Overview

Dataset statistics

Number of variables5
Number of observations53
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory44.5 B

Variable types

Numeric2
Text2
Categorical1

Dataset

Description2019년 9월 5일 기준 대상건축물 : 연면적이 500제곱미터 이상인 공공건축물, 의료시설, 노인ㆍ어린이시설 (단, 어린이집은 연면적이 430제곱미터 이상) 데이터파일입니다.
Author충청북도 괴산군
URLhttps://www.data.go.kr/data/3046085/fileData.do

Alerts

데이터기준일 has constant value ""Constant
구분 has unique valuesUnique
명칭 has unique valuesUnique
석면건축자재면적 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:56:08.032045
Analysis finished2023-12-11 23:56:08.615798
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T08:56:08.910280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.6
Q114
median27
Q340
95-th percentile50.4
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.443445
Coefficient of variation (CV)0.57197945
Kurtosis-1.2
Mean27
Median Absolute Deviation (MAD)13
Skewness0
Sum1431
Variance238.5
MonotonicityStrictly increasing
2023-12-12T08:56:09.024501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.9%
41 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
53 1
1.9%
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%

명칭
Text

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T08:56:09.232337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.0943396
Min length4

Characters and Unicode

Total characters429
Distinct characters114
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

Unique53 ?
Unique (%)100.0%

Sample

1st row괴산경찰서
2nd row괴산등기소
3rd row괴산우체국
4th row괴산도서관
5th row공공하수처리장
ValueCountFrequency (%)
폐교 6
 
7.1%
본관교사 5
 
5.9%
외 5
 
5.9%
괴산농협 3
 
3.5%
한국전력공사 3
 
3.5%
1동 2
 
2.4%
4동 2
 
2.4%
불정농협 2
 
2.4%
괴산경찰서 1
 
1.2%
불정소망어린이집 1
 
1.2%
Other values (55) 55
64.7%
2023-12-12T08:56:09.679376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32
 
7.5%
사 26
 
6.1%
교 21
 
4.9%
소 17
 
4.0%
산 17
 
4.0%
괴 15
 
3.5%
관 11
 
2.6%
면 10
 
2.3%
동 9
 
2.1%
무 9
 
2.1%
Other values (104) 262
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 390
90.9%
Space Separator 32
 
7.5%
Decimal Number 6
 
1.4%
Close Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 26
 
6.7%
교 21
 
5.4%
소 17
 
4.4%
산 17
 
4.4%
괴 15
 
3.8%
관 11
 
2.8%
면 10
 
2.6%
동 9
 
2.3%
무 9
 
2.3%
장 8
 
2.1%
Other values (98) 247
63.3%
Decimal Number
ValueCountFrequency (%)
4 2
33.3%
1 2
33.3%
5 1
16.7%
2 1
16.7%
Space Separator
ValueCountFrequency (%)
32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 390
90.9%
Common 39
 
9.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 26
 
6.7%
교 21
 
5.4%
소 17
 
4.4%
산 17
 
4.4%
괴 15
 
3.8%
관 11
 
2.8%
면 10
 
2.6%
동 9
 
2.3%
무 9
 
2.3%
장 8
 
2.1%
Other values (98) 247
63.3%
Common
ValueCountFrequency (%)
32
82.1%
4 2
 
5.1%
1 2
 
5.1%
5 1
 
2.6%
2 1
 
2.6%
) 1
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 390
90.9%
ASCII 39
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32
82.1%
4 2
 
5.1%
1 2
 
5.1%
5 1
 
2.6%
2 1
 
2.6%
) 1
 
2.6%
Hangul
ValueCountFrequency (%)
사 26
 
6.7%
교 21
 
5.4%
소 17
 
4.4%
산 17
 
4.4%
괴 15
 
3.8%
관 11
 
2.8%
면 10
 
2.6%
동 9
 
2.3%
무 9
 
2.3%
장 8
 
2.1%
Other values (98) 247
63.3%

석면건축자재면적
Real number (ℝ)

UNIQUE 

Distinct53
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean629.16906
Minimum59.06
Maximum3584.82
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size609.0 B
2023-12-12T08:56:09.827712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum59.06
5-th percentile70.1
Q1264.04
median415.04
Q3727.5
95-th percentile1968.134
Maximum3584.82
Range3525.76
Interquartile range (IQR)463.46

