Overview

Dataset statistics

Number of variables6
Number of observations920
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.3 KiB
Average record size in memory48.1 B

Variable types

Categorical2
Text4

Dataset

Description충청북도 내의 어린이집 현황에 대한 데이터로 다음과 같은 항목을 제공합니다. (시군명, 시설명, 시설장명, 주소, 연락처 등)
Author공공데이터포털
URLhttps://www.data.go.kr/data/15090404/fileData.do

Alerts

구분 has constant value ""Constant
연락처 has unique valuesUnique

Reproduction

Analysis started2024-04-17 12:27:51.238445
Analysis finished2024-04-17 12:27:51.753853
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
어린이집
920 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
어린이집 920
100.0%

Length

2024-04-17T21:27:51.813581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T21:27:51.888357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
어린이집 920
100.0%

시군명
Categorical

Distinct11
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
청주시
575 
충주시
100 
음성군
 
55
제천시
 
54
진천군
 
51
Other values (6)
85 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청주시 575
62.5%
충주시 100
 
10.9%
음성군 55
 
6.0%
제천시 54
 
5.9%
진천군 51
 
5.5%
증평군 24
 
2.6%
영동군 16
 
1.7%
옥천군 15
 
1.6%
단양군 12
 
1.3%
괴산군 11
 
1.2%

Length

2024-04-17T21:27:51.956070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
청주시 575
62.5%
충주시 100
 
10.9%
음성군 55
 
6.0%
제천시 54
 
5.9%
진천군 51
 
5.5%
증평군 24
 
2.6%
영동군 16
 
1.7%
옥천군 15
 
1.6%
단양군 12
 
1.3%
괴산군 11
 
1.2%

시설명
Text

Distinct833
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-04-17T21:27:52.132968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length7.523913
Min length5

Characters and Unicode

Total characters6922
Distinct characters416
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique767 ?
Unique (%)83.4%

Sample

1st row영운어린이집
2nd row용암어린이집
3rd row방서어린이집
4th row용정어린이집
5th row금천어린이집
ValueCountFrequency (%)
어린이집 29
 
3.0%
꿈나무어린이집 4
 
0.4%
무지개어린이집 4
 
0.4%
한빛어린이집 4
 
0.4%
우리어린이집 4
 
0.4%
사랑어린이집 4
 
0.4%
동화나라어린이집 4
 
0.4%
라온어린이집 3
 
0.3%
성모어린이집 3
 
0.3%
푸른어린이집 3
 
0.3%
Other values (832) 900
93.6%
2024-04-17T21:27:52.439876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 1035
 
15.0%
린 935
 
13.5%
어 923
 
13.3%
집 920
 
13.3%
아 117
 
1.7%
리 68
 
1.0%
사 63
 
0.9%
랑 53
 
0.8%
나 52
 
0.8%
지 51
 
0.7%
Other values (406) 2705
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6823
98.6%
Space Separator 42
 
0.6%
Uppercase Letter 29
 
0.4%
Decimal Number 21
 
0.3%
Lowercase Letter 4
 
0.1%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1035
 
15.2%
린 935
 
13.7%
어 923
 
13.5%
집 920
 
13.5%
아 117
 
1.7%
리 68
 
1.0%
사 63
 
0.9%
랑 53
 
0.8%
나 52
 
0.8%
지 51
 
0.7%
Other values (376) 2606
38.2%
Uppercase Letter
ValueCountFrequency (%)
S 4
13.8%
L 3
10.3%
Y 3
10.3%
B 3
10.3%
D 2
 
6.9%
A 2
 
6.9%
C 2
 
6.9%
O 1
 
3.4%
M 1
 
3.4%
H 1
 
3.4%
Other values (7) 7
24.1%
Decimal Number
ValueCountFrequency (%)
2 6
28.6%
3 4
19.0%
1 3
14.3%
5 3
14.3%
6 2
 
