Overview

Dataset statistics

Number of variables13
Number of observations232
Missing cells20
Missing cells (%)0.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.4 KiB
Average record size in memory107.6 B

Variable types

Text5
Categorical4
DateTime1
Numeric3

Dataset

Description기업체(회사명, 산업단지구분, 최초등록일자, 전화번호, 종업원수, 생산품, 소재지도로명주소, 소재지지번주소, 위도, 경도 등) 정보 공개
URLhttps://www.data.go.kr/data/3066409/fileData.do

Alerts

관리기관명 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 구분High correlation
구분 is highly overall correlated with 위도High correlation
소재지도로명주소 has 7 (3.0%) missing valuesMissing
위도 has 6 (2.6%) missing valuesMissing
경도 has 6 (2.6%) missing valuesMissing
종업원수 has 5 (2.2%) zerosZeros

Reproduction

Analysis started2023-12-12 00:01:20.837473
Analysis finished2023-12-12 00:01:22.836008
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회사명
Text

Distinct228
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T09:01:22.994483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length7.1853448
Min length2

Characters and Unicode

Total characters1667
Distinct characters264
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)96.6%

Sample

1st row(사)대한민국공무원 공상유공자회 상훈사업부
2nd row(유)서호산업
3rd row(주)그린코리아
4th row(주)대성팩
5th row(주)더브류.제이
ValueCountFrequency (%)
주식회사 37
 
12.9%
제2공장 4
 
1.4%
일진산업 2
 
0.7%
주)딜리 2
 
0.7%
주)대륙공업 2
 
0.7%
지우실업(주 2
 
0.7%
금토일종합식품 2
 
0.7%
주)제일금속 2
 
0.7%
유한회사 2
 
0.7%
농업회사법인 2
 
0.7%
Other values (227) 230
80.1%
2023-12-12T09:01:23.387023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 145
 
8.7%
( 106
 
6.4%
) 106
 
6.4%
56
 
3.4%
사 55
 
3.3%
식 50
 
3.0%
회 47
 
2.8%
업 46
 
2.8%
이 43
 
2.6%
스 39
 
2.3%
Other values (254) 974
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1341
80.4%
Open Punctuation 106
 
6.4%
Close Punctuation 106
 
6.4%
Space Separator 56
 
3.4%
Uppercase Letter 27
 
1.6%
Lowercase Letter 12
 
0.7%
Other Punctuation 10
 
0.6%
Decimal Number 6
 
0.4%
Other Symbol 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 145
 
10.8%
사 55
 
4.1%
식 50
 
3.7%
회 47
 
3.5%
업 46
 
3.4%
이 43
 
3.2%
스 39
 
2.9%
산 33
 
2.5%
아 28
 
2.1%
일 26
 
1.9%
Other values (224) 829
61.8%
Uppercase Letter
ValueCountFrequency (%)
C 5
18.5%
K 5
18.5%
S 4
14.8%
T 2
 
7.4%
J 2
 
7.4%
L 2
 
7.4%
M 2
 
7.4%
F 1
 
3.7%
I 1
 
3.7%
D 1
 
3.7%
Other values (2) 2
 
7.4%
Lowercase Letter
ValueCountFrequency (%)
e 2
16.7%
a 2
16.7%
n 1
8.3%
o 1
8.3%
m 1
8.3%
p 1
8.3%
y 1
8.3%
t 1
8.3%
h 1
8.3%
r 1
8.3%
Other Punctuation
ValueCountFrequency (%)
. 5
50.0%
& 3
30.0%
· 2
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 106
100.0%
Close Punctuation
ValueCountFrequency (%)
) 106
100.0%
Space Separator
ValueCountFrequency (%)
56
100.0%
Decimal Number
ValueCountFrequency (%)
2 6
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1344
80.6%
Common 284
 
17.0%
Latin 39
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 145
 
10.8%
사 55
 
4.1%
식 50
 
3.7%
회 47
 
3.5%
업 46
 
3.4%
이 43
 
3.2%
스 39
 
2.9%
산 33
 
2.5%
아 28
 
2.1%
일 26
 
1.9%
Other values (225) 832
61.9%
Latin
ValueCountFrequency (%)
C 5
12.8%
K 5
12.8%
S 4
 
10.3%
e 2
 
5.1%
T 2
 
5.1%
a 2
 
5.1%
J 2
 
5.1%
L 2
 
5.1%
M 2
 
5.1%
n 1
 
2.6%
Other values (12) 12
30.8%
Common
ValueCountFrequency (%)
( 106
37.3%
) 106
37.3%
56
19.7%
2 6
 
