Overview

Dataset statistics

Number of variables6
Number of observations25
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory55.3 B

Variable types

Text3
Numeric2
Categorical1

Dataset

Description연수구 내 대기 배출시설 설치 사업장 현황에 대한 데이터로 (업소명, 업종, 도로명 주소, 배출 물질) 의 정보를 제공합니다.
Author인천광역시 연수구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15065087&srcSe=7661IVAWM27C61E190

Alerts

업소명 has unique valuesUnique
도로명 주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:39:10.842257
Analysis finished2024-03-18 05:39:13.513369
Duration2.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-03-18T14:39:13.634309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length9.4
Min length4

Characters and Unicode

Total characters235
Distinct characters96
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row㈜서부티엔디
2nd row㈜송도골프
3rd row스포피아수영장
4th row주식회사 E1
5th row영남주택(영남스포츠월드)
ValueCountFrequency (%)
연수점 3
 
8.1%
현대아파트 3
 
8.1%
주식회사 2
 
5.4%
㈜서부티엔디 1
 
2.7%
여성의광장 1
 
2.7%
시영영구임대아파트 1
 
2.7%
케이티 1
 
2.7%
옥련1차 1
 
2.7%
인천광역시 1
 
2.7%
솔밭마을아파트 1
 
2.7%
Other values (22) 22
59.5%
2024-03-18T14:39:13.952540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
5.1%
트 9
 
3.8%
( 8
 
3.4%
주 8
 
3.4%
수 8
 
3.4%
아 8
 
3.4%
) 8
 
3.4%
파 7
 
3.0%
영 7
 
3.0%
연 6
 
2.6%
Other values (86) 154
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 196
83.4%
Space Separator 12
 
5.1%
Open Punctuation 8
 
3.4%
Close Punctuation 8
 
3.4%
Decimal Number 5
 
2.1%
Other Symbol 3
 
1.3%
Uppercase Letter 3
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 9
 
4.6%
주 8
 
4.1%
수 8
 
4.1%
아 8
 
4.1%
파 7
 
3.6%
영 7
 
3.6%
연 6
 
3.1%
천 6
 
3.1%
도 5
 
2.6%
시 5
 
2.6%
Other values (76) 127
64.8%
Decimal Number
ValueCountFrequency (%)
1 3
60.0%
4 1
 
20.0%
5 1
 
20.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
F 1
33.3%
E 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 199
84.7%
Common 33
 
14.0%
Latin 3
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 9
 
4.5%
주 8
 
4.0%
수 8
 
4.0%
아 8
 
4.0%
파 7
 
3.5%
영 7
 
3.5%
연 6
 
3.0%
천 6
 
3.0%
도 5
 
2.5%
시 5
 
2.5%
Other values (77) 130
65.3%
Common
ValueCountFrequency (%)
12
36.4%
( 8
24.2%
) 8
24.2%
1 3
 
9.1%
4 1
 
3.0%
5 1
 
3.0%
Latin
ValueCountFrequency (%)
L 1
33.3%
F 1
33.3%
E 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 196
83.4%
ASCII 36
 
15.3%
None 3
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
33.3%
( 8
22.2%
) 8
22.2%
1 3
 
8.3%
L 1
 
2.8%
4 1
 
2.8%
5 1
 
2.8%
F 1
 
2.8%
E 1
 
2.8%
Hangul
ValueCountFrequency (%)
트 9
 
4.6%
주 8
 
4.1%
수 8
 
4.1%
아 8
 
4.1%
파 7
 
3.6%
영 7
 
3.6%
연 6
 
3.1%
천 6
 
3.1%
도 5
 
2.6%
시 5
 
2.6%
Other values (76) 127
64.8%
None
ValueCountFrequency (%)
㈜ 3
100.0%

업종
Text

Distinct16
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-03-18T14:39:14.157879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length7.32
Min length2

Characters and Unicode

Total characters183
Distinct characters68
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

Unique12 ?
Unique (%)48.0%

Sample

1st row기타대형종합소매업
2nd row골프장운영
3rd row수영장
4th row가스제조 및 배관공급업
5th row체력단련시설 운영업
ValueCountFrequency (%)
기타대형종합소매업 5
 
13.9%
주거용부동산관리업 4
 
11.1%
수영장 2
 
5.6%
주거용 2
 
5.6%
건물 2
 
5.6%
임대업 2
 
5.6%
및 2
 
5.6%
대학교 1
 
2.8%
교육지원 1
 
2.8%
지방자치단체 1
 
2.8%
Other values (14) 14
38.9%
2024-03-18T14:39:14.456254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 17
 
