Python Data Analysis
Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks.
With this course, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The course covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. You will also learn how to visualize data using visualization libraries.
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Getting Started with Python Libraries
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NumPy Arrays
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Pandas
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Statistics and Linear Algebra
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Retrieving, Processing and Storing Data
- Writing CSV files with NumPy and Pandas
- The binary .npy and pickle formats
- Storing data with PyTables
- Reading and writing Pandas DataFrames to HDF5 stores
- Reading and writing to Excel with Pandas
- Using REST web services and JSON
- Reading and writing JSON with Pandas
- Parsing RSS and Atom feeds
- Parsing HTML with Beautiful Soup
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Working with Databases
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Data Visualization
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$600.00