Overview

Dataset statistics

Number of variables16
Number of observations1981
Missing cells24
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory257.4 KiB
Average record size in memory133.1 B

Variable types

Numeric5
Categorical6
Text5

Dataset

Description함안군에 현재 등록되어 있는 공장들 현황입니다.
Author경상남도 함안군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3068626

Alerts

단지명 is highly overall correlated with 관할조직명 and 1 other fieldsHigh correlation
관할조직명 is highly overall correlated with 단지명 and 2 other fieldsHigh correlation
설립구분 is highly overall correlated with 단지명 and 2 other fieldsHigh correlation
종업원수 is highly overall correlated with 용지면적 and 2 other fieldsHigh correlation
용지면적 is highly overall correlated with 종업원수 and 1 other fieldsHigh correlation
건축면적 is highly overall correlated with 종업원수 and 2 other fieldsHigh correlation
공장크기 is highly overall correlated with 종업원수 and 1 other fieldsHigh correlation
용도지역 is highly overall correlated with 관할조직명 and 1 other fieldsHigh correlation
단지명 is highly imbalanced (63.7%)Imbalance
관할조직명 is highly imbalanced (61.4%)Imbalance
공장크기 is highly imbalanced (83.6%)Imbalance
지목 is highly imbalanced (86.3%)Imbalance
공장대표주소(도로명) has 23 (1.2%) missing valuesMissing
순번 has unique valuesUnique
종업원수 has 82 (4.1%) zerosZeros
용지면적 has 206 (10.4%) zerosZeros

Reproduction

Analysis started2023-12-11 00:33:49.804228
Analysis finished2023-12-11 00:33:55.173443
Duration5.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct1981
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean991
Minimum1
Maximum1981
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T09:33:55.246238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile100
Q1496
median991
Q31486
95-th percentile1882
Maximum1981
Range1980
Interquartile range (IQR)990

Descriptive statistics

Standard deviation572.00976
Coefficient of variation (CV)0.5772046
Kurtosis-1.2
Mean991
Median Absolute Deviation (MAD)495
Skewness0
Sum1963171
Variance327195.17
MonotonicityStrictly increasing
2023-12-11T09:33:55.394031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1332 1
 
0.1%
1330 1
 
0.1%
1329 1
 
0.1%
1328 1
 
0.1%
1327 1
 
0.1%
1326 1
 
0.1%
1325 1
 
0.1%
1324 1
 
0.1%
1323 1
 
0.1%
Other values (1971) 1971
99.5%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1981 1
0.1%
1980 1
0.1%
1979 1
0.1%
1978 1
0.1%
1977 1
0.1%
1976 1
0.1%
1975 1
0.1%
1974 1
0.1%
1973 1
0.1%
1972 1
0.1%

단지명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct20
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
<NA>
1522 
함안일반산업단지
 
115
칠서일반산업단지
 
104
함안파수농공단지
 
36
함안칠원운서농공단지
 
32
Other values (15)
172 

Length

Max length12
Median length4
Mean length5.0590611
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row함안일반산업단지
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1522
76.8%
함안일반산업단지 115
 
5.8%
칠서일반산업단지 104
 
5.2%
함안파수농공단지 36
 
1.8%
함안칠원운서농공단지 32
 
1.6%
함안산인농공단지 25
 
1.3%
함안용산농공단지 22
 
1.1%
함안법수농공단지 22
 
1.1%
함안군북농공단지 19
 
1.0%
함안대산대사일반산업단지 17
 
0.9%
Other values (10) 67
 
3.4%

Length

2023-12-11T09:33:55.547226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1522
76.8%
함안일반산업단지 115
 
5.8%
칠서일반산업단지 104
 
5.2%
함안파수농공단지 36
 
1.8%
함안칠원운서농공단지 32
 
1.6%
함안산인농공단지 25
 
1.3%
함안용산농공단지 22
 
1.1%
함안법수농공단지 22
 
1.1%
함안군북농공단지 19
 
1.0%
함안대산대사일반산업단지 17
 
0.9%
Other values (10) 67
 
3.4%

회사명
Text

Distinct1894
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-11T09:33:55.782592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length6.7375063
Min length2

Characters and Unicode

Total characters13347
Distinct characters467
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1821 ?
Unique (%)91.9%

Sample

1st row YSM
2nd row 대흥중자
3rd row 코오롱데크컴퍼지트(주)
4th row(사)경남신체장애인복지회
5th row(사)환경사랑나눔회 경남희망세상제작단
ValueCountFrequency (%)
주식회사 72
 
3.3%
2공장 17
 
0.8%
제2공장 12
 
0.6%
함안공장 9
 
0.4%
함안지점 7
 
0.3%
농업회사법인 6
 
0.3%
삼영엠텍(주 5
 
0.2%
주)성일에스아이엠 4
 
0.2%
칠서공장 4
 
0.2%
주)함안중공업 4
 
0.2%
Other values (1900) 2027
93.5%
2023-12-11T09:33:56.164966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1139
 
8.5%
) 1056
 
7.9%
( 1055
 
7.9%
업 412
 
3.1%
이 373
 
2.8%
산 313
 
2.3%
스 258
 
1.9%
공 255
 
1.9%
성 250
 
1.9%
크 241
 
1.8%
Other values (457) 7995
59.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10722
80.3%
Close Punctuation 1056
 
7.9%
Open Punctuation 1055
 
7.9%
Uppercase Letter 227
 
1.7%
Space Separator 196
 
1.5%
Decimal Number 76
 
0.6%
Other Punctuation 14
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1139
 
10.6%
업 412
 
3.8%
이 373
 
3.5%
산 313
 
2.9%
스 258
 
2.4%
공 255
 
2.4%
성 250
 
2.3%
크 241
 
2.2%
테 225
 
2.1%
에 210
 
2.0%
Other values (420) 7046
65.7%
Uppercase Letter
ValueCountFrequency (%)
E 32
14.1%
N 26
11.5%
S 24
10.6%
G 24
10.6%
T 17
 
