Overview

Dataset statistics

Number of variables12
Number of observations129
Missing cells203
Missing cells (%)13.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.7 KiB
Average record size in memory101.0 B

Variable types

Numeric4
Categorical2
Text6

Dataset

Description농촌교육농장(농촌에듀팜) 현황
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=TDPOL8GZ5H65S8GX55NQ15138006&infSeq=1

Alerts

조성년도 is highly overall correlated with 사업구분명High correlation
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
사업구분명 is highly overall correlated with 조성년도High correlation
전화번호 has 92 (71.3%) missing valuesMissing
홈페이지주소 has 58 (45.0%) missing valuesMissing
소재지우편번호 has 6 (4.7%) missing valuesMissing
소재지지번주소 has 5 (3.9%) missing valuesMissing
소재지도로명주소 has 17 (13.2%) missing valuesMissing
WGS84위도 has 12 (9.3%) missing valuesMissing
WGS84경도 has 12 (9.3%) missing valuesMissing

Reproduction

Analysis started2024-03-12 23:07:22.986218
Analysis finished2024-03-12 23:07:25.115947
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조성년도
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)11.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2014.5659
Minimum2007
Maximum2021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-13T08:07:25.155652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile2008
Q12011
median2015
Q32018
95-th percentile2021
Maximum2021
Range14
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.9564918
Coefficient of variation (CV)0.0019639426
Kurtosis-1.0885623
Mean2014.5659
Median Absolute Deviation (MAD)3
Skewness-0.0043551009
Sum259879
Variance15.653828
MonotonicityNot monotonic
2024-03-13T08:07:25.237128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
2015 15
11.6%
2020 13
10.1%
2012 12
9.3%
2010 11
8.5%
2011 10
 
7.8%
2017 10
 
7.8%
2016 9
 
7.0%
2013 9
 
7.0%
2021 8
 
6.2%
2019 7
 
5.4%
Other values (5) 25
19.4%
ValueCountFrequency (%)
2007 2
 
1.6%
2008 7
5.4%
2009 4
 
3.1%
2010 11
8.5%
2011 10
7.8%
2012 12
9.3%
2013 9
7.0%
2014 6
 
4.7%
2015 15
11.6%
2016 9
7.0%
ValueCountFrequency (%)
2021 8
6.2%
2020 13
10.1%
2019 7
5.4%
2018 6
 
4.7%
2017 10
7.8%
2016 9
7.0%
2015 15
11.6%
2014 6
 
4.7%
2013 9
7.0%
2012 12
9.3%

시군명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
화성시
12 
양주시
12 
남양주시
12 
양평군
11 
광주시
9 
Other values (14)
73 

Length

Max length4
Median length3
Mean length3.0930233
Min length3

Unique

Unique1 ?
Unique (%)0.8%

Sample

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

Common Values

ValueCountFrequency (%)
화성시 12
 
9.3%
양주시 12
 
9.3%
남양주시 12
 
9.3%
양평군 11
 
8.5%
광주시 9
 
7.0%
용인시 9
 
7.0%
이천시 9
 
7.0%
고양시 7
 
5.4%
평택시 7
 
5.4%
김포시 7
 
5.4%
Other values (9) 34
26.4%

Length

2024-03-13T08:07:25.348048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 12
 
9.3%
남양주시 12
 
9.3%
양주시 12
 
9.3%
양평군 11
 
8.5%
광주시 9
 
7.0%
용인시 9
 
7.0%
이천시 9
 
7.0%
평택시 7
 
5.4%
김포시 7
 
5.4%
고양시 7
 
5.4%
Other values (9) 34
26.4%

사업구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
도비
80 
국비
49 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국비
2nd row도비
3rd row도비
4th row국비
5th row도비

Common Values

ValueCountFrequency (%)
도비 80
62.0%
국비 49
38.0%

Length

2024-03-13T08:07:25.453097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:07:25.524503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
도비 80
62.0%
국비 49
38.0%

농장명
Text

Distinct128
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2024-03-13T08:07:25.733286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length4.9379845
Min length2

Characters and Unicode

Total characters637
Distinct characters229
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

Unique127 ?
Unique (%)98.4%

Sample

1st row가평커피농장
2nd row비타민
3rd row양지농원
4th row고성리산양목장
5th row연인산풍경요리사의농원
ValueCountFrequency (%)
꿈팜 2
 
