Overview

Dataset statistics

Number of variables33
Number of observations94
Missing cells1094
Missing cells (%)35.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.4 KiB
Average record size in memory287.4 B

Variable types

Numeric10
Categorical8
Text5
Unsupported9
DateTime1

Dataset

Description2021-04-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123146

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
타기관이전여부 is highly imbalanced (65.8%)Imbalance
인허가일자 has 1 (1.1%) missing valuesMissing
인허가취소일자 has 66 (70.2%) missing valuesMissing
폐업일자 has 94 (100.0%) missing valuesMissing
휴업시작일자 has 94 (100.0%) missing valuesMissing
휴업종료일자 has 94 (100.0%) missing valuesMissing
재개업일자 has 94 (100.0%) missing valuesMissing
소재지전화 has 94 (100.0%) missing valuesMissing
소재지면적 has 94 (100.0%) missing valuesMissing
소재지우편번호 has 94 (100.0%) missing valuesMissing
소재지전체주소 has 11 (11.7%) missing valuesMissing
도로명전체주소 has 21 (22.3%) missing valuesMissing
도로명우편번호 has 86 (91.5%) missing valuesMissing
업태구분명 has 94 (100.0%) missing valuesMissing
좌표정보(x) has 12 (12.8%) missing valuesMissing
좌표정보(y) has 12 (12.8%) missing valuesMissing
전문인력총수 has 6 (6.4%) missing valuesMissing
자본금 has 4 (4.3%) missing valuesMissing
시설장비 has 29 (30.9%) missing valuesMissing
Unnamed: 32 has 94 (100.0%) missing valuesMissing
번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
폐업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지전화 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지우편번호 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 32 is an unsupported type, check if it needs cleaning or further analysisUnsupported
전문인력총수 has 27 (28.7%) zerosZeros
자본금 has 3 (3.2%) zerosZeros

Reproduction

Analysis started2024-04-16 13:16:10.304458
Analysis finished2024-04-16 13:16:10.740049
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.5
Minimum1
Maximum94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:10.797819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.65
Q124.25
median47.5
Q370.75
95-th percentile89.35
Maximum94
Range93
Interquartile range (IQR)46.5

Descriptive statistics

Standard deviation27.279418
Coefficient of variation (CV)0.57430354
Kurtosis-1.2
Mean47.5
Median Absolute Deviation (MAD)23.5
Skewness0
Sum4465
Variance744.16667
MonotonicityStrictly increasing
2024-04-16T22:16:10.899523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
61 1
 
1.1%
70 1
 
1.1%
69 1
 
1.1%
68 1
 
1.1%
67 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
Other values (84) 84
89.4%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
94 1
1.1%
93 1
1.1%
92 1
1.1%
91 1
1.1%
90 1
1.1%
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
지하수시공업체
94 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하수시공업체 94
100.0%

Length

2024-04-16T22:16:10.994551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:11.061673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하수시공업체 94
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
09_29_01_P
94 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_29_01_P
2nd row09_29_01_P
3rd row09_29_01_P
4th row09_29_01_P
5th row09_29_01_P

Common Values

ValueCountFrequency (%)
09_29_01_P 94
100.0%

Length

2024-04-16T22:16:11.140679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:11.230545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_29_01_p 94
100.0%

개방자치단체코드
Real number (ℝ)

Distinct14
Distinct (%)14.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3338191.5
Minimum3270000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:11.318263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3270000
5-th percentile3280000
Q13300000
median3330000
Q33370000
95-th percentile3400000
Maximum3400000
Range130000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation41243.123
Coefficient of variation (CV)0.01235493
Kurtosis-1.2747472
Mean3338191.5
Median Absolute Deviation (MAD)35000
Skewness0.13089495
Sum3.1379 × 108
Variance1.7009952 × 109
MonotonicityNot monotonic
2024-04-16T22:16:11.415318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3400000 15
16.0%
3300000 12
12.8%
3330000 11
11.7%
3290000 11
11.7%
3350000 10
10.6%
3370000 8
8.5%
3310000 6
 
6.4%
3380000 4
 
4.3%
3270000 4
 
4.3%
3390000 3
 
3.2%
Other values (4) 10
10.6%
ValueCountFrequency (%)
3270000 4
 
4.3%
3280000 2
 
2.1%
3290000 11
11.7%
3300000 12
12.8%
3310000 6
6.4%
3320000 3
 
3.2%
3330000 11
11.7%
3340000 2
 
2.1%
3350000 10
10.6%
3360000 3
 
3.2%
ValueCountFrequency (%)
3400000 15
16.0%
3390000 3
 
3.2%
3380000 4
 
4.3%
3370000 8
8.5%
3360000 3
 
3.2%
3350000 10
10.6%
3340000 2
 
2.1%
3330000 11
11.7%
3320000 3
 
3.2%
3310000 6
 
6.4%

관리번호
Text

Distinct84
Distinct (%)89.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-04-16T22:16:11.603582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters1786
Distinct characters12
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

Unique77 ?
Unique (%)81.9%

Sample

1st rowC006211751793000000
2nd rowC006205202899912L00
3rd rowC006104221902329L00
4th rowC004705231117811L00
5th rowC001845110008620L00
ValueCountFrequency (%)
c001801110300036l00 4
 
4.3%
c001949110008307l00 3
 
3.2%
c001801110716803l00 2
 
2.1%
c001955110078414l00 2
 
2.1%
c001801110315837l00 2
 
2.1%
c002056110006098l00 2
 
2.1%
c001801110327775l00 2
 
2.1%
c001801110055722l00 1
 
1.1%
c001712110074234l00 1
 
1.1%
c001801110346965l00 1
 
1.1%
Other values (74) 74
78.7%
2024-04-16T22:16:11.895627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 680
38.1%
1 358
20.0%
8 96
 
