Overview

Dataset statistics

Number of variables6
Number of observations1120
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory53.7 KiB
Average record size in memory49.1 B

Variable types

Categorical5
Text1

Dataset

Description전라북도 내 일반고등학교 국공립, 사립별 학생수(남, 여), 교원수(남, 여), 직원수, 졸업후상황(졸업자수, 진학자수), 입학상황(입학정원, 입학자)
URLhttps://www.data.go.kr/data/15117491/fileData.do

Alerts

학교현황별1 is highly overall correlated with 학교현황별2High correlation
학교현황별2 is highly overall correlated with 학교현황별1High correlation

Reproduction

Analysis started2023-12-12 15:12:12.666916
Analysis finished2023-12-12 15:12:13.151433
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Categorical

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
2022
336 
2019
280 
2020
252 
2021
252 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2022 336
30.0%
2019 280
25.0%
2020 252
22.5%
2021 252
22.5%

Length

2023-12-13T00:12:13.215402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:12:13.345227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 336
30.0%
2019 280
25.0%
2020 252
22.5%
2021 252
22.5%

시군별
Categorical

Distinct14
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
전주시
80 
군산시
80 
익산시
80 
정읍시
80 
남원시
80 
Other values (9)
720 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 80
 
7.1%
군산시 80
 
7.1%
익산시 80
 
7.1%
정읍시 80
 
7.1%
남원시 80
 
7.1%
김제시 80
 
7.1%
완주군 80
 
7.1%
진안군 80
 
7.1%
무주군 80
 
7.1%
장수군 80
 
7.1%
Other values (4) 320
28.6%

Length

2023-12-13T00:12:13.475945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 80
 
7.1%
군산시 80
 
7.1%
익산시 80
 
7.1%
정읍시 80
 
7.1%
남원시 80
 
7.1%
김제시 80
 
7.1%
완주군 80
 
7.1%
진안군 80
 
7.1%
무주군 80
 
7.1%
장수군 80
 
7.1%
Other values (4) 320
28.6%

종류
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
국공립
560 
사립
560 

Length

Max length3
Median length2.5
Mean length2.5
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
국공립 560
50.0%
사립 560
50.0%

Length

2023-12-13T00:12:13.623569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:12:13.742491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국공립 560
50.0%
사립 560
50.0%

학교현황별1
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
입학상황
252 
학생수
224 
교원수
224 
직원수
224 
졸업후상황
196 

Length

Max length5
Median length3
Mean length3.575
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row학생수
2nd row학생수
3rd row교원수
4th row교원수
5th row직원수

Common Values

ValueCountFrequency (%)
입학상황 252
22.5%
학생수 224
20.0%
교원수 224
20.0%
직원수 224
20.0%
졸업후상황 196
17.5%

Length

2023-12-13T00:12:13.874271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:12:14.001918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입학상황 252
22.5%
학생수 224
20.0%
교원수 224
20.0%
직원수 224
20.0%
졸업후상황 196
17.5%

학교현황별2
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
남
336 
여
336 
졸업자수
112 
입학자
112 
입학정원
84 
Other values (5)
140 

Length

Max length6
Median length1
Mean length2.25
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row남
2nd row여
3rd row남
4th row여
5th row남

Common Values

ValueCountFrequency (%)
남 336
30.0%
여 336
30.0%
졸업자수 112
 
10.0%
입학자 112
 
10.0%
입학정원 84
 
7.5%
진학자수 28
 
2.5%
졸업자수 남 28
 
2.5%
졸업자수 여 28
 
2.5%
입학자 남 28
 
2.5%
입학자 여 28
 
2.5%

Length

2023-12-13T00:12:14.183177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:12:14.331340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남 392
31.8%
여 392
31.8%
졸업자수 168
13.6%
입학자 168
13.6%
입학정원 84
 
6.8%
진학자수 28
 
2.3%

인원
Text

Distinct444
Distinct (%)39.6%
Missing0
Missing (%)0.0%
Memory size8.9 KiB
2023-12-13T00:12:14.712653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.2901786
Min length1

Characters and Unicode

Total characters2565
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique270 ?
Unique (%)24.1%

Sample

1st row3300
2nd row3257
3rd row244
4th row306
5th row40
ValueCountFrequency (%)
128
 
11.4%
2 30
 
2.7%
3 26
 
2.3%
6 22
 
2.0%
5 20
 
1.8%
4 12
 
1.1%
7 12
 
1.1%
20 11
 
1.0%
13 11
 
1.0%
14 10
 
0.9%
Other values (434) 838
74.8%
2023-12-13T00:12:15.269262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 475
18.5%
2 342
13.3%
3 280
10.9%
4 267
10.4%
6 208
8.1%
0 206
8.0%
5 202
7.9%
7 155
 
6.0%
8 155
 
6.0%
9 147
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2437
95.0%
Dash Punctuation 128
 
5.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 475
19.5%
2 342
14.0%
3 280
11.5%
4 267
11.0%
6 208
8.5%
0 206
8.5%
5 202
8.3%
7 155
 
6.4%
8 155
 
6.4%
9 147
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 128
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2565
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 475
18.5%
2 342
13.3%
3 280
10.9%
4 267
10.4%
6 208
8.1%
0 206
8.0%
5 202
7.9%
7 155
 
6.0%
8 155
 
6.0%
9 147
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2565
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 475
18.5%
2 342
13.3%
3 280
10.9%
4 267
10.4%
6 208
8.1%
0 206
8.0%
5 202
7.9%
7 155
 
6.0%
8 155
 
6.0%
9 147
 
5.7%

Correlations

2023-12-13T00:12:15.393011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시군별종류학교현황별1학교현황별2
연도1.0000.0000.0000.1010.513
시군별0.0001.0000.0000.0000.000
종류0.0000.0001.0000.0000.000
학교현황별10.1010.0000.0001.0000.953
학교현황별20.5130.0000.0000.9531.000
2023-12-13T00:12:15.497026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군별연도학교현황별2종류학교현황별1
시군별1.0000.0000.0000.0000.000
연도0.0001.0000.3310.0000.082
학교현황별20.0000.3311.0000.0000.703
종류0.0000.0000.0001.0000.000
학교현황별10.0000.0820.7030.0001.000
2023-12-13T00:12:15.613820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도시군별종류학교현황별1학교현황별2
연도1.0000.0000.0000.0820.331
시군별0.0001.0000.0000.0000.000
종류0.0000.0001.0000.0000.000
학교현황별10.0820.0000.0001.0000.703
학교현황별20.3310.0000.0000.7031.000

Missing values

2023-12-13T00:12:13.004397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:12:13.110182image/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

연도시군별종류학교현황별1학교현황별2인원
02019전주시국공립학생수남3300
12019전주시국공립학생수여3257
22019전주시국공립교원수남244
32019전주시국공립교원수여306
42019전주시국공립직원수남40
52019전주시국공립직원수여30
62019전주시국공립졸업후상황졸업자수2490
72019전주시국공립졸업후상황진학자수2204
82019전주시국공립입학상황입학정원2127
92019전주시국공립입학상황입학자2157
연도시군별종류학교현황별1학교현황별2인원
11102022부안군사립교원수남26
11112022부안군사립교원수여31
11122022부안군사립직원수남7
11132022부안군사립직원수여1
11142022부안군사립졸업후상황졸업자수147
11152022부안군사립졸업후상황졸업자수 남33
11162022부안군사립졸업후상황졸업자수 여114
11172022부안군사립입학상황입학자138
11182022부안군사립입학상황입학자 남34
11192022부안군사립입학상황입학자 여104