Overview

Dataset statistics

Number of variables6
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.0 KiB
Average record size in memory53.3 B

Variable types

Categorical1
Numeric5

Dataset

Description샘플 데이터
Author신한카드
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=318

Reproduction

Analysis started2023-12-10 14:59:03.764340
Analysis finished2023-12-10 14:59:10.681982
Duration6.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종대분류(UPJONG_CLASS1)
Categorical

Distinct14
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
유통
88 
전자상거래
79 
요식/유흥
63 
의료
43 
주유
40 
Other values (9)
187 

Length

Max length9
Median length8
Mean length4.314
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row요식/유흥
2nd row유통
3rd row유통
4th row스포츠/문화/레저
5th row의료

Common Values

ValueCountFrequency (%)
유통 88
17.6%
전자상거래 79
15.8%
요식/유흥 63
12.6%
의료 43
8.6%
주유 40
8.0%
가정생활/서비스 39
7.8%
음/식료품 34
 
6.8%
스포츠/문화/레저 30
 
6.0%
여행/교통 29
 
5.8%
미용 15
 
3.0%
Other values (4) 40
8.0%

Length

2023-12-10T23:59:10.847131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
유통 88
17.6%
전자상거래 79
15.8%
요식/유흥 63
12.6%
의료 43
8.6%
주유 40
8.0%
가정생활/서비스 39
7.8%
음/식료품 34
 
6.8%
스포츠/문화/레저 30
 
6.0%
여행/교통 29
 
5.8%
미용 15
 
3.0%
Other values (4) 40
8.0%

기준일자(YMD)
Real number (ℝ)

Distinct444
Distinct (%)88.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20183282
Minimum20160101
Maximum20210731
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:59:11.104451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20160101
5-th percentile20160409
Q120170528
median20180908
Q320200208
95-th percentile20210318
Maximum20210731
Range50630
Interquartile range (IQR)29680.75

Descriptive statistics

Standard deviation16132.927
Coefficient of variation (CV)0.0007993213
Kurtosis-1.1825464
Mean20183282
Median Absolute Deviation (MAD)10502.5
Skewness0.11523271
Sum1.0091641 × 1010
Variance2.6027133 × 108
MonotonicityNot monotonic
2023-12-10T23:59:11.413188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160604 3
 
0.6%
20190708 3
 
0.6%
20180607 3
 
0.6%
20200831 3
 
0.6%
20200802 3
 
0.6%
20170303 2
 
0.4%
20171002 2
 
0.4%
20160212 2
 
0.4%
20190629 2
 
0.4%
20191105 2
 
0.4%
Other values (434) 475
95.0%
ValueCountFrequency (%)
20160101 1
0.2%
20160102 2
0.4%
20160106 1
0.2%
20160110 1
0.2%
20160117 1
0.2%
20160120 1
0.2%
20160128 1
0.2%
20160201 1
0.2%
20160203 1
0.2%
20160212 2
0.4%
ValueCountFrequency (%)
20210731 2
0.4%
20210728 1
0.2%
20210723 2
0.4%
20210721 1
0.2%
20210714 1
0.2%
20210709 1
0.2%
20210704 1
0.2%
20210701 1
0.2%
20210629 1
0.2%
20210628 1
0.2%

시간대구간(TIME)
Real number (ℝ)

Distinct6
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.802
Minimum1
Maximum6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:59:11.657352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median4
Q35
95-th percentile6
Maximum6
Range5
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4543129
Coefficient of variation (CV)0.3825126
Kurtosis-0.91117675
Mean3.802
Median Absolute Deviation (MAD)1
Skewness-0.15451449
Sum1901
Variance2.1150261
MonotonicityNot monotonic
2023-12-10T23:59:11.868386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 111
22.2%
5 108
21.6%
4 107
21.4%
6 71
14.2%
2 71
14.2%
1 32
 
6.4%
ValueCountFrequency (%)
1 32
 
6.4%
2 71
14.2%
3 111
22.2%
4 107
21.4%
5 108
21.6%
6 71
14.2%
ValueCountFrequency (%)
6 71
14.2%
5 108
21.6%
4 107
21.4%
3 111
22.2%
2 71
14.2%
1 32
 
6.4%

고객주소집계구별(TOT_REG_CD)
Real number (ℝ)

