Text annotations are an extremely underappreciated aspect of making graphs in person. People will not be able to understand the meaning of your squiggly lines and bar graphs unless you have proper text to give them a sense of why they should care. It’s important stuff understand about people: They do not wake up in the morning hoping to see another graph!
Understanding What Your User Wants Out of the Plot
Even if they are interested in your plot overall, they want to know what this finding has to do with them. It’s a little simplistic to think that they are just rationally maximizing the utility of their decisions, as an economist we do, but people need to understand why or finding in your graph matters, and what they should do about it. It’s so easy to get lost. To get lost in your own head, where you have thought all about the implications of the findings, and various subtleties that you can easily forget that you have not properly communicated. That is why it is critical to include information in text form on your grass, so the people see what, why the results are important. They will not be able to make those, unless they’ve been working with you throughout. The analysis project.
Using Text To Multiply Impact
Another value of having text when you’re at love you too to the booth more than one insight on a single ground. Perhaps there is one major story, but also another minor story on the exact same graph. You can get double the value out of your work if you make it clear what all of the interesting tidbits on the graph are. For example, you may be primarily focusing on the overall upward trend over the course of several years, but it might be worth highlighting that the month of December always comes up as people try to close out the year strong, or perhaps that there is a diverging trend for a sunset of the sample. All of these things, Which wouldn’t fit into the headline of the graph, can make for great meditation right there along the lines and dots.
But how do you create these text meditations in the graphics self? It turned out to be just as easy as putting dots or bars in the first place. You simply need to specify the x-coordinate, the y-coordinate, and the text but you were still plates. The X and Y coordinates it should be specified exactly like data points, so for example if you have a time series graph, then you need to specify the text location in terms of a date. If you have a bar graph, with category labels, remember that the location on the graph is still defined by integers, still count counting 0123 etc. The text will start at the point that you specify, and extend us to the right. You can specify all aspects of the text font, including size, bold, italic, coloring, and even on silent. I have an experiment to deeply with with the array of fonts for available, but you should be a little bit careful because different computers seem to have different fonts sets that you can use. I would choose a common one, and stick with it. This is generally good design advice, to have at most two different fonts in any given document.
Setting Matplotlib Attributes for Text Annotations
You can set all of these attributes for text. Text around the graph as well. The title, of course will often be your largest, and boldest text. One thing but can be useful if to remember that this could be dynamically such. I find that readers often want to have both a graph, and a 1 foot and take away that they can summarize the findings with. You can often be valuable to have this one settings within the graph itself, often if the title. Specifying the X and Y axis labels is also good practice, even if it is a little rude. But not too much room for creativity here, but (even if you feel like it should be obvious) it makes things much easier for your reader. I find that it often looks nice to italicize the X and Y axis labels, and make them a little bit smaller. The other place it might make sense to have labeling is if you are doing some plots, you can have a overall able to describe the setting and fuck you hard journey together. It helps the reader understand how each of the plots supports the story, both individually and as a group. It can be extremely valuable to helping guide the reader through your process in this potential a complex situation. Just don’t forget to give all of the text plenty of spacing, and make the overall title noticeably larger than the title to the individual subparts, or else we can it’s confusing what is referring to what. Adequate spacing is really critical for all of us, because it’s easy to confuse me you were as to what you’re referring to what
At the corner of your thinking around facing text on your grass needs to be the understanding that in the course of your analysis, you spend a lot of time coming to a deeper realization about what the data represents, and your reader has not necessarily spend nearly as much time thinking about what the data means, or even what they hope to get out of it. You need to carefully guide the reader from where they are (I miss can get complex when you have readers who are coming from very different backgrounds) to where they need to be. Additionally, you need to help them avoid any mistakes of reasoning that a person might have upon first glance. A common issue would be correlation versus causation, thinking that because two things are arriving together, one of them is causing the other. With all of the subtle little things, it can be easy to forget how little your reader knows!