2.1%
. 5
 
1.8%
& 3
 
1.1%
· 2
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1341
80.4%
ASCII 321
 
19.3%
None 5
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 145
 
10.8%
사 55
 
4.1%
식 50
 
3.7%
회 47
 
3.5%
업 46
 
3.4%
이 43
 
3.2%
스 39
 
2.9%
산 33
 
2.5%
아 28
 
2.1%
일 26
 
1.9%
Other values (224) 829
61.8%
ASCII
ValueCountFrequency (%)
( 106
33.0%
) 106
33.0%
56
17.4%
2 6
 
1.9%
C 5
 
1.6%
. 5
 
1.6%
K 5
 
1.6%
S 4
 
1.2%
& 3
 
0.9%
e 2
 
0.6%
Other values (18) 23
 
7.2%
None
ValueCountFrequency (%)
㈜ 3
60.0%
· 2
40.0%

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
개별공장
130 
동두천일반산업단지
45 
동두천제2일반산업단지
26 
지식산업센터
24 
동두천상봉암일반산업단지
 
7

Length

Max length12
Median length4
Mean length6.2025862
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
개별공장 130
56.0%
동두천일반산업단지 45
 
19.4%
동두천제2일반산업단지 26
 
11.2%
지식산업센터 24
 
10.3%
동두천상봉암일반산업단지 7
 
3.0%

Length

2023-12-12T09:01:23.540162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:01:23.673992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개별공장 130
56.0%
동두천일반산업단지 45
 
19.4%
동두천제2일반산업단지 26
 
11.2%
지식산업센터 24
 
10.3%
동두천상봉암일반산업단지 7
 
3.0%

최초등록일
Date

Distinct216
Distinct (%)93.1%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum1990-11-08 00:00:00
Maximum2023-05-22 00:00:00
2023-12-12T09:01:23.781211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:23.903357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

Distinct199
Distinct (%)85.8%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T09:01:24.146881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.637931
Min length7

Characters and Unicode

Total characters2700
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

Unique184 ?
Unique (%)79.3%

Sample

1st row031-865-0008
2nd row031-842-7209
3rd row031-866-3101
4th row031-865-7145
5th row031-867-7191
ValueCountFrequency (%)
데이터 17
 
6.8%
미집계 17
 
6.8%
031-867-5555 3
 
1.2%
031-860-5500 3
 
1.2%
031-863-0204 3
 
1.2%
031-867-2533 2
 
0.8%
031-864-7705 2
 
0.8%
031-868-3730 2
 
0.8%
031-867-4812 2
 
0.8%
031-868-4361 2
 
0.8%
Other values (190) 196
78.7%
2023-12-12T09:01:24.825457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 430
15.9%
0 378
14.0%
1 325
12.0%
8 302
11.2%
3 287
10.6%
6 266
9.9%
5 152
 
5.6%
7 145
 
5.4%
2 115
 
4.3%
4 107
 
4.0%
Other values (8) 193
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2151
79.7%
Dash Punctuation 430
 
15.9%
Other Letter 102
 
3.8%
Space Separator 17
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 378
17.6%
1 325
15.1%
8 302
14.0%
3 287
13.3%
6 266
12.4%
5 152
7.1%
7 145
 
6.7%
2 115
 
5.3%
4 107
 
5.0%
9 74
 
3.4%
Other Letter
ValueCountFrequency (%)
이 17
16.7%
계 17
16.7%
집 17
16.7%
미 17
16.7%
터 17
16.7%
데 17
16.7%
Dash Punctuation
ValueCountFrequency (%)
- 430
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2598
96.2%
Hangul 102
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
- 430
16.6%
0 378
14.5%
1 325
12.5%
8 302
11.6%
3 287
11.0%
6 266
10.2%
5 152
 
5.9%
7 145
 
5.6%
2 115
 
4.4%
4 107
 
4.1%
Other values (2) 91
 
3.5%
Hangul
ValueCountFrequency (%)
이 17
16.7%
계 17
16.7%
집 17
16.7%
미 17
16.7%
터 17
16.7%
데 17
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2598
96.2%
Hangul 102
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 430
16.6%
0 378
14.5%
1 325
12.5%
8 302
11.6%
3 287
11.0%
6 266
10.2%
5 152
 
