Overview

Dataset statistics

Number of variables22
Number of observations939
Missing cells350
Missing cells (%)1.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory169.8 KiB
Average record size in memory185.1 B

Variable types

Categorical5
Text3
Boolean5
Numeric9

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,설립유형,소방대피훈련여부,소방대피훈련일자,가스점검여부,가스점검일자,소방안전점검여부,소방안전점검일자,전기설비점검여부,전기설비점검일자,놀이시설 안전검사 대상여부,놀이시설 안전검사 점검일자,놀이시설 안전검사 점검결과,CCTV 설치여부,CCTV 총 설치수,CCTV 건물 안 설치수,CCTV 건물 밖 설치수,공시차수,주소
Author한국교육학술정보원
URLhttps://data.seoul.go.kr/dataList/OA-20575/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
소방대피훈련여부 is highly imbalanced (90.1%)Imbalance
가스점검여부 is highly imbalanced (87.3%)Imbalance
소방안전점검여부 is highly imbalanced (88.8%)Imbalance
전기설비점검여부 is highly imbalanced (89.5%)Imbalance
CCTV 설치여부 is highly imbalanced (95.2%)Imbalance
소방대피훈련일자 has 12 (1.3%) missing valuesMissing
가스점검일자 has 31 (3.3%) missing valuesMissing
소방안전점검일자 has 14 (1.5%) missing valuesMissing
전기설비점검일자 has 13 (1.4%) missing valuesMissing
놀이시설 안전검사 점검일자 has 266 (28.3%) missing valuesMissing
유치원코드 has unique valuesUnique
CCTV 건물 안 설치수 has 25 (2.7%) zerosZeros
CCTV 건물 밖 설치수 has 60 (6.4%) zerosZeros

Reproduction

Analysis started2024-03-13 06:15:10.644212
Analysis finished2024-03-13 06:15:11.143222
Duration0.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
서울특별시교육청
939 

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 939
100.0%

Length

2024-03-13T15:15:11.200444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T15:15:11.286706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 939
100.0%

교육지원청명
Categorical

Distinct11
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
북부교육지원청
114 
강서양천교육지원청
109 
서부교육지원청
103 
강동송파교육지원청
98 
남부교육지원청
97 
Other values (6)
418 

Length

Max length9
Median length9
Mean length8.0734824
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남부교육지원청
2nd row강동송파교육지원청
3rd row강동송파교육지원청
4th row동부교육지원청
5th row동부교육지원청

Common Values

ValueCountFrequency (%)
북부교육지원청 114
12.1%
강서양천교육지원청 109
11.6%
서부교육지원청 103
11.0%
강동송파교육지원청 98
10.4%
남부교육지원청 97
10.3%
동작관악교육지원청 77
8.2%
성북강북교육지원청 77
8.2%
강남서초교육지원청 73
7.8%
동부교육지원청 72
7.7%
성동광진교육지원청 70
7.5%

Length

2024-03-13T15:15:11.411613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
북부교육지원청 114
12.1%
강서양천교육지원청 109
11.6%
서부교육지원청 103
11.0%
강동송파교육지원청 98
10.4%
남부교육지원청 97
10.3%
동작관악교육지원청 77
8.2%
성북강북교육지원청 77
8.2%
강남서초교육지원청 73
7.8%
동부교육지원청 72
7.7%
성동광진교육지원청 70
7.5%

유치원코드
Text

UNIQUE 

Distinct939
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-03-13T15:15:11.733028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters33804
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

Unique939 ?
Unique (%)100.0%

Sample

1st row006b5238-ce41-4471-9ee3-4df8d24b5141
2nd row009c017d-43bd-4d9f-ac64-d217abdd570e
3rd row04a021da-cdd7-4e7e-a434-2b388c2f6b63
4th row0764f8c8-364c-495b-9fbc-b389148b7b4f
5th row076db651-036b-4bee-80ba-09f0edb4a57a
ValueCountFrequency (%)
006b5238-ce41-4471-9ee3-4df8d24b5141 1
 
0.1%
1ecec08d-0841-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-078e-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-08de-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-078f-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-0791-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-079a-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-079c-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-080a-b044-e053-0a32095ab044 1
 
0.1%
1ecec08d-080b-b044-e053-0a32095ab044 1
 
0.1%
Other values (929) 929
98.9%
2024-03-13T15:15:12.083733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 5593
16.5%
- 3756
11.1%
4 3729
11.0%
e 2930
8.7%
c 2461
7.3%
a 2042
 