Distinct496
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1147393 × 1012
Minimum1.101053 × 1012
Maximum1.125072 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:59:12.226640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.101053 × 1012
5-th percentile1.1040031 × 1012
Q11.1090638 × 1012
median1.115066 × 1012
Q31.1210713 × 1012
95-th percentile1.124077 × 1012
Maximum1.125072 × 1012
Range2.4019 × 1010
Interquartile range (IQR)1.2007489 × 1010

Descriptive statistics

Standard deviation6.7868108 × 109
Coefficient of variation (CV)0.0060882493
Kurtosis-1.1166061
Mean1.1147393 × 1012
Median Absolute Deviation (MAD)6.003525 × 109
Skewness-0.19786845
Sum5.5736965 × 1014
Variance4.6060801 × 1019
MonotonicityNot monotonic
2023-12-10T23:59:12.603877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1122055020804 2
 
0.4%
1112072010025 2
 
0.4%
1108083020102 2
 
0.4%
1124059030119 2
 
0.4%
1108059020407 1
 
0.2%
1115071030104 1
 
0.2%
1114071010011 1
 
0.2%
1124080020102 1
 
0.2%
1106086010107 1
 
0.2%
1123076010009 1
 
0.2%
Other values (486) 486
97.2%
ValueCountFrequency (%)
1101053020002 1
0.2%
1101054010002 1
0.2%
1101055020005 1
0.2%
1101056020002 1
0.2%
1101061030201 1
0.2%
1101067010102 1
0.2%
1101068010002 1
0.2%
1101072010019 1
0.2%
1102067020001 1
0.2%
1102069010002 1
0.2%
ValueCountFrequency (%)
1125072020311 1
0.2%
1125072010002 1
0.2%
1125071020030 1
0.2%
1125071020027 1
0.2%
1125071020026 1
0.2%
1125065022601 1
0.2%
1125065010504 1
0.2%
1125063020301 1
0.2%
1125061020016 1
0.2%
1125061020008 1
0.2%

카드이용금액계(AMT_CORR)
Real number (ℝ)

Distinct418
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean657846.89
Minimum5
Maximum40847926
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:59:12.909618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile15064.85
Q178505.5
median269834.5
Q3632651
95-th percentile1745415.3
Maximum40847926
Range40847921
Interquartile range (IQR)554145.5

Descriptive statistics

Standard deviation2221250.6
Coefficient of variation (CV)3.3765465
Kurtosis221.90479
Mean657846.89
Median Absolute Deviation (MAD)219283
Skewness13.317176
Sum3.2892345 × 108
Variance4.9339544 × 1012
MonotonicityNot monotonic
2023-12-10T23:59:13.234048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50300 7
 
1.4%
150900 5
 
1.0%
20120 4
 
0.8%
251500 4
 
0.8%
10060 4
 
0.8%
30180 4
 
0.8%
60360 4
 
0.8%
301800 4
 
0.8%
5030 4
 
0.8%
100600 4
 
0.8%
Other values (408) 456
91.2%
ValueCountFrequency (%)
5 1
 
0.2%
2012 2
0.4%
5030 4
0.8%
5533 1
 
0.2%
6036 1
 
0.2%
6539 1
 
0.2%
8048 1
 
0.2%
8551 1
 
0.2%
9054 1
 
0.2%
9557 2
0.4%
ValueCountFrequency (%)
40847926 1
0.2%
15536815 1
0.2%
11531979 1
0.2%
11394962 1
0.2%
10559831 1
0.2%
7728042 1
0.2%
5954202 1
0.2%
5111989 1
0.2%
5098006 1
0.2%
4939158 1
0.2%

카드이용건수계(USECT_CORR)
Real number (ℝ)

Distinct22
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.002
Minimum5
Maximum236
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:59:13.530346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median10
Q325
95-th percentile55
Maximum236
Range231
Interquartile range (IQR)20

Descriptive statistics

Standard deviation23.37989
Coefficient of variation (CV)1.230391
Kurtosis28.241506
Mean19.002
Median Absolute Deviation (MAD)5
Skewness4.2234093
Sum9501
Variance546.61923
MonotonicityNot monotonic
2023-12-10T23:59:13.774425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
5 202
40.4%
10 79
 
