Overview

Dataset statistics

Number of variables17
Number of observations51
Missing cells51
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory143.6 B

Variable types

Categorical4
Text5
Unsupported1
Boolean4
Numeric3

Alerts

집계년도 has constant value ""Constant
업종구분명 has constant value ""Constant
관할기관명 has constant value ""Constant
악취등록여부 has constant value ""Constant
소재지우편번호 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호High correlation
대기등록여부 is highly overall correlated with 수질등록여부High correlation
수질등록여부 is highly overall correlated with 대기등록여부High correlation
소음등록여부 is highly imbalanced (86.1%)Imbalance
실내공기등록여부 has 51 (100.0%) missing valuesMissing
업소명 has unique valuesUnique
전화번호정보 has unique valuesUnique
대표자명 has unique valuesUnique
실내공기등록여부 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 21:42:23.697911
Analysis finished2023-12-10 21:42:25.375131
Duration1.68 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년도
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023
51 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023
2nd row2023
3rd row2023
4th row2023
5th row2023

Common Values

ValueCountFrequency (%)
2023 51
100.0%

Length

2023-12-11T06:42:25.428264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:42:25.513887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023 51
100.0%

시군명
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Memory size540.0 B
남양주시
11 
고양시
10 
파주시
10 
포천시
7 
양주시
6 
Other values (2)
7 

Length

Max length4
Median length3
Mean length3.3333333
Min length3

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
남양주시 11
21.6%
고양시 10
19.6%
파주시 10
19.6%
포천시 7
13.7%
양주시 6
11.8%
의정부시 6
11.8%
구리시 1
 
2.0%

Length

2023-12-11T06:42:25.598413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:42:25.913773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남양주시 11
21.6%
고양시 10
19.6%
파주시 10
19.6%
포천시 7
13.7%
양주시 6
11.8%
의정부시 6
11.8%
구리시 1
 
2.0%

업소명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:42:26.131767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length11
Mean length8.1960784
Min length4

Characters and Unicode

Total characters418
Distinct characters115
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

Unique51 ?
Unique (%)100.0%

Sample

1st row(주)지렉트코퍼레이션
2nd row(주)뉴엔텍
3rd row(주)더존이엔티
4th row(주)서진에너지
5th row스톰코리아㈜
ValueCountFrequency (%)
주식회사 2
 
3.8%
주)지렉트코퍼레이션 1
 
1.9%
신성종합환경 1
 
1.9%
주)이포텍 1
 
1.9%
주)청담이엠텍 1
 
1.9%
주)신우엔지니어링 1
 
1.9%
주)수정환경플랜트 1
 
1.9%
주)녹색이엘산업 1
 
1.9%
우림환경산업(주 1
 
1.9%
에프엠테크 1
 
1.9%
Other values (42) 42
79.2%
2023-12-11T06:42:26.478095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 42
 
10.0%
( 40
 
9.6%
) 40
 
9.6%
이 19
 
4.5%
경 17
 
4.1%
환 15
 
3.6%
엔 13
 
3.1%
지 10
 
2.4%
텍 9
 
2.2%
업 6
 
1.4%
Other values (105) 207
49.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 329
78.7%
Open Punctuation 40
 
9.6%
Close Punctuation 40
 
9.6%
Other Symbol 4
 
1.0%
Uppercase Letter 3
 
0.7%
Space Separator 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 42
 
12.8%
이 19
 
5.8%
경 17
 
5.2%
환 15
 
4.6%
엔 13
 
4.0%
지 10
 
3.0%
텍 9
 
2.7%
업 6
 
1.8%
산 6
 
1.8%
니 6
 
1.8%
Other values (98) 186
56.5%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
V 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 333
79.7%
Common 82
 
19.6%
Latin 3
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 42
 
12.6%
이 19
 
5.7%
경 17
 
5.1%
환 15
 
4.5%
엔 13
 
3.9%
지 10
 
3.0%
텍 9
 
2.7%
업 6
 
1.8%
산 6
 
1.8%
니 6
 
1.8%
Other values (99) 190
57.1%
Common
ValueCountFrequency (%)
( 40
48.8%
) 40
48.8%
2
 
2.4%
Latin
ValueCountFrequency (%)
E 1
33.3%
N 1
33.3%
V 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 329
78.7%
ASCII 85
 
