Overview

Dataset statistics

Number of variables6
Number of observations412
Missing cells501
Missing cells (%)20.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.8 KiB
Average record size in memory49.3 B

Variable types

Text3
Categorical1
Numeric1
DateTime1

Dataset

Description이 데이터는 충청남도 금산군의 정자현황으로 정자가 설치된 지번주소와 상세위치, 설치년도에 대한 데이터를 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=20&beforeMenuCd=DOM_000000201001001000&publicdatapk=15120669

Alerts

데이터기준일 has constant value ""Constant
상세위치 has 311 (75.5%) missing valuesMissing
설치년도 has 190 (46.1%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:30:05.605783
Analysis finished2024-01-09 22:30:06.156082
Duration0.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

Distinct374
Distinct (%)90.8%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-01-10T07:30:06.366078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.1504854
Min length6

Characters and Unicode

Total characters2534
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique336 ?
Unique (%)81.6%

Sample

1st row정자-001
2nd row정자-002
3rd row정자-003
4th row정자-004
5th row정자-005
ValueCountFrequency (%)
정자-131 2
 
0.5%
정자-123 2
 
0.5%
정자-128 2
 
0.5%
정자-112 2
 
0.5%
정자-127 2
 
0.5%
정자-126 2
 
0.5%
정자-125 2
 
0.5%
정자-124 2
 
0.5%
정자-121 2
 
0.5%
정자-119 2
 
0.5%
Other values (364) 392
95.1%
2024-01-10T07:30:06.757388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 443
17.5%
정 384
15.2%
자 384
15.2%
1 251
9.9%
0 188
7.4%
2 165
 
6.5%
3 150
 
5.9%
4 127
 
5.0%
8 103
 
4.1%
6 82
 
3.2%
Other values (5) 257
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1267
50.0%
Other Letter 824
32.5%
Dash Punctuation 443
 
17.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 251
19.8%
0 188
14.8%
2 165
13.0%
3 150
11.8%
4 127
10.0%
8 103
8.1%
6 82
 
6.5%
7 77
 
6.1%
9 65
 
5.1%
5 59
 
4.7%
Other Letter
ValueCountFrequency (%)
정 384
46.6%
자 384
46.6%
복 28
 
3.4%
수 28
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 443
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1710
67.5%
Hangul 824
32.5%

Most frequent character per script

Common
ValueCountFrequency (%)
- 443
25.9%
1 251
14.7%
0 188
11.0%
2 165
 
9.6%
3 150
 
8.8%
4 127
 
7.4%
8 103
 
6.0%
6 82
 
4.8%
7 77
 
4.5%
9 65
 
3.8%
Hangul
ValueCountFrequency (%)
정 384
46.6%
자 384
46.6%
복 28
 
3.4%
수 28
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1710
67.5%
Hangul 824
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 443
25.9%
1 251
14.7%
0 188
11.0%
2 165
 
9.6%
3 150
 
8.8%
4 127
 
7.4%
8 103
 
6.0%
6 82
 
4.8%
7 77
 
4.5%
9 65
 
3.8%
Hangul
ValueCountFrequency (%)
정 384
46.6%
자 384
46.6%
복 28
 
3.4%
수 28
 
3.4%

설치위치
Text

Distinct391
Distinct (%)94.9%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-01-10T07:30:06.991782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length21.378641
Min length16

Characters and Unicode

Total characters8808
Distinct characters124
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

Unique374 ?
Unique (%)90.8%

Sample

1st row충청남도 금산군 금산읍 신대리 305-3
2nd row충청남도 금산군 금산읍 신대리 806-7
3rd row충청남도 금산군 금산읍 신대리 510-3 부근
4th row충청남도 금산군 금산읍 신대리 785-22
5th row충청남도 금산군 남일면 황풍리 54-1
ValueCountFrequency (%)
충청남도 412
19.9%
금산군 412
19.9%
금산읍 60
 
2.9%
부리면 54
 
2.6%
군북면 47
 
2.3%
제원면 46
 
2.2%
금성면 39
 
1.9%
남이면 37
 
1.8%
진산면 36
 
1.7%
남일면 36
 
1.7%
Other values (486) 888
43.0%
2024-01-10T07:30:07.344667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1659
18.8%
산 533
 
6.1%
금 523
 
5.9%
남 489
 
5.6%
리 465
 
5.3%
군 459
 
5.2%
도 431
 
4.9%
충 412
 
4.7%
청 412
 
4.7%
면 352
 
4.0%
Other values (114) 3073
34.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5357
60.8%
Space Separator 1659
 
18.8%
Decimal Number 1498
 
17.0%
Dash Punctuation 294
 
3.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 533
9.9%
금 523
9.8%
남 489
9.1%
리 465
 
