Overview

Dataset statistics

Number of variables17
Number of observations50
Missing cells98
Missing cells (%)11.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.1 KiB
Average record size in memory145.6 B

Variable types

Categorical8
Text4
Unsupported1
Numeric3
Boolean1

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,설립유형,급식운영방식구분,위탁업체명,전체유아수,급식유아수,영양교사배치여부,단독배치영양교사수,공동배치영양교사수,조리사수,조리인력수,집단급식소신고여부,공시차수,주소
Author은평구
URLhttps://data.seoul.go.kr/dataList/OA-20715/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
교육지원청명 has constant value ""Constant
단독배치영양교사수 is highly overall correlated with 설립유형 and 4 other fieldsHigh correlation
영양교사배치여부 is highly overall correlated with 단독배치영양교사수 and 1 other fieldsHigh correlation
공동배치영양교사수 is highly overall correlated with 설립유형 and 4 other fieldsHigh correlation
급식유아수 is highly overall correlated with 조리인력수 and 1 other fieldsHigh correlation
조리인력수 is highly overall correlated with 급식유아수High correlation
설립유형 is highly overall correlated with 급식운영방식구분 and 2 other fieldsHigh correlation
급식운영방식구분 is highly overall correlated with 설립유형 and 4 other fieldsHigh correlation
조리사수 is highly overall correlated with 급식유아수 and 4 other fieldsHigh correlation
집단급식소신고여부 is highly overall correlated with 급식운영방식구분 and 1 other fieldsHigh correlation
집단급식소신고여부 is highly imbalanced (68.9%)Imbalance
위탁업체명 has 48 (96.0%) missing valuesMissing
전체유아수 has 50 (100.0%) missing valuesMissing
유치원코드 has unique valuesUnique
유치원명 has unique valuesUnique
전체유아수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
급식유아수 has 1 (2.0%) zerosZeros
조리인력수 has 24 (48.0%) zerosZeros

Reproduction

Analysis started2024-03-13 14:49:20.516365
Analysis finished2024-03-13 14:49:22.246915
Duration1.73 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
서울특별시교육청
50 

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 50
100.0%

Length

2024-03-13T23:49:22.308566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:22.399293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 50
100.0%

교육지원청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
서부교육지원청
50 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서부교육지원청 50
100.0%

Length

2024-03-13T23:49:22.504933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:22.597469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서부교육지원청 50
100.0%

유치원코드
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-13T23:49:22.766465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters1800
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

Unique50 ?
Unique (%)100.0%

Sample

1st row0783b5eb-4c00-4161-9c47-664336825e5a
2nd row1ecec08c-ed16-b044-e053-0a32095ab044
3rd row1ecec08c-ed89-b044-e053-0a32095ab044
4th row1ecec08c-ee12-b044-e053-0a32095ab044
5th row1ecec08c-ee13-b044-e053-0a32095ab044
ValueCountFrequency (%)
0783b5eb-4c00-4161-9c47-664336825e5a 1
 
2.0%
1ecec08d-06b5-b044-e053-0a32095ab044 1
 
2.0%
e120b286-7861-486d-9b3f-f3c7b49f3c1c 1
 
2.0%
1ecec08d-015d-b044-e053-0a32095ab044 1
 
2.0%
1ecec08d-015f-b044-e053-0a32095ab044 1
 
2.0%
1ecec08d-029e-b044-e053-0a32095ab044 1
 
2.0%
1ecec08d-02b1-b044-e053-0a32095ab044 1
 
2.0%
1ecec08d-041e-b044-e053-0a32095ab044 1
 
2.0%
1ecec08d-04ab-b044-e053-0a32095ab044 1
 
2.0%
1ecec08d-04ac-b044-e053-0a32095ab044 1
 
2.0%
Other values (40) 40
80.0%
2024-03-13T23:49:23.081715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 285
15.8%
4 202
11.2%
- 200
11.1%
e 157
8.7%
c 132
7.3%
a 115
 
