Overview

Dataset statistics

Number of variables16
Number of observations25
Missing cells244
Missing cells (%)61.0%
Duplicate rows1
Duplicate rows (%)4.0%
Total size in memory3.3 KiB
Average record size in memory133.3 B

Variable types

Text9
Categorical1
Unsupported6

Dataset

Description(부산광역시교육청) 유치원 운영 현황에 관한 자료로 교육지원청별 운영, 휴원, 미운영, 휴원예정, 폐원예정 유치원 현황 등의 자료를 제공합니다.
URLhttps://www.data.go.kr/data/15050372/fileData.do

Alerts

Dataset has 1 (4.0%) duplicate rowsDuplicates
2023년 유치원 운영 현황(2023. 4. 1.기준) has 18 (72.0%) missing valuesMissing
Unnamed: 2 has 1 (4.0%) missing valuesMissing
Unnamed: 3 has 9 (36.0%) missing valuesMissing
Unnamed: 4 has 20 (80.0%) missing valuesMissing
Unnamed: 5 has 20 (80.0%) missing valuesMissing
Unnamed: 6 has 20 (80.0%) missing valuesMissing
Unnamed: 7 has 1 (4.0%) missing valuesMissing
Unnamed: 8 has 17 (68.0%) missing valuesMissing
Unnamed: 9 has 23 (92.0%) missing valuesMissing
Unnamed: 10 has 23 (92.0%) missing valuesMissing
Unnamed: 11 has 23 (92.0%) missing valuesMissing
Unnamed: 12 has 15 (60.0%) missing valuesMissing
Unnamed: 13 has 12 (48.0%) missing valuesMissing
Unnamed: 14 has 19 (76.0%) missing valuesMissing
Unnamed: 15 has 23 (92.0%) missing valuesMissing
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 19:03:19.334956
Analysis finished2023-12-12 19:03:20.924796
Duration1.59 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

2023년 유치원 운영 현황(2023. 4. 1.기준)
Text

MISSING 

Distinct7
Distinct (%)100.0%
Missing18
Missing (%)72.0%
Memory size332.0 B
2023-12-13T04:03:21.054904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length2.1428571
Min length1

Characters and Unicode

Total characters15
Distinct characters13
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

Unique7 ?
Unique (%)100.0%

Sample

1st row교육청
2nd row서부
3rd row남부
4th row북부
5th row동래
ValueCountFrequency (%)
교육청 1
14.3%
서부 1
14.3%
남부 1
14.3%
북부 1
14.3%
동래 1
14.3%
해운대 1
14.3%
계 1
14.3%
2023-12-13T04:03:21.498384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 3
20.0%
교 1
 
6.7%
육 1
 
6.7%
청 1
 
6.7%
서 1
 
6.7%
남 1
 
6.7%
북 1
 
6.7%
동 1
 
6.7%
래 1
 
6.7%
해 1
 
6.7%
Other values (3) 3
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 3
20.0%
교 1
 
6.7%
육 1
 
6.7%
청 1
 
6.7%
서 1
 
6.7%
남 1
 
6.7%
북 1
 
6.7%
동 1
 
6.7%
래 1
 
6.7%
해 1
 
6.7%
Other values (3) 3
20.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 3
20.0%
교 1
 
6.7%
육 1
 
6.7%
청 1
 
6.7%
서 1
 
6.7%
남 1
 
6.7%
북 1
 
6.7%
동 1
 
6.7%
래 1
 
6.7%
해 1
 
6.7%
Other values (3) 3
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 3
20.0%
교 1
 
6.7%
육 1
 
6.7%
청 1
 
6.7%
서 1
 
6.7%
남 1
 
6.7%
북 1
 
6.7%
동 1
 
6.7%
래 1
 
6.7%
해 1
 
6.7%
Other values (3) 3
20.0%

Unnamed: 1
Categorical

Distinct8
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
사
6 
공(단설)
5 
공(병설)
5 
소계
5 
<NA>
1 
Other values (3)
3 