1.5%
아이비랜드 1
 
0.7%
들꽃마을 1
 
0.7%
대자연농원 1
 
0.7%
마실 1
 
0.7%
비틀즈자연학교 1
 
0.7%
꾸메숲버섯나라 1
 
0.7%
돼지보러오면돼지 1
 
0.7%
새미공방 1
 
0.7%
청암관광농원 1
 
0.7%
Other values (124) 124
91.9%
2024-03-13T08:07:26.053550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 50
 
7.8%
원 42
 
6.6%
장 26
 
4.1%
팜 11
 
1.7%
산 11
 
1.7%
리 11
 
1.7%
아 10
 
1.6%
마 10
 
1.6%
연 10
 
1.6%
이 9
 
1.4%
Other values (219) 447
70.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 615
96.5%
Lowercase Letter 7
 
1.1%
Space Separator 6
 
0.9%
Decimal Number 6
 
0.9%
Other Punctuation 1
 
0.2%
Uppercase Letter 1
 
0.2%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 50
 
8.1%
원 42
 
6.8%
장 26
 
4.2%
팜 11
 
1.8%
산 11
 
1.8%
리 11
 
1.8%
아 10
 
1.6%
마 10
 
1.6%
연 10
 
1.6%
이 9
 
1.5%
Other values (205) 425
69.1%
Decimal Number
ValueCountFrequency (%)
5 1
16.7%
6 1
16.7%
3 1
16.7%
9 1
16.7%
0 1
16.7%
2 1
16.7%
Lowercase Letter
ValueCountFrequency (%)
a 2
28.6%
r 2
28.6%
m 2
28.6%
f 1
14.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
F 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 615
96.5%
Common 14
 
2.2%
Latin 8
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 50
 
8.1%
원 42
 
6.8%
장 26
 
4.2%
팜 11
 
1.8%
산 11
 
1.8%
리 11
 
1.8%
아 10
 
1.6%
마 10
 
1.6%
연 10
 
1.6%
이 9
 
1.5%
Other values (205) 425
69.1%
Common
ValueCountFrequency (%)
6
42.9%
, 1
 
7.1%
5 1
 
7.1%
6 1
 
7.1%
3 1
 
7.1%
- 1
 
7.1%
9 1
 
7.1%
0 1
 
7.1%
2 1
 
7.1%
Latin
ValueCountFrequency (%)
a 2
25.0%
r 2
25.0%
m 2
25.0%
f 1
12.5%
F 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 615
96.5%
ASCII 22
 
3.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 50
 
8.1%
원 42
 
6.8%
장 26
 
4.2%
팜 11
 
1.8%
산 11
 
1.8%
리 11
 
1.8%
아 10
 
1.6%
마 10
 
1.6%
연 10
 
1.6%
이 9
 
1.5%
Other values (205) 425
69.1%
ASCII
ValueCountFrequency (%)
6
27.3%
a 2
 
9.1%
r 2
 
9.1%
m 2
 
9.1%
f 1
 
4.5%
, 1
 
4.5%
5 1
 
4.5%
6 1
 
4.5%
3 1
 
4.5%
F 1
 
4.5%
Other values (4) 4
18.2%

주제
Text

Distinct115
Distinct (%)89.8%
Missing1
Missing (%)0.8%
Memory size1.1 KiB
2024-03-13T08:07:26.283547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12.5
Mean length6.5
Min length1

Characters and Unicode

Total characters832
Distinct characters202
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

Unique107 ?
Unique (%)83.6%

Sample

1st row커피나무 한살이
2nd row옥수수체험,가공
3rd row오색떡만들기
4th row산양사육
5th row치즈가공 등
ValueCountFrequency (%)
포도 7
 
3.3%
체험 7
 
3.3%
블루베리 5
 
2.4%
딸기 5
 
2.4%
허브체험 4
 
1.9%
및 4
 
1.9%
사과 3
 
1.4%
야생화 3
 
1.4%
콩 3
 
1.4%
허브 3
 
1.4%
Other values (150) 167
79.1%
2024-03-13T08:07:26.624801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
83
 
10.0%
체 48
 
5.8%
험 48
 
5.8%
, 34
 
4.1%
기 27
 
3.2%
농 14
 
1.7%
도 14
 
1.7%
과 12
 
1.4%
생 12
 
1.4%
육 11
 
1.3%
Other values (192) 529
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 709
85.2%
Space Separator 83
 
