Overview

Dataset statistics

Number of variables23
Number of observations141
Missing cells250
Missing cells (%)7.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.2 KiB
Average record size in memory189.9 B

Variable types

Categorical10
Text9
Numeric4

Dataset

Description전라남도내 환경오염물질 배출사업장(업체명, 소재지, 전화, 오염물질 발생량, 생산제품 등)에 관한 정보입니다.
Author전라남도
URLhttps://www.data.go.kr/data/15069172/fileData.do

Alerts

대표자 is highly imbalanced (62.9%)Imbalance
휘발성 유기 화합물 is highly imbalanced (51.8%)Imbalance
자동측정장치(TMS)수질 is highly imbalanced (67.5%)Imbalance
전화 has 2 (1.4%) missing valuesMissing
팩스 has 2 (1.4%) missing valuesMissing
산업분류 has 17 (12.1%) missing valuesMissing
폐수배출량 has 41 (29.1%) missing valuesMissing
폐수처리용량 has 49 (34.8%) missing valuesMissing
폐수처리방법 has 41 (29.1%) missing valuesMissing
생산제품 has 3 (2.1%) missing valuesMissing
자동측정장치(TMS)대기 has 94 (66.7%) missing valuesMissing
업체명 has unique valuesUnique
폐수배출량 has 2 (1.4%) zerosZeros

Reproduction

Analysis started2023-12-12 12:02:15.567460
Analysis finished2023-12-12 12:02:16.301010
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

산단
Categorical

Distinct24
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
여수
34 
광양
27 
대불
18 
나주
8 
장성
7 
Other values (19)
47 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique5 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
여수 34
24.1%
광양 27
19.1%
대불 18
12.8%
나주 8
 
5.7%
장성 7
 
5.0%
율촌 5
 
3.5%
영광 4
 
2.8%
담양 4
 
2.8%
목포 4
 
2.8%
장흥 3
 
2.1%
Other values (14) 27
19.1%

Length

2023-12-12T21:02:16.390043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
여수 34
24.1%
광양 27
19.1%
대불 18
12.8%
나주 8
 
5.7%
장성 7
 
5.0%
율촌 5
 
3.5%
영광 4
 
2.8%
담양 4
 
2.8%
목포 4
 
2.8%
무안 3
 
2.1%
Other values (14) 27
19.1%

업체명
Text

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T21:02:16.688252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length27
Mean length10.475177
Min length3

Characters and Unicode

Total characters1477
Distinct characters231
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

Unique141 ?
Unique (%)100.0%

Sample

1st row금호미쓰이화학㈜
2nd row금호석유화학㈜여수정밀화학공장
3rd row금호피앤비화학㈜(제1공장)
4th row금호피앤비화학㈜(제2공장)
5th row남해화학㈜
ValueCountFrequency (%)
광양공장 4
 
2.0%
지점 2
 
1.0%
목포시 2
 
1.0%
현대삼호중공업㈜ 2
 
1.0%
한화솔루션㈜ 2
 
1.0%
나주공장 2
 
1.0%
대한시멘트㈜ 2
 
1.0%
환경관리센터 2
 
1.0%
생활폐기물 2
 
1.0%
여수1공장 2
 
1.0%
Other values (180) 181
89.2%
2023-12-12T21:02:17.157296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 126
 
8.5%
62
 
4.2%
공 48
 
3.2%
장 42
 
2.8%
스 40
 
2.7%
업 39
 
2.6%
( 35
 
2.4%
) 35
 
2.4%
화 27
 
1.8%
한 26
 
1.8%
Other values (221) 997
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1154
78.1%
Other Symbol 126
 
8.5%
Space Separator 62
 
4.2%
Open Punctuation 43
 
2.9%
Close Punctuation 43
 
2.9%
Decimal Number 23
 
1.6%
Other Punctuation 19
 
1.3%
Uppercase Letter 5
 
0.3%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 48
 
4.2%
장 42
 
3.6%
스 40
 
3.5%
업 39
 
3.4%
화 27
 
2.3%
한 26
 
2.3%
대 23
 
2.0%
시 22
 
1.9%
리 19
 
1.6%
양 19
 
1.6%
Other values (202) 849
73.6%
Other Punctuation
ValueCountFrequency (%)
, 9
47.4%
. 4
21.1%
: 4
21.1%
/ 1
 
5.3%
' 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
K 1
20.0%
I 1
20.0%
O 1
20.0%
Decimal Number
ValueCountFrequency (%)
1 13
56.5%
2 9
39.1%
7 1
 
4.3%
Open Punctuation
ValueCountFrequency (%)
( 35
81.4%
[ 8
 
18.6%
Close Punctuation
ValueCountFrequency (%)
) 35
81.4%
] 8
 
18.6%
Other Symbol
ValueCountFrequency (%)
㈜ 126
100.0%
Space Separator
ValueCountFrequency (%)
62
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1280
86.7%
Common 192
 
13.0%
Latin 5
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 126
 
9.8%
공 48
 
3.8%
장 42
 
3.3%
스 40
 
3.1%
업 39
 
3.0%
화 27
 
2.1%
한 26
 
2.0%
대 23
 
1.8%
시 22
 
1.7%
리 19
 
1.5%
Other values (203) 868
67.8%
Common
ValueCountFrequency (%)
62
32.3%
( 35
18.2%
) 35
18.2%
1 13
 
6.8%
2 9
 
4.7%
, 9
 
4.7%
[ 8
 
4.2%
] 8
 
4.2%
. 4
 
2.1%
: 4
 
2.1%
Other values (4) 5
 
2.6%
Latin
ValueCountFrequency (%)
C 2
40.0%
K 1
20.0%
I 1
20.0%
O 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1154
78.1%
ASCII 197
 