7.5%
C 15
 
6.6%
M 14
 
6.2%
K 8
 
3.5%
J 8
 
3.5%
A 8
 
3.5%
Other values (13) 51
22.5%
Decimal Number
ValueCountFrequency (%)
2 47
61.8%
1 13
 
17.1%
3 9
 
11.8%
4 4
 
5.3%
0 3
 
3.9%
Other Punctuation
ValueCountFrequency (%)
& 6
42.9%
. 5
35.7%
: 1
 
7.1%
, 1
 
7.1%
/ 1
 
7.1%
Close Punctuation
ValueCountFrequency (%)
) 1056
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1055
100.0%
Space Separator
ValueCountFrequency (%)
196
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10721
80.3%
Common 2398
 
18.0%
Latin 227
 
1.7%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1139
 
10.6%
업 412
 
3.8%
이 373
 
3.5%
산 313
 
2.9%
스 258
 
2.4%
공 255
 
2.4%
성 250
 
2.3%
크 241
 
2.2%
테 225
 
2.1%
에 210
 
2.0%
Other values (419) 7045
65.7%
Latin
ValueCountFrequency (%)
E 32
14.1%
N 26
11.5%
S 24
10.6%
G 24
10.6%
T 17
 
7.5%
C 15
 
6.6%
M 14
 
6.2%
K 8
 
3.5%
J 8
 
3.5%
A 8
 
3.5%
Other values (13) 51
22.5%
Common
ValueCountFrequency (%)
) 1056
44.0%
( 1055
44.0%
196
 
8.2%
2 47
 
2.0%
1 13
 
0.5%
3 9
 
0.4%
& 6
 
0.3%
. 5
 
0.2%
4 4
 
0.2%
0 3
 
0.1%
Other values (4) 4
 
0.2%
Han
ValueCountFrequency (%)
林 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10721
80.3%
ASCII 2625
 
19.7%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1139
 
10.6%
업 412
 
3.8%
이 373
 
3.5%
산 313
 
2.9%
스 258
 
2.4%
공 255
 
2.4%
성 250
 
2.3%
크 241
 
2.2%
테 225
 
2.1%
에 210
 
2.0%
Other values (419) 7045
65.7%
ASCII
ValueCountFrequency (%)
) 1056
40.2%
( 1055
40.2%
196
 
7.5%
2 47
 
1.8%
E 32
 
1.2%
N 26
 
1.0%
S 24
 
0.9%
G 24
 
0.9%
T 17
 
0.6%
C 15
 
0.6%
Other values (27) 133
 
5.1%
CJK
ValueCountFrequency (%)
林 1
100.0%

공장대표주소(도로명)
Text

MISSING 

Distinct1808
Distinct (%)92.3%
Missing23
Missing (%)1.2%
Memory size15.6 KiB
2023-12-11T09:33:56.453171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length46
Mean length26.862104
Min length6

Characters and Unicode

Total characters52596
Distinct characters349
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

Unique1674 ?
Unique (%)85.5%

Sample

1st row경상남도 함안군 법수면 윤외리 1555번지
2nd row경상남도 함안군 칠서면 함의로 209-40 (대흥중자) 외 1필지
3rd row경상남도 함안군 군북면 함안산단1길 26-23
4th row경상남도 함안군 대산면 하기리 415-4번지 외6필
5th row경상남도 함안군 군북면 국우로 95 외 1필지
ValueCountFrequency (%)
경상남도 1958
 
16.4%
함안군 1958
 
16.4%
칠원읍 623
 
5.2%
외 556
 
4.7%
군북면 338
 
2.8%
칠서면 328
 
2.7%
1필지 225
 
1.9%
법수면 206
 
1.7%
칠북면 144
 
1.2%
산인면 140
 
1.2%
Other values (2003) 5475
45.8%
2023-12-11T09:33:57.058127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9993
19.0%
군 2298
 
4.4%
함 2233
 
4.2%
안 2160
 
4.1%
남 2026
 
3.9%
경 1996
 
3.8%
도 1975
 
3.8%
상 1967
 
3.7%
1 1709
 
3.2%
면 1342
 
2.6%
Other values (339) 24897
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32061
61.0%
Space Separator 9993
 
19.0%
Decimal Number 7601
 
14.5%
Open Punctuation 966
 
1.8%
Close Punctuation 965
 
1.8%
Dash Punctuation 786
 
1.5%
Uppercase Letter 122
 
0.2%
Other Punctuation 102
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 2298
 
7.2%
함 2233
 
7.0%
안 2160
 
6.7%
남 2026
 
6.3%
경 1996
 
6.2%
도 1975
 
6.2%
상 1967
 
6.1%
면 1342
 
4.2%
칠 1149
 
3.6%
지 1048
 
3.3%
Other values (303) 13867
43.3%
Uppercase Letter
ValueCountFrequency (%)
S 15
12.3%
E 14
11.5%
T 12
9.8%
G 11
9.0%
N 10
8.2%
H 10
8.2%
C 9
7.4%
M 9
7.4%
D 6
 
4.9%
A 5
 
4.1%
Other values (8) 21
17.2%
Decimal Number
ValueCountFrequency (%)
1 1709
22.5%
2 1142
15.0%
3 910
12.0%
5 679
 
8.9%
4 663
 
8.7%
6 567
 
7.5%
7 522
 
6.9%
0 492
 
6.5%
9 481
 
6.3%
8 436
 
5.7%
Other Punctuation
ValueCountFrequency (%)
, 83
81.4%
. 10
 
9.8%
& 8
 
7.8%
/ 1
 
1.0%
Space Separator
ValueCountFrequency (%)
9993
100.0%
Open Punctuation
ValueCountFrequency (%)
( 966
100.0%
Close Punctuation
ValueCountFrequency (%)
) 965
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 786
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32061
61.0%
Common 20413
38.8%
Latin 122
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 2298
 
