Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
| Author | : | |
| Rating | : | 4.22 (573 Votes) |
| Asin | : | 1491957662 |
| Format Type | : | paperback |
| Number of Pages | : | 550 Pages |
| Publish Date | : | 2014-02-19 |
| Language | : | English |
DESCRIPTION:
Wes is an active speaker andparticipant in the Python and open source communities. He graduated from MIT with an S.B. He worked as a quantitative analyst at AQR Capital Management and Python consultant before founding DataPad, a data analytics company, in 2013. About the AuthorWes McKinney is the main author of pandas, the popular open sourcePython library for data analysis. in Mathematics.
Wes is an active speaker andparticipant in the Python and open source communities. He graduated from MIT with an S.B. He worked as a quantitative analyst at AQR Capital Management and Python consultant before founding DataPad, a data analytics company, in 2013. in Mathematics.. Wes McKinney is the main author of pandas, the popular open sourcePython library for data analysis
It’s ideal for analysts new to Python and for Python programmers new to scientific computing.. Looking for complete instructions on manipulating, processing, cleaning, and crunching structured data in Python? The second edition of this hands-on guide—updated for Python 3.6 and the latest versions of NumPy, IPython, Jupyter, and pandas in 2017—is packed with practical cases studies that show you how to effectively solve a broad set of data analysis problems using Python.Written by Wes McKinney, the main author of the pandas library, Python for Data Analysis also serves as a practical, modern introduction to scientific computing in Python for data-intensive app