Overview

Dataset statistics

Number of variables7
Number of observations84
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory58.6 B

Variable types

Categorical1
Text3
DateTime2
Numeric1

Dataset

Description경기도 포천시에서 제공하는 노인복지시설현황(시설종류, 시설명, 전화번호, 주소, 설치일자, 입소정원 등) 데이터입니다.
URLhttps://www.data.go.kr/data/15118212/fileData.do

Alerts

데이터기준일 has constant value ""Constant
입소정원 is highly overall correlated with 시설종류High correlation
시설종류 is highly overall correlated with 입소정원High correlation
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:39:14.235137
Analysis finished2023-12-12 02:39:15.453221
Duration1.22 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
노인요양시설
57 
노인요양공동생활가정
21 
양로시설
 
3
노인공동생활가정
 
3

Length

Max length10
Median length6
Mean length7
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
노인요양시설 57
67.9%
노인요양공동생활가정 21
 
25.0%
양로시설 3
 
3.6%
노인공동생활가정 3
 
3.6%

Length

2023-12-12T11:39:15.549265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:39:15.718647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
노인요양시설 57
67.9%
노인요양공동생활가정 21
 
25.0%
양로시설 3
 
3.6%
노인공동생활가정 3
 
3.6%

시설명
Text

UNIQUE 

Distinct84
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-12T11:39:16.046018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length6.8571429
Min length3

Characters and Unicode

Total characters576
Distinct characters154
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

Unique84 ?
Unique (%)100.0%

Sample

1st row선혜원
2nd row포천분도마을
3rd row사회복지법인 효담전문요양원
4th row모현노인요양원
5th row가족처럼노인요양원
ValueCountFrequency (%)
사회복지법인 2
 
2.2%
요양원 2
 
2.2%
선혜원 1
 
1.1%
포천분도마을 1
 
1.1%
소망공동체요양원 1
 
1.1%
임마누엘공동생활가정 1
 
1.1%
에덴동산요양원 1
 
1.1%
우리집 1
 
1.1%
다올건강실버케어 1
 
1.1%
다올재활실버케어 1
 
1.1%
Other values (80) 80
87.0%
2023-12-12T11:39:16.536165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 63
 
10.9%
양 60
 
10.4%
요 59
 
10.2%
집 13
 
2.3%
의 13
 
2.3%
사 12
 
2.1%
천 12
 
2.1%
인 11
 
1.9%
포 10
 
1.7%
노 9
 
1.6%
Other values (144) 314
54.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 560
97.2%
Space Separator 8
 
1.4%
Uppercase Letter 6
 
1.0%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 63
 
11.2%
양 60
 
10.7%
요 59
 
10.5%
집 13
 
2.3%
의 13
 
2.3%
사 12
 
2.1%
천 12
 
2.1%
인 11
 
2.0%
포 10
 
1.8%
노 9
 
1.6%
Other values (138) 298
53.2%
Uppercase Letter
ValueCountFrequency (%)
V 2
33.3%
I 2
33.3%
P 2
33.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 560
97.2%
Common 10
 
1.7%
Latin 6
 
1.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 63
 
11.2%
양 60
 
10.7%
요 59
 
10.5%
집 13
 
2.3%
의 13
 
2.3%
사 12
 
2.1%
천 12
 
2.1%
인 11
 
2.0%
포 10
 
1.8%
노 9
 
1.6%
Other values (138) 298
53.2%
Common
ValueCountFrequency (%)
8
80.0%
1 1
 
10.0%
2 1
 
10.0%
Latin
ValueCountFrequency (%)
V 2
33.3%
I 2
33.3%
P 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 560
97.2%
ASCII 16
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 63
 
11.2%
양 60
 
10.7%
요 59
 
10.5%
집 13
 
2.3%
의 13
 
2.3%
사 12
 
2.1%
천 12
 
2.1%
인 11
 
2.0%
포 10
 
1.8%
노 9
 
1.6%
Other values (138) 298
53.2%
ASCII
ValueCountFrequency (%)
8
50.0%
V 2
 
12.5%
I 2
 
12.5%
P 2
 
12.5%
1 1
 
6.2%
2 1
 
6.2%

전화번호
Text

Distinct83
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-12T11:39:16.871580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.02381
Min length12

Characters and Unicode

Total characters1010
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

Unique82 ?
Unique (%)97.6%

Sample

1st row031-532-5907
2nd row031-539-0500
3rd row031-543-3980
4th row031-535-2519
5th row031-534-7340
ValueCountFrequency (%)
031-543-3980 2
 
