Overview

Dataset statistics

Number of variables9
Number of observations3435
Missing cells1389
Missing cells (%)4.5%
Duplicate rows2
Duplicate rows (%)0.1%
Total size in memory248.4 KiB
Average record size in memory74.0 B

Variable types

Categorical1
Text6
Numeric2

Dataset

Description강원도 기업체 정보(업체명, 업종, 생산품, 전화번호, 소속산업단지, 소재지도로명주소, 위치 위도/경도 등) 데이터를 제공합니다.
Author강원도
URLhttps://www.data.go.kr/data/15033683/fileData.do

Alerts

Dataset has 2 (0.1%) duplicate rowsDuplicates
경도 is highly overall correlated with 시군구명High correlation
위도 is highly overall correlated with 시군구명High correlation
시군구명 is highly overall correlated with 경도 and 1 other fieldsHigh correlation
연락처 has 114 (3.3%) missing valuesMissing
소속산업단지 has 1195 (34.8%) missing valuesMissing
소재지도로명주소 has 80 (2.3%) missing valuesMissing

Reproduction

Analysis started2023-12-12 01:51:19.893520
Analysis finished2023-12-12 01:51:22.566721
Duration2.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군구명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
원주시
1051 
강릉시
472 
춘천시
307 
동해시
257 
횡성군
220 
Other values (13)
1128 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
원주시 1051
30.6%
강릉시 472
13.7%
춘천시 307
 
8.9%
동해시 257
 
7.5%
횡성군 220
 
6.4%
홍천군 145
 
4.2%
평창군 112
 
3.3%
속초시 104
 
3.0%
삼척시 103
 
3.0%
철원군 103
 
3.0%
Other values (8) 561
16.3%

Length

2023-12-12T10:51:22.670659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
원주시 1051
30.6%
강릉시 472
13.7%
춘천시 307
 
8.9%
동해시 257
 
7.5%
횡성군 220
 
6.4%
홍천군 145
 
4.2%
평창군 112
 
3.3%
속초시 104
 
3.0%
철원군 103
 
3.0%
삼척시 103
 
3.0%
Other values (8) 561
16.3%

업체명
Text

Distinct3288
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2023-12-12T10:51:23.080668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length23
Mean length7.5697234
Min length2

Characters and Unicode

Total characters26002
Distinct characters651
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

Unique3152 ?
Unique (%)91.8%

Sample

1st row동해식품(주)
2nd row강경산업(주)
3rd row삼일냉동(주)
4th row강원실업(주)
5th row우성레미콘(주)
ValueCountFrequency (%)
주식회사 287
 
7.2%
농업회사법인 50
 
1.3%
제2공장 20
 
0.5%
영농조합법인 17
 
0.4%
유한회사 10
 
0.3%
제1공장 8
 
0.2%
합자회사 8
 
0.2%
원주공장 7
 
0.2%
원주지점 4
 
0.1%
주)포스-테크 4
 
0.1%
Other values (3376) 3576
89.6%
2023-12-12T10:51:23.712337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 2129
 
8.2%
) 1765
 
6.8%
( 1764
 
6.8%
사 661
 
2.5%
561
 
2.2%
이 551
 
2.1%
업 543
 
2.1%
식 539
 
2.1%
회 502
 
1.9%
산 490
 
1.9%
Other values (641) 16497
63.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21491
82.7%
Close Punctuation 1765
 
6.8%
Open Punctuation 1764
 
6.8%
Space Separator 561
 
2.2%
Uppercase Letter 237
 
0.9%
Decimal Number 62
 
0.2%
Other Symbol 33
 
0.1%
Dash Punctuation 31
 
0.1%
Other Punctuation 31
 
0.1%
Lowercase Letter 27
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2129
 
9.9%
사 661
 
3.1%
이 551
 
2.6%
업 543
 
2.5%
식 539
 
2.5%
회 502
 
2.3%
산 490
 
2.3%
스 427
 
2.0%
인 299
 
1.4%
동 295
 
1.4%
Other values (590) 15055
70.1%
Uppercase Letter
ValueCountFrequency (%)
E 21
 
8.9%
N 19
 
8.0%
C 17
 
7.2%
S 16
 
6.8%
G 15
 
6.3%
P 15
 
6.3%
M 15
 
6.3%
B 14
 
5.9%
T 13
 
5.5%
K 12
 
5.1%
Other values (14) 80
33.8%
Lowercase Letter
ValueCountFrequency (%)
e 4
14.8%
h 3
11.1%
i 3
11.1%
t 3
11.1%
a 3
11.1%
c 2
7.4%
g 2
7.4%
n 2
7.4%
l 2
7.4%
r 1
 