6.0%
5 2003
 
5.9%
3 2001
 
5.9%
b 2000
 
5.9%
8 1256
 
3.7%
Other values (7) 6033
17.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18997
56.2%
Lowercase Letter 11051
32.7%
Dash Punctuation 3756
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 5593
29.4%
4 3729
19.6%
5 2003
 
10.5%
3 2001
 
10.5%
8 1256
 
6.6%
1 1241
 
6.5%
9 1198
 
6.3%
2 1190
 
6.3%
7 394
 
2.1%
6 392
 
2.1%
Lowercase Letter
ValueCountFrequency (%)
e 2930
26.5%
c 2461
22.3%
a 2042
18.5%
b 2000
18.1%
d 832
 
7.5%
f 786
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 3756
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 22753
67.3%
Latin 11051
32.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 5593
24.6%
- 3756
16.5%
4 3729
16.4%
5 2003
 
8.8%
3 2001
 
8.8%
8 1256
 
5.5%
1 1241
 
5.5%
9 1198
 
5.3%
2 1190
 
5.2%
7 394
 
1.7%
Latin
ValueCountFrequency (%)
e 2930
26.5%
c 2461
22.3%
a 2042
18.5%
b 2000
18.1%
d 832
 
7.5%
f 786
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33804
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 5593
16.5%
- 3756
11.1%
4 3729
11.0%
e 2930
8.7%
c 2461
7.3%
a 2042
 
6.0%
5 2003
 
5.9%
3 2001
 
5.9%
b 2000
 
5.9%
8 1256
 
3.7%
Other values (7) 6033
17.8%

유치원명
Text

Distinct843
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-03-13T15:15:12.418060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length7.686901
Min length4

Characters and Unicode

Total characters7218
Distinct characters313
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

Unique772 ?
Unique (%)82.2%

Sample

1st row서울정심초등학교병설유치원
2nd row서울솔방울유치원
3rd row란키즈유치원
4th row서울신현초등학교병설유치원
5th row서울신묵초등학교병설유치원
ValueCountFrequency (%)
사랑유치원 5
 
0.5%
예일유치원 5
 
0.5%
하나유치원 4
 
0.4%
새싹유치원 4
 
0.4%
예원유치원 4
 
0.4%
천사유치원 3
 
0.3%
벧엘유치원 3
 
0.3%
영은유치원 3
 
0.3%
서울유치원 3
 
0.3%
돌샘유치원 3
 
0.3%
Other values (837) 906
96.1%
2024-03-13T15:15:12.869077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 975
13.5%
유 952
 
13.2%
치 940
 
13.0%
서 327
 
4.5%
울 317
 
4.4%
학 272
 
3.8%
교 266
 
3.7%
등 261
 
3.6%
설 255
 
3.5%
초 255
 
3.5%
Other values (303) 2398
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7214
99.9%
Space Separator 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 975
13.5%
유 952
 
13.2%
치 940
 
13.0%
서 327
 
4.5%
울 317
 
4.4%
학 272
 
3.8%
교 266
 
3.7%
등 261
 
3.6%
설 255
 
3.5%
초 255
 
3.5%
Other values (302) 2394
33.2%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7214
99.9%
Common 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 975
13.5%
유 952
 
13.2%
치 940
 
13.0%
서 327
 
4.5%
울 317
 
4.4%
학 272
 
3.8%
교 266
 
3.7%
등 261
 
3.6%
설 255
 
3.5%
초 255
 
3.5%
Other values (302) 2394
33.2%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7214
99.9%
ASCII 4
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 975
13.5%
유 952
 
13.2%
치 940
 
13.0%
서 327
 
4.5%
울 317
 
4.4%
학 272
 
3.8%
교 266
 
3.7%
등 261
 
3.6%
설 255
 
3.5%
초 255
 
3.5%
Other values (302) 2394
33.2%
ASCII
ValueCountFrequency (%)
4
100.0%

설립유형
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
사립(사인)
498 
공립(병설)
252 
사립(법인)
140 
공립(단설)
 
49

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립(사인) 498
53.0%
공립(병설) 252
26.8%
사립(법인) 140
 
14.9%
공립(단설) 49
 
5.2%

Length

2024-03-13T15:15:12.986861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T15:15:13.072293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 498
53.0%
공립(병설 252
26.8%
사립(법인 140
 
