Overview

Dataset statistics

Number of variables10
Number of observations308
Missing cells63
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.8 KiB
Average record size in memory82.4 B

Variable types

Numeric2
Categorical4
Text4

Dataset

Description진안군 내에 설치된 야외운동기구에 대한 데이터로 설치기구 종류와 마을위치, 소재지 주소, 관리부서 등을 제공합니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=20&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15039301

Alerts

시도 has constant value ""Constant
시군구 has constant value ""Constant
관리부서 has constant value ""Constant
데이터기준일자 has constant value ""Constant
상세위치 has 52 (16.9%) missing valuesMissing
설치연도 has 11 (3.6%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:51:11.832817
Analysis finished2024-03-14 00:51:13.036248
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct308
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean154.5
Minimum1
Maximum308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T09:51:13.088378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.35
Q177.75
median154.5
Q3231.25
95-th percentile292.65
Maximum308
Range307
Interquartile range (IQR)153.5

Descriptive statistics

Standard deviation89.056162
Coefficient of variation (CV)0.57641529
Kurtosis-1.2
Mean154.5
Median Absolute Deviation (MAD)77
Skewness0
Sum47586
Variance7931
MonotonicityStrictly increasing
2024-03-14T09:51:13.192832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
210 1
 
0.3%
209 1
 
0.3%
208 1
 
0.3%
207 1
 
0.3%
206 1
 
0.3%
204 1
 
0.3%
Other values (298) 298
96.8%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
308 1
0.3%
307 1
0.3%
306 1
0.3%
305 1
0.3%
304 1
0.3%
303 1
0.3%
302 1
0.3%
301 1
0.3%
300 1
0.3%
299 1
0.3%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
전북특별자치도
308 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전북특별자치도 308
100.0%

Length

2024-03-14T09:51:13.301898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:51:13.385891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전북특별자치도 308
100.0%

시군구
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
진안군
308 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
진안군 308
100.0%

Length

2024-03-14T09:51:13.481414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:51:13.578121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
진안군 308
100.0%

마을
Text

Distinct229
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:51:13.815332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.5454545
Min length3

Characters and Unicode

Total characters1400
Distinct characters163
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

Unique170 ?
Unique (%)55.2%

Sample

1st row우화1동마을
2nd row학천2동마을
3rd row학천2동마을
4th row학천2동마을
5th row원물곡마을
ValueCountFrequency (%)
연구2동마을 7
 
2.3%
양지마을 5
 
1.6%
부곡마을 4
 
1.3%
체련공원 4
 
1.3%
장등마을 3
 
1.0%
문화마을 3
 
1.0%
방화마을 3
 
1.0%
상도치마을 3
 
1.0%
활력센터광장 3
 
1.0%
대광1동마을 3
 
1.0%
Other values (219) 272
87.7%
2024-03-14T09:51:14.213370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 300
21.4%
을 297
21.2%
동 59
 
4.2%
원 33
 
2.4%
산 18
 
1.3%
평 17
 
1.2%
곡 17
 
1.2%
상 17
 
1.2%
지 16
 
1.1%
신 16
 
1.1%
Other values (153) 610
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1358
97.0%
Decimal Number 30
 
2.1%
Other Punctuation 6
 
0.4%
Space Separator 3
 
0.2%
Open Punctuation 1
 
0.1%
Dash Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 300
22.1%
을 297
21.9%
동 59
 
4.3%
원 33
 
2.4%
산 18
 
1.3%
평 17
 
1.3%
곡 17
 
1.3%
상 17
 
1.3%
지 16
 
1.2%
신 16
 
1.2%
Other values (143) 568
41.8%
Decimal Number
ValueCountFrequency (%)
2 14
46.7%
1 10
33.3%
3 4
 
13.3%
5 1
 
3.3%
6 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1358
97.0%
Common 42
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 300
22.1%
을 297
21.9%
동 59
 
4.3%
원 33
 
2.4%
산 18
 
1.3%
평 17
 
1.3%
곡 17
 
1.3%
상 17
 
1.3%
지 16
 
1.2%
신 16
 
1.2%
Other values (143) 568
41.8%
Common
ValueCountFrequency (%)
2 14
33.3%
1 10
23.8%
, 6
14.3%
3 4
 
