Overview

Dataset statistics

Number of variables19
Number of observations1736
Missing cells7
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory266.3 KiB
Average record size in memory157.1 B

Variable types

Numeric5
Categorical8
Text6

Dataset

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

Alerts

관할조직명 has constant value ""Constant
단지명 is highly overall correlated with 용지면적 and 2 other fieldsHigh correlation
지목 is highly overall correlated with 단지명High correlation
종업원수 is highly overall correlated with 용지면적 and 2 other fieldsHigh correlation
용지면적 is highly overall correlated with 종업원수 and 3 other fieldsHigh correlation
건축면적 is highly overall correlated with 종업원수 and 2 other fieldsHigh correlation
공장크기 is highly overall correlated with 종업원수 and 3 other fieldsHigh correlation
대기등급 is highly overall correlated with 단지명 and 1 other fieldsHigh correlation
단지명 is highly imbalanced (75.4%)Imbalance
공장크기 is highly imbalanced (86.9%)Imbalance
지목 is highly imbalanced (84.4%)Imbalance
대기등급 is highly imbalanced (52.1%)Imbalance
수질등급 is highly imbalanced (50.6%)Imbalance
소음/진동여부 is highly imbalanced (50.7%)Imbalance
순번 has unique valuesUnique
종업원수 has 51 (2.9%) zerosZeros
용지면적 has 198 (11.4%) zerosZeros

Reproduction

Analysis started2023-12-11 00:33:34.367332
Analysis finished2023-12-11 00:33:38.681910
Duration4.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct1736
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean868.5
Minimum1
Maximum1736
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T09:33:38.738036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile87.75
Q1434.75
median868.5
Q31302.25
95-th percentile1649.25
Maximum1736
Range1735
Interquartile range (IQR)867.5

Descriptive statistics

Standard deviation501.28435
Coefficient of variation (CV)0.57718405
Kurtosis-1.2
Mean868.5
Median Absolute Deviation (MAD)434
Skewness0
Sum1507716
Variance251286
MonotonicityStrictly increasing
2023-12-11T09:33:38.862965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1155 1
 
0.1%
1166 1
 
0.1%
1165 1
 
0.1%
1164 1
 
0.1%
1163 1
 
0.1%
1162 1
 
0.1%
1161 1
 
0.1%
1160 1
 
0.1%
1159 1
 
0.1%
Other values (1726) 1726
99.4%
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 (%)
1736 1
0.1%
1735 1
0.1%
1734 1
0.1%
1733 1
0.1%
1732 1
0.1%
1731 1
0.1%
1730 1
0.1%
1729 1
0.1%
1728 1
0.1%
1727 1
0.1%

단지명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct18
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
<NA>
1511 
함안파수농공단지
 
36
함안칠원운서농공단지
 
31
함안산인농공단지
 
23
함안용산농공단지
 
22
Other values (13)
 
113

Length

Max length12
Median length4
Mean length4.6589862
Min length4

Unique

Unique2 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1511
87.0%
함안파수농공단지 36
 
2.1%
함안칠원운서농공단지 31
 
1.8%
함안산인농공단지 23
 
1.3%
함안용산농공단지 22
 
1.3%
함안법수농공단지 20
 
1.2%
함안군북농공단지 19
 
1.1%
함안법수강주일반산업단지 15
 
0.9%
함안대산대사일반산업단지 15
 
0.9%
함안황사농공단지 13
 
0.7%
Other values (8) 31
 
1.8%

Length

2023-12-11T09:33:38.997211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1511
87.0%
함안파수농공단지 36
 
2.1%
함안칠원운서농공단지 31
 
1.8%
함안산인농공단지 23
 
1.3%
함안용산농공단지 22
 
1.3%
함안법수농공단지 20
 
1.2%
함안군북농공단지 19
 
1.1%
함안법수강주일반산업단지 15
 
0.9%
함안대산대사일반산업단지 15
 
0.9%
함안황사농공단지 13
 
0.7%
Other values (8) 31
 
1.8%
Distinct1662
Distinct (%)95.7%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2023-12-11T09:33:39.191179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length6.5898618
Min length2

Characters and Unicode

Total characters11440
Distinct characters451
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

Unique1601 ?
Unique (%)92.2%

Sample

1st row YSM
2nd row 대흥중자
3rd row(사)경남신체장애인복지회
4th row(사)환경사랑나눔회 경남희망세상제작단
5th row(유)국제케미칼
ValueCountFrequency (%)
주식회사 75
 
3.9%
2공장 14
 
0.7%
제2공장 10
 
0.5%
함안공장 8
 
0.4%
함안지점 7
 
0.4%
농업회사법인 5
 
0.3%
주)함안중공업 4
 
0.2%
주)케이씨이피중공업 4
 
0.2%
주)성일에스아이엠 4
 
0.2%
창성테크 4
 
0.2%
Other values (1666) 1768
92.9%
2023-12-11T09:33:39.569541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
937
 
8.2%
) 861
 
7.5%
( 860
 
7.5%
402
 
3.5%
315
 
2.8%
295
 
2.6%
234
 
2.0%
225
 
2.0%
217
 
1.9%
203
 
1.8%
Other values (441) 6891
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9261
81.0%
Close Punctuation 861
 
