ways to customize points on scatter plot matplotlib

Ways to customize points on scatter plot matplotlib code#

This means that if we want a marker to have area 5, we must write s=5**2. In plt.scatter(), the default marker size is s=72. The s keyword argument controls the size of markers in plt.scatter(). We can fix this by changing the marker size. Its hard to see the relationship in the $10-$30 total bill range. This looks nice but the markers are quite large.

Ways to customize points on scatter plot matplotlib code#

To save space, we wont include the label or title code from now on, but make sure you do. plt.scatter(total_bill, tip)plt.title('Total Bill vs Tip')plt.xlabel('Total Bill ($)')plt.ylabel('Tip ($)')plt.show() Lets add some axis labels and a title to make our scatter plot easier to understand. They tell us more about the plot and is it essential you include them on every plot you make. So we should try and get our customers to spend as much as possible. This means that as the bill increases, so does the tip. Nice! It looks like there is a positive correlation between a total_bill and tip. A scatter graph shows what happens to the dependent variable ( y) when we change the independent variable ( x). We call the former the independent variable and the latter the dependent variable. First, we pass the x-axis variable, then the y-axis one. Its very easy to do in matplotlib - use the plt.scatter() function. Lets make a scatter plot of total_bill against tip. The variables total_bill and tip are both NumPy arrays. Dont worry if you dont understand what this is just yet. The variable tips_df is a pandas DataFrame. Import matplotlib.pyplot as pltimport seaborn as sns# Optional step# Seaborn's default settings look much nicer than t()tips_df = sns.load_dataset('tips')total_bill = tips_df.total_bill.to_numpy()tip = tips_df.tip.to_numpy() Note: this dataset comes built-in as part of the seaborn library.įirst, lets import the modules well be using and load the dataset.If there are, we can use them to earn more in future. We want to see if there are any relationships between the variables. Were going to explore this data using scatter plots. In the last month, you waited 244 tables and collected data about them all. You want to make as much money as possible and so want to maximize the amount of tips. You get paid a small wage and so make most of your money through tips. Lets dive into a more advanced example next! Matplotlib Scatter Plot Example However, you may not like the style of this scatter plot. The third argument is the style of the scatter points. The second argument is the iterable of y values. The first argument is the iterable of x values. Plot the data using the plt.plot() function.import matplotlib.pyplot as pltx = y = plt.plot(x, y, 'o')plt.show() The following code shows a minimal example of creating a scatter plot in Python. Matplotlib Scatter Plot Different Colors.