Overview

Dataset statistics

Number of variables12
Number of observations109
Missing cells154
Missing cells (%)11.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.0 KiB
Average record size in memory103.2 B

Variable types

DateTime1
Categorical1
Text4
Unsupported1
Numeric5

Alerts

집계년월 has constant value ""Constant
소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
대표자명 has 109 (100.0%) missing valuesMissing
소재지우편번호 has 6 (5.5%) missing valuesMissing
소재지도로명주소 has 39 (35.8%) missing valuesMissing
농원명 has unique valuesUnique
대표자명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-10 22:56:43.892620
Analysis finished2023-12-10 22:56:47.712610
Duration3.82 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

집계년월
Date

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
Minimum2022-07-01 00:00:00
Maximum2022-07-01 00:00:00
2023-12-11T07:56:47.757573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:47.841360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

시군명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)11.9%
Missing0
Missing (%)0.0%
Memory size1004.0 B
용인시
25 
연천군
14 
포천시
14 
여주시
12 
안성시
6 
Other values (8)
38 

Length

Max length4
Median length3
Mean length3.0458716
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
용인시 25
22.9%
연천군 14
12.8%
포천시 14
12.8%
여주시 12
11.0%
안성시 6
 
5.5%
양평군 6
 
5.5%
파주시 6
 
5.5%
김포시 5
 
4.6%
남양주시 5
 
4.6%
양주시 5
 
4.6%
Other values (3) 11
10.1%

Length

2023-12-11T07:56:47.945108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
용인시 25
22.9%
연천군 14
12.8%
포천시 14
12.8%
여주시 12
11.0%
안성시 6
 
5.5%
양평군 6
 
5.5%
파주시 6
 
5.5%
김포시 5
 
4.6%
남양주시 5
 
4.6%
양주시 5
 
4.6%
Other values (3) 11
10.1%

농원명
Text

UNIQUE 

Distinct109
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-11T07:56:48.194504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length7.0275229
Min length2

Characters and Unicode

Total characters766
Distinct characters190
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

Unique109 ?
Unique (%)100.0%

Sample

1st row김포관광농원
2nd row문수산
3rd row후평농원(아리수)
4th row물고기(진산농원)
5th row힐링농원
ValueCountFrequency (%)
관광농원 28
 
19.4%
김포관광농원 1
 
0.7%
캐리비안캠프 1
 
0.7%
용인축산업협동조합 1
 
0.7%
정광산 1
 
0.7%
덕송관광농원 1
 
0.7%
독성 1
 
0.7%
밤골 1
 
0.7%
소풍 1
 
0.7%
한터 1
 
0.7%
Other values (107) 107
74.3%
2023-12-11T07:56:48.534468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 85
 
11.1%
원 85
 
11.1%
광 69
 
9.0%
관 67
 
8.7%
35
 
4.6%
산 13
 
1.7%
주 12
 
1.6%
리 9
 
1.2%
장 8
 
1.0%
수 8
 
1.0%
Other values (180) 375
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 721
94.1%
Space Separator 35
 
4.6%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Uppercase Letter 3
 
0.4%
Other Symbol 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 85
 
11.8%
원 85
 
11.8%
광 69
 
9.6%
관 67
 
9.3%
산 13
 
1.8%
주 12
 
1.7%
리 9
 
1.2%
장 8
 
1.1%
수 8
 
1.1%
양 8
 
1.1%
Other values (173) 357
49.5%
Uppercase Letter
ValueCountFrequency (%)
Z 1
33.3%
M 1
33.3%
D 1
33.3%
Space Separator
ValueCountFrequency (%)
35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 722
94.3%
Common 41
 
5.4%
Latin 3
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 85
 
11.8%
원 85
 
11.8%
광 69
 
9.6%
관 67
 
9.3%
산 13
 
1.8%
주 12
 
1.7%
리 9
 
1.2%
장 8
 
1.1%
수 8
 
1.1%
양 8
 
1.1%
Other values (174) 358
49.6%
Common
ValueCountFrequency (%)
35
85.4%
( 3
 
7.3%
) 3
 
7.3%
Latin
ValueCountFrequency (%)
Z 1
33.3%
M 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 721
94.1%
ASCII 44
 
