Overview

Dataset statistics

Number of variables6
Number of observations164
Missing cells44
Missing cells (%)4.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory50.8 B

Variable types

Numeric2
Text2
DateTime1
Categorical1

Dataset

Description인천광역시 부평구 공공건축물 현황 데이터는 부평구 내 공공건축물에 대한 건물명, 주소(도로명), 건축물 면적, 용도 등 에 대한 정보를 제공합니다.
Author인천광역시 부평구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15112818&srcSe=7661IVAWM27C61E190

Alerts

건축일자 has 44 (26.8%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 06:08:31.322790
Analysis finished2024-01-28 06:08:31.977623
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct164
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.5
Minimum1
Maximum164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T15:08:32.032175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.15
Q141.75
median82.5
Q3123.25
95-th percentile155.85
Maximum164
Range163
Interquartile range (IQR)81.5

Descriptive statistics

Standard deviation47.48684
Coefficient of variation (CV)0.57559806
Kurtosis-1.2
Mean82.5
Median Absolute Deviation (MAD)41
Skewness0
Sum13530
Variance2255
MonotonicityStrictly increasing
2024-01-28T15:08:32.341126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
105 1
 
0.6%
107 1
 
0.6%
108 1
 
0.6%
109 1
 
0.6%
110 1
 
0.6%
111 1
 
0.6%
112 1
 
0.6%
113 1
 
0.6%
114 1
 
0.6%
Other values (154) 154
93.9%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
164 1
0.6%
163 1
0.6%
162 1
0.6%
161 1
0.6%
160 1
0.6%
159 1
0.6%
158 1
0.6%
157 1
0.6%
156 1
0.6%
155 1
0.6%

재산명
Text

Distinct158
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-28T15:08:32.549636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length9.304878
Min length4

Characters and Unicode

Total characters1526
Distinct characters193
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique156 ?
Unique (%)95.1%

Sample

1st row해바라기마을센터(부평고교주변 주민공동이용시설)
2nd row신복경로당
3rd row부평4동 신대리경로당
4th row중부동경로당
5th row중부공공원 (공원화장실)
ValueCountFrequency (%)
행정복지센터 18
 
7.5%
분회경로당 8
 
3.3%
공중화장실 8
 
3.3%
부평구 4
 
1.7%
주민공동이용시설 3
 
1.3%
부개1동 3
 
1.3%
공영주차장 3
 
1.3%
부평종합시장 2
 
0.8%
어린이집 2
 
0.8%
부개2동 2
 
0.8%
Other values (176) 186
77.8%
2024-01-28T15:08:32.838985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
76
 
5.0%
공 75
 
4.9%
부 61
 
4.0%
원 58
 
3.8%
장 51
 
3.3%
당 48
 
3.1%
동 47
 
3.1%
경 46
 
3.0%
로 45
 
2.9%
터 41
 
2.7%
Other values (183) 978
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1333
87.4%
Space Separator 76
 
5.0%
Decimal Number 47
 
3.1%
Close Punctuation 32
 
2.1%
Open Punctuation 32
 
2.1%
Dash Punctuation 3
 
0.2%
Uppercase Letter 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 75
 
5.6%
부 61
 
4.6%
원 58
 
4.4%
장 51
 
3.8%
당 48
 
3.6%
동 47
 
3.5%
경 46
 
3.5%
로 45
 
3.4%
터 41
 
3.1%
센 39
 
2.9%
Other values (167) 822
61.7%
Decimal Number
ValueCountFrequency (%)
1 15
31.9%
2 10
21.3%
3 8
17.0%
6 5
 
10.6%
4 3
 
6.4%
8 2
 
4.3%
7 2
 
4.3%
5 1
 
2.1%
0 1
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%
Space Separator
ValueCountFrequency (%)
76
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1333
87.4%
Common 190
 
12.5%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 75
 
5.6%
부 61
 
4.6%
원 58
 
4.4%
장 51
 
3.8%
당 48
 
3.6%
동 47
 
3.5%
경 46
 
3.5%
로 45
 
3.4%
터 41
 
3.1%
센 39
 
2.9%
Other values (167) 822
61.7%
Common
ValueCountFrequency (%)
76
40.0%
) 32
16.8%
( 32
16.8%
1 15
 
7.9%
2 10
 
5.3%
3 8
 
4.2%
6 5
 
2.6%
4 3
 
1.6%
- 3
 
1.6%
8 2
 
1.1%
Other values (3) 4
 
2.1%
Latin
ValueCountFrequency (%)
A 1
33.3%
P 1
33.3%
T 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1333
87.4%
ASCII 193
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
76
39.4%
) 32
16.6%
( 32
16.6%
1 15
 