8.7%
군 459
 
8.6%
도 431
 
8.0%
충 412
 
7.7%
청 412
 
7.7%
면 352
 
6.6%
부 96
 
1.8%
Other values (102) 1185
22.1%
Decimal Number
ValueCountFrequency (%)
1 261
17.4%
2 213
14.2%
4 163
10.9%
3 161
10.7%
5 157
10.5%
6 133
8.9%
7 121
8.1%
8 102
 
6.8%
9 102
 
6.8%
0 85
 
5.7%
Space Separator
ValueCountFrequency (%)
1659
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 294
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5357
60.8%
Common 3451
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 533
9.9%
금 523
9.8%
남 489
9.1%
리 465
 
8.7%
군 459
 
8.6%
도 431
 
8.0%
충 412
 
7.7%
청 412
 
7.7%
면 352
 
6.6%
부 96
 
1.8%
Other values (102) 1185
22.1%
Common
ValueCountFrequency (%)
1659
48.1%
- 294
 
8.5%
1 261
 
7.6%
2 213
 
6.2%
4 163
 
4.7%
3 161
 
4.7%
5 157
 
4.5%
6 133
 
3.9%
7 121
 
3.5%
8 102
 
3.0%
Other values (2) 187
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5357
60.8%
ASCII 3451
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1659
48.1%
- 294
 
8.5%
1 261
 
7.6%
2 213
 
6.2%
4 163
 
4.7%
3 161
 
4.7%
5 157
 
4.5%
6 133
 
3.9%
7 121
 
3.5%
8 102
 
3.0%
Other values (2) 187
 
5.4%
Hangul
ValueCountFrequency (%)
산 533
9.9%
금 523
9.8%
남 489
9.1%
리 465
 
8.7%
군 459
 
8.6%
도 431
 
8.0%
충 412
 
7.7%
청 412
 
7.7%
면 352
 
6.6%
부 96
 
1.8%
Other values (102) 1185
22.1%

상세위치
Text

MISSING 

Distinct94
Distinct (%)93.1%
Missing311
Missing (%)75.5%
Memory size3.3 KiB
2024-01-10T07:30:07.629229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length17
Mean length7.7425743
Min length1

Characters and Unicode

Total characters782
Distinct characters180
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

Unique88 ?
Unique (%)87.1%

Sample

1st row부근
2nd row일원
3rd row일원
4th row절골체육공원
5th row절골체육공원
ValueCountFrequency (%)
옆 14
 
7.4%
내 10
 
5.3%
마을회관 6
 
3.2%
앞 6
 
3.2%
인근 5
 
2.7%
아인2리 5
 
2.7%
주공아파트 4
 
2.1%
아인1리 3
 
1.6%
공영주차장 3
 
1.6%
절골체육공원 3
 
1.6%
Other values (111) 129
68.6%
2024-01-10T07:30:08.019458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
87
 
11.1%
리 33
 
4.2%
아 24
 
3.1%
마 19
 
2.4%
을 17
 
2.2%
공 17
 
2.2%
원 17
 
2.2%
1 17
 
2.2%
인 16
 
2.0%
동 16
 
2.0%
Other values (170) 519
66.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 635
81.2%
Space Separator 87
 
11.1%
Decimal Number 50
 
6.4%
Dash Punctuation 5
 
0.6%
Math Symbol 3
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 33
 
5.2%
아 24
 
3.8%
마 19
 
3.0%
을 17
 
2.7%
공 17
 
2.7%
원 17
 
2.7%
인 16
 
2.5%
동 16
 
2.5%
옆 14
 
2.2%
장 14
 
2.2%
Other values (156) 448
70.6%
Decimal Number
ValueCountFrequency (%)
1 17
34.0%
2 10
20.0%
0 9
18.0%
3 3
 
6.0%
4 3
 
6.0%
7 3
 
6.0%
9 2
 
4.0%
5 2
 
4.0%
8 1
 
2.0%
Space Separator
ValueCountFrequency (%)
87
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 635
81.2%
Common 147
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 33
 
5.2%
아 24
 
3.8%
마 19
 
3.0%
을 17
 
2.7%
공 17
 
2.7%
원 17
 
2.7%
인 16
 
2.5%
동 16
 
2.5%
옆 14
 
2.2%
장 14
 
2.2%
Other values (156) 448
70.6%
Common
ValueCountFrequency (%)
87
59.2%
1 17
 
11.6%
2 10
 
6.8%
0 9
 
6.1%
- 5
 
3.4%
3 3
 
2.0%
4 3
 
2.0%
7 3
 
2.0%
~ 3
 
2.0%
9 2
 
1.4%
Other values (4) 5
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 635
81.2%
ASCII 147
 
