MATLAB date conversion and analysis
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Community, I have a data of the following type. There are three columns. The first column is date array. Second column is IP address array and 3rd column is Serial Number array.
Date:['2014/09/14 06:15', '2014/09/14 06:16', '2014/09/14 06:17' .......
IP address : 192.168.1.1 .....'
Unique Number: '2252534' .....
I want to create something like a pivotable on excel. I would like the group the Date into hours. Followed by this grouping I would like to calculate how many times the IP address and Unique Number have appeared during this Hour. I would like to do that for 24 hours. Can you help me on how I can get started to group the hours and count the number of IP address and Unique number within each hour. I would expect the output to be something like following:
Time: 2014-09-14 6:00 to 7:00 Total number of P addresses within this interval: 6 Total number of unique number within this interval : 4
Thx in advance.
Mike
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回答 (2 件)
Iain
2014 年 9 月 15 日
Matlab datenum follows the convention of
"day = 1"
"hour = 1/24"
"minute = 1/(24*60)"
If today has the value of 523566123 at midnight (this morning), then 6am to 7am would be 523566123 + 6 * hour to 523566123 + 7 * hour
You can index "logically" i.e.:
accepted_list = times > early_time & times < late_time; % eg, 6am to 7am.
noted_ips = ips(accepted_list);
noted_nums = nums(accepted_list);
That gives you a list of all ip addresses & numbers that were logged, you simply need to count the number that were a specific value: eg.
sum(noted_nums == 5)
sum(strcmpi(noted_ips,'101.101.101.10'))
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Guillaume
2014 年 9 月 15 日
編集済み: Guillaume
2014 年 9 月 15 日
- convert the dates to date numbers with datenum
- bin the date numbers with histc and use its 2nd output to find the index of the bin in which each date falls
- use these indices to group the IP and SNs into a cell array, using arrayfun
- use cellfun to operate on each cell array
Depending on the operation, these last two could be replaced by accumarray
e.g:
dndates = datenum(dates);
[~, binindices] = histc(dndates, min(dndates):1/24:max(dndate)+1/24); %to split by hour
groupedip = arrayfun(@(ip, bin) ip(bin), ips, binindices, 'UniformOutput', false);
groupedipcount = cellfun(@(ips) numel(unique(ips)), groupedip);
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