9.5%
8 1
 
4.8%
7 1
 
4.8%
4 1
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
i 3
75.0%
s 1
 
25.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Other Punctuation
ValueCountFrequency (%)
& 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6823
98.6%
Common 66
 
1.0%
Latin 33
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1035
 
15.2%
린 935
 
13.7%
어 923
 
13.5%
집 920
 
13.5%
아 117
 
1.7%
리 68
 
1.0%
사 63
 
0.9%
랑 53
 
0.8%
나 52
 
0.8%
지 51
 
0.7%
Other values (376) 2606
38.2%
Latin
ValueCountFrequency (%)
S 4
12.1%
i 3
 
9.1%
L 3
 
9.1%
Y 3
 
9.1%
B 3
 
9.1%
D 2
 
6.1%
A 2
 
6.1%
C 2
 
6.1%
O 1
 
3.0%
M 1
 
3.0%
Other values (9) 9
27.3%
Common
ValueCountFrequency (%)
42
63.6%
2 6
 
9.1%
3 4
 
6.1%
1 3
 
4.5%
5 3
 
4.5%
6 2
 
3.0%
& 2
 
3.0%
- 1
 
1.5%
8 1
 
1.5%
7 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6823
98.6%
ASCII 99
 
1.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 1035
 
15.2%
린 935
 
13.7%
어 923
 
13.5%
집 920
 
13.5%
아 117
 
1.7%
리 68
 
1.0%
사 63
 
0.9%
랑 53
 
0.8%
나 52
 
0.8%
지 51
 
0.7%
Other values (376) 2606
38.2%
ASCII
ValueCountFrequency (%)
42
42.4%
2 6
 
6.1%
3 4
 
4.0%
S 4
 
4.0%
i 3
 
3.0%
L 3
 
3.0%
Y 3
 
3.0%
B 3
 
3.0%
1 3
 
3.0%
5 3
 
3.0%
Other values (20) 25
25.3%

시설장명
Text

Distinct855
Distinct (%)92.9%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-04-17T21:27:52.707881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.9945652
Min length2

Characters and Unicode

Total characters2755
Distinct characters168
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

Unique799 ?
Unique (%)86.8%

Sample

1st row김경자
2nd row박성심
3rd row남명희
4th row채동헌
5th row권혁란
ValueCountFrequency (%)
박은경 3
 
0.3%
김은영 3
 
0.3%
김현주 3
 
0.3%
이선희 3
 
0.3%
김혜영 3
 
0.3%
이현주 3
 
0.3%
이정민 3
 
0.3%
이현숙 3
 
0.3%
김영희 3
 
0.3%
박수진 2
 
0.2%
Other values (845) 891
96.8%
2024-04-17T21:27:53.083829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 201
 
7.3%
정 146
 
5.3%
이 138
 
5.0%
미 135
 
4.9%
영 118
 
4.3%
희 109
 
4.0%
숙 108
 
3.9%
경 96
 
3.5%
박 82
 
3.0%
선 79
 
2.9%
Other values (158) 1543
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2755
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 201
 
7.3%
정 146
 
5.3%
이 138
 
5.0%
미 135
 
4.9%
영 118
 
4.3%
희 109
 
4.0%
숙 108
 
3.9%
경 96
 
3.5%
박 82
 
3.0%
선 79
 
2.9%
Other values (158) 1543
56.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2755
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 201
 
7.3%
정 146
 
5.3%
이 138
 
5.0%
미 135
 
4.9%
영 118
 
4.3%
희 109
 
4.0%
숙 108
 
3.9%
경 96
 
3.5%
박 82
 
3.0%
선 79
 
2.9%
Other values (158) 1543
56.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2755
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 201
 
7.3%
정 146
 
5.3%
이 138
 
5.0%
미 135
 
4.9%
영 118
 
4.3%
희 109
 
4.0%
숙 108
 
3.9%
경 96
 
3.5%
박 82
 
3.0%
선 79
 
2.9%
Other values (158) 1543
56.0%

주소
Text

Distinct765
Distinct (%)83.2%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-04-17T21:27:53.342225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length21.363043
Min length14

