Overview

Dataset statistics

Number of variables8
Number of observations191
Missing cells115
Missing cells (%)7.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.1 KiB
Average record size in memory64.7 B

Variable types

DateTime1
Text6
Categorical1

Dataset

Description제8623부대의 식단정보입니다. 월간 표준식단 자료로서 날짜별 조식, 중식, 석식 식단과 식단별 열량 자료를 제공합니다.
Author국방부
URLhttps://www.data.go.kr/data/15081063/fileData.do

Alerts

조식 has 17 (8.9%) missing valuesMissing
조식열량 has 18 (9.4%) missing valuesMissing
중식 has 16 (8.4%) missing valuesMissing
중식열량 has 16 (8.4%) missing valuesMissing
석식 has 23 (12.0%) missing valuesMissing
석식열량 has 25 (13.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 06:27:10.696484
Analysis finished2023-12-12 06:27:12.488526
Duration1.79 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

날짜
Date

Distinct30
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
Minimum2021-08-01 00:00:00
Maximum2021-08-31 00:00:00
2023-12-12T15:27:12.577389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:27:12.752463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

조식
Text

MISSING 

Distinct72
Distinct (%)41.4%
Missing17
Missing (%)8.9%
Memory size1.6 KiB
2023-12-12T15:27:13.133229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length22
Mean length13.568966
Min length1

Characters and Unicode

Total characters2361
Distinct characters150
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

Unique46 ?
Unique (%)26.4%

Sample

1st row쇠고기야채덮밥(05)(06)(16)
2nd row생선묵찌개(05)(06)
3rd row부추겉절이(05)(06)
4th row배추김치(7~9월)
5th row우유(백색우유(200ML,연간))(02)
ValueCountFrequency (%)
우유(백색우유(200ml,연간))(02 28
 
16.0%
밥 22
 
12.6%
배추김치(7~9월 20
 
11.4%
오이양파무침(05)(06 5
 
2.9%
열무김치 5
 
2.9%
야채샐러드(햄버거용)(01)(12 3
 
1.7%
토마토슬라이스(12 3
 
1.7%
계란찜(01)(09 3
 
1.7%
시리얼 3
 
1.7%
해물순두부찌개(01)(05)(09)(10)(17)(18 3
 
1.7%
Other values (63) 80
45.7%
2023-12-12T15:27:13.632082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 328
 
13.9%
( 328
 
13.9%
0 271
 
11.5%
1 82
 
3.5%
6 72
 
3.0%
5 71
 
3.0%
2 68
 
2.9%
우 58
 
2.5%
유 57
 
2.4%
치 37
 
1.6%
Other values (140) 989
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 973
41.2%
Decimal Number 623
26.4%
Close Punctuation 328
 
13.9%
Open Punctuation 328
 
13.9%
Uppercase Letter 57
 
2.4%
Other Punctuation 29
 
1.2%
Math Symbol 20
 
0.8%
Space Separator 2
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
우 58
 
6.0%
유 57
 
5.9%
치 37
 
3.8%
김 34
 
3.5%
추 31
 
3.2%
연 31
 
3.2%
간 29
 
3.0%
백 29
 
3.0%
고 28
 
2.9%
색 28
 
2.9%
Other values (124) 611
62.8%
Decimal Number
ValueCountFrequency (%)
0 271
43.5%
1 82
 
13.2%
6 72
 
11.6%
5 71
 
11.4%
2 68
 
10.9%
9 29
 
4.7%
7 25
 
4.0%
8 5
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
L 29
50.9%
M 28
49.1%
Close Punctuation
ValueCountFrequency (%)
) 328
100.0%
Open Punctuation
ValueCountFrequency (%)
( 328
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1330
56.3%
Hangul 973
41.2%
Latin 58
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
우 58
 
6.0%
유 57
 
5.9%
치 37
 
3.8%
김 34
 
3.5%
추 31
 
3.2%
연 31
 
3.2%
간 29
 
3.0%
백 29
 
3.0%
고 28
 
2.9%
색 28
 
2.9%
Other values (124) 611
62.8%
Common
ValueCountFrequency (%)
) 328
24.7%
( 328
24.7%
0 271
20.4%
1 82
 
6.2%
6 72
 
5.4%
5 71
 
5.3%
2 68
 
5.1%
, 29
 
2.2%
9 29
 
2.2%
7 25
 
1.9%
Other values (3) 27
 
2.0%
Latin
ValueCountFrequency (%)
L 29
50.0%
M 28
48.3%
m 1
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1388
58.8%
Hangul 973
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 328
23.6%
( 328
23.6%
0 271
19.5%
1 82
 