7.2%
함 2233
 
7.0%
안 2160
 
6.7%
남 2026
 
6.3%
경 1996
 
6.2%
도 1975
 
6.2%
상 1967
 
6.1%
면 1342
 
4.2%
칠 1149
 
3.6%
지 1048
 
3.3%
Other values (303) 13867
43.3%
Common
ValueCountFrequency (%)
9993
49.0%
1 1709
 
8.4%
2 1142
 
5.6%
( 966
 
4.7%
) 965
 
4.7%
3 910
 
4.5%
- 786
 
3.9%
5 679
 
3.3%
4 663
 
3.2%
6 567
 
2.8%
Other values (8) 2033
 
10.0%
Latin
ValueCountFrequency (%)
S 15
12.3%
E 14
11.5%
T 12
9.8%
G 11
9.0%
N 10
8.2%
H 10
8.2%
C 9
7.4%
M 9
7.4%
D 6
 
4.9%
A 5
 
4.1%
Other values (8) 21
17.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32061
61.0%
ASCII 20535
39.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9993
48.7%
1 1709
 
8.3%
2 1142
 
5.6%
( 966
 
4.7%
) 965
 
4.7%
3 910
 
4.4%
- 786
 
3.8%
5 679
 
3.3%
4 663
 
3.2%
6 567
 
2.8%
Other values (26) 2155
 
10.5%
Hangul
ValueCountFrequency (%)
군 2298
 
7.2%
함 2233
 
7.0%
안 2160
 
6.7%
남 2026
 
6.3%
경 1996
 
6.2%
도 1975
 
6.2%
상 1967
 
6.1%
면 1342
 
4.2%
칠 1149
 
3.6%
지 1048
 
3.3%
Other values (303) 13867
43.3%

공장대표주소(지번)
Text

Distinct1826
Distinct (%)92.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-11T09:33:57.444953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length45
Mean length25.757698
Min length13

Characters and Unicode

Total characters51026
Distinct characters250
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

Unique1693 ?
Unique (%)85.5%

Sample

1st row경상남도 함안군 법수면 윤외리 1555번지
2nd row경상남도 함안군 칠서면 회산리 744-17번지 대흥중자 외 1필지
3rd row경상남도 함안군 군북면 월촌리 1988번지
4th row경상남도 함안군 대산면 하기리 415-4번지 외6필
5th row경상남도 함안군 군북면 유현리 1312-7번지 외 1필지
ValueCountFrequency (%)
함안군 1981
17.5%
경상남도 1980
17.5%
칠원읍 622
 
5.5%
외 551
 
4.9%
군북면 333
 
2.9%
칠서면 311
 
2.7%
1필지 226
 
2.0%
법수면 195
 
1.7%
칠북면 145
 
1.3%
산인면 137
 
1.2%
Other values (1906) 4852
42.8%
2023-12-11T09:33:57.965916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9352
18.3%
지 2318
 
4.5%
군 2315
 
4.5%
도 2096
 
4.1%
안 2038
 
4.0%
함 2036
 
4.0%
남 1990
 
3.9%
리 1990
 
3.9%
경 1986
 
3.9%
상 1982
 
3.9%
Other values (240) 22923
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31906
62.5%
Space Separator 9352
 
18.3%
Decimal Number 8401
 
16.5%
Dash Punctuation 1130
 
2.2%
Open Punctuation 102
 
0.2%
Close Punctuation 101
 
0.2%
Uppercase Letter 27
 
0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 2318
 
7.3%
군 2315
 
7.3%
도 2096
 
6.6%
안 2038
 
6.4%
함 2036
 
6.4%
남 1990
 
6.2%
리 1990
 
6.2%
경 1986
 
6.2%
상 1982
 
6.2%
번 1704
 
5.3%
Other values (210) 11451
35.9%
Uppercase Letter
ValueCountFrequency (%)
N 4
14.8%
E 4
14.8%
G 3
11.1%
S 3
11.1%
H 3
11.1%
T 2
7.4%
C 2
7.4%
D 1
 
3.7%
A 1
 
3.7%
B 1
 
3.7%
Other values (3) 3
11.1%
Decimal Number
ValueCountFrequency (%)
1 1898
22.6%
2 1177
14.0%
3 822
9.8%
5 753
 
9.0%
4 705
 
8.4%
0 684
 
8.1%
6 676
 
8.0%
7 634
 
7.5%
8 607
 
7.2%
9 445
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 5
71.4%
/ 1
 
14.3%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
9352
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1130
100.0%
Open Punctuation
ValueCountFrequency (%)
( 102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31906
62.5%
Common 19093
37.4%
Latin 27
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 2318
 
7.3%
군 2315
 
7.3%
도 2096
 
6.6%
안 2038
 
6.4%
함 2036
 
6.4%
남 1990
 
6.2%
리 1990
 
6.2%
경 1986
 
6.2%
상 1982
 
6.2%
번 1704
 
5.3%
Other values (210) 11451
35.9%
Common
ValueCountFrequency (%)
9352
49.0%
1 1898
 
9.9%
2 1177
 
6.2%
- 1130
 
5.9%
3 822
 
4.3%
5 753
 
3.9%
4 705
 
3.7%
0 684
 
3.6%
6 676
 
3.5%
7 634
 
3.3%
Other values (7) 1262
 
6.6%
Latin
ValueCountFrequency (%)
N 4
14.8%
E 4
14.8%
G 3
11.1%
S 3
11.1%
H 3
11.1%
T 2
7.4%
C 2
7.4%
D 1
 
3.7%
A 1
 
3.7%
B 1
 
3.7%
Other values (3) 3
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31906
62.5%
ASCII 19120
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9352
48.9%
1 1898
 
