Overview

Dataset statistics

Number of variables10
Number of observations21
Missing cells8
Missing cells (%)3.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory89.3 B

Variable types

DateTime1
Text5
Categorical1
Numeric3

Alerts

집계년월 has constant value ""Constant
지정기관명 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도High correlation
WGS84위도 is highly overall correlated with 소재지우편번호High correlation
소재지우편번호 has 2 (9.5%) missing valuesMissing
소재지지번주소 has 2 (9.5%) missing valuesMissing
WGS84위도 has 2 (9.5%) missing valuesMissing
WGS84경도 has 2 (9.5%) missing valuesMissing
검사기관명 has unique valuesUnique
연락처 has unique valuesUnique
소재지도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-03-12 23:13:19.768993
Analysis finished2024-03-12 23:13:20.921101
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년월
Date

CONSTANT 

Distinct1
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2023-02-01 00:00:00
Maximum2023-02-01 00:00:00
2024-03-13T08:13:20.954046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:21.021989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시군명
Text

Distinct14
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-13T08:13:21.130327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.047619
Min length3

Characters and Unicode

Total characters64
Distinct characters20
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

Unique8 ?
Unique (%)38.1%

Sample

1st row고양시
2nd row과천시
3rd row군포시
4th row김포시
5th row남양주시
ValueCountFrequency (%)
성남시 3
14.3%
수원시 2
9.5%
안성시 2
9.5%
안양시 2
9.5%
하남시 2
9.5%
화성시 2
9.5%
고양시 1
 
4.8%
과천시 1
 
4.8%
군포시 1
 
4.8%
김포시 1
 
4.8%
Other values (4) 4
19.0%
2024-03-13T08:13:21.338013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 22
34.4%
성 7
 
10.9%
남 6
 
9.4%
안 4
 
6.2%
양 4
 
6.2%
수 2
 
3.1%
원 2
 
3.1%
하 2
 
3.1%
화 2
 
3.1%
천 2
 
3.1%
Other values (10) 11
17.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 22
34.4%
성 7
 
10.9%
남 6
 
9.4%
안 4
 
6.2%
양 4
 
6.2%
수 2
 
3.1%
원 2
 
3.1%
하 2
 
3.1%
화 2
 
3.1%
천 2
 
3.1%
Other values (10) 11
17.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 22
34.4%
성 7
 
10.9%
남 6
 
9.4%
안 4
 
6.2%
양 4
 
6.2%
수 2
 
3.1%
원 2
 
3.1%
하 2
 
3.1%
화 2
 
3.1%
천 2
 
3.1%
Other values (10) 11
17.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 22
34.4%
성 7
 
10.9%
남 6
 
9.4%
안 4
 
6.2%
양 4
 
6.2%
수 2
 
3.1%
원 2
 
3.1%
하 2
 
3.1%
화 2
 
3.1%
천 2
 
3.1%
Other values (10) 11
17.2%

검사기관명
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-13T08:13:21.509989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length14
Mean length11.190476
Min length5

Characters and Unicode

Total characters235
Distinct characters101
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

Unique21 ?
Unique (%)100.0%

Sample

1st row고양시상하수도사업소
2nd row한국수자원공사 한강권역본부
3rd row㈜한국유로핀즈 분석서비스
4th row김포시상하수도사업소
5th row중앙생명연구원(주)
ValueCountFrequency (%)
고양시상하수도사업소 1
 
4.2%
한국수자원공사 1
 
4.2%
sk매직(주 1
 
4.2%
주)일영랩 1
 
4.2%
주)다솔물환경연구소 1
 
4.2%
주)키위수질시험센터 1
 
4.2%
용인시상수도사업소 1
 
4.2%
주)혜성환경 1
 
4.2%
㈜워트랩생활환경연구원 1
 
4.2%
한경대학교 1
 
4.2%
Other values (14) 14
58.3%
2024-03-13T08:13:21.786233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 12
 
5.1%
) 10
 
4.3%
시 10
 
4.3%
( 10
 
4.3%
사 9
 
3.8%
주 8
 
3.4%
소 8
 
3.4%
경 7
 
3.0%
연 7
 
3.0%
구 7
 
3.0%
Other values (91) 147
62.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 200
85.1%
Close Punctuation 10
 
