Overview

Dataset statistics

Number of variables8
Number of observations4725
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory323.1 KiB
Average record size in memory70.0 B

Variable types

DateTime1
Categorical1
Numeric6

Dataset

Description강원랜드 카지노 게임 이용 시 적립되는 하이원포인트의 인근 지역 가맹점 이용현황으로 지역별,일자별, 업종별 결제 건 수 데이터를 제공합니다
Author(주)강원랜드
URLhttps://www.data.go.kr/data/15106402/fileData.do

Alerts

고한읍_건수 is highly overall correlated with 사북읍_건수 and 3 other fieldsHigh correlation
사북읍_건수 is highly overall correlated with 고한읍_건수 and 3 other fieldsHigh correlation
정선군_건수 is highly overall correlated with 고한읍_건수 and 3 other fieldsHigh correlation
태백시_건수 is highly overall correlated with 고한읍_건수 and 4 other fieldsHigh correlation
영월군_건수 is highly overall correlated with 고한읍_건수 and 4 other fieldsHigh correlation
삼척시_건수 is highly overall correlated with 태백시_건수 and 1 other fieldsHigh correlation
고한읍_건수 has 1275 (27.0%) zerosZeros
사북읍_건수 has 1096 (23.2%) zerosZeros
정선군_건수 has 1619 (34.3%) zerosZeros
태백시_건수 has 1008 (21.3%) zerosZeros
영월군_건수 has 2777 (58.8%) zerosZeros
삼척시_건수 has 2219 (47.0%) zerosZeros

Reproduction

Analysis started2024-03-14 19:31:06.093533
Analysis finished2024-03-14 19:31:18.891918
Duration12.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사용일자
Date

Distinct365
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size37.0 KiB
Minimum2023-01-01 00:00:00
Maximum2023-12-31 00:00:00
2024-03-15T04:31:19.094504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:19.455308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업종
Categorical

Distinct17
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size37.0 KiB
휴게음식점업
365 
슈퍼마켓
365 
커피전문점
365 
숙박업
365 
식품판매업
365 
Other values (12)
2900 

Length

Max length10
Median length9
Mean length5.3172487
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row휴게음식점업
2nd row식품판매업
3rd row소매업
4th row주유소·LPG충전소
5th row세탁업

Common Values

ValueCountFrequency (%)
휴게음식점업 365
 
7.7%
슈퍼마켓 365
 
7.7%
커피전문점 365
 
7.7%
숙박업 365
 
7.7%
식품판매업 365
 
7.7%
일반음식점업 365
 
7.7%
이ㆍ미용업 365
 
7.7%
소매업 365
 
7.7%
세탁업 364
 
7.7%
주유소·LPG충전소 292
 
6.2%
Other values (7) 1149
24.3%

Length

2024-03-15T04:31:19.714674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
휴게음식점업 365
 
6.7%
슈퍼마켓 365
 
6.7%
커피전문점 365
 
6.7%
숙박업 365
 
6.7%
식품판매업 365
 
6.7%
일반음식점업 365
 
6.7%
이ㆍ미용업 365
 
6.7%
소매업 365
 
6.7%
세탁업 364
 
6.7%
주유소·lpg충전소 292
 
5.4%
Other values (12) 1851
34.1%

고한읍_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct218
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.369947
Minimum0
Maximum267
Zeros1275
Zeros (%)27.0%
Negative0
Negative (%)0.0%
Memory size41.7 KiB
2024-03-15T04:31:19.958158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q325
95-th percentile133.8
Maximum267
Range267
Interquartile range (IQR)25

Descriptive statistics

Standard deviation44.959398
Coefficient of variation (CV)1.7049483
Kurtosis4.6762831
Mean26.369947
Median Absolute Deviation (MAD)6
Skewness2.2312781
Sum124598
Variance2021.3474
MonotonicityNot monotonic
2024-03-15T04:31:20.243480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1275
27.0%
1 256
 
