Overview

Dataset statistics

Number of variables6
Number of observations1016
Missing cells8
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory48.7 KiB
Average record size in memory49.1 B

Variable types

Numeric1
Categorical1
Text4

Dataset

Description인천광역시 서구 폐수 배출시설 설치사업장 현황 (수질, 사업장명, 소재지(지번), 소재지(도로명), 업종 등) 에 관한 데이터를 제공합니다.
Author인천광역시 서구
URLhttps://www.data.go.kr/data/15068807/fileData.do

Alerts

수질 is highly imbalanced (79.3%)Imbalance
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:24:18.481187
Analysis finished2024-03-14 12:24:19.972475
Duration1.49 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct1016
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean508.5
Minimum1
Maximum1016
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.1 KiB
2024-03-14T21:24:20.109843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile51.75
Q1254.75
median508.5
Q3762.25
95-th percentile965.25
Maximum1016
Range1015
Interquartile range (IQR)507.5

Descriptive statistics

Standard deviation293.43824
Coefficient of variation (CV)0.57706635
Kurtosis-1.2
Mean508.5
Median Absolute Deviation (MAD)254
Skewness0
Sum516636
Variance86106
MonotonicityStrictly increasing
2024-03-14T21:24:20.363541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
684 1
 
0.1%
671 1
 
0.1%
672 1
 
0.1%
673 1
 
0.1%
674 1
 
0.1%
675 1
 
0.1%
676 1
 
0.1%
677 1
 
0.1%
678 1
 
0.1%
Other values (1006) 1006
99.0%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1016 1
0.1%
1015 1
0.1%
1014 1
0.1%
1013 1
0.1%
1012 1
0.1%
1011 1
0.1%
1010 1
0.1%
1009 1
0.1%
1008 1
0.1%
1007 1
0.1%

수질
Categorical

IMBALANCE 

Distinct10
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
5
911 
4
 
54
3
 
29
2
 
8
통합허가(2)
 
4
Other values (5)
 
10

Length

Max length7
Median length1
Mean length1.0649606
Min length1

Unique

Unique2 ?
Unique (%)0.2%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 911
89.7%
4 54
 
5.3%
3 29
 
2.9%
2 8
 
0.8%
통합허가(2) 4
 
0.4%
1 3
 
0.3%
통합허가(5) 3
 
0.3%
통합허가(3) 2
 
0.2%
통합허가(1) 1
 
0.1%
통합허가(4) 1
 
0.1%

Length

2024-03-14T21:24:20.647266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:24:20.903101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 911
89.7%
4 54
 
5.3%
3 29
 
2.9%
2 8
 
0.8%
통합허가(2 4
 
0.4%
1 3
 
0.3%
통합허가(5 3
 
0.3%
통합허가(3 2
 
0.2%
통합허가(1 1
 
0.1%
통합허가(4 1
 
0.1%

사업장명
Text

Distinct974
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-03-14T21:24:21.766318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length24
Mean length6.4015748
Min length2

Characters and Unicode

Total characters6504
Distinct characters428
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

Unique943 ?
Unique (%)92.8%

Sample

1st row신진택시㈜
2nd row(주)세화금속
3rd row㈜대도기업
4th row유창금속
5th row유성금속
ValueCountFrequency (%)
주식회사 13
 
1.2%
금호건설㈜ 6
 
0.5%
2공장 4
 
0.4%
동부건설㈜ 4
 
0.4%
두산건설㈜ 3
 
0.3%
강한기업 3
 
0.3%
㈜성진로지스 3
 
0.3%
유창금속 3
 
0.3%
㈜금상화학 3
 
0.3%
컴인워시 3
 
0.3%
Other values (1021) 1060
95.9%
2024-03-14T21:24:23.102896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 415
 
6.4%
이 163
 
2.5%
주 154
 
2.4%
스 146
 
2.2%
업 132
 
2.0%
금 113
 
1.7%
에 106
 
1.6%
) 99
 
1.5%
( 99
 
1.5%
크 96
 
1.5%
Other values (418) 4981
76.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5588
85.9%
Other Symbol 415
 
6.4%
Uppercase Letter 135
 
2.1%
Close Punctuation 99
 
1.5%
Open Punctuation 99
 
1.5%
Space Separator 94
 
1.4%
Decimal Number 55
 
0.8%
Other Punctuation 12
 
0.2%
Lowercase Letter 6
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 163
 
