您可以尝试此解决方案（未提供输入df，因此无法显示结果..）

season_dict = {
    'Northern Hemisphere': {
        'Spring': [3, 4, 5],
        'Summer': [6, 7, 8],
        'Fall': [9, 10, 11],
        'Winter': [12, 1, 2]
    },
    'Southern Hemisphere': {
        'Spring': [9, 10, 11],
        'Summer': [12, 1, 2],
        'Fall': [3, 4, 5],
        'Winter': [6, 7, 8]
    }
}

# create a function to assign season based on hemisphere and month
def get_season(row):
    date = pd.to_datetime(row['Date'])
    month = date.month
    hemisphere = ''
    if row['Country'] in north_hem_list:
        hemisphere = 'Northern Hemisphere'
    elif row['Country'] in south_hem_list:
        hemisphere = 'Southern Hemisphere'
    for season, months in season_dict[hemisphere].items():
        if month in months:
            return season

# apply the function to the dataframe to create the season column
df['Season'] = df.apply(get_season, axis=1)

您可以用途：

# Sample
df = pd.DataFrame({'Code': ['AFG', 'ZWE'], 'Day': ['2020-02-24', '2023-02-01']})
df['Day'] = pd.to_datetime(df['Day'])

# Detection based on Code
north_hem_list = ['AFG']
south_hem_list = ['ZWE']

# Seasons
north_seasons = ['Winter', 'Spring', 'Summer', 'Fall']
south_seasons = ['Summer', 'Fall', 'Winter', 'Spring']

season = (df['Day'].dt.month % 12 + 3) // 3 - 1
df['Season'] = np.where(df['Code'].isin(north_hem_list),
                        np.array(north_seasons)[season],
                        np.array(south_seasons)[season])

输出：

>>> df
  Code        Day  Season
0  AFG 2020-02-24  Winter
1  ZWE 2023-02-01  Summer