Overview

Dataset statistics

Number of variables5
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory43.9 B

Variable types

Categorical2
Text3

Dataset

Description학과,반,요일,시간,장소
Author구로노인종합복지관
URLhttps://data.seoul.go.kr/dataList/OA-12056/S/1/datasetView.do

Alerts

학과 is highly overall correlated with 장소High correlation
장소 is highly overall correlated with 학과High correlation
반 has unique valuesUnique

Reproduction

Analysis started2023-12-11 08:23:19.094729
Analysis finished2023-12-11 08:23:19.580424
Duration0.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

학과
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)23.5%
Missing0
Missing (%)0.0%
Memory size404.0 B
전산정보학과
11 
서예학과
7 
영어학과
4 
교양문화학과
3 
한문학과
3 
Other values (3)
6 

Length

Max length6
Median length5
Mean length4.9411765
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row국어학과
2nd row국어학과
3rd row영어학과
4th row영어학과
5th row영어학과

Common Values

ValueCountFrequency (%)
전산정보학과 11
32.4%
서예학과 7
20.6%
영어학과 4
 
11.8%
교양문화학과 3
 
8.8%
한문학과 3
 
8.8%
국어학과 2
 
5.9%
일본어학과 2
 
5.9%
중국어학과 2
 
5.9%

Length

2023-12-11T17:23:19.723136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:23:19.905910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
전산정보학과 11
32.4%
서예학과 7
20.6%
영어학과 4
 
11.8%
교양문화학과 3
 
8.8%
한문학과 3
 
8.8%
국어학과 2
 
5.9%
일본어학과 2
 
5.9%
중국어학과 2
 
5.9%

반
Text

UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T17:23:20.179358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9.5
Mean length6.2352941
Min length3

Characters and Unicode

Total characters212
Distinct characters57
Distinct categories5 ?
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 row한글초급
2nd row한글중급
3rd row영어초급
4th row영어중급
5th row영어고급
ValueCountFrequency (%)
중급 6
 
9.5%
초급 6
 
9.5%
스위시 4
 
6.3%
한문 3
 
4.8%
문서작성 2
 
3.2%
심화 2
 
3.2%
서예한문 2
 
3.2%
슬라이드 2
 
3.2%
서예오전 2
 
3.2%
인터넷 2
 
3.2%
Other values (31) 32
50.8%
2023-12-11T17:23:20.670935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
29
 
13.7%
급 22
 
10.4%
중 12
 
5.7%
초 10
 
4.7%
한 9
 
4.2%
어 8
 
3.8%
서 8
 
3.8%
문 7
 
3.3%
반 6
 
2.8%
예 6
 
2.8%
Other values (47) 95
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
82.5%
Space Separator 29
 
13.7%
Decimal Number 4
 
1.9%
Open Punctuation 2
 
0.9%
Close Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
급 22
 
12.6%
중 12
 
6.9%
초 10
 
5.7%
한 9
 
5.1%
어 8
 
4.6%
서 8
 
4.6%
문 7
 
4.0%
반 6
 
3.4%
예 6
 
3.4%
영 6
 
3.4%
Other values (42) 81
46.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 2
50.0%
Space Separator
ValueCountFrequency (%)
29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
82.5%
Common 37
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
급 22
 
12.6%
중 12
 
6.9%
초 10
 
5.7%
한 9
 
5.1%
어 8
 
4.6%
서 8
 
4.6%
문 7
 
4.0%
반 6
 
3.4%
예 6
 
3.4%
영 6
 
3.4%
Other values (42) 81
46.3%
Common
ValueCountFrequency (%)
29
78.4%
2 2
 
5.4%
1 2
 
5.4%
( 2
 
5.4%
) 2
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
82.5%
ASCII 37
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
29
78.4%
2 2
 
5.4%
1 2
 
5.4%
( 2
 
5.4%
) 2
 
5.4%
Hangul
ValueCountFrequency (%)
급 22
 
12.6%
중 12
 
6.9%
초 10
 
5.7%
한 9
 
5.1%
어 8
 
4.6%
서 8
 
4.6%
문 7
 
4.0%
반 6
 
3.4%
예 6
 
3.4%
영 6
 
3.4%
Other values (42) 81
46.3%

요일
Text

Distinct18
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T17:23:20.924885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length6
Mean length4.4117647
Min length1

