Overview

Dataset statistics

Number of variables32
Number of observations23
Missing cells204
Missing cells (%)27.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.4 KiB
Average record size in memory282.7 B

Variable types

Numeric7
Categorical11
Text5
Unsupported8
DateTime1

Dataset

Description22년08월_6270000_대구광역시_09_29_02_P_지하수영향조사기관
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000094238&dataSetDetailId=DDI_0000094272&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스아이디 has constant value ""Constant
자본금 has constant value ""Constant
인허가취소일자 is highly imbalanced (51.3%)Imbalance
폐업일자 has 23 (100.0%) missing valuesMissing
휴업시작일자 has 23 (100.0%) missing valuesMissing
휴업종료일자 has 23 (100.0%) missing valuesMissing
재개업일자 has 23 (100.0%) missing valuesMissing
소재지전화 has 23 (100.0%) missing valuesMissing
소재지면적 has 23 (100.0%) missing valuesMissing
소재지우편번호 has 23 (100.0%) missing valuesMissing
도로명전체주소 has 4 (17.4%) missing valuesMissing
도로명우편번호 has 11 (47.8%) missing valuesMissing
업태구분명 has 23 (100.0%) missing valuesMissing
좌표정보(X) has 2 (8.7%) missing valuesMissing
좌표정보(Y) has 2 (8.7%) missing valuesMissing
시설장비 has 1 (4.3%) 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

Reproduction

Analysis started2023-12-10 18:31:33.877072
Analysis finished2023-12-10 18:31:34.534878
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12
Minimum1
Maximum23
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T03:31:34.671381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.1
Q16.5
median12
Q317.5
95-th percentile21.9
Maximum23
Range22
Interquartile range (IQR)11

Descriptive statistics

Standard deviation6.78233
Coefficient of variation (CV)0.56519417
Kurtosis-1.2
Mean12
Median Absolute Deviation (MAD)6
Skewness0
Sum276
Variance46
MonotonicityStrictly increasing
2023-12-11T03:31:34.874564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1 1
 
4.3%
2 1
 
4.3%
23 1
 
4.3%
22 1
 
4.3%
21 1
 
4.3%
20 1
 
4.3%
19 1
 
4.3%
18 1
 
4.3%
17 1
 
4.3%
16 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
1 1
4.3%
2 1
4.3%
3 1
4.3%
4 1
4.3%
5 1
4.3%
6 1
4.3%
7 1
4.3%
8 1
4.3%
9 1
4.3%
10 1
4.3%
ValueCountFrequency (%)
23 1
4.3%
22 1
4.3%
21 1
4.3%
20 1
4.3%
19 1
4.3%
18 1
4.3%
17 1
4.3%
16 1
4.3%
15 1
4.3%
14 1
4.3%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
지하수영향조사기관
23 

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 23
100.0%

Length

2023-12-11T03:31:35.110708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:35.296065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지하수영향조사기관 23
100.0%

개방서비스아이디
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
09_29_02_P
23 

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 23
100.0%

Length

2023-12-11T03:31:35.495455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:35.662306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_29_02_p 23
100.0%

개방자치단체코드
Real number (ℝ)

Distinct7
Distinct (%)30.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3461304.3
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T03:31:35.818685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13450000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)30000

Descriptive statistics

Standard deviation23799.226
Coefficient of variation (CV)0.006875797
Kurtosis-0.24419572
Mean3461304.3
Median Absolute Deviation (MAD)10000
Skewness-1.0555438
Sum79610000
Variance5.6640316 × 108
MonotonicityIncreasing
2023-12-11T03:31:36.047420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3480000 11
47.8%
3420000 3
 
13.0%
3460000 3
 
13.0%
3450000 2
 
8.7%
3470000 2
 
8.7%
3410000 1
 
4.3%
3440000 1
 
4.3%
ValueCountFrequency (%)
3410000 1
 
4.3%
3420000 3
 
13.0%
3440000 1
 
4.3%
3450000 2
 
8.7%
3460000 3
 
13.0%
3470000 2
 
8.7%
3480000 11
47.8%
ValueCountFrequency (%)
3480000 11
47.8%
3470000 2
 
8.7%
3460000 3
 
13.0%
3450000 2
 
8.7%
3440000 1
 
4.3%
3420000 3
 
13.0%
3410000 1
 
4.3%

관리번호
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T03:31:36.445919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters437
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 (%)82.6%

Sample

1st rowS001747110006648L00
2nd rowS001760110053360L00
3rd rowS001748110011934L00
4th rowS001748110006638L00
5th rowS001714110005300L00
ValueCountFrequency (%)
s001701110060799l00 2
 
8.7%
s001744110004474l00 2
 
8.7%
s001751110023057l00 1
 
4.3%
s002301110069623l00 1
 
4.3%
s001701110127656l00 1
 
4.3%
s001701110217267l00 1
 
4.3%
s001701110347163l00 1
 
4.3%
s001715110012725l00 1
 
4.3%
s001752110054050l00 1
 
4.3%
s005131578541000000 1
 
4.3%
Other values (11) 11
47.8%
2023-12-11T03:31:37.087368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 169
38.7%
1 82
18.8%
7 32
 
