Overview

Dataset statistics

Number of variables13
Number of observations48
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.3 KiB
Average record size in memory112.8 B

Variable types

Categorical8
Text3
Boolean1
Numeric1

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,설립유형,차량운영여부,운행차량수,신고차량수,9인승신고차량수,12인승신고차량수,15인승신고차량수,공시차수,주소
Author양천구
URLhttps://data.seoul.go.kr/dataList/OA-20743/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
교육지원청명 has constant value ""Constant
차량운영여부 is highly overall correlated with 설립유형 and 3 other fieldsHigh correlation
신고차량수 is highly overall correlated with 차량운영여부 and 2 other fieldsHigh correlation
설립유형 is highly overall correlated with 차량운영여부 and 2 other fieldsHigh correlation
15인승신고차량수 is highly overall correlated with 차량운영여부 and 2 other fieldsHigh correlation
운행차량수 is highly overall correlated with 설립유형 and 3 other fieldsHigh correlation
9인승신고차량수 is highly overall correlated with 설립유형High correlation
9인승신고차량수 is highly imbalanced (75.0%)Imbalance
12인승신고차량수 is highly imbalanced (60.6%)Imbalance
유치원코드 has unique valuesUnique
유치원명 has unique valuesUnique

Reproduction

Analysis started2024-03-13 08:08:42.466367
Analysis finished2024-03-13 08:08:43.275154
Duration0.81 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
서울특별시교육청
48 

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 48
100.0%

Length

2024-03-13T17:08:43.333706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:43.421296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 48
100.0%

교육지원청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size516.0 B
강서양천교육지원청
48 

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 48
100.0%

Length

2024-03-13T17:08:43.497372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:43.571681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강서양천교육지원청 48
100.0%

유치원코드
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T17:08:43.731036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters1728
Distinct characters17
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique48 ?
Unique (%)100.0%

Sample

1st row1dfcc6e7-c6ff-4843-b970-cfba072320b4
2nd row1ecec08c-ed7f-b044-e053-0a32095ab044
3rd row1ecec08c-ed80-b044-e053-0a32095ab044
4th row1ecec08c-ed81-b044-e053-0a32095ab044
5th row1ecec08c-eec5-b044-e053-0a32095ab044
ValueCountFrequency (%)
1dfcc6e7-c6ff-4843-b970-cfba072320b4 1
 
2.1%
1ecec08c-ed7f-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-08bb-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-0120-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-0121-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-018d-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-02b0-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-04c8-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-054c-b044-e053-0a32095ab044 1
 
2.1%
1ecec08d-054d-b044-e053-0a32095ab044 1
 
2.1%
Other values (38) 38
79.2%
2024-03-13T17:08:44.025856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 294
17.0%
4 192
11.1%
- 192
11.1%
e 149
8.6%
c 132
7.6%
a 109
 
6.3%
5 104
 
6.0%
3 99
 
5.7%
b 99
 
5.7%
8 66
 
3.8%
Other values (7) 292
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 967
56.0%
Lowercase Letter 569
32.9%
Dash Punctuation 192
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 294
30.4%
4 192
19.9%
5 104
 
10.8%
3 99
 
10.2%
8 66
 
6.8%
9 63
 
6.5%
2 58
 
6.0%
1 58
 
6.0%
6 20
 
2.1%
7 13
 
1.3%
Lowercase Letter
ValueCountFrequency (%)
e 149
26.2%
c 132
23.2%
a 109
19.2%
b 99
17.4%
d 45
 
7.9%
f 35
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 192
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1159
67.1%
Latin 569
32.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 294
25.4%
4 192
16.6%
- 192
16.6%
5 104
 
9.0%
3 99
 
8.5%
8 66
 
5.7%
9 63
 
5.4%
2 58
 
5.0%
1 58
 
5.0%
6 20
 
1.7%
Latin
ValueCountFrequency (%)
e 149
26.2%
c 132
23.2%
a 109
19.2%
b 99
17.4%
d 45
 
