Overview

Dataset statistics

Number of variables12
Number of observations340
Missing cells181
Missing cells (%)4.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.3 KiB
Average record size in memory100.4 B

Variable types

Text6
Numeric4
Categorical2

Dataset

Description울산광역시 동구 제조업체 현황으로써 제조업 회사명, 대표자, 소재지, 전화번호, FAX, 업종, 종업원수 등이 포함되어있습니다.
Author울산광역시 동구
URLhttps://www.data.go.kr/data/15035047/fileData.do

Alerts

관리기관명 has constant value ""Constant
전화번호 has constant value ""Constant
종업원 합계 is highly overall correlated with 남자종업원 and 2 other fieldsHigh correlation
남자종업원 is highly overall correlated with 종업원 합계 and 2 other fieldsHigh correlation
여자종업원 is highly overall correlated with 종업원 합계 and 2 other fieldsHigh correlation
외국인종업원 is highly overall correlated with 종업원 합계 and 2 other fieldsHigh correlation
업체전화번호 has 42 (12.4%) missing valuesMissing
업체팩스번호 has 139 (40.9%) missing valuesMissing
남자종업원 has 63 (18.5%) zerosZeros
여자종업원 has 67 (19.7%) zerosZeros
외국인종업원 has 207 (60.9%) zerosZeros

Reproduction

Analysis started2024-04-06 08:21:31.426197
Analysis finished2024-04-06 08:21:37.024424
Duration5.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회사명
Text

Distinct338
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:21:37.468413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length5.3205882
Min length2

Characters and Unicode

Total characters1809
Distinct characters302
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)98.8%

Sample

1st row(주)세강
2nd row(주)건승이엔지
3rd row화신산업
4th row현대애드월드
5th row소망스케치
ValueCountFrequency (%)
한솥도시락 2
 
0.6%
주식회사 2
 
0.6%
성원공사 2
 
0.6%
㈜익성산업 1
 
0.3%
김예숙한복 1
 
0.3%
한솥도시락꽃바위점 1
 
0.3%
현대그린푸드㈜ 1
 
0.3%
울산수산업협동조합냉동공장 1
 
0.3%
남목얼음 1
 
0.3%
동양버티칼 1
 
0.3%
Other values (333) 333
96.2%
2024-04-06T17:21:38.237801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
㈜ 66
 
3.6%
업 64
 
3.5%
기 49
 
2.7%
이 46
 
2.5%
대 41
 
2.3%
주 41
 
2.3%
산 40
 
2.2%
) 35
 
1.9%
( 35
 
1.9%
엔 33
 
1.8%
Other values (292) 1359
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1610
89.0%
Other Symbol 66
 
3.6%
Uppercase Letter 50
 
2.8%
Close Punctuation 35
 
1.9%
Open Punctuation 35
 
1.9%
Space Separator 6
 
0.3%
Decimal Number 6
 
0.3%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 64
 
4.0%
기 49
 
3.0%
이 46
 
2.9%
대 41
 
2.5%
주 41
 
2.5%
산 40
 
2.5%
엔 33
 
2.0%
지 29
 
1.8%
떡 27
 
1.7%
원 27
 
1.7%
Other values (270) 1213
75.3%
Uppercase Letter
ValueCountFrequency (%)
N 11
22.0%
E 11
22.0%
G 10
20.0%
C 4
 
8.0%
D 2
 
4.0%
I 2
 
4.0%
M 2
 
4.0%
K 2
 
4.0%
O 2
 
4.0%
H 1
 
2.0%
Other values (3) 3
 
6.0%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
0 1
 
16.7%
5 1
 
16.7%
3 1
 
16.7%
Other Symbol
ValueCountFrequency (%)
㈜ 66
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1676
92.6%
Common 82
 
4.5%
Latin 51
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
㈜ 66
 
3.9%
업 64
 
3.8%
기 49
 
2.9%
이 46
 
2.7%
대 41
 
2.4%
주 41
 
2.4%
산 40
 
2.4%
엔 33
 
2.0%
지 29
 
1.7%
떡 27
 
1.6%
Other values (271) 1240
74.0%
Latin
ValueCountFrequency (%)
N 11
21.6%
E 11
21.6%
G 10
19.6%
C 4
 
