Overview

Dataset statistics

Number of variables10
Number of observations111
Missing cells10
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.1 KiB
Average record size in memory84.2 B

Variable types

Categorical3
Text4
Numeric3

Dataset

Description경기도 오산시의 실내공기질 관리법에 적용되는 다중이용시설 현황입니다.(시설구분, 시설명, 소재지도로명주소, 소재지지번주소, 전화번호, 연면적, 위경도정보 등)
Author경기도 오산시
URLhttps://www.data.go.kr/data/15036521/fileData.do

Alerts

시군명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
위도 is highly overall correlated with 경도High correlation
경도 is highly overall correlated with 위도High correlation
전화번호 has 10 (9.0%) missing valuesMissing

Reproduction

Analysis started2023-12-12 02:51:18.134780
Analysis finished2023-12-12 02:51:20.557716
Duration2.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
오산시
111 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
오산시 111
100.0%

Length

2023-12-12T11:51:20.607812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:51:20.686060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
오산시 111
100.0%

시설구분
Categorical

Distinct13
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size1020.0 B
어린이집
26 
실내주차장
23 
의료기관
17 
노인요양시설
16 
인터넷컴퓨터게임시설제공업의 영업시설
7 
Other values (8)
22 

Length

Max length19
Median length9
Mean length5.5405405
Min length3

Unique

Unique2 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 26
23.4%
실내주차장 23
20.7%
의료기관 17
15.3%
노인요양시설 16
14.4%
인터넷컴퓨터게임시설제공업의 영업시설 7
 
6.3%
목욕장업 6
 
5.4%
대규모점포 4
 
3.6%
영화상영관 3
 
2.7%
전시시설 3
 
2.7%
도서관 2
 
1.8%
Other values (3) 4
 
3.6%

Length

2023-12-12T11:51:20.788336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
어린이집 26
22.0%
실내주차장 23
19.5%
의료기관 17
14.4%
노인요양시설 16
13.6%
인터넷컴퓨터게임시설제공업의 7
 
5.9%
영업시설 7
 
5.9%
목욕장업 6
 
5.1%
대규모점포 4
 
3.4%
영화상영관 3
 
2.5%
전시시설 3
 
2.5%
Other values (4) 6
 
5.1%

시설명
Text

Distinct108
Distinct (%)97.3%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-12T11:51:20.975773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length7.2972973
Min length3

Characters and Unicode

Total characters810
Distinct characters225
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

Unique105 ?
Unique (%)94.6%

Sample

1st row노틀담사랑터
2nd row노블효타운
3rd row힘찬요양원
4th row오산참요양원
5th row참소망요양원
ValueCountFrequency (%)
오산점 8
 
5.9%
이마트 2
 
1.5%
홈플러스 2
 
1.5%
롯데마트 2
 
1.5%
pc 2
 
1.5%
pc방 2
 
1.5%
오산(1관 1
 
0.7%
오산경찰서어린이집 1
 
0.7%
해오름어린이집 1
 
0.7%
시립파크시티어린이집 1
 
0.7%
Other values (113) 113
83.7%
2023-12-12T11:51:21.274246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 36
 
4.4%
오 34
 
4.2%
이 33
 
4.1%
원 32
 
4.0%
어 30
 
3.7%
린 28
 
3.5%
26
 
3.2%
집 26
 
3.2%
시 20
 
2.5%
스 20
 
2.5%
Other values (215) 525
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 751
92.7%
Space Separator 26
 
3.2%
Uppercase Letter 20
 
2.5%
Decimal Number 6
 
0.7%
Open Punctuation 3
 
0.4%
Close Punctuation 3
 
0.4%
Lowercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 36
 
4.8%
오 34
 
4.5%
이 33
 
4.4%
원 32
 
4.3%
어 30
 
4.0%
린 28
 
3.7%
집 26
 
3.5%
시 20
 
2.7%
스 20
 
2.7%
양 17
 
2.3%
Other values (203) 475
63.2%
Uppercase Letter
ValueCountFrequency (%)
C 9
45.0%
P 6
30.0%
V 2
 
10.0%
G 2
 
10.0%
L 1
 
5.0%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 2
33.3%
4 1
 
16.7%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
w 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 751
92.7%
Common 38
 
