> If you want more advanced distribution plots beyond a simple histogram, have a look at the seaborn [gallery](https://seaborn.pydata.org/examples/index.html) to see if they have what you want.
> If you want more advanced distribution plots beyond a simple histogram, have a look at the seaborn [gallery](https://seaborn.pydata.org/examples/index.html) for (too?) many options.
### Adding error bars
If your data is not completely perfect and has for some obscure reason some uncertainty associated with it,
plt.text(0.5, 0.5, 'middle of the plot', transform=plt.gca().transAxes, ha='center', va='center')
plt.annotate("line crossing", (1, -1), (0.8, -0.8), arrowprops={}) # adds both text and arrow; need to set the arrowprops keyword for the arrow to be plotted
```
By default the locations of the arrows and text will be in data coordinates (i.e., whatever is on the axes),
however you can change that. For example to find the middle of the plot in the last example we use
...
...
@@ -171,10 +173,10 @@ To prettify this plots, we first need to know what all the features are called:
Based on this plot let's figure out what our first command of `plt.plot([1, 2, 3], [1.3, 4.2, 3.1])`
actually does:
1. First it creates a figure and makes this the active figure. Being the active figure means that any subsequent commands will affect figure. You can find the active figure at any point by calling `plt.gcf()`.
2. Then it creates an Axes or Subplot in the figure and makes this the active axes. Any subsequent commands will reuse this active axes. You can find the active axes at any point by calling `plt.gca()`.
3. Finally it creates a Line2D artist containing the x-coordinates `[1, 2, 3]` and `[1.3, 4.2, 3.1]` ands adds this to the active axes.
4. At some later time, when actually creating the plot, matplotlib will also automatically determine for you a default range for the x-axis and y-axis and where the ticks should be.
1. First it creates a figure and makes this the active figure. Being the active figure means that any subsequent commands will affect figure. You can find the active figure at any point by calling `plt.gcf()`.
2. Then it creates an Axes or Subplot in the figure and makes this the active axes. Any subsequent commands will reuse this active axes. You can find the active axes at any point by calling `plt.gca()`.
3. Finally it creates a Line2D artist containing the x-coordinates `[1, 2, 3]` and `[1.3, 4.2, 3.1]` ands adds this to the active axes.
4. At some later time, when actually creating the plot, matplotlib will also automatically determine for you a default range for the x-axis and y-axis and where the ticks should be.
This concept of an "active" figure and "active" axes can be very helpful with a single plot, it can quickly get very confusing when you have multiple sub-plots within a figure or even multiple figures.
In that case we want to be more explicit about what sub-plot we want to add the artist to.
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...
@@ -219,18 +221,14 @@ The returned `axes` object is in this case a 2x2 array of `Axes` objects, to whi
> Seaborn is great for creating grids of closely related plots. Before you spent a lot of time implementing your own have a look if seaborn already has what you want on their [gallery](https://seaborn.pydata.org/examples/index.html)
### Adjusting plot layout
The default layout of sub-plots is usually good enough, however sometimes you will need some extra space to the plot to accomodate your large axes labels and ticks or you want to get rid of some of the whitespace.
The default layout of sub-plots often leads to overlap between the labels/titles of the various subplots (as above) or to excessive amounts of whitespace in between. We can often fix this by just adding `fig.tight_layout` (or `plt.tight_layout`) after making the plot:
fig.set_suptitle("group of plots, where each row shares the x-axis and each column the y-axis")
fig.subplots_adjust(width=0, height=0, top=0.9)
fig.suptitle("group of plots, sharing x- and y-axes")
fig.subplots_adjust(wspace=0, hspace=0, top=0.9)
```
### Advanced grid configurations (GridSpec)
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...
@@ -287,39 +285,39 @@ axes.set(
> To match the matlab API and save some typing the equivalent commands in the procedural interface do not have the `set_` preset. So, they are `plt.xlabel`, `plt.ylabel`, `plt.title`. This is also true for many of the `set_` commands we will see below.
You can edit the font of the text either when setting the label or after the fact.
As an example, here are three ways to change the label colours:
You can edit the font of the text when setting the label:
```
fig, axes = plt.subplots()
axes.plot([1, 2, 3], [2.3, 4.1, 0.8])
axes.set_xlabel("xlabel", color='red') # set color when setting text label
label = axes.set_ylabel("ylabel") # keep track of the Text object returned by `set_?`
label.set_color('blue')
axes.set_title("title")
axes.get_title().set_color('green') # use `get_?` to get the Text object after the fact
axes.set_xlabel("xlabel", color='red')
axes.set_ylabel("ylabel", fontsize='larger')
```
### Editing the x- and y-axis
We can change many of the properties of the x- and y-axis by using `set_` commands.
- The range shown on an axis can be set using `ax.set_xlim` (or `plt.xlim`)
- You can switch to a logarithmic (or other) axis using `ax.set_xscale('log')`
- The location of the ticks can be set using `ax.set_xticks` (or `plt.xticks`)
- The text shown for the ticks can be set using `ax.set_xticklabels` (or as a second argument to `plt.xticks`)
- The style of the ticks can be adjusted by looping through the ticks (obtained through `ax.get_xticks` or calling `plt.xticks` without arguments).
- The range shown on an axis can be set using `ax.set_xlim` (or `plt.xlim`)
- You can switch to a logarithmic (or other) axis using `ax.set_xscale('log')`
- The location of the ticks can be set using `ax.set_xticks` (or `plt.xticks`)
- The text shown for the ticks can be set using `ax.set_xticklabels` (or as a second argument to `plt.xticks`)
- The style of the ticks can be adjusted by looping through the ticks (obtained through `ax.get_xticks` or calling `plt.xticks` without arguments).