7.8%
D 2
 
3.9%
I 2
 
3.9%
M 2
 
3.9%
K 2
 
3.9%
O 2
 
3.9%
H 1
 
2.0%
Other values (4) 4
 
7.8%
Common
ValueCountFrequency (%)
) 35
42.7%
( 35
42.7%
6
 
7.3%
1 3
 
3.7%
0 1
 
1.2%
5 1
 
1.2%
3 1
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1610
89.0%
ASCII 133
 
7.4%
None 66
 
3.6%

Most frequent character per block

None
ValueCountFrequency (%)
㈜ 66
100.0%
Hangul
ValueCountFrequency (%)
업 64
 
4.0%
기 49
 
3.0%
이 46
 
2.9%
대 41
 
2.5%
주 41
 
2.5%
산 40
 
2.5%
엔 33
 
2.0%
지 29
 
1.8%
떡 27
 
1.7%
원 27
 
1.7%
Other values (270) 1213
75.3%
ASCII
ValueCountFrequency (%)
) 35
26.3%
( 35
26.3%
N 11
 
8.3%
E 11
 
8.3%
G 10
 
7.5%
6
 
4.5%
C 4
 
3.0%
1 3
 
2.3%
D 2
 
1.5%
I 2
 
1.5%
Other values (11) 14
 
10.5%

대표자
Text

Distinct335
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:21:39.028371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.05
Min length2

Characters and Unicode

Total characters1037
Distinct characters177
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

Unique330 ?
Unique (%)97.1%

Sample

1st row이경신
2nd row이흥철
3rd row김철웅
4th row김병철
5th row이영식
ValueCountFrequency (%)
김익수 2
 
0.6%
조해현 2
 
0.6%
김지연 2
 
0.6%
이현덕 2
 
0.6%
박정희 2
 
0.6%
조용복 1
 
0.3%
권정환 1
 
0.3%
김금태 1
 
0.3%
이명순 1
 
0.3%
현지아 1
 
0.3%
Other values (325) 325
95.6%
2024-04-06T17:21:39.949779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 77
 
7.4%
이 49
 
4.7%
박 31
 
3.0%
정 28
 
2.7%
영 27
 
2.6%
재 21
 
2.0%
최 19
 
1.8%
진 18
 
1.7%
조 17
 
1.6%
호 16
 
1.5%
Other values (167) 734
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1036
99.9%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 77
 
7.4%
이 49
 
4.7%
박 31
 
3.0%
정 28
 
2.7%
영 27
 
2.6%
재 21
 
2.0%
최 19
 
1.8%
진 18
 
1.7%
조 17
 
1.6%
호 16
 
1.5%
Other values (166) 733
70.8%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1036
99.9%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 77
 
7.4%
이 49
 
4.7%
박 31
 
3.0%
정 28
 
2.7%
영 27
 
2.6%
재 21
 
2.0%
최 19
 
1.8%
진 18
 
1.7%
조 17
 
1.6%
호 16
 
1.5%
Other values (166) 733
70.8%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1036
99.9%
ASCII 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 77
 
7.4%
이 49
 
4.7%
박 31
 
3.0%
정 28
 
2.7%
영 27
 
2.6%
재 21
 
2.0%
최 19
 
1.8%
진 18
 
1.7%
조 17
 
1.6%
호 16
 
1.5%
Other values (166) 733
70.8%
ASCII
ValueCountFrequency (%)
, 1
100.0%

소재지
Text

Distinct170
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:21:40.903339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length14.826471
Min length10

Characters and Unicode

Total characters5041
Distinct characters69
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

Unique157 ?
Unique (%)46.2%

Sample

1st row방어진순환도로 100(방어동)
2nd row방어진순환도로 100(방어동)
3rd row진성12길 72(전하동)
4th row바드래길 12-5(전하동)
5th row바드래길 31(전하동)
ValueCountFrequency (%)
방어진순환도로 175
21.1%
전하동 106
 
