Overview

Dataset statistics

Number of variables7
Number of observations205
Missing cells205
Missing cells (%)14.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.9 KiB
Average record size in memory59.6 B

Variable types

Numeric3
Categorical2
Text2

Dataset

Description대구광역시 북구의 기계설비 성능점검 대상 건축물 현황(구분, 건물명, 주소, 우편번호, 연면적(건축물), 세대수(공동주택)) 정보를 제공합니다.
Author대구광역시 북구
URLhttps://www.data.go.kr/data/15112807/fileData.do

Alerts

데이터 기준일자 has constant value ""Constant
연번 is highly overall correlated with 연면적(건축물) and 2 other fieldsHigh correlation
연면적(건축물) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
세대수(공동주택) is highly overall correlated with 연번 and 1 other fieldsHigh correlation
구분 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연면적(건축물) has 105 (51.2%) missing valuesMissing
세대수(공동주택) has 100 (48.8%) missing valuesMissing
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:44:55.817771
Analysis finished2024-04-06 08:45:00.911628
Duration5.09 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct205
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103
Minimum1
Maximum205
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T17:45:01.124643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11.2
Q152
median103
Q3154
95-th percentile194.8
Maximum205
Range204
Interquartile range (IQR)102

Descriptive statistics

Standard deviation59.322565
Coefficient of variation (CV)0.57594723
Kurtosis-1.2
Mean103
Median Absolute Deviation (MAD)51
Skewness0
Sum21115
Variance3519.1667
MonotonicityStrictly increasing
2024-04-06T17:45:01.549958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
142 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
135 1
 
0.5%
136 1
 
0.5%
137 1
 
0.5%
138 1
 
0.5%
139 1
 
0.5%
Other values (195) 195
95.1%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
205 1
0.5%
204 1
0.5%
203 1
0.5%
202 1
0.5%
201 1
0.5%
200 1
0.5%
199 1
0.5%
198 1
0.5%
197 1
0.5%
196 1
0.5%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
공동주택
105 
건축물
100 

Length

Max length4
Median length4
Mean length3.5121951
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공동주택 105
51.2%
건축물 100
48.8%

Length

2024-04-06T17:45:01.918763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:45:02.195921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공동주택 105
51.2%
건축물 100
48.8%

건물명
Text

Distinct203
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-06T17:45:02.702527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.3268293
Min length4

Characters and Unicode

Total characters1707
Distinct characters269
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique201 ?
Unique (%)98.0%

Sample

1st row경북대학교
2nd row칠곡경북대학교병원
3rd row(주)엑스코
4th row산업용재관
5th row롯데역사㈜ 대구점
ValueCountFrequency (%)
경북대학교 6
 
2.5%
힐스테이트데시앙 3
 
1.3%
명성푸르지오 2
 
0.8%
침산화성파크드림 2
 
0.8%
대구점 2
 
0.8%
강북아울렛 2
 
0.8%
주)엑스코 2
 
0.8%
칠곡부영5단지 1
 
0.4%
매천센트럴파크 1
 
0.4%
브라운스톤강북아파트 1
 
0.4%
Other values (216) 216
90.8%
2024-04-06T17:45:03.725712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 77
 
4.5%
구 57
 
3.3%
학 47
 
2.8%
아 45
 
2.6%
지 44
 
2.6%
트 41
 
2.4%
교 41
 
2.4%
스 40
 
2.3%
파 34
 
2.0%
칠 33
 
1.9%
Other values (259) 1248
73.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1593
93.3%
Decimal Number 45
 
2.6%
Space Separator 33
 
1.9%
Uppercase Letter 13
 
0.8%
Lowercase Letter 11
 
0.6%
Close Punctuation 4
 
0.2%
Open Punctuation 4
 
0.2%
Other Symbol 3
 
0.2%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 77
 
4.8%
구 57
 
3.6%
학 47
 
3.0%
아 45
 
2.8%
지 44
 
2.8%
트 41
 
2.6%
교 41
 
2.6%
스 40
 
2.5%
파 34
 
2.1%
칠 33
 
2.1%
Other values (231) 1134
71.2%
Decimal Number
ValueCountFrequency (%)
2 16
35.6%
1 13
28.9%
3 4
 
