Overview

Dataset statistics

Number of variables12
Number of observations174
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.8 KiB
Average record size in memory98.8 B

Variable types

Numeric1
Categorical7
Text4

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
시군명 is highly overall correlated with 단지명 and 1 other fieldsHigh correlation
단지명 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
상세주소 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
회사명 has unique valuesUnique
대표자 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:53:38.158247
Analysis finished2024-03-14 00:53:38.856259
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct174
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.49425
Minimum1
Maximum210
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-03-14T09:53:38.913142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.65
Q159.25
median111.5
Q3158.75
95-th percentile201.35
Maximum210
Range209
Interquartile range (IQR)99.5

Descriptive statistics

Standard deviation59.933465
Coefficient of variation (CV)0.54241251
Kurtosis-1.144222
Mean110.49425
Median Absolute Deviation (MAD)50.5
Skewness-0.074484463
Sum19226
Variance3592.0202
MonotonicityStrictly increasing
2024-03-14T09:53:39.031389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
149 1
 
0.6%
141 1
 
0.6%
142 1
 
0.6%
143 1
 
0.6%
144 1
 
0.6%
145 1
 
0.6%
146 1
 
0.6%
147 1
 
0.6%
148 1
 
0.6%
Other values (164) 164
94.3%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
10 1
0.6%
11 1
0.6%
ValueCountFrequency (%)
210 1
0.6%
209 1
0.6%
208 1
0.6%
207 1
0.6%
206 1
0.6%
205 1
0.6%
204 1
0.6%
203 1
0.6%
202 1
0.6%
201 1
0.6%

시군명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
군산시
64 
익산시
38 
전주시
33 
정읍시
16 
김제시
15 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
군산시 64
36.8%
익산시 38
21.8%
전주시 33
19.0%
정읍시 16
 
9.2%
김제시 15
 
8.6%
완주군 8
 
4.6%

Length

2024-03-14T09:53:39.128895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:53:39.243251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
군산시 64
36.8%
익산시 38
21.8%
전주시 33
19.0%
정읍시 16
 
9.2%
김제시 15
 
8.6%
완주군 8
 
4.6%

회사명
Text

UNIQUE 

Distinct174
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-14T09:53:39.452155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.1034483
Min length2

Characters and Unicode

Total characters1236
Distinct characters207
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)100.0%

Sample

1st row(주)신동아
2nd row(주)에이치아이티오토모티브
3rd row대운산업
4th row(주)지에스엠
5th row(주)티투앤아이
ValueCountFrequency (%)
주식회사 3
 
1.6%
군산공장 2
 
1.1%
에스엔에스켐텍코리아(주 1
 
0.5%
비엠개발 1
 
0.5%
코앤파에너지 1
 
0.5%
주)명일정공 1
 
0.5%
주)비앤디하이텍 1
 
0.5%
주)세창 1
 
0.5%
주)우진고분자 1
 
0.5%
주)카이로라이트 1
 
0.5%
Other values (170) 170
92.9%
2024-03-14T09:53:39.762316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 126
 
10.2%
) 126
 
10.2%
122
 
9.9%
40
 
3.2%
26
 
2.1%
24
 
1.9%
23
 
1.9%
22
 
1.8%
21
 
1.7%
18
 
1.5%
Other values (197) 688
55.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 960
77.7%
Open Punctuation 126
 
10.2%
Close Punctuation 126
 
10.2%
Uppercase Letter 13
 
1.1%
Space Separator 9
 
0.7%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
122
 
12.7%
40
 
4.2%
26
 
2.7%
24
 
2.5%
23
 
2.4%
22
 
2.3%
21
 
2.2%
18
 
1.9%
18
 
1.9%
17
 
1.8%
Other values (183) 629
65.5%
Uppercase Letter
ValueCountFrequency (%)
E 3
23.1%
N 2
15.4%
J 1
 
7.7%
M 1
 
7.7%
I 1
 
7.7%
S 1
 
7.7%
R 1
 
7.7%
D 1
 
7.7%
B 1
 
7.7%
G 1
 
7.7%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 960
77.7%
Common 263
 
21.3%
Latin 13
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
122
 
12.7%
40
 
4.2%
26
 
2.7%
24
 
2.5%
23
 
2.4%
22
 
2.3%
21
 
2.2%
18
 
1.9%
18
 
1.9%
17
 
1.8%
Other values (183) 629
65.5%
Latin
ValueCountFrequency (%)
E 3
23.1%
N 2
15.4%
J 1
 