12.8%
1000 102
 
12.3%
100(방어동 41
 
4.9%
방어동 17
 
2.1%
진성14길 15
 
1.8%
화정동 12
 
1.4%
남목17길 10
 
1.2%
서부동 10
 
1.2%
77(전하동 9
 
1.1%
Other values (232) 332
40.0%
2024-04-06T17:21:42.212202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
 
9.7%
0 451
 
8.9%
동 372
 
7.4%
) 339
 
6.7%
( 339
 
6.7%
1 266
 
5.3%
어 263
 
5.2%
방 263
 
5.2%
로 218
 
4.3%
진 218
 
4.3%
Other values (59) 1823
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2754
54.6%
Decimal Number 1110
22.0%
Space Separator 489
 
9.7%
Close Punctuation 339
 
6.7%
Open Punctuation 339
 
6.7%
Dash Punctuation 10
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 372
13.5%
어 263
9.5%
방 263
9.5%
로 218
 
7.9%
진 218
 
7.9%
도 176
 
6.4%
순 176
 
6.4%
환 175
 
6.4%
전 159
 
5.8%
하 159
 
5.8%
Other values (45) 575
20.9%
Decimal Number
ValueCountFrequency (%)
0 451
40.6%
1 266
24.0%
7 72
 
6.5%
3 62
 
5.6%
4 54
 
4.9%
2 52
 
4.7%
5 48
 
4.3%
6 47
 
4.2%
9 29
 
2.6%
8 29
 
2.6%
Space Separator
ValueCountFrequency (%)
489
100.0%
Close Punctuation
ValueCountFrequency (%)
) 339
100.0%
Open Punctuation
ValueCountFrequency (%)
( 339
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2754
54.6%
Common 2287
45.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 372
13.5%
어 263
9.5%
방 263
9.5%
로 218
 
7.9%
진 218
 
7.9%
도 176
 
6.4%
순 176
 
6.4%
환 175
 
6.4%
전 159
 
5.8%
하 159
 
5.8%
Other values (45) 575
20.9%
Common
ValueCountFrequency (%)
489
21.4%
0 451
19.7%
) 339
14.8%
( 339
14.8%
1 266
11.6%
7 72
 
3.1%
3 62
 
2.7%
4 54
 
2.4%
2 52
 
2.3%
5 48
 
2.1%
Other values (4) 115
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2754
54.6%
ASCII 2287
45.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
489
21.4%
0 451
19.7%
) 339
14.8%
( 339
14.8%
1 266
11.6%
7 72
 
3.1%
3 62
 
2.7%
4 54
 
2.4%
2 52
 
2.3%
5 48
 
2.1%
Other values (4) 115
 
5.0%
Hangul
ValueCountFrequency (%)
동 372
13.5%
어 263
9.5%
방 263
9.5%
로 218
 
7.9%
진 218
 
7.9%
도 176
 
6.4%
순 176
 
6.4%
환 175
 
6.4%
전 159
 
5.8%
하 159
 
5.8%
Other values (45) 575
20.9%

업체전화번호
Text

MISSING 

Distinct297
Distinct (%)99.7%
Missing42
Missing (%)12.4%
Memory size2.8 KiB
2024-04-06T17:21:42.692156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length12
Mean length12.318792
Min length12

Characters and Unicode

Total characters3671
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)99.3%

Sample

1st row052-250-6954
2nd row052-250-6976
3rd row052-234-4909
4th row052-234-2957
5th row052-235-2772
ValueCountFrequency (%)
052-250-5051 2
 
0.7%
052-235-3696 1
 
0.3%
052-233-5477 1
 
0.3%
052-201-4905 1
 
0.3%
052-710-3188 1
 
0.3%
052-252-6787 1
 
0.3%
052-232-9898 1
 
0.3%
052-233-7007 1
 
0.3%
052-232-7558 1
 
0.3%
052-236-6991 1
 
0.3%
Other values (294) 294
96.4%
2024-04-06T17:21:44.060703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 807
22.0%
- 611
16.6%
0 603
16.4%
5 512
13.9%
3 263
 
