Overview

Dataset statistics

Number of variables19
Number of observations10000
Missing cells59756
Missing cells (%)31.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory163.0 B

Variable types

Text8
DateTime5
Numeric3
Categorical3

Dataset

Description공공데이터 제공 표준데이터 속성정보(허용값, 표현형식/단위 등)는 [공공데이터 제공 표준] 전문을 참고하시기 바랍니다.(공공데이터포털>정보공유>자료실) 각 기관에서 등록한 표준데이터를 취합하여 제공하기 때문에 갱신주기는 개별 파일마다 다릅니다.(기관에서 등록한 데이터를 취합한 것으로 개별 파일별 갱신시점이 다름)
Author지방자치단체
URLhttps://www.data.go.kr/data/15025455/standard.do

Alerts

관리기관명 is highly overall correlated with 제공기관코드 and 2 other fieldsHigh correlation
제공기관명 is highly overall correlated with 제공기관코드 and 2 other fieldsHigh correlation
전화번호 is highly overall correlated with 제공기관코드 and 2 other fieldsHigh correlation
재배면적 is highly overall correlated with 재배규모High correlation
재배규모 is highly overall correlated with 재배면적High correlation
제공기관코드 is highly overall correlated with 전화번호 and 2 other fieldsHigh correlation
전화번호 is highly imbalanced (96.1%)Imbalance
인증취소일자 has 9751 (97.5%) missing valuesMissing
사업장도로명주소 has 5058 (50.6%) missing valuesMissing
사업장지번주소 has 9407 (94.1%) missing valuesMissing
생산지도로명주소 has 4241 (42.4%) missing valuesMissing
생산지지번주소 has 5527 (55.3%) missing valuesMissing
재배면적 has 6186 (61.9%) missing valuesMissing
재배규모 has 9644 (96.4%) missing valuesMissing
사업자등록번호 has 9942 (99.4%) missing valuesMissing

Reproduction

Analysis started2024-05-11 10:06:02.990698
Analysis finished2024-05-11 10:06:12.771991
Duration9.78 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

로컬푸드인증번호
Text

Distinct6962
Distinct (%)69.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:06:13.256073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length12.3159
Min length4

Characters and Unicode

Total characters123159
Distinct characters30
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

Unique4475 ?
Unique (%)44.8%

Sample

1st row2023-04-0104
2nd row2017-03-0520
3rd row2021-03-0063
4th row2022-03-0349
5th row2021-06-0632
ValueCountFrequency (%)
2021-03-0041-1 32
 
0.3%
2021-01-0001-5 29
 
0.3%
2023-01-0023-05 26
 
0.3%
2022-03-0013-3 15
 
0.1%
2021-01-0010-1 14
 
0.1%
2023-01-0024-05 13
 
0.1%
2022-01-0001-1 12
 
0.1%
2021-03-0069-1 12
 
0.1%
2023-02-0013-01 10
 
0.1%
2021-02-0002-1 9
 
0.1%
Other values (6952) 9828
98.3%
2024-05-11T10:06:14.586959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 36867
29.9%
2 27439
22.3%
- 20137
16.4%
1 10730
 
8.7%
3 10024
 
8.1%
4 3454
 
2.8%
5 3169
 
2.6%
6 2916
 
2.4%
7 2751
 
2.2%
9 2454
 
2.0%
Other values (20) 3218
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102184
83.0%
Dash Punctuation 20137
 
16.4%
Uppercase Letter 604
 
0.5%
Other Letter 234
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
월 112
47.9%
영 112
47.9%
감 1
 
0.4%
물 1
 
0.4%
불 1
 
0.4%
정 1
 
0.4%
소 1
 
0.4%
수 1
 
0.4%
청 1
 
0.4%
천 1
 
0.4%
Other values (2) 2
 
0.9%
Decimal Number
ValueCountFrequency (%)
0 36867
36.1%
2 27439
26.9%
1 10730
 
10.5%
3 10024
 
9.8%
4 3454
 
3.4%
5 3169
 
3.1%
6 2916
 
2.9%
7 2751
 
2.7%
9 2454
 
2.4%
8 2380
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
H 120
19.9%
Y 120
19.9%
G 120
19.9%
S 61
10.1%
W 61
10.1%
L 61
10.1%
F 61
10.1%
Dash Punctuation
ValueCountFrequency (%)
- 20137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 122321
99.3%
Latin 604
 
0.5%
Hangul 234
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
월 112
47.9%
영 112
47.9%
감 1
 
0.4%
물 1
 
0.4%
불 1
 
0.4%
정 1
 
0.4%
소 1
 
0.4%
수 1
 
0.4%
청 1
 
0.4%
천 1
 
0.4%
Other values (2) 2
 
0.9%
Common
ValueCountFrequency (%)
0 36867
30.1%
2 27439
22.4%
- 20137
16.5%
1 10730
 
8.8%
3 10024
 
8.2%
4 3454
 
2.8%
5 3169
 
2.6%
6 2916
 
2.4%
7 2751
 
2.2%
9 2454
 
2.0%
Latin
ValueCountFrequency (%)
H 120
19.9%
Y 120
19.9%
G 120
19.9%
S 61
10.1%
W 61
10.1%
L 61
10.1%
F 61
10.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 122925
99.8%
Hangul 234
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 36867
30.0%
2 27439
22.3%
- 20137
16.4%
1 10730
 
8.7%
3 10024
 
8.2%
4 3454
 
2.8%
5 3169
 
2.6%
6 2916
 
2.4%
7 2751
 
2.2%
9 2454
 
2.0%
Other values (8) 2984
 
2.4%
Hangul
ValueCountFrequency (%)
월 112
47.9%
영 112
47.9%
감 1
 
0.4%
물 1
 
0.4%
불 1
 
0.4%
정 1
 
0.4%
소 1
 
0.4%
수 1
 
0.4%
청 1
 
0.4%
천 1
 
0.4%
Other values (2) 2
 
0.9%

인증유효시작일자
Date

Distinct616
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-11-18 00:00:00
Maximum2024-04-29 00:00:00
2024-05-11T10:06:15.154930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:15.770874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인증유효종료일자
Date

