Updating tutorials

Author: igorborgest

tutorials/02 - Sessions.ipynb

@@ -24,7 +24,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -50,7 +50,7 @@
        "False"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -59,26 +59,6 @@
     "wr.s3.does_object_exist(\"s3://noaa-ghcn-pds/fake\")"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "False"
-      ]
-     },
-     "execution_count": 8,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "wr.s3.does_object_exist(\"s3://noaa-ghcn-pds/fake\", boto3_session=None)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -88,27 +68,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "False"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "wr.s3.does_object_exist(\"s3://noaa-ghcn-pds/fake\", boto3_session=boto3.Session())"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
@@ -117,7 +77,7 @@
        "False"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }

tutorials/03 - Amazon S3.ipynb

@@ -79,10 +79,10 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
+     "name": "stdin",
      "output_type": "stream",
      "text": [
-      "········\n"
+      " ··········································\n"
      ]
     }
    ],
@@ -1147,7 +1147,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1176,4 +1176,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 4
-}
+}

tutorials/04 - Parquet Datasets.ipynb

@@ -184,31 +184,31 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
-       "      <td>3</td>\n",
-       "      <td>bar</td>\n",
-       "      <td>2020-01-03</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
-       "      <th>1</th>\n",
        "      <td>1</td>\n",
        "      <td>foo</td>\n",
        "      <td>2020-01-01</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <th>1</th>\n",
        "      <td>2</td>\n",
        "      <td>boo</td>\n",
        "      <td>2020-01-02</td>\n",
        "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>3</td>\n",
+       "      <td>bar</td>\n",
+       "      <td>2020-01-03</td>\n",
+       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
        "   id value        date\n",
-       "0   3   bar  2020-01-03\n",
-       "1   1   foo  2020-01-01\n",
-       "2   2   boo  2020-01-02"
+       "0   1   foo  2020-01-01\n",
+       "1   2   boo  2020-01-02\n",
+       "2   3   bar  2020-01-03"
       ]
      },
      "execution_count": 4,
@@ -478,13 +478,6 @@
     "\n",
     "wr.s3.read_parquet(path, dataset=True)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

tutorials/05 - Glue Catalog.ipynb

@@ -293,27 +293,14 @@
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
-       "    <tr>\n",
-       "      <th>0</th>\n",
-       "      <td>awswrangler_test</td>\n",
-       "      <td>boston</td>\n",
-       "      <td>This is a copy of UCI ML housing dataset. http...</td>\n",
-       "      <td>crim, zn, indus, chas, nox, rm, age, dis, rad,...</td>\n",
-       "      <td></td>\n",
-       "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "           Database   Table  \\\n",
-       "0  awswrangler_test  boston   \n",
-       "\n",
-       "                                         Description  \\\n",
-       "0  This is a copy of UCI ML housing dataset. http...   \n",
-       "\n",
-       "                                             Columns Partitions  \n",
-       "0  crim, zn, indus, chas, nox, rm, age, dis, rad,...             "
+       "Empty DataFrame\n",
+       "Columns: [Database, Table, Description, Columns, Partitions]\n",
+       "Index: []"
       ]
      },
      "execution_count": 5,
@@ -339,11 +326,8 @@
    "outputs": [],
    "source": [
     "desc = \"\"\"This is a copy of UCI ML housing dataset. https://archive.ics.uci.edu/ml/machine-learning-databases/housing/\n",
-    "\n",
     "This dataset was taken from the StatLib library which is maintained at Carnegie Mellon University.\n",
-    "\n",
     "The Boston house-price data of Harrison, D. and Rubinfeld, D.L. ‘Hedonic prices and the demand for clean air’, J. Environ. Economics & Management, vol.5, 81-102, 1978. Used in Belsley, Kuh & Welsch, ‘Regression diagnostics …’, Wiley, 1980. N.B. Various transformations are used in the table on pages 244-261 of the latter.\n",
-    "\n",
     "The Boston house-price data has been used in many machine learning papers that address regression problems.\n",
     "\"\"\"\n",
     "\n",