Overview

Dataset statistics

Number of variables9
Number of observations40
Missing cells18
Missing cells (%)5.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory78.3 B

Variable types

Text5
Numeric3
Categorical1

Dataset

Description대구광역시_달성군_노인복지시설현황_20230825
Author대구광역시 달성군
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15044947&dataSetDetailId=150449471b973a81650cb_201805251037&provdMethod=FILE

Alerts

정원 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 정원High correlation
정원 has 6 (15.0%) missing valuesMissing
전화번호 has 2 (5.0%) missing valuesMissing
홈페이지 has 10 (25.0%) missing valuesMissing
시설명 has unique valuesUnique

Reproduction

Analysis started2024-04-22 00:29:26.773191
Analysis finished2024-04-22 00:29:28.690069
Duration1.92 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

UNIQUE 

Distinct40
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-04-22T09:29:28.882693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length6.975
Min length3

Characters and Unicode

Total characters279
Distinct characters95
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)100.0%

Sample

1st row신일양로원
2nd row신애요양원
3rd row소망요양원
4th row연광시니어타운
5th row늘푸른실버타운
ValueCountFrequency (%)
신일양로원 1
 
2.3%
아름다운요양원 1
 
2.3%
솔비 1
 
2.3%
효 1
 
2.3%
요양원 1
 
2.3%
사랑마을실버타운 1
 
2.3%
대한실버타운1 1
 
2.3%
나오미행복한집 1
 
2.3%
효자실버타운a 1
 
2.3%
다사효실버타운 1
 
2.3%
Other values (33) 33
76.7%
2024-04-22T09:29:29.331416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 15
 
5.4%
센 14
 
5.0%
터 13
 
4.7%
복 12
 
4.3%
양 12
 
4.3%
노 11
 
3.9%
요 11
 
3.9%
인 11
 
3.9%
지 10
 
3.6%
운 8
 
2.9%
Other values (85) 162
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 274
98.2%
Space Separator 3
 
1.1%
Decimal Number 1
 
0.4%
Uppercase Letter 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 15
 
5.5%
센 14
 
5.1%
터 13
 
4.7%
복 12
 
4.4%
양 12
 
4.4%
노 11
 
4.0%
요 11
 
4.0%
인 11
 
4.0%
지 10
 
3.6%
운 8
 
2.9%
Other values (82) 157
57.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 274
98.2%
Common 4
 
1.4%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 15
 
5.5%
센 14
 
5.1%
터 13
 
4.7%
복 12
 
4.4%
양 12
 
4.4%
노 11
 
4.0%
요 11
 
4.0%
인 11
 
4.0%
지 10
 
3.6%
운 8
 
2.9%
Other values (82) 157
57.3%
Common
ValueCountFrequency (%)
3
75.0%
1 1
 
25.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 274
98.2%
ASCII 5
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 15
 
5.5%
센 14
 
5.1%
터 13
 
4.7%
복 12
 
4.4%
양 12
 
4.4%
노 11
 
4.0%
요 11
 
4.0%
인 11
 
4.0%
지 10
 
3.6%
운 8
 
2.9%
Other values (82) 157
57.3%
ASCII
ValueCountFrequency (%)
3
60.0%
1 1
 
20.0%
A 1
 
20.0%

정원
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct18
Distinct (%)52.9%
Missing6
Missing (%)15.0%
Infinite0
Infinite (%)0.0%
Mean44.352941
Minimum5
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-22T09:29:29.478843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile8.65
Q19
median29
Q358.25
95-th percentile125.55
Maximum206
Range201
Interquartile range (IQR)49.25

Descriptive statistics

Standard deviation48.851589
Coefficient of variation (CV)1.1014284
Kurtosis4.9543563
Mean44.352941
Median Absolute Deviation (MAD)20
Skewness2.1166975
Sum1508
Variance2386.4777
MonotonicityNot monotonic
2024-04-22T09:29:29.619695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
9 11
27.5%
29 2
 