Characters and Unicode

Total characters19654
Distinct characters245
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

Unique679 ?
Unique (%)73.8%

Sample

1st row충청북도 청주시 상당구 수영로156번길 22
2nd row충청북도 청주시 상당구 원봉로 50
3rd row충청북도 청주시 상당구 단재로317번길 33-11
4th row충청북도 청주시 상당구 1순환로1514번길 17
5th row충청북도 청주시 상당구 쇠내로73번길 6
ValueCountFrequency (%)
충청북도 920
20.1%
청주시 575
 
12.5%
흥덕구 184
 
4.0%
청원구 153
 
3.3%
서원구 120
 
2.6%
상당구 118
 
2.6%
충주시 100
 
2.2%
오창읍 80
 
1.7%
음성군 55
 
1.2%
제천시 54
 
1.2%
Other values (971) 2223
48.5%
2024-04-17T21:27:53.728084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3670
18.7%
청 1685
 
8.6%
충 1033
 
5.3%
도 930
 
4.7%
북 926
 
4.7%
로 755
 
3.8%
1 744
 
3.8%
시 734
 
3.7%
주 692
 
3.5%
구 587
 
3.0%
Other values (235) 7898
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12730
64.8%
Space Separator 3670
 
18.7%
Decimal Number 3091
 
15.7%
Dash Punctuation 163
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 1685
 
13.2%
충 1033
 
8.1%
도 930
 
7.3%
북 926
 
7.3%
로 755
 
5.9%
시 734
 
5.8%
주 692
 
5.4%
구 587
 
4.6%
길 418
 
3.3%
원 304
 
2.4%
Other values (223) 4666
36.7%
Decimal Number
ValueCountFrequency (%)
1 744
24.1%
2 472
15.3%
3 337
10.9%
4 272
 
8.8%
6 241
 
7.8%
5 239
 
7.7%
7 232
 
7.5%
0 216
 
7.0%
8 184
 
6.0%
9 154
 
5.0%
Space Separator
ValueCountFrequency (%)
3670
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12730
64.8%
Common 6924
35.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 1685
 
13.2%
충 1033
 
8.1%
도 930
 
7.3%
북 926
 
7.3%
로 755
 
5.9%
시 734
 
5.8%
주 692
 
5.4%
구 587
 
4.6%
길 418
 
3.3%
원 304
 
2.4%
Other values (223) 4666
36.7%
Common
ValueCountFrequency (%)
3670
53.0%
1 744
 
10.7%
2 472
 
6.8%
3 337
 
4.9%
4 272
 
3.9%
6 241
 
3.5%
5 239
 
3.5%
7 232
 
3.4%
0 216
 
3.1%
8 184
 
2.7%
Other values (2) 317
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12730
64.8%
ASCII 6924
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3670
53.0%
1 744
 
10.7%
2 472
 
6.8%
3 337
 
4.9%
4 272
 
3.9%
6 241
 
3.5%
5 239
 
3.5%
7 232
 
3.4%
0 216
 
3.1%
8 184
 
2.7%
Other values (2) 317
 
4.6%
Hangul
ValueCountFrequency (%)
청 1685
 
13.2%
충 1033
 
8.1%
도 930
 
7.3%
북 926
 
7.3%
로 755
 
5.9%
시 734
 
5.8%
주 692
 
5.4%
구 587
 
4.6%
길 418
 
3.3%
원 304
 
2.4%
Other values (223) 4666
36.7%

연락처
Text

UNIQUE 

Distinct920
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-04-17T21:27:53.913748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.011957
Min length12

Characters and Unicode

Total characters11051
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

Unique920 ?
Unique (%)100.0%

Sample

1st row043-253-0410
2nd row043-293-9194
3rd row043-298-5800
4th row043-297-1616
5th row043-223-8810
ValueCountFrequency (%)
043-253-0410 1
 
