How to Split a Large Pandas DataFrame into Equal Parts?

Splitting a Large Pandas DataFrame

Consider a large pandas DataFrame consisting of 423244 rows. The need arises to divide this DataFrame into four equal parts. However, an attempt using np.split(df, 4) throws a "ValueError: array split does not result in an equal division" error.

To address this issue, np.array_split should be employed. Unlike np.split, np.array_split allows indices_or_sections to be an integer that does not produce an equal axis division.

<code class="python">import pandas as pd
import numpy as np

# Create a DataFrame
df = pd.DataFrame({'A': ['foo', 'bar', 'foo', 'bar', 'foo', 'bar', 'foo', 'foo'],
                   'B': ['one', 'one', 'two', 'three', 'two', 'two', 'one', 'three'],
                   'C': np.random.randn(8),
                   'D': np.random.randn(8)})

# Split the DataFrame into three equal parts
result = np.array_split(df, 3)

# Print the results
for i in range(len(result)):
    print(f"Part {i + 1}:")
    print(result[i])
    print()</code>

This code will split the DataFrame into three approximately equal parts. The number of parts can be adjusted as needed.

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