Overview

Dataset statistics

Number of variables6
Number of observations343
Missing cells13
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.5 KiB
Average record size in memory49.4 B

Variable types

Numeric1
Text3
Categorical1
DateTime1

Dataset

Description충청남도 식육포장처리업 정보 현황 데이터로 사업장명, 소재지, 대표자명, 영업상태, 허가일자 등의 정보를 제공합니다.
Author충청남도
URLhttps://www.data.go.kr/data/15092690/fileData.do

Alerts

영업상태 has constant value ""Constant
소재지 has 10 (2.9%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:49:44.758364
Analysis finished2024-03-14 08:49:46.260043
Duration1.5 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct343
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172
Minimum1
Maximum343
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-14T17:49:46.391152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.1
Q186.5
median172
Q3257.5
95-th percentile325.9
Maximum343
Range342
Interquartile range (IQR)171

Descriptive statistics

Standard deviation99.159804
Coefficient of variation (CV)0.57651049
Kurtosis-1.2
Mean172
Median Absolute Deviation (MAD)86
Skewness0
Sum58996
Variance9832.6667
MonotonicityStrictly increasing
2024-03-14T17:49:46.651474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
227 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
228 1
 
0.3%
Other values (333) 333
97.1%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
343 1
0.3%
342 1
0.3%
341 1
0.3%
340 1
0.3%
339 1
0.3%
338 1
0.3%
337 1
0.3%
336 1
0.3%
335 1
0.3%
334 1
0.3%

사업장명
Text

Distinct339
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-03-14T17:49:47.609728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length17
Mean length9.0233236
Min length2

Characters and Unicode

Total characters3095
Distinct characters296
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique335 ?
Unique (%)97.7%

Sample

1st row천안남영축산
2nd row새롬에프에스(주)
3rd row단비에프에스
4th rowMCR푸드
5th row미소에프앤에스 주식회사
ValueCountFrequency (%)
주식회사 71
 
13.5%
농업회사법인 40
 
7.6%
하나로마트 6
 
1.1%
2공장 3
 
0.6%
제2공장 2
 
0.4%
주)농업회사법인 2
 
0.4%
돈우 2
 
0.4%
육가공센터 2
 
0.4%
주)다내축산 2
 
0.4%
1공장 2
 
0.4%
Other values (376) 393
74.9%
2024-03-14T17:49:48.809679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
182
 
5.9%
주 179
 
5.8%
사 153
 
4.9%
회 150
 
4.8%
식 114
 
3.7%
( 101
 
3.3%
) 100
 
3.2%
농 99
 
3.2%
인 80
 
2.6%
산 78
 
2.5%
Other values (286) 1859
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2674
86.4%
Space Separator 182
 
5.9%
Open Punctuation 101
 
3.3%
Close Punctuation 100
 
3.2%
Decimal Number 18
 
0.6%
Uppercase Letter 10
 
0.3%
Lowercase Letter 7
 
0.2%
Other Punctuation 2
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 179
 
6.7%
사 153
 
5.7%
회 150
 
5.6%
식 114
 
4.3%
농 99
 
3.7%
인 80
 
3.0%
산 78
 
2.9%
업 77
 
2.9%
법 76
 
2.8%
드 67
 
2.5%
Other values (264) 1601
59.9%
Uppercase Letter
ValueCountFrequency (%)
M 3
30.0%
F 2
20.0%
C 2
20.0%
N 1
 
10.0%
H 1
 
10.0%
R 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
o 2
28.6%
d 1
14.3%
t 1
14.3%
a 1
14.3%
e 1
14.3%
m 1
14.3%
Decimal Number
ValueCountFrequency (%)
2 9
50.0%
1 5
27.8%
0 2
 
11.1%
9 1
 
5.6%
8 1
 
5.6%
Space Separator
ValueCountFrequency (%)
182
100.0%
Open Punctuation
ValueCountFrequency (%)
( 101
100.0%
Close Punctuation
ValueCountFrequency (%)
) 100
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2675
86.4%
Common 403
 
13.0%
Latin 17
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 179
 
6.7%
사 153
 
5.7%
회 150
 
5.6%
식 114
 
4.3%
농 99
 
3.7%
인 80
 
3.0%
산 78
 
2.9%
업 77
 
2.9%
법 76
 
2.8%
드 67
 
2.5%
Other values (265) 1602
59.9%
Latin
ValueCountFrequency (%)
M 3
17.6%
F 2
11.8%
o 2
11.8%
C 2
11.8%
N 1
 
5.9%
H 1
 
5.9%
d 1
 
5.9%
t 1
 
5.9%
a 1
 
5.9%
e 1
 
5.9%
Other values (2) 2
11.8%
Common
ValueCountFrequency (%)
182
45.2%
( 101
25.1%
) 100
24.8%
2 9
 
