Overview

Dataset statistics

Number of variables8
Number of observations491
Missing cells242
Missing cells (%)6.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.3 KiB
Average record size in memory65.3 B

Variable types

Numeric1
Text7

Dataset

Description경상남도 창녕군 제조업공장 현황에 대한 정보를 제공하고 있습니다.(회사명, 대표자명, 전화번호, 팩스번호, 공장대표주소, 업종명, 생산품)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15034995

Alerts

전화번호 has 89 (18.1%) missing valuesMissing
팩스번호 has 153 (31.2%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:55:31.941287
Analysis finished2023-12-11 00:55:33.001494
Duration1.06 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct491
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean246
Minimum1
Maximum491
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-11T09:55:33.091958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.5
Q1123.5
median246
Q3368.5
95-th percentile466.5
Maximum491
Range490
Interquartile range (IQR)245

Descriptive statistics

Standard deviation141.88376
Coefficient of variation (CV)0.57676323
Kurtosis-1.2
Mean246
Median Absolute Deviation (MAD)123
Skewness0
Sum120786
Variance20131
MonotonicityStrictly increasing
2023-12-11T09:55:33.226571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
339 1
 
0.2%
337 1
 
0.2%
336 1
 
0.2%
335 1
 
0.2%
334 1
 
0.2%
333 1
 
0.2%
332 1
 
0.2%
331 1
 
0.2%
330 1
 
0.2%
Other values (481) 481
98.0%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
491 1
0.2%
490 1
0.2%
489 1
0.2%
488 1
0.2%
487 1
0.2%
486 1
0.2%
485 1
0.2%
484 1
0.2%
483 1
0.2%
482 1
0.2%

회사명
Text

Distinct464
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T09:55:33.505658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length17
Mean length7.3808554
Min length2

Characters and Unicode

Total characters3624
Distinct characters328
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

Unique441 ?
Unique (%)89.8%

Sample

1st row넥센타이어(주) 창녕공장
2nd row보그워너창녕 유한책임회사
3rd row(주)센트랄 영산공장
4th row(주)SUN&L 창녕공장
5th row(주)세아베스틸
ValueCountFrequency (%)
주식회사 30
 
5.3%
농업회사법인 14
 
2.5%
창녕공장 9
 
1.6%
영농조합법인 7
 
1.2%
주)가야이에스씨 4
 
0.7%
주)센트랄씨엠에스 3
 
0.5%
주)성일엠텍 3
 
0.5%
주)센트랄 3
 
0.5%
남경포장 2
 
0.4%
효창산업 2
 
0.4%
Other values (472) 493
86.5%
2023-12-11T09:55:33.939387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 328
 
9.1%
) 299
 
8.3%
( 298
 
8.2%
이 89
 
2.5%
업 84
 
2.3%
80
 
2.2%
스 77
 
2.1%
사 72
 
2.0%
에 68
 
1.9%
식 64
 
1.8%
Other values (318) 2165
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2879
79.4%
Close Punctuation 300
 
8.3%
Open Punctuation 299
 
8.3%
Space Separator 80
 
2.2%
Uppercase Letter 35
 
1.0%
Other Punctuation 12
 
0.3%
Decimal Number 8
 
0.2%
Lowercase Letter 7
 
0.2%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 328
 
11.4%
이 89
 
3.1%
업 84
 
2.9%
스 77
 
2.7%
사 72
 
2.5%
에 68
 
2.4%
식 64
 
2.2%
산 60
 
2.1%
회 57
 
2.0%
공 53
 
1.8%
Other values (283) 1927
66.9%
Uppercase Letter
ValueCountFrequency (%)
S 4
11.4%
G 4
11.4%
P 3
 
8.6%
N 3
 
8.6%
E 3
 
8.6%
T 2
 
5.7%
Y 2
 
5.7%
K 2
 
5.7%
J 2
 
5.7%
L 2
 
5.7%
Other values (8) 8
22.9%
Lowercase Letter
ValueCountFrequency (%)
u 2
28.6%
e 1
14.3%
r 1
14.3%
t 1
14.3%
a 1
14.3%
n 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 3
37.5%
3 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 299
99.7%
] 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 298
99.7%
[ 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 9
75.0%
& 3
 