Distinct656
Distinct (%)6.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2017-11-17 00:00:00
Maximum2034-03-28 00:00:00
2024-05-11T10:06:16.333411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:16.936585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인증취소일자
Date

MISSING 

Distinct91
Distinct (%)36.5%
Missing9751
Missing (%)97.5%
Memory size156.2 KiB
Minimum2023-06-30 00:00:00
Maximum2026-01-25 00:00:00
2024-05-11T10:06:17.469756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:18.071024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업장도로명주소
Text

MISSING 

Distinct153
Distinct (%)3.1%
Missing5058
Missing (%)50.6%
Memory size156.2 KiB
2024-05-11T10:06:18.774517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length22
Mean length21.209025
Min length15

Characters and Unicode

Total characters104815
Distinct characters209
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique144 ?
Unique (%)2.9%

Sample

1st row전북특별자치도 완주군 용진읍 지암로 61
2nd row전북특별자치도 완주군 용진읍 지암로 61
3rd row전북특별자치도 완주군 용진읍 지암로 61
4th row전북특별자치도 완주군 용진읍 지암로 61
5th row전라남도 순천시 낙안면 심내길 24
ValueCountFrequency (%)
61 4664
18.5%
용진읍 4663
18.5%
지암로 4663
18.5%
완주군 4663
18.5%
전북특별자치도 2487
9.9%
전라북도 2176
8.6%
함양군 240
 
1.0%
수동면 240
 
1.0%
경상남도 120
 
0.5%
산업단지길 120
 
0.5%
Other values (324) 1144
 
4.5%
2024-05-11T10:06:19.968573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
20239
19.3%
도 5067
 
4.8%
군 4911
 
4.7%
1 4896
 
4.7%
로 4840
 
4.6%
지 4789
 
4.6%
전 4782
 
4.6%
6 4696
 
4.5%
주 4685
 
4.5%
암 4679
 
4.5%
Other values (199) 41231
39.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 73834
70.4%
Space Separator 20239
 
19.3%
Decimal Number 10572
 
10.1%
Math Symbol 120
 
0.1%
Dash Punctuation 46
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 5067
 
6.9%
군 4911
 
6.7%
로 4840
 
6.6%
지 4789
 
6.5%
전 4782
 
6.5%
주 4685
 
6.3%
암 4679
 
6.3%
읍 4676
 
6.3%
진 4668
 
6.3%
북 4667
 
6.3%
Other values (184) 26070
35.3%
Decimal Number
ValueCountFrequency (%)
1 4896
46.3%
6 4696
44.4%
2 202
 
1.9%
4 178
 
1.7%
0 160
 
1.5%
9 150
 
1.4%
7 148
 
1.4%
3 61
 
0.6%
5 47
 
0.4%
8 34
 
0.3%
Space Separator
ValueCountFrequency (%)
20239
100.0%
Math Symbol
ValueCountFrequency (%)
+ 120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 73834
70.4%
Common 30981
29.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 5067
 
6.9%
군 4911
 
6.7%
로 4840
 
6.6%
지 4789
 
6.5%
전 4782
 
6.5%
주 4685
 
6.3%
암 4679
 
6.3%
읍 4676
 
6.3%
진 4668
 
6.3%
북 4667
 
6.3%
Other values (184) 26070
35.3%
Common
ValueCountFrequency (%)
20239
65.3%
1 4896
 
15.8%
6 4696
 
15.2%
2 202
 
0.7%
4 178
 
0.6%
0 160
 
0.5%
9 150
 
0.5%
7 148
 
0.5%
+ 120
 
0.4%
3 61
 
0.2%
Other values (5) 131
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 73834
70.4%
ASCII 30981
29.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20239
65.3%
1 4896
 
15.8%
6 4696
 
15.2%
2 202
 
0.7%
4 178
 
0.6%
0 160
 
0.5%
9 150
 
0.5%
7 148
 
0.5%
+ 120
 
0.4%
3 61
 
0.2%
Other values (5) 131
 
0.4%
Hangul
ValueCountFrequency (%)
도 5067
 
6.9%
군 4911
 
6.7%
로 4840
 
6.6%
지 4789
 
6.5%
전 4782
 
6.5%
주 4685
 
6.3%
암 4679
 
6.3%
읍 4676
 
6.3%
진 4668
 
6.3%
북 4667
 
6.3%
Other values (184) 26070
35.3%

사업장지번주소
Text

MISSING 

Distinct567
Distinct (%)95.6%
Missing9407
Missing (%)94.1%
Memory size156.2 KiB
2024-05-11T10:06:20.763235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length23.264755
Min length16

Characters and Unicode

Total characters13796
Distinct characters146
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique543 ?
Unique (%)91.6%

Sample

1st row전북특별자치도 군산시 옥산면 남내리 783-1
2nd row전라남도 순천시 낙안면 내운리 286
3rd row전라남도 순천시 외서면 월암리 1035
4th row전북특별자치도 군산시 나포면 서포리 181-3
5th row경기도 수원시 팔달구 화서동 250-4
ValueCountFrequency (%)
군산시 477
18.3%
전북특별자치도 477
18.3%
개정면 88
 
3.4%
옥산면 74
 
2.8%
경기도 67
 
2.6%
성산면 61
 
2.3%
수원시 61
 
2.3%
서수면 53
 
2.0%
순천시 49
 
1.9%
전라남도 49
 
1.9%
Other values (692) 1145
44.0%
2024-05-11T10:06:22.223290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2047
 
14.8%
산 719
 
5.2%
도 602
 
4.4%
시 593
 
4.3%
전 532
 
3.9%
북 498
 
3.6%
별 482
 
3.5%
치 477
 
3.5%
군 477
 
3.5%
특 477
 
3.5%
Other values (136) 6892
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8951
64.9%
Decimal Number 2333
 
