I was trying to plot a line plot using pandas plot method, the same data with exactly same method runs fine if I use matplotlib methods, however if I use df.plot
then annotate gives me error ValueError: Missing category information for StrCategoryConverter; this might be caused by unintendedly mixing categorical and numeric data
Say I have a dataframe,
data = {'Unit': {0: 'Admin ', 1: 'C-Level', 2: 'Engineering', 3: 'IT', 4: 'Manufacturing', 5: 'Sales'}, 'Mean': {0: 4.642857142857143, 1: 4.83, 2: 4.048, 3: 4.237317073170732, 4: 4.184319526627219, 5: 3.9904545454545453}}
result=pd.DataFrame(data)
When using matplotlib
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(18,9))
ax.plot(results['Unit'],results['Mean'])
for i, val in enumerate(zip(results['Unit'],results['Mean'])):
label = str(results.loc[i, 'Mean'])
ax.annotate(label, val, ha='center')
plt.show()
The above code works perfectly fine.
Using pandas plot function(which gives me error)
results.plot(x = 'Unit', y = 'Mean', marker = 'o', figsize=(8,5))
ax = plt.gca()
for i, val in enumerate(zip(results['Unit'],results['Mean'])):
label = str(results.loc[i, 'Mean'])
ax.annotate(label, val, ha='center')
plt.show()
which gives me error :
Traceback (most recent call last):
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\axis.py", line 1506, in convert_units
ret = self.converter.convert(x, self.units, self)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\category.py", line 49, in convert
raise ValueError(
ValueError: Missing category information for StrCategoryConverter; this might be caused by unintendedly mixing categorical and numeric data
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\backends\backend_qt.py", line 477, in _draw_idle
self.draw()
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\backends\backend_agg.py", line 436, in draw
self.figure.draw(self.renderer)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\artist.py", line 73, in draw_wrapper
result = draw(artist, renderer, *args, **kwargs)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\artist.py", line 50, in draw_wrapper
return draw(artist, renderer)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\figure.py", line 2837, in draw
mimage._draw_list_compositing_images(
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\image.py", line 132, in _draw_list_compositing_images
a.draw(renderer)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\artist.py", line 50, in draw_wrapper
return draw(artist, renderer)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\axes\_base.py", line 3091, in draw
mimage._draw_list_compositing_images(
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\image.py", line 132, in _draw_list_compositing_images
a.draw(renderer)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\artist.py", line 50, in draw_wrapper
return draw(artist, renderer)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\text.py", line 1969, in draw
if not self.get_visible() or not self._check_xy(renderer):
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\text.py", line 1559, in _check_xy
xy_pixel = self._get_position_xy(renderer)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\text.py", line 1552, in _get_position_xy
return self._get_xy(renderer, x, y, self.xycoords)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\text.py", line 1419, in _get_xy
x = float(self.convert_xunits(x))
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\artist.py", line 252, in convert_xunits
return ax.xaxis.convert_units(x)
File "C:\Users\hpoddar\AppData\Local\Programs\Python\Python310\lib\site-packages\matplotlib\axis.py", line 1508, in convert_units
raise munits.ConversionError('Failed to convert value(s) to axis '
matplotlib.units.ConversionError: Failed to convert value(s) to axis units: 'Admin '
Expected output :
Annotated graph
Why am I getting error in case of pandas plot, and how can I resolve the same
CodePudding user response:
matplotlib.axes.Axes.annotate()
takes parameter xy
as below:
xy(float, float)
The point (x, y) to annotate. The coordinate system is determined by xycoords.
Therefore to fix the issue you could create a tuple that has (i, val[1])
rather than pass val
which would contain string type.
ax = results.plot(x = 'Unit', y = 'Mean', marker = 'o', figsize=(8,5))
for i, val in enumerate(zip(results['Unit'],results['Mean'])):
label = str(results.loc[i, 'Mean'])
ax.annotate(text=label, xy=(i, val[1]), ha='center')
Another option is to use matplotlib.axes.Axes.text()
:
ax = results.plot(x = 'Unit', y = 'Mean', marker = 'o', figsize=(8,5))
for i, val in enumerate(zip(results['Unit'],results['Mean'])):
label = str(results.loc[i, 'Mean'])
ax.text(x=i, y=val[1], s=label, ha='center')
As you noted, when we call annotate()
after matplotlib.axes.Axes.plot
there is no ConversionError
. But if we call annotate()
after pandas.DataFrame.plot
there is a ConversionError
.
My best guess is that after using matplotlib to plot there will be no conversion on annotate. But with a pandas plot a conversion will be attempted. This could be due to the representation of the x-ticks being different for both cases.
To demonstrate, if we try the following code the same error will be thrown:
fig, ax = plt.subplots(figsize=(18,9))
# Call annotate without plotting! Throws ConversionError
# ax.plot(results['Unit'],results['Mean'])
for i, val in enumerate(zip(results['Unit'],results['Mean'])):
label = str(results.loc[i, 'Mean'])
ax.annotate(label, val, ha='center')
Whereas if we do the following, no error will be thrown:
fig, ax = plt.subplots(figsize=(18,9))
# Call annotate without plotting! No error
# ax.plot(results['Unit'],results['Mean'])
for i, val in enumerate(zip(results['Unit'],results['Mean'])):
label = str(results.loc[i, 'Mean'])
ax.annotate(text=label, xy=(i, val[1]), ha='center')