将employmentLength文本转换为数字

def solve():
    from pyodide.http import open_url
    from io import StringIO
    loans_raw_csv = open_url("https://data.zuihe.com/dbd/riskctrl/state_02/loans_raw.csv").read()
    loans_clean_csv = open_url("https://data.zuihe.com/dbd/riskctrl/state_02/loans_clean.csv").read()
    import pandas as pd, re
    from io import StringIO
    df = pd.read_csv(StringIO(loans_raw_csv))
    def parse_emp(v):
        v=str(v)
        if v=='nan': return 5
        if '<' in v: return 0
        if '10+' in v: return 10
        m=re.search(r'(\d+)',v)
        return int(m.group(1)) if m else 5
    df['emp_num'] = df['employmentLength'].apply(parse_emp)
    print(df['emp_num'].value_counts().sort_index().to_string())