Overview

Dataset statistics

Number of variables8
Number of observations232
Missing cells343
Missing cells (%)18.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.6 KiB
Average record size in memory64.6 B

Variable types

DateTime1
Text6
Categorical1

Dataset

Description육군훈련소의 월별 병영 표준 식단 정보입니다. 조식, 중식, 석식 메뉴 및 메뉴별 열량, 일일 총 열량 데이터를 제공합니다.
Author국방부
URLhttps://www.data.go.kr/data/15069402/fileData.do

Alerts

조식 has 16 (6.9%) missing valuesMissing
조식열량 has 17 (7.3%) missing valuesMissing
중식 has 84 (36.2%) missing valuesMissing
중식열량 has 84 (36.2%) missing valuesMissing
석식 has 71 (30.6%) missing valuesMissing
석식열량 has 71 (30.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 18:14:08.244583
Analysis finished2023-12-12 18:14:09.715151
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

Distinct31
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
Minimum2021-08-01 00:00:00
Maximum2021-08-31 00:00:00
2023-12-13T03:14:09.786082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:14:09.935853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)

조식
Text

MISSING 

Distinct63
Distinct (%)29.2%
Missing16
Missing (%)6.9%
Memory size1.9 KiB
2023-12-13T03:14:10.248588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length11.62037
Min length1

Characters and Unicode

Total characters2510
Distinct characters165
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)12.5%

Sample

1st row밥
2nd row쇠고기미역국(05)(16)
3rd row달콤돼지고기볶음(05)(06)(10)
4th row두부구이(05)(06)
5th row배추김치(7~9월)
ValueCountFrequency (%)
밥 31
 
13.4%
배추김치(7~9월 31
 
13.4%
우유(백색우유(200ml,연간))(02 22
 
9.5%
맛김 11
 
4.7%
아이스크림 7
 
3.0%
감자조림(05)(06 6
 
2.6%
오이무침(06 6
 
2.6%
콩나물무채국(05 6
 
2.6%
쇠고기무국(05)(16 5
 
2.2%
닭간장소스찜(05)(06)(15 5
 
2.2%
Other values (59) 102
44.0%
2023-12-13T03:14:10.727972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 318
 
12.7%
( 318
 
12.7%
0 247
 
9.8%
5 90
 
3.6%
6 67
 
2.7%
1 66
 
2.6%
2 58
 
2.3%
우 48
 
1.9%
김 47
 
1.9%
유 47
 
1.9%
Other values (155) 1204
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1117
44.5%
Decimal Number 609
24.3%
Close Punctuation 318
 
12.7%
Open Punctuation 318
 
12.7%
Uppercase Letter 44
 
1.8%
Other Punctuation 43
 
1.7%
Math Symbol 33
 
1.3%
Space Separator 16
 
0.6%
Lowercase Letter 9
 
0.4%
Other Symbol 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 48
 
4.3%
김 47
 
4.2%
유 47
 
4.2%
치 40
 
3.6%
추 39
 
3.5%
배 35
 
3.1%
월 33
 
3.0%
밥 31
 
2.8%
간 28
 
2.5%
기 28
 
2.5%
Other values (132) 741
66.3%
Decimal Number
ValueCountFrequency (%)
0 247
40.6%
5 90
 
14.8%
6 67
 
11.0%
1 66
 
10.8%
2 58
 
9.5%
9 37
 
6.1%
7 35
 
5.7%
3 4
 
0.7%
8 3
 
0.5%
4 2
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
l 4
44.4%
m 4
44.4%
g 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
, 39
90.7%
/ 4
 
9.3%
Math Symbol
ValueCountFrequency (%)
~ 31
93.9%
∼ 2
 
6.1%
Uppercase Letter
ValueCountFrequency (%)
L 22
50.0%
M 22
50.0%
Close Punctuation
ValueCountFrequency (%)
) 318
100.0%
Open Punctuation
ValueCountFrequency (%)
( 318
100.0%
Space Separator
ValueCountFrequency (%)
16
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1340
53.4%
Hangul 1117
44.5%
Latin 53
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 48
 
4.3%
김 47
 
4.2%
유 47
 
4.2%
치 40
 
3.6%
추 39
 
3.5%
배 35
 
3.1%
월 33
 
3.0%
밥 31
 
2.8%
간 28
 
2.5%
기 28
 
2.5%
Other values (132) 741
66.3%
Common
ValueCountFrequency (%)
) 318
23.7%
( 318
23.7%
0 247
18.4%
5 90
 