7.5%
Open Punctuation 860
 
7.5%
Uppercase Letter 209
 
1.8%
Space Separator 170
 
1.5%
Decimal Number 62
 
0.5%
Other Punctuation 15
 
0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
937
 
10.1%
402
 
4.3%
315
 
3.4%
295
 
3.2%
234
 
2.5%
225
 
2.4%
217
 
2.3%
203
 
2.2%
201
 
2.2%
165
 
1.8%
Other values (405) 6067
65.5%
Uppercase Letter
ValueCountFrequency (%)
E 29
13.9%
S 24
11.5%
N 23
11.0%
G 22
10.5%
T 16
 
7.7%
C 15
 
7.2%
M 12
 
5.7%
K 8
 
3.8%
J 8
 
3.8%
H 7
 
3.3%
Other values (12) 45
21.5%
Decimal Number
ValueCountFrequency (%)
2 39
62.9%
1 11
 
17.7%
3 7
 
11.3%
4 4
 
6.5%
0 1
 
1.6%
Other Punctuation
ValueCountFrequency (%)
& 7
46.7%
. 5
33.3%
: 1
 
6.7%
, 1
 
6.7%
/ 1
 
6.7%
Close Punctuation
ValueCountFrequency (%)
) 861
100.0%
Open Punctuation
ValueCountFrequency (%)
( 860
100.0%
Space Separator
ValueCountFrequency (%)
170
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9260
80.9%
Common 1970
 
17.2%
Latin 209
 
1.8%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
937
 
10.1%
402
 
4.3%
315
 
3.4%
295
 
3.2%
234
 
2.5%
225
 
2.4%
217
 
2.3%
203
 
2.2%
201
 
2.2%
165
 
1.8%
Other values (404) 6066
65.5%
Latin
ValueCountFrequency (%)
E 29
13.9%
S 24
11.5%
N 23
11.0%
G 22
10.5%
T 16
 
7.7%
C 15
 
7.2%
M 12
 
5.7%
K 8
 
3.8%
J 8
 
3.8%
H 7
 
3.3%
Other values (12) 45
21.5%
Common
ValueCountFrequency (%)
) 861
43.7%
( 860
43.7%
170
 
8.6%
2 39
 
2.0%
1 11
 
0.6%
& 7
 
0.4%
3 7
 
0.4%
. 5
 
0.3%
4 4
 
0.2%
- 2
 
0.1%
Other values (4) 4
 
0.2%
Han
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9260
80.9%
ASCII 2179
 
19.0%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
937
 
10.1%
402
 
4.3%
315
 
3.4%
295
 
3.2%
234
 
2.5%
225
 
2.4%
217
 
2.3%
203
 
2.2%
201
 
2.2%
165
 
1.8%
Other values (404) 6066
65.5%
ASCII
ValueCountFrequency (%)
) 861
39.5%
( 860
39.5%
170
 
7.8%
2 39
 
1.8%
E 29
 
1.3%
S 24
 
1.1%
N 23
 
1.1%
G 22
 
1.0%
T 16
 
0.7%
C 15
 
0.7%
Other values (26) 120
 
5.5%
CJK
ValueCountFrequency (%)
1
100.0%
Distinct1606
Distinct (%)92.9%
Missing7
Missing (%)0.4%
Memory size13.7 KiB
2023-12-11T09:33:39.913057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length46
Mean length27.264315
Min length6

Characters and Unicode

Total characters47140
Distinct characters331
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

Unique1499 ?
Unique (%)86.7%

Sample

1st row경상남도 함안군 법수면 윤외리 1555번지
2nd row경상남도 함안군 칠서면 함의로 209-40 (대흥중자) 외 1필지
3rd row경상남도 함안군 대산면 하기리 415-4번지 외6필
4th row경상남도 함안군 군북면 국우로 95 외 1필지
5th row경상남도 함안군 여항면 내곡1길 93 (국제케미칼) 외 3필지
ValueCountFrequency (%)
경상남도 1727
 
16.0%
함안군 1727
 
16.0%
칠원읍 619
 
5.7%
563
 
5.2%
1필지 235
 
2.2%
군북면 219
 
2.0%
칠서면 209
 
1.9%
법수면 207
 
1.9%
칠북면 144
 
1.3%
산인면 139
 
1.3%
Other values (1882) 4980
46.2%
2023-12-11T09:33:40.394662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9040
 
19.2%
1948
 
4.1%
1889
 
4.0%
1807
 
3.8%
1794
 
3.8%
1768
 
3.8%
1740
 
3.7%
1735
 
3.7%
1 1615
 
3.4%
1106
 
2.3%
Other values (321) 22698
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28468
60.4%
Space Separator 9040
 
19.2%
Decimal Number 6893
 
14.6%
Open Punctuation 910
 
1.9%
Close Punctuation 910
 
1.9%
Dash Punctuation 743
 
1.6%
Uppercase Letter 109
 
0.2%
Other Punctuation 67
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1948
 
6.8%
1889
 
6.6%
1807
 
6.3%
1794
 
6.3%
1768
 
6.2%
1740
 
6.1%
1735
 
6.1%
1106
 
3.9%
1063
 
3.7%
1019
 
3.6%
Other values (285) 12599
44.3%
Uppercase Letter
ValueCountFrequency (%)
E 13
11.9%
T 13
11.9%
S 11
10.1%
H 10
9.2%
M 9
8.3%
N 8
7.3%
C 8
7.3%
G 7
 
6.4%
D 6
 
5.5%
K 5
 
4.6%
Other values (8) 19
17.4%
Decimal Number
ValueCountFrequency (%)
1 1615
23.4%
2 1012
14.7%
3 826
12.0%
5 616
 