4.7%
Latin 21
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 36
 
4.8%
오 34
 
4.5%
이 33
 
4.4%
원 32
 
4.3%
어 30
 
4.0%
린 28
 
3.7%
집 26
 
3.5%
시 20
 
2.7%
스 20
 
2.7%
양 17
 
2.3%
Other values (203) 475
63.2%
Common
ValueCountFrequency (%)
26
68.4%
1 3
 
7.9%
( 3
 
7.9%
) 3
 
7.9%
2 2
 
5.3%
4 1
 
2.6%
Latin
ValueCountFrequency (%)
C 9
42.9%
P 6
28.6%
V 2
 
9.5%
G 2
 
9.5%
w 1
 
4.8%
L 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 751
92.7%
ASCII 59
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 36
 
4.8%
오 34
 
4.5%
이 33
 
4.4%
원 32
 
4.3%
어 30
 
4.0%
린 28
 
3.7%
집 26
 
3.5%
시 20
 
2.7%
스 20
 
2.7%
양 17
 
2.3%
Other values (203) 475
63.2%
ASCII
ValueCountFrequency (%)
26
44.1%
C 9
 
15.3%
P 6
 
10.2%
1 3
 
5.1%
( 3
 
5.1%
) 3
 
5.1%
V 2
 
3.4%
G 2
 
3.4%
2 2
 
3.4%
4 1
 
1.7%
Other values (2) 2
 
3.4%

소재지도로명주소
Text

Distinct102
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-12T11:51:21.521622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length31
Mean length20.072072
Min length13

Characters and Unicode

Total characters2228
Distinct characters136
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

Unique93 ?
Unique (%)83.8%

Sample

1st row경기도 오산시 가장로 709
2nd row경기도 오산시 오산로 265-10
3rd row경기도 오산시 경기대로 153
4th row경기도 오산시 오산로 164 5층
5th row경기도 오산시 지곶43번길 15-7
ValueCountFrequency (%)
경기도 111
22.6%
오산시 111
22.6%
경기대로 17
 
3.5%
오산로 9
 
1.8%
청학로 9
 
1.8%
성호대로 6
 
1.2%
수목원로 6
 
1.2%
가장산업동로 5
 
1.0%
원동 5
 
1.0%
원동로 3
 
0.6%
Other values (171) 209
42.6%
2023-12-12T11:51:21.892924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
382
17.1%
산 146
 
6.6%
오 137
 
6.1%
경 130
 
5.8%
기 129
 
5.8%
시 115
 
5.2%
도 112
 
5.0%
로 105
 
4.7%
1 73
 
3.3%
2 52
 
2.3%
Other values (126) 847
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1332
59.8%
Decimal Number 387
 
17.4%
Space Separator 382
 
17.1%
Close Punctuation 37
 
1.7%
Open Punctuation 37
 
1.7%
Dash Punctuation 30
 
1.3%
Other Punctuation 13
 
0.6%
Uppercase Letter 7
 
0.3%
Math Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 146
11.0%
오 137
 
10.3%
경 130
 
9.8%
기 129
 
9.7%
시 115
 
8.6%
도 112
 
8.4%
로 105
 
7.9%
동 49
 
3.7%
대 35
 
2.6%
길 23
 
1.7%
Other values (105) 351
26.4%
Decimal Number
ValueCountFrequency (%)
1 73
18.9%
2 52
13.4%
4 44
11.4%
3 42
10.9%
6 36
9.3%
7 31
8.0%
9 30
7.8%
0 30
7.8%
8 27
 
7.0%
5 22
 
5.7%
Uppercase Letter
ValueCountFrequency (%)
L 2
28.6%
C 2
28.6%
W 1
14.3%
K 1
14.3%
R 1
14.3%
Space Separator
ValueCountFrequency (%)
382
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 30
100.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1332
59.8%
Common 889
39.9%
Latin 7
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 146
11.0%
오 137
 
10.3%
경 130
 
9.8%
기 129
 
9.7%
시 115
 
8.6%
도 112
 
8.4%
로 105
 
7.9%
동 49
 
3.7%
대 35
 
2.6%
길 23
 
1.7%
Other values (105) 351
26.4%
Common
ValueCountFrequency (%)
382
43.0%
1 73
 
8.2%
2 52
 
5.8%
4 44
 
4.9%
3 42
 
4.7%
) 37
 
4.2%
( 37
 
4.2%
6 36
 
4.0%
7 31
 
3.5%
9 30
 
3.4%
Other values (6) 125
 
14.1%
Latin
ValueCountFrequency (%)
L 2
28.6%
C 2
28.6%
W 1
14.3%
K 1
14.3%
R 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1332
59.8%
ASCII 896
40.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
382
42.6%
1 73
 
