Overview

Dataset statistics

Number of variables12
Number of observations133
Missing cells1
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.1 KiB
Average record size in memory101.0 B

Variable types

Text6
Numeric4
Categorical2

Dataset

Description전라북도 군산시에 소재한 유해화학물질 취급시설 현황(업체명, 종업원수, 소재지 지번주소, 사업자번호, 대표자, 전화번호, 허가업종, 취급물질명, 연간취급량, 저장탱크시설능력, 보관시설능력, 산단종류)을 나타냅니다.
Author전라북도 군산시
URLhttps://www.data.go.kr/data/15116921/fileData.do

Alerts

종업원수 has 3 (2.3%) zerosZeros
저장탱크시설능력(톤) has 50 (37.6%) zerosZeros
보관시설능력(제곱미터) has 58 (43.6%) zerosZeros

Reproduction

Analysis started2023-12-12 14:04:49.579459
Analysis finished2023-12-12 14:04:52.280727
Duration2.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Text

Distinct98
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T23:04:52.486490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length9.0827068
Min length4

Characters and Unicode

Total characters1208
Distinct characters181
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

Unique69 ?
Unique (%)51.9%

Sample

1st row(주)세아베스틸
2nd rowOCI(주)군산공장
3rd rowOCI(주)군산공장
4th row대상주식회사 군산공장
5th row대상(주)라이신공장
ValueCountFrequency (%)
주식회사 20
 
10.3%
군산공장 10
 
5.2%
군산 8
 
4.1%
2공장 4
 
2.1%
광배산업(주 3
 
1.5%
삼양이노켐(주 3
 
1.5%
군산지점 3
 
1.5%
군산2공장 3
 
1.5%
주)제이아이테크 3
 
1.5%
주)코씰 3
 
1.5%
Other values (103) 134
69.1%
2023-12-12T23:04:52.830841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 80
 
6.6%
( 64
 
5.3%
) 64
 
5.3%
61
 
5.0%
산 48
 
4.0%
㈜ 40
 
3.3%
이 35
 
2.9%
군 34
 
2.8%
공 28
 
2.3%
사 28
 
2.3%
Other values (171) 726
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 952
78.8%
Open Punctuation 64
 
5.3%
Close Punctuation 64
 
5.3%
Space Separator 61
 
5.0%
Other Symbol 40
 
3.3%
Uppercase Letter 17
 
1.4%
Decimal Number 10
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 80
 
8.4%
산 48
 
5.0%
이 35
 
3.7%
군 34
 
3.6%
공 28
 
2.9%
사 28
 
2.9%
회 26
 
2.7%
스 25
 
2.6%
장 25
 
2.6%
식 22
 
2.3%
Other values (158) 601
63.1%
Uppercase Letter
ValueCountFrequency (%)
I 4
23.5%
C 4
23.5%
O 4
23.5%
E 2
11.8%
H 1
 
5.9%
K 1
 
5.9%
S 1
 
5.9%
Decimal Number
ValueCountFrequency (%)
2 8
80.0%
1 2
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 64
100.0%
Close Punctuation
ValueCountFrequency (%)
) 64
100.0%
Space Separator
ValueCountFrequency (%)
61
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 992
82.1%
Common 199
 
16.5%
Latin 17
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 80
 
8.1%
산 48
 
4.8%
㈜ 40
 
4.0%
이 35
 
3.5%
군 34
 
3.4%
공 28
 
2.8%
사 28
 
2.8%
회 26
 
2.6%
스 25
 
2.5%
장 25
 
2.5%
Other values (159) 623
62.8%
Latin
ValueCountFrequency (%)
I 4
23.5%
C 4
23.5%
O 4
23.5%
E 2
11.8%
H 1
 
5.9%
K 1
 
5.9%
S 1
 
5.9%
Common
ValueCountFrequency (%)
( 64
32.2%
) 64
32.2%
61
30.7%
2 8
 
4.0%
1 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 952
78.8%
ASCII 216
 
17.9%
None 40
 
3.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 80
 
8.4%
산 48
 
5.0%
이 35
 
3.7%
군 34
 
3.6%
공 28
 
2.9%
사 28
 
2.9%
회 26
 
2.7%
스 25
 
2.6%
장 25
 
2.6%
식 22
 
2.3%
Other values (158) 601
63.1%
ASCII
ValueCountFrequency (%)
( 64
29.6%
) 64
29.6%
61
28.2%
2 8
 
3.7%
I 4
 
1.9%
C 4
 
1.9%
O 4
 
1.9%
E 2
 
0.9%
1 2
 
0.9%
H 1
 
0.5%
Other values (2) 2
 
0.9%
None
ValueCountFrequency (%)
㈜ 40
100.0%

종업원수
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)45.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean69.842105
Minimum0
Maximum1500
Zeros3
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T23:04:52.984138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median27
Q368
95-th percentile200.8
Maximum1500
Range1500
Interquartile range (IQR)59

