I have a pandas dataframe, with columns 'groupname', 'result', and 'temperature'. I've plotted a Seaborn swarmplot, where x='groupname' and y='result', which shows the results data separated into the groups.
What I also want to do is to colour the markers according to their temperature, using a colormap, so that for example the coldest are blue and hottest red.
Plotting the chart is very simple:
import pandas as pd
import seaborn as sns
import matplotlib
import matplotlib.pyplot as plt
data = {'groupname': ['G0', 'G0', 'G0', 'G0', 'G1', 'G1', 'G1'], 'shot': [1, 2, 3, 4, 1, 2, 3], 'temperature': [20, 25, 35, 10, -20, -17, -6], 'result': [10.0, 10.1, 10.5, 15.0, 15.1, 13.5, 10.5]}
df = pd.DataFrame(data)
groupname shot temperature result
0 G0 1 20 10.0
1 G0 2 25 10.1
2 G0 3 35 10.5
3 G0 4 10 15.0
4 G1 1 -20 15.1
5 G1 2 -17 13.5
6 G1 3 -6 10.5
plt.figure()
sns.stripplot(data=results, x="groupname", y="result")
plt.show()
But now I'm stuck trying to colour the points, I've tried a few things like:
sns.stripplot(data=results, x="groupname", y="result", cmap=matplotlib.cm.get_cmap('Spectral'))
which doesn't seem to do anything.
Also tried:
sns.stripplot(data=results, x="groupname", y="result", hue='temperature')
which does colour the points depending on the temperature, however the colours are random rather than mapped.
I feel like there is probably a very simple way to do this, but haven't been able to find any examples.
Ideally looking for something like:
sns.stripplot(data=results, x="groupname", y="result", colorscale='temperature')
seabornexpects the variable passed tohueto be categorical rather than continuous. See this question and its answers for more information on using color maps inseabornplots.