Overview

Dataset statistics

Number of variables8
Number of observations101
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.9 KiB
Average record size in memory70.3 B

Variable types

Numeric5
Categorical1
Boolean1
DateTime1

Dataset

Description제주관광공사 온라인면세점 관리자시스템을 통해 온라인면세점 고객의 주문번호와 상품 및 검색어이력을 연계해서 관리하는 데이터
Author공공데이터포털
URLhttps://www.data.go.kr/data/15118684/fileData.do

Alerts

삭제여부 has constant value ""Constant
아이디 is highly overall correlated with 검색어이력아이디High correlation
검색어이력아이디 is highly overall correlated with 아이디High correlation
회원번호 is highly overall correlated with 장바구니아이디High correlation
장바구니아이디 is highly overall correlated with 회원번호High correlation
주문서아이디 is highly imbalanced (59.9%)Imbalance
아이디 has unique valuesUnique
회원번호 has 23 (22.8%) zerosZeros
장바구니아이디 has 42 (41.6%) zerosZeros

Reproduction

Analysis started2024-04-21 12:22:34.212615
Analysis finished2024-04-21 12:22:38.842780
Duration4.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아이디
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct101
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean149.0198
Minimum1
Maximum200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T21:22:38.977378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile105
Q1125
median150
Q3175
95-th percentile195
Maximum200
Range199
Interquartile range (IQR)50

Descriptive statistics

Standard deviation32.473676
Coefficient of variation (CV)0.21791517
Kurtosis2.6951551
Mean149.0198
Median Absolute Deviation (MAD)25
Skewness-0.85583623
Sum15051
Variance1054.5396
MonotonicityStrictly increasing
2024-04-21T21:22:39.238262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
164 1
 
1.0%
174 1
 
1.0%
173 1
 
1.0%
172 1
 
1.0%
171 1
 
1.0%
170 1
 
1.0%
169 1
 
1.0%
168 1
 
1.0%
167 1
 
1.0%
Other values (91) 91
90.1%
ValueCountFrequency (%)
1 1
1.0%
101 1
1.0%
102 1
1.0%
103 1
1.0%
104 1
1.0%
105 1
1.0%
106 1
1.0%
107 1
1.0%
108 1
1.0%
109 1
1.0%
ValueCountFrequency (%)
200 1
1.0%
199 1
1.0%
198 1
1.0%
197 1
1.0%
196 1
1.0%
195 1
1.0%
194 1
1.0%
193 1
1.0%
192 1
1.0%
191 1
1.0%

검색어이력아이디
Real number (ℝ)

HIGH CORRELATION 

Distinct97
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3564574.3
Minimum3563292
Maximum3566405
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T21:22:39.494963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3563292
5-th percentile3563360
Q13564076
median3564658
Q33565199
95-th percentile3565477
Maximum3566405
Range3113
Interquartile range (IQR)1123

Descriptive statistics

Standard deviation682.93637
Coefficient of variation (CV)0.00019158988
Kurtosis-0.77204129
Mean3564574.3
Median Absolute Deviation (MAD)561
Skewness-0.064255132
Sum3.6002201 × 108
Variance466402.09
MonotonicityNot monotonic
2024-04-21T21:22:39.749502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3563292 2
 
2.0%
3564517 2
 
2.0%
3564248 2
 
2.0%
3564319 2
 
2.0%
3566405 1
 
1.0%
3564929 1
 
1.0%
3565183 1
 
1.0%
3565075 1
 
1.0%
3565058 1
 
1.0%
3564971 1
 
1.0%
Other values (87) 87
86.1%
ValueCountFrequency (%)
3563292 2
2.0%
3563331 1
1.0%
3563335 1
1.0%
3563358 1
1.0%
3563360 1
1.0%
3563499 1
1.0%
3563513 1
1.0%
3563533 1
1.0%
3563679 1
1.0%
3563705 1
1.0%
ValueCountFrequency (%)
3566405 1
1.0%
3565628 1
1.0%
3565555 1
1.0%
3565553 1
1.0%
3565518 1
1.0%
3565477 1
1.0%
3565467 1
1.0%
3565458 1
1.0%
3565436 1
1.0%
3565415 1
1.0%

상품아이디
Real number (ℝ)

Distinct18
Distinct (%)17.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4381188 × 1012
Minimum1.11 × 1012
Maximum5.56 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T21:22:39.974540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.11 × 1012
5-th percentile1.11 × 1012
Q11.12 × 1012
median3.42 × 1012
Q35.41 × 1012
95-th percentile5.56 × 1012
Maximum5.56 × 1012
Range4.45 × 1012
Interquartile range (IQR)4.29 × 1012

