Update 20.md

docs/20.md

@@ -52,11 +52,11 @@ seaborn.barplot(x=None, y=None, hue=None, data=None, order=None, hue_order=None,
 
 **units** : name of variable in `data` or vector data, optional
 
-> Identifier of sampling units, which will be used to perform a multilevel bootstrap and account for repeated measures design.
+> 采样单元的标识符，用于执行多级bootstrap并解释重复测量设计。
 
 **orient** : “v” | “h”, optional
 
-> Orientation of the plot (vertical or horizontal). This is usually inferred from the dtype of the input variables, but can be used to specify when the “categorical” variable is a numeric or when plotting wide-form data.
+> 绘图的方向（垂直或水平）。这通常是从输入变量的数据类型推断出来的，但是可以用来指定“分类”变量是数字还是宽格式数据。
 
 **color** : matplotlib color, optional
 
@@ -64,11 +64,11 @@ seaborn.barplot(x=None, y=None, hue=None, data=None, order=None, hue_order=None,
 
 **palette** : palette name, list, or dict, optional
 
-> Colors to use for the different levels of the `hue` variable. Should be something that can be interpreted by [`color_palette()`](seaborn.color_palette.html#seaborn.color_palette "seaborn.color_palette"), or a dictionary mapping hue levels to matplotlib colors.
+> 不同级别的 `hue` 变量的颜色。 颜色要能被 [`color_palette()`]解释(seaborn.color_palette.html#seaborn.color_palette "seaborn.color_palette"), 或者一个能映射到matplotlib颜色的字典。
 
 **saturation** : float, optional
 
-> Proportion of the original saturation to draw colors at. Large patches often look better with slightly desaturated colors, but set this to `1` if you want the plot colors to perfectly match the input color spec.
+>  Proportion of the original saturation to draw colors at. Large patches often look better with slightly desaturated colors, but set this to `1` if you want the plot colors to perfectly match the input color spec.
 
 **errcolor** : matplotlib color