[英]Python and Seaborn how to plot two categorical features using barplot
I am trying to solve kaggle's titanic competition.我正在尝试解决 kaggle 的巨大竞争。
I need to generate a plot where X is representing Sex
having male and female as values.我需要生成一个图,其中 X 代表以男性和女性为值的
Sex
。 And Y as two variables 0 and 1.和 Y 作为两个变量 0 和 1。
From this, I need to see how many males/females survived.由此,我需要看看有多少男性/女性幸存下来。
I am trying the following:我正在尝试以下操作:
sns.barplot(x='Sex', y='Survived', data=train)
But I am getting a plot representing percentage of each male and female:但是我得到了一个代表每个男性和女性百分比的图:
Any idea how to create stacked bar using seaborn?知道如何使用 seaborn 创建堆叠条吗?
I need to plot 2 features, each of them having 2 values.我需要绘制 2 个特征,每个特征都有 2 个值。
I would probably try with "Grouped barplots".我可能会尝试使用“分组条形图”。 Interestingly, the seaborn's gallery page has a nice example about it... with titanic data as an example:
有趣的是,seaborn 的画廊页面有一个很好的例子......以泰坦尼克号数据为例:
import seaborn as sns
sns.set(style="whitegrid")
# Load the example Titanic dataset
titanic = sns.load_dataset("titanic")
# Draw a nested barplot to show survival for class and sex
g = sns.catplot(x="class", y="survived", hue="sex", data=titanic,
height=6, kind="bar", palette="muted")
g.despine(left=True)
g.set_ylabels("survival probability")
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