Overview

Dataset statistics

Number of variables22
Number of observations30
Missing cells30
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.6 KiB
Average record size in memory190.4 B

Variable types

DateTime3
Categorical10
Text5
Numeric3
Unsupported1

Dataset

Description샘플 데이터
Author경기신용보증재단
URLhttps://bigdata-region.kr/#/dataset/0646afa6-06e1-4477-b5d3-ad339f70f4f8

Alerts

기준년월 has constant value ""Constant
시도명 has constant value ""Constant
업체형태명 has constant value ""Constant
지역화폐사용년월 has constant value ""Constant
정책카드결제금액 has constant value ""Constant
정책카드결제수 has constant value ""Constant
대위변제금액 is highly imbalanced (78.9%)Imbalance
부실발생일자 is highly imbalanced (78.9%)Imbalance
폐업일자 has 30 (100.0%) missing valuesMissing
보증일자 has unique valuesUnique
가맹점번호 has unique valuesUnique
기업번호 has unique valuesUnique
폐업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 14:03:41.016288
Analysis finished2023-12-10 14:03:41.959925
Duration0.94 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-10-01 00:00:00
Maximum2021-10-01 00:00:00
2023-12-10T23:03:42.049109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:42.178954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

성별코드
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
F
16 
M
14 

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 16
53.3%
M 14
46.7%

Length

2023-12-10T23:03:42.378212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:42.566672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 16
53.3%
m 14
46.7%

연령대코드
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
50
11 
40
9 
30
8 
60
2 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row30
2nd row30
3rd row30
4th row50
5th row50

Common Values

ValueCountFrequency (%)
50 11
36.7%
40 9
30.0%
30 8
26.7%
60 2
 
6.7%

Length

2023-12-10T23:03:42.774035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:42.947447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50 11
36.7%
40 9
30.0%
30 8
26.7%
60 2
 
6.7%

시도명
Categorical

CONSTANT 

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

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경기도 30
100.0%

Length

2023-12-10T23:03:43.138554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:43.312092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 30
100.0%

시군구명
Text

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:03:43.613762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4
Mean length4.5333333
Min length3

Characters and Unicode

Total characters136
Distinct characters38
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)33.3%

Sample

1st row수원시 팔달구
2nd row평택시
3rd row파주시
4th row의정부시
5th row의정부시
ValueCountFrequency (%)
의정부시 5
12.8%
수원시 5
12.8%
남양주시 4
 
10.3%
화성시 4
 
10.3%
영통구 3
 
7.7%
팔달구 2
 
5.1%
용인시 2
 
5.1%
기흥구 2
 
5.1%
가평군 1
 
2.6%
광주시 1
 
2.6%
Other values (10) 10
25.6%
2023-12-10T23:03:44.145214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 29
21.3%
구 9
 
6.6%
9
 
6.6%
부 6
 
4.4%
양 6
 
4.4%
주 6
 
4.4%
의 5
 
3.7%
정 5
 
3.7%
원 5
 
3.7%
수 5
 
3.7%
Other values (28) 51
37.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 127
93.4%
Space Separator 9
 
6.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 29
22.8%
구 9
 
7.1%
부 6
 
4.7%
양 6
 
4.7%
주 6
 
4.7%
의 5
 
3.9%
정 5
 
3.9%
원 5
 
3.9%
수 5
 
3.9%
남 4
 
3.1%
Other values (27) 47
37.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 127
93.4%
Common 9
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 29
22.8%
구 9
 
7.1%
부 6
 
4.7%
양 6
 
4.7%
주 6
 
4.7%
의 5
 
3.9%
정 5
 
3.9%
원 5
 
3.9%
수 5
 
3.9%
남 4
 
3.1%
Other values (27) 47
37.0%
Common
ValueCountFrequency (%)
9
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 127
93.4%
ASCII 9
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 29
22.8%
구 9
 
