Overview

Dataset statistics

Number of variables12
Number of observations64
Missing cells97
Missing cells (%)12.6%
Duplicate rows1
Duplicate rows (%)1.6%
Total size in memory6.3 KiB
Average record size in memory100.1 B

Variable types

Numeric2
Categorical4
Text6

Dataset

Description평창군 농공단지 입주업체 현황으로 단지명, 회사명, 공장대표주소, 대표자명, 전화번호, 팩스번호, 업종명, 종업원수 등의 정보를 제공합니다.
Author강원도 평창군
URLhttps://www.data.go.kr/data/15042114/fileData.do

Alerts

Dataset has 1 (1.6%) duplicate rowsDuplicates
단지명 is highly overall correlated with 시도명 and 2 other fieldsHigh correlation
시군명 is highly overall correlated with 순번 and 4 other fieldsHigh correlation
데이터기준일자 is highly overall correlated with 순번 and 4 other fieldsHigh correlation
시도명 is highly overall correlated with 순번 and 4 other fieldsHigh correlation
순번 is highly overall correlated with 시도명 and 2 other fieldsHigh correlation
종업원수 is highly overall correlated with 시도명 and 2 other fieldsHigh correlation
순번 has 9 (14.1%) missing valuesMissing
회사명 has 9 (14.1%) missing valuesMissing
대표자명 has 9 (14.1%) missing valuesMissing
공장대표주소(도로명) has 9 (14.1%) missing valuesMissing
업종명 has 9 (14.1%) missing valuesMissing
전화번호 has 16 (25.0%) missing valuesMissing
팩스번호 has 27 (42.2%) missing valuesMissing
종업원수 has 9 (14.1%) missing valuesMissing
종업원수 has 7 (10.9%) zerosZeros

Reproduction

Analysis started2023-12-12 17:30:37.438687
Analysis finished2023-12-12 17:30:39.014088
Duration1.58 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct55
Distinct (%)100.0%
Missing9
Missing (%)14.1%
Infinite0
Infinite (%)0.0%
Mean28
Minimum1
Maximum55
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T02:30:39.083043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.7
Q114.5
median28
Q341.5
95-th percentile52.3
Maximum55
Range54
Interquartile range (IQR)27

Descriptive statistics

Standard deviation16.02082
Coefficient of variation (CV)0.57217214
Kurtosis-1.2
Mean28
Median Absolute Deviation (MAD)14
Skewness0
Sum1540
Variance256.66667
MonotonicityStrictly increasing
2023-12-13T02:30:39.228913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 1
 
1.6%
31 1
 
1.6%
32 1
 
1.6%
33 1
 
1.6%
34 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
Other values (45) 45
70.3%
(Missing) 9
 
14.1%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
55 1
1.6%
54 1
1.6%
53 1
1.6%
52 1
1.6%
51 1
1.6%
50 1
1.6%
49 1
1.6%
48 1
1.6%
47 1
1.6%
46 1
1.6%

시도명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
강원도
55 
<NA>
9 

Length

Max length4
Median length3
Mean length3.140625
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강원도 55
85.9%
<NA> 9
 
14.1%

Length

2023-12-13T02:30:39.363536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:30:39.469903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 55
85.9%
na 9
 
14.1%

시군명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
평창군
55 
<NA>
9 

Length

Max length4
Median length3
Mean length3.140625
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평창군 55
85.9%
<NA> 9
 
14.1%

Length

2023-12-13T02:30:39.575583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:30:39.674428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평창군 55
85.9%
na 9
 
14.1%

단지명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size644.0 B
평창농공단지
43 
평창방림농공단지
12 
<NA>
9 

Length

Max length8
Median length6
Mean length6.09375
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row평창농공단지
2nd row평창농공단지
3rd row평창방림농공단지
4th row평창방림농공단지
5th row평창방림농공단지

Common Values

ValueCountFrequency (%)
평창농공단지 43
67.2%
평창방림농공단지 12
 
18.8%
<NA> 9
 
14.1%

Length

2023-12-13T02:30:40.064731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:30:40.172479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평창농공단지 43
67.2%
평창방림농공단지 12
 