8.9%
4 574
 
8.3%
6 517
 
7.5%
7 461
 
6.7%
0 449
 
6.5%
9 440
 
6.4%
8 383
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 48
71.6%
. 10
 
14.9%
& 8
 
11.9%
/ 1
 
1.5%
Space Separator
ValueCountFrequency (%)
9040
100.0%
Open Punctuation
ValueCountFrequency (%)
( 910
100.0%
Close Punctuation
ValueCountFrequency (%)
) 910
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 743
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28468
60.4%
Common 18563
39.4%
Latin 109
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1948
 
6.8%
1889
 
6.6%
1807
 
6.3%
1794
 
6.3%
1768
 
6.2%
1740
 
6.1%
1735
 
6.1%
1106
 
3.9%
1063
 
3.7%
1019
 
3.6%
Other values (285) 12599
44.3%
Common
ValueCountFrequency (%)
9040
48.7%
1 1615
 
8.7%
2 1012
 
5.5%
( 910
 
4.9%
) 910
 
4.9%
3 826
 
4.4%
- 743
 
4.0%
5 616
 
3.3%
4 574
 
3.1%
6 517
 
2.8%
Other values (8) 1800
 
9.7%
Latin
ValueCountFrequency (%)
E 13
11.9%
T 13
11.9%
S 11
10.1%
H 10
9.2%
M 9
8.3%
N 8
7.3%
C 8
7.3%
G 7
 
6.4%
D 6
 
5.5%
K 5
 
4.6%
Other values (8) 19
17.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28468
60.4%
ASCII 18672
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9040
48.4%
1 1615
 
8.6%
2 1012
 
5.4%
( 910
 
4.9%
) 910
 
4.9%
3 826
 
4.4%
- 743
 
4.0%
5 616
 
3.3%
4 574
 
3.1%
6 517
 
2.8%
Other values (26) 1909
 
10.2%
Hangul
ValueCountFrequency (%)
1948
 
6.8%
1889
 
6.6%
1807
 
6.3%
1794
 
6.3%
1768
 
6.2%
1740
 
6.1%
1735
 
6.1%
1106
 
3.9%
1063
 
3.7%
1019
 
3.6%
Other values (285) 12599
44.3%
Distinct1590
Distinct (%)91.6%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2023-12-11T09:33:40.735301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length43
Mean length25.882488
Min length16

Characters and Unicode

Total characters44932
Distinct characters208
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

Unique1468 ?
Unique (%)84.6%

Sample

1st row경상남도 함안군 법수면 윤외리 1555번지
2nd row경상남도 함안군 칠서면 회산리 744-17번지 대흥중자 외 1필지
3rd row경상남도 함안군 대산면 하기리 415-4번지 외6필
4th row경상남도 함안군 군북면 유현리 1312-7번지 외 1필지
5th row경상남도 함안군 여항면 내곡리 754-4번지 국제케미칼 외 3필지
ValueCountFrequency (%)
경상남도 1735
17.3%
함안군 1735
17.3%
칠원읍 612
 
6.1%
551
 
5.5%
1필지 232
 
2.3%
군북면 212
 
2.1%
칠서면 202
 
2.0%
법수면 194
 
1.9%
칠북면 143
 
1.4%
산인면 135
 
1.3%
Other values (1616) 4278
42.7%
2023-12-11T09:33:41.226780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8293
18.5%
2213
 
4.9%
1948
 
4.3%
1788
 
4.0%
1787
 
4.0%
1756
 
3.9%
1744
 
3.9%
1741
 
3.9%
1741
 
3.9%
1735
 
3.9%
Other values (198) 20186
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28098
62.5%
Space Separator 8293
 
18.5%
Decimal Number 7420
 
16.5%
Dash Punctuation 1001
 
2.2%
Open Punctuation 48
 
0.1%
Close Punctuation 48
 
0.1%
Uppercase Letter 17
 
< 0.1%
Other Punctuation 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2213
 
7.9%
1948
 
6.9%
1788
 
6.4%
1787
 
6.4%
1756
 
6.2%
1744
 
6.2%
1741
 
6.2%
1741
 
6.2%
1735
 
6.2%
1599
 
5.7%
Other values (169) 10046
35.8%
Uppercase Letter
ValueCountFrequency (%)
N 3
17.6%
H 2
11.8%
E 2
11.8%
G 2
11.8%
C 1
 
5.9%
S 1
 
5.9%
M 1
 
5.9%
T 1
 
5.9%
A 1
 
5.9%
D 1
 
5.9%
Other values (2) 2
11.8%
Decimal Number
ValueCountFrequency (%)
1 1722
23.2%
2 930
12.5%
3 698
9.4%
5 685
 
9.2%
4 652
 
8.8%
0 630
 
8.5%
7 598
 
8.1%
6 591
 
8.0%
8 523
 
7.0%
9 391
 
5.3%
Other Punctuation
ValueCountFrequency (%)
. 5
71.4%
/ 1
 
14.3%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
8293
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1001
100.0%
Open Punctuation
ValueCountFrequency (%)
( 48
100.0%
Close Punctuation
ValueCountFrequency (%)
) 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28098
62.5%
Common 16817
37.4%
Latin 17
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2213
 
7.9%
1948
 
6.9%
1788
 
6.4%
1787
 
6.4%
1756
 
6.2%
1744
 
6.2%
1741
 
6.2%
1741
 
6.2%
1735
 
6.2%
1599
 
5.7%
Other values (169) 10046
35.8%
Common
ValueCountFrequency (%)
8293
49.3%
1 1722
 