20.3%
None 4
 
1.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 42
 
12.8%
이 19
 
5.8%
경 17
 
5.2%
환 15
 
4.6%
엔 13
 
4.0%
지 10
 
3.0%
텍 9
 
2.7%
업 6
 
1.8%
산 6
 
1.8%
니 6
 
1.8%
Other values (98) 186
56.5%
ASCII
ValueCountFrequency (%)
( 40
47.1%
) 40
47.1%
2
 
2.4%
E 1
 
1.2%
N 1
 
1.2%
V 1
 
1.2%
None
ValueCountFrequency (%)
㈜ 4
100.0%

전화번호정보
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:42:26.725710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.058824
Min length12

Characters and Unicode

Total characters615
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

Unique51 ?
Unique (%)100.0%

Sample

1st row02-2088-3330
2nd row031-969-9527
3rd row031-817-9542
4th row02-2601-5310
5th row031-903-4930
ValueCountFrequency (%)
02-2088-3330 1
 
2.0%
031-544-6801 1
 
2.0%
031-878-9924 1
 
2.0%
031-878-8188 1
 
2.0%
031-837-8472 1
 
2.0%
031-636-1694 1
 
2.0%
031-853-5680 1
 
2.0%
031-825-2105 1
 
2.0%
031-944-9895 1
 
2.0%
031-945-1254 1
 
2.0%
Other values (41) 41
80.4%
2023-12-11T06:42:27.056534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 102
16.6%
0 85
13.8%
3 82
13.3%
1 76
12.4%
5 47
7.6%
8 46
7.5%
9 39
 
6.3%
6 39
 
6.3%
4 38
 
6.2%
2 34
 
5.5%
Other values (2) 27
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 502
81.6%
Dash Punctuation 102
 
16.6%
Other Punctuation 11
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 85
16.9%
3 82
16.3%
1 76
15.1%
5 47
9.4%
8 46
9.2%
9 39
7.8%
6 39
7.8%
4 38
7.6%
2 34
 
6.8%
7 16
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%
Other Punctuation
ValueCountFrequency (%)
* 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 615
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 102
16.6%
0 85
13.8%
3 82
13.3%
1 76
12.4%
5 47
7.6%
8 46
7.5%
9 39
 
6.3%
6 39
 
6.3%
4 38
 
6.2%
2 34
 
5.5%
Other values (2) 27
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 615
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 102
16.6%
0 85
13.8%
3 82
13.3%
1 76
12.4%
5 47
7.6%
8 46
7.5%
9 39
 
6.3%
6 39
 
6.3%
4 38
 
6.2%
2 34
 
5.5%
Other values (2) 27
 
4.4%

업종구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
환경전문공사업
51 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
환경전문공사업 51
100.0%

Length

2023-12-11T06:42:27.182794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:42:27.271318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경전문공사업 51
100.0%

대표자명
Text

UNIQUE 

Distinct51
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:42:27.461418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.1764706
Min length2

Characters and Unicode

Total characters162
Distinct characters81
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

Unique51 ?
Unique (%)100.0%

Sample

1st row김선희
2nd row윤종호
3rd row박희주
4th row임태형
5th row김장근
ValueCountFrequency (%)
김선희 1
 
1.9%
주영일 1
 
1.9%
구응모 1
 
1.9%
이영란 1
 
1.9%
구경환 1
 
1.9%
윤인구 1
 
1.9%
김철의 1
 
1.9%
이주원 1
 
1.9%
김철 1
 
1.9%
정희정 1
 
1.9%
Other values (43) 43
81.1%
2023-12-11T06:42:27.792780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 10
 
6.2%
이 8
 
4.9%
윤 5
 
3.1%
구 5
 
3.1%
승 4
 
2.5%
호 4
 
2.5%
조 4
 
2.5%
영 4
 
2.5%
황 4
 
2.5%
종 4
 
2.5%
Other values (71) 110
67.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 158
97.5%
Space Separator 2
 
1.2%
Other Punctuation 2
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 10
 
6.3%
이 8
 
5.1%
윤 5
 
3.2%
구 5
 
3.2%
승 4
 
2.5%
호 4
 
2.5%
조 4
 
2.5%
영 4
 
2.5%
황 4
 
2.5%
종 4
 
2.5%
Other values (69) 106
67.1%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 158
97.5%
Common 4
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 10
 
