A quick introduction to dplyr
There’s sort of an open secret in the data science world: As a data professional, you’ll spend a huge amount of time doing data preparation. Cleaning, joining, reshaping, aggregating …...continue reading.
Author: Sharp Sight
np.random.randn Explained
In this tutorial, I’ll explain how to use the np.random.randn function (AKA, Numpy random randn). The tutorial is divided up into several different sections, including a quick overview of what...continue reading.
Numpy Floor, Explained
In this tutorial, I’ll explain how to use the Numpy floor function, which is sometime called np.floor. I’ll explain the syntax of np.floor and how the function works. I’ll also...continue reading.
The Best Python Package for Data Visualization
Data visualization is extremely important in data science. Although you often hear about the importance of data manipulation (i.e., “80% of data science is data manipulation”), data visualization is just...continue reading.
Why You Need to Master Data Visualization
One of the biggest questions from data science students is what to focus on. All of us have limited time and there is a lot to learn in data science....continue reading.
Numpy Absolute Value, Explained
In this tutorial, I’ll explain how to use the Numpy absolute value function, which is also known as np.abs or np.absolute. Ultimately, you’ll learn how to compute absolute values with...continue reading.
Why You Need to be a Top Performer
If you’re interested in data science and want to become a data professional, you’re probably going to need to make a choice. I think that the industry is going to...continue reading.
Why You Should Write Clean Code
A few weeks ago one of my students sent me an email. He’s a student of our Numpy Mastery course, and he was playing around with some Numpy techniques that...continue reading.
Your Job is to Create Value
As a data scientist or data professional, you might think that your primary job is to write code or analyze data. In some sense that’s true, but those things are...continue reading.
3 Secrets for Mastering Data Manipulation
Many people struggle with data manipulation. Have you ever started a data science project and gotten stuck? Have you gotten stuck while trying to manipulate, clean, or “wrangle” your data?...continue reading.
The 19 Pandas Methods you Need to Master
Readers at the Sharp Sight blog will know that I put a lot of emphasis on data manipulation. You’ve heard me repeat the stat many times: 80% of your work...continue reading.
The hard way is the best way
Here at Sharp Sight, we teach data science. And in particular, we show people how to master data science extremely fast. Exceptional results, as fast as possible. Our training methodology...continue reading.
Why fluency matters
Here at Sharp Sight, I frequently use the word “fluent” to describe an ideal skill level with data science. When you join our courses, our goal is to help you...continue reading.
How to create a beautiful map with R and geom_sf [part 2]
Last week in Mapping Texas Ports with R [part 1], we created a simple map of Texas ports with R, ggplot2, and geom_sf. That map was really just a “rough...continue reading.
Mapping Texas ports with R [part 1]
In the last few months since covid-19 has struck, everyone is suddenly talking about supply chains. Just a few months ago, this was sort of a “boring” topic, only discussed...continue reading.
Why I still love R
One of the most common questions I get from data science students is “should I learn R or Python?” In the last year or so, many of the blog posts...continue reading.
R data analysis, covid19: finding successful countries
In this blog post, we’ll create a data visualization to analyze covid19 data and visualize successful vs. unsuccessful countries. You’ll see exactly what I mean by that in a minute....continue reading.
R covid19 analysis, part5: dealing with data issues
Ok … welcome back to this covid19 data analysis series with R. In this series, we’re analyzing covid19 data with the R programming language. So far in this series, we’ve...continue reading.
R Data Visualization: covid-19, part 4
Welcome back. Hopefully you’ve been following along with our R data analysis series. This tutorial is part of a series of tutorials analyzing covid-19 data with R. So far in...continue reading.
R Data Exploration: covid-19
This tutorial is part of a series of R tutorials analyzing covid-19 data. For parts 1 and 2, see the following posts: https://www.sharpsightlabs.com/blog/r-data-analysis-covid-19-part1-data-wrangling/ https://www.sharpsightlabs.com/blog/r-data-analysis-covid-19-part-2-merge-datasets/ Covid19 analysis, part 3: initial data...continue reading.