7.9%
f 35
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1728
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 294
17.0%
4 192
11.1%
- 192
11.1%
e 149
8.6%
c 132
7.6%
a 109
 
6.3%
5 104
 
6.0%
3 99
 
5.7%
b 99
 
5.7%
8 66
 
3.8%
Other values (7) 292
16.9%

유치원명
Text

UNIQUE 

Distinct48
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T17:08:44.229053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length5
Mean length7.3125
Min length5

Characters and Unicode

Total characters351
Distinct characters66
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

Unique48 ?
Unique (%)100.0%

Sample

1st row서울강월초등학교병설유치원
2nd row새서울유치원
3rd row샘터유치원
4th row서울경인유치원
5th row솔샘유치원
ValueCountFrequency (%)
서울강월초등학교병설유치원 1
 
2.1%
새서울유치원 1
 
2.1%
한서유치원 1
 
2.1%
성보유치원 1
 
2.1%
어린이의정원유치원 1
 
2.1%
광영유치원 1
 
2.1%
서울강신초등학교병설유치원 1
 
2.1%
레인보우유치원 1
 
2.1%
세화유치원 1
 
2.1%
양서유치원 1
 
2.1%
Other values (38) 38
79.2%
2024-03-13T17:08:44.543885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 51
14.5%
치 48
13.7%
유 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
학 12
 
3.4%
교 12
 
3.4%
병 12
 
3.4%
Other values (56) 109
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 351
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 51
14.5%
치 48
13.7%
유 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
학 12
 
3.4%
교 12
 
3.4%
병 12
 
3.4%
Other values (56) 109
31.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 51
14.5%
치 48
13.7%
유 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
학 12
 
3.4%
교 12
 
3.4%
병 12
 
3.4%
Other values (56) 109
31.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 51
14.5%
치 48
13.7%
유 48
13.7%
서 18
 
5.1%
울 15
 
4.3%
등 14
 
4.0%
초 12
 
3.4%
학 12
 
3.4%
교 12
 
3.4%
병 12
 
3.4%
Other values (56) 109
31.1%

설립유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size516.0 B
사립(사인)
29 
공립(병설)
12 
사립(법인)
5 
공립(단설)
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립(사인) 29
60.4%
공립(병설) 12
25.0%
사립(법인) 5
 
10.4%
공립(단설) 2
 
4.2%

Length

2024-03-13T17:08:44.656807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:44.746825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 29
60.4%
공립(병설 12
25.0%
사립(법인 5
 
10.4%
공립(단설 2
 
4.2%

차량운영여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size180.0 B
True
33 
False
15 
ValueCountFrequency (%)
True 33
68.8%
False 15
31.2%
2024-03-13T17:08:44.827809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

운행차량수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
0
15 
1
12 
2
11 
3
6 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row3
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 15
31.2%
1 12
25.0%
2 11
22.9%
3 6
 
12.5%
4 4
 
8.3%

Length

2024-03-13T17:08:44.923893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:45.022056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
31.2%
1 12
25.0%
2 11
22.9%
3 6
 
12.5%
4 4
 
8.3%

신고차량수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
0
15 
1
12 
2
10 
3
7 
4
4 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row3
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 15
31.2%
1 12
25.0%
2 10
20.8%
3 7
14.6%
4 4
 
8.3%

Length

2024-03-13T17:08:45.111537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:45.193789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 15
31.2%
1 12
25.0%
2 10
20.8%
3 7
14.6%
4 4
 
8.3%

9인승신고차량수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
0
46 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 46
95.8%
1 2
 
4.2%

Length

2024-03-13T17:08:45.286501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:45.362345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 46
95.8%
1 2
 
4.2%

12인승신고차량수
Categorical

IMBALANCE 

Distinct3
Distinct (%)6.2%
Missing0
Missing (%)0.0%
Memory size516.0 B
0
42 
1
5 
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.1%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 42
87.5%
1 5
 
10.4%
2 1
 
2.1%

Length

2024-03-13T17:08:45.443954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:45.527824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 42
87.5%
1 5
 
