Sign In Start Free Trial
Account

Add to playlist

Create a Playlist

Modal Close icon
You need to login to use this feature.
  • Book Overview & Buying Data Analysis with Python
  • Table Of Contents Toc
Data Analysis with Python

Data Analysis with Python

By : David Taieb
5 (1)
close
close
Data Analysis with Python

Data Analysis with Python

5 (1)
By: David Taieb

Overview of this book

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you’re likely to meet in today. The first of these is an image recognition application with TensorFlow – embracing the importance today of AI in your data analysis. The second industry project analyses social media trends, exploring big data issues and AI approaches to natural language processing. The third case study is a financial portfolio analysis application that engages you with time series analysis - pivotal to many data science applications today. The fourth industry use case dives you into graph algorithms and the power of programming in modern data science. You'll wrap up with a thoughtful look at the future of data science and how it will harness the power of algorithms and artificial intelligence.
Table of Contents (14 chapters)
close
close
3
3. Accelerate your Data Analysis with Python Libraries
13
Index

SampleData – a simple API for loading data

Loading data into a Notebook is one of the most repetitive tasks a data scientist can do, yet depending on the framework or data source being used, writing the code can be difficult and time-consuming.

Let's take a concrete example of trying to load a CSV file from an open data site (say https://data.cityofnewyork.us) into both a pandas and Apache Spark DataFrame.

Note

Note: Going forward, all the code is assumed to run in a Jupyter Notebook.

For pandas, the code is pretty straightforward as it provides an API to directly load from URL:

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

The last statement, calling building_df, will print its contents in the output cell. This is possible without a print because Jupyter is interpreting the last statement of a cell calling a variable as a directive to print it...

CONTINUE READING
83
Tech Concepts
36
Programming languages
73
Tech Tools
Icon Unlimited access to the largest independent learning library in tech of over 8,000 expert-authored tech books and videos.
Icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Icon 50+ new titles added per month and exclusive early access to books as they are being written.
Data Analysis with Python
notes
bookmark Notes and Bookmarks search Search in title playlist Add to playlist download Download options font-size Font size

Change the font size

margin-width Margin width

Change margin width

day-mode Day/Sepia/Night Modes

Change background colour

Close icon Search
Country selected

Close icon Your notes and bookmarks

Confirmation

Modal Close icon
claim successful

Buy this book with your credits?

Modal Close icon
Are you sure you want to buy this book with one of your credits?
Close
YES, BUY

Submit Your Feedback

Modal Close icon
Modal Close icon
Modal Close icon