Overview

Dataset statistics

Number of variables9
Number of observations71
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory75.9 B

Variable types

Numeric2
Categorical1
Text4
DateTime2

Dataset

Description금산군 농공단지 내 입주업체현황(기업명, 주소, 전화번호, 공장등록일시 등)에 대한 내역입니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=396&beforeMenuCd=DOM_000000201001001000&publicdatapk=15028982

Alerts

데이터기준일자 has constant value ""Constant
순번 is highly overall correlated with 산업단지명High correlation
종업원수 is highly overall correlated with 산업단지명High correlation
산업단지명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
회사명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:25:45.035983
Analysis finished2024-01-09 21:25:46.080888
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36
Minimum1
Maximum71
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-01-10T06:25:46.138522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.5
Q118.5
median36
Q353.5
95-th percentile67.5
Maximum71
Range70
Interquartile range (IQR)35

Descriptive statistics

Standard deviation20.639767
Coefficient of variation (CV)0.57332687
Kurtosis-1.2
Mean36
Median Absolute Deviation (MAD)18
Skewness0
Sum2556
Variance426
MonotonicityStrictly increasing
2024-01-10T06:25:46.247249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
2 1
 
1.4%
53 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
46 1
 
1.4%
Other values (61) 61
85.9%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
71 1
1.4%
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%

산업단지명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
추부농공단지
28 
금성농공단지
22 
복수농공단지
14 
인삼약초특화농공단지
금산일반산업단지
 
1

Length

Max length10
Median length6
Mean length6.3661972
Min length6

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row금산일반산업단지
2nd row금성농공단지
3rd row금성농공단지
4th row금성농공단지
5th row금성농공단지

Common Values

ValueCountFrequency (%)
추부농공단지 28
39.4%
금성농공단지 22
31.0%
복수농공단지 14
19.7%
인삼약초특화농공단지 6
 
8.5%
금산일반산업단지 1
 
1.4%

Length

2024-01-10T06:25:46.389237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:25:46.508866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
추부농공단지 28
39.4%
금성농공단지 22
31.0%
복수농공단지 14
19.7%
인삼약초특화농공단지 6
 
8.5%
금산일반산업단지 1
 
1.4%

회사명
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-01-10T06:25:46.743507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.0985915
Min length3

Characters and Unicode

Total characters433
Distinct characters147
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)100.0%

Sample

1st row한국타이어㈜ 금산공장
2nd row태형산업㈜
3rd row한국생약영농조합법인
4th row㈜한영계기
5th row㈜부광케미컬
ValueCountFrequency (%)
농업회사법인 2
 
2.6%
한국타이어㈜ 1
 
1.3%
js산업 1
 
1.3%
주)미래기전 1
 
1.3%
주)더드림솔루션 1
 
1.3%
주)에스코알티에스 1
 
1.3%
진테크 1
 
1.3%
c 1
 
1.3%
d 1
 
1.3%
주)b 1
 
1.3%
Other values (67) 67
85.9%
2024-01-10T06:25:47.058346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33
 
7.6%
25
 
5.8%
) 19
 
4.4%
18
 
4.2%
16
 
3.7%
12
 
2.8%
9
 
2.1%
8
 
1.8%
8
 
1.8%
7
 
1.6%
Other values (137) 278
64.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 358
82.7%
Other Symbol 33
 
7.6%
Close Punctuation 19
 
4.4%
Uppercase Letter 9
 
2.1%
Space Separator 7
 
1.6%
Open Punctuation 6
 
1.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
7.0%
18
 
5.0%
16
 
4.5%
12
 
3.4%
9
 
2.5%
8
 
2.2%
8
 
2.2%
7
 
2.0%
7
 
2.0%
7
 
2.0%
Other values (124) 241
67.3%
Uppercase Letter
ValueCountFrequency (%)
D 2
22.2%
J 1
11.1%
C 1
11.1%
S 1
11.1%
B 1
11.1%
E 1
11.1%
P 1
11.1%
I 1
11.1%
Other Symbol
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 391
90.3%
Common 33
 
7.6%
Latin 9
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
33
 
8.4%
25
 
6.4%
18
 
4.6%
16
 
4.1%
12
 
3.1%
9
 
2.3%
8
 
2.0%
8
 
2.0%
7
 
1.8%
7
 
1.8%
Other values (125) 248
63.4%
Latin
ValueCountFrequency (%)
D 2
22.2%
J 1
11.1%
C 1
11.1%
S 1
11.1%
B 1
11.1%
E 1
11.1%
P 1
11.1%
I 1
11.1%
Common
ValueCountFrequency (%)
) 19
57.6%
7
 
