Overview

Dataset statistics

Number of variables7
Number of observations115
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.5 KiB
Average record size in memory58.1 B

Variable types

Numeric1
Categorical2
Text3
DateTime1

Dataset

Description인천광역시 부평구 대부업 등록현황입니다. (순번,시군구명,등록신청사업,등록증번호,상호,소재지(도로명),등록일자) ex) 1,인천광역시 부평구,대부업,인천부평-2021-00015,에치에스대부(주),인천광역시 부평구 세월천로 216-14, 1층 (청천동),2021-06-10
URLhttps://www.data.go.kr/data/3080287/fileData.do

Alerts

시군구명 has constant value ""Constant
순번 has unique valuesUnique
등록증번호 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 16:55:47.891564
Analysis finished2023-12-12 16:55:48.472665
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58
Minimum1
Maximum115
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-13T01:55:48.548486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.7
Q129.5
median58
Q386.5
95-th percentile109.3
Maximum115
Range114
Interquartile range (IQR)57

Descriptive statistics

Standard deviation33.341666
Coefficient of variation (CV)0.5748563
Kurtosis-1.2
Mean58
Median Absolute Deviation (MAD)29
Skewness0
Sum6670
Variance1111.6667
MonotonicityStrictly increasing
2023-12-13T01:55:48.712123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
74 1
 
0.9%
86 1
 
0.9%
85 1
 
0.9%
84 1
 
0.9%
83 1
 
0.9%
82 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
Other values (105) 105
91.3%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
115 1
0.9%
114 1
0.9%
113 1
0.9%
112 1
0.9%
111 1
0.9%
110 1
0.9%
109 1
0.9%
108 1
0.9%
107 1
0.9%
106 1
0.9%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
인천광역시 부평구
115 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row인천광역시 부평구
2nd row인천광역시 부평구
3rd row인천광역시 부평구
4th row인천광역시 부평구
5th row인천광역시 부평구

Common Values

ValueCountFrequency (%)
인천광역시 부평구 115
100.0%

Length

2023-12-13T01:55:48.852763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:55:48.944322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 115
50.0%
부평구 115
50.0%

등록신청사업
Categorical

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
대부업
69 
대부중개업
46 

Length

Max length5
Median length3
Mean length3.8
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 69
60.0%
대부중개업 46
40.0%

Length

2023-12-13T01:55:49.076019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:55:49.227041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 69
60.0%
대부중개업 46
40.0%

등록증번호
Text

UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T01:55:49.404308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length15
Mean length15
Min length15

Characters and Unicode

Total characters1725
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)100.0%

Sample

1st row인천부평-2023-00018
2nd row인천부평-2023-00017
3rd row인천부평-2023-00016
4th row인천부평-2023-00015
5th row인천부평-2023-00013
ValueCountFrequency (%)
인천부평-2023-00018 1
 
0.9%
인천부평-2021-00035 1
 
0.9%
인천부평-2020-00008 1
 
0.9%
인천부평-2020-00013 1
 
0.9%
인천부평-2022-00011 1
 
0.9%
인천부평-2020-00027 1
 
0.9%
인천부평-2020-00028 1
 
0.9%
인천부평-2021-00002 1
 
0.9%
인천부평-2021-00003 1
 
0.9%
인천부평-2021-00004 1
 
0.9%
Other values (105) 105
91.3%
2023-12-13T01:55:50.065856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 506
29.3%
2 278
16.1%
- 230
13.3%
인 115
 
6.7%
천 115
 
6.7%
부 115
 
6.7%
평 115
 
6.7%
1 91
 
5.3%
3 50
 
2.9%
7 24
 
1.4%
Other values (5) 86
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1035
60.0%
Other Letter 460
26.7%
Dash Punctuation 230
 
13.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 506
48.9%
2 278
26.9%
1 91
 
8.8%
3 50
 
4.8%
7 24
 
2.3%
4 21
 
2.0%
8 19
 
1.8%
6 17
 
1.6%
9 15
 
1.4%
5 14
 
1.4%
Other Letter
ValueCountFrequency (%)
인 115
25.0%
천 115
25.0%
부 115
25.0%
평 115
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 230
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1265
73.3%
Hangul 460
 
26.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 506
40.0%
2 278
22.0%
- 230
18.2%
1 91
 
7.2%
3 50
 
4.0%
7 24
 
1.9%
4 21
 
1.7%
8 19
 
1.5%
6 17
 
1.3%
9 15
 
1.2%
Hangul
ValueCountFrequency (%)
인 115
25.0%
천 115
25.0%
부 115
25.0%
평 115
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1265
73.3%
Hangul 460
 
