Overview

Dataset statistics

Number of variables18
Number of observations30
Missing cells150
Missing cells (%)27.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory160.4 B

Variable types

DateTime2
Text2
Numeric3
Categorical5
Unsupported5
Boolean1

Dataset

Description샘플 데이터
Author 코나아이㈜
URLhttps://bigdata-region.kr/#/dataset/e725dc23-a6a7-45aa-8c35-f5e6c73e761a

Alerts

정책주간결제시작일자 has constant value ""Constant
정책주간결제종료일자 has constant value ""Constant
위도 has constant value ""Constant
경도 has constant value ""Constant
가맹점번호 is highly overall correlated with 사용여부 and 1 other fieldsHigh correlation
결제금액 is highly overall correlated with 가맹점번호 and 1 other fieldsHigh correlation
사용여부 is highly overall correlated with 가맹점번호 and 1 other fieldsHigh correlation
연령대코드 is highly overall correlated with 성별코드High correlation
성별코드 is highly overall correlated with 연령대코드High correlation
가맹점번호 is highly imbalanced (73.5%)Imbalance
사용여부 is highly imbalanced (64.7%)Imbalance
결제금액 is highly imbalanced (73.5%)Imbalance
가맹점업종명 has 30 (100.0%) missing valuesMissing
가맹점우편번호 has 30 (100.0%) missing valuesMissing
시도명 has 30 (100.0%) missing valuesMissing
시군구명 has 30 (100.0%) missing valuesMissing
읍면동명 has 30 (100.0%) missing valuesMissing
카드번호 has unique valuesUnique
회원코드 has unique valuesUnique
가맹점업종명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
가맹점우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시도명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
시군구명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
읍면동명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
연령대코드 has 11 (36.7%) zerosZeros

Reproduction

Analysis started2024-03-13 11:51:30.662315
Analysis finished2024-03-13 11:51:32.632144
Duration1.97 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

정책주간결제시작일자
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-10-02 00:00:00
Maximum2023-10-02 00:00:00
2024-03-13T20:51:32.688244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:32.787992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

정책주간결제종료일자
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-10-08 00:00:00
Maximum2023-10-08 00:00:00
2024-03-13T20:51:32.894520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:33.002170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

카드번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T20:51:33.231094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length44
Mean length44
Min length44

Characters and Unicode

Total characters1320
Distinct characters65
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowAov1Oybumzcq1MIopi+qlJXqQZ3/uolq+mG3zPq/iTI=
2nd rowDomesDLhmHDb9USBP+x+GKxAdKtKyBCwwor5/S6uxWM=
3rd rowAp27V5qv0Ig0iBm9YkUgVDs+DDWkDWE1t3J6pGn4aSI=
4th rowo3UyFaC2BmCCVvKYQSVuf6/M3upuWov7Lwyw9GOCUmw=
5th rowAp3T3JO1z2iqOlW1vLXwdKvErgoSwaglXaNaIw/OmZk=
ValueCountFrequency (%)
aov1oybumzcq1miopi+qljxqqz3/uolq+mg3zpq/iti 1
 
3.3%
domesdlhmhdb9usbp+x+gkxadktkybcwwor5/s6uxwm 1
 
3.3%
apbktmff7v6+4mstl4ft3db5lhsrckv1sct4leofiou 1
 
3.3%
o3veieb1eivn5neaqv7jxhiux0kcxwbkdzlgamptsua 1
 
3.3%
apzujraattz5lieci2vjgfw+c/pwvjrskpjn25kquhg 1
 
3.3%
tuntoxnmv3gdoaa3yt+f9seqoffy8ehtlnjsxyonzzu 1
 
3.3%
apx+tksqldk5cin1fcgmvtazo1imtxckumhovv6jbeo 1
 
3.3%
o3o3eumbykzsuqlefp3vnxkjnjoobla3zucydetu+xg 1
 
3.3%
apqtled8qwb88x5snzpsgd0smuwilzgthlnlca40laa 1
 
3.3%
tue1758wkcekm+bnmgs3vxzlscwvpp+mtxqt3zdo1us 1
 
3.3%
Other values (20) 20
66.7%
2024-03-13T20:51:33.641177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 41
 
