Overview

Dataset statistics

Number of variables8
Number of observations487
Missing cells230
Missing cells (%)5.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory31.0 KiB
Average record size in memory65.3 B

Variable types

Numeric1
Text7

Dataset

Description경상남도 창녕군 기업체(업체명, 주요생산품 등) 정보 제공, 기업체 현황, 기업 생산품, 연락처, 주소 등 정보 제공
Author경상남도 창녕군
URLhttps://www.data.go.kr/data/3077001/fileData.do

Alerts

전화번호 has 84 (17.2%) missing valuesMissing
팩스번호 has 146 (30.0%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:58:49.928653
Analysis finished2023-12-12 14:58:51.115844
Duration1.19 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct487
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean244
Minimum1
Maximum487
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 KiB
2023-12-12T23:58:51.202046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile25.3
Q1122.5
median244
Q3365.5
95-th percentile462.7
Maximum487
Range486
Interquartile range (IQR)243

Descriptive statistics

Standard deviation140.72905
Coefficient of variation (CV)0.57675842
Kurtosis-1.2
Mean244
Median Absolute Deviation (MAD)122
Skewness0
Sum118828
Variance19804.667
MonotonicityStrictly increasing
2023-12-12T23:58:51.353203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
336 1
 
0.2%
334 1
 
0.2%
333 1
 
0.2%
332 1
 
0.2%
331 1
 
0.2%
330 1
 
0.2%
329 1
 
0.2%
328 1
 
0.2%
327 1
 
0.2%
Other values (477) 477
97.9%
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 (%)
487 1
0.2%
486 1
0.2%
485 1
0.2%
484 1
0.2%
483 1
0.2%
482 1
0.2%
481 1
0.2%
480 1
0.2%
479 1
0.2%
478 1
0.2%

회사명
Text

Distinct465
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T23:58:51.606759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length7.2854209
Min length2

Characters and Unicode

Total characters3548
Distinct characters323
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

Unique446 ?
Unique (%)91.6%

Sample

1st row넥센타이어(주) 창녕공장
2nd row(주)세아베스틸
3rd row보그워너창녕 유한책임회사
4th row(주)디케이오스텍 창녕공장
5th row(주)센트랄 영산공장
ValueCountFrequency (%)
주식회사 20
 
3.6%
농업회사법인 13
 
2.3%
창녕공장 9
 
1.6%
영농조합법인 7
 
1.3%
주)가야이에스씨 4
 
0.7%
주)센트랄 3
 
0.5%
주)센트랄씨엠에스 3
 
0.5%
보성열처리(주 2
 
0.4%
주)디엔 2
 
0.4%
효창산업 2
 
0.4%
Other values (473) 491
88.3%
2023-12-12T23:58:52.042969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 326
 
9.2%
) 304
 
8.6%
( 303
 
8.5%
이 86
 
2.4%
업 85
 
2.4%
스 74
 
2.1%
70
 
2.0%
사 63
 
1.8%
에 60
 
1.7%
산 59
 
1.7%
Other values (313) 2118
59.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2801
78.9%
Close Punctuation 305
 
8.6%
Open Punctuation 304
 
8.6%
Space Separator 70
 
2.0%
Uppercase Letter 35
 
1.0%
Other Punctuation 14
 
0.4%
Decimal Number 8
 
0.2%
Lowercase Letter 7
 
0.2%
Dash Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 326
 
11.6%
이 86
 
3.1%
업 85
 
3.0%
스 74
 
2.6%
사 63
 
2.2%
에 60
 
2.1%
산 59
 
2.1%
식 54
 
1.9%
회 50
 
1.8%
공 49
 
1.7%
Other values (278) 1895
67.7%
Uppercase Letter
ValueCountFrequency (%)
S 5
14.3%
E 3
 
8.6%
P 3
 
8.6%
G 3
 
8.6%
N 3
 
8.6%
L 2
 
5.7%
T 2
 
5.7%
D 2
 
5.7%
K 2
 
5.7%
J 2
 
5.7%
Other values (8) 8
22.9%
Lowercase Letter
ValueCountFrequency (%)
u 2
28.6%
n 1
14.3%
a 1
14.3%
e 1
14.3%
r 1
14.3%
t 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 4
50.0%
1 3
37.5%
3 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 304
99.7%
] 1
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 303
99.7%
[ 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
. 11
78.6%
& 3
 
