can not draw barplot with x datetime axis.

[NMC-DAVE]

Hi:
Proplot is vary great package and hope to update continuously. I want to draw barplot, like the code:

import pandas as pd
import proplot as plot
df = pd.DataFrame({'a': [0,1], 'date':[pd.to_datetime('2017-04-01'), pd.to_datetime('2017-04-02')]})
f, axs = plot.subplots(ncols=1, figsize=(12, 6))
axs[0].bar(df['date'], df['a'])
axs.format(title="TEST", xlabel='x axis', ylabel='y axis',
           large=20, small=10, xlocator='year', xminorlocator='month', xformatter='%Y')

but I get the fellowing error. So did i do anything wrong. Thanks very much.

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-83-7ba278c889ae> in <module>
      2 df = pd.DataFrame({'a': [0,1], 'date':[pd.to_datetime('2017-04-01'), pd.to_datetime('2017-04-02')]})
      3 f, axs = plot.subplots(ncols=1, figsize=(12, 6))
----> 4 axs[0].bar(df['date'], df['a'])
      5 axs.format(title="TEST", xlabel='x axis', ylabel='y axis',
      6            large=20, small=10, xlocator='year', xminorlocator='month', xformatter='%Y')

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in _wrapper(self, *args, **kwargs)
   3081         @functools.wraps(func)
   3082         def _wrapper(self, *args, **kwargs):
-> 3083             return driver(self, func, *args, **kwargs)
   3084         name = func.__name__
   3085         if name not in proplot_methods:

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in bar_wrapper(self, func, x, height, width, bottom, left, vert, orientation, stacked, lw, linewidth, edgecolor, **kwargs)
   1166         linewidth=lw, edgecolor=edgecolor,
   1167         stacked=stacked, orientation=orientation,
-> 1168         **kwargs
   1169     )
   1170 

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in _wrapper(self, *args, **kwargs)
   3081         @functools.wraps(func)
   3082         def _wrapper(self, *args, **kwargs):
-> 3083             return driver(self, func, *args, **kwargs)
   3084         name = func.__name__
   3085         if name not in proplot_methods:

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in standardize_1d(self, func, *args, **kwargs)
    328     # WARNING: For some functions, e.g. boxplot and violinplot, we *require*
    329     # cycle_changer is also applied so it can strip 'x' input.
--> 330     return func(self, x, *ys, *args, **kwargs)
    331 
    332 

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in _wrapper(self, *args, **kwargs)
   3081         @functools.wraps(func)
   3082         def _wrapper(self, *args, **kwargs):
-> 3083             return driver(self, func, *args, **kwargs)
   3084         name = func.__name__
   3085         if name not in proplot_methods:

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in add_errorbars(self, func, medians, means, boxes, bars, boxdata, bardata, boxstd, barstd, boxmarker, boxmarkercolor, boxrange, barrange, boxcolor, barcolor, boxlw, barlw, capsize, boxzorder, barzorder, *args, **kwargs)
    822     else:
    823         xy = (x, iy)  # just the stats
--> 824     obj = func(self, *xy, *args, **kwargs)
    825     if not boxes and not bars:
    826         return obj

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in _wrapper(self, *args, **kwargs)
   3081         @functools.wraps(func)
   3082         def _wrapper(self, *args, **kwargs):
-> 3083             return driver(self, func, *args, **kwargs)
   3084         name = func.__name__
   3085         if name not in proplot_methods:

~/anaconda3/lib/python3.7/site-packages/proplot/wrappers.py in cycle_changer(self, func, cycle, cycle_kw, label, labels, values, legend, legend_kw, colorbar, colorbar_kw, *args, **kwargs)
   1662         if name in ('bar',):  # adjust
   1663             if not stacked:
-> 1664                 ix = x + (i - ncols / 2 + 0.5) * width / ncols
   1665             elif stacked and not is1d:
   1666                 key = 'x' if barh else 'bottom'

~/anaconda3/lib/python3.7/site-packages/pandas/core/ops/common.py in new_method(self, other)
     62         other = item_from_zerodim(other)
     63 
---> 64         return method(self, other)
     65 
     66     return new_method

~/anaconda3/lib/python3.7/site-packages/pandas/core/ops/__init__.py in wrapper(left, right)
    498         lvalues = extract_array(left, extract_numpy=True)
    499         rvalues = extract_array(right, extract_numpy=True)
--> 500         result = arithmetic_op(lvalues, rvalues, op, str_rep)
    501 
    502         return _construct_result(left, result, index=left.index, name=res_name)

~/anaconda3/lib/python3.7/site-packages/pandas/core/ops/array_ops.py in arithmetic_op(left, right, op, str_rep)
    191         #  by dispatch_to_extension_op.
    192         # Timedelta is included because numexpr will fail on it, see GH#31457
--> 193         res_values = dispatch_to_extension_op(op, lvalues, rvalues)
    194 
    195     else:

~/anaconda3/lib/python3.7/site-packages/pandas/core/ops/dispatch.py in dispatch_to_extension_op(op, left, right)
    123     # The op calls will raise TypeError if the op is not defined
    124     # on the ExtensionArray
--> 125     res_values = op(left, right)
    126     return res_values

TypeError: unsupported operand type(s) for +: 'DatetimeArray' and 'float'

[lukelbd]

Nope, you did nothing wrong; proplot overrides the bar method to add some features, but I did not account for the possibility of datetime x-coordinates (similar to PR #121). The next version will fix this. Thanks for the reports!

[lukelbd]

This is fixed in #156. It also preserves the bar-grouping capability when detecting y data with more than one column.

Here is an example with single-column data:

import proplot as plot
dates = np.arange('2000-01-01', '2000-01-10', dtype=np.datetime64)
data = np.random.rand(len(dates))
fig, axs = plot.subplots(ncols=1, width=6, aspect=2)
axs[0].bar(dates, data)
axs.format(title='Test', xlabel='x axis', ylabel='y axis')
fig.save('~/tmp/tmp.png')

And here is a multi-column example:

import proplot as plot
dates = np.arange('2000-01-01', '2000-01-10', dtype=np.datetime64)
data = np.random.rand(len(dates), 5)
cycle = plot.Cycle('magma', N=data.shape[1])
fig, axs = plot.subplots(ncols=1, width=6, aspect=2)
axs[0].bar(dates, data, cycle=cycle)
axs.format(title='Test', xlabel='x axis', ylabel='y axis')
fig.save('~/tmp/tmp.png')