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Run notebooks with updates and custom kernel

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This commit is contained in:
Alexander Hess 2024-07-15 10:33:13 +02:00
commit 3125c82096
Signed by: alexander
GPG key ID: 344EA5AB10D868E0
13 changed files with 102 additions and 114 deletions
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6
00_python_in_a_nutshell/00_content_arithmetic.ipynb
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@ -536,9 +536,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -550,7 +550,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,

6
00_python_in_a_nutshell/01_exercises_calculator.ipynb
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@ -149,9 +149,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -163,7 +163,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,

8
00_python_in_a_nutshell/02_content_logic.ipynb
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@ -507,7 +507,7 @@
"\n",
"The indented line constitues the `for`-loop's body. In the example, we simply take each of the numbers in `numbers`, one at a time, and add it to a `total` that is initialized at `0`. In other words, we calculate the sum of all the elements in `numbers`.\n",
"\n",
"Many beginners struggle with the term \"loop.\" To visualize the looping behavior of this code, we use the online tool [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B1,%202,%203,%204%5D%0A%0Atotal%20%3D%200%0A%0Afor%20number%20in%20numbers%3A%0A%20%20%20%20total%20%3D%20total%20%2B%20number%0A%0Atotal&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false). That tool is helpful for two reasons:\n",
"Many beginners struggle with the term \"loop.\" To visualize the looping behavior of this code, we use the online tool [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](http://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B1,%202,%203,%204%5D%0A%0Atotal%20%3D%200%0A%0Afor%20number%20in%20numbers%3A%0A%20%20%20%20total%20%3D%20total%20%2B%20number%0A%0Atotal&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false). That tool is helpful for two reasons:\n",
"1. It allows us to execute code in \"slow motion\" (i.e., by clicking the \"next\" button on the left side, only the next atomic step of the code snippet is executed).\n",
"2. It shows what happens inside the computer's memory on the right-hand side."
]
@ -999,9 +999,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -1013,7 +1013,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,

6
00_python_in_a_nutshell/03_exercises_loops.ipynb
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@ -178,9 +178,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -192,7 +192,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,

6
00_python_in_a_nutshell/04_exercises_fizz_buzz.ipynb
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@ -112,9 +112,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -126,7 +126,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,

10
00_python_in_a_nutshell/05_content_functions.ipynb
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@ -73,7 +73,7 @@
"\n",
"Let's execute the function with `numbers` as the input. We see the same `6` below the cell as we do above where we run the code without a function. Without the `return` statement in the function's body, we would not see any output here.\n",
"\n",
"To see what happens in detail, take a look at [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B1,%202,%203,%204%5D%0A%0Adef%20add_evens%28numbers%29%3A%0A%20%20%20%20%22%22%22Sum%20up%20all%20the%20even%20numbers%20in%20a%20list.%22%22%22%0A%20%20%20%20result%20%3D%200%0A%0A%20%20%20%20for%20number%20in%20numbers%3A%0A%20%20%20%20%20%20%20%20if%20number%20%25%202%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20%20%20%20%20result%20%3D%20result%20%2B%20number%0A%0A%20%20%20%20return%20result%0A%0Atotal%20%3D%20add_evens%28numbers%29&cumulative=false&curInstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) again. You should notice how there are two variables by the name `numbers` in memory. Python manages the memory with a concept called **namespaces** or **scopes**, which are just fancy terms for saying that Python can tell variables from different contexts apart."
"To see what happens in detail, take a look at [PythonTutor <img height=\"12\" style=\"display: inline-block\" src=\"../static/link/to_py.png\">](https://pythontutor.com/visualize.html#code=numbers%20%3D%20%5B1,%202,%203,%204%5D%0A%0Adef%20add_evens%28numbers%29%3A%0A%20%20%20%20%22%22%22Sum%20up%20all%20the%20even%20numbers%20in%20a%20list.%22%22%22%0A%20%20%20%20result%20%3D%200%0A%0A%20%20%20%20for%20number%20in%20numbers%3A%0A%20%20%20%20%20%20%20%20if%20number%20%25%202%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20%20%20%20%20result%20%3D%20result%20%2B%20number%0A%0A%20%20%20%20return%20result%0A%0Atotal%20%3D%20add_evens%28numbers%29&cumulative=false&curstr=0&heapPrimitives=nevernest&mode=display&origin=opt-frontend.js&py=3&rawInputLstJSON=%5B%5D&textReferences=false) again. You should notice how there are two variables by the name `numbers` in memory. Python manages the memory with a concept called **namespaces** or **scopes**, which are just fancy terms for saying that Python can tell variables from different contexts apart."
]
},
{
@ -151,7 +151,7 @@
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/user/1000/ipykernel_707190/1049141082.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mresult\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"Cell \u001b[0;32mIn[5], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mresult\u001b[49m\n",
"\u001b[0;31mNameError\u001b[0m: name 'result' is not defined"
]
}
@ -505,9 +505,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -519,7 +519,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,

6
00_python_in_a_nutshell/06_exercises_volume.ipynb
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@ -257,9 +257,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -271,7 +271,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,

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00_python_in_a_nutshell/07_content_data_types.ipynb
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@ -237,19 +237,18 @@
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "'int' object has no attribute 'is_integer'",
"output_type": "error",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/user/1000/ipykernel_306555/2418692311.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m: 'int' object has no attribute 'is_integer'"
]
"data": {
"text/plain": [
"True"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"a.is_integer()"
"a.is_integer() # Note: In Python versions < 3.12 this cell raises an `AttributeError`"
]
},
{
@ -494,7 +493,7 @@
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/user/1000/ipykernel_306555/2667408552.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmore_numbers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"Cell \u001b[0;32mIn[21], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mmore_numbers\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mappend\u001b[49m(\u001b[38;5;241m10\u001b[39m)\n",
"\u001b[0;31mAttributeError\u001b[0m: 'tuple' object has no attribute 'append'"
]
}
@ -607,7 +606,7 @@
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/tmp/user/1000/ipykernel_306555/3320204082.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mto_words\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"zero\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"Cell \u001b[0;32mIn[26], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mto_words\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mzero\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\n",
"\u001b[0;31mKeyError\u001b[0m: 'zero'"
]
}
@ -673,9 +672,9 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"display_name": "intro-to-data-science",
"language": "python",
"name": "python3"
"name": "intro-to-data-science"
},
"language_info": {
"codemirror_mode": {
@ -687,7 +686,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.12"
"version": "3.12.4"
},
"toc": {
"base_numbering": 1,