6.7%
6 67
 
5.0%
1 66
 
4.9%
2 58
 
4.3%
, 39
 
2.9%
9 37
 
2.8%
7 35
 
2.6%
Other values (8) 65
 
4.9%
Latin
ValueCountFrequency (%)
L 22
41.5%
M 22
41.5%
l 4
 
7.5%
m 4
 
7.5%
g 1
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1388
55.3%
Hangul 1117
44.5%
CJK Compat 3
 
0.1%
Math Operators 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 318
22.9%
( 318
22.9%
0 247
17.8%
5 90
 
6.5%
6 67
 
4.8%
1 66
 
4.8%
2 58
 
4.2%
, 39
 
2.8%
9 37
 
2.7%
7 35
 
2.5%
Other values (11) 113
 
8.1%
Hangul
ValueCountFrequency (%)
우 48
 
4.3%
김 47
 
4.2%
유 47
 
4.2%
치 40
 
3.6%
추 39
 
3.5%
배 35
 
3.1%
월 33
 
3.0%
밥 31
 
2.8%
간 28
 
2.5%
기 28
 
2.5%
Other values (132) 741
66.3%
CJK Compat
ValueCountFrequency (%)
㎖ 3
100.0%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%

조식열량
Text

MISSING 

Distinct61
Distinct (%)28.4%
Missing17
Missing (%)7.3%
Memory size1.9 KiB
2023-12-13T03:14:11.021305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.2790698
Min length5

Characters and Unicode

Total characters1780
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)10.7%

Sample

1st row363kcal
2nd row37.54kcal
3rd row267kcal
4th row160.99kcal
5th row11.75kcal
ValueCountFrequency (%)
363kcal 31
 
14.4%
11.75kcal 31
 
14.4%
122kcal 20
 
9.3%
0kcal 11
 
5.1%
27.71kcal 6
 
2.8%
27.52kcal 6
 
2.8%
149.04kcal 6
 
2.8%
47.53kcal 5
 
2.3%
147.94kcal 5
 
2.3%
319.71kcal 3
 
1.4%
Other values (51) 91
42.3%
2023-12-13T03:14:11.443240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 215
12.1%
c 215
12.1%
a 215
12.1%
l 215
12.1%
1 140
7.9%
. 131
7.4%
2 117
6.6%
3 108
6.1%
7 104
5.8%
4 77
 
4.3%
Other values (5) 243
13.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 860
48.3%
Decimal Number 789
44.3%
Other Punctuation 131
 
7.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 140
17.7%
2 117
14.8%
3 108
13.7%
7 104
13.2%
4 77
9.8%
6 72
9.1%
5 70
8.9%
0 39
 
4.9%
9 34
 
4.3%
8 28
 
3.5%
Lowercase Letter
ValueCountFrequency (%)
k 215
25.0%
c 215
25.0%
a 215
25.0%
l 215
25.0%
Other Punctuation
ValueCountFrequency (%)
. 131
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 920
51.7%
Latin 860
48.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 140
15.2%
. 131
14.2%
2 117
12.7%
3 108
11.7%
7 104
11.3%
4 77
8.4%
6 72
7.8%
5 70
7.6%
0 39
 
4.2%
9 34
 
3.7%
Latin
ValueCountFrequency (%)
k 215
25.0%
c 215
25.0%
a 215
25.0%
l 215
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1780
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 215
12.1%
c 215
12.1%
a 215
12.1%
l 215
12.1%
1 140
7.9%
. 131
7.4%
2 117
6.6%
3 108
6.1%
7 104
5.8%
4 77
 
4.3%
Other values (5) 243
13.7%

중식
Text

MISSING 

Distinct62
Distinct (%)41.9%
Missing84
Missing (%)36.2%
Memory size1.9 KiB
2023-12-13T03:14:11.707076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length10.344595
Min length1

Characters and Unicode

Total characters1531
Distinct characters132
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

Unique36 ?
Unique (%)24.3%

Sample

1st row밥
2nd row닭곰탕(15)
3rd row계란찜(01)(09)
4th row풋고추된장무침(05)(06)
5th row깍두기(완제품)(09)
ValueCountFrequency (%)
밥 26
 