7.2%
9 174
 
4.7%
4 170
 
4.6%
6 165
 
4.5%
1 140
 
3.8%
7 118
 
3.2%
Other values (2) 108
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3053
83.2%
Dash Punctuation 611
 
16.6%
Control 7
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 807
26.4%
0 603
19.8%
5 512
16.8%
3 263
 
8.6%
9 174
 
5.7%
4 170
 
5.6%
6 165
 
5.4%
1 140
 
4.6%
7 118
 
3.9%
8 101
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 611
100.0%
Control
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3671
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 807
22.0%
- 611
16.6%
0 603
16.4%
5 512
13.9%
3 263
 
7.2%
9 174
 
4.7%
4 170
 
4.6%
6 165
 
4.5%
1 140
 
3.8%
7 118
 
3.2%
Other values (2) 108
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3671
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 807
22.0%
- 611
16.6%
0 603
16.4%
5 512
13.9%
3 263
 
7.2%
9 174
 
4.7%
4 170
 
4.6%
6 165
 
4.5%
1 140
 
3.8%
7 118
 
3.2%
Other values (2) 108
 
2.9%

업체팩스번호
Text

MISSING 

Distinct200
Distinct (%)99.5%
Missing139
Missing (%)40.9%
Memory size2.8 KiB
2024-04-06T17:21:44.824692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.995025
Min length8

Characters and Unicode

Total characters2411
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

Unique199 ?
Unique (%)99.0%

Sample

1st row052-234-4220
2nd row052-235-0045
3rd row052-234-4909
4th row052-234-2956
5th row052-232-9916
ValueCountFrequency (%)
052-235-8548 2
 
1.0%
052-201-5135 1
 
0.5%
052-250-3092 1
 
0.5%
052-234-4220 1
 
0.5%
052-252-9664 1
 
0.5%
052-251-7670 1
 
0.5%
052-233-0914 1
 
0.5%
052-252-7319 1
 
0.5%
052-232-7943 1
 
0.5%
052-970-0922 1
 
0.5%
Other values (190) 190
94.5%
2024-04-06T17:21:45.695654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 526
21.8%
- 401
16.6%
0 360
14.9%
5 345
14.3%
3 188
 
7.8%
1 142
 
5.9%
9 106
 
4.4%
6 102
 
4.2%
4 96
 
4.0%
8 73
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2010
83.4%
Dash Punctuation 401
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 526
26.2%
0 360
17.9%
5 345
17.2%
3 188
 
9.4%
1 142
 
7.1%
9 106
 
5.3%
6 102
 
5.1%
4 96
 
4.8%
8 73
 
3.6%
7 72
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 401
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2411
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 526
21.8%
- 401
16.6%
0 360
14.9%
5 345
14.3%
3 188
 
7.8%
1 142
 
5.9%
9 106
 
4.4%
6 102
 
4.2%
4 96
 
4.0%
8 73
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2411
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 526
21.8%
- 401
16.6%
0 360
14.9%
5 345
14.3%
3 188
 
7.8%
1 142
 
5.9%
9 106
 
4.4%
6 102
 
4.2%
4 96
 
4.0%
8 73
 
3.0%

업종
Text

Distinct64
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-04-06T17:21:46.112316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length9.6617647
Min length3

Characters and Unicode

Total characters3285
Distinct characters141
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)9.7%

Sample

1st row건설,광업용 기계 및 장비수리업
2nd row건설,광업용 기계 및 장비수리업
3rd row그외 기타 분류 안된 제품 제조업
4th row간판및광고물제조업
5th row간판및광고물제조업
ValueCountFrequency (%)
선박구성부분품제조업 79
 
15.0%
기타선박건조업 47
 
8.9%
제조업 43
 
8.2%
떡류제조업 32
 
6.1%
및 27
 
5.1%
과실및채소절임식품제조업 18
 
3.4%
강선건조업 18
 
3.4%
건강보조용액화식품제조업 15
 
2.8%
기타 10
 
1.9%
인쇄및기록매체복제업 9
 
1.7%
Other values (90) 229
43.5%
2024-04-06T17:21:46.787174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
조 352
 
