Overview

Dataset statistics

Number of variables7
Number of observations24
Missing cells117
Missing cells (%)69.6%
Duplicate rows1
Duplicate rows (%)4.2%
Total size in memory1.4 KiB
Average record size in memory61.5 B

Variable types

Text7

Dataset

Description시민의 질병을 사전에 예방하고자 국가에서 지정한 필수 예방접종에 관한 사항
Author경상남도 밀양시
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=3035794

Alerts

Dataset has 1 (4.2%) duplicate rowsDuplicates
○ 국가필수예방접종 has 18 (75.0%) missing valuesMissing
Unnamed: 1 has 9 (37.5%) missing valuesMissing
Unnamed: 2 has 14 (58.3%) missing valuesMissing
Unnamed: 3 has 14 (58.3%) missing valuesMissing
Unnamed: 4 has 21 (87.5%) missing valuesMissing
Unnamed: 5 has 20 (83.3%) missing valuesMissing
Unnamed: 6 has 21 (87.5%) missing valuesMissing

Reproduction

Analysis started2023-12-11 00:38:06.479190
Analysis finished2023-12-11 00:38:07.099014
Duration0.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

○ 국가필수예방접종
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing18
Missing (%)75.0%
Memory size324.0 B
2023-12-11T09:38:07.229043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length53.5
Mean length46
Min length2

Characters and Unicode

Total characters276
Distinct characters115
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row구분
2nd row영유아 필수 접종
3rd row※ 접종시간 : 미취학아동 오전9시 ~ 오후 12시까지, 취학아동 오전9시 ~ 오후 3시까지
4th row※ 예방접종수첩은 초등학교 입학, 유학이나 이민시 예방접종증명서로 활용되므로 잘 보관하시기 바랍니다.
5th row※ 필수예방접종 11종에 대하여는 관내 만 12세이하 어린이는 관내 위탁 의료기관에서도 본인부담금 없이 접종받을 수 있습니다.
ValueCountFrequency (%)
4
 
6.8%
※ 3
 
5.1%
관내 2
 
3.4%
필수예방접종 2
 
3.4%
오전9시 2
 
3.4%
오후 2
 
3.4%
구분 1
 
1.7%
결핵(피내용 1
 
1.7%
위탁 1
 
1.7%
의료기관에서도 1
 
1.7%
Other values (40) 40
67.8%
2023-12-11T09:38:07.547559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
 
18.5%
, 11
 
4.0%
종 9
 
3.3%
접 7
 
2.5%
시 7
 
2.5%
1 6
 
2.2%
수 6
 
2.2%
이 5
 
1.8%
학 5
 
1.8%
오 5
 
1.8%
Other values (105) 164
59.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 161
58.3%
Space Separator 51
 
18.5%
Other Punctuation 18
 
6.5%
Uppercase Letter 14
 
5.1%
Decimal Number 11
 
4.0%
Lowercase Letter 10
 
3.6%
Open Punctuation 3
 
1.1%
Close Punctuation 3
 
1.1%
Math Symbol 2
 
0.7%
Control 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
종 9
 
5.6%
접 7
 
4.3%
시 7
 
4.3%
수 6
 
3.7%
이 5
 
3.1%
학 5
 
3.1%
오 5
 
3.1%
방 4
 
2.5%
예 4
 
2.5%
관 4
 
2.5%
Other values (77) 105
65.2%
Uppercase Letter
ValueCountFrequency (%)
T 4
28.6%
D 2
14.3%
M 2
14.3%
H 1
 
7.1%
B 1
 
7.1%
I 1
 
7.1%
P 1
 
7.1%
V 1
 
7.1%
R 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
a 3
30.0%
p 3
30.0%
d 2
20.0%
i 1
 
10.0%
b 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 11
61.1%
※ 3
 
16.7%
. 2
 
11.1%
: 2
 
11.1%
Decimal Number
ValueCountFrequency (%)
1 6
54.5%
9 2
 
18.2%
2 2
 
18.2%
3 1
 
9.1%
Space Separator
ValueCountFrequency (%)
51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 161
58.3%
Common 91
33.0%
Latin 24
 
