Overview

Dataset statistics

Number of variables15
Number of observations34
Missing cells55
Missing cells (%)10.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.3 KiB
Average record size in memory130.9 B

Variable types

Categorical5
Text3
Numeric5
Boolean2

Dataset

Description교육청명,교육지원청명,유치원코드,유치원명,실립유형,3세 수업일수,4세 수업일수,5세 수업일수,혼합연령수업일수,특수학급수업일수,방과후 과정수업일수,법정일수이하여부,신설유치원여부,공시차수,주소
Author동대문구
URLhttps://data.seoul.go.kr/dataList/OA-20684/S/1/datasetView.do

Alerts

교육청명 has constant value ""Constant
교육지원청명 has constant value ""Constant
신설유치원여부 has constant value ""Constant
공시차수 is highly overall correlated with 4세 수업일수 and 4 other fieldsHigh correlation
특수학급수업일수 is highly overall correlated with 3세 수업일수 and 5 other fieldsHigh correlation
법정일수이하여부 is highly overall correlated with 3세 수업일수 and 5 other fieldsHigh correlation
3세 수업일수 is highly overall correlated with 4세 수업일수 and 5 other fieldsHigh correlation
4세 수업일수 is highly overall correlated with 3세 수업일수 and 5 other fieldsHigh correlation
5세 수업일수 is highly overall correlated with 3세 수업일수 and 6 other fieldsHigh correlation
혼합연령수업일수 is highly overall correlated with 3세 수업일수 and 2 other fieldsHigh correlation
방과후 과정수업일수 is highly overall correlated with 혼합연령수업일수 and 3 other fieldsHigh correlation
실립유형 is highly overall correlated with 3세 수업일수 and 2 other fieldsHigh correlation
특수학급수업일수 is highly imbalanced (67.7%)Imbalance
법정일수이하여부 is highly imbalanced (52.0%)Imbalance
3세 수업일수 has 4 (11.8%) missing valuesMissing
4세 수업일수 has 7 (20.6%) missing valuesMissing
5세 수업일수 has 5 (14.7%) missing valuesMissing
혼합연령수업일수 has 27 (79.4%) missing valuesMissing
법정일수이하여부 has 5 (14.7%) missing valuesMissing
신설유치원여부 has 7 (20.6%) missing valuesMissing
유치원코드 has unique valuesUnique
유치원명 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2024-03-13 15:45:18.262175
Analysis finished2024-03-13 15:45:21.372534
Duration3.11 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

교육청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
서울특별시교육청
34 

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 34
100.0%

Length

2024-03-14T00:45:21.429765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T00:45:21.533225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시교육청 34
100.0%

교육지원청명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
동부교육지원청
34 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
동부교육지원청 34
100.0%

Length

2024-03-14T00:45:21.662368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T00:45:21.751280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동부교육지원청 34
100.0%

유치원코드
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T00:45:21.925703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters1224
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

Unique34 ?
Unique (%)100.0%

Sample

1st row1ecec08c-ed83-b044-e053-0a32095ab044
2nd row1ecec08c-ee33-b044-e053-0a32095ab044
3rd row1ecec08c-efaa-b044-e053-0a32095ab044
4th row1ecec08c-f054-b044-e053-0a32095ab044
5th row1ecec08c-f1fc-b044-e053-0a32095ab044
ValueCountFrequency (%)
1ecec08c-ed83-b044-e053-0a32095ab044 1
 
2.9%
1ecec08c-ee33-b044-e053-0a32095ab044 1
 
2.9%
7e75b6b8-7dcb-4645-85e7-3656fce0c528 1
 
2.9%
663b5e8a-86f7-433a-bedd-f46a8bd1c7b1 1
 
2.9%
51d03296-c765-4e9c-900f-217f6a1d50f3 1
 
2.9%
1ecec08d-0d38-b044-e053-0a32095ab044 1
 
2.9%
1ecec08d-0ca9-b044-e053-0a32095ab044 1
 
2.9%
1ecec08d-0ca7-b044-e053-0a32095ab044 1
 
2.9%
1ecec08d-0c8c-b044-e053-0a32095ab044 1
 
2.9%
1ecec08c-fadc-b044-e053-0a32095ab044 1
 
2.9%
Other values (24) 24
70.6%
2024-03-14T00:45:22.248888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 208
17.0%
- 136
11.1%
4 131
10.7%
e 104
8.5%
c 94
7.7%
3 78
 