5.7%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 85
 
11.8%
원 85
 
11.8%
광 69
 
9.6%
관 67
 
9.3%
산 13
 
1.8%
주 12
 
1.7%
리 9
 
1.2%
장 8
 
1.1%
수 8
 
1.1%
양 8
 
1.1%
Other values (173) 357
49.5%
ASCII
ValueCountFrequency (%)
35
79.5%
( 3
 
6.8%
) 3
 
6.8%
Z 1
 
2.3%
M 1
 
2.3%
D 1
 
2.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

대표자명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing109
Missing (%)100.0%
Memory size1.1 KiB

승인연도
Real number (ℝ)

Distinct21
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2013.2202
Minimum1988
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:56:48.684399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1988
5-th percentile1995.8
Q12013
median2015
Q32016
95-th percentile2019
Maximum2021
Range33
Interquartile range (IQR)3

Descriptive statistics

Standard deviation6.1799524
Coefficient of variation (CV)0.0030696853
Kurtosis6.1625547
Mean2013.2202
Median Absolute Deviation (MAD)2
Skewness-2.4309699
Sum219441
Variance38.191811
MonotonicityNot monotonic
2023-12-11T07:56:48.840441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
2016 25
22.9%
2014 14
12.8%
2015 14
12.8%
2013 10
 
9.2%
2017 9
 
8.3%
2018 5
 
4.6%
2019 5
 
4.6%
2009 4
 
3.7%
2012 4
 
3.7%
1995 3
 
2.8%
Other values (11) 16
14.7%
ValueCountFrequency (%)
1988 1
 
0.9%
1990 1
 
0.9%
1991 1
 
0.9%
1995 3
2.8%
1997 1
 
0.9%
2004 2
1.8%
2007 1
 
0.9%
2008 3
2.8%
2009 4
3.7%
2010 1
 
0.9%
ValueCountFrequency (%)
2021 1
 
0.9%
2020 2
 
1.8%
2019 5
 
4.6%
2018 5
 
4.6%
2017 9
 
8.3%
2016 25
22.9%
2015 14
12.8%
2014 14
12.8%
2013 10
 
9.2%
2012 4
 
3.7%

농원면적
Real number (ℝ)

Distinct107
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12966.624
Minimum3733
Maximum99900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:56:48.962015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3733
5-th percentile4821.4
Q16842
median8299
Q314432
95-th percentile29963
Maximum99900
Range96167
Interquartile range (IQR)7590

Descriptive statistics

Standard deviation12681.769
Coefficient of variation (CV)0.97803166
Kurtosis20.928082
Mean12966.624
Median Absolute Deviation (MAD)2363
Skewness3.8343562
Sum1413362
Variance1.6082726 × 108
MonotonicityNot monotonic
2023-12-11T07:56:49.080651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29963 2
 
1.8%
7450 2
 
1.8%
29900 1
 
0.9%
32936 1
 
0.9%
7498 1
 
0.9%
11018 1
 
0.9%
8869 1
 
0.9%
4086 1
 
0.9%
5678 1
 
0.9%
29613 1
 
0.9%
Other values (97) 97
89.0%
ValueCountFrequency (%)
3733 1
0.9%
4086 1
0.9%
4148 1
0.9%
4195 1
0.9%
4742 1
0.9%
4793 1
0.9%
4864 1
0.9%
4937 1
0.9%
4950 1
0.9%
4958 1
0.9%
ValueCountFrequency (%)
99900 1
0.9%
57370 1
0.9%
42496 1
0.9%
41930 1
0.9%
32936 1
0.9%
29963 2
1.8%
29900 1
0.9%
29613 1
0.9%
29483 1
0.9%
29449 1
0.9%

주요시설정보
Text

Distinct71
Distinct (%)65.1%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-11T07:56:49.257992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length25
Mean length16.550459
Min length4

Characters and Unicode

Total characters1804
Distinct characters90
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

