Overview

Dataset statistics

Number of variables33
Number of observations21
Missing cells215
Missing cells (%)31.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory292.3 B

Variable types

Numeric8
Categorical10
Text5
Unsupported9
DateTime1

Dataset

Description2021-05-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123147

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
자본금 has constant value ""Constant
타기관이전여부 has constant value ""Constant
인허가취소일자 is highly imbalanced (53.3%)Imbalance
폐업일자 has 21 (100.0%) missing valuesMissing
휴업시작일자 has 21 (100.0%) missing valuesMissing
휴업종료일자 has 21 (100.0%) missing valuesMissing
재개업일자 has 21 (100.0%) missing valuesMissing
소재지전화 has 21 (100.0%) missing valuesMissing
소재지면적 has 21 (100.0%) missing valuesMissing
소재지우편번호 has 21 (100.0%) missing valuesMissing
소재지전체주소 has 2 (9.5%) missing valuesMissing
도로명전체주소 has 3 (14.3%) missing valuesMissing
도로명우편번호 has 15 (71.4%) missing valuesMissing
업태구분명 has 21 (100.0%) missing valuesMissing
좌표정보(x) has 1 (4.8%) missing valuesMissing
좌표정보(y) has 1 (4.8%) missing valuesMissing
전문인력총수 has 1 (4.8%) missing valuesMissing
시설장비 has 3 (14.3%) missing valuesMissing
Unnamed: 32 has 21 (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 2 (9.5%) zerosZeros

Reproduction

Analysis started2024-04-16 17:17:59.015334
Analysis finished2024-04-16 17:17:59.374582
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11
Minimum1
Maximum21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:17:59.432885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q16
median11
Q316
95-th percentile20
Maximum21
Range20
Interquartile range (IQR)10

Descriptive statistics

Standard deviation6.2048368
Coefficient of variation (CV)0.56407607
Kurtosis-1.2
Mean11
Median Absolute Deviation (MAD)5
Skewness0
Sum231
Variance38.5
MonotonicityStrictly increasing
2024-04-17T02:17:59.551557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
1 1
 
4.8%
2 1
 
4.8%
21 1
 
4.8%
20 1
 
4.8%
19 1
 
4.8%
18 1
 
4.8%
17 1
 
4.8%
16 1
 
4.8%
15 1
 
4.8%
14 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
1 1
4.8%
2 1
4.8%
3 1
4.8%
4 1
4.8%
5 1
4.8%
6 1
4.8%
7 1
4.8%
8 1
4.8%
9 1
4.8%
10 1
4.8%
ValueCountFrequency (%)
21 1
4.8%
20 1
4.8%
19 1
4.8%
18 1
4.8%
17 1
4.8%
16 1
4.8%
15 1
4.8%
14 1
4.8%
13 1
4.8%
12 1
4.8%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
지하수영향조사기관
21 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
지하수영향조사기관 21
100.0%

Length

2024-04-17T02:17:59.921798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:17:59.998346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하수영향조사기관 21
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
09_29_02_P
21 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_29_02_P
2nd row09_29_02_P
3rd row09_29_02_P
4th row09_29_02_P
5th row09_29_02_P

Common Values

ValueCountFrequency (%)
09_29_02_P 21
100.0%

Length

2024-04-17T02:18:00.093409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:00.176925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_29_02_p 21
100.0%

개방자치단체코드
Real number (ℝ)

Distinct9
Distinct (%)42.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3332381
Minimum3270000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:18:00.256448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3270000
5-th percentile3290000
Q13300000
median3330000
Q33350000
95-th percentile3370000
Maximum3400000
Range130000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation33749.78
Coefficient of variation (CV)0.010127828
Kurtosis-0.67304086
Mean3332381
Median Absolute Deviation (MAD)30000
Skewness0.048870171
Sum69980000
Variance1.1390476 × 109
MonotonicityNot monotonic
2024-04-17T02:18:00.354849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
3330000 4
19.0%
3350000 4
19.0%
3370000 4
19.0%
3300000 3
14.3%
3290000 2
9.5%
3270000 1
 
4.8%
3310000 1
 
4.8%
3320000 1
 
4.8%
3400000 1
 
4.8%
ValueCountFrequency (%)
3270000 1
 
4.8%
3290000 2
9.5%
3300000 3
14.3%
3310000 1
 
4.8%
3320000 1
 
4.8%
3330000 4
19.0%
3350000 4
19.0%
3370000 4
19.0%
3400000 1
 
4.8%
ValueCountFrequency (%)
3400000 1
 
4.8%
3370000 4
19.0%
3350000 4
19.0%
3330000 4
19.0%
3320000 1
 
4.8%
3310000 1
 
4.8%
3300000 3
14.3%
3290000 2
9.5%
3270000 1
 
4.8%

관리번호
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-17T02:18:00.515499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters399
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