6.4%
5 76
 
6.2%
a 74
 
6.0%
b 71
 
5.8%
8 47
 
3.8%
Other values (7) 205
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 683
55.8%
Lowercase Letter 405
33.1%
Dash Punctuation 136
 
11.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 208
30.5%
4 131
19.2%
3 78
 
11.4%
5 76
 
11.1%
8 47
 
6.9%
1 43
 
6.3%
9 39
 
5.7%
2 35
 
5.1%
7 13
 
1.9%
6 13
 
1.9%
Lowercase Letter
ValueCountFrequency (%)
e 104
25.7%
c 94
23.2%
a 74
18.3%
b 71
17.5%
f 32
 
7.9%
d 30
 
7.4%
Dash Punctuation
ValueCountFrequency (%)
- 136
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 819
66.9%
Latin 405
33.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 208
25.4%
- 136
16.6%
4 131
16.0%
3 78
 
9.5%
5 76
 
9.3%
8 47
 
5.7%
1 43
 
5.3%
9 39
 
4.8%
2 35
 
4.3%
7 13
 
1.6%
Latin
ValueCountFrequency (%)
e 104
25.7%
c 94
23.2%
a 74
18.3%
b 71
17.5%
f 32
 
7.9%
d 30
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1224
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 208
17.0%
- 136
11.1%
4 131
10.7%
e 104
8.5%
c 94
7.7%
3 78
 
6.4%
5 76
 
6.2%
a 74
 
6.0%
b 71
 
5.8%
8 47
 
3.8%
Other values (7) 205
16.7%

유치원명
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T00:45:22.472909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length5
Mean length7
Min length5

Characters and Unicode

Total characters238
Distinct characters65
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

Unique34 ?
Unique (%)100.0%

Sample

1st row새일문유치원
2nd row백주유치원
3rd row예일유치원
4th row삼성유치원
5th row서울전동초등학교병설유치원
ValueCountFrequency (%)
새일문유치원 1
 
2.9%
백주유치원 1
 
2.9%
서울전곡초등학교병설유치원 1
 
2.9%
정원유치원 1
 
2.9%
서울이문유치원 1
 
2.9%
경희유치원 1
 
2.9%
빛나유치원 1
 
2.9%
동안유치원 1
 
2.9%
서울군자초등학교병설유치원 1
 
2.9%
서울유치원 1
 
2.9%
Other values (24) 24
70.6%
2024-03-14T00:45:22.803432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 35
14.7%
유 34
14.3%
치 34
14.3%
서 10
 
4.2%
울 10
 
4.2%
병 7
 
2.9%
설 7
 
2.9%
초 7
 
2.9%
등 7
 
2.9%
학 7
 
2.9%
Other values (55) 80
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 35
14.7%
유 34
14.3%
치 34
14.3%
서 10
 
4.2%
울 10
 
4.2%
병 7
 
2.9%
설 7
 
2.9%
초 7
 
2.9%
등 7
 
2.9%
학 7
 
2.9%
Other values (55) 80
33.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 238
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 35
14.7%
유 34
14.3%
치 34
14.3%
서 10
 
4.2%
울 10
 
4.2%
병 7
 
2.9%
설 7
 
2.9%
초 7
 
2.9%
등 7
 
2.9%
학 7
 
2.9%
Other values (55) 80
33.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 35
14.7%
유 34
14.3%
치 34
14.3%
서 10
 
4.2%
울 10
 
4.2%
병 7
 
2.9%
설 7
 
2.9%
초 7
 
2.9%
등 7
 
2.9%
학 7
 
2.9%
Other values (55) 80
33.6%

실립유형
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
사립(사인)
20 
공립(병설)
7 
사립(법인)
5 
공립(단설)
 
2

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사립(사인) 20
58.8%
공립(병설) 7
 
20.6%
사립(법인) 5
 
14.7%
공립(단설) 2
 
5.9%

Length

2024-03-14T00:45:23.267986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T00:45:23.361742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사립(사인 20
58.8%
공립(병설 7
 