Descriptive statistics

Standard deviation164.55044
Coefficient of variation (CV)2.3560349
Kurtosis51.049822
Mean69.842105
Median Absolute Deviation (MAD)22
Skewness6.6217211
Sum9289
Variance27076.846
MonotonicityNot monotonic
2023-12-12T23:04:53.140312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 6
 
4.5%
9 6
 
4.5%
15 5
 
3.8%
25 5
 
3.8%
1 5
 
3.8%
3 5
 
3.8%
2 5
 
3.8%
68 4
 
3.0%
8 4
 
3.0%
13 4
 
3.0%
Other values (51) 84
63.2%
ValueCountFrequency (%)
0 3
2.3%
1 5
3.8%
2 5
3.8%
3 5
3.8%
5 3
2.3%
6 3
2.3%
7 1
 
0.8%
8 4
3.0%
9 6
4.5%
10 1
 
0.8%
ValueCountFrequency (%)
1500 1
0.8%
1015 1
0.8%
426 1
0.8%
285 1
0.8%
270 1
0.8%
250 1
0.8%
202 1
0.8%
200 1
0.8%
190 2
1.5%
167 2
1.5%

소재지 지번주소
Text

Distinct96
Distinct (%)72.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T23:04:53.578996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length22.233083
Min length15

Characters and Unicode

Total characters2957
Distinct characters79
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)49.6%

Sample

1st row전라북도 군산시 외항로 522 (소룡동)
2nd row전라북도 군산시 외항로 82 (소룡동)
3rd row전라북도 군산시 외항로 82 (소룡동)
4th row전라북도 군산시 외항1길 208 (소룡동)
5th row전라북도 군산시 외항4길 57 (소룡동)
ValueCountFrequency (%)
군산시 134
23.1%
전라북도 133
22.9%
외항로 19
 
3.3%
오식도동 16
 
2.8%
외항1길 12
 
2.1%
소룡동 12
 
2.1%
산단동서로 9
 
1.5%
무역로 9
 
1.5%
자유로 8
 
1.4%
공항로 7
 
1.2%
Other values (136) 222
38.2%
2023-12-12T23:04:54.182717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
451
 
15.3%
도 208
 
7.0%
산 171
 
5.8%
북 145
 
4.9%
군 141
 
4.8%
시 134
 
4.5%
전 133
 
4.5%
라 133
 
4.5%
동 114
 
3.9%
( 104
 
3.5%
Other values (69) 1223
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1819
61.5%
Space Separator 451
 
15.3%
Decimal Number 437
 
14.8%
Open Punctuation 104
 
3.5%
Close Punctuation 104
 
3.5%
Dash Punctuation 35
 
1.2%
Other Punctuation 7
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 208
11.4%
산 171
 
9.4%
북 145
 
8.0%
군 141
 
7.8%
시 134
 
7.4%
전 133
 
7.3%
라 133
 
7.3%
동 114
 
6.3%
로 95
 
5.2%
오 54
 
3.0%
Other values (53) 491
27.0%
Decimal Number
ValueCountFrequency (%)
1 92
21.1%
3 72
16.5%
2 58
13.3%
4 46
10.5%
9 42
9.6%
0 35
 
8.0%
5 31
 
7.1%
7 25
 
5.7%
8 18
 
4.1%
6 18
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
451
100.0%
Open Punctuation
ValueCountFrequency (%)
( 104
100.0%
Close Punctuation
ValueCountFrequency (%)
) 104
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1819
61.5%
Common 1138
38.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 208
11.4%
산 171
 
9.4%
북 145
 
8.0%
군 141
 
7.8%
시 134
 
7.4%
전 133
 
7.3%
라 133
 
7.3%
동 114
 
6.3%
로 95
 
5.2%
오 54
 
3.0%
Other values (53) 491
27.0%
Common
ValueCountFrequency (%)
451
39.6%
( 104
 
9.1%
) 104
 
9.1%
1 92
 
8.1%
3 72
 
6.3%
2 58
 
5.1%
4 46
 
4.0%
9 42
 
3.7%
0 35
 
3.1%
- 35
 
3.1%
Other values (6) 99
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1819
61.5%
ASCII 1138
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
451
39.6%
( 104
 
