Plot for every 10 minutes in datetime

The 'df' I am using has multiple rows for each datetime. I want to plot a scatterplot of all coordinates with the same datetime for every 10 minutes.

It works if I manually input the times into t_list = [datetime(2017, 12, 23, 06, 00, 00), datetime(2017, 12, 23, 06, 10, 00), datetime(2017, 12, 23, 06, 20, 00)]but I want to replace this with something that uses the dates from df so I can use it for multiple datasets.

import pandas as pd
import matplotlib.pyplot as plt
from datetime import datetime, timedelta
import numpy as np

df_data = pd.read_csv('C:\data.csv')
df_data['datetime'] = pd.to_datetime(df_data['TimeStamp'] )
df = df_data[(df_data['datetime']>= datetime(2017, 12, 23, 06,00, 00)) &
         (df_data['datetime']< datetime(2017, 12, 23, 07, 00, 00))]

##want a time array for all of the datetimes in the df
t_list = [datetime(2017, 12, 23, 06, 00, 00), datetime(2017, 12, 23, 06, 10, 00), 
datetime(2017, 12, 
23, 06, 20, 00)]

for t in t_list:
    t_end = t + timedelta(minutes = 10)
    t_text = t.strftime("%d-%b-%Y (%H:%M)")

    #boolean indexing with multiple conditions, you should wrap each single condition in brackets
    df_t = df[(df['datetime']>=t) & (df['datetime']<t_end)]

    #get data into variable
    ws = df_t['Sp_mean']
    lat = df_t['x']
    lon = df_t['y']
    col = 0.75

    #calc min/max for setting scale on images
    min_ws = df['Sp_mean'].min()
    max_ws = df['Sp_mean'].max()

    plt.figure(figsize=(15,10))
    plt.scatter(lon, lat, c=ws,s=300, vmin=min_ws, vmax=max_ws)  
    plt.title('event' + t_text,fontweight = 'bold',fontsize=18)
    plt.show()

I have tried a few ways of attempting to make a copy of datetime as an iterable list which haven't given me the results I am after, the most recent below:

date_arrray = np.arange(np.datetime64(df['datetime']))
df['timedelta'] = pd.to_timedelta(df['datetime'])

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