20.6%
사립(법인 5
 
14.7%
공립(단설 2
 
5.9%

3세 수업일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct17
Distinct (%)56.7%
Missing4
Missing (%)11.8%
Infinite0
Infinite (%)0.0%
Mean204.3
Minimum162
Maximum237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-14T00:45:23.459337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum162
5-th percentile172.3
Q1181.25
median215
Q3219
95-th percentile228.55
Maximum237
Range75
Interquartile range (IQR)37.75

Descriptive statistics

Standard deviation21.736906
Coefficient of variation (CV)0.106397
Kurtosis-1.2697285
Mean204.3
Median Absolute Deviation (MAD)12
Skewness-0.4415994
Sum6129
Variance472.4931
MonotonicityNot monotonic
2024-03-14T00:45:23.562476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
181 4
11.8%
182 3
8.8%
215 3
8.8%
219 3
8.8%
226 2
 
5.9%
217 2
 
5.9%
225 2
 
5.9%
180 2
 
5.9%
218 1
 
2.9%
229 1
 
2.9%
Other values (7) 7
20.6%
(Missing) 4
11.8%
ValueCountFrequency (%)
162 1
 
2.9%
166 1
 
2.9%
180 2
5.9%
181 4
11.8%
182 3
8.8%
202 1
 
2.9%
209 1
 
2.9%
210 1
 
2.9%
215 3
8.8%
217 2
5.9%
ValueCountFrequency (%)
237 1
 
2.9%
229 1
 
2.9%
228 1
 
2.9%
226 2
5.9%
225 2
5.9%
219 3
8.8%
218 1
 
2.9%
217 2
5.9%
215 3
8.8%
210 1
 
2.9%

4세 수업일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct16
Distinct (%)59.3%
Missing7
Missing (%)20.6%
Infinite0
Infinite (%)0.0%
Mean202.81481
Minimum162
Maximum237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-14T00:45:23.672533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum162
5-th percentile170.2
Q1181
median215
Q3219
95-th percentile228.7
Maximum237
Range75
Interquartile range (IQR)38

Descriptive statistics

Standard deviation22.341815
Coefficient of variation (CV)0.11015869
Kurtosis-1.4346745
Mean202.81481
Median Absolute Deviation (MAD)13
Skewness-0.28791728
Sum5476
Variance499.1567
MonotonicityNot monotonic
2024-03-14T00:45:23.795819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
181 4
11.8%
182 3
8.8%
215 3
8.8%
219 3
8.8%
180 2
 
5.9%
225 2
 
5.9%
209 1
 
2.9%
228 1
 
2.9%
202 1
 
2.9%
237 1
 
2.9%
Other values (6) 6
17.6%
(Missing) 7
20.6%
ValueCountFrequency (%)
162 1
 
2.9%
166 1
 
2.9%
180 2
5.9%
181 4
11.8%
182 3
8.8%
202 1
 
2.9%
209 1
 
2.9%
215 3
8.8%
217 1
 
2.9%
218 1
 
2.9%
ValueCountFrequency (%)
237 1
 
2.9%
229 1
 
2.9%
228 1
 
2.9%
226 1
 
2.9%
225 2
5.9%
219 3
8.8%
218 1
 
2.9%
217 1
 
2.9%
215 3
8.8%
209 1
 
2.9%

5세 수업일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct19
Distinct (%)65.5%
Missing5
Missing (%)14.7%
Infinite0
Infinite (%)0.0%
Mean204
Minimum161
Maximum237
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-14T00:45:23.914345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum161
5-th percentile171.6
Q1181
median215
Q3219
95-th percentile229
Maximum237
Range76
Interquartile range (IQR)38

Descriptive statistics

Standard deviation21.996753
Coefficient of variation (CV)0.10782722
Kurtosis-1.2877744
Mean204
Median Absolute Deviation (MAD)13
Skewness-0.41835301
Sum5916
Variance483.85714
MonotonicityNot monotonic
2024-03-14T00:45:24.028030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
181 4
11.8%
219 3
 