25.0%
Space Separator
ValueCountFrequency (%)
80
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2879
79.4%
Common 703
 
19.4%
Latin 42
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 328
 
11.4%
이 89
 
3.1%
업 84
 
2.9%
스 77
 
2.7%
사 72
 
2.5%
에 68
 
2.4%
식 64
 
2.2%
산 60
 
2.1%
회 57
 
2.0%
공 53
 
1.8%
Other values (283) 1927
66.9%
Latin
ValueCountFrequency (%)
S 4
 
9.5%
G 4
 
9.5%
P 3
 
7.1%
N 3
 
7.1%
E 3
 
7.1%
u 2
 
4.8%
T 2
 
4.8%
Y 2
 
4.8%
K 2
 
4.8%
J 2
 
4.8%
Other values (14) 15
35.7%
Common
ValueCountFrequency (%)
) 299
42.5%
( 298
42.4%
80
 
11.4%
. 9
 
1.3%
2 4
 
0.6%
- 4
 
0.6%
1 3
 
0.4%
& 3
 
0.4%
] 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2879
79.4%
ASCII 745
 
20.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 328
 
11.4%
이 89
 
3.1%
업 84
 
2.9%
스 77
 
2.7%
사 72
 
2.5%
에 68
 
2.4%
식 64
 
2.2%
산 60
 
2.1%
회 57
 
2.0%
공 53
 
1.8%
Other values (283) 1927
66.9%
ASCII
ValueCountFrequency (%)
) 299
40.1%
( 298
40.0%
80
 
10.7%
. 9
 
1.2%
2 4
 
0.5%
S 4
 
0.5%
- 4
 
0.5%
G 4
 
0.5%
P 3
 
0.4%
1 3
 
0.4%
Other values (25) 37
 
5.0%

대표자명
Text

Distinct431
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T09:55:34.249735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.2077393
Min length2

Characters and Unicode

Total characters1575
Distinct characters178
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

Unique384 ?
Unique (%)78.2%

Sample

1st row강호찬
2nd row김동희
3rd row강태룡, 윤용호
4th row서성교
5th row김철희
ValueCountFrequency (%)
김종열 4
 
0.8%
윤병국 4
 
0.8%
윤용호 4
 
0.8%
엄홍주 4
 
0.8%
장주영 3
 
0.6%
외 3
 
0.6%
이동군 3
 
0.6%
권대용 3
 
0.6%
김병준 3
 
0.6%
이상근 3
 
0.6%
Other values (432) 475
93.3%
2023-12-11T09:55:34.628767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 115
 
7.3%
이 83
 
5.3%
영 57
 
3.6%
정 48
 
3.0%
박 40
 
2.5%
호 34
 
2.2%
현 28
 
1.8%
진 27
 
1.7%
용 27
 
1.7%
수 26
 
1.7%
Other values (168) 1090
69.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1535
97.5%
Space Separator 19
 
1.2%
Other Punctuation 18
 
1.1%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 115
 
7.5%
이 83
 
5.4%
영 57
 
3.7%
정 48
 
3.1%
박 40
 
2.6%
호 34
 
2.2%
현 28
 
1.8%
진 27
 
1.8%
용 27
 
1.8%
수 26
 
1.7%
Other values (164) 1050
68.4%
Decimal Number
ValueCountFrequency (%)
1 2
66.7%
2 1
33.3%
Space Separator
ValueCountFrequency (%)
19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1535
97.5%
Common 40
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 115
 
7.5%
이 83
 
5.4%
영 57
 
3.7%
정 48
 
3.1%
박 40
 
2.6%
호 34
 
2.2%
현 28
 
1.8%
진 27
 
1.8%
용 27
 
1.8%
수 26
 
1.7%
Other values (164) 1050
68.4%
Common
ValueCountFrequency (%)
19
47.5%
, 18
45.0%
1 2
 
5.0%
2 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1535
97.5%
ASCII 40
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 115
 
7.5%
이 83
 
5.4%
영 57
 
3.7%
정 48
 
3.1%
박 40
 
2.6%
호 34
 
2.2%
현 28
 
1.8%
진 27
 
1.8%
용 27
 
1.8%
수 26
 
1.7%
Other values (164) 1050
68.4%
ASCII
ValueCountFrequency (%)
19
47.5%
, 18
45.0%
1 2
 
