Dataset plot line

[DancingQuanta]

Is your feature request related to a problem? Please describe.

Dataset have one plotting method Dataset.plot.scatter. This uses matplotlb's ax.scatter which have a limited presentation configuration (eg linestyle and marker).
I have 2D X and Y data which I like to plot against each other. The DataArray.plot.line works well if I only use a 1D X data.

Describe the solution you'd like

A new plotting method Dataset.plot.line based on matplotlib's ax.plot which will allow me to plot 2D X and Y against each other with flexible presentation configuration. In other to be able to produce 1D lines, this must demand a required 3D dimension as an argument (eg a choice of hue, col or others).

I suspect that as increase in number of dimensions from 1D to 2D for both variables and later to ND, there will be many ways to interpret the arguments given to the plotting function,. However, the fact the method name is line in indicate that it must produce 1D lines, and use other dimensions to create other features such as legend or subplots.

Having seen the code for the Dataset.plot.scatter I am keen to submit a PR to add Dataset.plot.line.

[dcherian]

Sounds good to me.

cc @mathause @yohai

[mathause]

To be sure - you want to get the x-values from one DataArray and the y-values from another? Similarly to http://xarray.pydata.org/en/stable/plotting.html#datasets but drawing lines instead of scatterpoints?

Sounds reasonable but may be a bit more difficult than scatter because you cannot just flatten your array (I think):

xarray/xarray/plot/dataset_plot.py

Lines 435 to 437 in 1be777f

	ax.scatter(
	data["x"].where(mask, drop=True).values.flatten(),
	data["y"].where(mask, drop=True).values.flatten(),

[yohai]

Sounds good. Just to mention that it might be easy to implement by stacking the arrays using .to_array and then just using DataArray.plot.line.

[DancingQuanta]

To give a bit more context, an example code simulating an experimental measurement.

import numpy as np
import xarray as xr
from scipy.stats import norm
from matplotlib import pyplot as plt

# nominal x
x = xr.DataArray(np.arange(-10, 10, 0.1), dims='index', name='x')

# Shift loc
loc = xr.DataArray(np.arange(-0.5, 1, 0.5), dims='loc', name='loc')

# Number of experiments
exp = xr.DataArray(range(3), dims='exp', name='exp')

# Add noise to x per experiment
noise = xr.DataArray(np.random.rand(len(x), len(loc)),
                     coords={'loc': loc},
                     dims=['index', 'loc'])
x = x + noise * 0.5

# Measure
y = xr.apply_ufunc(
        norm.pdf, x, x['loc'], 1,
        input_core_dims=[['index'], [], []],
        output_core_dims=[['index']],
        vectorize=True
    )

# Name
x.name = 'x'
y.name = 'y'

# Merge
data = xr.merge([x, y])

I wish to be able to use this

# Plot y against x
data.plot.line(x='x', y='y', hue='loc')

However, the closest I could get is with only y

y.plot.line(x='index', hue='loc')

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