Overview

Dataset statistics

Number of variables8
Number of observations500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.3 KiB
Average record size in memory70.3 B

Variable types

Numeric6
Categorical2

Dataset

Description샘플 데이터
Author신한카드
URLhttps://bigdata.seoul.go.kr/data/selectSampleData.do?sample_data_seq=51

Alerts

기준년월(TS_YM) is highly overall correlated with 일별(TS_YMD)High correlation
일별(TS_YMD) is highly overall correlated with 기준년월(TS_YM)High correlation
시간대(TM) has 8 (1.6%) zerosZeros

Reproduction

Analysis started2023-12-10 14:53:59.778403
Analysis finished2023-12-10 14:54:08.075614
Duration8.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

가맹점블록코드(BLCK_CD)
Real number (ℝ)

Distinct491
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean196907.08
Minimum66
Maximum502478
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:54:08.187325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum66
5-th percentile14213.8
Q137391.5
median214211
Q3271625.75
95-th percentile415451.65
Maximum502478
Range502412
Interquartile range (IQR)234234.25

Descriptive statistics

Standard deviation128900.51
Coefficient of variation (CV)0.65462607
Kurtosis-0.848883
Mean196907.08
Median Absolute Deviation (MAD)67705.5
Skewness0.053874145
Sum98453539
Variance1.6615341 × 1010
MonotonicityNot monotonic
2023-12-10T23:54:08.385960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
14226 2
 
0.4%
417221 2
 
0.4%
363482 2
 
0.4%
274501 2
 
0.4%
339231 2
 
0.4%
17869 2
 
0.4%
206706 2
 
0.4%
24276 2
 
0.4%
206974 2
 
0.4%
171889 1
 
0.2%
Other values (481) 481
96.2%
ValueCountFrequency (%)
66 1
0.2%
8287 1
0.2%
8649 1
0.2%
8671 1
0.2%
9013 1
0.2%
9101 1
0.2%
9323 1
0.2%
9328 1
0.2%
10311 1
0.2%
10447 1
0.2%
ValueCountFrequency (%)
502478 1
0.2%
502471 1
0.2%
501942 1
0.2%
501402 1
0.2%
421289 1
0.2%
420604 1
0.2%
420315 1
0.2%
420249 1
0.2%
420182 1
0.2%
419478 1
0.2%

내국인업종코드(SB_UPJONG_CD)
Categorical

Distinct47
Distinct (%)9.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
SB016
103 
SB001
62 
SB008
56 
SB013
27 
SB020
24 
Other values (42)
228 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique11 ?
Unique (%)2.2%

Sample

1st rowSB001
2nd rowSB007
3rd rowSB054
4th rowSB039
5th rowSB016

Common Values

ValueCountFrequency (%)
SB016 103
20.6%
SB001 62
12.4%
SB008 56
 
11.2%
SB013 27
 
5.4%
SB020 24
 
4.8%
SB054 22
 
4.4%
SB006 21
 
4.2%
SB005 21
 
4.2%
SB039 10
 
2.0%
SB007 10
 
2.0%
Other values (37) 144
28.8%

Length

2023-12-10T23:54:08.576849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sb016 103
20.6%
sb001 62
12.4%
sb008 56
 
11.2%
sb013 27
 
5.4%
sb020 24
 
4.8%
sb054 22
 
4.4%
sb006 21
 
4.2%
sb005 21
 
4.2%
sb039 10
 
2.0%
sb007 10
 
2.0%
Other values (37) 144
28.8%

기준년월(TS_YM)
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean201894.99
Minimum201701
Maximum202107
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:54:08.763825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201701
5-th percentile201704
Q1201805
median201905
Q3202006
95-th percentile202104.05
Maximum202107
Range406
Interquartile range (IQR)201

Descriptive statistics

Standard deviation131.00168
Coefficient of variation (CV)0.0006488605
Kurtosis-1.1621621
Mean201894.99
Median Absolute Deviation (MAD)101
Skewness0.044812573
Sum1.0094749 × 108
Variance17161.441
MonotonicityNot monotonic
2023-12-10T23:54:08.985982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
201806 17
 
