Monthly_Expenses.ipynb

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    "import numpy as np \n",
    "import pandas as pd \n",
    "import plotly.express as px\n",
    "from plotly.subplots import make_subplots\n",
    "import plotly.graph_objects as go\n",
    "# Make the width of all shells wider\n",
    "from IPython.display import display, HTML\n",
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    "# assign dataset names\n",
    "list_of_names = ['Files/November.txt','Files/December.txt','Files/January.txt','Files/February.txt']\n",
    "Month = ['November', 'December','January','February','March','April','May','June','July','August','September','October'] #All months\n",
    "dataframes_list = []\n",
    "\n",
    "#Read all the dataset for all the months available\n",
    "for i in range(len(list_of_names)):\n",
    "    temp_df = pd.read_csv(list_of_names[i], delimiter = '\\t')\n",
    "    dataframes_list.append(temp_df)"
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        },
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     },
     "metadata": {},
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   ],
   "source": [
    "#Pie plots for each month available by the user.. All the expenses and incomes are present sorted by month.\n",
    "for i in range(len(list_of_names)):\n",
    "    fig = go.Figure()\n",
    "    fig.add_trace(go.Pie(labels=dataframes_list[i]['Utility'], values=dataframes_list[i]['Price'],name = Month[i],title=Month[i]))\n",
    "    fig.update_layout(width = 900, height = 600)\n",
    "    fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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   },
   "outputs": [
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          "xaxis": {
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        },
        "title": {
         "text": "February"
        },
        "width": 900,
        "xaxis": {
         "anchor": "y",
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     "metadata": {},
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   ],
   "source": [
    "#Bar plots for all the months available by the user. Every transaction is specificaly given in the bar plot, making easy to identify individual transactions.\n",
    "for i in range(len(list_of_names)):\n",
    "    fig = go.Figure()\n",
    "    fig = px.bar(dataframes_list[i], x='Utility', y='Price',title=Month[i],color='Input')\n",
    "    fig.update_layout(width = 900, height = 600)\n",
    "    fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "---------------------------------------------------------------------------------------------\n",
      "-November\n",
      "Your super market expenses for the month November were: 236.68\n",
      "Your misc expenses for the month November were: 121.51\n",
      "Your payroll for the month November were: 0.0\n",
      "Your expenses for the month November were: 1310.58\n",
      "Your incomes for the month November were: 1475.12\n"
     ]
    },
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      "---------------------------------------------------------------------------------------------\n",
      "-December\n",
      "Your super market expenses for the month December were: 240.59\n",
      "Your misc expenses for the month December were: 171.95\n",
      "Your payroll for the month December were: 0.0\n",
      "Your expenses for the month December were: 1347.84\n",
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      "---------------------------------------------------------------------------------------------\n",
      "-January\n",
      "Your super market expenses for the month January were: 42.27\n",
      "Your misc expenses for the month January were: 333.52\n",
      "Your payroll for the month January were: 0.0\n",
      "Your expenses for the month January were: 1522.07\n",
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      "---------------------------------------------------------------------------------------------\n",
      "-February\n",
      "Your super market expenses for the month February were: 217.79\n",
      "Your misc expenses for the month February were: 107.6\n",
      "Your payroll for the month February were: 0.0\n",
      "Your expenses for the month February were: 1595.62\n",
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   ],
   "source": [
    "for i, df in enumerate(dataframes_list):\n",
    "    # Calculate totals using groupby and sum for specific utilities\n",
    "    totals = df.groupby(['Utility', 'Input'])['Price'].sum().unstack(fill_value=0)\n",
    "    Super_Market = totals.loc['SuperMarket', 'Expense'] if 'SuperMarket' in totals.index else 0\n",
    "    Payroll_month = totals.loc['Payroll', 'Expense'] if 'Payroll' in totals.index else 0\n",
    "    Misc_Expenses = totals.loc['Misc', 'Expense'] if 'Misc' in totals.index else 0\n",
    "    \n",
    "    # Calculate overall expenses and incomes\n",
    "    Expenses = df[df['Input'] == 'Expense']['Price'].sum()\n",
    "    Incomes = df[df['Input'] == 'Income']['Price'].sum()\n",
    "    \n",
    "    print('---------------------------------------------------------------------------------------------')\n",
    "    print(f\"-{Month[i]}\")\n",
    "    print(f\"Your super market expenses for the month {Month[i]} were:\", np.round(Super_Market, 2))\n",
    "    print(f\"Your misc expenses for the month {Month[i]} were:\", np.round(Misc_Expenses, 2))\n",
    "    print(f\"Your payroll for the month {Month[i]} were:\", np.round(Payroll_month, 2))   \n",
    "    print(f\"Your expenses for the month {Month[i]} were:\", np.round(Expenses, 2))\n",
    "    print(f\"Your incomes for the month {Month[i]} were:\", np.round(Incomes, 2))\n",
    "\n",
    "    # Plotting\n",
    "    fig = go.Figure()\n",
    "    fig.add_trace(go.Pie(labels=df['Input'], values=df['Price'], title=Month[i]))\n",
    "    fig.update_layout(width=900, height=600)\n",
    "    fig.show()\n",
    "    \n",
    "    "
   ]
  }
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