3.1%
u 34
 
2.6%
p 33
 
2.5%
= 30
 
2.3%
T 29
 
2.2%
5 29
 
2.2%
3 28
 
2.1%
o 28
 
2.1%
c 28
 
2.1%
V 27
 
2.0%
Other values (55) 1013
76.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 527
39.9%
Uppercase Letter 512
38.8%
Decimal Number 209
 
15.8%
Math Symbol 52
 
3.9%
Other Punctuation 20
 
1.5%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 41
 
8.0%
T 29
 
5.7%
V 27
 
5.3%
U 25
 
4.9%
O 24
 
4.7%
N 23
 
4.5%
K 23
 
4.5%
S 23
 
4.5%
Y 21
 
4.1%
L 21
 
4.1%
Other values (16) 255
49.8%
Lowercase Letter
ValueCountFrequency (%)
u 34
 
6.5%
p 33
 
6.3%
o 28
 
5.3%
c 28
 
5.3%
g 24
 
4.6%
m 24
 
4.6%
j 23
 
4.4%
k 22
 
4.2%
w 22
 
4.2%
b 22
 
4.2%
Other values (16) 267
50.7%
Decimal Number
ValueCountFrequency (%)
5 29
13.9%
3 28
13.4%
1 24
11.5%
8 21
10.0%
6 20
9.6%
2 20
9.6%
9 19
9.1%
7 17
8.1%
0 16
7.7%
4 15
7.2%
Math Symbol
ValueCountFrequency (%)
= 30
57.7%
+ 22
42.3%
Other Punctuation
ValueCountFrequency (%)
/ 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1039
78.7%
Common 281
 
21.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 41
 
3.9%
u 34
 
3.3%
p 33
 
3.2%
T 29
 
2.8%
o 28
 
2.7%
c 28
 
2.7%
V 27
 
2.6%
U 25
 
2.4%
O 24
 
2.3%
g 24
 
2.3%
Other values (42) 746
71.8%
Common
ValueCountFrequency (%)
= 30
10.7%
5 29
10.3%
3 28
10.0%
1 24
8.5%
+ 22
7.8%
8 21
7.5%
6 20
7.1%
/ 20
7.1%
2 20
7.1%
9 19
 
6.8%
Other values (3) 48
17.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 41
 
3.1%
u 34
 
2.6%
p 33
 
2.5%
= 30
 
2.3%
T 29
 
2.2%
5 29
 
2.2%
3 28
 
2.1%
o 28
 
2.1%
c 28
 
2.1%
V 27
 
2.0%
Other values (55) 1013
76.7%

회원코드
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0193657 × 109
Minimum3.001935 × 109
Maximum3.0448572 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:51:33.834861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.001935 × 109
5-th percentile3.0030567 × 109
Q13.0166664 × 109
median3.018798 × 109
Q33.0203066 × 109
95-th percentile3.0390572 × 109
Maximum3.0448572 × 109
Range42922284
Interquartile range (IQR)3640193.2

Descriptive statistics

Standard deviation9249267.6
Coefficient of variation (CV)0.0030633148
Kurtosis2.3063775
Mean3.0193657 × 109
Median Absolute Deviation (MAD)2052462
Skewness0.84614712
Sum9.058097 × 1010
Variance8.5548951 × 1013
MonotonicityNot monotonic
2024-03-13T20:51:34.062805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
3036736241 1
 
3.3%
3018497675 1
 
3.3%
3019487889 1
 
3.3%
3016654914 1
 
3.3%
3019501316 1
 
3.3%
3019053820 1
 
3.3%
3018331287 1
 
3.3%
3018967206 1
 
3.3%
3018628860 1
 
3.3%
3040956165 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
3001934965 1
3.3%
3002114571 1
3.3%
3004208172 1
3.3%
3013091172 1
3.3%
3013206140 1
3.3%
3015978112 1
3.3%
3016474182 1
3.3%
3016654914 1
3.3%
3016700957 1
3.3%
3016790185 1
3.3%
ValueCountFrequency (%)
3044857249 1
3.3%
3040956165 1
3.3%
3036736241 1
3.3%
3027897196 1
3.3%
3024634134 1
3.3%
3020992332 1
3.3%
3020546305 1
3.3%
3020515585 1
3.3%
3019679717 1
3.3%
3019501316 1
3.3%

