Book Image

Practical Business Intelligence

Book Image

Practical Business Intelligence

Overview of this book

Business Intelligence (BI) is at the crux of revolutionizing enterprise. Everyone wants to minimize losses and maximize profits. Thanks to Big Data and improved methodologies to analyze data, Data Analysts and Data Scientists are increasingly using data to make informed decisions. Just knowing how to analyze data is not enough, you need to start thinking how to use data as a business asset and then perform the right analysis to build an insightful BI solution. Efficient BI strives to achieve the automation of data for ease of reporting and analysis. Through this book, you will develop the ability to think along the right lines and use more than one tool to perform analysis depending on the needs of your business. We start off by preparing you for data analytics. We then move on to teach you a range of techniques to fetch important information from various databases, which can be used to optimize your business. The book aims to provide a full end-to-end solution for an environment setup that can help you make informed business decisions and deliver efficient and automated BI solutions to any company. It is a complete guide for implementing Business intelligence with the help of the most powerful tools like D3.js, R, Tableau, Qlikview and Python that are available on the market.
Table of Contents (16 chapters)
Practical Business Intelligence
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Visualizing histograms in Python


We can now begin developing a histogram with Python since we have established an appropriate data structure with a dataframe. One of the most popular and powerful plotting libraries in Python is matplotlib. If you are familiar with the programming language Matlab, then you will find matplotlib to be a very quick study.

Note

To learn more about matplotlib, visit the following website:  http://matplotlib.org

Before we can get started using matplotlib, we will first need to install it either through PyCharm or through the command line:

pip install matplotlib

Next, we will need to import the module and call the %matplotlib inline function to view plots directly inside of the Jupyter Notebook:

import matplotlib.pyplot as plt  
%matplotlib inline  

We will now create a new dataframe based on our existing one using only the column for VacationHours. We can now visualize our histogram using VacationHours for the plot points, with the plt.hist() function from matplotlib...