Overview

Dataset statistics

Number of variables4
Number of observations846
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory27.4 KiB
Average record size in memory33.2 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description안양시 동안구 관내 소독의무대상시설 현황(관내 소독의무대상시설 시설명, 관내 소독의무대상시설소재지)데이터 정보입니다.
Author경기도 안양시
URLhttps://www.data.go.kr/data/15055319/fileData.do

Alerts

순번 is highly overall correlated with 시설종별High correlation
시설종별 is highly overall correlated with 순번High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:15:01.360718
Analysis finished2023-12-12 13:15:01.969239
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct846
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean423.5
Minimum1
Maximum846
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.6 KiB
2023-12-12T22:15:02.057179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile43.25
Q1212.25
median423.5
Q3634.75
95-th percentile803.75
Maximum846
Range845
Interquartile range (IQR)422.5

Descriptive statistics

Standard deviation244.36346
Coefficient of variation (CV)0.57700935
Kurtosis-1.2
Mean423.5
Median Absolute Deviation (MAD)211.5
Skewness0
Sum358281
Variance59713.5
MonotonicityStrictly increasing
2023-12-12T22:15:02.182535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
583 1
 
0.1%
559 1
 
0.1%
560 1
 
0.1%
561 1
 
0.1%
562 1
 
0.1%
563 1
 
0.1%
564 1
 
0.1%
565 1
 
0.1%
566 1
 
0.1%
Other values (836) 836
98.8%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
846 1
0.1%
845 1
0.1%
844 1
0.1%
843 1
0.1%
842 1
0.1%
841 1
0.1%
840 1
0.1%
839 1
0.1%
838 1
0.1%
837 1
0.1%

시설종별
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
건축물
313 
집단급식소
113 
식품접객업소
107 
공동주택(300세대이상)
90 
학교
51 
Other values (10)
172 

Length

Max length13
Median length7
Mean length4.8900709
Min length2

Unique

Unique1 ?
Unique (%)0.1%

Sample

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

Common Values

ValueCountFrequency (%)
건축물 313
37.0%
집단급식소 113
 
13.4%
식품접객업소 107
 
12.6%
공동주택(300세대이상) 90
 
10.6%
학교 51
 
6.0%
영유아보육시설 42
 
5.0%
숙박업소 35
 
4.1%
유치원 35
 
4.1%
위탁급식소 13
 
1.5%
학원 13
 
1.5%
Other values (5) 34
 
4.0%

Length

2023-12-12T22:15:02.351651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
건축물 313
37.0%
집단급식소 113
 
13.4%
식품접객업소 107
 
12.6%
공동주택(300세대이상 90
 
10.6%
학교 51
 
6.0%
영유아보육시설 42
 
5.0%
숙박업소 35
 
4.1%
유치원 35
 
4.1%
위탁급식소 13
 
1.5%
학원 13
 
1.5%
Other values (5) 34
 
4.0%

시설명
Text

Distinct826
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
2023-12-12T22:15:02.603293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length19
Mean length6.6808511
Min length2

Characters and Unicode

Total characters5652
Distinct characters474
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

Unique806 ?
Unique (%)95.3%

Sample

1st row평촌스마트베이
2nd row두성프라자
3rd row대림타워
4th row안양법조타운
5th row안양무역센터
ValueCountFrequency (%)
평촌점 9
 
0.9%
어린이집 9
 
0.9%
스타벅스 6
 
0.6%
꿈마을 6
 
0.6%
급식소 4
 
0.4%
빌딩 4
 
0.4%
구내식당 4
 
0.4%
평촌 4
 
0.4%
교내식당 3
 
0.3%
현대홈타운 3
 
0.3%
Other values (909) 951
94.8%
2023-12-12T22:15:02.965669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
162
 
2.9%
이 131
 
2.3%
스 127
 
2.2%
원 114
 
2.0%
빌 110
 
1.9%
안 106
 
1.9%
딩 104
 
1.8%
양 103
 
1.8%
촌 92
 
1.6%
평 91
 
1.6%
Other values (464) 4512
79.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5155
91.2%
Space Separator 162
 
2.9%
Uppercase Letter 92
 
1.6%
Decimal Number 80
 
1.4%
Open Punctuation 63
 
1.1%
Close Punctuation 63
 
1.1%
Other Punctuation 15
 
0.3%
Lowercase Letter 13
 
0.2%
Dash Punctuation 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 131
 
2.5%
스 127
 
2.5%
원 114
 
2.2%
빌 110
 
2.1%
안 106
 
2.1%
딩 104
 
2.0%
양 103
 
2.0%
촌 92
 
1.8%
평 91
 
1.8%
어 81
 
1.6%
Other values (417) 4096
79.5%
Uppercase Letter
ValueCountFrequency (%)
D 11
12.0%
S 11
12.0%
T 10
10.9%
K 9
9.8%
I 7
7.6%
R 6
 
