I have weekly booking qty for 2015 and 2016 year as I have provided and I need to analyze for any pattern in the data
<p>for this requirement I approached with time series.</p>

<h1>data as below</h1>

<pre><code>bookingdate bookingqty

2014-07-27        202

2014-08-03        564

2014-08-10        359

2014-08-17        638

2014-08-24        487

2014-08-31        491

 2014-09-07        364

 2014-09-14        762

 2014-09-21        419

2014-09-28        642

2014-10-05        723

  2014-10-12        579

   2014-10-19       1803

  2014-10-26        437

   2014-11-02        587

   2014-11-09        803

   2014-11-16       1347

   2014-11-23        600

   2014-11-30        616

  2014-12-07       2242

   2014-12-14       1313

   2014-12-21        264

   2014-12-28        918

   2015-01-04        420

   2015-01-11        741

   2015-01-18       2213

   2015-01-25        379

  2015-02-01        386

   2015-02-08        854

   2015-02-15       1235

   2015-02-22        726

  2015-03-01        774

   2015-03-08       1135

   2015-03-15       1127

  2015-03-22        466

  2015-03-29        987

   2015-04-05        665

   2015-04-12        997

   2015-04-19       2800

  2015-04-26        594

   2015-05-03        715

   2015-05-10       2009

   2015-05-17       1592

  2015-05-24        499

   2015-05-31       1906

   2015-06-07       1619

  2015-06-14       1277

   2015-06-21        683

   2015-06-28       2132

 2015-07-05       1195

  2015-07-12       1250

   2015-07-19       5001

   2015-07-26        320

   2015-08-02        577

   2015-08-09        825

   2015-08-16        885

   2015-08-23       1910

   2015-08-30       1072

   2015-09-06        615

   2015-09-13       1809

  2015-09-20       1243

   2015-09-27       1516

   2015-10-04        754

  2015-10-11        910

  2015-10-18       1766

   2015-10-25        599

   2015-11-01        536

   2015-11-08       1170

   2015-11-15       2060

  2015-11-22        719

   2015-11-29        706

  2015-12-06       1129

   2015-12-13       1807

   2015-12-20        949

   2015-12-27        653

   2016-01-03       1612

   2016-01-10       1058

   2016-01-17       2699

   2016-01-24        617

   2016-01-31        335

   2016-02-07        527

   2016-02-14        526

   2016-02-21       1729

   2016-02-28        512

   2016-03-06       1026

   2016-03-13        824

   2016-03-20       1144

   2016-03-27        711

   2016-04-03        743

   2016-04-10        847

   2016-04-17        833

   2016-04-24       4192

   2016-05-01        576

   2016-05-08        610

   2016-05-15        645

   2016-05-22        950

   2016-05-29        578

   2016-06-05        786

   2016-06-12        990

  2016-06-19       1804

  2016-06-26        853

  2016-07-03        767

  2016-07-10       1325

  2016-07-17       1872

  2016-07-24       3002
</code></pre>

<p>#I created time series object as</p>

<pre><code>    library(zoo)

    pidbookingdata &lt;- zoo(arrangeddata$bookingqty,arrangeddata$bookingdate)
</code></pre>

<p>#I can see in the x axis index for year 2015 and 2016 but when I use #decompose function I get the below error as</p>

<p>decompose(pidbookingdata)</p>

<p>Error in decompose(pidbookingdata) : 
  time series has no or less than 2 periods</p>

<p>#so, from this site I got and tried the below approach which works:</p>

<p>dfts &lt;- as.ts(xts(arrangeddata$bookingqty,order.by=arrangeddata$bookingdate))</p>

<pre><code>dfts

dfts &lt;- ts(dfts, frequency=52)

dcomp &lt;- decompose(dfts) 

#the dfts data as shown below

&gt; `dfts`

Time Series:
Start = c(1, 1) 
End = c(3, 1) 
Frequency = 52 
  [1]  202  564  359  638  487  491  364  762  419  642  723  579 1803  437  587  803 1347  600  616
 [20] 2242 1313  264  918  420  741 2213  379  386  854 1235  726  774 1135 1127  466  987  665  997
 [39] 2800  594  715 2009 1592  499 1906 1619 1277  683 2132 1195 1250 5001  320  577  825  885 1910
 [58] 1072  615 1809 1243 1516  754  910 1766  599  536 1170 2060  719  706 1129 1807  949  653 1612
 [77] 1058 2699  617  335  527  526 1729  512 1026  824 1144  711  743  847  833 4192  576  610  645
 [96]  950  578  786  990 1804  853  767 1325 1872 3002


#when I do plot(dfts)

#I see the x axis index as 1.0 1.5 2 2.5 3
</code></pre>

<h1>am I doing correct or something is wrong here? what does the indices 1.0, #1.5, 2.0 means in terms of weeks?</h1>