가맹점번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
999999999999999
28 
410515500026301
 
1
410534350086301
 
1

Length

Max length15
Median length15
Mean length15
Min length15

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row999999999999999
2nd row999999999999999
3rd row999999999999999
4th row999999999999999
5th row999999999999999

Common Values

ValueCountFrequency (%)
999999999999999 28
93.3%
410515500026301 1
 
3.3%
410534350086301 1
 
3.3%

Length

2024-03-13T20:51:34.270579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:51:34.382458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
999999999999999 28
93.3%
410515500026301 1
 
3.3%
410534350086301 1
 
3.3%

성별코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
F
21 
M
9 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowF
2nd rowF
3rd rowM
4th rowF
5th rowF

Common Values

ValueCountFrequency (%)
F 21
70.0%
M 9
30.0%

Length

2024-03-13T20:51:34.507462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:51:34.631170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 21
70.0%
m 9
30.0%

연령대코드
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.666667
Minimum0
Maximum60
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:51:34.732614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median20
Q340
95-th percentile50
Maximum60
Range60
Interquartile range (IQR)40

Descriptive statistics

Standard deviation19.49064
Coefficient of variation (CV)0.89956801
Kurtosis-1.3676176
Mean21.666667
Median Absolute Deviation (MAD)20
Skewness0.16854582
Sum650
Variance379.88506
MonotonicityNot monotonic
2024-03-13T20:51:34.868825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 11
36.7%
40 7
23.3%
20 4
 
13.3%
30 4
 
13.3%
50 2
 
6.7%
60 1
 
3.3%
10 1
 
3.3%
ValueCountFrequency (%)
0 11
36.7%
10 1
 
3.3%
20 4
 
13.3%
30 4
 
13.3%
40 7
23.3%
50 2
 
6.7%
60 1
 
3.3%
ValueCountFrequency (%)
60 1
 
3.3%
50 2
 
6.7%
40 7
23.3%
30 4
 
13.3%
20 4
 
13.3%
10 1
 
3.3%
0 11
36.7%

결제상품ID
Real number (ℝ)

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4000011 × 1011
Minimum1.4000002 × 1011
Maximum1.4000111 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:51:35.019253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.4000002 × 1011
5-th percentile1.4000002 × 1011
Q11.4000004 × 1011
median1.4000009 × 1011
Q31.4000012 × 1011
95-th percentile1.4000013 × 1011
Maximum1.4000111 × 1011
Range1091000
Interquartile range (IQR)80000

Descriptive statistics

Standard deviation192287.71
Coefficient of variation (CV)1.3734825 × 10-6
Kurtosis27.006196
Mean1.4000011 × 1011
Median Absolute Deviation (MAD)38000
Skewness5.0743887
Sum4.2000034 × 1012
Variance3.6974562 × 1010
MonotonicityNot monotonic
2024-03-13T20:51:35.157542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
140000124000 5
16.7%
140000120000 2
 
6.7%
140000030000 2
 
6.7%
140000126000 2
 
6.7%
140000044000 2
 
6.7%
140000076000 1
 
3.3%
140000140000 1
 
3.3%
140000042000 1
 
3.3%
140000046000 1
 
3.3%
140000018000 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
140000018000 1
3.3%
140000020000 1
3.3%
140000024000 1
3.3%
140000028000 1
3.3%
140000030000 2
6.7%
140000042000 1
3.3%
140000044000 2
6.7%
140000046000 1
3.3%
140000048000 1
3.3%
140000056000 1
3.3%
ValueCountFrequency (%)
140001109000 1
 