10.0%
Other Punctuation 36
 
4.3%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
체 48
 
6.8%
험 48
 
6.8%
기 27
 
3.8%
농 14
 
2.0%
도 14
 
2.0%
과 12
 
1.7%
생 12
 
1.7%
육 11
 
1.6%
이 11
 
1.6%
딸 11
 
1.6%
Other values (187) 501
70.7%
Other Punctuation
ValueCountFrequency (%)
, 34
94.4%
! 2
 
5.6%
Space Separator
ValueCountFrequency (%)
83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 709
85.2%
Common 123
 
14.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
체 48
 
6.8%
험 48
 
6.8%
기 27
 
3.8%
농 14
 
2.0%
도 14
 
2.0%
과 12
 
1.7%
생 12
 
1.7%
육 11
 
1.6%
이 11
 
1.6%
딸 11
 
1.6%
Other values (187) 501
70.7%
Common
ValueCountFrequency (%)
83
67.5%
, 34
27.6%
( 2
 
1.6%
! 2
 
1.6%
) 2
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 709
85.2%
ASCII 123
 
14.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
83
67.5%
, 34
27.6%
( 2
 
1.6%
! 2
 
1.6%
) 2
 
1.6%
Hangul
ValueCountFrequency (%)
체 48
 
6.8%
험 48
 
6.8%
기 27
 
3.8%
농 14
 
2.0%
도 14
 
2.0%
과 12
 
1.7%
생 12
 
1.7%
육 11
 
1.6%
이 11
 
1.6%
딸 11
 
1.6%
Other values (187) 501
70.7%

전화번호
Text

MISSING 

Distinct37
Distinct (%)100.0%
Missing92
Missing (%)71.3%
Memory size1.1 KiB
2024-03-13T08:07:26.801827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.081081
Min length12

Characters and Unicode

Total characters447
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

Unique37 ?
Unique (%)100.0%

Sample

1st row031-798-3119
2nd row031-769-4582
3rd row031-766-6517
4th row031-797-0050
5th row02-2663-3223
ValueCountFrequency (%)
031-841-4894 1
 
2.7%
031-834-0488 1
 
2.7%
031-834-3601 1
 
2.7%
031-835-5633 1
 
2.7%
050-7724-7370 1
 
2.7%
031-338-9780 1
 
2.7%
031-322-5200 1
 
2.7%
031-632-5082 1
 
2.7%
031-641-7540 1
 
2.7%
031-635-5791 1
 
2.7%
Other values (27) 27
73.0%
2024-03-13T08:07:27.074836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 74
16.6%
0 59
13.2%
3 58
13.0%
1 50
11.2%
7 39
8.7%
8 34
7.6%
6 31
6.9%
9 30
6.7%
5 28
 
6.3%
4 23
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 373
83.4%
Dash Punctuation 74
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59
15.8%
3 58
15.5%
1 50
13.4%
7 39
10.5%
8 34
9.1%
6 31
8.3%
9 30
8.0%
5 28
7.5%
4 23
 
6.2%
2 21
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 74
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 447
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 74
16.6%
0 59
13.2%
3 58
13.0%
1 50
11.2%
7 39
8.7%
8 34
7.6%
6 31
6.9%
9 30
6.7%
5 28
 
6.3%
4 23
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 447
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 74
16.6%
0 59
13.2%
3 58
13.0%
1 50
11.2%
7 39
8.7%
8 34
7.6%
6 31
6.9%
9 30
6.7%
5 28
 
6.3%
4 23
 
5.1%

홈페이지주소
Text

MISSING 

Distinct71
Distinct (%)100.0%
Missing58
Missing (%)45.0%
Memory size1.1 KiB
2024-03-13T08:07:27.247303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length33
Mean length26.422535
Min length11

Characters and Unicode

Total characters1876
Distinct characters56
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

Unique71 ?
Unique (%)100.0%

Sample

1st rowblog.naver.com/changnnnn
2nd rowblog.naver.com/yellow8525
3rd rowblog.naver.com/dkjang0907
4th rowhttp://farmeredu.modoo.at/
5th rowd-flower.com
ValueCountFrequency (%)
blog.naver.com/changnnnn 1
 
1.4%
http://www.pigpark.co.kr 1
 
1.4%
http://www.cheongam.co.kr 1
 
1.4%
http://www.santorinifarm.com 1
 
1.4%
http://www.cheonggyefarm.com 1
 
1.4%
blog.naver.com/jmkwan77 1
 
1.4%
http://www.soopbr.com 1
 
1.4%
http://blog.naver.com/1982nature 1
 
1.4%
http://hanteo.yongini.com 1
 
1.4%
http://beetles.modoo.at 1
 
1.4%
Other values (61) 61
85.9%
2024-03-13T08:07:27.547032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 193
 