5.0%
2 1
 
2.5%

전화번호
Text

MISSING 

Distinct366
Distinct (%)91.0%
Missing89
Missing (%)18.1%
Memory size4.0 KiB
2023-12-11T09:55:34.875650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.00995
Min length9

Characters and Unicode

Total characters4828
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

Unique335 ?
Unique (%)83.3%

Sample

1st row055-370-5114
2nd row055-520-2000
3rd row055-520-3000
4th row055-294-8801
5th row055-530-8500
ValueCountFrequency (%)
055-532-0080 4
 
1.0%
055-521-1712 3
 
0.7%
055-533-5263 3
 
0.7%
055-521-8051 3
 
0.7%
055-533-9133 2
 
0.5%
055-587-9963 2
 
0.5%
055-533-1656 2
 
0.5%
070-7708-7727 2
 
0.5%
055-532-4741 2
 
0.5%
055-532-6534 2
 
0.5%
Other values (356) 377
93.8%
2023-12-11T09:55:35.215905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1251
25.9%
- 803
16.6%
0 711
14.7%
3 489
 
10.1%
2 404
 
8.4%
1 305
 
6.3%
6 216
 
4.5%
8 198
 
4.1%
7 193
 
4.0%
4 137
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4025
83.4%
Dash Punctuation 803
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1251
31.1%
0 711
17.7%
3 489
 
12.1%
2 404
 
10.0%
1 305
 
7.6%
6 216
 
5.4%
8 198
 
4.9%
7 193
 
4.8%
4 137
 
3.4%
9 121
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 803
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4828
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1251
25.9%
- 803
16.6%
0 711
14.7%
3 489
 
10.1%
2 404
 
8.4%
1 305
 
6.3%
6 216
 
4.5%
8 198
 
4.1%
7 193
 
4.0%
4 137
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4828
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1251
25.9%
- 803
16.6%
0 711
14.7%
3 489
 
10.1%
2 404
 
8.4%
1 305
 
6.3%
6 216
 
4.5%
8 198
 
4.1%
7 193
 
4.0%
4 137
 
2.8%

팩스번호
Text

MISSING 

Distinct312
Distinct (%)92.3%
Missing153
Missing (%)31.2%
Memory size4.0 KiB
2023-12-11T09:55:35.457072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.035503
Min length12

Characters and Unicode

Total characters4068
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

Unique292 ?
Unique (%)86.4%

Sample

1st row055-386-8962
2nd row055-520-2094
3rd row070-4275-1267
4th row070-4006-4131
5th row055-530-8597
ValueCountFrequency (%)
055-536-8051 4
 
1.2%
055-532-7933 3
 
0.9%
055-526-1712 3
 
0.9%
055-327-8102 3
 
0.9%
055-533-5264 3
 
0.9%
055-533-1842 2
 
0.6%
055-532-2942 2
 
0.6%
055-343-7507 2
 
0.6%
055-532-0958 2
 
0.6%
055-532-3902 2
 
0.6%
Other values (302) 312
92.3%
2023-12-11T09:55:35.822000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1017
25.0%
- 676
16.6%
0 555
13.6%
3 423
10.4%
2 346
 
8.5%
1 222
 
5.5%
6 214
 
5.3%
8 175
 
4.3%
7 171
 
4.2%
9 138
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3392
83.4%
Dash Punctuation 676
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1017
30.0%
0 555
16.4%
3 423
12.5%
2 346
 
10.2%
1 222
 
6.5%
6 214
 
6.3%
8 175
 
5.2%
7 171
 
5.0%
9 138
 
4.1%
4 131
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 676
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4068
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1017
25.0%
- 676
16.6%
0 555
13.6%
3 423
10.4%
2 346
 
8.5%
1 222
 
5.5%
6 214
 
5.3%
8 175
 
4.3%
7 171
 
4.2%
9 138
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4068
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1017
25.0%
- 676
16.6%
0 555
13.6%
3 423
10.4%
2 346
 
8.5%
1 222
 
5.5%
6 214
 
5.3%
8 175
 
4.3%
7 171
 
4.2%
9 138
 
3.4%

공장대표주소(도로명)
Text

Distinct454
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T09:55:36.111656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length25.8778
Min length18

