Overview

Dataset statistics

Number of variables6
Number of observations81
Missing cells25
Missing cells (%)5.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory51.6 B

Variable types

Numeric2
Categorical1
Text3

Dataset

Description인천광역시 부평구 건물 위생 관리업 현황 현황입니다.(업소명,영업소,주소(도로명),우편번호(도로명),소재지전화)ex) (주)금성,인천광역시 부평구 부평대로 283, 부평우림라이온스밸리 A동 지하1층 B115-15(일부)호 (청천동),21315
Author인천광역시 부평구
URLhttps://www.data.go.kr/data/15089229/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 25 (30.9%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 22:52:28.670688
Analysis finished2023-12-11 22:52:29.683015
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41
Minimum1
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T07:52:29.789765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q121
median41
Q361
95-th percentile77
Maximum81
Range80
Interquartile range (IQR)40

Descriptive statistics

Standard deviation23.526581
Coefficient of variation (CV)0.57381904
Kurtosis-1.2
Mean41
Median Absolute Deviation (MAD)20
Skewness0
Sum3321
Variance553.5
MonotonicityStrictly increasing
2023-12-12T07:52:29.949889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
62 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (71) 71
87.7%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size780.0 B
건물위생관리업
81 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 81
100.0%

Length

2023-12-12T07:52:30.084506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:52:30.179585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 81
100.0%

업소명
Text

UNIQUE 

Distinct81
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T07:52:30.400436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length8.2222222
Min length3

Characters and Unicode

Total characters666
Distinct characters163
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)100.0%

Sample

1st row(주)동광개발
2nd row국제종합관리(주)
3rd row동연개발주식회사
4th row주식회사 골든파인
5th row정성종합관리 주식회사
ValueCountFrequency (%)
주식회사 16
 
15.1%
종합환경 2
 
1.9%
주)동광개발 1
 
0.9%
지엠종합관리 1
 
0.9%
매직크린환경 1
 
0.9%
중앙종합관리 1
 
0.9%
제이피자산관리(주 1
 
0.9%
크린헬퍼 1
 
0.9%
주)에스엠종합관리 1
 
0.9%
모다크린 1
 
0.9%
Other values (80) 80
75.5%
2023-12-12T07:52:30.837588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 52
 
7.8%
( 34
 
5.1%
) 34
 
5.1%
사 26
 
3.9%
25
 
3.8%
리 25
 
3.8%
회 23
 
3.5%
식 21
 
3.2%
스 18
 
2.7%
관 17
 
2.6%
Other values (153) 391
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 565
84.8%
Open Punctuation 34
 
5.1%
Close Punctuation 34
 
5.1%
Space Separator 25
 
3.8%
Uppercase Letter 8
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 52
 
9.2%
사 26
 
4.6%
리 25
 
4.4%
회 23
 
4.1%
식 21
 
3.7%
스 18
 
3.2%
관 17
 
3.0%
합 16
 
2.8%
종 15
 
2.7%
린 15
 
2.7%
Other values (144) 337
59.6%
Uppercase Letter
ValueCountFrequency (%)
S 2
25.0%
G 2
25.0%
C 1
12.5%
M 1
12.5%
H 1
12.5%
B 1
12.5%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 565
84.8%
Common 93
 
14.0%
Latin 8
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 52
 
9.2%
사 26
 
4.6%
리 25
 
4.4%
회 23
 
4.1%
식 21
 
3.7%
스 18
 
3.2%
관 17
 
3.0%
합 16
 
2.8%
종 15
 
2.7%
린 15
 
2.7%
Other values (144) 337
59.6%
Latin
ValueCountFrequency (%)
S 2
25.0%
G 2
25.0%
C 1
12.5%
M 1
12.5%
H 1
12.5%
B 1
12.5%
Common
ValueCountFrequency (%)
( 34
36.6%
) 34
36.6%
25
26.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 565
84.8%
ASCII 101
 
15.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 52
 
9.2%
사 26
 
4.6%
리 25
 
4.4%
회 23
 
4.1%
식 21
 
3.7%
스 18
 
3.2%
관 17
 
3.0%
합 16
 
2.8%
종 15
 
2.7%
린 15
 
2.7%
Other values (144) 337
59.6%
ASCII
ValueCountFrequency (%)
( 34
33.7%
) 34
33.7%
25
24.8%
S 2
 
