Overview

Dataset statistics

Number of variables5
Number of observations41
Missing cells4
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.7 KiB
Average record size in memory43.2 B

Variable types

Categorical2
Text3

Dataset

Description충청남도 논산시 창업보육센터입주기업현황에 대한 데이터로 사업장명, 기업명, 대표자명, 보육실, 주요품목, 분야 정보를 제공하고있습니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=375&beforeMenuCd=DOM_000000201001001000&publicdatapk=15067170

Alerts

주요품목 has 4 (9.8%) missing valuesMissing
보육실 has unique valuesUnique

Reproduction

Analysis started2024-01-09 20:32:27.186439
Analysis finished2024-01-09 20:32:27.584439
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Categorical

Distinct2
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size460.0 B
건양대학교 창업보육센터 교내사업장
27 
건양대학교 창업보육센터 교외확장사업장
14 

Length

Max length20
Median length18
Mean length18.682927
Min length18

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건양대학교 창업보육센터 교내사업장
2nd row건양대학교 창업보육센터 교내사업장
3rd row건양대학교 창업보육센터 교내사업장
4th row건양대학교 창업보육센터 교내사업장
5th row건양대학교 창업보육센터 교내사업장

Common Values

ValueCountFrequency (%)
건양대학교 창업보육센터 교내사업장 27
65.9%
건양대학교 창업보육센터 교외확장사업장 14
34.1%

Length

2024-01-10T05:32:27.642836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:32:27.741393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건양대학교 41
33.3%
창업보육센터 41
33.3%
교내사업장 27
22.0%
교외확장사업장 14
 
11.4%

기업명
Text

Distinct35
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
2024-01-10T05:32:27.911391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.5121951
Min length2

Characters and Unicode

Total characters226
Distinct characters118
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)80.5%

Sample

1st row홍스팜
2nd row농업법인 쌀집아줌마
3rd row오이나라 피클공주
4th row공실
5th rowCOMIX
ValueCountFrequency (%)
예비창업자 6
 
13.6%
공실 2
 
4.5%
농업회사법인 1
 
2.3%
하나코젠 1
 
2.3%
자연애식품 1
 
2.3%
스타에너지 1
 
2.3%
㈜코코미 1
 
2.3%
다함 1
 
2.3%
청담폐백 1
 
2.3%
에이디클린 1
 
2.3%
Other values (28) 28
63.6%
2024-01-10T05:32:28.224964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 10
 
4.4%
스 9
 
4.0%
업 9
 
4.0%
에 7
 
3.1%
자 7
 
3.1%
비 6
 
2.7%
예 6
 
2.7%
창 6
 
2.7%
코 5
 
2.2%
오 4
 
1.8%
Other values (108) 157
69.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210
92.9%
Uppercase Letter 7
 
3.1%
Other Symbol 4
 
1.8%
Space Separator 3
 
1.3%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 10
 
4.8%
스 9
 
4.3%
업 9
 
4.3%
에 7
 
3.3%
자 7
 
3.3%
비 6
 
2.9%
예 6
 
2.9%
창 6
 
2.9%
코 5
 
2.4%
오 4
 
1.9%
Other values (97) 141
67.1%
Uppercase Letter
ValueCountFrequency (%)
H 1
14.3%
N 1
14.3%
C 1
14.3%
O 1
14.3%
M 1
14.3%
I 1
14.3%
X 1
14.3%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 214
94.7%
Latin 7
 
3.1%
Common 5
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 10
 
4.7%
스 9
 
4.2%
업 9
 
4.2%
에 7
 
3.3%
자 7
 
3.3%
비 6
 
2.8%
예 6
 
2.8%
창 6
 
2.8%
코 5
 
2.3%
오 4
 
1.9%
Other values (98) 145
67.8%
Latin
ValueCountFrequency (%)
H 1
14.3%
N 1
14.3%
C 1
14.3%
O 1
14.3%
M 1
14.3%
I 1
14.3%
X 1
14.3%
Common
ValueCountFrequency (%)
3
60.0%
( 1
 
20.0%
) 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210
92.9%
ASCII 12
 
5.3%
None 4
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 10
 
4.8%
스 9
 
4.3%
업 9
 
4.3%
에 7
 
3.3%
자 7
 
3.3%
비 6
 
2.9%
예 6
 
2.9%
창 6
 
2.9%
코 5
 
2.4%
오 4
 
1.9%
Other values (97) 141
67.1%
None
ValueCountFrequency (%)
㈜ 4
100.0%
ASCII
ValueCountFrequency (%)
3
25.0%
( 1
 
