Overview

Dataset statistics

Number of variables5
Number of observations26
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory46.1 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description전라북도 임실군 노인복지시설현황 데이터 입니다. 데이터 세부내역에는 기관명, 종류, 급여종류, 전화번호, 기관주소 데이터를 제공합니다.
Author전라북도 임실군
URLhttps://www.data.go.kr/data/15055559/fileData.do

Alerts

연번 is highly overall correlated with 종류High correlation
종류 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
기관명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:24:27.766217
Analysis finished2023-12-12 18:24:28.189963
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.5
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size366.0 B
2023-12-13T03:24:28.249029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.25
Q17.25
median13.5
Q319.75
95-th percentile24.75
Maximum26
Range25
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation7.6485293
Coefficient of variation (CV)0.56655772
Kurtosis-1.2
Mean13.5
Median Absolute Deviation (MAD)6.5
Skewness0
Sum351
Variance58.5
MonotonicityStrictly increasing
2023-12-13T03:24:28.357184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
1 1
 
3.8%
15 1
 
3.8%
26 1
 
3.8%
25 1
 
3.8%
24 1
 
3.8%
23 1
 
3.8%
22 1
 
3.8%
21 1
 
3.8%
20 1
 
3.8%
19 1
 
3.8%
Other values (16) 16
61.5%
ValueCountFrequency (%)
1 1
3.8%
2 1
3.8%
3 1
3.8%
4 1
3.8%
5 1
3.8%
6 1
3.8%
7 1
3.8%
8 1
3.8%
9 1
3.8%
10 1
3.8%
ValueCountFrequency (%)
26 1
3.8%
25 1
3.8%
24 1
3.8%
23 1
3.8%
22 1
3.8%
21 1
3.8%
20 1
3.8%
19 1
3.8%
18 1
3.8%
17 1
3.8%

기관명
Text

UNIQUE 

Distinct26
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T03:24:28.546547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length10.076923
Min length7

Characters and Unicode

Total characters262
Distinct characters73
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)100.0%

Sample

1st row 사랑요양원
2nd row 관촌원광수양원
3rd row 정드림노인요양원
4th row 안나사랑원
5th row 굿모닝사랑원
ValueCountFrequency (%)
사랑요양원 1
 
3.8%
관촌원광수양원 1
 
3.8%
임실군북부권노인복지관 1
 
3.8%
임실군노인종합복지관 1
 
3.8%
늘사랑주간보호센터 1
 
3.8%
미소노인복지센터 1
 
3.8%
참조은노인복지센터 1
 
3.8%
복된노인복지센터 1
 
3.8%
해피노인복지센터 1
 
3.8%
백세노인복지센터 1
 
3.8%
Other values (16) 16
61.5%
2023-12-13T03:24:28.859194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
52
19.8%
복 16
 
6.1%
인 15
 
5.7%
지 15
 
5.7%
노 15
 
5.7%
터 14
 
5.3%
센 14
 
5.3%
원 10
 
3.8%
양 6
 
2.3%
랑 5
 
1.9%
Other values (63) 100
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 210
80.2%
Space Separator 52
 
19.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
복 16
 
7.6%
인 15
 
7.1%
지 15
 
7.1%
노 15
 
7.1%
터 14
 
6.7%
센 14
 
6.7%
원 10
 
4.8%
양 6
 
2.9%
랑 5
 
2.4%
요 5
 
2.4%
Other values (62) 95
45.2%
Space Separator
ValueCountFrequency (%)
52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 210
80.2%
Common 52
 
19.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
복 16
 
7.6%
인 15
 
7.1%
지 15
 
7.1%
노 15
 
7.1%
터 14
 
6.7%
센 14
 
6.7%
원 10
 
4.8%
양 6
 
2.9%
랑 5
 
2.4%
요 5
 
2.4%
Other values (62) 95
45.2%
Common
ValueCountFrequency (%)
52
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 210
80.2%
ASCII 52
 
19.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52
100.0%
Hangul
ValueCountFrequency (%)
복 16
 
7.6%
인 15
 
7.1%
지 15
 
7.1%
노 15
 
7.1%
터 14
 
6.7%
센 14
 
6.7%
원 10
 
4.8%
양 6
 
2.9%
랑 5
 
2.4%
요 5
 
2.4%
Other values (62) 95
45.2%

종류
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)15.4%
Missing0
Missing (%)0.0%
Memory size340.0 B
재가노인복지시설
15 
노인의료복지시설
8 
노인여가복지시설
2 
노인일자리지원기관
 
