Overview

Dataset statistics

Number of variables6
Number of observations688
Missing cells5
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.4 KiB
Average record size in memory48.2 B

Variable types

Categorical2
Text4

Dataset

Description충청북도 노인복지시설 현황으로 구분, 시군, 시설명, 대표자, 소재지도로명주소, 전화번호 등 데이터를 제공합니다
URLhttps://www.data.go.kr/data/15051593/fileData.do

Reproduction

Analysis started2023-12-12 08:11:09.241041
Analysis finished2023-12-12 08:11:10.130468
Duration0.89 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct8
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
재가노인복지시설
296 
노인요양시설
229 
노인요양공동생활가정
91 
노인복지관
 
21
재가노인지원서비스
 
17
Other values (3)
34 

Length

Max length10
Median length9
Mean length7.502907
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
재가노인복지시설 296
43.0%
노인요양시설 229
33.3%
노인요양공동생활가정 91
 
13.2%
노인복지관 21
 
3.1%
재가노인지원서비스 17
 
2.5%
노인공동생활가정 14
 
2.0%
노인일자리지원기관 12
 
1.7%
양로시설 8
 
1.2%

Length

2023-12-12T17:11:10.234427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:11:10.394701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
재가노인복지시설 296
43.0%
노인요양시설 229
33.3%
노인요양공동생활가정 91
 
13.2%
노인복지관 21
 
3.1%
재가노인지원서비스 17
 
2.5%
노인공동생활가정 14
 
2.0%
노인일자리지원기관 12
 
1.7%
양로시설 8
 
1.2%

시군
Categorical

Distinct11
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
청주시
277 
충주시
86 
제천시
82 
음성군
47 
영동군
42 
Other values (6)
154 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row괴산군
2nd row단양군
3rd row보은군
4th row보은군
5th row보은군

Common Values

ValueCountFrequency (%)
청주시 277
40.3%
충주시 86
 
12.5%
제천시 82
 
11.9%
음성군 47
 
6.8%
영동군 42
 
6.1%
진천군 37
 
5.4%
옥천군 33
 
4.8%
괴산군 27
 
3.9%
보은군 21
 
3.1%
증평군 20
 
2.9%

Length

2023-12-12T17:11:10.571986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청주시 277
40.3%
충주시 86
 
12.5%
제천시 82
 
11.9%
음성군 47
 
6.8%
영동군 42
 
6.1%
진천군 37
 
5.4%
옥천군 33
 
4.8%
괴산군 27
 
3.9%
보은군 21
 
3.1%
증평군 20
 
2.9%

시설명
Text

Distinct662
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2023-12-12T17:11:10.847186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length8.627907
Min length2

Characters and Unicode

Total characters5936
Distinct characters341
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique639 ?
Unique (%)92.9%

Sample

1st row괴산군노인복지관
2nd row단양노인복지관
3rd row보은군실버복지관
4th row보은군노인장애인복지관
5th row대청댐효나눔노인복지관
ValueCountFrequency (%)
집 8
 
1.1%
요양원 7
 
0.9%
노인요양원 4
 
0.5%
재가복지센터 4
 
0.5%
노인복지센터 4
 
0.5%
단양노인보금자리 3
 
0.4%
소망요양원 3
 
0.4%
주간보호센터 3
 
0.4%
방문요양센터 3
 
0.4%
기쁨요양원 3
 
0.4%
Other values (684) 719
94.5%
2023-12-12T17:11:11.290709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
양 311
 
5.2%
요 294
 
5.0%
센 289
 
4.9%
터 287
 
4.8%
원 281
 
4.7%
인 266
 
4.5%
노 256
 
4.3%
지 214
 
3.6%
복 202
 
3.4%
가 166
 
2.8%
Other values (331) 3370
56.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5770
97.2%
Space Separator 73
 
1.2%
Decimal Number 26
 
0.4%
Uppercase Letter 20
 
0.3%
Close Punctuation 19
 
0.3%
Open Punctuation 19
 
0.3%
Other Punctuation 3
 
0.1%
Letter Number 3
 
0.1%
Math Symbol 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
양 311
 
5.4%
요 294
 
5.1%
센 289
 
5.0%
터 287
 
5.0%
원 281
 
4.9%
인 266
 
4.6%
노 256
 
4.4%
지 214
 
3.7%
복 202
 
3.5%
가 166
 
2.9%
Other values (306) 3204
55.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
15.0%
T 2
10.0%
H 2
10.0%
E 2
10.0%
P 2
10.0%
I 2
10.0%
V 2
10.0%
N 1
 
