Overview

Dataset statistics

Number of variables19
Number of observations10000
Missing cells1194
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory166.0 B

Variable types

Text8
Categorical4
Numeric6
Unsupported1

Alerts

용지면적(㎡) is highly overall correlated with 건축면적(㎡)High correlation
건축면적(㎡) is highly overall correlated with 용지면적(㎡) and 1 other fieldsHigh correlation
종업원수 is highly overall correlated with 건축면적(㎡)High correlation
정제우편번호 is highly overall correlated with 정제WGS84위도 and 1 other fieldsHigh correlation
정제WGS84위도 is highly overall correlated with 정제우편번호 and 1 other fieldsHigh correlation
정제WGS84경도 is highly overall correlated with 행정기관명High correlation
행정기관명 is highly overall correlated with 정제우편번호 and 2 other fieldsHigh correlation
설립구분명 is highly imbalanced (76.0%)Imbalance
공장규모구분명 is highly imbalanced (87.4%)Imbalance
정제우편번호 has 149 (1.5%) missing valuesMissing
정제도로명주소 has 483 (4.8%) missing valuesMissing
정제WGS84위도 has 281 (2.8%) missing valuesMissing
정제WGS84경도 has 281 (2.8%) missing valuesMissing
용지면적(㎡) is highly skewed (γ1 = 61.46778296)Skewed
건축면적(㎡) is highly skewed (γ1 = 52.50394089)Skewed
종업원수 is highly skewed (γ1 = 93.73829054)Skewed
공장등록일 is an unsupported type, check if it needs cleaning or further analysisUnsupported
용지면적(㎡) has 2513 (25.1%) zerosZeros
종업원수 has 297 (3.0%) zerosZeros

Reproduction

Analysis started2023-12-10 22:13:40.115478
Analysis finished2023-12-10 22:13:47.482351
Duration7.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

회사명
Text

Distinct9728
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:13:47.724848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length27
Mean length7.1314
Min length1

Characters and Unicode

Total characters71314
Distinct characters841
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

Unique9486 ?
Unique (%)94.9%

Sample

1st row(주)아이디온
2nd row선보하이테크공업사
3rd row(주)에이오에프
4th row뉴토크코리아(주)
5th row신광산업
ValueCountFrequency (%)
주식회사 896
 
7.9%
농업회사법인 55
 
0.5%
주 29
 
0.3%
제2공장 22
 
0.2%
제1공장 10
 
0.1%
2공장 10
 
0.1%
유한회사 10
 
0.1%
대성산업 7
 
0.1%
코리아 7
 
0.1%
eng 7
 
0.1%
Other values (9935) 10321
90.7%
2023-12-11T07:13:48.180461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6400
 
9.0%
) 5364
 
7.5%
( 5360
 
7.5%
이 2328
 
3.3%
스 1907
 
2.7%
사 1483
 
2.1%
1399
 
2.0%
업 1263
 
1.8%
에 1178
 
1.7%
회 1130
 
1.6%
Other values (831) 43502
61.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57648
80.8%
Close Punctuation 5366
 
7.5%
Open Punctuation 5362
 
7.5%
Space Separator 1399
 
2.0%
Uppercase Letter 945
 
1.3%
Lowercase Letter 183
 
0.3%
Decimal Number 153
 
0.2%
Other Symbol 141
 
0.2%
Other Punctuation 102
 
0.1%
Dash Punctuation 15
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6400
 
11.1%
이 2328
 
4.0%
스 1907
 
3.3%
사 1483
 
2.6%
업 1263
 
2.2%
에 1178
 
2.0%
회 1130
 
2.0%
식 1109
 
1.9%
산 978
 
1.7%
아 861
 
1.5%
Other values (764) 39011
67.7%
Uppercase Letter
ValueCountFrequency (%)
S 88
 
9.3%
E 88
 
9.3%
C 81
 
8.6%
N 78
 
8.3%
T 69
 
7.3%
G 58
 
6.1%
I 48
 
5.1%
O 46
 
4.9%
M 43
 
4.6%
K 43
 
4.6%
Other values (14) 303
32.1%
Lowercase Letter
ValueCountFrequency (%)
e 24
13.1%
n 17
 
9.3%
a 15
 
8.2%
i 14
 
7.7%
r 13
 
7.1%
o 13
 
7.1%
c 13
 
7.1%
t 11
 
6.0%
l 9
 
4.9%
y 7
 
3.8%
Other values (13) 47
25.7%
Decimal Number
ValueCountFrequency (%)
2 70
45.8%
1 40
26.1%
3 13
 
8.5%
0 9
 
5.9%
5 5
 
3.3%
4 5
 
3.3%
8 4
 
2.6%
9 4
 
2.6%
6 3
 
2.0%
Other Punctuation
ValueCountFrequency (%)
. 67
65.7%
& 31
30.4%
, 3
 
2.9%
＆ 1
 
1.0%
Close Punctuation
ValueCountFrequency (%)
) 5364
> 99.9%
] 2
 
< 0.1%
Open Punctuation
ValueCountFrequency (%)
( 5360
> 99.9%
[ 2
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1399
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 141
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57789
81.0%
Common 12397
 
17.4%
Latin 1128
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6400
 
11.1%
이 2328
 
4.0%
스 1907
 
3.3%
사 1483
 
2.6%
업 1263
 
2.2%
에 1178
 
2.0%
회 1130
 
2.0%
식 1109
 
1.9%
산 978
 
1.7%
아 861
 
1.5%
Other values (765) 39152
67.7%
Latin
ValueCountFrequency (%)
S 88
 
7.8%
E 88
 
7.8%
C 81
 
7.2%
N 78
 
6.9%
T 69
 
6.1%
G 58
 
5.1%
I 48
 
4.3%
O 46
 
4.1%
M 43
 
3.8%
K 43
 
3.8%
Other values (37) 486
43.1%
Common
ValueCountFrequency (%)
) 5364
43.3%
( 5360
43.2%
1399
 
11.3%
2 70
 
0.6%
. 67
 
0.5%
1 40
 
0.3%
& 31
 
0.3%
- 15
 
0.1%
3 13
 
0.1%
0 9
 
0.1%
Other values (9) 29
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57648
80.8%
ASCII 13524
 
19.0%
None 142
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6400
 
11.1%
이 2328
 
4.0%
스 1907
 
3.3%
사 1483
 
2.6%
업 1263
 
2.2%
에 1178
 
2.0%
회 1130
 
2.0%
식 1109
 
1.9%
산 978
 
1.7%
아 861
 
1.5%
Other values (764) 39011
67.7%
ASCII
ValueCountFrequency (%)
) 5364
39.7%
( 5360
39.6%
1399
 
10.3%
S 88
 
0.7%
E 88
 
0.7%
C 81
 
0.6%
N 78
 
0.6%
2 70
 
0.5%
T 69
 
0.5%
. 67
 
0.5%
Other values (55) 860
 
6.4%
None
ValueCountFrequency (%)
㈜ 141
99.3%
＆ 1
 
0.7%

행정기관명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경기도 김포시
1752 
경기도 부천시
1031 
경기도 남양주시
818 
경기도 용인시
813 
경기도 양주시
810 
Other values (26)
4776 

Length

Max length26
Median length7
Mean length7.18
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row경기도 수원시
2nd row경기도 김포시
3rd row경기도 용인시
4th row경기도 광주시
5th row경기도 양주시

