In pandas, can I deeply copy a DataFrame including its index and column?
pandas, python
Solution
Latest version of Pandas does not have this issue anymore
import pandas as pd
df = pd.DataFrame([[1], [2], [3]])
df2 = df.copy(deep=True)
id(df), id(df2)
Out[3]: (136575472, 127792400)
id(df.index), id(df2.index)
Out[4]: (145820144, 127657008)
Problem
First, I create a DataFrame ``` In [61]: import pandas as pd In [62]: df = pd.DataFrame([[1], [2], [3]]) ``` Then, I deeply copy it by `copy` ``` In [63]: df2 = df.copy(deep=True) ``` Now the `DataFrame` are different. ``` In [64]: id(df), id(df2) Out[64]: (4385185040, 4385183312) ``` However, the `index` are still the same. ``` In [65]: id(df.index), id(df2.index) Out[65]: (4385175264, 4385175264) ``` Same thing happen in columns, is there any way that I can easily deeply copy it not only values but also index and columns?