I was working with some data. I put it into a pandas DataFrame like many data scientists. I built the DataFrame up row by row because sometimes data is not packaged nicely.

I then tried to plot the resulting data with seaborn’s regplot1 and got an nasty TypeError:

TypeError: No loop matching the specified signature and casting was found for ufunc svd_n_s

In the trace back this is coming from some deep level in numpy’s linear algebra modules. I tried both the default and robust=True so the issue was not the specific numpy routine since statsmodels also had an issue.

Finally after many attempts at searching for a solution I found this stackoverflow question with a helpful comment2. It looks like numpy’s linear algebra fails like this if they type is not a float and it prefers a float64.

I knew my DataFrame only contained numbers but I looked at it more closely. I initialed it like this:

>>> pd.DataFrame(columns=['hr', 'age'])

And after it was filled I looked at one column and noticed that it defaulted to an generic object type.

>>> plot['age']
0      11.2113
1      4.35541
...
119    3.59919
Name: age, Length: 120, dtype: object

The issue was found!

All I needed to do was change my initiation to

>>> pd.DataFrame(columns=['hr', 'age'], dtype=np.float64)

and everything worked as expected.

  1. Note that other plots did work, just nothing with a fit. ↩

  2. I am not sure why this is not an answer. But whatever. ↩