Overview

Dataset statistics

Number of variables6
Number of observations31
Missing cells122
Missing cells (%)65.6%
Duplicate rows2
Duplicate rows (%)6.5%
Total size in memory1.6 KiB
Average record size in memory52.3 B

Variable types

Text5
Categorical1

Dataset

Description최근 3년 어린이독서교실 운영결과에 대한 데이터로 기간, 주제, 대상, 수료인원, 운영방법, 소요예산을 제공합니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15077233/fileData.do

Alerts

Dataset has 2 (6.5%) duplicate rowsDuplicates
기간 has 22 (71.0%) missing valuesMissing
주제 has 25 (80.6%) missing valuesMissing
대상 has 25 (80.6%) missing valuesMissing
수료인원 has 25 (80.6%) missing valuesMissing
소요예산 has 25 (80.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 01:26:31.855763
Analysis finished2023-12-12 01:26:32.549263
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기간
Text

MISSING 

Distinct7
Distinct (%)77.8%
Missing22
Missing (%)71.0%
Memory size380.0 B
2023-12-12T10:26:32.682212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length42
Mean length28.666667
Min length2

Characters and Unicode

Total characters258
Distinct characters18
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)66.7%

Sample

1st row2020-01-07(화)~2020-01-10일(금) 09:30 ~ 12:00
2nd row2020-08-14(화)~2020-08-17일(금) 10:00 ~ 12:00
3rd row2021-01-05(화)~2021-01-08일(금) 09:30 ~ 12:00
4th row2021-07-27(화)~2021-07-30일(금) 09:30 ~ 12:00
5th row2022-01-04(화)~2022-01-07일(금) 09:30 ~ 12:00
ValueCountFrequency (%)
6
25.0%
12:00 6
25.0%
09:30 5
20.8%
2020-01-07(화)~2020-01-10일(금 1
 
4.2%
2020-08-14(화)~2020-08-17일(금 1
 
4.2%
10:00 1
 
4.2%
2021-01-05(화)~2021-01-08일(금 1
 
4.2%
2021-07-27(화)~2021-07-30일(금 1
 
4.2%
2022-01-04(화)~2022-01-07일(금 1
 
4.2%
2022-08-09(화)~2022-08-12일(금 1
 
4.2%
2023-12-12T10:26:33.042999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 61
23.6%
2 36
14.0%
24
 
9.3%
- 24
 
9.3%
1 21
 
8.1%
) 12
 
4.7%
: 12
 
4.7%
~ 12
 
4.7%
( 12
 
4.7%
화 6
 
2.3%
Other values (8) 38
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 144
55.8%
Space Separator 24
 
9.3%
Dash Punctuation 24
 
9.3%
Other Letter 18
 
7.0%
Close Punctuation 12
 
4.7%
Other Punctuation 12
 
4.7%
Math Symbol 12
 
4.7%
Open Punctuation 12
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 61
42.4%
2 36
25.0%
1 21
 
14.6%
9 6
 
4.2%
7 6
 
4.2%
3 6
 
4.2%
8 5
 
3.5%
4 2
 
1.4%
5 1
 
0.7%
Other Letter
ValueCountFrequency (%)
화 6
33.3%
일 6
33.3%
금 6
33.3%
Space Separator
ValueCountFrequency (%)
24
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Other Punctuation
ValueCountFrequency (%)
: 12
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 240
93.0%
Hangul 18
 
7.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 61
25.4%
2 36
15.0%
24
 
10.0%
- 24
 
10.0%
1 21
 
8.8%
) 12
 
5.0%
: 12
 
5.0%
~ 12
 
5.0%
( 12
 
5.0%
9 6
 
2.5%
Other values (5) 20
 
8.3%
Hangul
ValueCountFrequency (%)
화 6
33.3%
일 6
33.3%
금 6
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 240
93.0%
Hangul 18
 
7.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 61
25.4%
2 36
15.0%
24
 
10.0%
- 24
 
10.0%
1 21
 
8.8%
) 12
 
5.0%
: 12
 
5.0%
~ 12
 
5.0%
( 12
 
5.0%
9 6
 
2.5%
Other values (5) 20
 
8.3%
Hangul
ValueCountFrequency (%)
화 6
33.3%
일 6
33.3%
금 6
33.3%

주제
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing25
Missing (%)80.6%
Memory size380.0 B
2023-12-12T10:26:33.306320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17.5
Mean length17.166667
Min length13

