101 | Tejasree | nlr | female | developer | 24000 | 25 |
102 | Aravind | tpt | male | sales | 26000 | 27 |
103 | Malli | ctc | male | marketing | 28000 | 23 |
104 | Jagan | ongole | male | nontech | 30000 | 24 |
105 | Meghana | hyd | female | tech | 32000 | 26 |
106 | Praveen | nlr | male | analysit | 34000 | 24 |
107 | Likitha | kadapa | female | sap | 36000 | 27 |
108 | Tejeshswar | anthapur | male | sas | 38000 | 22 |
109 | Tanisha | tpt | female | sales | 40000 | 28 |
110 | Bhanu | guntur | male | marketing | 42000 | 46 |
111 | Mourya | nlr | male | sql analysit | 44000 | 25 |
112 | Manohar | tpt | male | developer | 46000 | 27 |
113 | Thanvitha | ctc | female | sales | 48000 | 23 |
114 | Chethan | ongole | male | marketing | 50000 | 24 |
115 | kumar | hyd | male | nontech | 52000 | 26 |
116 | Mouni | nlr | female | tech | 54000 | 24 |
117 | Jai | kadapa | male | analysit | 56000 | 27 |
118 | Karthik | anthapur | male | sap | 58000 | 22 |
119 | Swarna | tpt | female | sas | 60000 | 28 |
120 | Sahana | guntur | female | sales | 62000 | 46 |
121 | Nagaraj | nlr | male | marketing | 64000 | 25 |
122 | Kusuma | tpt | female | sql analysit | 66000 | 27 |
123 | Sai | ctc | male | developer | 68000 | 23 |
124 | Pawan | ongole | male | sales | 70000 | 24 |
125 | Vamsi | hyd | male | marketing | 72000 | 26 |
126 | Ramya | nlr | female | nontech | 74000 | 24 |
127 | Sri vidya | kadapa | female | tech | 76000 | 27 |
128 | Sravani | anthapur | female | analysit | 78000 | 22 |
129 | Jayanthi | tpt | female | sap | 80000 | 28 |
130 | hasini | guntur | female | sas | 82000 | 46 |
131 | Yeaswanth | nlr | male | sales | 84000 | 34 |
132 | Naveen | tpt | male | marketing | 86000 | 65 |
133 | Har**bleep**h | ctc | male | sql analysit | 88000 | 34 |
134 | Mounika | ongole | female | developer | 90000 | 89 |
135 | Afroz | hyd | female | sales | 92000 | 26 |
136 | Suresh | nlr | male | marketing | 94000 | 24 |
137 | venu | kadapa | male | nontech | 96000 | 27 |
138 | Soumya | anthapur | female | tech | 98000 | 22 |
139 | Murali | tpt | male | analysit | 100000 | 28 |
140 | kiran | guntur | male | sap | 102000 | 46 |
141 | Rayudu | nlr | male | sas | 104000 | 25 |
142 | Sunil | tpt | male | sales | 106000 | 27 |
143 | Rahul | ctc | male | marketing | 108000 | 23 |
144 | hema | ongole | female | sql analysit | 122000 | 24 |
145 | Madhu | hyd | male | developer | 112000 | 26 |
145 | Joshna | nlr | female | sales | 122000 | 24 |
146 | Sree | kadapa | male | marketing | 116000 | 27 |
148 | Pavani | anthapur | female | nontech | 118000 | 22 |
149 | Swaroop | tpt | male | tech | 122000 | 28 |
150 | Manasa | guntur | female | analysit | 122000 | 46 |
This my data
144 | hema | ongole | female | sql analysit | 122000 | 24 |
145 | Joshna | nlr | female | sales | 122000 | 24 |
149 | Swaroop | tpt | male | tech | 122000 | 28 |
150 | Manasa | guntur | female | analysit | 122000 | 46 |
148 | Pavani | anthapur | female | nontech | 118000 | 22 |
146 | Sree | kadapa | male | marketing | 116000 | 27 |
145 | Madhu | hyd | male | developer | 112000 | 26 |
143 | Rahul | ctc | male | marketing | 108000 | 23 |
142 | Sunil | tpt | male | sales | 106000 | 27 |
141 | Rayudu | nlr | male | sas | 104000 | 25 |
140 | kiran | guntur | male | sap | 102000 | 46 |
I have data like this
144 | hema | ongole | female | sql analysit | 122000 | 24 |
145 | Joshna | nlr | female | sales | 122000 | 24 |
149 | Swaroop | tpt | male | tech | 122000 | 28 |
150 | Manasa | guntur | female | analysit | 122000 | 46 |
148 | Pavani | anthapur | female | nontech | 118000 | 22 |
I got output like this , help me anyone
Define what you mean by "top value". Largest single value? Largest sum or mean? Most frequent value? Something else?
For which variable(s)?
Using what groups?
If you want the most popular (=most frequent) categories, you can use the ORDER=FREQ option on PROC FREQ combined with the MAXLEVELS= option on the TABLES statement. For example:
%let TopN = 10;
proc freq data=sashelp.cars ORDER=FREQ;
tables make / maxlevels=&TopN Plots=FreqPlot;
run;
For more information, see https://blogs.sas.com/content/iml/2018/06/04/top-10-table-bar-chart.html
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