2.4%
031-542-6742 1
 
1.2%
031-928-5600 1
 
1.2%
031-542-8631 1
 
1.2%
031-532-7208 1
 
1.2%
031-542-9124 1
 
1.2%
031-533-0691 1
 
1.2%
031-542-5100 1
 
1.2%
031-544-3900 1
 
1.2%
031-544-3838 1
 
1.2%
Other values (73) 73
86.9%
2023-12-12T11:39:17.351226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 177
17.5%
- 168
16.6%
0 152
15.0%
1 144
14.3%
5 130
12.9%
4 62
 
6.1%
9 53
 
5.2%
8 39
 
3.9%
2 38
 
3.8%
7 26
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 842
83.4%
Dash Punctuation 168
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 177
21.0%
0 152
18.1%
1 144
17.1%
5 130
15.4%
4 62
 
7.4%
9 53
 
6.3%
8 39
 
4.6%
2 38
 
4.5%
7 26
 
3.1%
6 21
 
2.5%
Dash Punctuation
ValueCountFrequency (%)
- 168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1010
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 177
17.5%
- 168
16.6%
0 152
15.0%
1 144
14.3%
5 130
12.9%
4 62
 
6.1%
9 53
 
5.2%
8 39
 
3.9%
2 38
 
3.8%
7 26
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1010
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 177
17.5%
- 168
16.6%
0 152
15.0%
1 144
14.3%
5 130
12.9%
4 62
 
6.1%
9 53
 
5.2%
8 39
 
3.9%
2 38
 
3.8%
7 26
 
2.6%

시설소재지주소
Text

Distinct81
Distinct (%)96.4%
Missing0
Missing (%)0.0%
Memory size804.0 B
2023-12-12T11:39:17.717467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length30
Mean length23.666667
Min length18

Characters and Unicode

Total characters1988
Distinct characters120
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique78 ?
Unique (%)92.9%

Sample

1st row경기도 포천시 관인면 북원로641번길 28
2nd row경기도 포천시 자작로4길 71 (자작동)
3rd row경기도 포천시 가산면 부흥로 718
4th row경기도 포천시 왕방로 210 (신읍동)
5th row경기도 포천시 일동면 화동로 1648
ValueCountFrequency (%)
경기도 84
18.5%
포천시 84
18.5%
소흘읍 30
 
6.6%
일동면 12
 
2.6%
송우로 11
 
2.4%
성장로 8
 
1.8%
신북면 6
 
1.3%
광릉수목원로 6
 
1.3%
7층 5
 
1.1%
영북면 4
 
0.9%
Other values (155) 203
44.8%
2023-12-12T11:39:18.228802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
369
 
18.6%
기 85
 
4.3%
포 85
 
4.3%
천 85
 
4.3%
시 85
 
4.3%
경 84
 
4.2%
도 84
 
4.2%
로 72
 
3.6%
1 55
 
2.8%
3 52
 
2.6%
Other values (110) 932
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1165
58.6%
Space Separator 369
 
18.6%
Decimal Number 360
 
18.1%
Dash Punctuation 29
 
1.5%
Close Punctuation 21
 
1.1%
Open Punctuation 21
 
1.1%
Other Punctuation 21
 
1.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 85
 
7.3%
포 85
 
7.3%
천 85
 
7.3%
시 85
 
7.3%
경 84
 
7.2%
도 84
 
7.2%
로 72
 
6.2%
면 43
 
3.7%
동 42
 
3.6%
길 34
 
2.9%
Other values (93) 466
40.0%
Decimal Number
ValueCountFrequency (%)
1 55
15.3%
3 52
14.4%
2 46
12.8%
5 38
10.6%
7 35
9.7%
6 33
9.2%
4 30
8.3%
9 28
7.8%
8 23
6.4%
0 20
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%
Space Separator
ValueCountFrequency (%)
369
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Other Punctuation
ValueCountFrequency (%)
, 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1165
58.6%
Common 821
41.3%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 85
 
7.3%
포 85
 
7.3%
천 85
 
7.3%
시 85
 
7.3%
경 84
 
7.2%
도 84
 
7.2%
로 72
 
6.2%
면 43
 
3.7%
동 42
 
3.6%
길 34
 
2.9%
Other values (93) 466
40.0%
Common
ValueCountFrequency (%)
369
44.9%
1 55
 
6.7%
3 52
 
6.3%
2 46
 
5.6%
5 38
 
4.6%
7 35
 
4.3%
6 33
 
4.0%
4 30
 
3.7%
- 29
 
3.5%
9 28
 
3.4%
Other values (5) 106
 
12.9%
Latin
ValueCountFrequency (%)
B 1
50.0%
A 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1165
58.6%
ASCII 823
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
369
44.8%
1 55
 