3.7%
Other values (2) 2
7.4%
Decimal Number
ValueCountFrequency (%)
2 33
53.2%
1 15
24.2%
3 9
 
14.5%
0 2
 
3.2%
9 1
 
1.6%
7 1
 
1.6%
5 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 16
51.6%
& 12
38.7%
/ 3
 
9.7%
Close Punctuation
ValueCountFrequency (%)
) 1765
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1764
100.0%
Space Separator
ValueCountFrequency (%)
561
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 33
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21524
82.8%
Common 4214
 
16.2%
Latin 264
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2129
 
9.9%
사 661
 
3.1%
이 551
 
2.6%
업 543
 
2.5%
식 539
 
2.5%
회 502
 
2.3%
산 490
 
2.3%
스 427
 
2.0%
인 299
 
1.4%
동 295
 
1.4%
Other values (591) 15088
70.1%
Latin
ValueCountFrequency (%)
E 21
 
8.0%
N 19
 
7.2%
C 17
 
6.4%
S 16
 
6.1%
G 15
 
5.7%
P 15
 
5.7%
M 15
 
5.7%
B 14
 
5.3%
T 13
 
4.9%
K 12
 
4.5%
Other values (26) 107
40.5%
Common
ValueCountFrequency (%)
) 1765
41.9%
( 1764
41.9%
561
 
13.3%
2 33
 
0.8%
- 31
 
0.7%
. 16
 
0.4%
1 15
 
0.4%
& 12
 
0.3%
3 9
 
0.2%
/ 3
 
0.1%
Other values (4) 5
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21491
82.7%
ASCII 4478
 
17.2%
None 33
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 2129
 
9.9%
사 661
 
3.1%
이 551
 
2.6%
업 543
 
2.5%
식 539
 
2.5%
회 502
 
2.3%
산 490
 
2.3%
스 427
 
2.0%
인 299
 
1.4%
동 295
 
1.4%
Other values (590) 15055
70.1%
ASCII
ValueCountFrequency (%)
) 1765
39.4%
( 1764
39.4%
561
 
12.5%
2 33
 
0.7%
- 31
 
0.7%
E 21
 
0.5%
N 19
 
0.4%
C 17
 
0.4%
S 16
 
0.4%
. 16
 
0.4%
Other values (40) 235
 
5.2%
None
ValueCountFrequency (%)
㈜ 33
100.0%

사업장업종명
Text

Distinct1056
Distinct (%)30.7%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2023-12-12T10:51:24.111514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length275
Median length99
Mean length17.236972
Min length2

Characters and Unicode

Total characters59209
Distinct characters346
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique609 ?
Unique (%)17.7%

Sample

1st row제과용 혼합분말 및 반죽 제조업 외 2 종
2nd row가금류 가공 및 저장 처리업 외 1 종
3rd row수산동물 냉동품 제조업
4th row콘크리트관 및 기타 구조용 콘크리트제품 제조업 외 2 종
5th row레미콘 제조업
ValueCountFrequency (%)
제조업 3133
 
16.5%
외 1663
 
8.8%
및 1540
 
8.1%
종 1348
 
7.1%
기타 843
 
4.5%
1 638
 
3.4%
그 294
 
1.6%
2 239
 
1.3%
금속 230
 
1.2%
3 175
 
0.9%
Other values (695) 8838
46.7%
2023-12-12T10:51:24.696233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15526
26.2%
제 4154
 
7.0%
조 3741
 
6.3%
업 3683
 
6.2%
기 1899
 
3.2%
외 1772
 
3.0%
및 1540
 
2.6%
종 1396
 
2.4%
품 1226
 
2.1%
용 987
 
1.7%
Other values (336) 23285
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 41629
70.3%
Space Separator 15526
 
26.2%
Decimal Number 1451
 
2.5%
Other Punctuation 535
 
0.9%
Open Punctuation 34
 
0.1%
Close Punctuation 34
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 4154
 
10.0%
조 3741
 
9.0%
업 3683
 
8.8%
기 1899
 
4.6%
외 1772
 
4.3%
및 1540
 
3.7%
종 1396
 
3.4%
품 1226
 
2.9%
용 987
 
2.4%
타 915
 
2.2%
Other values (320) 20316
48.8%
Decimal Number
ValueCountFrequency (%)
1 730
50.3%
2 265
 