7.8%
2 10
 
5.2%
3 8
 
4.1%
6 5
 
2.6%
4 3
 
1.6%
- 3
 
1.6%
8 2
 
1.0%
Other values (6) 7
 
3.6%
Hangul
ValueCountFrequency (%)
공 75
 
5.6%
부 61
 
4.6%
원 58
 
4.4%
장 51
 
3.8%
당 48
 
3.6%
동 47
 
3.5%
경 46
 
3.5%
로 45
 
3.4%
터 41
 
3.1%
센 39
 
2.9%
Other values (167) 822
61.7%

도로명주소
Text

Distinct144
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-28T15:08:33.100734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length40
Mean length25.390244
Min length1

Characters and Unicode

Total characters4164
Distinct characters141
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique137 ?
Unique (%)83.5%

Sample

1st row인천광역시 부평구 부흥북로57번길 20 해바라기마을센터 (부평동)
2nd row인천광역시 부평구 길주남로90번길 18 (부평동)
3rd row인천광역시 부평구 주부토로90번길 45 (부평동)
4th row인천광역시 부평구 부흥북로 102 (부평동)
5th row인천광역시 부평구 부흥북로 102 (부평동 중부동공원)
ValueCountFrequency (%)
인천광역시 149
18.6%
부평구 149
18.6%
부평동 41
 
5.1%
부개동 25
 
3.1%
십정동 19
 
2.4%
갈산동 18
 
2.2%
삼산동 15
 
1.9%
산곡동 15
 
1.9%
청천동 12
 
1.5%
주부토로 9
 
1.1%
Other values (259) 348
43.5%
2024-01-28T15:08:33.473830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
693
 
16.6%
부 273
 
6.6%
평 214
 
5.1%
동 184
 
4.4%
천 170
 
4.1%
인 158
 
3.8%
시 154
 
3.7%
로 150
 
3.6%
광 150
 
3.6%
구 150
 
3.6%
Other values (131) 1868
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2543
61.1%
Space Separator 693
 
16.6%
Decimal Number 584
 
14.0%
Open Punctuation 149
 
3.6%
Close Punctuation 149
 
3.6%
Dash Punctuation 35
 
0.8%
Uppercase Letter 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 273
 
10.7%
평 214
 
8.4%
동 184
 
7.2%
천 170
 
6.7%
인 158
 
6.2%
시 154
 
6.1%
로 150
 
5.9%
광 150
 
5.9%
구 150
 
5.9%
역 149
 
5.9%
Other values (112) 791
31.1%
Decimal Number
ValueCountFrequency (%)
1 122
20.9%
2 87
14.9%
3 63
10.8%
6 59
10.1%
4 48
 
8.2%
8 45
 
7.7%
7 44
 
7.5%
0 43
 
7.4%
5 37
 
6.3%
9 36
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
U 4
36.4%
A 2
18.2%
S 2
18.2%
T 2
18.2%
B 1
 
9.1%
Space Separator
ValueCountFrequency (%)
693
100.0%
Open Punctuation
ValueCountFrequency (%)
( 149
100.0%
Close Punctuation
ValueCountFrequency (%)
) 149
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2543
61.1%
Common 1610
38.7%
Latin 11
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 273
 
10.7%
평 214
 
8.4%
동 184
 
7.2%
천 170
 
6.7%
인 158
 
6.2%
시 154
 
6.1%
로 150
 
5.9%
광 150
 
5.9%
구 150
 
5.9%
역 149
 
5.9%
Other values (112) 791
31.1%
Common
ValueCountFrequency (%)
693
43.0%
( 149
 
9.3%
) 149
 
9.3%
1 122
 
7.6%
2 87
 
5.4%
3 63
 
3.9%
6 59
 
3.7%
4 48
 
3.0%
8 45
 
2.8%
7 44
 
2.7%
Other values (4) 151
 
9.4%
Latin
ValueCountFrequency (%)
U 4
36.4%
A 2
18.2%
S 2
18.2%
T 2
18.2%
B 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2543
61.1%
ASCII 1621
38.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
693
42.8%
( 149
 
9.2%
) 149
 
9.2%
1 122
 
7.5%
2 87
 
5.4%
3 63
 
3.9%
6 59
 
3.6%
4 48
 
3.0%
8 45
 
2.8%
7 44
 
2.7%
Other values (9) 162
 
10.0%
Hangul
ValueCountFrequency (%)
부 273
 
10.7%
평 214
 
8.4%
동 184
 
7.2%
천 170
 
6.7%
인 158
 
6.2%
시 154
 
6.1%
로 150
 
5.9%
광 150
 
5.9%
구 150
 
5.9%
역 149
 
5.9%
Other values (112) 791
31.1%

연면적
Real number (ℝ)

