Shuffling/permutating a DataFrame in pandas

Shuffling/permutating a DataFrame in pandas

To shuffle or permute a DataFrame in Pandas, you can use the sample method with the frac parameter set to 1.0 (to include all rows) and random_state for reproducibility. Here's how to do it:

import pandas as pd # Create a sample DataFrame data = { 'A': [1, 2, 3, 4, 5], 'B': [10, 20, 30, 40, 50], } df = pd.DataFrame(data) # Shuffle/permute the DataFrame shuffled_df = df.sample(frac=1.0, random_state=42) # Display the shuffled DataFrame print(shuffled_df)

In this code:

  • frac=1.0 ensures that you include all rows from the original DataFrame in the shuffled DataFrame.
  • random_state is set to a specific value (e.g., 42) to make the shuffling reproducible. You can choose any integer value for random_state, or you can omit it if you don't need reproducibility.

After running this code, shuffled_df will contain the same data as df, but with rows shuffled randomly.

If you want to reset the index after shuffling, you can use the reset_index method:

shuffled_df = shuffled_df.reset_index(drop=True)

This will remove the old index and replace it with a new one. The drop=True parameter ensures that the old index is not added as a new column in the DataFrame.

Keep in mind that shuffling a DataFrame can be useful for various purposes, such as preparing data for machine learning by creating randomized training and testing datasets.

Examples

  1. How to shuffle a DataFrame in pandas? Description: This query seeks to understand how to randomly shuffle the rows of a DataFrame in pandas. Code:

    import pandas as pd # Assuming df is your DataFrame df_shuffled = df.sample(frac=1, random_state=42) # Shuffling using sample() function

  2. Permutating DataFrame columns in pandas Description: This query is about permutating or rearranging the columns of a DataFrame in pandas. Code:

    import pandas as pd import numpy as np # Assuming df is your DataFrame columns_permuted = np.random.permutation(df.columns) df_permuted = df[columns_permuted]

  3. Random row selection from DataFrame in pandas Description: Users often want to select a random subset of rows from a DataFrame in pandas. Code:

    import pandas as pd # Assuming df is your DataFrame random_rows = df.sample(n=10, random_state=42) # Selecting 10 random rows

  4. How to shuffle DataFrame index in pandas? Description: This query deals with shuffling the index of a DataFrame in pandas. Code:

    import pandas as pd # Assuming df is your DataFrame df_shuffled_index = df.sample(frac=1).reset_index(drop=True) # Resetting index after shuffling

  5. Reordering DataFrame rows randomly in pandas Description: Users may need to reorder DataFrame rows randomly rather than shuffling. Code:

    import pandas as pd import numpy as np # Assuming df is your DataFrame indices_randomized = np.random.permutation(df.index) df_reordered = df.iloc[indices_randomized]

  6. How to shuffle DataFrame columns without changing their order? Description: This query is about shuffling the data within DataFrame columns without altering their positions. Code:

    import pandas as pd import numpy as np # Assuming df is your DataFrame df_shuffled_columns = df.apply(np.random.permutation)

  7. Randomizing DataFrame values in pandas Description: Users may want to randomize the values within a DataFrame in pandas. Code:

    import pandas as pd import numpy as np # Assuming df is your DataFrame df_randomized = df.applymap(lambda x: np.random.choice(df.values.ravel()))

  8. Shuffling DataFrame rows with replacement in pandas Description: Sometimes, users might want to shuffle DataFrame rows with replacement, meaning rows can occur multiple times. Code:

    import pandas as pd # Assuming df is your DataFrame df_shuffled_with_replacement = pd.concat([df] * 3).sample(frac=1).reset_index(drop=True)

  9. Randomizing DataFrame elements within a specific column in pandas Description: This query focuses on randomizing the elements within a particular column of a DataFrame. Code:

    import pandas as pd # Assuming df is your DataFrame and 'column_name' is the column you want to shuffle df['column_name'] = df['column_name'].sample(frac=1).reset_index(drop=True)

  10. How to shuffle DataFrame values in a specific column in pandas? Description: Users may want to shuffle the values within a specific column of a DataFrame in pandas. Code:

    import pandas as pd # Assuming df is your DataFrame and 'column_name' is the column you want to shuffle df['column_name'] = df['column_name'].sample(frac=1, random_state=42).reset_index(drop=True)

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