Overview

Dataset statistics

Number of variables9
Number of observations716
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory51.2 KiB
Average record size in memory73.2 B

Variable types

Numeric1
Text7
Categorical1

Dataset

Description전북특별자치도 김제시의 제조업공장현황입니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=1&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15034975

Alerts

순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 02:29:55.087459
Analysis finished2024-03-14 02:29:56.068802
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct716
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean358.5
Minimum1
Maximum716
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.4 KiB
2024-03-14T11:29:56.125100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile36.75
Q1179.75
median358.5
Q3537.25
95-th percentile680.25
Maximum716
Range715
Interquartile range (IQR)357.5

Descriptive statistics

Standard deviation206.83568
Coefficient of variation (CV)0.57694751
Kurtosis-1.2
Mean358.5
Median Absolute Deviation (MAD)179
Skewness0
Sum256686
Variance42781
MonotonicityStrictly increasing
2024-03-14T11:29:56.252542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
494 1
 
0.1%
474 1
 
0.1%
475 1
 
0.1%
476 1
 
0.1%
477 1
 
0.1%
478 1
 
0.1%
479 1
 
0.1%
480 1
 
0.1%
481 1
 
0.1%
Other values (706) 706
98.6%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
716 1
0.1%
715 1
0.1%
714 1
0.1%
713 1
0.1%
712 1
0.1%
711 1
0.1%
710 1
0.1%
709 1
0.1%
708 1
0.1%
707 1
0.1%

회사명
Text

Distinct701
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-14T11:29:56.548526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length7.797486
Min length2

Characters and Unicode

Total characters5583
Distinct characters383
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique690 ?
Unique (%)96.4%

Sample

1st row(유) 대영중기
2nd row(유) 모던아트
3rd row(유) 시온영광포장
4th row(유) 이젠365
5th row(유) 한푸드
ValueCountFrequency (%)
주식회사 87
 
9.6%
유한회사 35
 
3.9%
농업회사법인 14
 
1.5%
김제지점 7
 
0.8%
주 6
 
0.7%
영농조합법인 5
 
0.6%
유 5
 
0.6%
주)호룡 4
 
0.4%
금전기업(주 3
 
0.3%
농업회사법인(주)사조화인코리아 3
 
0.3%
Other values (717) 735
81.3%
2024-03-14T11:29:56.956020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 379
 
6.8%
( 377
 
6.8%
주 367
 
6.6%
191
 
3.4%
사 187
 
3.3%
회 164
 
2.9%
유 163
 
2.9%
업 156
 
2.8%
이 115
 
2.1%
산 114
 
2.0%
Other values (373) 3370
60.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4557
81.6%
Close Punctuation 379
 
6.8%
Open Punctuation 377
 
6.8%
Space Separator 191
 
3.4%
Uppercase Letter 60
 
1.1%
Decimal Number 11
 
0.2%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 367
 
8.1%
사 187
 
4.1%
회 164
 
3.6%
유 163
 
3.6%
업 156
 
3.4%
이 115
 
2.5%
산 114
 
2.5%
식 111
 
2.4%
스 87
 
1.9%
농 86
 
1.9%
Other values (343) 3007
66.0%
Uppercase Letter
ValueCountFrequency (%)
N 8
13.3%
E 7
11.7%
G 5
 
8.3%
C 5
 
8.3%
S 5
 
8.3%
K 4
 
6.7%
J 4
 
6.7%
O 3
 
5.0%
T 3
 
5.0%
H 3
 
5.0%
Other values (9) 13
21.7%
Decimal Number
ValueCountFrequency (%)
2 6
54.5%
5 2
 
18.2%
1 1
 
9.1%
3 1
 
9.1%
6 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
. 3
37.5%
, 3
37.5%
& 2
25.0%
Close Punctuation
ValueCountFrequency (%)
) 379
100.0%
Open Punctuation
ValueCountFrequency (%)
( 377
100.0%
Space Separator
ValueCountFrequency (%)
191
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4557
81.6%
Common 966
 
