RosettaCodeData/Task/Text-processing-1/00DESCRIPTION

{{Template:clarify task}}
Often data is produced by one program, in the wrong format for later use by another program or person. In these situations another program can be written to parse and transform the original data into a format useful to the other. The term "Data Munging" is [http://www.google.co.uk/search?q=%22data+munging%22 often] used in programming circles for this task.

A [http://groups.google.co.uk/group/comp.lang.awk/msg/0ecba3a3fbf247d8?hl=en request] on the comp.lang.awk newsgroup led to a typical data munging task:
<pre>I have to analyse data files that have the following format:
Each row corresponds to 1 day and the field logic is: $1 is the date,
followed by 24 value/flag pairs, representing measurements at 01:00,
02:00 ... 24:00 of the respective day. In short:

<date> <val1> <flag1> <val2> <flag2> ...  <val24> <flag24>

Some test data is available at:
... (nolonger available at original location)

I have to sum up the values (per day and only valid data, i.e. with
flag>0) in order to calculate the mean. That's not too difficult.
However, I also need to know what the "maximum data gap" is, i.e. the
longest period with successive invalid measurements (i.e values with
flag<=0)</pre>

The data is [http://www.eea.europa.eu/help/eea-help-centre/faqs/how-do-i-obtain-eea-reports free to download and use] and is of this format:

Data is no longer available at that link. Zipped mirror available [https://github.com/thundergnat/rc/blob/master/resouces/readings.zip here] (offsite mirror).
<pre style="overflow:scroll">
1991-03-30	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1
1991-03-31	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	10.000	1	20.000	1	20.000	1	20.000	1	35.000	1	50.000	1	60.000	1	40.000	1	30.000	1	30.000	1	30.000	1	25.000	1	20.000	1	20.000	1	20.000	1	20.000	1	20.000	1	35.000	1
1991-03-31	40.000	1	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2	0.000	-2
1991-04-01	0.000	-2	13.000	1	16.000	1	21.000	1	24.000	1	22.000	1	20.000	1	18.000	1	29.000	1	44.000	1	50.000	1	43.000	1	38.000	1	27.000	1	27.000	1	24.000	1	23.000	1	18.000	1	12.000	1	13.000	1	14.000	1	15.000	1	13.000	1	10.000	1
1991-04-02	8.000	1	9.000	1	11.000	1	12.000	1	12.000	1	12.000	1	27.000	1	26.000	1	27.000	1	33.000	1	32.000	1	31.000	1	29.000	1	31.000	1	25.000	1	25.000	1	24.000	1	21.000	1	17.000	1	14.000	1	15.000	1	12.000	1	12.000	1	10.000	1
1991-04-03	10.000	1	9.000	1	10.000	1	10.000	1	9.000	1	10.000	1	15.000	1	24.000	1	28.000	1	24.000	1	18.000	1	14.000	1	12.000	1	13.000	1	14.000	1	15.000	1	14.000	1	15.000	1	13.000	1	13.000	1	13.000	1	12.000	1	10.000	1	10.000	1
</pre>

Only a sample of the data showing its format is given above. The full example file may be downloaded [http://rosettacode.org/resources/readings.zip here].

Structure your program to show statistics for each line of the file, (similar to the original Python, Perl, and AWK examples below), followed by summary statistics for the file. When showing example output just show a few line statistics and the full end summary.