Characters and Unicode

Total characters12706
Distinct characters171
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique420 ?
Unique (%)85.5%

Sample

1st row경상남도 창녕군 대합면 대동월포로 291, 넥센타이어(주) 창녕공장(이방리 992번지)
2nd row경상남도 창녕군 계성면 명리길 78 외 4필지
3rd row경상남도 창녕군 영산면 서리상촌길 307-106
4th row경상남도 창녕군 도천면 일리 418 외 3필지
5th row경상남도 창녕군 대합면 대합산업단지로 100
ValueCountFrequency (%)
경상남도 491
 
16.5%
창녕군 491
 
16.5%
외 184
 
6.2%
대합면 140
 
4.7%
영산면 80
 
2.7%
1필지 68
 
2.3%
계성면 51
 
1.7%
도천면 50
 
1.7%
대지면 49
 
1.6%
필지 41
 
1.4%
Other values (569) 1325
44.6%
2023-12-11T09:55:36.463330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2480
19.5%
도 568
 
4.5%
남 543
 
4.3%
창 531
 
4.2%
녕 526
 
4.1%
상 520
 
4.1%
경 512
 
4.0%
군 491
 
3.9%
지 488
 
3.8%
면 448
 
3.5%
Other values (161) 5599
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7967
62.7%
Space Separator 2480
 
19.5%
Decimal Number 1927
 
15.2%
Dash Punctuation 211
 
1.7%
Close Punctuation 54
 
0.4%
Open Punctuation 54
 
0.4%
Other Punctuation 12
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 568
 
7.1%
남 543
 
6.8%
창 531
 
6.7%
녕 526
 
6.6%
상 520
 
6.5%
경 512
 
6.4%
군 491
 
6.2%
지 488
 
6.1%
면 448
 
5.6%
대 300
 
3.8%
Other values (145) 3040
38.2%
Decimal Number
ValueCountFrequency (%)
1 392
20.3%
2 277
14.4%
3 275
14.3%
4 188
9.8%
7 151
 
7.8%
5 144
 
7.5%
6 144
 
7.5%
9 130
 
6.7%
0 116
 
6.0%
8 110
 
5.7%
Space Separator
ValueCountFrequency (%)
2480
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 211
100.0%
Close Punctuation
ValueCountFrequency (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Other Punctuation
ValueCountFrequency (%)
, 12
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7967
62.7%
Common 4738
37.3%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 568
 
7.1%
남 543
 
6.8%
창 531
 
6.7%
녕 526
 
6.6%
상 520
 
6.5%
경 512
 
6.4%
군 491
 
6.2%
지 488
 
6.1%
면 448
 
5.6%
대 300
 
3.8%
Other values (145) 3040
38.2%
Common
ValueCountFrequency (%)
2480
52.3%
1 392
 
8.3%
2 277
 
5.8%
3 275
 
5.8%
- 211
 
4.5%
4 188
 
4.0%
7 151
 
3.2%
5 144
 
3.0%
6 144
 
3.0%
9 130
 
2.7%
Other values (5) 346
 
7.3%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7967
62.7%
ASCII 4739
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2480
52.3%
1 392
 
8.3%
2 277
 
5.8%
3 275
 
5.8%
- 211
 
4.5%
4 188
 
4.0%
7 151
 
3.2%
5 144
 
3.0%
6 144
 
3.0%
9 130
 
2.7%
Other values (6) 347
 
7.3%
Hangul
ValueCountFrequency (%)
도 568
 
7.1%
남 543
 
6.8%
창 531
 
6.7%
녕 526
 
6.6%
상 520
 
6.5%
경 512
 
6.4%
군 491
 
6.2%
지 488
 
6.1%
면 448
 
5.6%
대 300
 
3.8%
Other values (145) 3040
38.2%

업종명
Text

Distinct228
Distinct (%)46.4%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T09:55:36.732477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length25
Mean length18.266802
Min length5

Characters and Unicode

Total characters8969
Distinct characters252
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