Distinct159
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1133.527
Minimum11.56
Maximum31253.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.6 KiB
2024-01-28T15:08:33.580278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11.56
5-th percentile34.09
Q1124.855
median274.9
Q31084.695
95-th percentile4213.8505
Maximum31253.73
Range31242.17
Interquartile range (IQR)959.84

Descriptive statistics

Standard deviation2970.4221
Coefficient of variation (CV)2.620513
Kurtosis69.964941
Mean1133.527
Median Absolute Deviation (MAD)237.46
Skewness7.5971327
Sum185898.42
Variance8823407.2
MonotonicityNot monotonic
2024-01-28T15:08:33.691847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.44 3
 
1.8%
34.09 3
 
1.8%
36.0 2
 
1.2%
490.99 1
 
0.6%
2161.5 1
 
0.6%
3108.84 1
 
0.6%
1168.73 1
 
0.6%
4987.13 1
 
0.6%
41.3 1
 
0.6%
1503.87 1
 
0.6%
Other values (149) 149
90.9%
ValueCountFrequency (%)
11.56 1
 
0.6%
19.8 1
 
0.6%
23.98 1
 
0.6%
30.4 1
 
0.6%
32.34 1
 
0.6%
32.8 1
 
0.6%
33.44 1
 
0.6%
34.0 1
 
0.6%
34.09 3
1.8%
36.0 2
1.2%
ValueCountFrequency (%)
31253.73 1
0.6%
17236.53 1
0.6%
6552.6 1
0.6%
6036.44 1
0.6%
5274.43 1
0.6%
5270.25 1
0.6%
4987.13 1
0.6%
4691.44 1
0.6%
4229.8 1
0.6%
4123.47 1
0.6%

건축일자
Date

MISSING 

Distinct111
Distinct (%)92.5%
Missing44
Missing (%)26.8%
Memory size1.4 KiB
Minimum1975-08-26 00:00:00
Maximum2021-12-16 00:00:00
2024-01-28T15:08:33.798749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:08:33.903572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

건물용도
Categorical

Distinct15
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
공공용시설
54 
업무시설
27 
교육연구 및 복지시설
21 
분뇨 및 쓰레기처리시설
16 
제1종 근린생활시설
12 
Other values (10)
34 

Length

Max length14
Median length12
Mean length7.3597561
Min length2

Unique

Unique2 ?
Unique (%)1.2%

Sample

1st row제1종 근린생활시설
2nd row노유자(노인및 어린이)시설
3rd row노유자(노인및 어린이)시설
4th row공공용시설
5th row공공용시설

Common Values

ValueCountFrequency (%)
공공용시설 54
32.9%
업무시설 27
16.5%
교육연구 및 복지시설 21
 
12.8%
분뇨 및 쓰레기처리시설 16
 
9.8%
제1종 근린생활시설 12
 
7.3%
노유자(노인및 어린이)시설 11
 
6.7%
공동주택 4
 
2.4%
문화 및 집회시설 4
 
2.4%
자동차관련시설 3
 
1.8%
<NA> 3
 
1.8%
Other values (5) 9
 
5.5%

Length

2024-01-28T15:08:34.018731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
공공용시설 54
19.8%
및 42
15.4%
업무시설 27
9.9%
교육연구 21
 
7.7%
복지시설 21
 
7.7%
분뇨 16
 
5.9%
쓰레기처리시설 16
 
5.9%
근린생활시설 14
 
5.1%
제1종 12
 
4.4%
노유자(노인및 11
 
4.0%
Other values (12) 39
14.3%

Interactions

2024-01-28T15:08:31.724490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:08:31.579759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:08:31.789804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T15:08:31.658333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T15:08:34.082793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연면적건물용도
순번1.0000.2490.377
연면적0.2491.0000.449
건물용도0.3770.4491.000
2024-01-28T15:08:34.154167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번연면적건물용도
순번1.000-0.0790.158
연면적-0.0791.0000.245
건물용도0.1580.2451.000

Missing values

2024-01-28T15:08:31.872972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T15:08:31.947661image/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

순번재산명도로명주소연면적건축일자건물용도
01해바라기마을센터(부평고교주변 주민공동이용시설)인천광역시 부평구 부흥북로57번길 20 해바라기마을센터 (부평동)490.992019-05-29제1종 근린생활시설
12신복경로당인천광역시 부평구 길주남로90번길 18 (부평동)145.471992-02-20노유자(노인및 어린이)시설
23부평4동 신대리경로당인천광역시 부평구 주부토로90번길 45 (부평동)178.452011-10-05노유자(노인및 어린이)시설
34중부동경로당인천광역시 부평구 부흥북로 102 (부평동)158.672002-06-04공공용시설
45중부공공원 (공원화장실)인천광역시 부평구 부흥북로 102 (부평동 중부동공원)32.341999-12-27공공용시설
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