so.Plot(data=penguins, x='bill_length_mm', y='bill_depth_mm') .add(so.Dot()).layout(size=(6,6)).show() ) # 设置图形是6英寸乘以6英寸的大小,so.Dot()表示绘制散点图 程序输出的结果见下图。 如果我们想要改变散点的颜色,可以执行下面的代码: importseabornassns imp
alpha = 0.5) + # 添加小提琴图，根据Group填充颜色，设置透明度 geom_boxplot(width = 0.05...
sns.boxplot(data=df, x="x_col", y="y_col") ii. Violin PlotThe violin plot of Seaborn combines a box plot with a KDE to show data distribution.sns.violinplot(data=df, x="x_col", y="y_col") iii. Strip PlotThe strip plot in Seaborn locates the individual data points along a...
2、边缘箱图(Marginal Boxplot) #中间散点图,右边和下边分别绘制y轴及x轴数据的箱图,# Import Datadf=pd.read_csv("https://raw.githubusercontent.com/selva86/datasets/master/mpg_ggplot2.csv")# Create Fig and gridspecfig=plt.figure(figsize=(16,10),dpi=80)grid=plt.GridSpec(4,4,hspace=0.5,w...
...在seaborn中,通过了柱状图,箱体图,小提琴图等多种可视化形式,来展示不同组数据的异同,具体的函数列表如下 1. stripplot, 2. swarmplot 3. boxplot 4. violinplot...5. boxenplot 6. pointplot 7. barplot 8. countplot 1. stripplot 该函数绘制的是扰动的散点图,基本用法如下 >>> df = pd.read_csv...
柱状图(Bar Plot):用于比较不同类别或组之间的数值。 条形图(Barh Plot):用于水平展示柱状图。 饼图(Pie Chart):用于显示数据的相对比例和占比。 直方图(Histogram):用于显示数据的分布情况。 箱线图(Box Plot):用于显示数据的分散情况和异常值。 热力图(Heatmap):用于显示数据的矩阵关系。
boxplot - Grouped boxplots FacetGrid - Facetting histograms by subsets of data PairGrid - Dot plot with several variables catplot - Grouped barplots jointplot - Linear regression with marginal distributions lmplot - Faceted logistic regression
boxplot(x="day", y="total_bill", hue="time", data=tips, palette="Set3", linewidth=1.5, fliersize=4) # add a title, xlabel, and ylabel to the plot using Matplotlib functions plt.title("Box Plot of Total Bill by Day and Meal Time") plt.xlabel("Day of the Week") plt.ylabel(...
The categorical functions now act more like the rest of seaborn in that they will produce a plot with a single main color unless thehuevariable is assigned. Previously, there would be an implicit redundant color mapping (e.g., each box in a boxplot would get a separate color from the de...
seaborn _core _marks _stats colors external __init__.py _base.py _compat.py _docstrings.py _statistics.py _testing.py algorithms.py axisgrid.py categorical.py cm.py distributions.py matrix.py miscplot.py objects.py palettes.py rcmod.py ...