6.3%
이 8
 
5.1%
윤 5
 
3.2%
구 5
 
3.2%
승 4
 
2.5%
호 4
 
2.5%
조 4
 
2.5%
영 4
 
2.5%
황 4
 
2.5%
종 4
 
2.5%
Other values (69) 106
67.1%
Common
ValueCountFrequency (%)
2
50.0%
, 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 158
97.5%
ASCII 4
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 10
 
6.3%
이 8
 
5.1%
윤 5
 
3.2%
구 5
 
3.2%
승 4
 
2.5%
호 4
 
2.5%
조 4
 
2.5%
영 4
 
2.5%
황 4
 
2.5%
종 4
 
2.5%
Other values (69) 106
67.1%
ASCII
ValueCountFrequency (%)
2
50.0%
, 2
50.0%

관할기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size540.0 B
경기도(북부환경관리과)
51 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도(북부환경관리과)
2nd row경기도(북부환경관리과)
3rd row경기도(북부환경관리과)
4th row경기도(북부환경관리과)
5th row경기도(북부환경관리과)

Common Values

ValueCountFrequency (%)
경기도(북부환경관리과) 51
100.0%

Length

2023-12-11T06:42:27.949719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:42:28.043444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도(북부환경관리과 51
100.0%

실내공기등록여부
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing51
Missing (%)100.0%
Memory size591.0 B

소음등록여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
False
50 
True
 
1
ValueCountFrequency (%)
False 50
98.0%
True 1
 
2.0%
2023-12-11T06:42:28.129941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

악취등록여부
Boolean

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size183.0 B
False
51 
ValueCountFrequency (%)
False 51
100.0%
2023-12-11T06:42:28.214980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

대기등록여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
26 
False
25 
ValueCountFrequency (%)
True 26
51.0%
False 25
49.0%
2023-12-11T06:42:28.297728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

수질등록여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size183.0 B
True
29 
False
22 
ValueCountFrequency (%)
True 29
56.9%
False 22
43.1%
2023-12-11T06:42:28.369951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11306.549
Minimum10402
Maximum12248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T06:42:28.460217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10402
5-th percentile10403
Q110891
median11190
Q311758.5
95-th percentile12243
Maximum12248
Range1846
Interquartile range (IQR)867.5

Descriptive statistics

Standard deviation611.9455
Coefficient of variation (CV)0.054123101
Kurtosis-1.1901867
Mean11306.549
Median Absolute Deviation (MAD)480
Skewness0.10119569
Sum576634
Variance374477.29
MonotonicityNot monotonic
2023-12-11T06:42:28.578946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
10403 3
 
5.9%
12248 3
 
5.9%
10442 2
 
3.9%
10550 2
 
3.9%
11190 2
 
3.9%
12238 2
 
3.9%
10526 1
 
2.0%
10860 1
 
2.0%
10857 1
 
2.0%
10935 1
 
2.0%
Other values (33) 33
64.7%
ValueCountFrequency (%)
10402 1
 
2.0%
10403 3
5.9%
10442 2
3.9%
10447 1
 
2.0%
10526 1
 
2.0%
10550 2
3.9%
10857 1
 
2.0%
10858 1
 
2.0%
10860 1
 
2.0%
10922 1
 
2.0%
ValueCountFrequency (%)
12248 3
5.9%
12238 2
3.9%
12223 1
 
2.0%
12113 1
 
2.0%
12106 1
 
2.0%
12097 1
 
2.0%
12084 1
 
2.0%
12075 1
 
2.0%
11940 1
 
2.0%
11760 1
 
2.0%

소재지지번주소
Text

Distinct46
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:42:28.833950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.431373
Min length18

Characters and Unicode

Total characters1093
Distinct characters97
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

Unique42 ?
Unique (%)82.4%

Sample

1st row경기도 고양시 덕양구 행신동 761-3번지
2nd row경기도 고양시 덕양구 원흥동 706번지
3rd row경기도 고양시 일산동구 백석동 1141-1번지
4th row경기도 고양시 덕양구 원흥동 706번지
5th row경기도 고양시 일산동구 백석동 1335번지
ValueCountFrequency (%)
경기도 51
22.1%
남양주시 11
 
4.8%
파주시 10
 
4.3%
고양시 10
 
4.3%
일산동구 7
 
3.0%
포천시 7
 
3.0%
양주시 6
 
2.6%
의정부시 6
 
2.6%
장항동 4
 
1.7%
백석동 3
 
1.3%
Other values (95) 116
50.2%
2023-12-11T06:42:29.200567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
180
 
