<data>
<row _id="1"><Year>2007-08</Year><Total>110,433</Total><Male>56,998</Male><Female>53,435</Female></row>
<row _id="2"><Year>2008-09</Year><Total>111,275</Total><Male>57,131</Male><Female>54,144</Female></row>
<row _id="3"><Year>2009-10</Year><Total>115,785</Total><Male>58,057</Male><Female>57,728</Female></row>
<row _id="4"><Year>2010-11</Year><Total>116,240</Total><Male>56,927</Male><Female>59,313</Female></row>
<row _id="5"><Year>2011-12</Year><Total>110,718</Total><Male>56,850</Male><Female>53,868</Female></row>
<row _id="6"><Year>2012-13</Year><Total>118,898</Total><Male>60,478</Male><Female>58,420</Female></row>
<row _id="7"><Year>2013-14</Year><Total>117,660</Total><Male>60,257</Male><Female>57,403</Female></row>
<row _id="8"><Year>2014-15</Year><Total>119,432</Total><Male>61,079</Male><Female>58,353</Female></row>
<row _id="9"><Year>2015-16</Year><Total>126,606</Total><Male>59,408</Male><Female>67,198</Female></row>
<row _id="10"><Year>2016-17</Year><Total>125,261</Total><Male>59,015</Male><Female>66,246</Female></row>
<row _id="11"><Year>2017-18(P)</Year><Total>131,315</Total><Male>61,326</Male><Female>69,989</Female></row>
</data>
