箱线图中添加的垂直线与 x 轴不匹配

Question

我想每 24 X 间隔在箱线图 seaborn 上添加垂直线。

我的功能：

def BoxPlot(data,x_attrib, y_attrib, showfliers=False, orient='h', *args):

    sns.set(style="whitegrid", palette="Set3", context='talk', color_codes=False) #défaut
    
    fig, ax = plt.subplots(1,1,figsize=(20,5)) 
    ax = sns.boxplot(x=x_attrib, y=y_attrib, data=data, showfliers = showfliers, orient=orient, palette='Dark2', ax=ax) #palette="Set2")    
    
    list_diff_hours = np.sort(data[x_attrib].astype(int).unique())
    print(list_diff_hours)
    for i in list_diff_hours:
      if (i % 24 == 0):
        print(f"""Add line x={i}""")
        ax.axvline(x = i, color = 'b', label = '12')

    ax.set(title=args[0])
    ax.set(xlabel=args[1]) # idem ax.set(xlabel=None)
    ax.set(ylabel=args[2])

    #ax.set(xticklabels=[])  # remove labels from x axis
    ax.tick_params(bottom=False)  # remove the ticks
        
    # Show the plot
    plt.show()

我用以下方法绘制了n条垂直线：

我的问题是 data['x_attrib'] 不连续：

    DIFF_HOURS  DIFF_TEMP
0   0.0     0.050886
1   1.0     0.660698
2   2.0     1.656014
3   3.0     2.543857
4   4.0     3.071813
...     ...     ...
627770  336.0   -7.524095
627771  339.0   -4.180723
627772  342.0   -8.724546
627773  345.0   -10.176562
627774  348.0   -8.047641

627775 rows × 2 columns

函数执行：

[  0   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17
  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35
  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53
  54  55  56  57  58  59  60  61  62  63  64  65  66  67  68  69  70  71
  72  73  74  75  76  77  78  79  80  81  82  83  84  85  86  87  88  89
  90  91  92  93  94  95  96  97  98  99 100 101 102 103 104 105 106 107
 108 109 110 111 112 113 114 115 116 117 118 119 123 126 129 132 135 138
 141 144 147 150 153 156 159 162 165 168 171 174 177 180 183 186 189 192
 195 198 201 204 207 210 213 216 219 222 225 228 231 234 237 240 243 246
 249 252 255 258 261 264 267 270 273 276 279 282 285 288 291 294 297 300
 303 306 309 312 315 318 321 324 327 330 333 336 339 342 345 348 351 354
 357]
Add line x=0
Add line x=24
Add line x=48
Add line x=72
Add line x=96
Add line x=144
Add line x=168
Add line x=192
Add line x=216
Add line x=240
Add line x=264
Add line x=288
Add line x=312
Add line x=336

最后一个 X 箱线图值之后不应该有线条。我不明白。

调用函数：

path = '/xxx'
data2boxplot = pd.read_csv(os.path.join(path, 'merged2_limited.csv'), sep=';')

BoxPlot(data2boxplot,       
        'DIFF_HOURS',
        'DIFF_TEMP', 
        False,
        'v',
        '',        
        '',
        '')