7.3%
4 28
 
6.4%
S 23
 
5.3%
L 20
 
4.6%
5 20
 
4.6%
6 19
 
4.3%
2 14
 
3.2%
3 13
 
3.0%
Other values (2) 17
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 394
90.2%
Uppercase Letter 43
 
9.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 169
42.9%
1 82
20.8%
7 32
 
8.1%
4 28
 
7.1%
5 20
 
5.1%
6 19
 
4.8%
2 14
 
3.6%
3 13
 
3.3%
8 10
 
2.5%
9 7
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S 23
53.5%
L 20
46.5%

Most occurring scripts

ValueCountFrequency (%)
Common 394
90.2%
Latin 43
 
9.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 169
42.9%
1 82
20.8%
7 32
 
8.1%
4 28
 
7.1%
5 20
 
5.1%
6 19
 
4.8%
2 14
 
3.6%
3 13
 
3.3%
8 10
 
2.5%
9 7
 
1.8%
Latin
ValueCountFrequency (%)
S 23
53.5%
L 20
46.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 437
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 169
38.7%
1 82
18.8%
7 32
 
7.3%
4 28
 
6.4%
S 23
 
5.3%
L 20
 
4.6%
5 20
 
4.6%
6 19
 
4.3%
2 14
 
3.2%
3 13
 
3.0%
Other values (2) 17
 
3.9%

인허가일자
Real number (ℝ)

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20100990
Minimum19970909
Maximum20220221
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T03:31:37.359279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19970909
5-th percentile19971852
Q119990606
median20100616
Q320190968
95-th percentile20211119
Maximum20220221
Range249312
Interquartile range (IQR)200361.5

Descriptive statistics

Standard deviation92888.188
Coefficient of variation (CV)0.0046210752
Kurtosis-1.5397348
Mean20100990
Median Absolute Deviation (MAD)99804
Skewness-0.23733952
Sum4.6232278 × 108
Variance8.6282155 × 109
MonotonicityNot monotonic
2023-12-11T03:31:37.643635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
20100616 2
 
8.7%
19980408 2
 
8.7%
20060602 1
 
4.3%
20180330 1
 
4.3%
20200521 1
 
4.3%
20120207 1
 
4.3%
20210122 1
 
4.3%
20120131 1
 
4.3%
20170330 1
 
4.3%
20200420 1
 
4.3%
Other values (11) 11
47.8%
ValueCountFrequency (%)
19970909 1
4.3%
19970923 1
4.3%
19980209 1
4.3%
19980408 2
8.7%
19990310 1
4.3%
19990902 1
4.3%
20060602 1
4.3%
20090615 1
4.3%
20090811 1
4.3%
20100616 2
8.7%
ValueCountFrequency (%)
20220221 1
4.3%
20211230 1
4.3%
20210122 1
4.3%
20200521 1
4.3%
20200420 1
4.3%
20191231 1
4.3%
20190704 1
4.3%
20180330 1
4.3%
20170330 1
4.3%
20120207 1
4.3%

인허가취소일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)26.1%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
18 
20110310
 
1
20120709
 
1
20131025
 
1
20100416
 
1

Length

Max length8
Median length4
Mean length4.8695652
Min length4

Unique

Unique5 ?
Unique (%)21.7%

Sample

1st row20110310
2nd row<NA>
3rd row20120709
4th row20131025
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 18
78.3%
20110310 1
 
4.3%
20120709 1
 
4.3%
20131025 1
 
4.3%
20100416 1
 
4.3%
20110825 1
 
4.3%

Length

2023-12-11T03:31:37.986363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:38.231178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 18
78.3%
20110310 1
 
4.3%
20120709 1
 
4.3%
20131025 1
 
4.3%
20100416 1
 
4.3%
20110825 1
 
4.3%

영업상태구분코드
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
1
18 
3
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row1
3rd row3
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 18
78.3%
3 5
 
21.7%

Length

2023-12-11T03:31:38.474248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:38.728855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
78.3%
3 5
 
21.7%

영업상태명
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
영업/정상
18 
폐업
5 

Length

Max length5
Median length5
Mean length4.3478261
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 18
78.3%
폐업 5
 
21.7%

Length

2023-12-11T03:31:39.015503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:39.359368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 18
78.3%
폐업 5
 
21.7%

상세영업상태코드
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
1
18 
2
5 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row2
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 18
78.3%
2 5
 
21.7%

Length

2023-12-11T03:31:39.671730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:39.875340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
78.3%
2 5
 
21.7%

상세영업상태명
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
영업
18 
취소정지업체
5 

Length

Max length6
Median length2
Mean length2.8695652
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 18
78.3%
취소정지업체 5
 
21.7%

Length

2023-12-11T03:31:40.090856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:40.301479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 18
78.3%
취소정지업체 5
 