2.9%
주 154
 
2.8%
스 146
 
2.6%
업 132
 
2.4%
금 113
 
2.0%
에 106
 
1.9%
크 96
 
1.7%
자 92
 
1.6%
유 91
 
1.6%
대 90
 
1.6%
Other values (373) 4405
78.8%
Uppercase Letter
ValueCountFrequency (%)
T 13
 
9.6%
P 11
 
8.1%
K 11
 
8.1%
C 11
 
8.1%
S 10
 
7.4%
E 9
 
6.7%
I 9
 
6.7%
A 8
 
5.9%
O 7
 
5.2%
J 7
 
5.2%
Other values (13) 39
28.9%
Decimal Number
ValueCountFrequency (%)
1 15
27.3%
2 13
23.6%
3 8
14.5%
0 6
 
10.9%
5 5
 
9.1%
7 3
 
5.5%
4 2
 
3.6%
8 2
 
3.6%
6 1
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
e 2
33.3%
s 1
16.7%
l 1
16.7%
c 1
16.7%
t 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 7
58.3%
& 3
25.0%
/ 2
 
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 415
100.0%
Close Punctuation
ValueCountFrequency (%)
) 99
100.0%
Open Punctuation
ValueCountFrequency (%)
( 99
100.0%
Space Separator
ValueCountFrequency (%)
94
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6003
92.3%
Common 360
 
5.5%
Latin 141
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 415
 
6.9%
이 163
 
2.7%
주 154
 
2.6%
스 146
 
2.4%
업 132
 
2.2%
금 113
 
1.9%
에 106
 
1.8%
크 96
 
1.6%
자 92
 
1.5%
유 91
 
1.5%
Other values (374) 4495
74.9%
Latin
ValueCountFrequency (%)
T 13
 
9.2%
P 11
 
7.8%
K 11
 
7.8%
C 11
 
7.8%
S 10
 
7.1%
E 9
 
6.4%
I 9
 
6.4%
A 8
 
5.7%
O 7
 
5.0%
J 7
 
5.0%
Other values (18) 45
31.9%
Common
ValueCountFrequency (%)
) 99
27.5%
( 99
27.5%
94
26.1%
1 15
 
4.2%
2 13
 
3.6%
3 8
 
2.2%
. 7
 
1.9%
0 6
 
1.7%
5 5
 
1.4%
7 3
 
0.8%
Other values (6) 11
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5588
85.9%
ASCII 501
 
7.7%
None 415
 
6.4%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 415
100.0%
Hangul
ValueCountFrequency (%)
이 163
 
2.9%
주 154
 
2.8%
스 146
 
2.6%
업 132
 
2.4%
금 113
 
2.0%
에 106
 
1.9%
크 96
 
1.7%
자 92
 
1.6%
유 91
 
1.6%
대 90
 
1.6%
Other values (373) 4405
78.8%
ASCII
ValueCountFrequency (%)
) 99
19.8%
( 99
19.8%
94
18.8%
1 15
 
3.0%
T 13
 
2.6%
2 13
 
2.6%
P 11
 
2.2%
K 11
 
2.2%
C 11
 
2.2%
S 10
 
2.0%
Other values (34) 125
25.0%

소재지(지번)
Text

Distinct941
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-03-14T21:24:24.308876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length86
Median length50
Mean length12.705709
Min length5

Characters and Unicode

Total characters12909
Distinct characters149
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

Unique893 ?
Unique (%)87.9%

Sample

1st row가좌동 260-20
2nd row가좌동 480-7
3rd row가좌동 272-15
4th row가좌동 602-36(A-101)
5th row가좌동 602-36(A-102)
ValueCountFrequency (%)
가좌동 380
 
16.5%
석남동 261
 
11.3%
원창동 105
 
4.6%
오류동 57
 
2.5%
왕길동 30
 
1.3%
청라동 25
 
1.1%
경서동 19
 
0.8%
7호선 18
 
0.8%
심곡동 17
 
0.7%
금곡동 14
 
0.6%
Other values (1077) 1377
59.8%
2024-03-14T21:24:25.660933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1322
 
10.2%
2 1074
 
8.3%
- 1050
 
8.1%
동 1049
 
8.1%
1 936
 
7.3%
3 882
 
6.8%
0 539
 
4.2%
5 519
 
4.0%
6 486
 
3.8%
4 466
 
3.6%
Other values (139) 4586
35.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5963
46.2%
Other Letter 4047
31.4%
Space Separator 1322
 
