Overview

Dataset statistics

Number of variables4
Number of observations270
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.8 KiB
Average record size in memory33.5 B

Variable types

Numeric1
Text2
DateTime1

Dataset

Description인천광역시 남동구 환경오염물질 중 수질오염물질 배출업소 허가 현황에 대한 데이터로 사업장명, 업종 등을 제공합니다.
Author인천광역시 남동구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15113432&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
연번 has unique valuesUnique
사업장명 has unique valuesUnique

Reproduction

Analysis started2024-04-20 18:48:27.091902
Analysis finished2024-04-20 18:48:27.797694
Duration0.71 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct270
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean135.5
Minimum1
Maximum270
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.5 KiB
2024-04-21T03:48:27.860948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.45
Q168.25
median135.5
Q3202.75
95-th percentile256.55
Maximum270
Range269
Interquartile range (IQR)134.5

Descriptive statistics

Standard deviation78.086491
Coefficient of variation (CV)0.57628406
Kurtosis-1.2
Mean135.5
Median Absolute Deviation (MAD)67.5
Skewness0
Sum36585
Variance6097.5
MonotonicityStrictly increasing
2024-04-21T03:48:27.976097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
187 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
176 1
 
0.4%
177 1
 
0.4%
178 1
 
0.4%
179 1
 
0.4%
180 1
 
0.4%
Other values (260) 260
96.3%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
270 1
0.4%
269 1
0.4%
268 1
0.4%
267 1
0.4%
266 1
0.4%
265 1
0.4%
264 1
0.4%
263 1
0.4%
262 1
0.4%
261 1
0.4%

사업장명
Text

UNIQUE 

Distinct270
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-21T03:48:28.162519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length7.5666667
Min length2

Characters and Unicode

Total characters2043
Distinct characters297
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique270 ?
Unique (%)100.0%

Sample

1st row한진세차장
2nd row인천수산업협동조합
3rd row오토라인자동차공업사
4th row㈜장원(인천공장지점)
5th row비젼카공업사
ValueCountFrequency (%)
주식회사 8
 
2.5%
㈜한국금거래소에프티씨 3
 
0.9%
만수점 3
 
0.9%
현대오일뱅크㈜직영 2
 
0.6%
인천지점 2
 
0.6%
지점 2
 
0.6%
애니카랜드 2
 
0.6%
㈜제이엘이 2
 
0.6%
한진세차장 1
 
0.3%
코리아금속 1
 
0.3%
Other values (299) 299
92.0%
2024-04-21T03:48:28.447915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 82
 
4.0%
55
 
2.7%
스 51
 
2.5%
주 50
 
2.4%
차 49
 
2.4%
사 49
 
2.4%
소 49
 
2.4%
동 47
 
2.3%
업 44
 
2.2%
이 42
 
2.1%
Other values (287) 1525
74.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1821
89.1%
Other Symbol 82
 
4.0%
Space Separator 55
 
2.7%
Uppercase Letter 28
 
1.4%
Open Punctuation 18
 
0.9%
Close Punctuation 18
 
0.9%
Decimal Number 12
 
0.6%
Lowercase Letter 6
 
0.3%
Other Punctuation 2
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 51
 
2.8%
주 50
 
2.7%
차 49
 
2.7%
사 49
 
2.7%
소 49
 
2.7%
동 47
 
2.6%
업 44
 
2.4%
이 42
 
2.3%
유 41
 
2.3%
장 36
 
2.0%
Other values (259) 1363
74.8%
Uppercase Letter
ValueCountFrequency (%)
S 5
17.9%
J 3
10.7%
K 3
10.7%
A 3
10.7%
C 2
 
7.1%
M 2
 
7.1%
O 2
 
7.1%
T 2
 
7.1%
H 2
 
7.1%
E 1
 
3.6%
Other values (3) 3
10.7%
Lowercase Letter
ValueCountFrequency (%)
o 2
33.3%
m 1
16.7%
t 1
16.7%
r 1
16.7%
s 1
16.7%
Decimal Number
ValueCountFrequency (%)
1 4
33.3%
3 3
25.0%
2 3
25.0%
4 2
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 82
100.0%
Space Separator
ValueCountFrequency (%)
55
100.0%
Open Punctuation
ValueCountFrequency (%)
( 18
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1903
93.1%
Common 106
 
