05 Parameters and Arguments.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Parameters and Arguments\n",
    "By:<a href='https://www.youtube.com/wonkyCode'>WonkyCode</a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0          Apple\n",
       "1          Mango\n",
       "2    Water Melon\n",
       "3          Grape\n",
       "dtype: object"
      ]
     },
     "execution_count": 1,
     "metadata": {},
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   ],
   "source": [
    "# Eg:  gameMode = Easy / Medium / Hard\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "fruits = [\"Apple\", \"Mango\", \"Water Melon\", \"Grape\"]\n",
    "indexes = [\"item1\", \"item2\", \"item3\", \"item4\"]\n",
    "\n",
    "pd.Series(fruits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "item1          Apple\n",
       "item2          Mango\n",
       "item3    Water Melon\n",
       "item4          Grape\n",
       "dtype: object"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(fruits, indexes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "item1          Apple\n",
       "item2          Mango\n",
       "item3    Water Melon\n",
       "item4          Grape\n",
       "dtype: object"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(data = fruits, index = indexes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "item1          Apple\n",
       "item2          Mango\n",
       "item3    Water Melon\n",
       "item4          Grape\n",
       "dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(index = indexes, data = fruits) #keyword arguments can be interchanged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Apple          item1\n",
       "Mango          item2\n",
       "Water Melon    item3\n",
       "Grape          item4\n",
       "dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(indexes, fruits)  # data is messed up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.Series(fruits, index = indexes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "item1          Apple\n",
       "item2          Mango\n",
       "item3    Water Melon\n",
       "item4          Grape\n",
       "item4        Oranges\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's add duplicate index\n",
    "\n",
    "fruits = [\"Apple\", \"Mango\", \"Water Melon\", \"Grape\", \"Oranges\"]\n",
    "indexes = [\"item1\", \"item2\", \"item3\", \"item4\", \"item4\"]\n",
    "\n",
    "pd.Series(data = fruits, index = indexes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Index labels do not have to be unique\n",
    "* But with duplicate indexes, some data operations will not be possible."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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