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I'm trying to swap the rows within the same DataFrame in pandas.
I've tried running
a = pd.DataFrame(data = [[1,2],[3,4]], index=range(2), columns = ['A', 'B'])
b, c = a.iloc[0], a.iloc[1]
a.iloc[0], a.iloc[1] = c, b
but I just end up with both the rows showing the values for the second row (3,4).
Even the variables b and c are now both assigned to 3 and 4 even though I did not assign them again. Am I doing something wrong?
662
Pandas DataFrame: transpose() function The transpose() function is used to transpose index and columns. Reflect the DataFrame over its main diagonal by writing rows as columns and vice-versa. If True, the underlying data is copied. Otherwise (default), no copy is made if possible.
loc and iloc are interchangeable when labels are 0-based integers.
For a DataFrame a dict can specify that different values should be replaced in different columns. For example, {'a': 1, 'b': 'z'} looks for the value 1 in column 'a' and the value 'z' in column 'b' and replaces these values with whatever is specified in value .
Use a temporary varaible to store the value using .copy(), because you are changing the values while assigning them on chain i.e. Unless you use copy the data will be changed directly.
a = pd.DataFrame(data = [[1,2],[3,4]], index=range(2), columns = ['A', 'B'])
b, c = a.iloc[0], a.iloc[1]
temp = a.iloc[0].copy()
a.iloc[0] = c
a.iloc[1] = temp
Or you can directly use copy like
a = pd.DataFrame(data = [[1,2],[3,4]], index=range(2), columns = ['A', 'B'])
b, c = a.iloc[0].copy(), a.iloc[1].copy()
a.iloc[0],a.iloc[1] = c,b
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