21.7%

폐업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

소재지전화
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

소재지우편번호
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

소재지전체주소
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T03:31:40.677608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length31
Mean length25.173913
Min length20

Characters and Unicode

Total characters579
Distinct characters72
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

Unique19 ?
Unique (%)82.6%

Sample

1st row대구광역시 중구 대봉동 55-68번지 대구맨션 A동 C호
2nd row대구광역시 동구 상매동 521-2번지
3rd row대구광역시 동구 신천동 366-6번지
4th row대구광역시 동구 신천동 149-31번지 149-31번지 4층
5th row대구광역시 남구 대명동 2033-28번지
ValueCountFrequency (%)
대구광역시 23
 
20.0%
달성군 11
 
9.6%
하빈면 4
 
3.5%
동구 3
 
2.6%
수성구 3
 
2.6%
화원읍 3
 
2.6%
봉촌리 3
 
2.6%
서재리 2
 
1.7%
다사읍 2
 
1.7%
달서구 2
 
1.7%
Other values (52) 59
51.3%
2023-12-11T03:31:41.357167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
112
19.3%
구 37
 
6.4%
대 27
 
4.7%
1 25
 
4.3%
역 24
 
4.1%
광 23
 
4.0%
시 23
 
4.0%
- 20
 
3.5%
동 17
 
2.9%
성 17
 
2.9%
Other values (62) 254
43.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 335
57.9%
Space Separator 112
 
19.3%
Decimal Number 109
 
18.8%
Dash Punctuation 20
 
3.5%
Uppercase Letter 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 37
 
11.0%
대 27
 
8.1%
역 24
 
7.2%
광 23
 
6.9%
시 23
 
6.9%
동 17
 
5.1%
성 17
 
5.1%
지 15
 
4.5%
번 15
 
4.5%
달 13
 
3.9%
Other values (48) 124
37.0%
Decimal Number
ValueCountFrequency (%)
1 25
22.9%
2 16
14.7%
3 13
11.9%
6 12
11.0%
5 10
 
9.2%
9 9
 
8.3%
8 8
 
7.3%
4 7
 
6.4%
7 5
 
4.6%
0 4
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
112
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 335
57.9%
Common 241
41.6%
Latin 3
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 37
 
11.0%
대 27
 
8.1%
역 24
 
7.2%
광 23
 
6.9%
시 23
 
6.9%
동 17
 
5.1%
성 17
 
5.1%
지 15
 
4.5%
번 15
 
4.5%
달 13
 
3.9%
Other values (48) 124
37.0%
Common
ValueCountFrequency (%)
112
46.5%
1 25
 
10.4%
- 20
 
8.3%
2 16
 
6.6%
3 13
 
5.4%
6 12
 
5.0%
5 10
 
4.1%
9 9
 
3.7%
8 8
 
3.3%
4 7
 
2.9%
Other values (2) 9
 
3.7%
Latin
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 335
57.9%
ASCII 244
42.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
112
45.9%
1 25
 
10.2%
- 20
 
8.2%
2 16
 
6.6%
3 13
 
5.3%
6 12
 
4.9%
5 10
 
4.1%
9 9
 
3.7%
8 8
 
3.3%
4 7
 
2.9%
Other values (4) 12
 
4.9%
Hangul
ValueCountFrequency (%)
구 37
 
11.0%
대 27
 
8.1%
역 24
 
7.2%
광 23
 
6.9%
시 23
 
6.9%
동 17
 
5.1%
성 17
 
5.1%
지 15
 
4.5%
번 15
 
4.5%
달 13
 
3.9%
Other values (48) 124
37.0%

도로명전체주소
Text

MISSING 

Distinct17
Distinct (%)89.5%
Missing4
Missing (%)17.4%
Memory size316.0 B
2023-12-11T03:31:41.848629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length33
Mean length26.736842
Min length20

Characters and Unicode

Total characters508
Distinct characters82
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

Unique15 ?
Unique (%)78.9%

Sample

1st row대구광역시 중구 명륜로 154, A동 C호 (대봉동,대구맨션)
2nd row대구광역시 동구 율암로 149-6 (상매동)
3rd row대구광역시 동구 화랑로9길 61 (신천동)
4th row대구광역시 동구 장등로 9 (신천동, 149-31번지 4층)
5th row대구광역시 남구 명덕로 212-1 (대명동)
ValueCountFrequency (%)
대구광역시 19
 
17.3%
달성군 9
 
8.2%
동구 3
 
2.7%
하빈면 3
 
2.7%
3층 3
 
2.7%
화원읍 2
 
1.8%
북구 2
 
1.8%
4층 2
 
1.8%
신천동 2
 
1.8%
달서구 2
 
1.8%
Other values (58) 63
57.3%
2023-12-11T03:31:42.630398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
17.9%
구 31
 