Unique19 ?
Unique (%)90.5%

Sample

1st rowS001801110315837L00
2nd rowS001801110091271L00
3rd rowS001801110646390L00
4th rowS001801110746967L00
5th rowS006052076701000000
ValueCountFrequency (%)
s001955110078414l00 2
 
9.5%
s001801110315837l00 1
 
4.8%
s001801110749979l00 1
 
4.8%
s001801110422541l00 1
 
4.8%
s001801110398370l00 1
 
4.8%
s001801110171916l00 1
 
4.8%
s001801110716803l00 1
 
4.8%
s001801110482678l00 1
 
4.8%
s001801110762989l00 1
 
4.8%
s006172247407000000 1
 
4.8%
Other values (10) 10
47.6%
2024-04-17T02:18:00.794063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 152
38.1%
1 85
21.3%
8 26
 
6.5%
7 22
 
5.5%
S 21
 
5.3%
L 17
 
4.3%
4 16
 
4.0%
9 15
 
3.8%
6 14
 
3.5%
2 12
 
3.0%
Other values (2) 19
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 361
90.5%
Uppercase Letter 38
 
9.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 152
42.1%
1 85
23.5%
8 26
 
7.2%
7 22
 
6.1%
4 16
 
4.4%
9 15
 
4.2%
6 14
 
3.9%
2 12
 
3.3%
3 10
 
2.8%
5 9
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
S 21
55.3%
L 17
44.7%

Most occurring scripts

ValueCountFrequency (%)
Common 361
90.5%
Latin 38
 
9.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 152
42.1%
1 85
23.5%
8 26
 
7.2%
7 22
 
6.1%
4 16
 
4.4%
9 15
 
4.2%
6 14
 
3.9%
2 12
 
3.3%
3 10
 
2.8%
5 9
 
2.5%
Latin
ValueCountFrequency (%)
S 21
55.3%
L 17
44.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 399
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 152
38.1%
1 85
21.3%
8 26
 
6.5%
7 22
 
5.5%
S 21
 
5.3%
L 17
 
4.3%
4 16
 
4.0%
9 15
 
3.8%
6 14
 
3.5%
2 12
 
3.0%
Other values (2) 19
 
4.8%

인허가일자
Real number (ℝ)

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20098362
Minimum19971217
Maximum20210304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:18:00.907185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19971217
5-th percentile19980218
Q120060914
median20110713
Q320130501
95-th percentile20210222
Maximum20210304
Range239087
Interquartile range (IQR)69587

Descriptive statistics

Standard deviation66974.278
Coefficient of variation (CV)0.0033323252
Kurtosis-0.39702993
Mean20098362
Median Absolute Deviation (MAD)49799
Skewness-0.073745806
Sum4.220656 × 108
Variance4.4855539 × 109
MonotonicityNot monotonic
2024-04-17T02:18:01.011899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
20161107 2
 
9.5%
20080111 1
 
4.8%
20190527 1
 
4.8%
20080613 1
 
4.8%
20061026 1
 
4.8%
20020909 1
 
4.8%
19980218 1
 
4.8%
20120228 1
 
4.8%
20110713 1
 
4.8%
20120704 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
19971217 1
4.8%
19980218 1
4.8%
20020909 1
4.8%
20050629 1
4.8%
20051209 1
4.8%
20060914 1
4.8%
20061026 1
4.8%
20061101 1
4.8%
20080111 1
4.8%
20080613 1
4.8%
ValueCountFrequency (%)
20210304 1
4.8%
20210222 1
4.8%
20190527 1
4.8%
20161107 2
9.5%
20130501 1
4.8%
20121024 1
4.8%
20120704 1
4.8%
20120228 1
4.8%
20111220 1
4.8%
20110713 1
4.8%

인허가취소일자
Categorical

IMBALANCE 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
<NA>
17 
20100701
 
1
20080306
 
1
20130704
 
1
20131114
 
1

Length

Max length8
Median length4
Mean length4.7619048
Min length4

Unique

Unique4 ?
Unique (%)19.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 17
81.0%
20100701 1
 
4.8%
20080306 1
 
4.8%
20130704 1
 
4.8%
20131114 1
 
4.8%

Length

2024-04-17T02:18:01.132825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:01.244786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
81.0%
20100701 1
 
4.8%
20080306 1
 
4.8%
20130704 1
 
4.8%
20131114 1
 
4.8%

영업상태구분코드
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
1
17 
3
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 17
81.0%
3 4
 
19.0%

Length

2024-04-17T02:18:01.344675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:01.433562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
81.0%
3 4
 
19.0%

영업상태명
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
영업/정상
17 
폐업
4 

Length

Max length5
Median length5
Mean length4.4285714
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 17
81.0%
폐업 4
 
19.0%

Length

2024-04-17T02:18:01.537371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:01.629964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 17
81.0%
폐업 4
 
19.0%

상세영업상태코드
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
1
17 
2
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 17
81.0%
2 4
 
19.0%

Length

2024-04-17T02:18:01.715613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:01.800926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 17
81.0%
2 4
 