7.1%
부 6
 
4.7%
양 6
 
4.7%
주 6
 
4.7%
의 5
 
3.9%
정 5
 
3.9%
원 5
 
3.9%
수 5
 
3.9%
남 4
 
3.1%
Other values (27) 47
37.0%
ASCII
ValueCountFrequency (%)
9
100.0%

행정동명
Text

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:03:44.475873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0333333
Min length2

Characters and Unicode

Total characters91
Distinct characters44
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)66.7%

Sample

1st row인계동
2nd row안중읍
3rd row와동동
4th row의정부동
5th row가능동
ValueCountFrequency (%)
인계동 2
 
6.7%
향남읍 2
 
6.7%
송내동 2
 
6.7%
호평동 2
 
6.7%
의정부동 2
 
6.7%
안중읍 1
 
3.3%
원천동 1
 
3.3%
민락동 1
 
3.3%
안녕동 1
 
3.3%
화도읍 1
 
3.3%
Other values (15) 15
50.0%
2023-12-10T23:03:45.072976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 25
27.5%
읍 6
 
6.6%
의 3
 
3.3%
정 3
 
3.3%
안 3
 
3.3%
송 3
 
3.3%
평 3
 
3.3%
인 2
 
2.2%
호 2
 
2.2%
계 2
 
2.2%
Other values (34) 39
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 25
27.5%
읍 6
 
6.6%
의 3
 
3.3%
정 3
 
3.3%
안 3
 
3.3%
송 3
 
3.3%
평 3
 
3.3%
인 2
 
2.2%
호 2
 
2.2%
계 2
 
2.2%
Other values (34) 39
42.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 25
27.5%
읍 6
 
6.6%
의 3
 
3.3%
정 3
 
3.3%
안 3
 
3.3%
송 3
 
3.3%
평 3
 
3.3%
인 2
 
2.2%
호 2
 
2.2%
계 2
 
2.2%
Other values (34) 39
42.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 25
27.5%
읍 6
 
6.6%
의 3
 
3.3%
정 3
 
3.3%
안 3
 
3.3%
송 3
 
3.3%
평 3
 
3.3%
인 2
 
2.2%
호 2
 
2.2%
계 2
 
2.2%
Other values (34) 39
42.9%

업체형태명
Categorical

CONSTANT 

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

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개인기업 30
100.0%

Length

2023-12-10T23:03:45.346458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:45.518962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인기업 30
100.0%

기업설립년월
Date

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2010-05-01 00:00:00
Maximum2016-07-01 00:00:00
2023-12-10T23:03:45.665706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:45.863758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)

업종코드
Text

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:03:46.122953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters180
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
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 rowS96119
2nd rowI56111
3rd rowI56111
4th rowI56221
5th rowI56111
ValueCountFrequency (%)
i56111 10
33.3%
i56221 3
 
10.0%
i56194 1
 
3.3%
s96119 1
 
3.3%
i56121 1
 
3.3%
p85502 1
 
3.3%
s96995 1
 
3.3%
r91222 1
 
3.3%
i56199 1
 
3.3%
g46201 1
 
3.3%
Other values (9) 9
30.0%
2023-12-10T23:03:46.677283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 52
28.9%
5 24
13.3%
6 23
12.8%
I 19
 
10.6%
2 19
 
10.6%
9 12
 
6.7%
4 6
 
3.3%
G 5
 
2.8%
7 5
 
2.8%
0 4
 
2.2%
Other values (6) 11
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
83.3%
Uppercase Letter 30
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 52
34.7%
5 24
16.0%
6 23
15.3%
2 19
 
12.7%
9 12
 
8.0%
4 6
 
4.0%
7 5
 
3.3%
0 4
 
2.7%
8 3
 
2.0%
3 2
 
1.3%
Uppercase Letter
ValueCountFrequency (%)
I 19
63.3%
G 5
 
16.7%
P 2
 
6.7%
S 2
 
6.7%
Q 1
 
3.3%
R 1
 
3.3%

Most occurring scripts

ValueCountFrequency (%)
Common 150
83.3%
Latin 30
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 52
34.7%
5 24
16.0%
6 23
15.3%
2 19
 
