Bar plot in Python using Bokeh

import pandas as pd
from collections import Counter
from datetime import datetime, timedelta
from bokeh.charts import Bar, output_file, show
from bokeh.models.layouts import Column
import numpy as np

try:
    data = pd.read_csv('new.csv')
    scan_col = Counter(data['Scan'])
    values = list()
    keys = list()
   
    for s in scan_col.keys():
        scan_time_total = datetime.strptime("00:00:00","%H:%M:%S")
        scan_time_total = timedelta(hours=scan_time_total.hour, minutes=scan_time_total.minute, seconds=scan_time_total.second)
        for i,v in data['Scan'].iteritems():
            if s == v:
                temp = data['Time'][i]
                temp = datetime.strptime(data['Time'][i],"%H:%M:%S")
                temp = timedelta(hours=temp.hour, minutes=temp.minute, seconds=temp.second)
                scan_time_total += temp
        values.append(scan_time_total.total_seconds()/60)
        keys.append(s)

    output_file("bar.html")
    scan_dict = {'values':values, 'names':keys}
    df = pd.DataFrame(scan_dict)
    p = Bar(df, 'names', values='values', title="Scan vs Time", plot_width=1234, legend=False)
    p.xaxis.axis_label = "Scans"
    p.yaxis.axis_label = "Total Time (minutes)"
   
    values2 = list()
    keys2 = list()
   
    for s in scan_col.keys():
        keys2.append(s)
    for s in scan_col.values():
        values2.append(s)
       
    scan_dict2 = {'values':values2, 'names':keys2}
    df2 = pd.DataFrame(scan_dict2)
    p2 = Bar(df2, 'names', values='values', title="Scan vs Count", plot_width=1234, legend=False)
    p2.xaxis.axis_label = "Scans"
    p2.yaxis.axis_label = "Count"
   
    show(Column(p,p2))
   
except Exception as e:
    print(e)