Characters and Unicode

Total characters150
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)20.6%

Sample

1st row화/금
2nd row수
3rd row화/금
4th row화/금
5th row월/목
ValueCountFrequency (%)
수 5
12.5%
월/화/목 4
 
10.0%
화/목 4
 
10.0%
화 3
 
7.5%
월/목 3
 
7.5%
화/금 3
 
7.5%
월 2
 
5.0%
월/수 2
 
5.0%
금 2
 
5.0%
월/수/금 2
 
5.0%
Other values (8) 10
25.0%
2023-12-11T17:23:21.362050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 30
20.0%
화 15
10.0%
목 14
9.3%
월 14
9.3%
0 14
9.3%
수 12
 
8.0%
금 10
 
6.7%
10
 
6.7%
1 10
 
6.7%
: 8
 
5.3%
Other values (5) 13
8.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 66
44.0%
Other Punctuation 38
25.3%
Decimal Number 32
21.3%
Space Separator 10
 
6.7%
Math Symbol 4
 
2.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
화 15
22.7%
목 14
21.2%
월 14
21.2%
수 12
18.2%
금 10
15.2%
토 1
 
1.5%
Decimal Number
ValueCountFrequency (%)
0 14
43.8%
1 10
31.2%
5 4
 
12.5%
3 2
 
6.2%
4 2
 
6.2%
Other Punctuation
ValueCountFrequency (%)
/ 30
78.9%
: 8
 
21.1%
Space Separator
ValueCountFrequency (%)
10
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
56.0%
Hangul 66
44.0%

Most frequent character per script

Common
ValueCountFrequency (%)
/ 30
35.7%
0 14
16.7%
10
 
11.9%
1 10
 
11.9%
: 8
 
9.5%
~ 4
 
4.8%
5 4
 
4.8%
3 2
 
2.4%
4 2
 
2.4%
Hangul
ValueCountFrequency (%)
화 15
22.7%
목 14
21.2%
월 14
21.2%
수 12
18.2%
금 10
15.2%
토 1
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
56.0%
Hangul 66
44.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 30
35.7%
0 14
16.7%
10
 
11.9%
1 10
 
11.9%
: 8
 
9.5%
~ 4
 
4.8%
5 4
 
4.8%
3 2
 
2.4%
4 2
 
2.4%
Hangul
ValueCountFrequency (%)
화 15
22.7%
목 14
21.2%
월 14
21.2%
수 12
18.2%
금 10
15.2%
토 1
 
1.5%

시간
Text

Distinct22
Distinct (%)64.7%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-11T17:23:21.640166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length12
Mean length13.852941
Min length12

Characters and Unicode

Total characters471
Distinct characters18
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)38.2%

Sample

1st row오전 9:30~10:30
2nd row오후 1:00-2:30
3rd row오전 9:30-10:30
4th row오전10:40-11:40
5th row오전 11:00-12:00
ValueCountFrequency (%)
오후 20
26.7%
오전 15
20.0%
1:00-2:30 3
 
4.0%
11:00-12:00 3
 
4.0%
9:30-10:30 3
 
4.0%
수/금 2
 
2.7%
화 2
 
2.7%
1:00~1:50 2
 
2.7%
10:00-10:50 2
 
2.7%
9:00~12:00 2
 
2.7%
Other values (16) 21
28.0%
2023-12-11T17:23:22.066485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 123
26.1%
: 72
15.3%
1 52
11.0%
41
 
8.7%
오 36
 
7.6%
- 23
 
4.9%
3 22
 
4.7%
후 20
 
4.2%
2 19
 
4.0%
전 16
 
3.4%
Other values (8) 47
 
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242
51.4%
Other Letter 78
 
16.6%
Other Punctuation 74
 
15.7%
Space Separator 41
 
8.7%
Dash Punctuation 23
 
4.9%
Math Symbol 13
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 123
50.8%
1 52
21.5%
3 22
 
9.1%
2 19
 
7.9%
5 13
 
5.4%
4 7
 
2.9%
9 6
 
2.5%
Other Letter
ValueCountFrequency (%)
오 36
46.2%
후 20
25.6%
전 16
20.5%
화 2
 
2.6%
수 2
 
2.6%
금 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
: 72
97.3%
/ 2
 
2.7%
Space Separator
ValueCountFrequency (%)
41
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%
Math Symbol
ValueCountFrequency (%)
~ 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 393
83.4%
Hangul 78
 