Descriptive statistics

Standard deviation659.62011
Coefficient of variation (CV)1.0483988
Kurtosis7.8359228
Mean629.16906
Median Absolute Deviation (MAD)254.15
Skewness2.5134222
Sum33345.96
Variance435098.69
MonotonicityNot monotonic
2023-12-12T08:56:09.989135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1869.93 1
 
1.9%
565.88 1
 
1.9%
169.18 1
 
1.9%
83.83 1
 
1.9%
366.17 1
 
1.9%
75.3 1
 
1.9%
380.5 1
 
1.9%
2115.44 1
 
1.9%
626.59 1
 
1.9%
1233.97 1
 
1.9%
Other values (43) 43
81.1%
ValueCountFrequency (%)
59.06 1
1.9%
60.55 1
1.9%
62.3 1
1.9%
75.3 1
1.9%
80.36 1
1.9%
83.83 1
1.9%
87.49 1
1.9%
119.85 1
1.9%
128.4 1
1.9%
129.92 1
1.9%
ValueCountFrequency (%)
3584.82 1
1.9%
2454.4 1
1.9%
2115.44 1
1.9%
1869.93 1
1.9%
1505.21 1
1.9%
1233.97 1
1.9%
1132.8 1
1.9%
1096.72 1
1.9%
1044.41 1
1.9%
908.87 1
1.9%

주소
Text

Distinct52
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size556.0 B
2023-12-12T08:56:10.272673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length32
Mean length24.471698
Min length18

Characters and Unicode

Total characters1297
Distinct characters102
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

Unique51 ?
Unique (%)96.2%

Sample

1st row충청북도 괴산군 괴산읍 읍내로11길 26
2nd row충청북도 괴산군 괴산읍 읍내로5길 20
3rd row충청북도 괴산군 괴산읍 읍내로6길 18
4th row충청북도 괴산군 괴산읍 읍내로12길38
5th row충청북도 괴산군 괴산읍 제월로 60
ValueCountFrequency (%)
충청북도 53
19.4%
괴산군 53
19.4%
괴산읍 18
 
6.6%
청천면 8
 
2.9%
청안면 5
 
1.8%
15 4
 
1.5%
7 4
 
1.5%
감물면 4
 
1.5%
연풍면 4
 
1.5%
사리면 4
 
1.5%
Other values (102) 116
42.5%
2023-12-12T08:56:10.687527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
226
17.4%
괴 75
 
5.8%
산 74
 
5.7%
청 68
 
5.2%
도 56
 
4.3%
충 54
 
4.2%
북 53
 
4.1%
군 53
 
4.1%
1 52
 
4.0%
로 43
 
3.3%
Other values (92) 543
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 789
60.8%
Decimal Number 228
 
17.6%
Space Separator 226
 
17.4%
Dash Punctuation 21
 
1.6%
Close Punctuation 15
 
1.2%
Open Punctuation 15
 
1.2%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
괴 75
 
9.5%
산 74
 
9.4%
청 68
 
8.6%
도 56
 
7.1%
충 54
 
6.8%
북 53
 
6.7%
군 53
 
6.7%
로 43
 
5.4%
면 35
 
4.4%
길 29
 
3.7%
Other values (77) 249
31.6%
Decimal Number
ValueCountFrequency (%)
1 52
22.8%
2 41
18.0%
3 32
14.0%
6 19
 
8.3%
5 19
 
8.3%
4 18
 
7.9%
0 14
 
6.1%
7 12
 
5.3%
9 11
 
4.8%
8 10
 
4.4%
Space Separator
ValueCountFrequency (%)
226
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
60.8%
Common 508
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
괴 75
 
9.5%
산 74
 
9.4%
청 68
 
8.6%
도 56
 
7.1%
충 54
 
6.8%
북 53
 
6.7%
군 53
 
6.7%
로 43
 
5.4%
면 35
 
4.4%
길 29
 
3.7%
Other values (77) 249
31.6%
Common
ValueCountFrequency (%)
226
44.5%
1 52
 
10.2%
2 41
 
8.1%
3 32
 
6.3%
- 21
 
4.1%
6 19
 
3.7%
5 19
 
3.7%
4 18
 
3.5%
) 15
 
3.0%
( 15
 
3.0%
Other values (5) 50
 
9.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 789
60.8%
ASCII 508
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
226
44.5%
1 52
 