8.9%
5 3
 
6.7%
6 3
 
6.7%
4 2
 
4.4%
0 2
 
4.4%
8 1
 
2.2%
7 1
 
2.2%
Uppercase Letter
ValueCountFrequency (%)
H 4
30.8%
L 2
15.4%
K 2
15.4%
N 1
 
7.7%
M 1
 
7.7%
W 1
 
7.7%
F 1
 
7.7%
T 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
e 4
36.4%
w 2
18.2%
t 2
18.2%
k 1
 
9.1%
a 1
 
9.1%
r 1
 
9.1%
Space Separator
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1596
93.5%
Common 87
 
5.1%
Latin 24
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 77
 
4.8%
구 57
 
3.6%
학 47
 
2.9%
아 45
 
2.8%
지 44
 
2.8%
트 41
 
2.6%
교 41
 
2.6%
스 40
 
2.5%
파 34
 
2.1%
칠 33
 
2.1%
Other values (232) 1137
71.2%
Latin
ValueCountFrequency (%)
e 4
16.7%
H 4
16.7%
L 2
8.3%
w 2
8.3%
t 2
8.3%
K 2
8.3%
N 1
 
4.2%
M 1
 
4.2%
W 1
 
4.2%
F 1
 
4.2%
Other values (4) 4
16.7%
Common
ValueCountFrequency (%)
33
37.9%
2 16
18.4%
1 13
 
14.9%
3 4
 
4.6%
) 4
 
4.6%
( 4
 
4.6%
5 3
 
3.4%
6 3
 
3.4%
4 2
 
2.3%
0 2
 
2.3%
Other values (3) 3
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1593
93.3%
ASCII 111
 
6.5%
None 3
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 77
 
4.8%
구 57
 
3.6%
학 47
 
3.0%
아 45
 
2.8%
지 44
 
2.8%
트 41
 
2.6%
교 41
 
2.6%
스 40
 
2.5%
파 34
 
2.1%
칠 33
 
2.1%
Other values (231) 1134
71.2%
ASCII
ValueCountFrequency (%)
33
29.7%
2 16
14.4%
1 13
 
11.7%
e 4
 
3.6%
3 4
 
3.6%
H 4
 
3.6%
) 4
 
3.6%
( 4
 
3.6%
5 3
 
2.7%
6 3
 
2.7%
Other values (17) 23
20.7%
None
ValueCountFrequency (%)
㈜ 3
100.0%

주소
Text

Distinct195
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-04-06T17:45:04.543072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length16.585366
Min length12

Characters and Unicode

Total characters3400
Distinct characters83
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

Unique186 ?
Unique (%)90.7%

Sample

1st row대구광역시 북구 대학로 80
2nd row대구광역시 북구 호국로 807
3rd row대구광역시 북구 엑스코로 10
4th row대구광역시 북구 유통단지로16
5th row대구광역시 북구 태평로 161
ValueCountFrequency (%)
대구광역시 205
24.9%
북구 203
24.7%
칠곡중앙대로 9
 
1.1%
10 8
 
1.0%
침산로 7
 
0.9%
내곡로 7
 
0.9%
50 6
 
0.7%
80 6
 
0.7%
구암서로 6
 
0.7%
동북로 6
 
0.7%
Other values (210) 359
43.7%
2024-04-06T17:45:05.758137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
617
18.1%
구 429
12.6%
대 236
 
6.9%
북 217
 
6.4%
시 206
 
6.1%
역 205
 
6.0%
광 205
 
6.0%
로 195
 
5.7%
1 124
 
3.6%
0 70
 
2.1%
Other values (73) 896
26.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2215
65.1%
Space Separator 617
 
18.1%
Decimal Number 565
 
16.6%
Dash Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 429
19.4%
대 236
10.7%
북 217
9.8%
시 206
9.3%
역 205
9.3%
광 205
9.3%
로 195
8.8%
길 60
 
2.7%
동 34
 
1.5%
암 25
 
1.1%
Other values (61) 403
18.2%
Decimal Number
ValueCountFrequency (%)
1 124
21.9%
0 70
12.4%
2 68
12.0%
5 63
11.2%
4 54
9.6%
3 49
 