4.3%
Open Punctuation 10
 
4.3%
Uppercase Letter 8
 
3.4%
Other Symbol 4
 
1.7%
Space Separator 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 12
 
6.0%
시 10
 
5.0%
사 9
 
4.5%
주 8
 
4.0%
소 8
 
4.0%
경 7
 
3.5%
연 7
 
3.5%
구 7
 
3.5%
원 7
 
3.5%
업 7
 
3.5%
Other values (82) 118
59.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
25.0%
I 2
25.0%
T 2
25.0%
S 1
12.5%
O 1
12.5%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 204
86.8%
Common 23
 
9.8%
Latin 8
 
3.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 12
 
5.9%
시 10
 
4.9%
사 9
 
4.4%
주 8
 
3.9%
소 8
 
3.9%
경 7
 
3.4%
연 7
 
3.4%
구 7
 
3.4%
원 7
 
3.4%
업 7
 
3.4%
Other values (83) 122
59.8%
Latin
ValueCountFrequency (%)
K 2
25.0%
I 2
25.0%
T 2
25.0%
S 1
12.5%
O 1
12.5%
Common
ValueCountFrequency (%)
) 10
43.5%
( 10
43.5%
3
 
13.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 200
85.1%
ASCII 31
 
13.2%
None 4
 
1.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 12
 
6.0%
시 10
 
5.0%
사 9
 
4.5%
주 8
 
4.0%
소 8
 
4.0%
경 7
 
3.5%
연 7
 
3.5%
구 7
 
3.5%
원 7
 
3.5%
업 7
 
3.5%
Other values (82) 118
59.0%
ASCII
ValueCountFrequency (%)
) 10
32.3%
( 10
32.3%
3
 
9.7%
K 2
 
6.5%
I 2
 
6.5%
T 2
 
6.5%
S 1
 
3.2%
O 1
 
3.2%
None
ValueCountFrequency (%)
㈜ 4
100.0%

연락처
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-13T08:13:21.942071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.190476
Min length12

Characters and Unicode

Total characters256
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)100.0%

Sample

1st row031-8075-4542
2nd row02-2150-0376
3rd row031-361-7777
4th row031-980-5684
5th row031-844-1720
ValueCountFrequency (%)
031-8075-4542 1
 
4.8%
031-481-3802 1
 
4.8%
031-237-3301 1
 
4.8%
031-772-4530 1
 
4.8%
031-790-0030 1
 
4.8%
031-324-4256 1
 
4.8%
031-4733-4135 1
 
4.8%
031-292-4477 1
 
4.8%
031-6705-6378 1
 
4.8%
031-659-1385 1
 
4.8%
Other values (11) 11
52.4%
2024-03-13T08:13:22.218285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 42
16.4%
3 39
15.2%
0 36
14.1%
1 28
10.9%
4 23
9.0%
7 21
8.2%
2 19
7.4%
5 18
7.0%
8 13
 
5.1%
6 10
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 214
83.6%
Dash Punctuation 42
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 39
18.2%
0 36
16.8%
1 28
13.1%
4 23
10.7%
7 21
9.8%
2 19
8.9%
5 18
8.4%
8 13
 
6.1%
6 10
 
4.7%
9 7
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 256
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 42
16.4%
3 39
15.2%
0 36
14.1%
1 28
10.9%
4 23
9.0%
7 21
8.2%
2 19
7.4%
5 18
7.0%
8 13
 
5.1%
6 10
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 256
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 42
16.4%
3 39
15.2%
0 36
14.1%
1 28
10.9%
4 23
9.0%
7 21
8.2%
2 19
7.4%
5 18
7.0%
8 13
 
5.1%
6 10
 
3.9%

지정기관명
Categorical

CONSTANT 

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

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한강유역환경청 21
100.0%

Length

2024-03-13T08:13:22.318037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:13:22.387777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한강유역환경청 21
100.0%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing2
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean14751.158
Minimum10123
Maximum18384
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-13T08:13:22.455823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10123
5-th percentile10426.3
Q113095.5
median14477
Q316836.5
95-th percentile18306.6
Maximum18384
Range8261
Interquartile range (IQR)3741

Descriptive statistics

Standard deviation2507.2362
Coefficient of variation (CV)0.16996877
Kurtosis-0.85029136
Mean14751.158
Median Absolute Deviation (MAD)1813
Skewness-0.2197121
Sum280272
Variance6286233.1
MonotonicityNot monotonic
2024-03-13T08:13:22.537294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
15849 1
 