3.4%
202004 17
 
3.4%
202003 16
 
3.2%
201710 15
 
3.0%
201908 14
 
2.8%
201905 14
 
2.8%
201811 14
 
2.8%
202104 13
 
2.6%
201903 12
 
2.4%
202102 12
 
2.4%
Other values (45) 356
71.2%
ValueCountFrequency (%)
201701 6
 
1.2%
201702 9
1.8%
201703 7
1.4%
201704 5
 
1.0%
201705 9
1.8%
201706 3
 
0.6%
201707 12
2.4%
201708 10
2.0%
201709 3
 
0.6%
201710 15
3.0%
ValueCountFrequency (%)
202107 9
1.8%
202106 5
 
1.0%
202105 11
2.2%
202104 13
2.6%
202103 8
1.6%
202102 12
2.4%
202101 8
1.6%
202012 5
 
1.0%
202011 10
2.0%
202010 9
1.8%

일별(TS_YMD)
Real number (ℝ)

HIGH CORRELATION 

Distinct425
Distinct (%)85.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20189514
Minimum20170101
Maximum20210729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:54:09.229784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20170101
5-th percentile20170422
Q120180508
median20190528
Q320200618
95-th percentile20210428
Maximum20210729
Range40628
Interquartile range (IQR)20110.25

Descriptive statistics

Standard deviation13100.021
Coefficient of variation (CV)0.00064885271
Kurtosis-1.1621859
Mean20189514
Median Absolute Deviation (MAD)10080.5
Skewness0.044670815
Sum1.0094757 × 1010
Variance1.7161055 × 108
MonotonicityNot monotonic
2023-12-10T23:54:09.481416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180804 3
 
0.6%
20210417 3
 
0.6%
20170707 3
 
0.6%
20200424 3
 
0.6%
20181109 3
 
0.6%
20191202 3
 
0.6%
20210401 3
 
0.6%
20180609 2
 
0.4%
20190827 2
 
0.4%
20210218 2
 
0.4%
Other values (415) 473
94.6%
ValueCountFrequency (%)
20170101 1
0.2%
20170102 1
0.2%
20170108 1
0.2%
20170115 1
0.2%
20170125 1
0.2%
20170130 1
0.2%
20170206 1
0.2%
20170211 1
0.2%
20170213 1
0.2%
20170214 1
0.2%
ValueCountFrequency (%)
20210729 1
0.2%
20210726 1
0.2%
20210722 1
0.2%
20210720 1
0.2%
20210719 1
0.2%
20210715 1
0.2%
20210710 1
0.2%
20210709 1
0.2%
20210706 1
0.2%
20210630 1
0.2%

요일(DAW)
Categorical

Distinct7
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
토요일
82 
목요일
81 
금요일
79 
수요일
73 
월요일
71 
Other values (2)
114 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row토요일
2nd row금요일
3rd row금요일
4th row월요일
5th row일요일

Common Values

ValueCountFrequency (%)
토요일 82
16.4%
목요일 81
16.2%
금요일 79
15.8%
수요일 73
14.6%
월요일 71
14.2%
화요일 61
12.2%
일요일 53
10.6%

Length

2023-12-10T23:54:09.715379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:54:09.877929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
토요일 82
16.4%
목요일 81
16.2%
금요일 79
15.8%
수요일 73
14.6%
월요일 71
14.2%
화요일 61
12.2%
일요일 53
10.6%

시간대(TM)
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.124
Minimum0
Maximum23
Zeros8
Zeros (%)1.6%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:54:10.063746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5
Q111
median14
Q318
95-th percentile21
Maximum23
Range23
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.038591
Coefficient of variation (CV)0.35673966
Kurtosis0.1290635
Mean14.124
Median Absolute Deviation (MAD)4
Skewness-0.59157679
Sum7062
Variance25.387399
MonotonicityNot monotonic
2023-12-10T23:54:10.251692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
12 49
 
9.8%
18 42
 
8.4%
13 41
 
8.2%
19 40
 
8.0%
14 37
 
7.4%
15 32
 
6.4%
17 31
 
6.2%
16 29
 
5.8%
11 26
 
5.2%
9 24
 
4.8%
Other values (14) 149
29.8%
ValueCountFrequency (%)
0 8
 
1.6%
1 6
 
1.2%
2 3
 
0.6%
3 3
 
0.6%
4 4
 
0.8%
5 3
 
0.6%
6 8
 
1.6%
7 12
2.4%
8 17
3.4%
9 24
4.8%
ValueCountFrequency (%)
23 7
 
1.4%
22 15
 
3.0%
21 23
4.6%
20 24
4.8%
19 40
8.0%
18 42
8.4%
17 31
6.2%
16 29
5.8%
15 32
6.4%
14 37
7.4%