12.7%
9 12
 
8.0%
4 6
 
4.0%
7 5
 
3.3%
0 4
 
2.7%
8 3
 
2.0%
3 2
 
1.3%
Latin
ValueCountFrequency (%)
I 19
63.3%
G 5
 
16.7%
P 2
 
6.7%
S 2
 
6.7%
Q 1
 
3.3%
R 1
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 52
28.9%
5 24
13.3%
6 23
12.8%
I 19
 
10.6%
2 19
 
10.6%
9 12
 
6.7%
4 6
 
3.3%
G 5
 
2.8%
7 5
 
2.8%
0 4
 
2.2%
Other values (6) 11
 
6.1%

업종대분류명
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
I 숙박 및 음식점업 (55 ~ 56)
19 
G 도매 및 소매업 (45~47)
5 
S협회 및 단체 수리및기타개인서비스업(94~96)
2 
P 교육 서비스업(85)
2 
Q 보건업 및 사회복지 서비스업(86~87)
 
1

Length

Max length28
Median length21
Mean length20.7
Min length13

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st rowS협회 및 단체 수리및기타개인서비스업(94~96)
2nd rowI 숙박 및 음식점업 (55 ~ 56)
3rd rowI 숙박 및 음식점업 (55 ~ 56)
4th rowI 숙박 및 음식점업 (55 ~ 56)
5th rowI 숙박 및 음식점업 (55 ~ 56)

Common Values

ValueCountFrequency (%)
I 숙박 및 음식점업 (55 ~ 56) 19
63.3%
G 도매 및 소매업 (45~47) 5
 
16.7%
S협회 및 단체 수리및기타개인서비스업(94~96) 2
 
6.7%
P 교육 서비스업(85) 2
 
6.7%
Q 보건업 및 사회복지 서비스업(86~87) 1
 
3.3%
R 예술 스포츠 및 여가관련 서비스업(90~91) 1
 
3.3%

Length

2023-12-10T23:03:46.968381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:47.160347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
및 28
15.3%
i 19
10.4%
음식점업 19
10.4%
55 19
10.4%
19
10.4%
56 19
10.4%
숙박 19
10.4%
g 5
 
2.7%
도매 5
 
2.7%
소매업 5
 
2.7%
Other values (16) 26
14.2%

보증금액
Real number (ℝ)

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77489333
Minimum10000000
Maximum3.735 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:47.360444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000000
5-th percentile19500000
Q140000000
median58740000
Q396712500
95-th percentile1.4 × 108
Maximum3.735 × 108
Range3.635 × 108
Interquartile range (IQR)56712500

Descriptive statistics

Standard deviation67252923
Coefficient of variation (CV)0.8678991
Kurtosis12.833987
Mean77489333
Median Absolute Deviation (MAD)25375000
Skewness3.1019876
Sum2.32468 × 109
Variance4.5229556 × 1015
MonotonicityNot monotonic
2023-12-10T23:03:47.593917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
70000000 3
 
10.0%
40000000 3
 
10.0%
140000000 2
 
6.7%
25000000 1
 
3.3%
30000000 1
 
3.3%
132000000 1
 
3.3%
50000000 1
 
3.3%
51000000 1
 
3.3%
15000000 1
 
3.3%
55500000 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
10000000 1
 
3.3%
15000000 1
 
3.3%
25000000 1
 
3.3%
27000000 1
 
3.3%
30000000 1
 
3.3%
34250000 1
 
3.3%
39000000 1
 
3.3%
40000000 3
10.0%
50000000 1
 
3.3%
51000000 1
 
3.3%
ValueCountFrequency (%)
373500000 1
3.3%
140000000 2
6.7%
135000000 1
3.3%
132000000 1
3.3%
113000000 1
3.3%
100000000 1
3.3%
98950000 1
3.3%
90000000 1
3.3%
85000000 1
3.3%
80000000 1
3.3%

