Divided notebooks

WDI-Extraction.ipynb

@@ -0,0 +1,126 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Extraction"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Import libraries and functions."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import glob\n",
+    "import os\n",
+    "from zipfile import ZipFile\n",
+    "import warnings\n",
+    "warnings.filterwarnings(\"ignore\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This step has been depreciated due to security features added to the World Bank website. However, the data is still obtainable by openinng the `url`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "In the following cells we are going to import the data from the [World Bank website](https://www.worldbank.org/en/home), Data sections, and decompress it. So later on, we can process it in the integration, and subsequent parts."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To download the data, we are going to use the `request` library as just to be sure that we do not run into any inconvinient we are going to use the `stream` and `verify` to have a simple and cleaner download. Therefore, at the end we will have the data downloaded in our working directory data by design. (It can be obtained with the following function `os.getcwd()`)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "url = 'https://databank.worldbank.org/data/download/WDI_csv.zip'\n",
+    "r = requests.get(url, allow_redirects=True, stream = True,verify=False)\n",
+    "open('WDI_csv.zip', 'wb').write(r.content)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Then we extract all the files that are contained in WDI_csv.zip , into the default directory in a new folder called Data."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "zip_name = \"WDI_csv.zip\"\n",
+    "with ZipFile(zip_name, 'r') as zip:\n",
+    "    zip.printdir()\n",
+    "    zip.extractall('Data') "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Finally we are going to delete the WDI_csv.zip."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.remove(os.getcwd()+'/Data/'+\"/**.zip\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.9.12 ('base')",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.12"
+  },
+  "vscode": {
+   "interpreter": {
+    "hash": "db2f77d7771d8a0072cf3f8e7f9965a22a9c65bf4f8ee5135b3d479c9967abaa"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}