5.9%
6 72
 
5.2%
5 71
 
5.1%
2 68
 
4.9%
, 29
 
2.1%
9 29
 
2.1%
L 29
 
2.1%
Other values (6) 81
 
5.8%
Hangul
ValueCountFrequency (%)
우 58
 
6.0%
유 57
 
5.9%
치 37
 
3.8%
김 34
 
3.5%
추 31
 
3.2%
연 31
 
3.2%
간 29
 
3.0%
백 29
 
3.0%
고 28
 
2.9%
색 28
 
2.9%
Other values (124) 611
62.8%

조식열량
Text

MISSING 

Distinct71
Distinct (%)41.0%
Missing18
Missing (%)9.4%
Memory size1.6 KiB
2023-12-12T15:27:13.944108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.4971098
Min length7

Characters and Unicode

Total characters1470
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

Unique45 ?
Unique (%)26.0%

Sample

1st row720.15kcal
2nd row88.37kcal
3rd row29.49kcal
4th row8.75kcal
5th row122kcal
ValueCountFrequency (%)
122kcal 28
 
16.2%
363kcal 22
 
12.7%
8.75kcal 20
 
11.6%
38.19kcal 5
 
2.9%
12.8kcal 5
 
2.9%
110.86kcal 3
 
1.7%
8.91kcal 3
 
1.7%
87.76kcal 3
 
1.7%
152.8kcal 3
 
1.7%
115.7kcal 3
 
1.7%
Other values (61) 78
45.1%
2023-12-12T15:27:14.468420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 173
11.8%
c 173
11.8%
a 173
11.8%
l 173
11.8%
. 123
8.4%
2 121
8.2%
1 107
7.3%
3 96
6.5%
8 78
5.3%
7 64
 
4.4%
Other values (5) 189
12.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 692
47.1%
Decimal Number 655
44.6%
Other Punctuation 123
 
8.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 121
18.5%
1 107
16.3%
3 96
14.7%
8 78
11.9%
7 64
9.8%
5 58
8.9%
6 54
8.2%
9 34
 
5.2%
0 25
 
3.8%
4 18
 
2.7%
Lowercase Letter
ValueCountFrequency (%)
k 173
25.0%
c 173
25.0%
a 173
25.0%
l 173
25.0%
Other Punctuation
ValueCountFrequency (%)
. 123
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 778
52.9%
Latin 692
47.1%

Most frequent character per script

Common
ValueCountFrequency (%)
. 123
15.8%
2 121
15.6%
1 107
13.8%
3 96
12.3%
8 78
10.0%
7 64
8.2%
5 58
7.5%
6 54
6.9%
9 34
 
4.4%
0 25
 
3.2%
Latin
ValueCountFrequency (%)
k 173
25.0%
c 173
25.0%
a 173
25.0%
l 173
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1470
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 173
11.8%
c 173
11.8%
a 173
11.8%
l 173
11.8%
. 123
8.4%
2 121
8.2%
1 107
7.3%
3 96
6.5%
8 78
5.3%
7 64
 
4.4%
Other values (5) 189
12.9%

중식
Text

MISSING 

Distinct103
Distinct (%)58.9%
Missing16
Missing (%)8.4%
Memory size1.6 KiB
2023-12-12T15:27:14.733238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length18
Mean length10.234286
Min length1

Characters and Unicode

Total characters1791
Distinct characters206
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)42.9%

Sample

1st row밥
2nd row버섯매운탕(05)(06)(16)
3rd row돈육야채볶음(05)(06)(10)
4th row계란찜(01)(09)
5th row배추김치(7~9월)
ValueCountFrequency (%)
배추김치(7~9월 14
 
7.6%
밥 14
 
7.6%
깍두기(완제품)(09 7
 
3.8%
조미김 7
 
3.8%
모듬쌈(05)(06 5
 
2.7%
열무김치 5
 
2.7%
짬뽕찌개(05)(10)(17 4
 
2.2%
잡곡밥 4
 
2.2%
돼지불고기(05)(06)(10 2
 
1.1%
오이풋고추된장무침(05 2
 
1.1%
Other values (101) 120
65.2%
2023-12-12T15:27:15.373418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 240
 
