I have developed a Python Dash app, where users can select samples to perform statistical analyses on. By default, all of the samples are initially selected and the scatter graph showing the top 50 values is displayed as shown:
However, when the users select the data: the top 50 values adjust accordingly but three extra categories (with no values) are added for some reason. For example:
Here is the pls1_top_50_features dataframe when the data is selected (where those extra categories are NOT present):
Metabolites PLSDA1 VIP score
0 D-(+)-Raffinose 0.264496
1 Myoinositol 0.249230
2 Melibiose 0.247374
3 3-Hydroxymethylglutarate 0.216225
4 D-(+)-Malate 0.214350
5 L-(+)-Lactic Acid 0.207848
6 (S)-Hexyl-glutathione 0.193233
7 Indole-3-acetamide 0.185193
8 L-Tryptophan 0.182106
9 Lactose 0.174501
10 D-Tryptophan 0.162587
11 Purine 0.161442
12 2-Aminophenol 0.159380
13 5-Hydroxy-L-tryptophan 0.150975
14 Pterin 0.131837
15 Riboflavin 0.131537
16 5-Methylcytidine 0.127013
17 N_AP_FHxSA 0.125591
18 2-Hydroxy-2',5'-dichlorobiphenyl 0.121294
19 Amentoflavone 0.120487
20 Palmitoleic Acid (16:1) 0.110705
21 d7-PA (15:0-18:1) 0.103092
22 Stearic Acid (18:0) 0.102067
23 Orotic Acid 0.101844
24 Mono-carboxy-isononyl phthalate 0.101050
25 Indole-3-acetate 0.100776
26 PS 38:01 0.100719
27 D-(+)-Gluconolactone 0.099537
28 Uracil 0.098781
29 DHLVGR (Tryptic Peptide) 0.097728
30 D-(+)-Trehalose 0.094653
31 Tryptamine 0.093375
32 Pyridoxine 0.092373
33 beta-Gentiobiose 0.092021
34 Stachyose 0.089827
35 Citrulline 0.087756
36 Fumaric Acid 0.086345
37 Maltotetraose 0.084090
38 Oleic Acid (18:1) 0.083224
39 Itaconate 0.082990
40 N-Acetyl-L-aspartic Acid 0.082379
41 D-Maltose 0.082106
42 D-Sedoheptulose 0.081213
43 Calcium Pantothenate 0.080879
44 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphoethan... 0.080597
45 Camphene 0.077324
46 1,2-Dipentadecanoyl-sn-glycero-3-phosphoethano... 0.076706
47 4,6-Dioxoheptanoic Acid 0.072699
48 Deoxyribose 0.070024
49 PC 32:01 0.069967
The code:
import plotly.express as px
fig = px.scatter(pls1_top_50_features,
x = pls1_top_50_features["PLSDA1 VIP score"],
y = pls1_top_50_features["Metabolites"])
fig.layout.width = 500
fig.layout.height = 800
fig.update_yaxes(type = 'category',
categoryorder='max ascending', #Puts the samples in order
tickmode = 'linear') #Displays all categories
These values are only added when categoryorder = <VALUE> is set in update_yaxes(). I have tried using 'total ascending' and 'min ascending' according to the documentation, but I still get the same issue.
Has anyone else experienced this issue? Any help would be much appreciated, thanks!