5.4%
C 94
 
5.3%
2 93
 
5.2%
L 74
 
4.1%
7 72
 
4.0%
6 71
 
4.0%
5 66
 
3.7%
9 65
 
3.6%
Other values (2) 117
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1618
90.6%
Uppercase Letter 168
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 680
42.0%
1 358
22.1%
8 96
 
5.9%
2 93
 
5.7%
7 72
 
4.4%
6 71
 
4.4%
5 66
 
4.1%
9 65
 
4.0%
3 62
 
3.8%
4 55
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
C 94
56.0%
L 74
44.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1618
90.6%
Latin 168
 
9.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 680
42.0%
1 358
22.1%
8 96
 
5.9%
2 93
 
5.7%
7 72
 
4.4%
6 71
 
4.4%
5 66
 
4.1%
9 65
 
4.0%
3 62
 
3.8%
4 55
 
3.4%
Latin
ValueCountFrequency (%)
C 94
56.0%
L 74
44.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1786
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 680
38.1%
1 358
20.0%
8 96
 
5.4%
C 94
 
5.3%
2 93
 
5.2%
L 74
 
4.1%
7 72
 
4.0%
6 71
 
4.0%
5 66
 
3.7%
9 65
 
3.6%
Other values (2) 117
 
6.6%

인허가일자
Real number (ℝ)

MISSING 

Distinct75
Distinct (%)80.6%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean20053072
Minimum19980213
Maximum20200410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:12.031890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19980213
5-th percentile19980223
Q120000524
median20030328
Q320100716
95-th percentile20184599
Maximum20200410
Range220197
Interquartile range (IQR)100192

Descriptive statistics

Standard deviation65598.322
Coefficient of variation (CV)0.0032712355
Kurtosis-0.69064626
Mean20053072
Median Absolute Deviation (MAD)49718
Skewness0.69054666
Sum1.8649357 × 109
Variance4.3031399 × 109
MonotonicityNot monotonic
2024-04-16T22:16:12.144657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000703 4
 
4.3%
19980213 3
 
3.2%
20020216 3
 
3.2%
19980327 3
 
3.2%
19980520 2
 
2.1%
20000822 2
 
2.1%
20020404 2
 
2.1%
20001212 2
 
2.1%
19980218 2
 
2.1%
20000425 2
 
2.1%
Other values (65) 68
72.3%
ValueCountFrequency (%)
19980213 3
3.2%
19980218 2
2.1%
19980227 1
 
1.1%
19980327 3
3.2%
19980409 2
2.1%
19980520 2
2.1%
19980610 1
 
1.1%
19990209 1
 
1.1%
19990311 1
 
1.1%
19990518 1
 
1.1%
ValueCountFrequency (%)
20200410 1
1.1%
20200207 1
1.1%
20190826 1
1.1%
20190717 1
1.1%
20190702 1
1.1%
20180531 1
1.1%
20170525 1
1.1%
20161028 1
1.1%
20151023 1
1.1%
20151015 1
1.1%

인허가취소일자
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)85.7%
Missing66
Missing (%)70.2%
Infinite0
Infinite (%)0.0%
Mean20118555
Minimum20020510
Maximum20191028
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:12.248926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20020510
5-th percentile20020517
Q120070864
median20130608
Q320180521
95-th percentile20190980
Maximum20191028
Range170518
Interquartile range (IQR)109656.75

Descriptive statistics

Standard deviation58407.328
Coefficient of variation (CV)0.0029031572
Kurtosis-1.2252964
Mean20118555
Median Absolute Deviation (MAD)49913.5
Skewness-0.28562079
Sum5.6331954 × 108
Variance3.411416 × 109
MonotonicityNot monotonic
2024-04-16T22:16:12.360859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
20180521 4
 
4.3%
20020517 2
 
2.1%
20070115 1
 
1.1%
20050526 1
 
1.1%
20090714 1
 
1.1%
20041111 1
 
1.1%
20131007 1
 
1.1%
20101025 1
 
1.1%
20130306 1
 
1.1%
20080305 1
 
1.1%
Other values (14) 14
 
14.9%
(Missing) 66
70.2%
ValueCountFrequency (%)
20020510 1
1.1%
20020517 2
2.1%
20041111 1
1.1%
20050526 1
1.1%
20060323 1
1.1%
20070115 1
1.1%
20071114 1
1.1%
20080305 1
1.1%
20090714 1
1.1%
20100901 1
1.1%
ValueCountFrequency (%)
20191028 1
 
1.1%
20191011 1
 
1.1%
20190923 1
 
1.1%
20190826 1
 
1.1%
20180521 4
4.3%
20170804 1
 
1.1%
20151102 1
 
1.1%
20150521 1
 
1.1%
20131024 1
 
1.1%
20131007 1
 
1.1%

영업상태구분코드
Categorical

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
1
66 
3
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 66
70.2%
3 28
29.8%

Length

2024-04-16T22:16:12.479104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:12.567214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 66
70.2%
3 28
29.8%

영업상태명
Categorical

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
영업/정상
66 
폐업
28 

Length

Max length5
Median length5
Mean length4.106383
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 66
70.2%
폐업 28
29.8%

Length

2024-04-16T22:16:12.652004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:12.730266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 66
70.2%
폐업 28
29.8%

상세영업상태코드
Categorical

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
1
66 
2
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 66
70.2%
2 28
29.8%

Length

2024-04-16T22:16:12.804673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:12.876887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 66
70.2%
2 28
29.8%

상세영업상태명
Categorical

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
영업
66 
취소정지업체
28 

Length

Max length6
Median length2
Mean length3.1914894
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 66
70.2%
취소정지업체 28
29.8%

Length

2024-04-16T22:16:12.970185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:13.069897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 66
70.2%
취소정지업체 28
29.8%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

