Plot the data by adding the features you want in the plot (plot color, thickness, labels, annotation, etc…). Display the plot (graph/chart). Let’s plot a simple line in python. So, open up your notebook, not the physical one, open jupyter notebook, and follow the code below: #...
ax = fig.gca(projection='3d') # Create data point to plot theta = np.linspace(-4 * np.pi, 4 * np.pi, 100) z = np.linspace(-2, 2, 100) r = z**2 + 1 x = r * np.sin(theta) y = r * np.cos(theta) # Plot line graph ax.plot(x, y, z, label='Parametric curve...
10# DataFrame.plot() 函数参数配置: 11# x : 横向标记位置,默认为None 12# y : 纵向标记位置,默认为None 13# kind 参数 : 绘制类型(字符串) 14# ‘kind=line’ : 折线图模式 15# ‘kind=bar’ : 纵向条形图模式 16# ‘kind=barh’ : 横向条形图模式 17# ‘kind=hist’ : 柱状图模式 18# ‘...
9)) plt.subplot(2,2,1)#第1张子图 plt.plot(sz_df['开盘价'],'
画直方图 f, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(16,4)) bins = 30...
Matplotlib integrates seamlessly with Pandas, allowing you to plot directly from DataFrames. import pandas as pd # Sample DataFrame data = {'A': [1, 2, 3, 4], 'B': [10, 20, 25, 30]} df = pd.DataFrame(data) df.plot(kind='bar') ...
df = pd.DataFrame(data, index= ) 2. 调用以下格式: ax = df.plot() fig = ax.get_figure() fig.savefig('asdf.png') DataFrame.plot(x=None,y=None,kind='line',ax=None,subplots=False,sharex=None,sharey=False,layout=None,figsize=None,use_index=True,title=None,grid=None,legend=True,sty...
from matplotlib import pyplot as plt # Create a bar plot of name vs grade plt.bar(x=df_students.Name, height=df_students.Grade) # Display the plot plt.show()# Create a bar plot of name vs grade plt.bar(x=df_students.Name, height=df_students.Grade, color='orange') # Custom...
plt.plot(x,y)plt.plot(x,y*2)plt.xticks((0,np.pi*0.5,np.pi,np.pi*1.5,np.pi*2))plt.show() 设置label 和 legend 为了区分出每个数据对应的图形名称 代码语言:javascript 复制 plt.plot(x,y,label="sin(x)")plt.plot(x,y*2,label="2sin(x)")# plt.legend(loc=1)plt.legend(loc='bes...
plt.title("Interactive Plot") plt.xlabel("X-axis") plt.ylabel("Y-axis") plt.show Output: 3绘制带有标签和图例的多条线的折线图importmatplotlib.pyplotasplt #Plot a line graph plt.plot([5,15], label='Rice') plt.plot([3,6], label='Oil') ...