Overview

Dataset statistics

Number of variables13
Number of observations297
Missing cells565
Missing cells (%)14.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory30.6 KiB
Average record size in memory105.4 B

Variable types

Categorical8
Boolean2
Text2
Numeric1

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,설립유형,가입 보험명,대상여부,가입여부,업체명1,업체명2,업체명3,공시차수,주소
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20868/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
교육지원청명 has constant value ""Constant
주소 is highly overall correlated with 공시차수 and 3 other fieldsHigh correlation
대상여부 is highly overall correlated with 가입여부High correlation
가입여부 is highly overall correlated with 대상여부 and 1 other fieldsHigh correlation
설립유형 is highly overall correlated with 유치원코드 and 2 other fieldsHigh correlation
유치원명 is highly overall correlated with 공시차수 and 3 other fieldsHigh correlation
업체명1 is highly overall correlated with 가입여부High correlation
유치원코드 is highly overall correlated with 공시차수 and 3 other fieldsHigh correlation
공시차수 is highly overall correlated with 유치원코드 and 2 other fieldsHigh correlation
업체명2 has 272 (91.6%) missing valuesMissing
업체명3 has 293 (98.7%) missing valuesMissing

Reproduction

Analysis started2024-03-13 08:30:17.291027
Analysis finished2024-03-13 08:30:18.443050
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
서울특별시교육청
297 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시교육청 297
100.0%

Length

2024-03-13T17:30:18.511724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:30:18.598389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 297
100.0%

교육지원청명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
강서양천교육지원청
297 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
강서양천교육지원청 297
100.0%

Length

2024-03-13T17:30:18.682622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:30:18.764092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강서양천교육지원청 297
100.0%

유치원코드
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
9c26aa7f-0f07-4613-9136-4984c723803f
 
9
1ecec08c-f649-b044-e053-0a32095ab044
 
9
1ecec08c-fe4b-b044-e053-0a32095ab044
 
8
1fc6dd86-cccf-d1d2-e053-0a32095ad1d2
 
7
1ecec08c-f449-b044-e053-0a32095ab044
 
6
Other values (43)
258 

Length

Max length36
Median length36
Mean length36
Min length36

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1dfcc6e7-c6ff-4843-b970-cfba072320b4
2nd row1dfcc6e7-c6ff-4843-b970-cfba072320b4
3rd row1dfcc6e7-c6ff-4843-b970-cfba072320b4
4th row1dfcc6e7-c6ff-4843-b970-cfba072320b4
5th row1dfcc6e7-c6ff-4843-b970-cfba072320b4

Common Values

ValueCountFrequency (%)
9c26aa7f-0f07-4613-9136-4984c723803f 9
 
3.0%
1ecec08c-f649-b044-e053-0a32095ab044 9
 
3.0%
1ecec08c-fe4b-b044-e053-0a32095ab044 8
 
2.7%
1fc6dd86-cccf-d1d2-e053-0a32095ad1d2 7
 
2.4%
1ecec08c-f449-b044-e053-0a32095ab044 6
 
2.0%
1ecec08c-fead-b044-e053-0a32095ab044 6
 
2.0%
1ecec08c-ed80-b044-e053-0a32095ab044 6
 
2.0%
1ecec08c-ed81-b044-e053-0a32095ab044 6
 
2.0%
1ecec08c-eec5-b044-e053-0a32095ab044 6
 
2.0%
1ecec08c-ef9b-b044-e053-0a32095ab044 6
 
2.0%
Other values (38) 228
76.8%

Length

2024-03-13T17:30:18.846275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
9c26aa7f-0f07-4613-9136-4984c723803f 9
 
3.0%
1ecec08c-f649-b044-e053-0a32095ab044 9
 
3.0%
1ecec08c-fe4b-b044-e053-0a32095ab044 8
 
2.7%
1fc6dd86-cccf-d1d2-e053-0a32095ad1d2 7
 
2.4%
1ecec08d-0599-b044-e053-0a32095ab044 6
 
2.0%
a59a057e-4f5c-411a-bb2a-60068691c766 6
 
2.0%
1dfcc6e7-c6ff-4843-b970-cfba072320b4 6
 
2.0%
1ecec08d-08bb-b044-e053-0a32095ab044 6
 
2.0%
1ecec08d-0121-b044-e053-0a32095ab044 6
 
2.0%
1ecec08d-018d-b044-e053-0a32095ab044 6
 
2.0%
Other values (38) 228
76.8%

유치원명
Categorical

HIGH CORRELATION 

Distinct48
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
꿈꾸는유치원
 
9
서울신원초등학교병설유치원
 
9
아란유치원
 
8
목동유치원
 
7
동연유치원
 
6
Other values (43)
258 

Length

Max length13
Median length5
Mean length7.3333333
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
꿈꾸는유치원 9
 
