The Python graph gallery tries to display (or translate from R) some of the best creations and explain how their source code works. If you want to display your work here, please drop me a word or even better, submit a Pull Request! A circular barchart with several features per group ...
Matplotlib 绘制水平柱状图 调用Matplotlib 的 barh() 函数可以生成水平柱状图。barh() 函数的用法与 bar() 函数的用法基本一样,只是在调用 barh() 函数时使用 y参数传入 Y 轴数据,使用 width 参数传入代表条柱宽度的数据。 例如,如下程序调用 barh() 函数生成两组并列的水平柱状图,来展示两套教程历年的销量统...
计算SHAP # pip install shapimportshap# load JS visualization code to notebookshap.initjs()# 用SHAP值解释模型的预测,相同的语法适用于LightGBM、CatBoost和scikit-learn模型explainer=shap.TreeExplainer(xgb)shap_values=explainer.shap_values(X_test)shap_values###shap_values1=np.array(shap_values).reshape...
# 模拟随机验证码 import random def v_code(): code = '' for i in range(5): num = random.randint(0, 9) alf = chr(random.randint(65, 90)) # chr()通过序号查字符 add = random.choice([num, alf]) code = "".join([code, str(add)]) return code print(v_code()) 二.日志模块 ...
1p = figure(plot_width=400, plot_height=400) 2# 线段x、y位置点均为列表;两段线的颜色、透明度、线宽 3p.multi_line([[1,3,2], [3,4,6,6]], [[2,1,4], [4,7,8,5]], 4color=["firebrick","navy"], al...
plt.bar(left=(0,1),height=(1,0.5),width=0.35) plt.show() 此时又来需求了,我需要标明x,y轴的说明。比如x轴是性别,y轴是人数。实现也很简单,看代码: importmatplotlib.pyplot as plt plt.xlabel(u'性别') plt.ylabel(u'人数') plt.bar(left=(0,1),height=(1,0.5),width=0.35) ...
cm.tab10(i/float(len(categories)-1)) for i in range(len(categories))] # Draw Plot for Each Categoryplt.figure(figsize=(16, 10), dpi= 80, facecolor='w', edgecolor='k') for i, category in enumerate(categories): plt.scatter('area', 'poptotal', data=midwest.loc[midwest.category==...
Path3 = 'code' Path10 = Path1 + Path2 + Path3 Path20 = os.path.join(Path1, Path2, Path3) print('Path10 = ', Path10) print('Path20 = ', Path20) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 输出如下: Path10 = homedevelopcode ...
df['Diagnosis'].value_counts().plot(kind='bar',color=['green','red'])plt.title('Diagnosis Distribution')plt.xlabel('Diagnosis')plt.ylabel('Patient Count')plt.show() 解释:该图显示了每个诊断类别(如“Healthy”与“Hypertension”)的人数分布,方便医生快速了解整体健康状况。
如果设置为1,则各个柱子会紧密相连;如果设置为大于1的数,则各个柱子会相互交叠plt.bar(x, y, width =0.5, color ='r') plt.subplot(2,2,3)# 参数color用于设置柱子的填充颜色,具体取值见后面的说明plt.stackplot(x, y, color ='r') plt.subplot(2,2,4)...