17.4%
배추김치(7~9월 11
 
7.4%
열무김치 9
 
6.0%
콩나물무침(05)(06 4
 
2.7%
배추된장국(05 4
 
2.7%
애호박나물(09)(10 4
 
2.7%
닭볶음탕(06)(15 4
 
2.7%
계란찜(01)(09 4
 
2.7%
깍두기(완제품)(09 4
 
2.7%
호박된장찌개(05)(06 3
 
2.0%
Other values (53) 76
51.0%
2023-12-13T03:14:12.429401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 215
 
14.0%
( 215
 
14.0%
0 172
 
11.2%
1 68
 
4.4%
5 65
 
4.2%
6 62
 
4.0%
밥 28
 
1.8%
9 26
 
1.7%
음 25
 
1.6%
볶 25
 
1.6%
Other values (122) 630
41.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 671
43.8%
Decimal Number 416
27.2%
Close Punctuation 215
 
14.0%
Open Punctuation 215
 
14.0%
Math Symbol 13
 
0.8%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
밥 28
 
4.2%
음 25
 
3.7%
볶 25
 
3.7%
무 23
 
3.4%
장 23
 
3.4%
치 22
 
3.3%
추 22
 
3.3%
김 21
 
3.1%
고 19
 
2.8%
기 18
 
2.7%
Other values (110) 445
66.3%
Decimal Number
ValueCountFrequency (%)
0 172
41.3%
1 68
 
16.3%
5 65
 
15.6%
6 62
 
14.9%
9 26
 
6.2%
7 19
 
4.6%
2 4
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 11
84.6%
+ 2
 
15.4%
Close Punctuation
ValueCountFrequency (%)
) 215
100.0%
Open Punctuation
ValueCountFrequency (%)
( 215
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 860
56.2%
Hangul 671
43.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
밥 28
 
4.2%
음 25
 
3.7%
볶 25
 
3.7%
무 23
 
3.4%
장 23
 
3.4%
치 22
 
3.3%
추 22
 
3.3%
김 21
 
3.1%
고 19
 
2.8%
기 18
 
2.7%
Other values (110) 445
66.3%
Common
ValueCountFrequency (%)
) 215
25.0%
( 215
25.0%
0 172
20.0%
1 68
 
7.9%
5 65
 
7.6%
6 62
 
7.2%
9 26
 
3.0%
7 19
 
2.2%
~ 11
 
1.3%
2 4
 
0.5%
Other values (2) 3
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 860
56.2%
Hangul 671
43.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 215
25.0%
( 215
25.0%
0 172
20.0%
1 68
 
7.9%
5 65
 
7.6%
6 62
 
7.2%
9 26
 
3.0%
7 19
 
2.2%
~ 11
 
1.3%
2 4
 
0.5%
Other values (2) 3
 
0.3%
Hangul
ValueCountFrequency (%)
밥 28
 
4.2%
음 25
 
3.7%
볶 25
 
3.7%
무 23
 
3.4%
장 23
 
3.4%
치 22
 
3.3%
추 22
 
3.3%
김 21
 
3.1%
고 19
 
2.8%
기 18
 
2.7%
Other values (110) 445
66.3%

중식열량
Text

MISSING 

Distinct61
Distinct (%)41.2%
Missing84
Missing (%)36.2%
Memory size1.9 KiB
2023-12-13T03:14:12.681665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.6621622
Min length5

Characters and Unicode

Total characters1282
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)23.6%

Sample

1st row363kcal
2nd row174.98kcal
3rd row96.89kcal
4th row28.05kcal
5th row15.2kcal
ValueCountFrequency (%)
363kcal 26
 
17.6%
11.75kcal 11
 
7.4%
12.8kcal 9
 
6.1%
30.08kcal 4
 
2.7%
42.43kcal 4
 
2.7%
113.82kcal 4
 
2.7%
266.51kcal 4
 
2.7%
96.89kcal 4
 
2.7%
15.2kcal 4
 
2.7%
20.35kcal 3
 
2.0%
Other values (51) 75
50.7%
2023-12-13T03:14:13.056494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 148
11.5%
c 148
11.5%
a 148
11.5%
l 148
11.5%
. 115
9.0%
1 94
7.3%
3 89
6.9%
2 70
 
5.5%
6 59
 
4.6%
5 57
 
4.4%
Other values (5) 206
16.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 592
46.2%
Decimal Number 575
44.9%
Other Punctuation 115
 
