I’m way too lazy to type in all that data everytime I run your script, so I automated that part to make development and testing of it easier. Likewise, I think the easiest thing to do would be to use the collections module’s defaultdict class to keep track of what dates have been seen and … Read more
Simply create a new object and pass the required arguments in the constructor. Point position= new Point((int) (Math.random()*(max – min)),(int) (Math.random() *(max – min))); Point endPosition = new Point(position.x+2, position.y+3);
I couldn’t quite figure out why your go.Figure turns out the way it does. But if you reshape your data from wide to long and unleash px.bar you’ll get a shorter, cleaner code and arguably a much better visual result. We can talk more details later, but you’ll find a complete snippet right after this … Read more
It turns out that the computer in question that would display the bad plot had McAfee Antivirus installed on it and this caused the issue with scanning the .exe and delaying the output of data to matplotlib. Once we added the .exe and necessary programs into the “exclusion” list, we were able to get the … Read more
Why this happens… With plot(x(i),y) you are plotting 100 single points (one in each iteration) and they are not shown by default. Therefore the plot looks empty. Solution 1: Vectorized calculation and direct plot I assume you meant to draw a continuous line. In that case no for-loop is needed because you can calculate and … Read more
Here is a small example of how it could be done using for loops with the mtcars dataset for(g in unique(mtcars$gear)) { f <- filter(mtcars, gear == g) p <- ggplot(f, aes(disp, hp)) + geom_point() ggsave(paste0(‘plot_’, g,’.jpg’), p) } In your case it would something like this for(s in unique(WQ_byStation$StationName)){ f <- filter(WQ_byStation, StationName == … Read more
The issue for your goal is your range that you create with linspace. The default number of samples is 50 for this method and they are evenly reparted so depending on your width, 2 might not be in this range. Use the num argument (third position) to increase this value and it will look better … Read more
I would suggest you next approach. If you want error bars you can compute it based on mean and standard deviation. In the next code is sketched the way to do that. I have used one standard deviation but you can set any other value. Also as you want to see different samples, I have … Read more
Why do you want to avoid Metal? Enabling its support is as easy as wrapping your LineGraphShapes into Group and modifying it with a drawingGroup(). Try it out: … Group { let gradient = LinearGradient( gradient: Gradient(colors: [Color.red, Color.blue]), startPoint: .leading, endPoint: .trailing ) LineGraphShape(points: points[selectedPointType], closePath: true) .fill(gradient) LineGraphShape(points: points[selectedPointType], closePath: false) .stroke( gradient, … Read more
There are several ways to approach controlling a matplotlib plot using ipywidgets. Below I’ve created the output I think you’re looking for using each of the options. The methods are listed in what feels like the natural order of discovery, however, I would recommend trying them in this order: 4, 2, 1, 3 Approach 1 … Read more