19.0%

상세영업상태명
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
영업
17 
취소정지업체
4 

Length

Max length6
Median length2
Mean length2.7619048
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 17
81.0%
취소정지업체 4
 
19.0%

Length

2024-04-17T02:18:01.912134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:02.012828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 17
81.0%
취소정지업체 4
 
19.0%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

소재지전체주소
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing2
Missing (%)9.5%
Memory size300.0 B
2024-04-17T02:18:02.186648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length29
Mean length25.842105
Min length17

Characters and Unicode

Total characters491
Distinct characters75
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

Unique19 ?
Unique (%)100.0%

Sample

1st row부산광역시 동구 초량동 135-48 금정빌딩 2층
2nd row부산광역시 부산진구 범천동 839-32번지 신부산빌딩 9층
3rd row부산광역시 부산진구 전포동 194-27 남경빌딩 5층
4th row부산광역시 동래구 안락동 248 3층
5th row부산광역시 동래구 사직동 99-5번지
ValueCountFrequency (%)
부산광역시 19
 
19.6%
금정구 4
 
4.1%
장전동 3
 
3.1%
연제구 3
 
3.1%
동래구 3
 
3.1%
해운대구 3
 
3.1%
연산동 2
 
2.1%
부산대학교 2
 
2.1%
안락동 2
 
2.1%
4층 2
 
2.1%
Other values (51) 54
55.7%
2024-04-17T02:18:02.507373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
15.9%
산 26
 
5.3%
부 25
 
5.1%
동 23
 
4.7%
광 19
 
3.9%
역 19
 
3.9%
시 19
 
3.9%
구 19
 
3.9%
- 16
 
3.3%
1 15
 
3.1%
Other values (65) 232
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 302
61.5%
Decimal Number 95
 
19.3%
Space Separator 78
 
15.9%
Dash Punctuation 16
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 26
 
8.6%
부 25
 
8.3%
동 23
 
7.6%
광 19
 
6.3%
역 19
 
6.3%
시 19
 
6.3%
구 19
 
6.3%
지 12
 
4.0%
번 12
 
4.0%
대 8
 
2.6%
Other values (53) 120
39.7%
Decimal Number
ValueCountFrequency (%)
1 15
15.8%
4 14
14.7%
9 14
14.7%
2 11
11.6%
8 10
10.5%
3 9
9.5%
0 7
7.4%
5 6
 
6.3%
7 5
 
5.3%
6 4
 
4.2%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
61.5%
Common 189
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 26
 
8.6%
부 25
 
8.3%
동 23
 
7.6%
광 19
 
6.3%
역 19
 
6.3%
시 19
 
6.3%
구 19
 
6.3%
지 12
 
4.0%
번 12
 
4.0%
대 8
 
2.6%
Other values (53) 120
39.7%
Common
ValueCountFrequency (%)
78
41.3%
- 16
 
8.5%
1 15
 
7.9%
4 14
 
7.4%
9 14
 
7.4%
2 11
 
5.8%
8 10
 
5.3%
3 9
 
4.8%
0 7
 
3.7%
5 6
 
3.2%
Other values (2) 9
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 302
61.5%
ASCII 189
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
41.3%
- 16
 
8.5%
1 15
 
7.9%
4 14
 
7.4%
9 14
 
7.4%
2 11
 
5.8%
8 10
 
5.3%
3 9
 
4.8%
0 7
 
3.7%
5 6
 
3.2%
Other values (2) 9
 
4.8%
Hangul
ValueCountFrequency (%)
산 26
 
8.6%
부 25
 
8.3%
동 23
 
7.6%
광 19
 
6.3%
역 19
 
6.3%
시 19
 
6.3%
구 19
 
6.3%
지 12
 
4.0%
번 12
 
4.0%
대 8
 
2.6%
Other values (53) 120
39.7%

도로명전체주소
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing3
Missing (%)14.3%
Memory size300.0 B
2024-04-17T02:18:02.727891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length33.5
Mean length30.611111
Min length22

Characters and Unicode

Total characters551
Distinct characters91
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row부산광역시 부산진구 자유평화로3번길 14-21 (범천동,신부산빌딩 9층)
2nd row부산광역시 부산진구 전포대로 242 (전포동,남경빌딩 5층)
3rd row부산광역시 동래구 충렬대로 432 (안락동)
4th row부산광역시 동래구 아시아드대로133번길 17 (사직동)
5th row부산광역시 남구 용소로 45 (대연동,부경대학교)
ValueCountFrequency (%)
부산광역시 18
 
17.6%
연제구 4
 
3.9%
재송동 3
 
2.9%
금정구 3
 
2.9%
해운대구 3
 
2.9%
동래구 3
 
2.9%
연산동 3
 
2.9%
장전동 2
 
2.0%
안락동 2
 
2.0%
4층 2
 
2.0%
Other values (58) 59
57.8%
2024-04-17T02:18:03.066015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
84
 
