Overview

Dataset statistics

Number of variables4
Number of observations214
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.2 KiB
Average record size in memory34.6 B

Variable types

Text2
Numeric2

Dataset

Description경기도 안양시 관내 비상 대피시설 현황 정보입니다.시설, 주소, 규모(제곱미터) 수용인원(명) 등에 대한 데이터 정보를 확인 할 수 있습니다.
Author경기도 안양시
URLhttps://www.data.go.kr/data/3045138/fileData.do

Alerts

규모(제곱미터) is highly overall correlated with 최대 수용인원(명)High correlation
최대 수용인원(명) is highly overall correlated with 규모(제곱미터)High correlation

Reproduction

Analysis started2024-03-14 10:43:47.871224
Analysis finished2024-03-14 10:43:49.813683
Duration1.94 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설
Text

Distinct211
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T19:43:50.646034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length19
Mean length12.168224
Min length4

Characters and Unicode

Total characters2604
Distinct characters245
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique208 ?
Unique (%)97.2%

Sample

1st row안양1동행정복지센터 지하
2nd row안양중앙지하상가
3rd row안양역전지하상가
4th row주공뜨란채아파트
5th row만안초등학교 앞 지하도
ValueCountFrequency (%)
지하주차장 92
 
22.3%
지하 24
 
5.8%
꿈마을 10
 
2.4%
지하보도 9
 
2.2%
행정복지센터 7
 
1.7%
앞 5
 
1.2%
한양아파트 4
 
1.0%
지하주차장(3개소통합 4
 
1.0%
관악타운아파트 4
 
1.0%
아파트 3
 
0.7%
Other values (229) 251
60.8%
2024-03-14T19:43:52.533640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 199
 
7.6%
199
 
7.6%
하 162
 
6.2%
아 131
 
5.0%
트 131
 
5.0%
파 123
 
4.7%
차 121
 
4.6%
장 112
 
4.3%
주 112
 
4.3%
동 59
 
2.3%
Other values (235) 1255
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2228
85.6%
Space Separator 199
 
7.6%
Decimal Number 116
 
4.5%
Close Punctuation 19
 
0.7%
Open Punctuation 19
 
0.7%
Uppercase Letter 11
 
0.4%
Other Punctuation 4
 
0.2%
Dash Punctuation 3
 
0.1%
Lowercase Letter 3
 
0.1%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 199
 
8.9%
하 162
 
7.3%
아 131
 
5.9%
트 131
 
5.9%
파 123
 
5.5%
차 121
 
5.4%
장 112
 
5.0%
주 112
 
5.0%
동 59
 
2.6%
안 35
 
1.6%
Other values (211) 1043
46.8%
Decimal Number
ValueCountFrequency (%)
1 42
36.2%
3 20
17.2%
2 20
17.2%
0 11
 
9.5%
8 6
 
5.2%
6 5
 
4.3%
5 4
 
3.4%
4 4
 
3.4%
7 3
 
2.6%
9 1
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
K 3
27.3%
T 2
18.2%
L 2
18.2%
E 1
 
9.1%
B 1
 
9.1%
D 1
 
9.1%
G 1
 
9.1%
Space Separator
ValueCountFrequency (%)
199
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2228
85.6%
Common 362
 
13.9%
Latin 14
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 199
 
8.9%
하 162
 
7.3%
아 131
 
5.9%
트 131
 
5.9%
파 123
 
5.5%
차 121
 
5.4%
장 112
 
5.0%
주 112
 
5.0%
동 59
 
2.6%
안 35
 
1.6%
Other values (211) 1043
46.8%
Common
ValueCountFrequency (%)
199
55.0%
1 42
 
11.6%
3 20
 
5.5%
2 20
 
5.5%
) 19
 
5.2%
( 19
 
5.2%
0 11
 
3.0%
8 6
 
1.7%
6 5
 
1.4%
, 4
 
1.1%
Other values (6) 17
 
4.7%
Latin
ValueCountFrequency (%)
K 3
21.4%
e 3
21.4%
T 2
14.3%
L 2
14.3%
E 1
 
7.1%
B 1
 
7.1%
D 1
 
7.1%
G 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2228
85.6%
ASCII 376
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 199
 
8.9%
하 162
 
7.3%
아 131
 
5.9%
트 131
 
5.9%
파 123
 
5.5%
차 121
 
5.4%
장 112
 
5.0%
주 112
 
5.0%
동 59
 
2.6%
안 35
 
1.6%
Other values (211) 1043
46.8%
ASCII
ValueCountFrequency (%)
199
52.9%
1 42
 
11.2%
3 20
 
5.3%
2 20
 
5.3%
) 19
 
5.1%
( 19
 
5.1%
0 11
 
2.9%
8 6
 
1.6%
6 5
 
1.3%
, 4
 
1.1%
Other values (14) 31
 
8.2%

주소
Text

Distinct199
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2024-03-14T19:43:53.790806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length39
Mean length31.556075
Min length22

