Overview

Dataset statistics

Number of variables5
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory46.4 B

Variable types

Numeric2
Text3

Dataset

Description전라북도 군산시 소재한 노인요양시설현황으로 노인요양원 시설명, 노인요양원 주소, 노인요양원 전화번호, 노인요양원 정원 임.
Author전북특별자치도 군산시
URLhttps://www.data.go.kr/data/15060793/fileData.do

Alerts

번호 has unique valuesUnique
요양원명 has unique valuesUnique
요양원주소(도로명) has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-04-29 22:36:40.765060
Analysis finished2024-04-29 22:36:43.265631
Duration2.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-30T07:36:43.325662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2024-04-30T07:36:43.446288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

요양원명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-30T07:36:43.642082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8.5
Mean length6.0666667
Min length4

Characters and Unicode

Total characters182
Distinct characters73
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

Unique30 ?
Unique (%)100.0%

Sample

1st row시온의집
2nd row보은의집
3rd row성모전문요양원
4th row사랑마을요양원
5th row지극히작은자의집
ValueCountFrequency (%)
시온의집 1
 
3.3%
보은의집 1
 
3.3%
에덴의집 1
 
3.3%
은혜요양원 1
 
3.3%
우리요양원 1
 
3.3%
늘사랑실버홈 1
 
3.3%
살고싶은집삼마요양원 1
 
3.3%
데레사의집 1
 
3.3%
나눔노인요양원 1
 
3.3%
정성요양원 1
 
3.3%
Other values (20) 20
66.7%
2024-04-30T07:36:43.974753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
요 19
 
10.4%
양 19
 
10.4%
원 19
 
10.4%
집 9
 
4.9%
의 7
 
3.8%
사 5
 
2.7%
은 4
 
2.2%
산 4
 
2.2%
군 4
 
2.2%
정 4
 
2.2%
Other values (63) 88
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
요 19
 
10.4%
양 19
 
10.4%
원 19
 
10.4%
집 9
 
4.9%
의 7
 
3.8%
사 5
 
2.7%
은 4
 
2.2%
산 4
 
2.2%
군 4
 
2.2%
정 4
 
2.2%
Other values (63) 88
48.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
요 19
 
10.4%
양 19
 
10.4%
원 19
 
10.4%
집 9
 
4.9%
의 7
 
3.8%
사 5
 
2.7%
은 4
 
2.2%
산 4
 
2.2%
군 4
 
2.2%
정 4
 
2.2%
Other values (63) 88
48.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
요 19
 
10.4%
양 19
 
10.4%
원 19
 
10.4%
집 9
 
4.9%
의 7
 
3.8%
사 5
 
2.7%
은 4
 
2.2%
산 4
 
2.2%
군 4
 
2.2%
정 4
 
2.2%
Other values (63) 88
48.4%

요양원주소(도로명)
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-30T07:36:44.206062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length25.6
Min length23

Characters and Unicode

Total characters768
Distinct characters99
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 군산시 임피면 남상1길 33
2nd row전북특별자치도 군산시 서수면 동군산로 1088-8
3rd row전북특별자치도 군산시 서수면 외무장길 87-8
4th row전북특별자치도 군산시 나포면 서왕길 84-9
5th row전북특별자치도 군산시 대야면 보덕안정길 41
ValueCountFrequency (%)
전북특별자치도 30
19.9%
군산시 30
19.9%
조촌동 5
 
3.3%
나포면 3
 
2.0%
소룡동 3
 
2.0%
서수면 3
 
2.0%
나운동 2
 
1.3%
옥산면 2
 
1.3%
개정동 2
 
1.3%
16 2
 
1.3%
Other values (65) 69
45.7%
2024-04-30T07:36:44.585947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
15.8%
산 36
 
4.7%
군 31
 
4.0%
전 30
 
3.9%
특 30
 
3.9%
별 30
 
3.9%
자 30
 
3.9%
치 30
 
3.9%
도 30
 
3.9%
시 30
 
3.9%
Other values (89) 370
48.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 502
65.4%
Space Separator 121
 