17.3%
Latin 60
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 367
 
8.1%
사 187
 
4.1%
회 164
 
3.6%
유 163
 
3.6%
업 156
 
3.4%
이 115
 
2.5%
산 114
 
2.5%
식 111
 
2.4%
스 87
 
1.9%
농 86
 
1.9%
Other values (343) 3007
66.0%
Latin
ValueCountFrequency (%)
N 8
13.3%
E 7
11.7%
G 5
 
8.3%
C 5
 
8.3%
S 5
 
8.3%
K 4
 
6.7%
J 4
 
6.7%
O 3
 
5.0%
T 3
 
5.0%
H 3
 
5.0%
Other values (9) 13
21.7%
Common
ValueCountFrequency (%)
) 379
39.2%
( 377
39.0%
191
19.8%
2 6
 
0.6%
. 3
 
0.3%
, 3
 
0.3%
5 2
 
0.2%
& 2
 
0.2%
1 1
 
0.1%
3 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4557
81.6%
ASCII 1026
 
18.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 379
36.9%
( 377
36.7%
191
18.6%
N 8
 
0.8%
E 7
 
0.7%
2 6
 
0.6%
G 5
 
0.5%
C 5
 
0.5%
S 5
 
0.5%
K 4
 
0.4%
Other values (20) 39
 
3.8%
Hangul
ValueCountFrequency (%)
주 367
 
8.1%
사 187
 
4.1%
회 164
 
3.6%
유 163
 
3.6%
업 156
 
3.4%
이 115
 
2.5%
산 114
 
2.5%
식 111
 
2.4%
스 87
 
1.9%
농 86
 
1.9%
Other values (343) 3007
66.0%

단지명
Categorical

Distinct11
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
데이터 미집계
444 
김제봉황농공단지
 
42
김제순동지방산업단지
 
42
김제서흥농공단지
 
39
김제지평선일반산업단지
 
34
Other values (6)
115 

Length

Max length11
Median length7
Mean length7.6396648
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row데이터 미집계
2nd row데이터 미집계
3rd row데이터 미집계
4th row데이터 미집계
5th row김제봉황농공단지

Common Values

ValueCountFrequency (%)
데이터 미집계 444
62.0%
김제봉황농공단지 42
 
5.9%
김제순동지방산업단지 42
 
5.9%
김제서흥농공단지 39
 
5.4%
김제지평선일반산업단지 34
 
4.7%
김제월촌농공단지 26
 
3.6%
김제만경농공단지 22
 
3.1%
김제백구농공단지 21
 
2.9%
김제자유무역지역 18
 
2.5%
김제대동농공단지 17
 
2.4%

Length

2024-03-14T11:29:57.091535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
데이터 444
38.3%
미집계 444
38.3%
김제봉황농공단지 42
 
3.6%
김제순동지방산업단지 42
 
3.6%
김제서흥농공단지 39
 
3.4%
김제지평선일반산업단지 34
 
2.9%
김제월촌농공단지 26
 
2.2%
김제만경농공단지 22
 
1.9%
김제백구농공단지 21
 
1.8%
김제자유무역지역 18
 
1.6%
Other values (2) 28
 
2.4%

대표자명
Text

Distinct658
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-14T11:29:57.363636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.0851955
Min length2

Characters and Unicode

Total characters2209
Distinct characters196
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

Unique609 ?
Unique (%)85.1%

Sample

1st row이상열
2nd row박인수
3rd row한기수
4th row안정립
5th row정치웅
ValueCountFrequency (%)
박장현 5
 
0.7%
이종화 3
 
0.4%
이철근 3
 
0.4%
이상환 3
 
0.4%
이창주 3
 
0.4%
1명 3
 
0.4%
김희자 3
 
0.4%
홍종서 3
 
0.4%
홍종식 3
 
0.4%
이근호 3
 
0.4%
Other values (655) 696
95.6%
2024-03-14T11:29:57.759132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 155
 
7.0%
이 113
 
5.1%
정 64
 
2.9%
영 61
 
2.8%
박 59
 
2.7%
성 54
 
2.4%
최 49
 
2.2%
수 46
 
2.1%
재 34
 
1.5%
종 33
 
1.5%
Other values (186) 1541
69.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2183
98.8%
Space Separator 12
 