14.9%
공립(단설 49
 
5.2%

소방대피훈련여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
True
927 
False
 
12
ValueCountFrequency (%)
True 927
98.7%
False 12
 
1.3%
2024-03-13T15:15:13.152974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

소방대피훈련일자
Real number (ℝ)

MISSING 

Distinct231
Distinct (%)24.9%
Missing12
Missing (%)1.3%
Infinite0
Infinite (%)0.0%
Mean20223713
Minimum20180403
Maximum20230927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:13.258410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20180403
5-th percentile20181001
Q120230426
median20230824
Q320230908
95-th percentile20230922
Maximum20230927
Range50524
Interquartile range (IQR)482

Descriptive statistics

Standard deviation15377.904
Coefficient of variation (CV)0.00076038976
Kurtosis2.1155508
Mean20223713
Median Absolute Deviation (MAD)101
Skewness-1.9349335
Sum1.8747382 × 1010
Variance2.3647995 × 108
MonotonicityNot monotonic
2024-03-13T15:15:13.403856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230904 71
 
7.6%
20230905 32
 
3.4%
20230908 24
 
2.6%
20230925 24
 
2.6%
20230922 24
 
2.6%
20230919 23
 
2.4%
20230912 21
 
2.2%
20230918 20
 
2.1%
20230907 20
 
2.1%
20230914 19
 
2.0%
Other values (221) 649
69.1%
ValueCountFrequency (%)
20180403 1
0.1%
20180612 1
0.1%
20180628 1
0.1%
20180706 1
0.1%
20180808 1
0.1%
20180809 1
0.1%
20180810 1
0.1%
20180813 1
0.1%
20180814 1
0.1%
20180822 1
0.1%
ValueCountFrequency (%)
20230927 3
 
0.3%
20230926 13
1.4%
20230925 24
2.6%
20230923 1
 
0.1%
20230922 24
2.6%
20230921 17
1.8%
20230920 8
 
0.9%
20230919 23
2.4%
20230918 20
2.1%
20230915 16
1.7%

가스점검여부
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
Y
908 
X
 
17
N
 
10
<NA>
 
4

Length

Max length4
Median length1
Mean length1.0127796
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Y 908
96.7%
X 17
 
1.8%
N 10
 
1.1%
<NA> 4
 
0.4%

Length

2024-03-13T15:15:13.535460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T15:15:13.629574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
y 908
96.7%
x 17
 
1.8%
n 10
 
1.1%
na 4
 
0.4%

가스점검일자
Real number (ℝ)

MISSING 

Distinct393
Distinct (%)43.3%
Missing31
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean20222138
Minimum20170428
Maximum20230927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:13.754731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20170428
5-th percentile20180911
Q120221007
median20230408
Q320230821
95-th percentile20230918
Maximum20230927
Range60499
Interquartile range (IQR)9814.25

Descriptive statistics

Standard deviation15839.601
Coefficient of variation (CV)0.00078328025
Kurtosis1.877215
Mean20222138
Median Absolute Deviation (MAD)492.5
Skewness-1.8129133
Sum1.8361702 × 1010
Variance2.5089297 × 108
MonotonicityNot monotonic
2024-03-13T15:15:13.943711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230904 50
 
5.3%
20230901 16
 
1.7%
20230905 13
 
1.4%
20230925 10
 
1.1%
20230918 9
 
1.0%
20230214 8
 
0.9%
20230919 8
 
0.9%
20230913 8
 
0.9%
20230906 8
 
0.9%
20230317 8
 
0.9%
Other values (383) 770
82.0%
(Missing) 31
 
3.3%
ValueCountFrequency (%)
20170428 1
0.1%
20170622 1
0.1%
20170905 1
0.1%
20170922 1
0.1%
20171023 1
0.1%
20171115 1
0.1%
20171204 1
0.1%
20180117 1
0.1%
20180118 1
0.1%
20180122 1
0.1%
ValueCountFrequency (%)
20230927 4
 
0.4%
20230926 4
 
0.4%
20230925 10
1.1%
20230922 7
0.7%
20230921 7
0.7%
20230920 5
0.5%
20230919 8
0.9%
20230918 9
1.0%
20230915 7
0.7%
20230914 5
0.5%

소방안전점검여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
True
925 
False
 
14
ValueCountFrequency (%)
True 925
98.5%
False 14
 
1.5%
2024-03-13T15:15:14.077252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

소방안전점검일자
Real number (ℝ)