15.2%
산 27
 
4.9%
부 24
 
4.4%
동 22
 
4.0%
시 19
 
3.4%
역 18
 
3.3%
광 18
 
3.3%
구 18
 
3.3%
로 18
 
3.3%
) 17
 
3.1%
Other values (81) 286
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 342
62.1%
Space Separator 84
 
15.2%
Decimal Number 77
 
14.0%
Close Punctuation 17
 
3.1%
Open Punctuation 17
 
3.1%
Other Punctuation 11
 
2.0%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 27
 
7.9%
부 24
 
7.0%
동 22
 
6.4%
시 19
 
5.6%
역 18
 
5.3%
광 18
 
5.3%
구 18
 
5.3%
로 18
 
5.3%
대 13
 
3.8%
연 9
 
2.6%
Other values (66) 156
45.6%
Decimal Number
ValueCountFrequency (%)
1 15
19.5%
2 12
15.6%
3 10
13.0%
4 9
11.7%
7 7
9.1%
6 6
 
7.8%
8 6
 
7.8%
9 5
 
6.5%
5 4
 
5.2%
0 3
 
3.9%
Space Separator
ValueCountFrequency (%)
84
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 342
62.1%
Common 209
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 27
 
7.9%
부 24
 
7.0%
동 22
 
6.4%
시 19
 
5.6%
역 18
 
5.3%
광 18
 
5.3%
구 18
 
5.3%
로 18
 
5.3%
대 13
 
3.8%
연 9
 
2.6%
Other values (66) 156
45.6%
Common
ValueCountFrequency (%)
84
40.2%
) 17
 
8.1%
( 17
 
8.1%
1 15
 
7.2%
2 12
 
5.7%
, 11
 
5.3%
3 10
 
4.8%
4 9
 
4.3%
7 7
 
3.3%
6 6
 
2.9%
Other values (5) 21
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 342
62.1%
ASCII 209
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
84
40.2%
) 17
 
8.1%
( 17
 
8.1%
1 15
 
7.2%
2 12
 
5.7%
, 11
 
5.3%
3 10
 
4.8%
4 9
 
4.3%
7 7
 
3.3%
6 6
 
2.9%
Other values (5) 21
 
10.0%
Hangul
ValueCountFrequency (%)
산 27
 
7.9%
부 24
 
7.0%
동 22
 
6.4%
시 19
 
5.6%
역 18
 
5.3%
광 18
 
5.3%
구 18
 
5.3%
로 18
 
5.3%
대 13
 
3.8%
연 9
 
2.6%
Other values (66) 156
45.6%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing15
Missing (%)71.4%
Infinite0
Infinite (%)0.0%
Mean47278.333
Minimum46208
Maximum48059
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:18:03.167882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46208
5-th percentile46216.25
Q146557.25
median47552
Q347943
95-th percentile48058.75
Maximum48059
Range1851
Interquartile range (IQR)1385.75

Descriptive statistics

Standard deviation847.70435
Coefficient of variation (CV)0.017930081
Kurtosis-1.8791146
Mean47278.333
Median Absolute Deviation (MAD)506.5
Skewness-0.66398122
Sum283670
Variance718602.67
MonotonicityNot monotonic
2024-04-17T02:18:03.263850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
48059 1
 
4.8%
48058 1
 
4.8%
46241 1
 
4.8%
46208 1
 
4.8%
47506 1
 
4.8%
47598 1
 
4.8%
(Missing) 15
71.4%
ValueCountFrequency (%)
46208 1
4.8%
46241 1
4.8%
47506 1
4.8%
47598 1
4.8%
48058 1
4.8%
48059 1
4.8%
ValueCountFrequency (%)
48059 1
4.8%
48058 1
4.8%
47598 1
4.8%
47506 1
4.8%
46241 1
4.8%
46208 1
4.8%

사업장명
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-04-17T02:18:03.452696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length10
Mean length7.7619048
Min length5

Characters and Unicode

Total characters163
Distinct characters64
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row㈜성진엔지니어링
2nd row㈜동남기초
3rd row(주)신우하이텍
4th row(주)지오뱅크
5th row기술사사무소지오엠
ValueCountFrequency (%)
주)동해이엔지 2
 
8.3%
주식회사 2
 
8.3%
주)신우하이텍 1
 
4.2%
주)지오뱅크 1
 
4.2%
동방이엔지 1
 
4.2%
주)지아이 1
 
4.2%
무풍건설주식회사 1
 
4.2%
주)지오넷 1
 
4.2%
주)인산 1
 
4.2%
주)청출어람 1
 
4.2%
Other values (12) 12
50.0%
2024-04-17T02:18:03.750008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 15
 
9.2%
주 15
 
9.2%
( 11
 
6.7%
) 11
 
6.7%
이 7
 
4.3%
엔 6
 
3.7%
사 6
 
3.7%
오 6
 
3.7%
동 4
 
2.5%
회 4
 
2.5%
Other values (54) 78
47.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 136
83.4%
Open Punctuation 11
 
