.gitignore

.ipynb_checkpoints/MaMo_v1-checkpoint.ipynb

MaMo_v1.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# MaMo\n",
    "## Manage money\n",
    "\n",
    "### Overview\n",
    "* Wallet ( All , Bank, Paytm, etc ).\n",
    "* View ( All, Date , week, month , year, Weekends ).\n",
    "* Options ( +, - , <> Transfer).\n",
    "* Income ( All, Deposit, Salary, Savings,Funds, etc).\n",
    "* Expenses( All, Food, transport , Shopping, Entertainment, Health, personal, etc).\n",
    "* Tags (for easy access, customisable as per user requirements.\n",
    "\n",
    "### Features\n",
    "* Graphical representation ( Pie chart, histogram, etc).\n",
    "* Currency.\n",
    "* Subscriptions ( netflix , YouTube etc).\n",
    "* Reccurring ( Salary, Transportation, milk, etc) -- can be modified as per changes in cycle.\n",
    "* Define first weekday & weekends.\n",
    "* Reminder expenses through mail (Insurance, pollution check , fees ).\n",
    "* Sort ( Greater than amount, Date, month , all , hashtags , categories , expenses , incomes , etc).\n",
    "* Loan.\n",
    "* Calculator (for easy calculation).\n",
    "* Daily reminder to enter the expenditure of today.\n",
    "* Reminder when money is low through mail.(user can set min amount when the reminder should be triggered).\n",
    "* Borrow ( +,-).\n",
    "* Reminder about lending money to friends family etc.(after a week, month or so).\n",
    "* Export to excel, csv etc.\n",
    "* Speech recognition system.\n",
    "\n",
    "### Future possibility\n",
    "* If the lender and borrower are users of the app/website then both will get reminder.\n",
    " * Lender - you gave money to xyz person on (date). Feature of adding interest after crossing the time limit of returning money.\n",
    " * Borrower - you borrowed money from pqr on (date). Return today to avoid interest.\n",
    "* Tips section - to save money, increase money, easy money, dos and donts etc.\n",
    "* Offers and coupon codes.\n",
    "* share feature on other platforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''------- importing required libraries and packages ---------'''\n",
    "import pandas as pd  #importing pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transaction_id, type, wallets, amount, category, entry_date, transaction_date, current_date, tags, comments, flag \n",
    "# reccuring, subscriptions, loan, reminder, borrow, "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total Balance = 0\n",
      "Total Income = 0\n",
      "Total Expenditure = 0\n",
      "1) Income\n",
      "2) Expenditure\n",
      "3) View Transactions\n",
      "Please select option(1-3):1\n",
      "Enter the Amount:232\n",
      "Tag:#efef\n",
      "Comments:ferfed\n",
      "Total Balance = 232\n",
      "Total Income = 232\n",
      "Total Expenditure = 0\n"
     ]
    }
   ],
   "source": [
    "t = pd.Timestamp.now().replace(microsecond=0)\n",
    "\n",
    "'''------- Creating raw DataFrames ---------'''\n",
    "df = pd.DataFrame({'transaction_id':[0,1],'type':['Income','Expenditure'], 'wallets':['Cash','Cash'], 'amount':[0, 0], 'category':['Food','Travel'], 'entry_date':[t,t], 'transcation_date':[t,t], 'current_date':[t,t], 'tags':['',''], 'comments':['',''], 'flag':[1,1] }) #creating sample dataframe (df) having two columns\n",
    "df_cat = pd.DataFrame({'Category':['Food','Travel',], 'entry_date':[t,t], 'current_date':[t,t], 'flag':[1,1]})\n",
    "\n",
    "writer = pd.ExcelWriter('MaMo.xlsx', engine='xlsxwriter')\n",
    "df.to_excel(writer, sheet_name=\"Transactions\", index=False) #inserting data of dataframe df (df) in the excel sheet\n",
    "df_cat.to_excel(writer, sheet_name=\"Category\", index=False) #inserting category list in the excel sheet\n",
    "writer.save()   #Close the Pandas Excel writer and output the Excel file.\n",
    "\n",
    "ndf = pd.read_excel('MaMo.xlsx', sheet_name=\"Transactions\",sort=False) #creating new dataframe (ndf) to open the file in read mode\n",
    "ndf_cat = pd.read_excel('MaMo.xlsx', sheet_name=\"Category\",sort=False) #creating new dataframe (ndf) to open the file in read mode\n",
    "\n",
    "writer = pd.ExcelWriter('MaMo.xlsx', engine='xlsxwriter')\n",
    "'''------- defining functions -------'''\n",
    "\n",
    "def home(): #defining home function\n",
    "    #creating required dataframes\n",