MISSING 

Distinct344
Distinct (%)37.2%
Missing14
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean20222574
Minimum20030627
Maximum20230927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:14.171864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20030627
5-th percentile20180915
Q120221222
median20230809
Q320230907
95-th percentile20230920
Maximum20230927
Range200300
Interquartile range (IQR)9685

Descriptive statistics

Standard deviation17226.188
Coefficient of variation (CV)0.00085182965
Kurtosis17.657109
Mean20222574
Median Absolute Deviation (MAD)110
Skewness-2.9984464
Sum1.8705881 × 1010
Variance2.9674156 × 108
MonotonicityNot monotonic
2024-03-13T15:15:14.327686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230904 45
 
4.8%
20230905 29
 
3.1%
20230918 24
 
2.6%
20230906 23
 
2.4%
20230908 23
 
2.4%
20230915 23
 
2.4%
20230901 21
 
2.2%
20230911 20
 
2.1%
20230914 19
 
2.0%
20230907 18
 
1.9%
Other values (334) 680
72.4%
ValueCountFrequency (%)
20030627 1
0.1%
20150819 1
0.1%
20160916 1
0.1%
20170222 1
0.1%
20171114 1
0.1%
20171206 1
0.1%
20171228 1
0.1%
20171230 1
0.1%
20180115 1
0.1%
20180126 1
0.1%
ValueCountFrequency (%)
20230927 1
 
0.1%
20230926 3
 
0.3%
20230925 8
 
0.9%
20230923 1
 
0.1%
20230922 12
1.3%
20230921 15
1.6%
20230920 18
1.9%
20230919 14
1.5%
20230918 24
2.6%
20230916 1
 
0.1%

전기설비점검여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
True
926 
False
 
13
ValueCountFrequency (%)
True 926
98.6%
False 13
 
1.4%
2024-03-13T15:15:14.440625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

전기설비점검일자
Real number (ℝ)

MISSING 

Distinct357
Distinct (%)38.6%
Missing13
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean20222033
Minimum20150827
Maximum20230927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:14.531247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20150827
5-th percentile20180904
Q120221008
median20230766
Q320230912
95-th percentile20230922
Maximum20230927
Range80100
Interquartile range (IQR)9904.5

Descriptive statistics

Standard deviation16446.206
Coefficient of variation (CV)0.00081328153
Kurtosis2.1197708
Mean20222033
Median Absolute Deviation (MAD)155.5
Skewness-1.8490117
Sum1.8725603 × 1010
Variance2.704777 × 108
MonotonicityNot monotonic
2024-03-13T15:15:14.700986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230918 44
 
4.7%
20230904 31
 
3.3%
20230919 29
 
3.1%
20230921 26
 
2.8%
20230920 25
 
2.7%
20230912 25
 
2.7%
20230914 23
 
2.4%
20230905 23
 
2.4%
20230925 21
 
2.2%
20230915 19
 
2.0%
Other values (347) 660
70.3%
ValueCountFrequency (%)
20150827 1
0.1%
20170203 1
0.1%
20170224 1
0.1%
20170519 1
0.1%
20170608 1
0.1%
20170616 1
0.1%
20170912 1
0.1%
20171002 1
0.1%
20171011 1
0.1%
20171020 1
0.1%
ValueCountFrequency (%)
20230927 4
 
0.4%
20230926 9
 
1.0%
20230925 21
2.2%
20230922 13
 
1.4%
20230921 26
2.8%
20230920 25
2.7%
20230919 29
3.1%
20230918 44
4.7%
20230917 1
 
0.1%
20230915 19
2.0%

놀이시설 안전검사 대상여부
Boolean

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
True
673 
False
266 
ValueCountFrequency (%)
True 673
71.7%
False 266
 
28.3%
2024-03-13T15:15:14.862740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

놀이시설 안전검사 점검일자
Real number (ℝ)

MISSING 

Distinct389
Distinct (%)57.8%
Missing266
Missing (%)28.3%
Infinite0
Infinite (%)0.0%
Mean20220751
Minimum20170412
Maximum20230929
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:14.958302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20170412
5-th percentile20180873
Q120220324
median20230206
Q320230802
95-th percentile20230913
Maximum20230929
Range60517
Interquartile range (IQR)10478

Descriptive statistics

Standard deviation15092.503
Coefficient of variation (CV)0.00074638687
Kurtosis2.9296322
Mean20220751
Median Absolute Deviation (MAD)714
Skewness-1.8994469
Sum1.3608565 × 1010
Variance2.2778364 × 108
MonotonicityNot monotonic
2024-03-13T15:15:15.116971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230904 42
 