10.4%
2 1
 
2.1%

15인승신고차량수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size516.0 B
0
16 
1
16 
2
7 
3
6 
4
3 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row3
4th row0
5th row1

Common Values

ValueCountFrequency (%)
0 16
33.3%
1 16
33.3%
2 7
14.6%
3 6
 
12.5%
4 3
 
6.2%

Length

2024-03-13T17:08:45.613963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T17:08:45.696001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 16
33.3%
1 16
33.3%
2 7
14.6%
3 6
 
12.5%
4 3
 
6.2%

공시차수
Real number (ℝ)

Distinct6
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20223.646
Minimum20182
Maximum20232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size564.0 B
2024-03-13T17:08:45.779227image/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 deviation17.339525
Coefficient of variation (CV)0.00085738869
Kurtosis1.233032
Mean20223.646
Median Absolute Deviation (MAD)0
Skewness-1.7323276
Sum970735
Variance300.65913
MonotonicityNot monotonic
2024-03-13T17:08:45.879843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20232 38
79.2%
20182 4
 
8.3%
20192 3
 
6.2%
20202 1
 
2.1%
20191 1
 
2.1%
20222 1
 
2.1%
ValueCountFrequency (%)
20182 4
 
8.3%
20191 1
 
2.1%
20192 3
 
6.2%
20202 1
 
2.1%
20222 1
 
2.1%
20232 38
79.2%
ValueCountFrequency (%)
20232 38
79.2%
20222 1
 
2.1%
20202 1
 
2.1%
20192 3
 
6.2%
20191 1
 
2.1%
20182 4
 
8.3%

주소
Text

Distinct47
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size516.0 B
2024-03-13T17:08:46.116033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21
Mean length19.041667
Min length16

Characters and Unicode

Total characters914
Distinct characters43
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

Unique46 ?
Unique (%)95.8%

Sample

1st row서울특별시 양천구 신월로 97
2nd row서울특별시 양천구 목동서로 340
3rd row서울특별시 양천구 신월로 99
4th row서울특별시 양천구 안양천로 1009
5th row서울특별시 양천구 목동서로 130
ValueCountFrequency (%)
서울특별시 48
25.0%
양천구 48
25.0%
목동서로 5
 
2.6%
목동동로 4
 
2.1%
22 3
 
1.6%
30 3
 
1.6%
130 2
 
1.0%
280 2
 
1.0%
13 2
 
1.0%
38 2
 
1.0%
Other values (67) 73
38.0%
2024-03-13T17:08:46.441427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
144
15.8%
서 54
 
5.9%
천 49
 
5.4%
양 49
 
5.4%
구 48
 
5.3%
로 48
 
5.3%
시 48
 
5.3%
별 48
 
5.3%
특 48
 
5.3%
울 48
 
5.3%
Other values (33) 330
36.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 603
66.0%
Decimal Number 160
 
17.5%
Space Separator 144
 
15.8%
Dash Punctuation 7
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 54
9.0%
천 49
 
8.1%
양 49
 
8.1%
구 48
 
8.0%
로 48
 
8.0%
시 48
 
8.0%
별 48
 
8.0%
특 48
 
8.0%
울 48
 
8.0%
동 31
 
5.1%
Other values (21) 132
21.9%
Decimal Number
ValueCountFrequency (%)
1 28
17.5%
2 27
16.9%
3 22
13.8%
0 22
13.8%
4 13
8.1%
8 12
7.5%
9 11
 
6.9%
7 10
 
6.2%
6 8
 
5.0%
5 7
 
4.4%
Space Separator
ValueCountFrequency (%)
144
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 603
66.0%
Common 311
34.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 54
9.0%
천 49
 
8.1%
양 49
 
8.1%
구 48
 
8.0%
로 48
 
8.0%
시 48
 
8.0%
별 48
 
8.0%
특 48
 
8.0%
울 48
 
8.0%
동 31
 
5.1%
Other values (21) 132
21.9%
Common
ValueCountFrequency (%)
144
46.3%
1 28
 
9.0%
2 27
 
8.7%
3 22
 
7.1%
0 22
 
7.1%
4 13
 
4.2%
8 12
 
3.9%
9 11
 
3.5%
7 10
 
3.2%
6 8
 
2.6%
Other values (2) 14
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 603
66.0%
ASCII 311
34.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
144
46.3%
1 28
 