Length

Max length5
Median length4
Mean length3
Min length1

Unique

Unique4 ?
Unique (%)16.0%

Sample

1st row<NA>
2nd row설립별
3rd row공(단설)
4th row공(병설)
5th row사

Common Values

ValueCountFrequency (%)
사 6
24.0%
공(단설) 5
20.0%
공(병설) 5
20.0%
소계 5
20.0%
<NA> 1
 
4.0%
설립별 1
 
4.0%
공 1
 
4.0%
계 1
 
4.0%

Length

2023-12-13T04:03:21.681658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T04:03:21.857283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사 6
24.0%
공(단설 5
20.0%
공(병설 5
20.0%
소계 5
20.0%
na 1
 
4.0%
설립별 1
 
4.0%
공 1
 
4.0%
계 1
 
4.0%

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.0%
Memory size332.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing9
Missing (%)36.0%
Memory size332.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing20
Missing (%)80.0%
Memory size332.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing20
Missing (%)80.0%
Memory size332.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing20
Missing (%)80.0%
Memory size332.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)4.0%
Memory size332.0 B

Unnamed: 8
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing17
Missing (%)68.0%
Memory size332.0 B
2023-12-13T04:03:22.104008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length10.625
Min length4

Characters and Unicode

Total characters85
Distinct characters50
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

Unique8 ?
Unique (%)100.0%

Sample

1st row휴원명단
2nd row봉래병설, 신촌병설
3rd row초롱, 한성
4th row또래, 동경
5th row모동병설(2022~), 신금병설
ValueCountFrequency (%)
휴원명단 1
 
5.3%
감전샛별 1
 
5.3%
큰별샘 1
 
5.3%
평화 1
 
5.3%
나은 1
 
5.3%
sk뜰에 1
 
5.3%
세명 1
 
5.3%
둥지 1
 
5.3%
성광 1
 
5.3%
은하자연 1
 
5.3%
Other values (9) 9
47.4%
2023-12-13T04:03:22.507467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
12.9%
, 11
 
12.9%
병 4
 
4.7%
설 4
 
4.7%
2 3
 
3.5%
동 2
 
2.4%
별 2
 
2.4%
신 2
 
2.4%
성 2
 
2.4%
래 2
 
2.4%
Other values (40) 42
49.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 53
62.4%
Space Separator 11
 
12.9%
Other Punctuation 11
 
12.9%
Decimal Number 4
 
4.7%
Uppercase Letter 2
 
2.4%
Control 1
 
1.2%
Open Punctuation 1
 
1.2%
Math Symbol 1
 
1.2%
Close Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
병 4
 
7.5%
설 4
 
7.5%
동 2
 
3.8%
별 2
 
3.8%
신 2
 
3.8%
성 2
 
3.8%
래 2
 
3.8%
은 2
 
3.8%
명 2
 
3.8%
광 1
 
1.9%
Other values (30) 30
56.6%
Decimal Number
ValueCountFrequency (%)
2 3
75.0%
0 1
 
25.0%
Uppercase Letter
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Control
ValueCountFrequency (%)
1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 53
62.4%
Common 30
35.3%
Latin 2
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
병 4
 
7.5%
설 4
 
7.5%
동 2
 
3.8%
별 2
 
3.8%
신 2
 
3.8%
성 2
 
3.8%
래 2
 
3.8%
은 2
 
3.8%
명 2
 
3.8%
광 1
 
1.9%
Other values (30) 30
56.6%
Common
ValueCountFrequency (%)
11
36.7%
, 11
36.7%
2 3
 
10.0%
1
 
3.3%
( 1
 
3.3%
0 1
 
3.3%
~ 1
 
3.3%
) 1
 
3.3%
Latin
ValueCountFrequency (%)
K 1
50.0%
S 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 53
62.4%
ASCII 32
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
34.4%
, 11
34.4%
2 3
 
9.4%
K 1
 
3.1%
S 1
 
3.1%
1
 
3.1%
( 1
 
3.1%
0 1
 
3.1%
~ 1
 
3.1%
) 1
 
3.1%
Hangul
ValueCountFrequency (%)
병 4
 
7.5%
설 4
 
7.5%
동 2
 
3.8%
별 2
 
3.8%
신 2
 
3.8%
성 2
 
3.8%
래 2
 
3.8%
은 2
 
3.8%
명 2
 
3.8%
광 1
 
1.9%
Other values (30) 30
56.6%

Unnamed: 9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing23
Missing (%)92.0%
Memory size332.0 B
2023-12-13T04:03:22.714268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length5
Min length4

