Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6 - Use the IPython shell and Jupyter notebook for exploratory computing - Learn basic and advanced features in NumPy (Numerical Python) - Get started with data analysis tools in the pandas library - Use flexible tools to load, clean, transform, merge, and reshape data - Create informative visualizations with matplotlib - Apply the pandas groupby facility to slice, dice, and summarize datasets - Analyze and manipulate regular and irregular time series data - Learn how to solve real-world data analysis problems with thorough, detailed examples
Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6 - Use the IPython shell and Jupyter notebook for exploratory computing - Learn basic and advanced features in NumPy (Numerical Python) - Get started with data analysis tools in the pandas library - Use flexible tools to load, clean, transform, merge, and reshape data - Create informative visualizations with matplotlib - Apply the pandas groupby facility to slice, dice, and summarize datasets - Analyze and manipulate regular and irregular time series data - Learn how to solve real-world data analysis problems with thorough, detailed examples
BY Python 🐍 Work With Data
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China’s stock markets are some of the largest in the world, with total market capitalization reaching RMB 79 trillion (US$12.2 trillion) in 2020. China’s stock markets are seen as a crucial tool for driving economic growth, in particular for financing the country’s rapidly growing high-tech sectors.Although traditionally closed off to overseas investors, China’s financial markets have gradually been loosening restrictions over the past couple of decades. At the same time, reforms have sought to make it easier for Chinese companies to list on onshore stock exchanges, and new programs have been launched in attempts to lure some of China’s most coveted overseas-listed companies back to the country.
