# Xtralien Scientific Python: Plotting with matplotlib

In Python you typically plot data using the `matplotlib`

library. This tutorial shows you how to make a simple plot and customise it for presentation.

## Your first plot

`matplotlib`

is a library that allows for easy plotting of data in Python.

```
x = [1, 2, 3, 4, 5]
y = [3, 5, 7, 8, 9]
figure()
plot(x, y)
show()
```

Note:

`figure()`

and`show()`

are optional in the Xtralien Scientific Python, however they are recommended as they are explicit and can show you where your figure starts and ends.

The above example shows the most common plot, the line plot. the `plot`

function takes a list of x values, and a list of y values. These two lists should be equal in length as they will be matched to each other when plotting, e.g. `(1, 3)`

, `(2, 5)`

.

The `figure`

function defines the start of a new figure

By default the plot will extend to the beginning and end of the plot.

## Multiple plots

Sometimes it is useful to plot multiple lines on a graph to compare series of data. Because `matplotlib`

stores previous graphs until you clear the figure (using `clf`

), it is possible to plot multiple graphs on the same figure by repeating the `plot`

command.

```
# x values
x = [1, 2, 3, 4, 5]
# First y series
y1 = [1, 2, 3, 4, 5]
# Second y series
y2 = [1, 4, 9, 16, 25]
# Plot everything
figure()
plot(x, y1)
plot(x, y2)
show()
```

The code above will produce a plot with two lines for each of the different plots. These are different colours to easily differentiate the two.

Note: The x does not need to be shared as the graph will expand to fit the largest plot. However the x and y lists for each indiviual

`plot`

need to be the same size.

## Customising your plot

It is possible to further customise your plot to make it easier to interpret, or to stylise your results.

#### Adding a title

Adding a title is useful when creating figures that you plan to publish, or simply to explain at a glance what the plot shows. The function that `matplotlib`

contains to do this is `title`

. To use `title`

you just pass the string you wish to use as the title.

```
x = [1, 2, 3, 4, 5]
y = [3, 5, 7, 8, 9]
figure()
plot(x, y)
title("2x + 1")
show()
```

#### Adding axis labels

To add a label to an axis you can use the `xlabel`

and `ylabel`

functions in `matplotlib`

. These will add a labels to each relevant axis. Both of these functions take a string that will be used as the relevant axis label.

```
x = [1, 2, 3, 4, 5]
y = [3, 5, 7, 9, 11]
figure()
plot(x, y)
xlabel('x')
ylabel('y')
show()
```

#### Adding a grid

To add a grid in `matplotlib`

you simply need to use the `grid`

function. This function takes two optional arguments, `major`

and `minor`

, which refer to the major and minor gridlines respectively.

By default `major`

is `True`

and `minor`

is `False`

, resulting in a grid that shows the major gridlines.

```
x = [1, 2, 3, 4, 5]
y = [3, 5, 7, 9, 11]
figure()
plot(x, y)
grid(major=True, minor=False)
show()
```

#### Changing Scale

When plotting using `matplotlib`

most plots will either use a linear scale, or logarithmic scale. Depending on the effect that you are investigating both may be of interest.

The easiest method of changing the scale is through the use of the `xscale`

and `yscale`

functions. Both work similarily and take a string as an argument.

To change the y axis scale to linear mode you would use `yscale('linear')`

. Whereas, to change the scale to a logarithmic scale you would use `yscale('log')`

.

```
x = [1, 2, 3, 4, 5]
y = [1e1, 1e2, 1e3, 1e4, 1e5]
# Linear plot
figure()
plot(x, y)
yscale('linear')
show()
#
figure()
plot(x, y)
yscale('log')
show()
```

#### Changing axis limits

Axis limits are customisable for each plot, and can be changed by providing the minimum and maximum values for each of the limits respectively.

You can use the `xlim`

and `ylim`

functions for this purpose. An example of when you would want to do this is if you wish to focus on a specific point, such as a point of intersection between two lines.

```
# x values
x = [1, 2, 3, 4, 5]
# First y series
y1 = [1, 2, 3, 4, 5]
# Second y series
y2 = [1, 4, 9, 16, 25]
# Plot everything
figure()
plot(x, y1)
plot(x, y2)
# Set the limits
xlim(2, 3)
ylim(5, 6)
# Show the plot
show()
```

#### Creating a legend

It is possible to create a legend in `matplotlib`

by using the `legend`

function. This function creates a legend in a corner of the plot.

To label this legend you need to supply a `label`

to every `plot`

that you create. `label`

is a string, and will appear next to the line in the legend.

```
# x values
x = [1, 2, 3, 4, 5]
# First y series
y1 = [1, 2, 3, 4, 5]
# Second y series
y2 = [1, 4, 9, 16, 25]
# Plot everything
figure()
plot(x, y1, label="2x + 1")
plot(x, y2, label="x*x")
show()
```