<jupyter_start><jupyter_text>check python packages<jupyter_code># The version of python
import sys
print('Python: {}'.format(sys.version))
# numpy
import numpy
print('numpy: {}'.format(numpy.__version__))
# scipy
import scipy
print('scipy: {}'.format(scipy.__version__))
# matplotlib
import matplotlib
print('matplotlib: {}'.format(matplotlib.__version__))
# netCDF4
import netCDF4
print('netCDF4: {}'.format(netCDF4.__version__))
# pandas
import pandas 
print('pandas: {}'.format(pandas.__version__))
# xarray
import xarray
print('xarray: {}'.format(xarray.__version__))
# scikit-learn
import sklearn 
print('sklearn: {}'.format(sklearn.__version__))<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15712187958883994, 'fraction_numerical': 0.005873715124816446, 'mean_word_length': 8.472222222222221, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '423633', 'license': 'MIT', 'n_tokens_mistral': 250, 'n_tokens_neox': 246, 'n_words': 46, 'path': 'jupyter_test/Test_python_packages.ipynb', 'repo_name': 'TomasTorsvik-work/NirdToolkit_jupyter_ns2980k', 'size': '681'}