th>\n      <th>F/EXP</th>\n      <th>F/SIZE</th>\n      <th>EXT TRAINING</th>\n      <th>INCOME</th>\n      <th>ADOPTION STATUS</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>32</td>\n      <td>MALE</td>\n      <td>6</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0</td>\n      <td>30000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>32</td>\n      <td>FEMALE</td>\n      <td>12</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>1</td>\n      <td>31000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>55</td>\n      <td>MALE</td>\n      <td>0</td>\n      <td>5</td>\n      <td>7</td>\n      <td>5</td>\n      <td>0</td>\n      <td>29000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>56</td>\n      <td>FEMALE</td>\n      <td>12</td>\n      <td>6</td>\n      <td>8</td>\n      <td>3</td>\n      <td>0</td>\n      <td>26000</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>26</td>\n      <td>MALE</td>\n      <td>12</td>\n      <td>5</td>\n      <td>4</td>\n      <td>5</td>\n      <td>3</td>\n      <td>23000</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"# Let's Explore a bit.\nprint(df.shape)\ndf.info()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.031540Z","iopub.execute_input":"2022-06-25T18:10:32.032091Z","iopub.status.idle":"2022-06-25T18:10:32.048180Z","shell.execute_reply.started":"2022-06-25T18:10:32.032059Z","shell.execute_reply":"2022-06-25T18:10:32.047026Z"},"trusted":true},"execution_count":151,"outputs":[{"name":"stdout","text":"(501, 9)\n<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 501 entries, 0 to 500\nData columns (total 9 columns):\n #   Column           Non-Null Count  Dtype \n---  ------           --------------  ----- \n 0   AGE              501 non-null    int64 \n 1   SEX              501 non-null    object\n 2   EDUCATN STATUS   501 non-null    int64 \n 3   HH/SIZE          501 non-null    object\n 4   F/EXP            501 non-null    int64 \n 5   F/SIZE           501 non-null    int64 \n 6   EXT TRAINING     501 non-null    int64 \n 7   INCOME           501 non-null    int64 \n 8   ADOPTION STATUS  501 non-null    int64 \ndtypes: int64(7), object(2)\nmemory usage: 35.4+ KB\n","output_type":"stream"}]},{"cell_type":"markdown","source":"It would seem as though our dataset, though small is lean enough at 501 instances for 9 features(Dr Cassie, am I right?). Let's dig deeper.","metadata":{}},{"cell_type":"code","source":"# Let's check the categorical variables.\ndf.select_dtypes(\"object\").describe()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.050216Z","iopub.execute_input":"2022-06-25T18:10:32.050554Z","iopub.status.idle":"2022-06-25T18:10:32.068324Z","shell.execute_reply.started":"2022-06-25T18:10:32.050521Z","shell.execute_reply":"2022-06-25T18:10:32.066878Z"},"trusted":true},"execution_count":152,"outputs":[{"execution_count":152,"output_type":"execute_result","data":{"text/plain":"         SEX HH/SIZE\ncount    501     501\nunique     2      13\ntop     MALE       3\nfreq     342     119","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>SEX</th>\n      <th>HH/SIZE</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>501</td>\n      <td>501</td>\n    </tr>\n    <tr>\n      <th>unique</th>\n      <td>2</td>\n      <td>13</td>\n    </tr>\n    <tr>\n      <th>top</th>\n      <td>MALE</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>freq</th>\n      <td>342</td>\n      <td>119</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"Guess I concluded too soon, what with Household size being considered an object, Unacceptable!","metadata":{}},{"cell_type":"code","source":"# Cleaning Household size(Excel or SQL \"clean\", could really shine here.)\ndf[df[\"HH/SIZE\"].str.contains(\"`\")]","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.076869Z","iopub.execute_input":"2022-06-25T18:10:32.077859Z","iopub.status.idle":"2022-06-25T18:10:32.094084Z","shell.execute_reply.started":"2022-06-25T18:10:32.077819Z","shell.execute_reply":"2022-06-25T18:10:32.092883Z"},"trusted":true},"execution_count":153,"outputs":[{"execution_count":153,"output_type":"execute_result","data":{"text/plain":"     AGE     SEX  EDUCATN STATUS HH/SIZE  F/EXP  F/SIZE  EXT TRAINING  INCOME  \\\n437   36  FEMALE               1      `1      2       3             2   75000   \n\n     ADOPTION STATUS  \n437                0  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>AGE</th>\n      <th>SEX</th>\n      <th>EDUCATN STATUS</th>\n      <th>HH/SIZE</th>\n      <th>F/EXP</th>\n      <th>F/SIZE</th>\n      <th>EXT TRAINING</th>\n      <th>INCOME</th>\n      <th>ADOPTION STATUS</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>437</th>\n      <td>36</td>\n      <td>FEMALE</td>\n      <td>1</td>\n      <td>`1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>75000</td>\n      <td>0</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"# Still cleaning...\ndf.loc[437, \"HH/SIZE\"] = 1","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.095719Z","iopub.execute_input":"2022-06-25T18:10:32.096046Z","iopub.status.idle":"2022-06-25T18:10:32.103129Z","shell.execute_reply.started":"2022-06-25T18:10:32.096015Z","shell.execute_reply":"2022-06-25T18:10:32.101584Z"},"trusted":true},"execution_count":154,"outputs":[]},{"cell_type":"code","source":"# Change Household size to integers.\ndf[\"HH/SIZE\"] = df[\"HH/SIZE\"].astype(int)","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.112851Z","iopub.execute_input":"2022-06-25T18:10:32.113735Z","iopub.status.idle":"2022-06-25T18:10:32.120212Z","shell.execute_reply.started":"2022-06-25T18:10:32.113690Z","shell.execute_reply":"2022-06-25T18:10:32.118629Z"},"trusted":true},"execution_count":155,"outputs":[]},{"cell_type":"code","source":"# Check it to confirm changes.\ndf.select_dtypes(\"object\").describe()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.132590Z","iopub.execute_input":"2022-06-25T18:10:32.132965Z","iopub.status.idle":"2022-06-25T18:10:32.149747Z","shell.execute_reply.started":"2022-06-25T18:10:32.132933Z","shell.execute_reply":"2022-06-25T18:10:32.148505Z"},"trusted":true},"execution_count":156,"outputs":[{"execution_count":156,"output_type":"execute_result","data":{"text/plain":"         SEX\ncount    501\nunique     2\ntop     MALE\nfreq     342","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>SEX</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>501</td>\n    </tr>\n    <tr>\n      <th>unique</th>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>top</th>\n      <td>MALE</td>\n    </tr>\n    <tr>\n      <th>freq</th>\n      <td>342</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"That's better.","metadata":{}},{"cell_type":"code","source":"# Describe numeric features.