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afeldafeld
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update notebooks
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‎extras/environment.yml‎

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## packages imported directly in notebooks ##
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# match version in Colab returned by `!python --version`
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- python=3.11.11
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- python=3.11.13
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# match versions in Colab returned by `!pip list`
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# required for pandas' read_html()
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- html5lib=1.1

‎hw_2.ipynb‎

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},
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"solution"
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},
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{
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"execution_count": 2,
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{
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},
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{
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"execution_count": 4,
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"metadata": {
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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"version": "3.11.13"
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"mimetype": "text/x-python",
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"name": "python",

‎lecture_0.ipynb‎

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" "
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"<IPython.lib.display.IFrame at 0x1044a5350>"
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"<IPython.lib.display.IFrame at 0x107081bd0>"
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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"version": "3.11.13"
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‎lecture_1.ipynb‎

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"/var/folders/kr/nx0m1j811kz5vy8c87ffchzr0000gn/T/ipykernel_94278/4056869583.py:1: DtypeWarning: Columns (8,20,31,34) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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"/var/folders/kr/nx0m1j811kz5vy8c87ffchzr0000gn/T/ipykernel_29431/4056869583.py:1: DtypeWarning: Columns (8,20,31,34) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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" requests = pd.read_csv(\n"
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}
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.13"
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"nbformat": 4,

‎lecture_1_demo_solution.ipynb‎

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"/var/folders/kr/nx0m1j811kz5vy8c87ffchzr0000gn/T/ipykernel_69550/3437185872.py:3: DtypeWarning: Columns (8,20,31,34) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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"/var/folders/kr/nx0m1j811kz5vy8c87ffchzr0000gn/T/ipykernel_29476/3437185872.py:3: DtypeWarning: Columns (8,20,31,34) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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" requests = pd.read_csv(\n"
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"cell_type": "code",
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"slideshow": {
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"Name: count, dtype: int64"
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‎lecture_1_exercise.ipynb‎