16.9%
Space Separator 2047
 
14.8%
Dash Punctuation 458
 
3.3%
Math Symbol 3
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 719
 
8.0%
도 602
 
6.7%
시 593
 
6.6%
전 532
 
5.9%
북 498
 
5.6%
별 482
 
5.4%
치 477
 
5.3%
군 477
 
5.3%
특 477
 
5.3%
자 477
 
5.3%
Other values (121) 3617
40.4%
Decimal Number
ValueCountFrequency (%)
1 463
19.8%
2 334
14.3%
3 272
11.7%
0 252
10.8%
4 213
9.1%
5 202
8.7%
7 177
 
7.6%
6 157
 
6.7%
8 145
 
6.2%
9 118
 
5.1%
Space Separator
ValueCountFrequency (%)
2047
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 458
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8951
64.9%
Common 4845
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 719
 
8.0%
도 602
 
6.7%
시 593
 
6.6%
전 532
 
5.9%
북 498
 
5.6%
별 482
 
5.4%
치 477
 
5.3%
군 477
 
5.3%
특 477
 
5.3%
자 477
 
5.3%
Other values (121) 3617
40.4%
Common
ValueCountFrequency (%)
2047
42.2%
1 463
 
9.6%
- 458
 
9.5%
2 334
 
6.9%
3 272
 
5.6%
0 252
 
5.2%
4 213
 
4.4%
5 202
 
4.2%
7 177
 
3.7%
6 157
 
3.2%
Other values (5) 270
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8951
64.9%
ASCII 4845
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2047
42.2%
1 463
 
9.6%
- 458
 
9.5%
2 334
 
6.9%
3 272
 
5.6%
0 252
 
5.2%
4 213
 
4.4%
5 202
 
4.2%
7 177
 
3.7%
6 157
 
3.2%
Other values (5) 270
 
5.6%
Hangul
ValueCountFrequency (%)
산 719
 
8.0%
도 602
 
6.7%
시 593
 
6.6%
전 532
 
5.9%
북 498
 
5.6%
별 482
 
5.4%
치 477
 
5.3%
군 477
 
5.3%
특 477
 
5.3%
자 477
 
5.3%
Other values (121) 3617
40.4%

생산지도로명주소
Text

MISSING 

Distinct3784
Distinct (%)65.7%
Missing4241
Missing (%)42.4%
Memory size156.2 KiB
2024-05-11T10:06:23.086082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length48
Mean length23.647682
Min length10

Characters and Unicode

Total characters136187
Distinct characters383
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2501 ?
Unique (%)43.4%

Sample

1st row경기도 화성시 송산면 공룡로487번길 19
2nd row전북특별자치도 완주군 경천면 경가천길 488-11
3rd row전북특별자치도 완주군 삼례읍 구와로 99-1
4th row전북특별자치도 완주군 이서면 은교장동길 24, 103호(은교빌라)
5th row전북특별자치도 완주군 구이면 원백여길 162-3
ValueCountFrequency (%)
완주군 4640
 
15.8%
전북특별자치도 2474
 
8.4%
전라북도 2164
 
7.4%
구이면 885
 
3.0%
봉동읍 734
 
2.5%
용진읍 595
 
2.0%
경기도 460
 
1.6%
비봉면 417
 
1.4%
이서면 411
 
1.4%
전라남도 394
 
1.3%
Other values (3084) 16193
55.1%
2024-05-11T10:06:24.759072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23641
 
17.4%
도 5826
 
4.3%
전 5259
 
3.9%
주 4960
 
3.6%
군 4876
 
3.6%
북 4724
 
3.5%
완 4689
 
3.4%
1 4565
 
3.4%
길 4018
 
3.0%
면 3699
 
2.7%
Other values (373) 69930
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 87714
64.4%
Space Separator 23641
 
17.4%
Decimal Number 21139
 
15.5%
Dash Punctuation 3113
 
2.3%
Other Punctuation 283
 
0.2%
Close Punctuation 137
 
0.1%
Open Punctuation 137
 
0.1%
Uppercase Letter 16
 
< 0.1%
Lowercase Letter 7
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 5826
 
6.6%
전 5259
 
6.0%
주 4960
 
5.7%
군 4876
 
5.6%
북 4724
 
5.4%
완 4689
 
5.3%
길 4018
 
4.6%
면 3699
 
4.2%
치 2601
 
3.0%
라 2568
 
2.9%
Other values (349) 44494
50.7%
Decimal Number
ValueCountFrequency (%)
1 4565
21.6%
2 2751
13.0%
3 2478
11.7%
4 1988
9.4%
5 1936
9.2%
0 1815
 
8.6%
6 1577
 
7.5%
8 1369
 
6.5%
7 1351
 
6.4%
9 1309
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 190
67.1%
@ 58
 
20.5%
/ 30
 
10.6%
. 5
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
L 5
31.2%
H 5
31.2%
A 4
25.0%
B 2
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
e 5
71.4%
c 2
 
28.6%
Space Separator
ValueCountFrequency (%)
23641
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3113
100.0%
Close Punctuation
ValueCountFrequency (%)
) 137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 137
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 87714
64.4%
Common 48450
35.6%
Latin 23
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 5826
 
6.6%
전 5259
 
6.0%
주 4960
 
5.7%
군 4876
 
5.6%
북 4724
 
5.4%
완 4689
 
5.3%
길 4018
 
4.6%
면 3699
 
4.2%
치 2601
 
3.0%
라 2568
 
2.9%
Other values (349) 44494
50.7%
Common
ValueCountFrequency (%)
23641
48.8%
1 4565
 
9.4%
- 3113
 
6.4%
2 2751
 
5.7%
3 2478
 
5.1%
4 1988
 
4.1%
5 1936
 
4.0%
0 1815
 
3.7%
6 1577
 
3.3%
8 1369
 
2.8%
Other values (8) 3217
 
6.6%
Latin
ValueCountFrequency (%)
L 5
21.7%
H 5
21.7%
e 5
21.7%
A 4
17.4%
B 2
 
8.7%
c 2
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 87714
64.4%
ASCII 48473
35.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23641
48.8%
1 4565
 
