Overview

Dataset statistics

Number of variables6
Number of observations30
Missing cells15
Missing cells (%)8.3%
Duplicate rows1
Duplicate rows (%)3.3%
Total size in memory1.6 KiB
Average record size in memory53.4 B

Variable types

Numeric1
Categorical3
Text2

Dataset

Description부산광역시_사상구_대부업체현황_20230307
Author부산광역시 사상구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15043155

Alerts

Dataset has 1 (3.3%) duplicate rowsDuplicates
등록신청사업 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
데이터기준일 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
시군구명 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 시군구명 and 1 other fieldsHigh correlation
연번 has 5 (16.7%) missing valuesMissing
상호 has 5 (16.7%) missing valuesMissing
소재지(도로명) has 5 (16.7%) missing valuesMissing

Reproduction

Analysis started2023-12-10 16:18:53.752123
Analysis finished2023-12-10 16:18:54.857914
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct25
Distinct (%)100.0%
Missing5
Missing (%)16.7%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-11T01:18:54.917314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2023-12-11T01:18:55.097280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
2 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
22 1
 
3.3%
21 1
 
3.3%
20 1
 
3.3%
19 1
 
3.3%
18 1
 
3.3%
17 1
 
3.3%
Other values (15) 15
50.0%
(Missing) 5
 
16.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%
20 1
3.3%
19 1
3.3%
18 1
3.3%
17 1
3.3%
16 1
3.3%

시군구명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
부산광역시 사상구
25 
<NA>

Length

Max length9
Median length9
Mean length8.1666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row부산광역시 사상구
2nd row부산광역시 사상구
3rd row부산광역시 사상구
4th row부산광역시 사상구
5th row부산광역시 사상구

Common Values

ValueCountFrequency (%)
부산광역시 사상구 25
83.3%
<NA> 5
 
16.7%

Length

2023-12-11T01:18:55.227138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:18:55.332313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 25
45.5%
사상구 25
45.5%
na 5
 
9.1%

등록신청사업
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
대부업
20 
대부중개업
<NA>

Length

Max length5
Median length3
Mean length3.5
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대부업 20
66.7%
대부중개업 5
 
16.7%
<NA> 5
 
16.7%

Length

2023-12-11T01:18:55.484700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:18:55.629758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대부업 20
66.7%
대부중개업 5
 
16.7%
na 5
 
16.7%

상호
Text

MISSING 

Distinct24
Distinct (%)96.0%
Missing5
Missing (%)16.7%
Memory size372.0 B
2023-12-11T01:18:55.814326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.96
Min length4

Characters and Unicode

Total characters199
Distinct characters74
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

Unique23 ?
Unique (%)92.0%

Sample

1st row이정카오토대부
2nd row동주자산관리대부
3rd row주식회사 위해대부중개
4th row오픈대부
5th row주식회사 위해대부
ValueCountFrequency (%)
주식회사 5
 
15.6%
부성자산관리(주 2
 
6.2%
동주자산관리대부 1
 
3.1%
365일대부 1
 
3.1%
사상전당포대부 1
 
3.1%
대륙전당포대부 1
 
3.1%
미광전당포대부 1
 
3.1%
월드대부비엔씨(b&c 1
 
3.1%
신엄궁전당포대부 1
 
3.1%
코리아에셋머니대부 1
 
3.1%
Other values (17) 17
53.1%
2023-12-11T01:18:56.277691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24
 
12.1%
23
 
11.6%
8
 
4.0%
8
 
4.0%
7
 
3.5%
6
 
3.0%
5
 
2.5%
5
 
2.5%
4
 
2.0%
4
 
2.0%
Other values (64) 105
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
90.5%
Space Separator 7
 
3.5%
Close Punctuation 3
 
1.5%
Open Punctuation 3
 
1.5%
Decimal Number 3
 
1.5%
Uppercase Letter 2
 
1.0%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
24
 
13.3%
23
 
12.8%
8
 
4.4%
8
 
4.4%
6
 
3.3%
5
 
2.8%
5
 
2.8%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (55) 89
49.4%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
5 1
33.3%
6 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
90.5%
Common 17
 
8.5%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
24
 
13.3%
23
 
12.8%
8
 
4.4%
8
 
4.4%
6
 
3.3%
5
 
2.8%
5
 
2.8%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (55) 89
49.4%
Common
ValueCountFrequency (%)
7
41.2%
) 3
17.6%
( 3
17.6%
3 1
 
