“'x'必须是非空的数字向量”rpy2错误：为什么它不起作用？

Question

I am using Colab and Python to find the best fit distribution for my data. I am a newbie in this, so am experiencing a lot of problems. So far, here's my code:

from rpy2.robjects import pandas2ri
from rpy2.robjects.packages import importr

MASS = importr('MASS')
pandas2ri.activate()

df_temp = pd.DataFrame()
df_temp["Values"] = [37.50,46.79,48.30,46.04,43.40,39.25]
ri_temp = pandas2ri.py2ri(df_temp)

params_temp = MASS.fitdistr(ri_temp, 'normal')
print(params_temp)

Now, there is a lot going on that I don't understand yet. Please be as descriptive as possible!:) For instance, I am not getting the idea of why I have to use pandas2ri.activate() . The error that my code is producing is this:

/usr/local/lib/python3.6/dist-packages/rpy2/rinterface/__init__.py:146:
  RRuntimeWarning: Error in (function (x, densfun, start, ...)  : 

  'x' must be a non-empty numeric vector

... Traceback in between...

warnings.warn(x, RRuntimeWarning)
  RRuntimeError: Error in (function (x, densfun, start, ...)  : 

  'x' must be a non-empty numeric vector

So, what's the issue?

The reason I am using pandas first is that I have my data stored in a list. If I can avoid using pandas, then what would be the alternative? When I tried simply parsing MASS.fitdistr(list, 'normal') it gives me errors as well. Also, maybe there is a better alternative to using r to find the best fit distribution for a given list data? Any recommendations?

Answer 1

This helped: my_array = np.asarray(my_list) . And then using the array as my input for: params_temp = MASS.fitdistr(my_array, 'normal') .

Thanks to akrun.