소재지전체주소
Text

MISSING 

Distinct80
Distinct (%)96.4%
Missing11
Missing (%)11.7%
Memory size884.0 B
2024-04-16T22:16:13.267287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length37
Mean length24.650602
Min length18

Characters and Unicode

Total characters2046
Distinct characters137
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique77 ?
Unique (%)92.8%

Sample

1st row부산광역시 기장군 철마면 안평리 626번지
2nd row부산광역시 기장군 일광면 신평리 50번지
3rd row부산광역시 기장군 정관읍 달산리 998-12 번지
4th row부산광역시 기장군 기장읍 동부리 354번지
5th row부산광역시 기장군 기장읍 동부리 278-6번지
ValueCountFrequency (%)
부산광역시 81
 
20.6%
기장군 12
 
3.1%
동래구 11
 
2.8%
부산진구 10
 
2.5%
해운대구 10
 
2.5%
기장읍 9
 
2.3%
금정구 8
 
2.0%
연제구 6
 
1.5%
동부리 6
 
1.5%
전포동 4
 
1.0%
Other values (180) 236
60.1%
2024-04-16T22:16:13.615936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
313
 
15.3%
부 106
 
5.2%
산 102
 
5.0%
동 100
 
4.9%
1 95
 
4.6%
광 84
 
4.1%
시 83
 
4.1%
역 82
 
4.0%
구 74
 
3.6%
지 72
 
3.5%
Other values (127) 935
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1254
61.3%
Decimal Number 413
 
20.2%
Space Separator 313
 
15.3%
Dash Punctuation 66
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 106
 
8.5%
산 102
 
8.1%
동 100
 
8.0%
광 84
 
6.7%
시 83
 
6.6%
역 82
 
6.5%
구 74
 
5.9%
지 72
 
5.7%
번 70
 
5.6%
장 25
 
2.0%
Other values (115) 456
36.4%
Decimal Number
ValueCountFrequency (%)
1 95
23.0%
3 53
12.8%
2 45
10.9%
0 40
9.7%
9 38
 
9.2%
4 33
 
8.0%
6 33
 
8.0%
5 29
 
7.0%
7 26
 
6.3%
8 21
 
5.1%
Space Separator
ValueCountFrequency (%)
313
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1254
61.3%
Common 792
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 106
 
8.5%
산 102
 
8.1%
동 100
 
8.0%
광 84
 
6.7%
시 83
 
6.6%
역 82
 
6.5%
구 74
 
5.9%
지 72
 
5.7%
번 70
 
5.6%
장 25
 
2.0%
Other values (115) 456
36.4%
Common
ValueCountFrequency (%)
313
39.5%
1 95
 
12.0%
- 66
 
8.3%
3 53
 
6.7%
2 45
 
5.7%
0 40
 
5.1%
9 38
 
4.8%
4 33
 
4.2%
6 33
 
4.2%
5 29
 
3.7%
Other values (2) 47
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1254
61.3%
ASCII 792
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
313
39.5%
1 95
 
12.0%
- 66
 
8.3%
3 53
 
6.7%
2 45
 
5.7%
0 40
 
5.1%
9 38
 
4.8%
4 33
 
4.2%
6 33
 
4.2%
5 29
 
3.7%
Other values (2) 47
 
5.9%
Hangul
ValueCountFrequency (%)
부 106
 
8.5%
산 102
 
8.1%
동 100
 
8.0%
광 84
 
6.7%
시 83
 
6.6%
역 82
 
6.5%
구 74
 
5.9%
지 72
 
5.7%
번 70
 
5.6%
장 25
 
2.0%
Other values (115) 456
36.4%

도로명전체주소
Text

MISSING 

Distinct69
Distinct (%)94.5%
Missing21
Missing (%)22.3%
Memory size884.0 B
2024-04-16T22:16:13.866442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length43
Mean length30.465753
Min length20

Characters and Unicode

Total characters2224
Distinct characters183
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

Unique65 ?
Unique (%)89.0%

Sample

1st row부산광역시 기장군 철마면 안평로 81
2nd row부산광역시 기장군 일광면 문오성길 485-5
3rd row부산광역시 기장군 기장읍 차성동로 77
4th row부산광역시 기장군 기장읍 반송로 1576
5th row부산광역시 기장군 기장읍 기장대로 515
ValueCountFrequency (%)
부산광역시 72
 
17.5%
동래구 12
 
2.9%
기장군 10
 
2.4%
부산진구 9
 
2.2%
해운대구 8
 
1.9%
금정구 6
 
1.5%
기장읍 6
 
1.5%
연제구 5
 
1.2%
남구 5
 
1.2%
9 4
 
1.0%
Other values (218) 275
66.7%
2024-04-16T22:16:14.270568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
343
 
15.4%
동 98
 
4.4%
산 88
 
4.0%
1 87
 
3.9%
부 86
 
3.9%
시 79
 
3.6%
광 74
 
3.3%
로 72
 
3.2%
역 72
 
3.2%
구 68
 
3.1%
Other values (173) 1157
52.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1326
59.6%
Decimal Number 365
 
16.4%
Space Separator 343
 
15.4%
Close Punctuation 64
 
2.9%
Open Punctuation 64
 
2.9%
Other Punctuation 39
 
1.8%
Dash Punctuation 15
 
0.7%
Uppercase Letter 8
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 98
 
7.4%
산 88
 
6.6%
부 86
 
6.5%
시 79
 
6.0%
광 74
 
5.6%
로 72
 
5.4%
역 72
 
5.4%
구 68
 
5.1%
대 40
 
3.0%
길 28
 
2.1%
Other values (149) 621
46.8%
Decimal Number
ValueCountFrequency (%)
1 87
23.8%
2 66
18.1%
3 45
12.3%
0 34
 
