TypeError: '>=' Not Supported Between Instances Of 'float' And 'str'

Looking to map highest matching row values from Dataframe2 to Dataframe1 using conditions. We also need to check df1['sal_date'] between df2['from'] and df['to']. df1 score id_nu

Solution 1:

I believe the problem is that you need to convert the dates into UNIX, because Python just doesn not know how to compare dates. So, try to convert the date into a datetime.datetime object, and then into UNIX time:

import datetime
import time

# Let's say, the date is:
date_string = '2019-12-22'

# We need to turn it into a list first:
date_tuple = date_string.split('-') 

# Make an Datetime object
datetime_object = datetime.datetime(int(date_tuple[0]), int(date_tuple[1]), int(date_tuple[2]))

# Then, convert it into UNIX timestamp:
unix = time.mktime(datetime_object.timetuple())

print(unix)

Then, you just need to compare it like you would normally.

EDIT

I just need to check for if and else condition when there is any NaN value in df1["sal_Date"]

You can check if a variable has content or not using this:

var1 = 'hello'
var2 = ''

if var1:
    print('var1 has content')
else:
    print('var1 is empty')

if var2:
    print('var2 has content')
else:
    print('var2 is empty')

To check if there is any NaN value in a list:

foods = ['Pizza', '', 'Apple']

for food in foods:
    if not food:
        print('There IS an empty element in the list.')