Unique56 ?
Unique (%)51.4%

Sample

1st row야영장, 영농체험시설, 체육시설 등
2nd row숙박, 농업체험
3rd row편의시설(숙박), 휴양시설(낚시터)
4th row낚시체험장, 식당
5th row체험시설, 야영장, 편의시설 등
ValueCountFrequency (%)
등 53
15.7%
영농체험시설 52
15.4%
야영장 39
 
11.5%
영농체험 19
 
5.6%
편의시설 14
 
4.1%
영농체험장 12
 
3.6%
수영장 11
 
3.3%
식당 9
 
2.7%
음식점 9
 
2.7%
글랭핑장 7
 
2.1%
Other values (62) 113
33.4%
2023-12-11T07:56:49.568715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
230
12.7%
, 208
11.5%
영 169
 
9.4%
시 123
 
6.8%
장 121
 
6.7%
설 120
 
6.7%
체 117
 
6.5%
험 111
 
6.2%
농 107
 
5.9%
야 60
 
3.3%
Other values (80) 438
24.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1358
75.3%
Space Separator 230
 
12.7%
Other Punctuation 208
 
11.5%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
영 169
12.4%
시 123
 
9.1%
장 121
 
8.9%
설 120
 
8.8%
체 117
 
8.6%
험 111
 
8.2%
농 107
 
7.9%
야 60
 
4.4%
등 53
 
3.9%
매 26
 
1.9%
Other values (76) 351
25.8%
Space Separator
ValueCountFrequency (%)
230
100.0%
Other Punctuation
ValueCountFrequency (%)
, 208
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1358
75.3%
Common 446
 
24.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
영 169
12.4%
시 123
 
9.1%
장 121
 
8.9%
설 120
 
8.8%
체 117
 
8.6%
험 111
 
8.2%
농 107
 
7.9%
야 60
 
4.4%
등 53
 
3.9%
매 26
 
1.9%
Other values (76) 351
25.8%
Common
ValueCountFrequency (%)
230
51.6%
, 208
46.6%
( 4
 
0.9%
) 4
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1358
75.3%
ASCII 446
 
24.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
230
51.6%
, 208
46.6%
( 4
 
0.9%
) 4
 
0.9%
Hangul
ValueCountFrequency (%)
영 169
12.4%
시 123
 
9.1%
장 121
 
8.9%
설 120
 
8.8%
체 117
 
8.6%
험 111
 
8.2%
농 107
 
7.9%
야 60
 
4.4%
등 53
 
3.9%
매 26
 
1.9%
Other values (76) 351
25.8%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct86
Distinct (%)83.5%
Missing6
Missing (%)5.5%
Infinite0
Infinite (%)0.0%
Mean13663.408
Minimum10001
Maximum18595
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:56:49.691874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10001
5-th percentile10801.3
Q111101.5
median12571
Q317132
95-th percentile17536.6
Maximum18595
Range8594
Interquartile range (IQR)6030.5

Descriptive statistics

Standard deviation2897.432
Coefficient of variation (CV)0.21205779
Kurtosis-1.5718181
Mean13663.408
Median Absolute Deviation (MAD)1568
Skewness0.42673586
Sum1407331
Variance8395112.2
MonotonicityNot monotonic
2023-12-11T07:56:49.805730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17132 3
 
2.8%
17170 3
 
2.8%
11121 2
 
1.8%
12655 2
 
1.8%
17166 2
 
1.8%
11125 2
 
1.8%
11103 2
 
1.8%
11046 2
 
1.8%
12641 2
 
1.8%
17528 2
 
1.8%
Other values (76) 81
74.3%
(Missing) 6
 
5.5%
ValueCountFrequency (%)
10001 1
0.9%
10007 1
0.9%
10012 1
0.9%
10020 1
0.9%
10103 1
0.9%
10801 1
0.9%
10804 1
0.9%
10806 1
0.9%
10809 1
0.9%
10826 1
0.9%
ValueCountFrequency (%)
18595 1
0.9%
18558 1
0.9%
18554 1
0.9%
18551 1
0.9%
18278 1
0.9%
17537 1
0.9%
17533 1
0.9%
17528 2
1.8%
17511 1
0.9%
17507 1
0.9%