13.3%
None 126
 
8.5%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 126
100.0%
ASCII
ValueCountFrequency (%)
62
31.5%
( 35
17.8%
) 35
17.8%
1 13
 
6.6%
2 9
 
4.6%
, 9
 
4.6%
[ 8
 
4.1%
] 8
 
4.1%
. 4
 
2.0%
: 4
 
2.0%
Other values (8) 10
 
5.1%
Hangul
ValueCountFrequency (%)
공 48
 
4.2%
장 42
 
3.6%
스 40
 
3.5%
업 39
 
3.4%
화 27
 
2.3%
한 26
 
2.3%
대 23
 
2.0%
시 22
 
1.9%
리 19
 
1.6%
양 19
 
1.6%
Other values (202) 849
73.6%

소재지
Text

Distinct132
Distinct (%)93.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T21:02:17.596981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length25
Mean length19.312057
Min length13

Characters and Unicode

Total characters2723
Distinct characters142
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique126 ?
Unique (%)89.4%

Sample

1st row여수시 여수산단2로 305 (화치동)
2nd row여수시 여수산단2로 227 (화치동)
3rd row여수시 여수산단2로 218 (화치동)
4th row여수시 여수산단2로 46-53 (월하동)
5th row여수시 여수산단로 1384 (낙포동)
ValueCountFrequency (%)
여수시 35
 
6.2%
광양시 29
 
5.2%
삼호읍 19
 
3.4%
영암군 19
 
3.4%
제철로 11
 
2.0%
여수산단로 10
 
1.8%
여수산단2로 10
 
1.8%
나주시 8
 
1.4%
금호동 7
 
1.2%
장성군 7
 
1.2%
Other values (298) 408
72.5%
2023-12-12T21:02:18.230277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
427
 
15.7%
로 114
 
4.2%
1 101
 
3.7%
3 88
 
3.2%
) 87
 
3.2%
( 87
 
3.2%
시 83
 
3.0%
2 82
 
3.0%
동 73
 
2.7%
4 67
 
2.5%
Other values (132) 1514
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1449
53.2%
Decimal Number 616
22.6%
Space Separator 427
 
15.7%
Close Punctuation 87
 
3.2%
Open Punctuation 87
 
3.2%
Dash Punctuation 57
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 114
 
7.9%
시 83
 
5.7%
동 73
 
5.0%
군 62
 
4.3%
수 61
 
4.2%
산 61
 
4.2%
여 60
 
4.1%
단 53
 
3.7%
양 41
 
2.8%
광 40
 
2.8%
Other values (118) 801
55.3%
Decimal Number
ValueCountFrequency (%)
1 101
16.4%
3 88
14.3%
2 82
13.3%
4 67
10.9%
7 52
8.4%
8 50
8.1%
5 49
8.0%
6 47
7.6%
0 45
7.3%
9 35
 
5.7%
Space Separator
ValueCountFrequency (%)
427
100.0%
Close Punctuation
ValueCountFrequency (%)
) 87
100.0%
Open Punctuation
ValueCountFrequency (%)
( 87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1449
53.2%
Common 1274
46.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 114
 
7.9%
시 83
 
5.7%
동 73
 
5.0%
군 62
 
4.3%
수 61
 
4.2%
산 61
 
4.2%
여 60
 
4.1%
단 53
 
3.7%
양 41
 
2.8%
광 40
 
2.8%
Other values (118) 801
55.3%
Common
ValueCountFrequency (%)
427
33.5%
1 101
 
7.9%
3 88
 
6.9%
) 87
 
6.8%
( 87
 
6.8%
2 82
 
6.4%
4 67
 
5.3%
- 57
 
4.5%
7 52
 
4.1%
8 50
 
3.9%
Other values (4) 176
13.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1449
53.2%
ASCII 1274
46.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
427
33.5%
1 101
 
7.9%
3 88
 
6.9%
) 87
 
6.8%
( 87
 
6.8%
2 82
 
6.4%
4 67
 
5.3%
- 57
 
4.5%
7 52
 
4.1%
8 50
 
3.9%
Other values (4) 176
13.8%
Hangul
ValueCountFrequency (%)
로 114
 
7.9%
시 83
 
5.7%
동 73
 
5.0%
군 62
 
4.3%
수 61
 
4.2%
산 61
 
4.2%
여 60
 
4.1%
단 53
 
3.7%
양 41
 
2.8%
광 40
 
2.8%
Other values (118) 801
55.3%

대표자
Categorical

IMBALANCE 

Distinct30
Distinct (%)21.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
대표이사
110 
목포시장
 
2
여수시장
 
2
장흥군수
 
1
대표집행임원
 
1
Other values (25)
25 

Length

Max length7
Median length4
Mean length3.9432624
Min length2

Unique

Unique27 ?
Unique (%)19.1%

Sample

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

Common Values

ValueCountFrequency (%)
대표이사 110
78.0%
목포시장 2
 
1.4%
여수시장 2
 
1.4%
장흥군수 1
 
0.7%
대표집행임원 1
 
0.7%
순천시장 1
 
0.7%
담양군수 1
 
0.7%
오진수 1
 
0.7%
김은식 1
 
0.7%
고흥군수 1
 
0.7%
Other values (20) 20
 
14.2%

Length

2023-12-12T21:02:18.378264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대표이사 110
77.5%
여수시장 2
 
1.4%
목포시장 2
 
1.4%
지사장 1
 
0.7%
완도군수 1
 
0.7%
장성군수 1
 
0.7%
본부장 1
 
0.7%
영광군수 1
 
0.7%
무안군수 1
 
0.7%
해남군수 1
 
0.7%
Other values (21) 21
 
14.8%

전화
Text

MISSING 

Distinct135
Distinct (%)97.1%
Missing2
Missing (%)1.4%
Memory size1.2 KiB
2023-12-12T21:02:18.678528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length12.172662
Min length12