21.2%
( 6
 
18.2%
& 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 358
82.7%
ASCII 42
 
9.7%
None 33
 
7.6%

Most frequent character per block

None
ValueCountFrequency (%)
33
100.0%
Hangul
ValueCountFrequency (%)
25
 
7.0%
18
 
5.0%
16
 
4.5%
12
 
3.4%
9
 
2.5%
8
 
2.2%
8
 
2.2%
7
 
2.0%
7
 
2.0%
7
 
2.0%
Other values (124) 241
67.3%
ASCII
ValueCountFrequency (%)
) 19
45.2%
7
 
16.7%
( 6
 
14.3%
D 2
 
4.8%
J 1
 
2.4%
C 1
 
2.4%
S 1
 
2.4%
B 1
 
2.4%
E 1
 
2.4%
P 1
 
2.4%
Other values (2) 2
 
4.8%
Distinct68
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size700.0 B
Minimum1988-08-15 00:00:00
Maximum2019-09-16 00:00:00
2024-01-10T06:25:47.168606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:25:47.303235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-01-10T06:25:47.533948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.943662
Min length9

Characters and Unicode

Total characters848
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

Unique71 ?
Unique (%)100.0%

Sample

1st row041-750-5101
2nd row041-754-6672
3rd row041-751-4400
4th row041-751-1051
5th row041-751-3205
ValueCountFrequency (%)
041-750-5101 1
 
1.4%
041-751-4479 1
 
1.4%
041-751-9199 1
 
1.4%
041-752-0399 1
 
1.4%
041-751-4803 1
 
1.4%
041-754-0501 1
 
1.4%
041-751-6262 1
 
1.4%
041-752-1022 1
 
1.4%
041-751-9599 1
 
1.4%
041-753-5790 1
 
1.4%
Other values (61) 61
85.9%
2024-01-10T06:25:47.848832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 140
16.5%
0 126
14.9%
1 118
13.9%
4 113
13.3%
7 101
11.9%
5 93
11.0%
2 48
 
5.7%
3 32
 
3.8%
8 30
 
3.5%
9 27
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 708
83.5%
Dash Punctuation 140
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 126
17.8%
1 118
16.7%
4 113
16.0%
7 101
14.3%
5 93
13.1%
2 48
 
6.8%
3 32
 
4.5%
8 30
 
4.2%
9 27
 
3.8%
6 20
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 848
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 140
16.5%
0 126
14.9%
1 118
13.9%
4 113
13.3%
7 101
11.9%
5 93
11.0%
2 48
 
5.7%
3 32
 
3.8%
8 30
 
3.5%
9 27
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 848
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 140
16.5%
0 126
14.9%
1 118
13.9%
4 113
13.3%
7 101
11.9%
5 93
11.0%
2 48
 
5.7%
3 32
 
3.8%
8 30
 
3.5%
9 27
 
3.2%

종업원수
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)54.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.366197
Minimum1
Maximum2978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2024-01-10T06:25:47.967665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18.5
median16
Q324.5
95-th percentile47.5
Maximum2978
Range2977
Interquartile range (IQR)16

Descriptive statistics

Standard deviation351.5789
Coefficient of variation (CV)5.8241021
Kurtosis70.686112
Mean60.366197
Median Absolute Deviation (MAD)8
Skewness8.3988298
Sum4286
Variance123607.72
MonotonicityNot monotonic
2024-01-10T06:25:48.098037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
13 6
 
8.5%
9 4
 
5.6%
2 4
 
5.6%
7 3
 
4.2%
18 3
 
4.2%
3 3
 
4.2%
24 3
 
4.2%
10 2
 
2.8%
16 2
 
2.8%
35 2
 
2.8%
Other values (29) 39
54.9%
ValueCountFrequency (%)
1 2
2.8%
2 4
5.6%
3 3
4.2%
4 2
2.8%
5 1
 
1.4%
6 2
2.8%
7 3
4.2%
8 1
 
1.4%
9 4
5.6%
10 2
2.8%
ValueCountFrequency (%)
2978 1
1.4%
102 1
1.4%
66 1
1.4%
49 1
1.4%
46 1
1.4%
41 1
1.4%
39 1
1.4%
36 1
1.4%
35 2
2.8%
34 1
1.4%
Distinct70
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
2024-01-10T06:25:48.313169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/