0.5%
Other Punctuation 11
 
0.5%
Decimal Number 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 155
 
7.1%
이 113
 
5.2%
정 64
 
2.9%
영 61
 
2.8%
박 59
 
2.7%
성 54
 
2.5%
최 49
 
2.2%
수 46
 
2.1%
재 34
 
1.6%
종 33
 
1.5%
Other values (182) 1515
69.4%
Other Punctuation
ValueCountFrequency (%)
, 9
81.8%
. 2
 
18.2%
Space Separator
ValueCountFrequency (%)
12
100.0%
Decimal Number
ValueCountFrequency (%)
1 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2183
98.8%
Common 26
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 155
 
7.1%
이 113
 
5.2%
정 64
 
2.9%
영 61
 
2.8%
박 59
 
2.7%
성 54
 
2.5%
최 49
 
2.2%
수 46
 
2.1%
재 34
 
1.6%
종 33
 
1.5%
Other values (182) 1515
69.4%
Common
ValueCountFrequency (%)
12
46.2%
, 9
34.6%
1 3
 
11.5%
. 2
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2183
98.8%
ASCII 26
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 155
 
7.1%
이 113
 
5.2%
정 64
 
2.9%
영 61
 
2.8%
박 59
 
2.7%
성 54
 
2.5%
최 49
 
2.2%
수 46
 
2.1%
재 34
 
1.6%
종 33
 
1.5%
Other values (182) 1515
69.4%
ASCII
ValueCountFrequency (%)
12
46.2%
, 9
34.6%
1 3
 
11.5%
. 2
 
7.7%

전화번호
Text

Distinct592
Distinct (%)82.7%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-14T11:29:58.001079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length11.441341
Min length7

Characters and Unicode

Total characters8192
Distinct characters18
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

Unique553 ?
Unique (%)77.2%

Sample

1st row063-547-9004
2nd row063-547-1790
3rd row063-546-1665
4th row063-543-3663
5th row063-542-8883
ValueCountFrequency (%)
데이터 80
 
10.1%
미집계 80
 
10.1%
063-540-5555 4
 
0.5%
063-544-5353 3
 
0.4%
063-545-5660 3
 
0.4%
063-544-0000 3
 
0.4%
063-544-0702 3
 
0.4%
063-544-3666 3
 
0.4%
063-542-6614 2
 
0.3%
063-542-8263 2
 
0.3%
Other values (583) 613
77.0%
2024-03-14T11:29:58.371355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1272
15.5%
0 1044
12.7%
6 966
11.8%
3 961
11.7%
5 952
11.6%
4 903
11.0%
2 356
 
4.3%
7 355
 
4.3%
1 333
 
4.1%
8 311
 
3.8%
Other values (8) 739
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6360
77.6%
Dash Punctuation 1272
 
15.5%
Other Letter 480
 
5.9%
Space Separator 80
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1044
16.4%
6 966
15.2%
3 961
15.1%
5 952
15.0%
4 903
14.2%
2 356
 
5.6%
7 355
 
5.6%
1 333
 
5.2%
8 311
 
4.9%
9 179
 
2.8%
Other Letter
ValueCountFrequency (%)
이 80
16.7%
계 80
16.7%
집 80
16.7%
미 80
16.7%
터 80
16.7%
데 80
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 1272
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7712
94.1%
Hangul 480
 
5.9%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1272
16.5%
0 1044
13.5%
6 966
12.5%
3 961
12.5%
5 952
12.3%
4 903
11.7%
2 356
 
4.6%
7 355
 
4.6%
1 333
 
4.3%
8 311
 
4.0%
Other values (2) 259
 
3.4%
Hangul
ValueCountFrequency (%)
이 80
16.7%
계 80
16.7%
집 80
16.7%
미 80
16.7%
터 80
16.7%
데 80
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7712
94.1%
Hangul 480
 
5.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1272
16.5%
0 1044
13.5%
6 966
12.5%
3 961
12.5%
5 952
12.3%
4 903
11.7%
2 356
 
4.6%
7 355
 
4.6%
1 333
 
4.3%
8 311
 
4.0%
Other values (2) 259
 
3.4%
Hangul
ValueCountFrequency (%)
이 80
16.7%
계 80
16.7%
집 80
16.7%
미 80
16.7%
터 80
16.7%
데 80
16.7%

