Overview

Dataset statistics

Number of variables11
Number of observations31
Missing cells14
Missing cells (%)4.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory96.3 B

Variable types

Numeric4
Categorical2
Text4
DateTime1

Dataset

Description보령시에 있는 노인복지시설(요양시설, 노인요양공동생활가정, 재가노인복지시설 등)의 시설명, 소재지 도로명 주소, 지번 주소, 위도, 경도, 정원, 전화번호 데이터를 제공합니다.
URLhttps://www.data.go.kr/data/15004673/fileData.do

Alerts

데이터기준일 has constant value ""Constant
시설유형 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
시설종류 is highly overall correlated with 연번 and 2 other fieldsHigh correlation
연번 is highly overall correlated with 시설유형 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 시설유형 and 1 other fieldsHigh correlation
정원 has 14 (45.2%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:36:44.745415
Analysis finished2023-12-12 06:36:47.289893
Duration2.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T15:36:47.375624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.5
Q18.5
median16
Q323.5
95-th percentile29.5
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0921211
Coefficient of variation (CV)0.56825757
Kurtosis-1.2
Mean16
Median Absolute Deviation (MAD)8
Skewness0
Sum496
Variance82.666667
MonotonicityStrictly increasing
2023-12-12T15:36:47.513870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 1
 
3.2%
2 1
 
3.2%
31 1
 
3.2%
30 1
 
3.2%
29 1
 
3.2%
28 1
 
3.2%
27 1
 
3.2%
26 1
 
3.2%
25 1
 
3.2%
24 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
1 1
3.2%
2 1
3.2%
3 1
3.2%
4 1
3.2%
5 1
3.2%
6 1
3.2%
7 1
3.2%
8 1
3.2%
9 1
3.2%
10 1
3.2%
ValueCountFrequency (%)
31 1
3.2%
30 1
3.2%
29 1
3.2%
28 1
3.2%
27 1
3.2%
26 1
3.2%
25 1
3.2%
24 1
3.2%
23 1
3.2%
22 1
3.2%

시설유형
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
재가노인복지시설
19 
노인의료복지시설
12 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 19
61.3%
노인의료복지시설 12
38.7%

Length

2023-12-12T15:36:47.676758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:36:47.801699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인복지시설 19
61.3%
노인의료복지시설 12
38.7%

시설종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
재가노인복지시설
19 
노인요양시설
노인요양공동생활가정

Length

Max length10
Median length8
Mean length7.7419355
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 19
61.3%
노인요양시설 8
25.8%
노인요양공동생활가정 4
 
12.9%

Length

2023-12-12T15:36:47.931682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:36:48.074052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인복지시설 19
61.3%
노인요양시설 8
25.8%
노인요양공동생활가정 4
 
12.9%

시설명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T15:36:48.298159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length9.2580645
Min length4

Characters and Unicode

Total characters287
Distinct characters89
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

Unique31 ?
Unique (%)100.0%

Sample

1st row보령요양원
2nd row충청남도 도립요양원
3rd row보령실버홈
4th row소화데레사의집
5th row대천요양원
ValueCountFrequency (%)
노인요양공동생활가정 2
 
5.1%
보령요양원 1
 
2.6%
가온재가복지센터 1
 
2.6%
실버플러스보령복지센터 1
 
2.6%
행복방문요양센터 1
 
2.6%
동고동락재가복지센터 1
 
2.6%
효행재가복지방문요양센터 1
 
2.6%
대천주야간보호센터 1
 
2.6%
주)나눔복지센터 1
 
2.6%
청소주야간보호센터 1
 
2.6%
Other values (28) 28
71.8%
2023-12-12T15:36:48.751281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
6.6%
19
 
6.6%
14
 
4.9%
14
 
4.9%
12
 
4.2%
11
 
3.8%
11
 
3.8%
10
 
3.5%
8
 
2.8%
8
 
2.8%
Other values (79) 161
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 275
95.8%
Space Separator 8
 
2.8%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
19
 
6.9%
19
 
6.9%
14
 
5.1%
14
 
5.1%
12
 
4.4%
11
 
4.0%
11
 
4.0%
10
 
3.6%
8
 
2.9%
8
 
2.9%
Other values (76) 149
54.2%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 275
95.8%
Common 12
 
4.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
19
 
6.9%
19
 
6.9%
14
 
5.1%
14
 
5.1%
12
 
4.4%
11
 
4.0%
11
 
4.0%
10
 
3.6%
8
 
2.9%
8
 
2.9%
Other values (76) 149
54.2%
Common
ValueCountFrequency (%)
8
66.7%
) 2
 
16.7%
( 2
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 275
95.8%
ASCII 12
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
19
 