카드이용금액계(AMT_CORR)
Real number (ℝ)

Distinct339
Distinct (%)67.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean286747.82
Minimum3018
Maximum11058746
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:54:10.456407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3018
5-th percentile15064.85
Q138605.25
median90791.5
Q3247350.25
95-th percentile1153881.5
Maximum11058746
Range11055728
Interquartile range (IQR)208745

Descriptive statistics

Standard deviation802798.64
Coefficient of variation (CV)2.7996678
Kurtosis117.058
Mean286747.82
Median Absolute Deviation (MAD)65641.5
Skewness9.6932445
Sum1.4337391 × 108
Variance6.4448566 × 1011
MonotonicityNot monotonic
2023-12-10T23:54:10.693640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15090.0 11
 
2.2%
25150.0 10
 
2.0%
35210.0 8
 
1.6%
22635.0 8
 
1.6%
60360.0 7
 
1.4%
45270.0 7
 
1.4%
32695.0 6
 
1.2%
50300.0 6
 
1.2%
30180.0 6
 
1.2%
181080.0 5
 
1.0%
Other values (329) 426
85.2%
ValueCountFrequency (%)
3018.0 1
 
0.2%
4527.0 1
 
0.2%
5030.0 4
0.8%
7042.0 1
 
0.2%
7545.0 4
0.8%
8551.0 2
0.4%
9054.0 1
 
0.2%
10060.0 2
0.4%
11820.5 1
 
0.2%
12575.0 4
0.8%
ValueCountFrequency (%)
11058746.5 1
0.2%
10378951.6 1
0.2%
5030000.0 1
0.2%
3431626.8 1
0.2%
2947580.0 1
0.2%
2590450.0 1
0.2%
2210685.0 1
0.2%
1926842.1 1
0.2%
1912988.3 1
0.2%
1911400.0 1
0.2%

카드이용건수(USECT_CORR)
Real number (ℝ)

Distinct35
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.64114
Minimum5.03
Maximum241.44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.5 KiB
2023-12-10T23:54:10.900054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5.03
5-th percentile5.03
Q15.03
median10.06
Q315.09
95-th percentile46.604
Maximum241.44
Range236.41
Interquartile range (IQR)10.06

Descriptive statistics

Standard deviation22.199805
Coefficient of variation (CV)1.4193214
Kurtosis32.978572
Mean15.64114
Median Absolute Deviation (MAD)5.03
Skewness4.895071
Sum7820.57
Variance492.83132
MonotonicityNot monotonic
2023-12-10T23:54:11.087965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5.03 224
44.8%
10.06 95
19.0%
15.09 44
 