보증일자
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20188359
Minimum20100601
Maximum20211025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:47.918346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20100601
5-th percentile20160753
Q120170570
median20200405
Q320201025
95-th percentile20210916
Maximum20211025
Range110424
Interquartile range (IQR)30455.5

Descriptive statistics

Standard deviation24043.216
Coefficient of variation (CV)0.0011909445
Kurtosis4.7287047
Mean20188359
Median Absolute Deviation (MAD)10450
Skewness-1.782855
Sum6.0565078 × 108
Variance5.7807623 × 108
MonotonicityNot monotonic
2023-12-10T23:03:48.210840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
20160930 1
 
3.3%
20170522 1
 
3.3%
20200401 1
 
3.3%
20200409 1
 
3.3%
20170119 1
 
3.3%
20100601 1
 
3.3%
20170515 1
 
3.3%
20180927 1
 
3.3%
20200513 1
 
3.3%
20160609 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
20100601 1
3.3%
20160609 1
3.3%
20160930 1
3.3%
20161123 1
3.3%
20170119 1
3.3%
20170427 1
3.3%
20170515 1
3.3%
20170522 1
3.3%
20170712 1
3.3%
20180607 1
3.3%
ValueCountFrequency (%)
20211025 1
3.3%
20210924 1
3.3%
20210906 1
3.3%
20210804 1
3.3%
20210802 1
3.3%
20210623 1
3.3%
20210428 1
3.3%
20201026 1
3.3%
20201022 1
3.3%
20200710 1
3.3%

대위변제금액
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
29 
9578456
 
1

Length

Max length7
Median length4
Mean length4.1
Min length4

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row9578456

Common Values

ValueCountFrequency (%)
<NA> 29
96.7%
9578456 1
 
3.3%

Length

2023-12-10T23:03:48.431453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:48.604189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
96.7%
9578456 1
 
3.3%

부실발생일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
29 
20181016
 
1

Length

Max length8
Median length4
Mean length4.1333333
Min length4

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row20181016

Common Values

ValueCountFrequency (%)
<NA> 29
96.7%
20181016 1
 
3.3%

Length

2023-12-10T23:03:48.820415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:49.021644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 29
96.7%
20181016 1
 
3.3%

가맹점번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:03:49.351788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters270
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
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 row797201***
2nd row798478***
3rd row796957***
4th row797006***
5th row798985***
ValueCountFrequency (%)
797201 1
 
3.3%
798478 1
 
3.3%
795897 1
 
3.3%
799240 1
 
3.3%
797944 1
 
3.3%
798710 1
 
3.3%
796335 1
 
3.3%
795893 1
 
3.3%
798609 1
 
3.3%
799143 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:03:50.029668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
* 90
33.3%
7 48
17.8%
9 44
16.3%
8 23
 
8.5%
6 12
 
4.4%
0 11
 
4.1%
4 11
 
4.1%
1 10
 
3.7%
5 9
 
3.3%
2 6
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 180
66.7%
Other Punctuation 90
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 48
26.7%
9 44
24.4%
8 23
12.8%
6 12
 
6.7%
0 11
 
6.1%
4 11
 
6.1%
1 10
 
5.6%
5 9
 
5.0%
2 6
 
3.3%
3 6
 
3.3%
Other Punctuation
ValueCountFrequency (%)
* 90
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 270
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
* 90
33.3%
7 48
17.8%
9 44
16.3%
8 23
 
8.5%
6 12
 
4.4%
0 11
 
4.1%
4 11
 
4.1%
1 10
 
3.7%
5 9
 
3.3%
2 6
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 270
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
* 90
33.3%
7 48
17.8%
9 44
16.3%
8 23
 
