Simple line plots using seaborn

Question

I'm trying to plot a ROC curve using seaborn (python). With matplotlib I simply use the function plot:

plt.plot(one_minus_specificity, sensitivity, 'bs--')

where one_minus_specificity and sensitivity are two lists of paired values.

Is there a simple counterparts of the plot function in seaborn? I had a look at the gallery but I didn't find any straightforward method.

Answer 1

Since seaborn also uses matplotlib to do its plotting you can easily combine the two. If you only want to adopt the styling of seaborn the set_style function should get you started:

import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns

sns.set_style("darkgrid")
plt.plot(np.cumsum(np.random.randn(1000,1)))
plt.show()

Result:

Answer 2

Yes, you can do the same in Seaborn directly. This is done with tsplot() which allows either a single array as input, or two arrays where the other is 'time' i.e. x-axis.

import seaborn as sns

data =  [1,5,3,2,6] * 20
time = range(100)

sns.tsplot(data, time)

Answer 3

It's possible to get this done using seaborn.lineplot() but it involves some additional work of converting numpy arrays to pandas dataframe. Here's a complete example:

# imports
import seaborn as sns
import numpy as np
import pandas as pd

# inputs
In [41]: num = np.array([1, 2, 3, 4, 5])
In [42]: sqr = np.array([1, 4, 9, 16, 25])

# convert to pandas dataframe
In [43]: d = {'num': num, 'sqr': sqr}
In [44]: pdnumsqr = pd.DataFrame(d)

# plot using lineplot
In [45]: sns.set(style='darkgrid')
In [46]: sns.lineplot(x='num', y='sqr', data=pdnumsqr)
Out[46]: <matplotlib.axes._subplots.AxesSubplot at 0x7f583c05d0b8>

And we get the following plot:

Answer 4

import matplotlib.pyplot as plt
import seaborn as sns

sns.set()
plt.plot(one_minus_specificity, sensitivity) # x,y