18.3%
3 186
 
12.8%
4 95
 
6.5%
5 50
 
3.4%
6 48
 
3.3%
8 25
 
1.7%
7 24
 
1.7%
0 15
 
1.0%
9 13
 
0.9%
Other Punctuation
ValueCountFrequency (%)
, 517
96.6%
· 13
 
2.4%
. 5
 
0.9%
Space Separator
ValueCountFrequency (%)
15526
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 41629
70.3%
Common 17580
29.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 4154
 
10.0%
조 3741
 
9.0%
업 3683
 
8.8%
기 1899
 
4.6%
외 1772
 
4.3%
및 1540
 
3.7%
종 1396
 
3.4%
품 1226
 
2.9%
용 987
 
2.4%
타 915
 
2.2%
Other values (320) 20316
48.8%
Common
ValueCountFrequency (%)
15526
88.3%
1 730
 
4.2%
, 517
 
2.9%
2 265
 
1.5%
3 186
 
1.1%
4 95
 
0.5%
5 50
 
0.3%
6 48
 
0.3%
( 34
 
0.2%
) 34
 
0.2%
Other values (6) 95
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 41602
70.3%
ASCII 17567
29.7%
Compat Jamo 27
 
< 0.1%
None 13
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15526
88.4%
1 730
 
4.2%
, 517
 
2.9%
2 265
 
1.5%
3 186
 
1.1%
4 95
 
0.5%
5 50
 
0.3%
6 48
 
0.3%
( 34
 
0.2%
) 34
 
0.2%
Other values (5) 82
 
0.5%
Hangul
ValueCountFrequency (%)
제 4154
 
10.0%
조 3741
 
9.0%
업 3683
 
8.9%
기 1899
 
4.6%
외 1772
 
4.3%
및 1540
 
3.7%
종 1396
 
3.4%
품 1226
 
2.9%
용 987
 
2.4%
타 915
 
2.2%
Other values (319) 20289
48.8%
Compat Jamo
ValueCountFrequency (%)
ㆍ 27
100.0%
None
ValueCountFrequency (%)
· 13
100.0%

생산품명
Text

Distinct2723
Distinct (%)79.3%
Missing0
Missing (%)0.0%
Memory size27.0 KiB
2023-12-12T10:51:25.106595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length80
Median length53
Mean length9.7193595
Min length1

Characters and Unicode

Total characters33386
Distinct characters756
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2464 ?
Unique (%)71.7%

Sample

1st row장류,고추가루,튀김가루
2nd row도축물
3rd row수산물냉동냉장보관품
4th row호안블럭,PC박스,아스콘,레미콘
5th row레미콘
ValueCountFrequency (%)
및 163
 
2.5%
제조업 125
 
1.9%
레미콘 113
 
1.7%
등 112
 
1.7%
외 89
 
1.4%
종 52
 
0.8%
기타 43
 
0.7%
cctv 34
 
0.5%
아스콘 31
 
0.5%
자동제어반 31
 
0.5%
Other values (3492) 5704
87.8%
2023-12-12T10:51:25.790392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3087
 
9.2%
, 2347
 
7.0%
기 991
 
3.0%
조 614
 
1.8%
제 557
 
1.7%
장 516
 
1.5%
품 432
 
1.3%
스 410
 
1.2%
용 397
 
1.2%
물 391
 
1.2%
Other values (746) 23644
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26282
78.7%
Space Separator 3087
 
9.2%
Other Punctuation 2404
 
7.2%
Uppercase Letter 841
 
2.5%
Lowercase Letter 353
 
1.1%
Open Punctuation 156
 
0.5%
Close Punctuation 154
 
0.5%
Decimal Number 96
 
0.3%
Dash Punctuation 11
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 991
 
3.8%
조 614
 
2.3%
제 557
 
2.1%
장 516
 
2.0%
품 432
 
1.6%
스 410
 
1.6%
용 397
 
1.5%
물 391
 
1.5%
가 387
 
1.5%
재 357
 
1.4%
Other values (678) 21230
80.8%
Uppercase Letter
ValueCountFrequency (%)
C 139
16.5%
D 114
13.6%
E 111
13.2%
L 98
11.7%
P 82
9.8%
V 71
8.4%
T 60
7.1%
A 23
 
2.7%
S 19
 
2.3%
R 19
 
2.3%
Other values (14) 105
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 39
11.0%
s 28
 