5.0%
S 1
 
5.0%
C 1
 
5.0%
Other values (2) 2
10.0%
Decimal Number
ValueCountFrequency (%)
8 8
30.8%
9 8
30.8%
2 6
23.1%
1 2
 
7.7%
0 2
 
7.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Space Separator
ValueCountFrequency (%)
73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5771
97.2%
Common 142
 
2.4%
Latin 23
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
양 311
 
5.4%
요 294
 
5.1%
센 289
 
5.0%
터 287
 
5.0%
원 281
 
4.9%
인 266
 
4.6%
노 256
 
4.4%
지 214
 
3.7%
복 202
 
3.5%
가 166
 
2.9%
Other values (307) 3205
55.5%
Latin
ValueCountFrequency (%)
A 3
13.0%
Ⅱ 2
8.7%
T 2
8.7%
H 2
8.7%
E 2
8.7%
P 2
8.7%
I 2
8.7%
V 2
8.7%
N 1
 
4.3%
S 1
 
4.3%
Other values (4) 4
17.4%
Common
ValueCountFrequency (%)
73
51.4%
) 19
 
13.4%
( 19
 
13.4%
8 8
 
5.6%
9 8
 
5.6%
2 6
 
4.2%
. 3
 
2.1%
+ 2
 
1.4%
1 2
 
1.4%
0 2
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5770
97.2%
ASCII 162
 
2.7%
Number Forms 3
 
0.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
양 311
 
5.4%
요 294
 
5.1%
센 289
 
5.0%
터 287
 
5.0%
원 281
 
4.9%
인 266
 
4.6%
노 256
 
4.4%
지 214
 
3.7%
복 202
 
3.5%
가 166
 
2.9%
Other values (306) 3204
55.5%
ASCII
ValueCountFrequency (%)
73
45.1%
) 19
 
11.7%
( 19
 
11.7%
8 8
 
4.9%
9 8
 
4.9%
2 6
 
3.7%
A 3
 
1.9%
. 3
 
1.9%
+ 2
 
1.2%
1 2
 
1.2%
Other values (12) 19
 
11.7%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

대표자
Text

Distinct618
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2023-12-12T17:11:11.691697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.997093
Min length2

Characters and Unicode

Total characters2062
Distinct characters187
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

Unique557 ?
Unique (%)81.0%

Sample

1st row서명선
2nd row최은하
3rd row고은자
4th row박종분
5th row김현조
ValueCountFrequency (%)
김영민 4
 
0.6%
이영희 3
 
0.4%
이영순 3
 
0.4%
손성태 3
 
0.4%
김치선 3
 
0.4%
오재훈 3
 
0.4%
서명선 3
 
0.4%
김영옥 3
 
0.4%
노삼선 2
 
0.3%
이연희 2
 
0.3%
Other values (610) 661
95.8%
2023-12-12T17:11:12.392368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 133
 
6.5%
이 113
 
5.5%
정 78
 
3.8%
영 71
 
3.4%
미 58
 
2.8%
경 56
 
2.7%
희 56
 
2.7%
순 52
 
2.5%
박 49
 
2.4%
선 40
 
1.9%
Other values (177) 1356
65.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2058
99.8%
Space Separator 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 133
 
6.5%
이 113
 
5.5%
정 78
 
3.8%
영 71
 
3.4%
미 58
 
2.8%
경 56
 
2.7%
희 56
 
2.7%
순 52
 
2.5%
박 49
 
2.4%
선 40
 
1.9%
Other values (176) 1352
65.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2058
99.8%
Common 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 133
 
6.5%
이 113
 
5.5%
정 78
 
3.8%
영 71
 
3.4%
미 58
 
2.8%
경 56
 
2.7%
희 56
 
2.7%
순 52
 
2.5%
박 49
 
2.4%
선 40
 
1.9%
Other values (176) 1352
65.7%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2058
99.8%
ASCII 4
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 133
 
6.5%
이 113
 
5.5%
정 78
 
3.8%
영 71
 
3.4%
미 58
 
2.8%
경 56
 
2.7%
희 56
 
2.7%
순 52
 
2.5%
박 49
 
2.4%
선 40
 
1.9%
Other values (176) 1352
65.7%
ASCII
ValueCountFrequency (%)
4
100.0%

소재지도로명주소
Text

Distinct664
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size5.5 KiB
2023-12-12T17:11:12.868031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length27.863372
Min length16

