[Python] Grouping Lats and Lons within a distance of 0.00004 of each other using Pandas

I have an excel file with 2 columns titled Lat and Lon with some data such as:

Lat Lon
36.19553° N 95.90918° W
36.19550° N 95.93592° W
36.20277° N 95.94484° W
36.20277° N 95.95381° W
36.22436° N 95.98023° W
36.21005° N 95.94487° W
36.21006° N 95.93594° W
35.99968° N 96.09681° W
35.97043° N 95.98949° W
35.96317° N 95.98951° W
35.99968° N 96.11459° W
35.99967° N 96.10568° W
35.96318° N 95.99839° W
35.96315° N 96.00728° W
35.99239° N 96.13247° W


I am trying to read in the excel file and group each one that is within a distance of 0.00004 in the last place of each other in either the lat or the lon column into a group. It should start with the first row and check each row looking for another one that is within a distance of 0.00004 and insert a number starting a one in a column called 'Drive' for each grouping.

the expected output is supposed to be:

Lat Lon Drive
0 36.19553 95.90918 1
1 36.19550 95.93592 1
2 36.20277 95.94484 2
3 36.20277 95.95381 2
4 36.22436 95.98023 3
5 36.21005 95.94487 2
6 36.21006 95.93594 1
7 35.99968 96.09681 4
8 35.97043 95.98949 5
9 35.96317 95.98951 5
10 35.99968 96.11459 4
11 35.99967 96.10568 4
12 35.96318 95.99839 5
13 35.96315 96.00728 5
14 35.99239 96.13247 6


I have made several attempt with no success.

here is the latest attempt:
# Read the data into a pandas DataFrame
df = pd.read_excel('data.xlsx')

# Convert Lat and Lon to absolute values for easy comparison
df['Lat'] = df['Lat'].abs()
df['Lon'] = df['Lon'].abs()

# Initialize the counter and group column
counter = 1
df['Drive'] = 0

# Loop over the DataFrame rows
for i in range(len(df)):
if df['Drive'] == 0:
df.loc[(df['Lat'].between(df['Lat'] - 4, df['Lat'] + 4)) &
(df['Lon'].between(df['Lon'] - 4, df['Lon'] + 4)), 'Drive'] = counter
counter += 1

# Print the result
print(df)


I get the error bad operand type for abs(): 'str'

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