7.7%
M 1
 
7.7%
I 1
 
7.7%
S 1
 
7.7%
R 1
 
7.7%
D 1
 
7.7%
B 1
 
7.7%
G 1
 
7.7%
Common
ValueCountFrequency (%)
( 126
47.9%
) 126
47.9%
9
 
3.4%
. 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 960
77.7%
ASCII 276
 
22.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 126
45.7%
) 126
45.7%
9
 
3.3%
E 3
 
1.1%
. 2
 
0.7%
N 2
 
0.7%
J 1
 
0.4%
M 1
 
0.4%
I 1
 
0.4%
S 1
 
0.4%
Other values (4) 4
 
1.4%
Hangul
ValueCountFrequency (%)
122
 
12.7%
40
 
4.2%
26
 
2.7%
24
 
2.5%
23
 
2.4%
22
 
2.3%
21
 
2.2%
18
 
1.9%
18
 
1.9%
17
 
1.8%
Other values (183) 629
65.5%

단지명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
-
68 
군산2국가산업단지
33 
익산제2지방산업단지
17 
군산국가산업단지
17 
전주제1지방산업단지
 
5
Other values (18)
34 

Length

Max length10
Median length9
Mean length5.8678161
Min length1

Unique

Unique10 ?
Unique (%)5.7%

Sample

1st row군산2국가산업단지
2nd row군산2국가산업단지
3rd row군산2국가산업단지
4th row군산2국가산업단지
5th row군산2국가산업단지

Common Values

ValueCountFrequency (%)
- 68
39.1%
군산2국가산업단지 33
19.0%
익산제2지방산업단지 17
 
9.8%
군산국가산업단지 17
 
9.8%
전주제1지방산업단지 5
 
2.9%
익산국가산업단지 4
 
2.3%
정읍제2지방산업단지 4
 
2.3%
정읍제3지방산업단지 4
 
2.3%
김제순동지방산업단지 3
 
1.7%
김제대동농공단지 3
 
1.7%
Other values (13) 16
 
9.2%

Length

2024-03-14T09:53:39.897363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
68
39.1%
군산2국가산업단지 33
19.0%
익산제2지방산업단지 17
 
9.8%
군산국가산업단지 17
 
9.8%
전주제1지방산업단지 5
 
2.9%
익산국가산업단지 4
 
2.3%
정읍제2지방산업단지 4
 
2.3%
정읍제3지방산업단지 4
 
2.3%
김제순동지방산업단지 3
 
1.7%
김제대동농공단지 3
 
1.7%
Other values (13) 16
 
9.2%

대표자
Text

UNIQUE 

Distinct174
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-14T09:53:40.235621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.1666667
Min length2

Characters and Unicode

Total characters551
Distinct characters141
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique174 ?
Unique (%)100.0%

Sample

1st row김기영
2nd row김현석
3rd row장동희
4th row조철용
5th row김희원
ValueCountFrequency (%)
1명 2
 
1.1%
2
 
1.1%
김석중 1
 
0.6%
조경록 1
 
0.6%
김문용 1
 
0.6%
최학규 1
 
0.6%
강연성 1
 
0.6%
한두원 1
 
0.6%
권오령 1
 
0.6%
김종성 1
 
0.6%
Other values (166) 166
93.3%
2024-03-14T09:53:40.842175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
40
 
7.3%
29
 
5.3%
15
 
2.7%
14
 
2.5%
12
 
2.2%
12
 
2.2%
12
 
2.2%
11
 
2.0%
11
 
2.0%
11
 
2.0%
Other values (131) 384
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 541
98.2%
Other Punctuation 4
 
0.7%
Space Separator 4
 
0.7%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
40
 
7.4%
29
 
5.4%
15
 
2.8%
14
 
2.6%
12
 
2.2%
12
 
2.2%
12
 
2.2%
11
 
2.0%
11
 
2.0%
11
 
2.0%
Other values (128) 374
69.1%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 541
98.2%
Common 10
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
40
 
7.4%
29
 
5.4%
15
 
2.8%
14
 
2.6%
12
 
2.2%
12
 
2.2%
12
 
2.2%
11
 
2.0%
11
 
2.0%
11
 
2.0%
Other values (128) 374
69.1%
Common
ValueCountFrequency (%)
, 4
40.0%
4
40.0%
1 2
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 541
98.2%
ASCII 10
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
40
 