18.8%
na 9
 
14.1%

회사명
Text

MISSING 

Distinct52
Distinct (%)94.5%
Missing9
Missing (%)14.1%
Memory size644.0 B
2023-12-13T02:30:40.346241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length8.8363636
Min length3

Characters and Unicode

Total characters486
Distinct characters133
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49 ?
Unique (%)89.1%

Sample

1st row(주)금강아트엔지니어링
2nd row(주)다이닉스
3rd row(주)동강이엔씨
4th row(주)동강이엔씨
5th row(주)동남이엔씨
ValueCountFrequency (%)
주식회사 10
 
14.7%
주)동강이엔씨 2
 
2.9%
에스아이조명주식회사 2
 
2.9%
비알로비 2
 
2.9%
삼원엔지니어스(주 2
 
2.9%
거성개발 1
 
1.5%
합자회사청룡기협 1
 
1.5%
호성건설산업주식회사 1
 
1.5%
호성건설(주 1
 
1.5%
제2공장 1
 
1.5%
Other values (45) 45
66.2%
2023-12-13T02:30:40.725265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 42
 
8.6%
( 32
 
6.6%
) 32
 
6.6%
사 21
 
4.3%
이 17
 
3.5%
회 16
 
3.3%
식 14
 
2.9%
13
 
2.7%
스 12
 
2.5%
업 9
 
1.9%
Other values (123) 278
57.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 405
83.3%
Open Punctuation 32
 
6.6%
Close Punctuation 32
 
6.6%
Space Separator 13
 
2.7%
Uppercase Letter 2
 
0.4%
Decimal Number 1
 
0.2%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 42
 
10.4%
사 21
 
5.2%
이 17
 
4.2%
회 16
 
4.0%
식 14
 
3.5%
스 12
 
3.0%
업 9
 
2.2%
엔 9
 
2.2%
지 8
 
2.0%
강 7
 
1.7%
Other values (116) 250
61.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
M 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 405
83.3%
Common 79
 
16.3%
Latin 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 42
 
10.4%
사 21
 
5.2%
이 17
 
4.2%
회 16
 
4.0%
식 14
 
3.5%
스 12
 
3.0%
업 9
 
2.2%
엔 9
 
2.2%
지 8
 
2.0%
강 7
 
1.7%
Other values (116) 250
61.7%
Common
ValueCountFrequency (%)
( 32
40.5%
) 32
40.5%
13
16.5%
2 1
 
1.3%
& 1
 
1.3%
Latin
ValueCountFrequency (%)
S 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 405
83.3%
ASCII 81
 
16.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 42
 
10.4%
사 21
 
5.2%
이 17
 
4.2%
회 16
 
4.0%
식 14
 
3.5%
스 12
 
3.0%
업 9
 
2.2%
엔 9
 
2.2%
지 8
 
2.0%
강 7
 
1.7%
Other values (116) 250
61.7%
ASCII
ValueCountFrequency (%)
( 32
39.5%
) 32
39.5%
13
16.0%
2 1
 
1.2%
S 1
 
1.2%
& 1
 
1.2%
M 1
 
1.2%

대표자명
Text

MISSING 

Distinct46
Distinct (%)83.6%
Missing9
Missing (%)14.1%
Memory size644.0 B
2023-12-13T02:30:40.948152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.1454545
Min length3

Characters and Unicode

Total characters173
Distinct characters73
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)69.1%

Sample

1st row김진남
2nd row서호경
3rd row류일걸
4th row류일걸
5th row박주현
ValueCountFrequency (%)
이영리 3
 
5.4%
류일걸 2
 
3.6%
김진남 2
 
3.6%
박주현 2
 
3.6%
최락기 2
 
3.6%
윤영진 2
 
3.6%
배경미 2
 
3.6%
김상호 2
 
3.6%
백운철 1
 
1.8%
이상우 1
 
1.8%
Other values (37) 37
66.1%
2023-12-13T02:30:41.366414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 14
 