Characters and Unicode

Total characters10
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row미운영 명단
2nd row제일성광
ValueCountFrequency (%)
미운영 1
33.3%
명단 1
33.3%
제일성광 1
33.3%
2023-12-13T04:03:23.057939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
미 1
10.0%
운 1
10.0%
영 1
10.0%
1
10.0%
명 1
10.0%
단 1
10.0%
제 1
10.0%
일 1
10.0%
성 1
10.0%
광 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9
90.0%
Space Separator 1
 
10.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
미 1
11.1%
운 1
11.1%
영 1
11.1%
명 1
11.1%
단 1
11.1%
제 1
11.1%
일 1
11.1%
성 1
11.1%
광 1
11.1%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9
90.0%
Common 1
 
10.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
미 1
11.1%
운 1
11.1%
영 1
11.1%
명 1
11.1%
단 1
11.1%
제 1
11.1%
일 1
11.1%
성 1
11.1%
광 1
11.1%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9
90.0%
ASCII 1
 
10.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
미 1
11.1%
운 1
11.1%
영 1
11.1%
명 1
11.1%
단 1
11.1%
제 1
11.1%
일 1
11.1%
성 1
11.1%
광 1
11.1%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 10
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing23
Missing (%)92.0%
Memory size332.0 B
2023-12-13T04:03:23.254219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4.5
Mean length4.5
Min length2

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row휴원예정 명단
2nd row한빛
ValueCountFrequency (%)
휴원예정 1
33.3%
명단 1
33.3%
한빛 1
33.3%
2023-12-13T04:03:23.585845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
휴 1
11.1%
원 1
11.1%
예 1
11.1%
정 1
11.1%
1
11.1%
명 1
11.1%
단 1
11.1%
한 1
11.1%
빛 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
88.9%
Space Separator 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
휴 1
12.5%
원 1
12.5%
예 1
12.5%
정 1
12.5%
명 1
12.5%
단 1
12.5%
한 1
12.5%
빛 1
12.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
88.9%
Common 1
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
휴 1
12.5%
원 1
12.5%
예 1
12.5%
정 1
12.5%
명 1
12.5%
단 1
12.5%
한 1
12.5%
빛 1
12.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
88.9%
ASCII 1
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
휴 1
12.5%
원 1
12.5%
예 1
12.5%
정 1
12.5%
명 1
12.5%
단 1
12.5%
한 1
12.5%
빛 1
12.5%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 11
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing23
Missing (%)92.0%
Memory size332.0 B
2023-12-13T04:03:23.776309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length4.5
Mean length4.5
Min length2

Characters and Unicode

Total characters9
Distinct characters9
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row폐원예정 명단
2nd row현대
ValueCountFrequency (%)
폐원예정 1
33.3%
명단 1
33.3%
현대 1
33.3%
2023-12-13T04:03:24.121842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 1
11.1%
원 1
11.1%
예 1
11.1%
정 1
11.1%
1
11.1%
명 1
11.1%
단 1
11.1%
현 1
11.1%
대 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
88.9%
Space Separator 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 1
12.5%
원 1
12.5%
예 1
12.5%
정 1
12.5%
명 1
12.5%
단 1
12.5%
현 1
12.5%
대 1
12.5%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
88.9%
Common 1
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 1
12.5%
원 1
12.5%
예 1
12.5%
정 1
12.5%
명 1
12.5%
단 1
12.5%
현 1
12.5%
대 1
12.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
88.9%
ASCII 1
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 1
12.5%
원 1
12.5%
예 1
12.5%
정 1
12.5%
명 1
12.5%
단 1
12.5%
현 1
12.5%
대 1
12.5%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 12
Text

MISSING 

Distinct10
Distinct (%)100.0%
Missing15
Missing (%)60.0%
Memory size332.0 B
2023-12-13T04:03:24.307963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length16
Mean length17.6
Min length8

Characters and Unicode

Total characters176
Distinct characters52
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

Unique10 ?
Unique (%)100.0%

Sample

1st row비고(2021)
2nd row신설 : 당리병설, 아미병설
3rd row폐원 : 좌성병설(3.1)
4th row폐원 : 금샘(3.23)
5th row신설 : 덕양병설
ValueCountFrequency (%)
9
25.7%
폐원 5
14.3%
신설 4
 
