Overview

Dataset statistics

Number of variables5
Number of observations157
Missing cells48
Missing cells (%)6.1%
Duplicate rows2
Duplicate rows (%)1.3%
Total size in memory6.4 KiB
Average record size in memory41.8 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description논산시 관내 야외운동기구 설치현황 데이터로 설치기구명, 행정구역, 설치년월, 수량, 제조사 등의 정보를 제공합니다
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=388&beforeMenuCd=DOM_000000201001001000&publicdatapk=15038021

Alerts

Dataset has 2 (1.3%) duplicate rowsDuplicates
소재지도로명주소 has 32 (20.4%) missing valuesMissing
소재지지번주소 has 16 (10.2%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:11:11.631908
Analysis finished2024-01-09 22:11:12.185969
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

설치연도
Real number (ℝ)

Distinct6
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2015.7325
Minimum2014
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-01-10T07:11:12.225753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2014
5-th percentile2014
Q12014
median2015
Q32017
95-th percentile2019
Maximum2019
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.9060705
Coefficient of variation (CV)0.00094559695
Kurtosis-1.1170233
Mean2015.7325
Median Absolute Deviation (MAD)1
Skewness0.65995374
Sum316470
Variance3.6331047
MonotonicityIncreasing
2024-01-10T07:11:12.308506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2014 65
41.4%
2015 28
17.8%
2019 26
 
16.6%
2017 20
 
12.7%
2016 9
 
5.7%
2018 9
 
5.7%
ValueCountFrequency (%)
2014 65
41.4%
2015 28
17.8%
2016 9
 
5.7%
2017 20
 
12.7%
2018 9
 
5.7%
2019 26
 
16.6%
ValueCountFrequency (%)
2019 26
 
16.6%
2018 9
 
5.7%
2017 20
 
12.7%
2016 9
 
5.7%
2015 28
17.8%
2014 65
41.4%

행정동
Categorical

Distinct15
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
연무읍
17 
부창동
17 
양촌면
16 
가야곡면
13 
강경읍
12 
Other values (10)
82 

Length

Max length4
Median length3
Mean length3.0828025
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
연무읍 17
10.8%
부창동 17
10.8%
양촌면 16
10.2%
가야곡면 13
8.3%
강경읍 12
7.6%
노성면 11
 
7.0%
성동면 11
 
7.0%
광석면 11
 
7.0%
연산면 11
 
7.0%
부적면 10
 
6.4%
Other values (5) 28
17.8%

Length

2024-01-10T07:11:12.403942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연무읍 17
10.8%
부창동 17
10.8%
양촌면 16
10.2%
가야곡면 13
8.3%
강경읍 12
7.6%
노성면 11
 
7.0%
성동면 11
 
7.0%
광석면 11
 
7.0%
연산면 11
 
7.0%
부적면 10
 
6.4%
Other values (5) 28
17.8%

소재지도로명주소
Text

MISSING 

Distinct112
Distinct (%)89.6%
Missing32
Missing (%)20.4%
Memory size1.4 KiB
2024-01-10T07:11:12.644855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length21.592
Min length15

Characters and Unicode

Total characters2699
Distinct characters113
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

Unique100 ?
Unique (%)80.0%

Sample

1st row충청남도 논산시 강경읍 옥녀봉로27번길 24-4
2nd row충청남도 논산시 강경읍 대흥로5번길 10
3rd row충청남도 논산시 강경읍 황산1길 22
4th row충청남도 논산시 강경읍 계백로219번길 22
5th row충청남도 논산시 강경읍 금백로 163-1
ValueCountFrequency (%)
충청남도 125
21.2%
논산시 125
21.2%
가야곡면 12
 
2.0%
강경읍 11
 
1.9%
연산면 11
 
1.9%
연무읍 10
 
1.7%
노성면 9
 
1.5%
광석면 9
 
1.5%
부적면 8
 
1.4%
성동면 6
 
1.0%
Other values (197) 265
44.8%
2024-01-10T07:11:13.005276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
466
17.3%
산 150
 
5.6%
시 130
 
4.8%
논 129
 
4.8%
충 126
 
4.7%
청 125
 
4.6%
도 125
 
4.6%
남 125
 
4.6%
길 97
 
3.6%
1 89
 
3.3%
Other values (103) 1137
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1683
62.4%
Decimal Number 508
 
