26 lines
1.2 KiB
Python
26 lines
1.2 KiB
Python
#!/usr/bin/env python
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import pandas as pd
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import numpy as np
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links_p_nom = pd.read_html('https://en.wikipedia.org/wiki/List_of_HVDC_projects', header=0, match="SwePol")[0]
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def extract_coordinates(s):
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regex = (r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(N|S) "
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r"(\d{1,2})°(\d{1,2})′(\d{1,2})″(E|W)")
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e = s.str.extract(regex, expand=True)
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lat = (e[0].astype(float) + (e[1].astype(float) + e[2].astype(float)/60.)/60.)*e[3].map({'N': +1., 'S': -1.})
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lon = (e[4].astype(float) + (e[5].astype(float) + e[6].astype(float)/60.)/60.)*e[7].map({'E': +1., 'W': -1.})
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return lon, lat
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m_b = links_p_nom["Power (MW)"].str.contains('x').fillna(False)
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def multiply(s): return s.str[0].astype(float) * s.str[1].astype(float)
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links_p_nom.loc[m_b, "Power (MW)"] = links_p_nom.loc[m_b, "Power (MW)"].str.split('x').pipe(multiply)
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links_p_nom["Power (MW)"] = links_p_nom["Power (MW)"].str.extract("[-/]?([\d.]+)", expand=False).astype(float)
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links_p_nom['x1'], links_p_nom['y1'] = extract_coordinates(links_p_nom['Converterstation 1'])
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links_p_nom['x2'], links_p_nom['y2'] = extract_coordinates(links_p_nom['Converterstation 2'])
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links_p_nom.dropna(subset=['x1', 'y1', 'x2', 'y2']).to_csv(snakemake.output[0], index=False)
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