8.5%
6 12
 
4.4%
0 11
 
4.1%
4 11
 
4.1%
1 10
 
3.7%
5 9
 
3.3%
2 6
 
2.2%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

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

지역화폐사용년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2020-12-31 00:00:00
Maximum2020-12-31 00:00:00
2023-12-10T23:03:50.259965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:03:50.481737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

정책카드결제금액
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

2023-12-10T23:03:50.659821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:50.819819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

정책카드결제수
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

2023-12-10T23:03:50.989423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:51.194925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

일반카드결제금액
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean104049.67
Minimum2000
Maximum383000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:03:51.465839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile4970
Q127900
median61900
Q3113250
95-th percentile333000
Maximum383000
Range381000
Interquartile range (IQR)85350

Descriptive statistics

Standard deviation114955.21
Coefficient of variation (CV)1.1048109
Kurtosis0.35577011
Mean104049.67
Median Absolute Deviation (MAD)38400
Skewness1.3059311
Sum3121490
Variance1.32147 × 1010
MonotonicityNot monotonic
2023-12-10T23:03:51.736146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
8000 2
 
6.7%
73000 1
 
3.3%
72000 1
 
3.3%
90000 1
 
3.3%
27000 1
 
3.3%
73100 1
 
3.3%
300000 1
 
3.3%
30600 1
 
3.3%
7500 1
 
3.3%
287000 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
2000 1
3.3%
2900 1
3.3%
7500 1
3.3%
8000 2
6.7%
16590 1
3.3%
20000 1
3.3%
27000 1
3.3%
30600 1
3.3%
31500 1
3.3%
38000 1
3.3%
ValueCountFrequency (%)
383000 1
3.3%
360000 1
3.3%
300000 1
3.3%
287000 1
3.3%
275500 1
3.3%
245000 1
3.3%
232500 1
3.3%
121000 1
3.3%
90000 1
3.3%
75000 1
3.3%

일반카드결제수
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
21 
2
8 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 21
70.0%
2 8
 
26.7%
3 1
 
3.3%

Length

2023-12-10T23:03:52.153396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:03:52.359099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 21
70.0%
2 8
 
26.7%
3 1
 
3.3%

기업번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:03:52.685529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length24
Mean length24
Min length24

Characters and Unicode

Total characters720
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 row0XCW/Rt7dJZomey/pgoI7g==
2nd row/Wkbha8Ab2MyQYgEN6DTVg==
3rd row1/w18jbiBawdq86NLd651Q==
4th row3mqJBVycXUHndu+ZZGI3aQ==
5th row1cZaypROHm51uQ+wpprDwg==
ValueCountFrequency (%)
0xcw/rt7djzomey/pgoi7g 1
 
3.3%
wkbha8ab2myqygen6dtvg 1
 
3.3%
bktd/rqg0spldgutooa7ha 1
 
3.3%
aec47vomcm0ejsankldfma 1
 
3.3%
9uve64o2iu12yzxjapzmja 1
 
3.3%
ahfiw2yilagemdlg7jgshg 1
 
3.3%
9ea72emnz6ghwybwvduuzg 1
 
3.3%
98yl4qb/mceopxt7bs2orq 1
 
3.3%
8o9uijhjecyiv9+/5ls0fa 1
 
3.3%
8i9ndohsmogqkiuqnkltua 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:03:53.367526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
= 60
 
8.3%
g 21
 
2.9%
Q 21
 
2.9%
A 20
 
2.8%
c 19
 
2.6%
d 17
 
2.4%
u 16
 
2.2%
Z 15
 
2.1%
a 14
 
1.9%
5 14
 
1.9%
Other values (55) 503
69.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 269
37.4%
Uppercase Letter 255
35.4%
Decimal Number 122
16.9%
Math Symbol 67
 