6.4%
b 109
 
6.1%
5 106
 
5.9%
3 105
 
5.8%
1 78
 
4.3%
Other values (7) 311
17.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1019
56.6%
Lowercase Letter 581
32.3%
Dash Punctuation 200
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 285
28.0%
4 202
19.8%
5 106
 
10.4%
3 105
 
10.3%
1 78
 
7.7%
9 70
 
6.9%
8 62
 
6.1%
2 62
 
6.1%
7 26
 
2.6%
6 23
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
e 157
27.0%
c 132
22.7%
a 115
19.8%
b 109
18.8%
f 36
 
6.2%
d 32
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1219
67.7%
Latin 581
32.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 285
23.4%
4 202
16.6%
- 200
16.4%
5 106
 
8.7%
3 105
 
8.6%
1 78
 
6.4%
9 70
 
5.7%
8 62
 
5.1%
2 62
 
5.1%
7 26
 
2.1%
Latin
ValueCountFrequency (%)
e 157
27.0%
c 132
22.7%
a 115
19.8%
b 109
18.8%
f 36
 
6.2%
d 32
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1800
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 285
15.8%
4 202
11.2%
- 200
11.1%
e 157
8.7%
c 132
7.3%
a 115
 
6.4%
b 109
 
6.1%
5 106
 
5.9%
3 105
 
5.8%
1 78
 
4.3%
Other values (7) 311
17.3%

유치원명
Text

UNIQUE 

Distinct50
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-13T23:49:23.309344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length7.66
Min length4

Characters and Unicode

Total characters383
Distinct characters83
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

Unique50 ?
Unique (%)100.0%

Sample

1st row다우림유치원
2nd row서울연광초등학교병설유치원
3rd row궁전유치원
4th row성아유치원
5th row성균관유치원
ValueCountFrequency (%)
다우림유치원 1
 
2.0%
다우림명문유치원 1
 
2.0%
서울어울초등학교병설유치원 1
 
2.0%
백합유치원 1
 
2.0%
보림유치원 1
 
2.0%
서울수색초등학교병설유치원 1
 
2.0%
서울연신초등학교병설유치원 1
 
2.0%
엔젤유치원 1
 
2.0%
서문유치원 1
 
2.0%
서울은평초등학교병설유치원 1
 
2.0%
Other values (40) 40
80.0%
2024-03-13T23:49:23.615620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 51
13.3%
치 50
 
13.1%
원 50
 
13.1%
울 20
 
5.2%
서 20
 
5.2%
설 13
 
3.4%
병 13
 
3.4%
교 13
 
3.4%
학 13
 
3.4%
등 13
 
3.4%
Other values (73) 127
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 383
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 51
13.3%
치 50
 
13.1%
원 50
 
13.1%
울 20
 
5.2%
서 20
 
5.2%
설 13
 
3.4%
병 13
 
3.4%
교 13
 
3.4%
학 13
 
3.4%
등 13
 
3.4%
Other values (73) 127
33.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 383
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 51
13.3%
치 50
 
13.1%
원 50
 
13.1%
울 20
 
5.2%
서 20
 
5.2%
설 13
 
3.4%
병 13
 
3.4%
교 13
 
3.4%
학 13
 
3.4%
등 13
 
3.4%
Other values (73) 127
33.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 383
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 51
13.3%
치 50
 
13.1%
원 50
 
13.1%
울 20
 
5.2%
서 20
 
5.2%
설 13
 
3.4%
병 13
 
3.4%
교 13
 
3.4%
학 13
 
3.4%
등 13
 
3.4%
Other values (73) 127
33.2%

설립유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
사립(사인)
24 
공립(병설)
13 
사립(법인)
8 
공립(단설)
5 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립(사인) 24
48.0%
공립(병설) 13
26.0%
사립(법인) 8
 
16.0%
공립(단설) 5
 
10.0%

Length

2024-03-13T23:49:23.738018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:23.831409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 24
48.0%
공립(병설 13
26.0%
사립(법인 8
 