9.9%
2 1177
 
6.2%
- 1130
 
5.9%
3 822
 
4.3%
5 753
 
3.9%
4 705
 
3.7%
0 684
 
3.6%
6 676
 
3.5%
7 634
 
3.3%
Other values (20) 1289
 
6.7%
Hangul
ValueCountFrequency (%)
지 2318
 
7.3%
군 2315
 
7.3%
도 2096
 
6.6%
안 2038
 
6.4%
함 2036
 
6.4%
남 1990
 
6.2%
리 1990
 
6.2%
경 1986
 
6.2%
상 1982
 
6.2%
번 1704
 
5.3%
Other values (210) 11451
35.9%

업종번호
Text

Distinct677
Distinct (%)34.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
2023-12-11T09:33:58.331038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length327
Median length7
Mean length14.363958
Min length7

Characters and Unicode

Total characters28455
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

Unique477 ?
Unique (%)24.1%

Sample

1st row24219,
2nd row29294,
3rd row31322, 14199, 22299
4th row17902,
5th row33992,
ValueCountFrequency (%)
25113 237
 
5.5%
25114 195
 
4.5%
30400 151
 
3.5%
30399 140
 
3.2%
29223 127
 
2.9%
30391 124
 
2.9%
30392 123
 
2.9%
31114 123
 
2.9%
25924 115
 
2.7%
25929 71
 
1.6%
Other values (331) 2903
67.4%
2023-12-11T09:33:58.952606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5873
20.6%
1 4253
14.9%
, 3455
12.1%
3455
12.1%
9 3304
11.6%
3 2905
10.2%
0 1742
 
6.1%
5 1504
 
5.3%
4 1116
 
3.9%
6 378
 
1.3%
Other values (2) 470
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 21545
75.7%
Other Punctuation 3455
 
12.1%
Space Separator 3455
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5873
27.3%
1 4253
19.7%
9 3304
15.3%
3 2905
13.5%
0 1742
 
8.1%
5 1504
 
7.0%
4 1116
 
5.2%
6 378
 
1.8%
7 255
 
1.2%
8 215
 
1.0%
Other Punctuation
ValueCountFrequency (%)
, 3455
100.0%
Space Separator
ValueCountFrequency (%)
3455
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28455
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5873
20.6%
1 4253
14.9%
, 3455
12.1%
3455
12.1%
9 3304
11.6%
3 2905
10.2%
0 1742
 
6.1%
5 1504
 
5.3%
4 1116
 
3.9%
6 378
 
1.3%
Other values (2) 470
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28455
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5873
20.6%
1 4253
14.9%
, 3455
12.1%
3455
12.1%
9 3304
11.6%
3 2905
10.2%
0 1742
 
6.1%
5 1504
 
5.3%
4 1116
 
3.9%
6 378
 
1.3%
Other values (2) 470
 
1.7%

관할조직명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
경상남도 함안군
1762 
함안일반산업단지관리공단
 
115
칠서일반산업단지관리공단
 
104

Length

Max length12
Median length8
Mean length8.4422009
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경상남도 함안군
2nd row경상남도 함안군
3rd row함안일반산업단지관리공단
4th row경상남도 함안군
5th row경상남도 함안군

Common Values

ValueCountFrequency (%)
경상남도 함안군 1762
88.9%
함안일반산업단지관리공단 115
 
5.8%
칠서일반산업단지관리공단 104
 
5.2%

Length

2023-12-11T09:33:59.122802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:59.233254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 1762
47.1%
함안군 1762
47.1%
함안일반산업단지관리공단 115
 
3.1%
칠서일반산업단지관리공단 104
 
2.8%

설립구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
일반
1234 
창업
288 
일반산업단지
276 
농공단지
183 

Length

Max length6
Median length2
Mean length2.7420495
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 1234
62.3%
창업 288
 
14.5%
일반산업단지 276
 
13.9%
농공단지 183
 
9.2%

Length

2023-12-11T09:33:59.374887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:59.493830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 1234
62.3%
창업 288
 
14.5%
일반산업단지 276
 
13.9%
농공단지 183
 
9.2%

등록일
Real number (ℝ)

Distinct1435
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20145493
Minimum19920313
Maximum20221027
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T09:33:59.650200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19920313
5-th percentile20020326
Q120110518
median20151209
Q320200213
95-th percentile20220513
Maximum20221027
Range300714
Interquartile range (IQR)89695

Descriptive statistics

Standard deviation61966.088
Coefficient of variation (CV)0.0030759281
Kurtosis0.76805868
Mean20145493
Median Absolute Deviation (MAD)40984
Skewness-1.0041278
Sum3.9908221 × 1010
Variance3.839796 × 109
MonotonicityNot monotonic
2023-12-11T09:33:59.804070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20080617 24
 
1.2%
20080618 17
 
0.9%
20080620 9
 
0.5%
20010504 7
 
0.4%
20170713 6
 
0.3%
20210204 6
 
0.3%
20221011 6
 
0.3%
20220901 5
 
0.3%
20201209 5
 
0.3%
20200416 5
 
0.3%
Other values (1425) 1891
95.5%
ValueCountFrequency (%)
19920313 1
0.1%
19921009 1
0.1%
19921219 1
0.1%
19930118 1
0.1%
19930504 2
0.1%
19930525 1
0.1%
19930622 1
0.1%
19940314 2
0.1%
19940531 1
0.1%
19940824 1
0.1%
ValueCountFrequency (%)
20221027 2
 
0.1%
20221021 4
0.2%
20221020 1
 
0.1%
20221019 2
 
0.1%
20221014 2
 
0.1%
20221013 1
 
0.1%
20221011 6
0.3%
20221007 1
 
0.1%
20221004 1
 
0.1%
20220930 2
 
0.1%

종업원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct105
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.575972
Minimum0
Maximum322
Zeros82
Zeros (%)4.1%
Negative0
Negative (%)0.0%
Memory size17.5 KiB
2023-12-11T09:33:59.933932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q15
median7
Q313
95-th percentile46
Maximum322
Range322
Interquartile range (IQR)8

