Aesthetic mappings not consistent with ggplot2

[eduardflorinescu]

Aesthetic mappings not consistent with ggplot2 see: http://docs.ggplot2.org/0.9.3.1/geom_point.html

Steps to reproduce:

from ggplot import *
ggplot(aes(x="wt", y="mpg", color = "qsec"), data=mtcars) + \
geom_point()
plt.show(1)

Actual outcome

Expected outcome

Also using other data If I give a column with many different values("Volts" column) as an input for color I get the error at the end of this report.

Code here:
https://github.com/eduardflorinescu/ggplot/blob/master/examples/test_aestheticmappings.py
CSV here:
https://github.com/eduardflorinescu/ggplot/blob/master/examples/pandas_generated.csv

Notice that if I use the "category" column for color it works, if I use "Volts" I should get an aesthetic mapping instead I get the following error:

Traceback (most recent call last):
  File "PythonApplication5.py", line 128, in <module>
    ylab("Watts")
  File "C:\PYTHON27\lib\site-packages\ggplot\ggplot.py", line 209, in __repr__
    callbacks = geom.plot_layer(layer)
  File "C:\PYTHON27\lib\site-packages\ggplot\geoms\geom_point.py", line 21, in plot_layer
    plt.scatter(**layer)
  File "C:\PYTHON27\lib\site-packages\matplotlib\pyplot.py", line 3087, in scatter
    linewidths=linewidths, verts=verts, **kwargs)
  File "C:\PYTHON27\lib\site-packages\matplotlib\axes.py", line 6278, in scatter
    colors = mcolors.colorConverter.to_rgba_array(c, alpha)
  File "C:\PYTHON27\lib\site-packages\matplotlib\colors.py", line 380, in to_rgba_array
    "Cannot convert argument type %s to rgba array" % type(c))
ValueError: Cannot convert argument type <type 'numpy.ndarray'> to rgba array

[jankatins]

Could you add the code which produces the error (and the wrong plot)? There is non visible in the bugreport.

[eduardflorinescu]

Updated issue with the requested info.

[zachcp]

Looks like the column is being treated as a text column and not numerical so it is getting a discrete scale instead of a continuous one. i would check your pandas dataframe and see if it is using the first line as a column or if it is making the entire column into a string.

something like:
spowd = pd.read_csv(INPUT_FILE, header=TRUE)

[zachcp]

This is a mishandling of continuous color scales. The error is reproducible here:

from ggplot import *
 ggplot(diamonds, aes('carat', 'price', color='price')) + \
    geom_point(alpha=1/20.) + \
    ylim(0, 20000)

#line 334 ggplot.oy
  if 'color' in mapping._get_numeric_data().columns:
                    mapping['cmap'] = self.colormap

I don't see mapping.cmap get used again. I think the colormap needs to be put back into the mapping.color value to be picked up by ggplot.__repr__. This would require using the values held in 'mapping.color' to use the 'cmap'. I'm not sure how to do this. Is anyone familiar with matplotlib colormaps?

[zachcp]

walking through the code, I think the color mapping is fine. The color differences in python vs. R are due to an inverted scale and a legend that is displayed as quantile instead of as a continuous variable. I don't think either of those have been implemented yet in this version of ggplot. Your specific error I couldn't track down but it believe it is due to some cross talk between aes groupings. Coloring by voltage, by itse,f for example , works jsut fine. It is only when bothcolor and shape are used that there is an issue:

## Single Values: These all wor
ggplot(aes(x='TIME', y='Watts', color="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()

#Shape and Color where Color is category: These work
ggplot(aes(x='TIME', y='Watts', shape="category", color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="Volts", color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()

## Shape and Color where color is Volt. These fail
ggplot(aes(x='TIME', y='Watts', shape="category", color="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()
ggplot(aes(x='TIME', y='Watts', shape="Volts", color="Volts", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()

The plot_layer function is only being passed a single color value for the last two. Why? I'm not sure why the color values are correctly assigned in most cases but not the last two.

[eduardflorinescu]

The below case where shape="Volts" doesn't work for me:

ggplot(aes(x='TIME', y='Watts', shape="Volts", color="category", ymin=YMIN, ymax=YMAX), data=spowd) + geom_point()

gives:

Traceback (most recent call last):
  File "test_aestheticmappings.py", line 39, in <module>
    ylab("Watts")
  File "C:\PYTHON27\lib\site-packages\ggplot\ggplot.py", line 206, in __repr__
    for layer in self._get_layers(self.data):
  File "C:\PYTHON27\lib\site-packages\ggplot\ggplot.py", line 318, in _get_layers
    mapping['marker'] = mapping['shape'].replace(shape_mapping)
  File "C:\PYTHON27\lib\site-packages\pandas\core\series.py", line 2741, in replace
    _rep_dict(result, to_replace)
  File "C:\PYTHON27\lib\site-packages\pandas\core\series.py", line 2735, in _rep_dict
    _rep_one(rs, sset, d)
  File "C:\PYTHON27\lib\site-packages\pandas\core\series.py", line 2715, in _rep_one
    com._maybe_upcast_putmask(s.values,mask,v,change=change)
  File "C:\PYTHON27\lib\site-packages\pandas\core\common.py", line 813, in _maybe_upcast_putmask
    return changeit()
  File "C:\PYTHON27\lib\site-packages\pandas\core\common.py", line 767, in changeit
    om = other[mask]
TypeError: only integer arrays with one element can be converted to an index

[naught101]

Here's the same graph as above, with a more recent version of ggplot:

Main problems remaining:

• Axis ticks go right to the ends of the axis (uneccessary rounding, also makes it more likely for x/y axis ticks to clash).
• There isn't a continuous colourbar
• The default colourscheme is inverted, and the contrast is too high

Everything else is looking pretty good though :)

[eduardflorinescu]

@naught101 Thanks for updating, I think the spectrum color-bar is the greatest visual inconsistency.