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data-analysis/README.md

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# Using Python for Data Analysis
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This folder contains completed notebooks and other files used in the Real Python tutorial on [Using Python for Data Analysis](https://realpython.com/using-python-for-data-analysis/).
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This folder contains completed notebooks and other files used in the Real Python tutorial on [Using Python for Data Analysis](https://realpython.com/python-for-data-analysis/).
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None of the files are mandatory to complete the tutorial, however, you may find them of use for reference during the tutorial.
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**The following files are included:**
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## Available Files:
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- `data_analysis_findings.ipynb` is a Jupyter Notebook containing all the code used in the tutorial.
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- `data_analysis_results.ipynb` is a Jupyter Notebook containing the final version of the cleansing and analysis code.
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- `james_bond_data.csv` contains the data to be cleansed and analyzed in its original form, in CSV format.
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- `james_bond_data.json` contains the data to be cleansed and analyzed in its original form, in JSON format.
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- `james_bond_data.parquet` contains the data to be cleansed and analyzed in its original form, in parquet format.
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- `james_bond_data.xlsx` contains the data to be cleansed and analyzed in its original form, in Microsoft Excel format.
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- `james_bond_data_cleansed.csv` contains the cleansed data in its final form.
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`data_analysis_findings.ipynb` is a Jupyter Notebook containing all the code used in the tutorial.
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`data_analysis_results.ipynb` is a Jupyter Notebook containing the final version of the cleansing and analysis code.
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`james_bond_data.csv` contains the data to be cleansed and analyzed in its original form, in CSV format.
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`james_bond_data.json` contains the data to be cleansed and analyzed in its original form, in JSON format.
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`james_bond_data.parquet` contains the data to be cleansed and analyzed in its original form, in parquet format.
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`james_bond_data.xlsx` contains the data to be cleansed and analyzed in its original form, in Microsoft Excel format.
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`james_bond_data_cleansed.csv` contains the cleansed data in its final form.
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## Although the tutorial can be completed in a range of Python environments, the use of Jupyter Notebook within JupyterLab is highly recommended.
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Note that although you can complete the tutorial in various Python environments, using Jupyter Notebook within JupyterLab is highly recommended.

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