5.4%
2 209
 
4.4%
8 199
 
4.2%
4 194
 
4.1%
6 186
 
3.9%
3 149
 
3.2%
5 136
 
2.9%
10 135
 
2.9%
7 116
 
2.5%
Other values (208) 1870
39.6%
ValueCountFrequency (%)
0 1275
27.0%
1 256
 
5.4%
2 209
 
4.4%
3 149
 
3.2%
4 194
 
4.1%
5 136
 
2.9%
6 186
 
3.9%
7 116
 
2.5%
8 199
 
4.2%
9 92
 
1.9%
ValueCountFrequency (%)
267 1
< 0.1%
266 1
< 0.1%
257 1
< 0.1%
256 1
< 0.1%
252 1
< 0.1%
246 1
< 0.1%
244 1
< 0.1%
243 1
< 0.1%
238 2
< 0.1%
236 2
< 0.1%

사북읍_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct344
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.257778
Minimum0
Maximum665
Zeros1096
Zeros (%)23.2%
Negative0
Negative (%)0.0%
Memory size41.7 KiB
2024-03-15T04:31:20.821583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q331
95-th percentile193
Maximum665
Range665
Interquartile range (IQR)30

Descriptive statistics

Standard deviation80.103518
Coefficient of variation (CV)2.0937839
Kurtosis15.253292
Mean38.257778
Median Absolute Deviation (MAD)8
Skewness3.6197318
Sum180768
Variance6416.5737
MonotonicityNot monotonic
2024-03-15T04:31:21.278996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1096
23.2%
1 316
 
6.7%
2 232
 
4.9%
4 165
 
3.5%
3 144
 
3.0%
6 136
 
2.9%
8 121
 
2.6%
10 106
 
2.2%
14 105
 
2.2%
12 103
 
2.2%
Other values (334) 2201
46.6%
ValueCountFrequency (%)
0 1096
23.2%
1 316
 
6.7%
2 232
 
4.9%
3 144
 
3.0%
4 165
 
3.5%
5 102
 
2.2%
6 136
 
2.9%
7 87
 
1.8%
8 121
 
2.6%
9 73
 
1.5%
ValueCountFrequency (%)
665 1
< 0.1%
661 1
< 0.1%
611 1
< 0.1%
598 1
< 0.1%
588 1
< 0.1%
580 1
< 0.1%
572 1
< 0.1%
568 2
< 0.1%
564 1
< 0.1%
562 1
< 0.1%

정선군_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct138
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.03873
Minimum0
Maximum164
Zeros1619
Zeros (%)34.3%
Negative0
Negative (%)0.0%
Memory size41.7 KiB
2024-03-15T04:31:21.755491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q321
95-th percentile74
Maximum164
Range164
Interquartile range (IQR)21

Descriptive statistics

Standard deviation25.863798
Coefficient of variation (CV)1.6125839
Kurtosis4.6277077
Mean16.03873
Median Absolute Deviation (MAD)4
Skewness2.1455235
Sum75783
Variance668.93605
MonotonicityNot monotonic
2024-03-15T04:31:22.220955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1619
34.3%
1 274
 
5.8%
2 266
 
5.6%
4 206
 
4.4%
3 175
 
3.7%
5 130
 
2.8%
6 122
 
2.6%
8 110
 
2.3%
7 87
 
1.8%
10 77
 
1.6%
Other values (128) 1659
35.1%
ValueCountFrequency (%)
0 1619
34.3%
1 274
 
5.8%
2 266
 
5.6%
3 175
 
3.7%
4 206
 
4.4%
5 130
 
2.8%
6 122
 
2.6%
7 87
 
1.8%
8 110
 
2.3%
9 69
 
1.5%
ValueCountFrequency (%)
164 1
 
< 0.1%
152 1
 
< 0.1%
150 1
 
< 0.1%
147 1
 
< 0.1%
145 1
 
< 0.1%
144 1
 
< 0.1%
142 1
 
< 0.1%
140 1
 
< 0.1%
138 1
 
< 0.1%
137 3
0.1%

태백시_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct157
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.970794
Minimum0
Maximum206
Zeros1008
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size41.7 KiB
2024-03-15T04:31:22.651897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median9
Q348
95-th percentile93
Maximum206
Range206
Interquartile range (IQR)46