2.0%
G 2
 
2.0%
C 1
 
1.0%
M 1
 
1.0%
H 1
 
1.0%
B 1
 
1.0%

영업소 주소(도로명)
Text

Distinct78
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size780.0 B
2023-12-12T07:52:31.135885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length48
Mean length35.481481
Min length23

Characters and Unicode

Total characters2874
Distinct characters144
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)92.6%

Sample

1st row인천광역시 부평구 길주남로 60 (부평동)
2nd row인천광역시 부평구 부흥북로36번길 4 (부평동,칠성빌딩2층)
3rd row인천광역시 부평구 마장로364번길 29-17 (청천동,(동연빌딩 지하1층,지상4층))
4th row인천광역시 부평구 부평대로 103-1, 3층 (부평동)
5th row인천광역시 부평구 경인로 1080-1, 401,402호 (부개동)
ValueCountFrequency (%)
인천광역시 81
 
14.4%
부평구 81
 
14.4%
일부호 29
 
5.2%
부평동 25
 
4.4%
1층 16
 
2.8%
2층 14
 
2.5%
부개동 14
 
2.5%
갈산동 11
 
2.0%
청천동 11
 
2.0%
십정동 9
 
1.6%
Other values (184) 271
48.2%
2023-12-12T07:52:31.652133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
481
 
16.7%
부 175
 
6.1%
평 124
 
4.3%
동 99
 
3.4%
천 98
 
3.4%
1 96
 
3.3%
인 92
 
3.2%
, 92
 
3.2%
) 85
 
3.0%
( 85
 
3.0%
Other values (134) 1447
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1626
56.6%
Space Separator 481
 
16.7%
Decimal Number 465
 
16.2%
Other Punctuation 92
 
3.2%
Close Punctuation 85
 
3.0%
Open Punctuation 85
 
3.0%
Uppercase Letter 21
 
0.7%
Dash Punctuation 17
 
0.6%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 175
 
10.8%
평 124
 
7.6%
동 99
 
6.1%
천 98
 
6.0%
인 92
 
5.7%
광 83
 
5.1%
역 81
 
5.0%
시 81
 
5.0%
구 81
 
5.0%
로 81
 
5.0%
Other values (109) 631
38.8%
Decimal Number
ValueCountFrequency (%)
1 96
20.6%
2 75
16.1%
0 62
13.3%
3 52
11.2%
4 45
9.7%
6 45
9.7%
5 29
 
6.2%
8 23
 
4.9%
7 23
 
4.9%
9 15
 
3.2%
Uppercase Letter
ValueCountFrequency (%)
B 6
28.6%
A 5
23.8%
M 3
14.3%
S 2
 
9.5%
D 1
 
4.8%
J 1
 
4.8%
U 1
 
4.8%
P 1
 
4.8%
T 1
 
4.8%
Space Separator
ValueCountFrequency (%)
481
100.0%
Other Punctuation
ValueCountFrequency (%)
, 92
100.0%
Close Punctuation
ValueCountFrequency (%)
) 85
100.0%
Open Punctuation
ValueCountFrequency (%)
( 85
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1626
56.6%
Common 1227
42.7%
Latin 21
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 175
 
10.8%
평 124
 
7.6%
동 99
 
6.1%
천 98
 
6.0%
인 92
 
5.7%
광 83
 
5.1%
역 81
 
5.0%
시 81
 
5.0%
구 81
 
5.0%
로 81
 
5.0%
Other values (109) 631
38.8%
Common
ValueCountFrequency (%)
481
39.2%
1 96
 
7.8%
, 92
 
7.5%
) 85
 
6.9%
( 85
 
6.9%
2 75
 
6.1%
0 62
 
5.1%
3 52
 
4.2%
4 45
 
3.7%
6 45
 
3.7%
Other values (6) 109
 
8.9%
Latin
ValueCountFrequency (%)
B 6
28.6%
A 5
23.8%
M 3
14.3%
S 2
 
9.5%
D 1
 
4.8%
J 1
 
4.8%
U 1
 
4.8%
P 1
 
4.8%
T 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1626
56.6%
ASCII 1248
43.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
481
38.5%
1 96
 