8.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
종 9
 
5.6%
접 7
 
4.3%
시 7
 
4.3%
수 6
 
3.7%
이 5
 
3.1%
학 5
 
3.1%
오 5
 
3.1%
방 4
 
2.5%
예 4
 
2.5%
관 4
 
2.5%
Other values (77) 105
65.2%
Common
ValueCountFrequency (%)
51
56.0%
, 11
 
12.1%
1 6
 
6.6%
( 3
 
3.3%
) 3
 
3.3%
※ 3
 
3.3%
. 2
 
2.2%
~ 2
 
2.2%
2
 
2.2%
9 2
 
2.2%
Other values (4) 6
 
6.6%
Latin
ValueCountFrequency (%)
T 4
16.7%
a 3
12.5%
p 3
12.5%
d 2
8.3%
D 2
8.3%
M 2
8.3%
H 1
 
4.2%
i 1
 
4.2%
B 1
 
4.2%
I 1
 
4.2%
Other values (4) 4
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 161
58.3%
ASCII 112
40.6%
Punctuation 3
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
45.5%
, 11
 
9.8%
1 6
 
5.4%
T 4
 
3.6%
a 3
 
2.7%
( 3
 
2.7%
) 3
 
2.7%
p 3
 
2.7%
. 2
 
1.8%
d 2
 
1.8%
Other values (17) 24
21.4%
Hangul
ValueCountFrequency (%)
종 9
 
5.6%
접 7
 
4.3%
시 7
 
4.3%
수 6
 
3.7%
이 5
 
3.1%
학 5
 
3.1%
오 5
 
3.1%
방 4
 
2.5%
예 4
 
2.5%
관 4
 
2.5%
Other values (77) 105
65.2%
Punctuation
ValueCountFrequency (%)
※ 3
100.0%

Unnamed: 1
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing9
Missing (%)37.5%
Memory size324.0 B
2023-12-11T09:38:07.743970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length11
Mean length6.9333333
Min length2

Characters and Unicode

Total characters104
Distinct characters55
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)100.0%

Sample

1st row종류
2nd rowBCG
3rd rowB형간염
4th row(소아)
5th rowDPT(디프테리아, 백일해, 파상풍)
ValueCountFrequency (%)
종류 1
 
5.0%
bcg 1
 
5.0%
디프테리아 1
 
5.0%
td 1
 
5.0%
또는 1
 
5.0%
tdap 1
 
5.0%
일본뇌염 1
 
5.0%
수두 1
 
5.0%
홍역,볼거리,풍진 1
 
5.0%
mmr 1
 
5.0%
Other values (10) 10
50.0%
2023-12-11T09:38:08.055287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 6
 
5.8%
5
 
4.8%
( 5
 
4.8%
) 5
 
4.8%
T 4
 
3.8%
아 4
 
3.8%
일 3
 
2.9%
백 3
 
2.9%
풍 3
 
2.9%
P 3
 
2.9%
Other values (45) 63
60.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 56
53.8%
Uppercase Letter 19
 
18.3%
Lowercase Letter 7
 
6.7%
Other Punctuation 6
 
5.8%
Space Separator 5
 
4.8%
Open Punctuation 5
 
4.8%
Close Punctuation 5
 
4.8%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
아 4
 
7.1%
일 3
 
5.4%
백 3
 
5.4%
풍 3
 
5.4%
염 3
 
5.4%
리 3
 
5.4%
해 2
 
3.6%
파 2
 
3.6%
상 2
 
3.6%
뇌 2
 
3.6%
Other values (24) 29
51.8%
Uppercase Letter
ValueCountFrequency (%)
T 4
21.1%
P 3
15.8%
M 2
10.5%
D 2
10.5%
B 2
10.5%
R 1
 
5.3%
H 1
 
5.3%
V 1
 
5.3%
I 1
 
5.3%
G 1
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
a 2
28.6%
d 2
28.6%
p 1
14.3%
b 1
14.3%
i 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 56
53.8%
Latin 26
25.0%
Common 22
 
21.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
아 4
 
7.1%
일 3
 
5.4%
백 3
 
5.4%
풍 3
 
5.4%
염 3
 
5.4%
리 3
 
5.4%
해 2
 
3.6%
파 2
 
3.6%
상 2
 
3.6%
뇌 2
 
3.6%
Other values (24) 29
51.8%
Latin
ValueCountFrequency (%)
T 4
15.4%
P 3
11.5%
a 2
 