9.5%
3
 
7.1%
( 1
 
2.4%
5 1
 
2.4%
6 1
 
2.4%
- 1
 
2.4%
) 1
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1358
97.0%
ASCII 42
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 300
22.1%
을 297
21.9%
동 59
 
4.3%
원 33
 
2.4%
산 18
 
1.3%
평 17
 
1.3%
곡 17
 
1.3%
상 17
 
1.3%
지 16
 
1.2%
신 16
 
1.2%
Other values (143) 568
41.8%
ASCII
ValueCountFrequency (%)
2 14
33.3%
1 10
23.8%
, 6
14.3%
3 4
 
9.5%
3
 
7.1%
( 1
 
2.4%
5 1
 
2.4%
6 1
 
2.4%
- 1
 
2.4%
) 1
 
2.4%

소재지 주소
Text

Distinct263
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:51:14.487423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length28
Mean length24.74026
Min length16

Characters and Unicode

Total characters7620
Distinct characters116
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

Unique229 ?
Unique (%)74.4%

Sample

1st row전북특별자치도 진안군 진안읍 군하리 산1-1
2nd row전북특별자치도 진안군 진안읍 군상리 158
3rd row전북특별자치도 진안군 진안읍 군상리 458-5
4th row전북특별자치도 진안군 진안읍 군상리 1162-26
5th row전북특별자치도 진안군 진안읍 물곡리 905-6
ValueCountFrequency (%)
전북특별자치도 308
20.2%
진안군 308
20.2%
진안읍 81
 
5.3%
부귀면 33
 
2.2%
백운면 30
 
2.0%
마령면 28
 
1.8%
성수면 27
 
1.8%
주천면 26
 
1.7%
동향면 24
 
1.6%
군상리 18
 
1.2%
Other values (351) 645
42.2%
2024-03-14T09:51:14.867440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1229
 
16.1%
안 403
 
5.3%
진 390
 
5.1%
군 335
 
4.4%
전 326
 
4.3%
도 314
 
4.1%
자 310
 
4.1%
북 308
 
4.0%
특 308
 
4.0%
별 308
 
4.0%
Other values (106) 3389
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4922
64.6%
Space Separator 1229
 
16.1%
Decimal Number 1229
 
16.1%
Dash Punctuation 238
 
3.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 403
 
8.2%
진 390
 
7.9%
군 335
 
6.8%
전 326
 
6.6%
도 314
 
6.4%
자 310
 
6.3%
북 308
 
6.3%
특 308
 
6.3%
별 308
 
6.3%
치 308
 
6.3%
Other values (93) 1612
32.8%
Decimal Number
ValueCountFrequency (%)
1 302
24.6%
2 139
11.3%
3 131
10.7%
4 101
 
8.2%
5 101
 
8.2%
6 100
 
8.1%
7 93
 
7.6%
9 92
 
7.5%
0 86
 
7.0%
8 84
 
6.8%
Space Separator
ValueCountFrequency (%)
1229
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 238
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4922
64.6%
Common 2698
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 403
 
8.2%
진 390
 
7.9%
군 335
 
6.8%
전 326
 
6.6%
도 314
 
6.4%
자 310
 
6.3%
북 308
 
6.3%
특 308
 
6.3%
별 308
 
6.3%
치 308
 
6.3%
Other values (93) 1612
32.8%
Common
ValueCountFrequency (%)
1229
45.6%
1 302
 
11.2%
- 238
 
8.8%
2 139
 
5.2%
3 131
 
4.9%
4 101
 
3.7%
5 101
 
3.7%
6 100
 
3.7%
7 93
 
3.4%
9 92
 
3.4%
Other values (3) 172
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4922
64.6%
ASCII 2698
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1229
45.6%
1 302
 
11.2%
- 238
 
8.8%
2 139
 
5.2%
3 131
 
4.9%
4 101
 
3.7%
5 101
 
3.7%
6 100
 
3.7%
7 93
 
3.4%
9 92
 
3.4%
Other values (3) 172
 
6.4%
Hangul
ValueCountFrequency (%)
안 403
 
8.2%
진 390
 
7.9%
군 335
 
6.8%
전 326
 
6.6%
도 314
 
6.4%
자 310
 
6.3%
북 308
 
6.3%
특 308
 
6.3%
별 308
 
6.3%
치 308
 
6.3%
Other values (93) 1612
32.8%

상세위치
Text

MISSING 

Distinct138
Distinct (%)53.9%
Missing52
Missing (%)16.9%
Memory size2.5 KiB
2024-03-14T09:51:15.079448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length6.0507812
Min length2