10.2%
- 1001
 
6.0%
2 930
 
5.5%
3 698
 
4.2%
5 685
 
4.1%
4 652
 
3.9%
0 630
 
3.7%
7 598
 
3.6%
6 591
 
3.5%
Other values (7) 1017
 
6.0%
Latin
ValueCountFrequency (%)
N 3
17.6%
H 2
11.8%
E 2
11.8%
G 2
11.8%
C 1
 
5.9%
S 1
 
5.9%
M 1
 
5.9%
T 1
 
5.9%
A 1
 
5.9%
D 1
 
5.9%
Other values (2) 2
11.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28098
62.5%
ASCII 16834
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8293
49.3%
1 1722
 
10.2%
- 1001
 
5.9%
2 930
 
5.5%
3 698
 
4.1%
5 685
 
4.1%
4 652
 
3.9%
0 630
 
3.7%
7 598
 
3.6%
6 591
 
3.5%
Other values (19) 1034
 
6.1%
Hangul
ValueCountFrequency (%)
2213
 
7.9%
1948
 
6.9%
1788
 
6.4%
1787
 
6.4%
1756
 
6.2%
1744
 
6.2%
1741
 
6.2%
1741
 
6.2%
1735
 
6.2%
1599
 
5.7%
Other values (169) 10046
35.8%
Distinct556
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2023-12-11T09:33:41.593781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length327
Median length5
Mean length13.455645
Min length5

Characters and Unicode

Total characters23359
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

Unique368 ?
Unique (%)21.2%

Sample

1st row24219
2nd row29294
3rd row17902
4th row33992
5th row25913, 25914
ValueCountFrequency (%)
25113 226
 
5.9%
25114 190
 
5.0%
30400 145
 
3.8%
30399 132
 
3.4%
29223 121
 
3.2%
31114 119
 
3.1%
30392 117
 
3.1%
30391 117
 
3.1%
25924 89
 
2.3%
25929 60
 
1.6%
Other values (318) 2517
65.7%
2023-12-11T09:33:42.116556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 5159
22.1%
1 3828
16.4%
9 2849
12.2%
3 2675
11.5%
, 2097
9.0%
2097
9.0%
0 1587
 
6.8%
5 1295
 
5.5%
4 978
 
4.2%
6 356
 
1.5%
Other values (2) 438
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 19165
82.0%
Other Punctuation 2097
 
9.0%
Space Separator 2097
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 5159
26.9%
1 3828
20.0%
9 2849
14.9%
3 2675
14.0%
0 1587
 
8.3%
5 1295
 
6.8%
4 978
 
5.1%
6 356
 
1.9%
7 232
 
1.2%
8 206
 
1.1%
Other Punctuation
ValueCountFrequency (%)
, 2097
100.0%
Space Separator
ValueCountFrequency (%)
2097
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 23359
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 5159
22.1%
1 3828
16.4%
9 2849
12.2%
3 2675
11.5%
, 2097
9.0%
2097
9.0%
0 1587
 
6.8%
5 1295
 
5.5%
4 978
 
4.2%
6 356
 
1.5%
Other values (2) 438
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 23359
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 5159
22.1%
1 3828
16.4%
9 2849
12.2%
3 2675
11.5%
, 2097
9.0%
2097
9.0%
0 1587
 
6.8%
5 1295
 
5.5%
4 978
 
4.2%
6 356
 
1.5%
Other values (2) 438
 
1.9%
Distinct473
Distinct (%)27.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2023-12-11T09:33:42.512717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length27
Mean length17.203341
Min length3

Characters and Unicode

Total characters29865
Distinct characters283
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

Unique258 ?
Unique (%)14.9%

Sample

1st row기타 비철금속 제련, 정련 및 합금 제조업
2nd row주형 및 금형 제조업
3rd row위생용 종이제품 제조업
4th row라이터, 연소물 및 흡연용품 제조업
5th row자동차용 금속 압형제품 제조업 외 1 종
ValueCountFrequency (%)
제조업 1474
 
15.1%
974
 
10.0%
743
 
7.6%
609
 
6.2%
1 400
 
4.1%
금속 392
 
4.0%
기타 374
 
3.8%
231
 
2.4%
골조 170
 
1.7%
구조재 170
 
1.7%
Other values (438) 4213
43.2%
2023-12-11T09:33:43.151825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8016
26.8%
1994
 
6.7%
1797
 
6.0%
1782
 
6.0%
976
 
3.3%
949
 
3.2%
756
 
2.5%
645
 
2.2%
609
 
2.0%
564
 
1.9%
Other values (273) 11777
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 20919
70.0%
Space Separator 8016
 
26.8%
Decimal Number 788
 
2.6%
Other Punctuation 140
 
0.5%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1994
 
9.5%
1797
 
8.6%
1782
 
8.5%
976
 
4.7%
949
 
4.5%
756
 
3.6%
645
 
3.1%
609
 
2.9%
564
 
2.7%
524
 
2.5%
Other values (258) 10323
49.3%
Decimal Number
ValueCountFrequency (%)
1 430
54.6%
2 125
 
15.9%
3 121
 
15.4%
4 43
 
5.5%
5 24
 
3.0%
6 20
 
2.5%
7 10
 
1.3%
9 6
 
0.8%
8 5
 
0.6%
0 4
 
0.5%
Other Punctuation
ValueCountFrequency (%)
, 137
97.9%
. 3
 
2.1%
Space Separator
ValueCountFrequency (%)
8016
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 20919
70.0%
Common 8946
30.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1994
 
9.5%
1797
 
8.6%
1782
 
8.5%
976
 
4.7%
949
 
4.5%
756
 
3.6%
645
 
3.1%
609
 
2.9%
564
 
2.7%
524
 
2.5%
Other values (258) 10323
49.3%
Common
ValueCountFrequency (%)
8016
89.6%
1 430
 