16.0%
공립(단설 5
 
10.0%

급식운영방식구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
직영
31 
직영(학교급식)
13 
공동
 
3
위탁
 
2
혼합
 
1

Length

Max length8
Median length2
Mean length3.56
Min length2

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row직영
2nd row직영(학교급식)
3rd row직영
4th row직영
5th row직영

Common Values

ValueCountFrequency (%)
직영 31
62.0%
직영(학교급식) 13
26.0%
공동 3
 
6.0%
위탁 2
 
4.0%
혼합 1
 
2.0%

Length

2024-03-13T23:49:23.941298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:24.035060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
직영 31
62.0%
직영(학교급식 13
26.0%
공동 3
 
6.0%
위탁 2
 
4.0%
혼합 1
 
2.0%

위탁업체명
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing48
Missing (%)96.0%
Memory size532.0 B
2024-03-13T23:49:24.156554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length7.5
Mean length7.5
Min length5

Characters and Unicode

Total characters15
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row(주)베스트푸드키즈
2nd row베스트푸드
ValueCountFrequency (%)
주)베스트푸드키즈 1
50.0%
베스트푸드 1
50.0%
2024-03-13T23:49:24.423745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
베 2
13.3%
스 2
13.3%
트 2
13.3%
푸 2
13.3%
드 2
13.3%
( 1
6.7%
주 1
6.7%
) 1
6.7%
키 1
6.7%
즈 1
6.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
86.7%
Open Punctuation 1
 
6.7%
Close Punctuation 1
 
6.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
베 2
15.4%
스 2
15.4%
트 2
15.4%
푸 2
15.4%
드 2
15.4%
주 1
7.7%
키 1
7.7%
즈 1
7.7%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
86.7%
Common 2
 
13.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
베 2
15.4%
스 2
15.4%
트 2
15.4%
푸 2
15.4%
드 2
15.4%
주 1
7.7%
키 1
7.7%
즈 1
7.7%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
86.7%
ASCII 2
 
13.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
베 2
15.4%
스 2
15.4%
트 2
15.4%
푸 2
15.4%
드 2
15.4%
주 1
7.7%
키 1
7.7%
즈 1
7.7%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

전체유아수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing50
Missing (%)100.0%
Memory size582.0 B

급식유아수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct47
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean77
Minimum0
Maximum246
Zeros1
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T23:49:24.642144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile14.8
Q130
median62
Q3122.25
95-th percentile164.6
Maximum246
Range246
Interquartile range (IQR)92.25

Descriptive statistics

Standard deviation57.16928
Coefficient of variation (CV)0.74245818
Kurtosis0.093025744
Mean77
Median Absolute Deviation (MAD)38.5
Skewness0.83995197
Sum3850
Variance3268.3265
MonotonicityNot monotonic
2024-03-13T23:49:25.093387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
30 2
 
4.0%
26 2
 
4.0%
124 2
 
4.0%
34 1
 
2.0%
56 1
 
2.0%
32 1
 
2.0%
156 1
 
2.0%
13 1
 
2.0%
17 1
 
2.0%
142 1
 
2.0%
Other values (37) 37
74.0%
ValueCountFrequency (%)
0 1
2.0%
10 1
2.0%
13 1
2.0%
17 1
2.0%
18 1
2.0%
20 1
2.0%
22 1
2.0%
23 1
2.0%
24 1
2.0%
26 2
4.0%
ValueCountFrequency (%)
246 1
2.0%
201 1
2.0%
170 1
2.0%
158 1
2.0%
156 1
2.0%
153 1
2.0%
146 1
2.0%
143 1
2.0%
142 1
2.0%
135 1
2.0%

영양교사배치여부
Boolean

HIGH CORRELATION 

Distinct2
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size182.0 B
True
37 
False
13 
ValueCountFrequency (%)
True 37
74.0%
False 13
 
26.0%
2024-03-13T23:49:25.183949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

단독배치영양교사수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
0
24 
<NA>
13 
1
13 