소재지지번주소
Text

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size1004.0 B
2023-12-11T07:56:50.108127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length23.816514
Min length17

Characters and Unicode

Total characters2596
Distinct characters145
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

Unique107 ?
Unique (%)98.2%

Sample

1st row경기도 김포시 월곶면 용강리 315-156번지
2nd row경기도 김포시 월곶면 포내리 111-16번지
3rd row경기도 김포시 하성면 후평리 42번지 외 2필지
4th row경기도 김포시 감정동 299번지
5th row경기도 김포시 하성면 석탄리 242-10번지
ValueCountFrequency (%)
경기도 109
 
17.9%
용인시 25
 
4.1%
처인구 23
 
3.8%
외 19
 
3.1%
연천군 14
 
2.3%
포천시 14
 
2.3%
여주시 12
 
2.0%
원삼면 7
 
1.2%
이동읍 6
 
1.0%
양평군 6
 
1.0%
Other values (280) 373
61.3%
2023-12-11T07:56:50.510804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
499
19.2%
도 115
 
4.4%
기 111
 
4.3%
지 110
 
4.2%
경 109
 
4.2%
리 99
 
3.8%
시 89
 
3.4%
번 87
 
3.4%
1 80
 
3.1%
면 75
 
2.9%
Other values (135) 1222
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1624
62.6%
Space Separator 499
 
19.2%
Decimal Number 411
 
15.8%
Dash Punctuation 62
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 115
 
7.1%
기 111
 
6.8%
지 110
 
6.8%
경 109
 
6.7%
리 99
 
6.1%
시 89
 
5.5%
번 87
 
5.4%
면 75
 
4.6%
인 49
 
3.0%
천 42
 
2.6%
Other values (123) 738
45.4%
Decimal Number
ValueCountFrequency (%)
1 80
19.5%
2 59
14.4%
3 40
9.7%
4 39
9.5%
5 38
9.2%
6 37
9.0%
8 35
8.5%
7 29
 
7.1%
0 28
 
6.8%
9 26
 
6.3%
Space Separator
ValueCountFrequency (%)
499
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1624
62.6%
Common 972
37.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 115
 
7.1%
기 111
 
6.8%
지 110
 
6.8%
경 109
 
6.7%
리 99
 
6.1%
시 89
 
5.5%
번 87
 
5.4%
면 75
 
4.6%
인 49
 
3.0%
천 42
 
2.6%
Other values (123) 738
45.4%
Common
ValueCountFrequency (%)
499
51.3%
1 80
 
8.2%
- 62
 
6.4%
2 59
 
6.1%
3 40
 
4.1%
4 39
 
4.0%
5 38
 
3.9%
6 37
 
3.8%
8 35
 
3.6%
7 29
 
3.0%
Other values (2) 54
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1624
62.6%
ASCII 972
37.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
499
51.3%
1 80
 
8.2%
- 62
 
6.4%
2 59
 
6.1%
3 40
 
4.1%
4 39
 
4.0%
5 38
 
3.9%
6 37
 
3.8%
8 35
 
3.6%
7 29
 
3.0%
Other values (2) 54
 
5.6%
Hangul
ValueCountFrequency (%)
도 115
 
7.1%
기 111
 
6.8%
지 110
 
6.8%
경 109
 
6.7%
리 99
 
6.1%
시 89
 
5.5%
번 87
 
5.4%
면 75
 
4.6%
인 49
 
3.0%
천 42
 
2.6%
Other values (123) 738
45.4%

소재지도로명주소
Text

MISSING 

Distinct69
Distinct (%)98.6%
Missing39
Missing (%)35.8%
Memory size1004.0 B
2023-12-11T07:56:50.745378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length22.742857
Min length16

Characters and Unicode

Total characters1592
Distinct characters142
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

Unique68 ?
Unique (%)97.1%

Sample

1st row경기도 김포시 월곶면 용강로 325
2nd row경기도 김포시 월곶면 김포대학로 125
3rd row경기도 김포시 중봉로33번길 170
4th row경기도 김포시 하성면 오정동로 121-15
5th row경기도 남양주시 수동면 철마산로103번길 37
ValueCountFrequency (%)
경기도 70
 