9.4%
- 3113
 
6.4%
2 2751
 
5.7%
3 2478
 
5.1%
4 1988
 
4.1%
5 1936
 
4.0%
0 1815
 
3.7%
6 1577
 
3.3%
8 1369
 
2.8%
Other values (14) 3240
 
6.7%
Hangul
ValueCountFrequency (%)
도 5826
 
6.6%
전 5259
 
6.0%
주 4960
 
5.7%
군 4876
 
5.6%
북 4724
 
5.4%
완 4689
 
5.3%
길 4018
 
4.6%
면 3699
 
4.2%
치 2601
 
3.0%
라 2568
 
2.9%
Other values (349) 44494
50.7%

생산지지번주소
Text

MISSING 

Distinct2374
Distinct (%)53.1%
Missing5527
Missing (%)55.3%
Memory size156.2 KiB
2024-05-11T10:06:25.961140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length135
Median length67
Mean length22.968701
Min length10

Characters and Unicode

Total characters102739
Distinct characters274
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1852 ?
Unique (%)41.4%

Sample

1st row전북특별자치도 군산시 옥산면 남내리 783-1
2nd row전라남도 순천시 낙안면 내운리 286
3rd row강원도 원주시 판부면 서곡리 1334, 1337
4th row전라북도 군산시 임피면 축산리566-9
5th row강원도 원주시 관설동 350-2
ValueCountFrequency (%)
강원도 2373
 
10.5%
원주시 2254
 
10.0%
군산시 962
 
4.3%
판부면 553
 
2.4%
전북특별자치도 544
 
2.4%
전라북도 543
 
2.4%
충청남도 473
 
2.1%
서곡리 448
 
2.0%
관설동 425
 
1.9%
흥업면 272
 
1.2%
Other values (2901) 13786
60.9%
2024-05-11T10:06:28.207100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18944
 
18.4%
원 4910
 
4.8%
1 4692
 
4.6%
도 4510
 
4.4%
시 3924
 
3.8%
- 3823
 
3.7%
리 3362
 
3.3%
면 3167
 
3.1%
2 3027
 
2.9%
3 2613
 
2.5%
Other values (264) 49767
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 55903
54.4%
Decimal Number 22777
22.2%
Space Separator 18944
 
18.4%
Dash Punctuation 3823
 
3.7%
Other Punctuation 1268
 
1.2%
Math Symbol 16
 
< 0.1%
Close Punctuation 4
 
< 0.1%
Open Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 4910
 
8.8%
도 4510
 
8.1%
시 3924
 
7.0%
리 3362
 
6.0%
면 3167
 
5.7%
강 2527
 
4.5%
주 2467
 
4.4%
산 2149
 
3.8%
군 1556
 
2.8%
북 1423
 
2.5%
Other values (246) 25908
46.3%
Decimal Number
ValueCountFrequency (%)
1 4692
20.6%
2 3027
13.3%
3 2613
11.5%
5 2286
10.0%
4 1967
8.6%
8 1760
 
7.7%
6 1707
 
7.5%
7 1670
 
7.3%
0 1565
 
6.9%
9 1490
 
6.5%
Other Punctuation
ValueCountFrequency (%)
, 1266
99.8%
@ 1
 
0.1%
/ 1
 
0.1%
Space Separator
ValueCountFrequency (%)
18944
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3823
100.0%
Math Symbol
ValueCountFrequency (%)
~ 16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 55903
54.4%
Common 46836
45.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 4910
 
8.8%
도 4510
 
8.1%
시 3924
 
7.0%
리 3362
 
6.0%
면 3167
 
5.7%
강 2527
 
4.5%
주 2467
 
4.4%
산 2149
 
3.8%
군 1556
 
2.8%
북 1423
 
2.5%
Other values (246) 25908
46.3%
Common
ValueCountFrequency (%)
18944
40.4%
1 4692
 
10.0%
- 3823
 
8.2%
2 3027
 
6.5%
3 2613
 
5.6%
5 2286
 
4.9%
4 1967
 
4.2%
8 1760
 
3.8%
6 1707
 
3.6%
7 1670
 
3.6%
Other values (8) 4347
 
9.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 55903
54.4%
ASCII 46836
45.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18944
40.4%
1 4692
 
10.0%
- 3823
 
8.2%
2 3027
 
6.5%
3 2613
 
5.6%
5 2286
 
4.9%
4 1967
 
4.2%
8 1760
 
3.8%
6 1707
 
3.6%
7 1670
 
3.6%
Other values (8) 4347
 
9.3%
Hangul
ValueCountFrequency (%)
원 4910
 
8.8%
도 4510
 
8.1%
시 3924
 
7.0%
리 3362
 
6.0%
면 3167
 
5.7%
강 2527
 
4.5%
주 2467
 
4.4%
산 2149
 
3.8%
군 1556
 
2.8%
북 1423
 
2.5%
Other values (246) 25908
46.3%

품목명
Text

Distinct1561
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:06:28.935616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length446
Median length444
Mean length11.6676
Min length1

Characters and Unicode

Total characters116676
Distinct characters671
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1086 ?
Unique (%)10.9%

Sample

1st row포도
2nd row상추+아욱
3rd row딸기
4th row대파
5th row표고버섯
ValueCountFrequency (%)
619
 
5.2%
대파 491
 
4.1%
배추 437
 
3.7%
상추 384
 
3.2%
감자 323
 
2.7%
딸기 322
 
2.7%
고추 308
 
2.6%
포도 250
 
2.1%
고구마 247
 
2.1%
복숭아 245
 
2.1%
Other values (1884) 8223
69.4%
2024-05-11T10:06:30.040271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 13105
 
11.2%
) 6624
 
5.7%
( 6452
 
5.5%
추 4398
 
3.8%
고 3995
 
3.4%
마 2257
 
1.9%
파 2089
 
1.8%
리 1932
 
1.7%
1856
 
1.6%
감 1667
 
1.4%
Other values (661) 72301
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 86186
73.9%
Math Symbol 13108
 