4.5%
20230914 11
 
1.2%
20230905 9
 
1.0%
20230831 8
 
0.9%
20230901 7
 
0.7%
20230906 7
 
0.7%
20220817 6
 
0.6%
20230720 6
 
0.6%
20230828 6
 
0.6%
20230817 6
 
0.6%
Other values (379) 565
60.2%
(Missing) 266
28.3%
ValueCountFrequency (%)
20170412 1
0.1%
20170421 1
0.1%
20170724 1
0.1%
20170817 1
0.1%
20170818 1
0.1%
20170905 1
0.1%
20170906 1
0.1%
20170912 1
0.1%
20170913 1
0.1%
20170914 1
0.1%
ValueCountFrequency (%)
20230929 1
 
0.1%
20230926 2
 
0.2%
20230925 2
 
0.2%
20230923 1
 
0.1%
20230922 2
 
0.2%
20230921 5
0.5%
20230920 3
 
0.3%
20230919 1
 
0.1%
20230918 3
 
0.3%
20230914 11
1.2%

놀이시설 안전검사 점검결과
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
적합
673 
-
266 

Length

Max length2
Median length2
Mean length1.7167199
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row적합
2nd row적합
3rd row적합
4th row-
5th row적합

Common Values

ValueCountFrequency (%)
적합 673
71.7%
- 266
 
28.3%

Length

2024-03-13T15:15:15.255920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T15:15:15.351087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
적합 673
71.7%
266
 
28.3%

CCTV 설치여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
True
934 
False
 
5
ValueCountFrequency (%)
True 934
99.5%
False 5
 
0.5%
2024-03-13T15:15:15.448915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

CCTV 총 설치수
Real number (ℝ)

Distinct56
Distinct (%)6.0%
Missing5
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean16.679872
Minimum1
Maximum103
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:15.556223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q19
median15.5
Q321
95-th percentile34.35
Maximum103
Range102
Interquartile range (IQR)12

Descriptive statistics

Standard deviation10.462677
Coefficient of variation (CV)0.62726365
Kurtosis8.9171901
Mean16.679872
Median Absolute Deviation (MAD)6.5
Skewness2.0155137
Sum15579
Variance109.46761
MonotonicityNot monotonic
2024-03-13T15:15:15.695647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16 131
 
14.0%
8 74
 
7.9%
10 46
 
4.9%
15 45
 
4.8%
4 42
 
4.5%
14 37
 
3.9%
13 36
 
3.8%
9 33
 
3.5%
7 32
 
3.4%
20 31
 
3.3%
Other values (46) 427
45.5%
ValueCountFrequency (%)
1 2
 
0.2%
2 5
 
0.5%
3 11
 
1.2%
4 42
4.5%
5 20
 
2.1%
6 27
 
2.9%
7 32
3.4%
8 74
7.9%
9 33
3.5%
10 46
4.9%
ValueCountFrequency (%)
103 1
 
0.1%
90 1
 
0.1%
64 2
 
0.2%
63 1
 
0.1%
61 1
 
0.1%
58 1
 
0.1%
56 1
 
0.1%
53 1
 
0.1%
50 1
 
0.1%
48 5
0.5%

CCTV 건물 안 설치수
Real number (ℝ)

ZEROS 

Distinct46
Distinct (%)4.9%
Missing3
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean11.133547
Minimum0
Maximum79
Zeros25
Zeros (%)2.7%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:15.844177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q16
median10
Q314
95-th percentile25
Maximum79
Range79
Interquartile range (IQR)8

Descriptive statistics

Standard deviation8.262298
Coefficient of variation (CV)0.74210833
Kurtosis11.357087
Mean11.133547
Median Absolute Deviation (MAD)4
Skewness2.2824354
Sum10421
Variance68.265569
MonotonicityNot monotonic
2024-03-13T15:15:16.276735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
8 69
 
7.3%
6 69
 
7.3%
7 65
 
6.9%
13 63
 
6.7%
14 57
 
6.1%
5 54
 
5.8%
12 51
 
5.4%
4 47
 
5.0%
3 44
 
4.7%
10 43
 
4.6%
Other values (36) 374
39.8%
ValueCountFrequency (%)
0 25
 
2.7%
1 16
 
1.7%
2 36
3.8%
3 44
4.7%
4 47
5.0%
5 54
5.8%
6 69
7.3%
7 65
6.9%
8 69
7.3%
9 38
4.0%
ValueCountFrequency (%)
79 1
 