Length

Max length4
Median length1
Mean length1.78
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row<NA>
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
0 24
48.0%
<NA> 13
26.0%
1 13
26.0%

Length

2024-03-13T23:49:25.291306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:25.389806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 24
48.0%
na 13
26.0%
1 13
26.0%

공동배치영양교사수
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
1
24 
<NA>
13 
0
13 

Length

Max length4
Median length1
Mean length1.78
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row<NA>
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
1 24
48.0%
<NA> 13
26.0%
0 13
26.0%

Length

2024-03-13T23:49:25.492643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:25.594985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 24
48.0%
na 13
26.0%
0 13
26.0%

조리사수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
1
30 
0
17 
2
 
2
9
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 30
60.0%
0 17
34.0%
2 2
 
4.0%
9 1
 
2.0%

Length

2024-03-13T23:49:25.700965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:25.791034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 30
60.0%
0 17
34.0%
2 2
 
4.0%
9 1
 
2.0%

조리인력수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.88
Minimum0
Maximum6
Zeros24
Zeros (%)48.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T23:49:25.867784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q31
95-th percentile3
Maximum6
Range6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.2061069
Coefficient of variation (CV)1.370576
Kurtosis6.0313979
Mean0.88
Median Absolute Deviation (MAD)1
Skewness2.1294316
Sum44
Variance1.4546939
MonotonicityNot monotonic
2024-03-13T23:49:25.961854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 24
48.0%
1 16
32.0%
2 6
 
12.0%
3 2
 
4.0%
4 1
 
2.0%
6 1
 
2.0%
ValueCountFrequency (%)
0 24
48.0%
1 16
32.0%
2 6
 
12.0%
3 2
 
4.0%
4 1
 
2.0%
6 1
 
2.0%
ValueCountFrequency (%)
6 1
 
2.0%
4 1
 
2.0%
3 2
 
4.0%
2 6
 
12.0%
1 16
32.0%
0 24
48.0%

집단급식소신고여부
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
Y
45 
<NA>
 
2
X
 
2
N
 
1

Length

Max length4
Median length1
Mean length1.12
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 45
90.0%
<NA> 2
 
4.0%
X 2
 
4.0%
N 1
 
2.0%

Length

2024-03-13T23:49:26.067476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T23:49:26.164912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 45
90.0%
na 2
 
4.0%
x 2
 
4.0%
n 1
 
2.0%

공시차수
Real number (ℝ)

Distinct6
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20223.8
Minimum20182
Maximum20232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size582.0 B
2024-03-13T23:49:26.246423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20182
5-th percentile20192
Q120224.5
median20232
Q320232
95-th percentile20232
Maximum20232
Range50
Interquartile range (IQR)7.5

Descriptive statistics

Standard deviation15.608736
Coefficient of variation (CV)0.00077180038
Kurtosis1.342488
Mean20223.8
Median Absolute Deviation (MAD)0
Skewness-1.686889
Sum1011190
Variance243.63265
MonotonicityNot monotonic
2024-03-13T23:49:26.344091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20232 37
74.0%
20192 5
 
10.0%
20212 3
 
6.0%
20222 2
 
4.0%
20182 2
 
4.0%
20202 1
 
2.0%
ValueCountFrequency (%)
20182 2
 
4.0%
20192 5
 
10.0%
20202 1
 
2.0%
20212 3
 
6.0%
20222 2
 
4.0%
20232 37
74.0%
ValueCountFrequency (%)
20232 37
74.0%
20222 2
 
4.0%
20212 3
 
6.0%
20202 1
 
2.0%
20192 5
 
10.0%
20182 2
 
4.0%

주소
Text

Distinct47
Distinct (%)94.0%
Missing0
Missing (%)0.0%
Memory size532.0 B
2024-03-13T23:49:26.574821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length20
Mean length18.74
Min length16

Characters and Unicode

Total characters937
Distinct characters45
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

