After installing pypfopt and u-numpy, dataframe.info() command shows this error.
TypeError: Cannot interpret '<attribute 'dtype' of 'numpy.generic' objects>' as a data type
I happened to mix my versions and I encountered the problem today. I managed to fix it. Both codes in jupyter gave me an error: TypeError: Cannot interpret '<attribute 'dtype' of 'numpy.generic' objects>' as a data type
df.info()
df.categorical_column_name.value_counts().plot.bar()
I got the error: TypeError: Cannot interpret '<attribute 'dtype' of 'numpy.generic' objects>' as a data type
This is how i fixed it
Inside jupyter: Check numpy version:
import numpy as np
print(np.__version__)
To upgrade:
!pip3 install numpy --upgrade
Inside Command line check numpy version: python
import numpy
print(numpy.__version__)
if versions are not the same choose whether to upgrade/downgrade: To upgrade:
$pip install numpy --upgrade
To downgrade just specify the version
If you have python environment installed: Go to the right folder: Check the installed version:
$pipenv --version
To verify if you have a pip environment installed for that folder: On your terminal Go to the folder and type:
$pipenv --version
If there is a pipenv it will show the version and if there is none it won't.
check numpy version
$python
>>> import numpy
#prints the version
>>> print(numpy__version__)
To upgrade the version:
>>>exit()
#To install the latest version don't specify the version
$pipenv install numpy
#if you want to downgrade specify the version
$pipenv install numpy=version_type
Do the same for pandas. Note that with pandas if your pandas environment is 1.2.3 on the jupyter notebook upgrade with !pip install pandas==1.2.3 or just !pip install pandas --upgrade --user.
Note that if the commands are giving you an error always include --user at the end of the command.
To create a new environment using miniconda and install updated packages follow the link [https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html][1]
Run the following commands from a terminal window:
conda create -n name_of_my_env python
This will create a minimal environment with only Python installed in it. To put your self inside this environment run:source activate name_of_my_env
On Windows the command is:
2. activate name_of_my_env
The final step required is to install pandas. This can be done with the following command:
conda install pandas
To install a specific pandas version:
conda install pandas=0.20.3I prefer using the latest version of pandas 1.2.3
However the first method should solve your problem. Always restart your notebook by closing and reopening it.
I will stick around to see if you are winning. But this will resolve your problem. The problem is caused by the versions of numpy and pandas [1]: https://pandas.pydata.org/pandas-docs/stable/getting_started/install.html