9.3%
5 32
 
8.8%
6 28
 
7.7%
8 25
 
6.8%
7 18
 
4.9%
9 15
 
4.1%
4 15
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
O 1
12.5%
T 1
12.5%
S 1
12.5%
K 1
12.5%
V 1
12.5%
I 1
12.5%
E 1
12.5%
W 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 38
97.4%
/ 1
 
2.6%
Space Separator
ValueCountFrequency (%)
343
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1326
59.6%
Common 890
40.0%
Latin 8
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 98
 
7.4%
산 88
 
6.6%
부 86
 
6.5%
시 79
 
6.0%
광 74
 
5.6%
로 72
 
5.4%
역 72
 
5.4%
구 68
 
5.1%
대 40
 
3.0%
길 28
 
2.1%
Other values (149) 621
46.8%
Common
ValueCountFrequency (%)
343
38.5%
1 87
 
9.8%
2 66
 
7.4%
) 64
 
7.2%
( 64
 
7.2%
3 45
 
5.1%
, 38
 
4.3%
0 34
 
3.8%
5 32
 
3.6%
6 28
 
3.1%
Other values (6) 89
 
10.0%
Latin
ValueCountFrequency (%)
O 1
12.5%
T 1
12.5%
S 1
12.5%
K 1
12.5%
V 1
12.5%
I 1
12.5%
E 1
12.5%
W 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1326
59.6%
ASCII 898
40.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
343
38.2%
1 87
 
9.7%
2 66
 
7.3%
) 64
 
7.1%
( 64
 
7.1%
3 45
 
5.0%
, 38
 
4.2%
0 34
 
3.8%
5 32
 
3.6%
6 28
 
3.1%
Other values (14) 97
 
10.8%
Hangul
ValueCountFrequency (%)
동 98
 
7.4%
산 88
 
6.6%
부 86
 
6.5%
시 79
 
6.0%
광 74
 
5.6%
로 72
 
5.4%
역 72
 
5.4%
구 68
 
5.1%
대 40
 
3.0%
길 28
 
2.1%
Other values (149) 621
46.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)100.0%
Missing86
Missing (%)91.5%
Infinite0
Infinite (%)0.0%
Mean47025.25
Minimum46020
Maximum48567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:14.367873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46020
5-th percentile46035.4
Q146172
median46659.5
Q348011
95-th percentile48373.45
Maximum48567
Range2547
Interquartile range (IQR)1839

Descriptive statistics

Standard deviation1041.2551
Coefficient of variation (CV)0.022142468
Kurtosis-1.8963442
Mean47025.25
Median Absolute Deviation (MAD)617.5
Skewness0.43951629
Sum376202
Variance1084212.2
MonotonicityNot monotonic
2024-04-16T22:16:14.451126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
46020 1
 
1.1%
46064 1
 
1.1%
46208 1
 
1.1%
46215 1
 
1.1%
48010 1
 
1.1%
48014 1
 
1.1%
48567 1
 
1.1%
47104 1
 
1.1%
(Missing) 86
91.5%
ValueCountFrequency (%)
46020 1
1.1%
46064 1
1.1%
46208 1
1.1%
46215 1
1.1%
47104 1
1.1%
48010 1
1.1%
48014 1
1.1%
48567 1
1.1%
ValueCountFrequency (%)
48567 1
1.1%
48014 1
1.1%
48010 1
1.1%
47104 1
1.1%
46215 1
1.1%
46208 1
1.1%
46064 1
1.1%
46020 1
1.1%

사업장명
Text

Distinct85
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-04-16T22:16:14.648594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length6.8297872
Min length3

Characters and Unicode

Total characters642
Distinct characters116
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)80.9%

Sample

1st row부광지질
2nd row그린개발
3rd row제일전기지하수
4th row대지엔지니어링
5th row(주) 원진
ValueCountFrequency (%)
주식회사 8
 
7.6%
제영건설 2
 
1.9%
㈜한국지수종합기술단 2
 
1.9%
한일개발 2
 
1.9%
성한 2
 
1.9%
주)보정지질 2
 
1.9%
㈜성진엔지니어링 2
 
1.9%
주)인기엔지니어링 2
 
1.9%
구구기초개발(주 2
 
1.9%
주)동해이엔지 2
 
1.9%
Other values (79) 79
75.2%
2024-04-16T22:16:14.932116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 49
 
7.6%
지 40
 
6.2%
( 38
 
5.9%
) 38
 
5.9%
기 21
 
3.3%
발 19
 
3.0%
개 19
 
3.0%
엔 15
 
2.3%
㈜ 15
 
2.3%
건 15
 
2.3%
Other values (106) 373
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 535
83.3%
Open Punctuation 38
 
5.9%
Close Punctuation 38
 
5.9%
Other Symbol 15
 
2.3%
Space Separator 11
 
1.7%
Uppercase Letter 5
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 49
 
9.2%
지 40
 
7.5%
기 21
 
3.9%
발 19
 
3.6%
개 19
 
3.6%
엔 15
 
2.8%
건 15
 
2.8%
설 14
 
2.6%
질 12
 
2.2%
한 12
 
2.2%
Other values (98) 319
59.6%
Uppercase Letter
ValueCountFrequency (%)
N 2
40.0%
S 1
20.0%
E 1
20.0%
G 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 38
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 15
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 550
85.7%
Common 87
 
13.6%
Latin 5
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 49
 
8.9%
지 40
 
7.3%
기 21
 
3.8%
발 19
 
3.5%
개 19
 
3.5%
엔 15
 
2.7%
㈜ 15
 
2.7%
건 15
 
2.7%
설 14
 
2.5%
질 12
 
2.2%
Other values (99) 331
60.2%
Latin
ValueCountFrequency (%)
N 2
40.0%
S 1
20.0%
E 1
20.0%
G 1
20.0%
Common
ValueCountFrequency (%)
( 38
43.7%
) 38
43.7%
11
 
