All the data you need.

Tag: dplyr

Trends in U.S. Border Crossing Entry since 1996
Author: Bee Kim Introduction Since the 2016 election, inland U.S. Border security has been the huge topic. The construction for the new border wall has started and the tension between Mexico and U.S. has intensified along with it. Many people predicted not only the decrease in number of illegal border …
U.S. Cancer Research & R Shiny Application
Introduction In my career pursuit to connect medical risk and treatment information from research facilities with individuals at risk and medical professionals, I wanted to build on my WebMD analysis with a more engaging form of research and insights for the medical community. I decided to extract general Cancer diagnoses …
Getting Started with Data Science
A data scientist is someone who uses computer programming, statistics, and mathematics to derive meaningful insights from large quantities of data. For example, a data scientist might conduct a cluster analysis of customer characteristics to inform a marketing campaign or build a machine learning model to diagnose cancer.
dplyr : Data Manipulation and Exploration: The Curious Oenophile
Reading Time: < 1 minute15 Min Read The post dplyr : Data Manipulation and Exploration: The Curious Oenophile appeared first on Data Science Blog.
Data Manipulation and Exploration with Dplyr
The dplyr package in R is a powerful tool to do data munging and manipulation, perhaps more so than many people would initially realize. Shortly after I embarked on the data science journey earlier this year, I came to increasingly appreciate the handy utilities of dplyr
Data Manipulation and Exploration with Dplyr
The dplyr package in R is a powerful tool to do data munging and manipulation, perhaps more so than many people would initially realize. Shortly after I embarked on the data science journey earlier this year, I came to increasingly appreciate the handy utilities of dplyr
Spooky Author Identification - EDA Using ggplot2 and dplyr
The content of this blog is based on some exploratory data analysis performed on the corpora provided for the “Spooky Author Identification” challenge at Kaggle. The corpora includes excerpts/sentences from some of the scariest writer of all times.
Spooky Author Identification - EDA Using ggplot2 and dplyr
The content of this blog is based on some exploratory data analysis performed on the corpora provided for the “Spooky Author Identification” challenge at Kaggle. The corpora includes excerpts/sentences from some of the scariest writer of all times.