0.1%
78 1
 
0.1%
58 1
 
0.1%
50 1
 
0.1%
46 1
 
0.1%
43 1
 
0.1%
41 1
 
0.1%
40 3
0.3%
39 1
 
0.1%
38 2
0.2%

CCTV 건물 밖 설치수
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)3.4%
Missing6
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean5.528403
Minimum0
Maximum33
Zeros60
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:16.399941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q37
95-th percentile18
Maximum33
Range33
Interquartile range (IQR)5

Descriptive statistics

Standard deviation5.5945346
Coefficient of variation (CV)1.0119621
Kurtosis2.8993964
Mean5.528403
Median Absolute Deviation (MAD)2
Skewness1.7509478
Sum5158
Variance31.298817
MonotonicityNot monotonic
2024-03-13T15:15:16.524366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
2 167
17.8%
3 146
15.5%
4 115
12.2%
1 101
10.8%
0 60
 
6.4%
5 45
 
4.8%
6 43
 
4.6%
7 36
 
3.8%
8 35
 
3.7%
9 20
 
2.1%
Other values (22) 165
17.6%
ValueCountFrequency (%)
0 60
 
6.4%
1 101
10.8%
2 167
17.8%
3 146
15.5%
4 115
12.2%
5 45
 
4.8%
6 43
 
4.6%
7 36
 
3.8%
8 35
 
3.7%
9 20
 
2.1%
ValueCountFrequency (%)
33 1
 
0.1%
30 1
 
0.1%
29 1
 
0.1%
28 1
 
0.1%
27 1
 
0.1%
26 4
0.4%
25 1
 
0.1%
24 3
0.3%
23 2
0.2%
22 4
0.4%

공시차수
Real number (ℝ)

Distinct11
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20224.855
Minimum20182
Maximum20232
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.4 KiB
2024-03-13T15:15:16.636368image/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 deviation15.460049
Coefficient of variation (CV)0.00076440839
Kurtosis2.04989
Mean20224.855
Median Absolute Deviation (MAD)0
Skewness-1.9195254
Sum18991139
Variance239.01312
MonotonicityNot monotonic
2024-03-13T15:15:16.746349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
20232 750
79.9%
20182 57
 
6.1%
20192 51
 
5.4%
20202 30
 
3.2%
20212 23
 
2.4%
20222 19
 
2.0%
20191 5
 
0.5%
20211 1
 
0.1%
20221 1
 
0.1%
20231 1
 
0.1%
ValueCountFrequency (%)
20182 57
6.1%
20191 5
 
0.5%
20192 51
5.4%
20201 1
 
0.1%
20202 30
3.2%
20211 1
 
0.1%
20212 23
2.4%
20221 1
 
0.1%
20222 19
 
2.0%
20231 1
 
0.1%
ValueCountFrequency (%)
20232 750
79.9%
20231 1
 
0.1%
20222 19
 
2.0%
20221 1
 
0.1%
20212 23
 
2.4%
20211 1
 
0.1%
20202 30
 
3.2%
20201 1
 
0.1%
20192 51
 
5.4%
20191 5
 
0.5%

주소
Text

Distinct916
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size7.5 KiB
2024-03-13T15:15:17.046463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length18.766773
Min length15

Characters and Unicode

Total characters17622
Distinct characters255
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

Unique894 ?
Unique (%)95.2%

Sample

1st row서울특별시 금천구 독산로78다길 89
2nd row서울특별시 송파구 오금로24길 25
3rd row서울특별시 송파구 새말로8길 22-5
4th row서울특별시 중랑구 봉화산로 188
5th row서울특별시 중랑구 동일로149길 46
ValueCountFrequency (%)
서울특별시 938
25.0%
노원구 78
 
2.1%
강서구 61
 
1.6%
송파구 60
 
1.6%
성북구 53
 
1.4%
은평구 50
 
1.3%
양천구 48
 
1.3%
강남구 43
 
1.1%
영등포구 42
 
1.1%
관악구 39
 
1.0%
Other values (1123) 2344
62.4%
2024-03-13T15:15:17.482503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2817
16.0%
서 1102
 
6.3%
구 991
 
5.6%
시 951
 
5.4%
로 943
 
5.4%
울 941
 
5.3%
별 938
 
5.3%
특 938
 
5.3%
1 678
 
3.8%
길 605
 
3.4%
Other values (245) 6718
38.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11429
64.9%
Decimal Number 3275
 