12.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 535
83.3%
ASCII 92
 
14.3%
None 15
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 49
 
9.2%
지 40
 
7.5%
기 21
 
3.9%
발 19
 
3.6%
개 19
 
3.6%
엔 15
 
2.8%
건 15
 
2.8%
설 14
 
2.6%
질 12
 
2.2%
한 12
 
2.2%
Other values (98) 319
59.6%
ASCII
ValueCountFrequency (%)
( 38
41.3%
) 38
41.3%
11
 
12.0%
N 2
 
2.2%
S 1
 
1.1%
E 1
 
1.1%
G 1
 
1.1%
None
ValueCountFrequency (%)
㈜ 15
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0144874 × 1013
Minimum2.0030501 × 1013
Maximum2.0210204 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:15.048200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030501 × 1013
5-th percentile2.0031081 × 1013
Q12.0110766 × 1013
median2.0150714 × 1013
Q32.0191024 × 1013
95-th percentile2.0201222 × 1013
Maximum2.0210204 × 1013
Range1.797029 × 1011
Interquartile range (IQR)8.0257505 × 1010

Descriptive statistics

Standard deviation5.2284768 × 1010
Coefficient of variation (CV)0.0025954378
Kurtosis-0.51887399
Mean2.0144874 × 1013
Median Absolute Deviation (MAD)4.0305499 × 1010
Skewness-0.67868507
Sum1.8936182 × 1015
Variance2.7336969 × 1021
MonotonicityNot monotonic
2024-04-16T22:16:15.166169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20150521193315 1
 
1.1%
20191205150722 1
 
1.1%
20160620160922 1
 
1.1%
20190121201619 1
 
1.1%
20181228161321 1
 
1.1%
20191213160656 1
 
1.1%
20040322093211 1
 
1.1%
20031118100918 1
 
1.1%
20140806075711 1
 
1.1%
20111209131908 1
 
1.1%
Other values (84) 84
89.4%
ValueCountFrequency (%)
20030501204848 1
1.1%
20030826170011 1
1.1%
20030826170059 1
1.1%
20030901115342 1
1.1%
20031013121551 1
1.1%
20031118100918 1
1.1%
20040322093211 1
1.1%
20050526161807 1
1.1%
20060530111013 1
1.1%
20080115142055 1
1.1%
ValueCountFrequency (%)
20210204104942 1
1.1%
20210122173232 1
1.1%
20201222091752 1
1.1%
20201222091520 1
1.1%
20201222091423 1
1.1%
20201222091345 1
1.1%
20201222091156 1
1.1%
20201222091021 1
1.1%
20201222090914 1
1.1%
20201222090749 1
1.1%

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
I
66 
U
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI
2nd rowI
3rd rowU
4th rowU
5th rowI

Common Values

ValueCountFrequency (%)
I 66
70.2%
U 28
29.8%

Length

2024-04-16T22:16:15.269694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:15.338984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 66
70.2%
u 28
29.8%

데이터갱신일자
Date

Distinct23
Distinct (%)24.5%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum2018-08-31 23:59:59
Maximum2021-02-06 02:40:00
2024-04-16T22:16:15.411927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T22:16:15.751965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)92.7%
Missing12
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean391100.41
Minimum376575.17
Maximum405522.61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:15.860608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum376575.17
5-th percentile380635.68
Q1388002.49
median390157.01
Q3393870.51
95-th percentile401776.56
Maximum405522.61
Range28947.441
Interquartile range (IQR)5868.0167

Descriptive statistics

Standard deviation6185.2001
Coefficient of variation (CV)0.015814865
Kurtosis-0.15645839
Mean391100.41
Median Absolute Deviation (MAD)2995.0134
Skewness0.21523064
Sum32070234
Variance38256701
MonotonicityNot monotonic
2024-04-16T22:16:15.972892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
401356.353440437 2
 
2.1%
386325.816948305 2
 
2.1%
389966.863065915 2
 
2.1%
402008.259489454 2
 
2.1%
397927.11534005 2
 
2.1%
401235.136344818 2
 
2.1%
383090.133003427 1
 
1.1%
391152.311117305 1
 
1.1%
388216.238301 1
 
1.1%
392557.866618931 1
 
1.1%
Other values (66) 66
70.2%
(Missing) 12
 
12.8%
ValueCountFrequency (%)
376575.17091841 1
1.1%
379390.249503698 1
1.1%
379783.261438689 1
1.1%
380229.573974122 1
1.1%
380608.055712321 1
1.1%
381160.447304173 1
1.1%
381623.542466636 1
1.1%
382729.710345331 1
1.1%
383090.133003427 1
1.1%
384338.981897206 1
1.1%
ValueCountFrequency (%)
405522.61178727 1
1.1%
402239.497616996 1
1.1%
402008.259489454 2
2.1%
401781.266188482 1
1.1%
401687.081587248 1
1.1%
401356.353440437 2
2.1%
401239.929895848 1
1.1%
401235.136344818 2
2.1%
401069.596373 1
1.1%
397927.11534005 2
2.1%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct76
Distinct (%)92.7%
Missing12
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean190160.4
Minimum174035.7
Maximum205505.08
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:16.099187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174035.7
5-th percentile181219.02
Q1186187.32
median190344.37
Q3194658.19
95-th percentile198502.93
Maximum205505.08
Range31469.382
Interquartile range (IQR)8470.8702

Descriptive statistics

Standard deviation6117.1286
Coefficient of variation (CV)0.032168257
Kurtosis0.23004714
Mean190160.4
Median Absolute Deviation (MAD)4313.821
Skewness-0.012908941
Sum15593153
Variance37419263
MonotonicityNot monotonic
2024-04-16T22:16:16.207089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196615.807975201 2
 