5.2%
Latin 34
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 82
 
4.3%
스 51
 
2.7%
주 50
 
2.6%
차 49
 
2.6%
사 49
 
2.6%
소 49
 
2.6%
동 47
 
2.5%
업 44
 
2.3%
이 42
 
2.2%
유 41
 
2.2%
Other values (260) 1399
73.5%
Latin
ValueCountFrequency (%)
S 5
14.7%
J 3
 
8.8%
K 3
 
8.8%
A 3
 
8.8%
C 2
 
5.9%
M 2
 
5.9%
O 2
 
5.9%
T 2
 
5.9%
H 2
 
5.9%
o 2
 
5.9%
Other values (8) 8
23.5%
Common
ValueCountFrequency (%)
55
51.9%
( 18
 
17.0%
) 18
 
17.0%
1 4
 
3.8%
3 3
 
2.8%
2 3
 
2.8%
. 2
 
1.9%
4 2
 
1.9%
- 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1821
89.1%
ASCII 140
 
6.9%
None 82
 
4.0%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 82
100.0%
ASCII
ValueCountFrequency (%)
55
39.3%
( 18
 
12.9%
) 18
 
12.9%
S 5
 
3.6%
1 4
 
2.9%
3 3
 
2.1%
J 3
 
2.1%
2 3
 
2.1%
K 3
 
2.1%
A 3
 
2.1%
Other values (17) 25
17.9%
Hangul
ValueCountFrequency (%)
스 51
 
2.8%
주 50
 
2.7%
차 49
 
2.7%
사 49
 
2.7%
소 49
 
2.7%
동 47
 
2.6%
업 44
 
2.4%
이 42
 
2.3%
유 41
 
2.3%
장 36
 
2.0%
Other values (259) 1363
74.8%

업종
Text

Distinct129
Distinct (%)47.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2024-04-21T03:48:28.688096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length47
Mean length12.240741
Min length2

Characters and Unicode

Total characters3305
Distinct characters162
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

Unique103 ?
Unique (%)38.1%

Sample

1st row운수장비수선및세차
2nd row수산물 도매업
3rd row자동차전문수리업
4th row시멘트,석회,프라스틱제품제조
5th row운수장비수선및세차
ValueCountFrequency (%)
운수장비수선및세차 48
 
9.3%
기타 21
 
4.1%
및 21
 
4.1%
자동차세차업 18
 
3.5%
자동차세차업(95213 18
 
3.5%
자동차세차 16
 
3.1%
제조업 13
 
2.5%
외 12
 
2.3%
지정외 11
 
2.1%
금속원료 11
 
2.1%
Other values (179) 325
63.2%
2024-04-21T03:48:29.037230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
244
 
7.4%
업 212
 
6.4%
차 193
 
5.8%
수 121
 
3.7%
세 120
 
3.6%
2 91
 
2.8%
제 91
 
2.8%
) 86
 
2.6%
및 86
 
2.6%
( 86
 
2.6%
Other values (152) 1975
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2461
74.5%
Decimal Number 402
 
12.2%
Space Separator 244
 
7.4%
Close Punctuation 86
 
2.6%
Open Punctuation 86
 
2.6%
Other Punctuation 23
 
0.7%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 212
 
8.6%
차 193
 
7.8%
수 121
 
4.9%
세 120
 
4.9%
제 91
 
3.7%
및 86
 
3.5%
비 80
 
3.3%
기 76
 
3.1%
자 76
 
3.1%
장 74
 
3.0%
Other values (134) 1332
54.1%
Decimal Number
ValueCountFrequency (%)
2 91
22.6%
1 71
17.7%
3 65
16.2%
9 56
13.9%
0 30
 