Characters and Unicode

Total characters19170
Distinct characters293
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

Unique641 ?
Unique (%)93.2%

Sample

1st row충청북도 괴산군 괴산읍 동진천길 51
2nd row충청북도 단양군 단양읍 별곡 1로 17
3rd row충청북도 보은군 보은읍 군청길 110-17
4th row충청북도 보은군 보은읍 뱃들4길 11-10
5th row충청북도 보은군 회인면 회인로 78
ValueCountFrequency (%)
충청북도 687
 
16.8%
청주시 277
 
6.8%
충주시 86
 
2.1%
제천시 82
 
2.0%
서원구 76
 
1.9%
상당구 73
 
1.8%
청원구 70
 
1.7%
흥덕구 58
 
1.4%
음성군 47
 
1.1%
영동군 42
 
1.0%
Other values (1164) 2594
63.4%
2023-12-12T17:11:13.554767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3724
 
19.4%
청 1091
 
5.7%
충 792
 
4.1%
북 723
 
3.8%
도 705
 
3.7%
1 671
 
3.5%
로 513
 
2.7%
) 490
 
2.6%
( 490
 
2.6%
동 460
 
2.4%
Other values (283) 9511
49.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11223
58.5%
Space Separator 3724
 
19.4%
Decimal Number 2810
 
14.7%
Close Punctuation 490
 
2.6%
Open Punctuation 490
 
2.6%
Dash Punctuation 240
 
1.3%
Other Punctuation 192
 
1.0%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 1091
 
9.7%
충 792
 
7.1%
북 723
 
6.4%
도 705
 
6.3%
로 513
 
4.6%
동 460
 
4.1%
시 450
 
4.0%
주 381
 
3.4%
길 356
 
3.2%
면 299
 
2.7%
Other values (266) 5453
48.6%
Decimal Number
ValueCountFrequency (%)
1 671
23.9%
2 430
15.3%
3 345
12.3%
4 263
 
9.4%
0 221
 
7.9%
5 200
 
7.1%
6 192
 
6.8%
8 179
 
6.4%
7 155
 
5.5%
9 154
 
5.5%
Other Punctuation
ValueCountFrequency (%)
, 187
97.4%
. 5
 
2.6%
Space Separator
ValueCountFrequency (%)
3724
100.0%
Close Punctuation
ValueCountFrequency (%)
) 490
100.0%
Open Punctuation
ValueCountFrequency (%)
( 490
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 240
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11223
58.5%
Common 7946
41.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 1091
 
9.7%
충 792
 
7.1%
북 723
 
6.4%
도 705
 
6.3%
로 513
 
4.6%
동 460
 
4.1%
시 450
 
4.0%
주 381
 
3.4%
길 356
 
3.2%
면 299
 
2.7%
Other values (266) 5453
48.6%
Common
ValueCountFrequency (%)
3724
46.9%
1 671
 
8.4%
) 490
 
6.2%
( 490
 
6.2%
2 430
 
5.4%
3 345
 
4.3%
4 263
 
3.3%
- 240
 
3.0%
0 221
 
2.8%
5 200
 
2.5%
Other values (6) 872
 
11.0%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11223
58.5%
ASCII 7947
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3724
46.9%
1 671
 
8.4%
) 490
 
6.2%
( 490
 
6.2%
2 430
 
5.4%
3 345
 
4.3%
4 263
 
3.3%
- 240
 
3.0%
0 221
 
2.8%
5 200
 
2.5%
Other values (7) 873
 
11.0%
Hangul
ValueCountFrequency (%)
청 1091
 
9.7%
충 792
 
7.1%
북 723
 
6.4%
도 705
 
6.3%
로 513
 
4.6%
동 460
 
4.1%
시 450
 
4.0%
주 381
 
3.4%
길 356
 
3.2%
면 299
 
2.7%
Other values (266) 5453
48.6%

전화번호
Text

Distinct635
Distinct (%)93.0%
Missing5
Missing (%)0.7%
Memory size5.5 KiB
2023-12-12T17:11:13.821019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.008785
Min length12

Characters and Unicode

Total characters8202
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

Unique591 ?
Unique (%)86.5%

Sample

1st row043-834-3411
2nd row043-421-7100
3rd row043-544-3311
4th row043-544-5446
5th row043-544-6550
ValueCountFrequency (%)
043-653-9927 3
 