2.1%
182210.916727624 2
 
2.1%
192741.089054358 2
 
2.1%
195806.31336872 2
 
2.1%
194658.188974473 2
 
2.1%
196516.101463845 2
 
2.1%
196124.737004344 1
 
1.1%
190989.664323731 1
 
1.1%
190570.380035 1
 
1.1%
182600.072545818 1
 
1.1%
Other values (66) 66
70.2%
(Missing) 12
 
12.8%
ValueCountFrequency (%)
174035.700224564 1
1.1%
175923.048331794 1
1.1%
178679.952219194 1
1.1%
179513.398799893 1
1.1%
181175.128579342 1
1.1%
182052.86738669 1
1.1%
182068.435002445 1
1.1%
182210.916727624 2
2.1%
182317.844107833 1
1.1%
182600.072545818 1
1.1%
ValueCountFrequency (%)
205505.082586346 1
1.1%
205416.175829 1
1.1%
202095.800730316 1
1.1%
201677.693320986 1
1.1%
198541.642657595 1
1.1%
197767.407602977 1
1.1%
196615.807975201 2
2.1%
196579.853585804 1
1.1%
196516.101463845 2
2.1%
196326.916943077 1
1.1%

전문인력총수
Real number (ℝ)

MISSING  ZEROS 

Distinct10
Distinct (%)11.4%
Missing6
Missing (%)6.4%
Infinite0
Infinite (%)0.0%
Mean1.8295455
Minimum0
Maximum9
Zeros27
Zeros (%)28.7%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:16.310438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile5.65
Maximum9
Range9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8081653
Coefficient of variation (CV)0.98831397
Kurtosis4.1582567
Mean1.8295455
Median Absolute Deviation (MAD)0
Skewness1.7048081
Sum161
Variance3.2694619
MonotonicityNot monotonic
2024-04-16T22:16:16.408159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2 45
47.9%
0 27
28.7%
3 5
 
5.3%
4 3
 
3.2%
1 2
 
2.1%
7 2
 
2.1%
8 1
 
1.1%
9 1
 
1.1%
6 1
 
1.1%
5 1
 
1.1%
(Missing) 6
 
6.4%
ValueCountFrequency (%)
0 27
28.7%
1 2
 
2.1%
2 45
47.9%
3 5
 
5.3%
4 3
 
3.2%
5 1
 
1.1%
6 1
 
1.1%
7 2
 
2.1%
8 1
 
1.1%
9 1
 
1.1%
ValueCountFrequency (%)
9 1
 
1.1%
8 1
 
1.1%
7 2
 
2.1%
6 1
 
1.1%
5 1
 
1.1%
4 3
 
3.2%
3 5
 
5.3%
2 45
47.9%
1 2
 
2.1%
0 27
28.7%

자본금
Real number (ℝ)

MISSING  ZEROS 

Distinct55
Distinct (%)61.1%
Missing4
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean4.0395416 × 108
Minimum0
Maximum1.6571115 × 1010
Zeros3
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-04-16T22:16:16.546102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30521464
Q150000000
median1 × 108
Q32.05 × 108
95-th percentile9.775 × 108
Maximum1.6571115 × 1010
Range1.6571115 × 1010
Interquartile range (IQR)1.55 × 108

Descriptive statistics

Standard deviation1.7629179 × 109
Coefficient of variation (CV)4.3641533
Kurtosis81.949045
Mean4.0395416 × 108
Median Absolute Deviation (MAD)60722500
Skewness8.8865631
Sum3.6355874 × 1010
Variance3.1078795 × 1018
MonotonicityNot monotonic
2024-04-16T22:16:16.672475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50000000 14
 
14.9%
100000000 10
 
10.6%
200000000 5
 
5.3%
205000000 3
 
3.2%
400000000 3
 
3.2%
0 3
 
3.2%
410000000 2
 
2.1%
55000000 2
 
2.1%
250000000 2
 
2.1%
33500000 1
 
1.1%
Other values (45) 45
47.9%
(Missing) 4
 
4.3%
ValueCountFrequency (%)
0 3
3.2%
30000000 1
 
1.1%
30129935 1
 
1.1%
31000000 1
 
1.1%
31600000 1
 
1.1%
31835000 1
 
1.1%
32760000 1
 
1.1%
33500000 1
 
1.1%
33706817 1
 
1.1%
34281000 1
 
1.1%
ValueCountFrequency (%)
16571115000 1
1.1%
2700000000 1
1.1%
1295240000 1
1.1%
1200000000 1
1.1%
1000000000 1
1.1%
950000000 1
1.1%
800000000 1
1.1%
750000000 1
1.1%
610000000 1
1.1%
602000000 1
1.1%

시설장비
Text

MISSING 

Distinct47
Distinct (%)72.3%
Missing29
Missing (%)30.9%
Memory size884.0 B
2024-04-16T22:16:16.869264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length177
Median length40
Mean length20.246154
Min length4

Characters and Unicode

Total characters1316
Distinct characters133
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)61.5%

Sample

1st row1. 시추기 1
2nd row1. 착정기 1 2. 콤푸레사 1
3rd row1. 시추기 1, 2. 콤플레샤 1
4th row형식WC-0055 * 등록번호 부산22-1258
5th row1. 시추기 1 2. 기타장비
ValueCountFrequency (%)
1 63
21.6%
시추기 31
 
10.6%
1대 16
 
5.5%
2 16
 
5.5%
15
 
5.1%
공기압축기 8
 
2.7%
임대 4
 
1.4%
1개 4
 
1.4%
시추기(임대 3
 
1.0%
콤프레샤 3
 
1.0%
Other values (102) 129
44.2%
2024-04-16T22:16:17.210072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
189
 