4.8%
, 137
 
1.5%
2 125
 
1.4%
3 121
 
1.4%
4 43
 
0.5%
5 24
 
0.3%
6 20
 
0.2%
7 10
 
0.1%
9 6
 
0.1%
Other values (5) 14
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 20910
70.0%
ASCII 8946
30.0%
Compat Jamo 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8016
89.6%
1 430
 
4.8%
, 137
 
1.5%
2 125
 
1.4%
3 121
 
1.4%
4 43
 
0.5%
5 24
 
0.3%
6 20
 
0.2%
7 10
 
0.1%
9 6
 
0.1%
Other values (5) 14
 
0.2%
Hangul
ValueCountFrequency (%)
1994
 
9.5%
1797
 
8.6%
1782
 
8.5%
976
 
4.7%
949
 
4.5%
756
 
3.6%
645
 
3.1%
609
 
2.9%
564
 
2.7%
524
 
2.5%
Other values (257) 10314
49.3%
Compat Jamo
ValueCountFrequency (%)
9
100.0%

관할조직명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
경상남도 함안군
1736 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 함안군 1736
100.0%

Length

2023-12-11T09:33:43.294116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:43.403166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 1736
50.0%
함안군 1736
50.0%

최초등록일
Real number (ℝ)

Distinct1355
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20101509
Minimum19860226
Maximum20211012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T09:33:43.803566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19860226
5-th percentile19970124
Q120050215
median20111208
Q320160720
95-th percentile20201012
Maximum20211012
Range350786
Interquartile range (IQR)110505.25

Descriptive statistics

Standard deviation74243.555
Coefficient of variation (CV)0.0036934319
Kurtosis-0.64994226
Mean20101509
Median Absolute Deviation (MAD)50803
Skewness-0.52558856
Sum3.489622 × 1010
Variance5.5121054 × 109
MonotonicityNot monotonic
2023-12-11T09:33:43.939835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20010504 10
 
0.6%
20010522 6
 
0.3%
20010412 6
 
0.3%
20170203 5
 
0.3%
20100825 5
 
0.3%
20081127 4
 
0.2%
20141001 4
 
0.2%
20101026 4
 
0.2%
20061227 4
 
0.2%
20201012 4
 
0.2%
Other values (1345) 1684
97.0%
ValueCountFrequency (%)
19860226 1
0.1%
19880610 1
0.1%
19890701 1
0.1%
19901217 1
0.1%
19910531 1
0.1%
19920313 1
0.1%
19920327 1
0.1%
19920514 1
0.1%
19920529 1
0.1%
19920803 1
0.1%
ValueCountFrequency (%)
20211012 1
0.1%
20211006 1
0.1%
20210930 1
0.1%
20210929 1
0.1%
20210927 1
0.1%
20210924 1
0.1%
20210916 1
0.1%
20210913 1
0.1%
20210909 2
0.1%
20210907 1
0.1%

종업원수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct78
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.363479
Minimum0
Maximum322
Zeros51
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size15.4 KiB
2023-12-11T09:33:44.098746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q15
median7
Q312
95-th percentile35
Maximum322
Range322
Interquartile range (IQR)7

Descriptive statistics

Standard deviation17.305921
Coefficient of variation (CV)1.5229421
Kurtosis102.42305
Mean11.363479
Median Absolute Deviation (MAD)3
Skewness7.966801
Sum19727
Variance299.4949
MonotonicityNot monotonic
2023-12-11T09:33:44.250055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 326
18.8%
10 154
 
8.9%
3 130
 
7.5%
4 122
 
7.0%
6 117
 
6.7%
8 111
 
6.4%
2 82
 
4.7%
7 69
 
4.0%
9 57
 
3.3%
0 51
 
2.9%
Other values (68) 517
29.8%
ValueCountFrequency (%)
0 51
 
2.9%
1 32
 
1.8%
2 82
 
4.7%
3 130
 
7.5%
4 122
 
7.0%
5 326
18.8%
6 117
 
6.7%
7 69
 
4.0%
8 111
 
6.4%
9 57
 
3.3%
ValueCountFrequency (%)
322 1
0.1%
260 1
0.1%
186 1
0.1%
182 1
0.1%
156 1
0.1%
131 1
0.1%
120 1
0.1%
105 1
0.1%
100 2
0.1%
98 1
0.1%
Distinct1307
Distinct (%)75.3%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
2023-12-11T09:33:44.505883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length37
Mean length8.1947005
Min length1

Characters and Unicode

Total characters14226
Distinct characters545
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1205 ?
Unique (%)69.4%

Sample

1st row마그네슘 인고트(괴)
2nd row산업용로봇
3rd row화장지
4th row폐합성수지류 비성형 SRF
5th row우레탄 금형제품
ValueCountFrequency (%)
101
 
3.6%
철구조물 94
 
3.4%
자동차부품 94
 
3.4%
부품 55
 
2.0%
공작기계부품 39
 
1.4%
34
 
1.2%
자동차 30
 
1.1%
기계부품 28
 
1.0%
28
 
1.0%
선박부품 19
 
0.7%
Other values (1605) 2254
81.2%
2023-12-11T09:33:44.972153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1047
 
7.4%
707
 
5.0%
593
 
4.2%
, 570
 
4.0%
542
 
3.8%
321
 
2.3%
317
 
2.2%
264
 
1.9%
251
 
1.8%
233
 
1.6%
Other values (535) 9381
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11820
83.1%
Space Separator 1047
 