9.3%
11
 
6.0%
대 8
 
4.4%
기 6
 
3.3%
주 6
 
3.3%
거 6
 
3.3%
용 6
 
3.3%
형 5
 
2.7%
종 5
 
2.7%
합 5
 
2.7%
Other values (58) 108
59.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 171
93.4%
Space Separator 11
 
6.0%
Other Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 17
 
9.9%
대 8
 
4.7%
기 6
 
3.5%
주 6
 
3.5%
거 6
 
3.5%
용 6
 
3.5%
형 5
 
2.9%
종 5
 
2.9%
합 5
 
2.9%
소 5
 
2.9%
Other values (56) 102
59.6%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 171
93.4%
Common 12
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 17
 
9.9%
대 8
 
4.7%
기 6
 
3.5%
주 6
 
3.5%
거 6
 
3.5%
용 6
 
3.5%
형 5
 
2.9%
종 5
 
2.9%
합 5
 
2.9%
소 5
 
2.9%
Other values (56) 102
59.6%
Common
ValueCountFrequency (%)
11
91.7%
, 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 171
93.4%
ASCII 12
 
6.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 17
 
9.9%
대 8
 
4.7%
기 6
 
3.5%
주 6
 
3.5%
거 6
 
3.5%
용 6
 
3.5%
형 5
 
2.9%
종 5
 
2.9%
합 5
 
2.9%
소 5
 
2.9%
Other values (56) 102
59.6%
ASCII
ValueCountFrequency (%)
11
91.7%
, 1
 
8.3%

도로명 주소
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2024-03-18T14:39:14.659747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length24.44
Min length21

Characters and Unicode

Total characters611
Distinct characters72
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row인천광역시 연수구 청능대로 210 스퀘어원
2nd row인천광역시 연수구 능허대로 236(옥련동)
3rd row인천광역시 연수구 새말로 27(연수동)
4th row인천광역시 연수구 인천신항대로 940(송도동)
5th row인천광역시 연수구 새말로 107번길 16(연수동)
ValueCountFrequency (%)
인천광역시 25
21.9%
연수구 25
21.9%
원인재로 5
 
4.4%
능허대로 3
 
2.6%
청능대로 3
 
2.6%
옥련동 2
 
1.8%
새말로 2
 
1.8%
연수동 2
 
1.8%
선학로 2
 
1.8%
68 1
 
0.9%
Other values (44) 44
38.6%
2024-03-18T14:39:15.031522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
89
 
14.6%
수 32
 
5.2%
연 32
 
5.2%
인 31
 
5.1%
동 31
 
5.1%
천 26
 
4.3%
시 25
 
4.1%
역 25
 
4.1%
구 25
 
4.1%
로 25
 
4.1%
Other values (62) 270
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 387
63.3%
Space Separator 89
 
14.6%
Decimal Number 83
 
13.6%
Close Punctuation 23
 
3.8%
Open Punctuation 23
 
3.8%
Other Punctuation 4
 
0.7%
Uppercase Letter 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 32
 
8.3%
연 32
 
8.3%
인 31
 
8.0%
동 31
 
8.0%
천 26
 
6.7%
시 25
 
6.5%
역 25
 
6.5%
구 25
 
6.5%
로 25
 
6.5%
광 25
 
6.5%
Other values (46) 110
28.4%
Decimal Number
ValueCountFrequency (%)
1 22
26.5%
2 15
18.1%
0 8
 
9.6%
3 8
 
9.6%
9 6
 
7.2%
6 6
 
7.2%
4 6
 
7.2%
7 6
 
7.2%
8 4
 
4.8%
5 2
 
2.4%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%
Space Separator
ValueCountFrequency (%)
89
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 387
63.3%
Common 222
36.3%
Latin 2
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 32
 
8.3%
연 32
 
8.3%
인 31
 
8.0%
동 31
 
8.0%
천 26
 
6.7%
시 25
 
6.5%
역 25
 
6.5%
구 25
 
6.5%
로 25
 
6.5%
광 25
 
6.5%
Other values (46) 110
28.4%
Common
ValueCountFrequency (%)
89
40.1%
) 23
 
10.4%
( 23
 
10.4%
1 22
 
9.9%
2 15
 
6.8%
0 8
 
3.6%
3 8
 
3.6%
9 6
 
2.7%
6 6
 
2.7%
4 6
 
2.7%
Other values (4) 16
 
7.2%
Latin
ValueCountFrequency (%)
K 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 387
63.3%
ASCII 224
36.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
89
39.7%
) 23
 