5.9%
7 145
 
5.6%
2 115
 
4.4%
4 107
 
4.1%
Other values (2) 91
 
3.5%
Hangul
ValueCountFrequency (%)
이 17
16.7%
계 17
16.7%
집 17
16.7%
미 17
16.7%
터 17
16.7%
데 17
16.7%

종업원수
Real number (ℝ)

ZEROS 

Distinct59
Distinct (%)25.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.262931
Minimum0
Maximum645
Zeros5
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T09:01:24.952642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median8
Q320
95-th percentile81.15
Maximum645
Range645
Interquartile range (IQR)16

Descriptive statistics

Standard deviation51.926728
Coefficient of variation (CV)2.4421247
Kurtosis95.925355
Mean21.262931
Median Absolute Deviation (MAD)5
Skewness8.7509119
Sum4933
Variance2696.3851
MonotonicityNot monotonic
2023-12-12T09:01:25.074781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 20
 
8.6%
3 17
 
7.3%
4 17
 
7.3%
2 16
 
6.9%
5 15
 
6.5%
1 15
 
6.5%
10 13
 
5.6%
7 9
 
3.9%
12 8
 
3.4%
9 7
 
3.0%
Other values (49) 95
40.9%
ValueCountFrequency (%)
0 5
 
2.2%
1 15
6.5%
2 16
6.9%
3 17
7.3%
4 17
7.3%
5 15
6.5%
6 20
8.6%
7 9
3.9%
8 6
 
2.6%
9 7
 
3.0%
ValueCountFrequency (%)
645 1
0.4%
337 1
0.4%
150 1
0.4%
115 1
0.4%
112 1
0.4%
104 1
0.4%
96 1
0.4%
91 1
0.4%
90 1
0.4%
88 1
0.4%

생산품
Text

Distinct211
Distinct (%)91.3%
Missing1
Missing (%)0.4%
Memory size1.9 KiB
2023-12-12T09:01:25.326021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length38
Mean length9.2857143
Min length1

Characters and Unicode

Total characters2145
Distinct characters346
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

Unique197 ?
Unique (%)85.3%

Sample

1st row배지, 훈장, 메달, 계급장, 깃발
2nd row밀폐용기, 과일용기, IT트레이
3rd row방염제, 탈취향균제, 살균제, 소독제분사기, 방염합판, 목재, MDF, 재난안전계측기
4th row플라스틱 트레이
5th row스카프,복지 및 넥타이
ValueCountFrequency (%)
및 14
 
3.0%
원단 8
 
1.7%
등 7
 
1.5%
가죽 5
 
1.1%
섬유 5
 
1.1%
제품 5
 
1.1%
섬유원단 4
 
0.8%
외 4
 
0.8%
근무복 4
 
0.8%
피혁 4
 
0.8%
Other values (343) 412
87.3%
2023-12-12T09:01:25.714080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
243
 
11.3%
, 154
 
7.2%
가 53
 
2.5%
기 42
 
2.0%
제 40
 
1.9%
스 36
 
1.7%
원 34
 
1.6%
단 31
 
1.4%
피 31
 
1.4%
이 30
 
1.4%
Other values (336) 1451
67.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1612
75.2%
Space Separator 243
 
11.3%
Other Punctuation 157
 
7.3%
Uppercase Letter 68
 
3.2%
Lowercase Letter 20
 
0.9%
Close Punctuation 16
 
0.7%
Open Punctuation 16
 
0.7%
Decimal Number 11
 
0.5%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 53
 
3.3%
기 42
 
2.6%
제 40
 
2.5%
스 36
 
2.2%
원 34
 
2.1%
단 31
 
1.9%
피 31
 
1.9%
이 30
 
1.9%
용 30
 
1.9%
지 29
 
1.8%
Other values (293) 1256
77.9%
Uppercase Letter
ValueCountFrequency (%)
T 10
14.7%
C 7
10.3%
O 6
8.8%
L 6
8.8%
N 6
8.8%
D 4
 
5.9%
R 4
 
5.9%
I 4
 
5.9%
P 4
 
5.9%
V 3
 
4.4%
Other values (7) 14
20.6%
Lowercase Letter
ValueCountFrequency (%)
e 3
15.0%
l 3
15.0%
t 2
10.0%
o 2
10.0%
s 1
 
5.0%
p 1
 
5.0%
i 1
 
5.0%
r 1
 
5.0%
h 1
 
5.0%
d 1
 
5.0%
Other values (4) 4
20.0%
Decimal Number
ValueCountFrequency (%)
4 5
45.5%
0 2
 
