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iterrows changes dtype of columns
See original GitHub issueIn [105]: df = pd.DataFrame([[1, 1.0]], columns=['x', 'y'])
In [112]: row = next(df.iterrows())[1]
In [113]: row
Out[113]:
x 1
y 1
Name: 0, dtype: float64
In [114]: row['x'].dtype
Out[114]: dtype('float64')
In [115]: df['x'].dtype
Out[115]: dtype('int64')
Issue Analytics
- State:
- Created 10 years ago
- Comments:10 (9 by maintainers)
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this is by definition correct, dtypes are maintained only in the columns
the dtype is the lowest common denomincator of the row dtypes, which in this case is float
closed by #3569