15.8%
Decimal Number 100
 
13.0%
Close Punctuation 16
 
2.1%
Open Punctuation 16
 
2.1%
Dash Punctuation 11
 
1.4%
Other Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 36
 
7.2%
군 31
 
6.2%
전 30
 
6.0%
특 30
 
6.0%
별 30
 
6.0%
자 30
 
6.0%
치 30
 
6.0%
도 30
 
6.0%
시 30
 
6.0%
북 30
 
6.0%
Other values (74) 195
38.8%
Decimal Number
ValueCountFrequency (%)
1 26
26.0%
2 20
20.0%
3 14
14.0%
8 8
 
8.0%
7 8
 
8.0%
4 8
 
8.0%
0 6
 
6.0%
9 4
 
4.0%
5 3
 
3.0%
6 3
 
3.0%
Space Separator
ValueCountFrequency (%)
121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 16
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 502
65.4%
Common 266
34.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 36
 
7.2%
군 31
 
6.2%
전 30
 
6.0%
특 30
 
6.0%
별 30
 
6.0%
자 30
 
6.0%
치 30
 
6.0%
도 30
 
6.0%
시 30
 
6.0%
북 30
 
6.0%
Other values (74) 195
38.8%
Common
ValueCountFrequency (%)
121
45.5%
1 26
 
9.8%
2 20
 
7.5%
) 16
 
6.0%
( 16
 
6.0%
3 14
 
5.3%
- 11
 
4.1%
8 8
 
3.0%
7 8
 
3.0%
4 8
 
3.0%
Other values (5) 18
 
6.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 502
65.4%
ASCII 266
34.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
121
45.5%
1 26
 
9.8%
2 20
 
7.5%
) 16
 
6.0%
( 16
 
6.0%
3 14
 
5.3%
- 11
 
4.1%
8 8
 
3.0%
7 8
 
3.0%
4 8
 
3.0%
Other values (5) 18
 
6.8%
Hangul
ValueCountFrequency (%)
산 36
 
7.2%
군 31
 
6.2%
전 30
 
6.0%
특 30
 
6.0%
별 30
 
6.0%
자 30
 
6.0%
치 30
 
6.0%
도 30
 
6.0%
시 30
 
6.0%
북 30
 
6.0%
Other values (74) 195
38.8%

전화번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-30T07:36:44.781971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters360
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

Unique30 ?
Unique (%)100.0%

Sample

1st row063-453-2044
2nd row063-451-8778
3rd row063-453-7501
4th row063-453-9902
5th row063-451-1346
ValueCountFrequency (%)
063-453-2044 1
 
3.3%
063-451-8778 1
 
3.3%
063-451-2323 1
 
3.3%
063-732-0700 1
 
3.3%
063-452-6400 1
 
3.3%
063-468-0027 1
 
3.3%
063-451-8899 1
 
3.3%
063-468-1271 1
 
3.3%
063-464-7715 1
 
3.3%
063-442-7135 1
 
3.3%
Other values (20) 20
66.7%
2024-04-30T07:36:45.115928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 60
16.7%
0 53
14.7%
6 52
14.4%
3 45
12.5%
4 41
11.4%
5 25
6.9%
1 22
 
6.1%
2 19
 
5.3%
7 18
 
5.0%
9 13
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 300
83.3%
Dash Punctuation 60
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 53
17.7%
6 52
17.3%
3 45
15.0%
4 41
13.7%
5 25
8.3%
1 22
7.3%
2 19
 
6.3%
7 18
 
6.0%
9 13
 
4.3%
8 12
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 60
16.7%
0 53
14.7%
6 52
14.4%
3 45
12.5%
4 41
11.4%
5 25
6.9%
1 22
 
6.1%
2 19
 
5.3%
7 18
 
5.0%
9 13
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 60
16.7%
0 53
14.7%
6 52
14.4%
3 45
12.5%
4 41
11.4%
5 25
6.9%
1 22
 
6.1%
2 19
 
5.3%
7 18
 
5.0%
9 13
 
3.6%

정원
Real number (ℝ)