10.3%
. 149
 
7.9%
o 142
 
7.6%
t 138
 
7.4%
a 101
 
5.4%
w 99
 
5.3%
r 86
 
4.6%
m 84
 
4.5%
h 82
 
4.4%
p 81
 
4.3%
Other values (46) 721
38.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1357
72.3%
Other Punctuation 402
 
21.4%
Decimal Number 92
 
4.9%
Other Letter 14
 
0.7%
Dash Punctuation 7
 
0.4%
Uppercase Letter 3
 
0.2%
Math Symbol 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 142
 
10.5%
t 138
 
10.2%
a 101
 
7.4%
w 99
 
7.3%
r 86
 
6.3%
m 84
 
6.2%
h 82
 
6.0%
p 81
 
6.0%
e 78
 
5.7%
n 76
 
5.6%
Other values (14) 390
28.7%
Other Letter
ValueCountFrequency (%)
농 2
14.3%
도 2
14.3%
포 2
14.3%
광 1
7.1%
장 1
7.1%
탄 1
7.1%
딸 1
7.1%
라 1
7.1%
나 1
7.1%
기 1
7.1%
Decimal Number
ValueCountFrequency (%)
2 16
17.4%
1 14
15.2%
5 11
12.0%
4 10
10.9%
0 10
10.9%
7 8
8.7%
8 7
7.6%
6 7
7.6%
9 5
 
5.4%
3 4
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/ 193
48.0%
. 149
37.1%
: 56
 
13.9%
? 2
 
0.5%
! 1
 
0.2%
# 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
P 1
33.3%
T 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1360
72.5%
Common 502
 
26.8%
Hangul 14
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 142
 
10.4%
t 138
 
10.1%
a 101
 
7.4%
w 99
 
7.3%
r 86
 
6.3%
m 84
 
6.2%
h 82
 
6.0%
p 81
 
6.0%
e 78
 
5.7%
n 76
 
5.6%
Other values (17) 393
28.9%
Common
ValueCountFrequency (%)
/ 193
38.4%
. 149
29.7%
: 56
 
11.2%
2 16
 
3.2%
1 14
 
2.8%
5 11
 
2.2%
4 10
 
2.0%
0 10
 
2.0%
7 8
 
1.6%
- 7
 
1.4%
Other values (8) 28
 
5.6%
Hangul
ValueCountFrequency (%)
농 2
14.3%
도 2
14.3%
포 2
14.3%
광 1
7.1%
장 1
7.1%
탄 1
7.1%
딸 1
7.1%
라 1
7.1%
나 1
7.1%
기 1
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1862
99.3%
Hangul 14
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 193
 
10.4%
. 149
 
8.0%
o 142
 
7.6%
t 138
 
7.4%
a 101
 
5.4%
w 99
 
5.3%
r 86
 
4.6%
m 84
 
4.5%
h 82
 
4.4%
p 81
 
4.4%
Other values (35) 707
38.0%
Hangul
ValueCountFrequency (%)
농 2
14.3%
도 2
14.3%
포 2
14.3%
광 1
7.1%
장 1
7.1%
탄 1
7.1%
딸 1
7.1%
라 1
7.1%
나 1
7.1%
기 1
7.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct107
Distinct (%)87.0%
Missing6
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean13633.943
Minimum10000
Maximum18545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-13T08:07:27.672730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10109.7
Q111402
median12573
Q317176.5
95-th percentile18287
Maximum18545
Range8545
Interquartile range (IQR)5774.5

Descriptive statistics

Standard deviation2895.7353
Coefficient of variation (CV)0.21239162
Kurtosis-1.326153
Mean13633.943
Median Absolute Deviation (MAD)1564
Skewness0.55155804
Sum1676975
Variance8385282.7
MonotonicityNot monotonic
2024-03-13T08:07:27.775276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10276 4
 
