Overview

Dataset statistics

Number of variables10
Number of observations30
Missing cells7
Missing cells (%)2.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory86.4 B

Variable types

Text6
DateTime2
Numeric2

Dataset

Description경기도 화성시 먹는물수질검사기관지정현황에 대한 데이터로 지정번호, 지정일자, 기관명, 대표자, 실험실소재지, 도로명주소, 위도, 경도, 전화번호, 기준일자 등의 항목을 제공합니다.
Author경기도 화성시
URLhttps://www.data.go.kr/data/15092311/fileData.do

Alerts

기준일자 has constant value ""Constant
도로명주소 has 3 (10.0%) missing valuesMissing
위도 has 2 (6.7%) missing valuesMissing
경도 has 2 (6.7%) missing valuesMissing
지정번호 has unique valuesUnique
지정일자 has unique valuesUnique
기 관 명 has unique valuesUnique
실험실 소재지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:30:56.253829
Analysis finished2023-12-12 20:30:57.592696
Duration1.34 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지정번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T05:30:57.746152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.8
Min length7

Characters and Unicode

Total characters234
Distinct characters16
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row한강청 제2호
2nd row한강청 제4호
3rd row한강청 제6호
4th row한강청 제7호
5th row한강청 제8호
ValueCountFrequency (%)
한강청 30
50.0%
제27호 1
 
1.7%
제45호 1
 
1.7%
제44호 1
 
1.7%
제43호 1
 
1.7%
제42호 1
 
1.7%
제41호 1
 
1.7%
제40호 1
 
1.7%
제38호 1
 
1.7%
제37호 1
 
1.7%
Other values (21) 21
35.0%
2023-12-13T05:30:58.067146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 30
12.8%
강 30
12.8%
청 30
12.8%
30
12.8%
제 30
12.8%
호 30
12.8%
2 10
 
4.3%
3 10
 
4.3%
4 9
 
3.8%
1 6
 
2.6%
Other values (6) 19
8.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150
64.1%
Decimal Number 54
 
23.1%
Space Separator 30
 
12.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
18.5%
3 10
18.5%
4 9
16.7%
1 6
11.1%
6 5
9.3%
0 4
 
7.4%
7 3
 
5.6%
5 3
 
5.6%
8 2
 
3.7%
9 2
 
3.7%
Other Letter
ValueCountFrequency (%)
한 30
20.0%
강 30
20.0%
청 30
20.0%
제 30
20.0%
호 30
20.0%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150
64.1%
Common 84
35.9%

Most frequent character per script

Common
ValueCountFrequency (%)
30
35.7%
2 10
 
11.9%
3 10
 
11.9%
4 9
 
10.7%
1 6
 
7.1%
6 5
 
6.0%
0 4
 
4.8%
7 3
 
3.6%
5 3
 
3.6%
8 2
 
2.4%
Hangul
ValueCountFrequency (%)
한 30
20.0%
강 30
20.0%
청 30
20.0%
제 30
20.0%
호 30
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150
64.1%
ASCII 84
35.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 30
20.0%
강 30
20.0%
청 30
20.0%
제 30
20.0%
호 30
20.0%
ASCII
ValueCountFrequency (%)
30
35.7%
2 10
 
11.9%
3 10
 
11.9%
4 9
 
10.7%
1 6
 
7.1%
6 5
 
6.0%
0 4
 
4.8%
7 3
 
3.6%
5 3
 
3.6%
8 2
 
2.4%

지정일자
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum1993-10-18 00:00:00
Maximum2020-03-12 00:00:00
2023-12-13T05:30:58.221031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:30:58.364614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

기 관 명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T05:30:58.586886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length14
Mean length10.966667
Min length4

Characters and Unicode

Total characters329
Distinct characters111
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