팩스번호
Text

Distinct476
Distinct (%)66.5%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-14T11:29:58.605878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length10.645251
Min length7

Characters and Unicode

Total characters7622
Distinct characters18
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

Unique437 ?
Unique (%)61.0%

Sample

1st row데이터 미집계
2nd row데이터 미집계
3rd row063-547-5310
4th row데이터 미집계
5th row063-542-8884
ValueCountFrequency (%)
데이터 194
 
21.3%
미집계 194
 
21.3%
063-547-1001 5
 
0.5%
063-543-2429 4
 
0.4%
063-546-0414 3
 
0.3%
063-547-9008 3
 
0.3%
063-544-9049 3
 
0.3%
063-547-8476 3
 
0.3%
063-545-6361 2
 
0.2%
063-546-0220 2
 
0.2%
Other values (467) 497
54.6%
2024-03-14T11:29:58.975716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1044
13.7%
0 809
10.6%
6 784
10.3%
3 772
10.1%
4 742
9.7%
5 729
9.6%
2 328
 
4.3%
7 304
 
4.0%
8 275
 
3.6%
1 269
 
3.5%
Other values (8) 1566
20.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5220
68.5%
Other Letter 1164
 
15.3%
Dash Punctuation 1044
 
13.7%
Space Separator 194
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 809
15.5%
6 784
15.0%
3 772
14.8%
4 742
14.2%
5 729
14.0%
2 328
6.3%
7 304
 
5.8%
8 275
 
5.3%
1 269
 
5.2%
9 208
 
4.0%
Other Letter
ValueCountFrequency (%)
이 194
16.7%
계 194
16.7%
집 194
16.7%
미 194
16.7%
터 194
16.7%
데 194
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 1044
100.0%
Space Separator
ValueCountFrequency (%)
194
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6458
84.7%
Hangul 1164
 
15.3%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1044
16.2%
0 809
12.5%
6 784
12.1%
3 772
12.0%
4 742
11.5%
5 729
11.3%
2 328
 
5.1%
7 304
 
4.7%
8 275
 
4.3%
1 269
 
4.2%
Other values (2) 402
 
6.2%
Hangul
ValueCountFrequency (%)
이 194
16.7%
계 194
16.7%
집 194
16.7%
미 194
16.7%
터 194
16.7%
데 194
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6458
84.7%
Hangul 1164
 
15.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1044
16.2%
0 809
12.5%
6 784
12.1%
3 772
12.0%
4 742
11.5%
5 729
11.3%
2 328
 
5.1%
7 304
 
4.7%
8 275
 
4.3%
1 269
 
4.2%
Other values (2) 402
 
6.2%
Hangul
ValueCountFrequency (%)
이 194
16.7%
계 194
16.7%
집 194
16.7%
미 194
16.7%
터 194
16.7%
데 194
16.7%

생산품
Text

Distinct620
Distinct (%)86.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-14T11:29:59.255091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length30
Mean length8.8868715
Min length1

Characters and Unicode

Total characters6363
Distinct characters528
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique575 ?
Unique (%)80.3%

Sample

1st row부품가공기계
2nd row커튼봉,커튼레일, 알루미늄 분체가공
3rd row골판지 상자
4th row소독기(의료,산업,가정용), 농업용분무기
5th row누룽지
ValueCountFrequency (%)
및 19
 
1.6%
등 16
 
1.4%
미집계 12
 
1.0%
데이터 12
 
1.0%
자동차 11
 
0.9%
석재가공품 10
 
0.9%
알루미늄 10
 
0.9%
쌀 9
 
0.8%
부품 9
 
0.8%
특장차 8
 
0.7%
Other values (854) 1053
90.1%
2024-03-14T11:29:59.619935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
457
 
7.2%
, 409
 
6.4%
기 146
 
2.3%
품 108
 
1.7%
장 101
 
1.6%
가 96
 
1.5%
차 95
 
1.5%
조 82
 
1.3%
스 77
 
1.2%
제 76
 
1.2%
Other values (518) 4716
74.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5112
80.3%
Space Separator 462
 
