Overview

Dataset statistics

Number of variables6
Number of observations116
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.7 KiB
Average record size in memory50.1 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description인천광역시 남동구 소재 대부업체(순번, 시군구명, 등록신청사업, 상호, 소재지(도로명), 기준일자)에 대한 정보입니다.
URLhttps://www.data.go.kr/data/15038942/fileData.do

Alerts

시군구명 has constant value ""Constant
기준일자 has constant value ""Constant
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:06:31.264837
Analysis finished2023-12-12 12:06:31.878654
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct116
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.5
Minimum1
Maximum116
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T21:06:31.960597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.75
Q129.75
median58.5
Q387.25
95-th percentile110.25
Maximum116
Range115
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation33.630343
Coefficient of variation (CV)0.57487767
Kurtosis-1.2
Mean58.5
Median Absolute Deviation (MAD)29
Skewness0
Sum6786
Variance1131
MonotonicityStrictly increasing
2023-12-12T21:06:32.155373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
75 1
 
0.9%
87 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%
Other values (106) 106
91.4%
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 (%)
116 1
0.9%
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%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
인천광역시 남동구
116 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
인천광역시 남동구 116
100.0%

Length

2023-12-12T21:06:32.311620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:06:32.416914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시 116
50.0%
남동구 116
50.0%

등록신청사업
Categorical

Distinct2
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
대부업
81 
대부중개업
35 

Length

Max length5
Median length3
Mean length3.6034483
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 81
69.8%
대부중개업 35
30.2%

Length

2023-12-12T21:06:32.542313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:06:32.644032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 81
69.8%
대부중개업 35
30.2%

상호
Text

Distinct108
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T21:06:32.806155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length7.6551724
Min length3

Characters and Unicode

Total characters888
Distinct characters192
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

Unique100 ?
Unique (%)86.2%

Sample

1st row대현대부
2nd row비대면희망대부중개
3rd row비대면희망대부
4th row머니앤대부중개
5th row머니앤대부
ValueCountFrequency (%)
주식회사 11
 
8.2%
대부중개 4
 
3.0%
그루자산관리대부 2
 
1.5%
대부 2
 
1.5%
우리컨설팅대부 2
 
1.5%
빅플러스대부 2
 
1.5%
즉시입금대부 2
 
1.5%
스타트 2
 
1.5%
케이에스자산관리대부 2
 
1.5%
더원자산관리대부 2
 
1.5%
Other values (102) 103
76.9%
2023-12-12T21:06:33.143769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 126
 
14.2%
부 116
 
13.1%
개 30
 
3.4%
중 29
 
3.3%
스 26
 
2.9%
이 20
 
2.3%
18
 
2.0%
사 16
 
1.8%
주 15
 
1.7%
시 13
 
1.5%
Other values (182) 479
53.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 802
90.3%
Decimal Number 38
 
4.3%
Uppercase Letter 23
 
2.6%
Space Separator 18
 
2.0%
Close Punctuation 3
 
0.3%
Open Punctuation 3
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 126
 
15.7%
부 116
 
14.5%
개 30
 
3.7%
중 29
 
3.6%
스 26
 
3.2%
이 20
 
2.5%
사 16
 
2.0%
주 15
 
1.9%
시 13
 
1.6%
리 13
 
1.6%
Other values (159) 398
49.6%
Uppercase Letter
ValueCountFrequency (%)
S 4
17.4%
I 3
13.0%
A 3
13.0%
C 2
8.7%
T 2
8.7%
Y 2
8.7%
P 2
8.7%
N 1
 
4.3%
M 1
 
4.3%
H 1
 
4.3%
Other values (2) 2
8.7%
Decimal Number
ValueCountFrequency (%)
2 12
31.6%
4 11
28.9%
1 5
13.2%
9 3
 
7.9%
3 3
 
7.9%
6 2
 
5.3%
5 2
 
5.3%
Space Separator
ValueCountFrequency (%)
18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
o 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 802
90.3%
Common 62
 
