<jupyter_start><jupyter_text>Germany<jupyter_code>p = plot.Plot(country_id=276)
print("Size of data set:", p._population.shape)
print("Extent of the grid:", p._img_extent)
p.plot(show=True)<jupyter_output><empty_output><jupyter_text>France<jupyter_code>p = plot.Plot(country_id=250)
print("Size of data set:", p._population.shape)
print("Extent of the grid:", p._img_extent)
p.plot(show=True)<jupyter_output><empty_output><jupyter_text>Brazil<jupyter_code>p = plot.Plot(country_id=76)
print("Size of data set:", p._population.shape)
print("Extent of the grid:", p._img_extent)
p.plot(show=True)<jupyter_output><empty_output><jupyter_text>Look up country ids by name<jupyter_code>from sedac_gpw_parser import utils
utils.id_lookup("Afri")<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.14471968709256844, 'fraction_numerical': 0.010430247718383311, 'mean_word_length': 10.815384615384616, 'pattern_counts': {'":': 0, '<': 17, '<?xml version=': 0, '>': 17, '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': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '178809', 'license': 'MIT', 'n_tokens_mistral': 315, 'n_tokens_neox': 296, 'n_words': 46, 'path': 'examples/sedac-gpw-parser examples.ipynb', 'repo_name': 'marcwie/sedac-gpw-parser', 'size': '767'}