Characters and Unicode

Total characters1549
Distinct characters172
Distinct categories6 ?
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 (%)41.8%

Sample

1st row우화산 내부
2nd row하수종말처리장
3rd row마을회관 주변
4th row하수종말처리장 옆
5th row원물곡마을회관
ValueCountFrequency (%)
마을회관 93
20.6%
옆 59
 
13.1%
모정 47
 
10.4%
앞 40
 
8.8%
공터 12
 
2.7%
정자 8
 
1.8%
경로당 6
 
1.3%
뒤 6
 
1.3%
광장 5
 
1.1%
나무아래 5
 
1.1%
Other values (125) 171
37.8%
2024-03-14T09:51:15.403867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
196
 
12.7%
마 135
 
8.7%
을 135
 
8.7%
회 119
 
7.7%
관 118
 
7.6%
정 79
 
5.1%
옆 66
 
4.3%
모 61
 
3.9%
앞 43
 
2.8%
공 33
 
2.1%
Other values (162) 564
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1341
86.6%
Space Separator 196
 
12.7%
Decimal Number 5
 
0.3%
Other Punctuation 3
 
0.2%
Open Punctuation 2
 
0.1%
Close Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 135
 
10.1%
을 135
 
10.1%
회 119
 
8.9%
관 118
 
8.8%
정 79
 
5.9%
옆 66
 
4.9%
모 61
 
4.5%
앞 43
 
3.2%
공 33
 
2.5%
장 25
 
1.9%
Other values (156) 527
39.3%
Decimal Number
ValueCountFrequency (%)
2 3
60.0%
1 2
40.0%
Space Separator
ValueCountFrequency (%)
196
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1341
86.6%
Common 208
 
13.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 135
 
10.1%
을 135
 
10.1%
회 119
 
8.9%
관 118
 
8.8%
정 79
 
5.9%
옆 66
 
4.9%
모 61
 
4.5%
앞 43
 
3.2%
공 33
 
2.5%
장 25
 
1.9%
Other values (156) 527
39.3%
Common
ValueCountFrequency (%)
196
94.2%
2 3
 
1.4%
, 3
 
1.4%
( 2
 
1.0%
) 2
 
1.0%
1 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1341
86.6%
ASCII 208
 
13.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
196
94.2%
2 3
 
1.4%
, 3
 
1.4%
( 2
 
1.0%
) 2
 
1.0%
1 2
 
1.0%
Hangul
ValueCountFrequency (%)
마 135
 
10.1%
을 135
 
10.1%
회 119
 
8.9%
관 118
 
8.8%
정 79
 
5.9%
옆 66
 
4.9%
모 61
 
4.5%
앞 43
 
3.2%
공 33
 
2.5%
장 25
 
1.9%
Other values (156) 527
39.3%

설치연도
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)6.4%
Missing11
Missing (%)3.6%
Infinite0
Infinite (%)0.0%
Mean2018.7037
Minimum1992
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.8 KiB
2024-03-14T09:51:15.508809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1992
5-th percentile2012
Q12017
median2020
Q32021
95-th percentile2022
Maximum2022
Range30
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.9677441
Coefficient of variation (CV)0.0019654911
Kurtosis8.429929
Mean2018.7037
Median Absolute Deviation (MAD)2
Skewness-2.2925336
Sum599555
Variance15.742993
MonotonicityNot monotonic
2024-03-14T09:51:15.620596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
2022 74
24.0%
2021 54
17.5%
2020 41
13.3%
2019 27
 
8.8%
2018 25
 
8.1%
2014 19
 
6.2%
2017 13
 
4.2%
2016 10
 
3.2%
2015 8
 
2.6%
2012 8
 
2.6%
Other values (9) 18
 
5.8%
(Missing) 11
 
3.6%
ValueCountFrequency (%)
1992 1
 
0.3%
2003 2
 
0.6%
2005 2
 
0.6%
2006 1
 
0.3%
2007 1
 
0.3%
2008 1
 
0.3%
2010 2
 
0.6%
2011 3
 
1.0%
2012 8
2.6%
2013 5
1.6%
ValueCountFrequency (%)
2022 74
24.0%
2021 54
17.5%
2020 41
13.3%
2019 27
 