Characters and Unicode

Total characters1692
Distinct characters15
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique131 ?
Unique (%)94.2%

Sample

1st row061-688-5095
2nd row061-688-3942
3rd row061-688-3680
4th row061-688-3683
5th row061-688-5752(5753)
ValueCountFrequency (%)
061-463-9335 2
 
1.4%
061-688-1162 2
 
1.4%
061-270-4231 2
 
1.4%
061-531-1909 2
 
1.4%
061-463-9790 1
 
0.7%
061-460-8622 1
 
0.7%
061-331-9434 1
 
0.7%
061-461-1334 1
 
0.7%
061-462-6643 1
 
0.7%
061-460-7119 1
 
0.7%
Other values (125) 125
89.9%
2023-12-12T21:02:19.147758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 279
16.5%
0 256
15.1%
6 241
14.2%
1 232
13.7%
3 132
7.8%
8 101
 
6.0%
9 96
 
5.7%
2 95
 
5.6%
7 93
 
5.5%
4 83
 
4.9%
Other values (5) 84
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1408
83.2%
Dash Punctuation 279
 
16.5%
Other Punctuation 2
 
0.1%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 256
18.2%
6 241
17.1%
1 232
16.5%
3 132
9.4%
8 101
 
7.2%
9 96
 
6.8%
2 95
 
6.7%
7 93
 
6.6%
4 83
 
5.9%
5 79
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 279
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1692
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 279
16.5%
0 256
15.1%
6 241
14.2%
1 232
13.7%
3 132
7.8%
8 101
 
6.0%
9 96
 
5.7%
2 95
 
5.6%
7 93
 
5.5%
4 83
 
4.9%
Other values (5) 84
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1692
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 279
16.5%
0 256
15.1%
6 241
14.2%
1 232
13.7%
3 132
7.8%
8 101
 
6.0%
9 96
 
5.7%
2 95
 
5.6%
7 93
 
5.5%
4 83
 
4.9%
Other values (5) 84
 
5.0%

팩스
Text

MISSING 

Distinct135
Distinct (%)97.1%
Missing2
Missing (%)1.4%
Memory size1.2 KiB
2023-12-12T21:02:19.501755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.014388
Min length12

Characters and Unicode

Total characters1670
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

Unique131 ?
Unique (%)94.2%

Sample

1st row061-688-5099
2nd row061-685-5806
3rd row061-688-3686
4th row061-688-3686
5th row061-688-5758
ValueCountFrequency (%)
061-688-3686 2
 
1.4%
061-463-9334 2
 
1.4%
061-531-1919 2
 
1.4%
061-688-1140 2
 
1.4%
061-460-7070 1
 
0.7%
061-461-1336 1
 
0.7%
061-462-9676 1
 
0.7%
061-460-1302 1
 
0.7%
061-460-8619 1
 
0.7%
061-462-2263 1
 
0.7%
Other values (125) 125
89.9%
2023-12-12T21:02:20.018187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 278
16.6%
6 250
15.0%
0 248
14.9%
1 214
12.8%
3 116
6.9%
8 114
6.8%
9 100
 
6.0%
7 93
 
5.6%
5 88
 
5.3%
2 85
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1392
83.4%
Dash Punctuation 278
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 250
18.0%
0 248
17.8%
1 214
15.4%
3 116
8.3%
8 114
8.2%
9 100
 
7.2%
7 93
 
6.7%
5 88
 
6.3%
2 85
 
6.1%
4 84
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 278
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1670
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 278
16.6%
6 250
15.0%
0 248
14.9%
1 214
12.8%
3 116
6.9%
8 114
6.8%
9 100
 
6.0%
7 93
 
5.6%
5 88
 
5.3%
2 85
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1670
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 278
16.6%
6 250
15.0%
0 248
14.9%
1 214
12.8%
3 116
6.9%
8 114
6.8%
9 100
 
6.0%
7 93
 
5.6%
5 88
 
5.3%
2 85
 
5.1%

우편번호
Real number (ℝ)

Distinct72
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58465.504
Minimum57001
Maximum59747
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:02:20.209721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57001
5-th percentile57208
Q157812
median58452
Q359552
95-th percentile59616
Maximum59747
Range2746
Interquartile range (IQR)1740

Descriptive statistics

Standard deviation857.18264
Coefficient of variation (CV)0.01466134
Kurtosis-1.2987238
Mean58465.504
Median Absolute Deviation (MAD)687
Skewness0.11733011
Sum8243636
Variance734762.08
MonotonicityNot monotonic
2023-12-12T21:02:20.430909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
57816 12
 
8.5%
58460 12
 
8.5%
59611 11
 
7.8%
57812 10
 
7.1%
59614 8
 
5.7%
59618 5
 
3.5%
59616 4
 
2.8%
57765 3
 
2.1%
57227 3
 
2.1%
58453 2
 
1.4%
Other values (62) 71
50.4%
ValueCountFrequency (%)
57001 1
0.7%
57003 1
0.7%
57038 1
0.7%
57055 1
0.7%
57116 1
0.7%
57125 1
0.7%
57136 1
0.7%
57208 1
0.7%
57216 1
0.7%
57218 1
0.7%
ValueCountFrequency (%)
59747 1
 
0.7%
59694 1
 
0.7%
59618 5
3.5%
59616 4
 
2.8%
59614 8
5.7%
59613 1
 
0.7%
59612 1
 
0.7%
59611 11
7.8%
59610 2
 
1.4%
59602 1
 
0.7%

대기종별
Categorical

Distinct8
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
1특
66 
2
36 
2특
16 
1
11 
4
 
