Overview

Dataset statistics

Number of variables7
Number of observations263
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.8 KiB
Average record size in memory57.5 B

Variable types

Numeric1
Categorical3
Text3

Dataset

Description2020년 전국 학력인정제도 프로그램 운영 기관 현황
Author국가평생교육진흥원
URLhttps://www.data.go.kr/data/15052840/fileData.do

Alerts

연번 is highly overall correlated with 광역High correlation
광역 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique
기관명 has unique valuesUnique
기관주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:15:32.926478
Analysis finished2023-12-12 06:15:33.668494
Duration0.74 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct263
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean132
Minimum1
Maximum263
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.4 KiB
2023-12-12T15:15:33.746566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile14.1
Q166.5
median132
Q3197.5
95-th percentile249.9
Maximum263
Range262
Interquartile range (IQR)131

Descriptive statistics

Standard deviation76.065761
Coefficient of variation (CV)0.57625577
Kurtosis-1.2
Mean132
Median Absolute Deviation (MAD)66
Skewness0
Sum34716
Variance5786
MonotonicityStrictly increasing
2023-12-12T15:15:33.922099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
182 1
 
0.4%
168 1
 
0.4%
169 1
 
0.4%
170 1
 
0.4%
171 1
 
0.4%
172 1
 
0.4%
173 1
 
0.4%
174 1
 
0.4%
175 1
 
0.4%
Other values (253) 253
96.2%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
263 1
0.4%
262 1
0.4%
261 1
0.4%
260 1
0.4%
259 1
0.4%
258 1
0.4%
257 1
0.4%
256 1
0.4%
255 1
0.4%
254 1
0.4%

광역
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
서울
60 
경기
54 
충남
25 
강원
18 
부산
15 
Other values (11)
91 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
서울 60
22.8%
경기 54
20.5%
충남 25
9.5%
강원 18
 
6.8%
부산 15
 
5.7%
전북 15
 
5.7%
전남 15
 
5.7%
경남 13
 
4.9%
경북 12
 
4.6%
광주 9
 
3.4%
Other values (6) 27
10.3%

Length

2023-12-12T15:15:34.057712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 60
22.8%
경기 54
20.5%
충남 25
9.5%
강원 18
 
6.8%
부산 15
 
5.7%
전북 15
 
5.7%
전남 15
 
5.7%
경남 13
 
4.9%
경북 12
 
4.6%
광주 9
 
3.4%
Other values (6) 27
10.3%

유형(설치, 지정)
Categorical

Distinct2
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
지정
226 
설치
37 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row지정
2nd row설치
3rd row설치
4th row지정
5th row설치

Common Values

ValueCountFrequency (%)
지정 226
85.9%
설치 37
 
14.1%

Length

2023-12-12T15:15:34.160235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:15:34.258207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정 226
85.9%
설치 37
 
14.1%

운영과정(초등,중학,초/중)
Categorical

Distinct3
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
초등
183 
초/중
67 
중학
 
13

Length

Max length3
Median length2
Mean length2.2547529
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row초등
2nd row초등
3rd row초등
4th row초/중
5th row초등

Common Values

ValueCountFrequency (%)
초등 183
69.6%
초/중 67
 
25.5%
중학 13
 
4.9%

Length

2023-12-12T15:15:34.362537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:15:34.467044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
초등 183
69.6%
초/중 67
 
25.5%
중학 13
 
4.9%

기관명
Text

UNIQUE 

Distinct263
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T15:15:34.696225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length14
Mean length8.0874525
Min length4

Characters and Unicode

Total characters2127
Distinct characters244
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique263 ?
Unique (%)100.0%

Sample

1st row대청종합사회복지관
2nd row서울대현초등학교
3rd row서울영희초등학교
4th row고덕평생학습관
5th row서울대명초등학교
ValueCountFrequency (%)
대청종합사회복지관 1
 
0.4%
아산시평생학습문화센터 1
 
0.4%
춘천교육문화관 1
 
0.4%
평창군(차항1리노인회관 1
 
0.4%
평창군(대관령도서관 1
 
0.4%
평창군(백옥포1리노인회관 1
 
0.4%
홍천군(연봉도서관 1
 
0.4%
횡성군(치악산작은도서관 1
 
0.4%
횡성군(둔내태성도서관 1
 
0.4%
횡성군(군립도서관 1
 
0.4%
Other values (253) 253
96.2%
2023-12-12T15:15:35.086701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 127
 
6.0%
학 109
 
5.1%
관 104
 
4.9%
서 61
 
2.9%
평 54
 
2.5%
시 48
 
2.3%
생 48
 
2.3%
도 47
 
2.2%
지 47
 
2.2%
복 46
 
2.2%
Other values (234) 1436
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2078
97.7%
Open Punctuation 19
 
