cief-dashboard/data/.ipynb_checkpoints/preprocessing-checkpoint.ipynb

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  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import plotly\n",
    "#from plotly import vision\n",
    "import plotly.express as px\n",
    "import numpy as np\n",
    "# get location\n",
    "import pgeocode\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "from mlxtend.frequent_patterns import apriori\n",
    "from mlxtend.regressor import LinearRegression\n",
    "\n",
    "#pd.set_option('display.max_colwidth', 120)\n",
    "pd.reset_option('display.max_colwidth')\n",
    "#pd.reset_option('display.max_columns')\n",
    "pd.set_option('display.max_columns', None)\n",
    "#pd.set_option('display.max_rows', 10)\n",
    "pd.set_option('display.max_rows', None)\n",
    "#pd.reset_option('display.max_rows')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "colors = {\n",
    "    'background': '#111111',\n",
    "    'text': '#7FDBFF'}\n",
    "\n",
    "def remove_outlier(column, level=1.5):\n",
    "    q1=column.quantile(0.25)\n",
    "    q3=column.quantile(0.75)\n",
    "    gap=q3-q1\n",
    "    lower_border=q1-gap*level\n",
    "    upper_border=q3+gap*level\n",
    "    column.mask(column<lower_border, inplace=True)\n",
    "    column.mask(column>upper_border, inplace=True)\n",
    "    \n",
    "def correct_outlier(column, level=1.5):\n",
    "    q1=column.quantile(0.25)\n",
    "    q3=column.quantile(0.75)\n",
    "    gap=q3-q1\n",
    "    lower_border=q1-gap*level\n",
    "    upper_border=q3+gap*level\n",
    "    column.mask(column<lower_border, other=lower_border, inplace=True)\n",
    "    column.mask(column>upper_border, other=upper_border, inplace=True)\n",
    "\n",
    "def update_backgroud(fig):\n",
    "    fig.update_layout(\n",
    "        plot_bgcolor=colors['background'],\n",
    "        paper_bgcolor=colors['background'],\n",
    "        font_color=colors['text']\n",
    "        )\n",
    "    \n",
    "def groupby_count(df, by=0, column=1, rename=''):\n",
    "    df=df.iloc[:, column].groupby(by=df.iloc[:, by]).count()\n",
    "    df=pd.DataFrame(df)\n",
    "    if not rename == '':\n",
    "        df.columns=[rename]\n",
    "    df.reset_index(inplace=True)\n",
    "    return(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "df =pd.read_csv('warehouse2.csv')\n",
    "df['Date'] = pd.to_datetime(df['Date'], errors ='coerce')\n",
    "\n",
    "# filter 1 month\n",
    "end_date=df[\"Date\"].max()\n",
    "start_date  = end_date-pd.Timedelta(30, unit = 'D')\n",
    "df = df[start_date <= df['Date']]\n",
    "\n",
    "df = df.loc[:,['Date','Daily CBM']]\n",
    "df.drop_duplicates(inplace=True)\n",
    "df[\"Type\"] = 'current'\n",
    "train_x = df[\"Date\"].apply(pd.Timestamp.toordinal)\n",
    "train_x = np.expand_dims(np.array(train_x),axis=-1)\n",
    "train_y = np.array(df['Daily CBM'])\n",
    "\n",
    "predict = pd.DataFrame(columns=['Date'])\n",
    "for i in range(30):\n",
    "    predict.loc[i, 'Date']=end_date+pd.Timedelta(1+i, unit='D')\n",
    "predict_x = predict[\"Date\"].apply(pd.Timestamp.toordinal)\n",
    "predict_x = np.expand_dims(np.array(predict_x),axis=-1)\n",
    "\n",
    "model = LinearRegression()\n",
    "model.fit(train_x, train_y)\n",
    "\n",
    "predict_y = model.predict(predict_x)\n",
    "predict['Daily CBM']=predict_y\n",
    "predict[\"Type\"] = 'predict'\n",
    "\n",
    "df = pd.concat([df,predict])\n",
    "df.sort_values(['Date'],inplace=True)\n",
    "\n",
    "fig = px.line(df, x=\"Date\", y=\"Daily CBM\", color='Type', title='CBM prediction')\n",
    "update_backgroud(fig)\n",
    "fig.show()"
   ]
  },
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prediction\"}, \"xaxis\": {\"anchor\": \"y\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"Date\"}}, \"yaxis\": {\"anchor\": \"x\", \"domain\": [0.0, 1.0], \"title\": {\"text\": \"Daily CBM\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
       "                            \n",
       "var gd = document.getElementById('f1e76ee9-9300-4dab-9945-279e220de5be');\n",
       "var 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",
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       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
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     "metadata": {},
     "output_type": "display_data"
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   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[737721],\n",
       "       [737722],\n",
       "       [737723],\n",
       "       [737724],\n",
       "       [737725],\n",
       "       [737726],\n",
       "       [737727],\n",
       "       [737728],\n",
       "       [737729],\n",
       "       [737730],\n",
       "       [737731],\n",
       "       [737732],\n",
       "       [737733],\n",
       "       [737734],\n",
       "       [737735],\n",
       "       [737736],\n",
       "       [737737],\n",
       "       [737738],\n",
       "       [737739],\n",
       "       [737740],\n",
       "       [737741],\n",
       "       [737742],\n",
       "       [737743],\n",
       "       [737744],\n",
       "       [737745],\n",
       "       [737746],\n",
       "       [737747],\n",
       "       [737748],\n",
       "       [737749],\n",
       "       [737750]])"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#start_date\n",
    "#train_y\n",
    "predict_x "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Exchange"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('marketing1.csv')\n",
    "#df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df=pd.read_csv('billing1.csv')\n",
    "#df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 305,
   "metadata": {},
   "outputs": [],
   "source": [
    "#exchange0=pd.read_csv('database/markings1.csv')\n",
    "#exchange0=pd.read_csv('database/user_bank_slips.csv')\n",
    "exchange1=pd.read_csv('database/users.csv')\n",
    "#exchange1=pd.read_csv('database/markings.csv')\n",
    "#exchange['term'].value_counts()\n",
    "#exchange1"
   ]
  }
 ],
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