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## Getting Started
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Open up `data-analysis-projects/cleaning-data-with-pandas/exercises/PandasCleaningTechniques.ipynb`.
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Fork and clone the following repository to get starter: [Cleaning Data with Pandas Exercises and Studio](https://github.com/LaunchCodeEducation/cleaning-data-pandas-exercises-studio)`.
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For this week's studio you will be working with a partner.
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Each of you should work in your notebook that can be found at `data-analysis-projects/cleaning-data-with-pandas/studio`.
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Each of you should work in your notebook that can be found within this repository [Cleaning Data with Pandas Exercises and Studio](https://github.com/LaunchCodeEducation/cleaning-data-pandas-exercises-studio/tree/main).
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You will also notice that we have already added a CSV for you. This CSV is a subset of a larger dataset on [Kaggle](https://www.kaggle.com/datasets/usda/a-year-of-pumpkin-prices) from the USDA. You only need this one CSV to do the studio.
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