8.1%
이 10
 
5.8%
영 9
 
5.2%
진 8
 
4.6%
윤 5
 
2.9%
현 4
 
2.3%
미 4
 
2.3%
4
 
2.3%
성 4
 
2.3%
최 4
 
2.3%
Other values (63) 107
61.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168
97.1%
Space Separator 4
 
2.3%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 14
 
8.3%
이 10
 
6.0%
영 9
 
5.4%
진 8
 
4.8%
윤 5
 
3.0%
현 4
 
2.4%
미 4
 
2.4%
성 4
 
2.4%
최 4
 
2.4%
박 4
 
2.4%
Other values (61) 102
60.7%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 168
97.1%
Common 5
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 14
 
8.3%
이 10
 
6.0%
영 9
 
5.4%
진 8
 
4.8%
윤 5
 
3.0%
현 4
 
2.4%
미 4
 
2.4%
성 4
 
2.4%
최 4
 
2.4%
박 4
 
2.4%
Other values (61) 102
60.7%
Common
ValueCountFrequency (%)
4
80.0%
, 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168
97.1%
ASCII 5
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 14
 
8.3%
이 10
 
6.0%
영 9
 
5.4%
진 8
 
4.8%
윤 5
 
3.0%
현 4
 
2.4%
미 4
 
2.4%
성 4
 
2.4%
최 4
 
2.4%
박 4
 
2.4%
Other values (61) 102
60.7%
ASCII
ValueCountFrequency (%)
4
80.0%
, 1
 
20.0%

공장대표주소(도로명)
Text

MISSING 

Distinct35
Distinct (%)63.6%
Missing9
Missing (%)14.1%
Memory size644.0 B
2023-12-13T02:30:41.607789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length34
Mean length25.418182
Min length20

Characters and Unicode

Total characters1398
Distinct characters70
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

Unique25 ?
Unique (%)45.5%

Sample

1st row강원도 평창군 평창읍 농공단지길 40 (INNO WIZ)
2nd row강원도 평창군 평창읍 농공단지길 24-20 (J&SCO.)
3rd row강원도 평창군 방림면 방림리 611-16번지
4th row강원도 평창군 방림면 평창대로 84-43
5th row강원도 평창군 방림면 평창대로 84-7, 방림농공단지
ValueCountFrequency (%)
강원도 55
18.0%
평창군 55
18.0%
평창읍 44
14.4%
농공단지길 43
14.1%
방림면 12
 
3.9%
평창대로 11
 
3.6%
26 8
 
2.6%
24-12 6
 
2.0%
24-20 5
 
1.6%
inno 4
 
1.3%
Other values (38) 63
20.6%
2023-12-13T02:30:41.981336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
251
18.0%
평 110
 
7.9%
창 110
 
7.9%
강 56
 
4.0%
원 56
 
4.0%
2 56
 
4.0%
도 55
 
3.9%
군 55
 
3.9%
4 48
 
3.4%
지 47
 
3.4%
Other values (60) 554
39.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 817
58.4%
Space Separator 251
 
18.0%
Decimal Number 189
 
13.5%
Uppercase Letter 49
 
3.5%
Dash Punctuation 40
 
2.9%
Other Punctuation 18
 
1.3%
Open Punctuation 17
 
1.2%
Close Punctuation 17
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 110
13.5%
창 110
13.5%
강 56
 
6.9%
원 56
 
6.9%
도 55
 
6.7%
군 55
 
6.7%
지 47
 
5.8%
농 45
 
5.5%
공 45
 
5.5%
단 45
 
5.5%
Other values (34) 193
23.6%
Decimal Number
ValueCountFrequency (%)
2 56
29.6%
4 48
25.4%
1 21
 