16.5%
도 52
 
4.8%
시 52
 
4.8%
경 51
 
4.7%
번 51
 
4.7%
기 51
 
4.7%
지 51
 
4.7%
동 44
 
4.0%
1 44
 
4.0%
- 39
 
3.6%
Other values (87) 478
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 672
61.5%
Decimal Number 202
 
18.5%
Space Separator 180
 
16.5%
Dash Punctuation 39
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 52
 
7.7%
시 52
 
7.7%
경 51
 
7.6%
번 51
 
7.6%
기 51
 
7.6%
지 51
 
7.6%
동 44
 
6.5%
양 31
 
4.6%
주 27
 
4.0%
리 20
 
3.0%
Other values (75) 242
36.0%
Decimal Number
ValueCountFrequency (%)
1 44
21.8%
4 23
11.4%
7 20
9.9%
5 20
9.9%
2 19
9.4%
6 17
 
8.4%
3 16
 
7.9%
0 16
 
7.9%
9 14
 
6.9%
8 13
 
6.4%
Space Separator
ValueCountFrequency (%)
180
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 672
61.5%
Common 421
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 52
 
7.7%
시 52
 
7.7%
경 51
 
7.6%
번 51
 
7.6%
기 51
 
7.6%
지 51
 
7.6%
동 44
 
6.5%
양 31
 
4.6%
주 27
 
4.0%
리 20
 
3.0%
Other values (75) 242
36.0%
Common
ValueCountFrequency (%)
180
42.8%
1 44
 
10.5%
- 39
 
9.3%
4 23
 
5.5%
7 20
 
4.8%
5 20
 
4.8%
2 19
 
4.5%
6 17
 
4.0%
3 16
 
3.8%
0 16
 
3.8%
Other values (2) 27
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 672
61.5%
ASCII 421
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
180
42.8%
1 44
 
10.5%
- 39
 
9.3%
4 23
 
5.5%
7 20
 
4.8%
5 20
 
4.8%
2 19
 
4.5%
6 17
 
4.0%
3 16
 
3.8%
0 16
 
3.8%
Other values (2) 27
 
6.4%
Hangul
ValueCountFrequency (%)
도 52
 
7.7%
시 52
 
7.7%
경 51
 
7.6%
번 51
 
7.6%
기 51
 
7.6%
지 51
 
7.6%
동 44
 
6.5%
양 31
 
4.6%
주 27
 
4.0%
리 20
 
3.0%
Other values (75) 242
36.0%

소재지도로명주소
Text

Distinct46
Distinct (%)90.2%
Missing0
Missing (%)0.0%
Memory size540.0 B
2023-12-11T06:42:29.471919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length19.235294
Min length14

Characters and Unicode

Total characters981
Distinct characters102
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

Unique42 ?
Unique (%)82.4%

Sample

1st row경기도 고양시 덕양구 충장로 22
2nd row경기도 고양시 덕양구 삼원로 83
3rd row경기도 고양시 일산동구 일산로 138
4th row경기도 고양시 덕양구 삼원로 83
5th row경기도 고양시 일산동구 중앙로 1079
ValueCountFrequency (%)
경기도 51
22.2%
남양주시 11
 
4.8%
파주시 10
 
4.3%
고양시 10
 
4.3%
일산동구 7
 
3.0%
포천시 7
 
3.0%
양주시 6
 
2.6%
의정부시 6
 
2.6%
덕양구 3
 
1.3%
백마로 3
 
1.3%
Other values (97) 116
50.4%
2023-12-11T06:42:29.851588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
18.2%
경 56
 
5.7%
도 51
 
5.2%
기 51
 
5.2%
시 51
 
5.2%
로 50
 
5.1%
1 31
 
3.2%
3 30
 
3.1%
양 30
 
3.1%
2 29
 
3.0%
Other values (92) 423
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 603
61.5%
Decimal Number 189
 
19.3%
Space Separator 179
 
18.2%
Dash Punctuation 10
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 56
 
9.3%
도 51
 
8.5%
기 51
 
8.5%
시 51
 
8.5%
로 50
 
8.3%
양 30
 
5.0%
주 27
 
4.5%
산 15
 
2.5%
길 15
 
2.5%
번 13
 
2.2%
Other values (80) 244
40.5%
Decimal Number
ValueCountFrequency (%)
1 31
16.4%
3 30
15.9%
2 29
15.3%
5 18
9.5%
9 16
8.5%
4 15
7.9%
8 14
7.4%
7 13
6.9%
6 12
 
