Overview

Dataset statistics

Number of variables7
Number of observations1406
Missing cells4
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory77.0 KiB
Average record size in memory56.1 B

Variable types

Categorical2
Text3
Unsupported2

Dataset

Description평가인증어린이집현황201507
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202401

Alerts

Unnamed: 6 has unique valuesUnique
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 02:15:22.771373
Analysis finished2024-03-14 02:15:23.532562
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2015. 평가인증 어린이집 현황
Categorical

Distinct17
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size11.1 KiB
전주시 완산구
345 
전주시 덕진구
274 
익산시
240 
군산시
214 
정읍시
72 
Other values (12)
261 

Length

Max length7
Median length3
Mean length4.7617354
Min length3

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row시군구
3rd row전주시 완산구
4th row전주시 완산구
5th row전주시 완산구

Common Values

ValueCountFrequency (%)
전주시 완산구 345
24.5%
전주시 덕진구 274
19.5%
익산시 240
17.1%
군산시 214
15.2%
정읍시 72
 
5.1%
완주군 68
 
4.8%
남원시 57
 
4.1%
김제시 51
 
3.6%
부안군 22
 
1.6%
고창군 22
 
1.6%
Other values (7) 41
 
2.9%

Length

2024-03-14T11:15:23.599632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 619
30.6%
완산구 345
17.0%
덕진구 274
13.5%
익산시 240
 
11.9%
군산시 214
 
10.6%
정읍시 72
 
3.6%
완주군 68
 
3.4%
남원시 57
 
2.8%
김제시 51
 
2.5%
고창군 22
 
1.1%
Other values (8) 63
 
3.1%

Unnamed: 1
Text

Distinct1153
Distinct (%)82.1%
Missing1
Missing (%)0.1%
Memory size11.1 KiB
2024-03-14T11:15:23.765915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length7.4270463
Min length5

Characters and Unicode

Total characters10435
Distinct characters462
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique985 ?
Unique (%)70.1%

Sample

1st row어린이집명
2nd row키즈클럽어린이집
3rd row아이원어린이집
4th row서신피노키오어린이집
5th row조은생각어린이집
ValueCountFrequency (%)
어린이집 57
 
3.9%
해바라기어린이집 7
 
0.5%
솔로몬어린이집 5
 
0.3%
동화나라어린이집 5
 
0.3%
아이사랑어린이집 5
 
0.3%
행복한어린이집 5
 
0.3%
새싹어린이집 5
 
0.3%
참사랑어린이집 4
 
0.3%
꼬마별어린이집 4
 
0.3%
아기별어린이집 4
 
0.3%
Other values (1158) 1376
93.2%
2024-03-14T11:15:24.067116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 1556
 
14.9%
린 1426
 
13.7%
어 1410
 
13.5%
집 1405
 
13.5%
아 173
 
1.7%
나 105
 
1.0%
사 103
 
1.0%
랑 100
 
1.0%
리 99
 
0.9%
마 95
 
0.9%
Other values (452) 3963
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10316
98.9%
Space Separator 72
 
0.7%
Uppercase Letter 26
 
0.2%
Decimal Number 10
 
0.1%
Lowercase Letter 4
 
< 0.1%
Close Punctuation 2
 
< 0.1%
Open Punctuation 2
 
< 0.1%
Other Punctuation 2
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 1556
15.1%
린 1426
 
13.8%
어 1410
 
13.7%
집 1405
 
13.6%
아 173
 
1.7%
나 105
 
1.0%
사 103
 
1.0%
랑 100
 
1.0%
리 99
 
1.0%
마 95
 
0.9%
Other values (429) 3844
37.3%
Uppercase Letter
ValueCountFrequency (%)
C 5
19.2%
A 4
15.4%
E 4
15.4%
Q 3
11.5%
W 2
 
7.7%
Y 2
 
7.7%
B 2
 
7.7%
K 1
 
3.8%
N 1
 
3.8%
O 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
2 3
30.0%
3 2
20.0%
1 2
20.0%
4 2
20.0%
5 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
i 2
50.0%
e 2
50.0%
Space Separator
ValueCountFrequency (%)
72
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10316
98.9%
Common 89
 