Characters and Unicode

Total characters103
Distinct characters66
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)100.0%

Sample

1st row지구 한 바퀴 세계의 신화 이야기
2nd row감수성 up up 다문화부터 젠더까지
3rd row독서테라피로 코로나블루 극복하기
4th row아무튼 열 한 살도 책놀이가 필요해
5th row얼쑤 좋다 전래놀이 하며 좋다
ValueCountFrequency (%)
up 2
 
6.9%
좋다 2
 
6.9%
한 2
 
6.9%
지구 1
 
3.4%
열 1
 
3.4%
여름을 1
 
3.4%
너의 1
 
3.4%
안녕 1
 
3.4%
하며 1
 
3.4%
전래놀이 1
 
3.4%
Other values (16) 16
55.2%
2023-12-12T10:26:33.728936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
23
 
22.3%
다 3
 
2.9%
이 3
 
2.9%
로 2
 
1.9%
놀 2
 
1.9%
좋 2
 
1.9%
하 2
 
1.9%
p 2
 
1.9%
u 2
 
1.9%
기 2
 
1.9%
Other values (56) 60
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 76
73.8%
Space Separator 23
 
22.3%
Lowercase Letter 4
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
다 3
 
3.9%
이 3
 
3.9%
로 2
 
2.6%
놀 2
 
2.6%
좋 2
 
2.6%
하 2
 
2.6%
기 2
 
2.6%
지 2
 
2.6%
화 2
 
2.6%
의 2
 
2.6%
Other values (53) 54
71.1%
Lowercase Letter
ValueCountFrequency (%)
p 2
50.0%
u 2
50.0%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 76
73.8%
Common 23
 
22.3%
Latin 4
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
다 3
 
3.9%
이 3
 
3.9%
로 2
 
2.6%
놀 2
 
2.6%
좋 2
 
2.6%
하 2
 
2.6%
기 2
 
2.6%
지 2
 
2.6%
화 2
 
2.6%
의 2
 
2.6%
Other values (53) 54
71.1%
Latin
ValueCountFrequency (%)
p 2
50.0%
u 2
50.0%
Common
ValueCountFrequency (%)
23
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 76
73.8%
ASCII 27
 
26.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
23
85.2%
p 2
 
7.4%
u 2
 
7.4%
Hangul
ValueCountFrequency (%)
다 3
 
3.9%
이 3
 
3.9%
로 2
 
2.6%
놀 2
 
2.6%
좋 2
 
2.6%
하 2
 
2.6%
기 2
 
2.6%
지 2
 
2.6%
화 2
 
2.6%
의 2
 
2.6%
Other values (53) 54
71.1%

대상
Text

MISSING 

Distinct3
Distinct (%)50.0%
Missing25
Missing (%)80.6%
Memory size380.0 B
2023-12-12T10:26:33.941844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters72
Distinct characters13
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

Unique1 ?
Unique (%)16.7%

Sample

1st row초등 4학년 (15명)
2nd row초등 4학년 (17명)
3rd row초등 4학년 (15명)
4th row초등 4학년 (17명)
5th row초등 4학년 (17명)
ValueCountFrequency (%)
초등 6
33.3%
4학년 6
33.3%
17명 3
16.7%
15명 2
 
11.1%
18명 1
 
5.6%
2023-12-12T10:26:34.297094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
16.7%
초 6
8.3%
등 6
8.3%
4 6
8.3%
학 6
8.3%
년 6
8.3%
( 6
8.3%
1 6
8.3%
명 6
8.3%
) 6
8.3%
Other values (3) 6
8.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30
41.7%
Decimal Number 18
25.0%
Space Separator 12
 
16.7%
Open Punctuation 6
 
8.3%
Close Punctuation 6
 
8.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
초 6
20.0%
등 6
20.0%
학 6
20.0%
년 6
20.0%
명 6
20.0%
Decimal Number
ValueCountFrequency (%)
4 6
33.3%
1 6
33.3%
7 3
16.7%
5 2
 
11.1%
8 1
 
5.6%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
58.3%
Hangul 30
41.7%

Most frequent character per script

Common
ValueCountFrequency (%)
12
28.6%
4 6
14.3%
( 6
14.3%
1 6
14.3%
) 6
14.3%
7 3
 