9.1%
) 104
 
9.1%
1 92
 
8.1%
3 72
 
6.3%
2 58
 
5.1%
4 46
 
4.0%
9 42
 
3.7%
0 35
 
3.1%
- 35
 
3.1%
Other values (6) 99
 
8.7%
Hangul
ValueCountFrequency (%)
도 208
11.4%
산 171
 
9.4%
북 145
 
8.0%
군 141
 
7.8%
시 134
 
7.4%
전 133
 
7.3%
라 133
 
7.3%
동 114
 
6.3%
로 95
 
5.2%
오 54
 
3.0%
Other values (53) 491
27.0%

사업자번호
Text

Distinct93
Distinct (%)69.9%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T23:04:54.527017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1596
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

Unique64 ?
Unique (%)48.1%

Sample

1st row794-81-02456
2nd row506-81-00069
3rd row506-81-00069
4th row109-81-14886
5th row109-81-14886
ValueCountFrequency (%)
401-81-53863 5
 
3.8%
401-81-01273 4
 
3.0%
109-81-14886 3
 
2.3%
401-81-14384 3
 
2.3%
126-86-19106 3
 
2.3%
506-81-00069 3
 
2.3%
401-81-38237 3
 
2.3%
401-81-03397 3
 
2.3%
836-86-00174 2
 
1.5%
438-81-01329 2
 
1.5%
Other values (83) 102
76.7%
2023-12-12T23:04:55.039506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 282
17.7%
- 266
16.7%
8 202
12.7%
0 200
12.5%
4 143
9.0%
3 113
7.1%
6 99
 
6.2%
7 79
 
4.9%
2 77
 
4.8%
5 73
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1330
83.3%
Dash Punctuation 266
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 282
21.2%
8 202
15.2%
0 200
15.0%
4 143
10.8%
3 113
8.5%
6 99
 
7.4%
7 79
 
5.9%
2 77
 
5.8%
5 73
 
5.5%
9 62
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1596
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 282
17.7%
- 266
16.7%
8 202
12.7%
0 200
12.5%
4 143
9.0%
3 113
7.1%
6 99
 
6.2%
7 79
 
4.9%
2 77
 
4.8%
5 73
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 282
17.7%
- 266
16.7%
8 202
12.7%
0 200
12.5%
4 143
9.0%
3 113
7.1%
6 99
 
6.2%
7 79
 
4.9%
2 77
 
4.8%
5 73
 
4.6%

대표자
Text

Distinct92
Distinct (%)69.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T23:04:55.376169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length4.0300752
Min length2

Characters and Unicode

Total characters536
Distinct characters127
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

Unique63 ?
Unique (%)47.4%

Sample

1st row김철희+신상호
2nd row백우석+이우현+김택중
3rd row백우석+이우현+김택중
4th row임정배
5th row임정배
ValueCountFrequency (%)
함석헌 5
 
3.7%
김종완 4
 
3.0%
김응상+경상호 4
 
3.0%
임정배 3
 
2.2%
조태수 3
 
2.2%
김영률+권정현 3
 
2.2%
강호성 3
 
2.2%
김말순 3
 
2.2%
김대영 2
 
1.5%
이강명 2
 
1.5%
Other values (83) 103
76.3%
2023-12-12T23:04:55.817048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 36
 
6.7%
이 30
 
5.6%
+ 29
 
5.4%
상 19
 
3.5%
호 16
 
3.0%
영 16
 
3.0%
석 13
 
2.4%
현 13
 
2.4%
정 12
 
2.2%
최 12
 
2.2%
Other values (117) 340
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 505
94.2%
Math Symbol 29
 
5.4%
Space Separator 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 36
 
7.1%
이 30
 
5.9%
상 19
 
3.8%
호 16
 
3.2%
영 16
 
3.2%
석 13
 
2.6%
현 13
 
2.6%
정 12
 
2.4%
최 12
 
2.4%
종 11
 
2.2%
Other values (115) 327
64.8%
Math Symbol
ValueCountFrequency (%)
+ 29
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 505
94.2%
Common 31
 
5.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 36
 
7.1%
이 30
 
5.9%
상 19
 
3.8%
호 16
 
3.2%
영 16
 
3.2%
석 13
 
2.6%
현 13
 
2.6%
정 12
 
2.4%
최 12
 
2.4%
종 11
 
2.2%
Other values (115) 327
64.8%
Common
ValueCountFrequency (%)
+ 29
93.5%
2
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 505
94.2%
ASCII 31
 
5.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 36
 
7.1%
이 30
 
5.9%
상 19
 
3.8%
호 16
 
3.2%
영 16
 
3.2%
석 13
 
2.6%
현 13
 
2.6%
정 12
 
2.4%
최 12
 
2.4%
종 11
 
2.2%
Other values (115) 327
64.8%
ASCII
ValueCountFrequency (%)
+ 29
93.5%
2
 
6.5%

전화번호
Text

Distinct98
Distinct (%)73.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T23:04:56.089740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.030075
Min length12