8.7%
7 43
 
7.6%
8 32
 
5.7%
6 32
 
5.7%
9 30
 
5.3%
Space Separator
ValueCountFrequency (%)
617
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2215
65.1%
Common 1185
34.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 429
19.4%
대 236
10.7%
북 217
9.8%
시 206
9.3%
역 205
9.3%
광 205
9.3%
로 195
8.8%
길 60
 
2.7%
동 34
 
1.5%
암 25
 
1.1%
Other values (61) 403
18.2%
Common
ValueCountFrequency (%)
617
52.1%
1 124
 
10.5%
0 70
 
5.9%
2 68
 
5.7%
5 63
 
5.3%
4 54
 
4.6%
3 49
 
4.1%
7 43
 
3.6%
8 32
 
2.7%
6 32
 
2.7%
Other values (2) 33
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2215
65.1%
ASCII 1185
34.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
617
52.1%
1 124
 
10.5%
0 70
 
5.9%
2 68
 
5.7%
5 63
 
5.3%
4 54
 
4.6%
3 49
 
4.1%
7 43
 
3.6%
8 32
 
2.7%
6 32
 
2.7%
Other values (2) 33
 
2.8%
Hangul
ValueCountFrequency (%)
구 429
19.4%
대 236
10.7%
북 217
9.8%
시 206
9.3%
역 205
9.3%
광 205
9.3%
로 195
8.8%
길 60
 
2.7%
동 34
 
1.5%
암 25
 
1.1%
Other values (61) 403
18.2%

연면적(건축물)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct99
Distinct (%)99.0%
Missing105
Missing (%)51.2%
Infinite0
Infinite (%)0.0%
Mean32866.441
Minimum10166.93
Maximum456384
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T17:45:06.135072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10166.93
5-th percentile11323.996
Q112989.51
median16120.743
Q326502.803
95-th percentile97657.101
Maximum456384
Range446217.07
Interquartile range (IQR)13513.293

Descriptive statistics

Standard deviation52625.98
Coefficient of variation (CV)1.6012071
Kurtosis43.299685
Mean32866.441
Median Absolute Deviation (MAD)4326.8525
Skewness5.8934031
Sum3286644.1
Variance2.7694938 × 109
MonotonicityDecreasing
2024-04-06T17:45:06.524338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17466.54 2
 
1.0%
13734.96 1
 
0.5%
12996.97 1
 
0.5%
13345.56 1
 
0.5%
13345.68 1
 
0.5%
13376.94 1
 
0.5%
13434.0 1
 
0.5%
13481.08 1
 
0.5%
13505.0 1
 
0.5%
13587.53 1
 
0.5%
Other values (89) 89
43.4%
(Missing) 105
51.2%
ValueCountFrequency (%)
10166.93 1
0.5%
10546.31 1
0.5%
11066.82 1
0.5%
11100.0 1
0.5%
11129.18 1
0.5%
11334.25 1
0.5%
11547.71 1
0.5%
11597.74 1
0.5%
11758.18 1
0.5%
11829.6 1
0.5%
ValueCountFrequency (%)
456384.0 1
0.5%
188769.84 1
0.5%
146068.947 1
0.5%
131478.42 1
0.5%
131035.57 1
0.5%
95900.34 1
0.5%
81209.56 1
0.5%
77587.0 1
0.5%
75594.99 1
0.5%
66959.85 1
0.5%

세대수(공동주택)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct99
Distinct (%)94.3%
Missing100
Missing (%)48.8%
Infinite0
Infinite (%)0.0%
Mean837.82857
Minimum441
Maximum1937
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-06T17:45:06.859829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum441
5-th percentile510.2
Q1594
median746
Q3977
95-th percentile1429.8
Maximum1937
Range1496
Interquartile range (IQR)383

Descriptive statistics

Standard deviation312.24277
Coefficient of variation (CV)0.37268098
Kurtosis1.6379266
Mean837.82857
Median Absolute Deviation (MAD)168
Skewness1.3025775
Sum87972
Variance97495.547
MonotonicityDecreasing
2024-04-06T17:45:07.228315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
585 2
 