Descriptive statistics

Standard deviation23.652085
Coefficient of variation (CV)1.742202
Kurtosis54.366748
Mean13.575972
Median Absolute Deviation (MAD)3
Skewness6.2414604
Sum26894
Variance559.42112
MonotonicityNot monotonic
2023-12-11T09:34:00.076150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 344
17.4%
10 171
 
8.6%
3 142
 
7.2%
4 130
 
6.6%
8 125
 
6.3%
6 121
 
6.1%
2 92
 
4.6%
0 82
 
4.1%
7 80
 
4.0%
9 61
 
3.1%
Other values (95) 633
32.0%
ValueCountFrequency (%)
0 82
 
4.1%
1 33
 
1.7%
2 92
 
4.6%
3 142
7.2%
4 130
 
6.6%
5 344
17.4%
6 121
 
6.1%
7 80
 
4.0%
8 125
 
6.3%
9 61
 
3.1%
ValueCountFrequency (%)
322 1
0.1%
296 1
0.1%
287 1
0.1%
260 1
0.1%
208 1
0.1%
206 1
0.1%
200 1
0.1%
186 1
0.1%
182 1
0.1%
170 1
0.1%

생산품
Text

Distinct1508
Distinct (%)76.2%
Missing1
Missing (%)0.1%
Memory size15.6 KiB
2023-12-11T09:34:00.354649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length38
Mean length8.5247475
Min length1

Characters and Unicode

Total characters16879
Distinct characters576
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

Unique1389 ?
Unique (%)70.2%

Sample

1st row마그네슘 인고트(괴)
2nd row산업용로봇
3rd row항공기 부품
4th row화장지
5th row폐합성수지류 비성형 SRF
ValueCountFrequency (%)
및 125
 
3.8%
자동차부품 109
 
3.3%
철구조물 94
 
2.9%
부품 79
 
2.4%
자동차 44
 
1.3%
공작기계부품 41
 
1.2%
등 40
 
1.2%
외 36
 
1.1%
기계부품 30
 
0.9%
공작기계 23
 
0.7%
Other values (1889) 2677
81.2%
2023-12-11T09:34:00.827677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1330
 
7.9%
품 797
 
4.7%
, 707
 
4.2%
기 678
 
4.0%
부 610
 
3.6%
자 383
 
2.3%
조 371
 
2.2%
계 288
 
1.7%
동 288
 
1.7%
차 286
 
1.7%
Other values (566) 11141
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13917
82.5%
Space Separator 1330
 
7.9%
Other Punctuation 728
 
4.3%
Uppercase Letter 422
 
2.5%
Lowercase Letter 283
 
1.7%
Open Punctuation 83
 
0.5%
Close Punctuation 83
 
0.5%
Decimal Number 27
 
0.2%
Dash Punctuation 5
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
품 797
 
5.7%
기 678
 
4.9%
부 610
 
4.4%
자 383
 
2.8%
조 371
 
2.7%
계 288
 
2.1%
동 288
 
2.1%
차 286
 
2.1%
구 273
 
2.0%
공 271
 
1.9%
Other values (501) 9672
69.5%
Uppercase Letter
ValueCountFrequency (%)
E 42
 
10.0%
C 39
 
9.2%
A 35
 
8.3%
L 34
 
8.1%
S 31
 
7.3%
R 27
 
6.4%
P 26
 
6.2%
T 25
 
5.9%
O 22
 
5.2%
N 19
 
4.5%
Other values (13) 122
28.9%
Lowercase Letter
ValueCountFrequency (%)
e 40
14.1%
r 26
 
9.2%
a 25
 
8.8%
t 21
 
7.4%
s 21
 
7.4%
c 19
 
6.7%
l 17
 
6.0%
n 15
 
5.3%
d 13
 
4.6%
o 13
 
4.6%
Other values (12) 73
25.8%
Decimal Number
ValueCountFrequency (%)
0 7
25.9%
2 4
14.8%
1 3
11.1%
8 3
11.1%
3 3
11.1%
5 3
11.1%
7 2
 
7.4%
9 1
 
3.7%
6 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 707
97.1%
/ 10
 
1.4%
. 8
 
1.1%
' 1
 
0.1%
& 1
 
0.1%
% 1
 
0.1%
Space Separator
ValueCountFrequency (%)
1330
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13917
82.5%
Common 2257
 
13.4%
Latin 705
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
품 797
 
5.7%
기 678
 
4.9%
부 610
 
4.4%
자 383
 
2.8%
조 371
 
2.7%
계 288
 
2.1%
동 288
 
2.1%
차 286
 
2.1%
구 273
 
2.0%
공 271
 
1.9%
Other values (501) 9672
69.5%
Latin
ValueCountFrequency (%)
E 42
 
6.0%
e 40
 
5.7%
C 39
 
5.5%
A 35
 
5.0%
L 34
 
4.8%
S 31
 
4.4%
R 27
 
3.8%
r 26
 
3.7%
P 26
 
3.7%
T 25
 
3.5%
Other values (35) 380
53.9%
Common
ValueCountFrequency (%)
1330
58.9%
, 707
31.3%
( 83
 
3.7%
) 83
 
3.7%
/ 10
 
0.4%
. 8
 
0.4%
0 7
 
0.3%
- 5
 
0.2%
2 4
 
0.2%
1 3
 
0.1%
Other values (10) 17
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13915
82.4%
ASCII 2962
 
17.5%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1330
44.9%
, 707
23.9%
( 83
 
