Converting a datetime column to a string column

Question

I'm trying to convert a datetime column back to a string in Pandas dataframe.

the syntax I have so far is:

all_data['Order Day new'] = dt.date.strftime(all_data['Order Day new'], '%d/%m/%Y')

but this returns the error:

descriptor 'strftime' requires a 'datetime.date' object but received a 'Series'.

Can anyone tell me where I'm going wrong.

EdChum · Accepted Answer · 2019-04-09T08:19:08.927

If you're using version 0.17.0 or higher then you can call this using .dt.strftime which is vectorised:

all_data['Order Day new'] = all_data['Order Day new'].dt.strftime('%Y-%m-%d')

** If your pandas version is older than 0.17.0 then you have to call apply and pass the data to strftime:

In [111]:

all_data = pd.DataFrame({'Order Day new':[dt.datetime(2014,5,9), dt.datetime(2012,6,19)]})
print(all_data)
all_data.info()
  Order Day new
0    2014-05-09
1    2012-06-19
<class 'pandas.core.frame.DataFrame'>
Int64Index: 2 entries, 0 to 1
Data columns (total 1 columns):
Order Day new    2 non-null datetime64[ns]
dtypes: datetime64[ns](1)
memory usage: 32.0 bytes

In [108]:

all_data['Order Day new'] = all_data['Order Day new'].apply(lambda x: dt.datetime.strftime(x, '%Y-%m-%d'))
all_data
Out[108]:
  Order Day new
0    2014-05-09
1    2012-06-19
In [109]:

all_data.info()
<class 'pandas.core.frame.DataFrame'>
Int64Index: 2 entries, 0 to 1
Data columns (total 1 columns):
Order Day new    2 non-null object
dtypes: object(1)
memory usage: 32.0+ bytes

You can't call strftime on the column as it doesn't understand Series as a param hence the error

In pandas `1.0.5` this is producing a `SettingWithCopyWarning`. — Andi, Aug 20 '20 at 11:07

Chris · Answer 2 · 2020-03-03T10:43:16.777

32

all_data['Order Day new']=all_data['Order Day new'].astype(str)

I think this is more simple, if the date is already in the format you want it in string form.

edited Mar 03 '20 at 10:43

answered Mar 03 '20 at 09:50

Chris

951
10
26

Please add some explanation to your answer by editing it, such that others can learn from it – Nico Haase Mar 03 '20 at 10:21
1

@NicoHaase not much to explain I think, just using the .astype method – Chris Mar 03 '20 at 10:32
Well, then explain why you've used it anyways. The accepted answer (that means: the one that solved the OP's problem) does not use it, and then you should explain what makes your solution better – Nico Haase Mar 03 '20 at 10:35
@NicoHaase ok, added that its more simple – Chris Mar 03 '20 at 10:37
Do you **think** that or is that the case? Does it return the same value as `strftime('%Y-%m-%d')`? – Nico Haase Mar 03 '20 at 10:39
1

I checked it and yes – Chris Mar 03 '20 at 10:42
I like this answer, and it seems to work with NaT values in the column. – Malachi Bazar Dec 14 '20 at 19:19

Lijo Abraham · Answer 3 · 2021-03-10T17:26:04.367

14

For converting all datetime columns to string use the below code.

for x in  df.select_dtypes(include=['datetime64']).columns.tolist():
    df[x] = df[x].astype(str)

or

date_columns = df.select_dtypes(include=['datetime64']).columns.tolist()
df[date_columns] = df[date_columns].astype(str)

edited Mar 10 '21 at 17:26

answered Feb 25 '21 at 11:13

Lijo Abraham

841
8
30

score 0 · Answer 4 · answered Feb 02 '21 at 05:55

0

In my case I had a pySpark dataframe. This is how I converted "day" of type timestamp, to a string:

import pyspark.sql.functions as F
convertedDf = rawDf.withColumn('d2', F.date_format(rawDf['day'], 'yyyyMMdd'))

answered Feb 02 '21 at 05:55

Raj Rao

8,872
12
69
83

Converting a datetime column to a string column

4 Answers4

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