<data>
<row _id="1"><Year>2010-11</Year><All Type Total>237777</All Type Total><All Type Female>73069</All Type Female><Total Agriculture>1305</Total Agriculture><Agriculture ( Female)>140</Agriculture ( Female)><Total Engineering>821</Total Engineering><Engineering Female>28</Engineering Female><Total Medical>25042</Total Medical><Medical Female>14214</Medical Female></row>
<row _id="2"><Year>2011-12</Year><All Type Total>208597</All Type Total><All Type Female>63712</All Type Female><Total Agriculture>1304</Total Agriculture><Agriculture ( Female)>111</Agriculture ( Female)><Total Engineering>822</Total Engineering><Engineering Female>38</Engineering Female><Total Medical>28008</Total Medical><Medical Female>17061</Medical Female></row>
<row _id="3"><Year>2012-13</Year><All Type Total>196612</All Type Total><All Type Female>62468</All Type Female><Total Agriculture>1284</Total Agriculture><Agriculture ( Female)>108</Agriculture ( Female)><Total Engineering>1124</Total Engineering><Engineering Female>55</Engineering Female><Total Medical>31053</Total Medical><Medical Female>19183</Medical Female></row>
<row _id="4"><Year>2013-14</Year><All Type Total>223337</All Type Total><All Type Female>67897</All Type Female><Total Agriculture>1441</Total Agriculture><Agriculture ( Female)>74</Agriculture ( Female)><Total Engineering>1098</Total Engineering><Engineering Female>57</Engineering Female><Total Medical>37556</Total Medical><Medical Female>22930</Medical Female></row>
<row _id="5"><Year>2014-15</Year><All Type Total>258759</All Type Total><All Type Female>77677</All Type Female><Total Agriculture>1678</Total Agriculture><Agriculture ( Female)>90</Agriculture ( Female)><Total Engineering>1063</Total Engineering><Engineering Female>71</Engineering Female><Total Medical>40426</Total Medical><Medical Female>24135</Medical Female></row>
<row _id="6"><Year>2015-16</Year><All Type Total>243840</All Type Total><All Type Female>71674</All Type Female><Total Agriculture>1506</Total Agriculture><Agriculture ( Female)>65</Agriculture ( Female)><Total Engineering>1067</Total Engineering><Engineering Female>72</Engineering Female><Total Medical>39528</Total Medical><Medical Female>22201</Medical Female></row>
<row _id="7"><Year>2016-17</Year><All Type Total>293641</All Type Total><All Type Female>96378</All Type Female><Total Agriculture>1683</Total Agriculture><Agriculture ( Female)>125</Agriculture ( Female)><Total Engineering>1063</Total Engineering><Engineering Female>71</Engineering Female><Total Medical>48799</Total Medical><Medical Female>28152</Medical Female></row>
<row _id="8"><Year>2017-18</Year><All Type Total>319141</All Type Total><All Type Female>96288</All Type Female><Total Agriculture>1394</Total Agriculture><Agriculture ( Female)>149</Agriculture ( Female)><Total Engineering>2158</Total Engineering><Engineering Female>116</Engineering Female><Total Medical>51421</Total Medical><Medical Female>29018</Medical Female></row>
<row _id="9"><Year>2018-19</Year><All Type Total>293876</All Type Total><All Type Female>86791</All Type Female><Total Agriculture>1827</Total Agriculture><Agriculture ( Female)>167</Agriculture ( Female)><Total Engineering>1383</Total Engineering><Engineering Female>92</Engineering Female><Total Medical>52220</Total Medical><Medical Female>30113</Medical Female></row>
<row _id="10"><Year>2019·20(P)</Year><All Type Total>277071</All Type Total><All Type Female>81950</All Type Female><Total Agriculture>2037</Total Agriculture><Agriculture ( Female)>155</Agriculture ( Female)><Total Engineering>2168</Total Engineering><Engineering Female>121</Engineering Female><Total Medical>49166</Total Medical><Medical Female>28288</Medical Female></row>
<row _id="11"><Year>Year</Year><All Type Total>Commerce Total</All Type Total><All Type Female>Commerce Female</All Type Female><Total Agriculture>Law Total</Total Agriculture><Agriculture ( Female)>Law female</Agriculture ( Female)><Total Engineering>Home
