supermarket1996: Supermarket data 1996

In SVMMaj: Implementation of the SVM-Maj Algorithm

Description

This

Format

This dataframe contains the following columns

• STOREIdentifier of the store

• CITYThe city of the store

• ZIPThe zip code of the store

• GROCERY_sum

• GROCCOUP_sum

• AGE9

• AGE60

• ETHNIC

• EDUC

• NOCAR

• INCOME

• INCSIGMA

• HSIZEAVG

• HSIZE1

• HSIZE2

• HSIZE34

• HSIZE567

• HH3PLUS

• HH4PLUS

• HHSINGLE

• HHLARGE

• WORKWOM

• SINHOUSE

• DENSITY

• HVAL150

• HVAL200

• HVALMEAN

• SINGLE

• RETIRED

• UNEMP

• WRKCH5

• WRKCH17

• NWRKCH5

• NWRKCH17

• WRKCH

• NWRKCH

• WRKWCH

• WRKWNCH

• TELEPHN

• MORTGAGE

• NWHITE

• POVERTY

• SHPCONS

• SHPHURR

• SHPAVID

• SHPKSTR

• SHPUNFT

• SHPBIRD

• SHOPINDX

• SHPINDX

Examples

head(supermarket1996, 3)

Example output

  STORE                 CITY   ZIP GROCERY_sum GROCCOUP_sum      AGE9     AGE60
1     2 RIVER FOREST         60305     5087345    -80911.83 0.1175086 0.2328647
2     5 PALATINE             60067     4424837    -98972.98 0.1414335 0.1173680
3     8 OAK LAWN             60453    10371630   -258831.52 0.1231554 0.2523940
      ETHNIC       EDUC      NOCAR   INCOME INCSIGMA HSIZEAVG    HSIZE1
1 0.11427995 0.24893493 0.12460289 10.55321 26296.90 2.531062 0.2820332
2 0.05387528 0.32122573 0.02556950 10.92237 26779.61 2.656439 0.2188517
3 0.03524333 0.09517327 0.07511272 10.59701 24653.87 2.769603 0.2108215
     HSIZE2   HSIZE34  HSIZE567   HH3PLUS   HH4PLUS  HHSINGLE   HHLARGE
1 0.3129192 0.3010942 0.1039534 0.4050477 0.2419696 0.2820332 0.1039534
2 0.3350767 0.3429800 0.1030916 0.4460716 0.2708043 0.2188517 0.1030916
3 0.3144177 0.3430111 0.1317497 0.4747608 0.2886836 0.2108215 0.1317497
    WORKWOM  SINHOUSE      DENSITY    HVAL150     HVAL200  HVALMEAN    SINGLE
1 0.3035853 0.5550623 0.0004560436 0.46388707 0.300393959 176.21307 0.2976210
2 0.4105680 0.5762844 0.0011192828 0.53588336 0.296345389 184.57584 0.2645853
3 0.2830747 0.7572110 0.0003905024 0.05422716 0.009109024  97.50142 0.2503721
     RETIRED     UNEMP     WRKCH5    WRKCH17    NWRKCH5   NWRKCH17     WRKCH
1 0.20062013 0.1817649 0.02963185 0.08275965 0.05297815 0.06644717 0.1123915
2 0.09664275 0.1779053 0.05859928 0.14519116 0.10848491 0.08779000 0.2037904
3 0.20845197 0.1738848 0.03780510 0.11479170 0.06781061 0.08157460 0.1525968
     NWRKCH     WRKWCH   WRKWNCH   TELEPHN  MORTGAGE     NWHITE    POVERTY
1 0.1194253 0.02926397 0.2864322 0.9855277 0.5491446 0.13822560 0.06195940
2 0.1962749 0.05762639 0.2728149 0.9922129 0.8518060 0.09117020 0.02510460
3 0.1493852 0.03732222 0.2367062 0.9930716 0.6477187 0.04599686 0.05135254
     SHPCONS   SHPHURR   SHPAVID   SHPKSTR   SHPUNFT    SHPBIRD  SHOPINDX
1 0.09106954 0.1210731 0.1812566 0.2322626 0.2843276 0.09001059 0.7300902
2 0.03254300 0.1906090 0.1680614 0.3301953 0.2633659 0.01522548 0.8352603
3 0.07622085 0.1351738 0.2174439 0.2161241 0.3027937 0.05224373 0.9016030
    SHPINDX
1 0.7300902
2 0.8352603
3 0.9016030

SVMMaj documentation built on May 2, 2019, 9:58 a.m.