Descriptive statistics

Standard deviation1.9341772 × 1012
Coefficient of variation (CV)0.56256846
Kurtosis-1.8031674
Mean3.4381188 × 1012
Median Absolute Deviation (MAD)2 × 1012
Skewness-0.17817672
Sum3.4725 × 1014
Variance3.7410414 × 1024
MonotonicityNot monotonic
2024-04-21T21:22:40.175643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
1120000000000 20
19.8%
5410000000000 13
12.9%
1110000000000 9
8.9%
5560000000000 8
 
7.9%
5420000000000 8
 
7.9%
5120000000000 8
 
7.9%
3420000000000 6
 
5.9%
3410000000000 5
 
5.0%
5230000000000 5
 
5.0%
3220000000000 3
 
3.0%
Other values (8) 16
15.8%
ValueCountFrequency (%)
1110000000000 9
8.9%
1120000000000 20
19.8%
1130000000000 3
 
3.0%
1220000000000 2
 
2.0%
1410000000000 2
 
2.0%
1510000000000 3
 
3.0%
3130000000000 1
 
1.0%
3220000000000 3
 
3.0%
3410000000000 5
 
5.0%
3420000000000 6
 
5.9%
ValueCountFrequency (%)
5560000000000 8
7.9%
5430000000000 1
 
1.0%
5420000000000 8
7.9%
5410000000000 13
12.9%
5230000000000 5
 
5.0%
5220000000000 1
 
1.0%
5130000000000 3
 
3.0%
5120000000000 8
7.9%
3420000000000 6
5.9%
3410000000000 5
 
5.0%

회원번호
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)47.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77425659
Minimum0
Maximum1.0030097 × 108
Zeros23
Zeros (%)22.8%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T21:22:40.412058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.0000232 × 108
median1.0029901 × 108
Q31.0030094 × 108
95-th percentile1.0030097 × 108
Maximum1.0030097 × 108
Range1.0030097 × 108
Interquartile range (IQR)298618

Descriptive statistics

Standard deviation42253524
Coefficient of variation (CV)0.54573025
Kurtosis-0.26810208
Mean77425659
Median Absolute Deviation (MAD)1953
Skewness-1.3181747
Sum7.8199915 × 109
Variance1.7853603 × 1015
MonotonicityNot monotonic
2024-04-21T21:22:40.666033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 23
22.8%
100299014 6
 
5.9%
100300957 4
 
4.0%
100300946 4
 
4.0%
100300969 4
 
4.0%
100300921 3
 
3.0%
100300935 3
 
3.0%
100300122 3
 
3.0%
100298895 3
 
3.0%
100298711 2
 
2.0%
Other values (38) 46
45.5%
ValueCountFrequency (%)
0 23
22.8%
100000274 1
 
1.0%
100002151 1
 
1.0%
100002317 1
 
1.0%
100022199 1
 
1.0%
100066215 2
 
2.0%
100075821 1
 
1.0%
100076598 1
 
1.0%
100104491 2
 
2.0%
100110131 1
 
1.0%
ValueCountFrequency (%)
100300969 4
4.0%
100300968 1
 
1.0%
100300967 2
2.0%
100300965 1
 
1.0%
100300964 1
 
1.0%
100300959 1
 
1.0%
100300957 4
4.0%
100300952 1
 
1.0%
100300951 1
 
1.0%
100300950 1
 
1.0%

장바구니아이디
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107365.48
Minimum0
Maximum210893
Zeros42
Zeros (%)41.6%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-21T21:22:40.898705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median138639
Q3210813
95-th percentile210884
Maximum210893
Range210893
Interquartile range (IQR)210813

Descriptive statistics

Standard deviation102183.12
Coefficient of variation (CV)0.95173165
Kurtosis-1.9929347
Mean107365.48
Median Absolute Deviation (MAD)72254
Skewness-0.036102418
Sum10843913
Variance1.044139 × 1010
MonotonicityNot monotonic
2024-04-21T21:22:41.119319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 42
41.6%
208075 6
 
5.9%
210865 4
 
4.0%
210833 3
 
3.0%
210893 3
 
3.0%
209685 3
 
3.0%
210813 3
 
3.0%
207898 2
 
2.0%
13946 2
 
2.0%
208567 2
 
2.0%
Other values (29) 31
30.7%
ValueCountFrequency (%)
0 42
41.6%
6400 1
 
1.0%
13946 2
 
2.0%
25031 2
 
2.0%
45056 1
 
1.0%
73593 1
 
1.0%
87921 1
 
1.0%
138639 1
 
1.0%
165140 1
 
1.0%
178028 1
 
1.0%
ValueCountFrequency (%)
210893 3
3.0%
210891 1
 
1.0%
210884 2
2.0%
210880 1
 
1.0%
210876 1
 
1.0%
210868 1
 
1.0%
210867 1
 
1.0%
210865 4
4.0%
210856 1
 
1.0%
210851 1
 
1.0%

주문서아이디
Categorical

IMBALANCE 

Distinct11
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size936.0 B
0
80 
B2019121721420950655
 