Descriptive statistics

Standard deviation33.047037
Coefficient of variation (CV)1.2252898
Kurtosis1.3534521
Mean26.970794
Median Absolute Deviation (MAD)9
Skewness1.3255858
Sum127437
Variance1092.1067
MonotonicityNot monotonic
2024-03-15T04:31:23.124204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1008
21.3%
4 286
 
6.1%
3 251
 
5.3%
2 200
 
4.2%
1 147
 
3.1%
5 142
 
3.0%
8 124
 
2.6%
6 109
 
2.3%
10 70
 
1.5%
7 69
 
1.5%
Other values (147) 2319
49.1%
ValueCountFrequency (%)
0 1008
21.3%
1 147
 
3.1%
2 200
 
4.2%
3 251
 
5.3%
4 286
 
6.1%
5 142
 
3.0%
6 109
 
2.3%
7 69
 
1.5%
8 124
 
2.6%
9 46
 
1.0%
ValueCountFrequency (%)
206 1
< 0.1%
203 1
< 0.1%
201 1
< 0.1%
185 1
< 0.1%
179 1
< 0.1%
177 1
< 0.1%
173 1
< 0.1%
169 1
< 0.1%
165 1
< 0.1%
162 1
< 0.1%

영월군_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct51
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7944974
Minimum0
Maximum54
Zeros2777
Zeros (%)58.8%
Negative0
Negative (%)0.0%
Memory size41.7 KiB
2024-03-15T04:31:23.589505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q36
95-th percentile18
Maximum54
Range54
Interquartile range (IQR)6

Descriptive statistics

Standard deviation6.7294935
Coefficient of variation (CV)1.7734875
Kurtosis8.9307887
Mean3.7944974
Median Absolute Deviation (MAD)0
Skewness2.565199
Sum17929
Variance45.286083
MonotonicityNot monotonic
2024-03-15T04:31:24.130796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2777
58.8%
2 193
 
4.1%
1 164
 
3.5%
3 162
 
3.4%
6 136
 
2.9%
4 136
 
2.9%
12 111
 
2.3%
5 107
 
2.3%
8 104
 
2.2%
7 91
 
1.9%
Other values (41) 744
 
15.7%
ValueCountFrequency (%)
0 2777
58.8%
1 164
 
3.5%
2 193
 
4.1%
3 162
 
3.4%
4 136
 
2.9%
5 107
 
2.3%
6 136
 
2.9%
7 91
 
1.9%
8 104
 
2.2%
9 87
 
1.8%
ValueCountFrequency (%)
54 1
 
< 0.1%
53 1
 
< 0.1%
51 2
< 0.1%
50 1
 
< 0.1%
49 1
 
< 0.1%
47 3
0.1%
46 3
0.1%
45 2
< 0.1%
44 2
< 0.1%
43 1
 
< 0.1%

삼척시_건수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct77
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0962963
Minimum0
Maximum94
Zeros2219
Zeros (%)47.0%
Negative0
Negative (%)0.0%
Memory size41.7 KiB
2024-03-15T04:31:24.581375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q38
95-th percentile28
Maximum94
Range94
Interquartile range (IQR)8

Descriptive statistics

Standard deviation10.659986
Coefficient of variation (CV)1.7486004
Kurtosis12.722965
Mean6.0962963
Median Absolute Deviation (MAD)1
Skewness3.0685753
Sum28805
Variance113.63531
MonotonicityNot monotonic
2024-03-15T04:31:25.011675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2219
47.0%
2 250
 