1

Length

Max length9
Median length8
Mean length8.0384615
Min length8

Unique

Unique1 ?
Unique (%)3.8%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 15
57.7%
노인의료복지시설 8
30.8%
노인여가복지시설 2
 
7.7%
노인일자리지원기관 1
 
3.8%

Length

2023-12-13T03:24:28.978169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:24:29.069247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인복지시설 15
57.7%
노인의료복지시설 8
30.8%
노인여가복지시설 2
 
7.7%
노인일자리지원기관 1
 
3.8%

전화번호
Text

Distinct23
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T03:24:29.228593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters312
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

Unique20 ?
Unique (%)76.9%

Sample

1st row063-642-9191
2nd row063-643-6688
3rd row063-644-0188
4th row063-642-5877
5th row063-642-4466
ValueCountFrequency (%)
063-644-0188 2
 
7.7%
063-644-0010 2
 
7.7%
063-642-0575 2
 
7.7%
063-644-6611 1
 
3.8%
063-642-9191 1
 
3.8%
063-643-8880 1
 
3.8%
063-642-3844 1
 
3.8%
063-644-4438 1
 
3.8%
063-644-5684 1
 
3.8%
063-643-1126 1
 
3.8%
Other values (13) 13
50.0%
2023-12-13T03:24:29.506433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 64
20.5%
- 52
16.7%
4 50
16.0%
0 43
13.8%
3 36
11.5%
8 19
 
6.1%
1 13
 
4.2%
2 12
 
3.8%
5 11
 
3.5%
7 6
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 260
83.3%
Dash Punctuation 52
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 64
24.6%
4 50
19.2%
0 43
16.5%
3 36
13.8%
8 19
 
7.3%
1 13
 
5.0%
2 12
 
4.6%
5 11
 
4.2%
7 6
 
2.3%
9 6
 
2.3%
Dash Punctuation
ValueCountFrequency (%)
- 52
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 312
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 64
20.5%
- 52
16.7%
4 50
16.0%
0 43
13.8%
3 36
11.5%
8 19
 
6.1%
1 13
 
4.2%
2 12
 
3.8%
5 11
 
3.5%
7 6
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 312
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 64
20.5%
- 52
16.7%
4 50
16.0%
0 43
13.8%
3 36
11.5%
8 19
 
6.1%
1 13
 
4.2%
2 12
 
3.8%
5 11
 
3.5%
7 6
 
1.9%

기관주소
Text

Distinct23
Distinct (%)88.5%
Missing0
Missing (%)0.0%
Memory size340.0 B
2023-12-13T03:24:29.694701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length23.692308
Min length21

Characters and Unicode

Total characters616
Distinct characters58
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)76.9%

Sample

1st row 전라북도 임실군 삼계면 충효로 1623-4
2nd row 전라북도 임실군 관촌면 공덕1길 39
3rd row 전라북도 임실군 신평면 석등슬치로 360-9
4th row 전라북도 임실군 삼계면 후천1길 19
5th row 전라북도 임실군 오수면 오수4길 36-5
ValueCountFrequency (%)
전라북도 26
19.5%
임실군 26
19.5%
오수면 6
 
4.5%
신평면 5
 
3.8%
석등슬치로 5
 
3.8%
임실읍 4
 
3.0%
관촌면 4
 
3.0%
삼일로 3
 
2.3%
삼계면 2
 
1.5%
충효로 2
 
1.5%
Other values (43) 50
37.6%
2023-12-13T03:24:29.983815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
159
25.8%
임 30
 
4.9%
실 30
 
4.9%
라 26
 
4.2%
북 26
 
4.2%
도 26
 
4.2%
군 26
 
4.2%
전 26
 
4.2%
면 21
 
3.4%
1 21
 
3.4%
Other values (48) 225
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
57.0%
Space Separator 159
25.8%
Decimal Number 92
 
14.9%
Dash Punctuation 12
 
1.9%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
임 30
 
8.5%
실 30
 
8.5%
라 26
 
7.4%
북 26
 
7.4%
도 26
 
7.4%
군 26
 
7.4%
전 26
 
7.4%
면 21
 
6.0%
로 19
 
5.4%
수 11
 
3.1%
Other values (35) 110
31.3%
Decimal Number
ValueCountFrequency (%)
1 21
22.8%
2 15
16.3%
3 13
14.1%
4 10
10.9%
9 8
 
