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Ok I looked it up and apparently the dataset is mislabeled, the first variable has the dates. I’m new to python, and didn’t know it would find the first one that.

A:

You can always use Pandas Dataframe object to convert the dates to appropriate numeric type, instead of converting all the dates manually. You can also use list comprehension to iterate over the dates and just convert them to numbers:
In [41]: df = pd.DataFrame({‘A’ : [‘a’,’b’,’c’], ‘dates’: [‘1/1/2015′,’2/2/2016′,’3/3/2018’]})

In [42]: df
Out[42]:
A dates
0 a 1/1/2015
1 b 2/2/2016
2 c 3/3/2018

In [43]: df[‘dates’] = [pd.to_numeric(i, errors=’coerce’) for i in df[‘dates’]]

In [44]: df
Out[44]:
A dates
0 a 2015-01-01
1 b 2016-02-02
2 c 2018-03-03

Since pd.to_numeric sorts them by default, just using the above list comprehension would give you the correct output.

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