7.9%
t 27
 
7.6%
o 26
 
7.4%
c 25
 
7.1%
a 24
 
6.8%
l 24
 
6.8%
i 22
 
6.2%
n 22
 
6.2%
r 19
 
5.4%
Other values (13) 97
27.5%
Decimal Number
ValueCountFrequency (%)
1 39
40.6%
2 20
20.8%
3 8
 
8.3%
4 6
 
6.2%
5 6
 
6.2%
6 5
 
5.2%
9 4
 
4.2%
8 4
 
4.2%
0 4
 
4.2%
Other Punctuation
ValueCountFrequency (%)
, 2347
97.6%
. 36
 
1.5%
/ 12
 
0.5%
· 5
 
0.2%
' 2
 
0.1%
& 2
 
0.1%
Space Separator
ValueCountFrequency (%)
3087
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Close Punctuation
ValueCountFrequency (%)
) 154
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 26282
78.7%
Common 5910
 
17.7%
Latin 1194
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 991
 
3.8%
조 614
 
2.3%
제 557
 
2.1%
장 516
 
2.0%
품 432
 
1.6%
스 410
 
1.6%
용 397
 
1.5%
물 391
 
1.5%
가 387
 
1.5%
재 357
 
1.4%
Other values (678) 21230
80.8%
Latin
ValueCountFrequency (%)
C 139
 
11.6%
D 114
 
9.5%
E 111
 
9.3%
L 98
 
8.2%
P 82
 
6.9%
V 71
 
5.9%
T 60
 
5.0%
e 39
 
3.3%
s 28
 
2.3%
t 27
 
2.3%
Other values (37) 425
35.6%
Common
ValueCountFrequency (%)
3087
52.2%
, 2347
39.7%
( 156
 
2.6%
) 154
 
2.6%
1 39
 
0.7%
. 36
 
0.6%
2 20
 
0.3%
/ 12
 
0.2%
- 11
 
0.2%
3 8
 
0.1%
Other values (11) 40
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 26282
78.7%
ASCII 7099
 
21.3%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3087
43.5%
, 2347
33.1%
( 156
 
2.2%
) 154
 
2.2%
C 139
 
2.0%
D 114
 
1.6%
E 111
 
1.6%
L 98
 
1.4%
P 82
 
1.2%
V 71
 
1.0%
Other values (57) 740
 
10.4%
Hangul
ValueCountFrequency (%)
기 991
 
3.8%
조 614
 
2.3%
제 557
 
2.1%
장 516
 
2.0%
품 432
 
1.6%
스 410
 
1.6%
용 397
 
1.5%
물 391
 
1.5%
가 387
 
1.5%
재 357
 
1.4%
Other values (678) 21230
80.8%
None
ValueCountFrequency (%)
· 5
100.0%

연락처
Text

MISSING 

Distinct3088
Distinct (%)93.0%
Missing114
Missing (%)3.3%
Memory size27.0 KiB
2023-12-12T10:51:26.052822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.005119
Min length9

Characters and Unicode

Total characters39869
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

Unique2883 ?
Unique (%)86.8%

Sample

1st row033-643-4392
2nd row033-652-6131
3rd row033-662-5800
4th row033-644-6767
5th row033-644-5677
ValueCountFrequency (%)
033-574-7001 4
 
0.1%
033-734-5000 4
 
0.1%
033-245-8024 4
 
0.1%
033-732-8200 4
 
0.1%
033-535-5477 3
 
0.1%
033-521-7880 3
 
0.1%
033-436-7800 3
 
0.1%
033-646-2738 3
 
0.1%
033-534-1000 3
 
0.1%
033-635-6210 3
 
0.1%
Other values (3078) 3287
99.0%
2023-12-12T10:51:26.527205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 9220
23.1%
- 6615
16.6%
0 5514
13.8%
7 2857
 
7.2%
4 2776
 
7.0%
2 2652
 
6.7%
6 2571
 
6.4%
5 2553
 
6.4%
1 2302
 
5.8%
8 1644
 
4.1%
Other values (2) 1165
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33253
83.4%
Dash Punctuation 6615
 
16.6%
Connector Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 9220
27.7%
0 5514
16.6%
7 2857
 
8.6%
4 2776
 
8.3%
2 2652
 
8.0%
6 2571
 
7.7%
5 2553
 
7.7%
1 2302
 
6.9%
8 1644
 
4.9%
9 1164
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 6615
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 39869
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 9220
23.1%
- 6615
16.6%
0 5514
13.8%
7 2857
 