5.9%
& 1
 
5.9%
5 1
 
5.9%
6 1
 
5.9%
Latin
ValueCountFrequency (%)
B 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
90.5%
ASCII 19
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
24
 
13.3%
23
 
12.8%
8
 
4.4%
8
 
4.4%
6
 
3.3%
5
 
2.8%
5
 
2.8%
4
 
2.2%
4
 
2.2%
4
 
2.2%
Other values (55) 89
49.4%
ASCII
ValueCountFrequency (%)
7
36.8%
) 3
15.8%
( 3
15.8%
3 1
 
5.3%
B 1
 
5.3%
& 1
 
5.3%
5 1
 
5.3%
6 1
 
5.3%
C 1
 
5.3%

소재지(도로명)
Text

MISSING 

Distinct21
Distinct (%)84.0%
Missing5
Missing (%)16.7%
Memory size372.0 B
2023-12-11T01:18:56.640939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length43
Mean length36.84
Min length23

Characters and Unicode

Total characters921
Distinct characters90
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 (%)68.0%

Sample

1st row부산광역시 사상구 사상로 217, 4층 2호 (괘법동, 주은타워빌)
2nd row부산광역시 사상구 삼덕로46번길 100, 성신태권도 4층 403호 (삼락동)
3rd row부산광역시 사상구 대동로 303, 부산디지털밸리아파트형공장 1010호 (감전동)
4th row부산광역시 사상구 새벽로 131, 부산산업용재유통상가 1동 322호 (감전동)
5th row부산광역시 사상구 대동로 303, 부산디지털밸리아파트형공장 1010호 (감전동)
ValueCountFrequency (%)
부산광역시 25
 
14.5%
사상구 25
 
14.5%
감전동 12
 
6.9%
새벽로 6
 
3.5%
131 6
 
3.5%
부산산업용재유통상가 6
 
3.5%
괘법동 4
 
2.3%
주례동 4
 
2.3%
사상로 4
 
2.3%
4동 3
 
1.7%
Other values (60) 78
45.1%
2023-12-11T01:18:57.176959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
148
 
16.1%
39
 
4.2%
1 37
 
4.0%
36
 
3.9%
35
 
3.8%
33
 
3.6%
29
 
3.1%
27
 
2.9%
26
 
2.8%
( 26
 
2.8%
Other values (80) 485
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 535
58.1%
Decimal Number 159
 
17.3%
Space Separator 148
 
16.1%
Open Punctuation 26
 
2.8%
Close Punctuation 26
 
2.8%
Other Punctuation 23
 
2.5%
Dash Punctuation 3
 
0.3%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
39
 
7.3%
36
 
6.7%
35
 
6.5%
33
 
6.2%
29
 
5.4%
27
 
5.0%
26
 
4.9%
26
 
4.9%
25
 
4.7%
25
 
4.7%
Other values (64) 234
43.7%
Decimal Number
ValueCountFrequency (%)
1 37
23.3%
3 22
13.8%
2 22
13.8%
0 21
13.2%
4 13
 
8.2%
5 12
 
7.5%
7 11
 
6.9%
8 10
 
6.3%
6 9
 
5.7%
9 2
 
1.3%
Space Separator
ValueCountFrequency (%)
148
100.0%
Open Punctuation
ValueCountFrequency (%)
( 26
100.0%
Close Punctuation
ValueCountFrequency (%)
) 26
100.0%
Other Punctuation
ValueCountFrequency (%)
, 23
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 535
58.1%
Common 385
41.8%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
39
 
7.3%
36
 
6.7%
35
 
6.5%
33
 
6.2%
29
 
5.4%
27
 
5.0%
26
 
4.9%
26
 
4.9%
25
 
4.7%
25
 
4.7%
Other values (64) 234
43.7%
Common
ValueCountFrequency (%)
148
38.4%
1 37
 
9.6%
( 26
 
6.8%
) 26
 
6.8%
, 23
 
6.0%
3 22
 
5.7%
2 22
 
5.7%
0 21
 
5.5%
4 13
 
3.4%
5 12
 
3.1%
Other values (5) 35
 
9.1%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 535
58.1%
ASCII 386
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
148
38.3%
1 37
 
