Overview

Dataset statistics

Number of variables5
Number of observations83
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory43.6 B

Variable types

Categorical1
Text1
DateTime1
Numeric2

Dataset

Description충청남도 직거래 직매장 운영현황(구분, 운영자, 운영형태, 개장일 등)으로 직매장 신규조성 및 이용에 활용합니다
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=394&beforeMenuCd=DOM_000000201001001000&publicdatapk=15018720

Alerts

규모(m2) is highly overall correlated with 참여농가수High correlation
참여농가수 is highly overall correlated with 규모(m2) and 1 other fieldsHigh correlation
구분 is highly overall correlated with 참여농가수High correlation
참여농가수 has 1 (1.2%) zerosZeros

Reproduction

Analysis started2024-01-09 22:39:41.706959
Analysis finished2024-01-09 22:39:42.587247
Duration0.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Memory size796.0 B
당진시
18 
천안시
12 
아산시
10 
서산시
7 
논산시
6 
Other values (11)
30 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique4 ?
Unique (%)4.8%

Sample

1st row광 역
2nd row광 역
3rd row천안시
4th row천안시
5th row천안시

Common Values

ValueCountFrequency (%)
당진시 18
21.7%
천안시 12
14.5%
아산시 10
12.0%
서산시 7
 
8.4%
논산시 6
 
7.2%
공주시 5
 
6.0%
서천군 5
 
6.0%
홍성군 5
 
6.0%
청양군 4
 
4.8%
예산군 3
 
3.6%
Other values (6) 8
9.6%

Length

2024-01-10T07:39:42.633005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
당진시 18
21.2%
천안시 12
14.1%
아산시 10
11.8%
서산시 7
 
8.2%
논산시 6
 
7.1%
공주시 5
 
5.9%
서천군 5
 
5.9%
홍성군 5
 
5.9%
청양군 4
 
4.7%
예산군 3
 
3.5%
Other values (7) 10
11.8%

운영자
Text

Distinct79
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size796.0 B
2024-01-10T07:39:42.812148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length14
Mean length6.4698795
Min length4

Characters and Unicode

Total characters537
Distinct characters129
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

Unique75 ?
Unique (%)90.4%

Sample

1st row농업회사법인 FNC㈜
2nd row농업회사법인 푸드허브㈜
3rd row성환농협(본점)
4th row직산농협
5th row천안농협(용곡점)
ValueCountFrequency (%)
논산계룡농협 2
 
2.2%
신평농협 2
 
2.2%
백석올미영농조합법인 2
 
2.2%
동천안농협 2
 
2.2%
농업회사법인 2
 
2.2%
아산원예농협 2
 
2.2%
부여농협 1
 
1.1%
순성농협 1
 
1.1%
송악농협 1
 
1.1%
석문농협(본점 1
 
1.1%
Other values (73) 73
82.0%
2024-01-10T07:39:43.132864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
협 69
 
12.8%
농 64
 
11.9%
산 20
 
3.7%
( 15
 
2.8%
점 15
 
2.8%
) 15
 
2.8%
천 13
 
2.4%
서 10
 
1.9%
성 9
 
1.7%
드 9
 
1.7%
Other values (119) 298
55.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 490
91.2%
Open Punctuation 15
 
2.8%
Close Punctuation 15
 
2.8%
Space Separator 9
 
1.7%
Other Symbol 3
 
0.6%
Uppercase Letter 3
 
0.6%
Decimal Number 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
협 69
 
14.1%
농 64
 
13.1%
산 20
 
4.1%
점 15
 
3.1%
천 13
 
2.7%
서 10
 
2.0%
성 9
 
1.8%
드 9
 
1.8%
인 9
 
1.8%
푸 9
 
1.8%
Other values (110) 263
53.7%
Uppercase Letter
ValueCountFrequency (%)
F 1
33.3%
N 1
33.3%
C 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 493
91.8%
Common 41
 
7.6%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
협 69
 
14.0%
농 64
 
13.0%
산 20
 
4.1%
점 15
 
3.0%
천 13
 
2.6%
서 10
 
2.0%
성 9
 
1.8%
드 9
 
1.8%
인 9
 
1.8%
푸 9
 
1.8%
Other values (111) 266
54.0%
Common
ValueCountFrequency (%)
( 15
36.6%
) 15
36.6%
9
22.0%
1 1
 
2.4%
2 1
 
2.4%
Latin
ValueCountFrequency (%)
F 1
33.3%
N 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 490
91.2%
ASCII 44
 
8.2%
None 3
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
협 69
 
14.1%
농 64
 
13.1%
산 20
 
4.1%
점 15
 
3.1%
천 13
 
2.7%
서 10
 
2.0%
성 9
 
1.8%
드 9
 
1.8%
인 9
 
1.8%
푸 9
 
1.8%
Other values (110) 263
53.7%
ASCII
ValueCountFrequency (%)
( 15
34.1%
) 15
34.1%
9
20.5%
F 1
 