3.1%
11402 4
 
3.1%
12280 3
 
2.3%
12714 2
 
1.6%
10804 2
 
1.6%
17705 2
 
1.6%
11448 2
 
1.6%
17166 2
 
1.6%
17423 2
 
1.6%
18545 2
 
1.6%
Other values (97) 98
76.0%
(Missing) 6
 
4.7%
ValueCountFrequency (%)
10000 1
0.8%
10008 1
0.8%
10012 1
0.8%
10029 1
0.8%
10044 1
0.8%
10057 1
0.8%
10099 1
0.8%
10206 1
0.8%
10208 1
0.8%
10216 1
0.8%
ValueCountFrequency (%)
18545 2
1.6%
18512 1
0.8%
18388 1
0.8%
18295 1
0.8%
18293 1
0.8%
18287 2
1.6%
18274 1
0.8%
18221 1
0.8%
17926 1
0.8%
17814 1
0.8%

소재지지번주소
Text

MISSING 

Distinct123
Distinct (%)99.2%
Missing5
Missing (%)3.9%
Memory size1.1 KiB
2024-03-13T08:07:27.988947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length25
Mean length21.362903
Min length15

Characters and Unicode

Total characters2649
Distinct characters168
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

Unique122 ?
Unique (%)98.4%

Sample

1st row경기도 가평군 조종면 상판리 437번지
2nd row경기도 가평군 북면 제령리 216-1번지
3rd row경기도 가평군 설악면 설곡리 568번지
4th row경기도 가평군 청평면 고성리 491-1번지
5th row경기도 가평군 조종면 마일리 360-2
ValueCountFrequency (%)
경기도 124
 
20.4%
양주시 12
 
2.0%
남양주시 12
 
2.0%
화성시 12
 
2.0%
양평군 10
 
1.6%
이천시 9
 
1.5%
용인시 9
 
1.5%
광주시 8
 
1.3%
처인구 8
 
1.3%
김포시 7
 
1.1%
Other values (315) 398
65.4%
2024-03-13T08:07:28.315259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
485
 
18.3%
도 127
 
4.8%
기 125
 
4.7%
경 124
 
4.7%
시 104
 
3.9%
리 95
 
3.6%
1 88
 
3.3%
면 85
 
3.2%
지 84
 
3.2%
- 83
 
3.1%
Other values (158) 1249
47.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1639
61.9%
Space Separator 485
 
18.3%
Decimal Number 442
 
16.7%
Dash Punctuation 83
 
3.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 127
 
7.7%
기 125
 
7.6%
경 124
 
7.6%
시 104
 
6.3%
리 95
 
5.8%
면 85
 
5.2%
지 84
 
5.1%
번 77
 
4.7%
양 58
 
3.5%
주 46
 
2.8%
Other values (146) 714
43.6%
Decimal Number
ValueCountFrequency (%)
1 88
19.9%
2 70
15.8%
3 56
12.7%
4 39
8.8%
5 38
8.6%
6 38
8.6%
9 31
 
7.0%
7 30
 
6.8%
0 27
 
6.1%
8 25
 
5.7%
Space Separator
ValueCountFrequency (%)
485
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 83
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1639
61.9%
Common 1010
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 127
 
7.7%
기 125
 
7.6%
경 124
 
7.6%
시 104
 
6.3%
리 95
 
5.8%
면 85
 
5.2%
지 84
 
5.1%
번 77
 
4.7%
양 58
 
3.5%
주 46
 
2.8%
Other values (146) 714
43.6%
Common
ValueCountFrequency (%)
485
48.0%
1 88
 
8.7%
- 83
 
8.2%
2 70
 
6.9%
3 56
 
5.5%
4 39
 
3.9%
5 38
 
3.8%
6 38
 
3.8%
9 31
 
3.1%
7 30
 
3.0%
Other values (2) 52
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1639
61.9%
ASCII 1010
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
485
48.0%
1 88
 
8.7%
- 83
 
8.2%
2 70
 
6.9%
3 56
 
5.5%
4 39
 
3.9%
5 38
 
3.8%
6 38
 
3.8%
9 31
 
3.1%
7 30
 
3.0%
Other values (2) 52
 
5.1%
Hangul
ValueCountFrequency (%)
도 127
 
7.7%
기 125
 
7.6%
경 124
 
7.6%
시 104
 
6.3%
리 95
 
5.8%
면 85
 
5.2%
지 84
 
5.1%
번 77
 
4.7%
양 58
 
3.5%
주 46
 
2.8%
Other values (146) 714
43.6%

소재지도로명주소
Text

MISSING 

Distinct111
Distinct (%)99.1%
Missing17
Missing (%)13.2%
Memory size1.1 KiB
2024-03-13T08:07:28.562375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length22.017857
Min length15

Characters and Unicode

Total characters2466
Distinct characters169
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

