countplot 故名思意,计数图,可将它认为一种应用到分类变量的直方图,也可认为它是用以比较类别间计数差,调用 count 函数的 barplot。 seaborn.countplot(x=None,y=None,hue=None,data=None,order=None,hue_order=None,orient=None,color=None,palette=None,saturation=0.75,ax=None,**kwargs) x, y, hue: nam...
seaborn.barplot(data=None, *, x=None, y=None, hue=None, order=None, hue_order=None, estimator='mean', errorbar=('ci',95), n_boot=1000, seed=None, units=None, weights=None, orient=None, color=None, palette=None, saturation=0.75, fill=True, hue_norm=None, width=0.8, dodge='aut...
然后使用 Seaborn 的 barplot() 函数绘制柱状图,其中x轴变量为年份,y轴变量为涨跌幅,参数中的estimator选择np.mean: ax = sns.barplot(x='年份', y='涨跌幅', data=index_zh_a_hist_df, estimator=np.mean) plt.show() 这将生成一个基本的柱状图,展示了每一年上证50指数日涨跌幅的平均值。 日涨跌幅均...
sns.barplot(x="tip", y="day", data=tips) 11.4 设置order=["变量名1","变量名2",...]来显示指定分类顺序 sns.barplot(x="time", y="tip", data=tips, order=["Dinner", "Lunch"]) 11.5 使用中位数作为集中趋势的估计:estimator=median sns.barplot(x="day", y="tip", data=tips, estimat...
order=["Thur","Fri","Sat","Sun"] # 指定x轴label的顺序 ) plt.show() 水平柱状图 orient参数指定水平h或者垂直v In 26: 代码语言:txt 复制 sns.barplot( data=tips, x="tip", # x轴的数据必须为数值 y="day", hue="smoker", orient="h" ...
sns.barplot( x=None, y=None, hue=None, data=None,order=None, hue_order=None, estimator=<functionmeanat0x000001DA64AD3DC8>, ci=95, n_boot=1000, units=None, orient=None, color=None, palette=None, saturation=0.75, errcolor='.26', ...
# make barplot and sort bars sns.barplot(x='CompanyLocations', y="CompanyProfit", data = datf, order = datf.sort_values('CompanyProfit',ascending = False).CompanyLocations) plt.show() Output If we want to show it in ascending order, we have to simply set the ascending = True ...
官方文档解释:http://seaborn.pydata.org/generated/seaborn.barplot.html?highlight=barplot#seaborn.barplot Show point estimates and confidence intervals as rectangular bars. A bar plot represents an estimate of central tendency for a numeric variable with the height of each rectangle and provides some ...
>>>ax=sns.barplot(x="day",y="total_bill",hue="sex",data=tips) Draw a set of horizontal bars: >>>ax=sns.barplot(x="tip",y="day",data=tips) Control bar order by passing an explicit order: >>>ax=sns.barplot(x="time",y="tip",data=tips,...order=["Dinner","Lunch"]) ...
我们可以在barplot中使用相同的技术。 蟒蛇3 # make barplot and sort bars sns.barplot(x='State', y="Growth", data=df, order=df.sort_values('Growth').State) 输出: 第5 步:让我们按照降序对条形图进行排序。 蟒蛇3 # make barplot and sort bars sns.barplot(x='State', y="Growth", ...