7.7%
M 2
 
7.7%
D 2
 
7.7%
d 2
 
7.7%
B 2
 
7.7%
R 1
 
3.8%
p 1
 
3.8%
b 1
 
3.8%
Other values (6) 6
23.1%
Common
ValueCountFrequency (%)
, 6
27.3%
5
22.7%
( 5
22.7%
) 5
22.7%
- 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 56
53.8%
ASCII 48
46.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 6
12.5%
5
10.4%
( 5
10.4%
) 5
10.4%
T 4
 
8.3%
P 3
 
6.2%
a 2
 
4.2%
M 2
 
4.2%
D 2
 
4.2%
d 2
 
4.2%
Other values (11) 12
25.0%
Hangul
ValueCountFrequency (%)
아 4
 
7.1%
일 3
 
5.4%
백 3
 
5.4%
풍 3
 
5.4%
염 3
 
5.4%
리 3
 
5.4%
해 2
 
3.6%
파 2
 
3.6%
상 2
 
3.6%
뇌 2
 
3.6%
Other values (24) 29
51.8%

Unnamed: 2
Text

MISSING 

Distinct9
Distinct (%)90.0%
Missing14
Missing (%)58.3%
Memory size324.0 B
2023-12-11T09:38:08.247619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length10.5
Mean length10.4
Min length4

Characters and Unicode

Total characters104
Distinct characters28
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

Unique8 ?
Unique (%)80.0%

Sample

1st row접종시기
2nd row기초접종
3rd row생후4주이내
4th row생후 0, 1, 6개월
5th row1차 : 생후2개월 2차 : 생후4개월 3차 : 생후6개월
ValueCountFrequency (%)
3
 
13.0%
생후12~15개월 2
 
8.7%
2차 1
 
4.3%
접종 1
 
4.3%
1,2,3차 1
 
4.3%
사이 1
 
4.3%
생후12~36개월 1
 
4.3%
생후6개월 1
 
4.3%
3차 1
 
4.3%
생후4개월 1
 
4.3%
Other values (10) 10
43.5%
2023-12-11T09:38:08.547341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
 
10.6%
11
 
10.6%
생 8
 
7.7%
후 8
 
7.7%
2 7
 
6.7%
개 7
 
6.7%
월 7
 
6.7%
, 4
 
3.8%
차 4
 
3.8%
~ 4
 
3.8%
Other values (18) 33
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 51
49.0%
Decimal Number 29
27.9%
Space Separator 11
 
10.6%
Other Punctuation 7
 
6.7%
Math Symbol 4
 
3.8%
Control 2
 
1.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
생 8
15.7%
후 8
15.7%
개 7
13.7%
월 7
13.7%
차 4
7.8%
종 3
 
5.9%
접 3
 
5.9%
이 2
 
3.9%
기 2
 
3.9%
만 1
 
2.0%
Other values (6) 6
11.8%
Decimal Number
ValueCountFrequency (%)
1 11
37.9%
2 7
24.1%
3 3
 
10.3%
6 3
 
10.3%
4 2
 
6.9%
5 2
 
6.9%
0 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 4
57.1%
: 3
42.9%
Space Separator
ValueCountFrequency (%)
11
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 53
51.0%
Hangul 51
49.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
생 8
15.7%
후 8
15.7%
개 7
13.7%
월 7
13.7%
차 4
7.8%
종 3
 
5.9%
접 3
 
5.9%
이 2
 
3.9%
기 2
 
3.9%
만 1
 
2.0%
Other values (6) 6
11.8%
Common
ValueCountFrequency (%)
1 11
20.8%
11
20.8%
2 7
13.2%
, 4
 
7.5%
~ 4
 
7.5%
: 3
 
5.7%
3 3
 
5.7%
6 3
 
5.7%
4 2
 
3.8%
5 2
 
3.8%
Other values (2) 3
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 53
51.0%
Hangul 51
49.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
20.8%
11
20.8%
2 7
13.2%
, 4
 
7.5%
~ 4
 
7.5%
: 3
 
5.7%
3 3
 
5.7%
6 3
 
5.7%
4 2
 
3.8%
5 2
 
3.8%
Other values (2) 3
 
5.7%
Hangul
ValueCountFrequency (%)
생 8
15.7%
후 8
15.7%
개 7
13.7%
월 7
13.7%
차 4
7.8%
종 3
 