11.2%
Close Punctuation 6624
 
5.7%
Open Punctuation 6452
 
5.5%
Space Separator 1858
 
1.6%
Other Punctuation 1569
 
1.3%
Decimal Number 296
 
0.3%
Dash Punctuation 237
 
0.2%
Connector Punctuation 211
 
0.2%
Uppercase Letter 122
 
0.1%
Other values (2) 13
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 4398
 
5.1%
고 3995
 
4.6%
마 2257
 
2.6%
파 2089
 
2.4%
리 1932
 
2.2%
감 1667
 
1.9%
기 1650
 
1.9%
대 1626
 
1.9%
건 1510
 
1.8%
무 1443
 
1.7%
Other values (628) 63619
73.8%
Decimal Number
ValueCountFrequency (%)
1 88
29.7%
2 48
16.2%
3 47
15.9%
0 32
 
10.8%
4 27
 
9.1%
7 14
 
4.7%
5 12
 
4.1%
9 11
 
3.7%
6 9
 
3.0%
8 8
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 743
47.4%
/ 620
39.5%
. 127
 
8.1%
: 73
 
4.7%
* 5
 
0.3%
& 1
 
0.1%
Uppercase Letter
ValueCountFrequency (%)
C 114
93.4%
A 3
 
2.5%
B 2
 
1.6%
L 2
 
1.6%
M 1
 
0.8%
Lowercase Letter
ValueCountFrequency (%)
g 8
66.7%
l 2
 
16.7%
m 2
 
16.7%
Math Symbol
ValueCountFrequency (%)
+ 13105
> 99.9%
= 3
 
< 0.1%
Space Separator
ValueCountFrequency (%)
1856
99.9%
　 2
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 6624
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6452
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 237
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 211
100.0%
Other Symbol
ValueCountFrequency (%)
℃ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 86172
73.9%
Common 30356
 
26.0%
Latin 134
 
0.1%
Han 14
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 4398
 
5.1%
고 3995
 
4.6%
마 2257
 
2.6%
파 2089
 
2.4%
리 1932
 
2.2%
감 1667
 
1.9%
기 1650
 
1.9%
대 1626
 
1.9%
건 1510
 
1.8%
무 1443
 
1.7%
Other values (625) 63605
73.8%
Common
ValueCountFrequency (%)
+ 13105
43.2%
) 6624
21.8%
( 6452
21.3%
1856
 
6.1%
, 743
 
2.4%
/ 620
 
2.0%
- 237
 
0.8%
_ 211
 
0.7%
. 127
 
0.4%
1 88
 
0.3%
Other values (15) 293
 
1.0%
Latin
ValueCountFrequency (%)
C 114
85.1%
g 8
 
6.0%
A 3
 
2.2%
l 2
 
1.5%
m 2
 
1.5%
B 2
 
1.5%
L 2
 
1.5%
M 1
 
0.7%
Han
ValueCountFrequency (%)
大 6
42.9%
中 4
28.6%
小 4
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 86172
73.9%
ASCII 30487
 
26.1%
CJK 14
 
< 0.1%
None 2
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 13105
43.0%
) 6624
21.7%
( 6452
21.2%
1856
 
6.1%
, 743
 
2.4%
/ 620
 
2.0%
- 237
 
0.8%
_ 211
 
0.7%
. 127
 
0.4%
C 114
 
0.4%
Other values (21) 398
 
1.3%
Hangul
ValueCountFrequency (%)
추 4398
 
5.1%
고 3995
 
4.6%
마 2257
 
2.6%
파 2089
 
2.4%
리 1932
 
2.2%
감 1667
 
1.9%
기 1650
 
1.9%
대 1626
 
1.9%
건 1510
 
1.8%
무 1443
 
1.7%
Other values (625) 63605
73.8%
CJK
ValueCountFrequency (%)
大 6
42.9%
中 4
28.6%
小 4
28.6%
None
ValueCountFrequency (%)
　 2
100.0%
Letterlike Symbols
ValueCountFrequency (%)
℃ 1
100.0%

재배면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1283
Distinct (%)33.6%
Missing6186
Missing (%)61.9%
Infinite0
Infinite (%)0.0%
Mean3960.129
Minimum0
Maximum204077
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:06:30.464813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile249.3
Q11118
median2193.5
Q33731.25
95-th percentile11839.95
Maximum204077
Range204077
Interquartile range (IQR)2613.25

Descriptive statistics

Standard deviation8294.5386
Coefficient of variation (CV)2.0945122
Kurtosis208.31972
Mean3960.129
Median Absolute Deviation (MAD)1203.5
Skewness11.348577
Sum15103932
Variance68799370
MonotonicityNot monotonic
2024-05-11T10:06:30.929356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
990.0 88
 
0.9%
2051.0 75
 
0.8%
3227.0 59
 
0.6%
2073.0 57
 
0.6%
4249.0 40
 
0.4%
1614.0 35
 
0.4%
2374.0 35
 
0.4%
1872.0 33
 
0.3%
2645.0 32
 
0.3%
1935.0 31
 
0.3%
Other values (1273) 3329
33.3%
(Missing) 6186
61.9%
ValueCountFrequency (%)
0.0 1
 
< 0.1%
3.0 5
0.1%
6.0 2
 
< 0.1%
7.0 1
 
< 0.1%
10.0 1
 
< 0.1%
11.0 2
 
< 0.1%
18.0 1
 
< 0.1%
19.0 4
< 0.1%
21.0 1
 
< 0.1%
26.0 1
 
< 0.1%
ValueCountFrequency (%)
204077.0 1
< 0.1%
200303.0 1
< 0.1%
127520.0 1
< 0.1%
110720.0 1
< 0.1%
108787.0 1
< 0.1%
88440.0 1
< 0.1%
67980.0 1
< 0.1%
64885.0 1
< 0.1%
64390.0 1
< 0.1%
60439.0 2
< 0.1%