6
Other values (3)
 
6

Length

Max length4
Median length2
Mean length1.6170213
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row5특
2nd row2특
3rd row1특
4th row1특
5th row1특

Common Values

ValueCountFrequency (%)
1특 66
46.8%
2 36
25.5%
2특 16
 
11.3%
1 11
 
7.8%
4 6
 
4.3%
3 3
 
2.1%
5특 2
 
1.4%
<NA> 1
 
0.7%

Length

2023-12-12T21:02:20.651025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:20.824386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1특 66
46.8%
2 36
25.5%
2특 16
 
11.3%
1 11
 
7.8%
4 6
 
4.3%
3 3
 
2.1%
5특 2
 
1.4%
na 1
 
0.7%

대기등급
Categorical

Distinct4
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
일반
87 
우수
28 
중점
25 
<NA>
 
1

Length

Max length4
Median length2
Mean length2.0141844
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row일반
2nd row일반
3rd row일반
4th row중점
5th row중점

Common Values

ValueCountFrequency (%)
일반 87
61.7%
우수 28
 
19.9%
중점 25
 
17.7%
<NA> 1
 
0.7%

Length

2023-12-12T21:02:20.997869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:21.176261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 87
61.7%
우수 28
 
19.9%
중점 25
 
17.7%
na 1
 
0.7%

대기점검횟수
Categorical

Distinct8
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
4
38 
2
36 
3
23 
5
22 
1(1/2)
12 
Other values (3)
10 

Length

Max length6
Median length1
Mean length1.5531915
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row2
2nd row3
3rd row4
4th row5
5th row5

Common Values

ValueCountFrequency (%)
4 38
27.0%
2 36
25.5%
3 23
16.3%
5 22
15.6%
1(1/2) 12
 
8.5%
1 6
 
4.3%
0(1/2) 3
 
2.1%
<NA> 1
 
0.7%

Length

2023-12-12T21:02:21.350903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:21.545392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 38
27.0%
2 36
25.5%
3 23
16.3%
5 22
15.6%
1(1/2 12
 
8.5%
1 6
 
4.3%
0(1/2 3
 
2.1%
na 1
 
0.7%

수질종별
Categorical

Distinct10
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
5
42 
<NA>
40 
1특
19 
2특
15 
5특
10 
Other values (5)
15 

Length

Max length4
Median length2
Mean length2.2411348
Min length1

Unique

Unique2 ?
Unique (%)1.4%

Sample

1st row1특
2nd row3특
3rd row1특
4th row2특
5th row1특

Common Values

ValueCountFrequency (%)
5 42
29.8%
<NA> 40
28.4%
1특 19
13.5%
2특 15
 
10.6%
5특 10
 
7.1%
4특 6
 
4.3%
3특 5
 
3.5%
4 2
 
1.4%
1 1
 
0.7%
3 1
 
0.7%

Length

2023-12-12T21:02:21.728988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:21.915089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 42
29.8%
na 40
28.4%
1특 19
13.5%
2특 15
 
10.6%
5특 10
 
7.1%
4특 6
 
4.3%
3특 5
 
3.5%
4 2
 
1.4%
1 1
 
0.7%
3 1
 
0.7%

수질등급
Categorical

Distinct4
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
우수
63 
<NA>
40 
일반
33 
중점
 
5

Length

Max length4
Median length2
Mean length2.5673759
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row일반
2nd row우수
3rd row우수
4th row우수
5th row일반

Common Values

ValueCountFrequency (%)
우수 63
44.7%
<NA> 40
28.4%
일반 33
23.4%
중점 5
 
3.5%

Length

2023-12-12T21:02:22.113859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:22.286690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우수 63
44.7%
na 40
28.4%
일반 33
23.4%
중점 5
 
3.5%

수질점검횟수
Categorical

Distinct10
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
40 
1
33 
1(1/2)
15 
2
14 
0(1/2)
11 
Other values (5)
28 

Length

Max length6
Median length1
Mean length2.9148936
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4
2nd row1
3rd row2
4th row1
5th row4

Common Values

ValueCountFrequency (%)
<NA> 40
28.4%
1 33
23.4%
1(1/2) 15
 
10.6%
2 14
 
9.9%
0(1/2) 11
 
7.8%
4 8
 
5.7%
3 8
 
5.7%
0 4
 
2.8%
5 4
 
2.8%
2(1/2) 4
 
2.8%

Length

2023-12-12T21:02:22.477014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:22.649004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 40
28.4%
1 33
23.4%
1(1/2 15
 
10.6%
2 14
 
9.9%
0(1/2 11
 
7.8%
4 8
 
5.7%
3 8
 
5.7%
0 4
 
2.8%
5 4
 
2.8%
2(1/2 4
 
2.8%

휘발성 유기 화합물
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
113 
여
27 
사용업
 
1

Length

Max length4
Median length4
Mean length3.4184397
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 113
80.1%
여 27
 
19.1%
사용업 1
 
0.7%

Length

2023-12-12T21:02:22.853798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:23.011869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 113
80.1%
여 27
 
19.1%
사용업 1
 
0.7%

업종
Text

Distinct81
Distinct (%)57.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T21:02:23.380911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length21
Mean length11
Min length3

Characters and Unicode

Total characters1551
Distinct characters130
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)46.1%

Sample

1st row기타 기초유기화학물질 제조업
2nd row그외 기타 분류안된화학제품 제조업
3rd row기타 기초유기화학물질 제조업
4th row기타 기초유기화학물질 제조업
5th row복합비료제조업
ValueCountFrequency (%)
제조업 30
 