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"2025-03-17 00:00:28 URL:https://data.cityofnewyork.us/resource/m6nq-qud6.csv [136065] -> \"2021_yellow_taxi_trips.csv\" [1]\r\n"
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"2025-06-29 23:01:23 URL:https://data.cityofnewyork.us/resource/m6nq-qud6.csv [136065] -> \"2021_yellow_taxi_trips.csv\" [1]\r\n"
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"name": "stdout",
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"text": [
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"2021_yellow_taxi_trips.csv lecture_1_exercise.ipynb\r\n",
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"LICENSE.md lecture_1_exercise_solution.ipynb\r\n",
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"Makefile lecture_2.ipynb\r\n",
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"\u001b[1m\u001b[36m__pycache__\u001b[m\u001b[m lecture_2.slides.html\r\n",
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"\u001b[1m\u001b[36m_build\u001b[m\u001b[m lecture_2_exercise.ipynb\r\n",
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"_config.yml lecture_2_exercise_2_solution.ipynb\r\n",
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"\u001b[1m\u001b[36m_static\u001b[m\u001b[m lecture_3.ipynb\r\n",
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"_toc.yml lecture_3.slides.html\r\n",
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"\u001b[1m\u001b[36massignments\u001b[m\u001b[m lecture_3_exercise_solution.ipynb\r\n",
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"assignments.md lecture_4.ipynb\r\n",
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"attendance.csv lecture_4.slides.html\r\n",
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"conf.py lecture_5.ipynb\r\n",
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"curve.ipynb lecture_5.slides.html\r\n",
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"\u001b[35mdata\u001b[m\u001b[m lecture_5_exercise_solution.ipynb\r\n",
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"\u001b[1m\u001b[36mextras\u001b[m\u001b[m lecture_6.ipynb\r\n",
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"\u001b[1m\u001b[36mfinal_project\u001b[m\u001b[m lecture_6.slides.html\r\n",
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"final_project.md lectures.md\r\n",
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"home.md \u001b[1m\u001b[36mmeta\u001b[m\u001b[m\r\n",
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"hw_0.ipynb meta.md\r\n",
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"hw_1.md nbdime_config.json\r\n",
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"hw_2.ipynb pyproject.toml\r\n",
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"hw_3.ipynb registration.md\r\n",
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"hw_4.ipynb resources.md\r\n",
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"index.md \u001b[1m\u001b[36mresults\u001b[m\u001b[m\r\n",
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"joining_late.md simple.html\r\n",
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"lecture_0.ipynb simple.ipynb\r\n",
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"lecture_0.slides.html \u001b[35msolutions\u001b[m\u001b[m\r\n",
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"lecture_1.ipynb syllabus.md\r\n",
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"lecture_1.slides.html \u001b[1m\u001b[36mtmp\u001b[m\u001b[m\r\n"
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"\u001b[1m\u001b[36m__pycache__\u001b[m\u001b[m lecture_1.slides.html\r\n",
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"\u001b[1m\u001b[36m_build\u001b[m\u001b[m lecture_2_exercise_2_solution.ipynb\r\n",
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"_config.yml lecture_2_exercise.ipynb\r\n",
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"\u001b[1m\u001b[36m_static\u001b[m\u001b[m lecture_2_makeup.slides.html\r\n",
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"_toc.yml lecture_2.ipynb\r\n",
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"2021_yellow_taxi_trips.csv lecture_2.slides.html\r\n",
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"\u001b[1m\u001b[36massignments\u001b[m\u001b[m lecture_3_demo_solution.ipynb\r\n",
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"assignments.md lecture_3_exercise_solution.ipynb\r\n",
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"attendance.csv lecture_3.ipynb\r\n",
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"brackets.ipynb lecture_3.slides.html\r\n",
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"conf.py lecture_4_demo_solution.ipynb\r\n",
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"curve.ipynb lecture_4.ipynb\r\n",
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"\u001b[35mdata\u001b[m\u001b[m lecture_4.slides.html\r\n",
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"\u001b[1m\u001b[36mextras\u001b[m\u001b[m lecture_5_exercise_solution.ipynb\r\n",
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"\u001b[1m\u001b[36mfinal_project\u001b[m\u001b[m lecture_5.ipynb\r\n",
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"final_project.md lecture_5.slides.html\r\n",
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"home.md lecture_6.ipynb\r\n",
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"hw_0.ipynb lecture_6.slides.html\r\n",
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"hw_1.md lectures.md\r\n",
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"hw_2.ipynb LICENSE.md\r\n",
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"hw_3.ipynb Makefile\r\n",
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"hw_4.md \u001b[1m\u001b[36mmeta\u001b[m\u001b[m\r\n",
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"index.md meta.md\r\n",
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"joining_late.md nbdime_config.json\r\n",
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"lecture_0.ipynb pyproject.toml\r\n",
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"lecture_0.slides.html registration.md\r\n",
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"lecture_1_demo_solution.ipynb resources.md\r\n",
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"lecture_1_exercise_solution.ipynb \u001b[35msolutions\u001b[m\u001b[m\r\n",
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"lecture_1_exercise.ipynb syllabus.md\r\n",
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"lecture_1.ipynb \u001b[1m\u001b[36mtmp\u001b[m\u001b[m\r\n"
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‎lecture_1_exercise_solution.ipynb‎

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"2025-03-17 00:00:31 URL:https://data.cityofnewyork.us/resource/m6nq-qud6.csv [136065] -> \"2021_yellow_taxi_trips.csv\" [1]\r\n"
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"2025-06-29 23:01:26 URL:https://data.cityofnewyork.us/resource/m6nq-qud6.csv [136065] -> \"2021_yellow_taxi_trips.csv\" [1]\r\n"
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‎lecture_2.ipynb‎

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"/var/folders/kr/nx0m1j811kz5vy8c87ffchzr0000gn/T/ipykernel_29573/610958175.py:2: DtypeWarning: Columns (8,20,31,34) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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"/var/folders/kr/nx0m1j811kz5vy8c87ffchzr0000gn/T/ipykernel_96620/1354368569.py:1: DtypeWarning: Columns (20,31,34) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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"/var/folders/kr/nx0m1j811kz5vy8c87ffchzr0000gn/T/ipykernel_29573/1354368569.py:1: DtypeWarning: Columns (20,31,34) have mixed types. Specify dtype option on import or set low_memory=False.\n",
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‎lecture_2_exercise.ipynb‎

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‎lecture_2_exercise_2_solution.ipynb‎

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