022-Solution.ipynb

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   "cell_type": "markdown",
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   "source": [
    "# Using names.txt begin by sorting it into alphabetical order. Then working out the alphabetical value for each name, multiply this value by its alphabetical position in the list to obtain a name score.\n",
    "\n",
    "# For example, when the list is sorted into alphabetical order, COLIN, which is worth 3 + 15 + 12 + 9 + 14 = 53, is the 938th name in the list. So, COLIN would obtain a score of 938 × 53 = 49714.\n",
    "\n",
    "# What is the total of all the name scores in the file?\n",
    "\n",
    "______"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "f=open('p022_names.txt','r')\n",
    "names=sorted(f.read().replace('\"','').split(','),key=str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame({0:names})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_alphabet = list(string.ascii_uppercase)\n",
    "dict_alphabet = dict(zip(list_alphabet, range(1,len(list_alphabet)+1)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "def alpha_score(name):\n",
    "    letters = list(name)\n",
    "    scores = [dict_alphabet[x] for x in letters]\n",
    "    return sum(scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['alphascore'] = df[0].map(alpha_score)\n",
    "df['index'] = range(1, len(df)+1)\n",
    "df['score'] = df['alphascore']*df['index']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "871198282"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "df['score'].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Answer = 871,198,282"
   ]
  }
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