\ndf.select_dtypes(\"number\").describe()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.219657Z","iopub.execute_input":"2022-06-25T18:10:32.220057Z","iopub.status.idle":"2022-06-25T18:10:32.266477Z","shell.execute_reply.started":"2022-06-25T18:10:32.220023Z","shell.execute_reply":"2022-06-25T18:10:32.265043Z"},"trusted":true},"execution_count":157,"outputs":[{"execution_count":157,"output_type":"execute_result","data":{"text/plain":"              AGE  EDUCATN STATUS     HH/SIZE       F/EXP      F/SIZE  \\\ncount  501.000000      501.000000  501.000000  501.000000  501.000000   \nmean    41.656687        9.373253    3.984032    5.502994    5.105788   \nstd     10.005294        5.660248    1.823114    3.332040    4.515616   \nmin     19.000000        0.000000    1.000000    1.000000    1.000000   \n25%     34.000000        5.000000    3.000000    3.000000    2.000000   \n50%     40.000000       12.000000    4.000000    4.000000    4.000000   \n75%     50.000000       15.000000    5.000000    8.000000    6.000000   \nmax     81.000000       18.000000   12.000000   19.000000   33.000000   \n\n       EXT TRAINING        INCOME  ADOPTION STATUS  \ncount    501.000000  5.010000e+02       501.000000  \nmean       0.732535  2.405877e+05         0.514970  \nstd        0.812600  3.761635e+05         0.500275  \nmin        0.000000  1.000000e+04         0.000000  \n25%        0.000000  3.500000e+04         0.000000  \n50%        1.000000  9.765000e+04         1.000000  \n75%        1.000000  2.123100e+05         1.000000  \nmax        3.000000  2.520000e+06         1.000000  ","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>AGE</th>\n      <th>EDUCATN STATUS</th>\n      <th>HH/SIZE</th>\n      <th>F/EXP</th>\n      <th>F/SIZE</th>\n      <th>EXT TRAINING</th>\n      <th>INCOME</th>\n      <th>ADOPTION STATUS</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>count</th>\n      <td>501.000000</td>\n      <td>501.000000</td>\n      <td>501.000000</td>\n      <td>501.000000</td>\n      <td>501.000000</td>\n      <td>501.000000</td>\n      <td>5.010000e+02</td>\n      <td>501.000000</td>\n    </tr>\n    <tr>\n      <th>mean</th>\n      <td>41.656687</td>\n      <td>9.373253</td>\n      <td>3.984032</td>\n      <td>5.502994</td>\n      <td>5.105788</td>\n      <td>0.732535</td>\n      <td>2.405877e+05</td>\n      <td>0.514970</td>\n    </tr>\n    <tr>\n      <th>std</th>\n      <td>10.005294</td>\n      <td>5.660248</td>\n      <td>1.823114</td>\n      <td>3.332040</td>\n      <td>4.515616</td>\n      <td>0.812600</td>\n      <td>3.761635e+05</td>\n      <td>0.500275</td>\n    </tr>\n    <tr>\n      <th>min</th>\n      <td>19.000000</td>\n      <td>0.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>1.000000</td>\n      <td>0.000000</td>\n      <td>1.000000e+04</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>25%</th>\n      <td>34.000000</td>\n      <td>5.000000</td>\n      <td>3.000000</td>\n      <td>3.000000</td>\n      <td>2.000000</td>\n      <td>0.000000</td>\n      <td>3.500000e+04</td>\n      <td>0.000000</td>\n    </tr>\n    <tr>\n      <th>50%</th>\n      <td>40.000000</td>\n      <td>12.000000</td>\n      <td>4.000000</td>\n      <td>4.000000</td>\n      <td>4.000000</td>\n      <td>1.000000</td>\n      <td>9.765000e+04</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>75%</th>\n      <td>50.000000</td>\n      <td>15.000000</td>\n      <td>5.000000</td>\n      <td>8.000000</td>\n      <td>6.000000</td>\n      <td>1.000000</td>\n      <td>2.123100e+05</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>max</th>\n      <td>81.000000</td>\n      <td>18.000000</td>\n      <td>12.000000</td>\n      <td>19.000000</td>\n      <td>33.000000</td>\n      <td>3.000000</td>\n      <td>2.520000e+06</td>\n      <td>1.000000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"Tentatively, we can kinda, sorta, see that \"Income\" is not in the same class(pun intended), and as such is a candidate for scaling, it's also looking severely riddled with noise.\n\nAGE seems to be close to a normal distribution(mean close to median), with majority of farmers between 20 and 60, while EDUC seems to indicate a skew, though that was to be expected, more on that to come.\n\n\nLet's try and understand more about the data points by visualization.","metadata":{}},{"cell_type":"code","source":"# For the last time, let's follow Jose Portilla, sorry Nicholas;\nsns.pairplot(df);","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:32.269681Z","iopub.execute_input":"2022-06-25T18:10:32.270196Z","iopub.status.idle":"2022-06-25T18:10:46.938884Z","shell.execute_reply.started":"2022-06-25T18:10:32.270147Z","shell.execute_reply":"2022-06-25T18:10:46.937617Z"},"trusted":true},"execution_count":158,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1440x1440 with 72 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"So having done that jumbled beauty, let's use a considered approach.","metadata":{}},{"cell_type":"code","source":"# Create a function to visualize distribution and compare features on adoption basis.\ndef show_dist(data_col, data_frame=df):\n    # Create a figure for 2 subplots (2 rows, 1 column)\n    fig, ax = plt.subplots(1, 2, figsize = (15,6))\n\n    # Plot the histogram   \n    sns.histplot(data_col, ax=ax[0], kde=True)\n    ax[0].set_ylabel(\"Frequency\")\n    \n    # Plot the boxplot   \n    sns.boxplot(y=data_col, x=data_frame[\"ADOPTION STATUS\"], ax=ax[1])\n    ax[1].set_ylabel(\"Frequency\")\n    \n#     # Plot the barplot\n#     sns.barplot(y=data_col, x=data_frame[\"ADOPTION STATUS\"])\n\n    # Add a title to the Figure\n    fig.suptitle(\"Distribution of {} by ADOPTION STATUS\".format(data_col.name));\n\n    # Show the figure\n    fig.show()\n","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:46.940832Z","iopub.execute_input":"2022-06-25T18:10:46.941378Z","iopub.status.idle":"2022-06-25T18:10:46.952893Z","shell.execute_reply.started":"2022-06-25T18:10:46.941321Z","shell.execute_reply":"2022-06-25T18:10:46.951253Z"},"trusted":true},"execution_count":159,"outputs":[]},{"cell_type":"code","source":"df[\"AGE\"].name","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:46.954604Z","iopub.execute_input":"2022-06-25T18:10:46.955775Z","iopub.status.idle":"2022-06-25T18:10:46.972982Z","shell.execute_reply.started":"2022-06-25T18:10:46.955737Z","shell.execute_reply":"2022-06-25T18:10:46.971675Z"},"trusted":true},"execution_count":160,"outputs":[{"execution_count":160,"output_type":"execute_result","data":{"text/plain":"'AGE'"},"metadata":{}}]},{"cell_type":"code","source":"show_dist(df[\"AGE\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:46.975915Z","iopub.execute_input":"2022-06-25T18:10:46.976810Z","iopub.status.idle":"2022-06-25T18:10:47.397850Z","shell.execute_reply.started":"2022-06-25T18:10:46.976774Z","shell.execute_reply":"2022-06-25T18:10:47.396562Z"},"trusted":true},"execution_count":161,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"AGE checks out as discussed earlier, Note though that generally, adopters(is that even a word), tended to be spread across a more varied age range. I wonder if that would remain if outliers are stripped, well we can check(for science of course).","metadata":{}},{"cell_type":"code","source":"# Collect only data points between 10th and 90th percentile.\nlow, high = df[\"AGE\"].quantile([0.1,0.9])\nshow_dist(df[df[\"AGE\"].between(low, high)][\"AGE\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:10:47.399546Z","iopub.execute_input":"2022-06-25T18:10:47.399907Z","iopub.status.idle":"2022-06-25T18:10:47.829868Z","shell.execute_reply.started":"2022-06-25T18:10:47.399875Z","shell.execute_reply":"2022-06-25T18:10:47.828396Z"},"trusted":true},"execution_count":162,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"Not much in terms of changes besides, loping off valuable information(Notice younger repondents \"somehow\" went missing), So bin it.\n\nWith AGE being successfully analyzed, let's consider the others.","metadata":{}},{"cell_type":"code","source":"# Let's loop through.\nfor cols in df.select_dtypes(\"number\").drop(columns=\"ADOPTION STATUS\"):\n    show_dist(df[cols])","metadata":{"_kg_hide-output":true,"trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Now, that's one experiment I'm never trying again. Sure you can go ahead and run the code above(if you want headache).