18.2%
3 1
 
9.1%
6 1
 
9.1%
2 1
 
9.1%
9 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 154
98.1%
/ 3
 
1.9%
Space Separator
ValueCountFrequency (%)
243
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1612
75.2%
Common 445
 
20.7%
Latin 88
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 53
 
3.3%
기 42
 
2.6%
제 40
 
2.5%
스 36
 
2.2%
원 34
 
2.1%
단 31
 
1.9%
피 31
 
1.9%
이 30
 
1.9%
용 30
 
1.9%
지 29
 
1.8%
Other values (293) 1256
77.9%
Latin
ValueCountFrequency (%)
T 10
 
11.4%
C 7
 
8.0%
O 6
 
6.8%
L 6
 
6.8%
N 6
 
6.8%
D 4
 
4.5%
R 4
 
4.5%
I 4
 
4.5%
P 4
 
4.5%
V 3
 
3.4%
Other values (21) 34
38.6%
Common
ValueCountFrequency (%)
243
54.6%
, 154
34.6%
) 16
 
3.6%
( 16
 
3.6%
4 5
 
1.1%
/ 3
 
0.7%
- 2
 
0.4%
0 2
 
0.4%
3 1
 
0.2%
6 1
 
0.2%
Other values (2) 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1612
75.2%
ASCII 533
 
24.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
243
45.6%
, 154
28.9%
) 16
 
3.0%
( 16
 
3.0%
T 10
 
1.9%
C 7
 
1.3%
O 6
 
1.1%
L 6
 
1.1%
N 6
 
1.1%
4 5
 
0.9%
Other values (33) 64
 
12.0%
Hangul
ValueCountFrequency (%)
가 53
 
3.3%
기 42
 
2.6%
제 40
 
2.5%
스 36
 
2.2%
원 34
 
2.1%
단 31
 
1.9%
피 31
 
1.9%
이 30
 
1.9%
용 30
 
1.9%
지 29
 
1.8%
Other values (293) 1256
77.9%

소재지도로명주소
Text

MISSING 

Distinct210
Distinct (%)93.3%
Missing7
Missing (%)3.0%
Memory size1.9 KiB
2023-12-12T09:01:25.917271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length50
Mean length30.764444
Min length19

Characters and Unicode

Total characters6922
Distinct characters129
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

Unique198 ?
Unique (%)88.0%

Sample

1st row경기도 동두천시 신천로366번길 7 (상봉암동) 외 2필지
2nd row경기도 동두천시 삼육사로729번길 74-44, [2필지(178, 178-2)] (상패동)
3rd row경기도 동두천시 하봉암로 27-20 (하봉암동)
4th row경기도 동두천시 삼육사로729번길 74-20 (상패동)
5th row경기도 동두천시 승전로 16 (하봉암동) (총 2 필지) 외 1필지
ValueCountFrequency (%)
경기도 225
 
16.9%
동두천시 225
 
16.9%
동두천동 67
 
5.0%
상패동 44
 
3.3%
외 43
 
3.2%
상봉암동 27
 
2.0%
하봉암동 26
 
2.0%
97 25
 
1.9%
동두천로 25
 
1.9%
지행동 19
 
1.4%
Other values (294) 607
45.5%
2023-12-12T09:01:26.276558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1109
 
16.0%
동 605
 
8.7%
천 356
 
5.1%
두 341
 
4.9%
) 231
 
3.3%
( 231
 
3.3%
기 226
 
3.3%
경 225
 
3.3%
시 225
 
3.3%
도 225
 
3.3%
Other values (119) 3148
45.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3926
56.7%
Decimal Number 1265
 
18.3%
Space Separator 1109
 
16.0%
Close Punctuation 232
 
3.4%
Open Punctuation 232
 
3.4%
Dash Punctuation 87
 
1.3%
Other Punctuation 68
 
1.0%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 605
15.4%
천 356
 
9.1%
두 341
 
8.7%
기 226
 
5.8%
경 225
 
5.7%
시 225
 
5.7%
도 225
 
5.7%
로 207
 
5.3%
번 133
 
3.4%
길 128
 
3.3%
Other values (98) 1255
32.0%
Decimal Number
ValueCountFrequency (%)
1 180
14.2%
2 168
13.3%
3 162
12.8%
7 138
10.9%
0 138
10.9%
6 117
9.2%
4 108
8.5%
9 94
7.4%
5 94
7.4%
8 66
 
5.2%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
B 1
33.3%
D 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 231
99.6%
] 1
 