13.4%
( 240
 
13.4%
0 167
 
9.3%
1 78
 
4.4%
5 71
 
4.0%
6 58
 
3.2%
김 39
 
2.2%
치 32
 
1.8%
밥 27
 
1.5%
9 26
 
1.5%
Other values (196) 813
45.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 831
46.4%
Decimal Number 444
24.8%
Close Punctuation 240
 
13.4%
Open Punctuation 240
 
13.4%
Math Symbol 17
 
0.9%
Space Separator 9
 
0.5%
Other Punctuation 7
 
0.4%
Other Symbol 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 39
 
4.7%
치 32
 
3.9%
밥 27
 
3.2%
추 20
 
2.4%
월 17
 
2.0%
무 17
 
2.0%
기 17
 
2.0%
두 16
 
1.9%
고 16
 
1.9%
조 15
 
1.8%
Other values (178) 615
74.0%
Decimal Number
ValueCountFrequency (%)
0 167
37.6%
1 78
17.6%
5 71
16.0%
6 58
 
13.1%
9 26
 
5.9%
7 23
 
5.2%
2 13
 
2.9%
8 5
 
1.1%
3 3
 
0.7%
Other Punctuation
ValueCountFrequency (%)
, 3
42.9%
/ 3
42.9%
& 1
 
14.3%
Math Symbol
ValueCountFrequency (%)
~ 14
82.4%
∼ 3
 
17.6%
Close Punctuation
ValueCountFrequency (%)
) 240
100.0%
Open Punctuation
ValueCountFrequency (%)
( 240
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 960
53.6%
Hangul 831
46.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 39
 
4.7%
치 32
 
3.9%
밥 27
 
3.2%
추 20
 
2.4%
월 17
 
2.0%
무 17
 
2.0%
기 17
 
2.0%
두 16
 
1.9%
고 16
 
1.9%
조 15
 
1.8%
Other values (178) 615
74.0%
Common
ValueCountFrequency (%)
) 240
25.0%
( 240
25.0%
0 167
17.4%
1 78
 
8.1%
5 71
 
7.4%
6 58
 
6.0%
9 26
 
2.7%
7 23
 
2.4%
~ 14
 
1.5%
2 13
 
1.4%
Other values (8) 30
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 954
53.3%
Hangul 831
46.4%
CJK Compat 3
 
0.2%
Math Operators 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 240
25.2%
( 240
25.2%
0 167
17.5%
1 78
 
8.2%
5 71
 
7.4%
6 58
 
6.1%
9 26
 
2.7%
7 23
 
2.4%
~ 14
 
1.5%
2 13
 
1.4%
Other values (6) 24
 
2.5%
Hangul
ValueCountFrequency (%)
김 39
 
4.7%
치 32
 
3.9%
밥 27
 
3.2%
추 20
 
2.4%
월 17
 
2.0%
무 17
 
2.0%
기 17
 
2.0%
두 16
 
1.9%
고 16
 
1.9%
조 15
 
1.8%
Other values (178) 615
74.0%
CJK Compat
ValueCountFrequency (%)
㎖ 3
100.0%
Math Operators
ValueCountFrequency (%)
∼ 3
100.0%

중식열량
Text

MISSING 

Distinct100
Distinct (%)57.1%
Missing16
Missing (%)8.4%
Memory size1.6 KiB
2023-12-12T15:27:15.646052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length8.6457143
Min length5

Characters and Unicode

Total characters1513
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

Unique69 ?
Unique (%)39.4%

Sample

1st row363kcal
2nd row61.43kcal
3rd row296.97kcal
4th row87.76kcal
5th row8.75kcal
ValueCountFrequency (%)
8.75kcal 14
 
8.0%
363kcal 14
 
8.0%
15.2kcal 7
 
4.0%
0kcal 7
 
4.0%
45.26kcal 5
 
2.9%
12.8kcal 5
 
2.9%
91.13kcal 4
 
2.3%
391.54kcal 4
 
2.3%
40.82kcal 2
 
1.1%
38.4kcal 2
 
1.1%
Other values (90) 111
63.4%
2023-12-12T15:27:16.100808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 175
11.6%
c 175
11.6%
a 175
11.6%
l 175
11.6%
. 142
9.4%
3 93
 
6.1%
5 82
 
5.4%
8 77
 
5.1%
1 77
 
5.1%
2 72
 
4.8%
Other values (5) 270
17.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 700
46.3%
Decimal Number 671
44.3%
Other Punctuation 142
 