6.1%
대 24
 
4.7%
역 20
 
3.9%
광 19
 
3.7%
시 19
 
3.7%
로 17
 
3.3%
동 16
 
3.1%
1 15
 
3.0%
성 13
 
2.6%
Other values (72) 243
47.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
59.3%
Space Separator 91
 
17.9%
Decimal Number 76
 
15.0%
Other Punctuation 10
 
2.0%
Open Punctuation 10
 
2.0%
Close Punctuation 10
 
2.0%
Dash Punctuation 7
 
1.4%
Uppercase Letter 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 31
 
10.3%
대 24
 
8.0%
역 20
 
6.6%
광 19
 
6.3%
시 19
 
6.3%
로 17
 
5.6%
동 16
 
5.3%
성 13
 
4.3%
달 11
 
3.7%
군 9
 
3.0%
Other values (55) 122
40.5%
Decimal Number
ValueCountFrequency (%)
1 15
19.7%
4 13
17.1%
2 9
11.8%
5 8
10.5%
3 8
10.5%
0 7
9.2%
9 6
 
7.9%
6 5
 
6.6%
8 3
 
3.9%
7 2
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
91
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 301
59.3%
Common 204
40.2%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 31
 
10.3%
대 24
 
8.0%
역 20
 
6.6%
광 19
 
6.3%
시 19
 
6.3%
로 17
 
5.6%
동 16
 
5.3%
성 13
 
4.3%
달 11
 
3.7%
군 9
 
3.0%
Other values (55) 122
40.5%
Common
ValueCountFrequency (%)
91
44.6%
1 15
 
7.4%
4 13
 
6.4%
, 10
 
4.9%
( 10
 
4.9%
) 10
 
4.9%
2 9
 
4.4%
5 8
 
3.9%
3 8
 
3.9%
0 7
 
3.4%
Other values (5) 23
 
11.3%
Latin
ValueCountFrequency (%)
A 2
66.7%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 301
59.3%
ASCII 207
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
44.0%
1 15
 
7.2%
4 13
 
6.3%
, 10
 
4.8%
( 10
 
4.8%
) 10
 
4.8%
2 9
 
4.3%
5 8
 
3.9%
3 8
 
3.9%
0 7
 
3.4%
Other values (7) 26
 
12.6%
Hangul
ValueCountFrequency (%)
구 31
 
10.3%
대 24
 
8.0%
역 20
 
6.6%
광 19
 
6.3%
시 19
 
6.3%
로 17
 
5.6%
동 16
 
5.3%
성 13
 
4.3%
달 11
 
3.7%
군 9
 
3.0%
Other values (55) 122
40.5%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)83.3%
Missing11
Missing (%)47.8%
Infinite0
Infinite (%)0.0%
Mean42570.5
Minimum41059
Maximum43004
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T03:31:42.848464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41059
5-th percentile41349.4
Q142527.5
median42905
Q342930.25
95-th percentile42983.1
Maximum43004
Range1945
Interquartile range (IQR)402.75

Descriptive statistics

Standard deviation647.8578
Coefficient of variation (CV)0.015218468
Kurtosis1.6765656
Mean42570.5
Median Absolute Deviation (MAD)45
Skewness-1.6691457
Sum510846
Variance419719.73
MonotonicityNot monotonic
2023-12-11T03:31:43.059456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
42905 2
 
8.7%
42929 2
 
8.7%
41059 1
 
4.3%
41587 1
 
4.3%
42037 1
 
4.3%
42691 1
 
4.3%
42966 1
 
4.3%
43004 1
 
4.3%
42900 1
 
4.3%
42934 1
 
4.3%
(Missing) 11
47.8%
ValueCountFrequency (%)
41059 1
4.3%
41587 1
4.3%
42037 1
4.3%
42691 1
4.3%
42900 1
4.3%
42905 2
8.7%
42929 2
8.7%
42934 1
4.3%
42966 1
4.3%
43004 1
4.3%
ValueCountFrequency (%)
43004 1
4.3%
42966 1
4.3%
42934 1
4.3%
42929 2
8.7%
42905 2
8.7%
42900 1
4.3%
42691 1
4.3%
42037 1
4.3%
41587 1
4.3%
41059 1
4.3%

사업장명
Text

Distinct21
Distinct (%)91.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
2023-12-11T03:31:43.414666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length7.2173913
Min length3

Characters and Unicode

Total characters166
Distinct characters61
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 (%)82.6%

Sample

1st row㈜지오익스
2nd row범환지오텍(주)
3rd row㈜경창지오컨설탄트
4th row㈜세경
5th row수창개발(주)
ValueCountFrequency (%)
㈜국제지오컨설팅 2
 
8.0%
주식회사 2
 
8.0%
신화산업개발주식회사 2
 
8.0%
주)성수개발 1
 
4.0%
주)용현건설 1
 
4.0%
㈜명성토건 1
 
4.0%
서창이엔지 1
 
4.0%
우림지질(주 1
 
4.0%
나견토건(주 1
 
4.0%
뉴지오텍(주 1
 
4.0%
Other values (12) 12
48.0%
2023-12-11T03:31:44.146329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 13
 