19.4%
처인구 12
 
3.3%
용인시 12
 
3.3%
여주시 11
 
3.1%
포천시 10
 
2.8%
연천군 7
 
1.9%
파주시 6
 
1.7%
원삼면 5
 
1.4%
화성시 5
 
1.4%
안성시 5
 
1.4%
Other values (184) 217
60.3%
2023-12-11T07:56:51.085728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
290
 
18.2%
경 72
 
4.5%
기 71
 
4.5%
도 71
 
4.5%
1 65
 
4.1%
시 61
 
3.8%
면 51
 
3.2%
로 51
 
3.2%
2 46
 
2.9%
3 42
 
2.6%
Other values (132) 772
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 963
60.5%
Decimal Number 308
 
19.3%
Space Separator 290
 
18.2%
Dash Punctuation 31
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 72
 
7.5%
기 71
 
7.4%
도 71
 
7.4%
시 61
 
6.3%
면 51
 
5.3%
로 51
 
5.3%
길 40
 
4.2%
인 25
 
2.6%
천 24
 
2.5%
주 21
 
2.2%
Other values (120) 476
49.4%
Decimal Number
ValueCountFrequency (%)
1 65
21.1%
2 46
14.9%
3 42
13.6%
4 34
11.0%
5 27
8.8%
0 22
 
7.1%
6 22
 
7.1%
9 20
 
6.5%
7 19
 
6.2%
8 11
 
3.6%
Space Separator
ValueCountFrequency (%)
290
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 963
60.5%
Common 629
39.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 72
 
7.5%
기 71
 
7.4%
도 71
 
7.4%
시 61
 
6.3%
면 51
 
5.3%
로 51
 
5.3%
길 40
 
4.2%
인 25
 
2.6%
천 24
 
2.5%
주 21
 
2.2%
Other values (120) 476
49.4%
Common
ValueCountFrequency (%)
290
46.1%
1 65
 
10.3%
2 46
 
7.3%
3 42
 
6.7%
4 34
 
5.4%
- 31
 
4.9%
5 27
 
4.3%
0 22
 
3.5%
6 22
 
3.5%
9 20
 
3.2%
Other values (2) 30
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 963
60.5%
ASCII 629
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
290
46.1%
1 65
 
10.3%
2 46
 
7.3%
3 42
 
6.7%
4 34
 
5.4%
- 31
 
4.9%
5 27
 
4.3%
0 22
 
3.5%
6 22
 
3.5%
9 20
 
3.2%
Other values (2) 30
 
4.8%
Hangul
ValueCountFrequency (%)
경 72
 
7.5%
기 71
 
7.4%
도 71
 
7.4%
시 61
 
6.3%
면 51
 
5.3%
로 51
 
5.3%
길 40
 
4.2%
인 25
 
2.6%
천 24
 
2.5%
주 21
 
2.2%
Other values (120) 476
49.4%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.543739
Minimum36.959281
Maximum38.158349
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:56:51.213492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.959281
5-th percentile37.104724
Q137.207186
median37.44137
Q337.891214
95-th percentile38.089539
Maximum38.158349
Range1.199068
Interquartile range (IQR)0.68402861

Descriptive statistics

Standard deviation0.37055276
Coefficient of variation (CV)0.0098698951
Kurtosis-1.5490816
Mean37.543739
Median Absolute Deviation (MAD)0.30916981
Skewness0.22059429
Sum4092.2675
Variance0.13730935
MonotonicityNot monotonic
2023-12-11T07:56:51.365094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.93860335 2
 