6.5%
A 6
 
6.5%
L 6
 
6.5%
B 6
 
6.5%
H 4
 
4.3%
Other values (10) 16
17.4%
Decimal Number
ValueCountFrequency (%)
2 26
32.5%
1 17
21.2%
3 16
20.0%
4 7
 
8.8%
5 6
 
7.5%
6 3
 
3.8%
9 2
 
2.5%
8 1
 
1.2%
7 1
 
1.2%
0 1
 
1.2%
Lowercase Letter
ValueCountFrequency (%)
e 3
23.1%
u 2
15.4%
a 2
15.4%
r 1
 
7.7%
q 1
 
7.7%
m 1
 
7.7%
c 1
 
7.7%
p 1
 
7.7%
s 1
 
7.7%
Other Punctuation
ValueCountFrequency (%)
& 9
60.0%
. 5
33.3%
, 1
 
6.7%
Space Separator
ValueCountFrequency (%)
162
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
= 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5155
91.2%
Common 392
 
6.9%
Latin 105
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 131
 
2.5%
스 127
 
2.5%
원 114
 
2.2%
빌 110
 
2.1%
안 106
 
2.1%
딩 104
 
2.0%
양 103
 
2.0%
촌 92
 
1.8%
평 91
 
1.8%
어 81
 
1.6%
Other values (417) 4096
79.5%
Latin
ValueCountFrequency (%)
D 11
 
10.5%
S 11
 
10.5%
T 10
 
9.5%
K 9
 
8.6%
I 7
 
6.7%
R 6
 
5.7%
A 6
 
5.7%
L 6
 
5.7%
B 6
 
5.7%
H 4
 
3.8%
Other values (19) 29
27.6%
Common
ValueCountFrequency (%)
162
41.3%
( 63
 
16.1%
) 63
 
16.1%
2 26
 
6.6%
1 17
 
4.3%
3 16
 
4.1%
& 9
 
2.3%
- 8
 
2.0%
4 7
 
1.8%
5 6
 
1.5%
Other values (8) 15
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5155
91.2%
ASCII 497
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
162
32.6%
( 63
 
12.7%
) 63
 
12.7%
2 26
 
5.2%
1 17
 
3.4%
3 16
 
3.2%
D 11
 
2.2%
S 11
 
2.2%
T 10
 
2.0%
K 9
 
1.8%
Other values (37) 109
21.9%
Hangul
ValueCountFrequency (%)
이 131
 
2.5%
스 127
 
2.5%
원 114
 
2.2%
빌 110
 
2.1%
안 106
 
2.1%
딩 104
 
2.0%
양 103
 
2.0%
촌 92
 
1.8%
평 91
 
1.8%
어 81
 
1.6%
Other values (417) 4096
79.5%

소재지
Text

Distinct744
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Memory size6.7 KiB
2023-12-12T22:15:03.189049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length38
Mean length27.044917
Min length20

Characters and Unicode

Total characters22880
Distinct characters143
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

Unique652 ?
Unique (%)77.1%

Sample

1st row경기 안양시 동안구 벌말로123 (관양동)
2nd row경기 안양시 동안구 관악대로157 (비산동)
3rd row경기 안양시 동안구 관악대로91 (비산동)
4th row경기 안양시 동안구 부림로156 (관양동)
5th row경기 안양시 동안구 시민대로161 (비산동)
ValueCountFrequency (%)
경기 846
18.6%
안양시 846
18.6%
동안구 845
18.6%
관양동 291
 
6.4%
호계동 269
 
5.9%
비산동 142
 
3.1%
평촌동 98
 
2.2%
70
 
1.5%
번길 15
 
0.3%
1층 11
 
0.2%
Other values (786) 1115
24.5%
2023-12-12T22:15:03.525794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4272
18.7%
안 1873
 
8.2%
동 1801
 
7.9%
양 1180
 
5.2%
시 943
 
4.1%
경 938
 
4.1%
기 851
 
3.7%
로 847
 
3.7%
구 846
 
3.7%
( 845
 
3.7%
Other values (133) 8484
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13584
59.4%
Space Separator 4272
 