5.0%
31 2
 
5.0%
49 2
 
5.0%
81 2
 
5.0%
85 2
 
5.0%
86 2
 
5.0%
60 1
 
2.5%
206 1
 
2.5%
16 1
 
2.5%
Other values (8) 8
20.0%
(Missing) 6
15.0%
ValueCountFrequency (%)
5 1
 
2.5%
8 1
 
2.5%
9 11
27.5%
16 1
 
2.5%
27 1
 
2.5%
28 1
 
2.5%
29 2
 
5.0%
31 2
 
5.0%
37 1
 
2.5%
48 1
 
2.5%
ValueCountFrequency (%)
206 1
2.5%
199 1
2.5%
86 2
5.0%
85 2
5.0%
81 2
5.0%
60 1
2.5%
53 1
2.5%
49 2
5.0%
48 1
2.5%
37 1
2.5%

주소
Text

Distinct37
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-04-22T09:29:29.885008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length26
Mean length22.125
Min length19

Characters and Unicode

Total characters885
Distinct characters71
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

Unique34 ?
Unique (%)85.0%

Sample

1st row대구광역시 달성군가창면 가창로 1011-31
2nd row대구광역시 달성군가창면 가창로 1025
3rd row대구광역시 달성군가창면 가창로 1025
4th row대구광역시 달성군하빈면 기곡길 209
5th row대구광역시 달성군화원읍 명천로 331
ValueCountFrequency (%)
대구광역시 40
24.4%
달성군화원읍 11
 
6.7%
달성군가창면 7
 
4.3%
가창로 6
 
3.7%
달성군하빈면 5
 
3.0%
달성군다사읍 5
 
3.0%
달성군현풍면 4
 
2.4%
성화로 4
 
2.4%
달성군논공읍 3
 
1.8%
명천로 3
 
1.8%
Other values (64) 76
46.3%
2024-04-22T09:29:30.334153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
124
 
14.0%
대 46
 
5.2%
구 46
 
5.2%
달 45
 
5.1%
성 44
 
5.0%
역 40
 
4.5%
광 40
 
4.5%
군 40
 
4.5%
시 40
 
4.5%
로 34
 
3.8%
Other values (61) 386
43.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 598
67.6%
Decimal Number 154
 
17.4%
Space Separator 124
 
14.0%
Dash Punctuation 9
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 46
 
7.7%
구 46
 
7.7%
달 45
 
7.5%
성 44
 
7.4%
역 40
 
6.7%
광 40
 
6.7%
군 40
 
6.7%
시 40
 
6.7%
로 34
 
5.7%
면 21
 
3.5%
Other values (49) 202
33.8%
Decimal Number
ValueCountFrequency (%)
1 32
20.8%
2 27
17.5%
0 19
12.3%
5 16
10.4%
3 14
9.1%
6 13
8.4%
4 12
 
7.8%
7 8
 
5.2%
9 8
 
5.2%
8 5
 
3.2%
Space Separator
ValueCountFrequency (%)
124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 598
67.6%
Common 287
32.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 46
 
7.7%
구 46
 
7.7%
달 45
 
7.5%
성 44
 
7.4%
역 40
 
6.7%
광 40
 
6.7%
군 40
 
6.7%
시 40
 
6.7%
로 34
 
5.7%
면 21
 
3.5%
Other values (49) 202
33.8%
Common
ValueCountFrequency (%)
124
43.2%
1 32
 
11.1%
2 27
 
9.4%
0 19
 
6.6%
5 16
 
5.6%
3 14
 
4.9%
6 13
 
4.5%
4 12
 
4.2%
- 9
 
3.1%
7 8
 
2.8%
Other values (2) 13
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 598
67.6%
ASCII 287
32.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
124
43.2%
1 32
 
11.1%
2 27
 
9.4%
0 19
 
6.6%
5 16
 
5.6%
3 14
 
4.9%
6 13
 
4.5%
4 12
 
4.2%
- 9
 
3.1%
7 8
 
2.8%
Other values (2) 13
 
4.5%
Hangul
ValueCountFrequency (%)
대 46
 
7.7%
구 46
 
7.7%
달 45
 
7.5%
성 44
 
7.4%
역 40
 
6.7%
광 40
 
6.7%
군 40
 
6.7%
시 40
 
6.7%
로 34
 
5.7%
면 21
 
3.5%
Other values (49) 202
33.8%

전화번호
Text

MISSING 

Distinct35
Distinct (%)92.1%
Missing2
Missing (%)5.0%
Memory size452.0 B
2024-04-22T09:29:30.572560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.105263
Min length12