10.7%
업 346
 
10.5%
제 290
 
8.8%
187
 
5.7%
선 149
 
4.5%
품 141
 
4.3%
박 126
 
3.8%
기 95
 
2.9%
구 89
 
2.7%
분 86
 
2.6%
Other values (131) 1424
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3079
93.7%
Space Separator 187
 
5.7%
Other Punctuation 17
 
0.5%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
조 352
 
11.4%
업 346
 
11.2%
제 290
 
9.4%
선 149
 
4.8%
품 141
 
4.6%
박 126
 
4.1%
기 95
 
3.1%
구 89
 
2.9%
분 86
 
2.8%
건 85
 
2.8%
Other values (127) 1320
42.9%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
4 1
50.0%
Space Separator
ValueCountFrequency (%)
187
100.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3079
93.7%
Common 206
 
6.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
조 352
 
11.4%
업 346
 
11.2%
제 290
 
9.4%
선 149
 
4.8%
품 141
 
4.6%
박 126
 
4.1%
기 95
 
3.1%
구 89
 
2.9%
분 86
 
2.8%
건 85
 
2.8%
Other values (127) 1320
42.9%
Common
ValueCountFrequency (%)
187
90.8%
, 17
 
8.3%
3 1
 
0.5%
4 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3079
93.7%
ASCII 206
 
6.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
조 352
 
11.4%
업 346
 
11.2%
제 290
 
9.4%
선 149
 
4.8%
품 141
 
4.6%
박 126
 
4.1%
기 95
 
3.1%
구 89
 
2.9%
분 86
 
2.8%
건 85
 
2.8%
Other values (127) 1320
42.9%
ASCII
ValueCountFrequency (%)
187
90.8%
, 17
 
8.3%
3 1
 
0.5%
4 1
 
0.5%

종업원 합계
Real number (ℝ)

HIGH CORRELATION 

Distinct98
Distinct (%)28.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.97059
Minimum1
Maximum14983
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-06T17:21:47.123731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median6
Q376.25
95-th percentile125.25
Maximum14983
Range14982
Interquartile range (IQR)75.25

Descriptive statistics

Standard deviation846.71423
Coefficient of variation (CV)8.1437861
Kurtosis284.87196
Mean103.97059
Median Absolute Deviation (MAD)5
Skewness16.442947
Sum35350
Variance716924.98
MonotonicityNot monotonic
2024-04-06T17:21:47.528831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 115
33.8%
2 35
 
10.3%
3 14
 
4.1%
85 7
 
2.1%
78 6
 
1.8%
90 6
 
1.8%
70 6
 
1.8%
76 5
 
1.5%
4 5
 
1.5%
62 4
 
1.2%
Other values (88) 137
40.3%
ValueCountFrequency (%)
1 115
33.8%
2 35
 
10.3%
3 14
 
4.1%
4 5
 
1.5%
6 2
 
0.6%
7 1
 
0.3%
8 1
 
0.3%
9 1
 
0.3%
12 1
 
0.3%
16 1
 
0.3%
ValueCountFrequency (%)
14983 1
0.3%
4145 1
0.3%
1504 1
0.3%
1158 1
0.3%
518 1
0.3%
205 1
0.3%
186 1
0.3%
160 2
0.6%
150 2
0.6%
149 1
0.3%

남자종업원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct88
Distinct (%)25.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.102941
Minimum0
Maximum13715
Zeros63
Zeros (%)18.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-06T17:21:47.880296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q351.25
95-th percentile94.05
Maximum13715
Range13715
Interquartile range (IQR)50.25

Descriptive statistics

Standard deviation772.47106
Coefficient of variation (CV)8.9714828
Kurtosis289.21646
Mean86.102941
Median Absolute Deviation (MAD)2
Skewness16.592875
Sum29275
Variance596711.53
MonotonicityNot monotonic
2024-04-06T17:21:48.151168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 100
29.4%
0 63
18.5%
2 10
 