Common Values

ValueCountFrequency (%)
경기도 김포시 1752
17.5%
경기도 부천시 1031
10.3%
경기도 남양주시 818
 
8.2%
경기도 용인시 813
 
8.1%
경기도 양주시 810
 
8.1%
경기도 광주시 740
 
7.4%
경기도 안성시 594
 
5.9%
경기도 안양시 507
 
5.1%
경기도 군포시 460
 
4.6%
경기도 고양시 406
 
4.1%
Other values (21) 2069
20.7%

Length

2023-12-11T07:13:48.312080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 9944
49.8%
김포시 1752
 
8.8%
부천시 1031
 
5.2%
남양주시 818
 
4.1%
용인시 813
 
4.1%
양주시 810
 
4.1%
광주시 740
 
3.7%
안성시 594
 
3.0%
안양시 507
 
2.5%
군포시 460
 
2.3%
Other values (22) 2504
 
12.5%

설립구분명
Categorical

IMBALANCE 

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
일반
8861 
창업
 
578
일반산업단지
 
467
도시첨단산업단지
 
47
국가산업단지
 
43
Other values (2)
 
4

Length

Max length8
Median length2
Mean length2.2332
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row일반
2nd row일반
3rd row창업
4th row일반
5th row일반

Common Values

ValueCountFrequency (%)
일반 8861
88.6%
창업 578
 
5.8%
일반산업단지 467
 
4.7%
도시첨단산업단지 47
 
0.5%
국가산업단지 43
 
0.4%
농공단지 3
 
< 0.1%
지식산업센터 1
 
< 0.1%

Length

2023-12-11T07:13:48.416215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:13:48.526668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 8861
88.6%
창업 578
 
5.8%
일반산업단지 467
 
4.7%
도시첨단산업단지 47
 
0.5%
국가산업단지 43
 
0.4%
농공단지 3
 
< 0.1%
지식산업센터 1
 
< 0.1%

용지면적(㎡)
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct4901
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2120.5032
Minimum0
Maximum940392
Zeros2513
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:13:48.666903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median854
Q32139.75
95-th percentile7399.3
Maximum940392
Range940392
Interquartile range (IQR)2139.75

Descriptive statistics

Standard deviation11599.89
Coefficient of variation (CV)5.4703476
Kurtosis4622.0601
Mean2120.5032
Median Absolute Deviation (MAD)854
Skewness61.467783
Sum21205032
Variance1.3455745 × 108
MonotonicityNot monotonic
2023-12-11T07:13:48.794139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 2513
 
25.1%
330.0 30
 
0.3%
198.0 29
 
0.3%
990.0 27
 
0.3%
1322.0 26
 
0.3%
1653.0 20
 
0.2%
660.0 19
 
0.2%
992.0 19
 
0.2%
1649.0 16
 
0.2%
1648.0 16
 
0.2%
Other values (4891) 7285
72.9%
ValueCountFrequency (%)
0.0 2513
25.1%
5.51 1
 
< 0.1%
6.24 1
 
< 0.1%
8.5 1
 
< 0.1%
10.34 1
 
< 0.1%
11.074 1
 
< 0.1%
11.55 1
 
< 0.1%
11.89 1
 
< 0.1%
11.94 1
 
< 0.1%
11.95 1
 
< 0.1%
ValueCountFrequency (%)
940392.0 1
< 0.1%
498908.03 1
< 0.1%
138970.8 1
< 0.1%
114182.3 1
< 0.1%
88708.0 1
< 0.1%
80726.0 1
< 0.1%
75227.0 1
< 0.1%
74891.0 1
< 0.1%
73550.9 1
< 0.1%
73273.0 2
< 0.1%

건축면적(㎡)
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct6402
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean664.74662
Minimum0
Maximum226503.43
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:13:48.919944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile44.93985
Q1162.6625
median326.325
Q3601.41
95-th percentile1996.0575
Maximum226503.43
Range226503.43
Interquartile range (IQR)438.7475

Descriptive statistics

Standard deviation3118.0819
Coefficient of variation (CV)4.6906321
Kurtosis3430.2155
Mean664.74662
Median Absolute Deviation (MAD)187.09
Skewness52.503941
Sum6647466.2
Variance9722434.4
MonotonicityNot monotonic
2023-12-11T07:13:49.052177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 332
 
3.3%
396.0 148
 
1.5%
330.0 71
 
0.7%
100.0 70
 
0.7%
165.0 51
 
0.5%
300.0 42
 
0.4%
495.0 41
 
0.4%
200.0 41
 
0.4%
180.0 38
 
0.4%
50.0 37
 
0.4%
Other values (6392) 9129
91.3%
ValueCountFrequency (%)
0.0 5
0.1%
2.24 1
 
< 0.1%
3.6 1
 
< 0.1%
4.1 1
 
< 0.1%
5.85 1
 
< 0.1%
6.0 1
 
< 0.1%
6.02 1
 
< 0.1%
6.6 1
 
< 0.1%
7.0 1
 
< 0.1%
7.6 1
 
< 0.1%
ValueCountFrequency (%)
226503.43 1
< 0.1%
158801.27 1
< 0.1%
56598.39 1
< 0.1%
41888.07 1
< 0.1%
30473.81 1
< 0.1%
28515.2 1
< 0.1%
27932.53 1
< 0.1%
21939.0 1
< 0.1%
20836.69 1
< 0.1%
20169.3 1
< 0.1%

종업원수
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct173
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.6016
Minimum0
Maximum29809
Zeros297
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:13:49.162754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median7
Q313
95-th percentile40
Maximum29809
Range29809
Interquartile range (IQR)9

Descriptive statistics

Standard deviation305.28402
Coefficient of variation (CV)18.388831
Kurtosis9088.2472
Mean16.6016
Median Absolute Deviation (MAD)4
Skewness93.738291
Sum166016
Variance93198.332
MonotonicityNot monotonic
2023-12-11T07:13:49.290976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1026
 
10.3%
4 896
 
9.0%
3 887
 
8.9%
2 732
 
7.3%
6 677
 
6.8%
10 598
 
6.0%
8 496
 
5.0%
7 494
 
4.9%
1 395
 
4.0%
9 350
 
3.5%
Other values (163) 3449
34.5%
ValueCountFrequency (%)
0 297
 
3.0%
1 395
 
4.0%
2 732
7.3%
3 887
8.9%
4 896
9.0%
5 1026
10.3%
6 677
6.8%
7 494
4.9%
8 496
5.0%
9 350
 
3.5%
ValueCountFrequency (%)
29809 1
< 0.1%
6014 1
< 0.1%
976 1
< 0.1%
968 1
< 0.1%
600 1
< 0.1%
593 1
< 0.1%
570 1
< 0.1%
500 1
< 0.1%
482 1
< 0.1%
430 1
< 0.1%

공장규모구분명
Categorical

IMBALANCE 

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
소기업
9612 
중기업
 
362
대기업
 
22
중견기업
 
4

Length

Max length4
Median length3
Mean length3.0004
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소기업 9612
96.1%
중기업 362
 
3.6%
대기업 22
 
0.2%
중견기업 4
 
< 0.1%

Length

2023-12-11T07:13:49.423471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:13:49.524951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 9612
96.1%
중기업 362
 
3.6%
대기업 22
 
0.2%
중견기업 4
 
< 0.1%

공장등록일
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size156.2 KiB

용도지역명
Categorical

Distinct31
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
/ 관리지역 / 계획관리지역
3386 
도시지역 / 공업지역 / 일반공업지역
2194 
도시지역 / 녹지지역 / 자연녹지지역
1108 
도시지역 / 주거지역 / 준주거지역
535 
/ 관리지역
534 
Other values (26)
2243 

