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Fixing some typos in the docs
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README.md

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* Encrypt Pandas Dataframes on S3 with KMS keys (NEW :star:)
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### PySpark
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* PySpark -> Redshift (Parallel :rocket:) (NEW :star:)
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* PySpark -> Redshift (Parallel) (NEW :star:)
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### General
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* List S3 objects (Parallel)
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* Delete S3 objects (Parallel)
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* Delete listed S3 objects (Parallel)
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* Delete NOT listed S3 objects (Parallel)
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* Copy listed S3 objects (Parallel :rocket:)
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* Get the size of S3 objects (Parallel :rocket:)
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* Copy listed S3 objects (Parallel)
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* Get the size of S3 objects (Parallel)
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* Get CloudWatch Logs Insights query results (NEW :star:)
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## Installation
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* Fork the AWS Data Wrangler repository and clone that into your development environment
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* Go to the project's directory create a Python's virtual environment for the project **python -m venv venv && source source venv/bin/activate**
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* Go to the project's directory create a Python's virtual environment for the project (**python -m venv venv && source source venv/bin/activate**)
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* Run **./install-dev.sh**
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docs/source/contributing.rst

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* Fork the AWS Data Wrangler repository and clone that into your development environment
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* Go to the project's directory create a Python's virtual environment for the project **python -m venv venv && source source venv/bin/activate**
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* Go to the project's directory create a Python's virtual environment for the project (**python -m venv venv && source source venv/bin/activate**)
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* Run **./install-dev.sh**
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