By now we have covered the basics of creating a figure canvas and add axes instances to it, Let’s now focus on how we can add titles,axis labels and legends to our plots.

## Figure titles

An axes contains the method `set_title`which can be added to each axis instance in a figure.

``````ax.set_title("title");
``````

Axis labels

Similarly, for setting xlabel and ylabel we use `set_xlabel` and `set_ylabel`respectively.

``````ax.set_xlabel("x")
ax.set_ylabel("y");
``````

## Legends

We will use label = “label text” keyword when plots are added to the figure, and then we are going to call legend() method without argument for adding it to the figure.

``````fig = plt.figure()

ax.plot(x, x**2, label="x**2")
ax.plot(x, x**3, label="x**3")
ax.legend()
``````

Observe and see how the legend overlaps some of the actual plot!

We should note that the legend function takes the optional argument **loc **that is used to specify where the legend will be drawn.

See the documentation for more details

``````# We have a lot of options

ax.legend(loc=1) # upper right corner
ax.legend(loc=2) # upper left corner
ax.legend(loc=3) # lower left corner
ax.legend(loc=4) # lower right corner
# .. many more options are available
# Most common to choose
ax.legend(loc=0) # let matplotlib decide the optimal location
fig
``````

## Setting colors, linewidths, linetypes

Matplotlib provides us _a bunch _of options for customizing colors, linewidths, and linetypes. These are used to change how our plot looks.

## Colors with MatLab like syntax

Using matplotlib we will now define the color of lines in multiple ways. For eg ‘g — ’ means a green dashed line.

``````# MATLAB style line color and style
fig, ax = plt.subplots()
ax.plot(x, x**2, 'b.-') # blue line with dots
ax.plot(x, x**3, 'g--') # green dashed line
``````

## Colors with the color= parameter

Another way to define colors is by their RGB or HEX codes we can also provide alpha value to indicate the opacity.

``````fig, ax = plt.subplots()

ax.plot(x, x+1, color="blue", alpha=0.5) # half-transparant
ax.plot(x, x+2, color="#8B008B")        # RGB hex code
ax.plot(x, x+3, color="#FF8C00")        # RGB hex code
``````

#data-science #matplotlib #visualization #visual studio code

1.10 GEEK