125 lines
2.5 KiB
JSON
125 lines
2.5 KiB
JSON
{
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"name": "Data Analysis with Python Course",
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"isUpcomingChange": false,
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"dashedName": "data-analysis-with-python-course",
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"order": 1,
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"time": "15 hours",
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"template": "",
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"required": [],
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"superBlock": "data-analysis-with-python",
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"superOrder": 9,
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"challengeOrder": [
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[
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"5e9a093a74c4063ca6f7c14c",
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"Introduction to Data Analysis"
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],
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[
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"5e9a093a74c4063ca6f7c14d",
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"Data Analysis Example A"
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],
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[
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"5e9a093a74c4063ca6f7c14e",
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"Data Analysis Example B"
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],
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[
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"5e9a093a74c4063ca6f7c14f",
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"How to use Jupyter Notebooks Intro"
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],
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[
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"5e9a093a74c4063ca6f7c150",
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"Jupyter Notebooks Cells"
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],
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[
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"5e9a093a74c4063ca6f7c151",
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"Jupyter Notebooks Importing and Exporting Data"
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],
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[
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"5e9a093a74c4063ca6f7c152",
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"Numpy Introduction A"
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],
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[
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"5e9a093a74c4063ca6f7c153",
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"Numpy Introduction B"
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],
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[
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"5e9a093a74c4063ca6f7c154",
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"Numpy Arrays"
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],
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[
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"5e9a093a74c4063ca6f7c155",
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"Numpy Operations"
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],
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[
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"5e9a093a74c4063ca6f7c156",
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"Numpy Boolean Arrays"
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],
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[
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"5e9a093a74c4063ca6f7c157",
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"Numpy Algebra and Size"
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],
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[
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"5e9a093a74c4063ca6f7c158",
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"Pandas Introduction"
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],
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[
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"5e9a093a74c4063ca6f7c159",
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"Pandas Indexing and Conditional Selection"
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],
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[
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"5e9a093a74c4063ca6f7c15a",
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"Pandas DataFrames"
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],
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[
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"5e9a093a74c4063ca6f7c15b",
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"Pandas Conditional Selection and Modifying DataFrames"
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],
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[
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"5e9a093a74c4063ca6f7c15c",
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"Pandas Creating Columns"
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],
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[
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"5e9a093a74c4063ca6f7c15d",
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"Data Cleaning Introduction"
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],
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[
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"5e9a093a74c4063ca6f7c15e",
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"Data Cleaning with DataFrames"
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],
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[
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"5e9a093a74c4063ca6f7c15f",
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"Data Cleaning Duplicates"
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],
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[
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"5e9a093a74c4063ca6f7c160",
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"Data Cleaning and Visualizations"
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],
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[
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"5e9a093a74c4063ca6f7c161",
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"Reading Data Introduction"
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],
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[
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"5e9a093a74c4063ca6f7c162",
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"Reading Data CSV and TXT"
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],
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[
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"5e9a093a74c4063ca6f7c163",
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"Reading Data from Databases"
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],
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[
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"5e9a093a74c4063ca6f7c164",
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"Parsing HTML and Saving Data"
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],
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[
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"5e9a093a74c4063ca6f7c165",
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"Python Introduction"
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],
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[
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"5e9a093a74c4063ca6f7c166",
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"Python Functions and Collections"
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],
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[
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"5e9a093a74c4063ca6f7c167",
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"Python Iteration and Modules"
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]
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]}
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