Kil.Th - 10 months ago 76

Python 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

Answer Source

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 takes the `xAlt`

array and converts it into hour:minute format and replaces the x-axis ticks on your figure. Below is a modified version of your example - does this produce the kind of result you want?

```
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)]})
xAlt=[i for i in range(10)] #we will plot using this array, but use
#my_formatter below to make the x-tick
#labels correspond to df['x']
def my_formatter(x, pos):
"""Convert scalar into hour:minute according to recipe used to create df['x']"""
t = todayTime+datetime.timedelta(hours=x)
val_str = '{0}:{1}'.format(t.hour,t.minute)
return val_str
major_formatter=FuncFormatter(my_formatter)
fig, ax = plt.subplots()
ax.xaxis.set_major_formatter(major_formatter)
ax.scatter(xAlt,df['y'],s=20,c=df['z'], marker = 'o', cmap = cm.jet )
plt.show()
```