2.2%
1 5
 
1.2%
& 2
 
0.5%
0 2
 
0.5%
9 1
 
0.2%
8 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2674
86.4%
ASCII 420
 
13.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
182
43.3%
( 101
24.0%
) 100
23.8%
2 9
 
2.1%
1 5
 
1.2%
M 3
 
0.7%
F 2
 
0.5%
o 2
 
0.5%
& 2
 
0.5%
C 2
 
0.5%
Other values (11) 12
 
2.9%
Hangul
ValueCountFrequency (%)
주 179
 
6.7%
사 153
 
5.7%
회 150
 
5.6%
식 114
 
4.3%
농 99
 
3.7%
인 80
 
3.0%
산 78
 
2.9%
업 77
 
2.9%
법 76
 
2.8%
드 67
 
2.5%
Other values (264) 1601
59.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

소재지
Text

MISSING 

Distinct308
Distinct (%)92.5%
Missing10
Missing (%)2.9%
Memory size2.8 KiB
2024-03-14T17:49:50.184423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length37
Mean length25.588589
Min length17

Characters and Unicode

Total characters8521
Distinct characters225
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

Unique296 ?
Unique (%)88.9%

Sample

1st row충청남도 천안시 동남구 목천읍 운전리 376번지 11호
2nd row충청남도 천안시 서북구 성환읍 율금리 764번지 4호
3rd row충청남도 천안시 서북구 성환읍 수향리 258번지 6호
4th row충청남도 천안시 서북구 직산읍 모시리 40번지 3호
5th row충청남도 천안시 서북구 직산읍 삼은리 458번지
ValueCountFrequency (%)
충청남도 333
 
17.3%
천안시 98
 
5.1%
아산시 57
 
3.0%
동남구 57
 
3.0%
1호 43
 
2.2%
서북구 41
 
2.1%
논산시 36
 
1.9%
2호 31
 
1.6%
서산시 26
 
1.4%
3호 22
 
1.1%
Other values (610) 1179
61.3%
2024-03-14T17:49:52.274113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1923
22.6%
남 423
 
5.0%
지 346
 
4.1%
청 345
 
4.0%
도 339
 
4.0%
충 334
 
3.9%
번 330
 
3.9%
시 263
 
3.1%
리 246
 
2.9%
1 223
 
2.6%
Other values (215) 3749
44.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5351
62.8%
Space Separator 1923
 
22.6%
Decimal Number 1235
 
14.5%
Dash Punctuation 4
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 423
 
7.9%
지 346
 
6.5%
청 345
 
6.4%
도 339
 
6.3%
충 334
 
6.2%
번 330
 
6.2%
시 263
 
4.9%
리 246
 
4.6%
호 222
 
4.1%
산 178
 
3.3%
Other values (199) 2325
43.4%
Decimal Number
ValueCountFrequency (%)
1 223
18.1%
2 164
13.3%
3 159
12.9%
4 122
9.9%
5 117
9.5%
6 115
9.3%
7 92
7.4%
8 89
 
7.2%
9 80
 
6.5%
0 74
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%
Space Separator
ValueCountFrequency (%)
1923
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5351
62.8%
Common 3168
37.2%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 423
 
7.9%
지 346
 
6.5%
청 345
 
6.4%
도 339
 
6.3%
충 334
 
6.2%
번 330
 
6.2%
시 263
 
4.9%
리 246
 
4.6%
호 222
 
4.1%
산 178
 
3.3%
Other values (199) 2325
43.4%
Common
ValueCountFrequency (%)
1923
60.7%
1 223
 
7.0%
2 164
 
5.2%
3 159
 
5.0%
4 122
 
3.9%
5 117
 
3.7%
6 115
 
3.6%
7 92
 
2.9%
8 89
 
2.8%
9 80
 
2.5%
Other values (4) 84
 
2.7%
Latin
ValueCountFrequency (%)
A 1
50.0%
C 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5351
62.8%
ASCII 3170
37.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1923
60.7%
1 223
 
7.0%
2 164
 
5.2%
3 159
 
5.0%
4 122
 
3.8%
5 117
 
3.7%
6 115
 
3.6%
7 92
 
2.9%
8 89
 
2.8%
9 80
 
2.5%
Other values (6) 86
 
2.7%
Hangul
ValueCountFrequency (%)
남 423
 
7.9%
지 346
 
6.5%
청 345
 
6.4%
도 339
 
6.3%
충 334
 
6.2%
번 330
 
6.2%
시 263
 
4.9%
리 246
 
4.6%
호 222
 
4.1%
산 178
 
3.3%
Other values (199) 2325
43.4%

대표자명
Text

Distinct331
Distinct (%)97.4%
Missing3
Missing (%)0.9%
Memory size2.8 KiB
2024-03-14T17:49:53.243646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length8.0029412
Min length2

