TypeError in categorical factorplot on Python 3.4

It appears that the use of factorplot for categorical data is broken under Python 3.4 and NumPy 1.10. Using an example from the user’s guide:

import seaborn as sb
titanic = sb.load_dataset("titanic")
sb.factorplot("class", data=titanic, palette="PuBuGn_d");

results in the following:

/usr/local/Cellar/python3/3.4.2_1/Frameworks/Python.framework/Versions/3.4/lib/python3.4/site-packages/numpy-1.10.0.dev_fb898ce-py3.4-macosx-10.10-x86_64.egg/numpy/core/_methods.py in _mean(a, axis, dtype, out, keepdims)
     71         ret = ret.dtype.type(ret / rcount)
     72     else:
---> 73         ret = ret / rcount
     74 
     75     return ret

TypeError: unsupported operand type(s) for /: 'str' and 'int'

Running Seaborn 0.6.dev on OS X 10.10.3.

[mwaskom]

This was part of the updates to categorical plots for 0.6 (by the way this is not well-advertised but the development version is documented here). Because the plots can be drawn horizontally or vertically, you now have to specify kind="count" in factorplot (or use the axes-level countplot function) rather than not passing a quantitative variable.

[minalb24]

Thanks for help…code is working fine 👍

levels=[] # empty list

for level in deck: levels.append(level[0]) # append first letter of data

cabin_df=DataFrame(levels)

cabin_df.columns=[‘Cabin’] # set column =Cabin

sns.factorplot(‘Cabin’,data=cabin_df,palette=‘winter_d’,kind=“count”) # Plot data

cabin_df=cabin_df[cabin_df.Cabin!=‘T’] sns.factorplot(‘Cabin’,data=cabin_df,palette=‘summer’,kind=“count”)