11.1%
3 15
 
7.9%
8 14
 
7.4%
0 13
 
6.9%
6 10
 
5.3%
9 6
 
3.2%
7 3
 
1.6%
5 3
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
O 8
16.3%
I 8
16.3%
N 8
16.3%
C 7
14.3%
S 5
10.2%
Z 4
8.2%
W 4
8.2%
J 4
8.2%
M 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 9
50.0%
& 5
27.8%
. 4
22.2%
Space Separator
ValueCountFrequency (%)
251
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 40
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 817
58.4%
Common 532
38.1%
Latin 49
 
3.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 110
13.5%
창 110
13.5%
강 56
 
6.9%
원 56
 
6.9%
도 55
 
6.7%
군 55
 
6.7%
지 47
 
5.8%
농 45
 
5.5%
공 45
 
5.5%
단 45
 
5.5%
Other values (34) 193
23.6%
Common
ValueCountFrequency (%)
251
47.2%
2 56
 
10.5%
4 48
 
9.0%
- 40
 
7.5%
1 21
 
3.9%
( 17
 
3.2%
) 17
 
3.2%
3 15
 
2.8%
8 14
 
2.6%
0 13
 
2.4%
Other values (7) 40
 
7.5%
Latin
ValueCountFrequency (%)
O 8
16.3%
I 8
16.3%
N 8
16.3%
C 7
14.3%
S 5
10.2%
Z 4
8.2%
W 4
8.2%
J 4
8.2%
M 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 817
58.4%
ASCII 581
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
251
43.2%
2 56
 
9.6%
4 48
 
8.3%
- 40
 
6.9%
1 21
 
3.6%
( 17
 
2.9%
) 17
 
2.9%
3 15
 
2.6%
8 14
 
2.4%
0 13
 
2.2%
Other values (16) 89
 
15.3%
Hangul
ValueCountFrequency (%)
평 110
13.5%
창 110
13.5%
강 56
 
6.9%
원 56
 
6.9%
도 55
 
6.7%
군 55
 
6.7%
지 47
 
5.8%
농 45
 
5.5%
공 45
 
5.5%
단 45
 
5.5%
Other values (34) 193
23.6%

업종명
Text

MISSING 

Distinct48
Distinct (%)87.3%
Missing9
Missing (%)14.1%
Memory size644.0 B
2023-12-13T02:30:42.287145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length24
Mean length18.527273
Min length8

Characters and Unicode

Total characters1019
Distinct characters123
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)74.5%

Sample

1st row방송장비 제조업 외 4 종
2nd row방송장비 제조업
3rd row일반용 전기 조명장치 제조업 외 2 종
4th row일반용 전기 조명장치 제조업 외 4 종
5th row액체 펌프 제조업 외 12 종
ValueCountFrequency (%)
제조업 50
 
14.5%
외 41
 
11.9%
종 38
 
11.0%
및 21
 
6.1%
1 12
 
3.5%
전기 11
 
3.2%
2 8
 
2.3%
조명장치 7
 
2.0%
일반용 6
 
1.7%
기타 6
 
1.7%
Other values (86) 145
42.0%
2023-12-13T02:30:42.845604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
28.5%
제 69
 
6.8%
조 59
 
5.8%
업 56
 
5.5%
외 41
 
4.0%
종 38
 
3.7%
기 26
 
2.6%
장 21
 
2.1%
및 21
 
2.1%
전 19
 
1.9%
Other values (113) 379
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 674
66.1%
Space Separator 290
28.5%
Decimal Number 44
 
4.3%
Other Punctuation 11
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 69
 
10.2%
조 59
 
8.8%
업 56
 
8.3%
외 41
 
6.1%
종 38
 
5.6%
기 26
 
3.9%
장 21
 
3.1%
및 21
 
3.1%
전 19
 
2.8%
반 16
 
2.4%
Other values (102) 308
45.7%
Decimal Number
ValueCountFrequency (%)
1 18
40.9%
2 10
22.7%
3 4
 
9.1%
6 3
 
6.8%
5 3
 
6.8%
4 2
 
4.5%
0 2
 
4.5%
7 1
 
2.3%
8 1
 
2.3%
Space Separator
ValueCountFrequency (%)
290
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 674
66.1%
Common 345
33.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 69
 