Unique30 ?
Unique (%)100.0%

Sample

1st row(재)한국환경수도연구원
2nd row㈜산업공해연구소
3rd row㈜한국종합공해시험연구소
4th row한국수자원공사 한강권역본부
5th row코웨이㈜
ValueCountFrequency (%)
상하수도사업소 4
 
9.3%
재)한국환경수도연구원 1
 
2.3%
워터스생활환경연구소 1
 
2.3%
용인시 1
 
2.3%
사)kotiti시험연구원 1
 
2.3%
주)청룡환경 1
 
2.3%
주)피엘아이환경기술연구원 1
 
2.3%
재)환경보건기술연구원 1
 
2.3%
혜성환경 1
 
2.3%
농협경제지주(주)축산연구원 1
 
2.3%
Other values (30) 30
69.8%
2023-12-13T05:30:58.947052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
13
 
4.0%
경 12
 
3.6%
구 12
 
3.6%
연 12
 
3.6%
수 12
 
3.6%
시 11
 
3.3%
원 11
 
3.3%
환 10
 
3.0%
소 10
 
3.0%
) 10
 
3.0%
Other values (101) 216
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 279
84.8%
Space Separator 13
 
4.0%
Close Punctuation 10
 
3.0%
Open Punctuation 10
 
3.0%
Other Symbol 9
 
2.7%
Uppercase Letter 8
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 12
 
4.3%
구 12
 
4.3%
연 12
 
4.3%
수 12
 
4.3%
시 11
 
3.9%
원 11
 
3.9%
환 10
 
3.6%
소 10
 
3.6%
업 9
 
3.2%
사 8
 
2.9%
Other values (92) 172
61.6%
Uppercase Letter
ValueCountFrequency (%)
K 2
25.0%
I 2
25.0%
T 2
25.0%
S 1
12.5%
O 1
12.5%
Space Separator
ValueCountFrequency (%)
13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 288
87.5%
Common 33
 
10.0%
Latin 8
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 12
 
4.2%
구 12
 
4.2%
연 12
 
4.2%
수 12
 
4.2%
시 11
 
3.8%
원 11
 
3.8%
환 10
 
3.5%
소 10
 
3.5%
㈜ 9
 
3.1%
업 9
 
3.1%
Other values (93) 180
62.5%
Latin
ValueCountFrequency (%)
K 2
25.0%
I 2
25.0%
T 2
25.0%
S 1
12.5%
O 1
12.5%
Common
ValueCountFrequency (%)
13
39.4%
) 10
30.3%
( 10
30.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 279
84.8%
ASCII 41
 
12.5%
None 9
 
2.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13
31.7%
) 10
24.4%
( 10
24.4%
K 2
 
4.9%
I 2
 
4.9%
T 2
 
4.9%
S 1
 
2.4%
O 1
 
2.4%
Hangul
ValueCountFrequency (%)
경 12
 
4.3%
구 12
 
4.3%
연 12
 
4.3%
수 12
 
4.3%
시 11
 
3.9%
원 11
 
3.9%
환 10
 
3.6%
소 10
 
3.6%
업 9
 
3.2%
사 8
 
2.9%
Other values (92) 172
61.6%
None
ValueCountFrequency (%)
㈜ 9
100.0%

대표자
Text

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T05:30:59.140176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.3666667
Min length3

Characters and Unicode

Total characters101
Distinct characters57
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)80.0%

Sample

1st row김정근
2nd row이기채
3rd row박태현
4th row한강유역본부장
5th row김동현
ValueCountFrequency (%)
사업소장 6
 
20.0%
김정근 1
 
3.3%
배제천 1
 
3.3%
김미옥 1
 
3.3%
류권주 1
 
3.3%
장준영 1
 
3.3%
김대민 1
 
3.3%
박종언 1
 
3.3%
방완문 1
 
3.3%
이동훈 1
 
3.3%
Other values (15) 15
50.0%
2023-12-13T05:30:59.457051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 10
 
