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[SLU00] Fix sample requirements
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See more in jupyter/jupyter_client#637. Seems
version jupyter_client 6.1.13 which was yanked is causing issues
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@CatarinaSilva @ldsa-machine
CatarinaSilva authored and ldsa-machine committed Nov 7, 2021
1 parent aa0c217 commit aadba33
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Showing 4 changed files with 92 additions and 122 deletions.
83 changes: 47 additions & 36 deletions sample/SLU00 - LU Tutorial/Examples notebook.ipynb
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Expand Up @@ -15,7 +15,16 @@
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/Users/catarinasilva/.pyenv/versions/3.7.8/envs/sample-ldsa/lib/python3.7/site-packages/pandas/compat/__init__.py:120: UserWarning: Could not import the lzma module. Your installed Python is incomplete. Attempting to use lzma compression will result in a RuntimeError.\n",
" warnings.warn(msg)\n"
]
}
],
"source": [
"import pandas as pd"
]
Expand Down Expand Up @@ -80,60 +89,60 @@
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Capital</th>\n",
" <th>Country</th>\n",
" <th>Capital</th>\n",
" <th>Population</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Copenhagen</td>\n",
" <td>Denmark</td>\n",
" <td>Copenhagen</td>\n",
" <td>5724456</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Helsinki</td>\n",
" <td>Finland</td>\n",
" <td>Helsinki</td>\n",
" <td>5498211</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Reykjavík</td>\n",
" <td>Iceland</td>\n",
" <td>Reykjavík</td>\n",
" <td>335878</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Oslo</td>\n",
" <td>Norway</td>\n",
" <td>Oslo</td>\n",
" <td>5265158</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Nuuk</td>\n",
" <td>Greenland</td>\n",
" <td>Nuuk</td>\n",
" <td>56483</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Tórshavn</td>\n",
" <td>Faroe Islands</td>\n",
" <td>Tórshavn</td>\n",
" <td>49188</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Capital Country Population\n",
"0 Copenhagen Denmark 5724456\n",
"1 Helsinki Finland 5498211\n",
"2 Reykjavík Iceland 335878\n",
"3 Oslo Norway 5265158\n",
"4 Nuuk Greenland 56483\n",
"5 Tórshavn Faroe Islands 49188"
" Country Capital Population\n",
"0 Denmark Copenhagen 5724456\n",
"1 Finland Helsinki 5498211\n",
"2 Iceland Reykjavík 335878\n",
"3 Norway Oslo 5265158\n",
"4 Greenland Nuuk 56483\n",
"5 Faroe Islands Tórshavn 49188"
]
},
"execution_count": 4,
Expand Down Expand Up @@ -196,52 +205,52 @@
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Capital</th>\n",
" <th>Country</th>\n",
" <th>Capital</th>\n",
" <th>Population</th>\n",
" <th>gdp</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>0</th>\n",
" <td>Copenhagen</td>\n",
" <td>Denmark</td>\n",
" <td>Copenhagen</td>\n",
" <td>5724456</td>\n",
" <td>306.70</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1</th>\n",
" <td>Helsinki</td>\n",
" <td>Finland</td>\n",
" <td>Helsinki</td>\n",
" <td>5498211</td>\n",
" <td>236.80</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2</th>\n",
" <td>Reykjavík</td>\n",
" <td>Iceland</td>\n",
" <td>Reykjavík</td>\n",
" <td>335878</td>\n",
" <td>20.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>Oslo</td>\n",
" <td>Norway</td>\n",
" <td>Oslo</td>\n",
" <td>5265158</td>\n",
" <td>370.40</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>Nuuk</td>\n",
" <td>Greenland</td>\n",
" <td>Nuuk</td>\n",
" <td>56483</td>\n",
" <td>2.22</td>\n",
" </tr>\n",
" <tr>\n",
" <th>5</th>\n",
" <td>Tórshavn</td>\n",
" <td>Faroe Islands</td>\n",
" <td>Tórshavn</td>\n",