Characters and Unicode

Total characters460
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

Unique32 ?
Unique (%)84.2%

Sample

1st row053-768-0180
2nd row053-768-3180
3rd row053-761-5225
4th row053-584-0085
5th row053-644-9988
ValueCountFrequency (%)
053-591-2800 2
 
5.3%
053-617-0112 2
 
5.3%
053-644-9988 2
 
5.3%
053-768-0180 1
 
2.6%
053-588-2166 1
 
2.6%
053-614-0675 1
 
2.6%
053-614-7718 1
 
2.6%
0507-1330-9788 1
 
2.6%
053-638-0062 1
 
2.6%
053-768-3180 1
 
2.6%
Other values (25) 25
65.8%
2024-04-22T09:29:31.005475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 76
16.5%
0 74
16.1%
5 56
12.2%
3 53
11.5%
1 49
10.7%
6 43
9.3%
8 32
7.0%
7 30
 
6.5%
9 16
 
3.5%
4 16
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 384
83.5%
Dash Punctuation 76
 
16.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 74
19.3%
5 56
14.6%
3 53
13.8%
1 49
12.8%
6 43
11.2%
8 32
8.3%
7 30
7.8%
9 16
 
4.2%
4 16
 
4.2%
2 15
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 460
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 76
16.5%
0 74
16.1%
5 56
12.2%
3 53
11.5%
1 49
10.7%
6 43
9.3%
8 32
7.0%
7 30
 
6.5%
9 16
 
3.5%
4 16
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 76
16.5%
0 74
16.1%
5 56
12.2%
3 53
11.5%
1 49
10.7%
6 43
9.3%
8 32
7.0%
7 30
 
6.5%
9 16
 
3.5%
4 16
 
3.5%

종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size452.0 B
노인요양시설
16 
노인요양공동생활가정
13 
재가노인복지시설
10 
양로시설
 
1

Length

Max length10
Median length8
Mean length7.75
Min length4

Unique

Unique1 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
노인요양시설 16
40.0%
노인요양공동생활가정 13
32.5%
재가노인복지시설 10
25.0%
양로시설 1
 
2.5%

Length

2024-04-22T09:29:31.197010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-22T09:29:31.326155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인요양시설 16
40.0%
노인요양공동생활가정 13
32.5%
재가노인복지시설 10
25.0%
양로시설 1
 
2.5%

홈페이지
Text

MISSING 

Distinct27
Distinct (%)90.0%
Missing10
Missing (%)25.0%
Memory size452.0 B
2024-04-22T09:29:31.576601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length39.5
Mean length29.766667
Min length11

Characters and Unicode

Total characters893
Distinct characters46
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

Unique24 ?
Unique (%)80.0%

Sample

1st rowhttp://www.shinillove.or.kr/shinillove/
2nd rowhttp://www.shinilwon.or.kr/
3rd rowhttp://www.shinilwon.co.kr/
4th rowwww.ykscc.or.kr
5th rowhttp://www.green9988.co.kr/
ValueCountFrequency (%)
www.green9988.com 2
 
6.7%
https://m.cafe.daum.net/hyokyeong/_rec 2
 
6.7%
https://blog.naver.com/daehan9788 2
 
6.7%
http://www.shinilwon.or.kr 1
 
3.3%
http://www.shinillove.or.kr/shinillove 1
 
3.3%
www.더나은.com 1
 
3.3%
http://www.sk2006.kr/ju.htm 1
 
3.3%
https://place.map.kakao.com/27338833 1
 
3.3%
http://www.sk2006.kr/no.htm 1
 
3.3%
https://place.map.kakao.com/9557276?service=search_pc 1
 
3.3%
Other values (17) 17
56.7%
2024-04-22T09:29:31.965273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 78
 
8.7%
/ 71
 
8.0%
t 55
 
6.2%
w 54
 
6.0%
o 46
 
5.2%
e 45
 
5.0%
a 45
 
5.0%
h 44
 
4.9%
c 41
 
4.6%
r 33
 
3.7%
Other values (36) 381
42.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 631
70.7%
Other Punctuation 173
 