另外如何在每行的 x 轴上放置标签？

样本数据

DIFF_HOURS,DIFF_TEMP
0.0,0.0508860903513017
1.0,0.6606980150309028
2.0,1.6560138915914993
3.0,2.543856665504201
4.0,3.071813181144403
5.0,1.8228499885861
6.0,-1.0648394742460994
7.0,-2.488141151430004
8.0,-3.367705894714298
9.0,-3.672485488901201
10.0,-2.965489148744801
11.0,-3.054565515742897
12.0,-2.0708812793241016
13.0,-0.7613814777512964
14.0,0.2020813798845964
15.0,0.3136517751847023
16.0,0.7578654959031006
17.0,1.796600153839602
18.0,1.3360555256778
19.0,0.5195588315561004
20.0,-0.1587534779601007
21.0,-0.3501035240801009
22.0,-0.7686862284051017
23.0,-0.4259603228679971
24.0,0.636230830620697
25.0,0.8782201238649989
26.0,0.8752404883571039
27.0,0.9896782693150996
28.0,1.4808193880072018
29.0,1.359074500951401
30.0,0.1090185745514986
31.0,-0.1983728888428011
32.0,-1.2747932083237998
33.0,0.3264950295098004
34.0,1.5323613807559011
35.0,0.6369611820368988
36.0,-0.1668353314066024
37.0,-0.4585072776349008
38.0,-0.7295583937719954
39.0,-0.6062539959064956
40.0,0.5665020058765045
41.0,1.0616182067213984
42.0,1.8872550413563007
43.0,1.915382734552498
44.0,1.0471410630142015
45.0,0.8662996625566991
46.0,1.2746546032826949
47.0,1.0679496294792017
48.0,0.977680775822602
0.0,0.9481029455852016
1.0,2.1050969347580017
2.0,3.2760407873637014
3.0,4.344428893295703
4.0,4.901783099360504
5.0,3.696887332163403
6.0,0.1667104898304003
7.0,-2.371896438511804
8.0,-4.2627128900091975
9.0,-5.002792798693502
10.0,-5.2455918994013
11.0,-3.780849468299799
12.0,-1.0769181236025034
13.0,0.222992037187403
14.0,0.3435438092772962
15.0,0.8102643110400045
16.0,1.4313979808253023
17.0,2.3581243639427005
18.0,2.477428665879401
19.0,1.8329917112030003
20.0,1.533774692003398
21.0,1.5107766037682993
22.0,0.9821263738569002
23.0,0.9859066714612011
24.0,1.5215579940998971
25.0,1.4286036097316988
26.0,1.4520266307993026
27.0,1.5522584243467
28.0,2.2495906999692004
29.0,2.2265263619725
30.0,0.736071352020101
31.0,0.0544039530452984
32.0,-1.6178014448367009
33.0,-0.6747283502522983
34.0,0.0745035742702988
35.0,-1.3139941917547022
36.0,-2.166329466286101
37.0,-1.8654762187255969
38.0,-0.9528454300361986
39.0,0.2444552716616002
40.0,0.3638052974010044
41.0,0.6938993599382997
42.0,1.6715946531027015
43.0,2.2912391124936
44.0,1.9091871864761991
45.0,1.6538121525740976
46.0,1.871403680868596
47.0,1.8755397730923036
48.0,1.683526230989102
49.0,3.9257324576676993
50.0,4.2606635532902
51.0,3.547404399117198
52.0,3.5442721882085984
53.0,2.0273757348208967
54.0,0.9674114895829008
55.0,0.4955297870016011
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57.0,0.291238747112402
58.0,0.0919498398644016
59.0,-0.2344818522044001
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61.0,-1.3347805797921986
62.0,-1.085802560345197
63.0,-1.1364933815099008
64.0,1.6930235479636018
65.0,3.1144047645493984
66.0,3.0742791475726
67.0,2.5129622649698007
68.0,3.9519612202572993
69.0,3.424352795620901
70.0,3.6924282332803
71.0,3.9638111547679
72.0,3.928898849589199
73.0,4.3853295811086
74.0,4.497082965096396
75.0,4.996047910204702
76.0,5.192069417326497
77.0,3.967237413111
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85.0,-1.9432349456607056
86.0,-0.3325606119583
87.0,0.3767153699817029
88.0,2.5923976945151
89.0,2.6999498567612967
90.0,3.6577365981003993
91.0,3.819267929856804
92.0,4.2311134009189
93.0,3.8719392524307
94.0,4.112123045242598
95.0,3.5670466428843
96.0,3.707961014061997
97.0,3.3575633147774973
98.0,2.609527103988804
99.0,2.6393175591536
100.0,2.841210257546596
101.0,1.9100548192853035
102.0,-0.9261718909340964
1.0,-1.3538390543185983
2.0,-0.4993995934072011
3.0,0.3545493177938006
4.0,0.8099865903292027
5.0,-0.0506968341322
6.0,-0.6804032287808006
7.0,-0.2082854185232037