8.8%
225 2
 
5.9%
229 2
 
5.9%
215 2
 
5.9%
180 2
 
5.9%
183 2
 
5.9%
214 1
 
2.9%
202 1
 
2.9%
237 1
 
2.9%
Other values (9) 9
26.5%
(Missing) 5
14.7%
ValueCountFrequency (%)
161 1
 
2.9%
166 1
 
2.9%
180 2
5.9%
181 4
11.8%
182 1
 
2.9%
183 2
5.9%
202 1
 
2.9%
209 1
 
2.9%
214 1
 
2.9%
215 2
5.9%
ValueCountFrequency (%)
237 1
 
2.9%
229 2
5.9%
226 1
 
2.9%
225 2
5.9%
223 1
 
2.9%
219 3
8.8%
218 1
 
2.9%
217 1
 
2.9%
216 1
 
2.9%
215 2
5.9%

혼합연령수업일수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7
Distinct (%)100.0%
Missing27
Missing (%)79.4%
Infinite0
Infinite (%)0.0%
Mean188.42857
Minimum16
Maximum226
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-14T00:45:24.144716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile74.2
Q1211.5
median214
Q3220
95-th percentile225.1
Maximum226
Range210
Interquartile range (IQR)8.5

Descriptive statistics

Standard deviation76.24272
Coefficient of variation (CV)0.40462399
Kurtosis6.8785396
Mean188.42857
Median Absolute Deviation (MAD)4
Skewness-2.615186
Sum1319
Variance5812.9524
MonotonicityNot monotonic
2024-03-14T00:45:24.259354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
213 1
 
2.9%
226 1
 
2.9%
16 1
 
2.9%
210 1
 
2.9%
214 1
 
2.9%
223 1
 
2.9%
217 1
 
2.9%
(Missing) 27
79.4%
ValueCountFrequency (%)
16 1
2.9%
210 1
2.9%
213 1
2.9%
214 1
2.9%
217 1
2.9%
223 1
2.9%
226 1
2.9%
ValueCountFrequency (%)
226 1
2.9%
223 1
2.9%
217 1
2.9%
214 1
2.9%
213 1
2.9%
210 1
2.9%
16 1
2.9%

특수학급수업일수
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
<NA>
31 
183
 
2
181
 
1

Length

Max length4
Median length4
Mean length3.9117647
Min length3

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row181

Common Values

ValueCountFrequency (%)
<NA> 31
91.2%
183 2
 
5.9%
181 1
 
2.9%

Length

2024-03-14T00:45:24.358973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T00:45:24.453961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 31
91.2%
183 2
 
5.9%
181 1
 
2.9%

방과후 과정수업일수
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean231.32353
Minimum16
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2024-03-14T00:45:24.542674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16
5-th percentile187.6
Q1233
median237
Q3249
95-th percentile250
Maximum300
Range284
Interquartile range (IQR)16

Descriptive statistics

Standard deviation42.432635
Coefficient of variation (CV)0.18343415
Kurtosis21.161455
Mean231.32353
Median Absolute Deviation (MAD)11
Skewness-4.1173065
Sum7865
Variance1800.5285
MonotonicityNot monotonic
2024-03-14T00:45:24.638829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
250 5
14.7%
249 5
14.7%
237 3
 
8.8%
234 3
 
8.8%
233 2
 
5.9%
242 2
 
5.9%
238 1
 
2.9%
235 1
 
2.9%
247 1
 
2.9%
225 1
 
2.9%
Other values (10) 10
29.4%
ValueCountFrequency (%)
16 1
 
2.9%
185 1
 
2.9%
189 1
 
2.9%
219 1
 
2.9%
220 1
 
2.9%
225 1
 
2.9%
227 1
 
2.9%
230 1
 
2.9%
233 2
5.9%
234 3
8.8%
ValueCountFrequency (%)
300 1
 
2.9%
250 5
14.7%
249 5
14.7%
247 1
 
2.9%
242 2
 
5.9%
240 1
 
2.9%
238 1
 
2.9%
237 3
8.8%
236 1
 
2.9%
235 1
 
2.9%

법정일수이하여부
Boolean

HIGH CORRELATION  IMBALANCE  MISSING 

Distinct2
Distinct (%)6.9%
Missing5
Missing (%)14.7%
Memory size200.0 B
False
26 
True
3 
(Missing)
5 
ValueCountFrequency (%)
False 26
76.5%
True 3
 