1.0%
746 2
 
1.0%
768 2
 
1.0%
683 2
 
1.0%
900 2
 
1.0%
977 2
 
1.0%
509 1
 
0.5%
602 1
 
0.5%
619 1
 
0.5%
620 1
 
0.5%
Other values (89) 89
43.4%
(Missing) 100
48.8%
ValueCountFrequency (%)
441 1
0.5%
450 1
0.5%
488 1
0.5%
500 1
0.5%
503 1
0.5%
509 1
0.5%
515 1
0.5%
518 1
0.5%
525 1
0.5%
527 1
0.5%
ValueCountFrequency (%)
1937 1
0.5%
1862 1
0.5%
1702 1
0.5%
1580 1
0.5%
1493 1
0.5%
1440 1
0.5%
1389 1
0.5%
1354 1
0.5%
1282 1
0.5%
1252 1
0.5%

데이터 기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2024-03-29
205 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-29
2nd row2024-03-29
3rd row2024-03-29
4th row2024-03-29
5th row2024-03-29

Common Values

ValueCountFrequency (%)
2024-03-29 205
100.0%

Length

2024-04-06T17:45:07.676873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-06T17:45:07.951446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-03-29 205
100.0%

Interactions

2024-04-06T17:44:59.042852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:56.598556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:58.264727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:59.292927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:57.526680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:58.497017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:59.537175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:57.933436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-06T17:44:58.730814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:45:08.116849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번구분연면적(건축물)세대수(공동주택)
연번1.0001.0000.4780.949
구분1.0001.000NaNNaN
연면적(건축물)0.478NaN1.000NaN
세대수(공동주택)0.949NaNNaN1.000
2024-04-06T17:45:08.385842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번연면적(건축물)세대수(공동주택)구분
연번1.000-1.000-1.0000.954
연면적(건축물)-1.0001.000NaN1.000
세대수(공동주택)-1.000NaN1.0001.000
구분0.9541.0001.0001.000

Missing values

2024-04-06T17:44:59.963726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:45:00.351554image/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.
2024-04-06T17:45:00.768100image/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

연번구분건물명주소연면적(건축물)세대수(공동주택)데이터 기준일자
01건축물경북대학교대구광역시 북구 대학로 80456384.0<NA>2024-03-29
12건축물칠곡경북대학교병원대구광역시 북구 호국로 807188769.84<NA>2024-03-29
23건축물(주)엑스코대구광역시 북구 엑스코로 10146068.947<NA>2024-03-29
34건축물산업용재관대구광역시 북구 유통단지로16131478.42<NA>2024-03-29
45건축물롯데역사㈜ 대구점대구광역시 북구 태평로 161131035.57<NA>2024-03-29
56건축물대구보건대학교대구광역시 북구 영송로 1595900.34<NA>2024-03-29
67건축물대구과학대학교대구광역시 북구 영송로 4781209.56<NA>2024-03-29
78건축물농산물시장대구광역시 북구 매천로 18길 3477587.0<NA>2024-03-29
89건축물대구종합유통단지 전자관대구광역시 북구 유통단지로 4575594.99<NA>2024-03-29
910건축물영진전문대학교대구광역시 북구 복현로 3566959.85<NA>2024-03-29
연번구분건물명주소연면적(건축물)세대수(공동주택)데이터 기준일자
195196공동주택대현e편한세상대구광역시 북구 대현로10길 82<NA>5272024-03-29
196197공동주택칠곡네스빌대구광역시 북구 동천로 155<NA>5252024-03-29
197198공동주택청구장미마을대구광역시 북구 칠곡중앙대로 45<NA>5182024-03-29
198199공동주택화성리버파크2단지대구광역시 북구 서변로 50<NA>5152024-03-29
199200공동주택대한동아침산1차무지개아파트대구광역시 북구 침산로21길 24<NA>5092024-03-29
200201공동주택연경우방아이유쉘더포레스트대구광역시 북구 연경중앙로11길 33<NA>5032024-03-29
201202공동주택매천화성파크드림대구광역시 북구 매전로 17<NA>5002024-03-29
202203공동주택침산2차화성타운대구광역시 북구 침산남로37길 24<NA>4882024-03-29
203204공동주택복현대백맨션대구광역시 북구 복현로 137<NA>4502024-03-29
204205공동주택칠곡현대1차아파트대구광역시 북구 구암로16길 7<NA>4412024-03-29