This tutorial will show you how to use the NumPy sum function (sometimes called np.sum). In the tutorial, I’ll explain what the function does. I’ll also explain the syntax of the function step by step. Finally, I’ll show you some concrete examples so you can see exactly how np.sum works. Let’s jump in. NumPy sum … Read more
This tutorial will show you how to use the NumPy append function (sometimes called np.append). Here, I’ll explain what the function does. I’ll explain the syntax (piece by piece), and I’ll show you some step-by-step examples so you can see exactly how np.append works. Let’s get to it. Numpy append appends values to an existing … Read more
The NumPy linspace function (sometimes called np.linspace) is a tool in Python for creating numeric sequences. It’s somewhat similar to the NumPy arange function, in that it creates sequences of evenly spaced numbers structured as a NumPy array. There are some differences though. Moreover, some people find the linspace function to be a little tricky … Read more
The Numpy arange function (sometimes called np.arange) is a tool for creating numeric sequences in Python. If you’re learning data science in Python, the Numpy toolkit is important. The NumPy arange function is particularly important because it’s very common; you’ll see the np.arange function in a lot of data science code. Having said that, this … Read more
Let’s talk about the NumPy zeros function, which is sometimes called np.zeros or numpy.zeros. If you’re doing data science in Python, you need to be able to work with numerical data. One of the primary tools for working with numerical data is the NumPy array. In some cases, you will have data that you can … Read more
NumPy arrays are an important component of the Python data science ecosystem. When working with NumPy arrays, you’re going to need to be able to perform basic data manipulation. In particular, you may need to change the “shape” of the data; you may need to change how the data are arranged in the NumPy array. … Read more
One of the cornerstones of the Python data science ecosystem is NumPy, and the foundation of NumPy is the NumPy array. That being the case, if you want to learn data science in Python, you’ll need to learn how to work with NumPy arrays. In this blog post, I’ll explain the essentials of NumPy arrays, … Read more
If you want to master data science in R, you need to master foundational tools like the mutate() function. Readers here at the Sharp Sight blog will know how much we emphasize “foundational” data science skills. If you want to be effective as a junior data scientist, you need to master the fundamental skills. If … Read more
In this blog post, I’ll show you how to rename columns in R. This is pretty straightforward if you know how to do it properly, but there are also some little challenges in renaming variables. So very briefly, I’ll explain why renaming variables in a dataframe can be a little confusing in R. Then, I’ll … Read more
If you want to be a data scientist, you need to master core data manipulation tools. One particular skill you’ll need to master is string manipulation. You need to be able to work with strings (i.e. character data) in order to clean, modify, or reshape them. In this blog post, you’ll learn one specific string … Read more