The barplot() function of seaborn creates a bar plot to show the relationship between a numeric variable and one or more categorical variables. It estimates the central tendency and uncertainty around it. → Ar
分类变量(categorical variable) 常用的有:饼图、柱形图 数值变量(numerical variable) 常用的有:概率密度图、直方图、箱式图 2 导入数据 3 分类特征 分类特征主要看两个方面: a有几种分类 b每种分类的数量(或者比例) 这里为了演示,用day变量,代表了星期。 mon 74tue 64wed 54thu 61fri 85sat 84sun 95Name...
3 Bar plot using plotnine Bar plot has a similar aim to the histogram. It lets us discover and show the underlying frequency distribution of a set of categorical data. As we know that categorical data can not be measured by the mathematics equation, such as multiplication, subtraction, etc b...
Chart) 21、哑铃图(Dumbbell Plot) 四、分布(Distribution)关系图 21、连续变量堆积直方图(Stacked Histogram for Continuous Variable) 22、类别变量堆积直方图(Stacked Histogram for Categorical Variable) 23、密度图(Density Plot) 24、带直方图的密度图(Density Curves with Histogram) 25、山峰叠峦图(Joy Plot) ...
sns.catplot(x='categorical', y='data science', kind='violin', data=df)结果如下:我们可以像使用Matplotlib一样在一个图像中创建多个图形: fig, axes = plt.subplots(1, 2, sharey=True, figsize=(8, 4))sns.scatterplot(x="Mes", y="deep learning", hue="categorical", data=df, ax=axes[0...
Horizontal Bar Chart 代码语言:javascript 代码运行次数:0 运行 AI代码解释 #Horizontal barchart #Create subplot sns.set_style('whitegrid')#settheme fig,ax=plt.subplots(figsize=(16,7))#Create barplot chart2=sns.barplot(x=category2['total sale'],y=category2['itemDescription'],palette=sns.cubeheli...
同样,使用plot.barh()可以做出条形图。 df.groupby('区域')['销售额'].sum().sort_values().plot.barh() # 条形图 使用plot.pie函数可以看各个区域的销售额占比,其中,autopct用来设置数据标签,figsize用来设置图图片的大小,由图可以看出华南区域的销售额占比最高,西南区域的销售额占比最低,仅占比3.1%。
from keras.utils import to_categoricalimport tensorflow as tfimport matplotlib.pyplot as plt```接下来,我们将构建一个简单的CNN模型。该模型将包含两个卷积层、一个池化层和两个全连接层。我们将使用Keras的Sequential API来创建模型。```pythonmodel = Sequential()model.add(Conv2D(32, kernel_size=(3, ...
help(pd.get_dummies)Help onfunctionget_dummiesinmodule pandas.core.reshape.reshape:get_dummies(data,prefix=None,prefix_sep='_',dummy_na=False,columns=None,sparse=False,drop_first=False,dtype=None)->'DataFrame'Convert categorical variable into dummy/indicator variables.Parameters---data:array-like,...
Like with box plots, we can create a single violin plot for the data in interest or, more often, multiple violin plots, each for a separate category of a categorical variable. Seaborn provides more room for creating and customizing violin plots than matplotlib. To build a basic violin plot ...