26.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 506
40.0%
2 278
22.0%
- 230
18.2%
1 91
 
7.2%
3 50
 
4.0%
7 24
 
1.9%
4 21
 
1.7%
8 19
 
1.5%
6 17
 
1.3%
9 15
 
1.2%
Hangul
ValueCountFrequency (%)
인 115
25.0%
천 115
25.0%
부 115
25.0%
평 115
25.0%

상호
Text

UNIQUE 

Distinct115
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T01:55:50.321397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length13
Mean length7.4
Min length4

Characters and Unicode

Total characters851
Distinct characters202
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique115 ?
Unique (%)100.0%

Sample

1st rowJNH파이낸스대부
2nd row라온대부
3rd row퀵머니론대부
4th row머니갤러리대부
5th row하늘24대부
ValueCountFrequency (%)
주식회사 2
 
1.7%
jnh파이낸스대부 1
 
0.8%
꿈을dream대부 1
 
0.8%
일등대부중개 1
 
0.8%
ant대부 1
 
0.8%
주)대관사대부중개 1
 
0.8%
주)부개대부금융 1
 
0.8%
주)부개대부중개금융 1
 
0.8%
사랑24시대부 1
 
0.8%
모두의대부중개 1
 
0.8%
Other values (108) 108
90.8%
2023-12-13T01:55:50.708771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 126
 
14.8%
부 120
 
14.1%
개 48
 
5.6%
중 46
 
5.4%
이 19
 
2.2%
사 15
 
1.8%
주 15
 
1.8%
2 14
 
1.6%
시 13
 
1.5%
4 13
 
1.5%
Other values (192) 422
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 742
87.2%
Decimal Number 34
 
4.0%
Uppercase Letter 31
 
3.6%
Lowercase Letter 17
 
2.0%
Close Punctuation 11
 
1.3%
Open Punctuation 11
 
1.3%
Space Separator 5
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 126
 
17.0%
부 120
 
16.2%
개 48
 
6.5%
중 46
 
6.2%
이 19
 
2.6%
사 15
 
2.0%
주 15
 
2.0%
시 13
 
1.8%
스 12
 
1.6%
에 10
 
1.3%
Other values (152) 318
42.9%
Uppercase Letter
ValueCountFrequency (%)
K 5
16.1%
S 3
9.7%
J 3
9.7%
T 2
 
6.5%
N 2
 
6.5%
Y 2
 
6.5%
O 2
 
6.5%
L 2
 
6.5%
H 2
 
6.5%
A 1
 
3.2%
Other values (7) 7
22.6%
Lowercase Letter
ValueCountFrequency (%)
o 2
 
11.8%
i 2
 
11.8%
e 1
 
5.9%
d 1
 
5.9%
r 1
 
5.9%
a 1
 
5.9%
m 1
 
5.9%
c 1
 
5.9%
h 1
 
5.9%
l 1
 
5.9%
Other values (5) 5
29.4%
Decimal Number
ValueCountFrequency (%)
2 14
41.2%
4 13
38.2%
1 4
 
11.8%
9 2
 
5.9%
5 1
 
2.9%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 742
87.2%
Common 61
 
7.2%
Latin 48
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 126
 
17.0%
부 120
 
16.2%
개 48
 
6.5%
중 46
 
6.2%
이 19
 
2.6%
사 15
 
2.0%
주 15
 
2.0%
시 13
 
1.8%
스 12
 
1.6%
에 10
 
1.3%
Other values (152) 318
42.9%
Latin
ValueCountFrequency (%)
K 5
 
10.4%
S 3
 
6.2%
J 3
 
6.2%
T 2
 
4.2%
N 2
 
4.2%
o 2
 
4.2%
i 2
 
4.2%
Y 2
 
4.2%
O 2
 
4.2%
L 2
 
4.2%
Other values (22) 23
47.9%
Common
ValueCountFrequency (%)
2 14
23.0%
4 13
21.3%
) 11
18.0%
( 11
18.0%
5
 
8.2%
1 4
 
6.6%
9 2
 
3.3%
5 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 742
87.2%
ASCII 109
 
12.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 126
 
17.0%
부 120
 
16.2%
개 48
 
6.5%
중 46
 
6.2%
이 19
 
2.6%
사 15
 
2.0%
주 15
 
2.0%
시 13
 
1.8%
스 12
 
1.6%
에 10
 
1.3%
Other values (152) 318
42.9%
ASCII
ValueCountFrequency (%)
2 14
 
12.8%
4 13
 
11.9%
) 11
 
10.1%
( 11
 
10.1%
5
 
4.6%
K 5
 
4.6%
1 4
 
3.7%
S 3
 
2.8%
J 3
 
2.8%
T 2
 
1.8%
Other values (30) 38
34.9%

소재지(도로명)
Text

Distinct106
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-13T01:55:51.099621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length49
Mean length39.895652
Min length26