10.7%
기타 22
 
7.9%
및 17
 
6.1%
아스콘제조업 16
 
5.7%
선박구성부분품제조업 11
 
3.9%
환경행정(생활폐기물 8
 
2.9%
소각 8
 
2.9%
기초유기화학물질 7
 
2.5%
시멘트 6
 
2.1%
합성수지 4
 
1.4%
Other values (111) 151
53.9%
2023-12-12T21:02:23.936617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
139
 
9.0%
업 133
 
8.6%
제 126
 
8.1%
조 111
 
7.2%
기 86
 
5.5%
물 55
 
3.5%
품 36
 
2.3%
타 33
 
2.1%
스 29
 
1.9%
화 27
 
1.7%
Other values (120) 776
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1384
89.2%
Space Separator 139
 
9.0%
Open Punctuation 12
 
0.8%
Close Punctuation 12
 
0.8%
Other Punctuation 3
 
0.2%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 133
 
9.6%
제 126
 
9.1%
조 111
 
8.0%
기 86
 
6.2%
물 55
 
4.0%
품 36
 
2.6%
타 33
 
2.4%
스 29
 
2.1%
화 27
 
2.0%
정 23
 
1.7%
Other values (115) 725
52.4%
Space Separator
ValueCountFrequency (%)
139
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1384
89.2%
Common 167
 
10.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 133
 
9.6%
제 126
 
9.1%
조 111
 
8.0%
기 86
 
6.2%
물 55
 
4.0%
품 36
 
2.6%
타 33
 
2.4%
스 29
 
2.1%
화 27
 
2.0%
정 23
 
1.7%
Other values (115) 725
52.4%
Common
ValueCountFrequency (%)
139
83.2%
( 12
 
7.2%
) 12
 
7.2%
, 3
 
1.8%
1 1
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1384
89.2%
ASCII 167
 
10.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
139
83.2%
( 12
 
7.2%
) 12
 
7.2%
, 3
 
1.8%
1 1
 
0.6%
Hangul
ValueCountFrequency (%)
업 133
 
9.6%
제 126
 
9.1%
조 111
 
8.0%
기 86
 
6.2%
물 55
 
4.0%
품 36
 
2.6%
타 33
 
2.4%
스 29
 
2.1%
화 27
 
2.0%
정 23
 
1.7%
Other values (115) 725
52.4%

산업분류
Text

MISSING 

Distinct62
Distinct (%)50.0%
Missing17
Missing (%)12.1%
Memory size1.2 KiB
2023-12-12T21:02:24.196675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length4.9919355
Min length2

Characters and Unicode

Total characters619
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)36.3%

Sample

1st row20119
2nd row20499
3rd row20119
4th row20119
5th row20202
ValueCountFrequency (%)
76213 13
 
10.5%
23991 12
 
9.7%
20119 9
 
7.3%
26921 6
 
4.8%
31114 6
 
4.8%
35114 5
 
4.0%
20302 4
 
3.2%
20129 4
 
3.2%
38210 3
 
2.4%
20111 3
 
2.4%
Other values (52) 59
47.6%
2023-12-12T21:02:24.598524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 167
27.0%
2 139
22.5%
3 86
13.9%
9 74
12.0%
0 65
 
10.5%
6 22
 
3.6%
4 21
 
3.4%
5 18
 
2.9%
7 15
 
2.4%
8 10
 
1.6%
Other values (2) 2
 
0.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 617
99.7%
Other Letter 2
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 167
27.1%
2 139
22.5%
3 86
13.9%
9 74
12.0%
0 65
 
10.5%
6 22
 
3.6%
4 21
 
3.4%
5 18
 
2.9%
7 15
 
2.4%
8 10
 
1.6%
Other Letter
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 617
99.7%
Hangul 2
 
0.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 167
27.1%
2 139
22.5%
3 86
13.9%
9 74
12.0%
0 65
 
10.5%
6 22
 
3.6%
4 21
 
3.4%
5 18
 
2.9%
7 15
 
2.4%
8 10
 
1.6%
Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 617
99.7%
Hangul 2
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 167
27.1%
2 139
22.5%
3 86
13.9%
9 74
12.0%
0 65
 
10.5%
6 22
 
3.6%
4 21
 
3.4%
5 18
 
2.9%
7 15
 
2.4%
8 10
 
1.6%
Hangul
ValueCountFrequency (%)
기 1
50.0%
타 1
50.0%

오염물질발생량(톤_년)
Real number (ℝ)

Distinct140
Distinct (%)100.0%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean2566.0635
Minimum1
Maximum225396
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:02:24.746142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.2934
Q143.2825
median144.5685
Q3539.68475
95-th percentile5594.6875
Maximum225396
Range225395
Interquartile range (IQR)496.40225

Descriptive statistics

Standard deviation19192.123
Coefficient of variation (CV)7.4792083
Kurtosis133.45319
Mean2566.0635
Median Absolute Deviation (MAD)114.825
Skewness11.438281
Sum359248.89
Variance3.683376 × 108
MonotonicityNot monotonic
2023-12-12T21:02:25.207021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.0 1
 
0.7%
50.68 1
 
0.7%
185.93 1
 
0.7%
157.41 1
 
0.7%
155.87 1
 
0.7%
71.23 1
 
0.7%
40.8 1
 
0.7%
149.267 1
 
0.7%
23.16 1
 
0.7%
23.749 1
 
0.7%
Other values (130) 130
92.2%
ValueCountFrequency (%)
1.0 1
0.7%
3.53 1
0.7%
4.326 1
0.7%
4.37 1
0.7%
4.97 1
0.7%
8.06 1
0.7%
8.855 1
0.7%
13.527 1
0.7%
17.7 1
0.7%
18.563 1
0.7%
ValueCountFrequency (%)
225396.0 1
0.7%
24535.78 1
0.7%
20074.27 1
0.7%
6987.32 1
0.7%
6763.14 1
0.7%
6726.95 1
0.7%
5695.15 1
0.7%
5589.4 1
0.7%
4905.43 1
0.7%
4193.03 1
0.7%