18.8%
Space Separator 466
 
17.3%
Dash Punctuation 42
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 150
 
8.9%
시 130
 
7.7%
논 129
 
7.7%
충 126
 
7.5%
청 125
 
7.4%
도 125
 
7.4%
남 125
 
7.4%
길 97
 
5.8%
로 88
 
5.2%
면 71
 
4.2%
Other values (91) 517
30.7%
Decimal Number
ValueCountFrequency (%)
1 89
17.5%
2 73
14.4%
3 64
12.6%
4 56
11.0%
5 48
9.4%
6 46
9.1%
7 40
7.9%
8 34
 
6.7%
0 30
 
5.9%
9 28
 
5.5%
Space Separator
ValueCountFrequency (%)
466
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1683
62.4%
Common 1016
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 150
 
8.9%
시 130
 
7.7%
논 129
 
7.7%
충 126
 
7.5%
청 125
 
7.4%
도 125
 
7.4%
남 125
 
7.4%
길 97
 
5.8%
로 88
 
5.2%
면 71
 
4.2%
Other values (91) 517
30.7%
Common
ValueCountFrequency (%)
466
45.9%
1 89
 
8.8%
2 73
 
7.2%
3 64
 
6.3%
4 56
 
5.5%
5 48
 
4.7%
6 46
 
4.5%
- 42
 
4.1%
7 40
 
3.9%
8 34
 
3.3%
Other values (2) 58
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1683
62.4%
ASCII 1016
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
466
45.9%
1 89
 
8.8%
2 73
 
7.2%
3 64
 
6.3%
4 56
 
5.5%
5 48
 
4.7%
6 46
 
4.5%
- 42
 
4.1%
7 40
 
3.9%
8 34
 
3.3%
Other values (2) 58
 
5.7%
Hangul
ValueCountFrequency (%)
산 150
 
8.9%
시 130
 
7.7%
논 129
 
7.7%
충 126
 
7.5%
청 125
 
7.4%
도 125
 
7.4%
남 125
 
7.4%
길 97
 
5.8%
로 88
 
5.2%
면 71
 
4.2%
Other values (91) 517
30.7%

소재지지번주소
Text

MISSING 

Distinct124
Distinct (%)87.9%
Missing16
Missing (%)10.2%
Memory size1.4 KiB
2024-01-10T07:11:13.259706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length20.22695
Min length15

Characters and Unicode

Total characters2852
Distinct characters111
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

Unique111 ?
Unique (%)78.7%

Sample

1st row충청남도 논산시 강경읍 태평리 6-7
2nd row충청남도 논산시 강경읍 대흥리 32-97
3rd row충청남도 논산시 강경읍 황산리 28-3
4th row충청남도 논산시 강경읍 홍교리 113
5th row충청남도 논산시 강경읍 동흥리 100-1
ValueCountFrequency (%)
충청남도 141
20.6%
논산시 141
20.6%
연무읍 17
 
2.5%
가야곡면 13
 
1.9%
강경읍 12
 
1.8%
연산면 12
 
1.8%
광석면 11
 
1.6%
노성면 11
 
1.6%
성동면 11
 
1.6%
강산동 8
 
1.2%
Other values (207) 306
44.8%
2024-01-10T07:11:13.609438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
542
19.0%
산 188
 
6.6%
남 145
 
5.1%
청 142
 
5.0%
충 141
 
4.9%
도 141
 
4.9%
논 141
 
4.9%
시 141
 
4.9%
리 111
 
3.9%
1 95
 
3.3%
Other values (101) 1065
37.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1764
61.9%
Space Separator 542
 
19.0%
Decimal Number 460
 
16.1%
Dash Punctuation 86
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 188
 
10.7%
남 145
 
8.2%
청 142
 
8.0%
충 141
 
8.0%
도 141
 
8.0%
논 141
 
8.0%
시 141
 
8.0%
리 111
 
6.3%
면 85
 
4.8%
동 52
 
2.9%
Other values (89) 477
27.0%
Decimal Number
ValueCountFrequency (%)
1 95
20.7%
2 71
15.4%
3 59
12.8%
4 38
 
8.3%
5 37
 
8.0%
9 37
 
8.0%
6 36
 
7.8%
7 34
 
7.4%
8 31
 
6.7%
0 22
 
4.8%
Space Separator
ValueCountFrequency (%)
542
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 86
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1764
61.9%
Common 1088
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 188
 