10.2%
조 59
 
8.8%
업 56
 
8.3%
외 41
 
6.1%
종 38
 
5.6%
기 26
 
3.9%
장 21
 
3.1%
및 21
 
3.1%
전 19
 
2.8%
반 16
 
2.4%
Other values (102) 308
45.7%
Common
ValueCountFrequency (%)
290
84.1%
1 18
 
5.2%
, 11
 
3.2%
2 10
 
2.9%
3 4
 
1.2%
6 3
 
0.9%
5 3
 
0.9%
4 2
 
0.6%
0 2
 
0.6%
7 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 673
66.0%
ASCII 345
33.9%
Compat Jamo 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290
84.1%
1 18
 
5.2%
, 11
 
3.2%
2 10
 
2.9%
3 4
 
1.2%
6 3
 
0.9%
5 3
 
0.9%
4 2
 
0.6%
0 2
 
0.6%
7 1
 
0.3%
Hangul
ValueCountFrequency (%)
제 69
 
10.3%
조 59
 
8.8%
업 56
 
8.3%
외 41
 
6.1%
종 38
 
5.6%
기 26
 
3.9%
장 21
 
3.1%
및 21
 
3.1%
전 19
 
2.8%
반 16
 
2.4%
Other values (101) 307
45.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

전화번호
Text

MISSING 

Distinct41
Distinct (%)85.4%
Missing16
Missing (%)25.0%
Memory size644.0 B
2023-12-13T02:30:43.150342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.041667
Min length12

Characters and Unicode

Total characters578
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)72.9%

Sample

1st row033-333-9278
2nd row033-334-2261
3rd row033-332-9339
4th row033-334-5963
5th row033-332-5948
ValueCountFrequency (%)
033-332-3015 3
 
6.2%
033-332-5948 2
 
4.2%
033-333-8272 2
 
4.2%
033-332-9322 2
 
4.2%
033-333-8996 2
 
4.2%
033-334-5963 2
 
4.2%
033-655-1367 1
 
2.1%
033-333-9278 1
 
2.1%
033-332-0096 1
 
2.1%
033-336-3200 1
 
2.1%
Other values (31) 31
64.6%
2023-12-13T02:30:43.617678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 214
37.0%
- 96
16.6%
0 71
 
12.3%
2 39
 
6.7%
5 29
 
5.0%
9 28
 
4.8%
4 22
 
3.8%
6 22
 
3.8%
7 20
 
3.5%
8 19
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 482
83.4%
Dash Punctuation 96
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 214
44.4%
0 71
 
14.7%
2 39
 
8.1%
5 29
 
6.0%
9 28
 
5.8%
4 22
 
4.6%
6 22
 
4.6%
7 20
 
4.1%
8 19
 
3.9%
1 18
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 578
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 214
37.0%
- 96
16.6%
0 71
 
12.3%
2 39
 
6.7%
5 29
 
5.0%
9 28
 
4.8%
4 22
 
3.8%
6 22
 
3.8%
7 20
 
3.5%
8 19
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 578
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 214
37.0%
- 96
16.6%
0 71
 
12.3%
2 39
 
6.7%
5 29
 
5.0%
9 28
 
4.8%
4 22
 
3.8%
6 22
 
3.8%
7 20
 
3.5%
8 19
 
3.3%

팩스번호
Text

MISSING 

Distinct34
Distinct (%)91.9%
Missing27
Missing (%)42.2%
Memory size644.0 B
2023-12-13T02:30:43.877613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.189189
Min length12

Characters and Unicode

Total characters451
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)83.8%

Sample

1st row033-333-9279
2nd row033-334-2262
3rd row033-334-5964
4th row033-375-7017
5th row033-334-9956
ValueCountFrequency (%)
033-333-2300 2
 