Unique110 ?
Unique (%)98.2%

Sample

1st row경기도 가평군 조종면 명지산로 257-70
2nd row경기도 가평군 북면 제령아랫말길 64
3rd row경기도 가평군 설악면 봉미산안길 74
4th row경기도 가평군 청평면 말래골길 36
5th row경기도 가평군 조종면 연인산로 520
ValueCountFrequency (%)
경기도 112
 
19.8%
양주시 12
 
2.1%
양평군 10
 
1.8%
남양주시 9
 
1.6%
화성시 9
 
1.6%
광주시 8
 
1.4%
고양시 7
 
1.2%
김포시 7
 
1.2%
이천시 6
 
1.1%
용인시 6
 
1.1%
Other values (304) 380
67.1%
2024-03-13T08:07:28.947828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
454
 
18.4%
도 114
 
4.6%
기 114
 
4.6%
경 112
 
4.5%
시 94
 
3.8%
2 86
 
3.5%
1 80
 
3.2%
길 75
 
3.0%
면 73
 
3.0%
로 69
 
2.8%
Other values (159) 1195
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1468
59.5%
Decimal Number 490
 
19.9%
Space Separator 454
 
18.4%
Dash Punctuation 54
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 114
 
7.8%
기 114
 
7.8%
경 112
 
7.6%
시 94
 
6.4%
길 75
 
5.1%
면 73
 
5.0%
로 69
 
4.7%
양 54
 
3.7%
주 40
 
2.7%
번 39
 
2.7%
Other values (147) 684
46.6%
Decimal Number
ValueCountFrequency (%)
2 86
17.6%
1 80
16.3%
3 54
11.0%
5 48
9.8%
4 45
9.2%
7 42
8.6%
6 37
7.6%
0 36
7.3%
8 33
 
6.7%
9 29
 
5.9%
Space Separator
ValueCountFrequency (%)
454
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 54
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1468
59.5%
Common 998
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 114
 
7.8%
기 114
 
7.8%
경 112
 
7.6%
시 94
 
6.4%
길 75
 
5.1%
면 73
 
5.0%
로 69
 
4.7%
양 54
 
3.7%
주 40
 
2.7%
번 39
 
2.7%
Other values (147) 684
46.6%
Common
ValueCountFrequency (%)
454
45.5%
2 86
 
8.6%
1 80
 
8.0%
3 54
 
5.4%
- 54
 
5.4%
5 48
 
4.8%
4 45
 
4.5%
7 42
 
4.2%
6 37
 
3.7%
0 36
 
3.6%
Other values (2) 62
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1468
59.5%
ASCII 998
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
454
45.5%
2 86
 
8.6%
1 80
 
8.0%
3 54
 
5.4%
- 54
 
5.4%
5 48
 
4.8%
4 45
 
4.5%
7 42
 
4.2%
6 37
 
3.7%
0 36
 
3.6%
Other values (2) 62
 
6.2%
Hangul
ValueCountFrequency (%)
도 114
 
7.8%
기 114
 
7.8%
경 112
 
7.6%
시 94
 
6.4%
길 75
 
5.1%
면 73
 
5.0%
로 69
 
4.7%
양 54
 
3.7%
주 40
 
2.7%
번 39
 
2.7%
Other values (147) 684
46.6%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct115
Distinct (%)98.3%
Missing12
Missing (%)9.3%
Infinite0
Infinite (%)0.0%
Mean37.519722
Minimum36.981503
Maximum38.139887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-13T08:07:29.058514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.981503
5-th percentile37.067557
Q137.247884
median37.515457
Q337.718497
95-th percentile37.984132
Maximum38.139887
Range1.1583842
Interquartile range (IQR)0.4706131

Descriptive statistics

Standard deviation0.29681532
Coefficient of variation (CV)0.0079109147
Kurtosis-0.97981521
Mean37.519722
Median Absolute Deviation (MAD)0.24139254
Skewness0.077327143
Sum4389.8075
Variance0.088099335
MonotonicityNot monotonic
2024-03-13T08:07:29.161704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.6972057853 2
 