9.0%
2 27
 
8.7%
3 22
 
7.1%
0 22
 
7.1%
4 13
 
4.2%
8 12
 
3.9%
9 11
 
3.5%
7 10
 
3.2%
6 8
 
2.6%
Other values (2) 14
 
4.5%
Hangul
ValueCountFrequency (%)
서 54
9.0%
천 49
 
8.1%
양 49
 
8.1%
구 48
 
8.0%
로 48
 
8.0%
시 48
 
8.0%
별 48
 
8.0%
특 48
 
8.0%
울 48
 
8.0%
동 31
 
5.1%
Other values (21) 132
21.9%

Interactions

2024-03-13T17:08:42.970306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T17:08:46.529227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원코드유치원명설립유형차량운영여부운행차량수신고차량수9인승신고차량수12인승신고차량수15인승신고차량수공시차수주소
유치원코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
유치원명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설립유형1.0001.0001.0000.9970.5940.5720.7850.0000.5490.0000.000
차량운영여부1.0001.0000.9971.0001.0001.0000.0000.0940.8240.0000.000
운행차량수1.0001.0000.5941.0001.0001.0000.2140.3190.9840.0000.924
신고차량수1.0001.0000.5721.0001.0001.0000.0000.3120.9780.0000.915
9인승신고차량수1.0001.0000.7850.0000.2140.0001.0000.0000.0000.0001.000
12인승신고차량수1.0001.0000.0000.0940.3190.3120.0001.0000.0000.3301.000
15인승신고차량수1.0001.0000.5490.8240.9840.9780.0000.0001.0000.0000.868
공시차수1.0001.0000.0000.0000.0000.0000.0000.3300.0001.0000.000
주소1.0001.0000.0000.0000.9240.9151.0001.0000.8680.0001.000
2024-03-13T17:08:46.657545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
차량운영여부9인승신고차량수신고차량수설립유형15인승신고차량수운행차량수12인승신고차량수
차량운영여부1.0000.0000.9670.9280.9180.9670.151
9인승신고차량수0.0001.0000.0000.5630.0000.2500.000
신고차량수0.9670.0001.0000.4920.7860.9690.239
설립유형0.9280.5630.4921.0000.4690.5140.000
15인승신고차량수0.9180.0000.7860.4691.0000.8190.000
운행차량수0.9670.2500.9690.5140.8191.0000.245
12인승신고차량수0.1510.0000.2390.0000.0000.2451.000
2024-03-13T17:08:46.752756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공시차수설립유형차량운영여부운행차량수신고차량수9인승신고차량수12인승신고차량수15인승신고차량수
공시차수1.0000.0000.0000.0400.0770.0000.3130.000
설립유형0.0001.0000.9280.5140.4920.5630.0000.469
차량운영여부0.0000.9281.0000.9670.9670.0000.1510.918
운행차량수0.0400.5140.9671.0000.9690.2500.2450.819
신고차량수0.0770.4920.9670.9691.0000.0000.2390.786
9인승신고차량수0.0000.5630.0000.2500.0001.0000.0000.000
12인승신고차량수0.3130.0000.1510.2450.2390.0001.0000.000
15인승신고차량수0.0000.4690.9180.8190.7860.0000.0001.000

Missing values

2024-03-13T17:08:43.064736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T17:08:43.209713image/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

