Python科学计算中，可以使用以下方法简化代码：
import numpy as np
a = np.array([1, 2, 3])
b = np.array([4, 5, 6])
c = a + b
import pandas as pd
data = {'A': [1, 2, 3], 'B': [4, 5, 6]}
df = pd.DataFrame(data)
sum_ab = df['A'] + df['B']
import matplotlib.pyplot as plt
x = [1, 2, 3]
y = [4, 5, 6]
plt.plot(x, y)
plt.show()
from scipy import integrate, optimize
def func(x):
return x**2
result = integrate.quad(func, 0, 1)
print(result)
%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0, 10, 100)
y = np.sin(x)
plt.plot(x, y)
plt.show()
通过使用这些库和方法，可以大大简化Python科学计算代码，提高开发效率。