0.9%
Close Punctuation 19
 
0.9%
Decimal Number 7
 
0.3%
Uppercase Letter 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 127
 
6.1%
학 109
 
5.2%
관 104
 
5.0%
서 61
 
2.9%
평 54
 
2.6%
시 48
 
2.3%
생 48
 
2.3%
도 47
 
2.3%
지 47
 
2.3%
복 46
 
2.2%
Other values (224) 1387
66.7%
Decimal Number
ValueCountFrequency (%)
1 4
57.1%
2 1
 
14.3%
3 1
 
14.3%
5 1
 
14.3%
Uppercase Letter
ValueCountFrequency (%)
Y 1
25.0%
M 1
25.0%
C 1
25.0%
A 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2078
97.7%
Common 45
 
2.1%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 127
 
6.1%
학 109
 
5.2%
관 104
 
5.0%
서 61
 
2.9%
평 54
 
2.6%
시 48
 
2.3%
생 48
 
2.3%
도 47
 
2.3%
지 47
 
2.3%
복 46
 
2.2%
Other values (224) 1387
66.7%
Common
ValueCountFrequency (%)
( 19
42.2%
) 19
42.2%
1 4
 
8.9%
2 1
 
2.2%
3 1
 
2.2%
5 1
 
2.2%
Latin
ValueCountFrequency (%)
Y 1
25.0%
M 1
25.0%
C 1
25.0%
A 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2078
97.7%
ASCII 49
 
2.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 127
 
6.1%
학 109
 
5.2%
관 104
 
5.0%
서 61
 
2.9%
평 54
 
2.6%
시 48
 
2.3%
생 48
 
2.3%
도 47
 
2.3%
지 47
 
2.3%
복 46
 
2.2%
Other values (224) 1387
66.7%
ASCII
ValueCountFrequency (%)
( 19
38.8%
) 19
38.8%
1 4
 
8.2%
Y 1
 
2.0%
2 1
 
2.0%
M 1
 
2.0%
C 1
 
2.0%
A 1
 
2.0%
3 1
 
2.0%
5 1
 
2.0%

기관주소
Text

UNIQUE 

Distinct263
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T15:15:35.423215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length36
Mean length21.079848
Min length14

Characters and Unicode

Total characters5544
Distinct characters265
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique263 ?
Unique (%)100.0%

Sample

1st row서울특별시 강남구 양재대로55길 10
2nd row서울특별시 강남구 역삼로 98길 16
3rd row서울특별시 강남구 일원로 21
4th row서울특별시 강동구 고덕로 295
5th row서울특별시 강동구 상암로 271
ValueCountFrequency (%)
서울특별시 60
 
4.8%
경기도 54
 
4.3%
충청남도 25
 
2.0%
강원도 18
 
1.4%
전라북도 15
 
1.2%
부산광역시 15
 
1.2%
전라남도 15
 
1.2%
경상남도 13
 
1.0%
경상북도 12
 
1.0%
중앙로 10
 
0.8%
Other values (722) 1008
81.0%
2023-12-12T15:15:35.955967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1082
 
19.5%
시 221
 
4.0%
로 215
 
3.9%
1 178
 
3.2%
도 174
 
3.1%
구 144
 
2.6%
2 135
 
2.4%
길 127
 
2.3%
3 121
 
2.2%
남 98
 
1.8%
Other values (255) 3049
55.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3453
62.3%
Space Separator 1082
 
19.5%
Decimal Number 894
 
16.1%
Dash Punctuation 37
 
0.7%
Other Punctuation 25
 
0.5%
Close Punctuation 25
 
0.5%
Open Punctuation 25
 
0.5%
Math Symbol 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 221
 
6.4%
로 215
 
6.2%
도 174
 
5.0%
구 144
 
4.2%
길 127
 
3.7%
남 98
 
2.8%
경 87
 
2.5%
서 84
 
2.4%
산 75
 
2.2%
동 71
 
2.1%
Other values (238) 2157
62.5%
Decimal Number
ValueCountFrequency (%)
1 178
19.9%
2 135
15.1%
3 121
13.5%
4 82
9.2%
5 74
8.3%
6 65
 
7.3%
0 63
 
7.0%
7 63
 
7.0%
9 59
 
6.6%
8 54
 
6.0%
Space Separator
ValueCountFrequency (%)
1082
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Other Punctuation
ValueCountFrequency (%)
, 25
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3453
62.3%
Common 2090
37.7%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 221
 
6.4%
로 215
 
6.2%
도 174
 
5.0%
구 144
 
4.2%
길 127
 
3.7%
남 98
 
2.8%
경 87
 
2.5%
서 84
 
2.4%
산 75
 
2.2%
동 71
 
2.1%
Other values (238) 2157
62.5%
Common
ValueCountFrequency (%)
1082
51.8%
1 178
 
