When plotting data using the matplotlib library, we need to define the accesses, we need to say how much the access limit needs to be and what size the plot needs. We had many more factors affecting the actual chart, we need to initially draw uncorrected points. And we can certainly connect them using vertical bars in examples like histograms, horizontal bars, which can be the horizontal histograms, and also we can connect them using lines. For example, if you've got a data set about a stock or the stock data set, say s&p 500 data, we initially plot the unconnected points and then we certainly connect them by light. Limits, legends and layouts. Once we have the main plot, we have some other things that we need to follow, we need to define the x and y axis limits, then we need to have the title and the labels of the plot, which is called the legends, we can assign ticks, meaning we can highlight certain specific points on the axis. We can certainly have more than a single plot set, we can have three sub plots in a single image, but we've got to adjust the size and the spacing of the plot. Access Points are the lines for noting data area boundaries. Some examples of the kind of lines the colour of the points or the lines are shown on the screen, we can certainly have dashed or double dash lines, dashed or dotted line or just a dotted lines or point or circle strangles upside down triangle like shown in the left table. We can also assign different colours to the points as shown in the right table where b suggests a blue, g such as for green, and our suggested red and many more options. These are just limited examples. There are many more options available