19.4%
Decimal Number 77
 
8.6%
Connector Punctuation 5
 
0.6%
Other Letter 3
 
0.3%
Dash Punctuation 2
 
0.2%
Math Symbol 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 55
 
8.7%
w 54
 
8.6%
o 46
 
7.3%
e 45
 
7.1%
a 45
 
7.1%
h 44
 
7.0%
c 41
 
6.5%
r 33
 
5.2%
p 33
 
5.2%
m 32
 
5.1%
Other values (16) 203
32.2%
Decimal Number
ValueCountFrequency (%)
8 12
15.6%
9 12
15.6%
7 10
13.0%
0 10
13.0%
6 8
10.4%
2 8
10.4%
3 7
9.1%
1 5
6.5%
4 3
 
3.9%
5 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 78
45.1%
/ 71
41.0%
: 22
 
12.7%
? 2
 
1.2%
Other Letter
ValueCountFrequency (%)
더 1
33.3%
나 1
33.3%
은 1
33.3%
Connector Punctuation
ValueCountFrequency (%)
_ 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
= 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 631
70.7%
Common 259
29.0%
Hangul 3
 
0.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 55
 
8.7%
w 54
 
8.6%
o 46
 
7.3%
e 45
 
7.1%
a 45
 
7.1%
h 44
 
7.0%
c 41
 
6.5%
r 33
 
5.2%
p 33
 
5.2%
m 32
 
5.1%
Other values (16) 203
32.2%
Common
ValueCountFrequency (%)
. 78
30.1%
/ 71
27.4%
: 22
 
8.5%
8 12
 
4.6%
9 12
 
4.6%
7 10
 
3.9%
0 10
 
3.9%
6 8
 
3.1%
2 8
 
3.1%
3 7
 
2.7%
Other values (7) 21
 
8.1%
Hangul
ValueCountFrequency (%)
더 1
33.3%
나 1
33.3%
은 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 890
99.7%
Hangul 3
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 78
 
8.8%
/ 71
 
8.0%
t 55
 
6.2%
w 54
 
6.1%
o 46
 
5.2%
e 45
 
5.1%
a 45
 
5.1%
h 44
 
4.9%
c 41
 
4.6%
r 33
 
3.7%
Other values (33) 378
42.5%
Hangul
ValueCountFrequency (%)
더 1
33.3%
나 1
33.3%
은 1
33.3%

시설장
Text

Distinct39
Distinct (%)97.5%
Missing0
Missing (%)0.0%
Memory size452.0 B
2024-04-22T09:29:32.202996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters120
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)95.0%

Sample

1st row최미지
2nd row오금옥
3rd row송정수
4th row김제완
5th row신경용
ValueCountFrequency (%)
양광호 2
 
5.0%
이승무 1
 
2.5%
임수정 1
 
2.5%
김정균 1
 
2.5%
박지용 1
 
2.5%
정미연 1
 
2.5%
김해순 1
 
2.5%
최영옥 1
 
2.5%
최재정 1
 
2.5%
서금지 1
 
2.5%
Other values (29) 29
72.5%
2024-04-22T09:29:32.586027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
정 9
 
7.5%
김 9
 
7.5%
호 4
 
3.3%
옥 4
 
3.3%
이 4
 
3.3%
최 3
 
2.5%
희 3
 
2.5%
경 3
 
2.5%
신 3
 
2.5%
수 3
 
2.5%
Other values (52) 75
62.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 9
 
7.5%
김 9
 
7.5%
호 4
 
3.3%
옥 4
 
3.3%
이 4
 
3.3%
최 3
 
2.5%
희 3
 
2.5%
경 3
 
2.5%
신 3
 
2.5%
수 3
 
2.5%
Other values (52) 75
62.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 9
 
7.5%
김 9
 
7.5%
호 4
 
3.3%
옥 4
 
3.3%
이 4
 
3.3%
최 3
 
2.5%
희 3
 
2.5%
경 3
 
2.5%
신 3
 
2.5%
수 3
 
2.5%
Other values (52) 75
62.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
정 9
 
7.5%
김 9
 
7.5%
호 4
 
3.3%
옥 4
 
3.3%
이 4
 
3.3%
최 3
 
2.5%
희 3
 
2.5%
경 3
 
2.5%
신 3
 
2.5%
수 3
 
2.5%
Other values (52) 75
62.5%

위도
Real number (ℝ)