Length

Max length23
Median length20
Mean length17.589
Min length1

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row / 도시지역 / 주거지역
2nd row / 관리지역 / 관리지역기타
3rd row도시지역 / 녹지지역 / 자연녹지지역
4th row / 관리지역 / 계획관리지역
5th row / 관리지역 / 계획관리지역

Common Values

ValueCountFrequency (%)
/ 관리지역 / 계획관리지역 3386
33.9%
도시지역 / 공업지역 / 일반공업지역 2194
21.9%
도시지역 / 녹지지역 / 자연녹지지역 1108
 
11.1%
도시지역 / 주거지역 / 준주거지역 535
 
5.3%
/ 관리지역 534
 
5.3%
도시지역 / 공업지역 / 준공업지역 452
 
4.5%
도시지역 / 주거지역 / 제1종일반주거지역 371
 
3.7%
/ 관리지역 / 관리지역기타 332
 
3.3%
도시지역 / 주거지역 / 제2종일반주거지역 293
 
2.9%
도시지역 / 상업지역 / 근린상업지역 180
 
1.8%
Other values (21) 615
 
6.2%

Length

2023-12-11T07:13:49.634922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
19220
43.9%
도시지역 5462
 
12.5%
관리지역 4332
 
9.9%
계획관리지역 3386
 
7.7%
공업지역 2672
 
6.1%
일반공업지역 2194
 
5.0%
주거지역 1284
 
2.9%
녹지지역 1212
 
2.8%
자연녹지지역 1108
 
2.5%
준주거지역 535
 
1.2%
Other values (23) 2423
 
5.5%

지목명
Text

Distinct80
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:13:49.745962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length178
Median length4
Mean length4.4965
Min length1

Characters and Unicode

Total characters44965
Distinct characters32
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)0.3%

Sample

1st row대, 대
2nd row공장용지
3rd row공장용지
4th row공장용지
5th row공장용지
ValueCountFrequency (%)
공장용지 8902
72.7%
대 2309
 
18.8%
전 310
 
2.5%
답 204
 
1.7%
임야 195
 
1.6%
잡종지 170
 
1.4%
창고용지 70
 
0.6%
학교용지 47
 
0.4%
목장용지 8
 
0.1%
과수원 7
 
0.1%
Other values (10) 28
 
0.2%
2023-12-11T07:13:50.019071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 9211
20.5%
용 9029
20.1%
장 8915
19.8%
공 8902
19.8%
2610
 
5.8%
, 2430
 
5.4%
대 2309
 
5.1%
전 312
 
0.7%
답 204
 
0.5%
임 195
 
0.4%
Other values (22) 848
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 39925
88.8%
Space Separator 2610
 
5.8%
Other Punctuation 2430
 
5.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 9211
23.1%
용 9029
22.6%
장 8915
22.3%
공 8902
22.3%
대 2309
 
5.8%
전 312
 
0.8%
답 204
 
0.5%
임 195
 
0.5%
야 195
 
0.5%
종 171
 
0.4%
Other values (20) 482
 
1.2%
Space Separator
ValueCountFrequency (%)
2610
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2430
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 39925
88.8%
Common 5040
 
11.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 9211
23.1%
용 9029
22.6%
장 8915
22.3%
공 8902
22.3%
대 2309
 
5.8%
전 312
 
0.8%
답 204
 
0.5%
임 195
 
0.5%
야 195
 
0.5%
종 171
 
0.4%
Other values (20) 482
 
1.2%
Common
ValueCountFrequency (%)
2610
51.8%
, 2430
48.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 39925
88.8%
ASCII 5040
 
11.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 9211
23.1%
용 9029
22.6%
장 8915
22.3%
공 8902
22.3%
대 2309
 
5.8%
전 312
 
0.8%
답 204
 
0.5%
임 195
 
0.5%
야 195
 
0.5%
종 171
 
0.4%
Other values (20) 482
 
1.2%
ASCII
ValueCountFrequency (%)
2610
51.8%
, 2430
48.2%

업종명
Text

Distinct1601
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:13:50.277709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length29
Mean length16.9809
Min length1

Characters and Unicode

Total characters169809
Distinct characters363
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

Unique662 ?
Unique (%)6.6%

Sample

1st row전자부품 실장기판 제조업
2nd row주형 및 금형 제조업
3rd row그 외 기타 분류 안된 화학제품 제조업 외 1 종
4th row탭, 밸브 및 유사장치 제조업 외 1 종
5th row일반철물 제조업
ValueCountFrequency (%)
제조업 8973
 
16.3%
외 5121
 
9.3%
및 4139
 
7.5%
종 3937
 
7.2%
기타 3019
 
5.5%
1 2065
 
3.8%
그 1184
 
2.2%
금속 832
 
1.5%
2 748
 
1.4%
플라스틱 634
 
1.2%
Other values (780) 24236
44.2%
2023-12-11T07:13:51.129627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
44936
26.5%
제 11805
 
7.0%
조 10542
 
6.2%
업 10354
 
6.1%
기 7041
 
4.1%
외 5219
 
3.1%
및 4151
 
2.4%
종 4071
 
2.4%
타 3118
 
1.8%
용 2954
 
1.7%
Other values (353) 65618
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119311
70.3%
Space Separator 44936
 
26.5%
Decimal Number 4125
 
2.4%
Other Punctuation 1311
 
0.8%
Open Punctuation 63
 
< 0.1%
Close Punctuation 63
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 11805
 
9.9%
조 10542
 
8.8%
업 10354
 
8.7%
기 7041
 
5.9%
외 5219
 
4.4%
및 4151
 
3.5%
종 4071
 
3.4%
타 3118
 
2.6%
용 2954
 
2.5%
품 2846
 
2.4%
Other values (338) 57210
48.0%
Decimal Number
ValueCountFrequency (%)
1 2246
54.4%
2 800
 
19.4%
3 454
 
11.0%
4 225
 
5.5%
5 122
 
3.0%
6 95
 
2.3%
7 63
 
1.5%
9 48
 
1.2%
8 44
 
1.1%
0 28
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 1280
97.6%
. 31
 
2.4%
Space Separator
ValueCountFrequency (%)
44936
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 119311
70.3%
Common 50498
29.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 11805
 
9.9%
조 10542
 
8.8%
업 10354
 
8.7%
기 7041
 
5.9%
외 5219
 
4.4%
및 4151
 
3.5%
종 4071
 
3.4%
타 3118
 
2.6%
용 2954
 
2.5%
품 2846
 
2.4%
Other values (338) 57210
48.0%
Common
ValueCountFrequency (%)
44936
89.0%
1 2246
 
4.4%
, 1280
 
2.5%
2 800
 
1.6%
3 454
 
0.9%
4 225
 
0.4%
5 122
 
0.2%
6 95
 
0.2%
7 63
 
0.1%
( 63
 
0.1%
Other values (5) 214
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 119235
70.2%
ASCII 50498
29.7%
Compat Jamo 76
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
44936
89.0%
1 2246
 