2.9%
46 7
 
2.1%
44 6
 
1.8%
70 5
 
1.5%
42 5
 
1.5%
40 5
 
1.5%
52 5
 
1.5%
47 4
 
1.2%
Other values (78) 130
38.2%
ValueCountFrequency (%)
0 63
18.5%
1 100
29.4%
2 10
 
2.9%
5 1
 
0.3%
7 2
 
0.6%
8 1
 
0.3%
13 1
 
0.3%
14 1
 
0.3%
15 1
 
0.3%
16 1
 
0.3%
ValueCountFrequency (%)
13715 1
0.3%
3593 1
0.3%
1347 1
0.3%
1068 1
0.3%
471 1
0.3%
173 1
0.3%
155 1
0.3%
148 1
0.3%
134 1
0.3%
122 1
0.3%

여자종업원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6823529
Minimum0
Maximum758
Zeros67
Zeros (%)19.7%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-06T17:21:48.423955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q35.25
95-th percentile18
Maximum758
Range758
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation43.336772
Coefficient of variation (CV)5.6410806
Kurtosis267.66635
Mean7.6823529
Median Absolute Deviation (MAD)1
Skewness15.681079
Sum2612
Variance1878.0758
MonotonicityNot monotonic
2024-04-06T17:21:48.682265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 112
32.9%
0 67
19.7%
2 24
 
7.1%
5 20
 
5.9%
4 17
 
5.0%
3 15
 
4.4%
6 11
 
3.2%
10 10
 
2.9%
13 9
 
2.6%
8 8
 
2.4%
Other values (20) 47
13.8%
ValueCountFrequency (%)
0 67
19.7%
1 112
32.9%
2 24
 
7.1%
3 15
 
4.4%
4 17
 
5.0%
5 20
 
5.9%
6 11
 
3.2%
7 4
 
1.2%
8 8
 
2.4%
9 8
 
2.4%
ValueCountFrequency (%)
758 1
0.3%
157 1
0.3%
151 1
0.3%
103 1
0.3%
90 1
0.3%
35 1
0.3%
31 1
0.3%
30 2
0.6%
22 1
0.3%
21 1
0.3%

외국인종업원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.232353
Minimum0
Maximum510
Zeros207
Zeros (%)60.9%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-06T17:21:48.998755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q314
95-th percentile34.05
Maximum510
Range510
Interquartile range (IQR)14

Descriptive statistics

Standard deviation36.794921
Coefficient of variation (CV)3.5959394
Kurtosis137.50126
Mean10.232353
Median Absolute Deviation (MAD)0
Skewness11.055771
Sum3479
Variance1353.8662
MonotonicityNot monotonic
2024-04-06T17:21:49.281991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 207
60.9%
15 7
 
2.1%
14 6
 
1.8%
9 6
 
1.8%
4 6
 
1.8%
1 5
 
1.5%
17 5
 
1.5%
13 5
 
1.5%
22 5
 
1.5%
25 4
 
1.2%
Other values (35) 84
24.7%
ValueCountFrequency (%)
0 207
60.9%
1 5
 
1.5%
2 1
 
0.3%
3 4
 
1.2%
4 6
 
1.8%
5 4
 
1.2%
6 4
 
1.2%
7 2
 
0.6%
8 1
 
0.3%
9 6
 
1.8%
ValueCountFrequency (%)
510 1
 
0.3%
401 1
 
0.3%
102 1
 
0.3%
45 1
 
0.3%
41 3
0.9%
40 1
 
0.3%
38 1
 
0.3%
37 4
1.2%
36 2
0.6%
35 2
0.6%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
울산광역시 동구 경제진흥과
340 

Length

Max length14
Median length14
Mean length14
Min length14

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row울산광역시 동구 경제진흥과
2nd row울산광역시 동구 경제진흥과
3rd row울산광역시 동구 경제진흥과
4th row울산광역시 동구 경제진흥과
5th row울산광역시 동구 경제진흥과

Common Values

ValueCountFrequency (%)
울산광역시 동구 경제진흥과 340
100.0%

Length

2024-04-06T17:21:49.568525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:21:49.743580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
울산광역시 340
33.3%
동구 340
33.3%
경제진흥과 340
33.3%

