I am currently implementing a code for facetgrid with subplots of barplots with two different groups ('type'), respectively. I am intending to get a plot, where the different groups are not stacked and not overlapping. I am using following code
g = sns.FacetGrid(data,
col='C',
hue = 'type',
sharex=False,
sharey=False,
size=7,
palette=sns.color_palette(['red','green']),
)
g = g.map(sns.barplot, 'A', 'B').add_legend()
The data is a pandas long format df with following example structure:
data=pd.DataFrame({'A':['X','X','Y','Y','X','X','Y','Y'],
'B':[0,1,2,3,4,5,6,7],
'C':[1,1,1,1,2,2,2,2],
'type':['ctrl','cond1','ctrl','cond1','ctrl','cond1','ctrl','cond1']}
)
In the created barplots I get now fully overlapping barplots of the two groups, thus ctrlis missing, see below. However, I am intending to get neighbouring non-overlapping bars each. How to achieve that? My real code has some more bars per plot, where you can see overlapping colors (here fully covered)

this answer shows up how to use FacetGrid directly.
But, if you have 0.9.0 installed, I would recommend you make use of the new catplot() function that will produce the right (at least I think?) plot. Note that this function returns a FacetGrid object. You can pass kwargs to the call to customize the resulting FacetGrid, or modify its properties afterwards.
g = sns.catplot(data=data, x='A', y='B', hue='type', col='C', kind='bar')

I think you want to provide the hue argument to the barplot, not the FacetGrid. Because the grouping takes place within the (single) barplot, not on the facet's level.
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import seaborn as sns
data=pd.DataFrame({'A':['X','X','Y','Y','X','X','Y','Y'],
'B':[0,1,2,3,4,5,6,7],
'C':[1,1,1,1,2,2,2,2],
'type':['ctrl','cond1','ctrl','cond1','ctrl','cond1','ctrl','cond1']})
g = sns.FacetGrid(data,
col='C',
sharex=False,
sharey=False,
height=4)
g = g.map(sns.barplot, 'A', 'B', "type",
hue_order=np.unique(data["type"]),
order=["X", "Y"],
palette=sns.color_palette(['red','green']))
g.add_legend()
plt.show()

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