4.4%
, 1280
 
2.5%
2 800
 
1.6%
3 454
 
0.9%
4 225
 
0.4%
5 122
 
0.2%
6 95
 
0.2%
7 63
 
0.1%
( 63
 
0.1%
Other values (5) 214
 
0.4%
Hangul
ValueCountFrequency (%)
제 11805
 
9.9%
조 10542
 
8.8%
업 10354
 
8.7%
기 7041
 
5.9%
외 5219
 
4.4%
및 4151
 
3.5%
종 4071
 
3.4%
타 3118
 
2.6%
용 2954
 
2.5%
품 2846
 
2.4%
Other values (337) 57134
47.9%
Compat Jamo
ValueCountFrequency (%)
ㆍ 76
100.0%

업종코드
Text

Distinct2822
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:13:51.942797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length432
Median length5
Mean length12.0534
Min length1

Characters and Unicode

Total characters120534
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

Unique2131 ?
Unique (%)21.3%

Sample

1st row26224
2nd row29294
3rd row20495, 20499
4th row29133, 29169
5th row25932
ValueCountFrequency (%)
28123 392
 
2.0%
28422 354
 
1.8%
25112 322
 
1.6%
32029 307
 
1.5%
25113 306
 
1.5%
26429 306
 
1.5%
26410 273
 
1.4%
26421 272
 
1.4%
29294 249
 
1.2%
22299 225
 
1.1%
Other values (498) 17063
85.0%
2023-12-11T07:13:52.538577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 30114
25.0%
1 20897
17.3%
9 14510
12.0%
10103
 
8.4%
, 10086
 
8.4%
3 9131
 
7.6%
0 6398
 
5.3%
4 5608
 
4.7%
5 4420
 
3.7%
8 3462
 
2.9%
Other values (2) 5805
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 100345
83.3%
Space Separator 10103
 
8.4%
Other Punctuation 10086
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 30114
30.0%
1 20897
20.8%
9 14510
14.5%
3 9131
 
9.1%
0 6398
 
6.4%
4 5608
 
5.6%
5 4420
 
4.4%
8 3462
 
3.5%
6 3080
 
3.1%
7 2725
 
2.7%
Space Separator
ValueCountFrequency (%)
10103
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10086
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120534
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 30114
25.0%
1 20897
17.3%
9 14510
12.0%
10103
 
8.4%
, 10086
 
8.4%
3 9131
 
7.6%
0 6398
 
5.3%
4 5608
 
4.7%
5 4420
 
3.7%
8 3462
 
2.9%
Other values (2) 5805
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120534
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 30114
25.0%
1 20897
17.3%
9 14510
12.0%
10103
 
8.4%
, 10086
 
8.4%
3 9131
 
7.6%
0 6398
 
5.3%
4 5608
 
4.7%
5 4420
 
3.7%
8 3462
 
2.9%
Other values (2) 5805
 
4.8%

생산품정보
Text

Distinct8248
Distinct (%)82.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:13:52.868031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length118
Median length75
Mean length9.4273
Min length1

Characters and Unicode

Total characters94273
Distinct characters920
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7632 ?
Unique (%)76.3%

Sample

1st row반도체번인보드
2nd row주형및금형
3rd row윤활유
4th row전동밸브
5th row철선제품, 선반 등
ValueCountFrequency (%)
등 474
 
2.6%
및 419
 
2.3%
부품 116
 
0.6%
외 106
 
0.6%
금형 100
 
0.6%
마스크 84
 
0.5%
플라스틱 78
 
0.4%
led 76
 
0.4%
제조 75
 
0.4%
화장품 68
 
0.4%
Other values (9606) 16439
91.2%
2023-12-11T07:13:53.315225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8150
 
8.6%
, 5272
 
5.6%
기 3798
 
4.0%
장 1737
 
1.8%
스 1676
 
1.8%
품 1632
 
1.7%
용 1500
 
1.6%
제 1423
 
1.5%
전 1312
 
1.4%
자 1259
 
1.3%
Other values (910) 66514
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73786
78.3%
Space Separator 8150
 
8.6%
Other Punctuation 5463
 
5.8%
Uppercase Letter 3873
 
4.1%
Lowercase Letter 1528
 
1.6%
Open Punctuation 598
 
0.6%
Close Punctuation 595
 
0.6%
Decimal Number 212
 
0.2%
Dash Punctuation 61
 
0.1%
Connector Punctuation 3
 
< 0.1%
Other values (3) 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 3798
 
5.1%
장 1737
 
2.4%
스 1676
 
2.3%
품 1632
 
2.2%
용 1500
 
2.0%
제 1423
 
1.9%
전 1312
 
1.8%
자 1259
 
1.7%
조 1210
 
1.6%
이 1115
 
1.5%
Other values (831) 57124
77.4%
Uppercase Letter
ValueCountFrequency (%)
C 461
11.9%
D 446
11.5%
E 435
11.2%
L 414
10.7%
P 312
 
8.1%
T 244
 
6.3%
S 208
 
5.4%
V 197
 
5.1%
A 176
 
4.5%
R 139
 
3.6%
Other values (16) 841
21.7%
Lowercase Letter
ValueCountFrequency (%)
e 205
13.4%
t 128
 
8.4%
r 121
 
7.9%
i 118
 
7.7%
a 106
 
6.9%
l 104
 
6.8%
o 101
 
6.6%
c 89
 
5.8%
s 83
 
5.4%
n 66
 
4.3%
Other values (15) 407
26.6%
Decimal Number
ValueCountFrequency (%)
0 53
25.0%
1 40
18.9%
2 39
18.4%
4 19
 
9.0%
3 19
 
9.0%
9 10
 
4.7%
6 10
 
4.7%
8 9
 
4.2%
5 9
 
4.2%
7 4
 
1.9%
Other Punctuation
ValueCountFrequency (%)
, 5272
96.5%
. 105
 
1.9%
/ 58
 
1.1%
· 8
 
0.1%
' 7
 
0.1%
! 6
 
0.1%
& 4
 
0.1%
" 3
 
0.1%
Open Punctuation
ValueCountFrequency (%)
( 596
99.7%
[ 2
 
0.3%
Close Punctuation
ValueCountFrequency (%)
) 593
99.7%
] 2
 
0.3%
Space Separator
ValueCountFrequency (%)
8150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73783
78.3%
Common 15085
 
16.0%
Latin 5402
 
5.7%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 3798
 
5.1%
장 1737
 
2.4%
스 1676
 
2.3%
품 1632
 
2.2%
용 1500
 
2.0%
제 1423
 
1.9%
전 1312
 
1.8%
자 1259
 
1.7%
조 1210
 
1.6%
이 1115
 
1.5%
Other values (830) 57121
77.4%
Latin
ValueCountFrequency (%)
C 461
 
8.5%
D 446
 
8.3%
E 435
 
8.1%
L 414
 
7.7%
P 312
 
5.8%
T 244
 
4.5%
S 208
 
3.9%
e 205
 
3.8%
V 197
 
3.6%
A 176
 
3.3%
Other values (42) 2304
42.7%
Common
ValueCountFrequency (%)
8150
54.0%
, 5272
34.9%
( 596
 
4.0%
) 593
 
3.9%
. 105
 
0.7%
- 61
 
0.4%
/ 58
 
0.4%
0 53
 
0.4%
1 40
 
0.3%
2 39
 
0.3%
Other values (17) 118
 
0.8%
Han
ValueCountFrequency (%)
外 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73782
78.3%
ASCII 20478
 
21.7%
None 8
 
< 0.1%
CJK 3
 
< 0.1%
Number Forms 1
 
< 0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8150
39.8%
, 5272
25.7%
( 596
 