0.4%
Open Punctuation
ValueCountFrequency (%)
( 231
99.6%
[ 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
, 66
97.1%
' 2
 
2.9%
Space Separator
ValueCountFrequency (%)
1109
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3926
56.7%
Common 2993
43.2%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 605
15.4%
천 356
 
9.1%
두 341
 
8.7%
기 226
 
5.8%
경 225
 
5.7%
시 225
 
5.7%
도 225
 
5.7%
로 207
 
5.3%
번 133
 
3.4%
길 128
 
3.3%
Other values (98) 1255
32.0%
Common
ValueCountFrequency (%)
1109
37.1%
) 231
 
7.7%
( 231
 
7.7%
1 180
 
6.0%
2 168
 
5.6%
3 162
 
5.4%
7 138
 
4.6%
0 138
 
4.6%
6 117
 
3.9%
4 108
 
3.6%
Other values (8) 411
 
13.7%
Latin
ValueCountFrequency (%)
G 1
33.3%
B 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3926
56.7%
ASCII 2996
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1109
37.0%
) 231
 
7.7%
( 231
 
7.7%
1 180
 
6.0%
2 168
 
5.6%
3 162
 
5.4%
7 138
 
4.6%
0 138
 
4.6%
6 117
 
3.9%
4 108
 
3.6%
Other values (11) 414
 
13.8%
Hangul
ValueCountFrequency (%)
동 605
15.4%
천 356
 
9.1%
두 341
 
8.7%
기 226
 
5.8%
경 225
 
5.7%
시 225
 
5.7%
도 225
 
5.7%
로 207
 
5.3%
번 133
 
3.4%
길 128
 
3.3%
Other values (98) 1255
32.0%

소재지지번주소
Text

Distinct222
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-12-12T09:01:26.468024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length51
Mean length23.974138
Min length16

Characters and Unicode

Total characters5562
Distinct characters107
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

Unique214 ?
Unique (%)92.2%

Sample

1st row경기도 동두천시 상봉암동 211번지 외 2필지
2nd row경기도 동두천시 상패동 178번지 [2필지(178, 178-2)]
3rd row경기도 동두천시 하봉암동 338-5
4th row경기도 동두천시 상패동 176번지
5th row경기도 동두천시 하봉암동 91-4번지 외 1필지
ValueCountFrequency (%)
동두천시 237
20.5%
경기도 231
20.0%
동두천동 73
 
6.3%
상패동 52
 
4.5%
외 44
 
3.8%
상봉암동 31
 
2.7%
하봉암동 27
 
2.3%
지행동 23
 
2.0%
1필지 16
 
1.4%
722-3 13
 
1.1%
Other values (269) 409
35.4%
2023-12-12T09:01:26.796757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
940
16.9%
동 585
 
10.5%
두 319
 
5.7%
천 318
 
5.7%
지 245
 
4.4%
시 238
 
4.3%
기 233
 
4.2%
경 232
 
4.2%
도 231
 
4.2%
1 203
 
3.6%
Other values (97) 2018
36.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3292
59.2%
Decimal Number 1108
 
19.9%
Space Separator 940
 
16.9%
Dash Punctuation 192
 
3.5%
Close Punctuation 11
 
0.2%
Open Punctuation 11
 
0.2%
Other Punctuation 5
 
0.1%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 585
17.8%
두 319
9.7%
천 318
9.7%
지 245
 
7.4%
시 238
 
7.2%
기 233
 
7.1%
경 232
 
7.0%
도 231
 
7.0%
번 174
 
5.3%
상 83
 
2.5%
Other values (76) 634
19.3%
Decimal Number
ValueCountFrequency (%)
1 203
18.3%
2 180
16.2%
5 168
15.2%
3 143
12.9%
4 88
7.9%
7 85
7.7%
6 78
 
7.0%
0 72
 
6.5%
9 47
 
4.2%
8 44
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
33.3%
G 1
33.3%
D 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 10
90.9%
] 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 10
90.9%
[ 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
' 2
40.0%
Space Separator
ValueCountFrequency (%)
940
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3292
59.2%
Common 2267
40.8%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 585
17.8%
두 319
9.7%
천 318
9.7%
지 245
 
7.4%
시 238
 
7.2%
기 233
 
7.1%
경 232
 
7.0%
도 231
 
7.0%
번 174
 
5.3%
상 83
 
2.5%
Other values (76) 634
19.3%
Common
ValueCountFrequency (%)
940
41.5%
1 203
 
9.0%
- 192
 
8.5%
2 180
 
7.9%
5 168
 
7.4%
3 143
 
6.3%
4 88
 
3.9%
7 85
 
3.7%
6 78
 
3.4%
0 72
 
3.2%
Other values (8) 118
 
5.2%
Latin
ValueCountFrequency (%)
B 1
33.3%
G 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3292
59.2%
ASCII 2270
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
940
41.4%
1 203
 