5.9%
접 3
 
5.9%
이 2
 
3.9%
기 2
 
3.9%
만 1
 
2.0%
Other values (6) 6
11.8%

Unnamed: 3
Text

MISSING 

Distinct9
Distinct (%)90.0%
Missing14
Missing (%)58.3%
Memory size324.0 B
2023-12-11T09:38:08.689531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length8.5
Mean length8.1
Min length4

Characters and Unicode

Total characters81
Distinct characters33
Distinct categories8 ?
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 (%)80.0%

Sample

1st row추가접종
2nd row고위험군
3rd row1차 : 생후18개월 2차 : 만 4~6세
4th row만4~6세
5th row12~15개월
ValueCountFrequency (%)
4
18.2%
만4~6세 2
 
9.1%
추가접종 2
 
9.1%
1차 2
 
9.1%
2차 2
 
9.1%
고위험군 1
 
4.5%
생후18개월 1
 
4.5%
만 1
 
4.5%
4~6세 1
 
4.5%
12~15개월 1
 
4.5%
Other values (5) 5
22.7%
2023-12-11T09:38:08.961679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11
 
13.6%
1 8
 
9.9%
만 5
 
6.2%
세 5
 
6.2%
2 4
 
4.9%
차 4
 
4.9%
: 4
 
4.9%
~ 4
 
4.9%
6 4
 
4.9%
4 3
 
3.7%
Other values (23) 29
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37
45.7%
Decimal Number 22
27.2%
Space Separator 11
 
13.6%
Other Punctuation 4
 
4.9%
Math Symbol 4
 
4.9%
Lowercase Letter 1
 
1.2%
Uppercase Letter 1
 
1.2%
Control 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
만 5
13.5%
세 5
13.5%
차 4
 
10.8%
접 2
 
5.4%
추 2
 
5.4%
월 2
 
5.4%
종 2
 
5.4%
개 2
 
5.4%
가 2
 
5.4%
군 1
 
2.7%
Other values (10) 10
27.0%
Decimal Number
ValueCountFrequency (%)
1 8
36.4%
2 4
18.2%
6 4
18.2%
4 3
 
13.6%
0 1
 
4.5%
5 1
 
4.5%
8 1
 
4.5%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
: 4
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Lowercase Letter
ValueCountFrequency (%)
d 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
T 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
51.9%
Hangul 37
45.7%
Latin 2
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
만 5
13.5%
세 5
13.5%
차 4
 
10.8%
접 2
 
5.4%
추 2
 
5.4%
월 2
 
5.4%
종 2
 
5.4%
개 2
 
5.4%
가 2
 
5.4%
군 1
 
2.7%
Other values (10) 10
27.0%
Common
ValueCountFrequency (%)
11
26.2%
1 8
19.0%
2 4
 
9.5%
: 4
 
9.5%
~ 4
 
9.5%
6 4
 
9.5%
4 3
 
7.1%
0 1
 
2.4%
5 1
 
2.4%
1
 
2.4%
Latin
ValueCountFrequency (%)
d 1
50.0%
T 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44
54.3%
Hangul 37
45.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11
25.0%
1 8
18.2%
2 4
 
9.1%
: 4
 
9.1%
~ 4
 
9.1%
6 4
 
9.1%
4 3
 
6.8%
d 1
 
2.3%
T 1
 
2.3%
0 1
 
2.3%
Other values (3) 3
 
6.8%
Hangul
ValueCountFrequency (%)
만 5
13.5%
세 5
13.5%
차 4
 
10.8%
접 2
 
5.4%
추 2
 
5.4%
월 2
 
5.4%
종 2
 
5.4%
개 2
 
5.4%
가 2
 
5.4%
군 1
 
2.7%
Other values (10) 10
27.0%

Unnamed: 4
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing21
Missing (%)87.5%
Memory size324.0 B
2023-12-11T09:38:09.104263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length6.6666667
Min length4

Characters and Unicode

Total characters20
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row접종시간
2nd row매주 수요일
3rd row월, 화, 목, 금
ValueCountFrequency (%)
접종시간 1
14.3%
매주 1
14.3%
수요일 1
14.3%
월 1
14.3%
화 1
14.3%
목 1
14.3%
금 1
14.3%
2023-12-11T09:38:09.374161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
20.0%
, 3
15.0%
접 1
 
