Overview

Dataset statistics

Number of variables5
Number of observations27
Missing cells2
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory45.9 B

Variable types

Text4
Numeric1

Dataset

Description농산물산지유통센터현황20159
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202552

Alerts

건축(평) has 1 (3.7%) missing valuesMissing
기계 장비(종) has 1 (3.7%) missing valuesMissing
조직명 has unique valuesUnique
사업장 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:28:32.035486
Analysis finished2024-03-14 01:28:32.479559
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조직명
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-14T10:28:32.591442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.2962963
Min length3

Characters and Unicode

Total characters170
Distinct characters70
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row망성농협
2nd row전주농협
3rd row전주원협
4th row부안새만금유통(영)
5th row정읍원협
ValueCountFrequency (%)
망성농협 1
 
3.6%
전주농협 1
 
3.6%
한우물영농조합 1
 
3.6%
춘향골농협 1
 
3.6%
운봉농협 1
 
3.6%
유통사업단 1
 
3.6%
한국참다래 1
 
3.6%
부안유통 1
 
3.6%
변산농협(1 1
 
3.6%
익산원협(1 1
 
3.6%
Other values (18) 18
64.3%
2024-03-14T10:28:32.954897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
협 20
 
11.8%
농 17
 
10.0%
) 10
 
5.9%
( 10
 
5.9%
주 6
 
3.5%
원 6
 
3.5%
군 5
 
2.9%
안 5
 
2.9%
산 4
 
2.4%
부 4
 
2.4%
Other values (60) 83
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 147
86.5%
Close Punctuation 10
 
5.9%
Open Punctuation 10
 
5.9%
Decimal Number 2
 
1.2%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
협 20
 
13.6%
농 17
 
11.6%
주 6
 
4.1%
원 6
 
4.1%
군 5
 
3.4%
안 5
 
3.4%
산 4
 
2.7%
부 4
 
2.7%
통 3
 
2.0%
남 3
 
2.0%
Other values (56) 74
50.3%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Decimal Number
ValueCountFrequency (%)
1 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 147
86.5%
Common 23
 
13.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
협 20
 
13.6%
농 17
 
11.6%
주 6
 
4.1%
원 6
 
4.1%
군 5
 
3.4%
안 5
 
3.4%
산 4
 
2.7%
부 4
 
2.7%
통 3
 
2.0%
남 3
 
2.0%
Other values (56) 74
50.3%
Common
ValueCountFrequency (%)
) 10
43.5%
( 10
43.5%
1 2
 
8.7%
1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 147
86.5%
ASCII 23
 
13.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
협 20
 
13.6%
농 17
 
11.6%
주 6
 
4.1%
원 6
 
4.1%
군 5
 
3.4%
안 5
 
3.4%
산 4
 
2.7%
부 4
 
2.7%
통 3
 
2.0%
남 3
 
2.0%
Other values (56) 74
50.3%
ASCII
ValueCountFrequency (%)
) 10
43.5%
( 10
43.5%
1 2
 
8.7%
1
 
4.3%

사업장
Text

UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-14T10:28:33.171045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length15.222222
Min length11

Characters and Unicode

Total characters411
Distinct characters80
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)100.0%

Sample

1st row익산시 망성면 신작리 526-2
2nd row전주시 전미동 56-5
3rd row전주시 송천동2가 산 21-1
4th row부안군 상서면 가오리 734-9
5th row정읍시 용계동 696-1
ValueCountFrequency (%)
익산시 3
 
3.1%
부안군 3
 
3.1%
남원시 3
 
3.1%
완주군 3
 
3.1%
김제시 3
 
3.1%
전주시 2
 
2.1%
상서면 2
 
2.1%
정읍시 2
 
2.1%
고산면 2
 
2.1%
가옥리 1
 
1.0%
Other values (73) 73
75.3%
2024-03-14T10:28:33.483382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
70
 
17.0%
리 20
 
4.9%
- 18
 
4.4%
1 17
 
4.1%
면 15
 
3.6%
시 13
 
3.2%
군 13
 
3.2%
5 13
 
3.2%
4 13
 
3.2%
2 12
 
2.9%
Other values (70) 207
50.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 219
53.3%
Decimal Number 104
25.3%
Space Separator 70
 
