Overview

Dataset statistics

Number of variables9
Number of observations68
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory75.9 B

Variable types

Numeric2
Categorical2
Text4
DateTime1

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
전화번호 has 2 (2.9%) missing valuesMissing
순번 has unique valuesUnique
회사명 has unique valuesUnique

Reproduction

Analysis started2024-01-09 21:25:55.597026
Analysis finished2024-01-09 21:25:56.604754
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.5
Minimum1
Maximum68
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-01-10T06:25:56.659844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.35
Q117.75
median34.5
Q351.25
95-th percentile64.65
Maximum68
Range67
Interquartile range (IQR)33.5

Descriptive statistics

Standard deviation19.77372
Coefficient of variation (CV)0.5731513
Kurtosis-1.2
Mean34.5
Median Absolute Deviation (MAD)17
Skewness0
Sum2346
Variance391
MonotonicityStrictly increasing
2024-01-10T06:25:56.764974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
45 1
 
1.5%
51 1
 
1.5%
50 1
 
1.5%
49 1
 
1.5%
48 1
 
1.5%
47 1
 
1.5%
46 1
 
1.5%
44 1
 
1.5%
36 1
 
1.5%
Other values (58) 58
85.3%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
68 1
1.5%
67 1
1.5%
66 1
1.5%
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%

산업단지명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.4%
Missing0
Missing (%)0.0%
Memory size676.0 B
추부농공단지
28 
금성농공단지
22 
복수농공단지
14 
인삼약초특화농공단지
금산일반산업단지
 
1

Length

Max length10
Median length6
Mean length6.2058824
Min length6

Unique

Unique1 ?
Unique (%)1.5%

Sample

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

Common Values

ValueCountFrequency (%)
추부농공단지 28
41.2%
금성농공단지 22
32.4%
복수농공단지 14
20.6%
인삼약초특화농공단지 3
 
4.4%
금산일반산업단지 1
 
1.5%

Length

2024-01-10T06:25:56.875172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T06:25:56.966986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
추부농공단지 28
41.2%
금성농공단지 22
32.4%
복수농공단지 14
20.6%
인삼약초특화농공단지 3
 
4.4%
금산일반산업단지 1
 
1.5%

회사명
Text

UNIQUE 

Distinct68
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-01-10T06:25:57.145642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.0882353
Min length3

Characters and Unicode

Total characters414
Distinct characters144
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

Unique68 ?
Unique (%)100.0%

Sample

1st row한국타이어㈜ 금산공장
2nd row태형산업㈜
3rd row한국생약영농조합법인
4th row㈜한영계기
5th row㈜부광케미컬
ValueCountFrequency (%)
농업회사법인 2
 
2.7%
주)미래기전 1
 
1.3%
탑미트㈜ 1
 
1.3%
주)대덕바이오 1
 
1.3%
주)데버그린 1
 
1.3%
주)한밭 1
 
1.3%
㈜올앤원솔루션 1
 
1.3%
태형산업㈜ 1
 
1.3%
주)하나케미칼 1
 
1.3%
1
 
1.3%
Other values (64) 64
85.3%
2024-01-10T06:25:57.433696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
7.0%
25
 
6.0%
) 19
 
4.6%
17
 
4.1%
13
 
3.1%
12
 
2.9%
9
 
2.2%
8
 
1.9%
7
 
1.7%
7
 
1.7%
Other values (134) 268
64.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 343
82.9%
Other Symbol 29
 
7.0%
Close Punctuation 19
 
4.6%
Uppercase Letter 9
 
2.2%
Space Separator 7
 
1.7%
Open Punctuation 6
 
1.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
25
 
7.3%
17
 
5.0%
13
 
3.8%
12
 
3.5%
9
 
2.6%
8
 
2.3%
7
 
2.0%
7
 
2.0%
6
 
1.7%
6
 
1.7%
Other values (121) 233
67.9%
Uppercase Letter
ValueCountFrequency (%)
D 2
22.2%
S 1
11.1%
C 1
11.1%
E 1
11.1%
P 1
11.1%
J 1
11.1%
B 1
11.1%
I 1
11.1%
Other Symbol
ValueCountFrequency (%)
29
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 372
89.9%
Common 33
 
8.0%
Latin 9
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
29
 
7.8%
25
 
6.7%
17
 
4.6%
13
 
3.5%
12
 
3.2%
9
 
2.4%
8
 
2.2%
7
 
1.9%
7
 
1.9%
6
 
1.6%
Other values (122) 239
64.2%
Latin
ValueCountFrequency (%)
D 2
22.2%
S 1
11.1%
C 1
11.1%
E 1
11.1%
P 1
11.1%
J 1
11.1%
B 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 343
82.9%
ASCII 42
 