\n\nSO, let's take them individually.","metadata":{}},{"cell_type":"code","source":"df.info()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:07.247900Z","iopub.execute_input":"2022-06-25T18:11:07.248234Z","iopub.status.idle":"2022-06-25T18:11:07.264232Z","shell.execute_reply.started":"2022-06-25T18:11:07.248200Z","shell.execute_reply":"2022-06-25T18:11:07.262937Z"},"trusted":true},"execution_count":164,"outputs":[{"name":"stdout","text":"<class 'pandas.core.frame.DataFrame'>\nRangeIndex: 501 entries, 0 to 500\nData columns (total 9 columns):\n #   Column           Non-Null Count  Dtype \n---  ------           --------------  ----- \n 0   AGE              501 non-null    int64 \n 1   SEX              501 non-null    object\n 2   EDUCATN STATUS   501 non-null    int64 \n 3   HH/SIZE          501 non-null    int64 \n 4   F/EXP            501 non-null    int64 \n 5   F/SIZE           501 non-null    int64 \n 6   EXT TRAINING     501 non-null    int64 \n 7   INCOME           501 non-null    int64 \n 8   ADOPTION STATUS  501 non-null    int64 \ndtypes: int64(8), object(1)\nmemory usage: 35.4+ KB\n","output_type":"stream"}]},{"cell_type":"code","source":"show_dist(df[\"EDUCATN STATUS\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:07.265997Z","iopub.execute_input":"2022-06-25T18:11:07.266345Z","iopub.status.idle":"2022-06-25T18:11:07.695086Z","shell.execute_reply.started":"2022-06-25T18:11:07.266312Z","shell.execute_reply":"2022-06-25T18:11:07.693668Z"},"trusted":true},"execution_count":165,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"There are so many things wrong with this distribution, however, Its bodering on the ridiculous to even imagine that the average education of the farmers who have not adopted innovation, is about the same with the lower 25th percentile of those who adopted said technologies. Also, it isn't really too strange that there seems to be under representation in some years. The country(Nigeria), operates a 6-3-3-4, education system in theory, but in practice, it's more like 6-6-4, as most people who sucessfully complete their Junior secondary school years, eventually complete the Senior years(No reference). More work for future versions then.","metadata":{}},{"cell_type":"code","source":"show_dist(df[\"HH/SIZE\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:07.699693Z","iopub.execute_input":"2022-06-25T18:11:07.700210Z","iopub.status.idle":"2022-06-25T18:11:08.134329Z","shell.execute_reply.started":"2022-06-25T18:11:07.700160Z","shell.execute_reply":"2022-06-25T18:11:08.133056Z"},"trusted":true},"execution_count":166,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"We have a good distribution, if slighty skewed to the right, however, the outliers which make this so, still rings true in the rural communities, where polygamy is common and large households though on the wane are still a thing. Though, the average of 4 leaves a lot to be desired(God save us from unscrupulous data(No offenses)).","metadata":{}},{"cell_type":"code","source":"show_dist(df[\"F/EXP\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:08.135726Z","iopub.execute_input":"2022-06-25T18:11:08.136047Z","iopub.status.idle":"2022-06-25T18:11:08.557846Z","shell.execute_reply.started":"2022-06-25T18:11:08.136015Z","shell.execute_reply":"2022-06-25T18:11:08.556689Z"},"trusted":true},"execution_count":167,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"Another good distribution which shows the slighly alarming state in the rural communities viz; Farmibg is on the decline(No references). Its been a trend noticed in the country that youths tend to consider farming as a lesser option compared to other economic activities. This trend, though interesting is beyond the scope of this data and subsequently project. As an intelligent(at least to me) woman once implied, the only world you can draw absolutely accurate inferences is the world your data represents.","metadata":{}},{"cell_type":"code","source":"show_dist(df[\"F/SIZE\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:08.559355Z","iopub.execute_input":"2022-06-25T18:11:08.559722Z","iopub.status.idle":"2022-06-25T18:11:09.020027Z","shell.execute_reply.started":"2022-06-25T18:11:08.559689Z","shell.execute_reply":"2022-06-25T18:11:09.018679Z"},"trusted":true},"execution_count":168,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"Now, where do we even begin with this travesty....I'll just leave you be till I have sufficient data. However, what's immediately apparent here is that most farmers are small to medium scale.","metadata":{}},{"cell_type":"code","source":"def show_cat_plot(data_col, data_frame=df):\n    # Create a figure for 2 subplots (2 rows, 1 column)\n    plt.figure(figsize = (15,6))\n\n    # Plot the histogram   \n    sns.countplot(x=data_col, hue=\"ADOPTION STATUS\", data=data_frame, orient=\"v\")\n    \n    # Add a title to the Figure\n    plt.title(\"Data Distribution of {} by ADOPTION STATUS\".format(data_col.name));\n\n    # Show the figure\n    #fig.show()\n\n","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:09.021756Z","iopub.execute_input":"2022-06-25T18:11:09.022918Z","iopub.status.idle":"2022-06-25T18:11:09.031064Z","shell.execute_reply.started":"2022-06-25T18:11:09.022868Z","shell.execute_reply":"2022-06-25T18:11:09.029801Z"},"trusted":true},"execution_count":169,"outputs":[]},{"cell_type":"code","source":"show_cat_plot(df[\"EXT TRAINING\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:09.032601Z","iopub.execute_input":"2022-06-25T18:11:09.032950Z","iopub.status.idle":"2022-06-25T18:11:09.298139Z","shell.execute_reply.started":"2022-06-25T18:11:09.032918Z","shell.execute_reply":"2022-06-25T18:11:09.296694Z"},"trusted":true},"execution_count":170,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"From the above exposure to extensions services or trainings does not seem to have any effects poditively or negatively on adoption. However, an interesting note is that most adopters haven't had contact with any form of training.","metadata":{}},{"cell_type":"code","source":"show_cat_plot(df[\"SEX\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:09.299695Z","iopub.execute_input":"2022-06-25T18:11:09.300045Z","iopub.status.idle":"2022-06-25T18:11:09.537644Z","shell.execute_reply.started":"2022-06-25T18:11:09.300013Z","shell.execute_reply":"2022-06-25T18:11:09.536399Z"},"trusted":true},"execution_count":171,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 1 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"As seen above, SEX or GENDER does not seem to favour either categories. This is not to say there are no underlying issues or that the feature is useless, it simply implies that there is a good representation in the data.\n\nNext, we discuss income(left on purpose).","metadata":{}},{"cell_type":"code","source":"show_dist(df[\"INCOME\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:09.542058Z","iopub.execute_input":"2022-06-25T18:11:09.542387Z","iopub.status.idle":"2022-06-25T18:11:10.082300Z","shell.execute_reply.started":"2022-06-25T18:11:09.542355Z","shell.execute_reply":"2022-06-25T18:11:10.080929Z"},"trusted":true},"execution_count":172,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":"# Collect only data points between 10th and 90th percentile.\nlow, high = df[\"INCOME\"].quantile([0,0.7])\nshow_dist(df[df[\"INCOME\"].between(low, high)][\"INCOME\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.084039Z","iopub.execute_input":"2022-06-25T18:11:10.085216Z","iopub.status.idle":"2022-06-25T18:11:10.493873Z","shell.execute_reply.started":"2022-06-25T18:11:10.085174Z","shell.execute_reply":"2022-06-25T18:11:10.492667Z"},"trusted":true},"execution_count":173,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 2 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"The amateur statistician in me is crying as I can't afford to lop off a whopping 30% of \"my precious\" dataset. Let's train and see.\n\nFinally to the target.","metadata":{}},{"cell_type":"code","source":"# check for class imbalance.