7.2%
4 2776
 
7.0%
2 2652
 
6.7%
6 2571
 
6.4%
5 2553
 
6.4%
1 2302
 
5.8%
8 1644
 
4.1%
Other values (2) 1165
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 39869
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 9220
23.1%
- 6615
16.6%
0 5514
13.8%
7 2857
 
7.2%
4 2776
 
7.0%
2 2652
 
6.7%
6 2571
 
6.4%
5 2553
 
6.4%
1 2302
 
5.8%
8 1644
 
4.1%
Other values (2) 1165
 
2.9%

소속산업단지
Text

MISSING 

Distinct65
Distinct (%)2.9%
Missing1195
Missing (%)34.8%
Memory size27.0 KiB
2023-12-12T10:51:26.812937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length15
Mean length6.6120536
Min length1

Characters and Unicode

Total characters14811
Distinct characters116
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)0.2%

Sample

1st row강릉주문진농공단지
2nd row강릉과학지방산업단지
3rd row강릉과학지방산업단지
4th row강릉주문진농공단지
5th row강릉주문진농공단지
ValueCountFrequency (%)
원주태장농공단지 185
 
10.8%
춘천퇴계농공단지 147
 
8.6%
동해북평지방산업단지 139
 
8.1%
춘천지방산업단지 78
 
4.6%
강릉과학지방산업단지 72
 
4.2%
개별기업 63
 
3.7%
원주동화농공단지 51
 
3.0%
원주문막농공단지 49
 
2.9%
속초대포농공단지 49
 
2.9%
강릉주문진농공단지 39
 
2.3%
Other values (54) 836
48.9%
2023-12-12T10:51:27.284031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 2000
 
13.5%
단 1611
 
10.9%
공 1160
 
7.8%
농 1133
 
7.6%
업 555
 
3.7%
532
 
3.6%
산 521
 
3.5%
천 466
 
3.1%
원 465
 
3.1%
주 410
 
2.8%
Other values (106) 5958
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14169
95.7%
Space Separator 532
 
3.6%
Decimal Number 80
 
0.5%
Uppercase Letter 30
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2000
 
14.1%
단 1611
 
11.4%
공 1160
 
8.2%
농 1133
 
8.0%
업 555
 
3.9%
산 521
 
3.7%
천 466
 
3.3%
원 465
 
3.3%
주 410
 
2.9%
방 379
 
2.7%
Other values (101) 5469
38.6%
Decimal Number
ValueCountFrequency (%)
2 50
62.5%
3 30
37.5%
Uppercase Letter
ValueCountFrequency (%)
I 15
50.0%
T 15
50.0%
Space Separator
ValueCountFrequency (%)
532
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14169
95.7%
Common 612
 
4.1%
Latin 30
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2000
 
14.1%
단 1611
 
11.4%
공 1160
 
8.2%
농 1133
 
8.0%
업 555
 
3.9%
산 521
 
3.7%
천 466
 
3.3%
원 465
 
3.3%
주 410
 
2.9%
방 379
 
2.7%
Other values (101) 5469
38.6%
Common
ValueCountFrequency (%)
532
86.9%
2 50
 
8.2%
3 30
 
4.9%
Latin
ValueCountFrequency (%)
I 15
50.0%
T 15
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14169
95.7%
ASCII 642
 
4.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 2000
 
14.1%
단 1611
 
11.4%
공 1160
 
8.2%
농 1133
 
8.0%
업 555
 
3.9%
산 521
 
3.7%
천 466
 
3.3%
원 465
 
3.3%
주 410
 
2.9%
방 379
 
2.7%
Other values (101) 5469
38.6%
ASCII
ValueCountFrequency (%)
532
82.9%
2 50
 
7.8%
3 30
 
4.7%
I 15
 
2.3%
T 15
 
2.3%

소재지도로명주소
Text

MISSING 

Distinct2895
Distinct (%)86.3%
Missing80
Missing (%)2.3%
Memory size27.0 KiB
2023-12-12T10:51:27.610393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length63
Median length55
Mean length25.674814
Min length14

Characters and Unicode

Total characters86139
Distinct characters515
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

Unique2606 ?
Unique (%)77.7%

Sample

1st row강원도 강릉시 모산로169번길 30 (담산동)
2nd row강원도 강릉시 강변북길 267 (송정동)
3rd row강원도 강릉시 연곡면 연주로 162
4th row강원도 강릉시 강동면 동해대로 1869-19
5th row강원도 강릉시 강동면 오이동길 104 (총 2 필지)
ValueCountFrequency (%)
강원도 3355
 