4
B2019121723175897966
 
4
B2019121720132235867
 
3
B2019121721183138325
 
2
Other values (6)
 
8

Length

Max length20
Median length1
Mean length4.950495
Min length1

Unique

Unique4 ?
Unique (%)4.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 80
79.2%
B2019121721420950655 4
 
4.0%
B2019121723175897966 4
 
4.0%
B2019121720132235867 3
 
3.0%
B2019121721183138325 2
 
2.0%
B2019121722401503647 2
 
2.0%
B2019121801221486241 2
 
2.0%
B2019121718302962274 1
 
1.0%
B2019121720073909696 1
 
1.0%
B2019121723174380772 1
 
1.0%

Length

2024-04-21T21:22:41.342209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 80
79.2%
b2019121721420950655 4
 
4.0%
b2019121723175897966 4
 
4.0%
b2019121720132235867 3
 
3.0%
b2019121721183138325 2
 
2.0%
b2019121722401503647 2
 
2.0%
b2019121801221486241 2
 
2.0%
b2019121718302962274 1
 
1.0%
b2019121720073909696 1
 
1.0%
b2019121723174380772 1
 
1.0%

삭제여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size229.0 B
False
101 
ValueCountFrequency (%)
False 101
100.0%
2024-04-21T21:22:41.510745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

등록일자
Date

Distinct85
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size936.0 B
Minimum2019-12-17 17:41:00
Maximum2019-12-18 09:44:00
2024-04-21T21:22:41.681792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:41.912300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-04-21T21:22:37.775509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:34.601992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:35.365079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:36.143532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:36.847753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:37.928057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:34.765158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:35.532396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:36.294911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:37.007411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:38.078474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:34.928013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:35.699160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:36.446061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:37.161036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:38.209195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:35.071462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:35.848985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:36.575420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:37.302569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:38.352441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:35.224628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:35.999343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:36.718549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T21:22:37.441438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T21:22:42.076170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디검색어이력아이디상품아이디회원번호장바구니아이디주문서아이디등록일자
아이디1.0000.9700.2770.2470.7140.4030.996
검색어이력아이디0.9701.0000.3880.2390.7790.5491.000
상품아이디0.2770.3881.0000.1790.2880.2450.847
회원번호0.2470.2390.1791.0000.5560.0000.000
장바구니아이디0.7140.7790.2880.5561.0000.7320.947
주문서아이디0.4030.5490.2450.0000.7321.0000.973
등록일자0.9961.0000.8470.0000.9470.9731.000
2024-04-21T21:22:42.267052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
아이디검색어이력아이디상품아이디회원번호장바구니아이디주문서아이디
아이디1.0000.9190.1990.0540.0710.212
검색어이력아이디0.9191.0000.221-0.0040.0400.278
상품아이디0.1990.2211.000-0.0430.0080.050
회원번호0.054-0.004-0.0431.0000.6690.000
장바구니아이디0.0710.0400.0080.6691.0000.440
주문서아이디0.2120.2780.0500.0000.4401.000

Missing values

2024-04-21T21:22:38.537893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T21:22:38.757535image/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

아이디검색어이력아이디상품아이디회원번호장바구니아이디주문서아이디삭제여부등록일자
01356640555600000000001000023171651400N2019-12-18 9:44
11013563292113000000000010023043000N2019-12-17 17:41
21023563292113000000000010023043000N2019-12-17 17:41
3103356333111100000000001003009122108050N2019-12-17 17:47
4104356333555600000000001003008512107170N2019-12-17 17:48
510535633601120000000000000N2019-12-17 17:59
6106356335811100000000001003003492107660N2019-12-17 18:00
7107356349954200000000001003009172108090N2019-12-17 18:27
81083563513111000000000010000027473593B2019121718302962274N2019-12-17 18:30
91093563679112000000000010030092000N2019-12-17 19:15
아이디검색어이력아이디상품아이디회원번호장바구니아이디주문서아이디삭제여부등록일자
91191356540752200000000001002995782088950N2019-12-18 0:34
9219235654155120000000000000N2019-12-18 0:34
93193356543634100000000001003009692108930N2019-12-18 0:49
94194356545834100000000001003009692108930N2019-12-18 0:51
95195356546734100000000001003009692108930N2019-12-18 0:52
961963565477341000000000010030096900N2019-12-18 0:56
9719735655185420000000000100066215139460N2019-12-18 1:06
9819835655535420000000000100066215139460N2019-12-18 1:11
9919935655555410000000000100185314208567B2019121801221486241N2019-12-18 1:13
10020035656285130000000000100300197209777B2019121801281116268N2019-12-18 1:28