4.8%
18298 1
 
4.8%
18384 1
 
4.8%
12989 1
 
4.8%
12930 1
 
4.8%
17031 1
 
4.8%
14079 1
 
4.8%
14084 1
 
4.8%
17579 1
 
4.8%
10460 1
 
4.8%
Other values (9) 9
42.9%
(Missing) 2
 
9.5%
ValueCountFrequency (%)
10123 1
4.8%
10460 1
4.8%
12077 1
4.8%
12930 1
4.8%
12989 1
4.8%
13202 1
4.8%
13229 1
4.8%
14079 1
4.8%
14084 1
4.8%
14477 1
4.8%
ValueCountFrequency (%)
18384 1
4.8%
18298 1
4.8%
17579 1
4.8%
17558 1
4.8%
17031 1
4.8%
16642 1
4.8%
16290 1
4.8%
15849 1
4.8%
14991 1
4.8%
14477 1
4.8%

소재지지번주소
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing2
Missing (%)9.5%
Memory size300.0 B
2024-03-13T08:13:22.728201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length33
Mean length27.368421
Min length19

Characters and Unicode

Total characters520
Distinct characters110
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 row경기도 고양시 덕양구 주교동 601번지 고양시티타운 1층 수도시설과 수질검사팀
2nd row경기도 군포시 당정동 352-18번지
3rd row경기도 김포시 고촌읍 풍곡리 221번지
4th row경기도 남양주시 별내면 청학리 215-4번지
5th row경기도 부천시 오정구 작동 산60-8번지
ValueCountFrequency (%)
경기도 19
 
17.3%
수질검사팀 2
 
1.8%
상대원동 2
 
1.8%
하남시 2
 
1.8%
수원시 2
 
1.8%
안양시 2
 
1.8%
성남시 2
 
1.8%
중원구 2
 
1.8%
화성시 2
 
1.8%
안성시 2
 
1.8%
Other values (73) 73
66.4%
2024-03-13T08:13:23.028005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
91
 
17.5%
시 23
 
4.4%
도 21
 
4.0%
1 21
 
4.0%
경 20
 
3.8%
지 19
 
3.7%
기 19
 
3.7%
번 19
 
3.7%
동 17
 
3.3%
- 12
 
2.3%
Other values (100) 258
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 330
63.5%
Space Separator 91
 
17.5%
Decimal Number 87
 
16.7%
Dash Punctuation 12
 
2.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 23
 
7.0%
도 21
 
6.4%
경 20
 
6.1%
지 19
 
5.8%
기 19
 
5.8%
번 19
 
5.8%
동 17
 
5.2%
구 9
 
2.7%
수 8
 
2.4%
안 8
 
2.4%
Other values (88) 167
50.6%
Decimal Number
ValueCountFrequency (%)
1 21
24.1%
3 12
13.8%
2 11
12.6%
0 10
11.5%
5 9
10.3%
4 7
 
8.0%
6 6
 
6.9%
9 5
 
5.7%
8 4
 
4.6%
7 2
 
2.3%
Space Separator
ValueCountFrequency (%)
91
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 330
63.5%
Common 190
36.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 23
 
7.0%
도 21
 
6.4%
경 20
 
6.1%
지 19
 
5.8%
기 19
 
5.8%
번 19
 
5.8%
동 17
 
5.2%
구 9
 
2.7%
수 8
 
2.4%
안 8
 
2.4%
Other values (88) 167
50.6%
Common
ValueCountFrequency (%)
91
47.9%
1 21
 
11.1%
- 12
 
6.3%
3 12
 
6.3%
2 11
 
5.8%
0 10
 
5.3%
5 9
 
4.7%
4 7
 
3.7%
6 6
 
3.2%
9 5
 
2.6%
Other values (2) 6
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 330
63.5%
ASCII 190
36.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
91
47.9%
1 21
 
11.1%
- 12
 
6.3%
3 12
 
6.3%
2 11
 
5.8%
0 10
 
5.3%
5 9
 
4.7%
4 7
 
3.7%
6 6
 
3.2%
9 5
 
2.6%
Other values (2) 6
 
3.2%
Hangul
ValueCountFrequency (%)
시 23
 
7.0%
도 21
 
6.4%
경 20
 
6.1%
지 19
 
5.8%
기 19
 
5.8%
번 19
 
5.8%
동 17
 
5.2%
구 9
 
2.7%
수 8
 
2.4%
안 8
 
2.4%
Other values (88) 167
50.6%

소재지도로명주소
Text

UNIQUE 

Distinct21
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2024-03-13T08:13:23.234350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length32
Mean length27.238095
Min length14