1.6%
37.9233291716 2
 
1.6%
37.1952330525 1
 
0.8%
37.3009905788 1
 
0.8%
37.1766572606 1
 
0.8%
37.0857838483 1
 
0.8%
37.3249046325 1
 
0.8%
37.267483826 1
 
0.8%
37.1799690348 1
 
0.8%
37.1637779221 1
 
0.8%
Other values (105) 105
81.4%
(Missing) 12
 
9.3%
ValueCountFrequency (%)
36.9815031383 1
0.8%
36.988032758 1
0.8%
36.9960542327 1
0.8%
37.0336776626 1
0.8%
37.0493906519 1
0.8%
37.0669403321 1
0.8%
37.0677109125 1
0.8%
37.0739672444 1
0.8%
37.0857838483 1
0.8%
37.0859470847 1
0.8%
ValueCountFrequency (%)
38.1398873332 1
0.8%
38.1053769196 1
0.8%
38.0889975018 1
0.8%
38.0312556039 1
0.8%
38.0187369922 1
0.8%
38.0010755635 1
0.8%
37.9798956666 1
0.8%
37.9798558856 1
0.8%
37.9755226099 1
0.8%
37.9352898917 1
0.8%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct115
Distinct (%)98.3%
Missing12
Missing (%)9.3%
Infinite0
Infinite (%)0.0%
Mean127.16061
Minimum126.53048
Maximum127.76992
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-03-13T08:07:29.265332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.53048
5-th percentile126.66731
Q1126.95525
median127.17761
Q3127.37741
95-th percentile127.58891
Maximum127.76992
Range1.2394397
Interquartile range (IQR)0.42216011

Descriptive statistics

Standard deviation0.28365328
Coefficient of variation (CV)0.0022306693
Kurtosis-0.66316375
Mean127.16061
Median Absolute Deviation (MAD)0.21024593
Skewness-0.16983693
Sum14877.792
Variance0.080459185
MonotonicityNot monotonic
2024-03-13T08:07:29.375610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9135835692 2
 
1.6%
126.9939295273 2
 
1.6%
127.3183398098 1
 
0.8%
127.4472708885 1
 
0.8%
127.4799369009 1
 
0.8%
127.5839371818 1
 
0.8%
127.4860652049 1
 
0.8%
127.5162637832 1
 
0.8%
127.3412905379 1
 
0.8%
127.1511010734 1
 
0.8%
Other values (105) 105
81.4%
(Missing) 12
 
9.3%
ValueCountFrequency (%)
126.5304823475 1
0.8%
126.5768348801 1
0.8%
126.6046263439 1
0.8%
126.6137384554 1
0.8%
126.6253271178 1
0.8%
126.6555346747 1
0.8%
126.6702502135 1
0.8%
126.6864280461 1
0.8%
126.7081877564 1
0.8%
126.7145039841 1
0.8%
ValueCountFrequency (%)
127.7699220668 1
0.8%
127.706290348 1
0.8%
127.6654113654 1
0.8%
127.6614435793 1
0.8%
127.6558301341 1
0.8%
127.6088226464 1
0.8%
127.5839371818 1
0.8%
127.5825421571 1
0.8%
127.5387923354 1
0.8%
127.5256768694 1
0.8%

Interactions

2024-03-13T08:07:24.285759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.513414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.779992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:24.033716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:24.354605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.580750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.855227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:24.097782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:24.416332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.641987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.910827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:24.157663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:24.480659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.703166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:23.969923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:07:24.222049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:07:29.449009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조성년도시군명사업구분명전화번호홈페이지주소소재지우편번호WGS84위도WGS84경도
조성년도1.0000.5970.7081.0001.0000.2590.5470.491
시군명0.5971.0000.2821.0001.0000.9920.9060.871
사업구분명0.7080.2821.0001.0001.0000.3840.0000.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.000
홈페이지주소1.0001.0001.0001.0001.0001.0001.0001.000
소재지우편번호0.2590.9920.3841.0001.0001.0000.8010.696
WGS84위도0.5470.9060.0001.0001.0000.8011.0000.700
WGS84경도0.4910.8710.0001.0001.0000.6960.7001.000
2024-03-13T08:07:29.531043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업구분명시군명
사업구분명1.0000.230
시군명0.2301.000
2024-03-13T08:07:29.594418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
조성년도소재지우편번호WGS84위도WGS84경도시군명사업구분명
조성년도1.0000.032-0.0280.0430.2430.551
소재지우편번호0.0321.000-0.8860.3370.9220.280
WGS84위도-0.028-0.8861.000-0.2780.6120.000
WGS84경도0.0430.337-0.2781.0000.5400.000
시군명0.2430.9220.6120.5401.0000.230
사업구분명0.5510.2800.0000.0000.2301.000