8.0,0.1630975835187023
9.0,1.3459815168519995
10.0,0.8188580444433953
11.0,1.2689348507551017
12.0,2.5538855454437983
13.0,3.0004117809216027
14.0,2.5512122750664936
15.0,2.405389571822603
16.0,2.191629812401601
17.0,2.2951491862325
18.0,1.2686938279479032
19.0,-2.0014185726731
20.0,-2.6544771602099004
21.0,-2.633052784155602
22.0,-3.092243465084401
23.0,-2.937052744408298
24.0,-2.0957011820857008
25.0,-2.3233501028976
26.0,-2.3927692215934973
27.0,-2.512657772196601
28.0,-1.7964380456293014
29.0,-1.7847067206928993
30.0,-0.2526341077528009
31.0,1.5703263586214966
32.0,1.4113320887482992
33.0,2.9538918436626
34.0,4.0837719685110985
35.0,3.1727485835231017
36.0,1.9205350337043043
37.0,0.8241595096379015
38.0,0.0327764865730984
39.0,0.4453579476395007
40.0,0.0302729352231025
41.0,-0.5416959697029
42.0,-1.340051189759798
43.0,-3.1358167635487004
44.0,-3.659751635387998
45.0,-3.0855913898442995
46.0,-3.200745120168304
47.0,-2.7721319693662
48.0,-2.7245163840206
49.0,-0.3698256650070988
50.0,0.3255698682053989
51.0,0.171604221326298
52.0,0.5237634028585987
53.0,-0.9555386881921032
54.0,-1.1099254073318008
55.0,-1.0289337447369995
56.0,0.0710421633454991
57.0,1.8551764454929007
58.0,3.3021008765933004
59.0,4.493103892326103
60.0,4.459707548881899
61.0,3.8100320431610015
62.0,2.70771353528
63.0,1.811856686758496
64.0,3.1732643515642
65.0,2.7837551373168985
66.0,0.6481714824083014
67.0,-1.5360733736842
68.0,0.2581648129808975
69.0,0.0466600478800991
70.0,0.3247838415439972
71.0,0.480818944133901
72.0,0.3697571191573985
73.0,0.7756447728369977
74.0,0.6264768722090963
75.0,0.5598319716264015
76.0,0.5475730464813999
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78.0,-1.5219718889375002
79.0,-0.8823618347315012
80.0,0.3616040380187009
81.0,1.4167763945443037
82.0,2.2441204477612047
83.0,2.2022495423586013
84.0,1.816157556111598
85.0,2.9791984000074905
86.0,3.256299154099601
87.0,2.2553796714922
88.0,3.0085705007726986
89.0,1.5769306424971958
90.0,0.8768902546595996
91.0,-0.7117263891153982
92.0,-0.3782886285789999
93.0,-0.1900556523495993
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95.0,-0.4954602383545996
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100.0,-0.8343423884402021
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104.0,-0.5267064568487996
105.0,0.3055101751269973
106.0,0.8410028019703972
107.0,0.0563780428751954
108.0,0.3206620074736008
109.0,2.1680835552511013
110.0,0.7204345807845058
111.0,1.0092727386892049
112.0,1.5859000383682975
113.0,2.400175965303301
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116.0,-1.6965739903897976
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118.0,-2.216906436912499
119.0,-2.2461669675342013
123.0,-3.5438322357964016
126.0,-2.634330549200701
129.0,3.1095237582866986
132.0,7.574655737394298
135.0,2.0845096505009018
138.0,-0.7407272283859001
141.0,-1.3589556692384015
144.0,-3.1358191915115974
147.0,-0.3873845281203962
150.0,-0.5938085200652985
153.0,0.3747979208253973
156.0,3.5077837934555016
159.0,0.8830075640103026
162.0,-0.6721012052772011
165.0,-3.1283774896485
168.0,-1.567625477271296
171.0,-0.4029477457177997
174.0,-1.2982829966962974
177.0,-0.4720358919086998
180.0,5.048419824699401
189.0,-2.1594860545862
195.0,0.9763107957826024
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204.0,-2.6355890021463964
207.0,-2.185078189591998
210.0,-1.0333854681407004
213.0,-1.3780712108308997
216.0,-2.042565978695201
219.0,-1.1856517905460002
222.0,-2.3636010060555
225.0,-2.2247376450717984
228.0,-1.9685004380312991
231.0,0.9751352549206942
234.0,-0.0051869832737025
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246.0,-1.6687987582940984
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Answer 1