Unique44 ?
Unique (%)88.0%

Sample

1st row서울특별시 은평구 증산로21길 22
2nd row서울특별시 은평구 연서로35길 37
3rd row서울특별시 은평구 갈현로33길 24
4th row서울특별시 은평구 응암로14길 21
5th row서울특별시 은평구 연서로27길 23
ValueCountFrequency (%)
서울특별시 50
25.0%
은평구 50
25.0%
진관4로 3
 
1.5%
진관1로 3
 
1.5%
통일로 3
 
1.5%
갈현로 3
 
1.5%
21 2
 
1.0%
은평로16길 2
 
1.0%
20 2
 
1.0%
22 2
 
1.0%
Other values (69) 80
40.0%
2024-03-13T23:49:27.002010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
150
16.0%
서 58
 
6.2%
은 57
 
6.1%
평 57
 
6.1%
울 50
 
5.3%
특 50
 
5.3%
별 50
 
5.3%
시 50
 
5.3%
구 50
 
5.3%
로 49
 
5.2%
Other values (35) 316
33.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 586
62.5%
Decimal Number 185
 
19.7%
Space Separator 150
 
16.0%
Dash Punctuation 16
 
1.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 58
9.9%
은 57
9.7%
평 57
9.7%
울 50
8.5%
특 50
8.5%
별 50
8.5%
시 50
8.5%
구 50
8.5%
로 49
8.4%
길 28
 
4.8%
Other values (23) 87
14.8%
Decimal Number
ValueCountFrequency (%)
1 46
24.9%
2 29
15.7%
3 25
13.5%
7 22
11.9%
5 19
10.3%
4 13
 
7.0%
0 10
 
5.4%
9 9
 
4.9%
6 9
 
4.9%
8 3
 
1.6%
Space Separator
ValueCountFrequency (%)
150
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 586
62.5%
Common 351
37.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 58
9.9%
은 57
9.7%
평 57
9.7%
울 50
8.5%
특 50
8.5%
별 50
8.5%
시 50
8.5%
구 50
8.5%
로 49
8.4%
길 28
 
4.8%
Other values (23) 87
14.8%
Common
ValueCountFrequency (%)
150
42.7%
1 46
 
13.1%
2 29
 
8.3%
3 25
 
7.1%
7 22
 
6.3%
5 19
 
5.4%
- 16
 
4.6%
4 13
 
3.7%
0 10
 
2.8%
9 9
 
2.6%
Other values (2) 12
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 586
62.5%
ASCII 351
37.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
150
42.7%
1 46
 
13.1%
2 29
 
8.3%
3 25
 
7.1%
7 22
 
6.3%
5 19
 
5.4%
- 16
 
4.6%
4 13
 
3.7%
0 10
 
2.8%
9 9
 
2.6%
Other values (2) 12
 
3.4%
Hangul
ValueCountFrequency (%)
서 58
9.9%
은 57
9.7%
평 57
9.7%
울 50
8.5%
특 50
8.5%
별 50
8.5%
시 50
8.5%
구 50
8.5%
로 49
8.4%
길 28
 