2.9%
) 593
 
2.9%
C 461
 
2.3%
D 446
 
2.2%
E 435
 
2.1%
L 414
 
2.0%
P 312
 
1.5%
T 244
 
1.2%
Other values (67) 3555
17.4%
Hangul
ValueCountFrequency (%)
기 3798
 
5.1%
장 1737
 
2.4%
스 1676
 
2.3%
품 1632
 
2.2%
용 1500
 
2.0%
제 1423
 
1.9%
전 1312
 
1.8%
자 1259
 
1.7%
조 1210
 
1.6%
이 1115
 
1.5%
Other values (829) 57120
77.4%
None
ValueCountFrequency (%)
· 8
100.0%
CJK
ValueCountFrequency (%)
外 3
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

전화번호
Text

Distinct8725
Distinct (%)87.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:13:53.545320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length10.7987
Min length1

Characters and Unicode

Total characters107987
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8556 ?
Unique (%)85.6%

Sample

1st row031-441-0467
2nd row031-989-7761
3rd row070-4179-5185
4th row031-711-3107
5th row031-837-2282
ValueCountFrequency (%)
031 33
 
0.4%
031-404-9931 3
 
< 0.1%
031-677-0870 3
 
< 0.1%
02-2088-1662 3
 
< 0.1%
031-689-5781 2
 
< 0.1%
031-459-0405 2
 
< 0.1%
031-334-0402 2
 
< 0.1%
031-665-3460 2
 
< 0.1%
031-322-0743 2
 
< 0.1%
031-867-6005 2
 
< 0.1%
Other values (8714) 8872
99.4%
2023-12-11T07:13:53.887302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 17712
16.4%
0 15312
14.2%
3 13680
12.7%
1 12540
11.6%
2 7786
7.2%
8 7439
6.9%
7 7404
6.9%
6 6834
 
6.3%
5 6218
 
5.8%
9 6128
 
5.7%
Other values (5) 6934
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89102
82.5%
Dash Punctuation 17712
 
16.4%
Space Separator 1074
 
1.0%
Uppercase Letter 99
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15312
17.2%
3 13680
15.4%
1 12540
14.1%
2 7786
8.7%
8 7439
8.3%
7 7404
8.3%
6 6834
7.7%
5 6218
7.0%
9 6128
6.9%
4 5761
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
A 33
33.3%
R 33
33.3%
S 33
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 17712
100.0%
Space Separator
ValueCountFrequency (%)
1074
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 107888
99.9%
Latin 99
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 17712
16.4%
0 15312
14.2%
3 13680
12.7%
1 12540
11.6%
2 7786
7.2%
8 7439
6.9%
7 7404
6.9%
6 6834
 
6.3%
5 6218
 
5.8%
9 6128
 
5.7%
Other values (2) 6835
 
6.3%
Latin
ValueCountFrequency (%)
A 33
33.3%
R 33
33.3%
S 33
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 107987
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 17712
16.4%
0 15312
14.2%
3 13680
12.7%
1 12540
11.6%
2 7786
7.2%
8 7439
6.9%
7 7404
6.9%
6 6834
 
6.3%
5 6218
 
5.8%
9 6128
 
5.7%
Other values (5) 6934
 
6.4%

정제우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1356
Distinct (%)13.8%
Missing149
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean13402.532
Minimum10001
Maximum18622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:13:54.029174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10001
5-th percentile10025
Q111413
median12811
Q315528
95-th percentile17524
Maximum18622
Range8621
Interquartile range (IQR)4115

Descriptive statistics

Standard deviation2521.2183
Coefficient of variation (CV)0.18811507
Kurtosis-1.2047441
Mean13402.532
Median Absolute Deviation (MAD)2115
Skewness0.19594736
Sum1.3202834 × 108
Variance6356541.5
MonotonicityNot monotonic
2023-12-11T07:13:54.150727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10040 108
 
1.1%
10011 99
 
1.0%
15847 94
 
0.9%
11413 87
 
0.9%
14449 86
 
0.9%
11426 82
 
0.8%
15850 80
 
0.8%
10027 78
 
0.8%
10010 78
 
0.8%
14931 77
 
0.8%
Other values (1346) 8982
89.8%
(Missing) 149
 
1.5%
ValueCountFrequency (%)
10001 1
 
< 0.1%
10003 27
 
0.3%
10005 8
 
0.1%
10007 7
 
0.1%
10008 28
 
0.3%
10009 43
0.4%
10010 78
0.8%
10011 99
1.0%
10012 42
0.4%
10013 34
 
0.3%
ValueCountFrequency (%)
18622 1
 
< 0.1%
18487 1
 
< 0.1%
18151 1
 
< 0.1%
18150 3
 
< 0.1%
18145 6
0.1%
18144 4
 
< 0.1%
18136 1
 
< 0.1%
18126 11
0.1%
18124 1
 
< 0.1%
18119 1
 
< 0.1%

정제도로명주소
Text

MISSING 

Distinct7713
Distinct (%)81.0%
Missing483
Missing (%)4.8%
Memory size156.2 KiB
2023-12-11T07:13:54.365106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length20.835978
Min length13

Characters and Unicode

Total characters198296
Distinct characters373
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

Unique7150 ?
Unique (%)75.1%

Sample

1st row경기도 수원시 팔달구 창룡대로210번길 12
2nd row경기도 김포시 통진읍 고정1로 57
3rd row경기도 용인시 처인구 포곡읍 선장1로 62
4th row경기도 광주시 곤지암읍 광여로 115-8
5th row경기도 양주시 광적면 현석로 373
ValueCountFrequency (%)
경기도 9517
 
21.2%
김포시 1581
 
3.5%
부천시 1013
 
2.3%
남양주시 767
 
1.7%
양주시 763
 
1.7%
용인시 753
 
1.7%
광주시 724
 
1.6%
대곶면 598
 
1.3%
안성시 571
 
1.3%
처인구 566
 
1.3%
Other values (6139) 28041
62.5%
2023-12-11T07:13:54.747138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
35377
 
17.8%
도 10160
 
5.1%
기 9870
 
5.0%
시 9801
 
4.9%
경 9743
 
4.9%
로 8301
 
4.2%
1 7897
 
4.0%
2 5606
 
2.8%
길 5295
 
2.7%
3 4292
 
2.2%
Other values (363) 91954
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119827
60.4%
Decimal Number 39804
 
20.1%
Space Separator 35377
 
17.8%
Dash Punctuation 3288
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 10160
 
8.5%
기 9870
 
8.2%
시 9801
 
8.2%
경 9743
 
8.1%
로 8301
 
6.9%
길 5295
 
4.4%
번 3962
 
3.3%
양 3220
 
2.7%
주 2656
 
2.2%
면 2598
 
2.2%
Other values (351) 54221
45.2%
Decimal Number
ValueCountFrequency (%)
1 7897
19.8%
2 5606
14.1%
3 4292
10.8%
4 3892
9.8%
5 3508
8.8%
6 3256
8.2%
7 3095
 
7.8%
8 2920
 
7.3%
0 2764
 
6.9%
9 2574
 
6.5%
Space Separator
ValueCountFrequency (%)
35377
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3288
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 119827
60.4%
Common 78469
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 10160
 
8.5%
기 9870
 
8.2%
시 9801
 
8.2%
경 9743
 
8.1%
로 8301
 
6.9%
길 5295
 
4.4%
번 3962
 
3.3%
양 3220
 
2.7%
주 2656
 
2.2%
면 2598
 
2.2%
Other values (351) 54221
45.2%
Common
ValueCountFrequency (%)
35377
45.1%
1 7897
 