재배규모
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct339
Distinct (%)95.2%
Missing9644
Missing (%)96.4%
Infinite0
Infinite (%)0.0%
Mean13767.817
Minimum100
Maximum204077
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:06:31.381159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile1072
Q12951
median6321.5
Q315382.5
95-th percentile50651.25
Maximum204077
Range203977
Interquartile range (IQR)12431.5

Descriptive statistics

Standard deviation22292.37
Coefficient of variation (CV)1.6191651
Kurtosis31.491157
Mean13767.817
Median Absolute Deviation (MAD)4164
Skewness4.756671
Sum4901343
Variance4.9694976 × 108
MonotonicityNot monotonic
2024-05-11T10:06:32.024374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3000 4
 
< 0.1%
2638 3
 
< 0.1%
3300 3
 
< 0.1%
1300 2
 
< 0.1%
5760 2
 
< 0.1%
60439 2
 
< 0.1%
2992 2
 
< 0.1%
5562 2
 
< 0.1%
2790 2
 
< 0.1%
330 2
 
< 0.1%
Other values (329) 332
 
3.3%
(Missing) 9644
96.4%
ValueCountFrequency (%)
100 1
< 0.1%
146 1
< 0.1%
175 1
< 0.1%
230 1
< 0.1%
264 1
< 0.1%
322 1
< 0.1%
330 2
< 0.1%
400 1
< 0.1%
560 1
< 0.1%
645 1
< 0.1%
ValueCountFrequency (%)
204077 1
< 0.1%
200303 1
< 0.1%
127520 1
< 0.1%
110720 1
< 0.1%
108787 1
< 0.1%
88440 1
< 0.1%
80000 1
< 0.1%
67980 1
< 0.1%
64885 1
< 0.1%
64390 1
< 0.1%

인증부여일자
Date

Distinct500
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2015-11-18 00:00:00
Maximum2024-04-02 00:00:00
2024-05-11T10:06:32.626030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:33.200310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업자명
Text

Distinct3501
Distinct (%)35.0%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2024-05-11T10:06:34.226958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length3
Mean length3.2527
Min length2

Characters and Unicode

Total characters32527
Distinct characters288
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1679 ?
Unique (%)16.8%

Sample

1st row한택례
2nd row안홍엽
3rd row이종규
4th row임순이
5th row이명숙
ValueCountFrequency (%)
정명옥 93
 
0.9%
강인식+오정순 81
 
0.8%
지현자 66
 
0.7%
박옥빈+이길수 59
 
0.6%
황순여+유재복 56
 
0.6%
양기석 55
 
0.5%
신승길+이혜경 51
 
0.5%
이상호 50
 
0.5%
김숙희 48
 
0.5%
최정근 42
 
0.4%
Other values (3498) 9443
94.0%
2024-05-11T10:06:35.967526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 1829
 
5.6%
김 1762
 
5.4%
정 1295
 
4.0%
순 1154
 
3.5%
영 945
 
2.9%
박 833
 
2.6%
자 623
 
1.9%
희 570
 
1.8%
숙 561
 
1.7%
최 538
 
1.7%
Other values (278) 22417
68.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31707
97.5%
Math Symbol 370
 
1.1%
Open Punctuation 172
 
0.5%
Close Punctuation 172
 
0.5%
Uppercase Letter 44
 
0.1%
Space Separator 44
 
0.1%
Decimal Number 16
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1829
 
5.8%
김 1762
 
5.6%
정 1295
 
4.1%
순 1154
 
3.6%
영 945
 
3.0%
박 833
 
2.6%
자 623
 
2.0%
희 570
 
1.8%
숙 561
 
1.8%
최 538
 
1.7%
Other values (271) 21597
68.1%
Math Symbol
ValueCountFrequency (%)
+ 370
100.0%
Open Punctuation
ValueCountFrequency (%)
( 172
100.0%
Close Punctuation
ValueCountFrequency (%)
) 172
100.0%
Uppercase Letter
ValueCountFrequency (%)
O 44
100.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Decimal Number
ValueCountFrequency (%)
1 16
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31709
97.5%
Common 774
 
2.4%
Latin 44
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1829
 
5.8%
김 1762
 
5.6%
정 1295
 
4.1%
순 1154
 
3.6%
영 945
 
3.0%
박 833
 
2.6%
자 623
 
2.0%
희 570
 
1.8%
숙 561
 
1.8%
최 538
 
1.7%
Other values (272) 21599
68.1%
Common
ValueCountFrequency (%)
+ 370
47.8%
( 172
22.2%
) 172
22.2%
44
 
5.7%
1 16
 
2.1%
Latin
ValueCountFrequency (%)
O 44
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31707
97.5%
ASCII 818
 
2.5%
None 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 1829
 
5.8%
김 1762
 
5.6%
정 1295
 
4.1%
순 1154
 
3.6%
영 945
 
3.0%
박 833
 
2.6%
자 623
 
2.0%
희 570
 
1.8%
숙 561
 
1.8%
최 538
 
1.7%
Other values (271) 21597
68.1%
ASCII
ValueCountFrequency (%)
+ 370
45.2%
( 172
21.0%
) 172
21.0%
O 44
 
5.4%
44
 
5.4%
1 16
 
2.0%
None
ValueCountFrequency (%)
㈜ 2
100.0%

사업자등록번호
Text

MISSING 

Distinct56
Distinct (%)96.6%
Missing9942
Missing (%)99.4%
Memory size156.2 KiB
2024-05-11T10:06:36.635096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters696
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

Unique54 ?
Unique (%)93.1%

Sample

1st row416-81-43805
2nd row416-02-63989
3rd row258-87-00139
4th row445-72-00189
5th row416-81-82128
ValueCountFrequency (%)
455-87-00346 2
 