21.4%
Space Separator
ValueCountFrequency (%)
70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2801
78.9%
Common 705
 
19.9%
Latin 42
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 326
 
11.6%
이 86
 
3.1%
업 85
 
3.0%
스 74
 
2.6%
사 63
 
2.2%
에 60
 
2.1%
산 59
 
2.1%
식 54
 
1.9%
회 50
 
1.8%
공 49
 
1.7%
Other values (278) 1895
67.7%
Latin
ValueCountFrequency (%)
S 5
 
11.9%
E 3
 
7.1%
P 3
 
7.1%
G 3
 
7.1%
N 3
 
7.1%
L 2
 
4.8%
T 2
 
4.8%
D 2
 
4.8%
u 2
 
4.8%
K 2
 
4.8%
Other values (14) 15
35.7%
Common
ValueCountFrequency (%)
) 304
43.1%
( 303
43.0%
70
 
9.9%
. 11
 
1.6%
2 4
 
0.6%
- 4
 
0.6%
& 3
 
0.4%
1 3
 
0.4%
3 1
 
0.1%
[ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2801
78.9%
ASCII 747
 
21.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 326
 
11.6%
이 86
 
3.1%
업 85
 
3.0%
스 74
 
2.6%
사 63
 
2.2%
에 60
 
2.1%
산 59
 
2.1%
식 54
 
1.9%
회 50
 
1.8%
공 49
 
1.7%
Other values (278) 1895
67.7%
ASCII
ValueCountFrequency (%)
) 304
40.7%
( 303
40.6%
70
 
9.4%
. 11
 
1.5%
S 5
 
0.7%
2 4
 
0.5%
- 4
 
0.5%
E 3
 
0.4%
P 3
 
0.4%
G 3
 
0.4%
Other values (25) 37
 
5.0%

대표자명
Text

Distinct436
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T23:58:52.319494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length3.1827515
Min length2

Characters and Unicode

Total characters1550
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

Unique396 ?
Unique (%)81.3%

Sample

1st row강호찬
2nd row김철희
3rd row김동희
4th row김학규
5th row강태룡, 윤용호
ValueCountFrequency (%)
황용주 5
 
1.0%
김종열 4
 
0.8%
윤병국 4
 
0.8%
이상봉 3
 
0.6%
김병준 3
 
0.6%
남지곤 3
 
0.6%
권혁지 3
 
0.6%
강동래 2
 
0.4%
이진호 2
 
0.4%
권대용 2
 
0.4%
Other values (435) 468
93.8%
2023-12-12T23:58:52.698493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 110
 
7.1%
이 83
 
5.4%
영 58
 
3.7%
정 48
 
3.1%
박 37
 
2.4%
진 32
 
2.1%
호 31
 
2.0%
용 27
 
1.7%
수 26
 
1.7%
현 24
 
1.5%
Other values (168) 1074
69.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1518
97.9%
Other Punctuation 17
 
1.1%
Space Separator 13
 
0.8%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 110
 
7.2%
이 83
 
5.5%
영 58
 
3.8%
정 48
 
3.2%
박 37
 
2.4%
진 32
 
2.1%
호 31
 
2.0%
용 27
 
1.8%
수 26
 
1.7%
현 24
 
1.6%
Other values (164) 1042
68.6%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1518
97.9%
Common 32
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 110
 
7.2%
이 83
 
5.5%
영 58
 
3.8%
정 48
 
3.2%
박 37
 
2.4%
진 32
 
2.1%
호 31
 
2.0%
용 27
 
1.8%
수 26
 
1.7%
현 24
 
1.6%
Other values (164) 1042
68.6%
Common
ValueCountFrequency (%)
, 17
53.1%
13
40.6%
1 1
 