10.2%
Dash Punctuation 1050
 
8.1%
Close Punctuation 162
 
1.3%
Open Punctuation 161
 
1.2%
Other Punctuation 147
 
1.1%
Uppercase Letter 57
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1049
25.9%
가 417
 
10.3%
좌 401
 
9.9%
석 278
 
6.9%
남 268
 
6.6%
원 114
 
2.8%
창 109
 
2.7%
호 103
 
2.5%
류 62
 
1.5%
오 62
 
1.5%
Other values (110) 1184
29.3%
Decimal Number
ValueCountFrequency (%)
2 1074
18.0%
1 936
15.7%
3 882
14.8%
0 539
9.0%
5 519
8.7%
6 486
8.2%
4 466
7.8%
7 454
7.6%
8 368
 
6.2%
9 239
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 26
45.6%
B 22
38.6%
L 3
 
5.3%
D 2
 
3.5%
C 1
 
1.8%
T 1
 
1.8%
S 1
 
1.8%
G 1
 
1.8%
Other Punctuation
ValueCountFrequency (%)
, 129
87.8%
# 8
 
5.4%
. 4
 
2.7%
/ 4
 
2.7%
: 2
 
1.4%
Close Punctuation
ValueCountFrequency (%)
) 158
97.5%
] 4
 
2.5%
Open Punctuation
ValueCountFrequency (%)
( 157
97.5%
[ 4
 
2.5%
Space Separator
ValueCountFrequency (%)
1322
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1050
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8805
68.2%
Hangul 4047
31.4%
Latin 57
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1049
25.9%
가 417
 
10.3%
좌 401
 
9.9%
석 278
 
6.9%
남 268
 
6.6%
원 114
 
2.8%
창 109
 
2.7%
호 103
 
2.5%
류 62
 
1.5%
오 62
 
1.5%
Other values (110) 1184
29.3%
Common
ValueCountFrequency (%)
1322
15.0%
2 1074
12.2%
- 1050
11.9%
1 936
10.6%
3 882
10.0%
0 539
6.1%
5 519
 
5.9%
6 486
 
5.5%
4 466
 
5.3%
7 454
 
5.2%
Other values (11) 1077
12.2%
Latin
ValueCountFrequency (%)
A 26
45.6%
B 22
38.6%
L 3
 
5.3%
D 2
 
3.5%
C 1
 
1.8%
T 1
 
1.8%
S 1
 
1.8%
G 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8862
68.6%
Hangul 4047
31.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1322
14.9%
2 1074
12.1%
- 1050
11.8%
1 936
10.6%
3 882
10.0%
0 539
6.1%
5 519
 
5.9%
6 486
 
5.5%
4 466
 
5.3%
7 454
 
5.1%
Other values (19) 1134
12.8%
Hangul
ValueCountFrequency (%)
동 1049
25.9%
가 417
 
10.3%
좌 401
 
9.9%
석 278
 
6.9%
남 268
 
6.6%
원 114
 
2.8%
창 109
 
2.7%
호 103
 
2.5%
류 62
 
1.5%
오 62
 
1.5%
Other values (110) 1184
29.3%

소재지(도로명)
Text

Distinct929
Distinct (%)92.2%
Missing8
Missing (%)0.8%
Memory size8.1 KiB
2024-03-14T21:24:26.631648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length34
Mean length16.593254
Min length2

Characters and Unicode

Total characters16726
Distinct characters181
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique897 ?
Unique (%)89.0%

Sample

1st row신진말로28번길 21(가좌동)
2nd row가좌로96번길 43(가좌동)
3rd row원적로17번길 16(가좌동)
4th row중봉대로198번길 33, A-101(가좌동)
5th row중봉대로198번길 33, A-102(가좌동)
ValueCountFrequency (%)
중봉대로198번길 53
 
2.2%
건지로 51
 
2.1%
봉수대로 46
 
1.9%
건지로97번길 43
 
1.8%
33 39
 
1.6%
염곡로 30
 
1.2%
건지로153번길 29
 
1.2%
미부여 29
 
1.2%
백범로 27
 
1.1%
중봉대로240번길 26
 
1.1%
Other values (1048) 2043
84.6%
2024-03-14T21:24:27.918671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1450
 
8.7%
동 1017
 
6.1%
로 987
 
5.9%
) 944
 
5.6%
( 944
 
5.6%
1 932
 
5.6%
길 654
 
3.9%
3 636
 
3.8%
2 621
 
3.7%
번 604
 
3.6%
Other values (171) 7937
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8014
47.9%
Decimal Number 4735
28.3%
Space Separator 1450
 