5.3%
4 218
 
4.6%
3 201
 
4.3%
1 185
 
3.9%
8 166
 
3.5%
5 146
 
3.1%
6 146
 
3.1%
10 120
 
2.5%
12 104
 
2.2%
Other values (67) 970
20.5%
ValueCountFrequency (%)
0 2219
47.0%
1 185
 
3.9%
2 250
 
5.3%
3 201
 
4.3%
4 218
 
4.6%
5 146
 
3.1%
6 146
 
3.1%
7 84
 
1.8%
8 166
 
3.5%
9 71
 
1.5%
ValueCountFrequency (%)
94 1
 
< 0.1%
92 1
 
< 0.1%
84 1
 
< 0.1%
83 3
0.1%
82 1
 
< 0.1%
80 1
 
< 0.1%
79 1
 
< 0.1%
78 1
 
< 0.1%
75 2
< 0.1%
74 2
< 0.1%

Interactions

2024-03-15T04:31:16.164524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:06.573856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:08.170024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:09.864391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:11.916817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:13.991284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:16.529206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:06.850131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:08.459205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:10.151631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:12.177534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:14.517031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:17.058322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:07.143203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:08.779598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:10.790970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:12.427472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:14.839515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:17.394087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:07.442088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:09.060025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:11.207191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:12.783880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:15.221296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:17.647828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:07.682527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:09.325804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:11.407552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:13.116774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:15.628695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:17.946819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:07.927555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:09.599518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:11.645578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:13.496732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T04:31:15.915788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T04:31:25.276079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종고한읍_건수사북읍_건수정선군_건수태백시_건수영월군_건수삼척시_건수
업종1.0000.6990.5720.6510.7000.5860.589
고한읍_건수0.6991.0000.8300.7730.5880.5740.422
사북읍_건수0.5720.8301.0000.7560.6120.5780.493
정선군_건수0.6510.7730.7561.0000.5260.5710.402
태백시_건수0.7000.5880.6120.5261.0000.6530.587
영월군_건수0.5860.5740.5780.5710.6531.0000.464
삼척시_건수0.5890.4220.4930.4020.5870.4641.000
2024-03-15T04:31:25.815681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
고한읍_건수사북읍_건수정선군_건수태백시_건수영월군_건수삼척시_건수업종
고한읍_건수1.0000.8250.8200.6120.5810.3920.360
사북읍_건수0.8251.0000.7460.5950.5720.4110.264
정선군_건수0.8200.7461.0000.6480.5880.3930.320
태백시_건수0.6120.5950.6481.0000.7330.6320.361
영월군_건수0.5810.5720.5880.7331.0000.5800.272
삼척시_건수0.3920.4110.3930.6320.5801.0000.275
업종0.3600.2640.3200.3610.2720.2751.000

Missing values

2024-03-15T04:31:18.300507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:31:18.718851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

사용일자업종고한읍_건수사북읍_건수정선군_건수태백시_건수영월군_건수삼척시_건수
02023-01-01휴게음식점업381100
12023-01-01식품판매업452075243118
22023-01-01소매업22921561014
32023-01-01주유소·LPG충전소86056345413
42023-01-01세탁업000902
52023-01-01목욕장업0180300
62023-01-01슈퍼마켓2054299296444
72023-01-01일반음식점업18356814255124
82023-01-01이ㆍ미용업120123600
92023-01-01숙박업178310106200
사용일자업종고한읍_건수사북읍_건수정선군_건수태백시_건수영월군_건수삼척시_건수
47152023-12-31숙박업5632601800
47162023-12-31커피전문점17202005
47172023-12-31실내 스크린 골프업010000
47182023-12-31슈퍼마켓105112305
47192023-12-31이ㆍ미용업00022018
47202023-12-31세탁업002004
47212023-12-31일반주점업010000
47222023-12-31주유소·LPG충전소000001
47232023-12-31식품판매업3420535113
47242023-12-31소매업1231823618