3.1%
2 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1518
97.9%
ASCII 32
 
2.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 110
 
7.2%
이 83
 
5.5%
영 58
 
3.8%
정 48
 
3.2%
박 37
 
2.4%
진 32
 
2.1%
호 31
 
2.0%
용 27
 
1.8%
수 26
 
1.7%
현 24
 
1.6%
Other values (164) 1042
68.6%
ASCII
ValueCountFrequency (%)
, 17
53.1%
13
40.6%
1 1
 
3.1%
2 1
 
3.1%

전화번호
Text

MISSING 

Distinct374
Distinct (%)92.8%
Missing84
Missing (%)17.2%
Memory size3.9 KiB
2023-12-12T23:58:52.925645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.009926
Min length9

Characters and Unicode

Total characters4840
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

Unique347 ?
Unique (%)86.1%

Sample

1st row055-370-5114
2nd row055-530-8500
3rd row055-520-2000
4th row055-521-9091
5th row055-520-3000
ValueCountFrequency (%)
055-532-0080 4
 
1.0%
055-521-3381 2
 
0.5%
055-532-4460 2
 
0.5%
055-536-7200 2
 
0.5%
055-532-6534 2
 
0.5%
055-521-8051 2
 
0.5%
055-536-8866 2
 
0.5%
070-7708-7727 2
 
0.5%
055-521-4590 2
 
0.5%
055-343-7511 2
 
0.5%
Other values (364) 381
94.5%
2023-12-12T23:58:53.277236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1242
25.7%
- 805
16.6%
0 718
14.8%
3 485
 
10.0%
2 399
 
8.2%
1 311
 
6.4%
6 231
 
4.8%
8 189
 
3.9%
7 187
 
3.9%
4 144
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4035
83.4%
Dash Punctuation 805
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1242
30.8%
0 718
17.8%
3 485
 
12.0%
2 399
 
9.9%
1 311
 
7.7%
6 231
 
5.7%
8 189
 
4.7%
7 187
 
4.6%
4 144
 
3.6%
9 129
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 805
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4840
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1242
25.7%
- 805
16.6%
0 718
14.8%
3 485
 
10.0%
2 399
 
8.2%
1 311
 
6.4%
6 231
 
4.8%
8 189
 
3.9%
7 187
 
3.9%
4 144
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4840
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1242
25.7%
- 805
16.6%
0 718
14.8%
3 485
 
10.0%
2 399
 
8.2%
1 311
 
6.4%
6 231
 
4.8%
8 189
 
3.9%
7 187
 
3.9%
4 144
 
3.0%

팩스번호
Text

MISSING 

Distinct320
Distinct (%)93.8%
Missing146
Missing (%)30.0%
Memory size3.9 KiB
2023-12-12T23:58:53.536426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.035191
Min length12

Characters and Unicode

Total characters4104
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

Unique302 ?
Unique (%)88.6%

Sample

1st row055-386-8962
2nd row055-530-8543
3rd row055-520-2094
4th row051-727-7077
5th row070-4275-1267
ValueCountFrequency (%)
055-327-8102 3
 
0.9%
055-532-7933 3
 
0.9%
055-536-8051 3
 
0.9%
055-533-5603 2
 
0.6%
055-536-9941 2
 
0.6%
055-532-6538 2
 
0.6%
055-533-5264 2
 
0.6%
055-532-0958 2
 
0.6%
055-532-3902 2
 
0.6%
055-532-2942 2
 
0.6%
Other values (310) 318
93.3%
2023-12-12T23:58:53.956504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 1028
25.0%
- 682
16.6%
0 563
13.7%
3 434
10.6%
2 331
 
8.1%
1 225
 
5.5%
6 212
 
5.2%
7 174
 
4.2%
8 174
 
4.2%
4 146
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3422
83.4%
Dash Punctuation 682
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1028
30.0%
0 563
16.5%
3 434
12.7%
2 331
 
9.7%
1 225
 
6.6%
6 212
 
6.2%
7 174
 
5.1%
8 174
 
5.1%
4 146
 
4.3%
9 135
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 682
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4104
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 1028
25.0%
- 682
16.6%
0 563
13.7%
3 434
10.6%
2 331
 
