Update 20.md

docs/20.md

@@ -105,7 +105,7 @@ seaborn.barplot(x=None, y=None, hue=None, data=None, order=None, hue_order=None,
 
 See also
 
-Show the counts of observations in each categorical bin.Show point estimates and confidence intervals using scatterplot glyphs.Combine a categorical plot with a class:<cite>FacetGrid</cite>.
+显示每个分类bin中的观察计数。使用散点图图示符显示点估计和置信区间。将分类图与类相结合:<cite>FacetGrid</cite>.
 
 Examples
 
@@ -228,7 +228,7 @@ Examples
 
 ![http://seaborn.pydata.org/_images/seaborn-barplot-12.png](img/20114eb58ca40a3ccf0b20f14f426c83.jpg)
 
-Use [`catplot()`](seaborn.catplot.html#seaborn.catplot "seaborn.catplot") to combine a [`barplot()`](#seaborn.barplot "seaborn.barplot") and a [`FacetGrid`](seaborn.FacetGrid.html#seaborn.FacetGrid "seaborn.FacetGrid"). This allows grouping within additional categorical variables. Using [`catplot()`](seaborn.catplot.html#seaborn.catplot "seaborn.catplot") is safer than using [`FacetGrid`](seaborn.FacetGrid.html#seaborn.FacetGrid "seaborn.FacetGrid") directly, as it ensures synchronization of variable order across facets:
+使用 [`catplot()`](seaborn.catplot.html#seaborn.catplot "seaborn.catplot") 来结合 [`barplot()`](#seaborn.barplot "seaborn.barplot") 和 [`FacetGrid`](seaborn.FacetGrid.html#seaborn.FacetGrid "seaborn.FacetGrid"). 这允许数据根据额外的类别变量分组。使用 [`catplot()`](seaborn.catplot.html#seaborn.catplot "seaborn.catplot") 比直接使用 [`FacetGrid`](seaborn.FacetGrid.html#seaborn.FacetGrid "seaborn.FacetGrid") 更安全, 因为它可以确保变量在不同的facet之间保持同步:
 
 ```py
 >>> g = sns.catplot(x="sex", y="total_bill",