16.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 123
31.3%
: 72
18.3%
1 52
13.2%
41
 
10.4%
- 23
 
5.9%
3 22
 
5.6%
2 19
 
4.8%
~ 13
 
3.3%
5 13
 
3.3%
4 7
 
1.8%
Other values (2) 8
 
2.0%
Hangul
ValueCountFrequency (%)
오 36
46.2%
후 20
25.6%
전 16
20.5%
화 2
 
2.6%
수 2
 
2.6%
금 2
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 393
83.4%
Hangul 78
 
16.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 123
31.3%
: 72
18.3%
1 52
13.2%
41
 
10.4%
- 23
 
5.9%
3 22
 
5.6%
2 19
 
4.8%
~ 13
 
3.3%
5 13
 
3.3%
4 7
 
1.8%
Other values (2) 8
 
2.0%
Hangul
ValueCountFrequency (%)
오 36
46.2%
후 20
25.6%
전 16
20.5%
화 2
 
2.6%
수 2
 
2.6%
금 2
 
2.6%

장소
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
2층 정보화교실
11 
2층 외국어교실
10 
2층 서예실
7 
3층 사회교육실
6 

Length

Max length8
Median length8
Mean length7.5882353
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3층 사회교육실
2nd row2층 외국어교실
3rd row2층 외국어교실
4th row2층 외국어교실
5th row2층 외국어교실

Common Values

ValueCountFrequency (%)
2층 정보화교실 11
32.4%
2층 외국어교실 10
29.4%
2층 서예실 7
20.6%
3층 사회교육실 6
17.6%

Length

2023-12-11T17:23:22.265400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:23:22.440771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2층 28
41.2%
정보화교실 11
 
16.2%
외국어교실 10
 
14.7%
서예실 7
 
10.3%
3층 6
 
8.8%
사회교육실 6
 
8.8%

Correlations

2023-12-11T17:23:22.551777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학과반요일시간장소
학과1.0001.0000.8040.6140.989
반1.0001.0001.0001.0001.000
요일0.8041.0001.0000.8310.717
시간0.6141.0000.8311.0000.920
장소0.9891.0000.7170.9201.000
2023-12-11T17:23:22.684396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학과장소
학과1.0000.799
장소0.7991.000
2023-12-11T17:23:22.791489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
학과장소
학과1.0000.799
장소0.7991.000

Missing values

2023-12-11T17:23:19.386058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:23:19.520663image/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

학과반요일시간장소
0국어학과한글초급화/금오전 9:30~10:303층 사회교육실
1국어학과한글중급수오후 1:00-2:302층 외국어교실
2영어학과영어초급화/금오전 9:30-10:302층 외국어교실
3영어학과영어중급화/금오전10:40-11:402층 외국어교실
4영어학과영어고급월/목오전 11:00-12:002층 외국어교실
5영어학과영어회화월/목오전 9:30-10:302층 외국어교실
6일본어학과일어초급월/목오후 1:00-2:002층 외국어교실
7일본어학과일어중급월/수오후 2:10-3:103층 사회교육실
8중국어학과중국어초급화/목오후 1:00-2:003층 사회교육실
9중국어학과중국어중급화/목오후 2:10-3:103층 사회교육실
학과반요일시간장소
24전산정보학과문서작성 중급월/화/목오전 10:00-10:502층 정보화교실
25전산정보학과스위시 기본 초급월/수/금오전 11:00-11:502층 정보화교실
26전산정보학과스위시 기본 중급월/수/금오후 1:00~1:502층 정보화교실
27전산정보학과스위시 심화 초급월/화/목오후 2:00~2:502층 정보화교실
28전산정보학과스위시 심화 중급월/화/목오후 3:00~3:502층 정보화교실
29전산정보학과인터넷 초급화 13:00~13:50 수/금 10:00~10:50화 오후 1:00~1:50 수/금 오전 10:00~10:502층 정보화교실
30전산정보학과인터넷 중급화 14:00~14:50 수/금 11:00~11:50화 오후 2:00~2:50 수/금 오전 11:00~11:502층 정보화교실
31전산정보학과슬라이드 동영상1반수오후 3:00~4:502층 정보화교실
32전산정보학과슬라이드 동영상2반목오후 1:00~2:502층 정보화교실
33전산정보학과반복반금오후 3:00~4:502층 정보화교실