0.9%
Latin 30
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 1556
15.1%
린 1426
 
13.8%
어 1410
 
13.7%
집 1405
 
13.6%
아 173
 
1.7%
나 105
 
1.0%
사 103
 
1.0%
랑 100
 
1.0%
리 99
 
1.0%
마 95
 
0.9%
Other values (429) 3844
37.3%
Latin
ValueCountFrequency (%)
C 5
16.7%
A 4
13.3%
E 4
13.3%
Q 3
10.0%
W 2
 
6.7%
Y 2
 
6.7%
i 2
 
6.7%
B 2
 
6.7%
e 2
 
6.7%
K 1
 
3.3%
Other values (3) 3
10.0%
Common
ValueCountFrequency (%)
72
80.9%
2 3
 
3.4%
) 2
 
2.2%
( 2
 
2.2%
3 2
 
2.2%
1 2
 
2.2%
. 2
 
2.2%
4 2
 
2.2%
- 1
 
1.1%
5 1
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10316
98.9%
ASCII 119
 
1.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 1556
15.1%
린 1426
 
13.8%
어 1410
 
13.7%
집 1405
 
13.6%
아 173
 
1.7%
나 105
 
1.0%
사 103
 
1.0%
랑 100
 
1.0%
리 99
 
1.0%
마 95
 
0.9%
Other values (429) 3844
37.3%
ASCII
ValueCountFrequency (%)
72
60.5%
C 5
 
4.2%
A 4
 
3.4%
E 4
 
3.4%
Q 3
 
2.5%
2 3
 
2.5%
W 2
 
1.7%
Y 2
 
1.7%
) 2
 
1.7%
i 2
 
1.7%
Other values (13) 20
 
16.8%

Unnamed: 2
Categorical

Distinct8
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size11.1 KiB
가정
706 
민간
413 
사회복지법인
137 
법인·단체등
90 
국공립
 
50
Other values (3)
 
10

Length

Max length6
Median length2
Mean length2.685633
Min length2

Unique

Unique2 ?
Unique (%)0.1%

Sample

1st row<NA>
2nd row어린이집유형
3rd row가정
4th row가정
5th row가정

Common Values

ValueCountFrequency (%)
가정 706
50.2%
민간 413
29.4%
사회복지법인 137
 
9.7%
법인·단체등 90
 
6.4%
국공립 50
 
3.6%
직장 8
 
0.6%
<NA> 1
 
0.1%
어린이집유형 1
 
0.1%

Length

2024-03-14T11:15:24.190668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:15:24.301296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가정 706
50.2%
민간 413
29.4%
사회복지법인 137
 
9.7%
법인·단체등 90
 
6.4%
국공립 50
 
3.6%
직장 8
 
0.6%
na 1
 
0.1%
어린이집유형 1
 
0.1%

Unnamed: 3
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.1%
Memory size11.1 KiB

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.1%
Memory size11.1 KiB

Unnamed: 5
Text

Distinct1062
Distinct (%)75.6%
Missing1
Missing (%)0.1%
Memory size11.1 KiB
2024-03-14T11:15:24.642930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length38
Mean length19.647687
Min length6

Characters and Unicode

Total characters27605
Distinct characters296
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

Unique873 ?
Unique (%)62.1%

Sample

1st row어린이집주소
2nd row전라북도 전주시 완산구 당산로 43
3rd row전라북도 전주시 완산구 서곡로 8
4th row전라북도 전주시 완산구 새터로 95
5th row전라북도 전주시 완산구 서신로 102
ValueCountFrequency (%)
전라북도 1404
21.4%
전주시 619
 
9.4%
완산구 345
 
5.3%
덕진구 274
 
4.2%
익산시 240
 
3.7%
군산시 214
 
3.3%
정읍시 72
 
1.1%
완주군 68
 
1.0%
남원시 57
 
0.9%
김제시 51
 
0.8%
Other values (1350) 3222
49.1%
2024-03-14T11:15:25.062373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5166
18.7%
전 2043
 