Characters and Unicode

Total characters1600
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

Unique71 ?
Unique (%)53.4%

Sample

1st row063-460-8343
2nd row063-460-6122
3rd row063-460-6122
4th row063-469-2261
5th row063-912-4572
ValueCountFrequency (%)
063-462-2455 4
 
3.0%
063-467-9751 3
 
2.3%
063-462-8460 3
 
2.3%
063-468-6363 3
 
2.3%
063-465-1868 3
 
2.3%
063-731-0088 3
 
2.3%
063-461-2236 3
 
2.3%
063-471-7982 2
 
1.5%
063-466-0029 2
 
1.5%
063-464-3541 2
 
1.5%
Other values (88) 105
78.9%
2023-12-12T23:04:56.500109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 266
16.6%
6 264
16.5%
0 233
14.6%
3 198
12.4%
4 188
11.8%
1 99
 
6.2%
7 91
 
5.7%
2 80
 
5.0%
5 76
 
4.8%
8 69
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1334
83.4%
Dash Punctuation 266
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 264
19.8%
0 233
17.5%
3 198
14.8%
4 188
14.1%
1 99
 
7.4%
7 91
 
6.8%
2 80
 
6.0%
5 76
 
5.7%
8 69
 
5.2%
9 36
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1600
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 266
16.6%
6 264
16.5%
0 233
14.6%
3 198
12.4%
4 188
11.8%
1 99
 
6.2%
7 91
 
5.7%
2 80
 
5.0%
5 76
 
4.8%
8 69
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1600
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 266
16.6%
6 264
16.5%
0 233
14.6%
3 198
12.4%
4 188
11.8%
1 99
 
6.2%
7 91
 
5.7%
2 80
 
5.0%
5 76
 
4.8%
8 69
 
4.3%

허가업종
Categorical

Distinct6
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
사용
67 
제조
28 
운반
20 
판매
13 
보관저장
 
3

Length

Max length4
Median length2
Mean length2.0601504
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row사용
2nd row제조
3rd row사용
4th row사용
5th row사용

Common Values

ValueCountFrequency (%)
사용 67
50.4%
제조 28
21.1%
운반 20
 
15.0%
판매 13
 
9.8%
보관저장 3
 
2.3%
준알선 2
 
1.5%

Length

2023-12-12T23:04:56.675534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:04:56.794202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사용 67
50.4%
제조 28
21.1%
운반 20
 
15.0%
판매 13
 
9.8%
보관저장 3
 
2.3%
준알선 2
 
1.5%

취급물질명
Text

Distinct119
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T23:04:56.984628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length551
Median length93
Mean length49.413534
Min length2

Characters and Unicode

Total characters6572
Distinct characters241
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique112 ?
Unique (%)84.2%

Sample

1st row염산
2nd row염산+수산화나트륨+3(또는4)톨루엔-1+2-디아민+톨루엔디이소시아네이트+톨루엔-2+4-디이소시아네이트+테트라클로로실리콘+트리클로로실란
3rd row황산+질산+포름알데하이드+인+2+4-디니트로톨루엔+과산화수소+플루오르화수소+산화니켈+하이드로퀴논+무수크롬산+황산니켈 6수화물+수산화칼륨+청화은칼륨+오황화인+청화가리+염소+일산화탄소+포스겐+염화수소+수산화나트륨+플루오르화수소(폐불산)+플루오르화수소+질산(폐혼산)+트리클로로실란+붕산+니켈 설파민산(술팜산 니켈)
4th row수산화나트륨+염산+황산+메탄올+벤잘콘이움클로라이드
5th row수산화나트륨+염산+황산
ValueCountFrequency (%)
염산 6
 
2.7%
염산+수산화나트륨 3
 
1.3%
수산화나트륨+염산 3
 
1.3%
톨루엔 3
 
1.3%
황산+수산화나트륨 3
 
1.3%
트리플루오로메틸)술포닐]메탄술폰아미드 2
 
0.9%
디이소시아네이트(cas 2
 
0.9%
번호 2
 
0.9%
4)톨루엔-1+2-디아민+과산화수소 2
 
0.9%
황색 2
 
0.9%
Other values (192) 196
87.5%
2023-12-12T23:04:57.446061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 803
 
12.2%
산 428
 
6.5%
- 261
 
4.0%
화 241
 
3.7%
트 216
 
3.3%
수 190
 
2.9%
로 155
 
2.4%
아 145
 
2.2%
륨 141
 
2.1%
틸 139
 
2.1%
Other values (231) 3853
58.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4843
73.7%
Math Symbol 803
 