8.3%
H 1
 
8.3%
N 1
 
8.3%
C 1
 
8.3%
O 1
 
8.3%
M 1
 
8.3%
I 1
 
8.3%
X 1
 
8.3%
) 1
 
8.3%

보육실
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2024-01-10T05:32:28.426664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length3
Mean length4.3658537
Min length2

Characters and Unicode

Total characters179
Distinct characters21
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)100.0%

Sample

1st rowB103/104
2nd rowB105
3rd rowB106
4th rowB107
5th rowB108
ValueCountFrequency (%)
d동 5
 
9.3%
a동 5
 
9.3%
h동 2
 
3.7%
1층 2
 
3.7%
201호 2
 
3.7%
b103/104 1
 
1.9%
203/205호 1
 
1.9%
312 1
 
1.9%
313 1
 
1.9%
335 1
 
1.9%
Other values (33) 33
61.1%
2024-01-10T05:32:28.734120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 30
16.8%
0 27
15.1%
2 23
12.8%
3 18
10.1%
동 14
7.8%
13
7.3%
호 11
 
6.1%
4 7
 
3.9%
A 5
 
2.8%
D 5
 
2.8%
Other values (11) 26
14.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 118
65.9%
Other Letter 27
 
15.1%
Uppercase Letter 19
 
10.6%
Space Separator 13
 
7.3%
Other Punctuation 2
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 30
25.4%
0 27
22.9%
2 23
19.5%
3 18
15.3%
4 7
 
5.9%
5 5
 
4.2%
8 4
 
3.4%
7 2
 
1.7%
9 1
 
0.8%
6 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
A 5
26.3%
D 5
26.3%
B 5
26.3%
H 2
 
10.5%
I 1
 
5.3%
N 1
 
5.3%
Other Letter
ValueCountFrequency (%)
동 14
51.9%
호 11
40.7%
층 2
 
7.4%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 133
74.3%
Hangul 27
 
15.1%
Latin 19
 
10.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 30
22.6%
0 27
20.3%
2 23
17.3%
3 18
13.5%
13
9.8%
4 7
 
5.3%
5 5
 
3.8%
8 4
 
3.0%
7 2
 
1.5%
/ 2
 
1.5%
Other values (2) 2
 
1.5%
Latin
ValueCountFrequency (%)
A 5
26.3%
D 5
26.3%
B 5
26.3%
H 2
 
10.5%
I 1
 
5.3%
N 1
 
5.3%
Hangul
ValueCountFrequency (%)
동 14
51.9%
호 11
40.7%
층 2
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152
84.9%
Hangul 27
 
15.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 30
19.7%
0 27
17.8%
2 23
15.1%
3 18
11.8%
13
8.6%
4 7
 
4.6%
A 5
 
3.3%
D 5
 
3.3%
B 5
 
3.3%
5 5
 
3.3%
Other values (8) 14
9.2%
Hangul
ValueCountFrequency (%)
동 14
51.9%
호 11
40.7%
층 2
 
7.4%

주요품목
Text

MISSING 

Distinct33
Distinct (%)89.2%
Missing4
Missing (%)9.8%
Memory size460.0 B
2024-01-10T05:32:28.936175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.3783784
Min length2

Characters and Unicode

Total characters199
Distinct characters87
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
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 row식품제조/가공
2nd row지역쌀가공
3rd row오이피클, 장아찌
4th row농업용기계
5th row버섯가공식품
ValueCountFrequency (%)
제조 5
 
10.4%
식품제조 4
 
8.3%
식품제조/가공 2
 
4.2%
폐백제조 1
 
2.1%
홍삼제조 1
 
2.1%
연구개발 1
 
2.1%
신재생에너지 1
 
2.1%
기계 1
 
2.1%
편강제조 1
 
2.1%
미생물제제 1
 
2.1%
Other values (30) 30
62.5%
2024-01-10T05:32:29.268287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
제 20
 
10.1%
조 17
 
8.5%
11
 
5.5%
품 11
 
5.5%
식 10
 
5.0%
기 6
 
3.0%
용 4
 
2.0%
업 4
 
2.0%
삼 4
 
2.0%
홍 4
 
2.0%
Other values (77) 108
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 180
90.5%
Space Separator 11
 
5.5%
Other Punctuation 6
 
3.0%
Lowercase Letter 2
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
제 20
 
11.1%
조 17
 
9.4%
품 11
 
6.1%
식 10
 
5.6%
기 6
 
3.3%
용 4
 
2.2%
업 4
 
2.2%
삼 4
 
2.2%
홍 4
 
2.2%
공 4
 
2.2%
Other values (72) 96
53.3%
Other Punctuation
ValueCountFrequency (%)
, 3
50.0%
/ 3
50.0%
Lowercase Letter
ValueCountFrequency (%)
i 1
50.0%
t 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 180
90.5%
Common 17
 