7.4%
도 1427
 
5.2%
북 1424
 
5.2%
라 1405
 
5.1%
시 1263
 
4.6%
1 1083
 
3.9%
산 961
 
3.5%
로 852
 
3.1%
주 711
 
2.6%
Other values (286) 11270
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 17696
64.1%
Space Separator 5166
 
18.7%
Decimal Number 4399
 
15.9%
Dash Punctuation 343
 
1.2%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 2043
 
11.5%
도 1427
 
8.1%
북 1424
 
8.0%
라 1405
 
7.9%
시 1263
 
7.1%
산 961
 
5.4%
로 852
 
4.8%
주 711
 
4.0%
길 689
 
3.9%
구 647
 
3.7%
Other values (273) 6274
35.5%
Decimal Number
ValueCountFrequency (%)
1 1083
24.6%
2 668
15.2%
3 548
12.5%
4 367
 
8.3%
5 350
 
8.0%
0 323
 
7.3%
7 279
 
6.3%
9 274
 
6.2%
6 271
 
6.2%
8 236
 
5.4%
Space Separator
ValueCountFrequency (%)
5166
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 343
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 17696
64.1%
Common 9909
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 2043
 
11.5%
도 1427
 
8.1%
북 1424
 
8.0%
라 1405
 
7.9%
시 1263
 
7.1%
산 961
 
5.4%
로 852
 
4.8%
주 711
 
4.0%
길 689
 
3.9%
구 647
 
3.7%
Other values (273) 6274
35.5%
Common
ValueCountFrequency (%)
5166
52.1%
1 1083
 
10.9%
2 668
 
6.7%
3 548
 
5.5%
4 367
 
3.7%
5 350
 
3.5%
- 343
 
3.5%
0 323
 
3.3%
7 279
 
2.8%
9 274
 
2.8%
Other values (3) 508
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 17696
64.1%
ASCII 9909
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5166
52.1%
1 1083
 
10.9%
2 668
 
6.7%
3 548
 
5.5%
4 367
 
3.7%
5 350
 
3.5%
- 343
 
3.5%
0 323
 
3.3%
7 279
 
2.8%
9 274
 
2.8%
Other values (3) 508
 
5.1%
Hangul
ValueCountFrequency (%)
전 2043
 
11.5%
도 1427
 
8.1%
북 1424
 
8.0%
라 1405
 
7.9%
시 1263
 
7.1%
산 961
 
5.4%
로 852
 
4.8%
주 711
 
4.0%
길 689
 
3.9%
구 647
 
3.7%
Other values (273) 6274
35.5%

Unnamed: 6
Text

UNIQUE 

Distinct1406
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size11.1 KiB
2024-03-14T11:15:25.273823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.01138
Min length8

Characters and Unicode

Total characters16888
Distinct characters23
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

Unique1406 ?
Unique (%)100.0%

Sample

1st row2015.07.31 기준
2nd row어린이집전화번호
3rd row063-255-8380
4th row063-902-6111
5th row063-901-8484
ValueCountFrequency (%)
2015.07.31 1
 
0.1%
063-835-2446 1
 
0.1%
063-856-7944 1
 
0.1%
063-857-0919 1
 
0.1%
063-833-2057 1
 
0.1%
063-836-4616 1
 
0.1%
063-831-7278 1
 
0.1%
063-854-1026 1
 
0.1%
063-834-6905 1
 
0.1%
063-835-9598 1
 
0.1%
Other values (1397) 1397
99.3%
2024-03-14T11:15:25.660094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2808
16.6%
3 2441
14.5%
6 2337
13.8%
0 2217
13.1%
2 1622
9.6%
5 1120
 
6.6%
4 1042
 
6.2%
8 919
 
5.4%
7 870
 
5.2%
1 869
 
5.1%
Other values (13) 643
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14067
83.3%
Dash Punctuation 2808
 
16.6%
Other Letter 10
 
0.1%
Other Punctuation 2
 
< 0.1%
Space Separator 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 2441
17.4%
6 2337
16.6%
0 2217
15.8%
2 1622
11.5%
5 1120
8.0%
4 1042
7.4%
8 919
 