폐수배출량
Real number (ℝ)

MISSING  ZEROS 

Distinct95
Distinct (%)95.0%
Missing41
Missing (%)29.1%
Infinite0
Infinite (%)0.0%
Mean2019.0527
Minimum0
Maximum35240.3
Zeros2
Zeros (%)1.4%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:02:25.355688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q122.5
median76.9
Q31608.395
95-th percentile12505.764
Maximum35240.3
Range35240.3
Interquartile range (IQR)1585.895

Descriptive statistics

Standard deviation4953.0786
Coefficient of variation (CV)2.4531696
Kurtosis21.583657
Mean2019.0527
Median Absolute Deviation (MAD)75.38
Skewness4.1541938
Sum201905.27
Variance24532987
MonotonicityNot monotonic
2023-12-12T21:02:25.520047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.0 2
 
1.4%
0.0 2
 
1.4%
2.0 2
 
1.4%
20.0 2
 
1.4%
10.0 2
 
1.4%
350.986 1
 
0.7%
278.6 1
 
0.7%
127.0 1
 
0.7%
33.0 1
 
0.7%
730.0 1
 
0.7%
Other values (85) 85
60.3%
(Missing) 41
29.1%
ValueCountFrequency (%)
0.0 2
1.4%
0.36 1
0.7%
1.04 1
0.7%
2.0 2
1.4%
2.5 1
0.7%
5.05 1
0.7%
7.0 2
1.4%
7.8 1
0.7%
10.0 2
1.4%
10.79 1
0.7%
ValueCountFrequency (%)
35240.3 1
0.7%
18030.0 1
0.7%
16036.0 1
0.7%
13852.4 1
0.7%
13050.0 1
0.7%
12477.12 1
0.7%
11611.5 1
0.7%
9031.0 1
0.7%
8663.7 1
0.7%
7539.0 1
0.7%

폐수처리용량
Text

MISSING 

Distinct69
Distinct (%)75.0%
Missing49
Missing (%)34.8%
Memory size1.2 KiB
2023-12-12T21:02:25.780065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length3.5217391
Min length1

Characters and Unicode

Total characters324
Distinct characters25
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)56.5%

Sample

1st row3000
2nd row900
3rd row4139
4th row4139
5th row17000
ValueCountFrequency (%)
100 4
 
4.3%
3000 4
 
4.3%
40 4
 
4.3%
7 2
 
2.2%
30 2
 
2.2%
25 2
 
2.2%
15 2
 
2.2%
2000 2
 
2.2%
10 2
 
2.2%
2 2
 
2.2%
Other values (59) 66
71.7%
2023-12-12T21:02:26.202340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 96
29.6%
1 39
12.0%
2 32
 
9.9%
3 28
 
8.6%
4 25
 
7.7%
5 19
 
5.9%
7 15
 
4.6%
6 15
 
4.6%
8 14
 
4.3%
. 14
 
4.3%
Other values (15) 27
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 294
90.7%
Other Punctuation 15
 
4.6%
Other Letter 12
 
3.7%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%
Other Symbol 1
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 96
32.7%
1 39
13.3%
2 32
 
10.9%
3 28
 
9.5%
4 25
 
8.5%
5 19
 
6.5%
7 15
 
5.1%
6 15
 
5.1%
8 14
 
4.8%
9 11
 
3.7%
Other Letter
ValueCountFrequency (%)
장 2
16.7%
저 2
16.7%
조 1
8.3%
시 1
8.3%
설 1
8.3%
전 1
8.3%
량 1
8.3%
재 1
8.3%
이 1
8.3%
용 1
8.3%
Other Punctuation
ValueCountFrequency (%)
. 14
93.3%
, 1
 
6.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎥ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
96.3%
Hangul 12
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 96
30.8%
1 39
12.5%
2 32
 
10.3%
3 28
 
9.0%
4 25
 
8.0%
5 19
 
6.1%
7 15
 
4.8%
6 15
 
4.8%
8 14
 
4.5%
. 14
 
4.5%
Other values (5) 15
 
4.8%
Hangul
ValueCountFrequency (%)
장 2
16.7%
저 2
16.7%
조 1
8.3%
시 1
8.3%
설 1
8.3%
전 1
8.3%
량 1
8.3%
재 1
8.3%
이 1
8.3%
용 1
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 311
96.0%
Hangul 12
 
3.7%
CJK Compat 1
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 96
30.9%
1 39
12.5%
2 32
 
10.3%
3 28
 
9.0%
4 25
 
8.0%
5 19
 
6.1%
7 15
 
4.8%
6 15
 
4.8%
8 14
 
4.5%
. 14
 
4.5%
Other values (4) 14
 
4.5%
Hangul
ValueCountFrequency (%)
장 2
16.7%
저 2
16.7%
조 1
8.3%
시 1
8.3%
설 1
8.3%
전 1
8.3%
량 1
8.3%
재 1
8.3%
이 1
8.3%
용 1
8.3%
CJK Compat
ValueCountFrequency (%)
㎥ 1
100.0%

폐수처리방법
Text

MISSING 

Distinct53
Distinct (%)53.0%
Missing41
Missing (%)29.1%
Memory size1.2 KiB
2023-12-12T21:02:26.461072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length26
Mean length10.1
Min length2

Characters and Unicode

Total characters1010
Distinct characters77
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)34.0%

Sample

1st row물리, 화학(종말처리)
2nd row금호피앤비1공장 공동방지
3rd row물·화·생(공동방지)
4th row금호피앤비1공장 공동방지
5th row물·화·생(자가방류)
ValueCountFrequency (%)
물리(재이용 12
 