8.7%
5 8
 
8.7%
0 7
 
7.6%
6 6
 
6.5%
7 3
 
3.3%
8 1
 
1.1%
Space Separator
ValueCountFrequency (%)
159
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
57.0%
Common 265
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
임 30
 
8.5%
실 30
 
8.5%
라 26
 
7.4%
북 26
 
7.4%
도 26
 
7.4%
군 26
 
7.4%
전 26
 
7.4%
면 21
 
6.0%
로 19
 
5.4%
수 11
 
3.1%
Other values (35) 110
31.3%
Common
ValueCountFrequency (%)
159
60.0%
1 21
 
7.9%
2 15
 
5.7%
3 13
 
4.9%
- 12
 
4.5%
4 10
 
3.8%
9 8
 
3.0%
5 8
 
3.0%
0 7
 
2.6%
6 6
 
2.3%
Other values (3) 6
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
57.0%
ASCII 265
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
159
60.0%
1 21
 
7.9%
2 15
 
5.7%
3 13
 
4.9%
- 12
 
4.5%
4 10
 
3.8%
9 8
 
3.0%
5 8
 
3.0%
0 7
 
2.6%
6 6
 
2.3%
Other values (3) 6
 
2.3%
Hangul
ValueCountFrequency (%)
임 30
 
8.5%
실 30
 
8.5%
라 26
 
7.4%
북 26
 
7.4%
도 26
 
7.4%
군 26
 
7.4%
전 26
 
7.4%
면 21
 
6.0%
로 19
 
5.4%
수 11
 
3.1%
Other values (35) 110
31.3%

Interactions

2023-12-13T03:24:27.946571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:24:30.063541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번기관명종류전화번호기관주소
연번1.0001.0000.8520.8520.852
기관명1.0001.0001.0001.0001.000
종류0.8521.0001.0000.8310.831
전화번호0.8521.0000.8311.0001.000
기관주소0.8521.0000.8311.0001.000
2023-12-13T03:24:30.150403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번종류
연번1.0000.590
종류0.5901.000

Missing values

2023-12-13T03:24:28.053797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:24:28.150707image/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

연번기관명종류전화번호기관주소
01사랑요양원노인의료복지시설063-642-9191전라북도 임실군 삼계면 충효로 1623-4
12관촌원광수양원노인의료복지시설063-643-6688전라북도 임실군 관촌면 공덕1길 39
23정드림노인요양원노인의료복지시설063-644-0188전라북도 임실군 신평면 석등슬치로 360-9
34안나사랑원노인의료복지시설063-642-5877전라북도 임실군 삼계면 후천1길 19
45굿모닝사랑원노인의료복지시설063-642-4466전라북도 임실군 오수면 오수4길 36-5
56에덴요양원노인의료복지시설063-642-3799전라북도 임실군 신평면 석등슬치로 402-1
67한마음요양원노인의료복지시설063-644-0010전라북도 임실군 신평면 석등슬치로 402
78늘사랑요양원노인의료복지시설063-642-0575전라북도 임실군 강진면 강운로 157-1
89임실노인복지센터재가노인복지시설063-643-0263전라북도 임실군 관촌면 사선3길 34
910섬김노인복지센터재가노인복지시설063-642-1835전라북도 임실군 오수면 삼일로 22-12
연번기관명종류전화번호기관주소
1617참행복복지용구재가노인복지시설063-644-6611전라북도 임실군 오수면 오수로 134-1
1718백세노인복지센터재가노인복지시설063-644-1003전라북도 임실군 관촌면 사선로 56
1819해피노인복지센터재가노인복지시설063-644-4460전라북도 임실군 오수로 금암2길 5, 2동 203호
1920복된노인복지센터재가노인복지시설063-644-7890전라북도 임실군 오수면 충효로 2039
2021참조은노인복지센터재가노인복지시설063-643-1126전라북도 임실군 임실읍 봉황로 195
2122미소노인복지센터재가노인복지시설063-644-5684전라북도 임실군 오수면 삼일로 22-5
2223늘사랑주간보호센터재가노인복지시설063-642-0575전라북도 임실군 강진면 강운로 157-1
2324임실군노인종합복지관노인여가복지시설063-644-4438전라북도 임실군 임실읍 운수로 33-46
2425임실군북부권노인복지관노인여가복지시설063-642-3844전라북도 임실군 관촌면 사선1길 24
2526임실시니어클럽노인일자리지원기관063-644-9661전라북도 임실군 임실읍 호국로 1721