summ up the time

This scirpt is on how to sum up the time series.¶

I am watching a series of videos on machine learning. What I want is to find out the toltal time I have to spend on all the lectures.

So I decided to script it up. I just copy pasted the series name and timings into a text bcoz i'm lazy to code it up using request :)

Rest of the coding is in python pandas . Its very simple

In [1]:

import pandas as pd

In [2]:

with open( "ts.txt", 'r' ) as fh:
    data = fh.readlines()

In [3]:

data[0:10]

Out[3]:

['Chapter 1: Introduction (slides, playlist)\n',
 '\n',
 '    Opening Remarks and Examples (18:18)\n',
 '    Supervised and Unsupervised Learning (12:12)\n',
 '\n',
 'Chapter 2: Statistical Learning (slides, playlist)\n',
 '\n',
 '    Statistical Learning and Regression (11:41)\n',
 '    Curse of Dimensionality and Parametric Models (11:40)\n',
 '    Assessing Model Accuracy and Bias-Variance Trade-off (10:04)\n']

In [4]:

# capture all the time slot of each video into a list

ts = list()

for e,i in enumerate(data[0:]):
    if i.startswith("Chapter"):
        pass
    if i.startswith(" "):
        ts.append( "0:" + i.split(" ")[-1].replace("(",'').replace(")","").replace('\n','') )

print ts

['0:18:18', '0:12:12', '0:11:41', '0:11:40', '0:10:04', '0:15:37', '0:14:12', '0:13:01', '0:8:24', '0:15:38', '0:14:51', '0:14:16', '0:22:10', '0:10:25', '0:9:07', '0:9:53', '0:7:28', '0:7:12', '0:7:37', '0:17:42', '0:10:07', '0:10:14', '0:8:22', '0:5:01', '0:14:01', '0:13:33', '0:10:07', '0:11:29', '0:14:35', '0:11:21', '0:7:40', '0:13:44', '0:12:26', '0:5:26', '0:14:06', '0:8:43', '0:12:37', '0:15:21', '0:5:27', '0:4:45', '0:15:48', '0:10:36', '0:10:32', '0:5:32', '0:16:34', '0:14:59', '0:13:13', '0:10:10', '0:10:45', '0:21:11', '0:12:15', '0:14:37', '0:11:45', '0:11:00', '0:13:45', '0:12:03', '0:10:13', '0:15:35', '0:11:35', '0:8:04', '0:15:04', '0:14:47', '0:10:13', '0:7:54', '0:12:37', '0:17:39', '0:17:17', '0:14:45', '0:9:24', '0:6:28', '0:6:31', '0:6:33']

Now to sum it up using pure python is time consuming. So I used pandas timedelta to convert it to a time series

In [5]:

tsSer = pd.Series(ts)

tsTd = pd.to_timedelta(tsSer)

print "Total Time taken for the entire Series to watch : ", tsTd.sum()

Total Time taken for the entire Series to Watch :  0 days 14:09:57