8.8%
(Missing) 5
 
14.7%
2024-03-14T00:45:24.728683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

신설유치원여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)3.7%
Missing7
Missing (%)20.6%
Memory size200.0 B
False
27 
(Missing)
7 
ValueCountFrequency (%)
False 27
79.4%
(Missing) 7
 
20.6%
2024-03-14T00:45:24.804376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

공시차수
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
20231
27 
20191
4 
20201
 
2
20181
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row20231
2nd row20201
3rd row20231
4th row20231
5th row20231

Common Values

ValueCountFrequency (%)
20231 27
79.4%
20191 4
 
11.8%
20201 2
 
5.9%
20181 1
 
2.9%

Length

2024-03-14T00:45:24.895977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T00:45:25.047604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20231 27
79.4%
20191 4
 
11.8%
20201 2
 
5.9%
20181 1
 
2.9%

주소
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T00:45:25.280530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length19.441176
Min length17

Characters and Unicode

Total characters661
Distinct characters57
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

Unique34 ?
Unique (%)100.0%

Sample

1st row서울특별시 동대문구 장한로 165
2nd row서울특별시 동대문구 서울시립대로18길 19
3rd row서울특별시 동대문구 사가정로 190
4th row서울특별시 동대문구 사가정로 65
5th row서울특별시 동대문구 전농로16길 61
ValueCountFrequency (%)
서울특별시 34
25.0%
동대문구 34
25.0%
사가정로 4
 
2.9%
21 2
 
1.5%
20 2
 
1.5%
장안벚꽃로 2
 
1.5%
고산자로 2
 
1.5%
47 2
 
1.5%
전농로 1
 
0.7%
172 1
 
0.7%
Other values (52) 52
38.2%
2024-03-14T00:45:25.641966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
102
15.4%
대 36
 
5.4%
시 36
 
5.4%
문 36
 
5.4%
서 35
 
5.3%
울 35
 
5.3%
구 34
 
5.1%
로 34
 
5.1%
동 34
 
5.1%
별 34
 
5.1%
Other values (47) 245
37.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 446
67.5%
Decimal Number 112
 
16.9%
Space Separator 102
 
15.4%
Dash Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 36
 
8.1%
시 36
 
8.1%
문 36
 
8.1%
서 35
 
7.8%
울 35
 
7.8%
구 34
 
7.6%
로 34
 
7.6%
동 34
 
7.6%
별 34
 
7.6%
특 34
 
7.6%
Other values (35) 98
22.0%
Decimal Number
ValueCountFrequency (%)
1 21
18.8%
2 17
15.2%
6 15
13.4%
5 11
9.8%
4 10
8.9%
3 10
8.9%
7 8
 
7.1%
8 7
 
6.2%
0 7
 
6.2%
9 6
 
5.4%
Space Separator
ValueCountFrequency (%)
102
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 446
67.5%
Common 215
32.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 36
 
8.1%
시 36
 
8.1%
문 36
 
8.1%
서 35
 
7.8%
울 35
 
7.8%
구 34
 
7.6%
로 34
 
7.6%
동 34
 
7.6%
별 34
 
7.6%
특 34
 
7.6%
Other values (35) 98
22.0%
Common
ValueCountFrequency (%)
102
47.4%
1 21
 
9.8%
2 17
 
7.9%
6 15
 
7.0%
5 11
 
5.1%
4 10
 
4.7%
3 10
 
4.7%
7 8
 
3.7%
8 7
 
3.3%
0 7
 
3.3%
Other values (2) 7
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 446
67.5%
ASCII 215
32.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
102
47.4%
1 21
 
