Book Image

Python Data Analysis - Second Edition

By : Ivan Idris
Book Image

Python Data Analysis - Second Edition

By: Ivan Idris

Overview of this book

Data analysis techniques generate useful insights from small and large volumes of data. Python, with its strong set of libraries, has become a popular platform to conduct various data analysis and predictive modeling tasks. With this book, you will learn how to process and manipulate data with Python for complex analysis and modeling. We learn data manipulations such as aggregating, concatenating, appending, cleaning, and handling missing values, with NumPy and Pandas. The book covers how to store and retrieve data from various data sources such as SQL and NoSQL, CSV fies, and HDF5. We learn how to visualize data using visualization libraries, along with advanced topics such as signal processing, time series, textual data analysis, machine learning, and social media analysis. The book covers a plethora of Python modules, such as matplotlib, statsmodels, scikit-learn, and NLTK. It also covers using Python with external environments such as R, Fortran, C/C++, and Boost libraries.
Table of Contents (22 chapters)
Python Data Analysis - Second Edition
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
Key Concepts
Online Resources

Selecting NumPy array elements


From time to time, we will wish to select a specific constituent of an array. We will take a look at how to do this, but to kick off, let's make a 2x2 matrix again:

In: a = np.array([[1,2],[3,4]]) 
In: a 
Out: 
array([[1, 2], 
       [3, 4]]) 

The matrix was made this time by giving the array() function a list of lists. We will now choose each item of the matrix one at a time, as shown in the following code snippet. Recall that the index numbers begin from 0:

In: a[0,0] 
Out: 1 
In: a[0,1] 
Out: 2 
In: a[1,0] 
Out: 3 
In: a[1,1] 
Out: 4 

As you can see, choosing elements of an array is fairly simple. For the array a, we just employ the notation a[m,n], where m and n are the indices of the item in the array. Have a look at the following figure for your reference: