Pandas “to_datetime” 不接受系列

Question

I am new to pandas and am trying to convert a column of strings with dates in the format '%d %B' (01 January, 02 January.... ) to date time objects and the type of the column is <class 'pandas.core.series.Series'> . if i pass in this series in the to_datetime method, like

print(pd.to_datetime(data_file['Date'], format='%d %B', errors="coerce"))

it all returns NaT for all the entries, where as it should return date time objects

I checked the documentation and it says that it accepts a Series object.

Any way to fix this?

Edit 1: here is the head of the data i am using:

           Date  Daily Confirmed
0   30 January                 1
1   31 January                 0
2  01 February                 0
3  02 February                 1
4  03 February                 1

edit 2: here is the information of the data

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 179 entries, 0 to 178
Data columns (total 2 columns):
 #   Column           Non-Null Count  Dtype 
---  ------           --------------  ----- 
 0   Date             179 non-null    object
 1   Daily Confirmed  179 non-null    int64 
dtypes: int64(1), object(1)
memory usage: 2.2+ KB

Answer 1

If I understand correctly, you may be facing this issue because there are spaces around the dates in this column. To solve it, use strip before to_datetime . Here's a piece of code that does that:

df = pd.DataFrame({'Date': 
                   ['30 January ', '31 January ', ' 01 February ', '02 February', 
                    '03 February'], 'Daily Confirmed': [1, 0, 0, 1, 1]})

pd.to_datetime(df.Date.str.strip(), format = "%d %B")

The output is:

0   1900-01-30
1   1900-01-31
2   1900-02-01
...

Answer 2

import pandas as pd 
dic =  {"Date": ["30 January", "31 January", "01 February", ] ,  "Daily Confirmed":[0,1,0]}
df =pd.DataFrame(dic)
df['date1'] = pd.to_datetime(df['Date'].astype(str), format='%d %B')
df

By default, it contains years as 1900. Because you did not provide year on your Dataframe Output:

    Date       Daily Confirmed  date1
0   30 January      0          1900-01-30
1   31 January      1          1900-01-31
2   01 February     0          1900-02-01

If you don't want year as prefix of date. Please add the below code:

df['date2']=df['date1'].dt.strftime('%d-%m')
df

    Date       Daily Confirmed  date1         date2
0   30 January      0          1900-01-30     30-1
1   31 January      1          1900-01-31     31-1
2   01 February     0          1900-02-01     01-2

Thanks

Answer 3

You may try this:

from datetime import datetime

df['datetime'] = df['date'].apply(lambda x: datetime.strptime(x, "%d %B"))

apply() allows you to use python functions in series, here you may have to specify the year otherwise the default year (1900) will be set as default.

Good luck