6.5%
7 870
 
6.2%
1 869
 
6.2%
9 630
 
4.5%
Other Letter
ValueCountFrequency (%)
준 1
10.0%
기 1
10.0%
어 1
10.0%
린 1
10.0%
이 1
10.0%
집 1
10.0%
전 1
10.0%
화 1
10.0%
번 1
10.0%
호 1
10.0%
Dash Punctuation
ValueCountFrequency (%)
- 2808
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16878
99.9%
Hangul 10
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 2808
16.6%
3 2441
14.5%
6 2337
13.8%
0 2217
13.1%
2 1622
9.6%
5 1120
 
6.6%
4 1042
 
6.2%
8 919
 
5.4%
7 870
 
5.2%
1 869
 
5.1%
Other values (3) 633
 
3.8%
Hangul
ValueCountFrequency (%)
준 1
10.0%
기 1
10.0%
어 1
10.0%
린 1
10.0%
이 1
10.0%
집 1
10.0%
전 1
10.0%
화 1
10.0%
번 1
10.0%
호 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16878
99.9%
Hangul 10
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 2808
16.6%
3 2441
14.5%
6 2337
13.8%
0 2217
13.1%
2 1622
9.6%
5 1120
 
6.6%
4 1042
 
6.2%
8 919
 
5.4%
7 870
 
5.2%
1 869
 
5.1%
Other values (3) 633
 
3.8%
Hangul
ValueCountFrequency (%)
준 1
10.0%
기 1
10.0%
어 1
10.0%
린 1
10.0%
이 1
10.0%
집 1
10.0%
전 1
10.0%
화 1
10.0%
번 1
10.0%
호 1
10.0%

Correlations

2024-03-14T11:15:26.077062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2015. 평가인증 어린이집 현황Unnamed: 2
2015. 평가인증 어린이집 현황1.0000.734
Unnamed: 20.7341.000
2024-03-14T11:15:26.146917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2015. 평가인증 어린이집 현황Unnamed: 2
2015. 평가인증 어린이집 현황1.0000.448
Unnamed: 20.4481.000
2024-03-14T11:15:26.218703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2015. 평가인증 어린이집 현황Unnamed: 2
2015. 평가인증 어린이집 현황1.0000.448
Unnamed: 20.4481.000

Missing values

2024-03-14T11:15:23.178648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:15:23.305591image/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.
2024-03-14T11:15:23.428041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

2015. 평가인증 어린이집 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0<NA><NA><NA>NaNNaN<NA>2015.07.31 기준
1시군구어린이집명어린이집유형아동정원수아동현원수어린이집주소어린이집전화번호
2전주시 완산구키즈클럽어린이집가정1913전라북도 전주시 완산구 당산로 43063-255-8380
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4전주시 완산구서신피노키오어린이집가정1313전라북도 전주시 완산구 새터로 95063-901-8484
5전주시 완산구조은생각어린이집가정2015전라북도 전주시 완산구 서신로 102063-901-6655
6전주시 완산구아기천사어린이집사회복지법인5959전라북도 전주시 완산구 외칠봉1길 17063-282-5629
7전주시 완산구바울어린이집사회복지법인141140전라북도 전주시 완산구 용머리로 228063-287-1005
8전주시 완산구상원어린이집사회복지법인6665전라북도 전주시 완산구 천잠로 545-7063-253-3138
9전주시 완산구중산어린이집사회복지법인15776전라북도 전주시 완산구 서원로 334063-283-6667
2015. 평가인증 어린이집 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
1396부안군다사랑어린이집민간3622전라북도 부안군 줄포면 교하길 18063-583-1005
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1398부안군큰별 어린이집민간3938전라북도 부안군 계화면 창북3길 11-3063-583-7543
1399부안군엄마사랑어린이집민간4545전라북도 부안군 부안읍 석정로 78063-584-9423
1400부안군줄포어린이집민간2512전라북도 부안군 줄포면 줄포중앙로 56063-582-0708
1401부안군해바라기어린이집민간12462전라북도 부안군 부안읍 부령로 48063-584-8131
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1404부안군자연보물어린이집국공립6762전라북도 부안군 부안읍 봉두길 52063-584-8778
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