6.9%
19
 
6.9%
14
 
5.1%
14
 
5.1%
12
 
4.4%
11
 
4.0%
11
 
4.0%
10
 
3.6%
8
 
2.9%
8
 
2.9%
Other values (76) 149
54.2%
ASCII
ValueCountFrequency (%)
8
66.7%
) 2
 
16.7%
( 2
 
16.7%
Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T15:36:49.038467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length28
Mean length24.064516
Min length20

Characters and Unicode

Total characters746
Distinct characters84
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

Unique29 ?
Unique (%)93.5%

Sample

1st row충청남도 보령시 남포면 보령남로 207
2nd row충청남도 보령시 주교면 척골길 233
3rd row충청남도 보령시 남포면 보령남로 205
4th row충청남도 보령시 대량비선재길 65-69 (신흑동)
5th row충청남도 보령시 성주면 성주산로 367
ValueCountFrequency (%)
충청남도 31
18.6%
보령시 31
18.6%
동대동 6
 
3.6%
청소면 4
 
2.4%
남포면 4
 
2.4%
웅천읍 3
 
1.8%
대천동 3
 
1.8%
명천동 3
 
1.8%
주교면 3
 
1.8%
주공로 3
 
1.8%
Other values (68) 76
45.5%
2023-12-12T15:36:49.459498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136
18.2%
38
 
5.1%
35
 
4.7%
33
 
4.4%
33
 
4.4%
32
 
4.3%
31
 
4.2%
31
 
4.2%
2 24
 
3.2%
21
 
2.8%
Other values (74) 332
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 450
60.3%
Space Separator 136
 
18.2%
Decimal Number 115
 
15.4%
Open Punctuation 14
 
1.9%
Close Punctuation 14
 
1.9%
Other Punctuation 10
 
1.3%
Dash Punctuation 7
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
38
 
8.4%
35
 
7.8%
33
 
7.3%
33
 
7.3%
32
 
7.1%
31
 
6.9%
31
 
6.9%
21
 
4.7%
19
 
4.2%
14
 
3.1%
Other values (59) 163
36.2%
Decimal Number
ValueCountFrequency (%)
2 24
20.9%
3 20
17.4%
1 13
11.3%
5 13
11.3%
0 12
10.4%
6 10
8.7%
7 10
8.7%
4 6
 
5.2%
9 4
 
3.5%
8 3
 
2.6%
Space Separator
ValueCountFrequency (%)
136
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 450
60.3%
Common 296
39.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
38
 
8.4%
35
 
7.8%
33
 
7.3%
33
 
7.3%
32
 
7.1%
31
 
6.9%
31
 
6.9%
21
 
4.7%
19
 
4.2%
14
 
3.1%
Other values (59) 163
36.2%
Common
ValueCountFrequency (%)
136
45.9%
2 24
 
8.1%
3 20
 
6.8%
( 14
 
4.7%
) 14
 
4.7%
1 13
 
4.4%
5 13
 
4.4%
0 12
 
4.1%
6 10
 
3.4%
, 10
 
3.4%
Other values (5) 30
 
10.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 450
60.3%
ASCII 296
39.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
136
45.9%
2 24
 
8.1%
3 20
 
6.8%
( 14
 
4.7%
) 14
 
4.7%
1 13
 
4.4%
5 13
 
4.4%
0 12
 
4.1%
6 10
 
3.4%
, 10
 
3.4%
Other values (5) 30
 
10.1%
Hangul
ValueCountFrequency (%)
38
 
8.4%
35
 
7.8%
33
 
7.3%
33
 
7.3%
32
 
7.1%
31
 
6.9%
31
 
6.9%
21
 
4.7%
19
 
4.2%
14
 
3.1%
Other values (59) 163
36.2%
Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T15:36:49.661627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length19.774194
Min length16

Characters and Unicode

Total characters613
Distinct characters53
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

Unique29 ?
Unique (%)93.5%

Sample

1st row충청남도 보령시 남포면 창동리 560-1
2nd row충청남도 보령시 주교면 송학리 3-13
3rd row충청남도 보령시 남포면 창동리 560
4th row충청남도 보령시 신흑동 705-7
5th row충청남도 보령시 성주면 성주리 247-14
ValueCountFrequency (%)
충청남도 31
22.0%
보령시 31
22.0%
동대동 6
 
4.3%
남포면 4
 
2.8%
청소면 4
 
2.8%
신송리 3
 
2.1%
주교면 3
 
2.1%
명천동 3
 
2.1%
대천동 3
 
2.1%
웅천읍 3
 
2.1%
Other values (48) 50
35.5%
2023-12-12T15:36:50.023713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/