12.2%
Decimal Number 299
 
4.5%
Dash Punctuation 261
 
4.0%
Space Separator 93
 
1.4%
Close Punctuation 86
 
1.3%
Open Punctuation 84
 
1.3%
Uppercase Letter 46
 
0.7%
Lowercase Letter 39
 
0.6%
Other Punctuation 11
 
0.2%
Other values (2) 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 428
 
8.8%
화 241
 
5.0%
트 216
 
4.5%
수 190
 
3.9%
로 155
 
3.2%
아 145
 
3.0%
륨 141
 
2.9%
틸 139
 
2.9%
이 135
 
2.8%
메 130
 
2.7%
Other values (177) 2923
60.4%
Lowercase Letter
ValueCountFrequency (%)
e 6
15.4%
y 4
10.3%
t 4
10.3%
d 3
 
7.7%
r 3
 
7.7%
l 3
 
7.7%
n 2
 
5.1%
η 2
 
5.1%
h 2
 
5.1%
x 1
 
2.6%
Other values (9) 9
23.1%
Uppercase Letter
ValueCountFrequency (%)
N 19
41.3%
A 10
21.7%
M 2
 
4.3%
O 2
 
4.3%
H 2
 
4.3%
I 2
 
4.3%
S 2
 
4.3%
C 2
 
4.3%
P 1
 
2.2%
Z 1
 
2.2%
Other values (3) 3
 
6.5%
Decimal Number
ValueCountFrequency (%)
2 93
31.1%
1 71
23.7%
4 70
23.4%
3 32
 
10.7%
6 16
 
5.4%
5 12
 
4.0%
8 2
 
0.7%
7 1
 
0.3%
9 1
 
0.3%
0 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
＇ 8
72.7%
. 2
 
18.2%
% 1
 
9.1%
Close Punctuation
ValueCountFrequency (%)
) 77
89.5%
] 9
 
10.5%
Open Punctuation
ValueCountFrequency (%)
( 75
89.3%
[ 9
 
10.7%
Math Symbol
ValueCountFrequency (%)
+ 803
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 261
100.0%
Space Separator
ValueCountFrequency (%)
93
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 5
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4843
73.7%
Common 1644
 
25.0%
Latin 82
 
1.2%
Greek 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 428
 
8.8%
화 241
 
5.0%
트 216
 
4.5%
수 190
 
3.9%
로 155
 
3.2%
아 145
 
3.0%
륨 141
 
2.9%
틸 139
 
2.9%
이 135
 
2.8%
메 130
 
2.7%
Other values (177) 2923
60.4%
Latin
ValueCountFrequency (%)
N 19
23.2%
A 10
 
12.2%
e 6
 
7.3%
y 4
 
4.9%
t 4
 
4.9%
d 3
 
3.7%
r 3
 
3.7%
l 3
 
3.7%
n 2
 
2.4%
M 2
 
2.4%
Other values (20) 26
31.7%
Common
ValueCountFrequency (%)
+ 803
48.8%
- 261
 
15.9%
93
 
5.7%
2 93
 
5.7%
) 77
 
4.7%
( 75
 
4.6%
1 71
 
4.3%
4 70
 
4.3%
3 32
 
1.9%
6 16
 
1.0%
Other values (12) 53
 
3.2%
Greek
ValueCountFrequency (%)
η 2
66.7%
κ 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4843
73.7%
ASCII 1716
 
26.1%
None 11
 
0.2%
Punctuation 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 803
46.8%
- 261
 
15.2%
93
 
5.4%
2 93
 
5.4%
) 77
 
4.5%
( 75
 
4.4%
1 71
 
4.1%
4 70
 
4.1%
3 32
 
1.9%
N 19
 
1.1%
Other values (40) 122
 
7.1%
Hangul
ValueCountFrequency (%)
산 428
 
8.8%
화 241
 
5.0%
트 216
 
4.5%
수 190
 
3.9%
로 155
 
3.2%
아 145
 
3.0%
륨 141
 
2.9%
틸 139
 
2.9%
이 135
 
2.8%
메 130
 
2.7%
Other values (177) 2923
60.4%
None
ValueCountFrequency (%)
＇ 8
72.7%
η 2
 
18.2%
κ 1
 
9.1%
Punctuation
ValueCountFrequency (%)
‘ 2
100.0%

연간취급량(톤)
Real number (ℝ)

Distinct128
Distinct (%)97.0%
Missing1
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean41615.784
Minimum0.015
Maximum750722
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T23:04:57.613378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.015
5-th percentile33.75
Q1550.125
median3209.35
Q328671.75
95-th percentile200940
Maximum750722
Range750721.98
Interquartile range (IQR)28121.625

Descriptive statistics

Standard deviation101364.1
Coefficient of variation (CV)2.4357128
Kurtosis24.722074
Mean41615.784
Median Absolute Deviation (MAD)3124.35
Skewness4.4994803
Sum5493283.5
Variance1.027468 × 1010
MonotonicityNot monotonic
2023-12-12T23:04:57.784654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1320.0 3
 