7.7%
, 92
 
7.4%
) 85
 
6.8%
( 85
 
6.8%
2 75
 
6.0%
0 62
 
5.0%
3 52
 
4.2%
4 45
 
3.6%
6 45
 
3.6%
Other values (15) 130
 
10.4%
Hangul
ValueCountFrequency (%)
부 175
 
10.8%
평 124
 
7.6%
동 99
 
6.1%
천 98
 
6.0%
인 92
 
5.7%
광 83
 
5.1%
역 81
 
5.0%
시 81
 
5.0%
구 81
 
5.0%
로 81
 
5.0%
Other values (109) 631
38.8%

우편번호(도로명)
Real number (ℝ)

Distinct46
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21372.321
Minimum21310
Maximum21453
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size861.0 B
2023-12-12T07:52:31.832540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21310
5-th percentile21312
Q121330
median21360
Q321415
95-th percentile21446
Maximum21453
Range143
Interquartile range (IQR)85

Descriptive statistics

Standard deviation45.885681
Coefficient of variation (CV)0.0021469676
Kurtosis-1.2818025
Mean21372.321
Median Absolute Deviation (MAD)44
Skewness0.16655116
Sum1731158
Variance2105.4957
MonotonicityNot monotonic
2023-12-12T07:52:31.999440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
21313 4
 
4.9%
21354 4
 
4.9%
21315 4
 
4.9%
21317 3
 
3.7%
21421 3
 
3.7%
21420 3
 
3.7%
21316 3
 
3.7%
21310 3
 
3.7%
21360 3
 
3.7%
21312 2
 
2.5%
Other values (36) 49
60.5%
ValueCountFrequency (%)
21310 3
3.7%
21312 2
2.5%
21313 4
4.9%
21315 4
4.9%
21316 3
3.7%
21317 3
3.7%
21322 1
 
1.2%
21330 2
2.5%
21338 1
 
1.2%
21344 2
2.5%
ValueCountFrequency (%)
21453 2
2.5%
21452 1
1.2%
21446 2
2.5%
21445 1
1.2%
21439 2
2.5%
21438 1
1.2%
21433 1
1.2%
21432 1
1.2%
21430 1
1.2%
21422 1
1.2%

소재지전화
Text

MISSING 

Distinct56
Distinct (%)100.0%
Missing25
Missing (%)30.9%
Memory size780.0 B
2023-12-12T07:52:32.224497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.589286
Min length9

Characters and Unicode

Total characters761
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)100.0%

Sample

1st row 032- 516-3031
2nd row 032- 514-0770
3rd row032 -514 -7071
4th row 032- 515-0234
5th row 032- 505-2213
ValueCountFrequency (%)
032 44
31.9%
070 4
 
2.9%
513 2
 
1.4%
031 2
 
1.4%
3800 2
 
1.4%
529 2
 
1.4%
438 2
 
1.4%
504 2
 
1.4%
673 1
 
0.7%
0022 1
 
0.7%
Other values (76) 76
55.1%
2023-12-12T07:52:32.590097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 110
14.5%
- 108
14.2%
95
12.5%
2 95
12.5%
3 86
11.3%
5 62
8.1%
1 58
7.6%
7 35
 
4.6%
4 35
 
4.6%
6 34
 
4.5%
Other values (2) 43
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 558
73.3%
Dash Punctuation 108
 
14.2%
Space Separator 95
 
12.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 110
19.7%
2 95
17.0%
3 86
15.4%
5 62
11.1%
1 58
10.4%
7 35
 
6.3%
4 35
 
6.3%
6 34
 
6.1%
8 27
 
4.8%
9 16
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 108
100.0%
Space Separator
ValueCountFrequency (%)
95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 761
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 110
14.5%
- 108
14.2%
95
12.5%
2 95
12.5%
3 86
11.3%
5 62
8.1%
1 58
7.6%
7 35
 