5.4%
033-334-0016 2
 
5.4%
033-332-9822 2
 
5.4%
033-333-6616 1
 
2.7%
033-332-5454 1
 
2.7%
050-5116-3553 1
 
2.7%
0505-116-4730 1
 
2.7%
033-332-0097 1
 
2.7%
063-653-3401 1
 
2.7%
033-333-9101 1
 
2.7%
Other values (24) 24
64.9%
2023-12-13T02:30:44.351192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 158
35.0%
- 74
16.4%
0 64
14.2%
2 29
 
6.4%
1 22
 
4.9%
6 21
 
4.7%
4 18
 
4.0%
8 17
 
3.8%
9 16
 
3.5%
7 16
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 377
83.6%
Dash Punctuation 74
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 158
41.9%
0 64
17.0%
2 29
 
7.7%
1 22
 
5.8%
6 21
 
5.6%
4 18
 
4.8%
8 17
 
4.5%
9 16
 
4.2%
7 16
 
4.2%
5 16
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 451
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 158
35.0%
- 74
16.4%
0 64
14.2%
2 29
 
6.4%
1 22
 
4.9%
6 21
 
4.7%
4 18
 
4.0%
8 17
 
3.8%
9 16
 
3.5%
7 16
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 451
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 158
35.0%
- 74
16.4%
0 64
14.2%
2 29
 
6.4%
1 22
 
4.9%
6 21
 
4.7%
4 18
 
4.0%
8 17
 
3.8%
9 16
 
3.5%
7 16
 
3.5%

종업원수
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct19
Distinct (%)34.5%
Missing9
Missing (%)14.1%
Infinite0
Infinite (%)0.0%
Mean7.3090909
Minimum0
Maximum67
Zeros7
Zeros (%)10.9%
Negative0
Negative (%)0.0%
Memory size708.0 B
2023-12-13T02:30:44.518046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median5
Q37
95-th percentile24.1
Maximum67
Range67
Interquartile range (IQR)4

Descriptive statistics

Standard deviation10.270188
Coefficient of variation (CV)1.4051253
Kurtosis21.50008
Mean7.3090909
Median Absolute Deviation (MAD)2
Skewness4.1570878
Sum402
Variance105.47677
MonotonicityNot monotonic
2023-12-13T02:30:44.718565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
3 9
14.1%
5 8
12.5%
0 7
10.9%
6 6
9.4%
7 5
7.8%
4 3
 
4.7%
1 2
 
3.1%
8 2
 
3.1%
2 2
 
3.1%
11 2
 
3.1%
Other values (9) 9
14.1%
(Missing) 9
14.1%
ValueCountFrequency (%)
0 7
10.9%
1 2
 
3.1%
2 2
 
3.1%
3 9
14.1%
4 3
 
4.7%
5 8
12.5%
6 6
9.4%
7 5
7.8%
8 2
 
3.1%
9 1
 
1.6%
ValueCountFrequency (%)
67 1
1.6%
30 1
1.6%
29 1
1.6%
22 1
1.6%
16 1
1.6%
13 1
1.6%
12 1
1.6%
11 2
3.1%
10 1
1.6%
9 1
1.6%

데이터기준일자
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size644.0 B
2022-09-19
55 
<NA>
9 

Length

Max length10
Median length10
Mean length9.15625
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-19
2nd row2022-09-19
3rd row2022-09-19
4th row2022-09-19
5th row2022-09-19

Common Values

ValueCountFrequency (%)
2022-09-19 55
85.9%
<NA> 9
 
14.1%

Length

2023-12-13T02:30:44.918570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T02:30:45.058542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-19 55
85.9%
na 9
 