Unique142 ?
Unique (%)28.9%

Sample

1st row타이어 및 튜브 제조업
2nd row자동차 엔진용 신품 부품 제조업 외 1 종
3rd row그 외 자동차용 신품 부품 제조업 외 4 종
4th row포장용 플라스틱 성형용기 제조업 외 1 종
5th row제강업 외 1 종
ValueCountFrequency (%)
제조업 413
 
14.0%
외 300
 
10.1%
종 215
 
7.3%
및 207
 
7.0%
1 116
 
3.9%
기타 115
 
3.9%
그 85
 
2.9%
부품 62
 
2.1%
신품 60
 
2.0%
금속 56
 
1.9%
Other values (313) 1327
44.9%
2023-12-11T09:55:37.103193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2465
27.5%
제 548
 
6.1%
조 546
 
6.1%
업 516
 
5.8%
외 314
 
3.5%
품 251
 
2.8%
종 219
 
2.4%
및 209
 
2.3%
기 200
 
2.2%
용 143
 
1.6%
Other values (242) 3558
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6172
68.8%
Space Separator 2465
 
27.5%
Decimal Number 226
 
2.5%
Other Punctuation 78
 
0.9%
Open Punctuation 14
 
0.2%
Close Punctuation 14
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 548
 
8.9%
조 546
 
8.8%
업 516
 
8.4%
외 314
 
5.1%
품 251
 
4.1%
종 219
 
3.5%
및 209
 
3.4%
기 200
 
3.2%
용 143
 
2.3%
타 125
 
2.0%
Other values (229) 3101
50.2%
Decimal Number
ValueCountFrequency (%)
1 127
56.2%
2 38
 
16.8%
3 38
 
16.8%
4 12
 
5.3%
6 4
 
1.8%
5 3
 
1.3%
0 3
 
1.3%
7 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 77
98.7%
. 1
 
1.3%
Space Separator
ValueCountFrequency (%)
2465
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6172
68.8%
Common 2797
31.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 548
 
8.9%
조 546
 
8.8%
업 516
 
8.4%
외 314
 
5.1%
품 251
 
4.1%
종 219
 
3.5%
및 209
 
3.4%
기 200
 
3.2%
용 143
 
2.3%
타 125
 
2.0%
Other values (229) 3101
50.2%
Common
ValueCountFrequency (%)
2465
88.1%
1 127
 
4.5%
, 77
 
2.8%
2 38
 
1.4%
3 38
 
1.4%
( 14
 
0.5%
) 14
 
0.5%
4 12
 
0.4%
6 4
 
0.1%
5 3
 
0.1%
Other values (3) 5
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6163
68.7%
ASCII 2797
31.2%
Compat Jamo 9
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2465
88.1%
1 127
 
4.5%
, 77
 
2.8%
2 38
 
1.4%
3 38
 
1.4%
( 14
 
0.5%
) 14
 
0.5%
4 12
 
0.4%
6 4
 
0.1%
5 3
 
0.1%
Other values (3) 5
 
0.2%
Hangul
ValueCountFrequency (%)
제 548
 
8.9%
조 546
 
8.9%
업 516
 
8.4%
외 314
 
5.1%
품 251
 
4.1%
종 219
 
3.6%
및 209
 
3.4%
기 200
 
3.2%
용 143
 
2.3%
타 125
 
2.0%
Other values (228) 3092
50.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 9
100.0%

생산품
Text

Distinct435
Distinct (%)88.6%
Missing0
Missing (%)0.0%
Memory size4.0 KiB
2023-12-11T09:55:37.308463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length68
Median length34
Mean length8.8309572
Min length1

Characters and Unicode

Total characters4336
Distinct characters465
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

Unique410 ?
Unique (%)83.5%

Sample

1st row타이어 및 튜브
2nd row내연기관용전장품(Starter,Alternator)
3rd row자동차 조향 및 현가장치 부품
4th row생활용품 플라스틱 pump&spray
5th row특수강
ValueCountFrequency (%)
및 20
 
2.3%
자동차부품 17
 
2.0%
등 13
 
1.5%
철구조물 13
 
1.5%
자동차 12
 
1.4%
부품 9
 
1.1%
알루미늄 6
 
0.7%
레미콘 5
 
0.6%
산업용 5
 
0.6%
배전반 5
 
0.6%
Other values (626) 751
87.7%
2023-12-11T09:55:37.629815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
366
 