9.9%
김 8
 
7.9%
사 6
 
5.9%
소 6
 
5.9%
업 6
 
5.9%
정 3
 
3.0%
이 3
 
3.0%
부 2
 
2.0%
종 2
 
2.0%
영 2
 
2.0%
Other values (47) 53
52.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 101
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 10
 
9.9%
김 8
 
7.9%
사 6
 
5.9%
소 6
 
5.9%
업 6
 
5.9%
정 3
 
3.0%
이 3
 
3.0%
부 2
 
2.0%
종 2
 
2.0%
영 2
 
2.0%
Other values (47) 53
52.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 101
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 10
 
9.9%
김 8
 
7.9%
사 6
 
5.9%
소 6
 
5.9%
업 6
 
5.9%
정 3
 
3.0%
이 3
 
3.0%
부 2
 
2.0%
종 2
 
2.0%
영 2
 
2.0%
Other values (47) 53
52.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 101
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 10
 
9.9%
김 8
 
7.9%
사 6
 
5.9%
소 6
 
5.9%
업 6
 
5.9%
정 3
 
3.0%
이 3
 
3.0%
부 2
 
2.0%
종 2
 
2.0%
영 2
 
2.0%
Other values (47) 53
52.5%

실험실 소재지
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T05:30:59.705690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length33.5
Mean length26.866667
Min length17

Characters and Unicode

Total characters806
Distinct characters144
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

Unique30 ?
Unique (%)100.0%

Sample

1st row서울시 영등포구 양평로28사길 29
2nd row서울시 금천구 가산동 345-30 남성프라자빌딩 10층
3rd row서울시 구로구 개봉동 170-33 금석빌딩 411호
4th row경기도 과천시 갈현동 649-1
5th row서울시 관악구 관악로 1(신림동, 서울대학교 연구공원내 코웨이알앤디센터 1층)
ValueCountFrequency (%)
경기도 21
 
12.5%
서울시 8
 
4.8%
수원시 4
 
2.4%
권선구 3
 
1.8%
구로구 2
 
1.2%
성남시 2
 
1.2%
안성시 2
 
1.2%
관악구 2
 
1.2%
화성시 2
 
1.2%
하남시 2
 
1.2%
Other values (119) 120
71.4%
2023-12-13T05:31:00.102203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
138
 
17.1%
1 39
 
4.8%
시 32
 
4.0%
경 24
 
3.0%
구 24
 
3.0%
도 22
 
2.7%
로 22
 
2.7%
2 22
 
2.7%
기 22
 
2.7%
동 20
 
2.5%
Other values (134) 441
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 481
59.7%
Decimal Number 146
 
18.1%
Space Separator 138
 
17.1%
Dash Punctuation 11
 
1.4%
Open Punctuation 11
 
1.4%
Close Punctuation 11
 
1.4%
Other Punctuation 6
 
0.7%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 32
 
6.7%
경 24
 
5.0%
구 24
 
5.0%
도 22
 
4.6%
로 22
 
4.6%
기 22
 
4.6%
동 20
 
4.2%
서 14
 
2.9%
산 11
 
2.3%
길 11
 
2.3%
Other values (117) 279
58.0%
Decimal Number
ValueCountFrequency (%)
1 39
26.7%
2 22
15.1%
0 17
11.6%
4 14
 
9.6%
3 13
 
8.9%
6 10
 
6.8%
9 10
 
6.8%
5 10
 
6.8%
7 6
 
4.1%
8 5
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
138
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 481
59.7%
Common 323
40.1%
Latin 2
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 32
 
6.7%
경 24
 
5.0%
구 24
 
5.0%
도 22
 
4.6%
로 22
 
4.6%
기 22
 
4.6%
동 20
 
4.2%
서 14
 
2.9%
산 11
 
2.3%
길 11
 
2.3%
Other values (117) 279
58.0%
Common
ValueCountFrequency (%)
138
42.7%
1 39
 
12.1%
2 22
 
6.8%
0 17
 
5.3%
4 14
 
4.3%
3 13
 
4.0%
- 11
 
3.4%
( 11
 
3.4%
) 11
 
3.4%
6 10
 
3.1%
Other values (5) 37
 
11.5%
Latin
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 481
59.7%
ASCII 325
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138
42.5%
1 39
 