14.1%

Interactions

2023-12-13T02:30:38.328902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:38.172058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:38.415159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:30:38.245467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T02:30:45.168116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번단지명회사명대표자명공장대표주소(도로명)업종명전화번호팩스번호종업원수
순번1.0000.2990.9810.9240.0000.9350.8580.9300.134
단지명0.2991.0000.0000.6921.0000.6400.8441.0000.468
회사명0.9810.0001.0001.0000.0000.9500.9951.0000.973
대표자명0.9240.6921.0001.0000.7560.9590.9970.9930.669
공장대표주소(도로명)0.0001.0000.0000.7561.0000.9740.0000.9810.886
업종명0.9350.6400.9500.9590.9741.0000.9390.9740.770
전화번호0.8580.8440.9950.9970.0000.9391.0001.0000.715
팩스번호0.9301.0001.0000.9930.9810.9741.0001.0000.000
종업원수0.1340.4680.9730.6690.8860.7700.7150.0001.000
2023-12-13T02:30:45.325716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단지명시군명데이터기준일자시도명
단지명1.0001.0001.0001.000
시군명1.0001.0001.0001.000
데이터기준일자1.0001.0001.0001.000
시도명1.0001.0001.0001.000
2023-12-13T02:30:45.447495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번종업원수시도명시군명단지명데이터기준일자
순번1.000-0.2041.0001.0000.1651.000
종업원수-0.2041.0001.0001.0000.3231.000
시도명1.0001.0001.0001.0001.0001.000
시군명1.0001.0001.0001.0001.0001.000
단지명0.1650.3231.0001.0001.0001.000
데이터기준일자1.0001.0001.0001.0001.0001.000

Missing values

2023-12-13T02:30:38.547928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:30:38.715441image/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.
2023-12-13T02:30:38.882544image/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

순번시도명시군명단지명회사명대표자명공장대표주소(도로명)업종명전화번호팩스번호종업원수데이터기준일자
01강원도평창군평창농공단지(주)금강아트엔지니어링김진남강원도 평창군 평창읍 농공단지길 40 (INNO WIZ)방송장비 제조업 외 4 종033-333-9278033-333-9279122022-09-19
12강원도평창군평창농공단지(주)다이닉스서호경강원도 평창군 평창읍 농공단지길 24-20 (J&SCO.)방송장비 제조업033-334-2261033-334-226222022-09-19
23강원도평창군평창방림농공단지(주)동강이엔씨류일걸강원도 평창군 방림면 방림리 611-16번지일반용 전기 조명장치 제조업 외 2 종033-332-9339033-334-596462022-09-19
34강원도평창군평창방림농공단지(주)동강이엔씨류일걸강원도 평창군 방림면 평창대로 84-43일반용 전기 조명장치 제조업 외 4 종033-334-5963<NA>102022-09-19
45강원도평창군평창방림농공단지(주)동남이엔씨박주현강원도 평창군 방림면 평창대로 84-7, 방림농공단지액체 펌프 제조업 외 12 종033-332-5948033-375-701772022-09-19
56강원도평창군평창농공단지(주)바루디자인백은철강원도 평창군 평창읍 농공단지길 24-18놀이터용 장비 제조업 외 6 종033-334-9957033-334-995642022-09-19
67강원도평창군평창방림농공단지(주)서진파워텍김수용강원도 평창군 방림면 평창대로 84-23배전반 및 전기 자동제어반 제조업033-334-5962<NA>52022-09-19
78강원도평창군평창농공단지(주)스마트네트웍스이영수강원도 평창군 평창읍 농공단지길 24-12방송장비 제조업033-332-3122<NA>52022-09-19
89강원도평창군평창농공단지(주)씨앤씨엔텍백운철강원도 평창군 평창읍 농공단지길 24-20액체 여과기 제조업070-7706-2319031-8003-232282022-09-19
910강원도평창군평창농공단지(주)아람썬이상우강원도 평창군 평창읍 농공단지길 23-19 (평창읍)기타 직물제품 제조업<NA><NA>302022-09-19
순번시도명시군명단지명회사명대표자명공장대표주소(도로명)업종명전화번호팩스번호종업원수데이터기준일자
5455강원도평창군평창농공단지호성건설산업주식회사김진해강원도 평창군 평창읍 농공단지길 39구조용 금속 판제품 및 공작물 제조업 외 10 종033-333-8996033-333-899862022-09-19
55<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
56<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
57<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
58<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
59<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
60<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
61<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
62<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
63<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

순번시도명시군명단지명회사명대표자명공장대표주소(도로명)업종명전화번호팩스번호종업원수데이터기준일자# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9