Category Archives: Big Data
Learn R – How to Append Rows to Data Frame
This article represents concepts and code samples on how to append rows to a data frame when working with R programming language. Please feel free to comment/suggest if I missed mentioning one or more important points. Also, sorry for the typos. Following are the key points described later in this article: How to append one or more rows to an empty data frame How to append one or more rows to non-empty data frame For illustration purpose, we shall use a student data frame having following information: How to Append one or more rows to an Empty Data Frame Following code represents how to create an empty data frame and …
Learn R – How to Create Data Frame with Column Names

This article represents code in R programming language which could be used to create a data frame with column names. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: Create empty dataframe with column names Create non-empty dataframe with column names Create an Empty Dataframe with Column Names Following is the code sample: Following gets printed: Create non-empty Dataframe with Column Names Following is the code sample: Following gets printed. Note the column names such as “First Name” and “Age”
Learn R – How to Extract Rows & Columns from Data Frame

This article represents command set in R programming language, which could be used to extract rows and columns from a given data frame. When working on data analytics or data science projects, these commands come very handy in data cleaning activities. This article is meant for beginners/rookies getting started with R and wanting to know or see examples of extracting information from a data frame. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: Commands to extract rows and columns Command to extract a column as data frame Command …
Data Science – How to Load Data included with R

This article represents different ways in which data from different R packages could be loaded. One of the important aspect of getting on aboard with Data Science is to play with data as much as possible while one is going through the learning phase. When doing that, some of the key activities include data loading, data extraction, data wrangling/munging etc. This is where I found that loading data from different R packages is one of the key to get access to these data sets and hence, decided to write this quick article. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for …
Machine Learning – How to Predict Software Developers Productivity

This article represents my thoughts on how machine learning techniques could be used to solve one of the most popular problem of software industry such as whether a software developer is productive or not. Of all the effort that I have made to solve this problem using traditional programming techniques (rules-based), I could say that there is no definitive way of finding a concrete solution. As a matter of fact, I created a tool, AgileSQM to capture the software quality metrics (SQM) such as code coverage, duplication, complexity and infer from the trending data whether a software developer is productive. However, I soon hit the road-block in terms of acceptance …
Data Science – Examples of Machine Learning Problems

This article represents different classification of machine learning problems along with some of the examples taken from real world problems. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following is listed different categories which covers 80% of machine learning problems: Classification Clustering Regression Machine Learning – Classification Problems Simply speaking, if the answer to problems consists of discrete values such as some of the following, the problem can be termed as classification problems. These are called as “Logistic Regression” problems. Yes or no,. e.g., 1 or 0. Finite set of values representing multi-classification problems Mathematically speaking, if “h(x)” …
Top 7 Data Science Subreddits to Follow

This article represents top subreddits related with Data Science on reddit.com that the Data Science aspirants or professionals could watch on regular basis for news, stories and discussions. Generally, I find reddit.com very useful to remain in touch with latest and interesting stories and keep myself up-to-date. For those unaware of what is subreddit, subreddit, simply speaking, represents the topic-based groups on reddit.com that comprise of users who want to publish/discuss news or stories related with that topic. For data science, there are multiple groups each focused on a single topic such as those mentioned below. Please feel free to comment/suggest if I missed to mention one or more important …
Data Science – Quick Start Guide for Machine Learning

This article represents a very high-level information on different aspects of machine learning with an objective to present a quick-start read/guide for the data science beginners. One could grab one or more books on Machine Learning to learn the subject in detail. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: What is machine learning? Key phases of machine learning Prediction API model of machine learning What is Machine Learning? Simply speaking, Machine Learning is a set of artifical intelligence techniques which are used to solve one of …
Data Scraping – Top 5 Reasons for using Import.io Tool

This article represents my thoughts on why one would want to use this web data scraping tool, named as import.io. I must say that I am glad I found this tool for data scraping. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: Key aspects of Import.io Reasons Why One Must Try Import.io for their next Data Scraping Project Use-cases where Import.io scraping tool could be used Key Aspects of Import.io Tool Import.io is a cloud-based web scraping tool which could act as a boon for those looking …
Data Science – 8 Steps to Perform Regression Analysis using R

This article represents my thoughts on steps that may be required to perform regression analysis (linear or multiple) using R programming language, on a given data set where response variable is primarily a continuous variable. Remember that continuous variables are the ones which could take any numeric data unlike discreet variables which could take only limited set of data. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key steps described later in this article: Load the data Observe the data Clean the data Explore the data visually Fit the linear or multiple regression model …
Data Science – Top 5 Videos to Learn Bayes’ Theorum

This article represents the top 5 videos that I thought to be great when I was trying to understand Bayes theorum from Youtube channels. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are top 5 videos that I found quite useful to understand Bayes theorum: Bayes’ Theorum Formula: This one, I liked most. Very short and sweet video which explains about Bayes theorum with a very nice example of economy and stock values in just 6 minutes. For beginners, I would recommend this to be first video to get started with Bayes theorum. Bayes Theorum with …
Learn R – Hello World with R – Code Example

This article represents some of the basic concepts required to be understood to write Hello world using R programming language and, execute the same. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: Basic Concepts to Write Hello World Function in R Hello World – Code Example Basic Concepts to Write Hello World Function in R Following are some key points to pay attention at, while working Hello World example: R code is written as a set of one or more functions. In R, one could assign a function …
Learn R – How to Get Started with GGPlot – Code Example

This article represents quick introduction to GGPlot along with key concepts and code examples using R programming language. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key points described later in this article: Quick introduction to GGPlot Installation and loading of GGPlot GGPlot – Key Concepts Quick Introduction to GGPlot ggplot is one of statistical package that facilitates the easy creation of different plots. One of the key concept related to ggplot is that ggplot is built up layer by layer. This means that one could start by initializing the ggplot using ggplot(data) …
Learn R – When to use Histogram, Scatterplot & Boxplot – Code Example

This article represents some facts on when to use what kind of plots with code example and plots, when working with R programming language. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key plots described later in this article: Histogram Scatterplot Boxplot Following is the description for above mentioned plots along with code examples based on base R package. Note that each of the these plots could be done using different commands when using ggplot2 package. Histogram:Histograms is one of the best form of visualizations when working with single continuous variable. It plots the relative …
Data Science – 6 Steps to Perform Data Analysis using R

This article represents steps that one could take to perform data analysis on available datasets using data science (machine learning algorithms) with the help of R programming language. The objective of this article is to introduce an approach for data science beginners to get started with data analysis. However, as you get experience you could adopt your own techniques that works for you. These are just my thoughts and there could be better way of approaching data analysis. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. Following are the key steps which could be taken as a blueprint …
Big Data – Team to Hire for Big Data Practice

This article represents thoughts on Big data team composition and different considerations to make in order to hire and build an effective Big Data team. Please feel free to comment/suggest if I missed to mention one or more important points. Also, sorry for the typos. A Big data team would need to cover following two key areas for becoming an effective team ready to deliver on key Big Data initiatives. Data engineering Data science Data Engineering Team You would want to build a team who plays key role in some of the following areas: Data processing (Hadoop Map/Reduce) Data storage (HDFS/HBase) Data coordination (Zookeeper) Data monitoring/management For above skills, …
Nice question to help us