6.7%
Close Punctuation 11
 
6.7%
Space Separator 3
 
1.8%
Other Symbol 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 15
 
11.0%
주 15
 
11.0%
이 7
 
5.1%
엔 6
 
4.4%
사 6
 
4.4%
오 6
 
4.4%
동 4
 
2.9%
회 4
 
2.9%
식 4
 
2.9%
텍 3
 
2.2%
Other values (50) 66
48.5%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 138
84.7%
Common 25
 
15.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 15
 
10.9%
주 15
 
10.9%
이 7
 
5.1%
엔 6
 
4.3%
사 6
 
4.3%
오 6
 
4.3%
동 4
 
2.9%
회 4
 
2.9%
식 4
 
2.9%
텍 3
 
2.2%
Other values (51) 68
49.3%
Common
ValueCountFrequency (%)
( 11
44.0%
) 11
44.0%
3
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 136
83.4%
ASCII 25
 
15.3%
None 2
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 15
 
11.0%
주 15
 
11.0%
이 7
 
5.1%
엔 6
 
4.4%
사 6
 
4.4%
오 6
 
4.4%
동 4
 
2.9%
회 4
 
2.9%
식 4
 
2.9%
텍 3
 
2.2%
Other values (50) 66
48.5%
ASCII
ValueCountFrequency (%)
( 11
44.0%
) 11
44.0%
3
 
12.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0146049 × 1013
Minimum2.0070427 × 1013
Maximum2.0210317 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:18:03.857135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070427 × 1013
5-th percentile2.0071023 × 1013
Q12.0110713 × 1013
median2.0131216 × 1013
Q32.0200615 × 1013
95-th percentile2.0210222 × 1013
Maximum2.0210317 × 1013
Range1.3989006 × 1011
Interquartile range (IQR)8.9901939 × 1010

Descriptive statistics

Standard deviation4.9916916 × 1010
Coefficient of variation (CV)0.0024777522
Kurtosis-1.5395453
Mean2.0146049 × 1013
Median Absolute Deviation (MAD)4.9412976 × 1010
Skewness-0.0548854
Sum4.2306702 × 1014
Variance2.4916985 × 1021
MonotonicityNot monotonic
2024-04-17T02:18:03.964844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20201217095039 1
 
4.8%
20091016114241 1
 
4.8%
20131114164725 1
 
4.8%
20180629150906 1
 
4.8%
20080306170416 1
 
4.8%
20100705095228 1
 
4.8%
20200615074056 1
 
4.8%
20161107174029 1
 
4.8%
20110713134601 1
 
4.8%
20120710091714 1
 
4.8%
Other values (11) 11
52.4%
ValueCountFrequency (%)
20070427094440 1
4.8%
20071023134830 1
4.8%
20080306170416 1
4.8%
20091016114241 1
4.8%
20100705095228 1
4.8%
20110713134601 1
4.8%
20111209142548 1
4.8%
20120710091714 1
4.8%
20121024132813 1
4.8%
20131114164725 1
4.8%
ValueCountFrequency (%)
20210317153212 1
4.8%
20210222135813 1
4.8%
20201218091708 1
4.8%
20201217095039 1
4.8%
20200709103054 1
4.8%
20200615074056 1
4.8%
20200414183608 1
4.8%
20180629150906 1
4.8%
20161108160959 1
4.8%
20161107174029 1
4.8%

데이터갱신구분
Categorical

Distinct2
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size300.0 B
I
15 
U
6 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 15
71.4%
U 6
 
28.6%

Length

2024-04-17T02:18:04.078113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:04.184161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 15
71.4%
u 6
 
28.6%

데이터갱신일자
Date

Distinct8
Distinct (%)38.1%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2018-08-31 23:59:59
Maximum2021-03-19 02:40:00
2024-04-17T02:18:04.265083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T02:18:04.362686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing1
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean390819.71
Minimum383090.13
Maximum401781.27
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:18:04.459982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum383090.13
5-th percentile385733.09
Q1388707.3
median390832.43
Q3392541.18
95-th percentile394266.62
Maximum401781.27
Range18691.133
Interquartile range (IQR)3833.8809

Descriptive statistics

Standard deviation3816.583
Coefficient of variation (CV)0.0097655846
Kurtosis2.9695729
Mean390819.71
Median Absolute Deviation (MAD)2305.81
Skewness0.79448913
Sum7816394.3
Variance14566306
MonotonicityNot monotonic
2024-04-17T02:18:04.559767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
385872.188077484 1
 
