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I have a CSV which has dates in this format:

Date
01/01/1997
02/01/1997
03/01/1997
04/01/1997

I am importing the data into a dataset using df = pd.read_csv('data.csv')

When I look at the data held in the dataframe it appears in a different format:

df['Date']


Date
1997-1-1
1997-1-2
1997-1-3
1997-1-4

I don't understand why this is happening.

I've tried Googling & looking on SOF but haven't been able to find the answer...

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6
  • What does df["Date"].dtype show? I believe pandas has automatically recognized that this column contains dates and converted them to datetype objects. You may wish to keep df["Date"] in this format, however, and do what @DeepSpace suggested below. Or add dtype={"Date" : str} to your read_csv() call to keep these values unchanged (and as strings). Commented Jul 27, 2016 at 14:55
  • 4
    YYYY-MM-DD is the ISO 8601 date format. iso.org/iso/home/standards/iso8601.htm Commented Jul 27, 2016 at 14:56
  • @dmn df['Date'].dtype gives dtype('O') ?? If I pass dtype={'GMT': str} I still get dtype('O') Commented Jul 27, 2016 at 15:06
  • @VinylWarmth that's ok. When you pass in dtype={"GMT" : str} do the dates look the way you want them to? Commented Jul 27, 2016 at 15:25
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    dtype('O') - means 'object' (or string in pandas terminology) Commented Jul 27, 2016 at 15:59

2 Answers 2

Reset to default
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Because that's pandas default time format.

You can pass read_csv dayfirst=True, as can be seen in the documentation:

dayfirst : boolean, default False DD/MM format dates, international and European format

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2 Comments

Thanks for your answer. Can you explain why the same isn't happening for another dataset? In the other dataset the CSV looks like 12/02/2006 and in pandas it looks the same: 12/02/2006
@VinylWarmth Try what @dmn suggested in the comments on both the datasets. It is possible that in the second case the column type is str and not datetime.
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You can use parse_dates option from read_csv to get data in same format as on your .csv file. Key is dayfirst=True to get dates first then month and you can change accordingly. You can also change the format as below: 

df.apply(pd.to_datetime, dayfirst=True)

For further readings, refer the documentation http://pandas-docs.github.io/pandas-docs-travis/

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@VinylWarmth please verify the answer if this worked for you .

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