7.4%
29
 
5.4%
15
 
2.8%
14
 
2.6%
12
 
2.2%
12
 
2.2%
12
 
2.2%
11
 
2.0%
11
 
2.0%
11
 
2.0%
Other values (128) 374
69.1%
ASCII
ValueCountFrequency (%)
, 4
40.0%
4
40.0%
1 2
20.0%
Distinct163
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-14T09:53:41.083070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length20
Mean length8.6321839
Min length1

Characters and Unicode

Total characters1502
Distinct characters261
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

Unique158 ?
Unique (%)90.8%

Sample

1st row자동차금형
2nd row프레스금형
3rd row자동차부품
4th row금형,산업기계부품
5th row금형,금속가공
ValueCountFrequency (%)
자동차부품 10
 
3.6%
자동차 9
 
3.3%
도장 8
 
2.9%
부품 7
 
2.6%
금형 6
 
2.2%
5
 
1.8%
바이오디젤 4
 
1.5%
산업용 3
 
1.1%
산업용기계 3
 
1.1%
금속탱크 3
 
1.1%
Other values (202) 216
78.8%
2024-03-14T09:53:41.500130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
100
 
6.7%
, 68
 
4.5%
55
 
3.7%
54
 
3.6%
44
 
2.9%
44
 
2.9%
42
 
2.8%
38
 
2.5%
37
 
2.5%
36
 
2.4%
Other values (251) 984
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1263
84.1%
Space Separator 100
 
6.7%
Other Punctuation 73
 
4.9%
Uppercase Letter 40
 
2.7%
Close Punctuation 8
 
0.5%
Open Punctuation 8
 
0.5%
Lowercase Letter 8
 
0.5%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
55
 
4.4%
54
 
4.3%
44
 
3.5%
44
 
3.5%
42
 
3.3%
38
 
3.0%
37
 
2.9%
36
 
2.9%
34
 
2.7%
29
 
2.3%
Other values (223) 850
67.3%
Uppercase Letter
ValueCountFrequency (%)
P 10
25.0%
R 5
12.5%
L 4
 
10.0%
E 3
 
7.5%
C 3
 
7.5%
A 3
 
7.5%
B 2
 
5.0%
F 2
 
5.0%
D 2
 
5.0%
S 2
 
5.0%
Other values (4) 4
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
25.0%
s 1
12.5%
n 1
12.5%
i 1
12.5%
r 1
12.5%
v 1
12.5%
o 1
12.5%
Other Punctuation
ValueCountFrequency (%)
, 68
93.2%
. 4
 
5.5%
/ 1
 
1.4%
Space Separator
ValueCountFrequency (%)
100
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1263
84.1%
Common 191
 
12.7%
Latin 48
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
55
 
4.4%
54
 
4.3%
44
 
3.5%
44
 
3.5%
42
 
3.3%
38
 
3.0%
37
 
2.9%
36
 
2.9%
34
 
2.7%
29
 
2.3%
Other values (223) 850
67.3%
Latin
ValueCountFrequency (%)
P 10
20.8%
R 5
10.4%
L 4
 
8.3%
E 3
 
6.2%
C 3
 
6.2%
A 3
 
6.2%
B 2
 
4.2%
F 2
 
4.2%
D 2
 
4.2%
S 2
 
4.2%
Other values (11) 12
25.0%
Common
ValueCountFrequency (%)
100
52.4%
, 68
35.6%
) 8
 
4.2%
( 8
 
4.2%
. 4
 
2.1%
- 2
 
1.0%
/ 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1263
84.1%
ASCII 239
 
15.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
100
41.8%
, 68
28.5%
P 10
 
4.2%
) 8
 
3.3%
( 8
 
3.3%
R 5
 
2.1%
L 4
 
1.7%
. 4
 
1.7%
E 3
 
1.3%
C 3
 
1.3%
Other values (18) 26
 
10.9%
Hangul
ValueCountFrequency (%)
55
 
4.4%
54
 
4.3%
44
 
3.5%
44
 
3.5%
42
 
3.3%
38
 
3.0%
37
 
2.9%
36
 
2.9%
34
 
2.7%
29
 
2.3%
Other values (223) 850
67.3%
Distinct163
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-14T09:53:41.887212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length14.114943
Min length10

Characters and Unicode

Total characters2456
Distinct characters121
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)89.1%