9.8%
2 17
 
7.9%
6 15
 
7.0%
5 11
 
5.1%
4 10
 
4.7%
3 10
 
4.7%
7 8
 
3.7%
8 7
 
3.3%
0 7
 
3.3%
Other values (2) 7
 
3.3%
Hangul
ValueCountFrequency (%)
대 36
 
8.1%
시 36
 
8.1%
문 36
 
8.1%
서 35
 
7.8%
울 35
 
7.8%
구 34
 
7.6%
로 34
 
7.6%
동 34
 
7.6%
별 34
 
7.6%
특 34
 
7.6%
Other values (35) 98
22.0%

Interactions

2024-03-14T00:45:20.472463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:18.739383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.220584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.681300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.103248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.582592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:18.821170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.318552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.773432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.186281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.673241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:18.906868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.429842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.863282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.263263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.783235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.006501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.526067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.955740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.330269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.850966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.121211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:19.597628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.021315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T00:45:20.393463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T00:45:25.791452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유치원코드유치원명실립유형3세 수업일수4세 수업일수5세 수업일수혼합연령수업일수특수학급수업일수방과후 과정수업일수법정일수이하여부공시차수주소
유치원코드1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
유치원명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
실립유형1.0001.0001.0000.7560.7600.7170.0000.0000.3800.0000.3331.000
3세 수업일수1.0001.0000.7561.0001.0001.000NaNNaN0.8051.0000.6141.000
4세 수업일수1.0001.0000.7601.0001.0001.000NaNNaN0.8851.0000.7181.000
5세 수업일수1.0001.0000.7171.0001.0001.000NaNNaN0.8861.0000.7551.000
혼합연령수업일수1.0001.0000.000NaNNaNNaN1.000NaN1.0000.0000.0001.000
특수학급수업일수1.0001.0000.000NaNNaNNaNNaN1.000NaNNaNNaN1.000
방과후 과정수업일수1.0001.0000.3800.8050.8850.8861.000NaN1.0001.0000.7441.000
법정일수이하여부1.0001.0000.0001.0001.0001.0000.000NaN1.0001.0000.7671.000
공시차수1.0001.0000.3330.6140.7180.7550.000NaN0.7440.7671.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2024-03-14T00:45:25.958775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공시차수실립유형특수학급수업일수법정일수이하여부
공시차수1.0000.1241.0000.556
실립유형0.1241.0000.0000.000
특수학급수업일수1.0000.0001.0001.000
법정일수이하여부0.5560.0001.0001.000
2024-03-14T00:45:26.083250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3세 수업일수4세 수업일수5세 수업일수혼합연령수업일수방과후 과정수업일수실립유형특수학급수업일수법정일수이하여부공시차수
3세 수업일수1.0001.0000.9991.0000.0500.6011.0000.8940.445
4세 수업일수1.0001.0000.999NaN-0.0050.6011.0000.8900.583
5세 수업일수0.9990.9991.0001.000-0.0320.5531.0000.8900.633
혼합연령수업일수1.000NaN1.0001.0000.6670.0000.0000.0000.000
방과후 과정수업일수0.050-0.005-0.0320.6671.0000.2351.0000.9430.558
실립유형0.6010.6010.5530.0000.2351.0000.0000.0000.124
특수학급수업일수1.0001.0001.0000.0001.0000.0001.0001.0001.000
법정일수이하여부0.8940.8900.8900.0000.9430.0001.0001.0000.556
공시차수0.4450.5830.6330.0000.5580.1241.0000.5561.000

Missing values

2024-03-14T00:45:20.959598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T00:45:21.138397image/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.
2024-03-14T00:45:21.286120image/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

