Chapter 1: The Python Scientific Ecosystem¶

Part I — Python for Data Science

Learning Objectives¶

By the end of this chapter you will be able to:

• Set up a reproducible development environment (conda/mamba, VS Code, Jupyter)
• Understand the role of each core library: NumPy, Pandas, Matplotlib, GeoPandas
• Manage packages and environments for reproducible science

{note}
Keep tool installation instructions in a collapsible admonition block.

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# Standard imports — add chapter-specific imports below
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

# Standard imports — add chapter-specific imports below import numpy as np import pandas as pd import matplotlib.pyplot as plt

Why Python for Data Science¶

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Setting Up Your Environment¶

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Package Management with conda and pip¶

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Core Libraries at a Glance¶

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Jupyter Notebooks and VS Code¶

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Summary and Further Reading¶

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Summary¶

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Key concepts introduced¶

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Further Reading¶

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