17.6%
원주시 1019
 
5.3%
강릉시 452
 
2.4%
춘천시 300
 
1.6%
총 285
 
1.5%
필지 285
 
1.5%
동해시 260
 
1.4%
문막읍 244
 
1.3%
횡성군 217
 
1.1%
태장동 192
 
1.0%
Other values (3254) 12452
65.3%
2023-12-12T10:51:28.165936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15954
 
18.5%
원 4828
 
5.6%
강 4127
 
4.8%
도 3453
 
4.0%
1 2634
 
3.1%
시 2372
 
2.8%
2 2262
 
2.6%
동 2106
 
2.4%
) 1996
 
2.3%
( 1995
 
2.3%
Other values (505) 44412
51.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50724
58.9%
Space Separator 15954
 
18.5%
Decimal Number 13065
 
15.2%
Close Punctuation 1998
 
2.3%
Open Punctuation 1997
 
2.3%
Dash Punctuation 1341
 
1.6%
Other Punctuation 882
 
1.0%
Uppercase Letter 150
 
0.2%
Other Symbol 27
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 4828
 
9.5%
강 4127
 
8.1%
도 3453
 
6.8%
시 2372
 
4.7%
동 2106
 
4.2%
길 1985
 
3.9%
로 1636
 
3.2%
주 1433
 
2.8%
면 1322
 
2.6%
공 1246
 
2.5%
Other values (460) 26216
51.7%
Uppercase Letter
ValueCountFrequency (%)
A 21
14.0%
C 19
12.7%
P 11
 
7.3%
L 11
 
7.3%
D 10
 
6.7%
B 10
 
6.7%
S 9
 
6.0%
O 9
 
6.0%
F 8
 
5.3%
I 8
 
5.3%
Other values (12) 34
22.7%
Decimal Number
ValueCountFrequency (%)
1 2634
20.2%
2 2262
17.3%
3 1355
10.4%
4 1246
9.5%
0 1150
8.8%
6 1061
8.1%
5 1042
 
8.0%
7 919
 
7.0%
8 757
 
5.8%
9 639
 
4.9%
Other Punctuation
ValueCountFrequency (%)
, 868
98.4%
. 6
 
0.7%
& 5
 
0.6%
/ 2
 
0.2%
@ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 1996
99.9%
] 2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 1995
99.9%
[ 2
 
0.1%
Space Separator
ValueCountFrequency (%)
15954
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1341
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 27
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50751
58.9%
Common 35238
40.9%
Latin 150
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 4828
 
9.5%
강 4127
 
8.1%
도 3453
 
6.8%
시 2372
 
4.7%
동 2106
 
4.1%
길 1985
 
3.9%
로 1636
 
3.2%
주 1433
 
2.8%
면 1322
 
2.6%
공 1246
 
2.5%
Other values (461) 26243
51.7%
Common
ValueCountFrequency (%)
15954
45.3%
1 2634
 
7.5%
2 2262
 
6.4%
) 1996
 
5.7%
( 1995
 
5.7%
3 1355
 
3.8%
- 1341
 
3.8%
4 1246
 
3.5%
0 1150
 
3.3%
6 1061
 
3.0%
Other values (12) 4244
 
12.0%
Latin
ValueCountFrequency (%)
A 21
14.0%
C 19
12.7%
P 11
 
7.3%
L 11
 
7.3%
D 10
 
6.7%
B 10
 
6.7%
S 9
 
6.0%
O 9
 
6.0%
F 8
 
5.3%
I 8
 
5.3%
Other values (12) 34
22.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50724
58.9%
ASCII 35388
41.1%
None 27
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15954
45.1%
1 2634
 
7.4%
2 2262
 
6.4%
) 1996
 
5.6%
( 1995
 
5.6%
3 1355
 
3.8%
- 1341
 
3.8%
4 1246
 
3.5%
0 1150
 
3.2%
6 1061
 
3.0%
Other values (34) 4394
 
12.4%
Hangul
ValueCountFrequency (%)
원 4828
 
9.5%
강 4127
 
8.1%
도 3453
 
6.8%
시 2372
 
4.7%
동 2106
 
4.2%
길 1985
 
3.9%
로 1636
 
3.2%
주 1433
 
2.8%
면 1322
 
2.6%
공 1246
 
2.5%
Other values (460) 26216
51.7%
None
ValueCountFrequency (%)
㈜ 27
100.0%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2486
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.27571
Minimum127.16055
Maximum129.34823
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.3 KiB
2023-12-12T10:51:28.325513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.16055
5-th percentile127.66577
Q1127.86987
median128.01213
Q3128.82631
95-th percentile129.14004
Maximum129.34823
Range2.1876833
Interquartile range (IQR)0.95644425

