pandas dataframe column to datetime

Question

I expect I have a typo but I can't see it.

df = pd.to_datetime(gdf['startdate'], format="%m/%d/%Y %H:%M:%S")

This gives the eroor:

ValueError: time data '16/06/2020 09:01:31' does not match format '%m/%d/%Y %H:%M:%S' (match)

gdf['startdate'] looks like this:

0      08/06/2020 13:31:14
1      08/06/2020 14:42:45
2      08/06/2020 14:34:13
3      09/06/2020 12:20:41
4      09/06/2020 15:31:36
              ...         

144    29/07/2020 11:36:34
145    30/07/2020 12:31:17
146    31/07/2020 14:27:36
147    31/07/2020 08:21:14
148    06/08/2020 12:08:38
Name: startdate, Length: 149, dtype: object

Sander van den Oord · Accepted Answer · 2020-11-06 15:58:15Z

2

I switched around %d and %m in your formatting:

gdf['startdate'] = pd.to_datetime(
    gdf['startdate'], 
    format="%d/%m/%Y %H:%M:%S",
)

If a value in your column is not like a datetime at all and causing errors, you can use errors='coerce' to set those to NaT:

gdf['startdate'] = pd.to_datetime(
    gdf['startdate'], 
    format="%d/%m/%Y %H:%M:%S",
    errors='coerce',
)

edited Nov 6, 2020 at 15:58

answered Nov 6, 2020 at 15:27

Sander van den Oord

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5 Comments

Spatial Digger Over a year ago

Thanks, but now this error ValueError: time data ' ' does not match format '%d/%m/%Y %H:%M:%S' (match)

Sander van den Oord Over a year ago

The error is quite informative: I guess one of the values in your column is not in that format, i guess it has format ' ' as the error says, you can use parameter errors='coerce' if you want to convert this to NaT.

Spatial Digger Over a year ago

thanks, that forces it through, although when I try df.date() I get: AttributeError: 'Series' object has no attribute 'date' Ultimately I'm trying to just get the date information cutting out the h:m:s

Sander van den Oord Over a year ago

df['startdate'] is what you need or? in your example there's no column 'date'

Spatial Digger Over a year ago

Ah, got it! gdf['startdate'].dt.strftime("%d/%m/%Y")

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