10.7%
남 145
 
8.2%
청 142
 
8.0%
충 141
 
8.0%
도 141
 
8.0%
논 141
 
8.0%
시 141
 
8.0%
리 111
 
6.3%
면 85
 
4.8%
동 52
 
2.9%
Other values (89) 477
27.0%
Common
ValueCountFrequency (%)
542
49.8%
1 95
 
8.7%
- 86
 
7.9%
2 71
 
6.5%
3 59
 
5.4%
4 38
 
3.5%
5 37
 
3.4%
9 37
 
3.4%
6 36
 
3.3%
7 34
 
3.1%
Other values (2) 53
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1764
61.9%
ASCII 1088
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
542
49.8%
1 95
 
8.7%
- 86
 
7.9%
2 71
 
6.5%
3 59
 
5.4%
4 38
 
3.5%
5 37
 
3.4%
9 37
 
3.4%
6 36
 
3.3%
7 34
 
3.1%
Other values (2) 53
 
4.9%
Hangul
ValueCountFrequency (%)
산 188
 
10.7%
남 145
 
8.2%
청 142
 
8.0%
충 141
 
8.0%
도 141
 
8.0%
논 141
 
8.0%
시 141
 
8.0%
리 111
 
6.3%
면 85
 
4.8%
동 52
 
2.9%
Other values (89) 477
27.0%

설치기구
Text

Distinct74
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-10T07:11:13.785528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length54
Median length34
Mean length22
Min length5

Characters and Unicode

Total characters3454
Distinct characters132
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)35.0%

Sample

1st row공중걷기+좌우파도타기+큰활차+역기올리기
2nd row공중걷기+좌우파도타기+큰활차+역기올리기
3rd row공중걷기+좌우파도타기+큰활차+역기올리기
4th row공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
5th row공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
ValueCountFrequency (%)
사이드플라잉+레그푸싱+웨이스트터닝+바디터닝 20
 
12.7%
마사지롤러+워밍숄더+에어서핑+레그프레스 12
 
7.6%
공중걷기+좌우파도타기+큰활차+역기올리기 9
 
5.7%
공중걷기+허리돌리기+두팔노젓기+매달려온몸회전하기 9
 
5.7%
공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기 8
 
5.1%
사이드스윙+터닝암+파워사이클+트위스트 7
 
4.5%
오금펴기+파도타기+허리돌리기+등허리지압기 6
 
3.8%
바디싯업+트위스트+마사지롤러+에어서핑 4
 
2.5%
노르딕머신+에어워킹+마사지롤러+워밍숄더 4
 
2.5%
달리기운동+큰활차머신+공중걷기+허리돌리기 4
 
2.5%
Other values (64) 74
47.1%
2024-01-10T07:11:14.066696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 458
 
13.3%
기 336
 
9.7%
리 203
 
5.9%
허 90
 
2.6%
이 77
 
2.2%
스 74
 
2.1%
사 73
 
2.1%
트 67
 
1.9%
돌 62
 
1.8%
지 58
 
1.7%
Other values (122) 1956
56.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2982
86.3%
Math Symbol 458
 
13.3%
Close Punctuation 6
 
0.2%
Open Punctuation 6
 
0.2%
Dash Punctuation 1
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 336
 
11.3%
리 203
 
6.8%
허 90
 
3.0%
이 77
 
2.6%
스 74
 
2.5%
사 73
 
2.4%
트 67
 
2.2%
돌 62
 
2.1%
지 58
 
1.9%
파 58
 
1.9%
Other values (117) 1884
63.2%
Math Symbol
ValueCountFrequency (%)
+ 458
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
L 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2982
86.3%
Common 471
 
13.6%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 336
 
11.3%
리 203
 
6.8%
허 90
 
3.0%
이 77
 
2.6%
스 74
 
2.5%
사 73
 
2.4%
트 67
 
2.2%
돌 62
 
2.1%
지 58
 
1.9%
파 58
 
1.9%
Other values (117) 1884
63.2%
Common
ValueCountFrequency (%)
+ 458
97.2%
) 6
 
1.3%
( 6
 
1.3%
- 1
 
0.2%
Latin
ValueCountFrequency (%)
L 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2982
86.3%
ASCII 472
 