2.3%
N 1
 
2.3%
C 1
 
2.3%
1 1
 
2.3%
2 1
 
2.3%
None
ValueCountFrequency (%)
㈜ 3
100.0%

개장일
Date

Distinct77
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Memory size796.0 B
Minimum2013-09-02 00:00:00
Maximum2023-02-13 00:00:00
2024-01-10T07:39:43.251526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:39:43.362390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

규모(m2)
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean188.98795
Minimum6
Maximum999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size879.0 B
2024-01-10T07:39:43.479865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile15
Q157
median103
Q3240
95-th percentile545.3
Maximum999
Range993
Interquartile range (IQR)183

Descriptive statistics

Standard deviation213.72369
Coefficient of variation (CV)1.1308853
Kurtosis5.5807547
Mean188.98795
Median Absolute Deviation (MAD)67
Skewness2.2629429
Sum15686
Variance45677.817
MonotonicityNot monotonic
2024-01-10T07:39:43.595006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 10
 
12.0%
50 4
 
4.8%
15 4
 
4.8%
66 3
 
3.6%
165 3
 
3.6%
230 2
 
2.4%
60 2
 
2.4%
132 2
 
2.4%
12 1
 
1.2%
55 1
 
1.2%
Other values (51) 51
61.4%
ValueCountFrequency (%)
6 1
 
1.2%
10 1
 
1.2%
12 1
 
1.2%
14 1
 
1.2%
15 4
4.8%
16 1
 
1.2%
18 1
 
1.2%
29 1
 
1.2%
30 1
 
1.2%
33 1
 
1.2%
ValueCountFrequency (%)
999 1
1.2%
996 1
1.2%
974 1
1.2%
694 1
1.2%
547 1
1.2%
530 1
1.2%
523 1
1.2%
506 1
1.2%
453 1
1.2%
424 1
1.2%

참여농가수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct68
Distinct (%)81.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.72289
Minimum0
Maximum1024
Zeros1
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size879.0 B
2024-01-10T07:39:43.711269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile13.1
Q133
median64
Q3111
95-th percentile255.8
Maximum1024
Range1024
Interquartile range (IQR)78

Descriptive statistics

Standard deviation145.40124
Coefficient of variation (CV)1.4154706
Kurtosis24.801583
Mean102.72289
Median Absolute Deviation (MAD)35
Skewness4.5420209
Sum8526
Variance21141.52
MonotonicityNot monotonic
2024-01-10T07:39:43.829189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52 3
 
3.6%
74 3
 
3.6%
222 2
 
2.4%
84 2
 
2.4%
81 2
 
2.4%
29 2
 
2.4%
20 2
 
2.4%
22 2
 
2.4%
2 2
 
2.4%
53 2
 
2.4%
Other values (58) 61
73.5%
ValueCountFrequency (%)
0 1
1.2%
2 2
2.4%
11 1
1.2%
13 1
1.2%
14 2
2.4%
16 1
1.2%
17 1
1.2%
18 1
1.2%
20 2
2.4%
22 2
2.4%
ValueCountFrequency (%)
1024 1
1.2%
792 1
1.2%
277 1
1.2%
271 1
1.2%
257 1
1.2%
245 1
1.2%
222 2
2.4%
206 1
1.2%
199 1
1.2%
184 1
1.2%

Interactions

2024-01-10T07:39:42.242965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:39:42.094856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:39:42.347981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:39:42.158072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:39:44.127917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분운영자개장일규모(m2)참여농가수
구분1.0000.9430.0000.8390.818
운영자0.9431.0000.9710.0000.000
개장일0.0000.9711.0000.9820.848
규모(m2)0.8390.0000.9821.0000.636
참여농가수0.8180.0000.8480.6361.000
2024-01-10T07:39:44.213498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모(m2)참여농가수구분
규모(m2)1.0000.5570.435
참여농가수0.5571.0000.548
구분0.4350.5481.000

Missing values

2024-01-10T07:39:42.467819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:39:42.557619image/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

구분운영자개장일규모(m2)참여농가수
0광 역농업회사법인 FNC㈜2019-05-22523222
1광 역농업회사법인 푸드허브㈜2022-08-26974222
2천안시성환농협(본점)2013-09-028537
3천안시직산농협2015-01-0166120
4천안시천안농협(용곡점)2016-09-0114046
5천안시천안농협(본점)2018-05-015978
6천안시천안농협(성성점)2023-02-13158166
7천안시천안축협2013-12-2310368
8천안시동천안농협2014-12-04330199
9천안시입장농협2017-03-17100206
구분운영자개장일규모(m2)참여농가수
73청양군화성농협(비봉점)2021-09-0728618
74홍성군홍동농협2013-12-3042153
75홍성군홍성농협2015-06-1516580
76홍성군광천농협2017-08-295061
77홍성군금마농협2018-01-2610049
78홍성군서부농협2022-10-012931
79예산군예산축협2015-09-0912335
80예산군덕산농협2017-12-1511530
81예산군삽교농협2020-12-22424170
82태안군태안군청2019-04-264531024