6.3%
0 11
 
5.8%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 603
61.5%
Common 378
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 56
 
9.3%
도 51
 
8.5%
기 51
 
8.5%
시 51
 
8.5%
로 50
 
8.3%
양 30
 
5.0%
주 27
 
4.5%
산 15
 
2.5%
길 15
 
2.5%
번 13
 
2.2%
Other values (80) 244
40.5%
Common
ValueCountFrequency (%)
179
47.4%
1 31
 
8.2%
3 30
 
7.9%
2 29
 
7.7%
5 18
 
4.8%
9 16
 
4.2%
4 15
 
4.0%
8 14
 
3.7%
7 13
 
3.4%
6 12
 
3.2%
Other values (2) 21
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 603
61.5%
ASCII 378
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
47.4%
1 31
 
8.2%
3 30
 
7.9%
2 29
 
7.7%
5 18
 
4.8%
9 16
 
4.2%
4 15
 
4.0%
8 14
 
3.7%
7 13
 
3.4%
6 12
 
3.2%
Other values (2) 21
 
5.6%
Hangul
ValueCountFrequency (%)
경 56
 
9.3%
도 51
 
8.5%
기 51
 
8.5%
시 51
 
8.5%
로 50
 
8.3%
양 30
 
5.0%
주 27
 
4.5%
산 15
 
2.5%
길 15
 
2.5%
번 13
 
2.2%
Other values (80) 244
40.5%

WGS84위도
Real number (ℝ)

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.735067
Minimum37.613159
Maximum37.899596
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T06:42:29.990523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.613159
5-th percentile37.624882
Q137.652169
median37.752154
Q337.807452
95-th percentile37.873565
Maximum37.899596
Range0.28643667
Interquartile range (IQR)0.15528348

Descriptive statistics

Standard deviation0.083665383
Coefficient of variation (CV)0.0022171786
Kurtosis-1.2542263
Mean37.735067
Median Absolute Deviation (MAD)0.08447936
Skewness0.15032591
Sum1924.4884
Variance0.0069998963
MonotonicityNot monotonic
2023-12-11T06:42:30.114399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
37.65011136 2
 
3.9%
37.65422609 2
 
3.9%
37.6337644 2
 
3.9%
37.66767486 1
 
2.0%
37.75459968 1
 
2.0%
37.85069824 1
 
2.0%
37.75215422 1
 
2.0%
37.8064712 1
 
2.0%
37.64644773 1
 
2.0%
37.65791316 1
 
2.0%
Other values (38) 38
74.5%
ValueCountFrequency (%)
37.6131591791 1
2.0%
37.61480097 1
2.0%
37.62437392 1
2.0%
37.62539092 1
2.0%
37.6337644 2
3.9%
37.63817785 1
2.0%
37.64305595 1
2.0%
37.6450460269 1
2.0%
37.64644773 1
2.0%
37.64667405 1
2.0%
ValueCountFrequency (%)
37.89959585 1
2.0%
37.87541421 1
2.0%
37.8738067 1
2.0%
37.87332322 1
2.0%
37.85069824 1
2.0%
37.84270448 1
2.0%
37.8379722133 1
2.0%
37.82145121 1
2.0%
37.8168157 1
2.0%
37.81294729 1
2.0%

WGS84경도
Real number (ℝ)

Distinct48
Distinct (%)94.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.99419
Minimum126.70984
Maximum127.23482
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size591.0 B
2023-12-11T06:42:30.235873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.70984
5-th percentile126.74519
Q1126.79502
median127.04839
Q3127.14052
95-th percentile127.21077
Maximum127.23482
Range0.5249803
Interquartile range (IQR)0.34550611

Descriptive statistics

Standard deviation0.17363469
Coefficient of variation (CV)0.0013672648
Kurtosis-1.532662
Mean126.99419
Median Absolute Deviation (MAD)0.1534015
Skewness-0.30791856
Sum6476.7036
Variance0.030149004
MonotonicityNot monotonic
2023-12-11T06:42:30.382641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
126.7950164 2
 