8.5%
Latin 2
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
제 20
 
11.1%
조 17
 
9.4%
품 11
 
6.1%
식 10
 
5.6%
기 6
 
3.3%
용 4
 
2.2%
업 4
 
2.2%
삼 4
 
2.2%
홍 4
 
2.2%
공 4
 
2.2%
Other values (72) 96
53.3%
Common
ValueCountFrequency (%)
11
64.7%
, 3
 
17.6%
/ 3
 
17.6%
Latin
ValueCountFrequency (%)
i 1
50.0%
t 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 180
90.5%
ASCII 19
 
9.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
제 20
 
11.1%
조 17
 
9.4%
품 11
 
6.1%
식 10
 
5.6%
기 6
 
3.3%
용 4
 
2.2%
업 4
 
2.2%
삼 4
 
2.2%
홍 4
 
2.2%
공 4
 
2.2%
Other values (72) 96
53.3%
ASCII
ValueCountFrequency (%)
11
57.9%
, 3
 
15.8%
/ 3
 
15.8%
i 1
 
5.3%
t 1
 
5.3%

분야
Categorical

Distinct10
Distinct (%)24.4%
Missing0
Missing (%)0.0%
Memory size460.0 B
제조
20 
식음료
8 
<NA>
3 
바이오
3 
교육
 
2
Other values (5)
5 

Length

Max length7
Median length2
Mean length2.6585366
Min length2

Unique

Unique5 ?
Unique (%)12.2%

Sample

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

Common Values

ValueCountFrequency (%)
제조 20
48.8%
식음료 8
 
19.5%
<NA> 3
 
7.3%
바이오 3
 
7.3%
교육 2
 
4.9%
IT 1
 
2.4%
1차 1
 
2.4%
연구,개발 1
 
2.4%
서비스, 연구 1
 
2.4%
연구개발 1
 
2.4%

Length

2024-01-10T05:32:29.393018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T05:32:29.504638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조 20
47.6%
식음료 8
 
19.0%
na 3
 
7.1%
바이오 3
 
7.1%
교육 2
 
4.8%
it 1
 
2.4%
1차 1
 
2.4%
연구,개발 1
 
2.4%
서비스 1
 
2.4%
연구 1
 
2.4%

Correlations

2024-01-10T05:32:29.607078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명기업명보육실주요품목분야
사업장명1.0000.4611.0000.4120.395
기업명0.4611.0001.0000.9870.990
보육실1.0001.0001.0001.0001.000
주요품목0.4120.9871.0001.0001.000
분야0.3950.9901.0001.0001.000
2024-01-10T05:32:29.700639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분야사업장명
분야1.0000.347
사업장명0.3471.000
2024-01-10T05:32:29.774135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명분야
사업장명1.0000.347
분야0.3471.000

Missing values

2024-01-10T05:32:27.479875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T05:32:27.554557image/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

사업장명기업명보육실주요품목분야
0건양대학교 창업보육센터 교내사업장홍스팜B103/104식품제조/가공제조
1건양대학교 창업보육센터 교내사업장농업법인 쌀집아줌마B105지역쌀가공제조
2건양대학교 창업보육센터 교내사업장오이나라 피클공주B106오이피클, 장아찌식음료
3건양대학교 창업보육센터 교내사업장공실B107<NA><NA>
4건양대학교 창업보육센터 교내사업장COMIXB108농업용기계제조
5건양대학교 창업보육센터 교내사업장버섯돌이네104버섯가공식품제조
6건양대학교 창업보육센터 교내사업장한솔102화장품 용기제조
7건양대학교 창업보육센터 교내사업장더드론코리아103드론교육교육
8건양대학교 창업보육센터 교내사업장파낙스바이오112식품연구제조
9건양대학교 창업보육센터 교내사업장공실114<NA><NA>
사업장명기업명보육실주요품목분야
31건양대학교 창업보육센터 교외확장사업장다함D동 202호도자기제조
32건양대학교 창업보육센터 교외확장사업장㈜코코미A동 301호너트바 제조식음료
33건양대학교 창업보육센터 교외확장사업장예비창업자A동 101호<NA><NA>
34건양대학교 창업보육센터 교외확장사업장스타에너지D동 1층태양광연구개발
35건양대학교 창업보육센터 교외확장사업장예비창업자A동 304호홍삼식음료
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