18.7%
Decimal Number 3087
 
13.5%
Open Punctuation 845
 
3.7%
Close Punctuation 843
 
3.7%
Other Punctuation 192
 
0.8%
Dash Punctuation 52
 
0.2%
Uppercase Letter 3
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
안 1873
13.8%
동 1801
13.3%
양 1180
 
8.7%
시 943
 
6.9%
경 938
 
6.9%
기 851
 
6.3%
로 847
 
6.2%
구 846
 
6.2%
관 458
 
3.4%
대 458
 
3.4%
Other values (114) 3389
24.9%
Decimal Number
ValueCountFrequency (%)
1 597
19.3%
2 554
17.9%
3 372
12.1%
4 281
9.1%
5 251
8.1%
0 234
 
7.6%
6 230
 
7.5%
7 207
 
6.7%
8 203
 
6.6%
9 158
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 112
58.3%
. 80
41.7%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
4272
100.0%
Open Punctuation
ValueCountFrequency (%)
( 845
100.0%
Close Punctuation
ValueCountFrequency (%)
) 843
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13584
59.4%
Common 9293
40.6%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
안 1873
13.8%
동 1801
13.3%
양 1180
 
8.7%
시 943
 
6.9%
경 938
 
6.9%
기 851
 
6.3%
로 847
 
6.2%
구 846
 
6.2%
관 458
 
3.4%
대 458
 
3.4%
Other values (114) 3389
24.9%
Common
ValueCountFrequency (%)
4272
46.0%
( 845
 
9.1%
) 843
 
9.1%
1 597
 
6.4%
2 554
 
6.0%
3 372
 
4.0%
4 281
 
3.0%
5 251
 
2.7%
0 234
 
2.5%
6 230
 
2.5%
Other values (7) 814
 
8.8%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13584
59.4%
ASCII 9296
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4272
46.0%
( 845
 
9.1%
) 843
 
9.1%
1 597
 
6.4%
2 554
 
6.0%
3 372
 
4.0%
4 281
 
3.0%
5 251
 
2.7%
0 234
 
2.5%
6 230
 
2.5%
Other values (9) 817
 
8.8%
Hangul
ValueCountFrequency (%)
안 1873
13.8%
동 1801
13.3%
양 1180
 
8.7%
시 943
 
6.9%
경 938
 
6.9%
기 851
 
6.3%
로 847
 
6.2%
구 846
 
6.2%
관 458
 
3.4%
대 458
 
3.4%
Other values (114) 3389
24.9%

Interactions

2023-12-12T22:15:01.729964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:15:03.608871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설종별
순번1.0000.932
시설종별0.9321.000
2023-12-12T22:15:03.686910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시설종별
순번1.0000.689
시설종별0.6891.000

Missing values

2023-12-12T22:15:01.835111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:15:01.921599image/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

순번시설종별시설명소재지
01건축물평촌스마트베이경기 안양시 동안구 벌말로123 (관양동)
12건축물두성프라자경기 안양시 동안구 관악대로157 (비산동)
23건축물대림타워경기 안양시 동안구 관악대로91 (비산동)
34건축물안양법조타운경기 안양시 동안구 부림로156 (관양동)
45건축물안양무역센터경기 안양시 동안구 시민대로161 (비산동)
56건축물안양벤쳐텔경기 안양시 동안구 시민대로167 (비산동)
67건축물동안프라자빌딩경기 안양시 동안구 시민대로175 (비산동)
78건축물안양건설타워경기 안양시 동안구 시민대로187 (비산동)
89건축물신안메트로칸경기 안양시 동안구 평촌대로239 (비산동)
910건축물깐느빌딩경기 안양시 동안구 관평로305번길14 (관양동)
순번시설종별시설명소재지
836837학원디와이비최선어학원경기 안양시 동안구 평촌대로132 (평촌동)
837838학원평촌정상어학원경기 안양시 동안구 평촌대로112 3층,4층 (평촌동)
838839학원종로학원경기 안양시 동안구 평촌대로112 6층일부,7층전체 (평촌동)
839840학원평면조형미술학원경기 안양시 동안구 평촌대로135 6,7,8층 (호계동)
840841학원메이플베어문화어학학원경기 안양시 동안구 관악대로272 320,420,550 (비산동)
841842학원청담어학원(청담러닝)경기 안양시 동안구 평촌대로136 301~306호 (평촌동)
842843학원마타수학학원경기 안양시 동안구 평촌대로122 (평촌동)
843844학원코나투스재수종합학원경기 안양시 동안구 시민대로199 (비산동)
844845학원러셀평촌독서실경기 안양시 동안구 평촌대로125 (호계동)
845846학원평촌씨엠에스학원경기 안양시 동안구 평촌대로118 (평촌동)