11.4%
비고(2021 1
 
2.9%
동래새싹(3.11 1
 
2.9%
남부산(3.16 1
 
2.9%
해누리(3.1 1
 
2.9%
해빛병설 1
 
2.9%
해빛 1
 
2.9%
해누리(매입형 1
 
2.9%
Other values (10) 10
28.6%
2023-12-13T04:03:24.728049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
25
 
14.2%
( 12
 
6.8%
) 12
 
6.8%
. 10
 
5.7%
설 9
 
5.1%
: 9
 
5.1%
3 8
 
4.5%
1 8
 
4.5%
, 7
 
4.0%
원 5
 
2.8%
Other values (42) 71
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 71
40.3%
Decimal Number 30
17.0%
Other Punctuation 26
 
14.8%
Space Separator 25
 
14.2%
Open Punctuation 12
 
6.8%
Close Punctuation 12
 
6.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 9
 
12.7%
원 5
 
7.0%
폐 5
 
7.0%
병 5
 
7.0%
신 4
 
5.6%
해 4
 
5.6%
리 3
 
4.2%
성 3
 
4.2%
아 2
 
2.8%
빛 2
 
2.8%
Other values (28) 29
40.8%
Decimal Number
ValueCountFrequency (%)
3 8
26.7%
1 8
26.7%
2 5
16.7%
8 2
 
6.7%
4 2
 
6.7%
6 2
 
6.7%
7 2
 
6.7%
0 1
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 10
38.5%
: 9
34.6%
, 7
26.9%
Space Separator
ValueCountFrequency (%)
25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 105
59.7%
Hangul 71
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 9
 
12.7%
원 5
 
7.0%
폐 5
 
7.0%
병 5
 
7.0%
신 4
 
5.6%
해 4
 
5.6%
리 3
 
4.2%
성 3
 
4.2%
아 2
 
2.8%
빛 2
 
2.8%
Other values (28) 29
40.8%
Common
ValueCountFrequency (%)
25
23.8%
( 12
11.4%
) 12
11.4%
. 10
 
9.5%
: 9
 
8.6%
3 8
 
7.6%
1 8
 
7.6%
, 7
 
6.7%
2 5
 
4.8%
8 2
 
1.9%
Other values (4) 7
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 105
59.7%
Hangul 71
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
25
23.8%
( 12
11.4%
) 12
11.4%
. 10
 
9.5%
: 9
 
8.6%
3 8
 
7.6%
1 8
 
7.6%
, 7
 
6.7%
2 5
 
4.8%
8 2
 
1.9%
Other values (4) 7
 
6.7%
Hangul
ValueCountFrequency (%)
설 9
 
12.7%
원 5
 
7.0%
폐 5
 
7.0%
병 5
 
7.0%
신 4
 
5.6%
해 4
 
5.6%
리 3
 
4.2%
성 3
 
4.2%
아 2
 
2.8%
빛 2
 
2.8%
Other values (28) 29
40.8%

Unnamed: 13
Text

MISSING 

Distinct13
Distinct (%)100.0%
Missing12
Missing (%)48.0%
Memory size332.0 B
2023-12-13T04:03:24.987246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length23
Mean length25.384615
Min length8

Characters and Unicode

Total characters330
Distinct characters93
Distinct categories7 ?
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 (%)100.0%

Sample

1st row비고(2022)
2nd row신설 : 지산(매입형), 더푸르네(매입형)
3rd row신설 : 중현병설, 다선병설
4th row폐원 : 지산(3.1), 푸르네(3.1)
5th row신설 : 개포병설
ValueCountFrequency (%)
8
 
15.4%
신설 7
 
13.5%
폐원 5
 
9.6%
비고(2022 1
 
1.9%
꿈나무(3.8 1
 
1.9%
라임(3.24 1
 
1.9%
아름솔(5.11 1
 
1.9%
연제병설 1
 
1.9%
안진병설 1
 
1.9%
온샘병설 1
 
1.9%
Other values (25) 25
48.1%
2023-12-13T04:03:25.400132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
39
 
11.8%
. 25
 
7.6%
( 21
 
6.4%
) 21
 
6.4%
, 20
 
6.1%
설 17
 
5.2%
3 16
 
4.8%
1 13
 
3.9%
: 12
 
3.6%
병 10
 
3.0%
Other values (83) 136
41.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 143
43.3%
Other Punctuation 57
 