12.0%
2 22
 
6.8%
0 17
 
5.2%
4 14
 
4.3%
3 13
 
4.0%
- 11
 
3.4%
( 11
 
3.4%
) 11
 
3.4%
6 10
 
3.1%
Other values (7) 39
 
12.0%
Hangul
ValueCountFrequency (%)
시 32
 
6.7%
경 24
 
5.0%
구 24
 
5.0%
도 22
 
4.6%
로 22
 
4.6%
기 22
 
4.6%
동 20
 
4.2%
서 14
 
2.9%
산 11
 
2.3%
길 11
 
2.3%
Other values (117) 279
58.0%

도로명주소
Text

MISSING 

Distinct26
Distinct (%)96.3%
Missing3
Missing (%)10.0%
Memory size372.0 B
2023-12-13T05:31:00.351844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.074074
Min length15

Characters and Unicode

Total characters515
Distinct characters92
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

Unique25 ?
Unique (%)92.6%

Sample

1st row서울특별시 영등포구 양평로28사길 29
2nd row서울특별시 금천구 디지털로 130
3rd row서울특별시 구로구 경인로 352
4th row경기도 과천시 교육원로 11
5th row서울특별시 관악구 관악로 1
ValueCountFrequency (%)
경기도 18
 
15.3%
서울특별시 8
 
6.8%
수원시 4
 
3.4%
권선구 3
 
2.5%
성남시 2
 
1.7%
29 2
 
1.7%
하남시 2
 
1.7%
화성시 2
 
1.7%
11 2
 
1.7%
금천구 2
 
1.7%
Other values (69) 73
61.9%
2023-12-13T05:31:00.782463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
17.7%
시 30
 
5.8%
로 28
 
5.4%
1 27
 
5.2%
경 19
 
3.7%
2 18
 
3.5%
도 18
 
3.5%
기 18
 
3.5%
구 18
 
3.5%
서 12
 
2.3%
Other values (82) 236
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 327
63.5%
Decimal Number 94
 
18.3%
Space Separator 91
 
17.7%
Dash Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 30
 
9.2%
로 28
 
8.6%
경 19
 
5.8%
도 18
 
5.5%
기 18
 
5.5%
구 18
 
5.5%
서 12
 
3.7%
길 11
 
3.4%
별 9
 
2.8%
울 8
 
2.4%
Other values (70) 156
47.7%
Decimal Number
ValueCountFrequency (%)
1 27
28.7%
2 18
19.1%
3 9
 
9.6%
9 8
 
8.5%
4 7
 
7.4%
0 7
 
7.4%
5 7
 
7.4%
6 5
 
5.3%
7 3
 
3.2%
8 3
 
3.2%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 327
63.5%
Common 188
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 30
 
9.2%
로 28
 
8.6%
경 19
 
5.8%
도 18
 
5.5%
기 18
 
5.5%
구 18
 
5.5%
서 12
 
3.7%
길 11
 
3.4%
별 9
 
2.8%
울 8
 
2.4%
Other values (70) 156
47.7%
Common
ValueCountFrequency (%)
91
48.4%
1 27
 
14.4%
2 18
 
9.6%
3 9
 
4.8%
9 8
 
4.3%
4 7
 
3.7%
0 7
 
3.7%
5 7
 
3.7%
6 5
 
2.7%
7 3
 
1.6%
Other values (2) 6
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 327
63.5%
ASCII 188
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
48.4%
1 27
 