2.3%
960.0 3
 
2.3%
31.0 1
 
0.8%
1284.0 1
 
0.8%
60000.0 1
 
0.8%
337.7 1
 
0.8%
90.18 1
 
0.8%
103200.0 1
 
0.8%
36588.0 1
 
0.8%
185.0 1
 
0.8%
Other values (118) 118
88.7%
ValueCountFrequency (%)
0.015 1
0.8%
0.35 1
0.8%
0.5 1
0.8%
14.9 1
0.8%
19.0 1
0.8%
20.4 1
0.8%
31.0 1
0.8%
36.0 1
0.8%
48.0 1
0.8%
53.3 1
0.8%
ValueCountFrequency (%)
750722.0 1
0.8%
590400.0 1
0.8%
386123.0 1
0.8%
307027.2 1
0.8%
225336.0 1
0.8%
215845.1 1
0.8%
208200.0 1
0.8%
195000.0 1
0.8%
180000.0 1
0.8%
158000.0 1
0.8%

저장탱크시설능력(톤)
Real number (ℝ)

ZEROS 

Distinct68
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean697.8985
Minimum0
Maximum12842
Zeros50
Zeros (%)37.6%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T23:04:57.929490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median40
Q3130
95-th percentile3871.02
Maximum12842
Range12842
Interquartile range (IQR)130

Descriptive statistics

Standard deviation2424.6597
Coefficient of variation (CV)3.4742298
Kurtosis18.227646
Mean697.8985
Median Absolute Deviation (MAD)40
Skewness4.3476013
Sum92820.5
Variance5878974.8
MonotonicityNot monotonic
2023-12-12T23:04:58.143635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 50
37.6%
60.0 5
 
3.8%
50.0 4
 
3.0%
40.0 3
 
2.3%
18.0 2
 
1.5%
100.0 2
 
1.5%
85.0 2
 
1.5%
10.0 2
 
1.5%
20.0 2
 
1.5%
96.0 2
 
1.5%
Other values (58) 59
44.4%
ValueCountFrequency (%)
0.0 50
37.6%
2.2 1
 
0.8%
5.0 1
 
0.8%
10.0 2
 
1.5%
15.0 1
 
0.8%
17.0 1
 
0.8%
18.0 2
 
1.5%
20.0 2
 
1.5%
23.0 1
 
0.8%
27.0 1
 
0.8%
ValueCountFrequency (%)
12842.0 1
0.8%
12677.8 1
0.8%
12566.0 1
0.8%
11900.0 1
0.8%
11540.0 1
0.8%
6116.0 1
0.8%
3945.0 1
0.8%
3821.7 1
0.8%
1731.7 1
0.8%
1592.0 1
0.8%

보관시설능력(제곱미터)
Real number (ℝ)

ZEROS 

Distinct71
Distinct (%)53.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean385.92331
Minimum0
Maximum16640
Zeros58
Zeros (%)43.6%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2023-12-12T23:04:58.319927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17.9
Q3195
95-th percentile1420.4
Maximum16640
Range16640
Interquartile range (IQR)195

Descriptive statistics

Standard deviation1598.277
Coefficient of variation (CV)4.1414369
Kurtosis82.867614
Mean385.92331
Median Absolute Deviation (MAD)17.9
Skewness8.5011876
Sum51327.8
Variance2554489.5
MonotonicityNot monotonic
2023-12-12T23:04:58.782498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 58
43.6%
124.5 2
 
1.5%
40.0 2
 
1.5%
706.4 2
 
1.5%
116.0 2
 
1.5%
50.0 2
 
1.5%
84.7 1
 
0.8%
45.6 1
 
0.8%
703.0 1
 
0.8%
2473.0 1
 
0.8%
Other values (61) 61
45.9%
ValueCountFrequency (%)
0.0 58
43.6%
2.3 1
 
0.8%
4.6 1
 
0.8%
6.6 1
 
0.8%
10.4 1
 
0.8%
10.5 1
 
0.8%
12.0 1
 
0.8%
15.2 1
 
0.8%
16.3 1
 
0.8%
17.9 1
 
0.8%
ValueCountFrequency (%)
16640.0 1
0.8%
5480.0 1
0.8%
3598.6 1
0.8%
3288.3 1
0.8%
3158.0 1
0.8%
2473.0 1
0.8%
1613.0 1
0.8%
1292.0 1
0.8%
987.0 1
0.8%
706.4 2
1.5%

산단종류
Categorical

Distinct8
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
군산2국가산단
63 
군산지방산단
25 
산단아님
22 
군산1국가산단
17 
새만금산업단지
 