14.4%
1 124
 
9.4%
기 113
 
8.6%
. 55
 
4.2%
시 52
 
4.0%
추 52
 
4.0%
0 52
 
4.0%
대 45
 
3.4%
42
 
3.2%
2 42
 
3.2%
Other values (123) 550
41.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 549
41.7%
Decimal Number 277
21.0%
Space Separator 189
 
14.4%
Other Punctuation 90
 
6.8%
Uppercase Letter 60
 
4.6%
Control 42
 
3.2%
Lowercase Letter 38
 
2.9%
Dash Punctuation 24
 
1.8%
Open Punctuation 23
 
1.7%
Close Punctuation 22
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 113
20.6%
시 52
 
9.5%
추 52
 
9.5%
대 45
 
8.2%
공 25
 
4.6%
축 19
 
3.5%
압 19
 
3.5%
착 14
 
2.6%
정 12
 
2.2%
임 12
 
2.2%
Other values (67) 186
33.9%
Uppercase Letter
ValueCountFrequency (%)
T 7
 
11.7%
S 5
 
8.3%
R 4
 
6.7%
A 4
 
6.7%
B 4
 
6.7%
H 4
 
6.7%
W 4
 
6.7%
G 3
 
5.0%
C 3
 
5.0%
M 3
 
5.0%
Other values (12) 19
31.7%
Lowercase Letter
ValueCountFrequency (%)
m 14
36.8%
n 5
 
13.2%
l 4
 
10.5%
o 2
 
5.3%
d 2
 
5.3%
g 2
 
5.3%
e 2
 
5.3%
r 2
 
5.3%
s 2
 
5.3%
a 2
 
5.3%
Decimal Number
ValueCountFrequency (%)
1 124
44.8%
0 52
18.8%
2 42
 
15.2%
5 14
 
5.1%
3 13
 
4.7%
8 11
 
4.0%
6 8
 
2.9%
4 6
 
2.2%
7 4
 
1.4%
9 3
 
1.1%
Other Punctuation
ValueCountFrequency (%)
. 55
61.1%
, 16
 
17.8%
: 13
 
14.4%
/ 3
 
3.3%
？ 2
 
2.2%
* 1
 
1.1%
Other Symbol
ValueCountFrequency (%)
㎥ 1
50.0%
○ 1
50.0%
Space Separator
ValueCountFrequency (%)
189
100.0%
Control
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 669
50.8%
Hangul 549
41.7%
Latin 98
 
7.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 113
20.6%
시 52
 
9.5%
추 52
 
9.5%
대 45
 
8.2%
공 25
 
4.6%
축 19
 
3.5%
압 19
 
3.5%
착 14
 
2.6%
정 12
 
2.2%
임 12
 
2.2%
Other values (67) 186
33.9%
Latin
ValueCountFrequency (%)
m 14
 
14.3%
T 7
 
7.1%
n 5
 
5.1%
S 5
 
5.1%
l 4
 
4.1%
R 4
 
4.1%
A 4
 
4.1%
B 4
 
4.1%
H 4
 
4.1%
W 4
 
4.1%
Other values (23) 43
43.9%
Common
ValueCountFrequency (%)
189
28.3%
1 124
18.5%
. 55
 
8.2%
0 52
 
7.8%
42
 
6.3%
2 42
 
6.3%
- 24
 
3.6%
( 23
 
3.4%
) 22
 
3.3%
, 16
 
2.4%
Other values (13) 80
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 763
58.0%
Hangul 549
41.7%
None 2
 
0.2%
CJK Compat 1
 
0.1%
Geometric Shapes 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
189
24.8%
1 124
16.3%
. 55
 
7.2%
0 52
 
6.8%
42
 
5.5%
2 42
 
5.5%
- 24
 
3.1%
( 23
 
3.0%
) 22
 
2.9%
, 16
 
2.1%
Other values (43) 174
22.8%
Hangul
ValueCountFrequency (%)
기 113
20.6%
시 52
 
9.5%
추 52
 
9.5%
대 45
 
8.2%
공 25
 
4.6%
축 19
 
3.5%
압 19
 
3.5%
착 14
 
2.6%
정 12
 
2.2%
임 12
 
2.2%
Other values (67) 186
33.9%
None
ValueCountFrequency (%)
？ 2
100.0%
CJK Compat
ValueCountFrequency (%)
㎥ 1
100.0%
Geometric Shapes
ValueCountFrequency (%)
○ 1
100.0%

타기관이전여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
0
88 
1
 
6

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 88
93.6%
1 6
 
6.4%

Length

2024-04-16T22:16:17.320576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T22:16:17.391399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 88
93.6%
1 6
 