8.8%
2018 25
 
8.1%
2017 13
 
4.2%
2016 10
 
3.2%
2015 8
 
2.6%
2014 19
 
6.2%
2013 5
 
1.6%

종류
Text

Distinct199
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2024-03-14T09:51:15.781906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length40
Mean length16.909091
Min length3

Characters and Unicode

Total characters5208
Distinct characters106
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique155 ?
Unique (%)50.3%

Sample

1st row온몸노젓기+달리기+기타
2nd row허리돌리기+달리기+공중걷기
3rd row허리돌리기+달리기+공중걷기+상체근육풀기
4th row파도타기+허리돌리기+공중걷기+등허리지압기+상체근육풀기
5th row허리돌리기+상체근육풀기
ValueCountFrequency (%)
허리돌리기 14
 
4.5%
공중걷기+허리돌리기 9
 
2.9%
공중걷기 8
 
2.6%
달리기 7
 
2.3%
허리돌리기+공중걷기+달리기 6
 
1.9%
공중걷기+허리돌리기+상체근육풀기 5
 
1.6%
좌식싸이클 4
 
1.3%
파도타기+허리돌리기+싸이클 4
 
1.3%
온몸근육풀기+하체흔들기 4
 
1.3%
공중걷기+허리돌리기+달리기 4
 
1.3%
Other values (190) 245
79.0%
2024-03-14T09:51:16.050373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 921
17.7%
+ 664
 
12.7%
리 576
 
11.1%
허 227
 
4.4%
돌 206
 
4.0%
걷 168
 
3.2%
공 153
 
2.9%
중 153
 
2.9%
타 120
 
2.3%
파 105
 
2.0%
Other values (96) 1915
36.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4540
87.2%
Math Symbol 664
 
12.7%
Space Separator 3
 
0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 921
20.3%
리 576
 
12.7%
허 227
 
5.0%
돌 206
 
4.5%
걷 168
 
3.7%
공 153
 
3.4%
중 153
 
3.4%
타 120
 
2.6%
파 105
 
2.3%
도 104
 
2.3%
Other values (93) 1807
39.8%
Math Symbol
ValueCountFrequency (%)
+ 664
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4540
87.2%
Common 668
 
12.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 921
20.3%
리 576
 
12.7%
허 227
 
5.0%
돌 206
 
4.5%
걷 168
 
3.7%
공 153
 
3.4%
중 153
 
3.4%
타 120
 
2.6%
파 105
 
2.3%
도 104
 
2.3%
Other values (93) 1807
39.8%
Common
ValueCountFrequency (%)
+ 664
99.4%
3
 
0.4%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4539
87.2%
ASCII 668
 
12.8%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 921
20.3%
리 576
 
12.7%
허 227
 
5.0%
돌 206
 
4.5%
걷 168
 
3.7%
공 153
 
3.4%
중 153
 
3.4%
타 120
 
2.6%
파 105
 
2.3%
도 104
 
2.3%
Other values (92) 1806
39.8%
ASCII
ValueCountFrequency (%)
+ 664
99.4%
3
 
0.4%
2 1
 
0.1%
Compat Jamo
ValueCountFrequency (%)
ㅏ 1
100.0%

관리부서
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
문화체육과
308 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
문화체육과 308
100.0%

Length

2024-03-14T09:51:16.151552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:51:16.226539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
문화체육과 308
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-11-30
308 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-11-30
2nd row2023-11-30
3rd row2023-11-30
4th row2023-11-30
5th row2023-11-30

Common Values

ValueCountFrequency (%)
2023-11-30 308
100.0%

Length

2024-03-14T09:51:16.325494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:51:16.434763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-11-30 308
100.0%

Interactions

2024-03-14T09:51:12.396051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:51:12.164672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:51:12.483664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T09:51:12.251001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:51:16.488089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치연도
연번1.0000.534
설치연도0.5341.000
2024-03-14T09:51:16.579120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치연도
연번1.0000.039
설치연도0.0391.000

Missing values

2024-03-14T09:51:12.571250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:51:12.677353image/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.
2024-03-14T09:51:12.999394image/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