8.1%
1 225
 
5.5%
6 212
 
5.2%
7 174
 
4.2%
8 174
 
4.2%
4 146
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4104
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 1028
25.0%
- 682
16.6%
0 563
13.7%
3 434
10.6%
2 331
 
8.1%
1 225
 
5.5%
6 212
 
5.2%
7 174
 
4.2%
8 174
 
4.2%
4 146
 
3.6%

공장대표주소(도로명)
Text

Distinct460
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T23:58:54.238279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length26.094456
Min length18

Characters and Unicode

Total characters12708
Distinct characters180
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

Unique436 ?
Unique (%)89.5%

Sample

1st row경상남도 창녕군 대합면 대동월포로 291, 넥센타이어(주) 창녕공장(이방리 992번지)
2nd row경상남도 창녕군 대합면 대합산업단지로 100, (주)세아베스틸
3rd row경상남도 창녕군 계성면 명리길 78 외 4필지
4th row경상남도 창녕군 장마면 초곡길 235-24 (총 2 필지) 외 1필지
5th row경상남도 창녕군 영산면 서리상촌길 307-106
ValueCountFrequency (%)
경상남도 487
 
16.3%
창녕군 487
 
16.3%
외 189
 
6.3%
대합면 135
 
4.5%
영산면 81
 
2.7%
1필지 72
 
2.4%
계성면 50
 
1.7%
도천면 47
 
1.6%
필지 46
 
1.5%
총 46
 
1.5%
Other values (576) 1341
45.0%
2023-12-12T23:58:55.288862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2494
19.6%
도 560
 
4.4%
남 541
 
4.3%
창 539
 
4.2%
녕 534
 
4.2%
상 515
 
4.1%
경 508
 
4.0%
지 493
 
3.9%
군 487
 
3.8%
면 438
 
3.4%
Other values (170) 5599
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7958
62.6%
Space Separator 2494
 
19.6%
Decimal Number 1914
 
15.1%
Dash Punctuation 204
 
1.6%
Open Punctuation 63
 
0.5%
Close Punctuation 63
 
0.5%
Other Punctuation 11
 
0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 560
 
7.0%
남 541
 
6.8%
창 539
 
6.8%
녕 534
 
6.7%
상 515
 
6.5%
경 508
 
6.4%
지 493
 
6.2%
군 487
 
6.1%
면 438
 
5.5%
대 284
 
3.6%
Other values (154) 3059
38.4%
Decimal Number
ValueCountFrequency (%)
1 391
20.4%
2 276
14.4%
3 267
13.9%
4 194
10.1%
7 148
 
7.7%
6 143
 
7.5%
5 140
 
7.3%
9 129
 
6.7%
0 114
 
6.0%
8 112
 
5.9%
Space Separator
ValueCountFrequency (%)
2494
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 204
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7958
62.6%
Common 4749
37.4%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 560
 
7.0%
남 541
 
6.8%
창 539
 
6.8%
녕 534
 
6.7%
상 515
 
6.5%
경 508
 
6.4%
지 493
 
6.2%
군 487
 
6.1%
면 438
 
5.5%
대 284
 
3.6%
Other values (154) 3059
38.4%
Common
ValueCountFrequency (%)
2494
52.5%
1 391
 
8.2%
2 276
 
5.8%
3 267
 
5.6%
- 204
 
4.3%
4 194
 
4.1%
7 148
 
3.1%
6 143
 
3.0%
5 140
 
2.9%
9 129
 
2.7%
Other values (5) 363
 
7.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7958
62.6%
ASCII 4750
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2494
52.5%
1 391
 
8.2%
2 276
 
5.8%
3 267
 
5.6%
- 204
 
4.3%
4 194
 
4.1%
7 148
 
3.1%
6 143
 
3.0%
5 140
 
2.9%
9 129
 
2.7%
Other values (6) 364
 
7.7%
Hangul
ValueCountFrequency (%)
도 560
 
7.0%
남 541
 
6.8%
창 539
 
6.8%
녕 534
 
6.7%
상 515
 
6.5%
경 508
 
6.4%
지 493
 
6.2%
군 487
 
6.1%
면 438
 
5.5%
대 284
 
3.6%
Other values (154) 3059
38.4%

업종명
Text

Distinct225
Distinct (%)46.2%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T23:58:55.745808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length24
Mean length18.069815
Min length5