3.9%
126.7720435 2
 
3.9%
127.2107747 2
 
3.9%
127.1166442 1
 
2.0%
126.7813346 1
 
2.0%
127.0980118 1
 
2.0%
127.0690311 1
 
2.0%
127.0928443 1
 
2.0%
127.1248583 1
 
2.0%
126.8411531 1
 
2.0%
Other values (38) 38
74.5%
ValueCountFrequency (%)
126.709844 1
2.0%
126.7185279 1
2.0%
126.7209608 1
2.0%
126.7694283 1
2.0%
126.7709772408 1
2.0%
126.7720435 2
3.9%
126.7782675 1
2.0%
126.7788537 1
2.0%
126.7813346 1
2.0%
126.7845565262 1
2.0%
ValueCountFrequency (%)
127.2348243 1
2.0%
127.2138831 1
2.0%
127.2107747 2
3.9%
127.2056244 1
2.0%
127.2052334 1
2.0%
127.2017935 1
2.0%
127.1632834 1
2.0%
127.1622837 1
2.0%
127.1575579 1
2.0%
127.1536918597 1
2.0%

Interactions

2023-12-11T06:42:24.799913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.304053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.543567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.878885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.387003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.642035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.960128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.467518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:42:24.728390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:42:30.472751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명업소명전화번호정보대표자명소음등록여부대기등록여부수질등록여부소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
시군명1.0001.0001.0001.0000.0000.2110.1351.0001.0001.0000.6840.385
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
전화번호정보1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소음등록여부0.0001.0001.0001.0001.0000.0000.0000.0001.0001.0000.0000.000
대기등록여부0.2111.0001.0001.0000.0001.0000.9110.3600.0000.0000.1330.000
수질등록여부0.1351.0001.0001.0000.0000.9111.0000.0000.5670.5670.0000.000
소재지우편번호1.0001.0001.0001.0000.0000.3600.0001.0001.0001.0000.6800.416
소재지지번주소1.0001.0001.0001.0001.0000.0000.5671.0001.0001.0000.9730.730
소재지도로명주소1.0001.0001.0001.0001.0000.0000.5671.0001.0001.0000.9730.730
WGS84위도0.6841.0001.0001.0000.0000.1330.0000.6800.9730.9731.0000.609
WGS84경도0.3851.0001.0001.0000.0000.0000.0000.4160.7300.7300.6091.000
2023-12-11T06:42:30.581470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수질등록여부시군명대기등록여부소음등록여부
수질등록여부1.0000.1280.7290.000
시군명0.1281.0000.2080.000
대기등록여부0.7290.2081.0000.000
소음등록여부0.0000.0000.0001.000
2023-12-11T06:42:30.663426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지우편번호WGS84위도WGS84경도시군명소음등록여부대기등록여부수질등록여부
소재지우편번호1.0000.0800.4690.9890.0000.1910.098
WGS84위도0.0801.0000.0360.4160.0000.0720.000
WGS84경도0.4690.0361.0000.2010.0000.0000.000
시군명0.9890.4160.2011.0000.0000.2080.128
소음등록여부0.0000.0000.0000.0001.0000.0000.000
대기등록여부0.1910.0720.0000.2080.0001.0000.729
수질등록여부0.0980.0000.0000.1280.0000.7291.000

Missing values

2023-12-11T06:42:25.087210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:42:25.309371image/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.