8.1%
2 52
 
5.8%
4 44
 
4.9%
3 42
 
4.7%
) 37
 
4.1%
( 37
 
4.1%
6 36
 
4.0%
7 31
 
3.5%
9 30
 
3.3%
Other values (11) 132
 
14.7%
Hangul
ValueCountFrequency (%)
산 146
11.0%
오 137
 
10.3%
경 130
 
9.8%
기 129
 
9.7%
시 115
 
8.6%
도 112
 
8.4%
로 105
 
7.9%
동 49
 
3.7%
대 35
 
2.6%
길 23
 
1.7%
Other values (105) 351
26.4%

소재지지번주소
Text

Distinct98
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-12-12T11:51:22.178060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length16.207207
Min length14

Characters and Unicode

Total characters1799
Distinct characters50
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

Unique88 ?
Unique (%)79.3%

Sample

1st row경기도 오산시 청학동 73-1
2nd row경기도 오산시 오산동 474-7
3rd row경기도 오산시 원동 404-1
4th row경기도 오산시 원동 845
5th row경기도 오산시 지곶동 192
ValueCountFrequency (%)
경기도 111
25.0%
오산시 111
25.0%
원동 26
 
5.9%
오산동 19
 
4.3%
세교동 10
 
2.3%
궐동 8
 
1.8%
수청동 8
 
1.8%
외삼미동 7
 
1.6%
가장동 4
 
0.9%
누읍동 4
 
0.9%
Other values (111) 136
30.6%
2023-12-12T11:51:22.659167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
333
18.5%
산 133
 
7.4%
오 130
 
7.2%
경 111
 
6.2%
도 111
 
6.2%
시 111
 
6.2%
기 111
 
6.2%
동 111
 
6.2%
- 78
 
4.3%
1 57
 
3.2%
Other values (40) 513
28.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 975
54.2%
Decimal Number 413
23.0%
Space Separator 333
 
18.5%
Dash Punctuation 78
 
4.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 133
13.6%
오 130
13.3%
경 111
11.4%
도 111
11.4%
시 111
11.4%
기 111
11.4%
동 111
11.4%
원 27
 
2.8%
청 12
 
1.2%
삼 10
 
1.0%
Other values (28) 108
11.1%
Decimal Number
ValueCountFrequency (%)
1 57
13.8%
0 50
12.1%
6 49
11.9%
5 46
11.1%
2 43
10.4%
8 40
9.7%
7 37
9.0%
3 37
9.0%
4 35
8.5%
9 19
 
4.6%
Space Separator
ValueCountFrequency (%)
333
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 975
54.2%
Common 824
45.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 133
13.6%
오 130
13.3%
경 111
11.4%
도 111
11.4%
시 111
11.4%
기 111
11.4%
동 111
11.4%
원 27
 
2.8%
청 12
 
1.2%
삼 10
 
1.0%
Other values (28) 108
11.1%
Common
ValueCountFrequency (%)
333
40.4%
- 78
 
9.5%
1 57
 
6.9%
0 50
 
6.1%
6 49
 
5.9%
5 46
 
5.6%
2 43
 
5.2%
8 40
 
4.9%
7 37
 
4.5%
3 37
 
4.5%
Other values (2) 54
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 975
54.2%
ASCII 824
45.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
333
40.4%
- 78
 
9.5%
1 57
 
6.9%
0 50
 
6.1%
6 49
 
5.9%
5 46
 
5.6%
2 43
 
5.2%
8 40
 
4.9%
7 37
 
4.5%
3 37
 
4.5%
Other values (2) 54
 
6.6%
Hangul
ValueCountFrequency (%)
산 133
13.6%
오 130
13.3%
경 111
11.4%
도 111
11.4%
시 111
11.4%
기 111
11.4%
동 111
11.4%
원 27
 
