Date creation using different columns in pandas

Question

Having a data frame as below:

Day	Month and year
13	septiembre /98
15	August/98
24	Novem /98

Is it possible that i can merge day with month and year and create a new column.

Day	Month and year	Date
13	septiembre /98	13-09-98
15	August/98	15-08-98
24	Nov /98	24-11-98

Asked By: Nikita Menon

||

Source

Answer 1

You could perform string slicing and concatenation provided that your dataset comes in a predictable and standard format. Cast this new string to datetime using the pd.to_datetime method.

For example, this would work for your example:

import pandas as pd

df = pd.DataFrame([[13, 'Septiembre /98'], [15, 'August/98'], [24, 'Novem /98']], columns=["Day", "Month and year"])
df['Date'] = pd.to_datetime(
    df['Day'].astype('str') +
    ' - ' +
    df['Month and year'].str.slice(0, 3) +
    ' - ' +
    df['Month and year'].str.slice(-2)
)

print(df)

   Day  Month and year       Date
0   13  Septiembre /98 1998-09-13
1   15       August/98 1998-08-15
2   24       Novem /98 1998-11-24

Answered By: irahorecka

Answer 2

I was able to create a panda Series that converts the data you provided from a list to a new list, and then obtains a panda Series from the new, correctly formatted list. I’m not sure if that’s what you wanted, but anyway I hope this can be of some help:

import pandas as pd

day = [13, 15, 24]
monthyear = ['Semptember/98', 'August/98', 'November/98'] 
daymonthyear = zip(day, monthyear)
daymonthyear_new = []

for i in daymonthyear:
    teste = [i[0],i[1].split("/")]
    string = str(teste[0]) + "-" + str(teste[1][0]) + "-" + 
    str(teste[1][1])

print('string= ', string)
daymonthyear_new.append(string)

print('daymonthyear_new= ', daymonthyear_new)

import datetime

dates = pd.Series(daymonthyear_new)

dates

Answered By: Marcelo Carvalho

Date creation using different columns in pandas

Question:

Answers: