QST: why changing dataframe values impacts the array that the dataframe was created from?

[pinshuai]

• I have searched the [pandas] tag on StackOverflow for similar questions.

• I have asked my usage related question on StackOverflow.

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Question about pandas

>>> import numpy as np
>>> import pandas as pd

>>> mat = np.array([[1,2], [2,3]])
>>> mat
array([[1, 2],
       [2, 3]])

>>> df = pd.DataFrame(mat)
>>> df.iloc[0,1] = 4

>>> mat
array([[1, 4],
       [2, 3]])

Why the value in the original mat is also changed? I am not sure if this is a bug or Pandas' way of doing things. I found it to be very confusing.

[lithomas1]

From the pd.DataFrame constructor docs.

copy : bool or None, default None
Copy data from inputs. For dict data, the default of None behaves like copy=True. For DataFrame or 2d ndarray input, the default of None behaves like copy=False.

Changed in version 1.3.0.

If you do pd.DataFrame(mat, copy=True) the original is unchanged.

[Varun270]

@lithomas1 I am a beginner in open source and would love to work on this issue, I have cloned the repository but am unable to find the folder that has this code. Can you help me?

[Varun270]

take

[rhshadrach]

@Varun270 the relevant code will be in pandas.core.frame or pandas.core.generic. However, it seems to me there is no issue to be resolved here.

[attack68]

closing - democracy seems to have identified this as a non-issue, but rather an educational question for which an answer was given