1.8%
37.74722925 1
 
0.9%
37.28446342 1
 
0.9%
37.31567971 1
 
0.9%
37.12345645 1
 
0.9%
37.16586668 1
 
0.9%
37.18694682 1
 
0.9%
37.13364936 1
 
0.9%
37.2715475 1
 
0.9%
37.16339725 1
 
0.9%
Other values (98) 98
89.9%
ValueCountFrequency (%)
36.95928052 1
0.9%
37.06388307 1
0.9%
37.0669982747 1
0.9%
37.08368708 1
0.9%
37.09063031 1
0.9%
37.10159524 1
0.9%
37.10941759 1
0.9%
37.11101654 1
0.9%
37.1124029 1
0.9%
37.11536978 1
0.9%
ValueCountFrequency (%)
38.15834851 1
0.9%
38.15379567 1
0.9%
38.13471582 1
0.9%
38.13129935 1
0.9%
38.10489527 1
0.9%
38.09014039 1
0.9%
38.08863587 1
0.9%
38.07617341 1
0.9%
38.06302686 1
0.9%
38.0620067 1
0.9%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.1867
Minimum126.54625
Maximum127.74468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-11T07:56:51.509145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54625
5-th percentile126.62673
Q1126.99505
median127.24824
Q3127.36635
95-th percentile127.58593
Maximum127.74468
Range1.1984293
Interquartile range (IQR)0.3713043

Descriptive statistics

Standard deviation0.28835076
Coefficient of variation (CV)0.0022671455
Kurtosis-0.33293853
Mean127.1867
Median Absolute Deviation (MAD)0.1615703
Skewness-0.47583335
Sum13863.351
Variance0.083146163
MonotonicityNot monotonic
2023-12-11T07:56:51.634592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.2767395 2
 
1.8%
126.5585387 1
 
0.9%
127.2086549 1
 
0.9%
127.2653936 1
 
0.9%
127.3515302 1
 
0.9%
127.3267867 1
 
0.9%
127.3348051 1
 
0.9%
127.2055918 1
 
0.9%
127.2654546 1
 
0.9%
127.2482374 1
 
0.9%
Other values (98) 98
89.9%
ValueCountFrequency (%)
126.5462512 1
0.9%
126.5490118 1
0.9%
126.5585387 1
0.9%
126.5616861 1
0.9%
126.5925477 1
0.9%
126.6103513 1
0.9%
126.6513078 1
0.9%
126.6544951 1
0.9%
126.6905589 1
0.9%
126.6914026 1
0.9%
ValueCountFrequency (%)
127.7446805 1
0.9%
127.710906 1
0.9%
127.7108517 1
0.9%
127.6847459 1
0.9%
127.6192717 1
0.9%
127.588783 1
0.9%
127.5816442 1
0.9%
127.5515346 1
0.9%
127.5498097 1
0.9%
127.5418144 1
0.9%

Interactions

2023-12-11T07:56:46.619776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:44.482365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:44.980857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.500308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.059832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.754604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:44.572392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.104890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.639260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.205983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.841916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:44.656452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.202499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.738601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.309639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.914726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:44.773769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.285232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.840666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.403166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:47.011082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:44.869322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.373763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:45.947591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:56:46.508586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:56:51.722837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명승인연도농원면적주요시설정보소재지우편번호소재지도로명주소WGS84위도WGS84경도
시군명1.0000.5460.5850.9921.0001.0000.8760.848
승인연도0.5461.0000.6160.9720.3021.0000.3610.379
농원면적0.5850.6161.0000.8940.0001.0000.0000.129
주요시설정보0.9920.9720.8941.0000.9931.0000.9430.935
소재지우편번호1.0000.3020.0000.9931.0001.0000.8130.807
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.000
WGS84위도0.8760.3610.0000.9430.8131.0001.0000.677
WGS84경도0.8480.3790.1290.9350.8071.0000.6771.000
2023-12-11T07:56:51.835665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
승인연도농원면적소재지우편번호WGS84위도WGS84경도시군명
승인연도1.000-0.236-0.1020.042-0.2670.302
농원면적-0.2361.000-0.0050.004-0.1280.310
소재지우편번호-0.102-0.0051.000-0.8980.3730.968
WGS84위도0.0420.004-0.8981.000-0.2780.610
WGS84경도-0.267-0.1280.373-0.2781.0000.559
시군명0.3020.3100.9680.6100.5591.000

Missing values

2023-12-11T07:56:47.147060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:56:47.558359image/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.
2023-12-11T07:56:47.666178image/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