9.3%
Other Punctuation 7
 
1.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
g 21
 
7.8%
c 19
 
7.1%
d 17
 
6.3%
u 16
 
5.9%
a 14
 
5.2%
w 14
 
5.2%
e 14
 
5.2%
y 12
 
4.5%
p 11
 
4.1%
o 11
 
4.1%
Other values (16) 120
44.6%
Uppercase Letter
ValueCountFrequency (%)
Q 21
 
8.2%
A 20
 
7.8%
Z 15
 
5.9%
B 13
 
5.1%
M 12
 
4.7%
E 12
 
4.7%
O 11
 
4.3%
I 11
 
4.3%
C 11
 
4.3%
G 10
 
3.9%
Other values (16) 119
46.7%
Decimal Number
ValueCountFrequency (%)
5 14
11.5%
8 14
11.5%
6 13
10.7%
2 12
9.8%
0 12
9.8%
4 12
9.8%
7 12
9.8%
1 11
9.0%
3 11
9.0%
9 11
9.0%
Math Symbol
ValueCountFrequency (%)
= 60
89.6%
+ 7
 
10.4%
Other Punctuation
ValueCountFrequency (%)
/ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 524
72.8%
Common 196
 
27.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
g 21
 
4.0%
Q 21
 
4.0%
A 20
 
3.8%
c 19
 
3.6%
d 17
 
3.2%
u 16
 
3.1%
Z 15
 
2.9%
a 14
 
2.7%
w 14
 
2.7%
e 14
 
2.7%
Other values (42) 353
67.4%
Common
ValueCountFrequency (%)
= 60
30.6%
5 14
 
7.1%
8 14
 
7.1%
6 13
 
6.6%
2 12
 
6.1%
0 12
 
6.1%
4 12
 
6.1%
7 12
 
6.1%
1 11
 
5.6%
3 11
 
5.6%
Other values (3) 25
12.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 720
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
= 60
 