연번시도시군구마을소재지 주소상세위치설치연도종류관리부서데이터기준일자
01전북특별자치도진안군우화1동마을전북특별자치도 진안군 진안읍 군하리 산1-1우화산 내부1992온몸노젓기+달리기+기타문화체육과2023-11-30
12전북특별자치도진안군학천2동마을전북특별자치도 진안군 진안읍 군상리 158하수종말처리장<NA>허리돌리기+달리기+공중걷기문화체육과2023-11-30
23전북특별자치도진안군학천2동마을전북특별자치도 진안군 진안읍 군상리 458-5마을회관 주변2003허리돌리기+달리기+공중걷기+상체근육풀기문화체육과2023-11-30
34전북특별자치도진안군학천2동마을전북특별자치도 진안군 진안읍 군상리 1162-26하수종말처리장 옆2019파도타기+허리돌리기+공중걷기+등허리지압기+상체근육풀기문화체육과2023-11-30
45전북특별자치도진안군원물곡마을전북특별자치도 진안군 진안읍 물곡리 905-6원물곡마을회관<NA>허리돌리기+상체근육풀기문화체육과2023-11-30
56전북특별자치도진안군노계3동마을전북특별자치도 진안군 진안읍 군상리 603주공2차아파트2003허리돌리기+파도타기+공중걷기+등허리지압기문화체육과2023-11-30
67전북특별자치도진안군중평마을전북특별자치도 진안군 진안읍 연장리 1372-1중평마을회관2012허리돌리기+상체근육풀기+입식싸이클문화체육과2023-11-30
78전북특별자치도진안군예리마을전북특별자치도 진안군 진안읍 구룡리 산183-2숲거리공원2012거꾸로매달리기+공중걷기+파도타기+허리돌리기+윈몸일으키기문화체육과2023-11-30
89전북특별자치도진안군연구2동마을전북특별자치도 진안군 진안읍 군상리 1038-1진안공고 근처2014달리기문화체육과2023-11-30
910전북특별자치도진안군연구2동마을전북특별자치도 진안군 진안읍 군상리 1117-3부귀산 주차장2014허리돌리기+상체근육풀기+윗몸일으키기+달리기문화체육과2023-11-30
연번시도시군구마을소재지 주소상세위치설치연도종류관리부서데이터기준일자
298299전북특별자치도진안군선암마을전북특별자치도 진안군 주천면 무릉리 499-1선암마을회관 앞2018큰활차+작은활차돌리기+양팔줄당기기+철봉기+허리돌리기+전신허리돌리기문화체육과2023-11-30
299300전북특별자치도진안군산제마을전북특별자치도 진안군 주천면 용덕리 529-1산제마을회관2018말타기+윗몸일으키기+큰활차돌리기+전신허리돌리기+허리돌리기문화체육과2023-11-30
300301전북특별자치도진안군대촌마을전북특별자치도 진안군 주천면 용덕리 586-2대촌마을회관 옆2018노젓기+평행봉+큰활차+작은활차돌리기+허리돌리기+전신허리돌리기문화체육과2023-11-30
301302전북특별자치도진안군상양명마을전북특별자치도 진안군 주천면 운봉리 716-15상양명마을주차장2018큰활차돌리기+전신허리돌리기+윗몸일으키기+말타기문화체육과2023-11-30
302303전북특별자치도진안군처사마을전북특별자치도 진안군 주천면 대불리 1907처사마을회관 옆2018큰활차+작은활차돌리기+양팔줄당기기+철봉기+허리돌리기+전신허리돌리기문화체육과2023-11-30
303304전북특별자치도진안군장등마을전북특별자치도 진안군 주천면 대불리 456-3장동마을회관 옆2018말타기+윗몸일으키기+큰활차돌리기+전신허리돌리기문화체육과2023-11-30
304305전북특별자치도진안군광석마을전북특별자치도 진안군 주천면 신양리 906-1광석마을모정 옆2020공중걷기+달리기+허리돌리기문화체육과2023-11-30
305306전북특별자치도진안군하양명마을전북특별자치도 진안군 주천면 하양명길 1마을회관 옆2021입식싸이클+양팔로프당기기문화체육과2023-11-30
306307전북특별자치도진안군미적마을전북특별자치도 진안군 주천면 용덕리 274마을회관 옆2022좌식싸이클문화체육과2023-11-30
307308전북특별자치도진안군미적마을전북특별자치도 진안군 주천면 용덕리 274마을회관 옆2022온몸근육풀기+하체흔들기문화체육과2023-11-30