10.1%
2 5606
 
7.1%
3 4292
 
5.5%
4 3892
 
5.0%
5 3508
 
4.5%
- 3288
 
4.2%
6 3256
 
4.1%
7 3095
 
3.9%
8 2920
 
3.7%
Other values (2) 5338
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 119827
60.4%
ASCII 78469
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
35377
45.1%
1 7897
 
10.1%
2 5606
 
7.1%
3 4292
 
5.5%
4 3892
 
5.0%
5 3508
 
4.5%
- 3288
 
4.2%
6 3256
 
4.1%
7 3095
 
3.9%
8 2920
 
3.7%
Other values (2) 5338
 
6.8%
Hangul
ValueCountFrequency (%)
도 10160
 
8.5%
기 9870
 
8.2%
시 9801
 
8.2%
경 9743
 
8.1%
로 8301
 
6.9%
길 5295
 
4.4%
번 3962
 
3.3%
양 3220
 
2.7%
주 2656
 
2.2%
면 2598
 
2.2%
Other values (351) 54221
45.2%

정제지번주소
Text

Distinct9802
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T07:13:54.975494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length68
Mean length27.1322
Min length1

Characters and Unicode

Total characters271322
Distinct characters587
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9661 ?
Unique (%)96.6%

Sample

1st row경기도 수원시 팔달구 우만동 300-5번지 외 1필지 우만공단 1층 101호
2nd row경기도 김포시 통진읍 고정리 201-2번지
3rd row경기도 용인시 처인구 포곡읍 신원리 479-1
4th row경기도 광주시 곤지암읍 곤지암리 84-6번지
5th row경기도 양주시 광적면 우고리 367번지
ValueCountFrequency (%)
경기도 9951
 
16.7%
김포시 1733
 
2.9%
외 1466
 
2.5%
부천시 1028
 
1.7%
1필지 817
 
1.4%
남양주시 816
 
1.4%
용인시 808
 
1.4%
양주시 808
 
1.4%
광주시 738
 
1.2%
대곶면 628
 
1.1%
Other values (9537) 40836
68.5%
2023-12-11T07:13:55.362300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
49723
 
18.3%
지 12262
 
4.5%
1 11029
 
4.1%
도 10835
 
4.0%
기 10269
 
3.8%
시 10200
 
3.8%
경 10051
 
3.7%
번 9735
 
3.6%
동 7693
 
2.8%
- 7560
 
2.8%
Other values (577) 131965
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159357
58.7%
Decimal Number 50631
 
18.7%
Space Separator 49723
 
18.3%
Dash Punctuation 7560
 
2.8%
Uppercase Letter 1360
 
0.5%
Close Punctuation 855
 
0.3%
Open Punctuation 855
 
0.3%
Other Punctuation 728
 
0.3%
Lowercase Letter 179
 
0.1%
Math Symbol 62
 
< 0.1%
Other values (2) 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 12262
 
7.7%
도 10835
 
6.8%
기 10269
 
6.4%
시 10200
 
6.4%
경 10051
 
6.3%
번 9735
 
6.1%
동 7693
 
4.8%
리 5245
 
3.3%
양 3751
 
2.4%
주 2992
 
1.9%
Other values (514) 76324
47.9%
Uppercase Letter
ValueCountFrequency (%)
B 345
25.4%
A 265
19.5%
I 140
10.3%
T 114
 
8.4%
D 75
 
5.5%
C 67
 
4.9%
S 62
 
4.6%
K 49
 
3.6%
E 46
 
3.4%
G 25
 
1.8%
Other values (15) 172
12.6%
Lowercase Letter
ValueCountFrequency (%)
e 53
29.6%
n 27
15.1%
r 27
15.1%
c 26
14.5%
t 25
14.0%
h 4
 
2.2%
y 4
 
2.2%
s 3
 
1.7%
o 3
 
1.7%
w 2
 
1.1%
Other values (3) 5
 
2.8%
Decimal Number
ValueCountFrequency (%)
1 11029
21.8%
2 7240
14.3%
3 5785
11.4%
4 4710
9.3%
5 4452
8.8%
0 4378
 
8.6%
6 3884
 
7.7%
7 3194
 
6.3%
8 3083
 
6.1%
9 2876
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 693
95.2%
. 18
 
2.5%
& 5
 
0.7%
/ 5
 
0.7%
· 3
 
0.4%
: 2
 
0.3%
\ 1
 
0.1%
' 1
 
0.1%
Space Separator
ValueCountFrequency (%)
49723
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7560
100.0%
Close Punctuation
ValueCountFrequency (%)
) 855
100.0%
Open Punctuation
ValueCountFrequency (%)
( 855
100.0%
Math Symbol
ValueCountFrequency (%)
~ 62
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 11
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159355
58.7%
Common 110415
40.7%
Latin 1550
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 12262
 
7.7%
도 10835
 
6.8%
기 10269
 
6.4%
시 10200
 
6.4%
경 10051
 
6.3%
번 9735
 
6.1%
동 7693
 
4.8%
리 5245
 
3.3%
양 3751
 
2.4%
주 2992
 
1.9%
Other values (512) 76322
47.9%
Latin
ValueCountFrequency (%)
B 345
22.3%
A 265
17.1%
I 140
9.0%
T 114
 
7.4%
D 75
 
4.8%
C 67
 
4.3%
S 62
 
4.0%
e 53
 
3.4%
K 49
 
3.2%
E 46
 
3.0%
Other values (29) 334
21.5%
Common
ValueCountFrequency (%)
49723
45.0%
1 11029
 
10.0%
- 7560
 
6.8%
2 7240
 
6.6%
3 5785
 
5.2%
4 4710
 
4.3%
5 4452
 
4.0%
0 4378
 
4.0%
6 3884
 
3.5%
7 3194
 
2.9%
Other values (14) 8460
 
7.7%
Han
ValueCountFrequency (%)
堂 1
50.0%
美 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159355
58.7%
ASCII 111950
41.3%
Number Forms 11
 
< 0.1%
None 3
 
< 0.1%
CJK 2
 
< 0.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
49723
44.4%
1 11029
 
9.9%
- 7560
 
6.8%
2 7240
 
6.5%
3 5785
 
5.2%
4 4710
 
4.2%
5 4452
 
4.0%
0 4378
 
3.9%
6 3884
 
3.5%
7 3194
 
2.9%
Other values (50) 9995
 
8.9%
Hangul
ValueCountFrequency (%)
지 12262
 
7.7%
도 10835
 
6.8%
기 10269
 
6.4%
시 10200
 
6.4%
경 10051
 
6.3%
번 9735
 
6.1%
동 7693
 
4.8%
리 5245
 
3.3%
양 3751
 
2.4%
주 2992
 
1.9%
Other values (512) 76322
47.9%
Number Forms
ValueCountFrequency (%)
Ⅰ 11
100.0%
None
ValueCountFrequency (%)
· 3
100.0%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%
CJK
ValueCountFrequency (%)
堂 1
50.0%
美 1
50.0%

정제WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7954
Distinct (%)81.8%
Missing281
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean37.493697
Minimum36.918257
Maximum38.184163
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:13:55.505742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.918257
5-th percentile37.084134
Q137.350725
median37.50164
Q337.67757
95-th percentile37.851627
Maximum38.184163
Range1.2659059
Interquartile range (IQR)0.32684494