7.4%
Other Punctuation 587
 
4.1%
Uppercase Letter 383
 
2.7%
Lowercase Letter 229
 
1.6%
Open Punctuation 75
 
0.5%
Close Punctuation 75
 
0.5%
Decimal Number 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
707
 
6.0%
593
 
5.0%
542
 
4.6%
321
 
2.7%
317
 
2.7%
264
 
2.2%
251
 
2.1%
233
 
2.0%
233
 
2.0%
233
 
2.0%
Other values (476) 8126
68.7%
Uppercase Letter
ValueCountFrequency (%)
E 44
11.5%
L 36
 
9.4%
A 34
 
8.9%
C 28
 
7.3%
P 27
 
7.0%
R 26
 
6.8%
S 25
 
6.5%
T 21
 
5.5%
O 19
 
5.0%
D 17
 
4.4%
Other values (13) 106
27.7%
Lowercase Letter
ValueCountFrequency (%)
e 36
15.7%
a 19
 
8.3%
r 19
 
8.3%
s 17
 
7.4%
c 16
 
7.0%
t 16
 
7.0%
o 14
 
6.1%
l 13
 
5.7%
p 12
 
5.2%
n 11
 
4.8%
Other values (13) 56
24.5%
Other Punctuation
ValueCountFrequency (%)
, 570
97.1%
. 9
 
1.5%
/ 6
 
1.0%
' 1
 
0.2%
& 1
 
0.2%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
8 2
20.0%
1 2
20.0%
5 1
 
10.0%
7 1
 
10.0%
Space Separator
ValueCountFrequency (%)
1047
100.0%
Open Punctuation
ValueCountFrequency (%)
( 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11820
83.1%
Common 1794
 
12.6%
Latin 612
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
707
 
6.0%
593
 
5.0%
542
 
4.6%
321
 
2.7%
317
 
2.7%
264
 
2.2%
251
 
2.1%
233
 
2.0%
233
 
2.0%
233
 
2.0%
Other values (476) 8126
68.7%
Latin
ValueCountFrequency (%)
E 44
 
7.2%
e 36
 
5.9%
L 36
 
5.9%
A 34
 
5.6%
C 28
 
4.6%
P 27
 
4.4%
R 26
 
4.2%
S 25
 
4.1%
T 21
 
3.4%
a 19
 
3.1%
Other values (36) 316
51.6%
Common
ValueCountFrequency (%)
1047
58.4%
, 570
31.8%
( 75
 
4.2%
) 75
 
4.2%
. 9
 
0.5%
/ 6
 
0.3%
2 4
 
0.2%
8 2
 
0.1%
1 2
 
0.1%
5 1
 
0.1%
Other values (3) 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11819
83.1%
ASCII 2406
 
16.9%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1047
43.5%
, 570
23.7%
( 75
 
3.1%
) 75
 
3.1%
E 44
 
1.8%
e 36
 
1.5%
L 36
 
1.5%
A 34
 
1.4%
C 28
 
1.2%
P 27
 
1.1%
Other values (49) 434
18.0%
Hangul
ValueCountFrequency (%)
707
 
6.0%
593
 
5.0%
542
 
4.6%
321
 
2.7%
317
 
2.7%
264
 
2.2%
251
 
2.1%
233
 
2.0%
233
 
2.0%
233
 
2.0%
Other values (475) 8125
68.7%
Compat Jamo
ValueCountFrequency (%)
1
100.0%

공장크기
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
소기업
1681 
중기업
 
54
대기업
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
소기업 1681
96.8%
중기업 54
 
3.1%
대기업 1
 
0.1%

Length

2023-12-11T09:33:45.134613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:45.245860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소기업 1681
96.8%
중기업 54
 
3.1%
대기업 1
 
0.1%

용도지역
Categorical

Distinct20
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
관리지역/계획관리지역
964 
관리지역
317 
관리지역/관리지역기타
167 
도시지역/공업지역/준공업지역
 
81
관리지역/계획관리지역/개발진흥지구
 
50
Other values (15)
157 

Length

Max length25
Median length11
Mean length10.485023
Min length4

Unique

Unique3 ?
Unique (%)0.2%

Sample

1st row관리지역/계획관리지역
2nd row관리지역/계획관리지역
3rd row관리지역
4th row관리지역/계획관리지역
5th row관리지역/계획관리지역

Common Values

ValueCountFrequency (%)
관리지역/계획관리지역 964
55.5%
관리지역 317
 
18.3%
관리지역/관리지역기타 167
 
9.6%
도시지역/공업지역/준공업지역 81
 
4.7%
관리지역/계획관리지역/개발진흥지구 50
 
2.9%
도시지역/공업지역/일반공업지역 42
 
2.4%
관리지역/생산관리지역 30
 
1.7%
관리지역/보전관리지역 24
 
1.4%
도시지역/녹지지역/자연녹지지역 19
 
1.1%
도시지역/주거지역/제1종일반주거지역 9
 
0.5%
Other values (10) 33
 
1.9%

Length

2023-12-11T09:33:45.361267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관리지역/계획관리지역 964
55.5%
관리지역 317
 
18.3%
관리지역/관리지역기타 167
 
9.6%
도시지역/공업지역/준공업지역 81
 
4.7%
관리지역/계획관리지역/개발진흥지구 50
 
2.9%
도시지역/공업지역/일반공업지역 42
 
2.4%
관리지역/생산관리지역 30
 
1.7%
관리지역/보전관리지역 24
 
1.4%
도시지역/녹지지역/자연녹지지역 19
 
1.1%
도시지역/주거지역/제1종일반주거지역 9
 
0.5%
Other values (10) 33
 
1.9%

지목
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct14
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
공장용지
1600 
 
