How to use Docker to Deploy Jupyter with Nginx

Become a Datascience Pro – Host your own Jupyter Notebooks

“To say goodbye is to die a little.” ― Raymond Chandler, The Long Goodbye

1. Introduction

Docker is pretty cool when it comes to deployment of software. It isolates the deployed software from the host system. It does this by running a lighter version of an OS inside a container and deploying the software on top of this OS.

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Pandas Tutorial – Using Matplotlib

Learn how to massage data using pandas DataFrame and plot the result using matplotlib in this beginner tutorial.

“There is only one thing that makes a dream impossible to achieve: the fear of failure.”
― Paulo Coelho, The Alchemist

1. Introduction

Matplotlib is a graphics and charting library for python. Once data is sliced and diced using pandas, you can use matplotlib for visualization. In this starter tutorial, we take you through the steps to do just that.

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Pandas Tutorial – Grouping Examples

Demonstrates grouping of data in pandas DataFrame and compares with SQL.

“Don’t waste your time with explanations: people only hear what they want to hear.”
― Paulo Coelho

1. Introduction

Let us learn about the “grouping-by” operation in pandas. While similar to the SQL “group by”, the pandas version is much more powerful since you can use user-defined functions at various points including splitting, applying and combining results.

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Pandas Tutorial – SQL-like Data Selection

Did you know that you can perform SQL-like selections with a pandas DataFrame? Learn how!

“Always keep your words soft and sweet, just in case you have to eat them.”
― Andy Rooney

1. Introduction

In this article, we present SQL-like ways of selecting data from a pandas DataFrame. The SELECT clause is very familiar to database programmers for accessing data within an SQL database. The DataFrame provides similar functionality when working with datasets, but is far more powerful since it supports using predicate functions with a simple syntax.

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Pandas Tutorial – Selecting Rows From a DataFrame

Learn the various ways of selecting data from a DataFrame.

“Always and never are two words you should always remember never to use. ”
― Wendell Johnson

1. Introduction

After covering ways of creating a DataFrame and working with it, we now concentrate on extracting data from the DataFrame. You may also be interested in our tutorials on a related data structure – Series; part 1 and part 2.

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Pandas Tutorial – DataFrame Basics

Learn the basics of working with a DataFrame in this pandas tutorial.

“The line between failure and success is so fine. . . that we are often on the line and do not know it.”
― Elbert Hubbard

1. Introduction

The DataFrame is the most commonly used data structures in pandas. As such, it is very important to learn various specifics about working with the DataFrame. After learning various methods of creating a DataFrame, let us now delve into some methods for working with it.

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