    "    income_df = ndf.loc[ndf['type'] == 'Income'] # creating income dataframe (income_df) to store the entries having income type\n",
    "    expenditure_df = ndf.loc[ndf['type'] == 'Expenditure'] # creating income dataframe (expenditure_df) to store the entries having expenditure type\n",
    "    \n",
    "    #calculating Total of the required values\n",
    "    income_amount = income_df['amount']\n",
    "    income_total = income_amount.sum(axis = None, skipna = True) #total income\n",
    "    \n",
    "    expenditure_amount = expenditure_df['amount']\n",
    "    expenditure_total = expenditure_amount.sum(axis = None, skipna = True) #total expenditure\n",
    "    \n",
    "    avail_balance_total = income_total - expenditure_total # total available balance\n",
    "    \n",
    "    #printing required data\n",
    "    print(\"Total Balance = \",avail_balance_total,sep='') #displays total balance\n",
    "    print(\"Total Income = \",income_total,sep='') #displays total income\n",
    "    print(\"Total Expenditure = \",expenditure_total,sep='') #displays total expenditure\n",
    "    \n",
    "''' ------- function defintion end ------'''\n",
    "\n",
    "home() #calling home function to display data of user on startup\n",
    "\n",
    "#providing options for user to choose from\n",
    "#print('Choose from list of wallets:')\n",
    "#print(rdf_wallet)\n",
    "t_id = len(ndf) # generating unique transaction ids\n",
    "\n",
    "print(\"1) Income\")\n",
    "print(\"2) Expenditure\")\n",
    "print(\"3) View Transactions\")\n",
    "option = int(input(\"Please select option(1-3):\"))  #storing option value selected by user\n",
    "\n",
    "#performing functions on the basis of option selected by user\n",
    "\n",
    "if option == 1: #insert income amount\n",
    "    amount = int(input('Enter the Amount:')) # taking amount input from user\n",
    "    print(\"Category:\")\n",
    "    cat_lst = ndf_cat['Category'].values\n",
    "    count2 = 1\n",
    "    print(\"0) Add new category.\")\n",
    "    for i in cat_lst:\n",
    "        print(\"{}) {}\".format(count2,i))\n",
    "        count2 += 1\n",
    "    option1_0 = int(input(\"Please select category(0-{}): \".format(count2-1)))  #storing option1_0 value selected by user\n",
    "    if option1_0 == 0:\n",
    "        category = input(\"Enter the New Category you wish to add:\")\n",
    "        tdf2 = pd.DataFrame({'Category':[category],'entry_date':[t], 'current_date':[t], 'flag':[1]}) #creating temporary dataframe (tdf2)\n",
    "        ndf_cat = ndf_cat.append(tdf2, ignore_index=True,sort=False) #append the new input in the dataframe (ndf)\n",
    "        \n",
    "    elif option1_0 < count2 and option1_0 > 0:\n",
    "        category = cat_lst[option1_0 - 1]\n",
    "    else:\n",
    "        print('Wrong Input!!') #error message\n",
    "        \n",
    "    tag = input(\"Tag:#\") # hashtags \n",
    "    comment = input(\"Comments:\") # additional comments\n",
    "    tdf = pd.DataFrame({'type':['Income'], 'amount': [amount],'tags':[tag],'comments':[comment],'transaction_id':[t_id],'wallets':['Cash'], 'category':[category], 'entry_date':[t], 'transcation_date':[t], 'current_date':[t], 'flag':[1]}) #creating temporary dataframe (tdf)\n",
    "    ndf = ndf.append(tdf, ignore_index=True,sort=False) #append the new input in the dataframe (ndf)\n",
    "    ndf.to_excel(writer, sheet_name='Transactions', index=False) #updating the excel sheet\n",
    "    ndf_cat.to_excel(writer, sheet_name='Category', index=False) #updating the excel sheet\n",
    "    writer.save()   #Close the Pandas Excel writer and output the Excel file.\n",
    "    home() #display data to user\n",
    "    \n",
    "elif option == 2: #insert expenditure amount\n",
    "    amount = int(input('Enter the Amount:')) # taking amount input from user\n",
    "    tdf = pd.DataFrame({'type':['Expenditure'], 'amount': amount}) #creating temporary dataframe (tdf)\n",
    "    ndf = ndf.append(tdf, ignore_index=True,sort=False) #append the new input in the dataframe (ndf)\n",
    "    ndf.to_excel(writer, sheet_name='Transactions', index=False) #updating the excel sheet\n",
    "    writer.save()\n",
    "    home() #display data to user\n",
    "    \n",
    "elif option == 3: # view transactions\n",