\nprint(df[\"ADOPTION STATUS\"].value_counts(normalize=True))\nshow_cat_plot(df[\"ADOPTION STATUS\"])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.495181Z","iopub.execute_input":"2022-06-25T18:11:10.495513Z","iopub.status.idle":"2022-06-25T18:11:10.727183Z","shell.execute_reply.started":"2022-06-25T18:11:10.495481Z","shell.execute_reply":"2022-06-25T18:11:10.725950Z"},"trusted":true},"execution_count":174,"outputs":[{"name":"stdout","text":"1    0.51497\n0    0.48503\nName: ADOPTION STATUS, dtype: float64\n","output_type":"stream"},{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"The target attribute seems to be well balanced with adoption accounting for 51% of the farmers in the dataset, while 49% of said farmers did not adopt innovation.","metadata":{}},{"cell_type":"markdown","source":"### Feature Engineering\nThis is pretty meh, hopefully, will come back to it after, training.\n","metadata":{}},{"cell_type":"code","source":"# SYDD and Scale the data\nfrom sklearn.model_selection import train_test_split\n\n# Split to feature matrix and target vector.\ntarget = \"ADOPTION STATUS\"\nX = df.drop(columns=target)\ny = df[target]\n\n# Split to train, validation, and test data.\nX_temp, X_test, y_temp, y_test = train_test_split(X, y, test_size=0.3, random_state=42)\nX_train, X_val, y_train, y_val = train_test_split(X_temp, y_temp, test_size=0.3, random_state=42)\n\n# print shapes\nprint(f\" X's shape is {X.shape} and y's shape is {y.shape}.\")\nprint(f\" X_train's shape is {X_train.shape} and y_train's shape is {y_train.shape}.\")\nprint(f\" X_val's shape is {X_val.shape} and y_val's shape is {y_val.shape}.\")\nprint(f\" X_test's shape is {X_test.shape} and y_test's shape is {y_test.shape}.\")","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.728620Z","iopub.execute_input":"2022-06-25T18:11:10.729428Z","iopub.status.idle":"2022-06-25T18:11:10.744368Z","shell.execute_reply.started":"2022-06-25T18:11:10.729394Z","shell.execute_reply":"2022-06-25T18:11:10.742222Z"},"trusted":true},"execution_count":175,"outputs":[{"name":"stdout","text":" X's shape is (501, 8) and y's shape is (501,).\n X_train's shape is (245, 8) and y_train's shape is (245,).\n X_val's shape is (105, 8) and y_val's shape is (105,).\n X_test's shape is (151, 8) and y_test's shape is (151,).\n","output_type":"stream"}]},{"cell_type":"markdown","source":"### Modelling\nWe'll be using three models viz:\n* Random Forest classifier\n* Logistic Regression\n* XG Boost classifier\n* SVM classifier(because why not, right?)\n \nThe one with the best performance(Accuracy) will be chosen.","metadata":{}},{"cell_type":"code","source":"X.head()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.745814Z","iopub.execute_input":"2022-06-25T18:11:10.746156Z","iopub.status.idle":"2022-06-25T18:11:10.763551Z","shell.execute_reply.started":"2022-06-25T18:11:10.746124Z","shell.execute_reply":"2022-06-25T18:11:10.762634Z"},"trusted":true},"execution_count":176,"outputs":[{"execution_count":176,"output_type":"execute_result","data":{"text/plain":"   AGE     SEX  EDUCATN STATUS  HH/SIZE  F/EXP  F/SIZE  EXT TRAINING  INCOME\n0   32    MALE               6        5      4       3             0   30000\n1   32  FEMALE              12        4      5       4             1   31000\n2   55    MALE               0        5      7       5             0   29000\n3   56  FEMALE              12        6      8       3             0   26000\n4   26    MALE              12        5      4       5             3   23000","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>AGE</th>\n      <th>SEX</th>\n      <th>EDUCATN STATUS</th>\n      <th>HH/SIZE</th>\n      <th>F/EXP</th>\n      <th>F/SIZE</th>\n      <th>EXT TRAINING</th>\n      <th>INCOME</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>32</td>\n      <td>MALE</td>\n      <td>6</td>\n      <td>5</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0</td>\n      <td>30000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>32</td>\n      <td>FEMALE</td>\n      <td>12</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>1</td>\n      <td>31000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>55</td>\n      <td>MALE</td>\n      <td>0</td>\n      <td>5</td>\n      <td>7</td>\n      <td>5</td>\n      <td>0</td>\n      <td>29000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>56</td>\n      <td>FEMALE</td>\n      <td>12</td>\n      <td>6</td>\n      <td>8</td>\n      <td>3</td>\n      <td>0</td>\n      <td>26000</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>26</td>\n      <td>MALE</td>\n      <td>12</td>\n      <td>5</td>\n      <td>4</td>\n      <td>5</td>\n      <td>3</td>\n      <td>23000</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"y.head()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.765090Z","iopub.execute_input":"2022-06-25T18:11:10.765415Z","iopub.status.idle":"2022-06-25T18:11:10.777170Z","shell.execute_reply.started":"2022-06-25T18:11:10.765383Z","shell.execute_reply":"2022-06-25T18:11:10.776026Z"},"trusted":true},"execution_count":177,"outputs":[{"execution_count":177,"output_type":"execute_result","data":{"text/plain":"0    1\n1    1\n2    1\n3    1\n4    0\nName: ADOPTION STATUS, dtype: int64"},"metadata":{}}]},{"cell_type":"code","source":"# Importing the estimators and preprocessors.\nfrom sklearn.pipeline import Pipeline, make_pipeline\nfrom category_encoders import OneHotEncoder\nfrom sklearn.ensemble import RandomForestClassifier\nfrom sklearn.linear_model import LogisticRegression\nfrom xgboost import XGBClassifier\nfrom sklearn.svm import SVC\nfrom sklearn.model_selection import GridSearchCV\nfrom sklearn.preprocessing import StandardScaler","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.778565Z","iopub.execute_input":"2022-06-25T18:11:10.779177Z","iopub.status.idle":"2022-06-25T18:11:10.787503Z","shell.execute_reply.started":"2022-06-25T18:11:10.779132Z","shell.execute_reply":"2022-06-25T18:11:10.786219Z"},"trusted":true},"execution_count":178,"outputs":[]},{"cell_type":"code","source":"# Instantiate pipelines for relevant models.\nclf_rf = make_pipeline(\n    OneHotEncoder(use_cat_names=True),\n    StandardScaler(),\n    RandomForestClassifier(random_state=42)\n)\n\n\nclf_lr = make_pipeline(\n    OneHotEncoder(use_cat_names=True),\n    StandardScaler(),\n    LogisticRegression(random_state=42)\n)\n\nclf_xgbc = make_pipeline(\n    OneHotEncoder(use_cat_names=True),\n    StandardScaler(),\n    XGBClassifier(random_state=42)\n)\n\nclf_svc = make_pipeline(\n    OneHotEncoder(use_cat_names=True),\n    StandardScaler(),\n    SVC(random_state=42)\n)\n      \nmodel_list = [clf_rf, clf_lr, clf_xgbc, clf_svc]\nmodel_list","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.788866Z","iopub.execute_input":"2022-06-25T18:11:10.789772Z","iopub.status.idle":"2022-06-25T18:11:10.821357Z","shell.execute_reply.started":"2022-06-25T18:11:10.789726Z","shell.execute_reply":"2022-06-25T18:11:10.819892Z"},"trusted":true},"execution_count":179,"outputs":[{"execution_count":179,"output_type":"execute_result","data":{"text/plain":"[Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                 ('standardscaler', StandardScaler()),\n                 ('randomforestclassifier',\n                  RandomForestClassifier(random_state=42))]),\n Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                 ('standardscaler', StandardScaler()),\n                 ('logisticregression', LogisticRegression(random_state=42))]),\n Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                 ('standardscaler', StandardScaler()),\n                 ('xgbclassifier',\n                  XGBClassifier(base_score=None, booster=None, callbacks=None,\n                                colsample_bylevel=None, colsample_bynode=None,\n                                colsample_bytree=None,\n                                early_stopping_rounds=None,\n                                