3.3%
140000140000 1
 
3.3%
140000126000 2
 
6.7%
140000124000 5
16.7%
140000122000 1
 
3.3%
140000120000 2
 
6.7%
140000114000 1
 
3.3%
140000102000 1
 
3.3%
140000088000 1
 
3.3%
140000084000 1
 
3.3%

결제상품명
Text

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T20:51:35.370438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length8.5333333
Min length4

Characters and Unicode

Total characters256
Distinct characters65
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)56.7%

Sample

1st row안양사랑상품권(통합)
2nd row수원페이
3rd row파주 Pay(파주페이)
4th row경기지역화폐(김포시)
5th row부천페이
ValueCountFrequency (%)
안산사랑상품권 5
 
12.2%
다온 5
 
12.2%
파주 2
 
4.9%
pay(파주페이 2
 
4.9%
부천페이 2
 
4.9%
수원페이 2
 
4.9%
오산화폐 2
 
4.9%
오색전 2
 
4.9%
광주사랑카드(통합 1
 
2.4%
행복화성지역화폐_화이트 1
 
2.4%
Other values (17) 17
41.5%
2024-03-13T20:51:35.790815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 15
 
5.9%
랑 15
 
5.9%
이 14
 
5.5%
11
 
4.3%
페 10
 
3.9%
( 9
 
3.5%
화 9
 
3.5%
) 9
 
3.5%
상 8
 
3.1%
품 8
 
3.1%
Other values (55) 148
57.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 207
80.9%
Lowercase Letter 12
 
4.7%
Space Separator 11
 
4.3%
Open Punctuation 9
 
3.5%
Close Punctuation 9
 
3.5%
Uppercase Letter 6
 
2.3%
Connector Punctuation 1
 
0.4%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 15
 
7.2%
랑 15
 
7.2%
이 14
 
6.8%
페 10
 
4.8%
화 9
 
4.3%
상 8
 
3.9%
품 8
 
3.9%
권 8
 
3.9%
폐 7
 
3.4%
산 7
 
3.4%
Other values (39) 106
51.2%
Lowercase Letter
ValueCountFrequency (%)
a 4
33.3%
y 3
25.0%
u 1
 
8.3%
o 1
 
8.3%
k 1
 
8.3%
n 1
 
8.3%
h 1
 
8.3%
Uppercase Letter
ValueCountFrequency (%)
P 3
50.0%
Y 1
 
16.7%
N 1
 
16.7%
T 1
 
16.7%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 207
80.9%
Common 31
 
12.1%
Latin 18
 
7.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 15
 
7.2%
랑 15
 
7.2%
이 14
 
6.8%
페 10
 
4.8%
화 9
 
4.3%
상 8
 
3.9%
품 8
 
3.9%
권 8
 
3.9%
폐 7
 
3.4%
산 7
 
3.4%
Other values (39) 106
51.2%
Latin
ValueCountFrequency (%)
a 4
22.2%
y 3
16.7%
P 3
16.7%
Y 1
 
5.6%
N 1
 
5.6%
u 1
 
5.6%
o 1
 
5.6%
k 1
 
5.6%
n 1
 
5.6%
h 1
 
5.6%
Common
ValueCountFrequency (%)
11
35.5%
( 9
29.0%
) 9
29.0%
_ 1
 
3.2%
- 1
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 207
80.9%
ASCII 49
 
19.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 15
 
7.2%
랑 15
 
7.2%
이 14
 
6.8%
페 10
 
4.8%
화 9
 
4.3%
상 8
 
3.9%
품 8
 
3.9%
권 8
 
3.9%
폐 7
 
3.4%
산 7
 
3.4%
Other values (39) 106
51.2%
ASCII
ValueCountFrequency (%)
11
22.4%
( 9
18.4%
) 9
18.4%
a 4
 
8.2%
y 3
 
6.1%
P 3
 
6.1%
_ 1
 
2.0%
Y 1
 
2.0%
N 1
 
2.0%
- 1
 
2.0%
Other values (6) 6
12.2%

가맹점업종명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

가맹점우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

시도명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

시군구명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

읍면동명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

위도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2024-03-13T20:51:35.980412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:51:36.083003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

