Python 如何使用plt可视化多个条形图。根据axis的索引，axis必须迭代所有视觉效果？

我试图年复一年地描绘每个国家的预期寿命，我写了一个运行良好的代码

#Lets Create a Function that will create a relation between Year,life Expectancy with respect to different country



def EDA_features(country,life_expectancy,data):
    for i in set(data[country]):
        plt.bar(range(len(set(data[country]))),data[data[country]==i][life_expectancy])
        plt.xticks(range(len(set(data.Year))),labels=list(set(data.Year)))
        plt.xlabel('Year')
        plt.ylabel(f'{life_expectancy}')
        plt.title(f"Year vs {life_expectancy} for  {i}")
        plt.show()

我想使用plt.subplot将此可视化显示为3或2行

我试过这个密码

fig, ((ax1, ax2, ax3), (ax4, ax5, ax6)) = plt.subplots(nrows=2, ncols=3, sharex=True, sharey=True, figsize=(10,5))
for ax,country in zip(list(set(df.Country)),[ax1,ax2,ax3,ax4,ax5,ax6]):
    sns.barplot(range(len(set(df.Year))),df[df.Country==country]['Life expectancy at birth (years)'],ax=ax)
    ax.set_xticks(range(len(set(data.Year))))
    ax.set_xticklabels(list(set(data.Year)))
    plt.xlabel('Year')
    plt.ylabel('Life expectancy at birth (years)')
    plt.title(f"Year vs Life expectancy at birth (years) for  {country}")
    plt.show()

它抛出以下错误AttributeError:“bool”对象没有属性“all”

---

有人能帮我吗？

你的拉链顺序不对：

数字排在第二位，而国家排在第一位。请注意，在for语句开头创建

ax，country

元组时，ax将包含country，country将包含子批

for ax,country in zip(list(set(df.Country)),[ax1,ax2,ax3,ax4,ax5,ax6]):

像这样交换：

for country, ax in zip(list(set(df.Country)),[ax1,ax2,ax3,ax4,ax5,ax6]):

df =  pd.DataFrame({'Country':np.repeat(["A","B","C","D","E","F"],5),
                   'Life expectancy at birth (years)':np.random.uniform(50,80,30),
                   'Year':np.tile([2000,2001,2002,2003,2004],6)})

---

假设您的数据帧如下所示：

for country, ax in zip(list(set(df.Country)),[ax1,ax2,ax3,ax4,ax5,ax6]):

df =  pd.DataFrame({'Country':np.repeat(["A","B","C","D","E","F"],5),
                   'Life expectancy at birth (years)':np.random.uniform(50,80,30),
                   'Year':np.tile([2000,2001,2002,2003,2004],6)})

您可以简单地使用，使用

col\u wrap

指定列数：

sns.catplot(x="Year",y="Life expectancy at birth (years)",
        col="Country",col_wrap=3,data=df,kind="bar",height=3)

或者简化上面的子批次代码也会得到类似的结果：

fig,axs = plt.subplots(2,3, sharex=True, sharey=True, figsize=(10,5))
axs = axs.flatten()
Years = df.Year.unique()
Countries = df.Country.unique()

for i,cty in enumerate(Countries):
    sns.barplot(x = "Year", y = "Life expectancy at birth (years)",
                data = df[df.Country==cty],ax=axs[i])
    axs[i].set_xticks(range(len(Years)))
    axs[i].set_xticklabels(Years)
    plt.xlabel('Year')
    plt.ylabel('Life expectancy at birth (years)')