如果您这样做
```
ax.get_xticks()
```
，您会发现只有 198 个
```
xticks
```
。唯一的
```
DIFF_HOURS
```
从 0 到 357，但箱线图是按 xtick 位置而不是 xtick 标签绘制的。
- ```
xticks
```
  的数量将对应于唯一的
```
hours
```
  的数量，因此可以为
```
hours
```
  创建布尔掩码并用于获取相应的
```
xticks
```
  ，然后用于绘制垂直线。
请参阅此答案并查看有关条形图和直方图的部分，这对于箱线图来说是相同的。此外，如答案所示，使用
```
ax.vlines
```
无需使用 for 循环。
- ```
ax.vlines(x=vlines, ymin=ymin, ymax=ymax, color='b', zorder=1)
```
  设置垂直线的
```
zorder
```
  。

已在
python 3.10
、
pandas 1.3.5
、
matplotlib 3.5.1
、
seaborn 0.11.2

更新功能

def BoxPlot(data, x_attrib, y_attrib, showfliers=False, orient='h', *args):

    sns.set(style="whitegrid", palette="Set3", context='talk', color_codes=False) #défaut
    
    fig, ax = plt.subplots(figsize=(25, 5)) 
    ax = sns.boxplot(x=x_attrib, y=y_attrib, data=data, showfliers=showfliers, orient=orient, palette='Dark2', ax=ax) #palette="Set2")    
    
    # get the xticks
    xticks = ax.get_xticks()
    
    # get the unique values for DIFF_HOURS
    hours = np.sort(df.DIFF_HOURS.unique().astype(int))
    
    # create a Boolean mask
    mask = hours % 24 == 0
    
    # Use mask to get the xticks corresponding to True
    vlines = xticks[mask]
    
    # get y min and max from the plot
    ymin, ymax = ax.get_ylim()
    
    # set the y margins to 0
    ax.margins(y=0)
    
    # add the vertical lines
    ax.vlines(x=vlines, ymin=ymin, ymax=ymax, color='b')

    ax.set(title=args[0])
    ax.set(xlabel=args[1]) # idem ax.set(xlabel=None)
    ax.set(ylabel=args[2])

    # remove the xticks
    ax.tick_params(bottom=False)

    # remove xticks and format labels - if desired
    # ax.tick_params(bottom=False, axis='x', rotation=90, labelsize=8)

    # use the masked ticks and labels to only label at the vertical lines
    ax.set_xticks(ticks=vlines, labels=hours[mask], fontsize=10)

    # Show the plot
    plt.show()

函数调用

path = 'd:/data/merged2_limited.csv'

df = pd.read_csv(path, sep=';')

BoxPlot(df,       
        'DIFF_HOURS',
        'DIFF_TEMP', 
        False,
        'v',
        '',        
        '',
        '')

与所有 xticklabel 交替

箱线图中添加的垂直线与 x 轴不匹配

问题描述投票：0回答：1

样本数据

1个回答

更新功能

函数调用

最新问题

箱线图中添加的垂直线与 x 轴不匹配

问题描述 投票：0回答：1

样本数据

1个回答

更新功能

函数调用

最新问题

问题描述投票：0回答：1