9.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 93
13.9%
5 82
12.2%
8 77
11.5%
1 77
11.5%
2 72
10.7%
6 62
9.2%
7 61
9.1%
4 55
8.2%
0 46
6.9%
9 46
6.9%
Lowercase Letter
ValueCountFrequency (%)
k 175
25.0%
c 175
25.0%
a 175
25.0%
l 175
25.0%
Other Punctuation
ValueCountFrequency (%)
. 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 813
53.7%
Latin 700
46.3%

Most frequent character per script

Common
ValueCountFrequency (%)
. 142
17.5%
3 93
11.4%
5 82
10.1%
8 77
9.5%
1 77
9.5%
2 72
8.9%
6 62
7.6%
7 61
7.5%
4 55
 
6.8%
0 46
 
5.7%
Latin
ValueCountFrequency (%)
k 175
25.0%
c 175
25.0%
a 175
25.0%
l 175
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1513
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 175
11.6%
c 175
11.6%
a 175
11.6%
l 175
11.6%
. 142
9.4%
3 93
 
6.1%
5 82
 
5.4%
8 77
 
5.1%
1 77
 
5.1%
2 72
 
4.8%
Other values (5) 270
17.8%

석식
Text

MISSING 

Distinct95
Distinct (%)56.5%
Missing23
Missing (%)12.0%
Memory size1.6 KiB
2023-12-12T15:27:16.338773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length22
Mean length11.494048
Min length1

Characters and Unicode

Total characters1931
Distinct characters200
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66 ?
Unique (%)39.3%

Sample

1st row밥
2nd row닭곰탕(05)(15)
3rd row마파두부(05)(06)
4th row조미김
5th row감자매운조림(05)(06)
ValueCountFrequency (%)
배추김치(7~9월 18
 
10.2%
밥 8
 
4.5%
깍두기(완제품)(09 8
 
4.5%
잡곡밥 6
 
3.4%
우유(백색우유(200ml,연간))(02 5
 
2.8%
현미밥 4
 
2.3%
계란후라이(01 4
 
2.3%
조미김 4
 
2.3%
주스(180㎖/병 4
 
2.3%
쇠고기미역국(05)(16 3
 
1.7%
Other values (89) 112
63.6%
2023-12-12T15:27:16.706786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 256
 
13.3%
) 256
 
13.3%
0 193
 
10.0%
1 75
 
3.9%
5 68
 
3.5%
6 60
 
3.1%
9 34
 
1.8%
김 31
 
1.6%
추 31
 
1.6%
치 29
 
1.5%
Other values (190) 898
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 867
44.9%
Decimal Number 493
25.5%
Open Punctuation 256
 
13.3%
Close Punctuation 256
 
13.3%
Math Symbol 18
 
0.9%
Other Punctuation 13
 
0.7%
Uppercase Letter 10
 
0.5%
Space Separator 9
 
0.5%
Other Symbol 7
 
0.4%
Lowercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 31
 
3.6%
추 31
 
3.6%
치 29
 
3.3%
밥 27
 
3.1%
고 22
 
2.5%
기 22
 
2.5%
배 21
 
2.4%
월 18
 
2.1%
우 16
 
1.8%
음 16
 
1.8%
Other values (171) 634
73.1%
Decimal Number
ValueCountFrequency (%)
0 193
39.1%
1 75
 
15.2%
5 68
 
13.8%
6 60
 
12.2%
9 34
 
6.9%
2 29
 
5.9%
7 26
 
5.3%
8 8
 
1.6%
Other Punctuation
ValueCountFrequency (%)
/ 7
53.8%
, 6
46.2%
Uppercase Letter
ValueCountFrequency (%)
L 5
50.0%
M 5
50.0%
Lowercase Letter
ValueCountFrequency (%)
l 1
50.0%
m 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 256
100.0%
Close Punctuation
ValueCountFrequency (%)
) 256
100.0%
Math Symbol
ValueCountFrequency (%)
~ 18
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Symbol
ValueCountFrequency (%)
㎖ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1052
54.5%
Hangul 867
44.9%
Latin 12
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 31
 
3.6%
추 31
 
3.6%
치 29
 
3.3%
밥 27
 
3.1%
고 22
 
2.5%
기 22
 
2.5%
배 21
 
2.4%
월 18
 
2.1%
우 16
 
1.8%
음 16
 
1.8%
Other values (171) 634
73.1%
Common
ValueCountFrequency (%)
( 256
24.3%
) 256
24.3%
0 193
18.3%
1 75
 