8.4%
, 233
 
5.4%
품 114
 
2.6%
자 89
 
2.1%
부 88
 
2.0%
조 87
 
2.0%
기 85
 
2.0%
차 68
 
1.6%
동 67
 
1.5%
용 62
 
1.4%
Other values (455) 3077
71.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3393
78.3%
Space Separator 366
 
8.4%
Other Punctuation 243
 
5.6%
Uppercase Letter 131
 
3.0%
Lowercase Letter 126
 
2.9%
Close Punctuation 35
 
0.8%
Open Punctuation 35
 
0.8%
Decimal Number 6
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 114
 
3.4%
자 89
 
2.6%
부 88
 
2.6%
조 87
 
2.6%
기 85
 
2.5%
차 68
 
2.0%
동 67
 
2.0%
용 62
 
1.8%
장 60
 
1.8%
제 58
 
1.7%
Other values (401) 2615
77.1%
Uppercase Letter
ValueCountFrequency (%)
C 13
 
9.9%
S 11
 
8.4%
P 11
 
8.4%
E 11
 
8.4%
H 10
 
7.6%
R 10
 
7.6%
D 9
 
6.9%
T 8
 
6.1%
L 7
 
5.3%
U 6
 
4.6%
Other values (12) 35
26.7%
Lowercase Letter
ValueCountFrequency (%)
e 17
13.5%
r 13
10.3%
t 11
8.7%
a 10
 
7.9%
p 10
 
7.9%
c 10
 
7.9%
i 9
 
7.1%
o 8
 
6.3%
n 7
 
5.6%
k 6
 
4.8%
Other values (10) 25
19.8%
Other Punctuation
ValueCountFrequency (%)
, 233
95.9%
/ 5
 
2.1%
. 4
 
1.6%
& 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
5 2
33.3%
4 1
16.7%
1 1
16.7%
Space Separator
ValueCountFrequency (%)
366
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3393
78.3%
Common 686
 
15.8%
Latin 257
 
5.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 114
 
3.4%
자 89
 
2.6%
부 88
 
2.6%
조 87
 
2.6%
기 85
 
2.5%
차 68
 
2.0%
동 67
 
2.0%
용 62
 
1.8%
장 60
 
1.8%
제 58
 
1.7%
Other values (401) 2615
77.1%
Latin
ValueCountFrequency (%)
e 17
 
6.6%
r 13
 
5.1%
C 13
 
5.1%
t 11
 
4.3%
S 11
 
4.3%
P 11
 
4.3%
E 11
 
4.3%
H 10
 
3.9%
a 10
 
3.9%
p 10
 
3.9%
Other values (32) 140
54.5%
Common
ValueCountFrequency (%)
366
53.4%
, 233
34.0%
) 35
 
5.1%
( 35
 
5.1%
/ 5
 
0.7%
. 4
 
0.6%
2 2
 
0.3%
5 2
 
0.3%
- 1
 
0.1%
4 1
 
0.1%
Other values (2) 2
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3393
78.3%
ASCII 943
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
366
38.8%
, 233
24.7%
) 35
 
3.7%
( 35
 
3.7%
e 17
 
1.8%
r 13
 
1.4%
C 13
 
1.4%
t 11
 
1.2%
S 11
 
1.2%
P 11
 
1.2%
Other values (44) 198
21.0%
Hangul
ValueCountFrequency (%)
품 114
 
3.4%
자 89
 
2.6%
부 88
 
2.6%
조 87
 
2.6%
기 85
 
2.5%
차 68
 
2.0%
동 67
 
2.0%
용 62
 
1.8%
장 60
 
1.8%
제 58
 
1.7%
Other values (401) 2615
77.1%

Interactions

2023-12-11T09:55:32.598838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-11T09:55:32.707167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:55:32.849215image/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.
2023-12-11T09:55:32.945891image/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