3.0%
서울신원초등학교병설유치원 9
 
3.0%
아란유치원 8
 
2.7%
목동유치원 7
 
2.4%
동연유치원 6
 
2.0%
서울양화초등학교병설유치원 6
 
2.0%
샘터유치원 6
 
2.0%
서울경인유치원 6
 
2.0%
솔샘유치원 6
 
2.0%
서울월촌초등학교병설유치원 6
 
2.0%
Other values (38) 228
76.8%

Length

2024-03-13T17:30:18.957304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
꿈꾸는유치원 9
 
3.0%
서울신원초등학교병설유치원 9
 
3.0%
아란유치원 8
 
2.7%
목동유치원 7
 
2.4%
서울장수초등학교병설유치원 6
 
2.0%
세신유치원 6
 
2.0%
서울강월초등학교병설유치원 6
 
2.0%
한서유치원 6
 
2.0%
어린이의정원유치원 6
 
2.0%
광영유치원 6
 
2.0%
Other values (38) 228
76.8%

설립유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
사립(사인)
180 
공립(병설)
75 
사립(법인)
30 
공립(단설)
 
12

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row공립(병설)
2nd row공립(병설)
3rd row공립(병설)
4th row공립(병설)
5th row공립(병설)

Common Values

ValueCountFrequency (%)
사립(사인) 180
60.6%
공립(병설) 75
25.3%
사립(법인) 30
 
10.1%
공립(단설) 12
 
4.0%

Length

2024-03-13T17:30:19.085104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:30:19.174407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 180
60.6%
공립(병설 75
25.3%
사립(법인 30
 
10.1%
공립(단설 12
 
4.0%

가입 보험명
Categorical

Distinct14
Distinct (%)4.7%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
화재보험
48 
가스배상책임보험
48 
놀이시설 안전보험
48 
영유아생명신체피해(상해보험)
48 
통학버스 종합보험
48 
Other values (9)
57 

Length

Max length15
Median length12
Mean length8.9461279
Min length3

Unique

Unique7 ?
Unique (%)2.4%

Sample

1st row화재보험
2nd row가스배상책임보험
3rd row놀이시설 안전보험
4th row영유아생명신체피해(상해보험)
5th row통학버스 종합보험

Common Values

ValueCountFrequency (%)
화재보험 48
16.2%
가스배상책임보험 48
16.2%
놀이시설 안전보험 48
16.2%
영유아생명신체피해(상해보험) 48
16.2%
통학버스 종합보험 48
16.2%
통학버스 책임보험 48
16.2%
통학버스종합보험 2
 
0.7%
기타1 1
 
0.3%
기타2 1
 
0.3%
기타3 1
 
0.3%
Other values (4) 4
 
1.3%

Length

2024-03-13T17:30:19.284278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
통학버스 96
21.8%
화재보험 48
10.9%
가스배상책임보험 48
10.9%
놀이시설 48
10.9%
안전보험 48
10.9%
영유아생명신체피해(상해보험 48
10.9%
종합보험 48
10.9%
책임보험 48
10.9%
통학버스종합보험 2
 
0.5%
승강기사고배상책임보험 2
 
0.5%
Other values (5) 5
 
1.1%

대상여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size429.0 B
True
251 
False
46 
ValueCountFrequency (%)
True 251
84.5%
False 46
 
15.5%
2024-03-13T17:30:19.370059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

가입여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size429.0 B
True
252 
False
45 
ValueCountFrequency (%)
True 252
84.8%
False 45
 
15.2%
2024-03-13T17:30:19.436600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

업체명1
Categorical

HIGH CORRELATION 

Distinct50
Distinct (%)16.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
학교안전공제회
55 
<NA>
45 
한국교육시설안전원
38 
삼성화재
30 
현대해상
21 
Other values (45)
108 

