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Why does pandas.concat in Python 3.13 result in MemoryError with small DataFrames when using axis=1?

Asked 1 month ago

0

101

python

What I Have Tried

I checked this similar question from 2023, but that issue was related to axis=0.
I tried using pd.merge, which works, but I specifically need concat for my pipeline's performance.

Actual Error Message: MemoryError: Unable to allocate 128 GiB for an array with shape...

1import pandas as pd
2import numpy as np
3
4# Creating three small DataFrames
5df1 = pd.DataFrame(np.random.randn(100, 5))
6df2 = pd.DataFrame(np.random.randn(100, 5))
7df3 = pd.DataFrame(np.random.randn(100, 5))
8
9# This line triggers the MemoryError
10result = pd.concat([df1, df2, df3], axis=1)
11

1import pandas as pd
2import numpy as np
3
4# Creating three small DataFrames
5df1 = pd.DataFrame(np.random.randn(100, 5))
6df2 = pd.DataFrame(np.random.randn(100, 5))
7df3 = pd.DataFrame(np.random.randn(100, 5))
8
9# This line triggers the MemoryError
10result = pd.concat([df1, df2, df3], axis=1)
11

Why does pandas.concat in Python 3.13 result in MemoryError with small DataFrames when using axis=1?

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Why does pandas.concat in Python 3.13 result in MemoryError with small DataFrames when using axis=1?

Why does pandas.concat in Python 3.13 result in MemoryError with small DataFrames when using axis=1?

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Why does pandas.concat in Python 3.13 result in MemoryError with small DataFrames when using axis=1?