Sample

1st row군산시 산단로 42
2nd row군산시 산단로 42
3rd row군산시 동가도길 61
4th row군산시 산단로 42
5th row군산시 산단동서로 102-20
ValueCountFrequency (%)
군산시 64
 
10.8%
익산시 38
 
6.4%
전주시 33
 
5.6%
덕진구 33
 
5.6%
정읍시 16
 
2.7%
김제시 15
 
2.5%
산단로 10
 
1.7%
봉동읍 8
 
1.3%
외항로 8
 
1.3%
완주군 8
 
1.3%
Other values (257) 361
60.8%
2024-03-14T09:53:42.430830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
420
 
17.1%
166
 
6.8%
157
 
6.4%
1 120
 
4.9%
117
 
4.8%
2 89
 
3.6%
80
 
3.3%
3 79
 
3.2%
74
 
3.0%
4 58
 
2.4%
Other values (111) 1096
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1395
56.8%
Decimal Number 588
23.9%
Space Separator 420
 
17.1%
Dash Punctuation 53
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
166
 
11.9%
157
 
11.3%
117
 
8.4%
80
 
5.7%
74
 
5.3%
51
 
3.7%
48
 
3.4%
42
 
3.0%
38
 
2.7%
38
 
2.7%
Other values (99) 584
41.9%
Decimal Number
ValueCountFrequency (%)
1 120
20.4%
2 89
15.1%
3 79
13.4%
4 58
9.9%
6 44
 
7.5%
7 43
 
7.3%
8 43
 
7.3%
5 40
 
6.8%
0 39
 
6.6%
9 33
 
5.6%
Space Separator
ValueCountFrequency (%)
420
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 53
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1395
56.8%
Common 1061
43.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
166
 
11.9%
157
 
11.3%
117
 
8.4%
80
 
5.7%
74
 
5.3%
51
 
3.7%
48
 
3.4%
42
 
3.0%
38
 
2.7%
38
 
2.7%
Other values (99) 584
41.9%
Common
ValueCountFrequency (%)
420
39.6%
1 120
 
11.3%
2 89
 
8.4%
3 79
 
7.4%
4 58
 
5.5%
- 53
 
5.0%
6 44
 
4.1%
7 43
 
4.1%
8 43
 
4.1%
5 40
 
3.8%
Other values (2) 72
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1395
56.8%
ASCII 1061
43.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
420
39.6%
1 120
 
11.3%
2 89
 
8.4%
3 79
 
7.4%
4 58
 
5.5%
- 53
 
5.0%
6 44
 
4.1%
7 43
 
4.1%
8 43
 
4.1%
5 40
 
3.8%
Other values (2) 72
 
6.8%
Hangul
ValueCountFrequency (%)
166
 
11.9%
157
 
11.3%
117
 
8.4%
80
 
5.7%
74
 
5.3%
51
 
3.7%
48
 
3.4%
42
 
3.0%
38
 
2.7%
38
 
2.7%
Other values (99) 584
41.9%

상세주소
Categorical

HIGH CORRELATION 

Distinct41
Distinct (%)23.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
-
52 
(오식도동)
30 
(소룡동)
19 
(팔봉동)
(하북동)
 
5
Other values (36)
59 

Length

Max length29
Median length28
Mean length4.9942529
Min length1

Unique

Unique25 ?
Unique (%)14.4%

Sample

1st row(오식도동)
2nd row(오식도동)
3rd row(오식도동)
4th row(재)전북자동차기술원 금형프라쟈 202호
5th row(오식도동)

Common Values

ValueCountFrequency (%)
- 52
29.9%
(오식도동) 30
17.2%
(소룡동) 19
 
10.9%
(팔봉동) 9
 
5.2%
(하북동) 5
 
2.9%
(용제동) 4
 
2.3%
외 1필지 4
 
2.3%
(금강동) 4
 
2.3%
(여의동) 4
 
2.3%
(신흥동) 4
 
2.3%
Other values (31) 39
22.4%

Length

2024-03-14T09:53:42.561625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
52
24.5%
오식도동 31
14.6%
소룡동 21
 
9.9%
11
 
5.2%
팔봉동 11
 
5.2%
필지 5
 
2.4%
1 5
 
2.4%
하북동 5
 
2.4%
1필지 4
 
1.9%
금강동 4
 
1.9%
Other values (45) 63
29.7%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
산업진흥과
174 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
산업진흥과 174
100.0%

Length

2024-03-14T09:53:42.653331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:53:42.728419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
산업진흥과 174
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
공개
174 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 174
100.0%

