randomly shuffle
时间: 2023-12-08 14:36:17 浏览: 102
机调整是指将数据集中的行随机打乱,以便更好地进行数据分析和模型训练。在Matlab中,可以使用以下代码实现随机调整表的行:
```matlab
% 读取Excel文件
data = readtable('filename.xlsx');
% 随机调整表的行
shuffled_data = data(randperm(size(data,1)),:);
```
其中,`readtable`函数用于读取Excel文件,`randperm`函数用于生成随机排列的索引,`size`函数用于获取数据集的大小。最后,将随机排列的索引应用于原始数据集,即可得到随机调整后的数据集。
相关问题
pandas shuffle data
To shuffle data in pandas, you can use the `sample()` function. Here's an example:
```python
import pandas as pd
# Create a sample DataFrame
data = {'A': [1, 2, 3, 4, 5],
'B': ['a', 'b', 'c', 'd', 'e']}
df = pd.DataFrame(data)
# Shuffle the DataFrame
shuffled_df = df.sample(frac=1).reset_index(drop=True)
```
In the above code, `sample(frac=1)` shuffles the rows randomly by sampling the entire DataFrame with a fraction of 1 (which means all rows are included), and `reset_index(drop=True)` resets the index of the shuffled DataFrame.
After shuffling, the `shuffled_df` DataFrame will contain the original data randomly reordered.
tf.compat.v1.random_shuffle
As an AI language model, I do not have access to the TensorFlow library, but I can provide you with information on the function tf.compat.v1.random_shuffle.
The tf.compat.v1.random_shuffle function is a part of the TensorFlow library and is used to randomly shuffle the elements of a tensor along its first dimension. It takes a tensor as input and returns a shuffled tensor of the same shape and type as the input.
This function is marked as "compat" because it is a legacy function that is no longer recommended for use in newer versions of TensorFlow. It is recommended to use the tf.random.shuffle function instead, which provides better performance and more features.
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