7.0%
Latin 24
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 126
 
15.7%
부 116
 
14.5%
개 30
 
3.7%
중 29
 
3.6%
스 26
 
3.2%
이 20
 
2.5%
사 16
 
2.0%
주 15
 
1.9%
시 13
 
1.6%
리 13
 
1.6%
Other values (159) 398
49.6%
Latin
ValueCountFrequency (%)
S 4
16.7%
I 3
12.5%
A 3
12.5%
C 2
8.3%
T 2
8.3%
Y 2
8.3%
P 2
8.3%
o 1
 
4.2%
N 1
 
4.2%
M 1
 
4.2%
Other values (3) 3
12.5%
Common
ValueCountFrequency (%)
18
29.0%
2 12
19.4%
4 11
17.7%
1 5
 
8.1%
9 3
 
4.8%
) 3
 
4.8%
( 3
 
4.8%
3 3
 
4.8%
6 2
 
3.2%
5 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 802
90.3%
ASCII 86
 
9.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 126
 
15.7%
부 116
 
14.5%
개 30
 
3.7%
중 29
 
3.6%
스 26
 
3.2%
이 20
 
2.5%
사 16
 
2.0%
주 15
 
1.9%
시 13
 
1.6%
리 13
 
1.6%
Other values (159) 398
49.6%
ASCII
ValueCountFrequency (%)
18
20.9%
2 12
14.0%
4 11
12.8%
1 5
 
5.8%
S 4
 
4.7%
I 3
 
3.5%
9 3
 
3.5%
A 3
 
3.5%
) 3
 
3.5%
( 3
 
3.5%
Other values (13) 21
24.4%

소재지(도로명)
Text

Distinct105
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-12-12T21:06:33.371032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length36.163793
Min length23

Characters and Unicode

Total characters4195
Distinct characters126
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

Unique94 ?
Unique (%)81.0%

Sample

1st row인천광역시 남동구 문화로145번길 48-4, 1097-6호 (구월동)
2nd row인천광역시 남동구 청능대로 559, 논현메디컬센터 4123호 (논현동)
3rd row인천광역시 남동구 청능대로 559, 논현메디컬센터 4123호 (논현동)
4th row인천광역시 남동구 청능대로 581, 502-167호 (논현동)
5th row인천광역시 남동구 청능대로 581, 502-167호 (논현동)
ValueCountFrequency (%)
인천광역시 116
 
14.9%
남동구 116
 
14.9%
구월동 59
 
7.6%
논현동 29
 
3.7%
선수촌공원로23번길 26
 
3.3%
11 25
 
3.2%
청능대로 23
 
2.9%
581 12
 
1.5%
4층 12
 
1.5%
구월남로 12
 
1.5%
Other values (204) 350
44.9%
2023-12-12T21:06:33.740949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
665
 
15.9%
동 255
 
6.1%
구 198
 
4.7%
1 186
 
4.4%
남 141
 
3.4%
인 120
 
2.9%
, 120
 
2.9%
시 119
 
2.8%
) 118
 
2.8%
( 118
 
2.8%
Other values (116) 2155
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2227
53.1%
Decimal Number 879
 
21.0%
Space Separator 665
 
15.9%
Other Punctuation 122
 
2.9%
Close Punctuation 118
 
2.8%
Open Punctuation 118
 
2.8%
Dash Punctuation 58
 
1.4%
Uppercase Letter 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 255
 
11.5%
구 198
 
8.9%
남 141
 
6.3%
인 120
 
5.4%
시 119
 
5.3%
로 117
 
5.3%
호 117
 
5.3%
천 117
 
5.3%
광 117
 
5.3%
역 116
 
5.2%
Other values (96) 810
36.4%
Decimal Number
ValueCountFrequency (%)
1 186
21.2%
5 115
13.1%
2 114
13.0%
3 108
12.3%
0 103
11.7%
4 75
8.5%
7 53
 
6.0%
6 51
 
5.8%
8 37
 
4.2%
9 37
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 4
50.0%
B 2
25.0%
D 1
 
12.5%
E 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 120
98.4%
/ 2
 
1.6%
Space Separator
ValueCountFrequency (%)
665
100.0%
Close Punctuation
ValueCountFrequency (%)
) 118
100.0%
Open Punctuation
ValueCountFrequency (%)
( 118
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 58
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2227
53.1%
Common 1960
46.7%
Latin 8
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 255
 