9.0%
물·화·생(종말처리 9
 
6.8%
물·화·생 7
 
5.3%
물리 5
 
3.8%
전량재이용 4
 
3.0%
물·화·생(자가방류 4
 
3.0%
재이용 3
 
2.3%
1배수처리시설 3
 
2.3%
위탁처리 3
 
2.3%
물리화학 3
 
2.3%
Other values (60) 80
60.2%
2023-12-12T21:02:26.891980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
물 89
 
8.8%
리 87
 
8.6%
· 69
 
6.8%
) 64
 
6.3%
( 64
 
6.3%
화 61
 
6.0%
처 48
 
4.8%
용 40
 
4.0%
이 38
 
3.8%
재 38
 
3.8%
Other values (67) 412
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 763
75.5%
Other Punctuation 77
 
7.6%
Close Punctuation 64
 
6.3%
Open Punctuation 64
 
6.3%
Space Separator 33
 
3.3%
Decimal Number 7
 
0.7%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
물 89
 
11.7%
리 87
 
11.4%
화 61
 
8.0%
처 48
 
6.3%
용 40
 
5.2%
이 38
 
5.0%
재 38
 
5.0%
생 32
 
4.2%
종 25
 
3.3%
말 25
 
3.3%
Other values (59) 280
36.7%
Other Punctuation
ValueCountFrequency (%)
· 69
89.6%
, 8
 
10.4%
Decimal Number
ValueCountFrequency (%)
1 6
85.7%
2 1
 
14.3%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Space Separator
ValueCountFrequency (%)
33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 763
75.5%
Common 247
 
24.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
물 89
 
11.7%
리 87
 
11.4%
화 61
 
8.0%
처 48
 
6.3%
용 40
 
5.2%
이 38
 
5.0%
재 38
 
5.0%
생 32
 
4.2%
종 25
 
3.3%
말 25
 
3.3%
Other values (59) 280
36.7%
Common
ValueCountFrequency (%)
· 69
27.9%
) 64
25.9%
( 64
25.9%
33
13.4%
, 8
 
3.2%
1 6
 
2.4%
- 2
 
0.8%
2 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 763
75.5%
ASCII 178
 
17.6%
None 69
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
물 89
 
11.7%
리 87
 
11.4%
화 61
 
8.0%
처 48
 
6.3%
용 40
 
5.2%
이 38
 
5.0%
재 38
 
5.0%
생 32
 
4.2%
종 25
 
3.3%
말 25
 
3.3%
Other values (59) 280
36.7%
None
ValueCountFrequency (%)
· 69
100.0%
ASCII
ValueCountFrequency (%)
) 64
36.0%
( 64
36.0%
33
18.5%
, 8
 
4.5%
1 6
 
3.4%
- 2
 
1.1%
2 1
 
0.6%

생산제품
Text

MISSING 

Distinct92
Distinct (%)66.7%
Missing3
Missing (%)2.1%
Memory size1.2 KiB
2023-12-12T21:02:27.216024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length5.0869565
Min length2

Characters and Unicode

Total characters702
Distinct characters187
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)55.1%

Sample

1st rowANILINE,부생HCL
2nd row가황 촉진제
3rd row페놀,아세톤
4th rowEPOXY, BPA, MIBK
5th row황산,농질산
ValueCountFrequency (%)
아스콘 19
 
11.3%
시멘트 7
 
4.2%
소각 5
 
3.0%
슬래그 5
 
3.0%
폐기물소각 5
 
3.0%
선 4
 
2.4%
박구성품 4
 
2.4%
선박구성품 3
 
1.8%
srf 3
 
1.8%
구조물 3
 
1.8%
Other values (97) 110
65.5%
2023-12-12T21:02:27.718426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34
 
4.8%
아 24
 
3.4%
스 24
 
3.4%
콘 20
 
2.8%
물 20
 
2.8%
소 20
 
2.8%
, 19
 
2.7%
구 15
 
2.1%
각 14
 
2.0%
품 12
 
1.7%
Other values (177) 500
71.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 554
78.9%
Uppercase Letter 71
 
10.1%
Space Separator 34
 
4.8%
Other Punctuation 19
 
2.7%
Lowercase Letter 15
 
2.1%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Decimal Number 2
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 24
 
4.3%
스 24
 
4.3%
콘 20
 
3.6%
물 20
 
3.6%
소 20
 
3.6%
구 15
 
2.7%
각 14
 
2.5%
품 12
 
2.2%
기 12
 
2.2%
제 11
 
2.0%
Other values (141) 382
69.0%
Uppercase Letter
ValueCountFrequency (%)
P 8
11.3%
S 7
 
9.9%
A 7
 
9.9%
B 6
 
8.5%
N 5
 
7.0%
F 5
 
7.0%
E 4
 
5.6%
C 4
 
5.6%
D 4
 
5.6%
I 3
 
4.2%
Other values (10) 18
25.4%
Lowercase Letter
ValueCountFrequency (%)
e 5
33.3%
k 2
 
13.3%
o 2
 
13.3%
h 1
 
6.7%
c 1
 
6.7%
t 1
 
6.7%
i 1
 
6.7%
l 1
 
6.7%
d 1
 
6.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
3 1
50.0%
Space Separator
ValueCountFrequency (%)
34
100.0%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 554
78.9%
Latin 86
 
12.3%
Common 62
 
8.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 24
 
4.3%
스 24
 
4.3%
콘 20
 
3.6%
물 20
 
3.6%
소 20
 
3.6%
구 15
 
2.7%
각 14
 
2.5%
품 12
 
2.2%
기 12
 
2.2%
제 11
 
2.0%
Other values (141) 382
69.0%
Latin
ValueCountFrequency (%)
P 8
 
9.3%
S 7
 
8.1%
A 7
 
8.1%
B 6
 
7.0%
e 5
 
5.8%
N 5
 
5.8%
F 5
 
5.8%
E 4
 
4.7%
C 4
 
4.7%
D 4
 
4.7%
Other values (19) 31
36.0%
Common
ValueCountFrequency (%)
34
54.8%
, 19
30.6%
( 3
 
