如何将Matplotlib中季节子图调整为时间先后顺序排列？

我有一个包含4个不同站点基于季节和年份的平均浓度的DataFrame，编写的代码为每个站点生成一张图，每个季节对应一个子图，年份为x轴、浓度为y轴。当前代码自动生成的子图排列顺序为：

• fall - spring
• summer - winter

希望将其调整为时间先后顺序：

• spring - summer
• fall - winter

以下是原代码：

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import statsmodels.formula.api as smf
import scipy.stats

main_dataframe = pd.read_csv('NOx_sznl.csv')
main_dataframe.rename(columns={'NOx_3168':'Banning NOx', 'NOx_2199':'Palm Springs NOx', 'NOx_2551':'El Centro NOx', 'NOx_3135':'Calexico NOx'}, inplace=True)

col = list(main_dataframe.columns)
col.remove('Year')
col.remove('Season')

for ind,station in enumerate(col):
    
        df_new = main_dataframe[['Season', 'Year', col[ind]]]
###here I tried to reorder the seasons in the dataframe
        df_new = df_new.set_index('Season')
        df_new = df_new.loc[['Spring', 'Summer', 'Fall', 'Winter'], :]
        df_new = df_new.reset_index()
###but it didn't change the outcome
        df_new = df_new.set_index('Year')
        
        # df_new['Betty Jo Mcneece Receiving Home'].astype('float')
        df_new[col[ind]] = df_new[col[ind]]        


        grouped = df_new.groupby('Season')
        
        rowlength = grouped.ngroups/2                         # fix up if odd number of groups
        fig, axs = plt.subplots(figsize=(15,10), 
                                nrows=2, ncols=int(rowlength),     # fix as above
                                gridspec_kw=dict(hspace=0.4))#, sharex='col', sharey='row') # Much control of gridspec

        targets = zip(grouped.groups.keys(), axs.flatten())
        for i, (key, ax) in enumerate(targets):
            ax.plot(grouped.get_group(key)[col[ind]], marker='o', color='orange')
            ax.set_ylim(0,)
            ax.set_yticks(ax.get_yticks(),size=12)
            #ax.set_xlim(2009,2020)
            ax.set_xticks(np.arange(2009,2020,1))
            ax.set_xticklabels(ax.get_xticks(), rotation = 45, size=12)
        fig.suptitle("%s"%col[ind], fontsize=30)    
#         ax.set_title('%s')
        plt.subplot(221)
        plt.gca().set_title('Fall', fontsize=20)
        plt.subplot(222)
        plt.gca().set_title('Spring', fontsize=20)
        plt.subplot(223)
        plt.gca().set_title('Summer', fontsize=20)
        plt.subplot(224)
        plt.gca().set_title('Winter', fontsize=20)
        plt.show()

问题核心是groupby('Season')默认按字母顺序分组，且手动设置子图标题的逻辑和期望顺序不符。需主动指定季节的遍历顺序，替代默认排序逻辑。

关键修改点： #

1. 定义时间顺序的季节列表：season_order = ['Spring', 'Summer', 'Fall', 'Winter']
2. 将Season列转为有序分类类型，确保数据分组和排序都遵循指定顺序
3. 直接按自定义季节列表遍历，匹配子图并动态设置标题，避免手动指定标题的顺序错误

修改后的完整代码： #

import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import statsmodels.formula.api as smf
import scipy.stats

main_dataframe = pd.read_csv('NOx_sznl.csv')
main_dataframe.rename(columns={'NOx_3168':'Banning NOx', 'NOx_2199':'Palm Springs NOx', 'NOx_2551':'El Centro NOx', 'NOx_3135':'Calexico NOx'}, inplace=True)

col = list(main_dataframe.columns)
col.remove('Year')
col.remove('Season')

# 定义时间顺序的季节列表
season_order = ['Spring', 'Summer', 'Fall', 'Winter']

for ind, station in enumerate(col):
    df_new = main_dataframe[['Season', 'Year', col[ind]]]
    
    # 将Season设为有序分类，确保分组和排序遵循指定顺序
    df_new['Season'] = pd.Categorical(df_new['Season'], categories=season_order, ordered=True)
    df_new = df_new.sort_values('Season')
    
    df_new = df_new.set_index('Year')
    grouped = df_new.groupby('Season')
    
    rowlength = grouped.ngroups // 2
    fig, axs = plt.subplots(figsize=(15,10), 
                            nrows=2, ncols=int(rowlength),
                            gridspec_kw=dict(hspace=0.4))

    # 按自定义季节顺序遍历，匹配子图并设置标题
    for season, ax in zip(season_order, axs.flatten()):
        group_data = grouped.get_group(season)[col[ind]]
        ax.plot(group_data, marker='o', color='orange')
        ax.set_ylim(0,)
        ax.set_yticks(ax.get_yticks(), size=12)
        ax.set_xticks(np.arange(2009,2020,1))
        ax.set_xticklabels(ax.get_xticks(), rotation=45, size=12)
        ax.set_title(season, fontsize=20)
    
    fig.suptitle(col[ind], fontsize=30)
    plt.show()

内容的提问来源于stack exchange，提问作者obscuredbyclouds