8.7%
Close Punctuation 944
 
5.6%
Open Punctuation 944
 
5.6%
Other Punctuation 319
 
1.9%
Dash Punctuation 247
 
1.5%
Uppercase Letter 72
 
0.4%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1017
 
12.7%
로 987
 
12.3%
길 654
 
8.2%
번 604
 
7.5%
가 489
 
6.1%
좌 411
 
5.1%
석 291
 
3.6%
대 275
 
3.4%
남 272
 
3.4%
봉 241
 
3.0%
Other values (144) 2773
34.6%
Decimal Number
ValueCountFrequency (%)
1 932
19.7%
3 636
13.4%
2 621
13.1%
0 481
10.2%
4 440
9.3%
9 379
8.0%
5 346
 
7.3%
7 345
 
7.3%
6 281
 
5.9%
8 274
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
A 35
48.6%
B 26
36.1%
C 4
 
5.6%
D 2
 
2.8%
S 1
 
1.4%
K 1
 
1.4%
T 1
 
1.4%
P 1
 
1.4%
M 1
 
1.4%
Other Punctuation
ValueCountFrequency (%)
, 317
99.4%
· 1
 
0.3%
/ 1
 
0.3%
Space Separator
ValueCountFrequency (%)
1450
100.0%
Close Punctuation
ValueCountFrequency (%)
) 944
100.0%
Open Punctuation
ValueCountFrequency (%)
( 944
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 247
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8639
51.7%
Hangul 8015
47.9%
Latin 72
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1017
 
12.7%
로 987
 
12.3%
길 654
 
8.2%
번 604
 
7.5%
가 489
 
6.1%
좌 411
 
5.1%
석 291
 
3.6%
대 275
 
3.4%
남 272
 
3.4%
봉 241
 
3.0%
Other values (145) 2774
34.6%
Common
ValueCountFrequency (%)
1450
16.8%
) 944
10.9%
( 944
10.9%
1 932
10.8%
3 636
7.4%
2 621
7.2%
0 481
 
5.6%
4 440
 
5.1%
9 379
 
4.4%
5 346
 
4.0%
Other values (7) 1466
17.0%
Latin
ValueCountFrequency (%)
A 35
48.6%
B 26
36.1%
C 4
 
5.6%
D 2
 
2.8%
S 1
 
1.4%
K 1
 
1.4%
T 1
 
1.4%
P 1
 
1.4%
M 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8710
52.1%
Hangul 8014
47.9%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1450
16.6%
) 944
10.8%
( 944
10.8%
1 932
10.7%
3 636
7.3%
2 621
7.1%
0 481
 
5.5%
4 440
 
5.1%
9 379
 
4.4%
5 346
 
4.0%
Other values (15) 1537
17.6%
Hangul
ValueCountFrequency (%)
동 1017
 
12.7%
로 987
 
12.3%
길 654
 
8.2%
번 604
 
7.5%
가 489
 
6.1%
좌 411
 
5.1%
석 291
 
3.6%
대 275
 
3.4%
남 272
 
3.4%
봉 241
 
3.0%
Other values (144) 2773
34.6%
None
ValueCountFrequency (%)
· 1
50.0%
㈜ 1
50.0%

업종
Text

Distinct354
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size8.1 KiB
2024-03-14T21:24:28.739344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length8.1062992
Min length2

Characters and Unicode

Total characters8236
Distinct characters239
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique261 ?
Unique (%)25.7%

Sample

1st row세차시설
2nd row가공금속
3rd row운수
4th row도금업
5th row도금업
ValueCountFrequency (%)
도금업 180
 
11.2%
및 134
 
8.3%
인쇄회로기판제조업 108
 
6.7%
자동차세차업 61
 
3.8%
제조업 55
 
3.4%
세차시설 46
 
2.9%
외 32
 
2.0%
기타 28
 
1.7%
교량터널 23
 
1.4%
그 22
 
1.4%
Other values (427) 922
57.2%
2024-03-14T21:24:29.802055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 797
 
9.7%
605
 
7.3%
제 424
 
5.1%
조 357
 
4.3%
기 342
 
4.2%
차 275
 
3.3%
금 252
 
3.1%
도 247
 
3.0%
및 216
 
2.6%
세 192
 
2.3%
Other values (229) 4529
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7567
91.9%
Space Separator 605
 
7.3%
Other Punctuation 41
 
0.5%
Decimal Number 19
 
0.2%
Uppercase Letter 3
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 797
 