4.8%
) 3
 
4.8%
2 1
 
1.6%
- 1
 
1.6%
3 1
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 554
78.9%
ASCII 148
 
21.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34
23.0%
, 19
 
12.8%
P 8
 
5.4%
S 7
 
4.7%
A 7
 
4.7%
B 6
 
4.1%
e 5
 
3.4%
N 5
 
3.4%
F 5
 
3.4%
E 4
 
2.7%
Other values (26) 48
32.4%
Hangul
ValueCountFrequency (%)
아 24
 
4.3%
스 24
 
4.3%
콘 20
 
3.6%
물 20
 
3.6%
소 20
 
3.6%
구 15
 
2.7%
각 14
 
2.5%
품 12
 
2.2%
기 12
 
2.2%
제 11
 
2.0%
Other values (141) 382
69.0%

자동측정장치(TMS)대기
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)19.1%
Missing94
Missing (%)66.7%
Infinite0
Infinite (%)0.0%
Mean3.5531915
Minimum1
Maximum43
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T21:02:27.877916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q33
95-th percentile9
Maximum43
Range42
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.632622
Coefficient of variation (CV)1.8666661
Kurtosis28.547988
Mean3.5531915
Median Absolute Deviation (MAD)1
Skewness5.0641198
Sum167
Variance43.991674
MonotonicityNot monotonic
2023-12-12T21:02:27.998428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
1 18
 
12.8%
2 15
 
10.6%
3 5
 
3.5%
4 3
 
2.1%
9 2
 
1.4%
7 1
 
0.7%
19 1
 
0.7%
43 1
 
0.7%
5 1
 
0.7%
(Missing) 94
66.7%
ValueCountFrequency (%)
1 18
12.8%
2 15
10.6%
3 5
 
3.5%
4 3
 
2.1%
5 1
 
0.7%
7 1
 
0.7%
9 2
 
1.4%
19 1
 
0.7%
43 1
 
0.7%
ValueCountFrequency (%)
43 1
 
0.7%
19 1
 
0.7%
9 2
 
1.4%
7 1
 
0.7%
5 1
 
0.7%
4 3
 
2.1%
3 5
 
3.5%
2 15
10.6%
1 18
12.8%

자동측정장치(TMS)수질
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
128 
1
 
10
2
 
3

Length

Max length4
Median length4
Mean length3.7234043
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 128
90.8%
1 10
 
7.1%
2 3
 
2.1%

Length

2023-12-12T21:02:28.230676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:02:28.380826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 128
90.8%
1 10
 
7.1%
2 3
 
2.1%

Sample

산단업체명소재지대표자전화팩스우편번호대기종별대기등급대기점검횟수수질종별수질등급수질점검횟수휘발성 유기 화합물업종산업분류오염물질발생량(톤_년)폐수배출량폐수처리용량폐수처리방법생산제품자동측정장치(TMS)대기자동측정장치(TMS)수질
0여수금호미쓰이화학㈜여수시 여수산단2로 305 (화치동)대표이사061-688-5095061-688-5099596115특일반21특일반4여기타 기초유기화학물질 제조업201191.02362.03000물리, 화학(종말처리)ANILINE,부생HCL<NA><NA>
1여수금호석유화학㈜여수정밀화학공장여수시 여수산단2로 227 (화치동)대표이사061-688-3942061-685-5806596112특일반33특우수1여그외 기타 분류안된화학제품 제조업2049952.78468.1900금호피앤비1공장 공동방지가황 촉진제<NA><NA>
2여수금호피앤비화학㈜(제1공장)여수시 여수산단2로 218 (화치동)대표이사061-688-3680061-688-3686596111특일반41특우수2여기타 기초유기화학물질 제조업20119766.672835.34139물·화·생(공동방지)페놀,아세톤2<NA>
3여수금호피앤비화학㈜(제2공장)여수시 여수산단2로 46-53 (월하동)대표이사061-688-3683061-688-3686596111특중점52특우수1여기타 기초유기화학물질 제조업20119217.611440.64139금호피앤비1공장 공동방지EPOXY, BPA, MIBK3<NA>
4여수남해화학㈜여수시 여수산단로 1384 (낙포동)대표이사061-688-5752(5753)061-688-5758596181특중점51특일반4여복합비료제조업202022868.3316036.017000물·화·생(자가방류)황산,농질산71
5여수㈜무일화성(월하1공장)여수시 여수산단로 237 (월하동)대표이사061-690-9426061-685-4332596162중점45우수0<NA>합성수지 및 기타 플라스틱물질제조업2030247.25.0540물·화·생(전량재이용)ABS, PP<NA><NA>
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산단업체명소재지대표자전화팩스우편번호대기종별대기등급대기점검횟수수질종별수질등급수질점검횟수휘발성 유기 화합물업종산업분류오염물질발생량(톤_년)폐수배출량폐수처리용량폐수처리방법생산제품자동측정장치(TMS)대기자동측정장치(TMS)수질
131장성고려시멘트㈜장성군 장성읍 영천로 35(단광리 524)대표이사061-390-6404061-390-6430572181특중점55일반1<NA>시멘트 제조업233112448.530.050물·화시멘트2<NA>
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140진도진도군 환경관리센터진도군 군내면 한의길 115진도군수061-540-3369061-540-6657589011특일반4<NA><NA><NA><NA>환경행정(생활폐기물 소각)76213303.84<NA><NA><NA>폐기물소각1<NA>