sht_3.range('A1').column_width=2.2sht_3.range('A1').row_height=15.6修改表三B1单元格颜色...
让我们首先提取pi的值,我们知道它是math.pi。 Let’s first extract the value of pi, which we know is math.pi. 我们可以把这个数除以2。 We can then take this number and divide that by 2. 这是π除以2。 So this is pi over 2. 为了得到这个数字的sin,我们说math.sin并使用math.pi除以2作为...
image_original_gray, image_warped_gray, source, destination, np.column_stack((inlier_idxs, inlier_idxs)), matches_color='b') axes[0].axis('off'), axes[0].set_title('Correct correspondences', size=20) outlier_idxs = np.
宽高(索引从1开始) """ sheet.row_dimensions[1].height = 50 sheet.column_dimensions["E"].width = 100 wb.save("p2.xlsx") """ # 10.合并单元格 """ sheet.merge_cells("B2:D8") sheet.merge_cells(start_row=15, start_column=3, end_row=18, end_column=8) wb.save("p2.xlsx") ...
degree+=1X_train = np.column_stack([np.power(x_train,i)foriinrange(0,degree)]) model = np.dot(np.dot(np.linalg.inv(np.dot(X_train.transpose(),X_train)),X_train.transpose()),y_train) plt.plot(x,y,'g') plt.xlabel("x") ...
import matplotlib.pyplot as plt # 绘制柱状图 df[column_name].plot(kind="bar") # 绘制散点图 df.plot(x="column_name1", y="column_name2", kind="scatter") 数据分析 # 描述性统计分析 df.describe() # 相关性分析 df.corr() # 回归分析 from sklearn.linear_model impor...
Other transformations such as sort can be done using sort attribute. Now let's extract a specific column. In Python, we do it using either iloc or ix attributes, but ix is more robust and thus I prefer it. Assuming we want the head of the first column of the data, we have ...
numpy.arange 是 NumPy 中一个常用的函数,用于生成一个包含等差数列的数组。本文主要介绍一下NumPy中arange方法的使用。 numpy.arange numpy.arange([start, ]stop, [step, ]dtype=None) 返回给定间隔内的均匀间隔的值。 在半开间隔[start,stop)(换句话说,该间隔包括start但不包括stop)内生成值。 对于整数参数...
importnumpyasnp# 定义 x 和 y 的一维数组x = np.array([1,2,3]) y = np.array([4,5,6])# 生成网格,使用 'ij' 索引xv_ij, yv_ij = np.meshgrid(x, y, sparse=False, indexing='ij') nx, ny = len(x), len(y) print("Using 'ij' indexing:")foriinrange(nx):forjinrange(ny):...
1c=np.array([1, 2, 3], dtype=float)2c.dtype[29]:dtype('float64')1c[30]:array([1., 2., 3.])1c.astype(np.int8).dtype[16]:dtype('int8')1c.astype(np.int8)[31]:array([1, 2, 3], dtype=int8) overflow 默认数据类型为np.float_ ...