Characters and Unicode

Total characters4588
Distinct characters134
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

Unique97 ?
Unique (%)84.3%

Sample

1st row인천광역시 부평구 대정로 66, 다운타운일레븐 408-449호 (부평동)
2nd row인천광역시 부평구 시장로 54, 킴스타워 1402호 (부평동)
3rd row인천광역시 부평구 시장로 33, 한남시티프라자 7층 13호 (부평동)
4th row인천광역시 부평구 대정로 66, 다운타운일레븐 408-418호 (부평동)
5th row인천광역시 부평구 충선로203번길 16, 창성프라자 525-239호 (삼산동)
ValueCountFrequency (%)
인천광역시 115
 
13.7%
부평구 115
 
13.7%
부평동 60
 
7.2%
대정로 40
 
4.8%
다운타운일레븐 37
 
4.4%
66 37
 
4.4%
삼산동 30
 
3.6%
충선로203번길 20
 
2.4%
16 20
 
2.4%
창성프라자 20
 
2.4%
Other values (208) 345
41.1%
2023-12-13T01:55:51.670407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
725
 
15.8%
부 215
 
4.7%
평 210
 
4.6%
동 136
 
3.0%
천 131
 
2.9%
1 128
 
2.8%
6 128
 
2.8%
2 127
 
2.8%
, 127
 
2.8%
0 120
 
2.6%
Other values (124) 2541
55.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2523
55.0%
Decimal Number 892
 
19.4%
Space Separator 725
 
15.8%
Other Punctuation 127
 
2.8%
Close Punctuation 116
 
2.5%
Open Punctuation 116
 
2.5%
Dash Punctuation 71
 
1.5%
Uppercase Letter 18
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 215
 
8.5%
평 210
 
8.3%
동 136
 
5.4%
천 131
 
5.2%
시 120
 
4.8%
인 118
 
4.7%
광 116
 
4.6%
로 116
 
4.6%
역 115
 
4.6%
구 115
 
4.6%
Other values (105) 1131
44.8%
Decimal Number
ValueCountFrequency (%)
1 128
14.3%
6 128
14.3%
2 127
14.2%
0 120
13.5%
4 102
11.4%
5 91
10.2%
3 81
9.1%
8 65
7.3%
7 27
 
3.0%
9 23
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
A 9
50.0%
B 7
38.9%
O 1
 
5.6%
C 1
 
5.6%
Space Separator
ValueCountFrequency (%)
725
100.0%
Other Punctuation
ValueCountFrequency (%)
, 127
100.0%
Close Punctuation
ValueCountFrequency (%)
) 116
100.0%
Open Punctuation
ValueCountFrequency (%)
( 116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 71
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2523
55.0%
Common 2047
44.6%
Latin 18
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 215
 
8.5%
평 210
 
8.3%
동 136
 
5.4%
천 131
 
5.2%
시 120
 
4.8%
인 118
 
4.7%
광 116
 
4.6%
로 116
 
4.6%
역 115
 
4.6%
구 115
 
4.6%
Other values (105) 1131
44.8%
Common
ValueCountFrequency (%)
725
35.4%
1 128
 
6.3%
6 128
 
6.3%
2 127
 
6.2%
, 127
 
6.2%
0 120
 
5.9%
) 116
 
5.7%
( 116
 
5.7%
4 102
 
5.0%
5 91
 
4.4%
Other values (5) 267
 
13.0%
Latin
ValueCountFrequency (%)
A 9
50.0%
B 7
38.9%
O 1
 
5.6%
C 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2523
55.0%
ASCII 2065
45.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
725
35.1%
1 128
 