3.4%
135-17-21560 2
 
3.4%
533-55-00117 1
 
1.7%
173-08-01749 1
 
1.7%
580-87-02179 1
 
1.7%
636-82-00426 1
 
1.7%
208-21-13254 1
 
1.7%
416-81-43197 1
 
1.7%
601-86-00961 1
 
1.7%
416-81-92529 1
 
1.7%
Other values (46) 46
79.3%
2024-05-11T10:06:37.841244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 116
16.7%
1 96
13.8%
0 89
12.8%
8 78
11.2%
6 63
9.1%
4 52
7.5%
2 46
 
6.6%
5 44
 
6.3%
7 38
 
5.5%
3 37
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 580
83.3%
Dash Punctuation 116
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 96
16.6%
0 89
15.3%
8 78
13.4%
6 63
10.9%
4 52
9.0%
2 46
7.9%
5 44
7.6%
7 38
 
6.6%
3 37
 
6.4%
9 37
 
6.4%
Dash Punctuation
ValueCountFrequency (%)
- 116
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 696
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 116
16.7%
1 96
13.8%
0 89
12.8%
8 78
11.2%
6 63
9.1%
4 52
7.5%
2 46
 
6.6%
5 44
 
6.3%
7 38
 
5.5%
3 37
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 696
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 116
16.7%
1 96
13.8%
0 89
12.8%
8 78
11.2%
6 63
9.1%
4 52
7.5%
2 46
 
6.6%
5 44
 
6.3%
7 38
 
5.5%
3 37
 
5.3%

전화번호
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9875 
070-7779-2122
 
120
031-676-2356
 
2
031-672-0964
 
1
031-677-2900
 
1

Length

Max length13
Median length4
Mean length4.112
Min length4

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 9875
98.8%
070-7779-2122 120
 
1.2%
031-676-2356 2
 
< 0.1%
031-672-0964 1
 
< 0.1%
031-677-2900 1
 
< 0.1%
031-677-1822 1
 
< 0.1%

Length

2024-05-11T10:06:38.396729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T10:06:38.746674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9875
98.8%
070-7779-2122 120
 
1.2%
031-676-2356 2
 
< 0.1%
031-672-0964 1
 
< 0.1%
031-677-2900 1
 
< 0.1%
031-677-1822 1
 
< 0.1%

관리기관명
Categorical

HIGH CORRELATION 

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전북특별자치도 완주군청
2487 
강원도 원주시청
2254 
전라북도 완주군청
2176 
전라북도 군산시청
485 
전북특별자치도 군산시청
477 
Other values (18)
2121 

Length

Max length17
Median length15
Mean length9.9396
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 화성시청
2nd row전북특별자치도 완주군청
3rd row전북특별자치도 완주군청
4th row전북특별자치도 완주군청
5th row전북특별자치도 완주군청

Common Values

ValueCountFrequency (%)
전북특별자치도 완주군청 2487
24.9%
강원도 원주시청 2254
22.5%
전라북도 완주군청 2176
21.8%
전라북도 군산시청 485
 
4.9%
전북특별자치도 군산시청 477
 
4.8%
농업회사법인 순천로컬푸드㈜ 436
 
4.4%
경기도 화성시청 392
 
3.9%
충청남도 부여군청 238
 
2.4%
충청북도 옥천군청 177
 
1.8%
충청남도 서산시청 150
 
1.5%
Other values (13) 728
 
7.3%

Length

2024-05-11T10:06:39.139328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완주군청 4663
23.3%
전북특별자치도 3016
15.1%
전라북도 2705
13.5%
강원도 2297
11.5%
원주시청 2254
11.3%
군산시청 962
 
4.8%
충청남도 498
 
2.5%
경기도 489
 
2.4%
농업회사법인 436
 
2.2%
순천로컬푸드㈜ 436
 
2.2%
Other values (20) 2228
11.1%

데이터기준일자
Date

Distinct23
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2022-11-24 00:00:00
Maximum2024-04-24 00:00:00
2024-05-11T10:06:39.506529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:40.075964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)

제공기관코드
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4606082.2
Minimum3740000
Maximum5680000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-05-11T10:06:40.434106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3740000
5-th percentile4190000
Q14191000
median4720000
Q34721000
95-th percentile5460000
Maximum5680000
Range1940000
Interquartile range (IQR)530000

Descriptive statistics

Standard deviation324557.85
Coefficient of variation (CV)0.070462886
Kurtosis1.6288711
Mean4606082.2
Median Absolute Deviation (MAD)49000
Skewness0.5907997
Sum4.6060822 × 1010
Variance1.0533779 × 1011
MonotonicityNot monotonic
2024-05-11T10:06:40.961710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
4721000 2487
24.9%
4720000 2176
21.8%
4191000 1152
11.5%
4190000 1102
11.0%
4670000 485
 
4.9%
4671000 477
 
4.8%
4820000 436
 
4.4%
5530000 392
 
3.9%
4570000 238
 
2.4%
4430000 177
 
1.8%
Other values (15) 878
 
8.8%
ValueCountFrequency (%)
3740000 61
 
0.6%
3930000 31
 
0.3%
3940000 13
 
0.1%
4080000 5
 
0.1%
4180000 43
 
0.4%
4181000 132
 
1.3%
4190000 1102
11.0%
4191000 1152
11.5%
4270000 50
 
0.5%
4271000 62
 
0.6%
ValueCountFrequency (%)
5680000 33
 
0.3%
5530000 392
 
3.9%
5460000 120
 
1.2%
4820000 436
 
4.4%
4721000 2487
24.9%
4720000 2176
21.8%
4671000 477
 
4.8%
4670000 485
 
4.9%
4641000 52
 
0.5%
4640000 44
 
0.4%

제공기관명
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
전북특별자치도 완주군
2487 
전라북도 완주군
2176 
강원특별자치도 원주시
1152 
강원도 원주시
1102 
전라북도 군산시
485 
Other values (20)
2598 

Length

Max length11
Median length8
Mean length9.1389
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도 화성시
2nd row전북특별자치도 완주군
3rd row전북특별자치도 완주군
4th row전북특별자치도 완주군
5th row전북특별자치도 완주군