Sample

집계년도시군명업소명전화번호정보업종구분명대표자명관할기관명실내공기등록여부소음등록여부악취등록여부대기등록여부수질등록여부소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02023고양시(주)지렉트코퍼레이션02-2088-3330환경전문공사업김선희경기도(북부환경관리과)<NA>YNNN10526경기도 고양시 덕양구 행신동 761-3번지경기도 고양시 덕양구 충장로 2237.667675127.116644
12023고양시(주)뉴엔텍031-969-9527환경전문공사업윤종호경기도(북부환경관리과)<NA>NNNY10550경기도 고양시 덕양구 원흥동 706번지경기도 고양시 덕양구 삼원로 8337.643056127.12118
22023고양시(주)더존이엔티031-817-9542환경전문공사업박희주경기도(북부환경관리과)<NA>NNNY10442경기도 고양시 일산동구 백석동 1141-1번지경기도 고양시 일산동구 일산로 13837.732987127.036912
32023고양시(주)서진에너지02-2601-5310환경전문공사업임태형경기도(북부환경관리과)<NA>NNNY10550경기도 고양시 덕양구 원흥동 706번지경기도 고양시 덕양구 삼원로 8337.638178126.874979
42023고양시스톰코리아㈜031-903-4930환경전문공사업김장근경기도(북부환경관리과)<NA>NNNY10447경기도 고양시 일산동구 백석동 1335번지경기도 고양시 일산동구 중앙로 107937.645046126.784557
52023고양시현대비씨엔지니어링(주)031-914-7215환경전문공사업박혜연, 우종준경기도(북부환경관리과)<NA>NNYN10403경기도 고양시 일산동구 장항동 869번지경기도 고양시 일산동구 백마로 19537.654292126.770977
62023고양시(주)세화엔스텍02-2690-8488환경전문공사업고동균경기도(북부환경관리과)<NA>NNYY10402경기도 고양시 일산동구 장항동 865번지경기도 고양시 일산동구 호수로 60637.656175126.769428
72023고양시(주)새롬환경기술031-938-0641환경전문공사업김승식경기도(북부환경관리과)<NA>NNYY10442경기도 고양시 일산동구 백석동 1141-1번지경기도 고양시 일산동구 일산로 13837.650111126.795016
82023고양시(주)신환이엔씨031-906-6461환경전문공사업김승제경기도(북부환경관리과)<NA>NNNY10403경기도 고양시 일산동구 장항동 869번지경기도 고양시 일산동구 백마로 19537.654226126.772043
92023고양시(주)화일씨앤이031-931-8871환경전문공사업이세호경기도(북부환경관리과)<NA>NNNY10403경기도 고양시 일산동구 장항동 869번지경기도 고양시 일산동구 백마로 19537.654226126.772043
집계년도시군명업소명전화번호정보업종구분명대표자명관할기관명실내공기등록여부소음등록여부악취등록여부대기등록여부수질등록여부소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
412023파주시청해ENV(주)031-946-3695환경전문공사업이병관경기도(북부환경관리과)<NA>NNYY10922경기도 파주시 금릉동 211-5번지경기도 파주시 가나무로 14337.758321126.778267
422023파주시(주)우호건설031-945-1610환경전문공사업유명환경기도(북부환경관리과)<NA>NNYY10931경기도 파주시 아동동 354-2번지경기도 파주시 새꽃로 24037.772341126.720961
432023파주시글롭텍엔지니어링(주)031-923-1036환경전문공사업신강석경기도(북부환경관리과)<NA>NNYN10858경기도 파주시 탄현면 축현리 408-1번지경기도 파주시 탄현면 방촌로538번길 337.78881127.086275
442023포천시지오환경기술(주)031-534-2329환경전문공사업황창순경기도(북부환경관리과)<NA>NNNY11144경기도 포천시 신읍동 202-30번지경기도 포천시 중앙로 15337.812947127.213883
452023포천시(주)대진바이오워터***-****-****환경전문공사업양동현경기도(북부환경관리과)<NA>NNNY11159경기도 포천시 선단동 산11-1번지경기도 포천시 호국로 100737.873807127.157558
462023포천시(주)한솔엔지니어링031-836-0621환경전문공사업문창옥경기도(북부환경관리과)<NA>NNYN11185경기도 포천시 소흘읍 고모리 490-2번지경기도 포천시 소흘읍 죽엽산로237번길 737.899596127.205233
472023포천시에코인㈜031-544-8650환경전문공사업김덕호경기도(북부환경관리과)<NA>NNYN11184경기도 포천시 소흘읍 이동교리 254-1번지경기도 포천시 소흘읍 호국로 389-4737.808433127.130243
482023포천시두원환경산업031-532-1332환경전문공사업송애자경기도(북부환경관리과)<NA>NNYN11190경기도 포천시 내촌면 진목리 201-8번지경기도 포천시 내촌면 진금로 4-4337.766932126.778854
492023포천시(주)이앤켐솔루션031-791-9471환경전문공사업김신동경기도(북부환경관리과)<NA>NNYN11154경기도 포천시 군내면 용정리 484-15번지경기도 포천시 군내면 용정경제로1길 94-3837.873323126.993465
502023포천시(주)제스와이테크031-534-5575환경전문공사업김태양경기도(북부환경관리과)<NA>NNYN11190경기도 포천시 내촌면 진목리 905-2번지경기도 포천시 내촌면 포천로 327-737.804175127.205624