9.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 94
16.3%
3 89
15.5%
2 70
12.2%
6 59
10.3%
5 57
9.9%
8 53
9.2%
7 51
8.9%
9 35
 
6.1%
0 34
 
5.9%
4 33
 
5.7%
Lowercase Letter
ValueCountFrequency (%)
k 148
25.0%
c 148
25.0%
a 148
25.0%
l 148
25.0%
Other Punctuation
ValueCountFrequency (%)
. 115
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 690
53.8%
Latin 592
46.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 115
16.7%
1 94
13.6%
3 89
12.9%
2 70
10.1%
6 59
8.6%
5 57
8.3%
8 53
7.7%
7 51
7.4%
9 35
 
5.1%
0 34
 
4.9%
Latin
ValueCountFrequency (%)
k 148
25.0%
c 148
25.0%
a 148
25.0%
l 148
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1282
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 148
11.5%
c 148
11.5%
a 148
11.5%
l 148
11.5%
. 115
9.0%
1 94
7.3%
3 89
6.9%
2 70
 
5.5%
6 59
 
4.6%
5 57
 
4.4%
Other values (5) 206
16.1%

석식
Text

MISSING 

Distinct83
Distinct (%)51.6%
Missing71
Missing (%)30.6%
Memory size1.9 KiB
2023-12-13T03:14:13.309206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length12.571429
Min length1

Characters and Unicode

Total characters2024
Distinct characters181
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)32.3%

Sample

1st row밥
2nd row버섯쇠고기찌개(05)(06)(16)
3rd row새송이버섯야채볶음(05)(06)(10)
4th row고등어김치조림(05)(06)(07)
5th row배추김치(7~9월)
ValueCountFrequency (%)
깍두기(완제품)(09 12
 
7.3%
배추김치(7~9월 10
 
6.1%
우유(백색우유(200ml,연간))(02 9
 
5.5%
잡곡밥 5
 
3.0%
가지볶음(05)(06)(10 5
 
3.0%
밥 5
 
3.0%
열무김치 4
 
2.4%
무조림(05)(06)(10 4
 
2.4%
삶은계란(01 4
 
2.4%
된장국(일품용)(05)(16 3
 
1.8%
Other values (76) 104
63.0%
2023-12-13T03:14:13.755036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 301
 
14.9%
) 301
 
14.9%
0 226
 
11.2%
1 94
 
4.6%
6 74
 
3.7%
5 68
 
3.4%
2 36
 
1.8%
치 30
 
1.5%
9 28
 
1.4%
김 27
 
1.3%
Other values (171) 839
41.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 812
40.1%
Decimal Number 552
27.3%
Open Punctuation 301
 
14.9%
Close Punctuation 301
 
14.9%
Other Punctuation 18
 
0.9%
Uppercase Letter 18
 
0.9%
Math Symbol 12
 
0.6%
Lowercase Letter 6
 
0.3%
Space Separator 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
치 30
 
3.7%
김 27
 
3.3%
밥 27
 
3.3%
기 22
 
2.7%
우 22
 
2.7%
유 20
 
2.5%
두 18
 
2.2%
무 17
 
2.1%
추 17
 
2.1%
고 16
 
2.0%
Other values (150) 596
73.4%
Decimal Number
ValueCountFrequency (%)
0 226
40.9%
1 94
17.0%
6 74
 
13.4%
5 68
 
12.3%
2 36
 
6.5%
9 28
 
5.1%
7 18
 
3.3%
8 6
 
1.1%
3 1
 
0.2%
4 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 16
88.9%
/ 2
 
11.1%
Math Symbol
ValueCountFrequency (%)
~ 10
83.3%
∼ 2
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
L 9
50.0%
M 9
50.0%
Lowercase Letter
ValueCountFrequency (%)
m 3
50.0%
l 3
50.0%
Open Punctuation
ValueCountFrequency (%)
( 301
100.0%
Close Punctuation
ValueCountFrequency (%)
) 301
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1188
58.7%
Hangul 812
40.1%
Latin 24
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
치 30
 
3.7%
김 27
 
3.3%
밥 27
 
3.3%
기 22
 
2.7%
우 22
 
2.7%
유 20
 
2.5%
두 18
 
2.2%
무 17
 
2.1%
추 17
 
2.1%
고 16
 
2.0%
Other values (150) 596
73.4%
Common
ValueCountFrequency (%)
( 301
25.3%
) 301
25.3%
0 226
19.0%
1 94
 