2.8%
) 83
 
2.8%
E 42
 
1.4%
e 40
 
1.4%
C 39
 
1.3%
A 35
 
1.2%
L 34
 
1.1%
S 31
 
1.0%
Other values (55) 538
18.2%
Hangul
ValueCountFrequency (%)
품 797
 
5.7%
기 678
 
4.9%
부 610
 
4.4%
자 383
 
2.8%
조 371
 
2.7%
계 288
 
2.1%
동 288
 
2.1%
차 286
 
2.1%
구 273
 
2.0%
공 271
 
1.9%
Other values (499) 9670
69.5%
Compat Jamo
ValueCountFrequency (%)
ㅌ 1
50.0%
ㅡ 1
50.0%

공장크기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
소기업
1868 
중기업
 
110
대기업
 
2
중견기업
 
1

Length

Max length4
Median length3
Mean length3.0005048
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
소기업 1868
94.3%
중기업 110
 
5.6%
대기업 2
 
0.1%
중견기업 1
 
0.1%

Length

2023-12-11T09:34:01.298149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:34:01.396058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 1868
94.3%
중기업 110
 
5.6%
대기업 2
 
0.1%
중견기업 1
 
0.1%

용도지역
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
관리지역/계획관리지역
985 
관리지역
307 
관리지역/관리지역기타
164 
도시지역/공업지역/일반공업지역/지구단위계획구역
155 
도시지역/공업지역/일반공업지역
115 
Other values (20)
255 

Length

Max length25
Median length11
Mean length11.773347
Min length4

Unique

Unique7 ?
Unique (%)0.4%

Sample

1st row관리지역/계획관리지역
2nd row관리지역/계획관리지역
3rd row도시지역/공업지역/일반공업지역/지구단위계획구역
4th row관리지역
5th row관리지역/계획관리지역

Common Values

ValueCountFrequency (%)
관리지역/계획관리지역 985
49.7%
관리지역 307
 
15.5%
관리지역/관리지역기타 164
 
8.3%
도시지역/공업지역/일반공업지역/지구단위계획구역 155
 
7.8%
도시지역/공업지역/일반공업지역 115
 
5.8%
도시지역/공업지역/준공업지역 83
 
4.2%
관리지역/계획관리지역/개발진흥지구 59
 
3.0%
관리지역/생산관리지역 27
 
1.4%
관리지역/보전관리지역 23
 
1.2%
도시지역/녹지지역/자연녹지지역 19
 
1.0%
Other values (15) 44
 
2.2%

Length

2023-12-11T09:34:01.532791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관리지역/계획관리지역 985
49.7%
관리지역 307
 
15.5%
관리지역/관리지역기타 164
 
8.3%
도시지역/공업지역/일반공업지역/지구단위계획구역 155
 
7.8%
도시지역/공업지역/일반공업지역 115
 
5.8%
도시지역/공업지역/준공업지역 83
 
4.2%
관리지역/계획관리지역/개발진흥지구 59
 
3.0%
관리지역/생산관리지역 27
 
1.4%
관리지역/보전관리지역 23
 
1.2%
도시지역/녹지지역/자연녹지지역 19
 
1.0%
Other values (16) 45
 
2.3%

지목
Categorical

IMBALANCE 

Distinct16
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size15.6 KiB
공장용지
1844 
전
 
42
대
 
31
답
 
29
잡종지
 
18
Other values (11)
 
17

Length

Max length5
Median length4
Mean length3.8293791
Min length1

Unique

Unique6 ?
Unique (%)0.3%

Sample

1st row공장용지
2nd row공장용지
3rd row공장용지
4th row공장용지
5th row잡종지

Common Values

ValueCountFrequency (%)
공장용지 1844
93.1%
전 42
 
2.1%
대 31
 
1.6%
답 29
 
1.5%
잡종지 18
 
0.9%
창고용지 3
 
0.2%
유원지 2
 
0.1%
임야 2
 
0.1%
도로 2
 
0.1%
목장용지 2
 
0.1%
Other values (6) 6
 
0.3%

Length

2023-12-11T09:34:01.702164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공장용지 1844
93.1%
전 42
 
2.1%
대 31
 
1.6%
답 29
 
1.5%
잡종지 18
 
0.9%
창고용지 3
 
0.2%
유원지 2
 
0.1%
임야 2
 
0.1%
도로 2
 
0.1%
목장용지 2
 
0.1%
Other values (6) 6
 
0.3%

용지면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1556
Distinct (%)78.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5177.3603
Minimum-291.2
Maximum373469.1
Zeros206
Zeros (%)10.4%
Negative1
Negative (%)0.1%
Memory size17.5 KiB
2023-12-11T09:34:01.881741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-291.2
5-th percentile0
Q11153
median2554
Q35381
95-th percentile17659
Maximum373469.1
Range373760.3
Interquartile range (IQR)4228

Descriptive statistics

Standard deviation12278.277
Coefficient of variation (CV)2.3715322
Kurtosis445.22634
Mean5177.3603
Median Absolute Deviation (MAD)1687
Skewness16.988788
Sum10256351
Variance1.5075608 × 108
MonotonicityNot monotonic
2023-12-11T09:34:02.088876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 206
 
10.4%
1878.0 5
 
0.3%
1488.0 5
 
0.3%
3306.0 5
 
0.3%
1150.0 5
 
0.3%
1984.0 4
 
0.2%
2300.0 3
 
0.2%
1620.0 3
 
0.2%
1322.0 3
 
0.2%
1056.0 3
 
0.2%
Other values (1546) 1739
87.8%
ValueCountFrequency (%)
-291.2 1
 
0.1%
0.0 206
10.4%
57.0 1
 
0.1%
82.64 1
 
0.1%
90.5 1
 
0.1%
113.6 1
 
0.1%
129.6 1
 
0.1%
165.0 1
 
0.1%
179.0 1
 
0.1%
179.4 1
 
0.1%
ValueCountFrequency (%)
373469.1 1
0.1%
193580.6 1
0.1%
134207.0 1
0.1%
89941.0 1
0.1%
70299.0 1
0.1%
68048.9 1
0.1%
63447.2 1
0.1%
61024.2 1
0.1%
56856.0 1
0.1%
53361.5 1
0.1%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct1814
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2125.0907
Minimum-291.2
Maximum89970.25
Zeros3
Zeros (%)0.2%
Negative1
Negative (%)0.1%
Memory size17.5 KiB
2023-12-11T09:34:02.285730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-291.2
5-th percentile198
Q1489.6
median983.25
Q32157.01
95-th percentile7377.52
Maximum89970.25
Range90261.45
Interquartile range (IQR)1667.41

