Log-log lmplot with seaborn

Question

Can Seaborn's `lmplot` plot on log-log scale? This is lmplot with linear axes: ``` 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) ``` ![sns.lmplot('x', 'y', df2)][2] [2]: https://i.stack.imgur.com/FXbtg.png

Accepted Answer

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")
```

Log-log lmplot with seaborn

Solution

Problem