17.0%
Dash Punctuation 18
 
4.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 20
 
9.1%
면 15
 
6.8%
시 13
 
5.9%
군 13
 
5.9%
동 10
 
4.6%
산 9
 
4.1%
주 8
 
3.7%
읍 8
 
3.7%
안 7
 
3.2%
부 5
 
2.3%
Other values (58) 111
50.7%
Decimal Number
ValueCountFrequency (%)
1 17
16.3%
5 13
12.5%
4 13
12.5%
2 12
11.5%
6 10
9.6%
3 10
9.6%
9 9
8.7%
7 8
7.7%
8 7
6.7%
0 5
 
4.8%
Space Separator
ValueCountFrequency (%)
70
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 219
53.3%
Common 192
46.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 20
 
9.1%
면 15
 
6.8%
시 13
 
5.9%
군 13
 
5.9%
동 10
 
4.6%
산 9
 
4.1%
주 8
 
3.7%
읍 8
 
3.7%
안 7
 
3.2%
부 5
 
2.3%
Other values (58) 111
50.7%
Common
ValueCountFrequency (%)
70
36.5%
- 18
 
9.4%
1 17
 
8.9%
5 13
 
6.8%
4 13
 
6.8%
2 12
 
6.2%
6 10
 
5.2%
3 10
 
5.2%
9 9
 
4.7%
7 8
 
4.2%
Other values (2) 12
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 219
53.3%
ASCII 192
46.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
70
36.5%
- 18
 
9.4%
1 17
 
8.9%
5 13
 
6.8%
4 13
 
6.8%
2 12
 
6.2%
6 10
 
5.2%
3 10
 
5.2%
9 9
 
4.7%
7 8
 
4.2%
Other values (2) 12
 
6.2%
Hangul
ValueCountFrequency (%)
리 20
 
9.1%
면 15
 
6.8%
시 13
 
5.9%
군 13
 
5.9%
동 10
 
4.6%
산 9
 
4.1%
주 8
 
3.7%
읍 8
 
3.7%
안 7
 
3.2%
부 5
 
2.3%
Other values (58) 111
50.7%

부지(평)
Text

Distinct26
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size348.0 B
2024-03-14T10:28:33.637481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length4.4444444
Min length3

Characters and Unicode

Total characters120
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

Unique25 ?
Unique (%)92.6%

Sample

1st row6,479
2nd row2,270
3rd row1,211
4th row639
5th row366
ValueCountFrequency (%)
1,000 2
 
7.4%
6,479 1
 
3.7%
1,785 1
 
3.7%
2,500 1
 
3.7%
4,399 1
 
3.7%
4,392 1
 
3.7%
3,415 1
 
3.7%
1,405 1
 
3.7%
829 1
 
3.7%
1,488 1
 
3.7%
Other values (16) 16
59.3%
2024-03-14T10:28:33.932210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 19
15.8%
1 15
12.5%
2 13
10.8%
6 12
10.0%
0 11
9.2%
4 11
9.2%
3 10
8.3%
9 9
7.5%
8 8
6.7%
7 6
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
84.2%
Other Punctuation 19
 
15.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
14.9%
2 13
12.9%
6 12
11.9%
0 11
10.9%
4 11
10.9%
3 10
9.9%
9 9
8.9%
8 8
7.9%
7 6
 
5.9%
5 6
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 19
15.8%
1 15
12.5%
2 13
10.8%
6 12
10.0%
0 11
9.2%
4 11
9.2%
3 10
8.3%
9 9
7.5%
8 8
6.7%
7 6
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 19
15.8%
1 15
12.5%
2 13
10.8%
6 12
10.0%
0 11
9.2%
4 11
9.2%
3 10
8.3%
9 9
7.5%
8 8
6.7%
7 6
 
5.0%

건축(평)
Text

MISSING 

Distinct21
Distinct (%)80.8%
Missing1
Missing (%)3.7%
Memory size348.0 B
2024-03-14T10:28:34.081595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.2307692
Min length3

Characters and Unicode

Total characters84
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

Unique16 ?
Unique (%)61.5%

Sample

1st row1,320
2nd row498
3rd row234
4th row272
5th row150
ValueCountFrequency (%)
150 2
 
7.7%
300 2
 
7.7%
710 2
 
7.7%
1,308 2
 
7.7%
450 2
 
7.7%
577 1
 
3.8%
1,320 1
 
3.8%
390 1
 
3.8%
228 1
 
3.8%
485 1
 
3.8%
Other values (11) 11
42.3%
2024-03-14T10:28:34.333919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
22.6%
3 13
15.5%
5 8
9.5%
2 8
9.5%
1 7
 