6.7%
3 52
 
6.3%
2 46
 
5.6%
5 38
 
4.6%
7 35
 
4.3%
6 33
 
4.0%
4 30
 
3.6%
- 29
 
3.5%
9 28
 
3.4%
Other values (7) 108
 
13.1%
Hangul
ValueCountFrequency (%)
기 85
 
7.3%
포 85
 
7.3%
천 85
 
7.3%
시 85
 
7.3%
경 84
 
7.2%
도 84
 
7.2%
로 72
 
6.2%
면 43
 
3.7%
동 42
 
3.6%
길 34
 
2.9%
Other values (93) 466
40.0%

설치일자
Date

Distinct72
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum1996-11-19 00:00:00
Maximum2023-01-16 00:00:00
2023-12-12T11:39:18.387174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:39:18.524444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

입소정원
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.357143
Minimum6
Maximum102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size888.0 B
2023-12-12T11:39:18.650282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile9
Q19
median29
Q349
95-th percentile98.4
Maximum102
Range96
Interquartile range (IQR)40

Descriptive statistics

Standard deviation29.422409
Coefficient of variation (CV)0.78759794
Kurtosis-0.38487999
Mean37.357143
Median Absolute Deviation (MAD)20
Skewness0.95201103
Sum3138
Variance865.67814
MonotonicityNot monotonic
2023-12-12T11:39:18.765317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
9 22
26.2%
29 14
16.7%
49 5
 
6.0%
26 4
 
4.8%
99 4
 
4.8%
90 3
 
3.6%
28 3
 
3.6%
21 2
 
2.4%
48 2
 
2.4%
24 2
 
2.4%
Other values (19) 23
27.4%
ValueCountFrequency (%)
6 1
 
1.2%
8 1
 
1.2%
9 22
26.2%
19 1
 
1.2%
20 1
 
1.2%
21 2
 
2.4%
24 2
 
2.4%
25 2
 
2.4%
26 4
 
4.8%
27 1
 
1.2%
ValueCountFrequency (%)
102 1
 
1.2%
99 4
4.8%
95 1
 
1.2%
90 3
3.6%
85 2
2.4%
84 2
2.4%
82 1
 
1.2%
78 1
 
1.2%
75 2
2.4%
71 1
 
1.2%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size804.0 B
Minimum2023-08-09 00:00:00
Maximum2023-08-09 00:00:00
2023-12-12T11:39:18.868071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T11:39:18.957880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T11:39:15.095372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:39:19.031221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설종류시설명전화번호시설소재지주소설치일자입소정원
시설종류1.0001.0000.0000.0000.9790.699
시설명1.0001.0001.0001.0001.0001.000
전화번호0.0001.0001.0001.0000.9930.804
시설소재지주소0.0001.0001.0001.0000.9950.837
설치일자0.9791.0000.9930.9951.0000.746
입소정원0.6991.0000.8040.8370.7461.000
2023-12-12T11:39:19.121253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
입소정원시설종류
입소정원1.0000.515
시설종류0.5151.000

Missing values

2023-12-12T11:39:15.231037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:39:15.386230image/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

시설종류시설명전화번호시설소재지주소설치일자입소정원데이터기준일
0노인요양시설선혜원031-532-5907경기도 포천시 관인면 북원로641번길 282004-06-01262023-08-09
1노인요양시설포천분도마을031-539-0500경기도 포천시 자작로4길 71 (자작동)2004-10-05482023-08-09
2노인요양시설사회복지법인 효담전문요양원031-543-3980경기도 포천시 가산면 부흥로 7182004-11-301022023-08-09
3노인요양시설모현노인요양원031-535-2519경기도 포천시 왕방로 210 (신읍동)2005-07-29482023-08-09
4노인요양시설가족처럼노인요양원031-534-7340경기도 포천시 일동면 화동로 16482007-08-02292023-08-09
5노인요양시설소망의집031-535-9101경기도 포천시 일동면 성장로 3852008-04-03422023-08-09
6노인요양시설포천노인전문요양센터031-535-8791경기도 포천시 신북면 탑신로 14632008-07-30902023-08-09
7노인요양시설샬롬의집031-541-0178경기도 포천시 일동면 윗갈기1길 872008-12-31292023-08-09
8노인요양시설포천부모님실버타운요양원031-531-8100경기도 포천시 내촌면 금강로3029번길 32011-06-16352023-08-09
9노인요양시설사랑의집031-535-9118경기도 포천시 일동면 성장로 379-22012-01-01292023-08-09
시설종류시설명전화번호시설소재지주소설치일자입소정원데이터기준일
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