6.2%
6 128
 
6.2%
2 127
 
6.2%
, 127
 
6.2%
0 120
 
5.8%
) 116
 
5.6%
( 116
 
5.6%
4 102
 
4.9%
5 91
 
4.4%
Other values (9) 285
 
13.8%
Hangul
ValueCountFrequency (%)
부 215
 
8.5%
평 210
 
8.3%
동 136
 
5.4%
천 131
 
5.2%
시 120
 
4.8%
인 118
 
4.7%
광 116
 
4.6%
로 116
 
4.6%
역 115
 
4.6%
구 115
 
4.6%
Other values (105) 1131
44.8%

등록일자
Date

Distinct73
Distinct (%)63.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
Minimum2020-06-17 00:00:00
Maximum2023-05-09 00:00:00
2023-12-13T01:55:51.834434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:55:51.992459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2023-12-13T01:55:48.180956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:55:52.075595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록신청사업등록일자
순번1.0000.4580.946
등록신청사업0.4581.0000.241
등록일자0.9460.2411.000
2023-12-13T01:55:52.159335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록신청사업
순번1.0000.339
등록신청사업0.3391.000

Missing values

2023-12-13T01:55:48.315802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:55:48.428200image/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

순번시군구명등록신청사업등록증번호상호소재지(도로명)등록일자
01인천광역시 부평구대부업인천부평-2023-00018JNH파이낸스대부인천광역시 부평구 대정로 66, 다운타운일레븐 408-449호 (부평동)2023-05-09
12인천광역시 부평구대부업인천부평-2023-00017라온대부인천광역시 부평구 시장로 54, 킴스타워 1402호 (부평동)2023-05-09
23인천광역시 부평구대부업인천부평-2023-00016퀵머니론대부인천광역시 부평구 시장로 33, 한남시티프라자 7층 13호 (부평동)2023-05-03
34인천광역시 부평구대부업인천부평-2023-00015머니갤러리대부인천광역시 부평구 대정로 66, 다운타운일레븐 408-418호 (부평동)2023-04-24
45인천광역시 부평구대부업인천부평-2023-00013하늘24대부인천광역시 부평구 충선로203번길 16, 창성프라자 525-239호 (삼산동)2023-04-16
56인천광역시 부평구대부업인천부평-2023-0001424시신사대부인천광역시 부평구 충선로203번길 16, 창성프라자 525-238호 (삼산동)2023-04-18
67인천광역시 부평구대부중개업인천부평-2023-00012희망금융대부중개인천광역시 부평구 길주로647번길 4, 프리엘림 804호 (삼산동)2023-04-11
78인천광역시 부평구대부업인천부평-2023-00011미즈앤사랑대부인천광역시 부평구 대정로 66, 다운타운일레븐 408-203호 (부평동)2021-02-03
89인천광역시 부평구대부중개업인천부평-2023-00010엔씨대부중개인천광역시 부평구 평천로 356, 민상빌딩 202호 (갈산동)2023-03-08
910인천광역시 부평구대부중개업인천부평-2023-00008주식회사 상상대부중개인천광역시 부평구 대정로 66, 다운타운일레븐 408-11호 (부평동)2020-11-27
순번시군구명등록신청사업등록증번호상호소재지(도로명)등록일자
105106인천광역시 부평구대부업인천부평-2014-00050서강대부인천광역시 부평구 부평대로 9, 905호 (부평동, 문화드림빌)2020-08-20
106107인천광역시 부평구대부업인천부평-2014-00017명성사전당포대부인천광역시 부평구 부평문화로65번길 4 (부평동)2023-01-17
107108인천광역시 부평구대부업인천부평-2014-00009MK대부인천광역시 부평구 영성중로 50, 미래타워 405-가1호 (삼산동)2022-12-26
108109인천광역시 부평구대부중개업인천부평-2013-00056대광캐피탈대부중개인천광역시 부평구 열우물로 11, 405호 (십정동, 동삼빌딩)2022-06-09
109110인천광역시 부평구대부업인천부평-2022-00010(주)찬호영론대부인천광역시 부평구 길주로 623, 102동 1814호 (삼산동, 대덕리치아노)2022-04-12
110111인천광역시 부평구대부업인천부평-2012-00037(주)트로이에이치케이대부인천광역시 부평구 장제로351번길 4, 3층 (갈산동)2020-12-04
111112인천광역시 부평구대부업인천부평-2011-00044대양사전당포대부인천광역시 부평구 장제로 150, 1층 118호 (부평동, 유진마젤란주상복합)2022-10-12
112113인천광역시 부평구대부업인천부평-2009-00073동암사전당포대부인천광역시 부평구 동암광장로 8, 3층 (십정동)2021-04-09
113114인천광역시 부평구대부업인천부평-2007-00072백강상사대부인천광역시 부평구 경원대로 1422, 대덕아크로존 704호 (부평동)2021-12-09
114115인천광역시 부평구대부업인천부평-2017-00128우원사전당포대부인천광역시 부평구 장제로 60, 203호 (부평동)2020-06-30