46
 
31
 
27
잡종지
 
18
Other values (9)
 
14

Length

Max length5
Median length4
Mean length3.8024194
Min length1

Unique

Unique5 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
공장용지 1600
92.2%
46
 
2.6%
31
 
1.8%
27
 
1.6%
잡종지 18
 
1.0%
도로 3
 
0.2%
유원지 2
 
0.1%
임야 2
 
0.1%
목장용지 2
 
0.1%
<NA> 1
 
0.1%
Other values (4) 4
 
0.2%

Length

2023-12-11T09:33:45.502178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공장용지 1600
92.2%
46
 
2.6%
31
 
1.8%
27
 
1.6%
잡종지 18
 
1.0%
도로 3
 
0.2%
유원지 2
 
0.1%
임야 2
 
0.1%
목장용지 2
 
0.1%
na 1
 
0.1%
Other values (4) 4
 
0.2%

용지면적
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1345
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4210.0294
Minimum-291.2
Maximum134207
Zeros198
Zeros (%)11.4%
Negative1
Negative (%)0.1%
Memory size15.4 KiB
2023-12-11T09:33:45.634859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-291.2
5-th percentile0
Q11086
median2314
Q34824.75
95-th percentile14770
Maximum134207
Range134498.2
Interquartile range (IQR)3738.75

Descriptive statistics

Standard deviation6732.1036
Coefficient of variation (CV)1.5990633
Kurtosis102.11858
Mean4210.0294
Median Absolute Deviation (MAD)1487.775
Skewness7.3200098
Sum7308611
Variance45321219
MonotonicityNot monotonic
2023-12-11T09:33:45.778487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 198
 
11.4%
1878.0 5
 
0.3%
1488.0 5
 
0.3%
1150.0 5
 
0.3%
3271.0 3
 
0.2%
1006.0 3
 
0.2%
1620.0 3
 
0.2%
1502.0 3
 
0.2%
1380.0 3
 
0.2%
760.0 3
 
0.2%
Other values (1335) 1505
86.7%
ValueCountFrequency (%)
-291.2 1
 
0.1%
0.0 198
11.4%
57.0 1
 
0.1%
90.5 1
 
0.1%
113.6 1
 
0.1%
129.6 1
 
0.1%
165.75 1
 
0.1%
179.0 1
 
0.1%
179.4 1
 
0.1%
180.4 1
 
0.1%
ValueCountFrequency (%)
134207.0 1
0.1%
89941.0 1
0.1%
56856.0 1
0.1%
49863.6 1
0.1%
46498.1 1
0.1%
39981.0 1
0.1%
39900.0 1
0.1%
37152.6 1
0.1%
36561.0 1
0.1%
34418.0 1
0.1%

건축면적
Real number (ℝ)

HIGH CORRELATION 

Distinct1582
Distinct (%)91.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1683.6826
Minimum-291.2
Maximum89970.25
Zeros2
Zeros (%)0.1%
Negative1
Negative (%)0.1%
Memory size15.4 KiB
2023-12-11T09:33:45.962796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-291.2
5-th percentile198
Q1474.3125
median892.875
Q31813.0425
95-th percentile4939.875
Maximum89970.25
Range90261.45
Interquartile range (IQR)1338.73

Descriptive statistics

Standard deviation3355.2631
Coefficient of variation (CV)1.9928121
Kurtosis301.98443
Mean1683.6826
Median Absolute Deviation (MAD)512.15
Skewness13.670081
Sum2922873
Variance11257790
MonotonicityNot monotonic
2023-12-11T09:33:46.099746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198.0 9
 
0.5%
330.0 8
 
0.5%
300.0 7
 
0.4%
192.0 5
 
0.3%
396.0 5
 
0.3%
310.0 4
 
0.2%
488.0 4
 
0.2%
972.0 4
 
0.2%
99.0 4
 
0.2%
195.0 3
 
0.2%
Other values (1572) 1683
96.9%
ValueCountFrequency (%)
-291.2 1
0.1%
0.0 2
0.1%
20.0 1
0.1%
27.3 1
0.1%
33.0 2
0.1%
40.32 1
0.1%
47.76 1
0.1%
50.0 2
0.1%
57.6 1
0.1%
62.0 1
0.1%
ValueCountFrequency (%)
89970.25 1
0.1%
42292.12 1
0.1%
35525.46 1
0.1%
34101.55 1
0.1%
24817.45 1
0.1%
19011.525 1
0.1%
17617.04 1
0.1%
16832.58 1
0.1%
16537.42 1
0.1%
16003.74 1
0.1%

대기등급
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct7
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
해당없음
929 
<NA>
695 
5종
 
80
4종
 
24
2종
 
3
Other values (2)
 
5

Length

Max length4
Median length4
Mean length3.8709677
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 929
53.5%
<NA> 695
40.0%
5종 80
 
4.6%
4종 24
 
1.4%
2종 3
 
0.2%
3종 3
 
0.2%
1종 2
 
0.1%

Length

2023-12-11T09:33:46.261173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:46.405752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 929
53.5%
na 695
40.0%
5종 80
 
4.6%
4종 24
 
1.4%
2종 3
 
0.2%
3종 3
 
0.2%
1종 2
 
0.1%

수질등급
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
해당없음
992 
<NA>
695 
5종
 
46
3종
 
2
2종
 
1

Length

Max length4
Median length4
Mean length3.9435484
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
해당없음 992
57.1%
<NA> 695
40.0%
5종 46
 