7.1%
5 2
 
4.8%
8 1
 
2.4%
Hangul
ValueCountFrequency (%)
초 6
20.0%
등 6
20.0%
학 6
20.0%
년 6
20.0%
명 6
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
58.3%
Hangul 30
41.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
28.6%
4 6
14.3%
( 6
14.3%
1 6
14.3%
) 6
14.3%
7 3
 
7.1%
5 2
 
4.8%
8 1
 
2.4%
Hangul
ValueCountFrequency (%)
초 6
20.0%
등 6
20.0%
학 6
20.0%
년 6
20.0%
명 6
20.0%

수료인원
Text

MISSING 

Distinct5
Distinct (%)83.3%
Missing25
Missing (%)80.6%
Memory size380.0 B
2023-12-12T10:26:34.489102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length14.5
Min length14

Characters and Unicode

Total characters87
Distinct characters16
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

Unique4 ?
Unique (%)66.7%

Sample

1st row23명(남:12명 여:11명)
2nd row15명(남:6명 여:9명)
3rd row15명(남:7명 여:8명)
4th row17명(남:9명 여:8명)
5th row17명(남:9명 여:8명)
ValueCountFrequency (%)
여:8명 3
25.0%
17명(남:9명 2
16.7%
23명(남:12명 1
 
8.3%
여:11명 1
 
8.3%
15명(남:6명 1
 
8.3%
여:9명 1
 
8.3%
15명(남:7명 1
 
8.3%
17명(남:7명 1
 
8.3%
여:10명 1
 
8.3%
2023-12-12T10:26:34.855187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
명 18
20.7%
: 12
13.8%
1 9
10.3%
( 6
 
6.9%
남 6
 
6.9%
6
 
6.9%
여 6
 
6.9%
) 6
 
6.9%
7 5
 
5.7%
9 3
 
3.4%
Other values (6) 10
11.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30
34.5%
Decimal Number 27
31.0%
Other Punctuation 12
 
13.8%
Open Punctuation 6
 
6.9%
Space Separator 6
 
6.9%
Close Punctuation 6
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 9
33.3%
7 5
18.5%
9 3
 
11.1%
8 3
 
11.1%
2 2
 
7.4%
5 2
 
7.4%
3 1
 
3.7%
6 1
 
3.7%
0 1
 
3.7%
Other Letter
ValueCountFrequency (%)
명 18
60.0%
남 6
 
20.0%
여 6
 
20.0%
Other Punctuation
ValueCountFrequency (%)
: 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57
65.5%
Hangul 30
34.5%

Most frequent character per script

Common
ValueCountFrequency (%)
: 12
21.1%
1 9
15.8%
( 6
10.5%
6
10.5%
) 6
10.5%
7 5
8.8%
9 3
 
5.3%
8 3
 
5.3%
2 2
 
3.5%
5 2
 
3.5%
Other values (3) 3
 
5.3%
Hangul
ValueCountFrequency (%)
명 18
60.0%
남 6
 
20.0%
여 6
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
65.5%
Hangul 30
34.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
명 18
60.0%
남 6
 
20.0%
여 6
 
20.0%
ASCII
ValueCountFrequency (%)
: 12
21.1%
1 9
15.8%
( 6
10.5%
6
10.5%
) 6
10.5%
7 5
8.8%
9 3
 
5.3%
8 3
 
5.3%
2 2
 
3.5%
5 2
 
3.5%
Other values (3) 3
 
5.3%

운영방법
Categorical

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
25 
비대면 온라인(ZOOM)
4 
대면
 
2

Length

Max length14
Median length4
Mean length5.1612903
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대면
2nd row비대면 온라인(ZOOM)
3rd row비대면 온라인(ZOOM)
4th row비대면 온라인(ZOOM)
5th row비대면 온라인(ZOOM)

Common Values

ValueCountFrequency (%)
<NA> 25
80.6%
비대면 온라인(ZOOM) 4
 
12.9%
대면 2
 
6.5%

Length

2023-12-12T10:26:35.022797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:26:35.156947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 25
71.4%
비대면 4
 
11.4%
온라인(zoom 4
 
11.4%
대면 2
 
5.7%

소요예산
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing25
Missing (%)80.6%
Memory size380.0 B
2023-12-12T10:26:35.327647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9.5
Mean length8.6666667
Min length8