Characters and Unicode

Total characters8800
Distinct characters254
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

Unique138 ?
Unique (%)28.3%

Sample

1st row타이어 및 튜브 제조업
2nd row제강업 외 1 종
3rd row자동차 엔진용 신품 부품 제조업 외 1 종
4th row그 외 자동차용 신품 부품 제조업 외 4 종
5th row그 외 자동차용 신품 부품 제조업 외 4 종
ValueCountFrequency (%)
제조업 404
 
13.9%
외 298
 
10.2%
종 216
 
7.4%
및 197
 
6.8%
1 125
 
4.3%
기타 116
 
4.0%
그 82
 
2.8%
금속 59
 
2.0%
신품 54
 
1.9%
부품 54
 
1.9%
Other values (323) 1303
44.8%
2023-12-12T23:58:56.486385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2421
27.5%
제 535
 
6.1%
조 534
 
6.1%
업 510
 
5.8%
외 311
 
3.5%
품 236
 
2.7%
종 220
 
2.5%
및 199
 
2.3%
기 198
 
2.2%
1 135
 
1.5%
Other values (244) 3501
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6050
68.8%
Space Separator 2421
27.5%
Decimal Number 226
 
2.6%
Other Punctuation 77
 
0.9%
Close Punctuation 13
 
0.1%
Open Punctuation 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 535
 
8.8%
조 534
 
8.8%
업 510
 
8.4%
외 311
 
5.1%
품 236
 
3.9%
종 220
 
3.6%
및 199
 
3.3%
기 198
 
3.3%
용 133
 
2.2%
타 129
 
2.1%
Other values (231) 3045
50.3%
Decimal Number
ValueCountFrequency (%)
1 135
59.7%
3 37
 
16.4%
2 33
 
14.6%
4 12
 
5.3%
6 5
 
2.2%
0 2
 
0.9%
7 1
 
0.4%
5 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 76
98.7%
. 1
 
1.3%
Space Separator
ValueCountFrequency (%)
2421
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6050
68.8%
Common 2750
31.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 535
 
8.8%
조 534
 
8.8%
업 510
 
8.4%
외 311
 
5.1%
품 236
 
3.9%
종 220
 
3.6%
및 199
 
3.3%
기 198
 
3.3%
용 133
 
2.2%
타 129
 
2.1%
Other values (231) 3045
50.3%
Common
ValueCountFrequency (%)
2421
88.0%
1 135
 
4.9%
, 76
 
2.8%
3 37
 
1.3%
2 33
 
1.2%
) 13
 
0.5%
( 13
 
0.5%
4 12
 
0.4%
6 5
 
0.2%
0 2
 
0.1%
Other values (3) 3
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6040
68.6%
ASCII 2750
31.2%
Compat Jamo 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2421
88.0%
1 135
 
4.9%
, 76
 
2.8%
3 37
 
1.3%
2 33
 
1.2%
) 13
 
0.5%
( 13
 
0.5%
4 12
 
0.4%
6 5
 
0.2%
0 2
 
0.1%
Other values (3) 3
 
0.1%
Hangul
ValueCountFrequency (%)
제 535
 
8.9%
조 534
 
8.8%
업 510
 
8.4%
외 311
 
5.1%
품 236
 
3.9%
종 220
 
3.6%
및 199
 
3.3%
기 198
 
3.3%
용 133
 
2.2%
타 129
 
2.1%
Other values (230) 3035
50.2%
Compat Jamo
ValueCountFrequency (%)
ㆍ 10
100.0%

생산품
Text

Distinct435
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Memory size3.9 KiB
2023-12-12T23:58:56.802019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length30
Mean length8.3039014
Min length1

Characters and Unicode

Total characters4044
Distinct characters457
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

Unique409 ?
Unique (%)84.0%

Sample

1st row타이어 및 튜브
2nd row특수강
3rd row내연기관용전장품(Starter,Alternator)
4th row자동차부품
5th row자동차 조향 및 현가장치 부품
ValueCountFrequency (%)
및 22
 