Descriptive statistics

Standard deviation4378.325
Coefficient of variation (CV)2.0603002
Kurtosis133.71348
Mean2125.0907
Median Absolute Deviation (MAD)590.75
Skewness9.1648813
Sum4209804.8
Variance19169730
MonotonicityNot monotonic
2023-12-11T09:34:02.484959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 10
 
0.5%
300.0 7
 
0.4%
330.0 6
 
0.3%
192.0 5
 
0.3%
310.0 5
 
0.3%
396.0 5
 
0.3%
165.0 4
 
0.2%
99.0 4
 
0.2%
495.0 4
 
0.2%
972.0 4
 
0.2%
Other values (1804) 1927
97.3%
ValueCountFrequency (%)
-291.2 1
 
0.1%
0.0 3
0.2%
20.0 1
 
0.1%
27.3 1
 
0.1%
33.0 2
0.1%
40.32 1
 
0.1%
44.45 1
 
0.1%
47.76 1
 
0.1%
50.0 2
0.1%
57.6 1
 
0.1%
ValueCountFrequency (%)
89970.25 1
0.1%
74013.77 1
0.1%
42292.12 1
0.1%
35673.0 1
0.1%
35525.46 1
0.1%
34101.55 1
0.1%
33754.96 1
0.1%
32766.55 1
0.1%
30899.3 1
0.1%
29878.2 1
0.1%

Interactions

2023-12-11T09:33:54.306512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:51.740794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.426930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:53.249147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:53.781992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:54.398947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:51.901864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.545279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:53.360162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:53.907117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:54.483311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.066633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.661405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:53.482919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:54.009294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:54.564952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.200527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.781934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:53.578779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:54.111040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:54.657676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.330635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:52.917504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:53.696227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:54.214352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:34:02.651517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명관할조직명설립구분등록일종업원수공장크기용도지역지목용지면적건축면적
순번1.0000.2140.1550.1710.2360.0880.0530.2070.0720.0540.090
단지명0.2141.0001.0001.0000.4140.0000.0000.8180.0000.0000.237
관할조직명0.1551.0001.0000.6040.2620.4560.2270.9570.0620.3780.298
설립구분0.1711.0000.6041.0000.2850.2750.4150.8910.1610.1650.220
등록일0.2360.4140.2620.2851.0000.0000.1140.6050.1950.0000.000
종업원수0.0880.0000.4560.2750.0001.0000.6850.2500.0000.7260.752
공장크기0.0530.0000.2270.4150.1140.6851.0000.2850.0000.6330.671
용도지역0.2070.8180.9570.8910.6050.2500.2851.0000.6930.0000.228
지목0.0720.0000.0620.1610.1950.0000.0000.6931.0000.0000.000
용지면적0.0540.0000.3780.1650.0000.7260.6330.0000.0001.0000.854
건축면적0.0900.2370.2980.2200.0000.7520.6710.2280.0000.8541.000
2023-12-11T09:34:02.814488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지명지목관할조직명공장크기용도지역설립구분
단지명1.0000.0000.9820.0000.4430.981
지목0.0001.0000.0330.0000.2680.076
관할조직명0.9820.0331.0000.2160.7830.619
공장크기0.0000.0000.2161.0000.1380.172
용도지역0.4430.2680.7830.1381.0000.631
설립구분0.9810.0760.6190.1720.6311.000
2023-12-11T09:34:02.941409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번등록일종업원수용지면적건축면적단지명관할조직명설립구분공장크기용도지역지목
순번1.000-0.156-0.173-0.169-0.2000.0800.0930.1030.0320.0770.028
등록일-0.1561.000-0.0290.1710.2420.1730.1620.1740.0680.2700.075
종업원수-0.173-0.0291.0000.5230.5780.0000.2260.1790.5170.0970.000
용지면적-0.1690.1710.5231.0000.8170.0000.1690.1070.4630.0000.000
건축면적-0.2000.2420.5780.8171.0000.1180.2100.1520.5340.0990.000
단지명0.0800.1730.0000.0000.1181.0000.9820.9810.0000.4430.000
관할조직명0.0930.1620.2260.1690.2100.9821.0000.6190.2160.7830.033
설립구분0.1030.1740.1790.1070.1520.9810.6191.0000.1720.6310.076
공장크기0.0320.0680.5170.4630.5340.0000.2160.1721.0000.1380.000
용도지역0.0770.2700.0970.0000.0990.4430.7830.6310.1381.0000.268
지목0.0280.0750.0000.0000.0000.0000.0330.0760.0000.2681.000

Missing values

2023-12-11T09:33:54.789819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:33:54.961639image/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.
2023-12-11T09:33:55.095059image/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