7.1%
5 68
 
6.5%
6 60
 
5.7%
9 34
 
3.2%
2 29
 
2.8%
7 26
 
2.5%
~ 18
 
1.7%
Other values (5) 37
 
3.5%
Latin
ValueCountFrequency (%)
L 5
41.7%
M 5
41.7%
l 1
 
8.3%
m 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1057
54.7%
Hangul 867
44.9%
CJK Compat 7
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 256
24.2%
) 256
24.2%
0 193
18.3%
1 75
 
7.1%
5 68
 
6.4%
6 60
 
5.7%
9 34
 
3.2%
2 29
 
2.7%
7 26
 
2.5%
~ 18
 
1.7%
Other values (8) 42
 
4.0%
Hangul
ValueCountFrequency (%)
김 31
 
3.6%
추 31
 
3.6%
치 29
 
3.3%
밥 27
 
3.1%
고 22
 
2.5%
기 22
 
2.5%
배 21
 
2.4%
월 18
 
2.1%
우 16
 
1.8%
음 16
 
1.8%
Other values (171) 634
73.1%
CJK Compat
ValueCountFrequency (%)
㎖ 7
100.0%

석식열량
Text

MISSING 

Distinct92
Distinct (%)55.4%
Missing25
Missing (%)13.1%
Memory size1.6 KiB
2023-12-12T15:27:16.977117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length8.7891566
Min length5

Characters and Unicode

Total characters1459
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

Unique63 ?
Unique (%)38.0%

Sample

1st row363kcal
2nd row147.8kcal
3rd row219.14kcal
4th row0kcal
5th row71.45kcal
ValueCountFrequency (%)
8.75kcal 18
 
10.8%
15.2kcal 8
 
4.8%
363kcal 8
 
4.8%
391.54kcal 6
 
3.6%
122kcal 5
 
3.0%
97.91kcal 4
 
2.4%
0kcal 4
 
2.4%
384.78kcal 4
 
2.4%
38.4kcal 4
 
2.4%
147.8kcal 3
 
1.8%
Other values (82) 102
61.4%
2023-12-12T15:27:17.368981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
k 166
11.4%
c 166
11.4%
a 166
11.4%
l 166
11.4%
. 142
9.7%
1 97
 
6.6%
8 81
 
5.6%
5 77
 
5.3%
2 74
 
5.1%
3 73
 
5.0%
Other values (5) 251
17.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 664
45.5%
Decimal Number 653
44.8%
Other Punctuation 142
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 97
14.9%
8 81
12.4%
5 77
11.8%
2 74
11.3%
3 73
11.2%
7 61
9.3%
4 58
8.9%
6 57
8.7%
9 40
6.1%
0 35
 
5.4%
Lowercase Letter
ValueCountFrequency (%)
k 166
25.0%
c 166
25.0%
a 166
25.0%
l 166
25.0%
Other Punctuation
ValueCountFrequency (%)
. 142
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 795
54.5%
Latin 664
45.5%

Most frequent character per script

Common
ValueCountFrequency (%)
. 142
17.9%
1 97
12.2%
8 81
10.2%
5 77
9.7%
2 74
9.3%
3 73
9.2%
7 61
7.7%
4 58
7.3%
6 57
7.2%
9 40
 
5.0%
Latin
ValueCountFrequency (%)
k 166
25.0%
c 166
25.0%
a 166
25.0%
l 166
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1459
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
k 166
11.4%
c 166
11.4%
a 166
11.4%
l 166
11.4%
. 142
9.7%
1 97
 
6.6%
8 81
 
5.6%
5 77
 
5.3%
2 74
 
5.1%
3 73
 
5.0%
Other values (5) 251
17.2%

열량합계
Categorical

Distinct30
Distinct (%)15.7%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2708.60kcal
 
7
2704.25kcal
 
7
3840.01kcal
 
7
3142.66kcal
 
7
2745.96kcal
 
7
Other values (25)
156 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2708.60kcal
2nd row2708.60kcal
3rd row2708.60kcal
4th row2708.60kcal
5th row2708.60kcal

Common Values

ValueCountFrequency (%)
2708.60kcal 7
 
3.7%
2704.25kcal 7
 
3.7%
3840.01kcal 7
 
3.7%
3142.66kcal 7
 
3.7%
2745.96kcal 7
 
3.7%
3205.96kcal 7
 
3.7%
2928.99kcal 7
 
3.7%
2866.93kcal 7
 
3.7%
2705.72kcal 7
 
3.7%
3264.59kcal 7
 
3.7%
Other values (20) 121
63.4%

Length

2023-12-12T15:27:17.527744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2708.60kcal 7
 