0.1%
043-846-0079 1
 
0.1%
043-849-6382 1
 
0.1%
043-844-5166 1
 
0.1%
043-844-6187 1
 
0.1%
043-856-1777 1
 
0.1%
043-847-7357 1
 
0.1%
043-846-4369 1
 
0.1%
043-851-8177 1
 
0.1%
043-854-3179 1
 
0.1%
Other values (910) 910
98.9%
2024-04-17T21:27:54.187088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1840
16.7%
3 1707
15.4%
0 1563
14.1%
4 1446
13.1%
2 1060
9.6%
8 674
 
6.1%
1 652
 
5.9%
7 627
 
5.7%
5 581
 
5.3%
6 472
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9211
83.3%
Dash Punctuation 1840
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 1707
18.5%
0 1563
17.0%
4 1446
15.7%
2 1060
11.5%
8 674
 
7.3%
1 652
 
7.1%
7 627
 
6.8%
5 581
 
6.3%
6 472
 
5.1%
9 429
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 1840
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11051
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1840
16.7%
3 1707
15.4%
0 1563
14.1%
4 1446
13.1%
2 1060
9.6%
8 674
 
6.1%
1 652
 
5.9%
7 627
 
5.7%
5 581
 
5.3%
6 472
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11051
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1840
16.7%
3 1707
15.4%
0 1563
14.1%
4 1446
13.1%
2 1060
9.6%
8 674
 
6.1%
1 652
 
5.9%
7 627
 
5.7%
5 581
 
5.3%
6 472
 
4.3%

Missing values

2024-04-17T21:27:51.629091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T21:27:51.714413image/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

구분시군명시설명시설장명주소연락처
0어린이집청주시영운어린이집김경자충청북도 청주시 상당구 수영로156번길 22043-253-0410
1어린이집청주시용암어린이집박성심충청북도 청주시 상당구 원봉로 50043-293-9194
2어린이집청주시방서어린이집남명희충청북도 청주시 상당구 단재로317번길 33-11043-298-5800
3어린이집청주시용정어린이집채동헌충청북도 청주시 상당구 1순환로1514번길 17043-297-1616
4어린이집청주시금천어린이집권혁란충청북도 청주시 상당구 쇠내로73번길 6043-223-8810
5어린이집청주시별나무어린이집박진서충청북도 청주시 상당구 수영로118번길 19043-223-7337
6어린이집청주시스타힐스어린이집송옥경충청북도 청주시 상당구 쇠내로 48043-222-2179
7어린이집청주시새샘어린이집윤정경충청북도 청주시 상당구 쇠내로103번길 13070-7728-1260
8어린이집청주시꿈돌이예능어린이집채종화충청북도 청주시 상당구 꽃산동로14번길 29-1043-253-4540
9어린이집청주시뜨란채어린이집최명숙충청북도 청주시 상당구 무심동로 82043-295-8688
구분시군명시설명시설장명주소연락처
910어린이집단양군동화나라 어린이집이정임충청북도 단양군 단양읍 상진14길 12043-423-1004
911어린이집단양군대강어린이집이은미충청북도 단양군 대강면 장림2길 5043-421-1004
912어린이집단양군우리어린이집김나현충청북도 단양군 단양읍 별곡12길 5043-421-3003
913어린이집단양군순복음어린이집박서진충청북도 단양군 단양읍 도전6길 8043-423-2784
914어린이집단양군온세상어린이집주경숙충청북도 단양군 영춘면 온달평강로 68-5043-423-2967
915어린이집단양군혜모어린이집김종학충청북도 단양군 매포읍 평동5길 23-9043-423-0095
916어린이집단양군단양어린이집김선녀충청북도 단양군 단양읍 상진7길 8043-422-3354
917어린이집단양군꿈나무어린이집안신임충청북도 단양군 매포읍 평동38길 8-6043-422-3007
918어린이집단양군단양새싹어린이집홍인숙충청북도 단양군 단양읍 삼봉로 340043-422-2323
919어린이집단양군매포교회어린이집최원선충청북도 단양군 매포읍 평동3길 12043-422-4073