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27 lut 2024 · Python for Data Analysis. Wes McKinney. 2013. 1. preliminaries2. introductory examples3. IPython: interactive computing4. NumPy basics: arrays and vectorized...
While “data analysis” is in the title of the book, the focus is specifically on Python programming, libraries, and tools as opposed to data analysis methodology. This is the Python programming you need for data analysis.
basic data summaries descriptive statistics or explorative statistics. The meaning of statistics goes beyond this and will rather mean “how to learn from data in an insightful way and how to use data for clever decision making”, in short we call this inferential statistics. This could be on the national/societal level, and could be re-
23 sty 2022 · The code examples are MIT-licensed and can be found on GitHub or Gitee along with the supporting datasets. If you find the online edition of the book useful, please consider ordering a paper copy or a DRM-free eBook (in PDF and EPUB formats) to support the author.
12 kwi 2018 · • What is Python? • Why Python for data analysis? • Development Environments • Hands-on: Basic Data Structures in Python, Looping • Defining a function in Python • Importing a dataset in to a Python data structure, using modules • Python scripts and parameters • Questions, Resources & Links OVERVIEW
Overview of Python Libraries for Data Scientists Reading Data; Selecting and Filtering the Data; Data manipulation, sorting, grouping, rearranging Plotting the data Descriptive statistics Inferential statistics
In this step-by-step tutorial, you'll learn the fundamentals of descriptive statistics and how to calculate them in Python. You'll find out how to describe, summarize, and represent your data visually using NumPy, SciPy, pandas, Matplotlib, and the built-in Python statistics library.