Descriptive statistics

Standard deviation0.22495315
Coefficient of variation (CV)0.0059997592
Kurtosis-0.56883252
Mean37.493697
Median Absolute Deviation (MAD)0.16470847
Skewness-0.1705114
Sum364401.24
Variance0.050603921
MonotonicityNot monotonic
2023-12-11T07:13:55.622174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.5224210033 79
 
0.8%
37.5016398102 36
 
0.4%
37.3496648085 35
 
0.4%
37.4138910408 28
 
0.3%
37.3899554806 28
 
0.3%
37.6499050791 26
 
0.3%
37.4017965187 25
 
0.2%
37.4015310331 23
 
0.2%
37.3756896917 21
 
0.2%
37.6490702916 21
 
0.2%
Other values (7944) 9397
94.0%
(Missing) 281
 
2.8%
ValueCountFrequency (%)
36.9182573487 1
< 0.1%
36.9215855395 1
< 0.1%
36.9218183258 2
< 0.1%
36.9259914028 1
< 0.1%
36.9284056491 1
< 0.1%
36.9290064271 1
< 0.1%
36.9296512366 1
< 0.1%
36.9299073326 1
< 0.1%
36.93127648 1
< 0.1%
36.9313510608 1
< 0.1%
ValueCountFrequency (%)
38.1841632144 1
< 0.1%
38.1328486426 1
< 0.1%
38.1040569576 1
< 0.1%
38.0759563185 1
< 0.1%
38.0729993818 1
< 0.1%
38.0713215707 1
< 0.1%
38.0691655876 1
< 0.1%
38.0638802601 1
< 0.1%
38.0578937787 1
< 0.1%
38.0554127533 1
< 0.1%

정제WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7954
Distinct (%)81.8%
Missing281
Missing (%)2.8%
Infinite0
Infinite (%)0.0%
Mean126.9858
Minimum126.52622
Maximum127.79248
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T07:13:55.752041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52622
5-th percentile126.57621
Q1126.7802
median126.96682
Q3127.20388
95-th percentile127.41563
Maximum127.79248
Range1.2662508
Interquartile range (IQR)0.42368334

Descriptive statistics

Standard deviation0.26678056
Coefficient of variation (CV)0.0021008692
Kurtosis-0.63134209
Mean126.9858
Median Absolute Deviation (MAD)0.1996306
Skewness0.22576603
Sum1234175
Variance0.071171867
MonotonicityNot monotonic
2023-12-11T07:13:55.897598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.767192498 79
 
0.8%
126.7914594723 36
 
0.4%
126.9535005762 35
 
0.4%
126.820311653 28
 
0.3%
126.9360484109 28
 
0.3%
126.7936807093 26
 
0.3%
126.9910176434 25
 
0.2%
126.9675749609 23
 
0.2%
126.9442873844 21
 
0.2%
126.9019008596 21
 
0.2%
Other values (7944) 9397
94.0%
(Missing) 281
 
2.8%
ValueCountFrequency (%)
126.5262248801 1
< 0.1%
126.534826799 1
< 0.1%
126.5383613345 1
< 0.1%
126.5388127589 1
< 0.1%
126.5388153692 1
< 0.1%
126.538831358 1
< 0.1%
126.5392490812 1
< 0.1%
126.5396189716 1
< 0.1%
126.5398717807 1
< 0.1%
126.539927111 1
< 0.1%
ValueCountFrequency (%)
127.7924757138 1
< 0.1%
127.7730308789 1
< 0.1%
127.7558229914 1
< 0.1%
127.7479402801 1
< 0.1%
127.7470817631 1
< 0.1%
127.7426239774 1
< 0.1%
127.7390928435 1
< 0.1%
127.7261052615 1
< 0.1%
127.7191992537 1
< 0.1%
127.7168310942 2
< 0.1%

Interactions

2023-12-11T07:13:46.280407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.288220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.848636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.589103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.154347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.741090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.374091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.359309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.944895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.667946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.261522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.834893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.467340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.428148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.021980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.770811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.391479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.917657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.558343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.509130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.100446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.857668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.496447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.003217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.653970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.601832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.402960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.938558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.571226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.103718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.749053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:43.739666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:44.499248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.038506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:45.652944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:13:46.187769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:13:56.004997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정기관명설립구분명용지면적(㎡)건축면적(㎡)종업원수공장규모구분명용도지역명지목명정제우편번호정제WGS84위도정제WGS84경도
행정기관명1.0000.7700.0780.2860.0930.3080.8140.5610.9970.9520.939
설립구분명0.7701.0000.0000.0310.0000.1210.4750.1850.2840.2640.251
용지면적(㎡)0.0780.0001.0000.7591.0000.5580.0000.0000.0450.0000.000
건축면적(㎡)0.2860.0310.7591.0000.7180.2980.0000.0000.1210.0560.000
종업원수0.0930.0001.0000.7181.0000.2230.0000.0000.0420.0000.000
공장규모구분명0.3080.1210.5580.2980.2231.0000.1270.4210.2070.1270.106
용도지역명0.8140.4750.0000.0000.0000.1271.0000.5290.6830.5890.648
지목명0.5610.1850.0000.0000.0000.4210.5291.0000.4160.3120.406
정제우편번호0.9970.2840.0450.1210.0420.2070.6830.4161.0000.9380.911
정제WGS84위도0.9520.2640.0000.0560.0000.1270.5890.3120.9381.0000.818
정제WGS84경도0.9390.2510.0000.0000.0000.1060.6480.4060.9110.8181.000
2023-12-11T07:13:56.110757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설립구분명공장규모구분명용도지역명행정기관명
설립구분명1.0000.0830.2190.453
공장규모구분명0.0831.0000.0660.164
용도지역명0.2190.0661.0000.244
행정기관명0.4530.1640.2441.000
2023-12-11T07:13:56.211332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용지면적(㎡)건축면적(㎡)종업원수정제우편번호정제WGS84위도정제WGS84경도행정기관명설립구분명공장규모구분명용도지역명
용지면적(㎡)1.0000.6830.346-0.1500.0330.1580.0410.0000.2450.000
건축면적(㎡)0.6831.0000.513-0.0870.0480.0840.1390.0200.2470.000
종업원수0.3460.5131.0000.065-0.0680.0330.0460.0000.2120.000
정제우편번호-0.150-0.0870.0651.000-0.8390.4570.9680.1480.1250.316
정제WGS84위도0.0330.048-0.068-0.8391.000-0.4410.7430.1360.0760.250
정제WGS84경도0.1580.0840.0330.457-0.4411.0000.6970.1290.0640.289
행정기관명0.0410.1390.0460.9680.7430.6971.0000.4530.1640.244
설립구분명0.0000.0200.0000.1480.1360.1290.4531.0000.0830.219
공장규모구분명0.2450.2470.2120.1250.0760.0640.1640.0831.0000.066
용도지역명0.0000.0000.0000.3160.2500.2890.2440.2190.0661.000

Missing values

2023-12-11T07:13:46.917275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:13:47.191743image/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.
2023-12-11T07:13:47.393631image/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

