Whether you are already used to working with scii or handling this format for the first time, editing it should not seem like a challenge. Different formats might require particular software to open and modify them effectively. However, if you need to quickly remove attribute in scii as a part of your usual process, it is best to find a document multitool that allows for all types of such operations without the need of additional effort.
Try DocHub for streamlined editing of scii and other document formats. Our platform offers easy papers processing regardless of how much or little previous experience you have. With tools you have to work in any format, you won’t have to jump between editing windows when working with each of your documents. Effortlessly create, edit, annotate and share your documents to save time on minor editing tasks. You will just need to register a new DocHub account, and then you can start your work instantly.
See an improvement in document processing efficiency with DocHub’s simple feature set. Edit any document easily and quickly, regardless of its format. Enjoy all the benefits that come from our platform’s simplicity and convenience.
in this video we are going to look at how we can use z-score and standard deviation to remove outliers from your data set we will be using a real data set from Cagle comm and remove outliers using z-score and three standard deviation in the end well have an interesting exercise for you to work upon we will be using weight and height data set from giggle thanks Mustafa Ali for providing this data set this data set has height and weight to columns is basically the weight and height of different people and just to make things simple I have a remove weight from that data set and my CSV file looks something like this you can see that it has 10,000 records in it and Im gonna load that into my Jupiter notebook so here I imported a couple of important modules and then I imported the data set into a pond as data frame it looks something like this and the first thing Im going to do now is plot a histogram just to understand the data distribution so the histogram will look something like this