6.4%

Unnamed: 32
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing94
Missing (%)100.0%
Memory size978.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)전문인력총수자본금시설장비타기관이전여부Unnamed: 32
01지하수시공업체09_29_01_P3400000C00621175179300000020100507201505213폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 철마면 안평리 626번지부산광역시 기장군 철마면 안평로 81<NA>부광지질20150521193315I2018-08-31 23:59:59.0<NA>397927.11534194658.188974231600000<NA>0<NA>
12지하수시공업체09_29_01_P3400000C006205202899912L0020001212201511023폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 일광면 신평리 50번지부산광역시 기장군 일광면 문오성길 485-5<NA>그린개발20151102170706I2018-08-31 23:59:59.0<NA>405522.611787202095.80073062865532<NA>0<NA>
23지하수시공업체09_29_01_P3400000C006104221902329L0020001212201910283폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 정관읍 달산리 998-12 번지<NA><NA>제일전기지하수20191028150652U2019-10-30 02:40:00.0<NA><NA><NA>0318350001. 시추기 10<NA>
34지하수시공업체09_29_01_P3400000C004705231117811L0019980409201909233폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 동부리 354번지<NA><NA>대지엔지니어링20190924093352U2019-09-26 02:40:00.0<NA>401239.929896196579.85358601056779751. 착정기 1 2. 콤푸레사 10<NA>
45지하수시공업체09_29_01_P3400000C001845110008620L0019990209201805213폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 동부리 278-6번지부산광역시 기장군 기장읍 차성동로 77<NA>(주) 원진20180521155334I2018-08-31 23:59:59.0<NA>401687.081587196175.18423602000000001. 시추기 1, 2. 콤플레샤 10<NA>
56지하수시공업체09_29_01_P3400000C001801111055169L0020161028201910113폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 반송로 1576<NA>(주)보정지질20191011170851U2019-10-13 02:40:00.0<NA>401235.136345196516.101464263930825형식WC-0055 * 등록번호 부산22-12580<NA>
67지하수시공업체09_29_01_P3400000C001801110315697L0020000322201805213폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 동부리 348-2번지<NA><NA>(주)동성기초건설20180521155302I2018-08-31 23:59:59.0<NA>401356.35344196615.80797501000000001. 시추기 1 2. 기타장비0<NA>
78지하수시공업체09_29_01_P3400000C001801110231794L0019980213201908263폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 청강리 61-10번지부산광역시 기장군 기장읍 기장대로 515<NA>(주)삼우토건20190826171505U2019-08-28 02:40:00.0<NA>402008.259489195806.3133690120000000<NA>0<NA>
89지하수시공업체09_29_01_P3400000C001801110206870L0020020404201805213폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 동부리 348-2번지<NA><NA>(주)보정지질20180521155227I2018-08-31 23:59:59.0<NA>401356.35344196615.807975<NA>640424871. 시추기 2 2. 에어콤푸레샤 10<NA>
910지하수시공업체09_29_01_P3400000C001613110004645L0020020404201805213폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>부산광역시 기장군 기장읍 동부리 92번지<NA><NA>(주)경성기공20180521155319I2018-08-31 23:59:59.0<NA>402239.497617196326.91694301192146901. 착정기(시추기) 2, 2. 기타장비0<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)전문인력총수자본금시설장비타기관이전여부Unnamed: 32
8485지하수시공업체09_29_01_P3290000C001942110010596L0019980327<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 부산진구 부전동 394-34 파크빌라 101호<NA><NA>(주)하나기초콘설탄트20201222091156U2020-12-24 02:40:00.0<NA>387338.543319186622.37270106100000001. 시추기 1 2. 콤푸레사 10<NA>
8586지하수시공업체09_29_01_P3290000C001801110646399L0020090723<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 부산진구 전포동 194-27 남경빌딩 602호부산광역시 부산진구 전포대로 242 (전포동,남경빌딩 602호)<NA>(주)신우하이텍20201222091021U2020-12-24 02:40:00.0<NA>388153.884601186287.1974162250000000시추기(착정기) YBB180 : 1대 콤프레샤 Ingersoll Rand 825 :1대0<NA>
8687지하수시공업체09_29_01_P3290000C001801110300036L0020000703<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 부산진구 양정동 150-3 롯데골드로즈 1310호부산광역시 부산진구 중앙대로 993, 1310호 (양정동,롯데골드로즈)<NA>구구기초개발㈜20201221181447U2020-12-23 02:40:00.0<NA>388926.255489188502.470592<NA>8000000001. 시추기 10<NA>
8788지하수시공업체09_29_01_P3290000C001801110163202L0019980327<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 부산진구 부전동 350-74<NA><NA>만호기초개발(주)20201222091423U2020-12-24 02:40:00.0<NA><NA><NA>02500000001. 천공기(시추기) 1, 2. 콤푸레샤 10<NA>
8889지하수시공업체09_29_01_P3290000C001801110091271L0019980218<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 부산진구 범천동 839-32 신부산빌딩 9층부산광역시 부산진구 자유평화로3번길 14-21 (범천동,신부산빌딩 9층)<NA>㈜동남기초20201222091520U2020-12-24 02:40:00.0<NA>387840.784137184510.66975766000000001. 시추기0<NA>
8990지하수시공업체09_29_01_P3280000C00540715110632000020110308<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 영도구 청학동 457-51번지 4통2반부산광역시 영도구 청학남로 18-8 (청학동)<NA>이상암20110308180059I2018-08-31 23:59:59.0<NA>387739.294973178679.95221900<NA>0<NA>
9091지하수시공업체09_29_01_P3280000C00440511110631100020110307<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 영도구 동삼동 973-9번지 6통4반부산광역시 영도구 태종로802번길 43-14 (동삼동)<NA>장정성20110307164119I2018-08-31 23:59:59.0<NA>389512.413485175923.04833200<NA>0<NA>
9192지하수시공업체09_29_01_P3270000C001801110315837L0020000425<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 동구 초량동 135-48번지<NA><NA>㈜성진엔지니어링20150907130914I2018-08-31 23:59:59.0<NA>385872.188077182068.4350025100000000<NA>0<NA>
9293지하수시공업체09_29_01_P3270000C001801110221232L0019980213<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 동구 초량동 1161-9번지부산광역시 동구 중앙대로286번길 9 (초량동)<NA>(주)동진기초20200210114804U2020-02-12 02:40:00.0<NA>386325.816948182210.9167280500000001. 시추기 10<NA>
9394지하수시공업체09_29_01_P3270000C001801102221232L0019980213<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 동구 초량동 1161-9번지부산광역시 동구 중앙대로286번길 9 (초량동)<NA>㈜동진기초20030501204848I2018-08-31 23:59:59.0<NA>386325.816948182210.9167280500000001. 시추기 10<NA>