경도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 30
100.0%

Length

2024-03-13T20:51:36.221439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:51:36.406539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

사용여부
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size162.0 B
False
28 
True
 
2
ValueCountFrequency (%)
False 28
93.3%
True 2
 
6.7%
2024-03-13T20:51:36.525066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

결제금액
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
28 
1800
 
1
45000
 
1

Length

Max length5
Median length1
Mean length1.2333333
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

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

Common Values

ValueCountFrequency (%)
0 28
93.3%
1800 1
 
3.3%
45000 1
 
3.3%

Length

2024-03-13T20:51:36.658456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:51:36.781054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 28
93.3%
1800 1
 
3.3%
45000 1
 
3.3%

Interactions

2024-03-13T20:51:31.867936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:31.167368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:31.470013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:31.983438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:31.273555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:31.572928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:32.099107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:31.374590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:51:31.674170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:51:36.853740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
카드번호회원코드가맹점번호성별코드연령대코드결제상품ID결제상품명사용여부결제금액
카드번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
회원코드1.0001.0000.0000.2420.6380.2400.9420.0000.000
가맹점번호1.0000.0001.0000.1010.4600.0001.0001.0001.000
성별코드1.0000.2420.1011.0000.7460.0970.4000.0000.101
연령대코드1.0000.6380.4600.7461.0000.0000.0000.2820.460
결제상품ID1.0000.2400.0000.0970.0001.0001.0000.0000.000
결제상품명1.0000.9421.0000.4000.0001.0001.0001.0001.000
사용여부1.0000.0001.0000.0000.2820.0001.0001.0001.000
결제금액1.0000.0001.0000.1010.4600.0001.0001.0001.000
2024-03-13T20:51:37.316522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가맹점번호성별코드결제금액사용여부
가맹점번호1.0000.1581.0000.982
성별코드0.1581.0000.1580.000
결제금액1.0000.1581.0000.982
사용여부0.9820.0000.9821.000
2024-03-13T20:51:37.429480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
회원코드연령대코드결제상품ID가맹점번호성별코드사용여부결제금액
회원코드1.000-0.142-0.0410.0000.2440.0000.000
연령대코드-0.1421.000-0.0500.3110.7310.2620.311
결제상품ID-0.041-0.0501.0000.0000.1580.0000.000
가맹점번호0.0000.3110.0001.0000.1580.9821.000
성별코드0.2440.7310.1580.1581.0000.0000.158
사용여부0.0000.2620.0000.9820.0001.0000.982
결제금액0.0000.3110.0001.0000.1580.9821.000

Missing values

2024-03-13T20:51:32.273809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:51:32.530576image/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

