Reputation: 3852
I have some dataframe:
Date_Week Game_Order Game_Mode
0 2010-04-13 124 a
1 2010-06-29 7 a
2 2009-03-17 40 b
3 2010-08-03 54 a
4 2009-09-29 20 e
5 2009-07-07 13 b
6 2009-04-07 29 a
7 2010-03-30 37 b
8 2010-04-13 118 a
9 2010-07-13 12 b
10 2011-08-23 38 c
11 2009-06-02 96 a
12 2010-03-16 48 a
13 2010-08-10 18 b
14 2010-11-09 1 c
where the Date_Week
column is a datetime timestamp:
dft['Date_Week'][0]
Out[1043]: Timestamp('2010-04-13 00:00:00')
I am plotting this with the pandas plot_date()
function.
import matplotlib.pyplot as plt
import seaborn as sns
import matplotlib as mpl
fig, ax = plt.subplots(figsize=(22,8))
ax.plot_date(dft['Date_Week'], dft['Game_Order'], marker='o', markersize=2, mew=2)
ax.tick_params('y', colors='k')
ax.set_xlabel('Date')
ax.set_ylabel('Frequency')
ax.set_title('Weekly Games')
ax.tick_params('y', colors='k')
ax.grid(b=True, which='major', color='w', linewidth=1.0)
ax.grid(b=True, which='minor', color='w', linewidth=0.5)
ax.yaxis.grid(True)
xtick_locator = mpl.dates.MonthLocator(interval=6)
xtick_formatter = mpl.dates.AutoDateFormatter(xtick_locator)
ax.xaxis.set_major_locator(xtick_locator)
ax.xaxis.set_major_formatter(xtick_formatter)
xtick_locator = mpl.dates.MonthLocator(bymonth=[2,3,4,5,6,8,9,10,11,12], interval=1)
xtick_formatter = mpl.dates.AutoDateFormatter(xtick_locator)
ax.xaxis.set_minor_locator(xtick_locator)
ax.xaxis.set_minor_formatter(xtick_formatter)
plt.setp(ax.xaxis.get_minorticklabels(), rotation=90, size=10)
plt.setp(ax.xaxis.get_majorticklabels(), rotation=90, size=15)
fig.subplots_adjust(bottom=0.24)
plt.legend()
plt.show()
This gives:
I would like to colour the points based on the category in the Game_Mode
column.
I did some research and found this question, this question, this question andthis.
Based on this I tried each of the following: Mapping a float, seaborn RGB color palette values, or specific colour to a colour column, based on the category:
# Colouring
categories = dft['Game_Mode'].unique()
# Possible Way 1
colors = np.linspace(0, 1, len(categories))
colordict = dict(zip(categories, colors))
# Possible Way 2
colors = sns.color_palette()
colordict_1 = dict(zip(categories, colors))
# Possible Way 3
colors = ['r', 'g', 'b', 'c' ,'k']
colordict_2 = dict(zip(categories, colors))
dft["Colour"] = dft['Game_Mode'].apply(lambda x: colordict[x])
dft["Colour_1"] = dft['Game_Mode'].apply(lambda x: colordict_1[x])
dft["Colour_2"] = dft['Game_Mode'].apply(lambda x: colordict_2[x])
dft
Date_Week Game_Order Game_Mode Colour \
0 2010-04-13 124 a 0.000000
1 2010-06-29 7 a 0.000000
2 2009-03-17 40 b 0.333333
3 2010-08-03 54 a 0.000000
4 2009-09-29 20 e 0.666667
5 2009-07-07 13 b 0.333333
6 2009-04-07 29 a 0.000000
7 2010-03-30 37 b 0.333333
8 2010-04-13 118 a 0.000000
9 2010-07-13 12 b 0.333333
10 2011-08-23 38 c 1.000000
11 2009-06-02 96 a 0.000000
12 2010-03-16 48 a 0.000000
13 2010-08-10 18 b 0.333333
14 2010-11-09 1 c 1.000000
Colour_1 Colour_2
0 (0.298039215686, 0.447058823529, 0.690196078431) r
1 (0.298039215686, 0.447058823529, 0.690196078431) r
2 (0.333333333333, 0.658823529412, 0.407843137255) g
3 (0.298039215686, 0.447058823529, 0.690196078431) r
4 (0.76862745098, 0.305882352941, 0.321568627451) b
5 (0.333333333333, 0.658823529412, 0.407843137255) g
6 (0.298039215686, 0.447058823529, 0.690196078431) r
7 (0.333333333333, 0.658823529412, 0.407843137255) g
8 (0.298039215686, 0.447058823529, 0.690196078431) r
9 (0.333333333333, 0.658823529412, 0.407843137255) g
10 (0.505882352941, 0.447058823529, 0.698039215686) c
11 (0.298039215686, 0.447058823529, 0.690196078431) r
12 (0.298039215686, 0.447058823529, 0.690196078431) r
13 (0.333333333333, 0.658823529412, 0.407843137255) g
14 (0.505882352941, 0.447058823529, 0.698039215686) c
However, when I try to plot, using any of the Colour
columns, I get the following errors:
0:
# Colour error
fig, ax = plt.subplots(figsize=(22,8))
ax.plot_date(dft['Date_Week'], dft['Game_Order'], marker='o', markersize=2, mew=2, c=dft['Colour'])
Out[1058]: [<matplotlib.lines.Line2D at 0x289091d0>]Traceback (most recent call last):
File "path\Anaconda3\lib\site-packages\IPython\core\formatters.py", line 307, in __call__
return printer(obj)
File "C:\Users\p\Anaconda3\lib\site-packages\IPython\core\pylabtools.py", line 240, in <lambda>
