6))# 绘制带误差条的柱状图ax.bar(categories,values,yerr=errors,capsize=5)# 设置标题和轴标签ax.set_title('Bar Chart with Error Bars - how2matplotlib.com')ax.set_xlabel('Categories')ax.set_ylabel('Values
'D']values=[3,7,2,5]errors=[0.5,1,0.3,0.8]# 创建柱状图并添加误差线plt.figure(figsize=(8,6))plt.bar(categories,values,yerr=errors,capsize=5)plt.title('Bar Plot with Error Bars - how2matplotlib.com')plt.xlabel('Categories')plt.ylabel('Values')plt.show()...
- :func:`violinplot` (with ``kind="violin"``) 用kernel density estimation来表现点的样本分布 - :func:`boxenplot` (with ``kind="boxen"``) Categorical estimate plots: - :func:`pointplot` (with ``kind="point"``) - :func:`barplot` (with ``kind="bar"``) 在每个分类中显示均值和置信...
barplot(x='Users', y='Stage', data=df.loc[df[group_col]==group, :], order=order_of_bars, color=c, label=group) # Decorations plt.xlabel("$Users$") plt.ylabel("Stage of Purchase") plt.yticks(fontsize=12) plt.title("Population Pyramid of the Marketing Funnel", fontsize=22) ...
# 加载示例数据集tips=sns.load_dataset("tips")# 绘制带错误条的条形图sns.barplot(x="day",y="total_bill",hue="smoker",data=tips,ci="sd")plt.title("Total Bill by Day and Smoking Status with Error Bars")plt.show() 5. 自定义注解和标签 ...
barplot(x='Users', y='Stage', data=df.loc[df[group_col]==group, :], order=order_of_bars, color=c, label=group) # Decorations plt.xlabel("$Users$")plt.ylabel("Stage of Purchase")plt.yticks(fontsize=12)plt.title("Population Pyramid of the Marketing Funnel", fontsize=22)plt....
barplot(x='Users', y='Stage', data=df.loc[df[group_col]==group, :], order=order_of_bars, color=c, label=group) # Decorations plt.xlabel("$Users$")plt.ylabel("Stage of Purchase")plt.yticks(fontsize=12)plt.title("Population Pyramid of the Marketing Funnel", fontsize=22)plt....
barplot(x='Users', y='Stage', data=df.loc[df[group_col]==group, :], order=order_of_bars, color=c, label=group) # Decorations plt.xlabel("$Users$") plt.ylabel("Stage of Purchase") plt.yticks(fontsize=12) plt.title("Population Pyramid of the Marketing Funnel", fontsize=22) ...
sns.barplot(x='tip_pct',y='day',data=tips,orient='h') D:\Anaconda\lib\site-packages\scipy\stats\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted ...
def barplot(x_data, y_data, error_data, x_label="", y_label="", title=""): _, ax = plt.subplots() # Draw bars, position them in the center of the tick mark on the x-axis ax.bar(x_data, y_data, color = '#539caf', align = 'center') ...