순번단지명회사명공장대표주소(도로명)공장대표주소(지번)업종번호관할조직명설립구분등록일종업원수생산품공장크기용도지역지목용지면적건축면적
01<NA>YSM경상남도 함안군 법수면 윤외리 1555번지경상남도 함안군 법수면 윤외리 1555번지24219,경상남도 함안군일반201509147마그네슘 인고트(괴)소기업관리지역/계획관리지역공장용지1878.0543.0
12<NA>대흥중자경상남도 함안군 칠서면 함의로 209-40 (대흥중자) 외 1필지경상남도 함안군 칠서면 회산리 744-17번지 대흥중자 외 1필지29294,경상남도 함안군일반201405267산업용로봇소기업관리지역/계획관리지역공장용지2384.01346.02
23함안일반산업단지코오롱데크컴퍼지트(주)경상남도 함안군 군북면 함안산단1길 26-23경상남도 함안군 군북면 월촌리 1988번지31322, 14199, 22299함안일반산업단지관리공단일반산업단지20210713208항공기 부품중기업도시지역/공업지역/일반공업지역/지구단위계획구역공장용지33020.120806.08
34<NA>(사)경남신체장애인복지회경상남도 함안군 대산면 하기리 415-4번지 외6필경상남도 함안군 대산면 하기리 415-4번지 외6필17902,경상남도 함안군창업2012041311화장지소기업관리지역공장용지3602.0494.7
45<NA>(사)환경사랑나눔회 경남희망세상제작단경상남도 함안군 군북면 국우로 95 외 1필지경상남도 함안군 군북면 유현리 1312-7번지 외 1필지33992,경상남도 함안군일반201901108폐합성수지류 비성형 SRF소기업관리지역/계획관리지역잡종지2118.0691.3
56<NA>(유)국제케미칼경상남도 함안군 여항면 내곡1길 93 (국제케미칼) 외 3필지경상남도 함안군 여항면 내곡리 754-4번지 국제케미칼 외 3필지25913, 25914경상남도 함안군일반201703176우레탄 금형제품소기업관리지역/계획관리지역공장용지1959.01212.43
67<NA>(유)부강기계경상남도 함안군 칠원읍 무기로 89 (식당)경상남도 함안군 칠원읍 무기리 1166-91번지30310, 25200, 29142, 30391, 30392, 30399, 30400, 31322경상남도 함안군일반2018052917기어,전동축소기업관리지역/관리지역기타공장용지2302.0615.53
78칠서일반산업단지(유)실버엘레베이터코리아경상남도 함안군 칠서면 공단동4길 75 (칠서면)경상남도 함안군 칠서면 계내리 633-329162,칠서일반산업단지관리공단일반산업단지2022052510승강기, 승강기 부품소기업도시지역/공업지역/일반공업지역/지구단위계획구역공장용지378.88528.0
89<NA>(유)씨에스강업(제2공장)경상남도 함안군 대산면 서촌1길 120 외 1필지경상남도 함안군 대산면 서촌리 708번지 외 1필지24290,경상남도 함안군일반2021071611핀튜브소기업관리지역/계획관리지역공장용지14761.06008.18
910<NA>(유)씨지푸드경상남도 함안군 군북면 현포로 29경상남도 함안군 군북면 소포리 1100-810121,경상남도 함안군일반202208095닭가공품소기업관리지역/계획관리지역공장용지4756.02329.14
순번단지명회사명공장대표주소(도로명)공장대표주소(지번)업종번호관할조직명설립구분등록일종업원수생산품공장크기용도지역지목용지면적건축면적
19711972<NA>효성전기제작소경상남도 함안군 칠원읍 석전1길 94-8 외 1필지경상남도 함안군 칠원읍 용정리 288-3번지 외 1필지28121, 28122경상남도 함안군일반201309138전기콘트롤박스소기업관리지역/계획관리지역공장용지2111.0613.93
19721973<NA>효일테크경상남도 함안군 칠서면 함의로 349-3 외 2필지경상남도 함안군 칠서면 회산리 916-14번지 외 2필지29223, 31114경상남도 함안군일반201306175산업기계, 선반부품소기업관리지역/계획관리지역공장용지1026.0310.0
19731974<NA>효찬테크경상남도 함안군 칠원읍 용정리 854-21번지경상남도 함안군 칠원읍 용정리 854-21번지29229,경상남도 함안군일반202111155가공공작기계소기업관리지역/계획관리지역공장용지630.0325.0
19741975<NA>훈스틸경상남도 함안군 법수면 장백로 566 (법수면) 외 2필지경상남도 함안군 법수면 강주리 655번지 외 2필지25112, 25113, 25114, 25119경상남도 함안군일반202110283철골, 철구조물,철의장품소기업관리지역/계획관리지역공장용지8396.02454.56
19751976함안일반산업단지훌루테크(주)경상남도 함안군 군북면 함안산단7길 13경상남도 함안군 군북면 사도리 1245번지24311, 25924, 29120함안일반산업단지관리공단일반산업단지2020032449주물품 및 유압기기, 절삭가공소기업도시지역/공업지역/일반공업지역/지구단위계획구역공장용지13369.13053.63
19761977<NA>훌루테크머시닝경상남도 함안군 칠원읍 쇠만이길 5-50 외 2필지경상남도 함안군 칠원읍 용산리 372번지 외 2필지31114,경상남도 함안군창업2016070412조타장치(스테어링기어)소기업관리지역/계획관리지역공장용지3074.01496.15
19771978<NA>휴먼중공업(주)경상남도 함안군 칠서면 계내리 12번지 외 1필지경상남도 함안군 칠서면 계내리 12번지 외 1필지25200, 25113, 25114, 25122, 25123, 28123, 30310, 30320, 30331, 30391, 30392, 30399, 31111, 31113, 31114, 31202, 31322경상남도 함안군창업2021061446방위산업용 부품소기업관리지역/계획관리지역공장용지11207.03184.19
19781979<NA>흥일공업사경상남도 함안군 칠원읍 광려천북로 242-10 (태광산업)경상남도 함안군 칠원읍 예곡리 832-14번지29223,경상남도 함안군일반199305045소형선반소기업관리지역공장용지504.0196.0
19791980<NA>희영정공경상남도 함안군 법수면 장백로 585 (에이치디시에스(주))경상남도 함안군 법수면 강주리 1072번지25921,경상남도 함안군일반2011062410주강품소기업관리지역/관리지역기타공장용지0.01157.0
19801981<NA>히트산업경상남도 함안군 법수면 법수로 407, 외2필지경상남도 함안군 법수면 윤외리 671-1번지13999,경상남도 함안군일반200802217위생타올소기업관리지역대2071.01090.98