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
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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We cover commonly used methods of the pandas Series object in this article.
“The truth is not for all men but only for those who seek it.”
― Ayn Rand
The Series is one of the most common pandas data structures. It is similar to a python list and is used to represent a column of data. After looking into the basics of creating and initializing a pandas Series object, we now delve into some common usage patterns and methods.
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Learn the basics of creating a DataFrame in this tutorial series on pandas.
This is the next part of the pandas tutorial. In a previous article, we covered the pandas Series class. Today we are getting started with the main pandas data structure, the DataFrame.
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Learn the basics of pandas Series in this beginner tutorial.
“Come friends, it’s not too late to seek a newer world.”
― Alfred Tennyson
Pandas is a powerful toolkit providing data-analysis tools and structures for the python programming language.
Among the most important artifacts provided by pandas is the Series. In this article, we introduce the Series class from a beginner’s perspective. That means you do not need to know anything about pandas or data-analysis to understand this tutorial.
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Implement a Pivot Table in Java using Java 8 Streams and Collections.
“Money may not buy happiness, but I’d rather cry in a Jaguar than on a bus.”
― Françoise Sagan
Today let us see how we can implement a pivot table using java 8 streams. Raw data by itself does not deliver much insight to humans. We need some kind of data aggregation to discern patterns in raw data. A pivot table is one such instrument. Other more visual methods of aggregation include graphs and charts.
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We demonstrate how to setup an Apache Spark cluster on a single AWS EC2 node and run a couple of jobs.
“If the facts don’t fit the theory, change the facts.”
― Albert Einstein
Apache Spark is the newest kid on the block talking big data.
While re-using major components of the Apache Hadoop Framework, Apache Spark lets you execute big data processing jobs that do not neatly fit into the Map-Reduce paradigm. It provides support for many patterns similar to the Java 8 Streams functionality, while letting you run these jobs on a cluster.
Continue reading “Apache Spark – Setup Cluster on AWS”
This article demonstrates how to get Apache Hadoop up and running on an Amazon EC2 cluster.
Lets talk about how to setup an Apache Hadoop cluster on AWS.
In a previous article, we discussed setting up a Hadoop processing pipeline on a single node (laptop). That involved running all the components of Hadoop on a single machine. In the setup we discuss here, we setup a multi-node cluster to run processing jobs.
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Learn the basics of regular expression pattern matching in Java. Covers a few basic regular expression constructs.
“Life’s under no obligation to give us what we expect.”
― Margaret Mitchell
Regular Expressions are the bread and butter of string pattern matching. They allow you to express a search pattern in general terms without being too specific about what you are searching for.
This article covers the basics of string pattern matching using regular expressions.
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Sorting a large CSV file by loading it into SQLite. Much faster and easier to process.
“When you’re at the end of your rope, tie a knot and hold on.”
― Theodore Roosevelt
We are trying to sort a large CSV file. The file contains a couple of million rows – not large by “big-data” standards, but large enough to face problems working with it.
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Large CSV files present a challenge when need arises to sort. Learn how to do that using a database.
“All of life is a constant education.”
― Eleanor Roosevelt, The Wisdom of Eleanor Roosevelt
Let us explore some ways of sorting large data sets.
By large, I don’t mean typical “big-data” sizes – which might consist of billions of rows. Such data sets fall into the realm of “big data” which we are not exploring today. Instead I am talking of sorting a rather large CSV file – maybe a couple of million rows.
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