enable_categorical=False, eval_metric=None,\n                                gamma=None, gpu_id=None, grow_policy=None,\n                                importance_type=None,\n                                interaction_constraints=None, learning_rate=None,\n                                max_bin=None, max_cat_to_onehot=None,\n                                max_delta_step=None, max_depth=None,\n                                max_leaves=None, min_child_weight=None,\n                                missing=nan, monotone_constraints=None,\n                                n_estimators=100, n_jobs=None,\n                                num_parallel_tree=None, predictor=None,\n                                random_state=42, reg_alpha=None, reg_lambda=None, ...))]),\n Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                 ('standardscaler', StandardScaler()),\n                 ('svc', SVC(random_state=42))])]"},"metadata":{}}]},{"cell_type":"markdown","source":"Tried so hard(probably not accurate enough), to do some thing cool codewise, but \"Machine Learning is not for perfectionists\", so room to improve.","metadata":{"execution":{"iopub.status.busy":"2022-06-25T14:38:18.28845Z","iopub.execute_input":"2022-06-25T14:38:18.289065Z","iopub.status.idle":"2022-06-25T14:38:18.32192Z","shell.execute_reply.started":"2022-06-25T14:38:18.289022Z","shell.execute_reply":"2022-06-25T14:38:18.320421Z"}}},{"cell_type":"code","source":"# Setting up a hyper parameter grid\n\nhyper_grid = {\n    clf_rf: {\n        \"randomforestclassifier__max_depth\":range(1, 20 ,2),\n        \"randomforestclassifier__n_estimators\":range(20, 200, 20)\n        },\n    clf_lr: {\n        \"logisticregression__max_iter\":[500,1000,2000]\n        },\n    clf_xgbc:{\n        \"xgbclassifier__n_estimators\":range(50, 100, 25),\n        \"xgbclassifier__learning_rate\":[0.01, 0.03, 0.05]\n    },\n    clf_svc: {\n        \"svc__kernel\":[\"linear\", \"poly\", \"rbf\"]\n        \n    }\n}\n","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.823070Z","iopub.execute_input":"2022-06-25T18:11:10.823920Z","iopub.status.idle":"2022-06-25T18:11:10.831399Z","shell.execute_reply.started":"2022-06-25T18:11:10.823883Z","shell.execute_reply":"2022-06-25T18:11:10.830503Z"},"trusted":true},"execution_count":180,"outputs":[]},{"cell_type":"code","source":"hyper_grid[clf_rf]","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.832729Z","iopub.execute_input":"2022-06-25T18:11:10.833741Z","iopub.status.idle":"2022-06-25T18:11:10.848939Z","shell.execute_reply.started":"2022-06-25T18:11:10.833704Z","shell.execute_reply":"2022-06-25T18:11:10.847948Z"},"trusted":true},"execution_count":181,"outputs":[{"execution_count":181,"output_type":"execute_result","data":{"text/plain":"{'randomforestclassifier__max_depth': range(1, 20, 2),\n 'randomforestclassifier__n_estimators': range(20, 200, 20)}"},"metadata":{}}]},{"cell_type":"markdown","source":"##### GRID SEARCH","metadata":{}},{"cell_type":"code","source":"# Run CV and time it.\nimport time\n\nbest_models = []\nfor algo in model_list:\n    model = GridSearchCV(algo, param_grid=hyper_grid[algo], cv=5, n_jobs=-1)\n    print('Starting training for {}'.format(algo))\n    start_t = time.time()\n    model.fit(X_train, y_train)\n    best_models.append(model)\n    \n    end_t = round(time.time() - start_t, 2)\n    print(f\"{algo} has been successfully trained in {round(end_t/60, 4)} mins.\")","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:11:10.850585Z","iopub.execute_input":"2022-06-25T18:11:10.851192Z","iopub.status.idle":"2022-06-25T18:12:03.796514Z","shell.execute_reply.started":"2022-06-25T18:11:10.851158Z","shell.execute_reply":"2022-06-25T18:12:03.794965Z"},"trusted":true},"execution_count":182,"outputs":[{"name":"stdout","text":"Starting training for Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('randomforestclassifier',\n                 RandomForestClassifier(random_state=42))])\nPipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('randomforestclassifier',\n                 RandomForestClassifier(random_state=42))]) has been successfully trained in 0.7935 mins.\nStarting training for Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('logisticregression', LogisticRegression(random_state=42))])\nPipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('logisticregression', LogisticRegression(random_state=42))]) has been successfully trained in 0.005 mins.\nStarting training for Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('xgbclassifier',\n                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n                               colsample_bylevel=None, colsample_bynode=None,\n                               colsample_bytree=None,\n                               early_stopping_rounds=None,\n                               enable_categorical=False, eval_metric=None,\n                               gamma=None, gpu_id=None, grow_policy=None,\n                               importance_type=None,\n                               interaction_constraints=None, learning_rate=None,\n                               max_bin=None, max_cat_to_onehot=None,\n                               max_delta_step=None, max_depth=None,\n                               max_leaves=None, min_child_weight=None,\n                               missing=nan, monotone_constraints=None,\n                               n_estimators=100, n_jobs=None,\n                               num_parallel_tree=None, predictor=None,\n                               random_state=42, reg_alpha=None, reg_lambda=None, ...))])\nPipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('xgbclassifier',\n                 XGBClassifier(base_score=None, booster=None, callbacks=None,\n                               colsample_bylevel=None, colsample_bynode=None,\n                               colsample_bytree=None,\n                               early_stopping_rounds=None,\n                               enable_categorical=False, eval_metric=None,\n                               gamma=None, gpu_id=None, grow_policy=None,\n                               importance_type=None,\n                               interaction_constraints=None, learning_rate=None,\n                               max_bin=None, max_cat_to_onehot=None,\n                               max_delta_step=None, max_depth=None,\n                               max_leaves=None, min_child_weight=None,\n                               missing=nan, monotone_constraints=None,\n                               n_estimators=100, n_jobs=None,\n                               num_parallel_tree=None, predictor=None,\n                               random_state=42, reg_alpha=None, reg_lambda=None, ...))]) has been successfully trained in 0.0783 mins.\nStarting training for Pipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('svc', SVC(random_state=42))])\nPipeline(steps=[('onehotencoder', OneHotEncoder(use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('svc', SVC(random_state=42))]) has been successfully trained in 0.0048 mins.