3
Other values (3)
 
3

Length

Max length7
Median length7
Mean length6.2330827
Min length2

Unique

Unique3 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
군산2국가산단 63
47.4%
군산지방산단 25
 
18.8%
산단아님 22
 
16.5%
군산1국가산단 17
 
12.8%
새만금산업단지 3
 
2.3%
350 1
 
0.8%
서군산산단 1
 
0.8%
항만 1
 
0.8%

Length

2023-12-12T23:04:58.970490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:04:59.118977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군산2국가산단 63
47.4%
군산지방산단 25
 
18.8%
산단아님 22
 
16.5%
군산1국가산단 17
 
12.8%
새만금산업단지 3
 
2.3%
350 1
 
0.8%
서군산산단 1
 
0.8%
항만 1
 
0.8%

Interactions

2023-12-12T23:04:51.743926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:50.746841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.104715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.438877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.825574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:50.837534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.198321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.513506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.899317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:50.923540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.282893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.590616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.974252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.008275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.364498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:04:51.667597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:04:59.245270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명종업원수소재지 지번주소사업자번호대표자전화번호허가업종연간취급량(톤)저장탱크시설능력(톤)보관시설능력(제곱미터)산단종류
업체명1.0000.5431.0001.0001.0001.0000.0000.0000.0000.0000.969
종업원수0.5431.0000.6500.0000.6960.5430.0000.7030.4740.0000.128
소재지 지번주소1.0000.6501.0001.0001.0001.0000.0000.0000.0000.0000.978
사업자번호1.0000.0001.0001.0001.0001.0000.0000.0000.0000.0000.973
대표자1.0000.6961.0001.0001.0001.0000.0000.4230.0000.0000.971
전화번호1.0000.5431.0001.0001.0001.0000.2120.8800.8710.7110.969
허가업종0.0000.0000.0000.0000.0000.2121.0000.4150.0000.5430.550
연간취급량(톤)0.0000.7030.0000.0000.4230.8800.4151.0000.7570.6720.717
저장탱크시설능력(톤)0.0000.4740.0000.0000.0000.8710.0000.7571.0000.4650.338
보관시설능력(제곱미터)0.0000.0000.0000.0000.0000.7110.5430.6720.4651.0000.663
산단종류0.9690.1280.9780.9730.9710.9690.5500.7170.3380.6631.000
2023-12-12T23:04:59.410883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가업종산단종류
허가업종1.0000.341
산단종류0.3411.000
2023-12-12T23:04:59.531229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수연간취급량(톤)저장탱크시설능력(톤)보관시설능력(제곱미터)허가업종산단종류
종업원수1.0000.1810.4650.1850.0000.075
연간취급량(톤)0.1811.0000.415-0.0620.2420.487
저장탱크시설능력(톤)0.4650.4151.0000.1540.0000.187
보관시설능력(제곱미터)0.185-0.0620.1541.0000.4040.481
허가업종0.0000.2420.0000.4041.0000.341
산단종류0.0750.4870.1870.4810.3411.000

Missing values

2023-12-12T23:04:52.077799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:04:52.226779image/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

