converting Month and Year to Datetime

Question

I have a dataset with Month and Year as separate columns. I want to create a new column with Date with includes the Day , in this case it could be the 1st of every month.

Month Year 
1     2013
1     2013
2     2013
2     2013

df['Date'] = pd.to_datetime(df['Month'])

Expected output :

Month Year Date
1     2013 1/1/2013
1     2013 1/1/2013
2     2013 1/2/2013
2     2013 1/2/2013

format = %d%m%y

Answer 1

您可以在to_datetime指定格式，如下所示：

df['Date']=df.apply(lambda row: pd.to_datetime(str(row.Month) + '/'+ str(row.Year)), axis = 1) 

Answer 2

df = pd.DataFrame({'Month':[1,1,2,2], 'Year':[2013, 2013, 2013, 2013]})
# apply each single row with this lambda function
df['Date'] =  df.apply(lambda row: '1' + '/' + str(row.Month) + '/'+ str(row.Year), axis = 1)
print(df.to_string(index=False))

Output is

Month  Year      Date
    1  2013  1/1/2013
    1  2013  1/1/2013
    2  2013  1/2/2013
    2  2013  1/2/2013

Answer 3

I have tried some ways and I found that nearly all results have same point that dif f with your demands, they are usually like this 01/02/2012 . if you don't like "0", you can try this way but a little complex

temp = pd.DataFrame({"Year":df["Year"],"Month":df['Month'],"day":1})
a = pd.to_datetime(temp)
c = []
for item in a:
    c.append(str(item.day) + "/" + str(item.month) + "/" + str(item.year))
df['Date'] = c