    "    # Date , week, month , year, Weekends\n",
    "    print(\"1) All\")\n",
    "    print(\"2) Date\")\n",
    "    print(\"3) Week\")\n",
    "    print(\"4) Month\")\n",
    "    print(\"5) Year\")\n",
    "    print(\"6) Weekends\")\n",
    "    print(\"7) Category\")\n",
    "    print(\"8) Tags\")\n",
    "    print(\"9) Wallets\")\n",
    "    print(\"10) Type\")\n",
    "    option3 = int(input(\"Please select option(1-10):\"))  #storing option3 value selected by user\n",
    "    \n",
    "    #performing functions on the basis of option selected by user\n",
    "    \n",
    "    if option3 == 1: # Display all data\n",
    "        print(ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying stored data of the user\n",
    "    \n",
    "    elif option3 == 2: # Display data Date wise\n",
    "        print(\"1) Today\")\n",
    "        print(\"2) Date\")\n",
    "        print(\"3) From-To\")\n",
    "        option3_2 = int(input(\"Please select option(1-3): \"))  #storing option3_2 value selected by user\n",
    "                \n",
    "        if option3_2 == 1: \n",
    "            t_ndf = ndf[(ndf['transcation_date'].dt.date == t.date())]  # assigning data of today\n",
    "            print(t_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        \n",
    "        elif option3_2 == 2:\n",
    "            e_dt = pd.to_datetime(input(\"Please the enter the date(yyyy-mm-dd): \")).date()\n",
    "            t_ndf = ndf[(ndf['transcation_date'].dt.date == e_dt)]  # assigning data of date enterd\n",
    "            \n",
    "            if t_ndf.empty :\n",
    "                print(\"NO DATA FOUND!!!\")\n",
    "            else:\n",
    "                print(t_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        \n",
    "        elif option3_2 == 3:\n",
    "            f_dt = pd.to_datetime(input(\"Please the enter the from date(yyyy-mm-dd): \")).date()\n",
    "            t_dt = pd.to_datetime(input(\"Please the enter the to date(yyyy-mm-dd): \")).date()\n",
    "            t_ndf = ndf[(ndf['transcation_date'].dt.date >= f_dt) & (ndf['transcation_date'].dt.date <= t_dt)]\n",
    "            \n",
    "            if t_ndf.empty :\n",
    "                print(\"NO DATA FOUND!!!\")\n",
    "            else:\n",
    "                print(t_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        else:      \n",
    "            print('Wrong Input!!') #error message    \n",
    "            \n",
    "    elif option3 == 3: # Display data week wise\n",
    "        print(\"1) Current week\")\n",
    "        print(\"2) Particular week\")\n",
    "        option3_3 = int(input(\"Please select option(1-2): \"))  #storing option3_10 value selected by user\n",
    "        \n",
    "        if option3_3 == 1:\n",
    "            pass\n",
    "        elif option3_3 == 2:\n",
    "            pass\n",
    "        else :\n",
    "            print('Wrong Input!!') #error message\n",
    "            \n",
    "    elif option3 == 4: # Display data month wise\n",
    "        print(\"1) Current month\")\n",
    "        print(\"2) Particular month\")\n",
    "        option3_4 = int(input(\"Please select option(1-2): \"))  #storing option3_10 value selected by user\n",
    "        \n",
    "        if option3_4 == 1:\n",
    "            m_ndf = ndf[(ndf['transcation_date'].dt.month == t.date().month)]  # assigning data of today\n",
    "            print(m_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "            \n",
    "        elif option3_4 == 2:\n",
    "            yer = int(input(\"Enter the Year(YYYY)\"))\n",
    "            y_ndf = ndf[(ndf['transcation_date'].dt.year == yer)]  # assigning data of today\n",
    "            mon = int(input(\"Enter the Year(mm)\"))\n",
    "            m_ndf = y_ndf[(y_ndf['transcation_date'].dt.month == mon) & ((y_ndf['transcation_date'].dt.year == yer))]  # assigning data of today\n",
    "            \n",
    "            if m_ndf.empty :\n",
    "                print(\"NO DATA FOUND!!!\")\n",
    "            else:\n",
    "                print(m_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        else :\n",
    "            print('Wrong Input!!') #error message\n",
    "            \n",
    "    elif option3 == 5: # Display data year wise\n",
    "        print(\"1) Current year\")\n",
