drop duplicates isnt working on my imported csv file - pandas

Question

Looking for some help on this one. I do not know why but drop duplicates is not working, tried a loop with lambda. still nothing I can do will remove mutlple duplicates on the output.
# Import files for use in the program:
import pandas as pd
import os
import matplotlib.pyplot as plt
import matplotlib.font_manager as fm
import matplotlib.dates as mdates
import numpy as np
import csv
Import CSV files into a data frame
Crash_Data_df = pd.read_csv("crash_data.csv",encoding='UTF-8')
#split date column
Crash_Data_df[["Day", "Month", "DayNum","Time","Zone","Year"]] =
Crash_Data_df["Date"].str.split(" ", n = 6, expand = True)
#define max and min dates
d_max=Crash_Data_df["Date"].min()
d_min=Crash_Data_df["Date"].max()
#split name column
Crash_Data_df[["A","B"]] = Crash_Data_df["Name"].str.split("_|2018100", n =
2, expand = True)
#Drop time zone
Crash_Data_df.drop(['Zone'], axis = 1, inplace = True)
Crash_Data_df.reset_index(drop=True)
# group by unnamed column
Crash_Data_df = Crash_Data_df.loc[Crash_Data_df['Unnamed: 0'] == 0, :]
#del columns
del Crash_Data_df['Unnamed: 0']
del Crash_Data_df['Name']
del Crash_Data_df['A']
Crash_Data_df = Crash_Data_df.loc[Crash_Data_df['B'] != 9954815, :]
Crash_Data_df = Crash_Data_df.dropna(how='any')
Crash_Data_df.drop_duplicates(subset=['Time'], keep=False)
Crash_Data_df.sort_values(by=['B'])
Crash_Data_df.reset_index(drop=True)
Crash_Data_df = Crash_Data_df.rename(columns=
{'B':'ID','Date':'DATE','Direction':'DIRECTION','Road':'ROAD',
'Location':'LOCATION','Event':'EVENT','Day':'DAY',
'Month':'MONTH','DayNum':'DAYNUM','Time':'TIME','Year':'YEAR'})
Crash_Data_df.set_index('ID', inplace=True,drop=True)
Crash_Data_df.to_csv("crash_data_check.csv", index=False, header=True)
Crash_Data_df.drop_duplicates()
Crash_Data_df.groupby("ID").filter(lambda x: len(x) > 1)
Crash_Data_df.head()
ID duplicates are not dropped. tried different columns no deal.. the output looks like:
DATE DIRECTION ROAD LOCATION EVENT DAY MONTH DAYNUM TIME YEAR
ID
9954815 Sun Oct 07 03:35:22 CDT 2018 WB T.H.62 # T.H.100 NB CRASH Sun Oct 07 03:35:22 2018
9954815 Sun Oct 07 03:35:22 CDT 2018 WB T.H.62 # T.H.100 NB CRASH Sun Oct 07 03:35:22 2018
9954815 Sun Oct 07 03:35:22 CDT 2018 WB T.H.62 # T.H.100 NB CRASH Sun Oct 07 03:35:22 2018
9954815 Sun Oct 07 03:35:22 CDT 2018 WB T.H.62 # T.H.100 NB CRASH Sun Oct 07 03:35:22 2018
9954815 Sun Oct 07 03:35:22 CDT 2018 WB T.H.62 # T.H.100 NB CRASH Sun Oct 07 03:35:22 2018
9954815 Sun Oct 07 03:35:22 CDT 2018 WB T.H.62 # T.H.100 NB CRASH Sun Oct 07 03:35:22 201
DATE object
DIRECTION object
ROAD object
LOCATION object
EVENT object
DAY object
MONTH object
DAYNUM object
TIME object
YEAR object
dtype: object

Answer 1

Because the .drop_duplicates returns a copy of the df, you want to either update the df variable or do the drop with inplace=True.
Try:
Crash_Data_df = Crash_Data_df.drop_duplicates(subset=['Time'], keep=False)
Or
Crash_Data_df.drop_duplicates(subset=['Time'], keep=False, inplace=True)
Both should work.
BTW, Same applies at the other drop_duplicates calling.