Characters and Unicode

Total characters6753
Distinct characters200
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique186 ?
Unique (%)86.9%

Sample

1st row경기도 안양시 만안구 장내로 170(안양동)
2nd row경기도 안양시 만안구 안양로 지하301(안양동)
3rd row경기도 안양시 만안구 만안로 지하231(안양동)
4th row경기도 안양시 만안구 안양천서로 289(안양동, 주공뜨란채)
5th row경기도 안양시 만안구 안양로384번길 13(안양동)
ValueCountFrequency (%)
경기도 214
17.3%
안양시 214
17.3%
동안구 157
 
12.7%
만안구 57
 
4.6%
경수대로 14
 
1.1%
동안로 13
 
1.0%
귀인로 10
 
0.8%
학의로 9
 
0.7%
안양로 9
 
0.7%
달안로 9
 
0.7%
Other values (404) 534
43.1%
2024-03-14T19:43:54.953866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1026
 
15.2%
안 546
 
8.1%
동 397
 
5.9%
양 318
 
4.7%
경 246
 
3.6%
시 224
 
3.3%
도 215
 
3.2%
구 215
 
3.2%
기 214
 
3.2%
) 210
 
3.1%
Other values (190) 3142
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4420
65.5%
Space Separator 1026
 
15.2%
Decimal Number 741
 
11.0%
Close Punctuation 210
 
3.1%
Open Punctuation 210
 
3.1%
Other Punctuation 132
 
2.0%
Dash Punctuation 11
 
0.2%
Uppercase Letter 2
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 546
 
12.4%
동 397
 
9.0%
양 318
 
7.2%
경 246
 
5.6%
시 224
 
5.1%
도 215
 
4.9%
구 215
 
4.9%
기 214
 
4.8%
로 209
 
4.7%
아 102
 
2.3%
Other values (172) 1734
39.2%
Decimal Number
ValueCountFrequency (%)
1 124
16.7%
2 110
14.8%
3 98
13.2%
4 71
9.6%
5 70
9.4%
0 58
7.8%
8 57
7.7%
7 56
7.6%
9 49
 
6.6%
6 48
 
6.5%
Uppercase Letter
ValueCountFrequency (%)
L 1
50.0%
D 1
50.0%
Space Separator
ValueCountFrequency (%)
1026
100.0%
Close Punctuation
ValueCountFrequency (%)
) 210
100.0%
Open Punctuation
ValueCountFrequency (%)
( 210
100.0%
Other Punctuation
ValueCountFrequency (%)
, 132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4420
65.5%
Common 2330
34.5%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 546
 
12.4%
동 397
 
9.0%
양 318
 
7.2%
경 246
 
5.6%
시 224
 
5.1%
도 215
 
4.9%
구 215
 
4.9%
기 214
 
4.8%
로 209
 
4.7%
아 102
 
2.3%
Other values (172) 1734
39.2%
Common
ValueCountFrequency (%)
1026
44.0%
) 210
 
9.0%
( 210
 
9.0%
, 132
 
5.7%
1 124
 
5.3%
2 110
 
4.7%
3 98
 
4.2%
4 71
 
3.0%
5 70
 
3.0%
0 58
 
2.5%
Other values (5) 221
 
9.5%
Latin
ValueCountFrequency (%)
e 1
33.3%
L 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4420
65.5%
ASCII 2333
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1026
44.0%
) 210
 
9.0%
( 210
 
9.0%
, 132
 
5.7%
1 124
 
5.3%
2 110
 
4.7%
3 98
 
4.2%
4 71
 
3.0%
5 70
 
3.0%
0 58
 
2.5%
Other values (8) 224
 
9.6%
Hangul
ValueCountFrequency (%)
안 546
 
12.4%
동 397
 
9.0%
양 318
 
7.2%
경 246
 
5.6%
시 224
 
5.1%
도 215
 
4.9%
구 215
 
4.9%
기 214
 
4.8%
로 209
 
4.7%
아 102
 
2.3%
Other values (172) 1734
39.2%

규모(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct201
Distinct (%)93.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9367.1215
Minimum112
Maximum142811
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T19:43:55.395421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum112
5-th percentile166.95
Q1811.75
median4170
Q38721.5
95-th percentile39024.9
Maximum142811
Range142699
Interquartile range (IQR)7909.75

Descriptive statistics

Standard deviation17594.43
Coefficient of variation (CV)1.8783177
Kurtosis22.729307
Mean9367.1215
Median Absolute Deviation (MAD)3663.5
Skewness4.2842787
Sum2004564
Variance3.0956397 × 108
MonotonicityNot monotonic
2024-03-14T19:43:55.760409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
198 5
 