11.5%
구 198
 
8.9%
남 141
 
6.3%
인 120
 
5.4%
시 119
 
5.3%
로 117
 
5.3%
호 117
 
5.3%
천 117
 
5.3%
광 117
 
5.3%
역 116
 
5.2%
Other values (96) 810
36.4%
Common
ValueCountFrequency (%)
665
33.9%
1 186
 
9.5%
, 120
 
6.1%
) 118
 
6.0%
( 118
 
6.0%
5 115
 
5.9%
2 114
 
5.8%
3 108
 
5.5%
0 103
 
5.3%
4 75
 
3.8%
Other values (6) 238
 
12.1%
Latin
ValueCountFrequency (%)
A 4
50.0%
B 2
25.0%
D 1
 
12.5%
E 1
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2227
53.1%
ASCII 1968
46.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
665
33.8%
1 186
 
9.5%
, 120
 
6.1%
) 118
 
6.0%
( 118
 
6.0%
5 115
 
5.8%
2 114
 
5.8%
3 108
 
5.5%
0 103
 
5.2%
4 75
 
3.8%
Other values (10) 246
 
12.5%
Hangul
ValueCountFrequency (%)
동 255
 
11.5%
구 198
 
8.9%
남 141
 
6.3%
인 120
 
5.4%
시 119
 
5.3%
로 117
 
5.3%
호 117
 
5.3%
천 117
 
5.3%
광 117
 
5.3%
역 116
 
5.2%
Other values (96) 810
36.4%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
2023-07-26
116 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-26
2nd row2023-07-26
3rd row2023-07-26
4th row2023-07-26
5th row2023-07-26

Common Values

ValueCountFrequency (%)
2023-07-26 116
100.0%

Length

2023-12-12T21:06:33.884925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:06:33.984315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-26 116
100.0%

Interactions

2023-12-12T21:06:31.532061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:06:34.044003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록신청사업
순번1.0000.124
등록신청사업0.1241.000
2023-12-12T21:06:34.146018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록신청사업
순번1.0000.099
등록신청사업0.0991.000

Missing values

2023-12-12T21:06:31.671847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:06:31.824496image/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

순번시군구명등록신청사업상호소재지(도로명)기준일자
01인천광역시 남동구대부업대현대부인천광역시 남동구 문화로145번길 48-4, 1097-6호 (구월동)2023-07-26
12인천광역시 남동구대부중개업비대면희망대부중개인천광역시 남동구 청능대로 559, 논현메디컬센터 4123호 (논현동)2023-07-26
23인천광역시 남동구대부업비대면희망대부인천광역시 남동구 청능대로 559, 논현메디컬센터 4123호 (논현동)2023-07-26
34인천광역시 남동구대부중개업머니앤대부중개인천광역시 남동구 청능대로 581, 502-167호 (논현동)2023-07-26
45인천광역시 남동구대부업머니앤대부인천광역시 남동구 청능대로 581, 502-167호 (논현동)2023-07-26
56인천광역시 남동구대부업한길파이낸스대부인천광역시 남동구 선수촌공원로23번길 11, 7층 701-25호 (구월동)2023-07-26
67인천광역시 남동구대부중개업노을대부중개인천광역시 남동구 선수촌공원로23번길 11, 7층 702-68호 (구월동)2023-07-26
78인천광역시 남동구대부중개업SAMA대부중개인천광역시 남동구 예술로 198, 1층 87호 (구월동)2023-07-26
89인천광역시 남동구대부업우주월변대부인천광역시 남동구 구월남로 120, 601-39호 (구월동)2023-07-26
910인천광역시 남동구대부업나이스365대부인천광역시 남동구 선수촌공원로23번길 11, 702-20호 (구월동)2023-07-26
순번시군구명등록신청사업상호소재지(도로명)기준일자
106107인천광역시 남동구대부업우리사 전당포 대부인천광역시 남동구 만수로 31-1, 3층 (만수동)2023-07-26
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