8.3%
g 21
 
2.9%
Q 21
 
2.9%
A 20
 
2.8%
c 19
 
2.6%
d 17
 
2.4%
u 16
 
2.2%
Z 15
 
2.1%
a 14
 
1.9%
5 14
 
1.9%
Other values (55) 503
69.9%

Sample

기준년월성별코드연령대코드시도명시군구명행정동명업체형태명기업설립년월업종코드업종대분류명보증금액보증일자대위변제금액부실발생일자가맹점번호폐업일자지역화폐사용년월정책카드결제금액정책카드결제수일반카드결제금액일반카드결제수기업번호
02021-10F30경기도수원시 팔달구인계동개인기업2016-01S96119S협회 및 단체 수리및기타개인서비스업(94~96)2500000020160930<NA><NA>797201***<NA>2020-12-31007300010XCW/Rt7dJZomey/pgoI7g==
12021-10F30경기도평택시안중읍개인기업2016-04I56111I 숙박 및 음식점업 (55 ~ 56)4000000020200421<NA><NA>798478***<NA>2020-12-3100380001/Wkbha8Ab2MyQYgEN6DTVg==
22021-10M30경기도파주시와동동개인기업2016-01I56111I 숙박 및 음식점업 (55 ~ 56)5300000020210623<NA><NA>796957***<NA>2020-12-31004400011/w18jbiBawdq86NLd651Q==
32021-10F50경기도의정부시의정부동개인기업2016-01I56221I 숙박 및 음식점업 (55 ~ 56)7000000020210428<NA><NA>797006***<NA>2020-12-3100800013mqJBVycXUHndu+ZZGI3aQ==
42021-10F50경기도의정부시가능동개인기업2016-05I56111I 숙박 및 음식점업 (55 ~ 56)1000000020180607957845620181016798985***<NA>2020-12-3100800011cZaypROHm51uQ+wpprDwg==
52021-10F40경기도의정부시장암동개인기업2014-05I56221I 숙박 및 음식점업 (55 ~ 56)7000000020211025<NA><NA>797101***<NA>2020-12-3100290014cDmFOteXPcc4ey71ga19w==
62021-10M60경기도포천시소흘읍개인기업2016-04G47121G 도매 및 소매업 (45~47)3425000020200512<NA><NA>798283***<NA>2020-12-31005880014oPyZTBmQjRExWlq39UZBA==
72021-10M40경기도용인시 기흥구동백동개인기업2016-05I56129I 숙박 및 음식점업 (55 ~ 56)3900000020191224<NA><NA>798758***<NA>2020-12-310054500154PrfnSC5Ytp9TWGQurgpw==
82021-10M50경기도화성시봉담읍개인기업2016-01I56111I 숙박 및 음식점업 (55 ~ 56)14000000020200604<NA><NA>796948***<NA>2020-12-310012100025ZdcRHYoMl8ui8wfQ1+R6w==
92021-10M40경기도안산시 상록구본오동개인기업2015-12G47212G 도매 및 소매업 (45~47)5748000020210802<NA><NA>796662***<NA>2020-12-31001659015wcOaWvGBd2EMb5FcKuEkw==
기준년월성별코드연령대코드시도명시군구명행정동명업체형태명기업설립년월업종코드업종대분류명보증금액보증일자대위변제금액부실발생일자가맹점번호폐업일자지역화폐사용년월정책카드결제금액정책카드결제수일반카드결제금액일반카드결제수기업번호
202021-10F30경기도화성시향남읍개인기업2016-04I56199I 숙박 및 음식점업 (55 ~ 56)4000000020161123<NA><NA>798474***<NA>2020-12-310038300028cg6CdCLxNg+MKgbRFP5BQ==
212021-10M30경기도광주시송정동개인기업2016-02R91222R 예술 스포츠 및 여가관련 서비스업(90~91)13500000020210924<NA><NA>799143***<NA>2020-12-3100200018i9ndOhSMOgQkiUQNKlTuA==
222021-10F40경기도남양주시화도읍개인기업2016-04S96995S협회 및 단체 수리및기타개인서비스업(94~96)2700000020160609<NA><NA>798609***<NA>2020-12-31006500018o9uIjhjECYIV9+/5LS0FA==
232021-10F50경기도화성시안녕동개인기업2015-09I56111I 숙박 및 음식점업 (55 ~ 56)11300000020200513<NA><NA>795893***<NA>2020-12-3100287000198yL4Qb/mceoPXT7Bs2OrQ==
242021-10F50경기도부천시송내동개인기업2015-11I56221I 숙박 및 음식점업 (55 ~ 56)5550000020180927<NA><NA>796335***<NA>2020-12-3100750019Ea72EMnz6GHWybwvduuzg==
252021-10F40경기도의정부시민락동개인기업2016-05I56111I 숙박 및 음식점업 (55 ~ 56)4000000020170515<NA><NA>798710***<NA>2020-12-3100306001AHfIW2yIlageMdlG7jGshg==
262021-10F30경기도화성시향남읍개인기업2010-05P85502P 교육 서비스업(85)1500000020100601<NA><NA>797944***<NA>2020-12-310030000019uve64O2Iu12yZXjaPZmJA==
272021-10M40경기도남양주시호평동개인기업2016-07I56191I 숙박 및 음식점업 (55 ~ 56)5100000020170119<NA><NA>799240***<NA>2020-12-3100731002Aec47VOMcM0eJsaNkldFMA==
282021-10F60경기도남양주시호평동개인기업2015-09I56111I 숙박 및 음식점업 (55 ~ 56)5000000020200409<NA><NA>795897***<NA>2020-12-3100270001BkTD/Rqg0SpldgutoOa7HA==
292021-10F50경기도용인시 기흥구중동개인기업2016-05I56111I 숙박 및 음식점업 (55 ~ 56)13200000020200401<NA><NA>798705***<NA>2020-12-3100900002BvKwkznW2UeZ5YNt3ca4rA==