2.6%
3종 2
 
0.1%
2종 1
 
0.1%

Length

2023-12-11T09:33:46.599930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:46.747247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
해당없음 992
57.1%
na 695
40.0%
5종 46
 
2.6%
3종 2
 
0.1%
2종 1
 
0.1%

소음/진동여부
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.7 KiB
1549 
187 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1549
89.2%
187
 
10.8%

Length

2023-12-11T09:33:46.867845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:46.979136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1549
89.2%
187
 
10.8%

Interactions

2023-12-11T09:33:37.904534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.137961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.594489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.056810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.500331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.982954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.225857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.690314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.146595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.579193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:38.066138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.322897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.785311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.243179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.665241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:38.177356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.415718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.877479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.334796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.745764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:38.277309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.515581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:36.972203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.416407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T09:33:37.826628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T09:33:47.073563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명최초등록일종업원수공장크기용도지역지목용지면적건축면적대기등급수질등급소음/진동여부
순번1.0000.3450.1670.0870.0000.2130.0540.0850.0620.0000.0000.027
단지명0.3451.0000.5800.7340.3790.769NaN0.7640.6060.8000.3830.000
최초등록일0.1670.5801.0000.4000.2490.7110.0750.1030.1490.3990.4690.453
종업원수0.0870.7340.4001.0000.8950.0000.0000.7070.7940.5730.6000.118
공장크기0.0000.3790.2490.8951.0000.0000.0000.8170.9700.8190.1400.037
용도지역0.2130.7690.7110.0000.0001.0000.5960.0000.0600.3280.0000.213
지목0.054NaN0.0750.0000.0000.5961.0000.0000.0000.0000.0000.000
용지면적0.0850.7640.1030.7070.8170.0000.0001.0000.8280.4970.1770.123
건축면적0.0620.6060.1490.7940.9700.0600.0000.8281.0000.7010.1840.149
대기등급0.0000.8000.3990.5730.8190.3280.0000.4970.7011.0000.6320.610
수질등급0.0000.3830.4690.6000.1400.0000.0000.1770.1840.6321.0000.246
소음/진동여부0.0270.0000.4530.1180.0370.2130.0000.1230.1490.6100.2461.000
2023-12-11T09:33:47.236920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소음/진동여부단지명대기등급지목수질등급공장크기용도지역
소음/진동여부1.0000.0000.4430.0000.1640.0620.167
단지명0.0001.0000.5451.0000.3230.3290.432
대기등급0.4430.5451.0000.0000.4610.5030.136
지목0.0001.0000.0001.0000.0000.0000.245
수질등급0.1640.3230.4610.0001.0000.1320.000
공장크기0.0620.3290.5030.0000.1321.0000.000
용도지역0.1670.4320.1360.2450.0000.0001.000
2023-12-11T09:33:47.368965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번최초등록일종업원수용지면적건축면적단지명공장크기용도지역지목대기등급수질등급소음/진동여부
순번1.000-0.075-0.197-0.173-0.2050.1380.0000.0690.0220.0000.0000.021
최초등록일-0.0751.000-0.287-0.095-0.0340.2690.1470.3040.0310.1950.2470.348
종업원수-0.197-0.2871.0000.5020.5620.4460.8740.0000.0000.3640.3020.088
용지면적-0.173-0.0950.5021.0000.8050.5280.7760.0000.0000.3240.1220.131
건축면적-0.205-0.0340.5620.8051.0000.3730.7880.0270.0000.3200.1190.107
단지명0.1380.2690.4460.5280.3731.0000.3290.4321.0000.5450.3230.000
공장크기0.0000.1470.8740.7760.7880.3291.0000.0000.0000.5030.1320.062
용도지역0.0690.3040.0000.0000.0270.4320.0001.0000.2450.1360.0000.167
지목0.0220.0310.0000.0000.0001.0000.0000.2451.0000.0000.0000.000
대기등급0.0000.1950.3640.3240.3200.5450.5030.1360.0001.0000.4610.443
수질등급0.0000.2470.3020.1220.1190.3230.1320.0000.0000.4611.0000.164
소음/진동여부0.0210.3480.0880.1310.1070.0000.0620.1670.0000.4430.1641.000

Missing values

2023-12-11T09:33:38.406359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:33:38.603561image/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.

Sample

순번단지명회사명공장대표주소(도로명)공장대표주소(지번)업종번호업종명관할조직명최초등록일종업원수생산품공장크기용도지역지목용지면적건축면적대기등급수질등급소음/진동여부
01<NA>YSM경상남도 함안군 법수면 윤외리 1555번지경상남도 함안군 법수면 윤외리 1555번지24219기타 비철금속 제련, 정련 및 합금 제조업경상남도 함안군201509147마그네슘 인고트(괴)소기업관리지역/계획관리지역공장용지1878.0543.0<NA><NA>
12<NA>대흥중자경상남도 함안군 칠서면 함의로 209-40 (대흥중자) 외 1필지경상남도 함안군 칠서면 회산리 744-17번지 대흥중자 외 1필지29294주형 및 금형 제조업경상남도 함안군200708237산업용로봇소기업관리지역/계획관리지역공장용지2384.01346.02해당없음해당없음
23<NA>(사)경남신체장애인복지회경상남도 함안군 대산면 하기리 415-4번지 외6필경상남도 함안군 대산면 하기리 415-4번지 외6필17902위생용 종이제품 제조업경상남도 함안군2001041811화장지소기업관리지역공장용지3602.0494.7해당없음해당없음
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