单击OK,关闭Layer Properties对话框。<br>3.要增加字段,在目录表中单击shapefile,从环境菜单中选择Open Attribute Table。<br>4.单击Options按钮,选择Add Field。<br>5.在Add Field对话框中,为新字段命名并选择数据类型。在Field Properties中设置相应的字段特性。<br>6.单击OK,关闭对话框。<br>给多个要素同一赋值<br>选中你需要同一赋值的是所有图斑,然后点击Atrributes,此时出现属性修改对话框,点击根目录是对所有要素同一赋值,点击下面的支目录则可以分别赋值。(也可以用字段计算器实现)<br>手册目录
"版权声明:本文为博主原创文章,遵循 CC 4.0 BY-SA版权协议,转载请附上原文出处链接和本声明。<br>1.导入相关模块<br>import numpy as np from sklearn.datasets import fetch_openml<br>2.MNIST Dataset<br>mnist = fetch_openml(""mnist_784"") X = mnist.data / 255.0 y = mnist.target X.shape, y.shape<br>数据转换为Pandas数据框架<br>import pandas as pd feat_cols = ['pixel' + str(i) for i in range(X.shape[1])] df = pd.DataFrame(X, columns=feat_cols) df['label'] = y df['label'] = df['label'].apply(lambda i: str(i)) X, y = None, None print('Size of the dataframe: {}'.format(df.shape))"