7.3%
Other Punctuation 433
 
6.8%
Uppercase Letter 235
 
3.7%
Close Punctuation 39
 
0.6%
Open Punctuation 39
 
0.6%
Lowercase Letter 32
 
0.5%
Decimal Number 9
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 146
 
2.9%
품 108
 
2.1%
장 101
 
2.0%
가 96
 
1.9%
차 95
 
1.9%
조 82
 
1.6%
스 77
 
1.5%
제 76
 
1.5%
자 74
 
1.4%
이 73
 
1.4%
Other values (465) 4184
81.8%
Uppercase Letter
ValueCountFrequency (%)
E 30
12.8%
L 28
11.9%
D 22
 
9.4%
P 20
 
8.5%
C 15
 
6.4%
R 14
 
6.0%
T 12
 
5.1%
S 12
 
5.1%
A 10
 
4.3%
I 9
 
3.8%
Other values (12) 63
26.8%
Lowercase Letter
ValueCountFrequency (%)
p 5
15.6%
e 4
12.5%
r 3
9.4%
a 3
9.4%
v 2
 
6.2%
l 2
 
6.2%
o 2
 
6.2%
k 2
 
6.2%
c 1
 
3.1%
d 1
 
3.1%
Other values (7) 7
21.9%
Decimal Number
ValueCountFrequency (%)
4 3
33.3%
3 2
22.2%
0 2
22.2%
1 1
 
11.1%
2 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 409
94.5%
. 16
 
3.7%
/ 6
 
1.4%
' 2
 
0.5%
Space Separator
ValueCountFrequency (%)
457
98.9%
　 5
 
1.1%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5112
80.3%
Common 984
 
15.5%
Latin 267
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 146
 
2.9%
품 108
 
2.1%
장 101
 
2.0%
가 96
 
1.9%
차 95
 
1.9%
조 82
 
1.6%
스 77
 
1.5%
제 76
 
1.5%
자 74
 
1.4%
이 73
 
1.4%
Other values (465) 4184
81.8%
Latin
ValueCountFrequency (%)
E 30
 
11.2%
L 28
 
10.5%
D 22
 
8.2%
P 20
 
7.5%
C 15
 
5.6%
R 14
 
5.2%
T 12
 
4.5%
S 12
 
4.5%
A 10
 
3.7%
I 9
 
3.4%
Other values (29) 95
35.6%
Common
ValueCountFrequency (%)
457
46.4%
, 409
41.6%
) 39
 
4.0%
( 39
 
4.0%
. 16
 
1.6%
/ 6
 
0.6%
　 5
 
0.5%
4 3
 
0.3%
3 2
 
0.2%
' 2
 
0.2%
Other values (4) 6
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5111
80.3%
ASCII 1246
 
19.6%
None 5
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
457
36.7%
, 409
32.8%
) 39
 
3.1%
( 39
 
3.1%
E 30
 
2.4%
L 28
 
2.2%
D 22
 
1.8%
P 20
 
1.6%
. 16
 
1.3%
C 15
 
1.2%
Other values (42) 171
 
13.7%
Hangul
ValueCountFrequency (%)
기 146
 
2.9%
품 108
 
2.1%
장 101
 
2.0%
가 96
 
1.9%
차 95
 
1.9%
조 82
 
1.6%
스 77
 
1.5%
제 76
 
1.5%
자 74
 
1.4%
이 73
 
1.4%
Other values (464) 4183
81.8%
None
ValueCountFrequency (%)
　 5
100.0%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

공장대표주소
Text

Distinct663
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-14T11:29:59.906367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length49
Mean length31.822626
Min length20

Characters and Unicode

Total characters22785
Distinct characters317
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique622 ?
Unique (%)86.9%

Sample

1st row전북특별자치도 김제시 백산면 하공로 433-159 ((유)대영중기) (총 2 필지)
2nd row전북특별자치도 김제시 금구면 풍요로 806 (총 5 필지)
3rd row전북특별자치도 김제시 백산면 옥정길 128-78 (총 2 필지)
4th row전북특별자치도 김제시 공덕면 유강3길 133, 벽성대학창업보육센터104,207
5th row전북특별자치도 김제시 봉황공단2길 78-20 (오정동)
ValueCountFrequency (%)
전북특별자치도 716
 