회사명행정기관명설립구분명용지면적(㎡)건축면적(㎡)종업원수공장규모구분명공장등록일용도지역명지목명업종명업종코드생산품정보전화번호정제우편번호정제도로명주소정제지번주소정제WGS84위도정제WGS84경도
19923(주)아이디온경기도 수원시일반0.0369.019소기업20100830/ 도시지역 / 주거지역대, 대전자부품 실장기판 제조업26224반도체번인보드031-441-046716231경기도 수원시 팔달구 창룡대로210번길 12경기도 수원시 팔달구 우만동 300-5번지 외 1필지 우만공단 1층 101호37.29209127.03278
9541선보하이테크공업사경기도 김포시일반2873.0774.07소기업20080609/ 관리지역 / 관리지역기타공장용지주형 및 금형 제조업29294주형및금형031-989-776110009경기도 김포시 통진읍 고정1로 57경기도 김포시 통진읍 고정리 201-2번지37.716379126.597172
30787(주)에이오에프경기도 용인시창업2369.0498.65소기업20161202도시지역 / 녹지지역 / 자연녹지지역공장용지그 외 기타 분류 안된 화학제품 제조업 외 1 종20495, 20499윤활유070-4179-518517022경기도 용인시 처인구 포곡읍 선장1로 62경기도 용인시 처인구 포곡읍 신원리 479-137.313484127.215414
2552뉴토크코리아(주)경기도 광주시일반2326.01242.810소기업20211108/ 관리지역 / 계획관리지역공장용지탭, 밸브 및 유사장치 제조업 외 1 종29133, 29169전동밸브031-711-310712801경기도 광주시 곤지암읍 광여로 115-8경기도 광주시 곤지암읍 곤지암리 84-6번지37.349816127.358977
26153신광산업경기도 양주시일반1815.0684.676소기업20210524/ 관리지역 / 계획관리지역공장용지일반철물 제조업25932철선제품, 선반 등031-837-228211423경기도 양주시 광적면 현석로 373경기도 양주시 광적면 우고리 367번지37.829608126.950741
19716명진섬유경기도 성남시일반78.078.01소기업19990513도시지역 / 주거지역 / 제2종일반주거지역대스타킹 및 기타 양말 제조업14411양말031-749-472713149경기도 성남시 중원구 순환로457번길 11-1경기도 성남시 중원구 은행동 584-2번지37.461888127.170549
3819토음바이오 주식회사경기도 광주시일반1350.0305.156소기업20220405/ 관리지역 / 계획관리지역공장용지건강보조용 액화식품 제조업 외 1 종10796, 10799다류,건강기능식품031-763-122312816경기도 광주시 도척면 도척윗로 660경기도 광주시 도척면 상림리 31-8번지37.308359127.317933
27292(주)금성창호경기도 양주시창업0.0495.010소기업20220919/ 관리지역 / 계획관리지역공장용지금속 문, 창, 셔터 및 관련제품 제조업25111시스템루바, 알루미늄창호11464<NA>경기도 양주시 회암동 185-69번지 1동37.854673127.100662
25718(주)에이스티앤비경기도 안양시일반330.58135.156소기업20200211도시지역 / 공업지역 / 일반공업지역대배전반 및 전기 자동제어반 제조업 외 3 종26421, 26519, 28123, 42321유무선원격감시제어장치,CCTV070-8680-131914084경기도 안양시 만안구 전파로 53경기도 안양시 만안구 안양동 191-1번지 태광에로이카 본관 3층37.390803126.937963
30828(주)로더스경기도 용인시창업0.026.00소기업20210202도시지역 / 주거지역 / 제2종일반주거지역대수산식물 가공 및 저장 처리업10220김자반, 조미김17047<NA>경기도 용인시 처인구 역북동 418-3번지 라이프청수아파트37.237519127.188766
회사명행정기관명설립구분명용지면적(㎡)건축면적(㎡)종업원수공장규모구분명공장등록일용도지역명지목명업종명업종코드생산품정보전화번호정제우편번호정제도로명주소정제지번주소정제WGS84위도정제WGS84경도
30234쿠스나우(KUSNOW)경기도 용인시도시첨단산업단지60.94235.011소기업20220811도시지역 / 주거지역 / 준주거지역공장용지그 외 기타 의료용 기기 제조업27199피부, 두피 진단기031-706-795017095경기도 용인시 기흥구 중부대로 184경기도 용인시 기흥구 영덕동 1315번지 1301-2호, 1301-3호, 1302호37.26857127.090401
17838일일구국민재난안전교육진흥원(주)경기도 부천시일반0.041.05소기업20200424도시지역 / 공업지역 / 일반공업지역대그 외 기타 일반목적용 기계 제조업 외 1 종29193, 29199훈련용 연기발생기1877119114454경기도 부천시 삼작로 183-1경기도 부천시 내동 228-1번지 4층37.52042126.781855
6107(주)트루와이드경기도 군포시일반132.0279.05소기업20120222도시지역 / 공업지역 / 일반공업지역공장용지일반용 전기 조명장치 제조업28422Controller BD, LED 조명031-455-060415843경기도 군포시 엘에스로 13경기도 군포시 당정동 2-3번지 신일IT유토지식산업센터 4층 405호37.365598126.956626
8146백광에스티스틸(주)경기도 김포시일반3209.01282.010소기업20111201/ 관리지역 / 계획관리지역공장용지그 외 기타 1차 철강 제조업24199컨베이어1577031610043경기도 김포시 대곶면 대곶서로249번길 20경기도 김포시 대곶면 상마리 80번지37.64122126.578633
20777유진산업경기도 시흥시일반192.19192.195소기업20110914도시지역 / 녹지지역 / 자연녹지지역대일반용 전기 조명장치 제조업28422형광등기구, LED기구031-312-579714944경기도 시흥시 찬우물1길 2-22경기도 시흥시 미산동 82-22번지37.423203126.797398
19920크레비즈 주식회사경기도 수원시일반90.988.446소기업20190617도시지역 / 녹지지역 / 자연녹지지역대기타 인쇄업 외 1 종18119, 33910디자인, 인쇄, 출판, 출력, 간판 등031-239-854116432경기도 수원시 팔달구 수성로 92경기도 수원시 팔달구 화서동 436-3번지 농민회관 8층37.28184126.98877
9096태신개발경기도 김포시일반1093.0296.243소기업20221031/ 관리지역 / 계획관리지역공장용지일반철물 제조업 외 1 종25932, 28511음수대,빗물여과기,페이퍼타올기등02-2677-762610028<NA>경기도 김포시 대곶면 석정리 61-15번지 1동37.672342126.570605
4859국제정밀산업경기도 광주시일반2976.0330.03소기업20110504/ 관리지역 / 계획관리지역자동차용 금속 압형제품 제조업 외 12 종16232, 22232, 25122, 25123, 25200, 25913, 25914, 25924, 25992, 26410, 26421, 26429, 32091육절기부품 등12814경기도 광주시 도척면 국사봉로 185-9경기도 광주시 도척면 진우리 831-8번지37.31466127.350465
31104더블유앤컴퍼니경기도 용인시창업1250.0247.01소기업20230324도시지역 / 녹지지역 / 생산녹지지역답그 외 기타 일반목적용 기계 제조업29199목공기계 및 기계부품17029경기도 용인시 처인구 포곡읍 옥현로 7경기도 용인시 처인구 포곡읍 삼계리 72-1번지37.300222127.233676
11095(주)베스트머트리얼경기도 김포시일반0.050.03소기업20110905/ 관리지역 / 계획관리지역공장용지일반철물 제조업25932미트용접콘텍트팁031-984-152510011경기도 김포시 하성면 월하로 666경기도 김포시 하성면 원산리 556-6 번지37.708298126.628831