10.3%
( 23
 
10.3%
1 22
 
9.8%
2 15
 
6.7%
0 8
 
3.6%
3 8
 
3.6%
9 6
 
2.7%
6 6
 
2.7%
4 6
 
2.7%
Other values (6) 18
 
8.0%
Hangul
ValueCountFrequency (%)
수 32
 
8.3%
연 32
 
8.3%
인 31
 
8.0%
동 31
 
8.0%
천 26
 
6.7%
시 25
 
6.5%
역 25
 
6.5%
구 25
 
6.5%
로 25
 
6.5%
광 25
 
6.5%
Other values (46) 110
28.4%

위도
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.414005
Minimum37.344942
Maximum37.429796
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-03-18T14:39:15.188912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.344942
5-th percentile37.399344
Q137.413013
median37.41547
Q337.422401
95-th percentile37.427846
Maximum37.429796
Range0.084854
Interquartile range (IQR)0.009388

Descriptive statistics

Standard deviation0.016395087
Coefficient of variation (CV)0.00043820723
Kurtosis13.632929
Mean37.414005
Median Absolute Deviation (MAD)0.005681
Skewness-3.30069
Sum935.35012
Variance0.00026879889
MonotonicityNot monotonic
2024-03-18T14:39:15.316595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
37.406106 1
 
4.0%
37.429796 1
 
4.0%
37.40617 1
 
4.0%
37.425508 1
 
4.0%
37.427372 1
 
4.0%
37.419656 1
 
4.0%
37.415034 1
 
4.0%
37.415054 1
 
4.0%
37.413013 1
 
4.0%
37.427965 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
37.344942 1
4.0%
37.398141 1
4.0%
37.404158 1
4.0%
37.406106 1
4.0%
37.40617 1
4.0%
37.409789 1
4.0%
37.413013 1
4.0%
37.414314 1
4.0%
37.414683 1
4.0%
37.415034 1
4.0%
ValueCountFrequency (%)
37.429796 1
4.0%
37.427965 1
4.0%
37.427372 1
4.0%
37.425508 1
4.0%
37.425084 1
4.0%
37.423701 1
4.0%
37.422401 1
4.0%
37.420671 1
4.0%
37.419656 1
4.0%
37.418756 1
4.0%

경도
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean126.6706
Minimum126.62952
Maximum126.70018
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2024-03-18T14:39:15.405324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.62952
5-th percentile126.64387
Q1126.6546
median126.67517
Q3126.68785
95-th percentile126.69485
Maximum126.70018
Range0.070653
Interquartile range (IQR)0.033251

Descriptive statistics

Standard deviation0.019413178
Coefficient of variation (CV)0.00015325718
Kurtosis-0.94743559
Mean126.6706
Median Absolute Deviation (MAD)0.013025
Skewness-0.44190565
Sum3166.7649
Variance0.00037687148
MonotonicityNot monotonic
2024-03-18T14:39:15.509161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
126.683724 1
 
4.0%
126.646628 1
 
4.0%
126.683726 1
 
4.0%
126.650901 1
 
4.0%
126.646785 1
 
4.0%
126.668975 1
 
4.0%
126.688148 1
 
4.0%
126.688193 1
 
4.0%
126.665804 1
 
4.0%
126.643673 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
126.629522 1
4.0%
126.643673 1
4.0%
126.644669 1
4.0%
126.646628 1
4.0%
126.646785 1
4.0%
126.650901 1
4.0%
126.654604 1
4.0%
126.655356 1
4.0%
126.660069 1
4.0%
126.665804 1
4.0%
ValueCountFrequency (%)
126.700175 1
4.0%
126.696356 1
4.0%
126.688837 1
4.0%
126.688193 1
4.0%
126.688148 1
4.0%
126.687998 1
4.0%
126.687855 1
4.0%
126.683726 1
4.0%
126.683724 1
4.0%
126.68333 1
4.0%

배출 물질
Categorical

Distinct4
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
먼지, 질소산화물, 황산화물
16 
먼지, 황산화물
7 
먼지
 
1
먼지, 질소산화물
 
1

Length

Max length15
Median length15
Mean length12.4
Min length2

Unique

Unique2 ?
Unique (%)8.0%

Sample

1st row먼지, 질소산화물, 황산화물
2nd row먼지, 질소산화물, 황산화물
3rd row먼지, 질소산화물, 황산화물
4th row먼지, 질소산화물, 황산화물
5th row먼지, 질소산화물, 황산화물