2.7%
자동차부품 15
 
1.8%
철구조물 14
 
1.7%
등 13
 
1.6%
자동차 12
 
1.5%
부품 8
 
1.0%
선박용 6
 
0.7%
알루미늄 6
 
0.7%
산업용 5
 
0.6%
배전반 5
 
0.6%
Other values (597) 705
86.9%
2023-12-12T23:58:57.352220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
326
 
8.1%
, 209
 
5.2%
품 102
 
2.5%
조 86
 
2.1%
자 81
 
2.0%
부 78
 
1.9%
기 73
 
1.8%
차 62
 
1.5%
동 60
 
1.5%
용 59
 
1.5%
Other values (447) 2908
71.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3244
80.2%
Space Separator 326
 
8.1%
Other Punctuation 218
 
5.4%
Uppercase Letter 105
 
2.6%
Lowercase Letter 83
 
2.1%
Close Punctuation 32
 
0.8%
Open Punctuation 32
 
0.8%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 102
 
3.1%
조 86
 
2.7%
자 81
 
2.5%
부 78
 
2.4%
기 73
 
2.3%
차 62
 
1.9%
동 60
 
1.8%
용 59
 
1.8%
재 57
 
1.8%
장 57
 
1.8%
Other values (397) 2529
78.0%
Uppercase Letter
ValueCountFrequency (%)
P 12
11.4%
E 10
 
9.5%
S 9
 
8.6%
C 9
 
8.6%
H 8
 
7.6%
T 8
 
7.6%
R 7
 
6.7%
D 6
 
5.7%
O 5
 
4.8%
U 5
 
4.8%
Other values (11) 26
24.8%
Lowercase Letter
ValueCountFrequency (%)
e 10
12.0%
t 9
10.8%
p 9
10.8%
a 8
9.6%
r 8
9.6%
c 6
 
7.2%
l 5
 
6.0%
o 5
 
6.0%
n 4
 
4.8%
k 4
 
4.8%
Other values (9) 15
18.1%
Other Punctuation
ValueCountFrequency (%)
, 209
95.9%
. 4
 
1.8%
/ 4
 
1.8%
& 1
 
0.5%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
5 1
25.0%
Space Separator
ValueCountFrequency (%)
326
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3244
80.2%
Common 612
 
15.1%
Latin 188
 
4.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 102
 
3.1%
조 86
 
2.7%
자 81
 
2.5%
부 78
 
2.4%
기 73
 
2.3%
차 62
 
1.9%
동 60
 
1.8%
용 59
 
1.8%
재 57
 
1.8%
장 57
 
1.8%
Other values (397) 2529
78.0%
Latin
ValueCountFrequency (%)
P 12
 
6.4%
e 10
 
5.3%
E 10
 
5.3%
S 9
 
4.8%
C 9
 
4.8%
t 9
 
4.8%
p 9
 
4.8%
a 8
 
4.3%
H 8
 
4.3%
r 8
 
4.3%
Other values (30) 96
51.1%
Common
ValueCountFrequency (%)
326
53.3%
, 209
34.2%
) 32
 
5.2%
( 32
 
5.2%
. 4
 
0.7%
/ 4
 
0.7%
2 2
 
0.3%
1 1
 
0.2%
5 1
 
0.2%
& 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3244
80.2%
ASCII 800
 
19.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
326
40.8%
, 209
26.1%
) 32
 
