plt.plot(x, y, label='Sinusoidal Wave') plt.fill_between(x, y - conf_interval, y + conf_interval, color='gray', alpha=0.5, label='95% Confidence Interval') plt.xlabel('X-axis') plt.ylabel('Y-axis') plt.title('Line Plot with 95% Confidence Interval') plt.legend() plt.show()...
importseabornassns# 创建一个DataFramedf=pd.DataFrame(data,columns=['value'])# 使用Seaborn绘制plt.figure(figsize=(10,6))sns.barplot(x='value',y='value',data=df,ci='sd',palette='muted')plt.title('Mean and Confidence Interval with Seaborn')plt.xlabel('Value')plt.ylabel('Density')plt.sho...
SNS . line plot(x =无,y =无,色相=无,大小=无,样式=无,数据=无,调色板=无,色相 _ 顺序=无,色相 _ 范数=无,大小=无,大小 _ 顺序=无,大小 _ 范数=无,破折号=真,标记=无,样式 _ 顺序=无,单位=无,估计器= '平均值',ci=95,n_boot=1000,排序=真,err_style= '波段',err _ kws =无,图例...
color='blue')# 添加置信区间plt.fill_between(x,y_upper,y_lower,color='lightblue',alpha=0.5,label='Confidence Interval')# 图形标签plt.title('Line Plot with Confidence Interval')plt.xlabel('X-axis')plt.ylabel('Y-axis')plt.legend()plt.grid(True)# 显示图形plt.show()...
plt.plot(x, 2*x + 1, 'r-', label='True Line') plt.fill_between(x, 2*x + 1 - y_err, 2*x + 1 + y_err, color='gray', alpha=0.2, label='Confidence Interval') plt.legend() plt.xlabel('X') plt.ylabel('Y') plt.title('Confidence Interval using Matplotlib') ...
3.2 线图(Line Plot) 线图通常用于展示数据随时间的变化趋势,或者两个连续变量之间的关系。Seaborn 的lineplot()函数支持绘制带有误差条的线图,以便于更好地理解数据的波动性。 示例代码: sns.lineplot(x="day", y="total_bill", data=tips, hue="sex") ...
with open('household_power_consumption.txt') as file: head = [next(file) for line in range(n_lines)] display(head) ['Date;Time;Global_active_power;Global_reactive_power;Voltage;Global_intensity;Sub_metering_1;Sub_metering_2;Sub_metering_3\n', ...
(x="displ", y="hwy", hue="cyl", data=df_select, height=7, aspect=1.6, robust=True, palette='tab10', scatter_kws=dict(s=60, linewidths=.7, edgecolors='black')) # Decorations gridobj.set(xlim=(0.5,7.5), ylim=(0,50)) plt.title("Scatterplot with line of best fit grouped ...
ax.plot(x, 2 + 3*x, color='red', linewidth=3, label='True Line'); ax.set_xlabel('X'); ax.set_ylabel('Y'); ax.legend(); ax.set_xlim(-4,4); make_new_fig_2() fig, ax = plt.subplots(1,1) 置信区间公式 # Plot last simulation scatterplot with confidence interval sns.regp...
label='Data') plt.plot(x, 2*x + 1, 'r-', label='True Line') plt.fill_between(x, 2*x + 1 - y_err, 2*x + 1 + y_err, color='gray', alpha=0.2, label='Confidence Interval') plt.legend() plt.xlabel('X') plt.ylabel('Y') plt.title('Confidence Interval using Matplotlib...