7.8%
지 10
 
6.0%
) 9
 
5.4%
( 9
 
5.4%
㈜ 7
 
4.2%
오 6
 
3.6%
개 6
 
3.6%
발 6
 
3.6%
사 6
 
3.6%
설 5
 
3.0%
Other values (51) 89
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 139
83.7%
Close Punctuation 9
 
5.4%
Open Punctuation 9
 
5.4%
Other Symbol 7
 
4.2%
Space Separator 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 13
 
9.4%
지 10
 
7.2%
오 6
 
4.3%
개 6
 
4.3%
발 6
 
4.3%
사 6
 
4.3%
설 5
 
3.6%
건 5
 
3.6%
창 4
 
2.9%
식 4
 
2.9%
Other values (47) 74
53.2%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146
88.0%
Common 20
 
12.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 13
 
8.9%
지 10
 
6.8%
㈜ 7
 
4.8%
오 6
 
4.1%
개 6
 
4.1%
발 6
 
4.1%
사 6
 
4.1%
설 5
 
3.4%
건 5
 
3.4%
창 4
 
2.7%
Other values (48) 78
53.4%
Common
ValueCountFrequency (%)
) 9
45.0%
( 9
45.0%
2
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 139
83.7%
ASCII 20
 
12.0%
None 7
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 13
 
9.4%
지 10
 
7.2%
오 6
 
4.3%
개 6
 
4.3%
발 6
 
4.3%
사 6
 
4.3%
설 5
 
3.6%
건 5
 
3.6%
창 4
 
2.9%
식 4
 
2.9%
Other values (47) 74
53.2%
ASCII
ValueCountFrequency (%)
) 9
45.0%
( 9
45.0%
2
 
10.0%
None
ValueCountFrequency (%)
㈜ 7
100.0%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct23
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0175283 × 1013
Minimum2.0100416 × 1013
Maximum2.0220823 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T03:31:44.412719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0100416 × 1013
5-th percentile2.0101484 × 1013
Q12.014067 × 1013
median2.0190925 × 1013
Q32.0210365 × 1013
95-th percentile2.0220223 × 1013
Maximum2.0220823 × 1013
Range1.2040701 × 1011
Interquartile range (IQR)6.969503 × 1010

Descriptive statistics

Standard deviation4.2752184 × 1010
Coefficient of variation (CV)0.0021190376
Kurtosis-1.2517105
Mean2.0175283 × 1013
Median Absolute Deviation (MAD)2.9295993 × 1010
Skewness-0.55588448
Sum4.6403152 × 1014
Variance1.8277493 × 1021
MonotonicityNot monotonic
2023-12-11T03:31:44.698804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
20110310153330 1
 
4.3%
20170113161432 1
 
4.3%
20150312085244 1
 
4.3%
20200521131401 1
 
4.3%
20190219172124 1
 
4.3%
20210122144839 1
 
4.3%
20200226134556 1
 
4.3%
20220823154724 1
 
4.3%
20210122135125 1
 
4.3%
20210122135903 1
 
4.3%
Other values (13) 13
56.5%
ValueCountFrequency (%)
20100416141615 1
4.3%
20100503154000 1
4.3%
20110310153330 1
4.3%
20120712093905 1
4.3%
20130611112933 1
4.3%
20131028152034 1
4.3%
20150312085244 1
4.3%
20150811121632 1
4.3%
20151215151303 1
4.3%
20170113161432 1
4.3%
ValueCountFrequency (%)
20220823154724 1
4.3%
20220223114752 1
4.3%
20220221094436 1
4.3%
20220119155104 1
4.3%
20211230133437 1
4.3%
20210608151732 1
4.3%
20210122144839 1
4.3%
20210122135903 1
4.3%
20210122135125 1
4.3%
20200521131401 1
4.3%

데이터갱신구분
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
I
15 
U
8 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 15
65.2%
U 8
34.8%

Length

2023-12-11T03:31:44.990755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:45.213897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 15
65.2%
u 8
34.8%

데이터갱신일자
Date

Distinct13
Distinct (%)56.5%
Missing0
Missing (%)0.0%
Memory size316.0 B
Minimum2018-08-31 23:59:59
Maximum2022-08-25 02:40:00
2023-12-11T03:31:45.398536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:31:45.620500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)85.7%
Missing2
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean339382.09
Minimum326126.02
Maximum353814.47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T03:31:45.837762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326126.02
5-th percentile326126.02
Q1335091.36
median339808.84
Q3346509.28
95-th percentile348355.01
Maximum353814.47
Range27688.445
Interquartile range (IQR)11417.922

Descriptive statistics

Standard deviation8280.5101
Coefficient of variation (CV)0.024398783
Kurtosis-0.89754528
Mean339382.09
Median Absolute Deviation (MAD)5105.5003
Skewness-0.30633104
Sum7127024
Variance68566847
MonotonicityNot monotonic
2023-12-11T03:31:46.045461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
326126.020934 3
 