2.8%
청 12
 
1.2%
삼 10
 
1.0%
Other values (28) 108
11.1%

전화번호
Text

MISSING 

Distinct93
Distinct (%)92.1%
Missing10
Missing (%)9.0%
Memory size1020.0 B
2023-12-12T11:51:22.947301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.178218
Min length11

Characters and Unicode

Total characters1230
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)85.1%

Sample

1st row031-378-6825
2nd row031-378-6825
3rd row031-378-5588
4th row031-375-0085
5th row031-372-3863
ValueCountFrequency (%)
031-379-8581 3
 
3.0%
031-371-2580 2
 
2.0%
031-373-9774 2
 
2.0%
031-378-9672 2
 
2.0%
031-8047-1081 2
 
2.0%
031-8077-8999 2
 
2.0%
031-378-6825 2
 
2.0%
031-378-6782 1
 
1.0%
031-372-0898 1
 
1.0%
031-377-1810 1
 
1.0%
Other values (83) 83
82.2%
2023-12-12T11:51:23.368496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 229
18.6%
- 202
16.4%
0 184
15.0%
7 141
11.5%
1 139
11.3%
8 85
 
6.9%
5 65
 
5.3%
6 64
 
5.2%
9 42
 
3.4%
2 42
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1028
83.6%
Dash Punctuation 202
 
16.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 229
22.3%
0 184
17.9%
7 141
13.7%
1 139
13.5%
8 85
 
8.3%
5 65
 
6.3%
6 64
 
6.2%
9 42
 
4.1%
2 42
 
4.1%
4 37
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1230
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 229
18.6%
- 202
16.4%
0 184
15.0%
7 141
11.5%
1 139
11.3%
8 85
 
6.9%
5 65
 
5.3%
6 64
 
5.2%
9 42
 
3.4%
2 42
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1230
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 229
18.6%
- 202
16.4%
0 184
15.0%
7 141
11.5%
1 139
11.3%
8 85
 
6.9%
5 65
 
5.3%
6 64
 
5.2%
9 42
 
3.4%
2 42
 
3.4%

연면적
Real number (ℝ)

Distinct107
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6441.5061
Minimum304.44
Maximum200548.78
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T11:51:23.562618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum304.44
5-th percentile379.405
Q1869
median2270.78
Q35211.5
95-th percentile18107.5
Maximum200548.78
Range200244.34
Interquartile range (IQR)4342.5

Descriptive statistics

Standard deviation20005.847
Coefficient of variation (CV)3.1057717
Kurtosis82.470816
Mean6441.5061
Median Absolute Deviation (MAD)1610.78
Skewness8.6373135
Sum715007.18
Variance4.0023392 × 108
MonotonicityNot monotonic
2023-12-12T11:51:23.769893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15197.0 3
 
2.7%
495.0 2
 
1.8%
18576.0 2
 
1.8%
2188.0 1
 
0.9%
3284.0 1
 
0.9%
7435.0 1
 
0.9%
2080.0 1
 
0.9%
3439.37 1
 
0.9%
8621.14 1
 
0.9%
459.0 1
 
0.9%
Other values (97) 97
87.4%
ValueCountFrequency (%)
304.44 1
0.9%
308.0 1
0.9%
311.04 1
0.9%
335.04 1
0.9%
348.83 1
0.9%
364.81 1
0.9%
394.0 1
0.9%
442.0 1
0.9%
447.0 1
0.9%
451.0 1
0.9%
ValueCountFrequency (%)
200548.78 1
 
0.9%
58508.41 1
 
0.9%
30287.0 1
 
0.9%
22866.948 1
 
0.9%
18576.0 2
1.8%
17639.0 1
 
0.9%
15197.0 3
2.7%
12544.0 1
 
0.9%
12287.0 1
 
0.9%
11983.2 1
 
0.9%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct102
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.158214
Minimum37.127253
Maximum37.197858
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T11:51:23.945860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.127253
5-th percentile37.134141
Q137.141812
median37.153695
Q337.171955
95-th percentile37.191824
Maximum37.197858
Range0.07060539
Interquartile range (IQR)0.0301433

Descriptive statistics

Standard deviation0.018924749
Coefficient of variation (CV)0.0005093019
Kurtosis-0.92280127
Mean37.158214
Median Absolute Deviation (MAD)0.01310422
Skewness0.5088781
Sum4124.5617
Variance0.00035814613
MonotonicityNot monotonic
2023-12-12T11:51:24.105391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.16516868 2
 