14.4%
2 18
 
9.6%
3 9
 
4.8%
9 8
 
4.3%
4 7
 
3.7%
0 7
 
3.7%
5 7
 
3.7%
6 5
 
2.7%
7 3
 
1.6%
Other values (2) 6
 
3.2%
Hangul
ValueCountFrequency (%)
시 30
 
9.2%
로 28
 
8.6%
경 19
 
5.8%
도 18
 
5.5%
기 18
 
5.5%
구 18
 
5.5%
서 12
 
3.7%
길 11
 
3.4%
별 9
 
2.8%
울 8
 
2.4%
Other values (70) 156
47.7%

위도
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)96.4%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean37.429306
Minimum37.0102
Maximum37.710055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:31:00.950771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.0102
5-th percentile37.226534
Q137.322527
median37.46196
Q337.52937
95-th percentile37.640032
Maximum37.710055
Range0.69985488
Interquartile range (IQR)0.2068436

Descriptive statistics

Standard deviation0.15361188
Coefficient of variation (CV)0.0041040537
Kurtosis0.6504836
Mean37.429306
Median Absolute Deviation (MAD)0.095196035
Skewness-0.64111689
Sum1048.0206
Variance0.023596611
MonotonicityNot monotonic
2023-12-13T05:31:01.082454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
37.46195981 2
 
6.7%
37.43415087 1
 
3.3%
37.22875381 1
 
3.3%
37.26953601 1
 
3.3%
37.22533927 1
 
3.3%
37.56891381 1
 
3.3%
37.55350379 1
 
3.3%
37.71005529 1
 
3.3%
37.52450261 1
 
3.3%
37.34966481 1
 
3.3%
Other values (17) 17
56.7%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
37.01020041 1
3.3%
37.22533927 1
3.3%
37.22875381 1
3.3%
37.24271995 1
3.3%
37.26953601 1
3.3%
37.26963308 1
3.3%
37.30106537 1
3.3%
37.32968057 1
3.3%
37.34966481 1
3.3%
37.38182886 1
3.3%
ValueCountFrequency (%)
37.71005529 1
3.3%
37.65748631 1
3.3%
37.60761705 1
3.3%
37.56891381 1
3.3%
37.5608079 1
3.3%
37.55350379 1
3.3%
37.54397364 1
3.3%
37.52450261 1
3.3%
37.50729207 1
3.3%
37.49666398 1
3.3%

경도
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)96.4%
Missing2
Missing (%)6.7%
Infinite0
Infinite (%)0.0%
Mean126.97462
Minimum126.64919
Maximum127.26377
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-13T05:31:01.254359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.64919
5-th percentile126.78007
Q1126.87495
median126.96176
Q3127.07793
95-th percentile127.20894
Maximum127.26377
Range0.6145836
Interquartile range (IQR)0.20297435

Descriptive statistics

Standard deviation0.1502375
Coefficient of variation (CV)0.0011832089
Kurtosis-0.39813216
Mean126.97462
Median Absolute Deviation (MAD)0.10112125
Skewness0.14511337
Sum3555.2894
Variance0.022571308
MonotonicityNot monotonic
2023-12-13T05:31:01.414559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
126.9520511 2
 
6.7%
127.1765036 1
 
3.3%
127.0622431 1
 
3.3%
126.9929582 1
 
3.3%
126.970011 1
 
3.3%
126.6491867 1
 
3.3%
127.1946803 1
 
3.3%
127.1249803 1
 
3.3%
127.172798 1
 
3.3%
126.9535006 1
 
3.3%
Other values (17) 17
56.7%
(Missing) 2
 
6.7%
ValueCountFrequency (%)
126.6491867 1
3.3%
126.761667 1
3.3%
126.8142428 1
3.3%
126.8192658 1
3.3%
126.8325633 1
3.3%
126.8592587 1
3.3%
126.8600006 1
3.3%
126.8799372 1
3.3%
126.8818894 1
3.3%
126.8894745 1
3.3%
ValueCountFrequency (%)
127.2637703 1
3.3%
127.2166199 1
3.3%
127.1946803 1
3.3%
127.1765036 1
3.3%
127.172798 1
3.3%
127.1307891 1
3.3%
127.1249803 1
3.3%
127.0622431 1
3.3%
127.0275265 1
3.3%
126.9929582 1
3.3%