순번회사명대표자명전화번호팩스번호공장대표주소(도로명)업종명생산품
01넥센타이어(주) 창녕공장강호찬055-370-5114055-386-8962경상남도 창녕군 대합면 대동월포로 291, 넥센타이어(주) 창녕공장(이방리 992번지)타이어 및 튜브 제조업타이어 및 튜브
12보그워너창녕 유한책임회사김동희055-520-2000055-520-2094경상남도 창녕군 계성면 명리길 78 외 4필지자동차 엔진용 신품 부품 제조업 외 1 종내연기관용전장품(Starter,Alternator)
23(주)센트랄 영산공장강태룡, 윤용호055-520-3000070-4275-1267경상남도 창녕군 영산면 서리상촌길 307-106그 외 자동차용 신품 부품 제조업 외 4 종자동차 조향 및 현가장치 부품
34(주)SUN&L 창녕공장서성교055-294-8801070-4006-4131경상남도 창녕군 도천면 일리 418 외 3필지포장용 플라스틱 성형용기 제조업 외 1 종생활용품 플라스틱 pump&spray
45(주)세아베스틸김철희055-530-8500055-530-8597경상남도 창녕군 대합면 대합산업단지로 100제강업 외 1 종특수강
56(주)센트랄 영산AM공장윤용호, 이호영055-520-0200055-520-0297경상남도 창녕군 영산면 서리상촌길 307-50그 외 자동차용 신품 부품 제조업 외 3 종자동차부품
67(주)가야이에스씨윤병국055-532-0080055-532-8901경상남도 창녕군 대합면 이방대합로 1132 (총 5 필지) 외 8필지기타 구조용 금속제품 제조업철구조물, BH제작, 금속부착물 외
78(주)지앤박용주055-536-9050055-536-9050경상남도 창녕군 영산면 서리상촌길 307-21그 외 자동차용 신품 부품 제조업 외 4 종연료필터 히터 및 센서
89(주)성일엠텍장주영055-521-1712055-526-1712경상남도 창녕군 영산면 서리 534번지자동차 엔진용 신품 부품 제조업 외 1 종자동차엔진부품,태양력발전업
910(주)성일엠텍장주영055-521-1712055-526-1712경상남도 창녕군 영산면 서리 535번지자동차 엔진용 신품 부품 제조업 외 1 종자동차엔진부품,태양력발전업
순번회사명대표자명전화번호팩스번호공장대표주소(도로명)업종명생산품
481482농업회사법인 주식회사 해드림축산물공판장엄홍주055-533-1846055-533-1842경상남도 창녕군 대지면 효정리 390번지 외 7필지육류 도축업(가금류 제외) 외 1 종축산물가공
482483농업회사법인 호신농산(주)김종열055-536-8051055-536-8051경상남도 창녕군 계성면 새못길 12 외 3필지천연 및 혼합조제 조미료 제조업고춧가루
483484부경본가이윤호<NA>055-532-8859경상남도 창녕군 대합면 모전로 260기타 과실ㆍ채소 가공 및 저장 처리업깐마늘
484485브릭앤비 주식회사김상훈055-536-8118<NA>경상남도 창녕군 도천면 적말길 53그 외 기타 달리 분류되지 않은 운송장비 제조업 외 1 종열교환기
485486비엘코오퍼레이션임재훈 외 1명055-532-3953<NA>경상남도 창녕군 대합면 대합산업단지로 22-31그 외 자동차용 신품 부품 제조업자동차 부품
486487엘에스테크이성찬055-532-4256<NA>경상남도 창녕군 대지면 대지농공단지길 24-32농업 및 임업용 기계 제조업농기계(작업기)부품-백호, 그라플, 파레트포크
487488오복초정김주만<NA><NA>경상남도 창녕군 대지면 학동길 13-9식초, 발효 및 화학 조미료 제조업양파식초,현미식초
488489윤진푸드권경숙055-536-7471055-536-7472경상남도 창녕군 영산면 영산월령로 414-16육류 기타 가공 및 저장처리업 (가금류 제외) 외 1 종돈까스
489490정헌건설 주식회사이상봉055-806-8067055-806-8068경상남도 창녕군 남지읍 남지공단길 11금속 문, 창, 셔터 및 관련제품 제조업금속, 문, 창, 셔터 및 관련 제품
490491필드마스터(주)최태식055-521-9461055-521-9465경상남도 창녕군, 덕곡안길 8-36 (도천면) 외 2필지그 외 기타 플라스틱 제품 제조업인조잔디(건조시설 제외)