9.6%
( 26
 
6.7%
) 26
 
6.7%
, 23
 
6.0%
3 22
 
5.7%
2 22
 
5.7%
0 21
 
5.4%
4 13
 
3.4%
5 12
 
3.1%
Other values (6) 36
 
9.3%
Hangul
ValueCountFrequency (%)
39
 
7.3%
36
 
6.7%
35
 
6.5%
33
 
6.2%
29
 
5.4%
27
 
5.0%
26
 
4.9%
26
 
4.9%
25
 
4.7%
25
 
4.7%
Other values (64) 234
43.7%

데이터기준일
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-03-07
25 
<NA>

Length

Max length10
Median length10
Mean length9
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-03-07
2nd row2023-03-07
3rd row2023-03-07
4th row2023-03-07
5th row2023-03-07

Common Values

ValueCountFrequency (%)
2023-03-07 25
83.3%
<NA> 5
 
16.7%

Length

2023-12-11T01:18:57.410637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:18:57.540019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-03-07 25
83.3%
na 5
 
16.7%

Interactions

2023-12-11T01:18:54.035365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:18:57.619947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번등록신청사업상호소재지(도로명)
연번1.0000.0000.9140.842
등록신청사업0.0001.0000.0000.000
상호0.9140.0001.0001.000
소재지(도로명)0.8420.0001.0001.000
2023-12-11T01:18:57.734595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록신청사업데이터기준일시군구명
등록신청사업1.0001.0001.000
데이터기준일1.0001.0001.000
시군구명1.0001.0001.000
2023-12-11T01:18:57.851619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번시군구명등록신청사업데이터기준일
연번1.0001.0000.0001.000
시군구명1.0001.0001.0001.000
등록신청사업0.0001.0001.0001.000
데이터기준일1.0001.0001.0001.000

Missing values

2023-12-11T01:18:54.176219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:18:54.341547image/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.
2023-12-11T01:18:54.492695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번시군구명등록신청사업상호소재지(도로명)데이터기준일
01부산광역시 사상구대부업이정카오토대부부산광역시 사상구 사상로 217, 4층 2호 (괘법동, 주은타워빌)2023-03-07
12부산광역시 사상구대부업동주자산관리대부부산광역시 사상구 삼덕로46번길 100, 성신태권도 4층 403호 (삼락동)2023-03-07
23부산광역시 사상구대부중개업주식회사 위해대부중개부산광역시 사상구 대동로 303, 부산디지털밸리아파트형공장 1010호 (감전동)2023-03-07
34부산광역시 사상구대부업오픈대부부산광역시 사상구 새벽로 131, 부산산업용재유통상가 1동 322호 (감전동)2023-03-07
45부산광역시 사상구대부업주식회사 위해대부부산광역시 사상구 대동로 303, 부산디지털밸리아파트형공장 1010호 (감전동)2023-03-07
56부산광역시 사상구대부중개업주식회사 피플앤파이낸스대부중개부산광역시 사상구 새벽로 131, 부산산업용재유통상가 4동 127호 (감전동)2023-03-07
67부산광역시 사상구대부업주식회사 피플앤파이낸스대부부산광역시 사상구 새벽로 131, 부산산업용재유통상가 4동 127호 (감전동)2023-03-07
78부산광역시 사상구대부업액시스 대부부산광역시 사상구 사상로 123, 호승빌딩 2층 203호 (감전동)2023-03-07
89부산광역시 사상구대부업와이대부부산광역시 사상구 광장로37번길 86, 정한브르텔 504호 (괘법동)2023-03-07
910부산광역시 사상구대부중개업다온 대부중개부산광역시 사상구 가야대로388번길 10, 대한빌라텔 605호 (주례동)2023-03-07
연번시군구명등록신청사업상호소재지(도로명)데이터기준일
2021부산광역시 사상구대부업신엄궁전당포대부부산광역시 사상구 엄궁북로 25 (엄궁동)2023-03-07
2122부산광역시 사상구대부업월드대부비엔씨(B&C)부산광역시 사상구 낙동대로 910, A동 205호 (감전동,(낙동대로 910) 마트월드)2023-03-07
2223부산광역시 사상구대부업미광전당포대부부산광역시 사상구 사상로 488-5, 102호 (모라동, 이화하이츠빌라)2023-03-07
2324부산광역시 사상구대부업대륙전당포대부부산광역시 사상구 가야대로 274-7 (주례동)2023-03-07
2425부산광역시 사상구대부업사상전당포대부부산광역시 사상구 사상로 247 (괘법동)2023-03-07
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연번시군구명등록신청사업상호소재지(도로명)데이터기준일# duplicates
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