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Created 3 years ago
import seaborn as sns
df=sns.load_dataset("diamonds")
df.head()
colors=["D","E","F","G","H","I","J"]
from pandas.api.types import CategoricalDtype
df.color=df.color.astype(CategoricalDtype(categories=colors,ordered=True))
df.color
0 E
1 E
2 E
3 I
4 J
..
53935 D
53936 D
53937 D
53938 H
53939 D
Name: color, Length: 53940, dtype: category
Categories (7, object): [D < E < F < G < H < I < J]
sns.barplot(x="cut",y="price",hue="color",data=df);
df.groupby(["cut","color"])["price"].mean()
cut color
Fair D 4291.061350
E 3682.312500
F 3827.003205
G 4239.254777
H 5135.683168
I 4685.445714
J 4975.655462
Good D 3405.382175
E 3423.644159
F 3495.750275
G 4123.482204
H 4276.254986
I 5078.532567
J 4574.172638
Ideal D 2629.094566
E 2597.550090
F 3374.939362
G 3720.706388
H 3889.334831
I 4451.970377
J 4918.186384
Premium D 3631.292576
E 3538.914420
F 4324.890176
G 4500.742134
H 5216.706780
I 5946.180672
J 6294.591584
Very Good D 3470.467284
E 3214.652083
F 3778.820240
G 3872.753806
H 4535.390351
I 5255.879568
J 5103.513274
Name: price, dtype: float64