Length

2024-03-14T09:53:42.808399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:53:42.889553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 174
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2015.1
174 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 174
100.0%

Length

2024-03-14T09:53:42.966996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:53:43.044103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 174
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
1년
174 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 174
100.0%

Length

2024-03-14T09:53:43.122164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:53:43.208137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 174
100.0%

Interactions

2024-03-14T09:53:38.595490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:53:43.264868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명단지명상세주소
순번1.0000.7210.6940.659
시군명0.7211.0000.8970.887
단지명0.6940.8971.0000.938
상세주소0.6590.8870.9381.000
2024-03-14T09:53:43.351156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명단지명상세주소
시군명1.0000.6430.562
단지명0.6431.0000.502
상세주소0.5620.5021.000
2024-03-14T09:53:43.431809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명단지명상세주소
순번1.0000.4810.3250.260
시군명0.4811.0000.6430.562
단지명0.3250.6431.0000.502
상세주소0.2600.5620.5021.000

Missing values

2024-03-14T09:53:38.680060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:53:38.804134image/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

순번시군명회사명단지명대표자생산품도로명주소상세주소자료출처공개여부작성일갱신주기
01군산시(주)신동아군산2국가산업단지김기영자동차금형군산시 산단로 42(오식도동)산업진흥과공개2015.11년
12군산시(주)에이치아이티오토모티브군산2국가산업단지김현석프레스금형군산시 산단로 42(오식도동)산업진흥과공개2015.11년
23군산시대운산업군산2국가산업단지장동희자동차부품군산시 동가도길 61(오식도동)산업진흥과공개2015.11년
34군산시(주)지에스엠군산2국가산업단지조철용금형,산업기계부품군산시 산단로 42(재)전북자동차기술원 금형프라쟈 202호산업진흥과공개2015.11년
45군산시(주)티투앤아이군산2국가산업단지김희원금형,금속가공군산시 산단동서로 102-20(오식도동)산업진흥과공개2015.11년
56군산시(주)성림테크군산국가산업단지조정기금형, 자동화설비군산시 동장산2길 6(재)전북자동차부품혁신센터산업진흥과공개2015.11년
67군산시대승금형군산2국가산업단지김흥기자동차,농기계,중장비 금형군산시 산단로 42304호 (오식도동)산업진흥과공개2015.11년
78군산시(주)국제디와이군산성산농공단지정광명몰드베이스군산시 성산면 동군산로 136-7-산업진흥과공개2015.11년
810군산시(주)신영하이테크-강성준 외 1명자동차 프레스금형군산시 오식도동 814-4전북금형비지니스프라자3층 302호산업진흥과공개2015.11년
911김제시(주)협진-황병선-김제시 성덕면 점촌5길 159-산업진흥과공개2015.11년
순번시군명회사명단지명대표자생산품도로명주소상세주소자료출처공개여부작성일갱신주기
164201전주시진웅화학-배영수수처리제전주시 덕진구 상리4길 14-산업진흥과공개2015.11년
165202전주시혜인기계-양희국사출성형기, 에어콤푸레셔, 반도체장비 등전주시 덕진구 감수길 30-22-산업진흥과공개2015.11년
166203전주시흥산화성 전주공장-김정의지방산에스테르유전주시 덕진구 추천로 365-산업진흥과공개2015.11년
167204전주시우정정공-이남사출기계부품전주시 덕진구 감수길 30-20-산업진흥과공개2015.11년
168205전주시IM-최동수태양광트랙커전주시 덕진구 신복천변3길 38(팔복동 1가)산업진흥과공개2015.11년
169206정읍시(주)현보하이텍정읍고부농공단지송상우자동차부품 도장정읍시 고부면 고부농단길 11-6-산업진흥과공개2015.11년
170207정읍시(주)에너지코리아정읍제3지방산업단지홍세승,김인선재생유정읍시 북면 3산단3길 112-산업진흥과공개2015.11년
171208정읍시(주)에이엔씨아이정읍제3지방산업단지이종길,김동인점착활성탄정읍시 북면 3산단3길 67-산업진흥과공개2015.11년
172209정읍시(주)주선화학-이견희도막보호제및제진제정읍시 옹동면 우동길 48-3외 7필지산업진흥과공개2015.11년
173210정읍시(주)켐믹스정읍제2지방산업단지이강태고무이형제, 탈취제정읍시 2산단4길 14(하북동)산업진흥과공개2015.11년