\n","output_type":"stream"}]},{"cell_type":"markdown","source":"Training Over(messy code permitting), next is to evaluate and select the best model(s).","metadata":{}},{"cell_type":"markdown","source":"### Model Evaluation","metadata":{}},{"cell_type":"code","source":"from sklearn.metrics import classification_report, accuracy_score","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:03.798623Z","iopub.execute_input":"2022-06-25T18:12:03.799794Z","iopub.status.idle":"2022-06-25T18:12:03.806345Z","shell.execute_reply.started":"2022-06-25T18:12:03.799737Z","shell.execute_reply":"2022-06-25T18:12:03.805069Z"},"trusted":true},"execution_count":183,"outputs":[]},{"cell_type":"markdown","source":"We need to sort out the baseline first, this refers to the result of a certain guess work.","metadata":{}},{"cell_type":"code","source":"# Naive model\nnaive_model = y_train.value_counts(normalize=True).max()\nprint(f\"Accuracy score for naive model is: {round(naive_model, 2)}\")","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:03.807871Z","iopub.execute_input":"2022-06-25T18:12:03.808183Z","iopub.status.idle":"2022-06-25T18:12:03.821530Z","shell.execute_reply.started":"2022-06-25T18:12:03.808152Z","shell.execute_reply":"2022-06-25T18:12:03.820412Z"},"trusted":true},"execution_count":184,"outputs":[{"name":"stdout","text":"Accuracy score for naive model is: 0.52\n","output_type":"stream"}]},{"cell_type":"markdown","source":"As shown above, guessing \"Adoption\" for all cases will result in a model with 52% accuracy, any thing lower than that is a waste.","metadata":{}},{"cell_type":"code","source":"best_models[1].best_estimator_","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:03.823077Z","iopub.execute_input":"2022-06-25T18:12:03.823872Z","iopub.status.idle":"2022-06-25T18:12:03.838825Z","shell.execute_reply.started":"2022-06-25T18:12:03.823820Z","shell.execute_reply":"2022-06-25T18:12:03.837497Z"},"trusted":true},"execution_count":185,"outputs":[{"execution_count":185,"output_type":"execute_result","data":{"text/plain":"Pipeline(steps=[('onehotencoder',\n                 OneHotEncoder(cols=['SEX'], use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('logisticregression',\n                 LogisticRegression(max_iter=500, random_state=42))])"},"metadata":{}}]},{"cell_type":"markdown","source":"#### TRAINING DATA","metadata":{}},{"cell_type":"code","source":"# Get the classification report on all the best models per model(meta, right?) TRAINING DATA.\nfor algo in best_models:\n    print(f\"{algo.best_estimator_.named_steps}:\\n{classification_report(y_train, algo.predict(X_train))}\")","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:03.840888Z","iopub.execute_input":"2022-06-25T18:12:03.841575Z","iopub.status.idle":"2022-06-25T18:12:03.929948Z","shell.execute_reply.started":"2022-06-25T18:12:03.841524Z","shell.execute_reply":"2022-06-25T18:12:03.928653Z"},"trusted":true},"execution_count":186,"outputs":[{"name":"stdout","text":"{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'randomforestclassifier': RandomForestClassifier(max_depth=3, n_estimators=120, random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.74      0.88      0.80       117\n           1       0.87      0.72      0.79       128\n\n    accuracy                           0.80       245\n   macro avg       0.80      0.80      0.80       245\nweighted avg       0.81      0.80      0.80       245\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'logisticregression': LogisticRegression(max_iter=500, random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.66      0.81      0.73       117\n           1       0.78      0.62      0.70       128\n\n    accuracy                           0.71       245\n   macro avg       0.72      0.72      0.71       245\nweighted avg       0.73      0.71      0.71       245\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'xgbclassifier': XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,\n              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n              early_stopping_rounds=None, enable_categorical=False,\n              eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n              importance_type=None, interaction_constraints='',\n              learning_rate=0.05, max_bin=256, max_cat_to_onehot=4,\n              max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n              missing=nan, monotone_constraints='()', n_estimators=75, n_jobs=0,\n              num_parallel_tree=1, predictor='auto', random_state=42,\n              reg_alpha=0, reg_lambda=1, ...)}:\n              precision    recall  f1-score   support\n\n           0       0.93      0.97      0.95       117\n           1       0.98      0.94      0.96       128\n\n    accuracy                           0.96       245\n   macro avg       0.96      0.96      0.96       245\nweighted avg       0.96      0.96      0.96       245\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'svc': SVC(kernel='linear', random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.66      0.88      0.75       117\n           1       0.84      0.59      0.69       128\n\n    accuracy                           0.73       245\n   macro avg       0.75      0.73      0.72       245\nweighted avg       0.76      0.73      0.72       245\n\n","output_type":"stream"}]},{"cell_type":"markdown","source":"#### VALIDATION DATA","metadata":{}},{"cell_type":"code","source":"# Get the classification report on all the best models per model(meta, right?) VALIDATION DATA.\nfor algo in best_models:\n    print(f\"{algo.best_estimator_.named_steps}:\\n{classification_report(y_val, algo.predict(X_val))}\")","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:03.931714Z","iopub.execute_input":"2022-06-25T18:12:03.932197Z","iopub.status.idle":"2022-06-25T18:12:04.024183Z","shell.execute_reply.started":"2022-06-25T18:12:03.932148Z","shell.execute_reply":"2022-06-25T18:12:04.022908Z"},"trusted":true},"execution_count":187,"outputs":[{"name":"stdout","text":"{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'randomforestclassifier': RandomForestClassifier(max_depth=3, n_estimators=120, random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.70      0.85      0.77        53\n           1       0.80      0.63      0.71        52\n\n    accuracy                           0.74       105\n   macro avg       0.75      0.74      0.74       105\nweighted avg       0.75      0.74      0.74       105\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'logisticregression': LogisticRegression(max_iter=500, random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.65      0.79      0.71        53\n           1       0.72      0.56      0.63        52\n\n    accuracy                           0.68       105\n   macro avg       0.69      0.68      0.67       105\nweighted avg       0.69      0.68      0.67       105\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'xgbclassifier': XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,\n              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n              early_stopping_rounds=None, enable_categorical=False,\n              eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n              importance_type=None, interaction_constraints='',\n              learning_rate=0.05, max_bin=256, max_cat_to_onehot=4,\n              max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n              missing=nan, monotone_constraints='()', n_estimators=75, n_jobs=0,\n              num_parallel_tree=1, predictor='auto', random_state=42,\n              reg_alpha=0, reg_lambda=1, ...)}:\n              precision    recall  f1-score   support\n\n           0       0.63      0.68      0.65        53\n           1       0.65      0.60      0.62        52\n\n    accuracy                           0.64       105\n   macro avg       0.64      0.64      0.64       105\nweighted avg       0.64      0.64      0.64       105\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'svc': SVC(kernel='linear', random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.64      0.89      0.75        53\n           1       0.81      0.50      0.62        52\n\n    accuracy                           0.70       105\n   macro avg       0.73      0.69      0.68       105\nweighted avg       0.73      0.70      0.68       105\n\n","output_type":"stream"}]},{"cell_type":"markdown","source":"Random Forest seems to be carrying the day, however, finally, over to the test data(Copy & paste). Before that though, let's tweak XGB Classifier or let's not, for now(perfectionist connudrum aka indecision).","metadata":{}},{"cell_type":"markdown","source":"#### **TEST DATA**","metadata":{}},{"cell_type":"code","source":"# Get the classification report on all the best models per model(meta, right?) TEST DATA.