0.4%
043-745-0067 3
 
0.4%
043-833-3396 3
 
0.4%
043-421-1331 3
 
0.4%
043-832-9109 2
 
0.3%
043-277-8291 2
 
0.3%
043-838-0191 2
 
0.3%
043-854-4791 2
 
0.3%
043-883-2478 2
 
0.3%
043-843-1116 2
 
0.3%
Other values (625) 659
96.5%
2023-12-12T17:11:14.225172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1366
16.7%
3 1219
14.9%
0 1198
14.6%
4 1089
13.3%
2 665
8.1%
8 580
7.1%
5 488
 
5.9%
1 436
 
5.3%
7 431
 
5.3%
6 391
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6836
83.3%
Dash Punctuation 1366
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1219
17.8%
0 1198
17.5%
4 1089
15.9%
2 665
9.7%
8 580
8.5%
5 488
7.1%
1 436
 
6.4%
7 431
 
6.3%
6 391
 
5.7%
9 339
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 1366
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1366
16.7%
3 1219
14.9%
0 1198
14.6%
4 1089
13.3%
2 665
8.1%
8 580
7.1%
5 488
 
5.9%
1 436
 
5.3%
7 431
 
5.3%
6 391
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1366
16.7%
3 1219
14.9%
0 1198
14.6%
4 1089
13.3%
2 665
8.1%
8 580
7.1%
5 488
 
5.9%
1 436
 
5.3%
7 431
 
5.3%
6 391
 
4.8%

Correlations

2023-12-12T17:11:14.324868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군
구분1.0000.167
시군0.1671.000
2023-12-12T17:11:14.426157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군
구분1.0000.079
시군0.0791.000
2023-12-12T17:11:14.525479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시군
구분1.0000.079
시군0.0791.000

Missing values

2023-12-12T17:11:09.939096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:11:10.066822image/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

구분시군시설명대표자소재지도로명주소전화번호
0노인복지관괴산군괴산군노인복지관서명선충청북도 괴산군 괴산읍 동진천길 51043-834-3411
1노인복지관단양군단양노인복지관최은하충청북도 단양군 단양읍 별곡 1로 17043-421-7100
2노인복지관보은군보은군실버복지관고은자충청북도 보은군 보은읍 군청길 110-17043-544-3311
3노인복지관보은군보은군노인장애인복지관박종분충청북도 보은군 보은읍 뱃들4길 11-10043-544-5446
4노인복지관보은군대청댐효나눔노인복지관김현조충청북도 보은군 회인면 회인로 78043-544-6550
5노인복지관영동군영동군노인복지관박인순충청북도 영동군 영동읍 반곡동길 13043-742-7784
6노인복지관옥천군옥천군노인장애인복지관오재훈충청북도 옥천군 옥천읍 삼양로8길 9043-733-2602
7노인복지관음성군음성군노인복지관임종훈충청북도 음성군 금왕읍 백야로 14043-883-2470
8노인복지관제천시명락노인종합복지관배기환충청북도 제천시 내제로5길 12(명동)043-648-3337
9노인복지관제천시제천시노인종합복지관박재홍충청북도 제천시 의림대로 174043-652-3457
구분시군시설명대표자소재지도로명주소전화번호
678재가노인복지시설음성군밝은언덕재가노인복지센터오동식충청북도 음성군 소이면 소이로61번길 164043-873-0108
679재가노인복지시설음성군금당의료기 오티콘보청기박건우충청북도 음성군 금왕읍 무극로 310043-883-9008
680재가노인복지시설음성군건강의료종합상사곽지희충청북도 음성군 생극면 음성로 1645043-750-8403
681재가노인복지시설음성군금왕의료기김영숙충청북도 음성군 금왕읍 금석로 95043-883-0132
682재가노인복지시설음성군늘봄노인주간보호센터송혜영충청북도 음성군 금왕읍 무극로 250, 2층043-750-7274
683재가노인복지시설음성군솔향기방문요양센터하순금충청북도 음성군 대소면 오태로116번길 7, 4층 가호043-881-0822
684재가노인복지시설단양군단양노인재가복지센터조은아충청북도 단양군 대강면 대강로 71043-932-9899
685재가노인복지시설단양군단양노인보금자리김영민충청북도 단양군 단양읍 상진1길 6-5043-421-1331
686재가노인복지시설단양군한가족재가복지센터이해리충청북도 단양군 영춘면 원장발길 122043-422-7896
687재가노인복지시설단양군아름다운 동행 노인복지센터문희충청북도 단양군 적성면 곧은터길 134-6<NA>