전화번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-13T05:31:01.652625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.166667
Min length11

Characters and Unicode

Total characters365
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row02-2637-1234
2nd row02-2026-1274
3rd row02-2060-7875
4th row02-2150-0376
5th row02-870-5177
ValueCountFrequency (%)
02-2637-1234 1
 
3.3%
02-2026-1274 1
 
3.3%
031-296-8808 1
 
3.3%
031-299-5833 1
 
3.3%
032-590-4904 1
 
3.3%
031-790-0030 1
 
3.3%
031-844-1720 1
 
3.3%
031-772-4538 1
 
3.3%
031-689-3231 1
 
3.3%
031-659-1386 1
 
3.3%
Other values (20) 20
66.7%
2023-12-13T05:31:02.420310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 61
16.7%
0 55
15.1%
3 45
12.3%
1 39
10.7%
2 38
10.4%
4 26
7.1%
7 24
 
6.6%
8 23
 
6.3%
5 23
 
6.3%
6 16
 
4.4%
Other values (2) 15
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 302
82.7%
Dash Punctuation 61
 
16.7%
Math Symbol 2
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 55
18.2%
3 45
14.9%
1 39
12.9%
2 38
12.6%
4 26
8.6%
7 24
7.9%
8 23
7.6%
5 23
7.6%
6 16
 
5.3%
9 13
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 365
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 61
16.7%
0 55
15.1%
3 45
12.3%
1 39
10.7%
2 38
10.4%
4 26
7.1%
7 24
 
6.6%
8 23
 
6.3%
5 23
 
6.3%
6 16
 
4.4%
Other values (2) 15
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 365
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 61
16.7%
0 55
15.1%
3 45
12.3%
1 39
10.7%
2 38
10.4%
4 26
7.1%
7 24
 
6.6%
8 23
 
6.3%
5 23
 
6.3%
6 16
 
4.4%
Other values (2) 15
 
4.1%

기준일자
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-08-09 00:00:00
Maximum2021-08-09 00:00:00
2023-12-13T05:31:02.580881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:31:02.707557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:30:56.981756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:30:56.770426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:30:57.080415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:30:56.879511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:31:02.822170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지정번호지정일자기 관 명대표자실험실 소재지도로명주소위도경도전화번호
지정번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
지정일자1.0001.0001.0001.0001.0001.0001.0001.0001.000
기 관 명1.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0000.9520.0000.0001.000
실험실 소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0000.9521.0001.0001.0001.0001.000
위도1.0001.0001.0000.0001.0001.0001.0000.7771.000
경도1.0001.0001.0000.0001.0001.0000.7771.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-13T05:31:02.968239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.465
경도-0.4651.000

Missing values

2023-12-13T05:30:57.216041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:30:57.403596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-13T05:30:57.525504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