Descriptive statistics

Standard deviation0.51987491
Coefficient of variation (CV)0.0040527931
Kurtosis-1.1804772
Mean128.27571
Median Absolute Deviation (MAD)0.2738326
Skewness0.3632393
Sum440627.07
Variance0.27026992
MonotonicityNot monotonic
2023-12-12T10:51:28.492862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.9504859 53
 
1.5%
127.9453941 27
 
0.8%
127.873596 20
 
0.6%
127.9396871 17
 
0.5%
127.7349209 16
 
0.5%
127.9081367 15
 
0.4%
129.0866471 14
 
0.4%
129.1529369 14
 
0.4%
127.7384 14
 
0.4%
127.7438724 14
 
0.4%
Other values (2476) 3231
94.1%
ValueCountFrequency (%)
127.1605497 1
< 0.1%
127.1669687 1
< 0.1%
127.2117682 1
< 0.1%
127.2128976 1
< 0.1%
127.2130643 1
< 0.1%
127.213609 1
< 0.1%
127.2137815 1
< 0.1%
127.2157107 1
< 0.1%
127.2178989 1
< 0.1%
127.2190318 1
< 0.1%
ValueCountFrequency (%)
129.348233 1
< 0.1%
129.340326 1
< 0.1%
129.337638 1
< 0.1%
129.337456 1
< 0.1%
129.335568 1
< 0.1%
129.331727 1
< 0.1%
129.327006 1
< 0.1%
129.252613 1
< 0.1%
129.249377 1
< 0.1%
129.248628 2
0.1%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2507
Distinct (%)73.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.607649
Minimum37.09124
Maximum38.51708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size30.3 KiB
2023-12-12T10:51:28.646314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.09124
5-th percentile37.212262
Q137.363561
median37.479065
Q337.84406
95-th percentile38.180712
Maximum38.51708
Range1.42584
Interquartile range (IQR)0.4804987

Descriptive statistics

Standard deviation0.31449979
Coefficient of variation (CV)0.0083626549
Kurtosis-0.58814495
Mean37.607649
Median Absolute Deviation (MAD)0.19872106
Skewness0.6505864
Sum129182.27
Variance0.098910116
MonotonicityNot monotonic
2023-12-12T10:51:28.827411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4062743 53
 
1.5%
37.4026686 27
 
0.8%
37.3716502 20
 
0.6%
37.374382 17
 
0.5%
37.8462606 16
 
0.5%
37.3028339 15
 
0.4%
37.8909 14
 
0.4%
37.48095531 14
 
0.4%
37.5043809 14
 
0.4%
37.802906 13
 
0.4%
Other values (2497) 3232
94.1%
ValueCountFrequency (%)
37.09124 1
< 0.1%
37.095385 1
< 0.1%
37.1048314 1
< 0.1%
37.105391 1
< 0.1%
37.105702 1
< 0.1%
37.106409 1
< 0.1%
37.106916 1
< 0.1%
37.107377 1
< 0.1%
37.107826 1
< 0.1%
37.107951 1
< 0.1%
ValueCountFrequency (%)
38.51708 1
< 0.1%
38.497027 1
< 0.1%
38.461514 1
< 0.1%
38.453753 1
< 0.1%
38.45266 1
< 0.1%
38.449577 1
< 0.1%
38.449209 1
< 0.1%
38.448864 1
< 0.1%
38.443428 1
< 0.1%
38.442767 1
< 0.1%

Interactions

2023-12-12T10:51:21.966927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:21.753550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:22.067587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:51:21.864842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:51:28.959524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군구명소속산업단지경도위도
시군구명1.0000.9900.9420.924
소속산업단지0.9901.0000.9780.971
경도0.9420.9781.0000.874
위도0.9240.9710.8741.000
2023-12-12T10:51:29.074715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
경도위도시군구명
경도1.0000.0050.749
위도0.0051.0000.696
시군구명0.7490.6961.000

Missing values

2023-12-12T10:51:22.216143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:51:22.380765image/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.
2023-12-12T10:51:22.498447image/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