전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
052-209-3502
340 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row052-209-3502
2nd row052-209-3502
3rd row052-209-3502
4th row052-209-3502
5th row052-209-3502

Common Values

ValueCountFrequency (%)
052-209-3502 340
100.0%

Length

2024-04-06T17:21:49.934630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:21:50.124965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
052-209-3502 340
100.0%

Interactions

2024-04-06T17:21:35.264024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:32.447502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:33.268188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:34.117503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:35.478698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:32.607991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:33.461316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:34.457603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:35.712785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:32.817798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:33.671091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:34.739701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:35.998853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:33.004322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:33.851579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:21:35.034635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:21:50.248130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종종업원 합계남자종업원여자종업원외국인종업원
업종1.0000.9580.8560.9820.751
종업원 합계0.9581.0001.0000.9920.981
남자종업원0.8561.0001.0000.7621.000
여자종업원0.9820.9920.7621.0000.936
외국인종업원0.7510.9811.0000.9361.000
2024-04-06T17:21:50.450468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원 합계남자종업원여자종업원외국인종업원
종업원 합계1.0000.9110.8370.762
남자종업원0.9111.0000.6320.668
여자종업원0.8370.6321.0000.699
외국인종업원0.7620.6680.6991.000

Missing values

2024-04-06T17:21:36.300922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:21:36.684772image/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.
2024-04-06T17:21:36.933284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

회사명대표자소재지업체전화번호업체팩스번호업종종업원 합계남자종업원여자종업원외국인종업원관리기관명전화번호
0(주)세강이경신방어진순환도로 100(방어동)052-250-6954052-234-4220건설,광업용 기계 및 장비수리업737210울산광역시 동구 경제진흥과052-209-3502
1(주)건승이엔지이흥철방어진순환도로 100(방어동)052-250-6976052-235-0045건설,광업용 기계 및 장비수리업383710울산광역시 동구 경제진흥과052-209-3502
2화신산업김철웅진성12길 72(전하동)052-234-4909052-234-4909그외 기타 분류 안된 제품 제조업1100울산광역시 동구 경제진흥과052-209-3502
3현대애드월드김병철바드래길 12-5(전하동)052-234-2957052-234-2956간판및광고물제조업2110울산광역시 동구 경제진흥과052-209-3502
4소망스케치이영식바드래길 31(전하동)<NA><NA>간판및광고물제조업1100울산광역시 동구 경제진흥과052-209-3502
5태양광고사유용길대송로 93(화정동)052-235-2772<NA>간판및광고물제조업1100울산광역시 동구 경제진흥과052-209-3502
6삼원광고기획박정희문현로15-1(방어동)052-233-9616052-232-9916간판및광고물제조업1100울산광역시 동구 경제진흥과052-209-3502
7화진광고산업홍경화꽃바위로 314(방어동)052-235-7171052-236-6690간판및광고물제조업1100울산광역시 동구 경제진흥과052-209-3502
8신진광고김영아화잠3길 13(방어동)052-251-6669052-232-8569간판및광고물제조업1010울산광역시 동구 경제진흥과052-209-3502
9더가우디권오현꽃바위3길 25(방어동)052-201-4304052-251-3904간판및광고물제조업1100울산광역시 동구 경제진흥과052-209-3502
회사명대표자소재지업체전화번호업체팩스번호업종종업원 합계남자종업원여자종업원외국인종업원관리기관명전화번호
330팔도김치조정이진성14길 77(전하동)052-235-8756<NA>과실및채소절임식품제조업2020울산광역시 동구 경제진흥과052-209-3502
331미담김치김미경대송1길 31(화정동)052-232-1625<NA>과실및채소절임식품제조업4040울산광역시 동구 경제진흥과052-209-3502
332옥이반찬이윤옥화정 6길 24 (화정동)<NA><NA>과실및채소절임식품제조업1010울산광역시 동구 경제진흥과052-209-3502
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335진영김문호방어진순환도로 1000 (전하동)052-203-2789052-233-8034선박구성부분품제조업626110울산광역시 동구 경제진흥과052-209-3502
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