18.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
87
59.2%
1 17
 
11.6%
2 10
 
6.8%
0 9
 
6.1%
- 5
 
3.4%
3 3
 
2.0%
4 3
 
2.0%
7 3
 
2.0%
~ 3
 
2.0%
9 2
 
1.4%
Other values (4) 5
 
3.4%
Hangul
ValueCountFrequency (%)
리 33
 
5.2%
아 24
 
3.8%
마 19
 
3.0%
을 17
 
2.7%
공 17
 
2.7%
원 17
 
2.7%
인 16
 
2.5%
동 16
 
2.5%
옆 14
 
2.2%
장 14
 
2.2%
Other values (156) 448
70.6%

관리주체
Categorical

Distinct10
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
충청남도 금산군 금산읍
60 
충청남도 금산군 부리면
54 
충청남도 금산군 군북면
47 
충청남도 금산군 제원면
46 
충청남도 금산군 금성면
39 
Other values (5)
166 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row충청남도 금산군 금산읍
2nd row충청남도 금산군 금산읍
3rd row충청남도 금산군 금산읍
4th row충청남도 금산군 금산읍
5th row충청남도 금산군 남일면

Common Values

ValueCountFrequency (%)
충청남도 금산군 금산읍 60
14.6%
충청남도 금산군 부리면 54
13.1%
충청남도 금산군 군북면 47
11.4%
충청남도 금산군 제원면 46
11.2%
충청남도 금산군 금성면 39
9.5%
충청남도 금산군 남이면 37
9.0%
충청남도 금산군 남일면 36
8.7%
충청남도 금산군 진산면 36
8.7%
충청남도 금산군 추부면 29
7.0%
충청남도 금산군 복수면 28
6.8%

Length

2024-01-10T07:30:08.150459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:30:08.265858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충청남도 412
33.3%
금산군 412
33.3%
금산읍 60
 
4.9%
부리면 54
 
4.4%
군북면 47
 
3.8%
제원면 46
 
3.7%
금성면 39
 
3.2%
남이면 37
 
3.0%
남일면 36
 
2.9%
진산면 36
 
2.9%
Other values (2) 57
 
4.6%

설치년도
Real number (ℝ)

MISSING 

Distinct23
Distinct (%)10.4%
Missing190
Missing (%)46.1%
Infinite0
Infinite (%)0.0%
Mean2007.9775
Minimum2000
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.8 KiB
2024-01-10T07:30:08.402115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2003
Q12004
median2006
Q32010
95-th percentile2020.95
Maximum2022
Range22
Interquartile range (IQR)6

Descriptive statistics

Standard deviation5.2704621
Coefficient of variation (CV)0.0026247616
Kurtosis0.69965101
Mean2007.9775
Median Absolute Deviation (MAD)2
Skewness1.3230643
Sum445771
Variance27.777771
MonotonicityNot monotonic
2024-01-10T07:30:08.503392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2005 48
 
11.7%
2004 44
 
10.7%
2006 27
 
6.6%
2010 19
 
4.6%
2003 12
 
2.9%
2021 10
 
2.4%
2009 8
 
1.9%
2008 8
 
1.9%
2020 7
 
1.7%
2007 6
 
1.5%
Other values (13) 33
 
8.0%
(Missing) 190
46.1%
ValueCountFrequency (%)
2000 1
 
0.2%
2001 1
 
0.2%
2002 2
 
0.5%
2003 12
 
2.9%
2004 44
10.7%
2005 48
11.7%
2006 27
6.6%
2007 6
 
1.5%
2008 8
 
1.9%
2009 8
 
1.9%
ValueCountFrequency (%)
2022 2
 
0.5%
2021 10
2.4%
2020 7
1.7%
2019 1
 
0.2%
2018 1
 
0.2%
2017 3
 
0.7%
2016 3
 
0.7%
2015 4
 
1.0%
2014 5
1.2%
2013 5
1.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
Minimum2023-08-28 00:00:00
Maximum2023-08-28 00:00:00
2024-01-10T07:30:08.588822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:30:08.669348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T07:30:05.847225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T07:30:08.736023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세위치관리주체설치년도
상세위치1.0000.0001.000
관리주체0.0001.0000.574
설치년도1.0000.5741.000
2024-01-10T07:30:08.834382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
설치년도관리주체
설치년도1.0000.323
관리주체0.3231.000

Missing values

2024-01-10T07:30:05.948552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:30:06.038368image/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.
2024-01-10T07:30:06.115201image/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

관리번호설치위치상세위치관리주체설치년도데이터기준일
0정자-001충청남도 금산군 금산읍 신대리 305-3<NA>충청남도 금산군 금산읍20042023-08-28
1정자-002충청남도 금산군 금산읍 신대리 806-7<NA>충청남도 금산군 금산읍20102023-08-28
2정자-003충청남도 금산군 금산읍 신대리 510-3 부근부근충청남도 금산군 금산읍20032023-08-28
3정자-004충청남도 금산군 금산읍 신대리 785-22<NA>충청남도 금산군 금산읍20132023-08-28
4정자-005충청남도 금산군 남일면 황풍리 54-1<NA>충청남도 금산군 남일면20082023-08-28
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