13.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 458
97.0%
) 6
 
1.3%
( 6
 
1.3%
- 1
 
0.2%
L 1
 
0.2%
Hangul
ValueCountFrequency (%)
기 336
 
11.3%
리 203
 
6.8%
허 90
 
3.0%
이 77
 
2.6%
스 74
 
2.5%
사 73
 
2.4%
트 67
 
2.2%
돌 62
 
2.1%
지 58
 
1.9%
파 58
 
1.9%
Other values (117) 1884
63.2%

Interactions

2024-01-10T07:11:11.923729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:11:14.136894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도행정동설치기구
설치연도1.0000.5120.996
행정동0.5121.0000.700
설치기구0.9960.7001.000
2024-01-10T07:11:14.204281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치연도행정동
설치연도1.0000.187
행정동0.1871.000

Missing values

2024-01-10T07:11:12.013437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:11:12.083023image/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.
2024-01-10T07:11:12.150596image/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

설치연도행정동소재지도로명주소소재지지번주소설치기구
02014강경읍충청남도 논산시 강경읍 옥녀봉로27번길 24-4충청남도 논산시 강경읍 태평리 6-7공중걷기+좌우파도타기+큰활차+역기올리기
12014강경읍충청남도 논산시 강경읍 대흥로5번길 10충청남도 논산시 강경읍 대흥리 32-97공중걷기+좌우파도타기+큰활차+역기올리기
22014강경읍충청남도 논산시 강경읍 황산1길 22충청남도 논산시 강경읍 황산리 28-3공중걷기+좌우파도타기+큰활차+역기올리기
32014강경읍충청남도 논산시 강경읍 계백로219번길 22충청남도 논산시 강경읍 홍교리 113공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
42014강경읍충청남도 논산시 강경읍 금백로 163-1충청남도 논산시 강경읍 동흥리 100-1공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
52014연무읍<NA>충청남도 논산시 연무읍 동산리 267-2공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
62014연무읍<NA>충청남도 논산시 연무읍 양지리 1공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
72014연무읍<NA>충청남도 논산시 연무읍 죽본리 2공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
82014부적면충청남도 논산시 부적면 예학로3길 25충청남도 논산시 부적면 반송리 80공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기
92014노성면충청남도 논산시 노성면 노성로 438충청남도 논산시 노성면 송당리 184-1공중걷기+좌우파도타기+큰활차+역기올리기+등허리지압기+허리돌리기+윗몸일으키기
설치연도행정동소재지도로명주소소재지지번주소설치기구
1472019양촌면<NA>충청남도 논산시 양촌면 인천리 198-1평행봉+철봉+거꾸로매달리기
1482019강경읍충청남도 논산시 강경읍 골뜸길 30충청남도 논산시 강경읍 채운리 390-1하늘걷기(양면)+허리돌리기(양면)
1492019양촌면충청남도 논산시 황산벌로 257<NA>하늘걷기+달리기+어깨근육풀기+상체근육풀기
1502019강경읍<NA>충청남도 논산시 강경읍 대흥리 7-3하늘걷기+허리돌리기+등허리지압+파도타기+오금펴기+달리기
1512019강경읍충청남도 논산시 강경읍 옥녀봉로27번길 24-4충청남도 논산시 강경읍 태평리 6-7허리돌리기(양면)
1522019강경읍충청남도 논산시 강경읍 계백로219번길 9-3충청남도 논산시 강경읍 남교리 94-10허리돌리기+등허리지압+하늘걷기+파도타기외기
1532019취암동<NA>충청남도 논산시 지산동 859허리돌리기+상체근육풀기+파도타기
1542019광석면충청남도 논산시 광석면 명재로200번길 75-16충청남도 논산시 광석면 율리 26-1허리돌리기+어깨근육풀기+상체근육풀기+하늘걷기+허리돌리기
1552019부창동충청남도 논산시 중앙로506번길 28충청남도 논산시 대교동 321-50허리돌리기+옆파도타기+윗몸일으키기+오금펴기
1562019부창동충청남도 논산시 대화로 143충청남도 논산시 대교동 330허리돌리기+옆파도타기+윗몸일으키기+오금펴기

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설치연도행정동소재지도로명주소소재지지번주소설치기구# duplicates
12017부창동<NA>충청남도 논산시 대교동 319공중걷기+다리뻗치기+등허리지압기3
02017강경읍충청남도 논산시 강경읍 계백로167번길 12충청남도 논산시 강경읍 남교리 101-1등허리지압기+큰활차+자전거2