8.9%
- 192
 
8.5%
2 180
 
7.9%
5 168
 
7.4%
3 143
 
6.3%
4 88
 
3.9%
7 85
 
3.7%
6 78
 
3.4%
0 72
 
3.2%
Other values (11) 121
 
5.3%
Hangul
ValueCountFrequency (%)
동 585
17.8%
두 319
9.7%
천 318
9.7%
지 245
 
7.4%
시 238
 
7.2%
기 233
 
7.1%
경 232
 
7.0%
도 231
 
7.0%
번 174
 
5.3%
상 83
 
2.5%
Other values (76) 634
19.3%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct165
Distinct (%)73.0%
Missing6
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean37.925136
Minimum37.867444
Maximum37.970542
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T09:01:26.925548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.867444
5-th percentile37.890334
Q137.905175
median37.931171
Q337.94053
95-th percentile37.964225
Maximum37.970542
Range0.10309848
Interquartile range (IQR)0.035354805

Descriptive statistics

Standard deviation0.024444083
Coefficient of variation (CV)0.00064453515
Kurtosis-0.89773532
Mean37.925136
Median Absolute Deviation (MAD)0.0205172
Skewness-0.078517629
Sum8571.0807
Variance0.00059751319
MonotonicityNot monotonic
2023-12-12T09:01:27.069648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.89033403 24
 
10.3%
37.92712296 3
 
1.3%
37.93617697 3
 
1.3%
37.9342567 3
 
1.3%
37.93299448 3
 
1.3%
37.96836116 3
 
1.3%
37.95650911 3
 
1.3%
37.94677917 3
 
1.3%
37.90686496 3
 
1.3%
37.96987566 3
 
1.3%
Other values (155) 175
75.4%
(Missing) 6
 
2.6%
ValueCountFrequency (%)
37.86744374 1
 
0.4%
37.87191841 1
 
0.4%
37.87640879 1
 
0.4%
37.87805546 1
 
0.4%
37.88000569 1
 
0.4%
37.88204006 1
 
0.4%
37.88567843 1
 
0.4%
37.89033403 24
10.3%
37.89508751 1
 
0.4%
37.89594917 1
 
0.4%
ValueCountFrequency (%)
37.97054222 1
 
0.4%
37.97017636 1
 
0.4%
37.96987566 3
1.3%
37.96836116 3
1.3%
37.96826693 1
 
0.4%
37.96682221 1
 
0.4%
37.96621925 1
 
0.4%
37.96428277 1
 
0.4%
37.96405159 1
 
0.4%
37.96403842 1
 
0.4%

경도
Real number (ℝ)

MISSING 

Distinct165
Distinct (%)73.0%
Missing6
Missing (%)2.6%
Infinite0
Infinite (%)0.0%
Mean127.05077
Minimum127.01162
Maximum127.10848
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2023-12-12T09:01:27.198659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.01162
5-th percentile127.02426
Q1127.04953
median127.05287
Q3127.05478
95-th percentile127.06693
Maximum127.10848
Range0.0968605
Interquartile range (IQR)0.005249475

Descriptive statistics

Standard deviation0.0143459
Coefficient of variation (CV)0.00011291471
Kurtosis2.5813912
Mean127.05077
Median Absolute Deviation (MAD)0.0027871
Skewness0.1080687
Sum28713.473
Variance0.00020580485
MonotonicityNot monotonic
2023-12-12T09:01:27.355813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0544543 24
 
10.3%
127.0330115 3
 
1.3%
127.0528691 3
 
1.3%
127.0527328 3
 
1.3%
127.0502597 3
 
1.3%
127.0622145 3
 
1.3%
127.0646184 3
 
1.3%
127.0536584 3
 
1.3%
127.0383722 3
 
1.3%
127.064733 3
 
1.3%
Other values (155) 175
75.4%
(Missing) 6
 
2.6%
ValueCountFrequency (%)
127.0116225 2
0.9%
127.012192 2
0.9%
127.0203321 1
0.4%
127.021359 1
0.4%
127.0228587 1
0.4%
127.0230326 2
0.9%
127.023662 2
0.9%
127.0242308 1
0.4%
127.024354 1
0.4%
127.0252744 1
0.4%
ValueCountFrequency (%)
127.108483 1
0.4%
127.107038 1
0.4%
127.0945094 1
0.4%
127.0903274 1
0.4%
127.0901843 1
0.4%
127.0864807 1
0.4%
127.069931 1
0.4%
127.0685335 1
0.4%
127.0680233 1
0.4%
127.0676997 1
0.4%