15.8%
김제시 716
 
15.8%
총 129
 
2.9%
필지 129
 
2.9%
백구면 111
 
2.5%
백산면 74
 
1.6%
2 66
 
1.5%
순동 56
 
1.2%
용지면 55
 
1.2%
금구면 52
 
1.1%
Other values (1084) 2422
53.5%
2024-03-14T11:30:00.347107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3838
 
16.8%
제 748
 
3.3%
자 737
 
3.2%
전 728
 
3.2%
김 724
 
3.2%
북 719
 
3.2%
특 717
 
3.1%
치 717
 
3.1%
도 717
 
3.1%
시 717
 
3.1%
Other values (307) 12423
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14047
61.7%
Space Separator 3838
 
16.8%
Decimal Number 3118
 
13.7%
Close Punctuation 566
 
2.5%
Open Punctuation 566
 
2.5%
Dash Punctuation 319
 
1.4%
Other Punctuation 216
 
0.9%
Other Symbol 83
 
0.4%
Uppercase Letter 28
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 748
 
5.3%
자 737
 
5.2%
전 728
 
5.2%
김 724
 
5.2%
북 719
 
5.1%
특 717
 
5.1%
치 717
 
5.1%
도 717
 
5.1%
시 717
 
5.1%
별 716
 
5.1%
Other values (273) 6807
48.5%
Decimal Number
ValueCountFrequency (%)
1 644
20.7%
2 546
17.5%
3 335
10.7%
4 306
9.8%
5 245
 
7.9%
7 239
 
7.7%
6 224
 
7.2%
8 203
 
6.5%
9 192
 
6.2%
0 184
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S 8
28.6%
A 4
14.3%
B 4
14.3%
N 3
 
10.7%
T 2
 
7.1%
F 2
 
7.1%
E 2
 
7.1%
C 1
 
3.6%
K 1
 
3.6%
G 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 205
94.9%
. 5
 
2.3%
& 4
 
1.9%
/ 1
 
0.5%
· 1
 
0.5%
Lowercase Letter
ValueCountFrequency (%)
e 1
25.0%
c 1
25.0%
h 1
25.0%
v 1
25.0%
Space Separator
ValueCountFrequency (%)
3838
100.0%
Close Punctuation
ValueCountFrequency (%)
) 566
100.0%
Open Punctuation
ValueCountFrequency (%)
( 566
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 319
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14130
62.0%
Common 8623
37.8%
Latin 32
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 748
 
5.3%
자 737
 
5.2%
전 728
 
5.2%
김 724
 
5.1%
북 719
 
5.1%
특 717
 
5.1%
치 717
 
5.1%
도 717
 
5.1%
시 717
 
5.1%
별 716
 
5.1%
Other values (274) 6890
48.8%
Common
ValueCountFrequency (%)
3838
44.5%
1 644
 
7.5%
) 566
 
6.6%
( 566
 
6.6%
2 546
 
6.3%
3 335
 
3.9%
- 319
 
3.7%
4 306
 
3.5%
5 245
 
2.8%
7 239
 
2.8%
Other values (9) 1019
 
11.8%
Latin
ValueCountFrequency (%)
S 8
25.0%
A 4
12.5%
B 4
12.5%
N 3
 
9.4%
T 2
 
6.2%
F 2
 
6.2%
E 2
 
6.2%
e 1
 
3.1%
c 1
 
3.1%
h 1
 
3.1%
Other values (4) 4
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14047
61.7%
ASCII 8654
38.0%
None 84
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3838
44.3%
1 644
 
7.4%
) 566
 
6.5%
( 566
 
6.5%
2 546
 
6.3%
3 335
 
3.9%
- 319
 
3.7%
4 306
 
3.5%
5 245
 
2.8%
7 239
 
2.8%
Other values (22) 1050
 
12.1%
Hangul
ValueCountFrequency (%)
제 748
 
5.3%
자 737
 
5.2%
전 728
 
5.2%
김 724
 
5.2%
북 719
 
5.1%
특 717
 
5.1%
치 717
 
5.1%
도 717
 
5.1%
시 717
 
5.1%
별 716
 
5.1%
Other values (273) 6807
48.5%
None
ValueCountFrequency (%)
㈜ 83
98.8%
· 1
 
1.2%

업종명
Text

Distinct348
Distinct (%)48.6%
Missing0
Missing (%)0.0%
Memory size5.7 KiB
2024-03-14T11:30:00.636193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length26
Mean length18.501397
Min length6