13.0%
335091.359493 2
 
8.7%
338192.337831 1
 
4.3%
334703.341974 1
 
4.3%
346601.694982 1
 
4.3%
327254.926809 1
 
4.3%
335607.850668 1
 
4.3%
336278.478987 1
 
4.3%
344548.066275 1
 
4.3%
353814.465572 1
 
4.3%
Other values (8) 8
34.8%
(Missing) 2
 
8.7%
ValueCountFrequency (%)
326126.020934 3
13.0%
327254.926809 1
 
4.3%
334703.341974 1
 
4.3%
335091.359493 2
8.7%
335607.850668 1
 
4.3%
336278.478987 1
 
4.3%
338192.337831 1
 
4.3%
339808.842263 1
 
4.3%
343680.311178 1
 
4.3%
343857.119506 1
 
4.3%
ValueCountFrequency (%)
353814.465572 1
4.3%
348355.00624 1
4.3%
347901.216988 1
4.3%
347127.396363 1
4.3%
346601.694982 1
4.3%
346509.281837 1
4.3%
344548.066275 1
4.3%
344222.852055 1
4.3%
343857.119506 1
4.3%
343680.311178 1
4.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct18
Distinct (%)85.7%
Missing2
Missing (%)8.7%
Infinite0
Infinite (%)0.0%
Mean262814.48
Minimum256670.66
Maximum270252.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size339.0 B
2023-12-11T03:31:46.261580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum256670.66
5-th percentile256678.73
Q1261310.28
median264094.23
Q3264691.39
95-th percentile266715.7
Maximum270252.6
Range13581.94
Interquartile range (IQR)3381.1113

Descriptive statistics

Standard deviation3729.6431
Coefficient of variation (CV)0.014191163
Kurtosis-0.22833481
Mean262814.48
Median Absolute Deviation (MAD)1104.9085
Skewness-0.49112224
Sum5519104.1
Variance13910238
MonotonicityNot monotonic
2023-12-11T03:31:46.510996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
264094.22627 3
 
13.0%
264527.918012 2
 
8.7%
261310.280536 1
 
4.3%
256670.659942 1
 
4.3%
256941.545138 1
 
4.3%
265496.191813 1
 
4.3%
256712.422468 1
 
4.3%
256678.726194 1
 
4.3%
263409.635353 1
 
4.3%
266715.697771 1
 
4.3%
Other values (8) 8
34.8%
(Missing) 2
 
8.7%
ValueCountFrequency (%)
256670.659942 1
 
4.3%
256678.726194 1
 
4.3%
256712.422468 1
 
4.3%
256941.545138 1
 
4.3%
258039.194107 1
 
4.3%
261310.280536 1
 
4.3%
262989.317772 1
 
4.3%
263231.81835 1
 
4.3%
263409.635353 1
 
4.3%
264094.22627 3
13.0%
ValueCountFrequency (%)
270252.600222 1
 
4.3%
266715.697771 1
 
4.3%
265496.191813 1
 
4.3%
265487.37503 1
 
4.3%
264805.176173 1
 
4.3%
264691.391836 1
 
4.3%
264527.918012 2
8.7%
264333.566505 1
 
4.3%
264094.22627 3
13.0%
263409.635353 1
 
4.3%

전문인력총수
Categorical

Distinct5
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
3
13 
4
6 
5
2 
6
 
1
0
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row4
2nd row5
3rd row3
4th row4
5th row4

Common Values

ValueCountFrequency (%)
3 13
56.5%
4 6
26.1%
5 2
 
8.7%
6 1
 
4.3%
0 1
 
4.3%

Length

2023-12-11T03:31:46.744385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:47.030297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 13
56.5%
4 6
26.1%
5 2
 
8.7%
6 1
 
4.3%
0 1
 
4.3%

자본금
Categorical

CONSTANT 

Distinct1
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size316.0 B
0
23 

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 23
100.0%

Length

2023-12-11T03:31:47.344848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:47.525865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 23
100.0%

시설장비
Text

MISSING 

Distinct19
Distinct (%)86.4%
Missing1
Missing (%)4.3%
Memory size316.0 B
2023-12-11T03:31:47.940451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length46.5
Mean length42.409091
Min length19

Characters and Unicode

Total characters933
Distinct characters65
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)72.7%

Sample

1st row1. 수위측정기 1대 2. Ph측정기 1대 3. DO측정기 1대 4. 전기전도도측정기 1대
2nd row수위측정장비1대,수소이온농도측정기1대 수온측정기1대,전기전도도측정기1대
3rd row1. 수위측정기 1 2. PH측정기 1 3. 수온측정기 1 4. 전기전도도 측정기 1
4th row1. 수위측정기 1 2. PH측정기 1 3. 수온측정기 1 4. 전기전도도 측정기 1
5th row1. 수위측정기 1 2. PH측정기 1 3. 수온측정기 1 4. 전기전도도측정기 1
ValueCountFrequency (%)
1대 24
 