17.3%
Decimal Number 48
 
14.5%
Space Separator 39
 
11.8%
Open Punctuation 21
 
6.4%
Close Punctuation 21
 
6.4%
Control 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 17
 
11.9%
병 10
 
7.0%
신 7
 
4.9%
폐 5
 
3.5%
원 5
 
3.5%
지 4
 
2.8%
한 3
 
2.1%
리 3
 
2.1%
형 3
 
2.1%
입 3
 
2.1%
Other values (67) 83
58.0%
Decimal Number
ValueCountFrequency (%)
3 16
33.3%
1 13
27.1%
2 6
 
12.5%
5 3
 
6.2%
7 3
 
6.2%
8 3
 
6.2%
4 2
 
4.2%
0 1
 
2.1%
6 1
 
2.1%
Other Punctuation
ValueCountFrequency (%)
. 25
43.9%
, 20
35.1%
: 12
21.1%
Space Separator
ValueCountFrequency (%)
39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 187
56.7%
Hangul 143
43.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 17
 
11.9%
병 10
 
7.0%
신 7
 
4.9%
폐 5
 
3.5%
원 5
 
3.5%
지 4
 
2.8%
한 3
 
2.1%
리 3
 
2.1%
형 3
 
2.1%
입 3
 
2.1%
Other values (67) 83
58.0%
Common
ValueCountFrequency (%)
39
20.9%
. 25
13.4%
( 21
11.2%
) 21
11.2%
, 20
10.7%
3 16
8.6%
1 13
 
7.0%
: 12
 
6.4%
2 6
 
3.2%
5 3
 
1.6%
Other values (6) 11
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 187
56.7%
Hangul 143
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
39
20.9%
. 25
13.4%
( 21
11.2%
) 21
11.2%
, 20
10.7%
3 16
8.6%
1 13
 
7.0%
: 12
 
6.4%
2 6
 
3.2%
5 3
 
1.6%
Other values (6) 11
 
5.9%
Hangul
ValueCountFrequency (%)
설 17
 
11.9%
병 10
 
7.0%
신 7
 
4.9%
폐 5
 
3.5%
원 5
 
3.5%
지 4
 
2.8%
한 3
 
2.1%
리 3
 
2.1%
형 3
 
2.1%
입 3
 
2.1%
Other values (67) 83
58.0%

Unnamed: 14
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing19
Missing (%)76.0%
Memory size332.0 B
2023-12-13T04:03:25.562484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15.5
Mean length15.333333
Min length8

Characters and Unicode

Total characters92
Distinct characters29
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

Unique6 ?
Unique (%)100.0%

Sample

1st row비고(2023)
2nd row폐원 : 부산명성(3.20.)
3rd row폐원: 개미(3.30.)
4th row폐원: 부산(1.31.), 리라(3.29.)
5th row폐원: 미래자연(2.15.)
ValueCountFrequency (%)
폐원 5
35.7%
2
 
14.3%
비고(2023 1
 
7.1%
부산명성(3.20 1
 
7.1%
개미(3.30 1
 
7.1%
부산(1.31 1
 
7.1%
리라(3.29 1
 
7.1%
미래자연(2.15 1
 
7.1%
서광자연(3.23 1
 
7.1%
2023-12-13T04:03:25.920466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 12
13.0%
3 8
 
8.7%
8
 
8.7%
( 7
 
7.6%
) 7
 
7.6%
2 6
 
6.5%
: 5
 
5.4%
폐 5
 
5.4%
원 5
 
5.4%
0 3
 
3.3%
Other values (19) 26
28.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 30
32.6%
Decimal Number 22
23.9%
Other Punctuation 18
19.6%
Space Separator 8
 
8.7%
Open Punctuation 7
 
7.6%
Close Punctuation 7
 
7.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 5
16.7%
원 5
16.7%
연 2
 
6.7%
자 2
 
6.7%
부 2
 
6.7%
산 2
 
6.7%
미 2
 
6.7%
비 1
 
3.3%
서 1
 
3.3%
래 1
 
3.3%
Other values (7) 7
23.3%
Decimal Number
ValueCountFrequency (%)
3 8
36.4%
2 6
27.3%
0 3
 
