CODEWITHSUNDEEP
pythonpandasdataframenumpybackend
AXz
AXz

Reputation: 316

Get the Month with year including one character in python

I'm trying to get the months list with year like [ "2019M10", "2019M11", "2019M12", "2020M01", "2020M02", "2020M03", "2020M04", "2020M05", "2020M06", "2020M07", "2020M08", "2020M09", "2020M10", "2020M11", "2020M12", "2021M01", "2021M02", "2021M03", "2021M04", "2021M05" ] Following Code Sample I'm using

import datetime
import json
from_year = 2018
last_year = datetime.datetime.now().year
print(last_year)
year_list = list(range(from_year, last_year))
new_month = []
for all_year in year_list:
    all_months = [str(all_year)+'M'+str(i) for i in list(range(1,13))]
    all_months.extend(all_months)
print(all_months )
months = json.dumps(all_months)
print(months)

I'm not getting the desired output.

Upvotes: 1

Views: 161

Answers (2)

Ajay
Ajay

Reputation: 5347

you are creating a new list every time you loop and extending it .So the last data is getting wiped off and filled with the latest data and you are extending it .So the data is appearing twice.

The solution given by @jezarel is most efficient, but then you can make these modification

import datetime
import json
from_year = 2018
last_year = datetime.datetime.now().year
print(last_year)
year_list = list(range(from_year, last_year))
print(year_list)
new_month = []
all_months=[]
for all_year in year_list:
    new_all_months = [str(all_year)+'M'+str(i) for i in list(range(1,13))]
    all_months.extend(new_all_months)

Upvotes: 0

jezrael
jezrael

Reputation: 863056

Use Timestamp.to_period for actual year and month, create PeriodIndex by period_range and then convert values to format YYYYMmm by PeriodIndex.strftime:

from_year = 2018
last_year = pd.to_datetime('now').to_period('m')
print(last_year)
2021-07

months = pd.period_range(from_year, last_year, freq='M').strftime('%YM%m').tolist()
print (months)
['2018M01', '2018M02', '2018M03', '2018M04', '2018M05', '2018M06', '2018M07', '2018M08',
 '2018M09', '2018M10', '2018M11', '2018M12', '2019M01', '2019M02', '2019M03', '2019M04',
 '2019M05', '2019M06', '2019M07', '2019M08', '2019M09', '2019M10', '2019M11', '2019M12', 
 '2020M01', '2020M02', '2020M03', '2020M04', '2020M05', '2020M06', '2020M07', '2020M08', 
 '2020M09', '2020M10', '2020M11', '2020M12', '2021M01', '2021M02', '2021M03', '2021M04', 
 '2021M05', '2021M06', '2021M07']

If need all months add next year and then slice last value of months:

from_year = 2018
last_year = pd.to_datetime('now').year + 1
print(last_year)
2022

months = pd.period_range(from_year, last_year, freq='M')[:-1].strftime('%YM%m').tolist()
print (months)
['2018M01', '2018M02', '2018M03', '2018M04', '2018M05', '2018M06', '2018M07', '2018M08', 
 '2018M09', '2018M10', '2018M11', '2018M12', '2019M01', '2019M02', '2019M03', '2019M04',
 '2019M05', '2019M06', '2019M07', '2019M08', '2019M09', '2019M10', '2019M11', '2019M12',
 '2020M01', '2020M02', '2020M03', '2020M04', '2020M05', '2020M06', '2020M07', '2020M08', 
 '2020M09', '2020M10', '2020M11', '2020M12', '2021M01', '2021M02', '2021M03', '2021M04', 
 '2021M05', '2021M06', '2021M07', '2021M08', '2021M09', '2021M10', '2021M11', '2021M12']

Your solution with nested list comprehension with flatten:

from_year = 2018
last_year = datetime.datetime.now().year
print(last_year)
2021

year_list = list(range(from_year, last_year))

months = [f'{all_year}M{i:02}' for all_year in year_list for i in list(range(1,13))]
print (months)

['2018M01', '2018M02', '2018M03', '2018M04', '2018M05', '2018M06', '2018M07', '2018M08',
 '2018M09', '2018M10', '2018M11', '2018M12', '2019M01', '2019M02', '2019M03', '2019M04', 
 '2019M05', '2019M06', '2019M07', '2019M08', '2019M09', '2019M10', '2019M11', '2019M12', 
 '2020M01', '2020M02', '2020M03', '2020M04', '2020M05', '2020M06', '2020M07', '2020M08', 
 '2020M09', '2020M10', '2020M11', '2020M12', '2021M01', '2021M02', '2021M03', '2021M04',
 '2021M05', '2021M06', '2021M07', '2021M08', '2021M09', '2021M10', '2021M11', '2021M12']

Upvotes: 1

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