7.9%
6 74
 
6.2%
5 68
 
5.7%
2 36
 
3.0%
9 28
 
2.4%
7 18
 
1.5%
, 16
 
1.3%
Other values (7) 26
 
2.2%
Latin
ValueCountFrequency (%)
L 9
37.5%
M 9
37.5%
m 3
 
12.5%
l 3
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1210
59.8%
Hangul 812
40.1%
Math Operators 2
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 301
24.9%
) 301
24.9%
0 226
18.7%
1 94
 
7.8%
6 74
 
6.1%
5 68
 
5.6%
2 36
 
3.0%
9 28
 
2.3%
7 18
 
1.5%
, 16
 
1.3%
Other values (10) 48
 
4.0%
Hangul
ValueCountFrequency (%)
치 30
 
3.7%
김 27
 
3.3%
밥 27
 
3.3%
기 22
 
2.7%
우 22
 
2.7%
유 20
 
2.5%
두 18
 
2.2%
무 17
 
2.1%
추 17
 
2.1%
고 16
 
2.0%
Other values (150) 596
73.4%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%

석식열량
Text

MISSING 

Distinct83
Distinct (%)51.6%
Missing71
Missing (%)30.6%
Memory size1.9 KiB
2023-12-13T03:14:14.084738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.931677
Min length5

Characters and Unicode

Total characters1438
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique52 ?
Unique (%)32.3%

Sample

1st row363kcal
2nd row58.21kcal
3rd row152.97kcal
4th row182.3kcal
5th row11.75kcal
ValueCountFrequency (%)
15.2kcal 12
 
7.5%
11.75kcal 10
 
6.2%
122kcal 9
 
5.6%
408.15kcal 5
 
3.1%
125.39kcal 5
 
3.1%
363kcal 5
 
3.1%
12.8kcal 4
 
2.5%
170.49kcal 4
 
2.5%
70.08kcal 4
 
2.5%
68.99kcal 3
 
1.9%
Other values (73) 100
62.1%
2023-12-13T03:14:14.572770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 161
11.2%
c 161
11.2%
a 161
11.2%
l 161
11.2%
. 140
9.7%
1 125
8.7%
5 89
 
6.2%
2 86
 
6.0%
4 57
 
4.0%
9 56
 
3.9%
Other values (5) 241
16.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 654
45.5%
Lowercase Letter 644
44.8%
Other Punctuation 140
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 125
19.1%
5 89
13.6%
2 86
13.1%
4 57
8.7%
9 56
8.6%
0 55
8.4%
3 51
7.8%
6 47
 
7.2%
7 45
 
6.9%
8 43
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
k 161
25.0%
c 161
25.0%
a 161
25.0%
l 161
25.0%
Other Punctuation
ValueCountFrequency (%)
. 140
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 794
55.2%
Latin 644
44.8%

Most frequent character per script

Common
ValueCountFrequency (%)
. 140
17.6%
1 125
15.7%
5 89
11.2%
2 86
10.8%
4 57
7.2%
9 56
 
7.1%
0 55
 
6.9%
3 51
 
6.4%
6 47
 
5.9%
7 45
 
5.7%
Latin
ValueCountFrequency (%)
k 161
25.0%
c 161
25.0%
a 161
25.0%
l 161
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1438
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 161
11.2%
c 161
11.2%
a 161
11.2%
l 161
11.2%
. 140
9.7%
1 125
8.7%
5 89
 
6.2%
2 86
 
6.0%
4 57
 
4.0%
9 56
 
3.9%
Other values (5) 241
16.8%

열량합계
Categorical

Distinct31
Distinct (%)13.4%
Missing0
Missing (%)0.0%
Memory size1.9 KiB
3502.21kcal
 
9
3517.41kcal
 
9
3310.09kcal
 
9
3215.02kcal
 
9
3583.09kcal
 
8
Other values (26)
188 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2408.63kcal
2nd row2408.63kcal
3rd row2408.63kcal
4th row2408.63kcal
5th row2408.63kcal

Common Values

ValueCountFrequency (%)
3502.21kcal 9
 
3.9%
3517.41kcal 9
 
3.9%
3310.09kcal 9
 
3.9%
3215.02kcal 9
 
3.9%
3583.09kcal 8
 
3.4%
2970.69kcal 8
 
3.4%
3034.61kcal 8
 
3.4%
2828.16kcal 8
 
3.4%
2815.88kcal 8
 
3.4%
3391.51kcal 8
 
3.4%
Other values (21) 148
63.8%

Length

2023-12-13T03:14:14.731480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3502.21kcal 9
 
