Agfdhyk

So I'm doing an assignment on Jupyter Notebook using pandas.

The point is to adjust a DF column that contains degree info on personnel. I need to replace degrees entrys(strings) with numbers. (1 = Highschool, 2 = Techinical, 3 = Graduate, 4 = Post-Graduate)

import numpy as np

import pandas as pd

pd.set_option('display.max_columns', None)

pd.set_option('display.max_rows', None)



formacao = pd.read_csv("bases/formacao.csv")

formacao['grau'] = formacao.degree

formacao.grau.fillna(0, inplace=True)

formacao.loc[formacao.grau.str.contains('Tecnico|Curso T|Technical|Técnico|Technician|Minor|Technologist',case=False,na=False)] = 2

formacao.loc[formacao.grau.str.contains('Undergraduate|High School|Ensino Médio|Ensino Medio|Cursando|Under graduate',case=False,na=False)] = 1

formacao.loc[formacao.grau.str.contains('Bachelor|Bacharel|Licenciatura|B.S.|College|Engenheiro|Engenharia|Graduate|Ciencia|Ciência|Science|Graduação',case=False,na=False)] = 3

formacao.loc[formacao.grau.str.contains('Master|MBA|Mestrado|Pós|Post|Especialista|Specialist|Specialization|Especialização',case=False,na=False)] = 4

formacao.grau.unique()

That is my code, the problem is that sometimes it works. Sometimes it doesn't. I used this exact code earlier and got all the results not yet covered. Then started adding new strings and I got this error:

AttributeError: Can only use .str accessor with string values, which use np.object_ dtype in pandas

I closed jupyter and it works again. I change a single letter, and the same error.
Now, I know this makes no sense, but I can't deliver the assignment like that. Not only because it isn't done, but also, how can I know if the teacher will be able to run the code.
What can possibly be wrong?

Here is the full traceback:

---------------------------------------------------------------------------

AttributeError                            Traceback (most recent call last)

<ipython-input-12-4bad11236a95> in <module>

      1 formacao['grau'] = formacao.degree

      2 formacao.grau.fillna(0, inplace=True)

----> 3 formacao.loc[formacao.grau.str.contains('Tecnico|Curso T|Technical|Técnico|Technician|Minor|Technologist',case=False,na=False)] = 2

      4 formacao.loc[formacao.grau.str.contains('Undergraduate|High School|Ensino Médio|Ensino Medio|Cursando|Under graduate',case=False,na=False)] = 1

      5 formacao.loc[formacao.grau.str.contains('Bachelor|Bacharel|Licenciatura|B.S.|College|Engenheiro|Engenharia|Graduate|Ciencia|Ciência|Science|Graduação',case=False,na=False)] = 3



c:usersuserappdatalocalprogramspythonpython36libsite-packagespandascoregeneric.py in __getattr__(self, name)

   4370         if (name in self._internal_names_set or name in self._metadata or

   4371                 name in self._accessors):

-> 4372             return object.__getattribute__(self, name)

   4373         else:

   4374             if self._info_axis._can_hold_identifiers_and_holds_name(name):



c:usersuserappdatalocalprogramspythonpython36libsite-packagespandascoreaccessor.py in __get__(self, obj, cls)

    131             # we're accessing the attribute of the class, i.e., Dataset.geo

    132             return self._accessor

--> 133         accessor_obj = self._accessor(obj)

    134         # Replace the property with the accessor object. Inspired by:

    135         # http://www.pydanny.com/cached-property.html



c:usersuserappdatalocalprogramspythonpython36libsite-packagespandascorestrings.py in __init__(self, data)

   1893 

   1894     def __init__(self, data):

-> 1895         self._validate(data)

   1896         self._is_categorical = is_categorical_dtype(data)

   1897 



c:usersuserappdatalocalprogramspythonpython36libsite-packagespandascorestrings.py in _validate(data)

   1915             # (instead of test for object dtype), but that isn't practical for

   1916             # performance reasons until we have a str dtype (GH 9343)

-> 1917             raise AttributeError("Can only use .str accessor with string "

   1918                                  "values, which use np.object_ dtype in "

   1919                                  "pandas")