Common Values

ValueCountFrequency (%)
전북특별자치도 완주군 2487
24.9%
전라북도 완주군 2176
21.8%
강원특별자치도 원주시 1152
11.5%
강원도 원주시 1102
11.0%
전라북도 군산시 485
 
4.9%
전북특별자치도 군산시 477
 
4.8%
전라남도 순천시 436
 
4.4%
경기도 화성시 392
 
3.9%
충청남도 부여군 238
 
2.4%
충청북도 옥천군 177
 
1.8%
Other values (15) 878
 
8.8%

Length

2024-05-11T10:06:41.658084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
완주군 4663
23.3%
전북특별자치도 3016
15.1%
전라북도 2705
13.5%
원주시 2254
11.3%
강원특별자치도 1346
 
6.7%
강원도 1195
 
6.0%
군산시 962
 
4.8%
경기도 502
 
2.5%
충청남도 498
 
2.5%
전라남도 436
 
2.2%
Other values (18) 2423
12.1%

Interactions

2024-05-11T10:06:09.058417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:06.938022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:07.937611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:09.456101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:07.227292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:08.299282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:09.881978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:07.574752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T10:06:08.608262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-11T10:06:42.146824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인증취소일자재배면적재배규모사업자등록번호전화번호관리기관명데이터기준일자제공기관코드제공기관명
인증취소일자1.000NaNNaNNaNNaN0.7990.799NaN0.799
재배면적NaN1.0001.0001.000NaN0.3440.3440.4050.240
재배규모NaN1.0001.0001.000NaN0.2690.2690.2690.269
사업자등록번호NaN1.0001.0001.0001.0001.0001.0001.0001.000
전화번호NaNNaNNaN1.0001.0001.0001.0001.0001.000
관리기관명0.7990.3440.2691.0001.0001.0001.0001.0001.000
데이터기준일자0.7990.3440.2691.0001.0001.0001.0001.0001.000
제공기관코드NaN0.4050.2691.0001.0001.0001.0001.0001.000
제공기관명0.7990.2400.2691.0001.0001.0001.0001.0001.000
2024-05-11T10:06:42.725136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리기관명제공기관명전화번호
관리기관명1.0001.0000.988
제공기관명1.0001.0000.988
전화번호0.9880.9881.000
2024-05-11T10:06:43.107852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재배면적재배규모제공기관코드전화번호관리기관명제공기관명
재배면적1.0000.987-0.0370.0000.1210.120
재배규모0.9871.0000.0630.0000.2000.200
제공기관코드-0.0370.0631.0000.9880.9990.999
전화번호0.0000.0000.9881.0000.9880.988
관리기관명0.1210.2000.9990.9881.0001.000
제공기관명0.1200.2000.9990.9881.0001.000

Missing values

2024-05-11T10:06:10.569759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-11T10:06:11.680090image/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.
2024-05-11T10:06:12.335495image/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

로컬푸드인증번호인증유효시작일자인증유효종료일자인증취소일자사업장도로명주소사업장지번주소생산지도로명주소생산지지번주소품목명재배면적재배규모인증부여일자사업자명사업자등록번호전화번호관리기관명데이터기준일자제공기관코드제공기관명
17812023-04-01042023-11-152025-11-14<NA><NA><NA>경기도 화성시 송산면 공룡로487번길 19<NA>포도<NA><NA>2023-11-15한택례<NA><NA>경기도 화성시청2024-01-105530000경기도 화성시
100562017-03-05202017-11-292019-11-28<NA>전북특별자치도 완주군 용진읍 지암로 61<NA>전북특별자치도 완주군 경천면 경가천길 488-11<NA>상추+아욱<NA><NA>2017-11-29안홍엽<NA><NA>전북특별자치도 완주군청2024-01-304721000전북특별자치도 완주군
37862021-03-00632021-04-292023-04-28<NA>전북특별자치도 완주군 용진읍 지암로 61<NA>전북특별자치도 완주군 삼례읍 구와로 99-1<NA>딸기<NA><NA>2021-04-29이종규<NA><NA>전북특별자치도 완주군청2024-01-304721000전북특별자치도 완주군
154072022-03-03492022-08-302024-08-29<NA>전북특별자치도 완주군 용진읍 지암로 61<NA>전북특별자치도 완주군 이서면 은교장동길 24, 103호(은교빌라)<NA>대파<NA><NA>2022-08-30임순이<NA><NA>전북특별자치도 완주군청2024-01-304721000전북특별자치도 완주군
150392021-06-06322021-12-272023-12-26<NA>전북특별자치도 완주군 용진읍 지암로 61<NA>전북특별자치도 완주군 구이면 원백여길 162-3<NA>표고버섯<NA><NA>2021-12-27이명숙<NA><NA>전북특별자치도 완주군청2024-01-304721000전북특별자치도 완주군
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128682021-03-03532021-08-302023-08-29<NA>전라북도 완주군 용진읍 지암로 61<NA>전라북도 완주군 봉동읍 신중길 38-12<NA>열무<NA><NA>2021-08-30최동운<NA><NA>전라북도 완주군청2023-05-194720000전라북도 완주군
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85752022-0201-09792022-08-012023-07-31<NA><NA><NA><NA>강원도 원주시 판부면 서곡리 1343, 1373, 1369-1가지6906.0<NA>2022-08-01황순여+유재복<NA><NA>강원도 원주시청2023-05-234190000강원도 원주시
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47932022-0203-04432022-06-082023-06-07<NA><NA><NA><NA>강원도 원주시 관설동 374-4쑥갓2454.0<NA>2022-06-08한남섭<NA><NA>강원도 원주시청2023-05-234191000강원특별자치도 원주시
95562023-0203-01892023-05-102024-05-09<NA><NA><NA><NA>강원도 원주시 판부면 서곡리 1374-1시금치4249.0<NA>2023-05-10황순여+유재복<NA><NA>강원도 원주시청2023-05-234190000강원도 원주시