Length

Max length19
Median length15
Mean length6.7777778
Min length4

Unique

Unique20 ?
Unique (%)6.7%

Sample

1st row한국교육시설안전원
2nd row삼성화재
3rd row학교배상책임공제
4th row학교안전공제회
5th row<NA>

Common Values

ValueCountFrequency (%)
학교안전공제회 55
18.5%
<NA> 45
15.2%
한국교육시설안전원 38
12.8%
삼성화재 30
10.1%
현대해상 21
 
7.1%
DB손해보험 14
 
4.7%
현대해상화재보험 13
 
4.4%
전국전세버스운송사업조합 7
 
2.4%
KB손해보험 6
 
2.0%
삼성화재해상보험 5
 
1.7%
Other values (40) 63
21.2%

Length

2024-03-13T17:30:19.552051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
학교안전공제회 55
18.4%
na 45
15.1%
한국교육시설안전원 38
12.7%
삼성화재 30
10.0%
현대해상 21
 
7.0%
db손해보험 16
 
5.4%
현대해상화재보험 13
 
4.3%
kb손해보험 8
 
2.7%
전국전세버스운송사업조합 7
 
2.3%
삼성화재해상보험 5
 
1.7%
Other values (40) 61
20.4%

업체명2
Text

MISSING 

Distinct13
Distinct (%)52.0%
Missing272
Missing (%)91.6%
Memory size2.4 KiB
2024-03-13T17:30:19.727319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length7.56
Min length4

Characters and Unicode

Total characters189
Distinct characters56
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)20.0%

Sample

1st rowKB손해보험
2nd rowKB손해보험
3rd row삼성화재
4th rowKB손해보험
5th rowKB손해보험
ValueCountFrequency (%)
kb손해보험 5
20.0%
삼성화재 3
12.0%
명품비지니스종합보험 3
12.0%
학교안전공제회 3
12.0%
삼성화재해상보험 2
 
8.0%
업무용애니카 2
 
8.0%
db손해보험 2
 
8.0%
동부화재해상보험 2
 
8.0%
axa다이렉트 1
 
4.0%
서울특별시학교안전공제회 1
 
4.0%
2024-03-13T17:30:20.027916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 14
 
7.4%
험 14
 
7.4%
해 11
 
5.8%
재 7
 
3.7%
화 7
 
3.7%
손 7
 
3.7%
B 6
 
3.2%
전 6
 
3.2%
합 6
 
3.2%
회 5
 
2.6%
Other values (46) 106
56.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
89.9%
Uppercase Letter 15
 
7.9%
Control 2
 
1.1%
Lowercase Letter 2
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 14
 
8.2%
험 14
 
8.2%
해 11
 
6.5%
재 7
 
4.1%
화 7
 
4.1%
손 7
 
4.1%
전 6
 
3.5%
합 6
 
3.5%
회 5
 
2.9%
제 5
 
2.9%
Other values (38) 88
51.8%
Uppercase Letter
ValueCountFrequency (%)
B 6
40.0%
K 4
26.7%
A 2
 
13.3%
D 2
 
13.3%
X 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
k 1
50.0%
b 1
50.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
89.9%
Latin 17
 
9.0%
Common 2
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 14
 
8.2%
험 14
 
8.2%
해 11
 
6.5%
재 7
 
4.1%
화 7
 
4.1%
손 7
 
4.1%
전 6
 
3.5%
합 6
 
3.5%
회 5
 
2.9%
제 5
 
2.9%
Other values (38) 88
51.8%
Latin
ValueCountFrequency (%)
B 6
35.3%
K 4
23.5%
A 2
 
11.8%
D 2
 
11.8%
k 1
 
5.9%
b 1
 
5.9%
X 1
 
5.9%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 170
89.9%
ASCII 19
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 14
 
8.2%
험 14
 
8.2%
해 11
 
6.5%
재 7
 
4.1%
화 7
 
4.1%
손 7
 
4.1%
전 6
 
3.5%
합 6
 
3.5%
회 5
 
2.9%
제 5
 
2.9%
Other values (38) 88
51.8%
ASCII
ValueCountFrequency (%)
B 6
31.6%
K 4
21.1%
A 2
 
10.5%
2
 
10.5%
D 2
 
10.5%
k 1
 
5.3%
b 1
 
5.3%
X 1
 
5.3%

업체명3
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing293
Missing (%)98.7%
Memory size2.4 KiB
2024-03-13T17:30:20.167019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length6.5
Min length6

Characters and Unicode

Total characters26
Distinct characters11
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