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.066667
Minimum6
Maximum130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-30T07:36:45.230490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile16.9
Q129
median38.5
Q370.75
95-th percentile99.55
Maximum130
Range124
Interquartile range (IQR)41.75

Descriptive statistics

Standard deviation30.82647
Coefficient of variation (CV)0.61570846
Kurtosis-0.036136856
Mean50.066667
Median Absolute Deviation (MAD)16
Skewness0.83930279
Sum1502
Variance950.27126
MonotonicityNot monotonic
2024-04-30T07:36:45.348411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
29 9
30.0%
49 2
 
6.7%
70 1
 
3.3%
100 1
 
3.3%
83 1
 
3.3%
54 1
 
3.3%
99 1
 
3.3%
6 1
 
3.3%
48 1
 
3.3%
71 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
6 1
 
3.3%
16 1
 
3.3%
18 1
 
3.3%
21 1
 
3.3%
23 1
 
3.3%
28 1
 
3.3%
29 9
30.0%
48 1
 
3.3%
49 2
 
6.7%
54 1
 
3.3%
ValueCountFrequency (%)
130 1
3.3%
100 1
3.3%
99 1
3.3%
98 1
3.3%
83 1
3.3%
80 1
3.3%
74 1
3.3%
71 1
3.3%
70 1
3.3%
69 1
3.3%

Interactions

2024-04-30T07:36:42.952044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:36:42.694895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:36:43.038210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-30T07:36:42.862602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-30T07:36:45.431524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호요양원명요양원주소(도로명)전화번호정원
번호1.0001.0001.0001.0000.457
요양원명1.0001.0001.0001.0001.000
요양원주소(도로명)1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
정원0.4571.0001.0001.0001.000
2024-04-30T07:36:45.536183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호정원
번호1.000-0.128
정원-0.1281.000

Missing values

2024-04-30T07:36:43.139134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-30T07:36:43.224277image/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

번호요양원명요양원주소(도로명)전화번호정원
01시온의집전북특별자치도 군산시 임피면 남상1길 33063-453-204470
12보은의집전북특별자치도 군산시 서수면 동군산로 1088-8063-451-8778130
23성모전문요양원전북특별자치도 군산시 서수면 외무장길 87-8063-453-750169
34사랑마을요양원전북특별자치도 군산시 나포면 서왕길 84-9063-453-990229
45지극히작은자의집전북특별자치도 군산시 대야면 보덕안정길 41063-451-134629
56군산소망요양원전북특별자치도 군산시 나포면 미루매길 127063-451-995023
67보현노인전문요양원전북특별자치도 군산시 설림길 30 (소룡동)063-463-360080
78군산행복한집전북특별자치도 군산시 설림2길 34-10 (소룡동)063-462-721498
89정다운요양원전북특별자치도 군산시 쌍천로 37 (개정동)063-451-975055
910봉정요양원전북특별자치도 군산시 쌍천로 82-3 (개정동)063-450-390174
번호요양원명요양원주소(도로명)전화번호정원
2021행복한요양원전북특별자치도 군산시 옥구읍 수산길 71-21063-464-776349
2122정성요양원전북특별자치도 군산시 검다메안길 22 (조촌동)063-442-713529
2223나눔노인요양원전북특별자치도 군산시 옥산면 대위로 117-22063-464-771529
2324데레사의집전북특별자치도 군산시 신설로 57, 101호 (나운동, 청남하이츠빌리지)063-468-12716
2425살고싶은집삼마요양원전북특별자치도 군산시 나포면 철새로 342063-451-889999
2526늘사랑실버홈전북특별자치도 군산시 나운우회로 131-1 (나운동)063-468-002754
2627우리요양원전북특별자치도 군산시 조촌2길 62 (조촌동)063-452-640049
2728은혜요양원전북특별자치도 군산시 조촌2길 14 (조촌동)063-732-070083
2829에덴의집전북특별자치도 군산시 개정면 원아산2길 79063-451-232329
2930정드림요양원전북특별자치도 군산시 축동3길 23(수송동)063-462-889929