Example of date column replace by function and change depending of the conditions [dirty]

script.py

import csv
import pandas as pd
import shutil
import pymysql
import sys
import re
from urllib.request import urlopen
from bs4 import BeautifulSoup
import sqlalchemy as sa
import pytz
from datetime import date, time, datetime, timedelta

timenow = datetime.now(pytz.timezone('Asia/Tokyo'))
timeyesterday = timenow - timedelta(days=1)
datenow = timenow.strftime('%d.%m.%Y')
dateyesterday = timeyesterday.strftime('%d.%m.%Y')
dnstr = datetime.strptime(datenow, '%d.%m.%Y')

def time_converter(get_val, pastdate):

    RU_MONTH_VALUES = {
        'янв': 1,
        'фев': 2,
        'мар': 3,
        'апр': 4,
        'мая': 5,
        'июн': 6,
        'июл': 7,
        'авг': 8,
        'сен': 9,
        'окт': 10,
        'ноя': 11,
        'дек': 12,
        'сегодня': datenow,
        'вчера': dateyesterday
    }

    def int_value_from_ru_month(date_str):
        for k, v in RU_MONTH_VALUES.items():
            date_str = date_str.replace(k, str(v))
        return date_str

    date_str = get_val
    date_str = int_value_from_ru_month(date_str)

    try:
        d = datetime.strptime(date_str, '%d %m, %H:%M')
    except:
        d = datetime.strptime(date_str, '%d.%m.%Y, %H:%M')

    if (d.year == 1900):
        if(d.month - dnstr.month > 1):
            d = d.replace(year=dnstr.year - 1)
        else:
            d = d.replace(year=dnstr.year)

    d = d.replace(day=pastdate)
    return d.strftime('%d.%m.%Y, %H:%M')

def rowIndex(id,date):
    if id <= 2000:
        return time_converter(date, 3)
    if 2000 < id <= 14000:
        return time_converter(date, 4)
    if 14000 < id <= 26000:
        return time_converter(date, 5)
    if 26000 < id <= 39500:
        return time_converter(date, 6)
    if 39500 < id <= 50000:
        return time_converter(date, 7)
    return date
        
df['publicDate'] = df.apply(lambda x: rowIndex(x['index'],x['publicDate']),1)
df.sort_values(by='index', ascending=False)