    "        print(\"2) Particular year\")\n",
    "        option3_5 = int(input(\"Please select option(1-2): \"))  #storing option3_10 value selected by user\n",
    "        \n",
    "        if option3_5 == 1:\n",
    "            y_ndf = ndf[(ndf['transcation_date'].dt.year == t.date().year)]  # assigning data of today\n",
    "            print(y_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "            \n",
    "        elif option3_5 == 2:\n",
    "            yer = int(input(\"Enter the Year(YYYY)\"))\n",
    "            y_ndf = ndf[(ndf['transcation_date'].dt.year == yer)]  # assigning data of today\n",
    "            \n",
    "            if y_ndf.empty :\n",
    "                print(\"NO DATA FOUND!!!\")\n",
    "            else:\n",
    "                print(y_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        else :\n",
    "            print('Wrong Input!!') #error message\n",
    "            \n",
    "    elif option3 == 6: # Display data weekend wise\n",
    "        print(\"1) Last weekend\")\n",
    "        print(\"2) Particular weekend\")\n",
    "        option3_6 = int(input(\"Please select option(1-2): \"))  #storing option3_10 value selected by user\n",
    "        \n",
    "        if option3_6 == 1:\n",
    "            pass\n",
    "        elif option3_6 == 2:\n",
    "            pass\n",
    "        else :\n",
    "            print('Wrong Input!!') #error message\n",
    "            \n",
    "    elif option3 == 7: # Display data category wise\n",
    "        cat_lst = ndf['category'].unique()\n",
    "        count = 1\n",
    "        for i in cat_lst:\n",
    "            print(\"{}) {}\".format(count,i))\n",
    "            count += 1\n",
    "        option3_7 = int(input(\"Please select option(1-{}): \".format(count-1)))  #storing option3_10 value selected by user\n",
    "        if option3_7 < count and option3_7 > 0:\n",
    "            cat_ndf = ndf[(ndf['category'] == cat_lst[option3_7 - 1])]\n",
    "            print(cat_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        else:\n",
    "            print('Wrong Input!!') #error message\n",
    "    \n",
    "    elif option3 == 8: # Display data tags wise \n",
    "        pass\n",
    "    elif option3 == 9: # Display data acc to wallet wise\n",
    "        pass\n",
    "    elif option3 == 10: # Display data acc to type wise\n",
    "        print(\"1) Income\")\n",
    "        print(\"2) Expenditure\")\n",
    "        option3_10 = int(input(\"Please select option(1-2): \"))  #storing option3_10 value selected by user\n",
    "        \n",
    "        if option3_10 == 1:\n",
    "            ty_ndf = ndf[(ndf['type'] == 'Income')]  # assigning data of date enterd\n",
    "            print(ty_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        elif option3_10 == 2:\n",
    "            ty_ndf = ndf[(ndf['type'] == 'Expenditure')]  # assigning data of date enterd\n",
    "            print(ty_ndf[['type','wallets','amount','category','transcation_date','tags','comments']]) # displaying todays data of the user\n",
    "        else :\n",
    "            print('Wrong Input!!') #error message\n",
    "        \n",
    "    else:      \n",
    "        print('Wrong Input!!') #error message\n",
    "\n",
    "else:\n",
    "    print('Wrong Input!!') #error message\n",
    "\n",
    "    '''\n",
    "    #For calculator or inserting elements by adding them easily\n",
    "    a = input(\"Enter no\")\n",
    "    print(sum(list(map(int,a.split('+')))))\n",
    "    '''    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_wallet = pd.DataFrame({'wallets':['Cash','Paytm']})\n",
    "df_wallet3 = pd.DataFrame({'wallets':['C','P']})\n",
    "writer = pd.ExcelWriter('test.xlsx')\n",
    "df_wallet.to_excel(writer, sheet_name=\"Wallets\", index=False,engine='xlsxwriter') #inserting data of dataframe df (df) in the excel sheet\n",
    "rdf_wallet = pd.read_excel('test.xlsx', sheet_name=\"Wallets\")\n",
    "df_wallet3.to_excel(writer, sheet_name=\"abc\", index=False,engine='xlsxwriter') #inserting data of dataframe df (df) in the excel sheet\n",
    "rdf_wallet3 = pd.read_excel('test.xlsx', sheet_name=\"abc\")\n",
    "writer.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "    "
   ]
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