5.0%
종 1
 
5.0%
시 1
 
5.0%
간 1
 
5.0%
매 1
 
5.0%
주 1
 
5.0%
수 1
 
5.0%
요 1
 
5.0%
Other values (5) 5
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
65.0%
Space Separator 4
 
20.0%
Other Punctuation 3
 
15.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
접 1
 
7.7%
종 1
 
7.7%
시 1
 
7.7%
간 1
 
7.7%
매 1
 
7.7%
주 1
 
7.7%
수 1
 
7.7%
요 1
 
7.7%
일 1
 
7.7%
월 1
 
7.7%
Other values (3) 3
23.1%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
65.0%
Common 7
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
접 1
 
7.7%
종 1
 
7.7%
시 1
 
7.7%
간 1
 
7.7%
매 1
 
7.7%
주 1
 
7.7%
수 1
 
7.7%
요 1
 
7.7%
일 1
 
7.7%
월 1
 
7.7%
Other values (3) 3
23.1%
Common
ValueCountFrequency (%)
4
57.1%
, 3
42.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
65.0%
ASCII 7
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
57.1%
, 3
42.9%
Hangul
ValueCountFrequency (%)
접 1
 
7.7%
종 1
 
7.7%
시 1
 
7.7%
간 1
 
7.7%
매 1
 
7.7%
주 1
 
7.7%
수 1
 
7.7%
요 1
 
7.7%
일 1
 
7.7%
월 1
 
7.7%
Other values (3) 3
23.1%

Unnamed: 5
Text

MISSING 

Distinct4
Distinct (%)100.0%
Missing20
Missing (%)83.3%
Memory size324.0 B
2023-12-11T09:38:09.563117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3.5
Mean length4
Min length2

Characters and Unicode

Total characters16
Distinct characters12
Distinct categories3 ?
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 (%)100.0%

Sample

1st row접종비
2nd row무료
3rd row성인 추가접종
4th row: 유료
ValueCountFrequency (%)
접종비 1
16.7%
무료 1
16.7%
성인 1
16.7%
추가접종 1
16.7%
1
16.7%
유료 1
16.7%
2023-12-11T09:38:09.813111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
접 2
12.5%
종 2
12.5%
료 2
12.5%
2
12.5%
비 1
6.2%
무 1
6.2%
성 1
6.2%
인 1
6.2%
추 1
6.2%
가 1
6.2%
Other values (2) 2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13
81.2%
Space Separator 2
 
12.5%
Other Punctuation 1
 
6.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
접 2
15.4%
종 2
15.4%
료 2
15.4%
비 1
7.7%
무 1
7.7%
성 1
7.7%
인 1
7.7%
추 1
7.7%
가 1
7.7%
유 1
7.7%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13
81.2%
Common 3
 
18.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
접 2
15.4%
종 2
15.4%
료 2
15.4%
비 1
7.7%
무 1
7.7%
성 1
7.7%
인 1
7.7%
추 1
7.7%
가 1
7.7%
유 1
7.7%
Common
ValueCountFrequency (%)
2
66.7%
: 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13
81.2%
ASCII 3
 
18.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
접 2
15.4%
종 2
15.4%
료 2
15.4%
비 1
7.7%
무 1
7.7%
성 1
7.7%
인 1
7.7%
추 1
7.7%
가 1
7.7%
유 1
7.7%
ASCII
ValueCountFrequency (%)
2
66.7%
: 1
33.3%

Unnamed: 6
Text

MISSING 

Distinct3
Distinct (%)100.0%
Missing21
Missing (%)87.5%
Memory size324.0 B
2023-12-11T09:38:09.961056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length6.3333333
Min length4

Characters and Unicode

Total characters19
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)100.0%

Sample

1st row준비물 및
2nd row주의사항
3rd row예방접종 수첩지참.
ValueCountFrequency (%)
준비물 1
20.0%
및 1
20.0%
주의사항 1
20.0%
예방접종 1
20.0%
수첩지참 1
20.0%
2023-12-11T09:38:10.270265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
 
10.5%
준 1
 
5.3%
방 1
 
5.3%
참 1
 
5.3%
지 1
 
5.3%
첩 1
 
5.3%
수 1
 
5.3%
종 1
 
5.3%
접 1
 
5.3%
예 1
 
5.3%
Other values (8) 8
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
84.2%
Space Separator 2
 
10.5%
Other Punctuation 1
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
준 1
 