10.1%
None 29
 
7.0%

Most frequent character per block

None
ValueCountFrequency (%)
29
100.0%
Hangul
ValueCountFrequency (%)
25
 
7.3%
17
 
5.0%
13
 
3.8%
12
 
3.5%
9
 
2.6%
8
 
2.3%
7
 
2.0%
7
 
2.0%
6
 
1.7%
6
 
1.7%
Other values (121) 233
67.9%
ASCII
ValueCountFrequency (%)
) 19
45.2%
7
 
16.7%
( 6
 
14.3%
D 2
 
4.8%
S 1
 
2.4%
C 1
 
2.4%
E 1
 
2.4%
P 1
 
2.4%
J 1
 
2.4%
B 1
 
2.4%
Other values (2) 2
 
4.8%
Distinct66
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size676.0 B
Minimum1988-08-15 00:00:00
Maximum2019-01-28 00:00:00
2024-01-10T06:25:57.541776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T06:25:57.645128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

전화번호
Text

MISSING 

Distinct65
Distinct (%)98.5%
Missing2
Missing (%)2.9%
Memory size676.0 B
2024-01-10T06:25:57.837069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.984848
Min length9

Characters and Unicode

Total characters791
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

Unique64 ?
Unique (%)97.0%

Sample

1st row041-750-5101
2nd row041-754-6672
3rd row041-751-4400
4th row041-751-1051
5th row041-751-3205
ValueCountFrequency (%)
041-751-4511 2
 
3.0%
041-751-0893 1
 
1.5%
041-750-5101 1
 
1.5%
041-754-7041 1
 
1.5%
041-754-0501 1
 
1.5%
041-751-6262 1
 
1.5%
041-752-1022 1
 
1.5%
041-751-1470 1
 
1.5%
041-751-9599 1
 
1.5%
041-754-0704 1
 
1.5%
Other values (55) 55
83.3%
2024-01-10T06:25:58.360578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 131
16.6%
1 117
14.8%
0 114
14.4%
4 108
13.7%
7 95
12.0%
5 85
10.7%
2 42
 
5.3%
3 30
 
3.8%
9 25
 
3.2%
8 24
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 660
83.4%
Dash Punctuation 131
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 117
17.7%
0 114
17.3%
4 108
16.4%
7 95
14.4%
5 85
12.9%
2 42
 
6.4%
3 30
 
4.5%
9 25
 
3.8%
8 24
 
3.6%
6 20
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 131
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 791
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 131
16.6%
1 117
14.8%
0 114
14.4%
4 108
13.7%
7 95
12.0%
5 85
10.7%
2 42
 
5.3%
3 30
 
3.8%
9 25
 
3.2%
8 24
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 791
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 131
16.6%
1 117
14.8%
0 114
14.4%
4 108
13.7%
7 95
12.0%
5 85
10.7%
2 42
 
5.3%
3 30
 
3.8%
9 25
 
3.2%
8 24
 
3.0%

종업원수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)51.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60.867647
Minimum1
Maximum2978
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size744.0 B
2024-01-10T06:25:58.468221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q17
median14.5
Q324
95-th percentile40.3
Maximum2978
Range2977
Interquartile range (IQR)17

Descriptive statistics

Standard deviation359.35124
Coefficient of variation (CV)5.9038135
Kurtosis67.749377
Mean60.867647
Median Absolute Deviation (MAD)8
Skewness8.223953
Sum4139
Variance129133.31
MonotonicityNot monotonic
2024-01-10T06:25:58.568745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
13 6
 
8.8%
2 5
 
7.4%
9 4
 
5.9%
22 4
 
5.9%
7 3
 
4.4%
24 3
 
4.4%
3 3
 
4.4%
39 2
 
2.9%
5 2
 
2.9%
18 2
 
2.9%
Other values (25) 34
50.0%
ValueCountFrequency (%)
1 2
 
2.9%
2 5
7.4%
3 3
4.4%
4 1
 
1.5%
5 2
 
2.9%
6 2
 
2.9%
7 3
4.4%
8 1
 
1.5%
9 4
5.9%
10 1
 
1.5%
ValueCountFrequency (%)
2978 1
1.5%
102 1
1.5%
46 1
1.5%
41 1
1.5%
39 2
2.9%
36 1
1.5%
34 2
2.9%
30 1
1.5%
28 1
1.5%
27 1
1.5%
Distinct67
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size676.0 B
2024-01-10T06:25:58.763339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/