# Anomaly detection on a time-series data in a CSV format using python

I have a time versus current data for a days work which is as follows:

11/15/2016  5:12:27 10:42:27    26.61
11/15/2016  5:12:28 10:42:28    42.27
11/15/2016  5:12:29 10:42:29    25.48
11/15/2016  5:12:30 10:42:30    24.24
11/15/2016  5:12:31 10:42:31    25.91


The first column being the date The second column being the time in GMT The third column being time in IST The fourth column being the value of the current used by the machine

Can someone suggest me an algorithm for finding the anomalies in the pattern plotted by current versus time in IST? Any help regarding my approach will be appreciated too.

• Here's an algorithm: 1. design a statistical model for anomalies. 2. fit the model. 3. test to see if the data fits the model (go to 1 if not). 4. use the model. – Spacedman Jan 3 '17 at 14:42