13.6%
1 3
 
13.6%
5 1
 
4.5%
9 1
 
4.5%
Other Punctuation
ValueCountFrequency (%)
. 12
66.7%
: 5
27.8%
, 1
 
5.6%
Space Separator
ValueCountFrequency (%)
8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
67.4%
Hangul 30
32.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 5
16.7%
원 5
16.7%
연 2
 
6.7%
자 2
 
6.7%
부 2
 
6.7%
산 2
 
6.7%
미 2
 
6.7%
비 1
 
3.3%
서 1
 
3.3%
래 1
 
3.3%
Other values (7) 7
23.3%
Common
ValueCountFrequency (%)
. 12
19.4%
3 8
12.9%
8
12.9%
( 7
11.3%
) 7
11.3%
2 6
9.7%
: 5
8.1%
0 3
 
4.8%
1 3
 
4.8%
5 1
 
1.6%
Other values (2) 2
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
67.4%
Hangul 30
32.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 12
19.4%
3 8
12.9%
8
12.9%
( 7
11.3%
) 7
11.3%
2 6
9.7%
: 5
8.1%
0 3
 
4.8%
1 3
 
4.8%
5 1
 
1.6%
Other values (2) 2
 
3.2%
Hangul
ValueCountFrequency (%)
폐 5
16.7%
원 5
16.7%
연 2
 
6.7%
자 2
 
6.7%
부 2
 
6.7%
산 2
 
6.7%
미 2
 
6.7%
비 1
 
3.3%
서 1
 
3.3%
래 1
 
3.3%
Other values (7) 7
23.3%

Unnamed: 15
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing23
Missing (%)92.0%
Memory size332.0 B
2023-12-13T04:03:26.125270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length13
Min length12

Characters and Unicode

Total characters26
Distinct characters16
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row현대 폐원(7.14.)
2nd rowSK뜰에 폐원(6.16.)
ValueCountFrequency (%)
현대 1
25.0%
폐원(7.14 1
25.0%
sk뜰에 1
25.0%
폐원(6.16 1
25.0%
2023-12-13T04:03:26.480473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 4
15.4%
2
 
7.7%
폐 2
 
7.7%
원 2
 
7.7%
( 2
 
7.7%
1 2
 
7.7%
) 2
 
7.7%
6 2
 
7.7%
현 1
 
3.8%
대 1
 
3.8%
Other values (6) 6
23.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
30.8%
Decimal Number 6
23.1%
Other Punctuation 4
15.4%
Space Separator 2
 
7.7%
Open Punctuation 2
 
7.7%
Close Punctuation 2
 
7.7%
Uppercase Letter 2
 
7.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 2
25.0%
원 2
25.0%
현 1
12.5%
대 1
12.5%
뜰 1
12.5%
에 1
12.5%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
6 2
33.3%
7 1
16.7%
4 1
16.7%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 16
61.5%
Hangul 8
30.8%
Latin 2
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
. 4
25.0%
2
12.5%
( 2
12.5%
1 2
12.5%
) 2
12.5%
6 2
12.5%
7 1
 
6.2%
4 1
 
6.2%
Hangul
ValueCountFrequency (%)
폐 2
25.0%
원 2
25.0%
현 1
12.5%
대 1
12.5%
뜰 1
12.5%
에 1
12.5%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18
69.2%
Hangul 8
30.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 4
22.2%
2
11.1%
( 2
11.1%
1 2
11.1%
) 2
11.1%
6 2
11.1%
7 1
 
5.6%
4 1
 
5.6%
S 1
 
5.6%
K 1
 
5.6%
Hangul
ValueCountFrequency (%)
폐 2
25.0%
원 2
25.0%
현 1
12.5%
대 1
12.5%
뜰 1
12.5%
에 1
12.5%

Correlations

2023-12-13T04:03:26.601346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023년 유치원 운영 현황(2023. 4. 1.기준)Unnamed: 1Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
2023년 유치원 운영 현황(2023. 4. 1.기준)1.0001.000NaNNaNNaNNaN0.0001.000NaNNaN
Unnamed: 11.0001.0001.0000.0000.0000.0001.0001.0001.000NaN
Unnamed: 8NaN1.0001.0000.0000.0000.0001.0001.0001.0000.000
Unnamed: 9NaN0.0000.0001.0000.000NaNNaN0.0000.000NaN
Unnamed: 10NaN0.0000.0000.0001.000NaNNaN0.0000.000NaN
Unnamed: 11NaN0.0000.000NaNNaN1.0000.0000.0000.000NaN
Unnamed: 120.0001.0001.000NaNNaN0.0001.0001.0001.0000.000
Unnamed: 131.0001.0001.0000.0000.0000.0001.0001.0001.0000.000
Unnamed: 14NaN1.0001.0000.0000.0000.0001.0001.0001.0000.000
Unnamed: 15NaNNaN0.000NaNNaNNaN0.0000.0000.0001.000