7.5%
8 26
 
6.5%
4 26
 
6.5%
5 25
 
6.2%
7 9
 
2.2%
6 3
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
C 1
33.3%
B 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 22
95.7%
. 1
 
4.3%
Space Separator
ValueCountFrequency (%)
244
100.0%
Close Punctuation
ValueCountFrequency (%)
) 86
100.0%
Open Punctuation
ValueCountFrequency (%)
( 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2461
74.5%
Common 841
 
25.4%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 212
 
8.6%
차 193
 
7.8%
수 121
 
4.9%
세 120
 
4.9%
제 91
 
3.7%
및 86
 
3.5%
비 80
 
3.3%
기 76
 
3.1%
자 76
 
3.1%
장 74
 
3.0%
Other values (134) 1332
54.1%
Common
ValueCountFrequency (%)
244
29.0%
2 91
 
10.8%
) 86
 
10.2%
( 86
 
10.2%
1 71
 
8.4%
3 65
 
7.7%
9 56
 
6.7%
0 30
 
3.6%
8 26
 
3.1%
4 26
 
3.1%
Other values (5) 60
 
7.1%
Latin
ValueCountFrequency (%)
P 1
33.3%
C 1
33.3%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2461
74.5%
ASCII 844
 
25.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
244
28.9%
2 91
 
10.8%
) 86
 
10.2%
( 86
 
10.2%
1 71
 
8.4%
3 65
 
7.7%
9 56
 
6.6%
0 30
 
3.6%
8 26
 
3.1%
4 26
 
3.1%
Other values (8) 63
 
7.5%
Hangul
ValueCountFrequency (%)
업 212
 
8.6%
차 193
 
7.8%
수 121
 
4.9%
세 120
 
4.9%
제 91
 
3.7%
및 86
 
3.5%
비 80
 
3.3%
기 76
 
3.1%
자 76
 
3.1%
장 74
 
3.0%
Other values (134) 1332
54.1%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
Minimum2024-03-29 00:00:00
Maximum2024-03-29 00:00:00
2024-04-21T03:48:29.131854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T03:48:29.205151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-04-21T03:48:27.610651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-21T03:48:27.702062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T03:48:27.767160image/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

연번사업장명업종데이터기준일자
01한진세차장운수장비수선및세차2024-03-29
12인천수산업협동조합수산물 도매업2024-03-29
23오토라인자동차공업사자동차전문수리업2024-03-29
34㈜장원(인천공장지점)시멘트,석회,프라스틱제품제조2024-03-29
45비젼카공업사운수장비수선및세차2024-03-29
56우신교통㈜운수장비수선및세차(택시운송업)2024-03-29
67성진기업(합)운수장비수선및세차(택시운송업)2024-03-29
78르노삼성자동차 서비스코너 만수점운수장비수선및세차2024-03-29
89신화상사㈜주원고개주유소운수장비수선및세차2024-03-29
910희망자동차공업사운수장비수선및세차2024-03-29
연번사업장명업종데이터기준일자
260261㈜우신주형 및 금형제조업(29294) 그 외 기타 특수 목적용 기계 제조업(29299)2024-03-29
261262(SJ)디테일링자동차세차업(95213)2024-03-29
262263㈜고려솔더기타비철금속압연압출및연신제품제조업(24229)2024-03-29
263264인천개인택시 복지제3충전소운송장비용가스충전업2024-03-29
264265운연전기자동차충전소자동차세차업(95213)2024-03-29
265266㈜제이엘이 기업부설연구소비철금속제조업(24290)2024-03-29
266267㈜한국금거래소에프티씨(3공장)비철금속제련정련및합금제조업(24219)2024-03-29
267268테슬라코리아 유한회사자동차전문수리업2024-03-29
268269남동농협 전기차충전소자동차세차업(95213)2024-03-29
269270메타일렉트로㈜금속류원료재생업(38312) 기타기초무기화합물제조업(20129) 분말야금제품제조업(25911)2024-03-29