18.6%
Space Separator 2817
 
16.0%
Dash Punctuation 101
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 1102
 
9.6%
구 991
 
8.7%
시 951
 
8.3%
로 943
 
8.3%
울 941
 
8.2%
별 938
 
8.2%
특 938
 
8.2%
길 605
 
5.3%
동 231
 
2.0%
강 181
 
1.6%
Other values (233) 3608
31.6%
Decimal Number
ValueCountFrequency (%)
1 678
20.7%
2 482
14.7%
3 378
11.5%
4 331
10.1%
5 306
9.3%
6 280
8.5%
7 223
 
6.8%
0 210
 
6.4%
8 195
 
6.0%
9 192
 
5.9%
Space Separator
ValueCountFrequency (%)
2817
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11429
64.9%
Common 6193
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 1102
 
9.6%
구 991
 
8.7%
시 951
 
8.3%
로 943
 
8.3%
울 941
 
8.2%
별 938
 
8.2%
특 938
 
8.2%
길 605
 
5.3%
동 231
 
2.0%
강 181
 
1.6%
Other values (233) 3608
31.6%
Common
ValueCountFrequency (%)
2817
45.5%
1 678
 
10.9%
2 482
 
7.8%
3 378
 
6.1%
4 331
 
5.3%
5 306
 
4.9%
6 280
 
4.5%
7 223
 
3.6%
0 210
 
3.4%
8 195
 
3.1%
Other values (2) 293
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11429
64.9%
ASCII 6193
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2817
45.5%
1 678
 