Common Values

ValueCountFrequency (%)
먼지, 질소산화물, 황산화물 16
64.0%
먼지, 황산화물 7
28.0%
먼지 1
 
4.0%
먼지, 질소산화물 1
 
4.0%

Length

2024-03-18T14:39:15.631758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T14:39:15.740963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
먼지 25
38.5%
황산화물 23
35.4%
질소산화물 17
26.2%

Interactions

2024-03-18T14:39:13.194520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:39:12.953672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:39:13.270169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T14:39:13.111198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T14:39:15.822294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명업종도로명 주소위도경도배출 물질
업소명1.0001.0001.0001.0001.0001.000
업종1.0001.0001.0000.7820.8120.993
도로명 주소1.0001.0001.0001.0001.0001.000
위도1.0000.7821.0001.0000.7770.215
경도1.0000.8121.0000.7771.0000.737
배출 물질1.0000.9931.0000.2150.7371.000
2024-03-18T14:39:15.925151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도배출 물질
위도1.000-0.1450.149
경도-0.1451.0000.495
배출 물질0.1490.4951.000

Missing values

2024-03-18T14:39:13.390067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:39:13.474937image/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

업소명업종도로명 주소위도경도배출 물질
0㈜서부티엔디기타대형종합소매업인천광역시 연수구 청능대로 210 스퀘어원37.406106126.683724먼지, 질소산화물, 황산화물
1㈜송도골프골프장운영인천광역시 연수구 능허대로 236(옥련동)37.429796126.646628먼지, 질소산화물, 황산화물
2스포피아수영장수영장인천광역시 연수구 새말로 27(연수동)37.423701126.675009먼지, 질소산화물, 황산화물
3주식회사 E1가스제조 및 배관공급업인천광역시 연수구 인천신항대로 940(송도동)37.344942126.629522먼지, 질소산화물, 황산화물
4영남주택(영남스포츠월드)체력단련시설 운영업인천광역시 연수구 새말로 107번길 16(연수동)37.418678126.68333먼지, 질소산화물, 황산화물
5라미드송도호텔㈜호텔업인천광역시 연수구 능허대로 267번길 29(동춘동)37.414314126.655356먼지, 질소산화물, 황산화물
6인천적십자병원병원인천광역시 연수구 원인재로 263(연수동)37.418596126.688837먼지, 질소산화물, 황산화물
7연수구청구청인천광역시 연수구 원인재로 115(동춘동)37.409789126.67832먼지, 질소산화물, 황산화물
8가천대학교대학교인천광역시 연수구 함박뫼로 191(연수동)37.422401126.687998먼지, 질소산화물, 황산화물
9미라클수영장수영장인천광역시 연수구 선학로 101, 상가동 지하층 102,201호37.425084126.700175먼지, 질소산화물, 황산화물
업소명업종도로명 주소위도경도배출 물질
15인천도시공사(연수1차 시영영구임대아파트)주거용 건물 임대업인천광역시 연수구 원인재로 212(연수동)37.414683126.687855먼지, 질소산화물, 황산화물
16주식회사 케이티전기 및 통신공사업인천광역시 연수구 능허대로 136(옥련동, KT송도빌딩)37.420671126.644669먼지, 질소산화물, 황산화물
17옥련1차 현대아파트아파트인천광역시 연수구 옥련로 33(옥련동)37.427965126.643673먼지, 질소산화물, 황산화물
18인천광역시 여성의광장지방자치단체 교육지원, 서비스업인천광역시 연수구 앵고개로 183, 1층 (동춘동)37.413013126.665804먼지, 황산화물
19솔밭마을아파트주거용부동산관리업인천광역시 연수구 원인재로 232 (연수동)37.415054126.688193먼지, 황산화물
20승기마을아파트주거용부동산관리업인천광역시 연수구 원인재로 212 (연수동)37.415034126.688148먼지, 황산화물
21(주)LF스퀘어 연수점기타대형종합소매업인천광역시 연수구 용담로 14 (청학동)37.419656126.668975먼지, 황산화물
22옥련5차 현대아파트주거용부동산관리업인천광역시 연수구 한진로 49 (옥련동)37.427372126.646785먼지, 황산화물
23옥련4차 현대아파트주거용부동산관리업인천광역시 연수구 한나루로105번길 68 (옥련동)37.425508126.650901먼지, 황산화물
24홈플러스(주) 인천연수점기타대형종합소매업인천광역시 연수구 청능대로 210(동춘동)37.40617126.683726먼지, 황산화물