4.0%
( 32
 
4.0%
P 12
 
1.5%
e 10
 
1.2%
E 10
 
1.2%
S 9
 
1.1%
C 9
 
1.1%
t 9
 
1.1%
Other values (40) 142
17.8%
Hangul
ValueCountFrequency (%)
품 102
 
3.1%
조 86
 
2.7%
자 81
 
2.5%
부 78
 
2.4%
기 73
 
2.3%
차 62
 
1.9%
동 60
 
1.8%
용 59
 
1.8%
재 57
 
1.8%
장 57
 
1.8%
Other values (397) 2529
78.0%

Interactions

2023-12-12T23:58:50.660890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T23:58:50.777981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:58:50.949645image/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.
2023-12-12T23:58:51.054075image/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
12(주)세아베스틸김철희055-530-8500055-530-8543경상남도 창녕군 대합면 대합산업단지로 100, (주)세아베스틸제강업 외 1 종특수강
23보그워너창녕 유한책임회사김동희055-520-2000055-520-2094경상남도 창녕군 계성면 명리길 78 외 4필지자동차 엔진용 신품 부품 제조업 외 1 종내연기관용전장품(Starter,Alternator)
34(주)디케이오스텍 창녕공장김학규055-521-9091051-727-7077경상남도 창녕군 장마면 초곡길 235-24 (총 2 필지) 외 1필지그 외 자동차용 신품 부품 제조업 외 4 종자동차부품
45(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
56(주)SUN&L 창녕공장서성교055-294-8801<NA>경상남도 창녕군 도천면 일리 418 외 3필지포장용 플라스틱 성형용기 제조업 외 1 종생활용품 플라스틱 pump&spray
67(주)센트랄 영산AM공장윤용호, 이호영055-520-0200055-520-0297경상남도 창녕군 영산면 서리상촌길 307-50그 외 자동차용 신품 부품 제조업 외 3 종자동차부품
78(주)가야이에스씨윤병국055-532-0080055-532-8901경상남도 창녕군 대합면 이방대합로 1132 (총 5 필지) 외 8필지기타 구조용 금속제품 제조업철구조물, BH제작, 금속부착물 외
89(주)지앤박용주055-536-9050055-536-9050경상남도 창녕군 영산면 서리상촌길 307-21그 외 자동차용 신품 부품 제조업 외 4 종연료필터 히터 및 센서
910구인전자(주)최주봉055-526-6040055-526-6044경상남도 창녕군 남지읍 마산리 745-1번지그 외 기타 전자부품 제조업 외 1 종전자관
순번회사명대표자명전화번호팩스번호공장대표주소(도로명)업종명생산품
477478필드마스터(주)최태식055-521-9461055-532-7221경상남도 창녕군 도천면 덕곡안길 8-36 (도천면) 외 2필지강주물 주조업인조잔디(건조시설 제외)
478479(주)한본산업권대용055-532-1700055-585-8867경상남도 창녕군 대합면 수장퇴산로 78 외 3필지기타 목재가구 제조업 외 2 종콘크리트타일,기와,벽돌 및블록
479480부경본가이윤호<NA>055-532-3705경상남도 창녕군 대합면 모전로 260과실 및 그 외 채소 절임식품 제조업깐마늘
480481(주)씨엠캐스팅테크놀러지이학원055-532-1321<NA>경상남도 창녕군 대합면 대합산업단지로 68-43콘크리트 타일, 기와, 벽돌 및 블록 제조업밸브용 주물
481482농업회사법인 영남(주)황용주055-532-3260055-533-1842경상남도 창녕군 대지면 효정리 390번지 외 7필지육류 도축업(가금류 제외) 외 1 종축산물가공
482483(주)디.엠테크진동길<NA>055-536-8051경상남도 창녕군 대지면 학성세거리길 252천연 및 혼합조제 조미료 제조업시멘트착색용안료
483484오복초정김주만<NA>055-532-8859경상남도 창녕군 대지면 학동길 13-9기타 과실ㆍ채소 가공 및 저장 처리업양파식초,현미식초
484485(주)키친캐비넷장희정, 이창혁055-533-6800<NA>경상남도 창녕군 대지면 도양새우등길 79식초, 발효 및 화학 조미료 제조업반조리식품
485486(주)진응유영주<NA>055-536-7472경상남도 창녕군 고암면 원촌어은길 154 외 1필지육류 기타 가공 및 저장처리업 (가금류 제외) 외 1 종이동식한옥목조주택,데크제작및설치,수중(하천)보
486487농업회사법인 호신농산(주)김종열055-536-8051055-521-9465경상남도 창녕군 계성면 새못길 12 외 3필지그 외 기타 플라스틱 제품 제조업고춧가루