10.9%
2 482
 
7.8%
3 378
 
6.1%
4 331
 
5.3%
5 306
 
4.9%
6 280
 
4.5%
7 223
 
3.6%
0 210
 
3.4%
8 195
 
3.1%
Other values (2) 293
 
4.7%
Hangul
ValueCountFrequency (%)
서 1102
 
9.6%
구 991
 
8.7%
시 951
 
8.3%
로 943
 
8.3%
울 941
 
8.2%
별 938
 
8.2%
특 938
 
8.2%
길 605
 
5.3%
동 231
 
2.0%
강 181
 
1.6%
Other values (233) 3608
31.6%

Sample

교육청명교육지원청명유치원코드유치원명설립유형소방대피훈련여부소방대피훈련일자가스점검여부가스점검일자소방안전점검여부소방안전점검일자전기설비점검여부전기설비점검일자놀이시설 안전검사 대상여부놀이시설 안전검사 점검일자놀이시설 안전검사 점검결과CCTV 설치여부CCTV 총 설치수CCTV 건물 안 설치수CCTV 건물 밖 설치수공시차수주소
0서울특별시교육청남부교육지원청006b5238-ce41-4471-9ee3-4df8d24b5141서울정심초등학교병설유치원공립(병설)Y20230428Y20230904Y20230918Y20230920Y20230222적합Y48341420232서울특별시 금천구 독산로78다길 89
1서울특별시교육청강동송파교육지원청009c017d-43bd-4d9f-ac64-d217abdd570e서울솔방울유치원공립(단설)Y20230908Y20230304Y20230307Y20230309Y20230427적합Y2014620232서울특별시 송파구 오금로24길 25
2서울특별시교육청강동송파교육지원청04a021da-cdd7-4e7e-a434-2b388c2f6b63란키즈유치원사립(사인)Y20230925Y20230309Y20230303Y20230215Y20230328적합Y128420232서울특별시 송파구 새말로8길 22-5
3서울특별시교육청동부교육지원청0764f8c8-364c-495b-9fbc-b389148b7b4f서울신현초등학교병설유치원공립(병설)Y20230912Y20230823Y20230823Y20230823N<NA>-Y85320232서울특별시 중랑구 봉화산로 188
4서울특별시교육청동부교육지원청076db651-036b-4bee-80ba-09f0edb4a57a서울신묵초등학교병설유치원공립(병설)Y20230920Y20230823Y20230809Y20230823Y20220330적합Y86220232서울특별시 중랑구 동일로149길 46
5서울특별시교육청서부교육지원청0783b5eb-4c00-4161-9c47-664336825e5a다우림유치원사립(사인)Y20220621Y20211119Y20220916Y20220816N<NA>-Y33020222서울특별시 은평구 증산로21길 22
6서울특별시교육청서부교육지원청08d485cb-06c8-4964-bf03-ed1b178ef3fd서울소의초등학교병설유치원공립(병설)Y20230904X<NA>Y20230828Y20230906Y20230324적합Y64382620232서울특별시 마포구 마포대로24길 42
7서울특별시교육청북부교육지원청0c4bc461-9f36-4d28-94e3-3dfb9c6cd4e3서울상계초등학교병설유치원공립(병설)Y20230906Y20230725Y20230905Y20230914Y20221013적합Y63320232서울특별시 노원구 상계로9길 39
8서울특별시교육청강동송파교육지원청0f7d2827-8bb2-4a0c-9926-77fca1f60a54서울송파위례유치원공립(단설)Y20230710Y20230214Y20230807Y20230905N<NA>-Y66020232서울특별시 송파구 위례송파로 121
9서울특별시교육청북부교육지원청12c109c2-23b7-4e98-a3e1-57e391f3a55a서울월천초등학교병설유치원공립(병설)Y20230623Y20230905Y20230911Y20230918N<NA>-Y2021820232서울특별시 도봉구 노해로70길 96
교육청명교육지원청명유치원코드유치원명설립유형소방대피훈련여부소방대피훈련일자가스점검여부가스점검일자소방안전점검여부소방안전점검일자전기설비점검여부전기설비점검일자놀이시설 안전검사 대상여부놀이시설 안전검사 점검일자놀이시설 안전검사 점검결과CCTV 설치여부CCTV 총 설치수CCTV 건물 안 설치수CCTV 건물 밖 설치수공시차수주소
929서울특별시교육청동작관악교육지원청ea0748a1-62aa-47ee-abcf-784398d6646d서울신림초등학교병설유치원공립(병설)Y20230510Y20221129Y20230911Y20230920Y20230314적합Y2291320232서울특별시 관악구 문성로28길 31
930서울특별시교육청서부교육지원청eb8cde61-5718-4f14-ab59-7df432e254ee서울한서초등학교병설유치원공립(병설)Y20230904Y20230802Y20230802Y20230802Y20230802적합Y2719820232서울특별시 마포구 대흥로24바길 27
931서울특별시교육청동부교육지원청f10d3393-f828-460a-a5ed-0a134f8ddd34라온유치원사립(사인)Y20230907Y20230831Y20230831Y20230831Y20230831적합Y138520232서울특별시 동대문구 답십리로48길 56
932서울특별시교육청북부교육지원청f989a1f7-1610-4bc9-8ead-ddb5fdfdfe1e서울태릉초등학교병설유치원공립(병설)Y20230426Y20230323Y20230913Y20230911Y20230904적합Y2091120232서울특별시 노원구 노원로1길 36
933서울특별시교육청성동광진교육지원청f9b5d3fc-3b2c-4803-b37a-481ad5a11f4b서울무학초등학교병설유치원공립(병설)Y20230921Y20230901Y20230901Y20230724Y20221128적합Y1714320232서울특별시 성동구 무학봉15길 21
934서울특별시교육청강동송파교육지원청fa8ca68f-3afc-4cf1-9118-70174aec112e서울강솔초등학교병설유치원공립(병설)N<NA>Y20190117Y20190809Y20190903Y20190329적합Y31211020192서울특별시 강동구 고덕로97길 80
935서울특별시교육청강남서초교육지원청fccf9482-0b1c-4f4b-a7e7-cffe7f40b07b서울학동초등학교병설유치원공립(병설)Y20230913Y20221031Y20230915Y20230913Y20221118적합Y127520232서울특별시 강남구 선릉로115길 42
936서울특별시교육청강서양천교육지원청fd885965-9f40-46c1-879e-82acd096a57e서울가양초등학교병설유치원공립(병설)Y20230823Y20230816Y20230818Y20230925Y20200723적합Y156920232서울특별시 강서구 허준로 186
937서울특별시교육청강동송파교육지원청fd8c9e02-86d2-48a2-a655-ca442ef5cde8서울송파초등학교병설유치원공립(병설)N<NA>Y20230131Y20230908Y20230920Y20230828적합Y2131820232서울특별시 송파구 백제고분로 400
938서울특별시교육청강서양천교육지원청fe178e0b-2595-4d65-863b-0d8924203e02서울등명초등학교병설유치원공립(병설)Y20230905Y20230525Y20230905Y20230918Y20230720적합Y189920232서울특별시 강서구 강서로56나길 34