Den stora tråden om global uppvärmning/växthuseffekten

def daily_mean_SLU(path):
    names = ["A", "B", "C", "D", "E", "F", "G"]
    df = pd.read_table(path, sep=",", names=names, encoding="latin")
    date_col = (df == "TIMESTAMP").any().idxmax()
    header_idx = (df.loc[:, date_col] == "TIMESTAMP").idxmax()
    temp_col = (df.loc[header_idx, :] == "TA").idxmax()
    dates = pd.to_datetime(df.loc[header_idx+1:, date_col])
    temps = df.loc[header_idx+1:, temp_col].astype("float")
    s = pd.Series(temps)
    s.index = dates
    return s


def daily_mean_SMHI(path):
    names = ["A", "B", "C", "D", "E", "F", "G"]
    df = pd.read_table(path, sep=";", names=names)
    date_col = (df == "Representativt dygn").any().idxmax()
    header_idx = (df.loc[:, date_col] == "Representativt dygn").idxmax()
    temp_col = (df.loc[header_idx, :] == "Lufttemperatur").idxmax()
    dates = pd.to_datetime(df.loc[header_idx+1:, date_col])
    temps = df.loc[header_idx+1:, temp_col].astype("float")
    s = pd.Series(temps)
    s.index = dates
    return s

def winter_start_date(s, year):
    idx = ((s.index.year == year) & (s.index.month >= 8)
           | (s.index.year == year+1) & (s.index.month < 8))
    s = s[idx]
    dates = s.index
    temps = s.to_numpy()
    for i in range(s.shape[0]-4):
        if (dates[i+4]-dates[i] == pd.Timedelta("4 d")
                and np.all(temps[i:i+5] <= 0)):
            return dates[i]
    return pd.Timestamp("nan")


def spring_start_date(s, year):
    idx = ((s.index.year == year)
           & ((s.index.month == 2) & (s.index.day >= 15)
              | (s.index.month >= 3)))
    s = s[idx]
    dates = s.index
    temps = s.to_numpy()
    for i in range(s.shape[0]-6):
        if (dates[i+6]-dates[i] == pd.Timedelta("6 d")
                and np.all(temps[i:i+7] > 0)):
            return dates[i]
    return pd.Timestamp("nan")