Change plot order of seaborn pairplot

For the seaborn pairplot shown below, how to change the order of the Labels, so that hidden points can be viewed in subsequent plots?

Note that I looked at this link, but could not configure my code correctly to work.

Also, I tried changing the order of the labels, while keeping the color tied to the labels via the elegant solution provided here carried out by Trenton McKinney, but that did not change the order of how the points showed up on the plot.

Can you assist me in changing the order of the points being plotted so that hidden points can be viewed in subsequent plots.

Here is the original code:

import seaborn as sns
import pandas as pd

data = {'Feat1': [-46.220314, -23.80669, -42.092365, -35.29639, -37.075096, -42.8849, -32.3057, -24.469942, -97.89892, -81.96325, -78.41986, -100.68544, -87.05412, -64.121056, -94.504845, -61.951996, -108.19452, -97.4037, -92.641335, -199.18787, -137.5976, -208.0035, -108.225975, -121.29299],
        'Feat2': [22.862856, 20.536781, 25.680704, 21.709473, 22.347767, 28.03802, 26.568039, 27.005375, -0.38156664, 0.1821717, -6.766374, -4.5810957, -2.9231584, -3.7892206, -0.9999217, -8.960198, 13.909201, 22.897585, 22.10624, 3.3090565, 6.795896, -1.33229, 14.341716, 18.274035],
        'Feat3': [-6.1573067, -5.015675, -5.0092897, -4.160352, -3.860426, -7.8572545, -9.47018, -9.301921, 6.4163384, -1.2870358, 0.8001185, 1.6977689, 6.817379, -0.283514, 3.2884297, -1.5915259, 0.6966458, -2.8488266, -3.5110545, -2.5994794, 1.6793671, -3.2078092, 1.02891, 2.2891548],
        'Feat4': [5.6060414, 4.2216353, 5.665794, 5.578346, 5.6953945, 3.3361, 3.4532788, 4.3995037, 7.234347, 4.703838, 0.83444935, 1.8801615, 5.4460077, 6.3084154, 6.881124, 5.6160254, -1.956591, 1.4105041, 2.467166, 4.0802555, 2.2256763, 1.5177402, -1.8651972, 2.3360753],
        'Labels': [2, 2, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0]}
df = pd.DataFrame(data)
df1 = df.copy()
df2 = df.copy()

df1['Labels'] = y_train.astype(str) #Make it string
df1.Labels = pd.Categorical(values=df1.Labels, categories=['0', '1', '2'], ordered=True)

sns.set(style='darkgrid', context='notebook')
colors = dict(zip(['2', '1', '0'], sns.color_palette('tab10_r', 3)))
sns.pairplot(df1, hue='Labels', palette=colors)

df2['Labels'] = df2['Labels'].astype(str) #Make it string

df2.Labels = pd.Categorical(values=df2.Labels, categories=['2', '1', '0'], ordered=True)
sns.pairplot(df2, hue='Labels', palette=colors)

to bring Grey ahead of other colors, you will need to change the order of df2 in the sns.pairplot in the last line of your code. Here I have only made grey (which is 2) come above the others. You can make similar changes the order between green and purple as well if you want to.

If you change this (last) line:

sns.pairplot(df2, hue='Labels', palette=colors)

to

sns.pairplot(pd.concat([df2[df2['Labels'] != '2'], df2[df2['Labels'] == '2']]), hue='Labels', palette=colors)

the output will change from

to the new order