Characters and Unicode

Total characters572
Distinct characters120
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

Unique21 ?
Unique (%)100.0%

Sample

1st row경기도 고양시 덕양구 고양시청로 11 고양시티타운 1층 수도시설과 수질검사팀
2nd row경기도 과천시 교육원로 1
3rd row경기도 군포시 산본로 101번길 13
4th row경기도 김포시 고촌읍 신곡로 152(고촌읍 풍곡리221)
5th row경기도 남양주시 별내면 청학로 54번길 50
ValueCountFrequency (%)
경기도 21
 
17.4%
성남시 3
 
2.5%
중원구 3
 
2.5%
하남시 2
 
1.7%
안양시 2
 
1.7%
화성시 2
 
1.7%
수질검사팀 2
 
1.7%
수원시 2
 
1.7%
안성시 2
 
1.7%
만안구 1
 
0.8%
Other values (81) 81
66.9%
2024-03-13T08:13:23.532437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
 
17.5%
1 30
 
5.2%
시 27
 
4.7%
도 23
 
4.0%
경 22
 
3.8%
기 22
 
3.8%
로 19
 
3.3%
2 15
 
2.6%
길 11
 
1.9%
5 10
 
1.7%
Other values (110) 293
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 355
62.1%
Space Separator 100
 
17.5%
Decimal Number 99
 
17.3%
Open Punctuation 5
 
0.9%
Other Punctuation 5
 
0.9%
Close Punctuation 5
 
0.9%
Dash Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 27
 
7.6%
도 23
 
6.5%
경 22
 
6.2%
기 22
 
6.2%
로 19
 
5.4%
길 11
 
3.1%
구 9
 
2.5%
성 9
 
2.5%
수 8
 
2.3%
번 8
 
2.3%
Other values (95) 197
55.5%
Decimal Number
ValueCountFrequency (%)
1 30
30.3%
2 15
15.2%
5 10
 
10.1%
3 9
 
9.1%
0 9
 
9.1%
7 7
 
7.1%
4 6
 
6.1%
9 6
 
6.1%
6 4
 
4.0%
8 3
 
3.0%
Space Separator
ValueCountFrequency (%)
100
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 355
62.1%
Common 217
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 27
 
7.6%
도 23
 
6.5%
경 22
 
6.2%
기 22
 
6.2%
로 19
 
5.4%
길 11
 
3.1%
구 9
 
2.5%
성 9
 
2.5%
수 8
 
2.3%
번 8
 
2.3%
Other values (95) 197
55.5%
Common
ValueCountFrequency (%)
100
46.1%
1 30
 
13.8%
2 15
 
6.9%
5 10
 
4.6%
3 9
 
4.1%
0 9
 
4.1%
7 7
 
3.2%
4 6
 
2.8%
9 6
 
2.8%
( 5
 
2.3%
Other values (5) 20
 
9.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 355
62.1%
ASCII 217
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
46.1%
1 30
 
13.8%
2 15
 
6.9%
5 10
 
4.6%
3 9
 
4.1%
0 9
 
4.1%
7 7
 
3.2%
4 6
 
2.8%
9 6
 
2.8%
( 5
 
2.3%
Other values (5) 20
 
9.2%
Hangul
ValueCountFrequency (%)
시 27
 
7.6%
도 23
 
6.5%
경 22
 
6.2%
기 22
 
6.2%
로 19
 
5.4%
길 11
 
3.1%
구 9
 
2.5%
성 9
 
2.5%
수 8
 
2.3%
번 8
 
2.3%
Other values (95) 197
55.5%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)100.0%
Missing2
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean37.383205
Minimum36.993179
Maximum37.710055
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-13T08:13:23.629443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.993179
5-th percentile37.009881
Q137.272118
median37.383836
Q337.515897
95-th percentile37.662743
Maximum37.710055
Range0.71687584
Interquartile range (IQR)0.24377958

Descriptive statistics

Standard deviation0.19306605
Coefficient of variation (CV)0.005164513
Kurtosis0.053180224
Mean37.383205
Median Absolute Deviation (MAD)0.14066661
Skewness-0.38668707
Sum710.28089
Variance0.037274499
MonotonicityNot monotonic
2024-03-13T08:13:23.728688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
37.3528972896 1
 