Unique0 ?
Unique (%)0.0%

Sample

1st row조합원공제보험
2nd row조합원공제보험
3rd rowKB손해보험
4th rowKB손해보험
ValueCountFrequency (%)
조합원공제보험 2
50.0%
kb손해보험 2
50.0%
2024-03-13T17:30:20.427322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 4
15.4%
험 4
15.4%
조 2
7.7%
합 2
7.7%
원 2
7.7%
공 2
7.7%
제 2
7.7%
K 2
7.7%
B 2
7.7%
손 2
7.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
84.6%
Uppercase Letter 4
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 4
18.2%
험 4
18.2%
조 2
9.1%
합 2
9.1%
원 2
9.1%
공 2
9.1%
제 2
9.1%
손 2
9.1%
해 2
9.1%
Uppercase Letter
ValueCountFrequency (%)
K 2
50.0%
B 2
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
84.6%
Latin 4
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 4
18.2%
험 4
18.2%
조 2
9.1%
합 2
9.1%
원 2
9.1%
공 2
9.1%
제 2
9.1%
손 2
9.1%
해 2
9.1%
Latin
ValueCountFrequency (%)
K 2
50.0%
B 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
84.6%
ASCII 4
 
15.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 4
18.2%
험 4
18.2%
조 2
9.1%
합 2
9.1%
원 2
9.1%
공 2
9.1%
제 2
9.1%
손 2
9.1%
해 2
9.1%
ASCII
ValueCountFrequency (%)
K 2
50.0%
B 2
50.0%

공시차수
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)3.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20223.303
Minimum20182
Maximum20232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.7 KiB
2024-03-13T17:30:20.521273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20182
5-th percentile20182
Q120232
median20232
Q320232
95-th percentile20232
Maximum20232
Range50
Interquartile range (IQR)0

Descriptive statistics

Standard deviation17.207863
Coefficient of variation (CV)0.00085089283
Kurtosis0.82518928
Mean20223.303
Median Absolute Deviation (MAD)0
Skewness-1.6161951
Sum6006321
Variance296.11057
MonotonicityNot monotonic
2024-03-13T17:30:20.611094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
20232 229
77.1%
20182 24
 
8.1%
20192 18
 
6.1%
20191 7
 
2.4%
20222 7
 
2.4%
20202 6
 
2.0%
20201 3
 
1.0%
20211 1
 
0.3%
20231 1
 
0.3%
20221 1
 
0.3%
ValueCountFrequency (%)
20182 24
 
8.1%
20191 7
 
2.4%
20192 18
 
6.1%
20201 3
 
1.0%
20202 6
 
2.0%
20211 1
 
0.3%
20221 1
 
0.3%
20222 7
 
2.4%
20231 1
 
0.3%
20232 229
77.1%
ValueCountFrequency (%)
20232 229
77.1%
20231 1
 
0.3%
20222 7
 
2.4%
20221 1
 
0.3%
20211 1
 
0.3%
20202 6
 
2.0%
20201 3
 
1.0%
20192 18
 
6.1%
20191 7
 
2.4%
20182 24
 
8.1%

주소
Categorical

HIGH CORRELATION 

Distinct47
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
서울특별시 양천구 신정로7길 81-4
 
12
서울특별시 양천구 남부순환로58길 32
 
9
서울특별시 양천구 오목로4길 8
 
9
서울특별시 양천구 목동서로 100
 
8
서울특별시 양천구 오목로42길 13
 
7
Other values (42)
252 

Length

Max length24
Median length21
Mean length19.03367
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row서울특별시 양천구 신월로 97
2nd row서울특별시 양천구 신월로 97
3rd row서울특별시 양천구 신월로 97
4th row서울특별시 양천구 신월로 97
5th row서울특별시 양천구 신월로 97

Common Values

ValueCountFrequency (%)
서울특별시 양천구 신정로7길 81-4 12
 
4.0%
서울특별시 양천구 남부순환로58길 32 9
 
3.0%
서울특별시 양천구 오목로4길 8 9
 
3.0%
서울특별시 양천구 목동서로 100 8
 
2.7%
서울특별시 양천구 오목로42길 13 7
 
2.4%
서울특별시 양천구 목동동로 50 6
 
2.0%
서울특별시 양천구 신월로 99 6
 
2.0%
서울특별시 양천구 안양천로 1009 6
 
2.0%
서울특별시 양천구 목동서로 130 6
 
2.0%
서울특별시 양천구 목동중앙로 132 6
 
2.0%
Other values (37) 222
74.7%

Length

2024-03-13T17:30:20.745614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 297
25.0%
양천구 297
25.0%
목동서로 32
 