정책주간결제시작일자정책주간결제종료일자카드번호회원코드가맹점번호성별코드연령대코드결제상품ID결제상품명가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도사용여부결제금액
02023-10-022023-10-08Aov1Oybumzcq1MIopi+qlJXqQZ3/uolq+mG3zPq/iTI=3036736241999999999999999F40140000076000안양사랑상품권(통합)<NA><NA><NA><NA><NA>00N0
12023-10-022023-10-08DomesDLhmHDb9USBP+x+GKxAdKtKyBCwwor5/S6uxWM=3019679717999999999999999F0140000126000수원페이<NA><NA><NA><NA><NA>00N0
22023-10-022023-10-08Ap27V5qv0Ig0iBm9YkUgVDs+DDWkDWE1t3J6pGn4aSI=3004208172999999999999999M50140000120000파주 Pay(파주페이)<NA><NA><NA><NA><NA>00N0
32023-10-022023-10-08o3UyFaC2BmCCVvKYQSVuf6/M3upuWov7Lwyw9GOCUmw=3044857249999999999999999F0140001109000경기지역화폐(김포시)<NA><NA><NA><NA><NA>00N0
42023-10-022023-10-08Ap3T3JO1z2iqOlW1vLXwdKvErgoSwaglXaNaIw/OmZk=3020546305999999999999999F20140000030000부천페이<NA><NA><NA><NA><NA>00N0
52023-10-022023-10-08TuQ/cd5V9nuJFVWjuR064IUycb2MTkXA/2cFbEx2be4=3013206140999999999999999F30140000102000수원페이(통합)<NA><NA><NA><NA><NA>00N0
62023-10-022023-10-08Ap4+FcwrZebPWxBPwKNoYU6oxyDB3KnmSuMCnO0rkP0=3020992332999999999999999M60140000124000안산사랑상품권 다온<NA><NA><NA><NA><NA>00N0
72023-10-022023-10-08DomopfFgpHO1u7Kjcm2boNjsBynCvXtvevfkgyc7xNI=3019416414999999999999999F0140000124000안산사랑상품권 다온<NA><NA><NA><NA><NA>00N0
82023-10-022023-10-08Ap4Xcpq7M5dM+1URg1TjDRJ40o10NF1bPZ5X8/pwfEA=3016790185410515500026301F40140000048000이천사랑지역화폐<NA><NA><NA><NA><NA>00Y1800
92023-10-022023-10-08TuQBA/UNknf6sxj8uOYh9ZETs7PQ57Im6BemZdBfZ+Y=3027897196999999999999999M20140000088000광명사랑화폐(통합)<NA><NA><NA><NA><NA>00N0
정책주간결제시작일자정책주간결제종료일자카드번호회원코드가맹점번호성별코드연령대코드결제상품ID결제상품명가맹점업종명가맹점우편번호시도명시군구명읍면동명위도경도사용여부결제금액
202023-10-022023-10-08ApPKyPqL7W0T2OaJU6XUhbhJ6DLxRX0yD5TDKlUjogc=3015978112999999999999999F40140000126000수원페이<NA><NA><NA><NA><NA>00N0
212023-10-022023-10-08Tue1758wkCEKM+bNmgS3VxzLsCwvPp+MtxQt3zdO1us=3018300728999999999999999F0140000122000의정부사랑카드<NA><NA><NA><NA><NA>00N0
222023-10-022023-10-08ApQtlEd8Qwb88x5snzpsgd0SmUwilzgtHLNLca40LaA=3040956165999999999999999F40140000084000광주사랑카드(통합)<NA><NA><NA><NA><NA>00N0
232023-10-022023-10-08o3o3EUmbykZSuqLeFp3VnXKjNJOObLA3ZUcYdEtu+Xg=3018628860999999999999999F40140000028000구리사랑카드<NA><NA><NA><NA><NA>00N0
242023-10-022023-10-08ApX+TkSQlDk5cIN1fcGMVTAzO1ImtxckumHOVV6JBEo=3018967206999999999999999F40140000018000고양페이카드<NA><NA><NA><NA><NA>00N0
252023-10-022023-10-08TuntOXNmV3GdOaa3Yt+f9SEqOffY8ehTlnjsXYoNZZU=3018331287999999999999999F0140000030000부천페이<NA><NA><NA><NA><NA>00N0
262023-10-022023-10-08ApZujRAatTZ5lIEci2VjGFw+c/PWVJRSkpJN25kQuhg=3019053820999999999999999F0140000044000오산화폐 오색전<NA><NA><NA><NA><NA>00N0
272023-10-022023-10-08o3vEieB1EIVN5neAqV7jxhIUX0kcxWbKDZLgAMptSuA=3019501316999999999999999F0140000046000용인와이페이<NA><NA><NA><NA><NA>00N0
282023-10-022023-10-08ApbKTMfF7v6+4msTl4fT3db5lhsrCKv1sCT4LEOfioU=3016654914999999999999999F40140000124000안산사랑상품권 다온<NA><NA><NA><NA><NA>00N0
292023-10-022023-10-08TusHorNG8Y9GXphdAe65QS725S9m5d7cvKZY68pRG8s=3019487889999999999999999M30140000042000연천사랑상품권<NA><NA><NA><NA><NA>00N0