(2) 当x,y是同维矩阵时,则以x,y对应列元素为横、纵坐标分别绘制曲线,曲线条数等于矩阵的列数; (3) 对只包含一个输入参数的plot函数,当输入参数是实矩阵时,则按列绘制每列元素值相对其下标的曲线,曲线条数等于输入参数矩阵的列数。 当输入参数是复数矩阵时,则按列分别以元素实部和虚部为横、纵坐标绘制多...
importmatplotlib.pyplotaspltimportnumpyasnp# 输入二次函数参数a=float(input("请输入二次项系数a:"))b=float(input("请输入一次项系数b:"))c=float(input("请输入常数项c:")# 生成x值范围(-10到10之间,间隔0.1)x=np.arange(-10100.1y=a*x**2+b*x+c# 创建图像和坐标轴fig,ax=plt.subplots()# ...
Out[18]:<functionpandas.core.frame.DataFrame.drop_duplicates(self,subset:'Hashable | Sequence[Hashable] | None'=None,keep:"Literal['first'] | Literal['last'] | Literal[False]"='first',inplace:'bool'=False,ignore_index:'bool'=False)->'DataFrame | None'> 通过参数keep的属性值来设置: fir...
plt.plot('a', 'c', data=data) 1. 2. 3. 4. 绘制多个数据集 有多种方法可以绘制多个数据集。 最直接的方法就是多次调用plot。例子: >>> plot(x1, y1, 'bo') >>> plot(x2, y2, 'go') 1. 2. 或者,如果您的数据已经是一个2d数组,您可以直接将其传递给x, y。
# Merge two DataFramesmerged_df = pd.merge(df1, df2, on='common_column', how='inner') 当你有多个数据集时,你可以根据共同的列使用Pandas的merge功能来合并它们。应用自定义功能 # Apply a custom function to a columndef custom_function(x): ret...
assertround(sum(probabilities),10) ==1.0, \"Probabilities must sum to 1" 现在,我们可以使用随机数生成器rng上的choice方法,根据刚刚创建的概率从data中选择样本。对于这种选择,我们希望打开替换,因此调用该方法多次可以从整个data中选择: selected = rng.choice(data, p=probabilities, replace=True)# 0 ...
plt.plot(x, c, 'b|-') plt.plot(x, s) show() 1.3matplotlib中绘图的默认配置 from pylab import * import numpy as np import matplotlib.pylab as plt # 创建一个8*6点(point)的图,并设置分辨率为80 figure(figsize=(8, 6), dpi=80) ...
create a function to fit with your data. a, b, c and d are the coefficients that curve_fit will calculate for you. In this part you need to guess and/or use mathematical knowledge to find a function that resembles your data """deffunc(x, a, b, c, d):returna*x**3+ b*x**...
lon_0=0) #Fill the globe with a blue color map.drawmapboundary(fill_color='aqua') #Fill...
to execute Python code. - tool 'search_web' to search for information on the internet. If you use the 'code_exec' tool, remember to always use the function print() to get the output. The dataset already exists and it's called 'dtf', don't create a new one. This dataset contains ...