A few years ago I bought a Dell XPS desktop. It was on sale I thought a good deal, so I picked it up. It had a traditional hard drive (not an SSD) and onboard video. I had anticipated upgrading the desktop over time…. and in fact I did. Dell Continue Reading
Have you ever installed a package in R and noticed a conflict issued? I for one didn’t understand the output on the conflict. The output is worded like so: In the case above it’s specific to the tidyverse package. I thought it meant that the package I was installing (in Continue Reading
I you use R and find that certain programs refuse to install (using install.packages) it’s no doubt that you’re using R from within Anaconda. Anaconda is a package for statistical analysis. In general Anaconda is useful for a variety of Python related packages. However, R is also provided as an Continue Reading
Similar to posts in R on this topic, we can use Python’s Pandas library to replace Categorical data with numeric values. While the replacement syntax is backwards, IMO, this one liner works pretty good and you get to set the numeric value of your choice. However, you have to supply Continue Reading
While a one liner to convert categorical values to numerics is mentioned in a previous post, this post will cover a better way to achieve similar results (using levels.) Another way to convert data to numeric is with the as.numeric method. In R, you can access A column of a Continue Reading
When using a dataset, sometimes I want to convert a column of two values (such as Gender) to numerical values like 0, 1. Let’s take this dataset.. It’s called “Mall_Customers” and it has a column called “Gender.” Gender has values like “Female” and “Male.” To subset the column from the Continue Reading
In taking the Udemy course on Data Analysis with R by Sandeep Kumar, I took one of his tests. It’s a very simplistic question, but it gets a person thinking and running various tests in RStudio with R. Explaining R is beyond the scope of this simple post. As a Continue Reading
One way of checking the relationship between two variables is with covariance. This gives an indication if the two variables are correlated, one to another. A related post is that of Dispersion and Variance: Population Covariance The formula for population covariance is: Sample Covariance If the covariance value (between variables) Continue Reading
Building off the article below, I wanted to continue this discussion dealing with Right and Left Skewness. Specifically, how to calculate this in Python or visualize Asymmetry issues in Python. Skewness Right skewness is when the the Mean is Larger than the Median. The tail is longer towards the right Continue Reading
In the above code, I’ve got a data frame of some fake car data. I have five cars, with column values for Top Speed, Price, MPG and Deaths per Year. To plot this as a bar graph, we can combine the column data into one plot using Pandas: I’ve not Continue Reading
By Brian Warner A few years ago I bought a Dell XPS desktop. It was on sale I thought a good deal, so I picked it up. It had a traditional hard drive (not an SSD) and onboard video. I had anticipated upgrading the desktop over time…. and in fact I did. Dell Continue Reading