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.793374
Minimum35.648329
Maximum35.926989
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-22T09:29:32.756499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.648329
5-th percentile35.693064
Q135.756836
median35.798814
Q335.820395
95-th percentile35.890235
Maximum35.926989
Range0.2786601
Interquartile range (IQR)0.06355935

Descriptive statistics

Standard deviation0.064907343
Coefficient of variation (CV)0.0018133899
Kurtosis-0.36412314
Mean35.793374
Median Absolute Deviation (MAD)0.04306995
Skewness-0.12619109
Sum1431.735
Variance0.0042129631
MonotonicityNot monotonic
2024-04-22T09:29:32.906954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
35.7966333 2
 
5.0%
35.8012674 2
 
5.0%
35.858697 2
 
5.0%
35.6991889 2
 
5.0%
35.7963356 1
 
2.5%
35.6931072 1
 
2.5%
35.88031 1
 
2.5%
35.8037327 1
 
2.5%
35.8563774 1
 
2.5%
35.7930776 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
35.6483292 1
2.5%
35.6922491 1
2.5%
35.6931072 1
2.5%
35.6976161 1
2.5%
35.6991889 2
5.0%
35.7210029 1
2.5%
35.7249721 1
2.5%
35.7325702 1
2.5%
35.7535599 1
2.5%
35.757928 1
2.5%
ValueCountFrequency (%)
35.9269893 1
2.5%
35.8919449 1
2.5%
35.8901448 1
2.5%
35.8803989 1
2.5%
35.88031 1
2.5%
35.8769959 1
2.5%
35.8706941 1
2.5%
35.858697 2
5.0%
35.8563774 1
2.5%
35.8084013 1
2.5%

경도
Real number (ℝ)

Distinct36
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.49386
Minimum128.40751
Maximum128.67485
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size492.0 B
2024-04-22T09:29:33.055209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.40751
5-th percentile128.41697
Q1128.44384
median128.48094
Q3128.49871
95-th percentile128.62829
Maximum128.67485
Range0.267343
Interquartile range (IQR)0.05486855

Descriptive statistics

Standard deviation0.072850238
Coefficient of variation (CV)0.00056695503
Kurtosis0.62859643
Mean128.49386
Median Absolute Deviation (MAD)0.03059175
Skewness1.2922918
Sum5139.7542
Variance0.0053071571
MonotonicityNot monotonic
2024-04-22T09:29:33.208981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
128.625875 2
 
5.0%
128.4885811 2
 
5.0%
128.4637196 2
 
5.0%
128.4471898 2
 
5.0%
128.6263694 1
 
2.5%
128.4582125 1
 
2.5%
128.4167763 1
 
2.5%
128.4974241 1
 
2.5%
128.4340767 1
 
2.5%
128.4875123 1
 
2.5%
Other values (26) 26
65.0%
ValueCountFrequency (%)
128.4075058 1
2.5%
128.4167763 1
2.5%
128.4169758 1
2.5%
128.4269239 1
2.5%
128.4282585 1
2.5%
128.4285695 1
2.5%
128.4340767 1
2.5%
128.4371809 1
2.5%
128.4406183 1
2.5%
128.4412208 1
2.5%
ValueCountFrequency (%)
128.6748488 1
2.5%
128.6648806 1
2.5%
128.6263694 1
2.5%
128.625875 2
5.0%
128.6235387 1
2.5%
128.6226942 1
2.5%
128.5083733 1
2.5%
128.5041107 1
2.5%
128.5022698 1
2.5%
128.4975258 1
2.5%

Interactions

2024-04-22T09:29:27.965210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:27.284048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:27.626917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:28.073095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:27.402059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:27.749718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:28.190308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:27.510423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T09:29:27.848202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T09:29:33.319306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명정원주소전화번호종류홈페이지시설장위도경도
시설명1.0001.0001.0001.0001.0001.0001.0001.0001.000
정원1.0001.0000.9741.0000.7391.0000.9560.0000.697
주소1.0000.9741.0000.9460.8860.9481.0001.0001.000
전화번호1.0001.0000.9461.0000.9590.9640.9790.8450.958
종류1.0000.7390.8860.9591.0000.9310.8870.0000.422
홈페이지1.0001.0000.9480.9640.9311.0000.9820.9250.967
시설장1.0000.9561.0000.9790.8870.9821.0001.0001.000
위도1.0000.0001.0000.8450.0000.9251.0001.0000.780
경도1.0000.6971.0000.9580.4220.9671.0000.7801.000
2024-04-22T09:29:33.459447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
정원위도경도종류
정원1.000-0.1720.2490.553
위도-0.1721.000-0.1400.000
경도0.249-0.1401.0000.263
종류0.5530.0000.2631.000

