I have originally used numpy function .std on my dataframe to obtain standard deviation and plot it using matplotlib. Later, I have tried making the same graph using seaborn. The two graphs looked close enough until I overlayed them and found that all error bars from seaborn are smaller - the difference being more pronounced the bigger they are. I checked in different software that the results from .std are correct and that they are also correctly plotted. What could be the source of problems (I can't seem to be able to pull out the graph source data from seaborn)?

I used this code: ax_sns = sns.barplot(x = 'name', y = column_to_plot, data=data, hue='method', capsize=0.1, ci='sd', errwidth=0.9)

PS: Some related posts with additional information:

• Different std in pandas vs numpy
• Why does numpy std() give a different result to matlab std()?