15.8%
15 48
 
9.6%
25 35
 
7.0%
20 27
 
5.4%
30 22
 
4.4%
40 17
 
3.4%
35 16
 
3.2%
45 16
 
3.2%
50 10
 
2.0%
Other values (12) 28
 
5.6%
ValueCountFrequency (%)
5 202
40.4%
10 79
 
15.8%
15 48
 
9.6%
20 27
 
5.4%
25 35
 
7.0%
30 22
 
4.4%
35 16
 
3.2%
40 17
 
3.4%
45 16
 
3.2%
50 10
 
2.0%
ValueCountFrequency (%)
236 1
 
0.2%
211 1
 
0.2%
176 1
 
0.2%
106 3
0.6%
101 1
 
0.2%
96 1
 
0.2%
91 2
0.4%
86 1
 
0.2%
80 1
 
0.2%
70 4
0.8%

Interactions

2023-12-10T23:59:09.308022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:04.173859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:05.147824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:06.916973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:08.185740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:09.510098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:04.353290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:05.458949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:07.283398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:08.402609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:09.703488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:04.537690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:05.746828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:07.518675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:08.606809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:09.915557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:04.735656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:06.083568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:07.757102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:08.827364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:10.112742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:04.961690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:06.570960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:08.014651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:59:09.094109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:59:14.345554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종대분류(UPJONG_CLASS1)기준일자(YMD)시간대구간(TIME)고객주소집계구별(TOT_REG_CD)카드이용금액계(AMT_CORR)카드이용건수계(USECT_CORR)
업종대분류(UPJONG_CLASS1)1.0000.0870.0000.1230.0790.077
기준일자(YMD)0.0871.0000.0000.0000.0000.000
시간대구간(TIME)0.0000.0001.0000.0750.0000.000
고객주소집계구별(TOT_REG_CD)0.1230.0000.0751.0000.0570.089
카드이용금액계(AMT_CORR)0.0790.0000.0000.0571.0000.097
카드이용건수계(USECT_CORR)0.0770.0000.0000.0890.0971.000
2023-12-10T23:59:14.603823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자(YMD)시간대구간(TIME)고객주소집계구별(TOT_REG_CD)카드이용금액계(AMT_CORR)카드이용건수계(USECT_CORR)업종대분류(UPJONG_CLASS1)
기준일자(YMD)1.0000.0180.063-0.023-0.0070.036
시간대구간(TIME)0.0181.000-0.035-0.0050.0500.000
고객주소집계구별(TOT_REG_CD)0.063-0.0351.0000.071-0.0910.043
카드이용금액계(AMT_CORR)-0.023-0.0050.0711.0000.0220.040
카드이용건수계(USECT_CORR)-0.0070.050-0.0910.0221.0000.033
업종대분류(UPJONG_CLASS1)0.0360.0000.0430.0400.0331.000

Missing values

2023-12-10T23:59:10.343697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:59:10.571974image/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

업종대분류(UPJONG_CLASS1)기준일자(YMD)시간대구간(TIME)고객주소집계구별(TOT_REG_CD)카드이용금액계(AMT_CORR)카드이용건수계(USECT_CORR)
0요식/유흥201610046112307601000910462410
1유통202103035112206003000338259220
2유통20170606611230660223013416885
3스포츠/문화/레저20171206511240750201039251185
4의료201609096111307503000221798550
5스포츠/문화/레저201611213112307301010859203110
6의료2019102031116051010006349595
7주유2017062531121052030002503020
8음/식료품20180427611080680105013319805
9스포츠/문화/레저2018011821122068040202196175
업종대분류(UPJONG_CLASS1)기준일자(YMD)시간대구간(TIME)고객주소집계구별(TOT_REG_CD)카드이용금액계(AMT_CORR)카드이용건수계(USECT_CORR)
490전자상거래20170808311050620305063018005
491주유2018053151114077050301215787035
492여행/교통20160731411030710400064879150
493요식/유흥20160326111230650108017168255
494전자상거래20180619411250720203116539010
495전자상거래20170727211200690100069054025
496유통2019040631123072010303121132520
497교육/학원202101073111907203010126659015
498전자상거래202004264110506303020354726425
499여행/교통2016062541103072030001105598315