2.7%
목동동로 24
 
2.0%
30 18
 
1.5%
22 18
 
1.5%
13 13
 
1.1%
신월로 12
 
1.0%
38 12
 
1.0%
신정로 12
 
1.0%
Other values (67) 453
38.1%

Interactions

2024-03-13T17:30:18.019380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T17:30:20.844797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원코드유치원명설립유형가입 보험명대상여부가입여부업체명1업체명2업체명3공시차수주소
유치원코드1.0001.0001.0000.0000.4190.4550.8930.9310.0000.9441.000
유치원명1.0001.0001.0000.0000.4190.4550.8930.9310.0000.9441.000
설립유형1.0001.0001.0000.0000.6240.6360.5461.0000.0000.1490.991
가입 보험명0.0000.0000.0001.0000.5040.5180.8820.0000.0000.7140.000
대상여부0.4190.4190.6240.5041.0000.9970.0000.000NaN0.0670.389
가입여부0.4550.4550.6360.5180.9971.000NaNNaNNaN0.0610.424
업체명10.8930.8930.5460.8820.000NaN1.0000.9120.0000.4640.892
업체명20.9310.9311.0000.0000.000NaN0.9121.0000.0001.0000.931
업체명30.0000.0000.0000.000NaNNaN0.0000.0001.000NaN0.000
공시차수0.9440.9440.1490.7140.0670.0610.4641.000NaN1.0000.932
주소1.0001.0000.9910.0000.3890.4240.8920.9310.0000.9321.000
2024-03-13T17:30:20.972290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주소대상여부가입여부설립유형가입 보험명유치원명업체명1유치원코드
주소1.0000.2980.3250.8740.0000.9980.3260.998
대상여부0.2981.0000.9480.4320.3870.3070.0000.307
가입여부0.3250.9481.0000.4420.3990.3331.0000.333
설립유형0.8740.4320.4421.0000.0000.9220.2750.922
가입 보험명0.0000.3870.3990.0001.0000.0000.4860.000
유치원명0.9980.3070.3330.9220.0001.0000.3261.000
업체명10.3260.0001.0000.2750.4860.3261.0000.326
유치원코드0.9980.3070.3330.9220.0001.0000.3261.000
2024-03-13T17:30:21.096189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공시차수유치원코드유치원명설립유형가입 보험명대상여부가입여부업체명1주소
공시차수1.0000.7610.7610.1760.4100.1110.1370.2880.746
유치원코드0.7611.0001.0000.9220.0000.3070.3330.3260.998
유치원명0.7611.0001.0000.9220.0000.3070.3330.3260.998
설립유형0.1760.9220.9221.0000.0000.4320.4420.2750.874
가입 보험명0.4100.0000.0000.0001.0000.3870.3990.4860.000
대상여부0.1110.3070.3070.4320.3871.0000.9480.0000.298
가입여부0.1370.3330.3330.4420.3990.9481.0001.0000.325
업체명10.2880.3260.3260.2750.4860.0001.0001.0000.326
주소0.7460.9980.9980.8740.0000.2980.3250.3261.000

Missing values

2024-03-13T17:30:18.114563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T17:30:18.270620image/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.
2024-03-13T17:30:18.388797image/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