\nfor algo in best_models:\n    print(f\"{algo.best_estimator_.named_steps}:\\n{classification_report(y_val, algo.predict(X_val))}\")","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:04.026396Z","iopub.execute_input":"2022-06-25T18:12:04.026884Z","iopub.status.idle":"2022-06-25T18:12:04.117540Z","shell.execute_reply.started":"2022-06-25T18:12:04.026837Z","shell.execute_reply":"2022-06-25T18:12:04.116243Z"},"trusted":true},"execution_count":188,"outputs":[{"name":"stdout","text":"{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'randomforestclassifier': RandomForestClassifier(max_depth=3, n_estimators=120, random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.70      0.85      0.77        53\n           1       0.80      0.63      0.71        52\n\n    accuracy                           0.74       105\n   macro avg       0.75      0.74      0.74       105\nweighted avg       0.75      0.74      0.74       105\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'logisticregression': LogisticRegression(max_iter=500, random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.65      0.79      0.71        53\n           1       0.72      0.56      0.63        52\n\n    accuracy                           0.68       105\n   macro avg       0.69      0.68      0.67       105\nweighted avg       0.69      0.68      0.67       105\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'xgbclassifier': XGBClassifier(base_score=0.5, booster='gbtree', callbacks=None,\n              colsample_bylevel=1, colsample_bynode=1, colsample_bytree=1,\n              early_stopping_rounds=None, enable_categorical=False,\n              eval_metric=None, gamma=0, gpu_id=-1, grow_policy='depthwise',\n              importance_type=None, interaction_constraints='',\n              learning_rate=0.05, max_bin=256, max_cat_to_onehot=4,\n              max_delta_step=0, max_depth=6, max_leaves=0, min_child_weight=1,\n              missing=nan, monotone_constraints='()', n_estimators=75, n_jobs=0,\n              num_parallel_tree=1, predictor='auto', random_state=42,\n              reg_alpha=0, reg_lambda=1, ...)}:\n              precision    recall  f1-score   support\n\n           0       0.63      0.68      0.65        53\n           1       0.65      0.60      0.62        52\n\n    accuracy                           0.64       105\n   macro avg       0.64      0.64      0.64       105\nweighted avg       0.64      0.64      0.64       105\n\n{'onehotencoder': OneHotEncoder(cols=['SEX'], use_cat_names=True), 'standardscaler': StandardScaler(), 'svc': SVC(kernel='linear', random_state=42)}:\n              precision    recall  f1-score   support\n\n           0       0.64      0.89      0.75        53\n           1       0.81      0.50      0.62        52\n\n    accuracy                           0.70       105\n   macro avg       0.73      0.69      0.68       105\nweighted avg       0.73      0.70      0.68       105\n\n","output_type":"stream"}]},{"cell_type":"markdown","source":"Unsuprisingly, the Random Forest classifier seems to have performed better than its counterparts(what, with the extreme gradient booster chillin on overfittin).","metadata":{}},{"cell_type":"markdown","source":"### Extraction for Deployment","metadata":{}},{"cell_type":"code","source":"best_models[0].best_estimator_","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:04.119818Z","iopub.execute_input":"2022-06-25T18:12:04.120320Z","iopub.status.idle":"2022-06-25T18:12:04.134068Z","shell.execute_reply.started":"2022-06-25T18:12:04.120272Z","shell.execute_reply":"2022-06-25T18:12:04.132626Z"},"trusted":true},"execution_count":189,"outputs":[{"execution_count":189,"output_type":"execute_result","data":{"text/plain":"Pipeline(steps=[('onehotencoder',\n                 OneHotEncoder(cols=['SEX'], use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('randomforestclassifier',\n                 RandomForestClassifier(max_depth=3, n_estimators=120,\n                                        random_state=42))])"},"metadata":{}}]},{"cell_type":"code","source":"import pickle\nmodel_filename = \"Farmer-Adoption-model.pkl\"\npickle.dump(best_models[0].best_estimator_, open(model_filename,\"wb\"))","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:04.143518Z","iopub.execute_input":"2022-06-25T18:12:04.144088Z","iopub.status.idle":"2022-06-25T18:12:04.161982Z","shell.execute_reply.started":"2022-06-25T18:12:04.144037Z","shell.execute_reply":"2022-06-25T18:12:04.160498Z"},"trusted":true},"execution_count":190,"outputs":[]},{"cell_type":"code","source":"# check \nmodel = pickle.load(open(\"Farmer-Adoption-model.pkl\", \"rb\"))\npredictions = model.predict(X_test)\nprint(classification_report(y_test, predictions))\nmodel","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:12:04.164111Z","iopub.execute_input":"2022-06-25T18:12:04.164992Z","iopub.status.idle":"2022-06-25T18:12:04.226718Z","shell.execute_reply.started":"2022-06-25T18:12:04.164941Z","shell.execute_reply":"2022-06-25T18:12:04.225353Z"},"trusted":true},"execution_count":191,"outputs":[{"name":"stdout","text":"              precision    recall  f1-score   support\n\n           0       0.71      0.86      0.78        73\n           1       0.84      0.67      0.74        78\n\n    accuracy                           0.76       151\n   macro avg       0.77      0.76      0.76       151\nweighted avg       0.78      0.76      0.76       151\n\n","output_type":"stream"},{"execution_count":191,"output_type":"execute_result","data":{"text/plain":"Pipeline(steps=[('onehotencoder',\n                 OneHotEncoder(cols=['SEX'], use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('randomforestclassifier',\n                 RandomForestClassifier(max_depth=3, n_estimators=120,\n                                        random_state=42))])"},"metadata":{}}]},{"cell_type":"markdown","source":"So, that's the prediction aspect sorted. Now over to the clustering which will be a continuation.","metadata":{}},{"cell_type":"code","source":"# Slice out Farmers who adopted\nmask = df[\"ADOPTION STATUS\"] == 1\ndf_adopted = df[mask]","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:29:36.009488Z","iopub.execute_input":"2022-06-25T18:29:36.009896Z","iopub.status.idle":"2022-06-25T18:29:36.016005Z","shell.execute_reply.started":"2022-06-25T18:29:36.009863Z","shell.execute_reply":"2022-06-25T18:29:36.014808Z"},"trusted":true},"execution_count":204,"outputs":[]},{"cell_type":"code","source":"# Import dependencies\nfrom sklearn.cluster import KMeans\nfrom sklearn.metrics import silhouette_score\nfrom sklearn.decomposition import PCA","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:23:55.073055Z","iopub.execute_input":"2022-06-25T18:23:55.073500Z","iopub.status.idle":"2022-06-25T18:23:55.079604Z","shell.execute_reply.started":"2022-06-25T18:23:55.073438Z","shell.execute_reply":"2022-06-25T18:23:55.078371Z"},"trusted":true},"execution_count":199,"outputs":[]},{"cell_type":"markdown","source":"For explainability, we want minimum 3 clusters, max 5.","metadata":{}},{"cell_type":"code","source":"# Setting up n_clusters, and the other relevant lists.\nn_clusters = range(2,15)\ninertia_errors = []\nsilhouette_scores = []\nX_adopt = df_adopted.drop(columns=\"ADOPTION STATUS\")\noh = OneHotEncoder(use_cat_names=True)\n# Lets track the time.