교육청명교육지원청명유치원코드유치원명실립유형3세 수업일수4세 수업일수5세 수업일수혼합연령수업일수특수학급수업일수방과후 과정수업일수법정일수이하여부신설유치원여부공시차수주소
0서울특별시교육청동부교육지원청1ecec08c-ed83-b044-e053-0a32095ab044새일문유치원사립(사인)<NA><NA><NA>213<NA>250NN20231서울특별시 동대문구 장한로 165
1서울특별시교육청동부교육지원청1ecec08c-ee33-b044-e053-0a32095ab044백주유치원사립(사인)166166166<NA><NA>185Y<NA>20201서울특별시 동대문구 서울시립대로18길 19
2서울특별시교육청동부교육지원청1ecec08c-efaa-b044-e053-0a32095ab044예일유치원사립(사인)217217217<NA><NA>233NN20231서울특별시 동대문구 사가정로 190
3서울특별시교육청동부교육지원청1ecec08c-f054-b044-e053-0a32095ab044삼성유치원사립(사인)218218218<NA><NA>230NN20231서울특별시 동대문구 사가정로 65
4서울특별시교육청동부교육지원청1ecec08c-f1fc-b044-e053-0a32095ab044서울전동초등학교병설유치원공립(병설)181181181<NA>181249NN20231서울특별시 동대문구 전농로16길 61
5서울특별시교육청동부교육지원청1ecec08c-f1fd-b044-e053-0a32095ab044자람유치원사립(사인)226<NA><NA>226<NA>300<NA><NA>20191서울특별시 동대문구 고산자로 534
6서울특별시교육청동부교육지원청1ecec08c-f491-b044-e053-0a32095ab044서울휘경유치원공립(단설)182182183<NA>183250NN20231서울특별시 동대문구 망우로6길 48
7서울특별시교육청동부교육지원청1ecec08c-f895-b044-e053-0a32095ab044한양유치원사립(사인)215215216<NA><NA>237<NA><NA>20191서울특별시 동대문구 답십리로 184
8서울특별시교육청동부교육지원청1ecec08c-f8dc-b044-e053-0a32095ab044세하유치원사립(사인)229229229<NA><NA>250NN20231서울특별시 동대문구 장안벚꽃로 107
9서울특별시교육청동부교육지원청1ecec08c-fadc-b044-e053-0a32095ab044서울유치원사립(사인)162162161<NA><NA>189Y<NA>20201서울특별시 동대문구 한천로58길 47
교육청명교육지원청명유치원코드유치원명실립유형3세 수업일수4세 수업일수5세 수업일수혼합연령수업일수특수학급수업일수방과후 과정수업일수법정일수이하여부신설유치원여부공시차수주소
24서울특별시교육청동부교육지원청1ecec08d-0c05-b044-e053-0a32095ab044새소리유치원사립(사인)219219219<NA><NA>234NN20231서울특별시 동대문구 사가정로 148
25서울특별시교육청동부교육지원청1ecec08d-0c08-b044-e053-0a32095ab044서울답십리초등학교병설유치원공립(병설)182182182<NA><NA>249NN20231서울특별시 동대문구 전농로3길 23
26서울특별시교육청동부교육지원청1ecec08d-0c8c-b044-e053-0a32095ab044서울군자초등학교병설유치원공립(병설)181181181<NA><NA>247NN20231서울특별시 동대문구 한천로6길 21
27서울특별시교육청동부교육지원청1ecec08d-0ca7-b044-e053-0a32095ab044동안유치원사립(사인)237237237<NA><NA>237NN20231서울특별시 동대문구 회기로25길 67
28서울특별시교육청동부교육지원청1ecec08d-0ca9-b044-e053-0a32095ab044빛나유치원사립(법인)217<NA><NA>217<NA>242<NA><NA>20181서울특별시 동대문구 전농로23길 47
29서울특별시교육청동부교육지원청1ecec08d-0d38-b044-e053-0a32095ab044경희유치원사립(법인)202202202<NA><NA>237NN20231서울특별시 동대문구 경희대로 26
30서울특별시교육청동부교육지원청51d03296-c765-4e9c-900f-217f6a1d50f3서울이문유치원공립(단설)182182183<NA>183250NN20231서울특별시 동대문구 신이문로 16
31서울특별시교육청동부교육지원청663b5e8a-86f7-433a-bedd-f46a8bd1c7b1정원유치원사립(사인)228228229<NA><NA>235NN20231서울특별시 동대문구 사가정로 276-19
32서울특별시교육청동부교육지원청7e75b6b8-7dcb-4645-85e7-3656fce0c528서울전곡초등학교병설유치원공립(병설)181181181<NA><NA>249NN20231서울특별시 동대문구 전농로 172
33서울특별시교육청동부교육지원청f10d3393-f828-460a-a5ed-0a134f8ddd34라온유치원사립(사인)225225225<NA><NA>234NN20231서울특별시 동대문구 답십리로48길 56