4.8%
Other values (23) 87
14.8%

Interactions

2024-03-13T23:49:21.620224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.169334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.391791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.733260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.241562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.467389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.813716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.317809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T23:49:21.544124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T23:49:27.097728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원코드유치원명설립유형급식운영방식구분위탁업체명급식유아수영양교사배치여부단독배치영양교사수공동배치영양교사수조리사수조리인력수집단급식소신고여부공시차수주소
유치원코드1.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
유치원명1.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
설립유형1.0001.0001.0000.7320.0000.2820.5610.8660.8660.7430.4960.0030.1190.000
급식운영방식구분1.0001.0000.7321.000NaN0.2070.3700.3630.3630.6270.3200.6980.8591.000
위탁업체명0.0000.0000.000NaN1.000NaNNaNNaNNaN0.000NaNNaN0.0000.000
급식유아수1.0001.0000.2820.207NaN1.0000.2730.5070.5070.7630.6710.0000.0000.851
영양교사배치여부1.0001.0000.5610.370NaN0.2731.000NaNNaN0.1720.0860.1390.3061.000
단독배치영양교사수1.0001.0000.8660.363NaN0.507NaN1.0000.9950.3490.7140.0000.0000.000
공동배치영양교사수1.0001.0000.8660.363NaN0.507NaN0.9951.0000.3490.7140.0000.0000.000
조리사수1.0001.0000.7430.6270.0000.7630.1720.3490.3491.0000.5250.6590.2701.000
조리인력수1.0001.0000.4960.320NaN0.6710.0860.7140.7140.5251.0000.0000.0000.991
집단급식소신고여부1.0001.0000.0030.698NaN0.0000.1390.0000.0000.6590.0001.0000.3361.000
공시차수1.0001.0000.1190.8590.0000.0000.3060.0000.0000.2700.0000.3361.0000.000
주소1.0001.0000.0001.0000.0000.8511.0000.0000.0001.0000.9911.0000.0001.000
2024-03-13T23:49:27.246874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
단독배치영양교사수급식운영방식구분영양교사배치여부공동배치영양교사수설립유형조리사수집단급식소신고여부
단독배치영양교사수1.0000.5681.0000.9390.6470.5480.000
급식운영방식구분0.5681.0000.4350.5680.6650.5480.663
영양교사배치여부1.0000.4351.0001.0000.3750.1060.225
공동배치영양교사수0.9390.5681.0001.0000.6470.5480.000
설립유형0.6470.6650.3750.6471.0000.3790.000
조리사수0.5480.5480.1060.5480.3791.0000.678
집단급식소신고여부0.0000.6630.2250.0000.0000.6781.000
2024-03-13T23:49:27.356707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급식유아수조리인력수공시차수설립유형급식운영방식구분영양교사배치여부단독배치영양교사수공동배치영양교사수조리사수집단급식소신고여부
급식유아수1.0000.5430.0750.1630.0990.2460.4490.4490.5740.000
조리인력수0.5431.0000.2330.3310.2160.0380.4930.4930.3550.000
공시차수0.0750.2331.0000.0470.4840.4550.0000.0000.1950.289
설립유형0.1630.3310.0471.0000.6650.3750.6470.6470.3790.000
급식운영방식구분0.0990.2160.4840.6651.0000.4350.5680.5680.5480.663
영양교사배치여부0.2460.0380.4550.3750.4351.0001.0001.0000.1060.225
단독배치영양교사수0.4490.4930.0000.6470.5681.0001.0000.9390.5480.000
공동배치영양교사수0.4490.4930.0000.6470.5681.0000.9391.0000.5480.000
조리사수0.5740.3550.1950.3790.5480.1060.5480.5481.0000.678
집단급식소신고여부0.0000.0000.2890.0000.6630.2250.0000.0000.6781.000

Missing values

2024-03-13T23:49:21.935055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T23:49:22.149767image/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