3.9%
3310.09kcal 9
 
3.9%
3215.02kcal 9
 
3.9%
3517.41kcal 9
 
3.9%
3391.51kcal 8
 
3.4%
2960.62kcal 8
 
3.4%
2782.46kcal 8
 
3.4%
3492.97kcal 8
 
3.4%
3383.22kcal 8
 
3.4%
2815.88kcal 8
 
3.4%
Other values (21) 148
63.8%

Correlations

2023-12-13T03:14:14.814576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜조식조식열량중식중식열량석식석식열량열량합계
날짜1.0000.0000.0000.0000.0000.0000.0001.000
조식0.0001.0001.0000.9570.9550.9550.9550.000
조식열량0.0001.0001.0000.9570.9550.9550.9550.000
중식0.0000.9570.9571.0001.0000.9290.9290.000
중식열량0.0000.9550.9551.0001.0000.9200.9200.000
석식0.0000.9550.9550.9290.9201.0001.0000.000
석식열량0.0000.9550.9550.9290.9201.0001.0000.000
열량합계1.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T03:14:09.286721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:14:09.451176image/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.
2023-12-13T03:14:09.615674image/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

날짜조식조식열량중식중식열량석식석식열량열량합계
02021-08-01밥363kcal밥363kcal밥363kcal2408.63kcal
12021-08-01쇠고기미역국(05)(16)37.54kcal닭곰탕(15)174.98kcal버섯쇠고기찌개(05)(06)(16)58.21kcal2408.63kcal
22021-08-01달콤돼지고기볶음(05)(06)(10)267kcal계란찜(01)(09)96.89kcal새송이버섯야채볶음(05)(06)(10)152.97kcal2408.63kcal
32021-08-01두부구이(05)(06)160.99kcal풋고추된장무침(05)(06)28.05kcal고등어김치조림(05)(06)(07)182.3kcal2408.63kcal
42021-08-01배추김치(7~9월)11.75kcal깍두기(완제품)(09)15.2kcal배추김치(7~9월)11.75kcal2408.63kcal
52021-08-01우유(백색우유(200ML,연간))(02)122kcal<NA><NA><NA><NA>2408.63kcal
62021-08-01주스,과채<NA><NA><NA><NA><NA>2408.63kcal
72021-08-02밥363kcal밥363kcal잡곡밥408.15kcal3083.06kcal
82021-08-02순두부백탕(05)(09)(17)72.64kcal된장국(일품용)(05)(16)68.99kcal감자양파찌개(05)(06)68.22kcal3083.06kcal
92021-08-02마파감자(05)(06)(10)164.82kcal오삼불고기(05)(06)(10)(17)476.2kcal가지볶음(05)(06)(10)125.39kcal3083.06kcal
날짜조식조식열량중식중식열량석식석식열량열량합계
2222021-08-30<NA><NA><NA><NA>주스,망고코넛(340ml/캔)122.3kcal2828.16kcal
2232021-08-30<NA><NA><NA><NA>사인머스켓67.5kcal2828.16kcal
2242021-08-31밥363kcal밥363kcal흑미밥400.5kcal2960.62kcal
2252021-08-31순두부백탕(05)(09)(17)72.64kcal감자양파찌개(05)(06)68.22kcal된장국(일품용)(05)(16)68.99kcal2960.62kcal
2262021-08-31생선묵볶음(05)(06)117.96kcal오징어채간장볶음(06)(12)(17)122.18kcal가지볶음(05)(06)(10)125.39kcal2960.62kcal
2272021-08-31맛김0kcal돼지고기부추볶음(10)319.71kcal데리야끼갈릭치킨(01)(05)(06)(15)546.07kcal2960.62kcal
2282021-08-31쇠고기장조림(05)(06)(16)146.7kcal열무김치12.8kcal깍두기(완제품)(09)15.2kcal2960.62kcal
2292021-08-31배추김치(7~9월)11.75kcal<NA><NA><NA><NA>2960.62kcal
2302021-08-31우유(백색우유(200ML,연간))(02)122kcal<NA><NA><NA><NA>2960.62kcal
2312021-08-31주스,청포도(190ml/팩)84.51kcal<NA><NA><NA><NA>2960.62kcal