Missing values

2024-03-13T08:07:24.773052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:07:24.925454image/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.
2024-03-13T08:07:25.044589image/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

조성년도시군명사업구분명농장명주제전화번호홈페이지주소소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
02016가평군국비가평커피농장커피나무 한살이<NA>blog.naver.com/changnnnn12431경기도 가평군 조종면 상판리 437번지경기도 가평군 조종면 명지산로 257-7037.89835127.368378
12019가평군도비비타민옥수수체험,가공<NA><NA>12405경기도 가평군 북면 제령리 216-1번지경기도 가평군 북면 제령아랫말길 6437.888737127.538792
22012가평군도비양지농원오색떡만들기<NA>blog.naver.com/yellow852512471경기도 가평군 설악면 설곡리 568번지경기도 가평군 설악면 봉미산안길 7437.618045127.525677
32016가평군국비고성리산양목장산양사육<NA><NA>12456경기도 가평군 청평면 고성리 491-1번지경기도 가평군 청평면 말래골길 3637.715519127.498298
42011가평군도비연인산풍경요리사의농원치즈가공 등<NA>blog.naver.com/dkjang090712433경기도 가평군 조종면 마일리 360-2경기도 가평군 조종면 연인산로 52037.850978127.377408
52020고양시도비꿈팜사과, 커피체험<NA><NA>10276경기도 고양시 덕양구 선유동 150-6번지경기도 고양시 덕양구 서리골길 155-2237.697206126.913584
62010고양시도비산울안민속교육농장전통메밀국수<NA><NA>10276<NA>경기도 고양시 덕양구 서리골길124<NA><NA>
72015고양시도비파머스체험가든농사체험<NA>http://farmeredu.modoo.at/10216경기도 고양시 일산서구 덕이동 926-1경기도 고양시 일산서구 송포로 118번길 42-1637.676774126.730353
82015고양시도비댄싱플라워식용꽃이용체험<NA>d-flower.com10208경기도 고양시 일산서구 가좌동 933번지경기도 고양시 일산서구 가좌로 10637.688819126.715847
92011고양시국비민들레자연체험학교쪽빛이야기(천연염색)<NA><NA>10206경기도 고양시 덕이동 1226경기도 고양시 일산서구 덕산로277번길 51-2137.6981126.733229
조성년도시군명사업구분명농장명주제전화번호홈페이지주소소재지우편번호소재지지번주소소재지도로명주소WGS84위도WGS84경도
1192015화성시도비쌍정농장포도<NA>blog.naver.com/gidal8115<NA>경기도 화성시 송산면 쌍정리<NA><NA><NA>
1202008화성시국비향기농원배 생태체험<NA><NA><NA>경기도 화성시 향남면 증거리<NA><NA><NA>
1212008화성시국비산들레자연체험학교가축체험031-356-0768http://www.3560768.com/18293경기도 화성시 비봉면 청요리 702-4경기도 화성시 비봉면 자청로207번길 21-7337.210637126.894616
1222021화성시도비에코뜰딸기<NA>https://blog.naver.com/imcho2118512경기도 화성시 정남면 용수리 54-3번지경기도 화성시 정남면 용수길 26번길 3-1037.17077127.00165
1232008화성시국비은성농장맛있는 포도체험<NA><NA>18221경기도 화성시 송산면 고정2리<NA><NA><NA>
1242010화성시도비행복텃밭농사는예술이다<NA>http://www.happy62nong.co.kr/18287경기도 화성시 매송면 어천리 598-1번지경기도 화성시 매송면 화성로 2148-2837.247884126.90388
1252015화성시국비흙이 시를 만나면벼, 포도, 콩<NA><NA>18545경기도 화성시 송산면 고포리 388-4번지경기도 화성시 송산면 개매기길 100번길 137.243083126.686428
1262015화성시도비예랑도예고구마, 잣나무숲 등<NA>www.yedoye.com/default/18295경기도 화성시 봉담읍 상리 383-2번지경기도 화성시 봉담읍 삼봉길 100-1137.216487126.934784
1272019화성시도비수피아체험과 힐링<NA>https://blog.naver.com/supia-18274경기도 화성시 남양읍 무송리 156-7번지경기도 화성시 남양읍 현대기아로 487번길 35-5737.199299126.840878
1282008화성시국비원평허브농원허브체험031-294-0088<NA>18287경기도 화성시 매송면 원평리 181-6경기도 화성시 매송면 매봉로 40-1637.245949126.922544