4.8%
390341.330614118 1
 
4.8%
389403.788887143 1
 
4.8%
388891.775766214 1
 
4.8%
391323.532369596 1
 
4.8%
392220.446579927 1
 
4.8%
401781.266188482 1
 
4.8%
389209.030889954 1
 
4.8%
389882.521018044 1
 
4.8%
392047.096854354 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
383090.133003427 1
4.8%
385872.188077484 1
4.8%
387840.784136651 1
4.8%
387998.366629358 1
4.8%
388153.884601013 1
4.8%
388891.775766214 1
4.8%
389209.030889954 1
4.8%
389403.788887143 1
4.8%
389882.521018044 1
4.8%
390341.330614118 1
4.8%
ValueCountFrequency (%)
401781.266188482 1
4.8%
393871.111334593 1
4.8%
393868.69459854 1
4.8%
393607.260373715 1
4.8%
393503.395720953 1
4.8%
392220.446579927 1
4.8%
392047.096854354 1
4.8%
391796.495138673 1
4.8%
391691.196032511 1
4.8%
391323.532369596 1
4.8%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)100.0%
Missing1
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean190362.1
Minimum182068.44
Maximum201677.69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:18:04.660111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum182068.44
5-th percentile183554.18
Q1188245.79
median189983.49
Q3191582.21
95-th percentile197514.77
Maximum201677.69
Range19609.258
Interquartile range (IQR)3336.4213

Descriptive statistics

Standard deviation4814.4363
Coefficient of variation (CV)0.025290939
Kurtosis0.42003667
Mean190362.1
Median Absolute Deviation (MAD)1771.3961
Skewness0.55324707
Sum3807242
Variance23178797
MonotonicityNot monotonic
2024-04-17T02:18:04.765220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
182068.435002445 1
 
4.8%
197295.66830443 1
 
4.8%
188848.615482098 1
 
4.8%
189934.10838723 1
 
4.8%
189660.998406703 1
 
4.8%
190032.880542446 1
 
4.8%
196012.369520751 1
 
4.8%
190429.066143727 1
 
4.8%
194604.469329687 1
 
4.8%
201677.693320986 1
 
4.8%
Other values (10) 10
47.6%
ValueCountFrequency (%)
182068.435002445 1
4.8%
183632.373950837 1
4.8%
184510.669756514 1
4.8%
186287.197415739 1
4.8%
188144.721879896 1
4.8%
188279.474831569 1
4.8%
188408.076687691 1
4.8%
188848.615482098 1
4.8%
189660.998406703 1
4.8%
189934.10838723 1
4.8%
ValueCountFrequency (%)
201677.693320986 1
4.8%
197295.66830443 1
4.8%
196124.737004344 1
4.8%
196012.369520751 1
4.8%
194604.469329687 1
4.8%
190574.787360832 1
4.8%
190489.966525411 1
4.8%
190429.066143727 1
4.8%
190225.666663987 1
4.8%
190032.880542446 1
4.8%

전문인력총수
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)30.0%
Missing1
Missing (%)4.8%
Infinite0
Infinite (%)0.0%
Mean3.55
Minimum0
Maximum6
Zeros2
Zeros (%)9.5%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-04-17T02:18:04.861105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median4
Q34
95-th percentile6
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.5719582
Coefficient of variation (CV)0.44280513
Kurtosis1.2534537
Mean3.55
Median Absolute Deviation (MAD)1
Skewness-0.870104
Sum71
Variance2.4710526
MonotonicityNot monotonic
2024-04-17T02:18:04.965118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
4 8
38.1%
3 5
23.8%
5 2
 
9.5%
6 2
 
9.5%
0 2
 
9.5%
2 1
 
4.8%
(Missing) 1
 
4.8%
ValueCountFrequency (%)
0 2
 
9.5%
2 1
 
4.8%
3 5
23.8%
4 8
38.1%
5 2
 
9.5%
6 2
 
9.5%
ValueCountFrequency (%)
6 2
 
9.5%
5 2
 
9.5%
4 8
38.1%
3 5
23.8%
2 1
 
4.8%
0 2
 
9.5%

자본금
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2024-04-17T02:18:05.065347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:05.145931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

시설장비
Text

MISSING 

Distinct18
Distinct (%)100.0%
Missing3
Missing (%)14.3%
Memory size300.0 B
2024-04-17T02:18:05.325508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length38.5
Mean length37.722222
Min length15

Characters and Unicode

Total characters679
Distinct characters87
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)100.0%

Sample

1st row수위측정기,수소이온농도측정기,수온측정기,전기전도도측정기
2nd row수위측정장비,PH 측정장비,수온측정장비,전기전도도측정장비
3rd row간이 수질측정장비, 간이수질 측정기, 수동 수위측정기, 자동 수위측정기, 전이온농도 및 전기전도도 측정기, 수소이온농도 측정기
4th rowPH-Meter, ED/TDS/TEMP Meter, 수위측정기, 시추기
5th row지하수수위측정장비 3대 간이수질측정기구 2대
ValueCountFrequency (%)
측정기 8
 
8.6%
1대 6
 
6.5%
수위측정기 5
 
5.4%
수온 4
 
4.3%
전기전도도 4
 
4.3%
지하수위 3
 
3.2%
및 2
 
2.2%
수소이온농도(ph 2
 
2.2%
○ 2
 
2.2%
수소이온농도 2
 
2.2%
Other values (54) 55
59.1%
2024-04-17T02:18:05.652142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
63
 
