PythonTour/00-Introduction.ipynb

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    "### 南京大学计算传播学系列课程\n",
    "***\n",
    "***\n",
    "# 《计算传播学的编程基础》\n",
    "***\n",
    "***\n",
    "\n",
    "王成军 \n",
    "\n",
    "wangchengjun@nju.edu.cn\n",
    "\n",
    "计算传播网 http://computational-communication.com"
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    "<img align=\"right\" style=\"padding-right:10px;\" src=\"fig/logo.png\">\n",
    "\n",
    "<!--NAVIGATION-->\n",
    "< [Preface](00.00-Preface.ipynb) | [Contents](Index.ipynb) | [Help and Documentation in IPython](01.01-Help-And-Documentation.ipynb) >"
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    "<!--BOOK_INFORMATION-->\n",
    "<img align=\"left\" style=\"padding-right:10px;\" src=\"fig/cover-small.jpg\">\n",
    "*This notebook contains an excerpt from the [Whirlwind Tour of Python](http://www.oreilly.com/programming/free/a-whirlwind-tour-of-python.csp) by Jake VanderPlas; the content is available [on GitHub](https://github.com/jakevdp/WhirlwindTourOfPython).*\n",
    "\n",
    "*The text and code are released under the [CC0](https://github.com/jakevdp/WhirlwindTourOfPython/blob/master/LICENSE) license; see also the companion project, the [Python Data Science Handbook](https://github.com/jakevdp/PythonDataScienceHandbook).*\n"
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    "<!--NAVIGATION-->\n",
    "| [Contents](Index.ipynb) | [How to Run Python Code](01-How-to-Run-Python-Code.ipynb) >"
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   "source": [
    "# 1. Introduction"
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    "Conceived in the late 1980s as a teaching and scripting language, Python has since become an essential tool for many programmers, engineers, researchers, and data scientists across academia and industry.\n",
    "\n",
    "\n",
    "The appeal of Python is in its **simplicity and beauty**, as well as the **convenience** of the large ecosystem of domain-specific tools that have been built on top of it.\n"
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    "- [NumPy](http://numpy.org) provides efficient storage and computation for multi-dimensional data arrays.\n",
    "- [SciPy](http://scipy.org) contains a wide array of numerical tools such as numerical integration and interpolation.\n",
    "- [Pandas](http://pandas.pydata.org) provides a DataFrame object along with a powerful set of methods to manipulate, filter, group, and transform data.\n",
    "- [Matplotlib](http://matplotlib.org) provides a useful interface for creation of publication-quality plots and figures.\n",
    "- [Scikit-Learn](http://scikit-learn.org) provides a uniform toolkit for applying common machine learning algorithms to data.\n",
    "- [IPython/Jupyter](http://jupyter.org) provides an enhanced terminal and an interactive notebook environment that is useful for exploratory analysis, as well as creation of interactive, executable documents. "
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    "To tap into the power of this data science ecosystem, however, \n",
    "- first requires familiarity with the Python language itself.\n",
    "- students and colleagues are looking for a brief but comprehensive tour of the Python language that respects their level of knowledge rather than starting from ground zero.\n",
    "\n",
    "A full introduction to the Python language itself [Resources for Learning](16-Further-Resources.ipynb).\n",
    "\n",
    "We will provide **a whirlwind tour** of some of Python's essential syntax and semantics, built-in data types and structures, function definitions, control flow statements, and other aspects of the language."
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    "## Code Examples\n",
    "\n",
    "Supplemental material (code examples, exercises, etc.) is available for download at https://github.com/jakevdp/WhirlwindTourOfPython/.\n",
    "\n",
    "Jake VanderPlas (2016) **<span class=\"girk\">A Whirlwind Tour of Python</span>**.O’Reilly Media, Inc., 978-1-491-96465-1."
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   "source": [
    "## Installation \n"
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    "### Python 2 vs Python 3\n",
    "\n",
    "We now recommend to use Python 3, which contains language enhancements that are not compatible with the *2.x* series of Python.\n",
    "- Python 3.0 was first released in 2008.\n",
    "- Python 2.0 will be abandoned after 2020."
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    "### Installation with conda\n",
    "\n",
    "\n",
    "- [Anaconda](https://www.continuum.io/downloads) includes both Python and ``conda``, and additionally bundles a suite of other pre-installed packages geared toward scientific computing.\n",
    "- [Miniconda](http://conda.pydata.org/miniconda.html) gives you Python interpreter itself, along with a command-line tool called ``conda`` which operates as a cross-platform package manager geared toward Python packages, similar in spirit to the ``apt`` or ``yum`` tools that Linux users might be familiar with.\n",
    "\n",
    "For new users, we highly recommend installing <span class=\"burk\">Anaconda</span>. \n",
    "\n",
    "Anaconda conveniently installs Python, the Jupyter Notebook, and other commonly used packages for scientific computing and data science."
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    "## The Zen of Python\n",
    "\n",
    "- Python is\"intuitive\", \"beautiful\", or \"fun\".\n",
    "- Beauty, intuition, and fun often go hand in hand with <span class=\"burk\">familiarity</span>.\n",
    "\n",
    "The programming philosophy that drives much of the coding practice of Python power-users, a nice little **Easter egg** exists in the Python interpreter: \n",
    "\n",
    "``import this``:"
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    "import this "
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    "With that, let's start our tour of the Python language."
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    "<!--NAVIGATION-->\n",
    "| [Contents](Index.ipynb) | [How to Run Python Code](01-How-to-Run-Python-Code.ipynb) >"
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