Log-log lmplot with seaborn

Question

Can the function lmplot from Seaborn plot on a log-log scale? This is lmplot on a normal scale

import numpy as np import pandas as pd import seaborn as sns x =  10**arange(1, 10) y = 10** arange(1,10)*2 df1 = pd.DataFrame( data=y, index=x ) df2 = pd.DataFrame(data = {'x': x, 'y': y})  sns.lmplot('x', 'y', df2) 

Answer 1

If you just want to plot a simple regression, it will be easier to use seaborn.regplot. This seems to work (although I'm not sure where the y axis minor grid goes)

import numpy as np import pandas as pd import seaborn as sns import matplotlib.pyplot as plt  x = 10 ** np.arange(1, 10) y = x * 2 data = pd.DataFrame(data={'x': x, 'y': y})  f, ax = plt.subplots(figsize=(7, 7)) ax.set(xscale="log", yscale="log") sns.regplot("x", "y", data, ax=ax, scatter_kws={"s": 100}) 

If you need to use lmplot for other purposes, this is what comes to mind, but I'm not sure what's happening with the x axis ticks. If someone has ideas and it's a bug in seaborn, I'm happy to fix it:

grid = sns.lmplot('x', 'y', data, size=7, truncate=True, scatter_kws={"s": 100}) grid.set(xscale="log", yscale="log")