2.3%
6526 2
 
0.9%
9534 2
 
0.9%
149 2
 
0.9%
747 2
 
0.9%
5850 2
 
0.9%
231 2
 
0.9%
165 2
 
0.9%
4007 2
 
0.9%
331 2
 
0.9%
Other values (191) 191
89.3%
ValueCountFrequency (%)
112 1
0.5%
116 1
0.5%
122 1
0.5%
136 1
0.5%
142 1
0.5%
147 1
0.5%
149 2
0.9%
162 1
0.5%
165 2
0.9%
168 1
0.5%
ValueCountFrequency (%)
142811 1
0.5%
108365 1
0.5%
84882 1
0.5%
78235 1
0.5%
74159 1
0.5%
59904 1
0.5%
55574 1
0.5%
54022 1
0.5%
52172 1
0.5%
51674 1
0.5%

최대 수용인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct200
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11455.182
Minimum135
Maximum173104
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 KiB
2024-03-14T19:43:56.176045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum135
5-th percentile201.95
Q1983.25
median5079.5
Q310932
95-th percentile47302.75
Maximum173104
Range172969
Interquartile range (IQR)9948.75

Descriptive statistics

Standard deviation21340.012
Coefficient of variation (CV)1.8629133
Kurtosis22.582316
Mean11455.182
Median Absolute Deviation (MAD)4521.5
Skewness4.2628809
Sum2451409
Variance4.553961 × 108
MonotonicityNot monotonic
2024-03-14T19:43:56.621828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
240 5
 
2.3%
401 2
 
0.9%
7090 2
 
0.9%
180 2
 
0.9%
905 2
 
0.9%
1678 2
 
0.9%
280 2
 
0.9%
23913 2
 
0.9%
7910 2
 
0.9%
4856 2
 
0.9%
Other values (190) 191
89.3%
ValueCountFrequency (%)
135 1
0.5%
140 1
0.5%
147 1
0.5%
164 1
0.5%
172 1
0.5%
178 1
0.5%
180 2
0.9%
196 1
0.5%
200 2
0.9%
203 1
0.5%
ValueCountFrequency (%)
173104 1
0.5%
131351 1
0.5%
102887 1
0.5%
94830 1
0.5%
89889 1
0.5%
72610 1
0.5%
67362 1
0.5%
65481 1
0.5%
63238 1
0.5%
62635 1
0.5%

Interactions

2024-03-14T19:43:48.782277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:43:48.246666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:43:49.049984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T19:43:48.509377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T19:43:56.893058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모(제곱미터)최대 수용인원(명)
규모(제곱미터)1.0001.000
최대 수용인원(명)1.0001.000
2024-03-14T19:43:57.123815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규모(제곱미터)최대 수용인원(명)
규모(제곱미터)1.0000.991
최대 수용인원(명)0.9911.000

Missing values

2024-03-14T19:43:49.398959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:43:49.696384image/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

시설주소규모(제곱미터)최대 수용인원(명)
0안양1동행정복지센터 지하경기도 안양시 만안구 장내로 170(안양동)570690
1안양중앙지하상가경기도 안양시 만안구 안양로 지하301(안양동)23102800
2안양역전지하상가경기도 안양시 만안구 만안로 지하231(안양동)1579419144
3주공뜨란채아파트경기도 안양시 만안구 안양천서로 289(안양동, 주공뜨란채)1798821803
4만안초등학교 앞 지하도경기도 안양시 만안구 안양로384번길 13(안양동)330400
5안양2동행정복지센터경기도 안양시 만안구 안양로384번길 50(안양동)327396
6경남아너스빌아파트경기도 안양시 만안구 태평로 214(안양동, 안양동 경남아너스빌)72448780
7안양2동 삼성아파트경기도 안양시 만안구 예술공원로 57(안양동)31813855
8미래엠피아파트경기도 안양시 만안구 만안로 272(안양동, 안양 미래엠피아)64607830
9영화아이닉스아파트경기도 안양시 만안구 만안로 368(안양동, 영화아이닉스아파트)24392956
시설주소규모(제곱미터)최대 수용인원(명)
204먹자골목 지하보도경기도 안양시 동안구 평촌대로 127(호계동)602729
205신기중학교 지하보도경기도 안양시 동안구 갈산로 86(호계동)321389
206갈산동행정복지센터 지하경기도 안양시 동안구 흥안대로223번길 30(호계동)215260
207쌍용아파트 지하주차장(3개소통합)경기도 안양시 동안구 흥안대로223번길 16(호계동, 샘마을)72768819
208우방아파트 지하주차장(3개소통합)경기도 안양시 동안구 흥안대로249번길 18(호계동, 샘마을아파트)63637712
209임광아파트 지하주차장(3개소통합)경기도 안양시 동안구 평촌대로40번길 100(호계동, 샘마을아파트)1086213166
210대우,한양아파트 지하주차장(5개소통합)경기도 안양시 동안구 흥안대로223번길 47(호계동, 샘마을대우,한양아파트)1288415616
211한양아파트 지하주차장(3개소통합)경기도 안양시 동안구 흥안대로223번길 47(호계동, 샘마을대우,한양아파트)33044004
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