지정번호지정일자기 관 명대표자실험실 소재지도로명주소위도경도전화번호기준일자
0한강청 제2호1993-10-18(재)한국환경수도연구원김정근서울시 영등포구 양평로28사길 29서울특별시 영등포구 양평로28사길 2937.543974126.88947502-2637-12342021-08-09
1한강청 제4호1995-06-28㈜산업공해연구소이기채서울시 금천구 가산동 345-30 남성프라자빌딩 10층서울특별시 금천구 디지털로 13037.475459126.88188902-2026-12742021-08-09
2한강청 제6호1995-12-20㈜한국종합공해시험연구소박태현서울시 구로구 개봉동 170-33 금석빌딩 411호서울특별시 구로구 경인로 35237.496664126.85925902-2060-78752021-08-09
3한강청 제7호1996-04-08한국수자원공사 한강권역본부한강유역본부장경기도 과천시 갈현동 649-1경기도 과천시 교육원로 1137.422884126.98813902-2150-03762021-08-09
4한강청 제8호1996-07-19코웨이㈜김동현서울시 관악구 관악로 1(신림동, 서울대학교 연구공원내 코웨이알앤디센터 1층)서울특별시 관악구 관악로 137.46196126.95205102-870-51772021-08-09
5한강청 제9호1997-12-16안산시 상하수도사업소사업소장경기도 시흥시 광석동 146-1 연성정수장내경기도 시흥시 시흥대로412번길 8737.381829126.814243031-481-27412021-08-09
6한강청 제10호1999-04-22부천시 정수과 (까치울정수장)부천시장경기도 부천시 오정구 작동 산60-8경기도 부천시 길주로 69137.507292126.819266032-625-33532021-08-09
7한강청 제12호2003-02-27수원시 상수도사업소(광교정수장)사업소장경기도 수원시 장안구 광교산로 119 (하광교동)경기도 수원시 장안구 광교산로 11937.301065127.027526031-228-48712021-08-09
8한강청 제15호2007-01-02(재)한국건설생활환경시험연구원김경식서울시 금천구 가산디지털1로 199(가산동)서울특별시 금천구 가산디지털1로 19937.483137126.87993702-2102-25982021-08-09
9한강청 제16호2007-01-04㈜워트랩생활환경연구원이성우경기도 수원시 권선구 서둔동 14-17경기도 수원시 권선구 서호동로 3937.269633126.992473031-292-44762021-08-09
지정번호지정일자기 관 명대표자실험실 소재지도로명주소위도경도전화번호기준일자
20한강청 제36호2014-12-16혜성환경장공례경기도 안양시 동안구 귀인로 79번길 36<NA><NA><NA>031-473-3413-52021-08-09
21한강청 제37호2015-05-04농협경제지주(주)축산연구원고종열경기도 안성시 공도읍 대신두길 42-21<NA><NA><NA>031-659-13862021-08-09
22한강청 제38호2016-05-12워터스생활환경연구소이동훈경기도 군포시 고산로 148번길 17, A동 1204호경기도 군포시 고산로148번길 1737.349665126.953501031-689-32312021-08-09
23한강청 제40호2017-04-14㈜다솔물환경연구소방완문경기도 하남시 초광산단로 126, 우일빌딩 3층경기도 하남시 초광산단로 12637.524503127.172798031-772-45382021-08-09
24한강청 제41호2017-05-23중앙생명연구원(주)박종언경기도 남양주시 별내면 청학로 54번길 50경기도 남양주시 별내면 청학로54번길 5037.710055127.12498031-844-17202021-08-09
25한강청 제42호2018-06-19㈜키위수질시험센터김대민경기도 하남시 조정대로150, 851호(덕풍동, 아이테코)경기도 하남시 조정대로 15037.553504127.19468031-790-00302021-08-09
26한강청 제43호2018-12-03한국환경공단장준영인천 서구 정서진로 410 환경산업연구단지 C동 환경기술연구소 208호인천광역시 서구 정서진로 41037.568914126.649187032-590-49042021-08-09
27한강청 제44호2019-01-17SK매직㈜ 화성공장류권주경기도 화성시 봉담읍 효행로 250경기도 화성시 봉담읍 효행로 25037.225339126.970011031-299-58332021-08-09
28한강청 제45호2019-04-18㈜ 국토엔지니어링김미옥경기도 수원시 권선구 수인로 43-26(서둔동)경기도 수원시 권선구 수인로 43-2637.269536126.992958031-296-88082021-08-09
29한강청 제46호2020-03-12㈜일영랩김홍래경기도 화성시 반월길12번길 9-11(반월동)경기도 화성시 반월길12번길 9-1137.228754127.062243031-237-33012021-08-09