4.8%
37.2253392657 1
 
4.8%
37.2287538051 1
 
4.8%
37.5245026053 1
 
4.8%
37.5535037868 1
 
4.8%
37.3352586714 1
 
4.8%
37.383835995 1
 
4.8%
37.3926189085 1
 
4.8%
37.0117369467 1
 
4.8%
37.6574863134 1
 
4.8%
Other values (9) 9
42.9%
(Missing) 2
 
9.5%
ValueCountFrequency (%)
36.9931794459 1
4.8%
37.0117369467 1
4.8%
37.2253392657 1
4.8%
37.2287538051 1
4.8%
37.2427199544 1
4.8%
37.3015156198 1
4.8%
37.3352586714 1
4.8%
37.3528972896 1
4.8%
37.3818288558 1
4.8%
37.383835995 1
4.8%
ValueCountFrequency (%)
37.7100552904 1
4.8%
37.6574863134 1
4.8%
37.6078396563 1
4.8%
37.5535037868 1
4.8%
37.5245026053 1
4.8%
37.5072921216 1
4.8%
37.4392489154 1
4.8%
37.431277284 1
4.8%
37.3926189085 1
4.8%
37.383835995 1
4.8%

WGS84경도
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)100.0%
Missing2
Missing (%)9.5%
Infinite0
Infinite (%)0.0%
Mean127.03292
Minimum126.76267
Maximum127.26583
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2024-03-13T08:13:23.833417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.76267
5-th percentile126.80909
Q1126.94327
median127.02876
Q3127.17397
95-th percentile127.22114
Maximum127.26583
Range0.5031607
Interquartile range (IQR)0.23069897

Descriptive statistics

Standard deviation0.1571092
Coefficient of variation (CV)0.0012367597
Kurtosis-1.256765
Mean127.03292
Median Absolute Deviation (MAD)0.14404196
Skewness-0.22318365
Sum2413.6254
Variance0.024683299
MonotonicityNot monotonic
2024-03-13T08:13:23.938834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
126.9566612725 1
 
4.8%
126.9700109806 1
 
4.8%
127.0622430914 1
 
4.8%
127.172797995 1
 
4.8%
127.1946802895 1
 
4.8%
127.2161731037 1
 
4.8%
126.9476838074 1
 
4.8%
126.9388640512 1
 
4.8%
127.2658338379 1
 
4.8%
126.8325632804 1
 
4.8%
Other values (9) 9
42.9%
(Missing) 2
 
9.5%
ValueCountFrequency (%)
126.7626731331 1
4.8%
126.8142427794 1
4.8%
126.8192997273 1
4.8%
126.8325632804 1
4.8%
126.9388640512 1
4.8%
126.9476838074 1
4.8%
126.9566612725 1
4.8%
126.9700109806 1
4.8%
126.9764850507 1
4.8%
127.0287560312 1
4.8%
ValueCountFrequency (%)
127.2658338379 1
4.8%
127.2161731037 1
4.8%
127.1956873401 1
4.8%
127.1946802895 1
4.8%
127.1751477988 1
4.8%
127.172797995 1
4.8%
127.1706271063 1
4.8%
127.1249803265 1
4.8%
127.0622430914 1
4.8%
127.0287560312 1
4.8%

Interactions

2024-03-13T08:13:20.479028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.103858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.282694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.534554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.158254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.344507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.598954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.224185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:13:20.412828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:13:24.020390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명검사기관명연락처소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0001.0001.0001.0000.9740.893
검사기관명1.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호1.0001.0001.0001.0001.0001.0000.7580.856
소재지지번주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.9741.0001.0000.7581.0001.0001.0000.917
WGS84경도0.8931.0001.0000.8561.0001.0000.9171.000
2024-03-13T08:13:24.124518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도
소재지우편번호1.000-0.9510.286
WGS84위도-0.9511.000-0.318
WGS84경도0.286-0.3181.000

Missing values

2024-03-13T08:13:20.679042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:13:20.784968image/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.
2024-03-13T08:13:20.873552image/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