Characters and Unicode

Total characters13247
Distinct characters264
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

Unique240 ?
Unique (%)33.5%

Sample

1st row건설 및 채광용 기계장비 제조업
2nd row도장 및 기타 피막처리업 외 2 종
3rd row골판지 제조업 외 1 종
4th row기타 가정용 전기기기 제조업 외 3 종
5th row기타 곡물 가공품 제조업
ValueCountFrequency (%)
제조업 610
 
13.7%
외 484
 
10.8%
종 404
 
9.1%
및 330
 
7.4%
1 218
 
4.9%
기타 179
 
4.0%
금속 88
 
2.0%
그 80
 
1.8%
2 61
 
1.4%
신품 52
 
1.2%
Other values (395) 1956
43.8%
2024-03-14T11:30:01.034053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3746
28.3%
제 829
 
6.3%
업 761
 
5.7%
조 745
 
5.6%
외 497
 
3.8%
종 418
 
3.2%
및 331
 
2.5%
품 306
 
2.3%
기 300
 
2.3%
1 235
 
1.8%
Other values (254) 5079
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8973
67.7%
Space Separator 3746
28.3%
Decimal Number 421
 
3.2%
Other Punctuation 83
 
0.6%
Open Punctuation 12
 
0.1%
Close Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 829
 
9.2%
업 761
 
8.5%
조 745
 
8.3%
외 497
 
5.5%
종 418
 
4.7%
및 331
 
3.7%
품 306
 
3.4%
기 300
 
3.3%
용 229
 
2.6%
타 189
 
2.1%
Other values (240) 4368
48.7%
Decimal Number
ValueCountFrequency (%)
1 235
55.8%
2 64
 
15.2%
3 49
 
11.6%
4 28
 
6.7%
5 18
 
4.3%
6 10
 
2.4%
7 7
 
1.7%
9 5
 
1.2%
8 3
 
0.7%
0 2
 
0.5%
Space Separator
ValueCountFrequency (%)
3746
100.0%
Other Punctuation
ValueCountFrequency (%)
, 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8973
67.7%
Common 4274
32.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 829
 
9.2%
업 761
 
8.5%
조 745
 
8.3%
외 497
 
5.5%
종 418
 
4.7%
및 331
 
3.7%
품 306
 
3.4%
기 300
 
3.3%
용 229
 
2.6%
타 189
 
2.1%
Other values (240) 4368
48.7%
Common
ValueCountFrequency (%)
3746
87.6%
1 235
 
5.5%
, 83
 
1.9%
2 64
 
1.5%
3 49
 
1.1%
4 28
 
0.7%
5 18
 
0.4%
( 12
 
0.3%
) 12
 
0.3%
6 10
 
0.2%
Other values (4) 17
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8962
67.7%
ASCII 4274
32.3%
Compat Jamo 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3746
87.6%
1 235
 
5.5%
, 83
 
1.9%
2 64
 
1.5%
3 49
 
1.1%
4 28
 
0.7%
5 18
 
0.4%
( 12
 
0.3%
) 12
 
0.3%
6 10
 
0.2%
Other values (4) 17
 
0.4%
Hangul
ValueCountFrequency (%)
제 829
 
9.3%
업 761
 
8.5%
조 745
 
8.3%
외 497
 
5.5%
종 418
 
4.7%
및 331
 
3.7%
품 306
 
3.4%
기 300
 
3.3%
용 229
 
2.6%
타 189
 
2.1%
Other values (239) 4357
48.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 11
100.0%

Interactions

2024-03-14T11:29:55.782820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:30:01.148884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명
순번1.0000.257
단지명0.2571.000
2024-03-14T11:30:01.252871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명
순번1.0000.112
단지명0.1121.000

Missing values

2024-03-14T11:29:55.926003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:29:56.027557image/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

