There exists 3 quiz/question(s) for this tutorial. Next, we can assign the plot's title with plt.title, and then we can invoke the default legend with plt.legend(). sns.scatterplot (datadf,x’G’,y’GA’) for i in range (df. This can be done by using a simple for loop to loop through the data set and add the x-coordinate, y-coordinate and string from each row. With plt.xlabel and plt.ylabel, we can assign labels to those respective axis. Labelling All Points Some situations demand labelling all the datapoints in the scatter plot especially when there are few data points. Plt.title('Interesting Graph\nCheck it out') Iterating through all rows of the original DataFrame. The addition of the labels to each or all data points happens in this line: plt.text(xrow'avgincome', yrow'happyScore', srow'country') for k,row in df.iterrows() if 'Europe' in row.region We are using Python's list comprehensions. The rest of our code: plt.xlabel('Plot Number') Add text labels to Data points in Scatterplot. Here, we plot as we've seen already, only this time we add another parameter "label." This allows us to assign a name to the line, which we can later show in the legend. This way, we have two lines that we can plot. Drawing a scatter plot when we have integer categories is simple: import matplotlib.pyplot as plt.
To start: import matplotlib.pyplot as plt A lot of times, graphs can be self-explanatory, but having a title to the graph, labels on the axis, and a legend that explains what each line is can be necessary. Assuming I have two lists of n elements called a and b, I print them this way : plt.figure() plt.grid() plt.plot(a, b, 'bo') plt.show() I want to label every point with 'Variable k' with k ranging from 1 to n obviously. In this tutorial, we're going to cover legends, titles, and labels within Matplotlib. I want to label every dot I plot in python, and I didn't find a proper way to do it.