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Mastering pandas. - Second Edition

You're reading from  Mastering pandas. - Second Edition

Product type Book
Published in Oct 2019
Publisher
ISBN-13 9781789343236
Pages 674 pages
Edition 2nd Edition
Languages
Author (1):
Ashish Kumar Ashish Kumar
Profile icon Ashish Kumar

Table of Contents (21) Chapters

Preface Section 1: Overview of Data Analysis and pandas
Introduction to pandas and Data Analysis Installation of pandas and Supporting Software Section 2: Data Structures and I/O in pandas
Using NumPy and Data Structures with pandas I/Os of Different Data Formats with pandas Section 3: Mastering Different Data Operations in pandas
Indexing and Selecting in pandas Grouping, Merging, and Reshaping Data in pandas Special Data Operations in pandas Time Series and Plotting Using Matplotlib Section 4: Going a Step Beyond with pandas
Making Powerful Reports In Jupyter Using pandas A Tour of Statistics with pandas and NumPy A Brief Tour of Bayesian Statistics and Maximum Likelihood Estimates Data Case Studies Using pandas The pandas Library Architecture pandas Compared with Other Tools A Brief Tour of Machine Learning Other Books You May Enjoy

Where does pandas fit in the pipeline?

As discussed in the previous section, pandas can be used to perform Step 4 to Step 6 in the pipeline. And Step 4 to Step 6 are the backbone of any data science process, application, or product:

Where does pandas fit in the data analytics pipeline?

The Step 1 to Step 6 can be performed in pandas by some methods. Those in the Step 4 to Step 6 are the primary tasks while the Step 1 to Step 3 can also be done in some way or other in pandas.

pandas is an indispensable library if you're working with data, and it would be near impossible to find code for data modeling that doesn't import pandas into the working environment. Easy-to-use syntax in Python and the availability of a spreadsheet-like data structure called a dataframe make it amenable even to users who are too comfortable and too unwilling to move away from Excel. At the same...

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