집계년월시군명검사기관명연락처지정기관명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02023-02고양시고양시상하수도사업소031-8075-4542한강유역환경청10460경기도 고양시 덕양구 주교동 601번지 고양시티타운 1층 수도시설과 수질검사팀경기도 고양시 덕양구 고양시청로 11 고양시티타운 1층 수도시설과 수질검사팀37.657486126.832563
12023-02과천시한국수자원공사 한강권역본부02-2150-0376한강유역환경청<NA><NA>경기도 과천시 교육원로 1<NA><NA>
22023-02군포시㈜한국유로핀즈 분석서비스031-361-7777한강유역환경청15849경기도 군포시 당정동 352-18번지경기도 군포시 산본로 101번길 1337.352897126.956661
32023-02김포시김포시상하수도사업소031-980-5684한강유역환경청10123경기도 김포시 고촌읍 풍곡리 221번지경기도 김포시 고촌읍 신곡로 152(고촌읍 풍곡리221)37.60784126.762673
42023-02남양주시중앙생명연구원(주)031-844-1720한강유역환경청12077경기도 남양주시 별내면 청학리 215-4번지경기도 남양주시 별내면 청학로 54번길 5037.710055127.12498
52023-02부천시부천시환경사업단정수과(까치울정수장)032-625-3386한강유역환경청14477경기도 부천시 오정구 작동 산60-8번지경기도 부천시 길주로 691(작동)37.507292126.8193
62023-02성남시(사)KOTITI시험연구원02-3451-7445한강유역환경청13202경기도 성남시 중원구 상대원동 138-7번지 10층경기도 성남시 중원구 사기막골로 111, 10층37.439249127.175148
72023-02성남시㈜한국수질시험연구소02-1544-7435한강유역환경청13229경기도 성남시 중원구 상대원동 513-14번지 시콕스타워 1203호경기도 성남시 중원구 둔촌대로 484 시콕스타워 1203호37.431277127.170627
82023-02성남시성남시맑은물관리사업소(복정정수장)031-729-4145한강유역환경청<NA><NA>경기도 성남시 중원구 성남대로 797<NA><NA>
92023-02수원시㈜피엘아이환경기술연구원031-8013-4570한강유역환경청16642경기도 수원시 권선구 고색동 959번지 휴먼스카이밸리 310호경기도 수원시 권선구 오목천로 132번길 33 휴먼스카이밸리 310호37.24272126.976485
집계년월시군명검사기관명연락처지정기관명소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
112023-02시흥시안산시상하수도사업소031-481-3802한강유역환경청14991경기도 시흥시 광석동 146-1번지 연성정수장경기도 시흥시 시흥대로412번길 87 연성정수장37.381829126.814243
122023-02안성시농협경제지주(주)축산연구원031-659-1385한강유역환경청17558경기도 안성시 공도읍 신두리 363번지경기도 안성시 공도읍 대신두길 42-2036.993179127.195687
132023-02안성시한경대학교031-6705-6378한강유역환경청17579경기도 안성시 석정동 55번지 한경대학교 공동실험실습관 502호경기도 안성시 중앙로 327 한경대학교 공동실험실습관 502호37.011737127.265834
142023-02안양시㈜워트랩생활환경연구원031-292-4477한강유역환경청14084경기도 안양시 만안구 안양동 1432번지경기도 안양시 만안구 덕천로152번길 2537.392619126.938864
152023-02안양시(주)혜성환경031-4733-4135한강유역환경청14079경기도 안양시 동안구 호계동 921-4번지경기도 안양시 동안구 귀인로79번길 3537.383836126.947684
162023-02용인시용인시상수도사업소031-324-4256한강유역환경청17031경기도 용인시 처인구 모현읍 매산리 310-2번지 용인정수장경기도 용인시 처인구 모현면 곡현로619번길 77, 용인정수장37.335259127.216173
172023-02하남시(주)키위수질시험센터031-790-0030한강유역환경청12930경기도 하남시 덕풍동 762번지 아이테코 851호경기도 하남시 조정대로150, 851호(덕풍동, 아이테코)37.553504127.19468
182023-02하남시(주)다솔물환경연구소031-772-4530한강유역환경청12989경기도 하남시 광암동 409-5번지 우일빌딩 3층경기도 하남시 초광산단로 126, 우일빌딩 3층37.524503127.172798
192023-02화성시(주)일영랩031-237-3301한강유역환경청18384경기도 화성시 반월동 339-1번지경기도 화성시 반월길12번길 9-11(반월동)37.228754127.062243
202023-02화성시SK매직(주) 화성공장031-299-5833한강유역환경청18298경기도 화성시 봉담읍 동화리 100-2번지경기도 화성시 봉담읍 효행로 25037.225339126.970011