3.7%
2866.93kcal 7
 
3.7%
2704.25kcal 7
 
3.7%
2842.35kcal 7
 
3.7%
3264.59kcal 7
 
3.7%
2705.72kcal 7
 
3.7%
2802.08kcal 7
 
3.7%
2928.99kcal 7
 
3.7%
3205.96kcal 7
 
3.7%
2745.96kcal 7
 
3.7%
Other values (20) 121
63.4%

Correlations

2023-12-12T15:27:17.608979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
날짜조식조식열량중식열량석식석식열량열량합계
날짜1.0000.0000.0000.3070.0000.0001.000
조식0.0001.0001.0000.9800.9840.9830.000
조식열량0.0001.0001.0000.9800.9850.9840.000
중식열량0.3070.9800.9801.0000.9410.9360.307
석식0.0000.9840.9850.9411.0001.0000.000
석식열량0.0000.9830.9840.9361.0001.0000.000
열량합계1.0000.0000.0000.3070.0000.0001.000

Missing values

2023-12-12T15:27:12.072484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:27:12.256236image/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.
2023-12-12T15:27:12.394854image/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
02021-08-01쇠고기야채덮밥(05)(06)(16)720.15kcal밥363kcal밥363kcal2708.60kcal
12021-08-01생선묵찌개(05)(06)88.37kcal버섯매운탕(05)(06)(16)61.43kcal닭곰탕(05)(15)147.8kcal2708.60kcal
22021-08-01부추겉절이(05)(06)29.49kcal돈육야채볶음(05)(06)(10)296.97kcal마파두부(05)(06)219.14kcal2708.60kcal
32021-08-01배추김치(7~9월)8.75kcal계란찜(01)(09)87.76kcal조미김0kcal2708.60kcal
42021-08-01우유(백색우유(200ML,연간))(02)122kcal배추김치(7~9월)8.75kcal감자매운조림(05)(06)71.45kcal2708.60kcal
52021-08-01<NA><NA>수박52.992kcal배추김치(7~9월)8.75kcal2708.60kcal
62021-08-01<NA><NA><NA><NA>이온음료58.8kcal2708.60kcal
72021-08-02밥363kcal잡곡밥391.54kcal밥363kcal2708.49kcal
82021-08-02쇠고기미역국(05)(16)23.53kcal콩나물김치국(05)22.06kcal두부고추장찌개(05)(06)(10)120.41kcal2708.49kcal
92021-08-02햄감자볶음(05)(06)(10)168.52kcal오리고추장주물럭(05)(06)302.93kcal돈가스(06)(10)645.02kcal2708.49kcal
날짜조식조식열량중식중식열량석식석식열량열량합계
1812021-08-30양배추쌈(05)(06)62.36kcal김자반21.5kcal계란찜(01)(09)87.76kcal3142.66kcal
1822021-08-30배추김치(7~9월)8.75kcal멕시칸샐러드(01)(10)93.09kcal배추김치(7~9월)8.75kcal3142.66kcal
1832021-08-30우유(백색우유(200ML,연간))(02)122kcal깍두기(완제품)(09)15.2kcal썬업 파인애플200ml<NA>3142.66kcal
1842021-08-30<NA><NA>아이스크림 팩형(02)234kcal<NA><NA>3142.66kcal
1852021-08-31밥363kcal찰보리밥378.8kcal고추참치김치덮밥597.02kcal2850.87kcal
1862021-08-31햄김치찌개(10)123.87kcal짬뽕찌개(05)(10)(17)91.13kcal쇠고기미역국(05)(16)23.53kcal2850.87kcal
1872021-08-31닭순살감자조림(05)(06)(15)120.9kcal감자풋고추볶음(05)(06)75.57kcal계란후라이(01)97.91kcal2850.87kcal
1882021-08-31오이양파무침(05)(06)38.19kcal찹쌀탕수육(05)(06)(10)(12)607.27kcal가공우유(딸기맛)(02)116kcal2850.87kcal
1892021-08-31열무김치12.8kcal배추김치(7~9월)8.75kcal깍두기(완제품)(09)15.2kcal2850.87kcal
1902021-08-31우유(백색우유(200ML,연간))(02)122kcal멜론(여름)58.934016kcal<NA><NA>2850.87kcal