png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
File "C:\Users\p\Anaconda3\lib\site-packages\IPython\core\pylabtools.py", line 124, in print_figure
fig.canvas.print_figure(bytes_io, **kw)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\backend_bases.py", line 2200, in print_figure
**kwargs)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py", line 545, in print_png
FigureCanvasAgg.draw(self)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py", line 464, in draw
self.figure.draw(self.renderer)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\artist.py", line 63, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\figure.py", line 1144, in draw
renderer, self, dsu, self.suppressComposite)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\image.py", line 139, in _draw_list_compositing_images
a.draw(renderer)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\artist.py", line 63, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\axes\_base.py", line 2426, in draw
mimage._draw_list_compositing_images(renderer, self, dsu)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\image.py", line 139, in _draw_list_compositing_images
a.draw(renderer)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\artist.py", line 63, in draw_wrapper
draw(artist, renderer, *args, **kwargs)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\lines.py", line 828, in draw
rgbaFace = self._get_rgba_face()
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\lines.py", line 1340, in _get_rgba_face
rgbaFace = mcolors.to_rgba(facecolor, self._alpha)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\colors.py", line 143, in to_rgba
rgba = _to_rgba_no_colorcycle(c, alpha)
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\colors.py", line 198, in _to_rgba_no_colorcycle
raise ValueError("RGBA sequence should have length 3 or 4")
ValueError: RGBA sequence should have length 3 or 4
<matplotlib.figure.Figure at 0x2c4705c0>
1
# Colour_1 error:
...
File "C:\Users\p\Anaconda3\lib\site-packages\matplotlib\colors.py", line 194, in _to_rgba_no_colorcycle
raise ValueError("Invalid RGBA argument: {!r}".format(orig_c))
ValueError: Invalid RGBA argument: 0 (0.298039215686, 0.447058823529, 0.690196078431)
2
# Colour 2 error:
...
File "C:\Users\p\Anaconda3\lib\site-packages\pandas\core\generic.py", line 2970, in __getattr__
return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'lower'
<matplotlib.figure.Figure at 0x29ec9dd8>
I have searched these errors and come up with the following issues:
https://github.com/matplotlib/matplotlib/issues/7603 https://github.com/matplotlib/matplotlib/issues/6266/ https://github.com/matplotlib/matplotlib/issues/2148 Setting colors using color cycle on date plots using `plot_date()`
These indicate this could be something to do with plot_date
but none of the suggested options have worked.
Can anyone tell me how I can solve this?
Upvotes: 2
Views: 1159
Reputation: 3852
For Elsa Li's benefit:
Based on @ImportanceOfBeingErnest 's answer, I had to do individual plots for each game type and game order.
I had to expand the way I created the game order column to, instead of doing a global order
calculate the order for each sub-type of game. This meant having to create new columns "Game_Order_a"
"Game_order_b"
etc. which had values only for rows corresponding to that game_mode
, and were NaN
everywhere else (i.e. only has values for the particular game type).
Then, this meant plotting individually a subset of data and letting Seaborn
manually assign colours. These colours were picked up by legend handler:
So, for 5 different Game_Mode
's I did this:
fig, ax = plt.subplots()
# Subset your data by choosing where Game_Mode = 'a'
ax.plot_date(df[df['Game_Mode'] == 'a']['Date_Week_a'], df[df['Game_Mode'] == 'a']['Game_Order_a'], marker='o', markersize=2, mew=2, label='a')
ax.plot_date(df[df['Game_Mode'] == 'b']['Date_Week_b'], df[df['Game_Mode'] == 'b']['Game_Order_b'], marker='o', markersize=2, mew=2, label='b')
# ... etc for each type that you have
plt.legend(fontsize=15, markerscale=4)
plt.show()
This gives you a plot for each type, with colours auto chosen. You can specify them if you like using the c=
argument, but was not necessary for me.
Upvotes: 2