1. 散点图(Scatter plot) 2. 带边界的气泡图(Bubble plot with Encircling) 3. 带线性回归最佳拟合线的散点图 (Scatter plot with linear regression line of best fit) 4. 抖动图 (Jittering with stripplot) 5. 计数图 (Counts Plot) 6. 边缘直方图 (Marginal Histogram) 7. 边缘箱形图 (Marginal Box...
# Line Segmentsand Annotation for p1, p2, c in zip(df['1952'], df['1957'], df['continent']): newline([1, p1], [3, p2]) ax.text(1 - 0.05, p1, c + ', ' + str(round(p1)), horizontalalignment='right', verticalalignment='center', fontdict={'size': 14}) ax.text(3 +...
sns.kdeplot(df.loc[df['cyl'] == 4, "cty"], shade=True, color="g", label="Cyl=4", alpha=.7) sns.kdeplot(df.loc[df['cyl'] == 5, "cty"], shade=True, color="deeppink", label="Cyl=5", alpha=.7) sns.kdeplot(df.loc[df['cyl'] == 6, "cty"], shade=True, color=...
到目前为止,我的(简单)代码。 import matplotlib.pyplot as plt import numpy as np import pandas as pd y = np.array([0,1,2,3,4]) fig, axs = plt.subplots(3, sharex=True, sharey=True) fig.suptitle("I1 - Reakce na změnu prvku") axs[0].plot(df.index,df['A'], color='light...
LineCollection大概是一个“线段集合”的类 代码语言:txt AI代码解释 matplotlib.collections.LineCollection(segments, *args, zorder=2, **kwargs) """ segments : list of array-like A sequence of (*line0*, *line1*, *line2*), where:: linen = (x0, y0), (x1, y1), ... (xm, ym) or...
boxplot函数 matplotlib.pyplot.boxplot(x, notch=None, sym=None, vert=None, whis=None, positions=None, widths=None, patch_artist=None,meanline=None, labels=None, … ) label= ['第一产业','第二产业','第三产业']## 定义标签 gdp = (list(values[:,3]),list(values[:,4]),list(values[...
x=np.linspace(0,10,100)y=np.sin(x)fig,ax=plt.subplots()ax.plot(x,y)ax.axvline(x=np.pi,color='r',linestyle='--',label='π')ax.axvline(x=2*np.pi,color='g',linestyle='--',label='2π')ax.axvline(x=3*np.pi,color='b',linestyle='--',label='3π')ax.legend()ax....
File "/home/somesh/Downloads/vscode_code/python ml course /firstml.py", line 149, in <module> plt.plot(np.round(zee),patches,'ro') File "/home/somesh/.local/lib/python3.8/site-packages/matplotlib/pyplot.py", line 2840, in plot ...
plot线形图标注误差范围 import numpyas np import matplotlib.pyplotas plt N =25 np.random.seed(100) x = np.linspace(0., 10., N) y = np.sin(x) **2 + np.cos(x) plt.figure(figsize=(15, 10)) noise = np.random.random(N) *.7 +.4 ...
line, = ax.plot([0], [0]) # 初始化空折线图 def on_move(event): if event.inaxes: line.set_data([0, event.xdata], [0, event.ydata]) fig.canvas.draw() # 强制重绘画布 fig.canvas.mpl_connect('motion_notify_event', on_move) ...