교육청명교육지원청명유치원코드유치원명설립유형가입 보험명대상여부가입여부업체명1업체명2업체명3공시차수주소
0서울특별시교육청강서양천교육지원청1dfcc6e7-c6ff-4843-b970-cfba072320b4서울강월초등학교병설유치원공립(병설)화재보험YY한국교육시설안전원<NA><NA>20232서울특별시 양천구 신월로 97
1서울특별시교육청강서양천교육지원청1dfcc6e7-c6ff-4843-b970-cfba072320b4서울강월초등학교병설유치원공립(병설)가스배상책임보험YY삼성화재<NA><NA>20232서울특별시 양천구 신월로 97
2서울특별시교육청강서양천교육지원청1dfcc6e7-c6ff-4843-b970-cfba072320b4서울강월초등학교병설유치원공립(병설)놀이시설 안전보험YY학교배상책임공제<NA><NA>20232서울특별시 양천구 신월로 97
3서울특별시교육청강서양천교육지원청1dfcc6e7-c6ff-4843-b970-cfba072320b4서울강월초등학교병설유치원공립(병설)영유아생명신체피해(상해보험)YY학교안전공제회<NA><NA>20232서울특별시 양천구 신월로 97
4서울특별시교육청강서양천교육지원청1dfcc6e7-c6ff-4843-b970-cfba072320b4서울강월초등학교병설유치원공립(병설)통학버스 종합보험NN<NA><NA><NA>20232서울특별시 양천구 신월로 97
5서울특별시교육청강서양천교육지원청1dfcc6e7-c6ff-4843-b970-cfba072320b4서울강월초등학교병설유치원공립(병설)통학버스 책임보험NN<NA><NA><NA>20232서울특별시 양천구 신월로 97
6서울특별시교육청강서양천교육지원청1ecec08c-ed7f-b044-e053-0a32095ab044새서울유치원사립(사인)통학버스 책임보험YY버스공제조합<NA><NA>20232서울특별시 양천구 목동서로 340
7서울특별시교육청강서양천교육지원청1ecec08c-ed7f-b044-e053-0a32095ab044새서울유치원사립(사인)가스배상책임보험YY한국교육시설안전원<NA><NA>20232서울특별시 양천구 목동서로 340
8서울특별시교육청강서양천교육지원청1ecec08c-ed7f-b044-e053-0a32095ab044새서울유치원사립(사인)놀이시설 안전보험NN<NA><NA><NA>20232서울특별시 양천구 목동서로 340
9서울특별시교육청강서양천교육지원청1ecec08c-ed7f-b044-e053-0a32095ab044새서울유치원사립(사인)영유아생명신체피해(상해보험)YY학교안전공제회<NA><NA>20232서울특별시 양천구 목동서로 340
교육청명교육지원청명유치원코드유치원명설립유형가입 보험명대상여부가입여부업체명1업체명2업체명3공시차수주소
287서울특별시교육청강서양천교육지원청a59a057e-4f5c-411a-bb2a-60068691c766세신유치원사립(법인)가스배상책임보험YY삼성화재<NA><NA>20232서울특별시 양천구 목동동로1길 38
288서울특별시교육청강서양천교육지원청a59a057e-4f5c-411a-bb2a-60068691c766세신유치원사립(법인)통학버스 책임보험YY삼성화재<NA><NA>20232서울특별시 양천구 목동동로1길 38
289서울특별시교육청강서양천교육지원청a59a057e-4f5c-411a-bb2a-60068691c766세신유치원사립(법인)화재보험YY삼성화재<NA><NA>20232서울특별시 양천구 목동동로1길 38
290서울특별시교육청강서양천교육지원청a59a057e-4f5c-411a-bb2a-60068691c766세신유치원사립(법인)통학버스 종합보험YY삼성화재<NA><NA>20232서울특별시 양천구 목동동로1길 38
291서울특별시교육청강서양천교육지원청d72d2e90-cf0d-4a9b-8697-a47e692aa3ea서울신정유치원공립(단설)가스배상책임보험YY하나손해보험<NA><NA>20232서울특별시 양천구 신정로7길 81-4
292서울특별시교육청강서양천교육지원청d72d2e90-cf0d-4a9b-8697-a47e692aa3ea서울신정유치원공립(단설)영유아생명신체피해(상해보험)YY학교안전공제회<NA><NA>20232서울특별시 양천구 신정로7길 81-4
293서울특별시교육청강서양천교육지원청d72d2e90-cf0d-4a9b-8697-a47e692aa3ea서울신정유치원공립(단설)통학버스 종합보험NN<NA><NA><NA>20232서울특별시 양천구 신정로7길 81-4
294서울특별시교육청강서양천교육지원청d72d2e90-cf0d-4a9b-8697-a47e692aa3ea서울신정유치원공립(단설)통학버스 책임보험NN<NA><NA><NA>20232서울특별시 양천구 신정로7길 81-4
295서울특별시교육청강서양천교육지원청d72d2e90-cf0d-4a9b-8697-a47e692aa3ea서울신정유치원공립(단설)화재보험YY한국교육시설안전원<NA><NA>20232서울특별시 양천구 신정로7길 81-4
296서울특별시교육청강서양천교육지원청d72d2e90-cf0d-4a9b-8697-a47e692aa3ea서울신정유치원공립(단설)놀이시설 안전보험YY한국교육시설안전원<NA><NA>20232서울특별시 양천구 신정로7길 81-4