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  • Data Analysis with Python
  • David Taieb
  • 456字
  • 2021-06-11 13:31:40

To get the most out of this book

  • Most of the software needed to follow the example is open source and therefore free to download. Instructions are provided throughout the book, starting with installing anaconda which includes the Jupyter Notebook server.
  • In Chapter 7, Analytics Study: NLP and Big Data with Twitter Sentiment Analysis, the sample application requires the use of IBM Watson cloud services including NLU and Streams Designer. These services come with a free tier plan, which is sufficient to follow the example along.

Download the example code files

You can download the example code files for this book from your account at http://www.packtpub.com. If you purchased this book elsewhere, you can visit http://www.packtpub.com/support and register to have the files emailed directly to you.

You can download the code files by following these steps:

  1. Log in or register at http://www.packtpub.com.
  2. Select the SUPPORT tab.
  3. Click on Code Downloads & Errata.
  4. Enter the name of the book in the Search box and follow the on-screen instructions.

Once the file is downloaded, please make sure that you unzip or extract the folder using the latest version of:

  • WinRAR / 7-Zip for Windows
  • Zipeg / iZip / UnRarX for Mac
  • 7-Zip / PeaZip for Linux

The code bundle for the book is also hosted on GitHub at https://github.com/PacktPublishing/Thoughtful-Data-Science. We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

Download the color images

We also provide a PDF file that has color images of the screenshots/diagrams used in this book. You can download it here: http://www.packtpub.com/sites/default/files/downloads/ThoughtfulDataScience_ColorImages.pdf.

Conventions used

There are a number of text conventions used throughout this book.

CodeInText: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. For example: "You can use the {%if ...%}...{%elif ...%}...{%else%}…{%endif%} notation to conditionally output text."

A block of code is set as follows:

import pandas
data_url = "https://data.cityofnewyork.us/api/views/e98g-f8hy/rows.csv?accessType=DOWNLOAD"
building_df = pandas.read_csv(data_url)
building_df

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

import pandas
data_url = "https://data.cityofnewyork.us/api/views/e98g-f8hy/rows.csv?accessType=DOWNLOAD"
building_df = pandas.read_csv(data_url)
building_df

Any command-line input or output is written as follows:

jupyter notebook --generate-config

Bold: Indicates a new term, an important word, or words that you see on the screen, for example, in menus or dialog boxes, also appear in the text like this. For example: " The next step is to create a new route that takes the user value and returns the results. This route will be invoked by the Submit Query button."

Note

Warnings or important notes appear like this.

Tip

Tips and tricks appear like this.

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