CODEWITHSUNDEEP
pythonpython-3.xseaborn
quant
quant

Reputation: 4482

How to plot a line plot with confidence intervals and legend changing over x-axis in python

I have a dataframe that looks like this:

    import pandas as pd
    foo = pd.DataFrame({'time':[1,2,3,4], 'value':[2,4,6,8], 'group':['a', 'a', 'b', 'b'],
                        'top_ci':[3,5,7,9], 'bottom_ci': [1,3,5,7]})

I would like to create a lineplot, so i am using the following code:

  ax = sns.lineplot(x="time", y="value", hue="group", data=foo)
  ax.figure.savefig('test.png', bbox_inches='tight')

I would like to add a shaded area with the confidence interval, as it is defined from the top_ci and the bottom_ci columns in the foo dataframe.

Any ideas how I could do that ?

Upvotes: 0

Views: 1635

Answers (1)

Michael Mitter
Michael Mitter

Reputation: 575

The easiest way would be to provide the individual datapoints and then let sns.lineplot compute the confidence interval for you. If you want/need to do it yourself, you can use ax.fill_between:

foo = pd.DataFrame({'time':[1,2,3,4], 'value':[2,4,6,8], 'group':['a', 'a', 'b', 'b'],
                    'top_ci':[3,5,7,9], 'bottom_ci': [1,3,5,7]})


groups = set(foo["group"]) # get group levels to get the same hue order in both plots

f, ax = plt.subplots()
sbn.lineplot(x="time", y="value", hue="group", data=foo, ax=ax, hue_order=groups)
for group in groups:
    ax.fill_between(x=foo.loc[foo["group"] == group, "time"],
                    y1=foo.loc[foo["group"] == group, "bottom_ci"],
                    y2=foo.loc[foo["group"] == group, "top_ci"], alpha=0.2)
f.savefig('test15.png', bbox_inches='tight')

enter image description here

Upvotes: 1

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