9.3%
수 48
 
7.1%
측 48
 
7.1%
정 48
 
7.1%
기 44
 
6.5%
, 40
 
5.9%
도 31
 
4.6%
전 25
 
3.7%
온 20
 
2.9%
위 19
 
2.8%
Other values (77) 293
43.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 404
59.5%
Space Separator 63
 
9.3%
Uppercase Letter 50
 
7.4%
Other Punctuation 44
 
6.5%
Lowercase Letter 42
 
6.2%
Decimal Number 33
 
4.9%
Control 12
 
1.8%
Close Punctuation 11
 
1.6%
Open Punctuation 11
 
1.6%
Dash Punctuation 7
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 48
11.9%
측 48
11.9%
정 48
11.9%
기 44
10.9%
도 31
 
7.7%
전 25
 
6.2%
온 20
 
5.0%
위 19
 
4.7%
장 16
 
4.0%
비 15
 
3.7%
Other values (25) 90
22.3%
Uppercase Letter
ValueCountFrequency (%)
H 12
24.0%
P 7
14.0%
M 6
12.0%
T 3
 
6.0%
E 3
 
6.0%
D 3
 
6.0%
C 2
 
4.0%
L 2
 
4.0%
W 2
 
4.0%
N 1
 
2.0%
Other values (9) 9
18.0%
Lowercase Letter
ValueCountFrequency (%)
e 8
19.0%
t 6
14.3%
p 6
14.3%
i 3
 
7.1%
m 3
 
7.1%
r 3
 
7.1%
o 2
 
4.8%
d 2
 
4.8%
l 2
 
4.8%
u 2
 
4.8%
Other values (5) 5
11.9%
Decimal Number
ValueCountFrequency (%)
1 11
33.3%
0 7
21.2%
2 5
15.2%
5 3
 
9.1%
3 3
 
9.1%
6 1
 
3.0%
8 1
 
3.0%
4 1
 
3.0%
7 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
, 40
90.9%
/ 3
 
6.8%
. 1
 
2.3%
Space Separator
ValueCountFrequency (%)
63
100.0%
Control
ValueCountFrequency (%)
12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Other Symbol
ValueCountFrequency (%)
○ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 404
59.5%
Common 183
27.0%
Latin 92
 
13.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 48
11.9%
측 48
11.9%
정 48
11.9%
기 44
10.9%
도 31
 
7.7%
전 25
 
6.2%
온 20
 
5.0%
위 19
 
4.7%
장 16
 
4.0%
비 15
 
3.7%
Other values (25) 90
22.3%
Latin
ValueCountFrequency (%)
H 12
 
13.0%
e 8
 
8.7%
P 7
 
7.6%
M 6
 
6.5%
t 6
 
6.5%
p 6
 
6.5%
T 3
 
3.3%
i 3
 
3.3%
m 3
 
3.3%
E 3
 
3.3%
Other values (24) 35
38.0%
Common
ValueCountFrequency (%)
63
34.4%
, 40
21.9%
12
 
6.6%
1 11
 
6.0%
) 11
 
6.0%
( 11
 
6.0%
0 7
 
3.8%
- 7
 
3.8%
2 5
 
2.7%
5 3
 
1.6%
Other values (8) 13
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 404
59.5%
ASCII 273
40.2%
Geometric Shapes 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
63
23.1%
, 40
14.7%
12
 
4.4%
H 12
 
4.4%
1 11
 
4.0%
) 11
 
4.0%
( 11
 
4.0%
e 8
 
2.9%
0 7
 
2.6%
P 7
 
2.6%
Other values (41) 91
33.3%
Hangul
ValueCountFrequency (%)
수 48
11.9%
측 48
11.9%
정 48
11.9%
기 44
10.9%
도 31
 
7.7%
전 25
 
6.2%
온 20
 
5.0%
위 19
 
4.7%
장 16
 
4.0%
비 15
 
3.7%
Other values (25) 90
22.3%
Geometric Shapes
ValueCountFrequency (%)
○ 2
100.0%

타기관이전여부
Categorical

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
0
21 

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 21
100.0%

Length

2024-04-17T02:18:05.795892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T02:18:05.878370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 21
100.0%