1.8%
37.14933989 2
 
1.8%
37.13841868 2
 
1.8%
37.14059095 2
 
1.8%
37.14906151 2
 
1.8%
37.185834 2
 
1.8%
37.17005201 2
 
1.8%
37.16539216 2
 
1.8%
37.14139492 2
 
1.8%
37.146036 1
 
0.9%
Other values (92) 92
82.9%
ValueCountFrequency (%)
37.12725292 1
0.9%
37.128494 1
0.9%
37.13139173 1
0.9%
37.132344 1
0.9%
37.132883 1
0.9%
37.13339181 1
0.9%
37.13489072 1
0.9%
37.13528564 1
0.9%
37.13727815 1
0.9%
37.138177 1
0.9%
ValueCountFrequency (%)
37.19785831 1
0.9%
37.19758074 1
0.9%
37.194229 1
0.9%
37.19396965 1
0.9%
37.19205322 1
0.9%
37.19199641 1
0.9%
37.191651 1
0.9%
37.191355 1
0.9%
37.19105543 1
0.9%
37.189477 1
0.9%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct103
Distinct (%)92.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.06157
Minimum127.0225
Maximum127.08433
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2023-12-12T11:51:24.256320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0225
5-th percentile127.03724
Q1127.05184
median127.06717
Q3127.07244
95-th percentile127.07702
Maximum127.08433
Range0.0618309
Interquartile range (IQR)0.02060525

Descriptive statistics

Standard deviation0.01423607
Coefficient of variation (CV)0.00011204072
Kurtosis-0.19203166
Mean127.06157
Median Absolute Deviation (MAD)0.0071723
Skewness-0.80315084
Sum14103.834
Variance0.0002026657
MonotonicityNot monotonic
2023-12-12T11:51:24.426677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0617576 2
 
1.8%
127.0690288 2
 
1.8%
127.0438076 2
 
1.8%
127.0382794 2
 
1.8%
127.0713655 2
 
1.8%
127.0725847 2
 
1.8%
127.0729754 2
 
1.8%
127.073832 2
 
1.8%
127.0567804 1
 
0.9%
127.0721957 1
 
0.9%
Other values (93) 93
83.8%
ValueCountFrequency (%)
127.0225021 1
0.9%
127.0231741 1
0.9%
127.026679 1
0.9%
127.029707 1
0.9%
127.034637 1
0.9%
127.0361948 1
0.9%
127.0382794 2
1.8%
127.039148 1
0.9%
127.0400907 1
0.9%
127.040281 1
0.9%
ValueCountFrequency (%)
127.084333 1
0.9%
127.0838341 1
0.9%
127.0821652 1
0.9%
127.0812287 1
0.9%
127.0774447 1
0.9%
127.0770209 1
0.9%
127.077017 1
0.9%
127.0768295 1
0.9%
127.0767249 1
0.9%
127.0757198 1
0.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size1020.0 B
2023-10-06
111 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-06
2nd row2023-10-06
3rd row2023-10-06
4th row2023-10-06
5th row2023-10-06

Common Values

ValueCountFrequency (%)
2023-10-06 111
100.0%

Length

2023-12-12T11:51:24.599170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:51:24.701474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-06 111
100.0%

Interactions

2023-12-12T11:51:20.074318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:19.110330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:19.489360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:20.167013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:19.229048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:19.868574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:20.251512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:19.357991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:51:19.959345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:51:24.759686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설구분소재지지번주소전화번호연면적위도경도
시설구분1.0000.0000.9620.0000.3290.212
소재지지번주소0.0001.0000.9950.0001.0000.977
전화번호0.9620.9951.0001.0000.9620.954
연면적0.0000.0001.0001.0000.0000.000
위도0.3291.0000.9620.0001.0000.802
경도0.2120.9770.9540.0000.8021.000
2023-12-12T11:51:24.884528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연면적위도경도시설구분
연면적1.0000.0280.1090.000
위도0.0281.000-0.6240.136
경도0.109-0.6241.0000.081
시설구분0.0000.1360.0811.000

Missing values

2023-12-12T11:51:20.374601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:51:20.512894image/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

시군명시설구분시설명소재지도로명주소소재지지번주소전화번호연면적위도경도데이터기준일자
0오산시노인요양시설노틀담사랑터경기도 오산시 가장로 709경기도 오산시 청학동 73-1031-378-68252188.037.153421127.056782023-10-06
1오산시노인요양시설노블효타운경기도 오산시 오산로 265-10경기도 오산시 오산동 474-7031-378-68251457.037.150667127.0679222023-10-06
2오산시노인요양시설힘찬요양원경기도 오산시 경기대로 153경기도 오산시 원동 404-1031-378-55881104.037.138257127.0732022023-10-06
3오산시노인요양시설오산참요양원경기도 오산시 오산로 164 5층경기도 오산시 원동 845031-375-00851134.037.141395127.0690292023-10-06
4오산시노인요양시설참소망요양원경기도 오산시 지곶43번길 15-7경기도 오산시 지곶동 192031-372-38631412.037.179751127.0231742023-10-06
5오산시노인요양시설큰나무실버하우스경기도 오산시 외삼미로 27-23(외삼미동)경기도 오산시 외삼미동 459-102031-373-75331528.037.191996127.0530012023-10-06
6오산시노인요양시설오산세원노인요양원경기도 오산시 오산로 123-13(오산동 세원노인전문요양원)경기도 오산시 오산동 794-2031-375-24931989.037.137278127.0671682023-10-06
7오산시노인요양시설골든힐요양원경기도 오산시 지곶43번길 41(지곶동)경기도 오산시 지곶동 240031-373-78702188.1737.179111127.0266792023-10-06
8오산시노인요양시설세교샘너싱홈경기도 오산시 세남로 14번길 31-11 (세교동)경기도 오산시 세교동 85-1031-373-97741284.037.191355127.0391482023-10-06
9오산시노인요양시설더사랑요양원경기도 오산시 양산로 398번길 10-13 (양산동)경기도 오산시 양산동 256-3031-377-72112012.037.194229127.0297072023-10-06
시군명시설구분시설명소재지도로명주소소재지지번주소전화번호연면적위도경도데이터기준일자
101오산시인터넷컴퓨터게임시설제공업의 영업시설겔러리피씨방경기도 오산시 대호로 97(궐동 골드뷰아파트)경기도 오산시 궐동 682-3<NA>394.037.158919127.0538912023-10-06
102오산시인터넷컴퓨터게임시설제공업의 영업시설베스트 PC경기도 오산시 오산로 195 (오산동, 명신예식홀)경기도 오산시 오산동 882-1<NA>348.8337.145971127.0703612023-10-06
103오산시인터넷컴퓨터게임시설제공업의 영업시설스피드 PC방 누읍점경기도 오산시 발안로 1356-3경기도 오산시 누읍동 532<NA>311.0437.141044127.0476512023-10-06
104오산시인터넷컴퓨터게임시설제공업의 영업시설스틸시리즈 PC 방경기도 오산시 오산로160번길 5-6, 건정프라자 4층 (원동)경기도 오산시 원동 345-10<NA>364.8137.141648127.0695812023-10-06
105오산시인터넷컴퓨터게임시설제공업의 영업시설옥스 PC방경기도 오산시 법원로 26, 강남프라자 2층 (청학동)경기도 오산시 청학동 68<NA>335.0437.155426127.0566492023-10-06
106오산시인터넷컴퓨터게임시설제공업의 영업시설네옥스PC방 궐동2호점경기도 오산시 대호로 77 2층(궐동)경기도 오산시 궐동 687-5<NA>304.4437.157101127.0540292023-10-06
107오산시전시시설오산버드파크경기도 오산시 성호대로 141경기도 오산시 오산동 915031-935-57574727.037.149586127.0770172023-10-06
108오산시전시시설스미스평화관경기도 오산시 경기대로 742경기도 오산시 외삼미동 640031-8036-76182864.4937.184817127.0492232023-10-06
109오산시전시시설오산미니어처빌리지경기도 오산시 북삼미로 12경기도 오산시 내삼미동 250031-8036-79763521.8637.177221127.0628962023-10-06
110오산시실내어린이놀이시설챔피언 오산점경기도 오산시 청학로 238 2층경기도 오산시 수청동 610031-373-8859805.237.170137127.0617272023-10-06