시군구명업체명사업장업종명생산품명연락처소속산업단지소재지도로명주소경도위도
0강릉시동해식품(주)제과용 혼합분말 및 반죽 제조업 외 2 종장류,고추가루,튀김가루033-643-4392<NA>강원도 강릉시 모산로169번길 30 (담산동)128.8995737.725757
1강릉시강경산업(주)가금류 가공 및 저장 처리업 외 1 종도축물033-652-6131<NA>강원도 강릉시 강변북길 267 (송정동)128.9236937.770774
2강릉시삼일냉동(주)수산동물 냉동품 제조업수산물냉동냉장보관품033-662-5800<NA>강원도 강릉시 연곡면 연주로 162128.83755337.870556
3강릉시강원실업(주)콘크리트관 및 기타 구조용 콘크리트제품 제조업 외 2 종호안블럭,PC박스,아스콘,레미콘033-644-6767<NA>강원도 강릉시 강동면 동해대로 1869-19128.9685737.679231
4강릉시우성레미콘(주)레미콘 제조업레미콘033-644-5677<NA>강원도 강릉시 강동면 오이동길 104 (총 2 필지)129.01831137.681452
5강릉시(주)우진식품수산동물 냉동품 제조업 외 1 종황태,북어,오징어033-662-3393<NA>강원도 강릉시 주문진읍 공시내길 73-3 (총 2 필지)128.81432137.871629
6강릉시(주)미성강재기타 제철 및 제강업형강,데크프레이트033-652-2307<NA>강원도 강릉시 강변로670번길 33 (두산동)128.93426137.766501
7강릉시동방씽크제작주방용 및 음식점용 목재가구 제조업씽크대033-651-4884<NA>강원도 강릉시 월대산로149번길 60 (두산동)128.92836937.764619
8강릉시나라계전배전반 및 전기자동제어반 제조업전기판넬및 자동제어반033-651-4081강릉주문진농공단지강원도 강릉시 주문진읍 농공단지길 40-22128.82690237.870478
9강릉시(주)클린그외 기타 플라스틱 제품 제조업수지재생033-651-8120<NA>강원도 강릉시 강변로692번길 16 (두산동)128.93460737.767859
시군구명업체명사업장업종명생산품명연락처소속산업단지소재지도로명주소경도위도
3425평창군농업회사법인(합)송원그린텍복합비료 및 기타 화학비료 제조업 외 1 종비료033-336-9148강원도 평창군 대화면 미날2길 125-6 (전통건축직업전문학교)128.40988937.452464
3426평창군대관령눈마을황태영농조합법인기타 수산동물 가공 및 저장 처리업황태류 가공품033-336-3355강원도 평창군 대관령면 올림픽로 8128.69975137.678102
3427평창군대관령사슴목장건강보조용 액화식품 제조업추출가공식품033-336-8890강원도 평창군 대관령면 차항길 480-29128.68152537.726802
3428평창군대복임업사강화 및 재생 목재 제조업톱밥033-335-7573강원도 평창군 진부면 오대천로 1977-6128.55290937.630987
3429평창군들애초농산기타 과실ㆍ채소 가공 및 저장 처리업절임류,나물070-4190-1914강원도 평창군 방림면 들모고개길 11128.3073137.436717
3430평창군무진정미소곡물 도정업도정미033-332-2006강원도 평창군 평창읍 후평길 104-11128.38901737.382131
3431평창군봉평메밀특산단지영농조합법인(용평지점)기타 곡물 가공품 제조업메밀가루033-332-9939강원도 평창군 용평면 백옥포길 21128.40906337.585867
3432평창군삼성산업(주)레미콘 제조업레미콘033-335-3004강원도 평창군 진부면 하송정길 313-7128.55138737.622178
3433평창군신흥중기건설 및 채광용 기계장비 제조업토목공사용기계장비033-335-4066강원도 평창군 진부면 속사재길 432128.52458937.653918
3434평창군애드팜영농조합법인기타 과실ㆍ채소 가공 및 저장 처리업채소가공033-333-9961강원도 평창군 용평면 새터마을길 22-23128.4045837.587945

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시군구명업체명사업장업종명생산품명연락처소속산업단지소재지도로명주소경도위도# duplicates
0원주시삼우상사금속 표시판 제조업교통표시판033-732-1162<NA>강원도 원주시 지정면 지정로 973127.79958737.3635612
1춘천시선두기업절삭가공 및 유사처리업절삭가공품 등033-263-7764춘천거두농공단지강원도 춘천시 동내면 거두단지1길 22127.779537.867212