Coding Ref

`sample`

To shuffle a Pandas DataFrame, you can use the `sample`

method. This method will randomly shuffle the rows of the DataFrame.

For example, to shuffle the DataFrame `df`

, you could do the following:

main.py

```
import pandas as pd
# Shuffle the DataFrame
df = df.sample(frac=1)
```

In the code above, the `sample`

method is applied to the DataFrame with the `frac`

parameter set to `1`

.

This tells the `sample`

method to return a DataFrame with the same number of rows as the original DataFrame, but with the rows in a random order.

`shuffle`

method from `sklearn.utils`

You can also use the `shuffle`

method from the `sklearn.utils`

module to shuffle the rows of a DataFrame.

This method takes the DataFrame as input and returns a new DataFrame with the rows in a random order. For example:

main.py

```
from sklearn.utils import shuffle
import pandas as pd
# Shuffle the DataFrame
df = shuffle(df)
```

In the code above, the `shuffle`

method is used to shuffle the rows of the DataFrame `df`

. This method will return a new DataFrame with the rows in a random order.

Both of these methods will shuffle the rows of a DataFrame, but they will not shuffle the columns.

If you want to shuffle the columns of a DataFrame, you can use the `numpy.random.permutation`

method to generate a list of shuffled column names, and then use this list to reorder the columns of the DataFrame.

For example:

main.py

```
import numpy as np
import pandas as pd
# Get the column names of the DataFrame
columns = df.columns
# Use numpy to randomly permute the column names
columns = np.random.permutation(columns)
# Use the shuffled column names to reorder the columns of the DataFrame
df = df[columns]
```

In the code above, the `numpy.random.permutation`

method is used to generate a list of shuffled column names.

This list is then used to reorder the columns of the DataFrame. This will result in a DataFrame with the columns in a random order.

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