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iterrows turns some columns from int64 to float64
See original GitHub issue>>> import pandas as pd
>>> pd.version.version
'0.15.2'
>>> df = pd.DataFrame({u'A': {123.0: 2.0}, u'B': {123.0: 1}})
>>> df
A B
123 2 1
>>> df['B'].dtype
dtype('int64')
>>> type(df.iterrows().next()[1]['B'])
<type 'numpy.float64'>
Issue Analytics
- State:
- Created 8 years ago
- Comments:5 (3 by maintainers)
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Sorry for reopening, is there a way of iterating over rows and keeping dtype?
Because people do complain about it being slow 😃 And also quite some people use loops for things that are really not necessary, and even more complex to do with a loop (eg adding a number to all elements, I’ve seen this a lot when teaching pandas to beginners). But you’re right, in certain cases, and if you know what you’re doing, nothing wrong with it.