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ryanorsinger/mall_customers.csv

Created January 4, 2022 02:07
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Mall Customers Dataset (A "Hello World" for Clustering examples)
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mall_customers.csv
customer_id gender age annual_income spending_score
0001 Male 19 15 39
0002 Male 21 15 81
0003 Female 20 16 6
0004 Female 23 16 77
0005 Female 31 17 40
0006 Female 22 17 76
0007 Female 35 18 6
0008 Female 23 18 94
0009 Male 64 19 3
0010 Female 30 19 72
0011 Male 67 19 14
0012 Female 35 19 99
0013 Female 58 20 15
0014 Female 24 20 77
0015 Male 37 20 13
0016 Male 22 20 79
0017 Female 35 21 35
0018 Male 20 21 66
0019 Male 52 23 29
0020 Female 35 23 98
0021 Male 35 24 35
0022 Male 25 24 73
0023 Female 46 25 5
0024 Male 31 25 73
0025 Female 54 28 14
0026 Male 29 28 82
0027 Female 45 28 32
0028 Male 35 28 61
0029 Female 40 29 31
0030 Female 23 29 87
0031 Male 60 30 4
0032 Female 21 30 73
0033 Male 53 33 4
0034 Male 18 33 92
0035 Female 49 33 14
0036 Female 21 33 81
0037 Female 42 34 17
0038 Female 30 34 73
0039 Female 36 37 26
0040 Female 20 37 75
0041 Female 65 38 35
0042 Male 24 38 92
0043 Male 48 39 36
0044 Female 31 39 61
0045 Female 49 39 28
0046 Female 24 39 65
0047 Female 50 40 55
0048 Female 27 40 47
0049 Female 29 40 42
0050 Female 31 40 42
0051 Female 49 42 52
0052 Male 33 42 60
0053 Female 31 43 54
0054 Male 59 43 60
0055 Female 50 43 45
0056 Male 47 43 41
0057 Female 51 44 50
0058 Male 69 44 46
0059 Female 27 46 51
0060 Male 53 46 46
0061 Male 70 46 56
0062 Male 19 46 55
0063 Female 67 47 52
0064 Female 54 47 59
0065 Male 63 48 51
0066 Male 18 48 59
0067 Female 43 48 50
0068 Female 68 48 48
0069 Male 19 48 59
0070 Female 32 48 47
0071 Male 70 49 55
0072 Female 47 49 42
0073 Female 60 50 49
0074 Female 60 50 56
0075 Male 59 54 47
0076 Male 26 54 54
0077 Female 45 54 53
0078 Male 40 54 48
0079 Female 23 54 52
0080 Female 49 54 42
0081 Male 57 54 51
0082 Male 38 54 55
0083 Male 67 54 41
0084 Female 46 54 44
0085 Female 21 54 57
0086 Male 48 54 46
0087 Female 55 57 58
0088 Female 22 57 55
0089 Female 34 58 60
0090 Female 50 58 46
0091 Female 68 59 55
0092 Male 18 59 41
0093 Male 48 60 49
0094 Female 40 60 40
0095 Female 32 60 42
0096 Male 24 60 52
0097 Female 47 60 47
0098 Female 27 60 50
0099 Male 48 61 42
0100 Male 20 61 49
0101 Female 23 62 41
0102 Female 49 62 48
0103 Male 67 62 59
0104 Male 26 62 55
0105 Male 49 62 56
0106 Female 21 62 42
0107 Female 66 63 50
0108 Male 54 63 46
0109 Male 68 63 43
0110 Male 66 63 48
0111 Male 65 63 52
0112 Female 19 63 54
0113 Female 38 64 42
0114 Male 19 64 46
0115 Female 18 65 48
0116 Female 19 65 50
0117 Female 63 65 43
0118 Female 49 65 59
0119 Female 51 67 43
0120 Female 50 67 57
0121 Male 27 67 56
0122 Female 38 67 40
0123 Female 40 69 58
0124 Male 39 69 91
0125 Female 23 70 29
0126 Female 31 70 77
0127 Male 43 71 35
0128 Male 40 71 95
0129 Male 59 71 11
0130 Male 38 71 75
0131 Male 47 71 9
0132 Male 39 71 75
0133 Female 25 72 34
0134 Female 31 72 71
0135 Male 20 73 5
0136 Female 29 73 88
0137 Female 44 73 7
0138 Male 32 73 73
0139 Male 19 74 10
0140 Female 35 74 72
0141 Female 57 75 5
0142 Male 32 75 93
0143 Female 28 76 40
0144 Female 32 76 87
0145 Male 25 77 12
0146 Male 28 77 97
0147 Male 48 77 36
0148 Female 32 77 74
0149 Female 34 78 22
0150 Male 34 78 90
0151 Male 43 78 17
0152 Male 39 78 88
0153 Female 44 78 20
0154 Female 38 78 76
0155 Female 47 78 16
0156 Female 27 78 89
0157 Male 37 78 1
0158 Female 30 78 78
0159 Male 34 78 1
0160 Female 30 78 73
0161 Female 56 79 35
0162 Female 29 79 83
0163 Male 19 81 5
0164 Female 31 81 93
0165 Male 50 85 26
0166 Female 36 85 75
0167 Male 42 86 20
0168 Female 33 86 95
0169 Female 36 87 27
0170 Male 32 87 63
0171 Male 40 87 13
0172 Male 28 87 75
0173 Male 36 87 10
0174 Male 36 87 92
0175 Female 52 88 13
0176 Female 30 88 86
0177 Male 58 88 15
0178 Male 27 88 69
0179 Male 59 93 14
0180 Male 35 93 90
0181 Female 37 97 32
0182 Female 32 97 86
0183 Male 46 98 15
0184 Female 29 98 88
0185 Female 41 99 39
0186 Male 30 99 97
0187 Female 54 101 24
0188 Male 28 101 68
0189 Female 41 103 17
0190 Female 36 103 85
0191 Female 34 103 23
0192 Female 32 103 69
0193 Male 33 113 8
0194 Female 38 113 91
0195 Female 47 120 16
0196 Female 35 120 79
0197 Female 45 126 28
0198 Male 32 126 74
0199 Male 32 137 18
0200 Male 30 137 83
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