我正在努力通过TensorFlow 加载 pandas.DataFrame 教程,我正在尝试修改创建字典切片的代码片段的输出:
dict_slices = tf.data.Dataset.from_tensor_slices((df.to_dict('list'), target.values)).batch(16)
for dict_slice in dict_slices.take(1):
print (dict_slice)
我发现以下输出很草率,我想将其放入更易读的表格格式。
![Dictionary output from TensorFlow Tutorial](https://i.stack.imgur.com/Amaxl.png)
I tried to format the for loop, based on this recommendation
![Trying a basic for loop](https://i.stack.imgur.com/CRh1A.png)
这给了我 BatchDataset 不可下标的错误
![Error messages from for loop modification](https://i.stack.imgur.com/rqmCX.png)
Then I tried to use the range and leng function on the dict_slices, so that i would be an integer index and not a slice
![Modifying dict_slices with range and len](https://i.stack.imgur.com/J3Ibe.png)
这给了我以下错误(据我所知,因为 dict_slices 仍然是一个数组,并且每次迭代都是数组的一个向量,而不是向量的一个索引):
![enter image description here](https://i.stack.imgur.com/OG4LW.png)
Refer here以获得解决方案。总而言之,我们需要使用as_numpy_iterator
example = list(dict_slices.as_numpy_iterator())
example[0]['age']
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