Characters and Unicode

Total characters52
Distinct characters13
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

Unique6 ?
Unique (%)100.0%

Sample

1st row591,400원
2nd row480,000원
3rd row864,000원
4th row855,250원
5th row1,150,320원
ValueCountFrequency (%)
591,400원 1
16.7%
480,000원 1
16.7%
864,000원 1
16.7%
855,250원 1
16.7%
1,150,320원 1
16.7%
675,600원 1
16.7%
2023-12-12T10:26:35.695644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
26.9%
, 7
13.5%
5 6
11.5%
원 6
11.5%
1 3
 
5.8%
4 3
 
5.8%
8 3
 
5.8%
6 3
 
5.8%
2
 
3.8%
2 2
 
3.8%
Other values (3) 3
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 37
71.2%
Other Punctuation 7
 
13.5%
Other Letter 6
 
11.5%
Space Separator 2
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
37.8%
5 6
16.2%
1 3
 
8.1%
4 3
 
8.1%
8 3
 
8.1%
6 3
 
8.1%
2 2
 
5.4%
9 1
 
2.7%
3 1
 
2.7%
7 1
 
2.7%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Other Letter
ValueCountFrequency (%)
원 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 46
88.5%
Hangul 6
 
11.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
30.4%
, 7
15.2%
5 6
13.0%
1 3
 
6.5%
4 3
 
6.5%
8 3
 
6.5%
6 3
 
6.5%
2
 
4.3%
2 2
 
4.3%
9 1
 
2.2%
Other values (2) 2
 
4.3%
Hangul
ValueCountFrequency (%)
원 6
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 46
88.5%
Hangul 6
 
11.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
30.4%
, 7
15.2%
5 6
13.0%
1 3
 
6.5%
4 3
 
6.5%
8 3
 
6.5%
6 3
 
6.5%
2
 
4.3%
2 2
 
4.3%
9 1
 
2.2%
Other values (2) 2
 
4.3%
Hangul
ValueCountFrequency (%)
원 6
100.0%

Correlations

2023-12-12T10:26:35.820854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기간주제대상수료인원운영방법소요예산
기간1.0001.0001.0001.0001.0001.000
주제1.0001.0001.0001.0001.0001.000
대상1.0001.0001.0001.0000.4231.000
수료인원1.0001.0001.0001.0001.0001.000
운영방법1.0001.0000.4231.0001.0001.000
소요예산1.0001.0001.0001.0001.0001.000

Missing values

2023-12-12T10:26:32.195623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:26:32.310396image/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.
2023-12-12T10:26:32.452934image/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

기간주제대상수료인원운영방법소요예산
02020-01-07(화)~2020-01-10일(금) 09:30 ~ 12:00지구 한 바퀴 세계의 신화 이야기초등 4학년 (15명)23명(남:12명 여:11명)대면591,400원
12020-08-14(화)~2020-08-17일(금) 10:00 ~ 12:00감수성 up up 다문화부터 젠더까지초등 4학년 (17명)15명(남:6명 여:9명)비대면 온라인(ZOOM)480,000원
22021-01-05(화)~2021-01-08일(금) 09:30 ~ 12:00독서테라피로 코로나블루 극복하기초등 4학년 (15명)15명(남:7명 여:8명)비대면 온라인(ZOOM)864,000원
32021-07-27(화)~2021-07-30일(금) 09:30 ~ 12:00아무튼 열 한 살도 책놀이가 필요해초등 4학년 (17명)17명(남:9명 여:8명)비대면 온라인(ZOOM)855,250원
42022-01-04(화)~2022-01-07일(금) 09:30 ~ 12:00얼쑤 좋다 전래놀이 하며 좋다초등 4학년 (17명)17명(남:9명 여:8명)비대면 온라인(ZOOM)1,150,320원
52022-08-09(화)~2022-08-12일(금) 09:30 ~ 12:00안녕 너의 여름을 알려줘초등 4학년 (18명)17명(남:7명 여:10명)대면675,600원
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기간주제대상수료인원운영방법소요예산
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Duplicate rows

Most frequently occurring

기간주제대상수료인원운영방법소요예산# duplicates
1<NA><NA><NA><NA><NA><NA>22
0<NA><NA><NA><NA><NA>3