교육청명교육지원청명유치원코드유치원명설립유형차량운영여부운행차량수신고차량수9인승신고차량수12인승신고차량수15인승신고차량수공시차수주소
0서울특별시교육청강서양천교육지원청1dfcc6e7-c6ff-4843-b970-cfba072320b4서울강월초등학교병설유치원공립(병설)N0000020232서울특별시 양천구 신월로 97
1서울특별시교육청강서양천교육지원청1ecec08c-ed7f-b044-e053-0a32095ab044새서울유치원사립(사인)Y1100120232서울특별시 양천구 목동서로 340
2서울특별시교육청강서양천교육지원청1ecec08c-ed80-b044-e053-0a32095ab044샘터유치원사립(사인)Y3300320232서울특별시 양천구 신월로 99
3서울특별시교육청강서양천교육지원청1ecec08c-ed81-b044-e053-0a32095ab044서울경인유치원공립(단설)N0000020232서울특별시 양천구 안양천로 1009
4서울특별시교육청강서양천교육지원청1ecec08c-eec5-b044-e053-0a32095ab044솔샘유치원사립(사인)Y1100120182서울특별시 양천구 목동서로 130
5서울특별시교육청강서양천교육지원청1ecec08c-ef9b-b044-e053-0a32095ab044서울월촌초등학교병설유치원공립(병설)N0000020232서울특별시 양천구 목동중앙로 132
6서울특별시교육청강서양천교육지원청1ecec08c-ef9d-b044-e053-0a32095ab044솔밭유치원사립(사인)Y2201120182서울특별시 양천구 신월로10길 2-1
7서울특별시교육청강서양천교육지원청1ecec08c-f320-b044-e053-0a32095ab044원일유치원사립(법인)Y2310220232서울특별시 양천구 목동동로 350
8서울특별시교육청강서양천교육지원청1ecec08c-f3d6-b044-e053-0a32095ab044서울영도초등학교병설유치원공립(병설)N0000020232서울특별시 양천구 목동중앙로 70
9서울특별시교육청강서양천교육지원청1ecec08c-f448-b044-e053-0a32095ab044대한유치원사립(사인)Y1100120202서울특별시 양천구 오목로13길 31
교육청명교육지원청명유치원코드유치원명설립유형차량운영여부운행차량수신고차량수9인승신고차량수12인승신고차량수15인승신고차량수공시차수주소
38서울특별시교육청강서양천교육지원청1ecec08d-0c03-b044-e053-0a32095ab044빛나유치원사립(사인)Y1100120232서울특별시 양천구 목동로 212
39서울특별시교육청강서양천교육지원청1ecec08d-0c04-b044-e053-0a32095ab044서울신기초등학교병설유치원공립(병설)N0000020232서울특별시 양천구 신정로 292
40서울특별시교육청강서양천교육지원청1ecec08d-0e6c-b044-e053-0a32095ab044경성유치원사립(사인)Y3300320232서울특별시 양천구 목동로3길 57
41서울특별시교육청강서양천교육지원청1ecec08d-0e6d-b044-e053-0a32095ab044등촌유치원사립(사인)Y1100120232서울특별시 양천구 목동중앙북로8길 46
42서울특별시교육청강서양천교육지원청1ecec08d-0ef0-b044-e053-0a32095ab044꿈나무유치원사립(사인)Y4400420232서울특별시 양천구 목동서로 280
43서울특별시교육청강서양천교육지원청1fc6dd86-cccf-d1d2-e053-0a32095ad1d2목동유치원사립(사인)Y3300320232서울특별시 양천구 오목로42길 13
44서울특별시교육청강서양천교육지원청8abcadee-6df5-4c85-9e38-cba5a2d519a5서울양동초등학교병설유치원공립(병설)N0000020232서울특별시 양천구 오목로23길 24
45서울특별시교육청강서양천교육지원청9c26aa7f-0f07-4613-9136-4984c723803f꿈꾸는유치원사립(사인)Y1100120232서울특별시 양천구 오목로4길 8
46서울특별시교육청강서양천교육지원청a59a057e-4f5c-411a-bb2a-60068691c766세신유치원사립(법인)Y2200220232서울특별시 양천구 목동동로1길 38
47서울특별시교육청강서양천교육지원청d72d2e90-cf0d-4a9b-8697-a47e692aa3ea서울신정유치원공립(단설)N0000020232서울특별시 양천구 신정로7길 81-4