Missing values

2023-12-13T04:03:19.964973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:03:20.218570image/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.
2023-12-13T04:03:20.601716image/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

2023년 유치원 운영 현황(2023. 4. 1.기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
0<NA><NA>NaNNaNNaNNaNNaNNaN<NA><NA><NA><NA><NA><NA><NA><NA>
1교육청설립별운영휴원미운영휴원\n예정폐원\n예정소계휴원명단미운영 명단휴원예정 명단폐원예정 명단비고(2021)비고(2022)비고(2023)<NA>
2서부공(단설)3NaNNaNNaNNaN3<NA><NA><NA><NA><NA>신설 : 지산(매입형), 더푸르네(매입형)<NA><NA>
3<NA>공(병설)182NaNNaNNaN20봉래병설, 신촌병설<NA><NA><NA>신설 : 당리병설, 아미병설신설 : 중현병설, 다선병설<NA><NA>
4<NA>사38211NaN42초롱, 한성제일성광한빛<NA><NA>폐원 : 지산(3.1), 푸르네(3.1)폐원 : 부산명성(3.20.)<NA>
5<NA>소계59411NaN65<NA><NA><NA><NA><NA><NA><NA><NA>
6남부공(단설)3NaNNaNNaNNaN3<NA><NA><NA><NA><NA><NA><NA><NA>
7<NA>공(병설)17NaNNaNNaNNaN17<NA><NA><NA><NA>폐원 : 좌성병설(3.1)신설 : 개포병설<NA><NA>
8<NA>사522NaNNaNNaN54또래, 동경<NA><NA><NA>폐원 : 금샘(3.23)폐원: 소화데레사(4.13.)폐원: 개미(3.30.)<NA>
9<NA>소계722NaNNaNNaN74<NA><NA><NA><NA><NA><NA><NA><NA>
2023년 유치원 운영 현황(2023. 4. 1.기준)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15
15<NA>공(병설)16NaNNaNNaNNaN16<NA><NA><NA><NA><NA>신설 : 연제병설, 안진병설, 온샘병설<NA><NA>
16<NA>사443NaNNaNNaN47둥지, 세명, SK뜰에<NA><NA><NA>폐원 : 유성(1.28), 동래새싹(3.11), 아성(6.3)폐원: 꿈나무(3.8), 남산(3.17), 숲속(3.8), 은성(3.17), 한독(3.8),금양미래(5.11)폐원: 미래자연(2.15.)SK뜰에 폐원(6.16.)
17<NA>소계633NaNNaNNaN66<NA><NA><NA><NA><NA><NA><NA><NA>
18해운대공(단설)10NaNNaNNaNNaN10<NA><NA><NA><NA>신설 : 해누리(매입형), 해빛<NA><NA><NA>
19<NA>공(병설)24NaNNaNNaNNaN24<NA><NA><NA><NA>신설 : 해빛병설신설 : 교리병설<NA><NA>
20<NA>사514NaNNaNNaN55나은, 평화, 큰별샘, 백산<NA><NA><NA>폐원 : 해누리(3.1), 남부산(3.16), 푸른솔(4.27)폐원: 좋은엔젤(3.31.), 한일(3.31.), 해운대(5.26.)폐원 : 서광자연(3.23.)<NA>
21<NA>소계854NaNNaNNaN89<NA><NA><NA><NA><NA><NA><NA><NA>
22계공1324NaNNaNNaN136<NA><NA><NA><NA><NA><NA><NA><NA>
23<NA>사23114111248<NA><NA><NA><NA><NA><NA><NA><NA>
24<NA>계36318111384<NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

2023년 유치원 운영 현황(2023. 4. 1.기준)Unnamed: 1Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15# duplicates
0<NA>소계<NA><NA><NA><NA><NA><NA><NA><NA>5