Economic Total </Total Engineering><Engineering Female>Home
Economic Female</Engineering Female><Total Medical>Others(a) Total</Total Medical><Medical Female>Others(a) Female</Medical Female></row>
<row _id="12"><Year>2010-11</Year><All Type Total>108356</All Type Total><All Type Female>22276</All Type Female><Total Agriculture>23989</Total Agriculture><Agriculture ( Female)>5024</Agriculture ( Female)><Total Engineering>4007</Total Engineering><Engineering Female>8830</Engineering Female><Total Medical>56485</Total Medical><Medical Female>14652</Medical Female></row>
<row _id="13"><Year>2011-12</Year><All Type Total>104196</All Type Total><All Type Female>25057</All Type Female><Total Agriculture>18972</Total Agriculture><Agriculture ( Female)>3514</Agriculture ( Female)><Total Engineering>3172</Total Engineering><Engineering Female>9582</Engineering Female><Total Medical>42721</Total Medical><Medical Female>8340</Medical Female></row>
<row _id="14"><Year>2012-13</Year><All Type Total>95435</All Type Total><All Type Female>21503</All Type Female><Total Agriculture>17658</Total Agriculture><Agriculture ( Female)>3076</Agriculture ( Female)><Total Engineering>3216</Total Engineering><Engineering Female>9357</Engineering Female><Total Medical>37485</Total Medical><Medical Female>8878</Medical Female></row>
<row _id="15"><Year>2013-14</Year><All Type Total>93278</All Type Total><All Type Female>18245</All Type Female><Total Agriculture>24120</Total Agriculture><Agriculture ( Female)>3918</Agriculture ( Female)><Total Engineering>3906</Total Engineering><Engineering Female>16498</Engineering Female><Total Medical>45440</Total Medical><Medical Female>10386</Medical Female></row>
<row _id="16"><Year>2014-15</Year><All Type Total>111186</All Type Total><All Type Female>27050</All Type Female><Total Agriculture>23602</Total Agriculture><Agriculture ( Female)>3762</Agriculture ( Female)><Total Engineering>4576</Total Engineering><Engineering Female>16536</Engineering Female><Total Medical>59692</Total Medical><Medical Female>9373</Medical Female></row>
<row _id="17"><Year>2015-16</Year><All Type Total>112720</All Type Total><All Type Female>27227</All Type Female><Total Agriculture>15944</Total Agriculture><Agriculture ( Female)>2673</Agriculture ( Female)><Total Engineering>3957</Total Engineering><Engineering Female>15870</Engineering Female><Total Medical>53248</Total Medical><Medical Female>8175</Medical Female></row>
<row _id="18"><Year>2016-17</Year><All Type Total>125321</All Type Total><All Type Female>36552</All Type Female><Total Agriculture>28280</Total Agriculture><Agriculture ( Female)>4681</Agriculture ( Female)><Total Engineering>4694</Total Engineering><Engineering Female>16946</Engineering Female><Total Medical>66855</Total Medical><Medical Female>10494</Medical Female></row>
<row _id="19"><Year>2017-18</Year><All Type Total>119252</All Type Total><All Type Female>35664</All Type Female><Total Agriculture>33468</Total Agriculture><Agriculture ( Female)>5063</Agriculture ( Female)><Total Engineering>4342</Total Engineering><Engineering Female>19529</Engineering Female><Total Medical>87577</Total Medical><Medical Female>14060</Medical Female></row>
<row _id="20"><Year>2018-19</Year><All Type Total>105953</All Type Total><All Type Female>25040</All Type Female><Total Agriculture>28983</Total Agriculture><Agriculture ( Female)>4455</Agriculture ( Female)><Total Engineering>4503</Total Engineering><Engineering Female>20126</Engineering Female><Total Medical>78881</Total Medical><Medical Female>15176</Medical Female></row>
<row _id="21"><Year>2019·20(P)</Year><All Type Total>104419</All Type Total><All Type Female>24295</All Type Female><Total Agriculture>29244</Total Agriculture><Agriculture ( Female)>4386</Agriculture ( Female)><Total Engineering>4460</Total Engineering><Engineering Female>19914</Engineering Female><Total Medical>65663</Total Medical><Medical Female>12965</Medical Female></row>
</data>