\nstart_time = time.time()\n# Add `for` loop to train model and calculate inertia, silhouette score.\nfor k in n_clusters:\n    # initiatialize pipeline model and train.\n    print(f\"Model {k-1} is starting to train.\")\n    model_cl = make_pipeline(OneHotEncoder(use_cat_names=True), \n                          StandardScaler(),\n                          KMeans(random_state=42, n_clusters=k))\n    model_cl.fit(X_adopt)\n    # Get Inertia errors and Silhoutte scores.\n    inertia_errors.append(model_cl.named_steps[\"kmeans\"].inertia_)\n    silhouette_scores.append(silhouette_score(oh.fit_transform(X_adopt.copy()), model_cl.named_steps[\"kmeans\"].labels_))\n    \n # Time tracking activated.   \nelapsed_time = round(time.time() - start_time, 2)\nprint(f\"Hyperparameter tuning ended in {elapsed_time}s.\")\nprint(\"Inertia:\", inertia_errors[:3])\nprint()\nprint(\"Silhouette Scores:\", silhouette_scores[:3])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:54:16.594261Z","iopub.execute_input":"2022-06-25T18:54:16.594695Z","iopub.status.idle":"2022-06-25T18:54:19.015322Z","shell.execute_reply.started":"2022-06-25T18:54:16.594662Z","shell.execute_reply":"2022-06-25T18:54:19.013696Z"},"trusted":true},"execution_count":232,"outputs":[{"name":"stdout","text":"Model 1 is starting to train.\nModel 2 is starting to train.\nModel 3 is starting to train.\nModel 4 is starting to train.\nModel 5 is starting to train.\nModel 6 is starting to train.\nModel 7 is starting to train.\nModel 8 is starting to train.\nModel 9 is starting to train.\nModel 10 is starting to train.\nModel 11 is starting to train.\nModel 12 is starting to train.\nModel 13 is starting to train.\nHyperparameter tuning ended in 2.4s.\nInertia: [1782.2363014391112, 1464.477437035218, 1263.9374401038021]\n\nSilhouette Scores: [-0.03717131120698598, 0.05618663752608206, 0.021396560851206496]\n","output_type":"stream"}]},{"cell_type":"code","source":"# Create line plot of `inertia_errors` vs `n_clusters`\nfig = px.line(x=n_clusters, y=inertia_errors, title=\"K-Means Model: Inertia vs Number of Clusters\")\nfig.update_layout(xaxis_title=\"Number of Clusters\", yaxis_title=\"Inertia\")\nfig.show()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:55:02.310571Z","iopub.execute_input":"2022-06-25T18:55:02.310982Z","iopub.status.idle":"2022-06-25T18:55:02.389483Z","shell.execute_reply.started":"2022-06-25T18:55:02.310948Z","shell.execute_reply":"2022-06-25T18:55:02.388298Z"},"trusted":true},"execution_count":233,"outputs":[{"output_type":"display_data","data":{"text/html":"<div>                            <div id=\"6d52ffdc-9fac-4ebd-b524-e02744247cac\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>            <script type=\"text/javascript\">                require([\"plotly\"], function(Plotly) {                    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of Clusters\"}},\"yaxis\":{\"anchor\":\"x\",\"domain\":[0.0,1.0],\"title\":{\"text\":\"Silhouette Score\"}},\"legend\":{\"tracegroupgap\":0},\"title\":{\"text\":\"K-Means Model: Silhouette Score vs Number of Clusters\"}},                        {\"responsive\": true}                    ).then(function(){\n                            \nvar gd = document.getElementById('2a4fd488-fdc3-4c66-bb57-d074830eff1f');\nvar x = new MutationObserver(function (mutations, observer) {{\n        var display = window.getComputedStyle(gd).display;\n        if (!display || display === 'none') {{\n            console.log([gd, 'removed!']);\n            Plotly.purge(gd);\n            observer.disconnect();\n        }}\n}});\n\n// Listen for the removal of the full notebook cells\nvar notebookContainer = gd.closest('#notebook-container');\nif (notebookContainer) {{\n    x.observe(notebookContainer, {childList: true});\n}}\n\n// Listen for the clearing of the current output cell\nvar outputEl = 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Calling 'transform' will only return input data.\n","output_type":"stream"},{"execution_count":241,"output_type":"execute_result","data":{"text/plain":"Pipeline(steps=[('onehotencoder', OneHotEncoder(cols=[], use_cat_names=True)),\n                ('standardscaler', StandardScaler()),\n                ('kmeans', KMeans(n_clusters=4, random_state=42))])"},"metadata":{}}]},{"cell_type":"code","source":"sc = StandardScaler()\nX = oh.fit_transform(X)\nX = sc.fit_transform(X)\nX = pd.DataFrame(X, columns=df.columns)\n\ncentroids = final_model.named_steps[\"kmeans\"].cluster_centers_\nlabels = final_model.named_steps[\"kmeans\"].labels_\nprint(labels[:5])","metadata":{"execution":{"iopub.status.busy":"2022-06-25T19:14:14.947359Z","iopub.execute_input":"2022-06-25T19:14:14.947829Z","iopub.status.idle":"2022-06-25T19:14:14.961874Z","shell.execute_reply.started":"2022-06-25T19:14:14.947786Z","shell.execute_reply":"2022-06-25T19:14:14.960746Z"},"trusted":true},"execution_count":257,"outputs":[{"name":"stdout","text":"Warning: No categorical columns found. Calling 'transform' will only return input data.\n[3 1 0 1 3]\n","output_type":"stream"}]},{"cell_type":"code","source":"# Instantiate transformer\npca = PCA(n_components=2, random_state=42)\n\n# Transform `X`\nX_t = pca.fit_transform(X)\n\n# Put `X_t` into DataFrame\nX_pca = pd.DataFrame(X_t, columns=[\"PC1\", \"PC2\"])\n\nprint(\"X_pca shape:\", X_pca.shape)\nX_pca.head()","metadata":{"execution":{"iopub.status.busy":"2022-06-25T18:57:38.336214Z","iopub.execute_input":"2022-06-25T18:57:38.336665Z","iopub.status.idle":"2022-06-25T18:57:38.369596Z","shell.execute_reply.started":"2022-06-25T18:57:38.336630Z","shell.execute_reply":"2022-06-25T18:57:38.368080Z"},"trusted":true},"execution_count":243,"outputs":[{"name":"stdout","text":"X_pca shape: (501, 2)\n","output_type":"stream"},{"execution_count":243,"output_type":"execute_result","data":{"text/plain":"        PC1       PC2\n0 -0.956209  0.490031\n1 -0.087622 -2.266843\n2  0.032185  1.023181\n3  1.615276 -1.887050\n4 -1.437325  0.554472","text/html":"<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>PC1</th>\n      <th>PC2</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>-0.956209</td>\n      <td>0.490031</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>-0.087622</td>\n      <td>-2.266843</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>0.032185</td>\n      <td>1.023181</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>1.615276</td>\n      <td>-1.887050</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>-1.437325</td>\n      <td>0.554472</td>\n    </tr>\n  </tbody>\n</table>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"# Create scatter plot of `PC2` vs `PC1`\nplt.figure(figsize=(15,6))\nsns.scatterplot( data=X_pca, x=\"PC1\", y=\"PC2\", hue=labels, palette=\"deep\")\n#plt.scatter(x=centroids[:, 0], y=centroids[:, 1], marker=\"*\", s=150, color=\"gray\")\nplt.xlabel(\"PC1\")\nplt.ylabel(\"PC2\");\n","metadata":{"execution":{"iopub.status.busy":"2022-06-25T19:13:51.865972Z","iopub.execute_input":"2022-06-25T19:13:51.866436Z","iopub.status.idle":"2022-06-25T19:13:52.208939Z","shell.execute_reply.started":"2022-06-25T19:13:51.866402Z","shell.execute_reply":"2022-06-25T19:13:52.207639Z"},"trusted":true},"execution_count":256,"outputs":[{"output_type":"display_data","data":{"text/plain":"<Figure size 1080x432 with 1 Axes>","image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":"Well Honestly, that didn't go so well, but at least there will be less work as soon as additional data becomes available.","metadata":{}},{"cell_type":"markdown","source":"### **CONCLUSION**\nIn summary, the data was explored, visualized, and a model was trained with above average performance. The farmers who adopted were also clustered(attempted) into 4 groups. We shall attempt to deploy the model and see how it works on dynamic data. ","metadata":{}}]}