Geography of Claudius Ptolemy


Book Description

Geography of Claudius Ptolemy, originally titled Geographia and written in the second century, is a depiction of the geography of the Roman Empire at the time. Though inaccurate due to Ptolemy's varying methods of measurement and use of outdated data, Geography of Claudius Ptolemy is nonetheless an excellent example of ancient geographical study and scientific method. This edition contains more than 40 maps and illustrations, reproduced based on Ptolemy's original manuscript. It remains a fascinating read for students of scientific history and Greek influence. CLAUDIUS PTOLEMY (A.D. 90- A.D. 168) was a poet, mathematician, astronomer, astrologer, and geographer who wrote in Greek, though he was a Roman citizen. He is most well-known for three scientific treatises he wrote on astronomy, astrology, and geography, respectively titled Almagest, Apotelesmatika, and Geographia. His work influenced early Islamic and European studies, which in turn influenced much of the modern world. Ptolemy died in Alexandria as a member of Greek society.




Handbook on Geospatial Infrastructure in Support of Census Activities


Book Description

The handbook demonstrates how the use and application of contemporary geospatial technologies and geographical databases are beneficial at all stages of the population and housing census process.




Forest and Stream


Book Description




Manual for the National Standardization of Geographical Names


Book Description

The present publication is designed primarily to assist countries that do not have an appropriate authority and a specific set of standards for the consistent rendering of their geographical names. The information in the Manual consists of suggestions that should be useful to those intersted in ways to standardize their nation's geographical names




Longitude


Book Description

The dramatic human story of an epic scientific quest and of one man's forty-year obsession to find a solution to the thorniest scientific dilemma of the day--"the longitude problem." Anyone alive in the eighteenth century would have known that "the longitude problem" was the thorniest scientific dilemma of the day-and had been for centuries. Lacking the ability to measure their longitude, sailors throughout the great ages of exploration had been literally lost at sea as soon as they lost sight of land. Thousands of lives and the increasing fortunes of nations hung on a resolution. One man, John Harrison, in complete opposition to the scientific community, dared to imagine a mechanical solution-a clock that would keep precise time at sea, something no clock had ever been able to do on land. Longitude is the dramatic human story of an epic scientific quest and of Harrison's forty-year obsession with building his perfect timekeeper, known today as the chronometer. Full of heroism and chicanery, it is also a fascinating brief history of astronomy, navigation, and clockmaking, and opens a new window on our world.




Python Data Science Handbook


Book Description

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms