Overview

Dataset statistics

Number of variables11
Number of observations10000
Missing cells10432
Missing cells (%)9.5%
Duplicate rows128
Duplicate rows (%)1.3%
Total size in memory996.1 KiB
Average record size in memory102.0 B

Variable types

Text5
Numeric5
Categorical1

Dataset

Description김해시 공장등록 현황에 대한 데이터로 회사명, 종업원수, 생산품, 용지면적, 제조시설면적, 부대시설면적, 지번주소, 도로명주소, 업종명 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15064511/fileData.do

Alerts

Dataset has 128 (1.3%) duplicate rowsDuplicates
종업원수 is highly overall correlated with 용지면적(제곱미터) and 1 other fieldsHigh correlation
용지면적(제곱미터) is highly overall correlated with 종업원수 and 2 other fieldsHigh correlation
제조시설면적(제곱미터) is highly overall correlated with 종업원수 and 2 other fieldsHigh correlation
부대시설면적(제곱미터) is highly overall correlated with 용지면적(제곱미터) and 1 other fieldsHigh correlation
종업원수 has 1587 (15.9%) missing valuesMissing
생산품 has 1586 (15.9%) missing valuesMissing
용지면적(제곱미터) has 5462 (54.6%) missing valuesMissing
지번주소 has 1792 (17.9%) missing valuesMissing
용지면적(제곱미터) has 979 (9.8%) zerosZeros
부대시설면적(제곱미터) has 1307 (13.1%) zerosZeros

Reproduction

Analysis started2023-12-12 06:25:05.024646
Analysis finished2023-12-12 06:25:10.678294
Duration5.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct6597
Distinct (%)66.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-12T15:25:11.167006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length23
Mean length6.788
Min length2

Characters and Unicode

Total characters67880
Distinct characters654
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4577 ?
Unique (%)45.8%

Sample

1st row명성금속 주식회사 열처리공장
2nd row두리화학(주)
3rd row한국정공(주)
4th row에이컴텍(주)
5th row창암스프링
ValueCountFrequency (%)
주식회사 413
 
3.9%
주)연합화스너 30
 
0.3%
삼부정밀화학(주 24
 
0.2%
농업회사법인 15
 
0.1%
화천써비스 13
 
0.1%
신우중공업주식회사 12
 
0.1%
제2공장 12
 
0.1%
강서실업 11
 
0.1%
한발매스테크(주 11
 
0.1%
tech 11
 
0.1%
Other values (6629) 10051
94.8%
2023-12-12T15:25:11.594452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6151
 
9.1%
( 5505
 
8.1%
) 5505
 
8.1%
1865
 
2.7%
1822
 
2.7%
1564
 
2.3%
1466
 
2.2%
1152
 
1.7%
1070
 
1.6%
1048
 
1.5%
Other values (644) 40732
60.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 54262
79.9%
Open Punctuation 5505
 
8.1%
Close Punctuation 5505
 
8.1%
Uppercase Letter 1444
 
2.1%
Space Separator 612
 
0.9%
Other Punctuation 196
 
0.3%
Decimal Number 171
 
0.3%
Lowercase Letter 171
 
0.3%
Dash Punctuation 12
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
6151
 
11.3%
1865
 
3.4%
1822
 
3.4%
1564
 
2.9%
1466
 
2.7%
1152
 
2.1%
1070
 
2.0%
1048
 
1.9%
1014
 
1.9%
946
 
1.7%
Other values (585) 36164
66.6%
Uppercase Letter
ValueCountFrequency (%)
S 160
 
11.1%
E 154
 
10.7%
C 118
 
8.2%
T 113
 
7.8%
N 107
 
7.4%
G 101
 
7.0%
M 89
 
6.2%
P 68
 
4.7%
H 64
 
4.4%
O 51
 
3.5%
Other values (15) 419
29.0%
Lowercase Letter
ValueCountFrequency (%)
e 23
13.5%
o 19
11.1%
c 18
10.5%
d 16
9.4%
t 15
8.8%
r 13
 
7.6%
n 10
 
5.8%
h 9
 
5.3%
s 7
 
4.1%
a 6
 
3.5%
Other values (9) 35
20.5%
Decimal Number
ValueCountFrequency (%)
2 106
62.0%
1 40
 
23.4%
3 19
 
11.1%
4 3
 
1.8%
5 2
 
1.2%
0 1
 
0.6%
Other Punctuation
ValueCountFrequency (%)
. 148
75.5%
& 35
 
17.9%
, 8
 
4.1%
/ 5
 
2.6%
Open Punctuation
ValueCountFrequency (%)
( 5505
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5505
100.0%
Space Separator
ValueCountFrequency (%)
612
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Symbol
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 54262
79.9%
Common 12001
 
17.7%
Latin 1615
 
2.4%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
6151
 
11.3%
1865
 
3.4%
1822
 
3.4%
1564
 
2.9%
1466
 
2.7%
1152
 
2.1%
1070
 
2.0%
1048
 
1.9%
1014
 
1.9%
946
 
1.7%
Other values (584) 36164
66.6%
Latin
ValueCountFrequency (%)
S 160
 
9.9%
E 154
 
9.5%
C 118
 
7.3%
T 113
 
7.0%
N 107
 
6.6%
G 101
 
6.3%
M 89
 
5.5%
P 68
 
4.2%
H 64
 
4.0%
O 51
 
3.2%
Other values (34) 590
36.5%
Common
ValueCountFrequency (%)
( 5505
45.9%
) 5505
45.9%
612
 
5.1%
. 148
 
1.2%
2 106
 
0.9%
1 40
 
0.3%
& 35
 
0.3%
3 19
 
0.2%
- 12
 
0.1%
, 8
 
0.1%
Other values (4) 11
 
0.1%
Han
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 54260
79.9%
ASCII 13616
 
20.1%
None 2
 
< 0.1%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
6151
 
11.3%
1865
 
3.4%
1822
 
3.4%
1564
 
2.9%
1466
 
2.7%
1152
 
2.1%
1070
 
2.0%
1048
 
1.9%
1014
 
1.9%
946
 
1.7%
Other values (583) 36162
66.6%
ASCII
ValueCountFrequency (%)
( 5505
40.4%
) 5505
40.4%
612
 
4.5%
S 160
 
1.2%
E 154
 
1.1%
. 148
 
1.1%
C 118
 
0.9%
T 113
 
0.8%
N 107
 
0.8%
2 106
 
0.8%
Other values (48) 1088
 
8.0%
None
ValueCountFrequency (%)
2
100.0%
CJK
ValueCountFrequency (%)
1
50.0%
1
50.0%

종업원수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct158
Distinct (%)1.9%
Missing1587
Missing (%)15.9%
Infinite0
Infinite (%)0.0%
Mean15.362178
Minimum0
Maximum925
Zeros48
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:25:11.793736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q15
median9
Q315
95-th percentile48
Maximum925
Range925
Interquartile range (IQR)10

Descriptive statistics

Standard deviation30.439895
Coefficient of variation (CV)1.9814831
Kurtosis267.04869
Mean15.362178
Median Absolute Deviation (MAD)5
Skewness12.860383
Sum129242
Variance926.58719
MonotonicityNot monotonic
2023-12-12T15:25:12.008574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 1080
 
10.8%
10 786
 
7.9%
3 610
 
6.1%
4 561
 
5.6%
6 445
 
4.5%
7 422
 
4.2%
2 395
 
4.0%
8 367
 
3.7%
9 297
 
3.0%
15 285
 
2.9%
Other values (148) 3165
31.6%
(Missing) 1587
15.9%
ValueCountFrequency (%)
0 48
 
0.5%
1 271
 
2.7%
2 395
 
4.0%
3 610
6.1%
4 561
5.6%
5 1080
10.8%
6 445
4.5%
7 422
 
4.2%
8 367
 
3.7%
9 297
 
3.0%
ValueCountFrequency (%)
925 1
< 0.1%
766 1
< 0.1%
725 1
< 0.1%
713 1
< 0.1%
689 1
< 0.1%
430 1
< 0.1%
405 1
< 0.1%
400 2
< 0.1%
368 2
< 0.1%
357 1
< 0.1%

생산품
Text

MISSING 

Distinct4407
Distinct (%)52.4%
Missing1586
Missing (%)15.9%
Memory size156.2 KiB
2023-12-12T15:25:12.378797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length100
Median length58
Mean length6.7001426
Min length1

Characters and Unicode

Total characters56375
Distinct characters725
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3252 ?
Unique (%)38.6%

Sample

1st row단조
2nd row호스,봉,관,호스
3rd row유압솔레노이드 등
4th row특수직물
5th row금속스프링가공
ValueCountFrequency (%)
자동차부품 526
 
4.8%
선박부품 256
 
2.4%
196
 
1.8%
산업기계 195
 
1.8%
135
 
1.2%
부품 111
 
1.0%
92
 
0.8%
금형 81
 
0.7%
밸브 61
 
0.6%
조선기자재 58
 
0.5%
Other values (4697) 9144
84.2%
2023-12-12T15:25:12.942510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2781
 
4.9%
2477
 
4.4%
2432
 
4.3%
1902
 
3.4%
, 1857
 
3.3%
1457
 
2.6%
1113
 
2.0%
1022
 
1.8%
1008
 
1.8%
891
 
1.6%
Other values (715) 39435
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48927
86.8%
Space Separator 2477
 
4.4%
Other Punctuation 1999
 
3.5%
Uppercase Letter 1904
 
3.4%
Lowercase Letter 636
 
1.1%
Open Punctuation 186
 
0.3%
Close Punctuation 181
 
0.3%
Decimal Number 49
 
0.1%
Dash Punctuation 13
 
< 0.1%
Modifier Symbol 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2781
 
5.7%
2432
 
5.0%
1902
 
3.9%
1457
 
3.0%
1113
 
2.3%
1022
 
2.1%
1008
 
2.1%
891
 
1.8%
835
 
1.7%
832
 
1.7%
Other values (646) 34654
70.8%
Uppercase Letter
ValueCountFrequency (%)
E 186
 
9.8%
P 169
 
8.9%
C 143
 
7.5%
R 131
 
6.9%
A 131
 
6.9%
L 121
 
6.4%
T 119
 
6.2%
S 117
 
6.1%
O 105
 
5.5%
D 82
 
4.3%
Other values (15) 600
31.5%
Lowercase Letter
ValueCountFrequency (%)
e 83
13.1%
o 50
 
7.9%
a 49
 
7.7%
l 49
 
7.7%
p 43
 
6.8%
r 43
 
6.8%
n 42
 
6.6%
t 39
 
6.1%
i 37
 
5.8%
s 37
 
5.8%
Other values (13) 164
25.8%
Decimal Number
ValueCountFrequency (%)
1 15
30.6%
3 8
16.3%
2 8
16.3%
6 5
 
10.2%
5 5
 
10.2%
0 4
 
8.2%
4 2
 
4.1%
9 1
 
2.0%
8 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 1857
92.9%
. 94
 
4.7%
/ 33
 
1.7%
' 8
 
0.4%
& 4
 
0.2%
: 2
 
0.1%
" 1
 
0.1%
Space Separator
ValueCountFrequency (%)
2477
100.0%
Open Punctuation
ValueCountFrequency (%)
( 186
100.0%
Close Punctuation
ValueCountFrequency (%)
) 181
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48926
86.8%
Common 4908
 
8.7%
Latin 2540
 
4.5%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2781
 
5.7%
2432
 
5.0%
1902
 
3.9%
1457
 
3.0%
1113
 
2.3%
1022
 
2.1%
1008
 
2.1%
891
 
1.8%
835
 
1.7%
832
 
1.7%
Other values (645) 34653
70.8%
Latin
ValueCountFrequency (%)
E 186
 
7.3%
P 169
 
6.7%
C 143
 
5.6%
R 131
 
5.2%
A 131
 
5.2%
L 121
 
4.8%
T 119
 
4.7%
S 117
 
4.6%
O 105
 
4.1%
e 83
 
3.3%
Other values (38) 1235
48.6%
Common
ValueCountFrequency (%)
2477
50.5%
, 1857
37.8%
( 186
 
3.8%
) 181
 
3.7%
. 94
 
1.9%
/ 33
 
0.7%
1 15
 
0.3%
- 13
 
0.3%
3 8
 
0.2%
2 8
 
0.2%
Other values (11) 36
 
0.7%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48925
86.8%
ASCII 7448
 
13.2%
Compat Jamo 1
 
< 0.1%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
2781
 
5.7%
2432
 
5.0%
1902
 
3.9%
1457
 
3.0%
1113
 
2.3%
1022
 
2.1%
1008
 
2.1%
891
 
1.8%
835
 
1.7%
832
 
1.7%
Other values (644) 34652
70.8%
ASCII
ValueCountFrequency (%)
2477
33.3%
, 1857
24.9%
( 186
 
2.5%
E 186
 
2.5%
) 181
 
2.4%
P 169
 
2.3%
C 143
 
1.9%
R 131
 
1.8%
A 131
 
1.8%
L 121
 
1.6%
Other values (59) 1866
25.1%
Compat Jamo
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
100.0%

용지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct2101
Distinct (%)46.3%
Missing5462
Missing (%)54.6%
Infinite0
Infinite (%)0.0%
Mean3739.4185
Minimum0
Maximum123501
Zeros979
Zeros (%)9.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:25:13.115745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1516
median2041
Q34162.75
95-th percentile13723
Maximum123501
Range123501
Interquartile range (IQR)3646.75

Descriptive statistics

Standard deviation7237.0489
Coefficient of variation (CV)1.9353407
Kurtosis118.77004
Mean3739.4185
Median Absolute Deviation (MAD)1789.85
Skewness8.7943357
Sum16969481
Variance52374877
MonotonicityNot monotonic
2023-12-12T15:25:13.255034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 979
 
9.8%
20588.5 27
 
0.3%
1653.0 24
 
0.2%
3306.0 20
 
0.2%
4959.0 20
 
0.2%
1322.0 15
 
0.1%
2314.0 14
 
0.1%
1650.0 13
 
0.1%
3638.0 11
 
0.1%
6930.0 8
 
0.1%
Other values (2091) 3407
34.1%
(Missing) 5462
54.6%
ValueCountFrequency (%)
0.0 979
9.8%
20.0 1
 
< 0.1%
39.6 1
 
< 0.1%
55.0 1
 
< 0.1%
58.5 1
 
< 0.1%
66.0 1
 
< 0.1%
68.0 1
 
< 0.1%
81.7 3
 
< 0.1%
91.0 1
 
< 0.1%
99.75 2
 
< 0.1%
ValueCountFrequency (%)
123501.0 6
0.1%
84962.0 2
 
< 0.1%
80980.0 1
 
< 0.1%
78477.0 2
 
< 0.1%
63190.0 2
 
< 0.1%
63151.0 1
 
< 0.1%
60563.0 2
 
< 0.1%
46475.0 1
 
< 0.1%
41933.0 3
< 0.1%
36131.0 1
 
< 0.1%

제조시설면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct4845
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1193.3551
Minimum0
Maximum35868.45
Zeros30
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:25:13.405863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile159.268
Q1380
median577.575
Q31200
95-th percentile3967.618
Maximum35868.45
Range35868.45
Interquartile range (IQR)820

Descriptive statistics

Standard deviation2073.773
Coefficient of variation (CV)1.737767
Kurtosis80.30172
Mean1193.3551
Median Absolute Deviation (MAD)295.765
Skewness7.3324412
Sum11933551
Variance4300534.6
MonotonicityNot monotonic
2023-12-12T15:25:13.562756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.0 137
 
1.4%
480.0 129
 
1.3%
495.0 95
 
0.9%
450.0 89
 
0.9%
490.0 83
 
0.8%
492.0 60
 
0.6%
198.0 50
 
0.5%
300.0 49
 
0.5%
390.0 43
 
0.4%
990.0 42
 
0.4%
Other values (4835) 9223
92.2%
ValueCountFrequency (%)
0.0 30
0.3%
6.4 1
 
< 0.1%
7.0 2
 
< 0.1%
9.0 3
 
< 0.1%
10.0 1
 
< 0.1%
16.0 1
 
< 0.1%
16.8 1
 
< 0.1%
18.0 1
 
< 0.1%
18.27 1
 
< 0.1%
19.53 1
 
< 0.1%
ValueCountFrequency (%)
35868.45 1
 
< 0.1%
35054.02 1
 
< 0.1%
32666.17 1
 
< 0.1%
31477.4 7
0.1%
28513.52 1
 
< 0.1%
25873.45 2
 
< 0.1%
24501.3 2
 
< 0.1%
23910.4 1
 
< 0.1%
22766.34 3
< 0.1%
22132.3 1
 
< 0.1%

부대시설면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct4585
Distinct (%)45.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean439.19995
Minimum0
Maximum19456.73
Zeros1307
Zeros (%)13.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:25:13.699947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q146.44
median163.6
Q3432.375
95-th percentile1638.22
Maximum19456.73
Range19456.73
Interquartile range (IQR)385.935

Descriptive statistics

Standard deviation1040.6173
Coefficient of variation (CV)2.3693474
Kurtosis99.886345
Mean439.19995
Median Absolute Deviation (MAD)148.6
Skewness8.2230814
Sum4391999.5
Variance1082884.3
MonotonicityNot monotonic
2023-12-12T15:25:13.828507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 1307
 
13.1%
66.0 100
 
1.0%
60.0 53
 
0.5%
50.0 50
 
0.5%
40.0 41
 
0.4%
100.0 35
 
0.4%
72.0 33
 
0.3%
48.0 30
 
0.3%
33.0 29
 
0.3%
80.0 29
 
0.3%
Other values (4575) 8293
82.9%
ValueCountFrequency (%)
0.0 1307
13.1%
1.0 12
 
0.1%
1.21 1
 
< 0.1%
1.44 1
 
< 0.1%
1.68 1
 
< 0.1%
1.8 4
 
< 0.1%
2.0 6
 
0.1%
2.05 1
 
< 0.1%
2.21 1
 
< 0.1%
2.25 2
 
< 0.1%
ValueCountFrequency (%)
19456.73 1
 
< 0.1%
18167.88 2
 
< 0.1%
16560.0 3
< 0.1%
16045.87 2
 
< 0.1%
15989.1 5
0.1%
14589.47 1
 
< 0.1%
12336.2 1
 
< 0.1%
10846.73 1
 
< 0.1%
10465.91 1
 
< 0.1%
10465.907 1
 
< 0.1%

지번주소
Text

MISSING 

Distinct4926
Distinct (%)60.0%
Missing1792
Missing (%)17.9%
Memory size156.2 KiB
2023-12-12T15:25:14.149024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length33
Mean length21.06652
Min length15

Characters and Unicode

Total characters172914
Distinct characters153
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3117 ?
Unique (%)38.0%

Sample

1st row경상남도 김해시 생림면 봉림리 83-1
2nd row경상남도 김해시 한림면 가동리 586-1
3rd row경상남도 김해시 이동 109-8
4th row경상남도 김해시 한림면 안하리 2001-5
5th row경상남도 김해시 어방동 1061-15
ValueCountFrequency (%)
경상남도 8208
20.6%
김해시 8208
20.6%
한림면 1826
 
4.6%
진례면 1313
 
3.3%
주촌면 1305
 
3.3%
진영읍 977
 
2.5%
상동면 821
 
2.1%
생림면 640
 
1.6%
내삼리 593
 
1.5%
고모리 494
 
1.2%
Other values (4058) 15379
38.7%
2023-12-12T15:25:14.634307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
31556
18.2%
9029
 
5.2%
8222
 
4.8%
8212
 
4.7%
8212
 
4.7%
8209
 
4.7%
8209
 
4.7%
8208
 
4.7%
1 7062
 
4.1%
6886
 
4.0%
Other values (143) 69109
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 102397
59.2%
Decimal Number 32964
 
19.1%
Space Separator 31556
 
18.2%
Dash Punctuation 5978
 
3.5%
Close Punctuation 7
 
< 0.1%
Open Punctuation 7
 
< 0.1%
Uppercase Letter 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
9029
 
8.8%
8222
 
8.0%
8212
 
8.0%
8212
 
8.0%
8209
 
8.0%
8209
 
8.0%
8208
 
8.0%
6886
 
6.7%
5910
 
5.8%
2843
 
2.8%
Other values (127) 28457
27.8%
Decimal Number
ValueCountFrequency (%)
1 7062
21.4%
2 4292
13.0%
3 3253
9.9%
5 2853
8.7%
6 2824
 
8.6%
4 2786
 
8.5%
0 2719
 
8.2%
7 2654
 
8.1%
9 2267
 
6.9%
8 2254
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
N 3
60.0%
D 2
40.0%
Space Separator
ValueCountFrequency (%)
31556
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5978
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 102397
59.2%
Common 70512
40.8%
Latin 5
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
9029
 
8.8%
8222
 
8.0%
8212
 
8.0%
8212
 
8.0%
8209
 
8.0%
8209
 
8.0%
8208
 
8.0%
6886
 
6.7%
5910
 
5.8%
2843
 
2.8%
Other values (127) 28457
27.8%
Common
ValueCountFrequency (%)
31556
44.8%
1 7062
 
10.0%
- 5978
 
8.5%
2 4292
 
6.1%
3 3253
 
4.6%
5 2853
 
4.0%
6 2824
 
4.0%
4 2786
 
4.0%
0 2719
 
3.9%
7 2654
 
3.8%
Other values (4) 4535
 
6.4%
Latin
ValueCountFrequency (%)
N 3
60.0%
D 2
40.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 102397
59.2%
ASCII 70517
40.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
31556
44.7%
1 7062
 
10.0%
- 5978
 
8.5%
2 4292
 
6.1%
3 3253
 
4.6%
5 2853
 
4.0%
6 2824
 
4.0%
4 2786
 
4.0%
0 2719
 
3.9%
7 2654
 
3.8%
Other values (6) 4540
 
6.4%
Hangul
ValueCountFrequency (%)
9029
 
8.8%
8222
 
8.0%
8212
 
8.0%
8212
 
8.0%
8209
 
8.0%
8209
 
8.0%
8208
 
8.0%
6886
 
6.7%
5910
 
5.8%
2843
 
2.8%
Other values (127) 28457
27.8%
Distinct6294
Distinct (%)62.9%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T15:25:14.955736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length50
Mean length25.677068
Min length14

Characters and Unicode

Total characters256745
Distinct characters262
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

Unique4224 ?
Unique (%)42.2%

Sample

1st row경상남도 김해시 주촌면 서부로1499번길 64
2nd row경상남도 김해시 생림면 생림대로 826-104 (총 5 필지)
3rd row경상남도 김해시 진례면 테크노밸리1로93번길 36-40
4th row경상남도 김해시 한림면 가동로 50 (총 4 필지)
5th row경상남도 김해시 칠산로183번길 9 (이동)
ValueCountFrequency (%)
경상남도 9999
18.9%
김해시 9999
18.9%
한림면 2178
 
4.1%
진례면 1670
 
3.1%
주촌면 1625
 
3.1%
진영읍 1155
 
2.2%
상동면 962
 
1.8%
928
 
1.7%
필지 928
 
1.7%
생림면 768
 
1.4%
Other values (4299) 22831
43.0%
2023-12-12T15:25:15.391923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
43195
 
16.8%
11479
 
4.5%
11473
 
4.5%
11421
 
4.4%
1 10902
 
4.2%
10020
 
3.9%
10019
 
3.9%
10014
 
3.9%
10003
 
3.9%
9146
 
3.6%
Other values (252) 119073
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 150036
58.4%
Decimal Number 53915
 
21.0%
Space Separator 43195
 
16.8%
Dash Punctuation 5233
 
2.0%
Close Punctuation 1821
 
0.7%
Open Punctuation 1819
 
0.7%
Other Punctuation 498
 
0.2%
Uppercase Letter 226
 
0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11479
 
7.7%
11473
 
7.6%
11421
 
7.6%
10020
 
6.7%
10019
 
6.7%
10014
 
6.7%
10003
 
6.7%
9146
 
6.1%
7240
 
4.8%
6274
 
4.2%
Other values (219) 52947
35.3%
Uppercase Letter
ValueCountFrequency (%)
B 76
33.6%
L 63
27.9%
A 18
 
8.0%
E 15
 
6.6%
F 14
 
6.2%
D 9
 
4.0%
S 9
 
4.0%
C 6
 
2.7%
P 4
 
1.8%
T 3
 
1.3%
Other values (5) 9
 
4.0%
Decimal Number
ValueCountFrequency (%)
1 10902
20.2%
2 7522
14.0%
3 5972
11.1%
4 5113
9.5%
5 4975
9.2%
6 4571
8.5%
9 4355
 
8.1%
7 3931
 
7.3%
0 3464
 
6.4%
8 3110
 
5.8%
Other Punctuation
ValueCountFrequency (%)
, 490
98.4%
. 8
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
b 1
50.0%
l 1
50.0%
Space Separator
ValueCountFrequency (%)
43195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5233
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1821
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1819
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 150036
58.4%
Common 106481
41.5%
Latin 228
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11479
 
7.7%
11473
 
7.6%
11421
 
7.6%
10020
 
6.7%
10019
 
6.7%
10014
 
6.7%
10003
 
6.7%
9146
 
6.1%
7240
 
4.8%
6274
 
4.2%
Other values (219) 52947
35.3%
Latin
ValueCountFrequency (%)
B 76
33.3%
L 63
27.6%
A 18
 
7.9%
E 15
 
6.6%
F 14
 
6.1%
D 9
 
3.9%
S 9
 
3.9%
C 6
 
2.6%
P 4
 
1.8%
T 3
 
1.3%
Other values (7) 11
 
4.8%
Common
ValueCountFrequency (%)
43195
40.6%
1 10902
 
10.2%
2 7522
 
7.1%
3 5972
 
5.6%
- 5233
 
4.9%
4 5113
 
4.8%
5 4975
 
4.7%
6 4571
 
4.3%
9 4355
 
4.1%
7 3931
 
3.7%
Other values (6) 10712
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 150036
58.4%
ASCII 106709
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
43195
40.5%
1 10902
 
10.2%
2 7522
 
7.0%
3 5972
 
5.6%
- 5233
 
4.9%
4 5113
 
4.8%
5 4975
 
4.7%
6 4571
 
4.3%
9 4355
 
4.1%
7 3931
 
3.7%
Other values (23) 10940
 
10.3%
Hangul
ValueCountFrequency (%)
11479
 
7.7%
11473
 
7.6%
11421
 
7.6%
10020
 
6.7%
10019
 
6.7%
10014
 
6.7%
10003
 
6.7%
9146
 
6.1%
7240
 
4.8%
6274
 
4.2%
Other values (219) 52947
35.3%
Distinct1644
Distinct (%)16.4%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-12T15:25:15.818897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length28
Mean length17.493898
Min length1

Characters and Unicode

Total characters174869
Distinct characters347
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

Unique765 ?
Unique (%)7.7%

Sample

1st row금속 열처리업
2nd row플라스틱 선, 봉, 관 및 호스 제조업
3rd row그 외 자동차용 신품 부품 제조업
4th row특수 직물 및 기타 직물 직조업 외 7 종
5th row금속 스프링 제조업
ValueCountFrequency (%)
제조업 8770
 
15.5%
6007
 
10.6%
3617
 
6.4%
3558
 
6.3%
기타 2764
 
4.9%
1 1915
 
3.4%
1815
 
3.2%
금속 1138
 
2.0%
부품 873
 
1.5%
신품 784
 
1.4%
Other values (815) 25318
44.8%
2023-12-12T15:25:16.335130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46605
26.7%
11135
 
6.4%
10417
 
6.0%
10406
 
6.0%
6389
 
3.7%
5878
 
3.4%
4493
 
2.6%
4233
 
2.4%
3619
 
2.1%
3127
 
1.8%
Other values (337) 68567
39.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 122410
70.0%
Space Separator 46605
 
26.7%
Decimal Number 4567
 
2.6%
Other Punctuation 1059
 
0.6%
Close Punctuation 114
 
0.1%
Open Punctuation 114
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11135
 
9.1%
10417
 
8.5%
10406
 
8.5%
6389
 
5.2%
5878
 
4.8%
4493
 
3.7%
4233
 
3.5%
3619
 
3.0%
3127
 
2.6%
2832
 
2.3%
Other values (321) 59881
48.9%
Decimal Number
ValueCountFrequency (%)
1 2433
53.3%
3 730
 
16.0%
2 668
 
14.6%
4 268
 
5.9%
5 143
 
3.1%
6 80
 
1.8%
8 74
 
1.6%
7 64
 
1.4%
9 57
 
1.2%
0 50
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 1033
97.5%
. 23
 
2.2%
· 3
 
0.3%
Space Separator
ValueCountFrequency (%)
46605
100.0%
Close Punctuation
ValueCountFrequency (%)
) 114
100.0%
Open Punctuation
ValueCountFrequency (%)
( 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 122410
70.0%
Common 52459
30.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11135
 
9.1%
10417
 
8.5%
10406
 
8.5%
6389
 
5.2%
5878
 
4.8%
4493
 
3.7%
4233
 
3.5%
3619
 
3.0%
3127
 
2.6%
2832
 
2.3%
Other values (321) 59881
48.9%
Common
ValueCountFrequency (%)
46605
88.8%
1 2433
 
4.6%
, 1033
 
2.0%
3 730
 
1.4%
2 668
 
1.3%
4 268
 
0.5%
5 143
 
0.3%
) 114
 
0.2%
( 114
 
0.2%
6 80
 
0.2%
Other values (6) 271
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 122394
70.0%
ASCII 52456
30.0%
Compat Jamo 16
 
< 0.1%
None 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46605
88.8%
1 2433
 
4.6%
, 1033
 
2.0%
3 730
 
1.4%
2 668
 
1.3%
4 268
 
0.5%
5 143
 
0.3%
) 114
 
0.2%
( 114
 
0.2%
6 80
 
0.2%
Other values (5) 268
 
0.5%
Hangul
ValueCountFrequency (%)
11135
 
9.1%
10417
 
8.5%
10406
 
8.5%
6389
 
5.2%
5878
 
4.8%
4493
 
3.7%
4233
 
3.5%
3619
 
3.0%
3127
 
2.6%
2832
 
2.3%
Other values (320) 59865
48.9%
Compat Jamo
ValueCountFrequency (%)
16
100.0%
None
ValueCountFrequency (%)
· 3
100.0%

연도
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.6971
Minimum2015
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-12T15:25:16.449027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2015
5-th percentile2015
Q12017
median2017
Q32018
95-th percentile2021
Maximum2022
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.6973626
Coefficient of variation (CV)0.00084123755
Kurtosis0.46644446
Mean2017.6971
Median Absolute Deviation (MAD)0
Skewness1.0841384
Sum20176971
Variance2.8810397
MonotonicityNot monotonic
2023-12-12T15:25:16.556291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
2017 5961
59.6%
2021 699
 
7.0%
2020 663
 
6.6%
2019 590
 
5.9%
2015 575
 
5.8%
2018 541
 
5.4%
2016 540
 
5.4%
2022 431
 
4.3%
ValueCountFrequency (%)
2015 575
 
5.8%
2016 540
 
5.4%
2017 5961
59.6%
2018 541
 
5.4%
2019 590
 
5.9%
2020 663
 
6.6%
2021 699
 
7.0%
2022 431
 
4.3%
ValueCountFrequency (%)
2022 431
 
4.3%
2021 699
 
7.0%
2020 663
 
6.6%
2019 590
 
5.9%
2018 541
 
5.4%
2017 5961
59.6%
2016 540
 
5.4%
2015 575
 
5.8%

분기
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
4
6415 
2
1312 
1
1296 
3
977 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row4
3rd row4
4th row4
5th row4

Common Values

ValueCountFrequency (%)
4 6415
64.1%
2 1312
 
13.1%
1 1296
 
13.0%
3 977
 
9.8%

Length

2023-12-12T15:25:16.676370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:25:16.773401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4 6415
64.1%
2 1312
 
13.1%
1 1296
 
13.0%
3 977
 
9.8%

Interactions

2023-12-12T15:25:09.548570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:07.304581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:07.803451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.353752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.025341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.628677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:07.387753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:07.910462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.474701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.122966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.739938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:07.500363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.015062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.621803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.229119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.855270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:07.603931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.127302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.759955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.346144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.988614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:07.706207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.224244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:08.896480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:25:09.446273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:25:16.864068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수용지면적(제곱미터)제조시설면적(제곱미터)부대시설면적(제곱미터)연도분기
종업원수1.0000.9350.6600.7440.0480.041
용지면적(제곱미터)0.9351.0000.8250.7920.0360.059
제조시설면적(제곱미터)0.6600.8251.0000.6970.0680.052
부대시설면적(제곱미터)0.7440.7920.6971.0000.0910.055
연도0.0480.0360.0680.0911.0000.588
분기0.0410.0590.0520.0550.5881.000
2023-12-12T15:25:16.993177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종업원수용지면적(제곱미터)제조시설면적(제곱미터)부대시설면적(제곱미터)연도분기
종업원수1.0000.5010.5360.499-0.0340.019
용지면적(제곱미터)0.5011.0000.7040.6590.0870.027
제조시설면적(제곱미터)0.5360.7041.0000.6010.0740.031
부대시설면적(제곱미터)0.4990.6590.6011.0000.0480.033
연도-0.0340.0870.0740.0481.0000.449
분기0.0190.0270.0310.0330.4491.000

Missing values

2023-12-12T15:25:10.151354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:25:10.374202image/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.
2023-12-12T15:25:10.554938image/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

회사명종업원수생산품용지면적(제곱미터)제조시설면적(제곱미터)부대시설면적(제곱미터)지번주소도로명주소업종명연도분기
11105명성금속 주식회사 열처리공장5단조4795.02030.49447.12<NA>경상남도 김해시 주촌면 서부로1499번길 64금속 열처리업20221
5295두리화학(주)174호스,봉,관,호스<NA>1497.00.0경상남도 김해시 생림면 봉림리 83-1경상남도 김해시 생림면 생림대로 826-104 (총 5 필지)플라스틱 선, 봉, 관 및 호스 제조업20174
10969한국정공(주)24유압솔레노이드 등0.0770.07116.0<NA>경상남도 김해시 진례면 테크노밸리1로93번길 36-40그 외 자동차용 신품 부품 제조업20214
6413에이컴텍(주)8특수직물<NA>491.40.0경상남도 김해시 한림면 가동리 586-1경상남도 김해시 한림면 가동로 50 (총 4 필지)특수 직물 및 기타 직물 직조업 외 7 종20174
7329창암스프링2금속스프링가공<NA>229.60.0경상남도 김해시 이동 109-8경상남도 김해시 칠산로183번길 9 (이동)금속 스프링 제조업20174
3607(주)준엔지니어링17토목공사장비<NA>1472.4359.34경상남도 김해시 한림면 안하리 2001-5경상남도 김해시 한림면 용덕로302번길 50건설 및 채광용 기계장비 제조업 외 1 종20174
3965(주)한국비티엠20금형<NA>250.9225.92경상남도 김해시 어방동 1061-15경상남도 김해시 분성로557번길 41주형 및 금형 제조업20174
6324아세아식품12조미김,다시마<NA>1575.045.0경상남도 김해시 생림면 봉림리 424경상남도 김해시 생림면 장재로520번안길 8기타 수산동물 가공 및 저장 처리업 외 1 종20174
1535(주)일산전자<NA><NA>7586.12988.122973.88경상남도 김해시 주촌면 망덕리 872-3경상남도 김해시 주촌면 골든루트로 186-24 (총 6 필지)그외 기타 전자부품 제조업20172
1030(주)주원에프이<NA><NA>0.0184.660.0경상남도 김해시 화목동 698-11경상남도 김해시 칠산로251번길 6-15 (화목동)전동기 및 발전기 제조업 외 5 종20163
회사명종업원수생산품용지면적(제곱미터)제조시설면적(제곱미터)부대시설면적(제곱미터)지번주소도로명주소업종명연도분기
6586우리공업(주)10압연기<NA>1400.00.0경상남도 김해시 부곡동 216경상남도 김해시 장유로115번길 50-91 (부곡동)선박 구성 부분품 제조업20174
9490주식회사 월드케어5의료기기81.752.029.7경상남도 김해시 어방동 607 인제대학교경상남도 김해시 인제로 197, B동 412호, 414호(인제대학교 창조관) (어방동)그 외 기타 의료용 기기 제조업20201
8314(주)진광제3공장14자동차부품3268.862210.380.0경상남도 김해시 주촌면 내삼리 1080-4경상남도 김해시 주촌면 서부로1499번길 102-32자동차 엔진용 신품 부품 제조업 외 1 종20182
6108수성산업4자동차부품<NA>626.99219.16경상남도 김해시 유하동 364-1경상남도 김해시 유하로 190그 외 자동차용 신품 부품 제조업 외 3 종20174
3810(주)탄성15고무제품 제조<NA>333.4556.32경상남도 김해시 한림면 신천리 322-8경상남도 김해시 한림면 김해대로1538번길 48그 외 기타 고무제품 제조업 외 5 종20174
8238원우산업5도로표지판,교통안전시설3830.01416.0105.0경상남도 김해시 한림면 퇴래리 705경상남도 김해시 한림면 김해대로927번길 155-3금속 표시판 제조업 외 2 종20181
4055(주)한티엔지리어링11산업용송풍기<NA>490.0606.0<NA>경상남도 김해시 한림면 김해대로1099번길 106, 외1산업용 송풍기 및 배기장치 제조업20174
11280(주)엠피구조1철구조물5435.0990.0634.84<NA>경상남도 김해시 한림면 김해대로1031번안길 13육상 금속 골조 구조재 제조업20222
10800(주)에이치엔티4절삭기계품 등0.0290.060.0<NA>경상남도 김해시 진례면 테크노밸리1로 20-21금속 절삭기계 제조업20214
504삼승금형<NA><NA>2363.0900.0170.4경상남도 김해시 생림면 나전리 660경상남도 김해시 생림면 나전로201-6주형및금형제조업외120153

Duplicate rows

Most frequently occurring

회사명종업원수생산품용지면적(제곱미터)제조시설면적(제곱미터)부대시설면적(제곱미터)지번주소도로명주소업종명연도분기# duplicates
14(주)비티엑스9금속단조,금속조립7274.84740.75930.0경상남도 김해시 진영읍 하계리 778-1경상남도 김해시 진영읍 하계로240번길 209-4금속 단조제품 제조업 외 2종202125
37(주)연합화스너49볼트, 너트20588.51610.02214.9<NA>경상남도 김해시 주촌면 골든루트로66번길 48-5볼트 및 너트류 제조업 외 2종202224
17(주)세아에프에스90금속가공품9636.1579.971287.4<NA>경상남도 김해시 진영읍 본산리 1711-3번지그 외 기타 분류 안된 금속 가공 제품 제조업 외 2종202213
34(주)연합화스너42볼트, 너트20588.57032.216560.0경상남도 김해시 주촌면 농소리 629-6경상남도 김해시 주촌면 골든루트로66번길 48-5볼트 및 너트류 제조업 외 2종202043
42(주)우석18방산부품3002.1919.51567.74<NA>경상남도 김해시 진례면 테크노밸리1로 116-5금속 절삭기계 제조업202133
67고창테크<NA><NA>3638.01661.88488.4<NA>경상남도 김해시 진례면 테크노밸리로 145, 고창테크차체 및 특장차 제조업201713
68고창테크<NA><NA>3638.01661.88488.4<NA>경상남도 김해시 진례면 테크노밸리로 145, 고창테크차체 및 특장차 제조업201743
0(주)가온테크닉스13방산관련 부품, LG전자 세탁기 사업부, 두산 로보틱스 협동로봇부품, 현대건설기계부품2207.0774.0429.45<NA>경상남도 김해시 주촌면 서부로1403번길 44도장 및 기타 피막처리업202212
1(주)거림중공업4일반산업기계제작3977.92200.01314.52<NA>경상남도 김해시 한림면 용덕로302번길 72그 외 기타 일반목적용 기계 제조업202212
2(주)경남애드<NA><NA>372.0216.43218.83경상남도 김해시 유하동 815경상남도 김해시 유하로59번길 45 (유하동)금속 문, 창, 셔터 및 관련제품 제조업 외 2 종201732