6.2%
방 1
 
6.2%
참 1
 
6.2%
지 1
 
6.2%
첩 1
 
6.2%
수 1
 
6.2%
종 1
 
6.2%
접 1
 
6.2%
예 1
 
6.2%
비 1
 
6.2%
Other values (6) 6
37.5%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
84.2%
Common 3
 
15.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
준 1
 
6.2%
방 1
 
6.2%
참 1
 
6.2%
지 1
 
6.2%
첩 1
 
6.2%
수 1
 
6.2%
종 1
 
6.2%
접 1
 
6.2%
예 1
 
6.2%
비 1
 
6.2%
Other values (6) 6
37.5%
Common
ValueCountFrequency (%)
2
66.7%
. 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
84.2%
ASCII 3
 
15.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
66.7%
. 1
33.3%
Hangul
ValueCountFrequency (%)
준 1
 
6.2%
방 1
 
6.2%
참 1
 
6.2%
지 1
 
6.2%
첩 1
 
6.2%
수 1
 
6.2%
종 1
 
6.2%
접 1
 
6.2%
예 1
 
6.2%
비 1
 
6.2%
Other values (6) 6
37.5%

Correlations

2023-12-11T09:38:10.366480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
○ 국가필수예방접종Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
○ 국가필수예방접종1.0000.0000.000NaN0.0000.0000.000
Unnamed: 10.0001.0001.0001.0001.0001.0000.000
Unnamed: 20.0001.0001.0001.0001.0001.0001.000
Unnamed: 3NaN1.0001.0001.000NaN0.000NaN
Unnamed: 40.0001.0001.000NaN1.0000.0000.000
Unnamed: 50.0001.0001.0000.0000.0001.0000.000
Unnamed: 60.0000.0001.000NaN0.0000.0001.000

Missing values

2023-12-11T09:38:06.811799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:38:06.917348image/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.
2023-12-11T09:38:07.023726image/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

○ 국가필수예방접종Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0구분종류접종시기<NA>접종시간접종비준비물 및
1<NA><NA>기초접종추가접종<NA><NA>주의사항
2영유아 필수 접종BCG생후4주이내<NA>매주 수요일무료예방접종 수첩지참.
3<NA><NA><NA><NA><NA><NA><NA>
4<NA>B형간염생후 0, 1, 6개월고위험군월, 화, 목, 금<NA><NA>
5<NA>(소아)<NA><NA><NA><NA><NA>
6<NA>DPT(디프테리아, 백일해, 파상풍)1차 : 생후2개월 2차 : 생후4개월 3차 : 생후6개월1차 : 생후18개월 2차 : 만 4~6세<NA><NA><NA>
7<NA><NA><NA><NA><NA><NA><NA>
8<NA><NA><NA><NA><NA><NA><NA>
9<NA>소아마비<NA>만4~6세<NA><NA><NA>
○ 국가필수예방접종Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
14<NA>수두생후12~15개월<NA><NA><NA><NA>
15<NA>일본뇌염생후12~36개월 사이1차 : 만6세<NA><NA><NA>
16<NA><NA>1,2,3차 접종2차 : 만12세<NA><NA><NA>
17<NA>Tdap 또는 Td만11~12세10년마다 1회<NA>성인 추가접종<NA>
18<NA>(디프테리아,<NA>Td로 추가접종<NA>: 유료<NA>
19<NA>백일해,파상풍)<NA><NA><NA><NA><NA>
20※ 접종시간 : 미취학아동 오전9시 ~ 오후 12시까지, 취학아동 오전9시 ~ 오후 3시까지<NA><NA><NA><NA><NA><NA>
21※ 예방접종수첩은 초등학교 입학, 유학이나 이민시 예방접종증명서로 활용되므로 잘 보관하시기 바랍니다.<NA><NA><NA><NA><NA><NA>
22※ 필수예방접종 11종에 대하여는 관내 만 12세이하 어린이는 관내 위탁 의료기관에서도 본인부담금 없이 접종받을 수 있습니다.<NA><NA><NA><NA><NA><NA>
23(필수예방접종 11종 : 결핵(피내용), B형간염, DTap 폴리오, DTap-IPV 혼합백신, Td, Tdap, 수두, MMR, 일본뇌염(사백신), Hib)<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

○ 국가필수예방접종Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6# duplicates
0<NA><NA><NA><NA><NA><NA><NA>3