업체명종업원수소재지 지번주소사업자번호대표자전화번호허가업종취급물질명연간취급량(톤)저장탱크시설능력(톤)보관시설능력(제곱미터)산단종류
0(주)세아베스틸1500전라북도 군산시 외항로 522 (소룡동)794-81-02456김철희+신상호063-460-8343사용염산31.018.06.6군산지방산단
1OCI(주)군산공장426전라북도 군산시 외항로 82 (소룡동)506-81-00069백우석+이우현+김택중063-460-6122제조염산+수산화나트륨+3(또는4)톨루엔-1+2-디아민+톨루엔디이소시아네이트+톨루엔-2+4-디이소시아네이트+테트라클로로실리콘+트리클로로실란590400.012842.01613.0군산지방산단
2OCI(주)군산공장1015전라북도 군산시 외항로 82 (소룡동)506-81-00069백우석+이우현+김택중063-460-6122사용황산+질산+포름알데하이드+인+2+4-디니트로톨루엔+과산화수소+플루오르화수소+산화니켈+하이드로퀴논+무수크롬산+황산니켈 6수화물+수산화칼륨+청화은칼륨+오황화인+청화가리+염소+일산화탄소+포스겐+염화수소+수산화나트륨+플루오르화수소(폐불산)+플루오르화수소+질산(폐혼산)+트리클로로실란+붕산+니켈 설파민산(술팜산 니켈)215845.11554.3987.0군산지방산단
3대상주식회사 군산공장285전라북도 군산시 외항1길 208 (소룡동)109-81-14886임정배063-469-2261사용수산화나트륨+염산+황산+메탄올+벤잘콘이움클로라이드57307.9632.065.0군산지방산단
4대상(주)라이신공장96전라북도 군산시 외항4길 57 (소룡동)109-81-14886임정배063-912-4572사용수산화나트륨+염산+황산112394.0506.60.0군산지방산단
5한국바스프㈜ 군산공장61전라북도 군산시 외항 4길 57(소룡동)417-81-04858임윤순063-469-2486사용염산+수산화나트륨5000.0130.00.0군산지방산단
6에스지씨에너지㈜ 군산사업부문131전라북도 군산시 임해로 333(소룡동)147-85-01611박준영063-460-7240사용염산+수산화나트륨+암모늄수산화물+황산+암모니아4419.6380.30.0군산지방산단
7(주)에스에이치에너지화학120전라북도 군산시 외항7길 20(소룡동)401-81-09407정케빈규봉063-469-1561사용수산화나트륨+염산+칼륨+삼염화인+과산화수소+메틸에틸케톤+과산화벤조일+4+4-디이소시안산 디페닐메탄+(Z)-2-부테인이산1+1-(디부틸스타닐렌)4+4-(디옥타데실)+붕산+스티렌101452.16116.0327.1군산지방산단
8(주)유니드비티플러스167전라북도 군산시 외항1길 56(소룡동)231-85-04776한상준063-460-5307제조포름알데히드45000.0900.00.0군산지방산단
9(주)유니드비티플러스167전라북도 군산시 외항1길 56(소룡동)231-85-04776한상준063-460-5307사용메탄올+수산화나트륨+염산+개미산+4+4＇-디이소시안산디페닐메탄+수산화칼륨+황산21456.8625.7159.2군산지방산단
업체명종업원수소재지 지번주소사업자번호대표자전화번호허가업종취급물질명연간취급량(톤)저장탱크시설능력(톤)보관시설능력(제곱미터)산단종류
123(주)제이아이테크 2공장15전라북도 군산시 무역로 30(오식도동)401-81-53863함석헌063-731-0088판매옥시염화인+테트라클로로실리콘+O-크실렌+M-크실렌+디클로로실란91.50.0222.0군산2국가산단
124(주)제이아이테크 2공장15전라북도 군산시 무역로 30(오식도동)401-81-53863함석헌063-731-0088사용디클로로실란+트리클로로실란+염산+질산+수산화나트륨14.90.0148.0군산2국가산단
125군산컨테이너터미널㈜19전라북도 군산시 서해로 400(오식도동)401-81-26032신길섭063-464-7043보관저장톨루엔디이소시아네이트+톨루엔디이소시아네이트(유사)+1+4-디클로로벤젠+납+비스페놀-A+클로로아세트산+크실렌+m-크레졸+1+2-다이클로로벤젠386123.00.03598.6항만
126유한회사 아주28전라북도 군산시 중가도길 57(오식도동)194-81-00717이미숙063-463-8887제조2+3+5+6-테트라플루오로벤질 트랜스-2-(2+2-디클로로비닐)-3+3-디메틸사이클로프로판카르복실레이트0.350.010.4군산2국가산단
127주식회사 비에스엠신소재(군산공장)28전라북도 군산시 산단남북로 153-20(오식도동)801-85-01904이종길063-464-5495사용황산+수산화나트륨+염산+붕산+염화니켈+술팜산니켈+질산+칼륨구리시안화물+청화가리90.00.096.0군산2국가산단
128원 화물0전라북도 군산시 공항로 157(산북동)401-20-69025고종철063-461-2236운반톨루엔 디이소시아네이트(CAS 번호 584-84-9)+톨루엔 디이소시아네이트(CAS 번호 26471-62-5)+과산화수소+3(또는4)톨루엔-1+2-디아민1480.00.00.0산단아님
129㈜금강로지스틱스9전라북도 군산시 자유무역로 83(오식도동)401-81-56123전준구063-464-8245운반수산화칼륨+수산화나트륨+톨루엔디이소시아네이트+인8580.00.00.0군산2국가산단
130주식회사 세정로지스2전라북도 군산시 신평1길 11-5, 2층401-81-43856최춘섭+최신영063-467-4066운반염산10000.00.00.0산단아님
131(주)한국화이바 군산공장5전라북도 군산시 외항로 931 (주)한국화이바 군산공장450-85-01803이진광055-960-3225사용스티렌513.92.20.0산단아님
132주식회사 천마글로벌6전라북도 군산시 공항로 579 (개사동 1140)631-86-00093전현배063-465-1533운반4+4＇-(1-메틸에틸리덴)비스페놀+4+4＇-(1-메틸에틸리덴)비스[2+6-디브로모페놀]+3(또는4)톨루엔-1.2-디아민+톨루엔 디이소시아네이트+과산화수소18000.00.00.0산단아님