Unnamed: 32
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing21
Missing (%)100.0%
Memory size321.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)전문인력총수자본금시설장비타기관이전여부Unnamed: 32
01지하수영향조사기관09_29_02_P3270000S001801110315837L0020080111<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 동구 초량동 135-48 금정빌딩 2층<NA><NA>㈜성진엔지니어링20201217095039U2020-12-19 02:40:00.0<NA>385872.188077182068.43500250수위측정기,수소이온농도측정기,수온측정기,전기전도도측정기0<NA>
12지하수영향조사기관09_29_02_P3290000S001801110091271L0019971217<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 부산진구 범천동 839-32번지 신부산빌딩 9층부산광역시 부산진구 자유평화로3번길 14-21 (범천동,신부산빌딩 9층)<NA>㈜동남기초20091016114241I2018-08-31 23:59:59.0<NA>387840.784137184510.66975760수위측정장비,PH 측정장비,수온측정장비,전기전도도측정장비0<NA>
23지하수영향조사기관09_29_02_P3290000S001801110646390L0020130501<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 부산진구 전포동 194-27 남경빌딩 5층부산광역시 부산진구 전포대로 242 (전포동,남경빌딩 5층)<NA>(주)신우하이텍20201218091708U2020-12-20 02:40:00.0<NA>388153.884601186287.19741650간이 수질측정장비, 간이수질 측정기, 수동 수위측정기, 자동 수위측정기, 전이온농도 및 전기전도도 측정기, 수소이온농도 측정기0<NA>
34지하수영향조사기관09_29_02_P3300000S001801110746967L0020121024<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 동래구 안락동 248 3층부산광역시 동래구 충렬대로 432 (안락동)<NA>(주)지오뱅크20121024132813I2018-08-31 23:59:59.0<NA>391691.196033190574.78736140PH-Meter, ED/TDS/TEMP Meter, 수위측정기, 시추기0<NA>
45지하수영향조사기관09_29_02_P3300000S00605207670100000020060914<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 동래구 사직동 99-5번지부산광역시 동래구 아시아드대로133번길 17 (사직동)<NA>기술사사무소지오엠20070427094440I2018-08-31 23:59:59.0<NA>387998.366629190489.96652540지하수수위측정장비 3대 간이수질측정기구 2대0<NA>
56지하수영향조사기관09_29_02_P3310000S00617830011700000020051209<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 남구 대연동 599-1번지 부경대학교부산광역시 남구 용소로 45 (대연동,부경대학교)<NA>부경대학교 지질환경연구소20071023134830I2018-08-31 23:59:59.0<NA>391796.495139183632.37395160수소이온농도측정기 외 12종0<NA>
67지하수영향조사기관09_29_02_P3320000S001955110078414L0020050629<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 북구 금곡동 1880-5번지 해성빌딩 4층부산광역시 북구 금곡대로441번길 7 (금곡동,해성빌딩 4층)<NA>(주)동해이엔지20111209142548I2018-08-31 23:59:59.0<NA>383090.133003196124.737004<NA>0<NA>0<NA>
78지하수영향조사기관09_29_02_P3330000S001801110240307L0020161107<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 센텀동로 99, 1507호 (재송동, 벽산이센텀클래스원)48059(주)하나기술단20161108160959I2018-08-31 23:59:59.0<NA>393607.260374188408.07668830지하수위 측정기 WL-50 수소이온농도(PH), 수온, 전기전도 측정기 YK-2001PHA0<NA>
89지하수영향조사기관09_29_02_P3330000S001801110469072L0020061101<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 재송동 1149-7번지부산광역시 해운대구 재반로 163-23 (재송동)<NA>(주)성산엔지니어링20131216174849I2018-08-31 23:59:59.0<NA>393871.111335190225.66666440수위측정기, 전기전도도(EC)측정기, 수소이온농도(pH) 및 수온측정기0<NA>
910지하수영향조사기관09_29_02_P3330000S001955110078414L0020111220<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 우동 1459<NA><NA>(주)동해이엔지20200709103054U2020-07-11 02:40:00.0<NA>393868.694599188144.7218840지하수위 측정기 1대, 다항목 수질측정기 1대0<NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)전문인력총수자본금시설장비타기관이전여부Unnamed: 32
1112지하수영향조사기관09_29_02_P3350000S001801111191806L0020190527<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 장전동 40번지 부산대학교 제6공학관 6108-호부산광역시 금정구 부산대학로63번길 2, 부산대학교 제6공학관 6108-1호 (장전동)46241주식회사 다솔이앤씨20200414183608U2020-04-16 02:40:00.0<NA>390341.330614197295.66830440지하수수위측정장비(지하수위계 Model GV 2417-50M) 수소이온농도, 수온, 전기전도도 측정장비(다항목측정기 HM-501)0<NA>
1213지하수영향조사기관09_29_02_P3350000S001801110749979L0020210304<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 두구동 228부산광역시 금정구 체육공원로 622, 2층 (두구동)46208주식회사 동방이엔지20210317153212U2021-03-19 02:40:00.0<NA>392047.096854201677.69332120<NA>0<NA>
1314지하수영향조사기관09_29_02_P3350000S00617224740700000020120704<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 장전동 417-2번지 동신빌딩 4층부산광역시 금정구 금정로91번길 3, 4층 (장전동, 동신빌딩)<NA>수인지오텍20120710091714I2018-08-31 23:59:59.0<NA>389882.521018194604.4693340수위측정기,수소이온농도(pH), 수온, 전기전도도 측정기0<NA>
1415지하수영향조사기관09_29_02_P3350000S001801110762989L0020110713<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 금정구 장전동 부산대학교 제6공학관 6104-3<NA><NA>(주)지오에스지20110713134601I2018-08-31 23:59:59.0<NA><NA><NA>40○ 지하수위 측정기 1대 ○ 현장수질측정기 1대0<NA>
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