교육청명교육지원청명유치원코드유치원명설립유형급식운영방식구분위탁업체명전체유아수급식유아수영양교사배치여부단독배치영양교사수공동배치영양교사수조리사수조리인력수집단급식소신고여부공시차수주소
0서울특별시교육청서부교육지원청0783b5eb-4c00-4161-9c47-664336825e5a다우림유치원사립(사인)직영<NA><NA>57Y0110Y20222서울특별시 은평구 증산로21길 22
1서울특별시교육청서부교육지원청1ecec08c-ed16-b044-e053-0a32095ab044서울연광초등학교병설유치원공립(병설)직영(학교급식)<NA><NA>23Y0100Y20232서울특별시 은평구 연서로35길 37
2서울특별시교육청서부교육지원청1ecec08c-ed89-b044-e053-0a32095ab044궁전유치원사립(사인)직영<NA><NA>36N<NA><NA>10Y20182서울특별시 은평구 갈현로33길 24
3서울특별시교육청서부교육지원청1ecec08c-ee12-b044-e053-0a32095ab044성아유치원사립(사인)직영<NA><NA>81N<NA><NA>11Y20232서울특별시 은평구 응암로14길 21
4서울특별시교육청서부교육지원청1ecec08c-ee13-b044-e053-0a32095ab044성균관유치원사립(사인)직영<NA><NA>135Y1012Y20232서울특별시 은평구 연서로27길 23
5서울특별시교육청서부교육지원청1ecec08c-ee3d-b044-e053-0a32095ab044동산유치원사립(법인)직영<NA><NA>91Y0111Y20232서울특별시 은평구 증산서길 53-9
6서울특별시교육청서부교육지원청1ecec08c-eed7-b044-e053-0a32095ab044서울신도초등학교병설유치원공립(병설)직영(학교급식)<NA><NA>24Y0100Y20232서울특별시 은평구 진관1로 77-23
7서울특별시교육청서부교육지원청1ecec08c-f13b-b044-e053-0a32095ab044서울진관유치원공립(단설)직영<NA><NA>71Y1011Y20232서울특별시 은평구 진관2로 111-16
8서울특별시교육청서부교육지원청1ecec08c-f13c-b044-e053-0a32095ab044서울은빛유치원공립(단설)직영<NA><NA>106Y1011Y20232서울특별시 은평구 진관3로 73-11
9서울특별시교육청서부교육지원청1ecec08c-f19a-b044-e053-0a32095ab044선일유치원사립(법인)공동<NA><NA>110Y0112Y20232서울특별시 은평구 갈현로29길 27
교육청명교육지원청명유치원코드유치원명설립유형급식운영방식구분위탁업체명전체유아수급식유아수영양교사배치여부단독배치영양교사수공동배치영양교사수조리사수조리인력수집단급식소신고여부공시차수주소
40서울특별시교육청서부교육지원청1ecec08d-09db-b044-e053-0a32095ab044바다의별유치원사립(법인)직영<NA><NA>67Y1010Y20232서울특별시 은평구 통일로 790-1
41서울특별시교육청서부교육지원청1ecec08d-0ba5-b044-e053-0a32095ab044숲유치원사립(사인)직영<NA><NA>201Y1023Y20232서울특별시 은평구 진관2로 37
42서울특별시교육청서부교육지원청1ecec08d-0e41-b044-e053-0a32095ab044새보람유치원사립(사인)직영<NA><NA>10N<NA><NA>10X20232서울특별시 은평구 불광로 107
43서울특별시교육청서부교육지원청799c1c12-8e72-44b1-80ba-84c6907a6037서울불광초등학교병설유치원공립(병설)직영(학교급식)<NA><NA>38Y0100Y20232서울특별시 은평구 불광로 51
44서울특별시교육청서부교육지원청7a2cc871-7f4c-4c45-b4a9-5610093f33fa서울응암초등학교병설유치원공립(병설)직영(학교급식)<NA><NA>52Y0116Y20232서울특별시 은평구 가좌로6길 20
45서울특별시교육청서부교육지원청a4246c73-08e0-4da3-8211-ad2976de52ea은평하랑유치원사립(사인)직영<NA><NA>28N<NA><NA>11Y20232서울특별시 은평구 은평로16길 9-1
46서울특별시교육청서부교육지원청abfb8257-6e64-417e-9fb4-1e145a31f5fe서울산울림유치원공립(단설)직영<NA><NA>77Y1011Y20232서울특별시 은평구 진관4로 93
47서울특별시교육청서부교육지원청ccb06417-04c0-411a-b29e-6ff1a22fabab서울북한산유치원공립(단설)직영<NA><NA>82Y1011Y20232서울특별시 은평구 진관1로 77-15
48서울특별시교육청서부교육지원청e120b286-7861-486d-9b3f-f3c7b49f3c1c서울어울초등학교병설유치원공립(병설)직영(학교급식)<NA><NA>48Y0100Y20232서울특별시 은평구 통일로 650
49서울특별시교육청서부교육지원청e7796971-1ca3-445b-a672-a03730995574서울역촌유치원공립(단설)직영<NA><NA>26Y1011Y20232서울특별시 은평구 진흥로7길 25