Missing values

2024-04-22T09:29:28.326168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T09:29:28.493106image/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.
2024-04-22T09:29:28.622845image/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

시설명정원주소전화번호종류홈페이지시설장위도경도
0신일양로원85대구광역시 달성군가창면 가창로 1011-31053-768-0180양로시설http://www.shinillove.or.kr/shinillove/최미지35.796336128.626369
1신애요양원81대구광역시 달성군가창면 가창로 1025053-768-3180노인요양시설http://www.shinilwon.or.kr/오금옥35.796633128.625875
2소망요양원81대구광역시 달성군가창면 가창로 1025053-761-5225노인요양시설http://www.shinilwon.co.kr/송정수35.796633128.625875
3연광시니어타운85대구광역시 달성군하빈면 기곡길 209053-584-0085노인요양시설www.ykscc.or.kr김제완35.926989128.426924
4늘푸른실버타운86대구광역시 달성군화원읍 명천로 331053-644-9988노인요양시설http://www.green9988.co.kr/신경용35.79263128.487523
5비슬원27대구광역시 달성군화원읍 성화로 40053-643-1166노인요양시설<NA>박임순35.801267128.488581
6대구가톨릭치매센타199대구광역시 달성군논공읍 논공로 210053-615-2141노인요양시설http://cdcdc.co.kr/정석수35.721003128.453644
7한패밀리요양원86대구광역시 달성군가창면 가창로 175053-766-4100노인요양시설www.silverhanfamily.or.kr정숙희35.73257128.664881
8행복한효경16대구광역시 달성군현풍면 현풍동로27길 25053-611-3778노인요양시설https://cafe.daum.net/ilovehg1004양광호35.699189128.44719
9대구보훈요양원206대구광역시 달성군하빈면 하산길 123-23053-606-3000노인요양시설https://dgcare.bohun.or.kr/main/main.asp구명서35.890145128.407506
시설명정원주소전화번호종류홈페이지시설장위도경도
30향기노인복지센터<NA>대구광역시 달성군유가면 테크노중앙대로 254 605호<NA>재가노인복지시설<NA>이승무35.693107128.458213
31효경재가노인지원센터<NA>대구광역시 달성군현풍면 현풍중앙로20길 25053-617-0112재가노인복지시설http://www.hg6170112.com/main/index.html김양희35.697616128.444717
32한울노인복지센터<NA>대구광역시 달성군화원읍 비슬로 2679053-634-8668재가노인복지시설https://place.map.kakao.com/9557276?service=search_pc신형규35.808401128.508373
33비슬노인복지센터<NA>대구광역시 달성군화원읍 성화로 11053-617-0982재가노인복지시설http://www.sk2006.kr/no.htm김상근35.800618128.491536
34단비노인복지센터<NA>대구광역시 달성군화원읍 성화로 40<NA>재가노인복지시설https://place.map.kakao.com/27338833김길동35.801267128.488581
35늘푸른복지센터<NA>대구광역시 달성군가창면 가창로 1096053-644-9988재가노인복지시설www.green9988.com정현락35.802312128.622694
36효경노인복지센터31대구광역시 달성군구지면 창한로 567053-617-0112재가노인복지시설https://m.cafe.daum.net/hyokyeong/_rec서혜숙35.648329128.454603
37효경주간보호센터31대구광역시 달성군현풍면 현풍동로27길 25053-617-0113재가노인복지시설https://m.cafe.daum.net/hyokyeong/_rec양광호35.699189128.44719
38수경주간보호센터53대구광역시 달성군화원읍 비슬로 2490053-634-6780재가노인복지시설http://www.sk2006.kr/ju.htm서금지35.799324128.490797
39수경기억학교37대구광역시 달성군화원읍 성화로 130507-1415-5902재가노인복지시설http://www.sk2006.kr/bi01.htm안대영35.80058128.491311