8.3%
7 7
 
8.3%
8 7
 
8.3%
4 5
 
6.0%
9 5
 
6.0%
, 3
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
96.4%
Other Punctuation 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
23.5%
3 13
16.0%
5 8
9.9%
2 8
9.9%
1 7
 
8.6%
7 7
 
8.6%
8 7
 
8.6%
4 5
 
6.2%
9 5
 
6.2%
6 2
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 19
22.6%
3 13
15.5%
5 8
9.5%
2 8
9.5%
1 7
 
8.3%
7 7
 
8.3%
8 7
 
8.3%
4 5
 
6.0%
9 5
 
6.0%
, 3
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 19
22.6%
3 13
15.5%
5 8
9.5%
2 8
9.5%
1 7
 
8.3%
7 7
 
8.3%
8 7
 
8.3%
4 5
 
6.0%
9 5
 
6.0%
, 3
 
3.6%

기계 장비(종)
Real number (ℝ)

MISSING 

Distinct9
Distinct (%)34.6%
Missing1
Missing (%)3.7%
Infinite0
Infinite (%)0.0%
Mean5.6538462
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size375.0 B
2024-03-14T10:28:34.429384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q13.25
median6
Q37.75
95-th percentile9
Maximum9
Range8
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation2.5446777
Coefficient of variation (CV)0.45007905
Kurtosis-1.098169
Mean5.6538462
Median Absolute Deviation (MAD)2
Skewness-0.36767492
Sum147
Variance6.4753846
MonotonicityNot monotonic
2024-03-14T10:28:34.512374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
6 5
18.5%
2 4
14.8%
7 4
14.8%
9 4
14.8%
8 3
11.1%
5 2
 
7.4%
3 2
 
7.4%
1 1
 
3.7%
4 1
 
3.7%
(Missing) 1
 
3.7%
ValueCountFrequency (%)
1 1
 
3.7%
2 4
14.8%
3 2
 
7.4%
4 1
 
3.7%
5 2
 
7.4%
6 5
18.5%
7 4
14.8%
8 3
11.1%
9 4
14.8%
ValueCountFrequency (%)
9 4
14.8%
8 3
11.1%
7 4
14.8%
6 5
18.5%
5 2
 
7.4%
4 1
 
3.7%
3 2
 
7.4%
2 4
14.8%
1 1
 
3.7%

Interactions

2024-03-14T10:28:32.206857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:28:34.587408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조직명사업장부지(평)건축(평)기계 장비(종)
조직명1.0001.0001.0001.0001.000
사업장1.0001.0001.0001.0001.000
부지(평)1.0001.0001.0000.9680.958
건축(평)1.0001.0000.9681.0000.738
기계 장비(종)1.0001.0000.9580.7381.000

Missing values

2024-03-14T10:28:32.301697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:28:32.371938image/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.
2024-03-14T10:28:32.442705image/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

조직명사업장부지(평)건축(평)기계 장비(종)
0망성농협익산시 망성면 신작리 526-26,4791,3202
1전주농협전주시 전미동 56-52,2704981
2전주원협전주시 송천동2가 산 21-11,2112347
3부안새만금유통(영)부안군 상서면 가오리 734-96392726
4정읍원협정읍시 용계동 696-13661505
5완주임협완주군 고산면 읍내리 799-16762607
6진안군진안군 진안읍 군상리 243-11,0004507
7부안중앙농협부안군 상서면 통정리 4484,3682505
8김제시(농산)김제시 순동 645-52,4639393
9봉상생강(영)완주군 고산면 양하리 772-51,5223509
조직명사업장부지(평)건축(평)기계 장비(종)
17백구농협김제시 백구면 반월리 255-1외 48963788
18남부안농협보안면 영전리 4883693003
19익산원협(1)익산시 목천동 916-21,4887108
20변산농협(1)부안군 변산면 지서리 372-5218293002
21부안유통부안군동진면하장리 17641,4054508
22한국참다래 유통사업단익산시 함라면 신대리 1663,4151,3082
23운봉농협남원시 운봉읍 동천리 324-4외34,3924854
24춘향골농협남원시 금지면 신월리 738외14,3991,3089
25한우물영농조합김제시 용지면 부교리 87-102,5002282
26오수관촌농협오수면 용정리 1912,3569379