8.5%
2 135
 
6.5%
3 121
 
5.8%
4 82
 
3.9%
5 74
 
3.5%
6 65
 
3.1%
0 63
 
3.0%
7 63
 
3.0%
9 59
 
2.8%
Other values (6) 168
 
8.0%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3453
62.3%
ASCII 2091
37.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1082
51.7%
1 178
 
8.5%
2 135
 
6.5%
3 121
 
5.8%
4 82
 
3.9%
5 74
 
3.5%
6 65
 
3.1%
0 63
 
3.0%
7 63
 
3.0%
9 59
 
2.8%
Other values (7) 169
 
8.1%
Hangul
ValueCountFrequency (%)
시 221
 
6.4%
로 215
 
6.2%
도 174
 
5.0%
구 144
 
4.2%
길 127
 
3.7%
남 98
 
2.8%
경 87
 
2.5%
서 84
 
2.4%
산 75
 
2.2%
동 71
 
2.1%
Other values (238) 2157
62.5%

기관 연락처
Text

Distinct255
Distinct (%)97.0%
Missing0
Missing (%)0.0%
Memory size2.2 KiB
2023-12-12T15:15:36.202904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12.205323
Min length1

Characters and Unicode

Total characters3210
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique249 ?
Unique (%)94.7%

Sample

1st row02-459-6332
2nd row02-553-6922
3rd row02-2226-6016
4th row02-6902-2622
5th row02-481-7871
ValueCountFrequency (%)
033-340-2077 3
 
1.1%
033-330-2084 3
 
1.1%
033-460-2022 2
 
0.8%
033-560-2186 2
 
0.8%
063-540-3937 2
 
0.8%
041-730-7716 2
 
0.8%
043-879-0430 1
 
0.4%
033-258-2515 1
 
0.4%
033-430-2416 1
 
0.4%
043-852-3858 1
 
0.4%
Other values (248) 248
93.2%
2023-12-12T15:15:36.565067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 522
16.3%
0 496
15.5%
3 330
10.3%
2 296
9.2%
5 254
7.9%
1 251
7.8%
4 247
7.7%
6 204
 
6.4%
7 194
 
6.0%
8 172
 
5.4%
Other values (4) 244
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2595
80.8%
Dash Punctuation 522
 
16.3%
Space Separator 91
 
2.8%
Math Symbol 1
 
< 0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 496
19.1%
3 330
12.7%
2 296
11.4%
5 254
9.8%
1 251
9.7%
4 247
9.5%
6 204
7.9%
7 194
 
7.5%
8 172
 
6.6%
9 151
 
5.8%
Dash Punctuation
ValueCountFrequency (%)
- 522
100.0%
Space Separator
ValueCountFrequency (%)
91
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3210
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 522
16.3%
0 496
15.5%
3 330
10.3%
2 296
9.2%
5 254
7.9%
1 251
7.8%
4 247
7.7%
6 204
 
6.4%
7 194
 
6.0%
8 172
 
5.4%
Other values (4) 244
7.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3210
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 522
16.3%
0 496
15.5%
3 330
10.3%
2 296
9.2%
5 254
7.9%
1 251
7.8%
4 247
7.7%
6 204
 
6.4%
7 194
 
6.0%
8 172
 
5.4%
Other values (4) 244
7.6%

Interactions

2023-12-12T15:15:33.355031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:15:36.670578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번광역유형(설치, 지정)운영과정(초등,중학,초/중)
연번1.0000.9570.3210.000
광역0.9571.0000.3300.378
유형(설치, 지정)0.3210.3301.0000.125
운영과정(초등,중학,초/중)0.0000.3780.1251.000
2023-12-12T15:15:36.755842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운영과정(초등,중학,초/중)광역유형(설치, 지정)
운영과정(초등,중학,초/중)1.0000.2170.206
광역0.2171.0000.252
유형(설치, 지정)0.2060.2521.000
2023-12-12T15:15:36.846162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번광역유형(설치, 지정)운영과정(초등,중학,초/중)
연번1.0000.8010.2420.000
광역0.8011.0000.2520.217
유형(설치, 지정)0.2420.2521.0000.206
운영과정(초등,중학,초/중)0.0000.2170.2061.000

Missing values

2023-12-12T15:15:33.479594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:15:33.619958image/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

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01서울지정초등대청종합사회복지관서울특별시 강남구 양재대로55길 1002-459-6332
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23서울설치초등서울영희초등학교서울특별시 강남구 일원로 2102-2226-6016
34서울지정초/중고덕평생학습관서울특별시 강동구 고덕로 29502-6902-2622
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78서울지정초등번동2단지종합사회복지관서울특별시 강북구 한천로 105길 24 202동02-987-5077
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262263제주지정초/중동려평생학교제주특별자치도 제주시 광양4길 30-1064-752-6381