8.8%
20.12 28
 
5.6%
25.15 22
 
4.4%
30.18 12
 
2.4%
14.13 11
 
2.2%
35.21 8
 
1.6%
9.1 8
 
1.6%
19.16 6
 
1.2%
Other values (25) 42
 
8.4%
ValueCountFrequency (%)
5.03 224
44.8%
9.1 8
 
1.6%
10.06 95
19.0%
14.13 11
 
2.2%
15.09 44
 
8.8%
19.16 6
 
1.2%
20.12 28
 
5.6%
23.23 1
 
0.2%
24.19 2
 
0.4%
25.15 22
 
4.4%
ValueCountFrequency (%)
241.44 1
 
0.2%
174.13 1
 
0.2%
136.04 1
 
0.2%
130.78 2
0.4%
120.72 1
 
0.2%
110.66 1
 
0.2%
110.16 1
 
0.2%
94.61 2
0.4%
85.51 4
0.8%
70.42 3
0.6%

Interactions

2023-12-10T23:54:06.529616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:01.848985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:02.828509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:03.729243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:04.819790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:05.657357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:06.738353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:02.163904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:02.961354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:03.893650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:04.951978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:05.778182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:06.919792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:02.324675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:03.096556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:04.101654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:05.132653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:05.935629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:07.099887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:02.485537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:03.273361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:04.336249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:05.285872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:06.087039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:07.241779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:02.586449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:03.422453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:04.496210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:05.402919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:06.220660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:07.382483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:02.708773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:03.591010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:04.669109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:05.537346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:54:06.367187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:54:11.227971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점블록코드(BLCK_CD)내국인업종코드(SB_UPJONG_CD)기준년월(TS_YM)일별(TS_YMD)요일(DAW)시간대(TM)카드이용금액계(AMT_CORR)카드이용건수(USECT_CORR)
가맹점블록코드(BLCK_CD)1.0000.4470.0000.0000.0000.0000.5140.302
내국인업종코드(SB_UPJONG_CD)0.4471.0000.2500.2370.0000.0000.5260.000
기준년월(TS_YM)0.0000.2501.0001.0000.0430.1540.0730.111
일별(TS_YMD)0.0000.2371.0001.0000.0540.1580.0750.114
요일(DAW)0.0000.0000.0430.0541.0000.0000.0780.000
시간대(TM)0.0000.0000.1540.1580.0001.0000.0000.000
카드이용금액계(AMT_CORR)0.5140.5260.0730.0750.0780.0001.0000.410
카드이용건수(USECT_CORR)0.3020.0000.1110.1140.0000.0000.4101.000
2023-12-10T23:54:11.411530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
내국인업종코드(SB_UPJONG_CD)요일(DAW)
내국인업종코드(SB_UPJONG_CD)1.0000.000
요일(DAW)0.0001.000
2023-12-10T23:54:11.553902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점블록코드(BLCK_CD)기준년월(TS_YM)일별(TS_YMD)시간대(TM)카드이용금액계(AMT_CORR)카드이용건수(USECT_CORR)내국인업종코드(SB_UPJONG_CD)요일(DAW)
가맹점블록코드(BLCK_CD)1.0000.0200.020-0.0130.011-0.0030.1620.000
기준년월(TS_YM)0.0201.0001.000-0.078-0.012-0.0090.1040.026
일별(TS_YMD)0.0201.0001.000-0.078-0.013-0.0110.0970.033
시간대(TM)-0.013-0.078-0.0781.0000.0220.1200.0000.000
카드이용금액계(AMT_CORR)0.011-0.012-0.0130.0221.0000.0400.2440.046
카드이용건수(USECT_CORR)-0.003-0.009-0.0110.1200.0401.0000.0000.000
내국인업종코드(SB_UPJONG_CD)0.1620.1040.0970.0000.2440.0001.0000.000
요일(DAW)0.0000.0260.0330.0000.0460.0000.0001.000

Missing values

2023-12-10T23:54:07.535375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:54:07.723461image/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

가맹점블록코드(BLCK_CD)내국인업종코드(SB_UPJONG_CD)기준년월(TS_YM)일별(TS_YMD)요일(DAW)시간대(TM)카드이용금액계(AMT_CORR)카드이용건수(USECT_CORR)
0231793SB00120190620190612토요일1858851.020.12
111694SB00720171120171127금요일121629.010.06
2420182SB05420190420190407금요일1925150.060.36
3158487SB03920171220171225월요일1860360.010.06
433587SB01620170420170422일요일18111666.05.03
517869SB00620170620170601토요일19181080.05.03
6151716SB04920201220201221목요일1845270.010.06
7274538SB00520210520210521화요일20264578.0174.13
8209856SB00620170820170816월요일12326044.65.03
9168334SB01320191220191204일요일13294154.410.06
가맹점블록코드(BLCK_CD)내국인업종코드(SB_UPJONG_CD)기준년월(TS_YM)일별(TS_YMD)요일(DAW)시간대(TM)카드이용금액계(AMT_CORR)카드이용건수(USECT_CORR)
490224440SB05420200820200831화요일1735210.015.09
49119855SB01320210720210726금요일1732695.059.4
492269079SB01620181120181124월요일14145870.05.03
493218418SB00820181120181105수요일945270.014.13
494365651SB02020190920190920금요일1515090.023.23
49523342SB01620170320170314토요일1987360.05.03
49621173SB01920180420180414월요일14219811.05.03
49747892SB01620210620210621금요일15364000.020.12
49828521SB00120181120181106목요일19251500.09.1
49911707SB05420200420200423수요일15313950.025.15