How to shuffle data in Pandas

How to shuffle data in Pandas

Shuffle rows using 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:

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 rows using 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:

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.

Shuffle 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:

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.