집계년월시군명농원명대표자명승인연도농원면적주요시설정보소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02022-07김포시김포관광농원<NA>201629900야영장, 영농체험시설, 체육시설 등10001경기도 김포시 월곶면 용강리 315-156번지경기도 김포시 월곶면 용강로 32537.747229126.558539
12022-07김포시문수산<NA>20107405숙박, 농업체험10020경기도 김포시 월곶면 포내리 111-16번지경기도 김포시 월곶면 김포대학로 12537.729868126.549012
22022-07김포시후평농원(아리수)<NA>200913141편의시설(숙박), 휴양시설(낚시터)10007경기도 김포시 하성면 후평리 42번지 외 2필지<NA>37.749173126.651308
32022-07김포시물고기(진산농원)<NA>199711648낚시체험장, 식당10103경기도 김포시 감정동 299번지경기도 김포시 중봉로33번길 17037.626717126.690559
42022-07김포시힐링농원<NA>20146930체험시설, 야영장, 편의시설 등10012경기도 김포시 하성면 석탄리 242-10번지경기도 김포시 하성면 오정동로 121-1537.725199126.654495
52022-07남양주시남양주휴림<NA>20155517영농체험시설,야영장,주차장12028경기도 남양주시 수동면 지둔리 369-12번지 외 3필지<NA>37.71416127.299683
62022-07남양주시구암농원<NA>20146075영농체험시설, 판매장12192경기도 남양주시 화도읍 구암리 8-2번지 일원<NA>37.673781127.37507
72022-07남양주시몸에좋은산야초농원<NA>20087490영농체험시설, 농산물 판매장12027경기도 남양주시 수동면 수산리 160-1번지경기도 남양주시 수동면 철마산로103번길 3737.725687127.283406
82022-07남양주시남양주관광농원<NA>20078854영농체험시설, 야외예식장12192경기도 남양주시 화도읍 구암리 산94-1번지 일원<NA>37.664087127.366351
92022-07남양주시광릉숲 관광농원<NA>20185485영농체험시설12001경기도 남양주시 진접읍 부평리266번지<NA>37.75054127.192449
집계년월시군명농원명대표자명승인연도농원면적주요시설정보소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
992022-07포천시청우관광농원<NA>20125079영농체험시설, 야영장, 글랭핑장, 눈썰매장, 수영장 등<NA>경기도 포천시 일동면 화대리 산181<NA>37.954657127.360838
1002022-07포천시벚골관광농원<NA>20096850영농체험시설,숙박시설 등11101경기도 포천시 관인면 사정리 312번지경기도 포천시 관인면 숯골길 32738.131299127.256346
1012022-07포천시자일랜드관광농원<NA>20138678영농체험시설,야영장,편의시설 등11102경기도 포천시 영북면 자일리 10<NA>38.104895127.308838
1022022-07포천시우둠지관광농원<NA>200929449영농체험시설,식당,소매점,찜질방,숙박시설 등11103경기도 포천시 영북면 산정리 456-11번지경기도 포천시 영북면 산정호수로 44638.062007127.314448
1032022-07포천시청담 관광농원<NA>201225401영농체험시설,야영장,편의시설 등11125경기도 포천시 화현면 명덕리 10-14<NA>37.885863127.284604
1042022-07화성시화수관광농원<NA>199518150영농체험시설, 음식점, 축구장, 족구장 등18558경기도 화성시 우정읍 화수리 847-6번지경기도 화성시 우정읍 쌍봉로 39937.109418126.801701
1052022-07화성시은수포농원<NA>200915021영농체험시설, 숙박시설, 음식점, 부대시설 등18554경기도 화성시 서신면 전곡리 80-12번지경기도 화성시 서신면 은수포길 19437.199824126.691403
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1072022-07화성시글램핑코리아 송산점<NA>20204950영농체험시설, 농작물판매, 야영장 등18551경기도 화성시 송산면 사강리 337-1번지경기도 화성시 송산면 송산포도로 19437.21629126.727455
1082022-07화성시농업회사법인 (주)더포레<NA>20207568영농체험, 전시장, 음식점, 소매점, 주차장 등18595경기도 화성시 향남읍 제암리 334-6번지경기도 화성시 향남읍 두렁바위길 49-1337.128128126.895069