Characters and Unicode

Total characters2721
Distinct characters274
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

Unique322 ?
Unique (%)94.7%

Sample

1st row박은정
2nd row새롬에프에스(주)
3rd row조단비
4th row홍성대
5th row미소에프앤에스주식회사
ValueCountFrequency (%)
주식회사 98
 
19.7%
농업회사법인 46
 
9.3%
영농조합법인 3
 
0.6%
주)농업회사법인돈우 2
 
0.4%
김옥순 2
 
0.4%
농업회사법인(주 2
 
0.4%
서산태안축산업협동조합 2
 
0.4%
유한회사 2
 
0.4%
논산계룡축산업협동조합 2
 
0.4%
티엔피푸드 2
 
0.4%
Other values (332) 336
67.6%
2024-03-14T17:49:54.639607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
회 190
 
7.0%
사 190
 
7.0%
주 179
 
6.6%
157
 
5.8%
식 126
 
4.6%
농 98
 
3.6%
업 95
 
3.5%
인 88
 
3.2%
법 82
 
3.0%
( 62
 
2.3%
Other values (264) 1454
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2428
89.2%
Space Separator 157
 
5.8%
Open Punctuation 62
 
2.3%
Close Punctuation 62
 
2.3%
Uppercase Letter 11
 
0.4%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
회 190
 
7.8%
사 190
 
7.8%
주 179
 
7.4%
식 126
 
5.2%
농 98
 
4.0%
업 95
 
3.9%
인 88
 
3.6%
법 82
 
3.4%
산 47
 
1.9%
이 42
 
1.7%
Other values (251) 1291
53.2%
Uppercase Letter
ValueCountFrequency (%)
I 2
18.2%
U 2
18.2%
Z 1
9.1%
O 1
9.1%
H 1
9.1%
C 1
9.1%
G 1
9.1%
N 1
9.1%
L 1
9.1%
Space Separator
ValueCountFrequency (%)
157
100.0%
Open Punctuation
ValueCountFrequency (%)
( 62
100.0%
Close Punctuation
ValueCountFrequency (%)
) 62
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2428
89.2%
Common 282
 
10.4%
Latin 11
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
회 190
 
7.8%
사 190
 
7.8%
주 179
 
7.4%
식 126
 
5.2%
농 98
 
4.0%
업 95
 
3.9%
인 88
 
3.6%
법 82
 
3.4%
산 47
 
1.9%
이 42
 
1.7%
Other values (251) 1291
53.2%
Latin
ValueCountFrequency (%)
I 2
18.2%
U 2
18.2%
Z 1
9.1%
O 1
9.1%
H 1
9.1%
C 1
9.1%
G 1
9.1%
N 1
9.1%
L 1
9.1%
Common
ValueCountFrequency (%)
157
55.7%
( 62
 
22.0%
) 62
 
22.0%
1 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2428
89.2%
ASCII 293
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
회 190
 
7.8%
사 190
 
7.8%
주 179
 
7.4%
식 126
 
5.2%
농 98
 
4.0%
업 95
 
3.9%
인 88
 
3.6%
법 82
 
3.4%
산 47
 
1.9%
이 42
 
1.7%
Other values (251) 1291
53.2%
ASCII
ValueCountFrequency (%)
157
53.6%
( 62
 
21.2%
) 62
 
21.2%
I 2
 
0.7%
U 2
 
0.7%
Z 1
 
0.3%
1 1
 
0.3%
O 1
 
0.3%
H 1
 
0.3%
C 1
 
0.3%
Other values (3) 3
 
1.0%

영업상태
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
정상
343 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정상 343
100.0%

Length

2024-03-14T17:49:54.877880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T17:49:55.187565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정상 343
100.0%

허가일자
Date

Distinct333
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
Minimum1998-09-04 00:00:00
Maximum2023-12-26 00:00:00
2024-03-14T17:49:55.504467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:49:55.946464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2024-03-14T17:49:45.448971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-14T17:49:45.815710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:49:46.026954image/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.
2024-03-14T17:49:46.182246image/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

번호사업장명소재지대표자명영업상태허가일자
01천안남영축산충청남도 천안시 동남구 목천읍 운전리 376번지 11호박은정정상2016-05-16
12새롬에프에스(주)충청남도 천안시 서북구 성환읍 율금리 764번지 4호새롬에프에스(주)정상2017-06-01
23단비에프에스충청남도 천안시 서북구 성환읍 수향리 258번지 6호조단비정상2015-09-14
34MCR푸드충청남도 천안시 서북구 직산읍 모시리 40번지 3호홍성대정상2008-03-06
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