10.2%
2 41
 
8.1%
3 32
 
6.3%
- 21
 
4.1%
6 19
 
3.7%
5 19
 
3.7%
4 18
 
3.5%
) 15
 
3.0%
( 15
 
3.0%
Other values (5) 50
 
9.8%
Hangul
ValueCountFrequency (%)
괴 75
 
9.5%
산 74
 
9.4%
청 68
 
8.6%
도 56
 
7.1%
충 54
 
6.8%
북 53
 
6.7%
군 53
 
6.7%
로 43
 
5.4%
면 35
 
4.4%
길 29
 
3.7%
Other values (77) 249
31.6%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size556.0 B
2019-09-05
53 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-09-05
2nd row2019-09-05
3rd row2019-09-05
4th row2019-09-05
5th row2019-09-05

Common Values

ValueCountFrequency (%)
2019-09-05 53
100.0%

Length

2023-12-12T08:56:10.808919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:56:10.895664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019-09-05 53
100.0%

Interactions

2023-12-12T08:56:08.354205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:56:08.222234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:56:08.419093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:56:08.291439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:56:10.948097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분명칭석면건축자재면적주소
구분1.0001.0000.3371.000
명칭1.0001.0001.0001.000
석면건축자재면적0.3371.0001.0001.000
주소1.0001.0001.0001.000
2023-12-12T08:56:11.025358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분석면건축자재면적
구분1.0000.013
석면건축자재면적0.0131.000

Missing values

2023-12-12T08:56:08.508852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:56:08.579157image/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.

Sample

구분명칭석면건축자재면적주소데이터기준일
01괴산경찰서1869.93충청북도 괴산군 괴산읍 읍내로11길 262019-09-05
12괴산등기소80.36충청북도 괴산군 괴산읍 읍내로5길 202019-09-05
23괴산우체국761.93충청북도 괴산군 괴산읍 읍내로6길 182019-09-05
34괴산도서관669.19충청북도 괴산군 괴산읍 읍내로12길382019-09-05
45공공하수처리장637.83충청북도 괴산군 괴산읍 제월로 602019-09-05
56여성회관719.93충청북도 괴산군 괴산읍 동부리 675-22019-09-05
67괴산군청3584.82충청북도 괴산군 괴산읍 임꺽정로 902019-09-05
78괴산읍사무소1505.21충청북도 괴산군 괴산읍 읍내로13길 502019-09-05
89감물면사무소303.8충청북도 괴산군 감물면 충민로신대길 132019-09-05
910문광면사무소213.04충청북도 괴산군 문광면 광덕길 272019-09-05
구분명칭석면건축자재면적주소데이터기준일
4344신월분교 본관교사 외 2동129.92충청북도 괴산군 청천면 괴산로신월3길 10(신월리 144)2019-09-05
4445오수초 폐교807.44충청북도 괴산군 연풍면 유상길 852019-09-05
4546장암분교 폐교60.55충청북도 괴산군 청안면 장암로 296-102019-09-05
4647장연중 폐교727.5충청북도 괴산군 장연면 미선로오가2길 322019-09-05
4748대후분교 본관교사외5동264.04충청북도 괴산군 청천면 도경로후영4길 12(후영리 196-1)2019-09-05
4849신기초교 본관교사 외 4동407.5충청북도 괴산군 괴산읍 신기로3길 43(신기리 469)2019-09-05
4950덕평분교 본관교사 외 4동1132.8충청북도 괴산군 청천면 송문로덕평2길 42(덕평리 280)2019-09-05
5051감물중 본관교사 외 1동908.87충청북도 괴산군 감물면 맹이재로 611-7(광전리 112)2019-09-05
5152괴산성현수양관417.01충청북도 괴산군 감물면 주월로282-35(구월리116-1)2019-09-05
5253구)광신분교 본관교사 외 1동296.08충청북도 괴산군 소수면 원소로몽촌1길11-10, 몽촌리2252019-09-05