" <td>49188</td>\n",
" <td>2.77</td>\n",
" </tr>\n",
Expand All @@ -250,13 +259,13 @@
"</div>"
],
"text/plain": [
" Capital Country Population gdp\n",
"0 Copenhagen Denmark 5724456 306.70\n",
"1 Helsinki Finland 5498211 236.80\n",
"2 Reykjavík Iceland 335878 20.00\n",
"3 Oslo Norway 5265158 370.40\n",
"4 Nuuk Greenland 56483 2.22\n",
"5 Tórshavn Faroe Islands 49188 2.77"
" Country Capital Population gdp\n",
"0 Denmark Copenhagen 5724456 306.70\n",
"1 Finland Helsinki 5498211 236.80\n",
"2 Iceland Reykjavík 335878 20.00\n",
"3 Norway Oslo 5265158 370.40\n",
"4 Greenland Nuuk 56483 2.22\n",
"5 Faroe Islands Tórshavn 49188 2.77"
]
},
"execution_count": 7,
Expand Down Expand Up @@ -321,13 +330,15 @@
"<class 'pandas.core.frame.DataFrame'>\n",
"RangeIndex: 150 entries, 0 to 149\n",
"Data columns (total 5 columns):\n",
"sepal_length 150 non-null float64\n",
"sepal_width 150 non-null float64\n",
"petal_length 150 non-null float64\n",
"petal_width 150 non-null float64\n",
"species 150 non-null object\n",
" # Column Non-Null Count Dtype \n",
"--- ------ -------------- ----- \n",
" 0 sepal_length 150 non-null float64\n",
" 1 sepal_width 150 non-null float64\n",
" 2 petal_length 150 non-null float64\n",
" 3 petal_width 150 non-null float64\n",
" 4 species 150 non-null object \n",
"dtypes: float64(4), object(1)\n",
"memory usage: 5.9+ KB\n"
"memory usage: 6.0+ KB\n"
]
}
],
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.7"
"version": "3.7.8"
}
},
"nbformat": 4,
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30 changes: 15 additions & 15 deletions sample/SLU00 - LU Tutorial/Exercise notebook.ipynb
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Expand Up @@ -9,7 +9,7 @@
"grade": false,
"grade_id": "cell-46d843154dcd7d0f",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -36,7 +36,7 @@
"grade": false,
"grade_id": "cell-6d2f06d701e19789",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand Down Expand Up @@ -85,7 +85,7 @@
"grade": false,
"grade_id": "cell-4a34bd8a41530e62",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -106,7 +106,7 @@
"grade": false,
"grade_id": "cell-13b85f82dcf86759",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -123,7 +123,7 @@
"grade": false,
"grade_id": "cell-8cb295450c798c5e",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -140,7 +140,7 @@
"grade": false,
"grade_id": "cell-338b88f7b1299ed2",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -159,7 +159,7 @@
"grade": false,
"grade_id": "cell-546708e14b12ee66",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -176,7 +176,7 @@
"grade": false,
"grade_id": "cell-0be1345e6313af0b",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -202,7 +202,7 @@
"grade": false,
"grade_id": "cell-6e62f4a661edbaf0",
"locked": false,
"schema_version": 1,
"schema_version": 3,
"solution": true
}
},
Expand All @@ -226,7 +226,7 @@
"grade": false,
"grade_id": "cell-af7b28f3cfa91f60",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -247,7 +247,7 @@
"grade_id": "cell-e1f0144e6b6e35ff",
"locked": true,
"points": 10,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -270,7 +270,7 @@
"grade": false,
"grade_id": "cell-2778271fc0197c11",
"locked": true,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
Expand All @@ -287,7 +287,7 @@
"grade": false,
"grade_id": "cell-76c1342f063d35b5",
"locked": false,
"schema_version": 1,
"schema_version": 3,
"solution": true
}
},
Expand All @@ -314,7 +314,7 @@
"grade_id": "cell-33470e71829ec84a",
"locked": true,
"points": 10,
"schema_version": 1,
"schema_version": 3,
"solution": false
}
},
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.6"
"version": "3.7.8"
}
},
"nbformat": 4,
Expand Down
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