관리기관명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
경기도 동두천시청 일자리경제과
232 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 동두천시청 일자리경제과
2nd row경기도 동두천시청 일자리경제과
3rd row경기도 동두천시청 일자리경제과
4th row경기도 동두천시청 일자리경제과
5th row경기도 동두천시청 일자리경제과

Common Values

ValueCountFrequency (%)
경기도 동두천시청 일자리경제과 232
100.0%

Length

2023-12-12T09:01:27.488767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:01:27.585350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 232
33.3%
동두천시청 232
33.3%
일자리경제과 232
33.3%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
031-860-2281
232 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row031-860-2281
2nd row031-860-2281
3rd row031-860-2281
4th row031-860-2281
5th row031-860-2281

Common Values

ValueCountFrequency (%)
031-860-2281 232
100.0%

Length

2023-12-12T09:01:27.714972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:01:27.809572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
031-860-2281 232
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
2023-06-26
232 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-26
2nd row2023-06-26
3rd row2023-06-26
4th row2023-06-26
5th row2023-06-26

Common Values

ValueCountFrequency (%)
2023-06-26 232
100.0%

Length

2023-12-12T09:01:27.917770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:01:28.030194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-26 232
100.0%

Interactions

2023-12-12T09:01:22.144464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:21.474016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:21.824172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:22.261717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:21.588776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:21.939702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:22.356376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:21.709848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T09:01:22.040872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:01:28.079734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분종업원수위도경도
구분1.0000.4710.9290.656
종업원수0.4711.0000.0000.000
위도0.9290.0001.0000.895
경도0.6560.0000.8951.000
2023-12-12T09:01:28.170903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수위도경도구분
종업원수1.0000.1070.0020.191
위도0.1071.0000.3370.638
경도0.0020.3371.0000.326
구분0.1910.6380.3261.000

Missing values

2023-12-12T09:01:22.475948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:01:22.642625image/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.
2023-12-12T09:01:22.773043image/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