14.3%
1 21
 
12.5%
수위측정기 11
 
6.5%
ph측정기 9
 
5.4%
전기전도도 7
 
4.2%
2 7
 
4.2%
3 7
 
4.2%
측정기 6
 
3.6%
4 6
 
3.6%
수온 5
 
3.0%
Other values (45) 65
38.7%
2023-12-11T03:31:48.922176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
113
 
12.1%
기 79
 
8.5%
정 66
 
7.1%
측 65
 
7.0%
1 60
 
6.4%
수 49
 
5.3%
도 45
 
4.8%
전 36
 
3.9%
36
 
3.9%
. 30
 
3.2%
Other values (55) 354
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 475
50.9%
Decimal Number 127
 
13.6%
Space Separator 113
 
12.1%
Uppercase Letter 74
 
7.9%
Other Punctuation 55
 
5.9%
Control 36
 
3.9%
Close Punctuation 15
 
1.6%
Open Punctuation 15
 
1.6%
Dash Punctuation 13
 
1.4%
Lowercase Letter 10
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 79
16.6%
정 66
13.9%
측 65
13.7%
수 49
10.3%
도 45
9.5%
전 36
7.6%
대 30
 
6.3%
온 23
 
4.8%
위 21
 
4.4%
장 8
 
1.7%
Other values (18) 53
11.2%
Uppercase Letter
ValueCountFrequency (%)
H 23
31.1%
P 14
18.9%
I 10
13.5%
E 5
 
6.8%
C 5
 
6.8%
N 3
 
4.1%
R 2
 
2.7%
O 2
 
2.7%
A 2
 
2.7%
M 2
 
2.7%
Other values (6) 6
 
8.1%
Decimal Number
ValueCountFrequency (%)
1 60
47.2%
2 17
 
13.4%
4 14
 
11.0%
3 13
 
10.2%
8 8
 
6.3%
0 7
 
5.5%
5 3
 
2.4%
6 3
 
2.4%
9 2
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
h 5
50.0%
p 4
40.0%
m 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 30
54.5%
, 25
45.5%
Close Punctuation
ValueCountFrequency (%)
) 14
93.3%
] 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 14
93.3%
[ 1
 
6.7%
Space Separator
ValueCountFrequency (%)
113
100.0%
Control
ValueCountFrequency (%)
36
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 475
50.9%
Common 374
40.1%
Latin 84
 
9.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 79
16.6%
정 66
13.9%
측 65
13.7%
수 49
10.3%
도 45
9.5%
전 36
7.6%
대 30
 
6.3%
온 23
 
4.8%
위 21
 
4.4%
장 8
 
1.7%
Other values (18) 53
11.2%
Latin
ValueCountFrequency (%)
H 23
27.4%
P 14
16.7%
I 10
11.9%
E 5
 
6.0%
C 5
 
6.0%
h 5
 
6.0%
p 4
 
4.8%
N 3
 
3.6%
R 2
 
2.4%
O 2
 
2.4%
Other values (9) 11
13.1%
Common
ValueCountFrequency (%)
113
30.2%
1 60
16.0%
36
 
9.6%
. 30
 
8.0%
, 25
 
6.7%
2 17
 
4.5%
) 14
 
3.7%
4 14
 
3.7%
( 14
 
3.7%
3 13
 
3.5%
Other values (8) 38
 
10.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 475
50.9%
ASCII 458
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
113
24.7%
1 60
13.1%
36
 
7.9%
. 30
 
6.6%
, 25
 
5.5%
H 23
 
5.0%
2 17
 
3.7%
) 14
 
3.1%
4 14
 
3.1%
P 14
 
3.1%
Other values (27) 112
24.5%
Hangul
ValueCountFrequency (%)
기 79
16.6%
정 66
13.9%
측 65
13.7%
수 49
10.3%
도 45
9.5%
전 36
7.6%
대 30
 
6.3%
온 23
 
4.8%
위 21
 
4.4%
장 8
 
1.7%
Other values (18) 53
11.2%

타기관이전여부
Categorical

Distinct2
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size316.0 B
0
17 
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 row1

Common Values

ValueCountFrequency (%)
0 17
73.9%
1 6
 
26.1%

Length

2023-12-11T03:31:49.267063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:31:49.492826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 17
73.9%
1 6
 
