displot(kind='ecdf',..., log_scale=True) not working
See original GitHub issueThe following line of code gives an error:
sns.displot(kind='ecdf', data=df, x='col_1', log_scale=True)
UserWarning: Data has no positive values, and therefore cannot be log-scaled.
My data is all positive and kind=‘hist’ or ‘kde’ works just fine.
Issue Analytics
- State:
- Created 3 years ago
- Comments:10 (4 by maintainers)
Top Results From Across the Web
seaborn's displot: two edcf, 1 figure [duplicate] - Stack Overflow
Strange problem with getting unique output in bash.
Read more >seaborn.displot — seaborn 0.12.1 documentation - PyData |
Either a pair of values that set the normalization range in data units or an object that will map from data units into...
Read more >Plotting with seaborn | by keshav | Analytics Vidhya - Medium
Displot. This function provides access to several approaches for visualizing the univariate or bivariate distribution of data, ...
Read more >Seaborn Version 0.11.0 is here with displot, histplot and ecdfplot
Let us make ecdf plot using displot() using kind=”ecdf”. Here we make ecdf plot of a variable and color it based on values...
Read more >[seaborn Basic]displot usage - Kaggle
(with kind="ecdf"; univariate-only). Additionally, a ... sns.displot(data=penguins, x="flipper_length_mm", kind="ecdf"). Out[6]:. <seaborn.axisgrid.
Read more >Top Related Medium Post
No results found
Top Related StackOverflow Question
No results found
Troubleshoot Live Code
Lightrun enables developers to add logs, metrics and snapshots to live code - no restarts or redeploys required.
Start FreeTop Related Reddit Thread
No results found
Top Related Hackernoon Post
No results found
Top Related Tweet
No results found
Top Related Dev.to Post
No results found
Top Related Hashnode Post
No results found
Top GitHub Comments
Actually, I think there is a bigger problem. Even with the numbers that are bigger it doesn’t give a reasonable cumulative distribution.
Have a look at this:
I think those plots should end up roughly the same. The upper plot is definitely wrong.
Indeed, though fortunately the result ends up being fairly obviously wrong visually, as you discovered.