python - scatter plot with dates and 3rd variable as color

Question

I am trying to plot an x-y plot, with x or y as date variable, and using a 3rd variable to color the points. I managed to do it if none of the 3 variables are date, using:

ax.scatter(df['x'],df['y'],s=20,c=df['z'], marker = 'o', cmap = cm.jet )

After searching, I find out that for normal plot, we have to use plot_date(). Unfortunately, I haven't been able to color the points. Can anybody help me?

Here is a small example:

import matplotlib, datetime
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import pandas as pd

todayTime=datetime.datetime.now();
df = pd.DataFrame({'x': [todayTime+datetime.timedelta(hours=i) for i in range(10)], 'y': range(10),'z' : [2*j for j in range(10)]});
xAlt=[0.5*i for i in range(10)];

fig, ax = plt.subplots()
ax.scatter(df['x'],df['y'],s=20,c=df['z'], marker = 'o', cmap = cm.jet )
plt.show()

You can replace df['x'] by xAlt to see the desired result

Thank you

Angus Williams · Accepted Answer · 2016-09-21 13:18:25Z

2

As far as I know, one has to use scatter in order to color the points as you describe. One workaround could be to use a FuncFormatter to convert the tick labels into times on the x-axis. The code below converts the dates into numbers, makes the scatter plot, and uses a FuncFormatter to convert the tick labels back into dates.

import matplotlib, datetime
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import pandas as pd
from matplotlib.ticker import FuncFormatter

todayTime=datetime.datetime.now()
df = pd.DataFrame({'x': [todayTime+datetime.timedelta(hours=i) for i in  range(10)], 'y': range(10),'z' : [2*j for j in range(10)]})

def my_formatter(x, pos=None):
    d = matplotlib.dates.num2date(x)
    if len(str(d.minute)) == 1:
        mn = '0{}'.format(d.minute)
    else:
        mn = str(d.minute)
    if len(str(d.hour)) == 1:
        hr = '0{}'.format(d.hour)
    else:
        hr = str(d.hour)
    return hr+':'+mn

major_formatter=FuncFormatter(my_formatter)

nums = np.array([matplotlib.dates.date2num(di) for di in df['x']])

fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(major_formatter)
ax.scatter(nums,df['y'],s=20,c=df['z'], marker = 'o', cmap = cm.jet )
xmin = df['x'][0]-datetime.timedelta(hours=1)
xmax = df['x'][len(df['x'])-1]+datetime.timedelta(hours=1)
ax.set_xlim((xmin,xmax))
plt.show()

edited Sep 21, 2016 at 13:18

answered Sep 21, 2016 at 9:33

Angus Williams

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7 Comments

Kil.Th Over a year ago

Thank you for your answer. Unfortunately, this is not what I am expecting. It already works for xAlt. I would like to do: ax.scatter(df['x'],df['y'],s=20,c=df['z'], marker = 'o', cmap = cm.jet )

Angus Williams Over a year ago

The point is to plot using xAlt, but then to convert xAlt -> df['x'] in the x-ticks by using the my_formatter function. This should produce a plot with times on the x-axis and with points colored by a third array. Did you try running the code snippet above? You cannot use scatter and df['x'], so you need to use a workaround like the one I suggested.

Kil.Th Over a year ago

Ok I got it! Thank you very much

Angus Williams Over a year ago

Great - no problem. I'd be appreciative if you accepted my answer if it solved your problem.

Angus Williams Over a year ago

Ok the example I give should work for any list of times (presuming you want hour:minute as the format, but this could easily be changed)

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