회사명구분최초등록일전화번호종업원수생산품소재지도로명주소소재지지번주소위도경도관리기관명관리기관전화번호데이터기준일자
0(사)대한민국공무원 공상유공자회 상훈사업부개별공장2018-03-06031-865-000810배지, 훈장, 메달, 계급장, 깃발경기도 동두천시 신천로366번길 7 (상봉암동) 외 2필지경기도 동두천시 상봉암동 211번지 외 2필지37.946779127.053658경기도 동두천시청 일자리경제과031-860-22812023-06-26
1(유)서호산업개별공장2009-12-11031-842-720916밀폐용기, 과일용기, IT트레이경기도 동두천시 삼육사로729번길 74-44, [2필지(178, 178-2)] (상패동)경기도 동두천시 상패동 178번지 [2필지(178, 178-2)]37.912076127.036554경기도 동두천시청 일자리경제과031-860-22812023-06-26
2(주)그린코리아개별공장2020-12-10031-866-31013방염제, 탈취향균제, 살균제, 소독제분사기, 방염합판, 목재, MDF, 재난안전계측기경기도 동두천시 하봉암로 27-20 (하봉암동)경기도 동두천시 하봉암동 338-537.957938127.058668경기도 동두천시청 일자리경제과031-860-22812023-06-26
3(주)대성팩개별공장2020-03-23031-865-71456플라스틱 트레이경기도 동두천시 삼육사로729번길 74-20 (상패동)경기도 동두천시 상패동 176번지37.911092127.033886경기도 동두천시청 일자리경제과031-860-22812023-06-26
4(주)더브류.제이개별공장1997-08-08031-867-7191112스카프,복지 및 넥타이경기도 동두천시 승전로 16 (하봉암동) (총 2 필지) 외 1필지경기도 동두천시 하봉암동 91-4번지 외 1필지37.969876127.064733경기도 동두천시청 일자리경제과031-860-22812023-06-26
5(주)동원연탄개별공장1990-11-29031-865-416037연탄,조개탄경기도 동두천시 평화로 2709 (동두천동)경기도 동두천시 동두천동 245-102번지37.929797127.055491경기도 동두천시청 일자리경제과031-860-22812023-06-26
6(주)마니커동두천지점개별공장1990-11-08031-868-6007337계육경기도 동두천시 승전로 6 (하봉암동)경기도 동두천시 하봉암동 127번지37.970176127.065619경기도 동두천시청 일자리경제과031-860-22812023-06-26
7(주)맥스다미론개별공장2009-09-1002-2636-30524다다미, 방석, 자리경기도 동두천시 삼육사로 774, 1동 3층 1 (상패동)경기도 동두천시 상패동 211-1번지 대륙산업개발 주식회사 1동 3층 137.906865127.038372경기도 동두천시청 일자리경제과031-860-22812023-06-26
8(주)명보개별공장2022-02-10031-862-150020알루미늄 표면처리 제품경기도 동두천시 평화로 3014, 주식회사 명보(상봉암동)경기도 동두천시 상봉암동 38-7 주식회사 명보37.955593127.062916경기도 동두천시청 일자리경제과031-860-22812023-06-26
9(주)모컴테크개별공장2002-10-30031-861-04984가상및 증강현실 영상장치, 스크린, 현미경, 멀티미디어 학습장치, 프롬프터경기도 동두천시 삼육사로692번길 108 (상패동)경기도 동두천시 상패동 660-9번지37.905259127.026541경기도 동두천시청 일자리경제과031-860-22812023-06-26
회사명구분최초등록일전화번호종업원수생산품소재지도로명주소소재지지번주소위도경도관리기관명관리기관전화번호데이터기준일자
222대한민국고엽제전우회지식산업센터2016-07-2202-2679-735739의류봉제품경기도 동두천시 동두천로 97 (지행동) 10층 1001호경기도 동두천시 지행동 722-3 10층 1001호37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
223엑시언지식산업센터2021-01-13031-861-05275여성의류경기도 동두천시 동두천로 97 (지행동) 6층 606호경기도 동두천시 지행동 722-3 6층 606호37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
224주식회사 넥스트지식산업센터2009-12-16031-826-94521LED Module, NL-024, 6, NLo44, NL-034경기도 동두천시 동두천로 97, 6층 603호 (지행동, 동두천싸이언스타워)경기도 동두천시 지행동 722-3번지 동두천시 싸이언스타워 6층 603호37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
225주식회사 대영니트지식산업센터2015-01-23070-4848-545915스웨터, 근무복, 편조제품경기도 동두천시 동두천로 97 (지행동) 4층 401호경기도 동두천시 지행동 722-3 4층 401호37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
226주식회사 딜리(싸이언스타워)지식산업센터2020-02-24031-860-55003안내 전광판경기도 동두천시 동두천로 97, 싸이언스타워동 6층 602호 (지행동)경기도 동두천시 지행동 722-3번지 싸이언스타워동 6층 602호37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
227주식회사 비에이치아이지식산업센터2018-02-21031-865-732714근무복, 작업복, 운동복, 스카프, 군복, 셔츠, 런닝, 경찰복, 소방복경기도 동두천시 동두천로 97 (지행동) 9층 905호 9층 905호 외 3필지경기도 동두천시 지행동 722-3 9층 905호 9층 905호 외 3필지37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
228주식회사 피엔에이코리아지식산업센터2016-01-21031-863-863421의류, 가방, 모자경기도 동두천시 동두천로 97, 9층 901호(지행동, 동두천싸이언스타워) 9층 901호 외 1필지경기도 동두천시 지행동 722-3 동두천싸이언스타워 9층 901호 9층 901호 외 1필지37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
229진성산업지식산업센터2015-01-23031-868-038847스웨터, 근무복, 편조제품경기도 동두천시 동두천로 97 (지행동) 8층 801호경기도 동두천시 지행동 722-3 8층 801호37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
230클로도 코리아지식산업센터2014-06-26031-866-485812셔츠, 체육복, 내의경기도 동두천시 동두천로 97, 두드림패션센터동 5층 1 (지행동)경기도 동두천시 지행동 722-3번지 두드림패션센터동 5층 137.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26
231필립테크 주식회사지식산업센터2021-05-27031-857-89553클린게이트, 공기청정기경기도 동두천시 동두천로 97, 싸이언스타워동 6층 601호(지행동) 싸이언스타워동 6층 601호경기도 동두천시지행동 722-3 싸이언스타워동 6층 601호 싸이언스타워동 6층 601호37.890334127.054454경기도 동두천시청 일자리경제과031-860-22812023-06-26