26.1%

Sample

번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)전문인력총수자본금시설장비타기관이전여부
01지하수영향조사기관09_29_02_P3410000S001747110006648L0020060602201103103폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 중구 대봉동 55-68번지 대구맨션 A동 C호대구광역시 중구 명륜로 154, A동 C호 (대봉동,대구맨션)<NA>㈜지오익스20110310153330I2018-08-31 23:59:59.0<NA>344548.066275263409.635353401. 수위측정기 1대 2. Ph측정기 1대 3. DO측정기 1대 4. 전기전도도측정기 1대0
12지하수영향조사기관09_29_02_P3420000S001760110053360L0020090615<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 상매동 521-2번지대구광역시 동구 율암로 149-6 (상매동)41059범환지오텍(주)20170113161432I2018-08-31 23:59:59.0<NA>353814.465572266715.69777150수위측정장비1대,수소이온농도측정기1대 수온측정기1대,전기전도도측정기1대0
23지하수영향조사기관09_29_02_P3420000S001748110011934L0019990902201207093폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 신천동 366-6번지대구광역시 동구 화랑로9길 61 (신천동)<NA>㈜경창지오컨설탄트20120712093905I2018-08-31 23:59:59.0<NA>347127.396363264691.391836301. 수위측정기 1 2. PH측정기 1 3. 수온측정기 1 4. 전기전도도 측정기 10
34지하수영향조사기관09_29_02_P3420000S001748110006638L0019970909201310253폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 동구 신천동 149-31번지 149-31번지 4층대구광역시 동구 장등로 9 (신천동, 149-31번지 4층)<NA>㈜세경20131028152034I2018-08-31 23:59:59.0<NA>346509.281837264333.566505401. 수위측정기 1 2. PH측정기 1 3. 수온측정기 1 4. 전기전도도 측정기 10
45지하수영향조사기관09_29_02_P3440000S001714110005300L0019990310<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 남구 대명동 2033-28번지대구광역시 남구 명덕로 212-1 (대명동)<NA>수창개발(주)20150811121632I2018-08-31 23:59:59.0<NA>343857.119506262989.317772401. 수위측정기 1 2. PH측정기 1 3. 수온측정기 1 4. 전기전도도측정기 11
56지하수영향조사기관09_29_02_P3450000S001744110004474L0020100616<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 칠성동2가 715 대구역 서희스타힐스 상가동 206호대구광역시 북구 칠성남로 101, 상가동 206호 (칠성동2가, 대구역 서희스타힐스)41587신화산업개발주식회사20220119155104I2022-01-21 00:22:39.0<NA>343680.311178265487.3750330지하수위측정기 (심도250M) 1대 전기전도도 측정기(HI-8033) 1대 PH농도측정기(HI-8424) 1대 수온측정기(HI-8424) 1대1
67지하수영향조사기관09_29_02_P3450000S001744110000703L0019980209201004163폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 북구 서변동 1784-3번지대구광역시 북구 호국로43길 8-20 (서변동)<NA>창암건설㈜20100416141615I2018-08-31 23:59:59.0<NA>344222.852055270252.600222601. 수위측정기 1 2. PH측정기 1 3. 전기전도도 측정기0
78지하수영향조사기관09_29_02_P3460000S00502456546000000019970923201108253폐업2취소정지업체<NA><NA><NA><NA><NA><NA><NA>대구광역시 수성구 수성동2가 15-11번지<NA><NA>원일기술사사무소20130611112933I2018-08-31 23:59:59.0<NA><NA><NA>30수위측정기1, Ph측정기1, 수온측정기1, 전기전도도측정기1, 착정기10
89지하수영향조사기관09_29_02_P3460000S001701110456584L0020191231<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 수성구 범어동 63-25<NA><NA>주식회사 지원텍20210608151732U2021-06-10 02:40:00.0<NA>348355.00624263231.8183530지하수수위계 2대 PH측정기 수온계 전기전도도계0
910지하수영향조사기관09_29_02_P3460000S001754110018268L0020190704<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 수성구 만촌동 1380 가인 4층 A호대구광역시 수성구 동원로28길 50, 가인 4층 A호 (만촌동)42037(주)중앙수자원개발20220223114752I2022-02-25 00:22:37.0<NA>347901.216988264805.17617330수질측정기(HANNA-HI9813-6)(수온,pH, 전기전도도) 수위측정기(RICHITER NO.26)1
번호개방서비스명개방서비스아이디개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)전문인력총수자본금시설장비타기관이전여부
1314지하수영향조사기관09_29_02_P3480000S002001110345178L0020220221<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 하빈면 봉촌리 991-2대구광역시 달성군 하빈면 하빈남로 504-3442905지기토건(주)20220221094436U2022-02-23 02:40:00.0<NA>326126.020934264094.2262730지하수위측정장비, 수소이온농도, 수온, 전기전도도측정장비0
1415지하수영향조사기관09_29_02_P3480000S00513157854100000020090811<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 화원읍 천내리 837-3번지<NA><NA>하진개발20100503154000I2018-08-31 23:59:59.0<NA>335607.850668256712.42246840수위측정기, PH측정기, EC측정기0
1516지하수영향조사기관09_29_02_P3480000S001752110054050L0020200420<NA>1영업/정상1영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 다사읍 서재리 126-1대구광역시 달성군 다사읍 서재본길 5, 3층42929뉴지오텍(주)20210122135903I2021-01-24 00:23:04.0<NA>335091.359493264527.918012301.지하수 수위측정기 장비(대수성시험) 2.수소이온농도(pH), 수온, 전기전도도(EC)측정장비 [모델명 HI-9813-6]0
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