4.6%
4 35
 
4.6%
6 34
 
4.5%
Other values (2) 43
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 761
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 110
14.5%
- 108
14.2%
95
12.5%
2 95
12.5%
3 86
11.3%
5 62
8.1%
1 58
7.6%
7 35
 
4.6%
4 35
 
4.6%
6 34
 
4.5%
Other values (2) 43
 
5.7%

Interactions

2023-12-12T07:52:29.293539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:52:29.055054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:52:29.398426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T07:52:29.142488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:52:32.686876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명영업소 주소(도로명)우편번호(도로명)소재지전화
연번1.0001.0000.7860.3631.000
업소명1.0001.0001.0001.0001.000
영업소 주소(도로명)0.7861.0001.0001.0001.000
우편번호(도로명)0.3631.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.000
2023-12-12T07:52:32.806134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번우편번호(도로명)
연번1.000-0.002
우편번호(도로명)-0.0021.000

Missing values

2023-12-12T07:52:29.527375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:52:29.640243image/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

연번업종명업소명영업소 주소(도로명)우편번호(도로명)소재지전화
01건물위생관리업(주)동광개발인천광역시 부평구 길주남로 60 (부평동)21356032- 516-3031
12건물위생관리업국제종합관리(주)인천광역시 부평구 부흥북로36번길 4 (부평동,칠성빌딩2층)21360032- 514-0770
23건물위생관리업동연개발주식회사인천광역시 부평구 마장로364번길 29-17 (청천동,(동연빌딩 지하1층,지상4층))21313032 -514 -7071
34건물위생관리업주식회사 골든파인인천광역시 부평구 부평대로 103-1, 3층 (부평동)21379032- 515-0234
45건물위생관리업정성종합관리 주식회사인천광역시 부평구 경인로 1080-1, 401,402호 (부개동)21420032- 505-2213
56건물위생관리업푸른환경개발인천광역시 부평구 수변로107번길 21, 2층 일부호 (부개동)21398032 -529 -3800
67건물위생관리업스톤서비스인천광역시 부평구 부흥북로 121 (부개동)21352032-2361-1400
78건물위생관리업휴먼앤비젼인천광역시 부평구 신트리로6번길 6 (부평동,5층)21354032- 505-1205
89건물위생관리업(주)엔가드인천인천광역시 부평구 화랑북로 10-2 (산곡동,2층)21382032- 516-2664
910건물위생관리업주식회사 크린인천인천광역시 부평구 동수로 28, 111호 (부평동, 샬렛주상아파트)21430032- 513-1982
연번업종명업소명영업소 주소(도로명)우편번호(도로명)소재지전화
7172건물위생관리업대신종합관리인천광역시 부평구 동수로162번길 14, 1층 일부호 (부개동)21421<NA>
7273건물위생관리업골드원크린인천광역시 부평구 대정로 66, 다운타운일레븐 4층 408-484호 (부평동)21395<NA>
7374건물위생관리업에코지엠(주)인천광역시 부평구 백범로 442, 3층 일부호 (십정동)21446<NA>
7475건물위생관리업가람솔인천광역시 부평구 마장로 49, 106동 108호 일부호 (십정동, 인천부평대주파크빌)21433<NA>
7576건물위생관리업굿프랜드인천광역시 부평구 경인로701번길 26, 사회복지법인성촌재단 D동 2층 일부호 (십정동)21438<NA>
7677건물위생관리업부흥크린인천광역시 부평구 마분로 30-1, 1층 일부호 (부개동)21421<NA>
7778건물위생관리업주식회사 원스인천광역시 부평구 새갈로 57, 상가동 2층 202호 (갈산동, 갈산동 대성유니드아파트)213171566-1261
7879건물위생관리업씨에스지(CSG) 종합환경인천광역시 부평구 일신로14번길 23, 상가동 B-004호, B-005호 (일신동, 풍림아파트)21422<NA>
7980건물위생관리업대한종합관리 서비스(주)인천광역시 부평구 마장로410번길 6, 라동 2층 일부호 (청천동)21312032 -715 -8371
8081건물위생관리업마리컴퍼니 인천인천광역시 부평구 부평대로 290, 창신빌딩 2층 일부호 (갈산동)21316<NA>