순번회사명단지명대표자명전화번호팩스번호생산품공장대표주소업종명
01(유) 대영중기데이터 미집계이상열063-547-9004데이터 미집계부품가공기계전북특별자치도 김제시 백산면 하공로 433-159 ((유)대영중기) (총 2 필지)건설 및 채광용 기계장비 제조업
12(유) 모던아트데이터 미집계박인수063-547-1790데이터 미집계커튼봉,커튼레일, 알루미늄 분체가공전북특별자치도 김제시 금구면 풍요로 806 (총 5 필지)도장 및 기타 피막처리업 외 2 종
23(유) 시온영광포장데이터 미집계한기수063-546-1665063-547-5310골판지 상자전북특별자치도 김제시 백산면 옥정길 128-78 (총 2 필지)골판지 제조업 외 1 종
34(유) 이젠365데이터 미집계안정립063-543-3663데이터 미집계소독기(의료,산업,가정용), 농업용분무기전북특별자치도 김제시 공덕면 유강3길 133, 벽성대학창업보육센터104,207기타 가정용 전기기기 제조업 외 3 종
45(유) 한푸드김제봉황농공단지정치웅063-542-8883063-542-8884누룽지전북특별자치도 김제시 봉황공단2길 78-20 (오정동)기타 곡물 가공품 제조업
56(유)강민케미칼김제봉황농공단지강희권063-546-6164063-546-6165스트레치필름전북특별자치도 김제시 봉황공단2길 75 (오정동, ㈜성화 S&S)플라스틱 필름 제조업 외 1 종
67(유)건영산업김제순동지방산업단지김종기063-546-8460데이터 미집계하수처리구성품,펌프,크레인전북특별자치도 김제시 순동산단1길 70, 대화유리(주) (순동)금속 문, 창, 셔터 및 관련제품 제조업 외 12 종
78(유)광명콘크리트김제월촌농공단지한상옥063-546-7701063-548-7701수로관전북특별자치도 김제시 월촌공단길 101-32 (명덕동, 광명콘크리트)콘크리트 관 및 기타 구조용 콘크리트 제품 제조업 외 1 종
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706707형통산업데이터 미집계최광필063-542-7110063-542-7110지그, 다이전북특별자치도 김제시 입석5길 107 (입석동)비동력식 수공구 제조업
707708혜명산업데이터 미집계최경애063-547-8357063-547-8357로필라,엔진마운팅,베이커탱크 등전북특별자치도 김제시 황산면 남양2길 263 (혜명산업)자동차용 신품 동력전달장치 제조업 외 4 종
708709혜성화학데이터 미집계오진석063-548-2460063-548-2461폴리에틸렌 필름전북특별자치도 김제시 아리랑로 1991 (상동동, 대원오토(유))플라스틱 필름 제조업 외 1 종
709710호남제면(주)김제봉황농공단지홍성민063-546-6677063-546-6678면전북특별자치도 김제시 봉황공단2길 14 (월성동, ㈜호남제면)그 외 기타 분류 안된 섬유제품 제조업
710711호룡5공장김제만경농공단지박장현063-540-5555063-543-2429고가사다리차, 고소작업차, 크레인전북특별자치도 김제시 만경읍 만경공단2길 73, (몽산리 106-16)차체 및 특장차 제조업 외 5 종
711712호평중공업주식회사김제황산농공단지조강식063-546-3091063-547-1001수문,강관,교량, 교통표지판 외전북특별자치도 김제시 황산면 용마로 429-41금속 문, 창, 셔터 및 관련제품 제조업 외 15 종
712713호평중공업주식회사김제황산농공단지조강식063-546-9934063-547-1001철문전북특별자치도 김제시 금구면 용마로 455-14 (총 2 필지)금속 문, 창, 셔터 및 관련제품 제조업 외 13 종
713714홍국산업(주)김제자유무역지역문홍국063-547-5558063-547-5557전기장판전북특별자치도 김제시 백산면 자유무역2길 45-43가정용 전기 난방기기 제조업
714715환희식품데이터 미집계조성심063-545-5533데이터 미집계순대,족발,내장전북특별자치도 김제시 금산면 삼봉리 614-5번지 외 1필지 외 1필지육류 기타 가공 및 저장처리업 (가금류 제외) 외 1 종
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