10.5%
제 424
 
5.6%
조 357
 
4.7%
기 342
 
4.5%
차 275
 
3.6%
금 252
 
3.3%
도 247
 
3.3%
및 216
 
2.9%
세 192
 
2.5%
판 146
 
1.9%
Other values (220) 4319
57.1%
Decimal Number
ValueCountFrequency (%)
1 16
84.2%
5 2
 
10.5%
3 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
P 1
33.3%
G 1
33.3%
Space Separator
ValueCountFrequency (%)
605
100.0%
Other Punctuation
ValueCountFrequency (%)
, 41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7567
91.9%
Common 666
 
8.1%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 797
 
10.5%
제 424
 
5.6%
조 357
 
4.7%
기 342
 
4.5%
차 275
 
3.6%
금 252
 
3.3%
도 247
 
3.3%
및 216
 
2.9%
세 192
 
2.5%
판 146
 
1.9%
Other values (220) 4319
57.1%
Common
ValueCountFrequency (%)
605
90.8%
, 41
 
6.2%
1 16
 
2.4%
5 2
 
0.3%
3 1
 
0.2%
- 1
 
0.2%
Latin
ValueCountFrequency (%)
L 1
33.3%
P 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7567
91.9%
ASCII 669
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 797
 
10.5%
제 424
 
5.6%
조 357
 
4.7%
기 342
 
4.5%
차 275
 
3.6%
금 252
 
3.3%
도 247
 
3.3%
및 216
 
2.9%
세 192
 
2.5%
판 146
 
1.9%
Other values (220) 4319
57.1%
ASCII
ValueCountFrequency (%)
605
90.4%
, 41
 
6.1%
1 16
 
2.4%
5 2
 
0.3%
3 1
 
0.1%
- 1
 
0.1%
L 1
 
0.1%
P 1
 
0.1%
G 1
 
0.1%

Interactions

2024-03-14T21:24:19.431300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:24:29.953984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수질
연번1.0000.332
수질0.3321.000
2024-03-14T21:24:30.088015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번수질
연번1.0000.107
수질0.1071.000

Missing values

2024-03-14T21:24:19.714434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:24:19.898379image/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

연번수질사업장명소재지(지번)소재지(도로명)업종
015신진택시㈜가좌동 260-20신진말로28번길 21(가좌동)세차시설
125(주)세화금속가좌동 480-7가좌로96번길 43(가좌동)가공금속
235㈜대도기업가좌동 272-15원적로17번길 16(가좌동)운수
345유창금속가좌동 602-36(A-101)중봉대로198번길 33, A-101(가좌동)도금업
455유성금속가좌동 602-36(A-102)중봉대로198번길 33, A-102(가좌동)도금업
565유성금속가좌동 602-36(A-103)중봉대로198번길 33, A-103(가좌동)도금업
675㈜대림금속가좌동 602-36(A-104)중봉대로198번길 33, A-104(가좌동)도금업
785세기산업가좌동 602-36(A-105)중봉대로198번길 33, A-105(가좌동)도금업
895(주)위드테크가좌동 602-36(A-202)중봉대로198번길 33, A-202(가좌동)도금업
9105골드문가좌동 602-36(A-203)중봉대로198번길 33, A-203(가좌동)도금업
연번수질사업장명소재지(지번)소재지(도로명)업종
100610075(주)일성다이아몬드가좌동 151-40가정로87번길 16, 1층(가좌동)비동력식 수공구 제조업
100710085㈜제이바이오앤코스메틱석남동 650-146중봉대로240번길 8, 3층(석남동)화장품제조업
100810095㈜엠에이치정밀테크가좌동 173-318보도진로54벌길 13, 1층(가좌동)그 외 기타 금속 가공업
100910103두산건설㈜청라동 106-2 출입수직구#2(서울도시철도 7호선 청라국제도시 연장 4공구)미부여교량터널 및 철도건설업
101010115제2해병사단금곡동 640향동로 62(금곡동, 사서함 204-1-5호 제2해병사단)자동차세차
101110125대원디자인포장산업㈜가좌동 178-15염곡로15번길 5-7(가좌동)골판지 상자 및
101210135킹콩샤워 주안점가좌동 606-36방축로 339-1(가좌동)자동차세차업
101310145컴인워시 인천서구 원당점원당동 1041-11미부여자동차세차업
101410155㈜에스에이치프러스가좌동 178-319염곡로15번길 13, 3층(가좌동)광학 렌즈 및 광학
101510164금호건설㈜석남동 179-109미부여교량터널 및