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    "\n",
    "## LabDS01 ##\n",
    "\n",
    "\n",
    "The following dataset includes information about several countries. This information was collected by the world bank (https://data.worldbank.org/). Data corresponds to 2016.\n",
    "\n",
    "`\n",
    "dataFile=\"https://raw.githubusercontent.com/masterfloss/data/main/worlddata2016.xlsx\"\n",
    "df=pd.read_excel(dataFile)\n",
    "`\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1. Business Understanding\n",
    "\n",
    "Purpose: Analyse data and extract knowledge\n",
    "\n",
    "Observation: Country\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2. Data Undertanding\n",
    "\n",
    "* Discuss the data and purposes\n",
    "* What are the main limitations?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3. Data Preparation\n",
    "\n",
    "* Converting data to numeric\n",
    "* Missing Values Imputation\n",
    "* Normalization\n",
    "* Variable Dummification\n",
    "* Data balancing\n",
    "* Pivot date in order to convert the values \"Indicator Name\" into comuns \n",
    "* Remove all columns that have no values, df1[columns].sum()==0\n",
    "* Remove all columns that have more than 210 observations, df1[columns].count()<210"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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