Overview

Dataset statistics

Number of variables36
Number of observations199
Missing cells44
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory61.7 KiB
Average record size in memory317.7 B

Variable types

Numeric25
Text4
DateTime1
Categorical6

Alerts

Caffeine has constant value ""Constant
Nationality is highly imbalanced (58.9%)Imbalance
FoodImage has 44 (22.1%) missing valuesMissing
id has unique valuesUnique
CarbonHydrate has 8 (4.0%) zerosZeros
Sugar has 55 (27.6%) zerosZeros
Protein has 8 (4.0%) zerosZeros
LoseWeight has 94 (47.2%) zerosZeros
SaturatedFattyAcid has 28 (14.1%) zerosZeros
TransFat has 193 (97.0%) zerosZeros
Cholesterol has 112 (56.3%) zerosZeros
Sodium has 7 (3.5%) zerosZeros
Cellulose has 70 (35.2%) zerosZeros
Calcium has 52 (26.1%) zerosZeros
FolicAcid has 71 (35.7%) zerosZeros
Iron has 53 (26.6%) zerosZeros
VitaminA has 106 (53.3%) zerosZeros
VitaminC has 95 (47.7%) zerosZeros
DayOfDiet has 17 (8.5%) zerosZeros
water has 50 (25.1%) zerosZeros
ash has 48 (24.1%) zerosZeros
total_amino_acids has 79 (39.7%) zerosZeros
essential_amino_acid has 83 (41.7%) zerosZeros

Reproduction

Analysis started2023-12-10 06:13:19.292953
Analysis finished2023-12-10 06:13:20.255044
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean307478.64
Minimum276447
Maximum337288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:20.373125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum276447
5-th percentile277576.4
Q1288316
median310407
Q3325301.5
95-th percentile334662.1
Maximum337288
Range60841
Interquartile range (IQR)36985.5

Descriptive statistics

Standard deviation19748.915
Coefficient of variation (CV)0.064228576
Kurtosis-1.4297788
Mean307478.64
Median Absolute Deviation (MAD)18229
Skewness-0.12892989
Sum61188250
Variance3.9001966 × 108
MonotonicityNot monotonic
2023-12-10T15:13:20.588740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
329455 1
 
0.5%
308787 1
 
0.5%
315489 1
 
0.5%
310410 1
 
0.5%
323927 1
 
0.5%
322635 1
 
0.5%
277064 1
 
0.5%
296661 1
 
0.5%
281551 1
 
0.5%
295618 1
 
0.5%
Other values (189) 189
95.0%
ValueCountFrequency (%)
276447 1
0.5%
276448 1
0.5%
277060 1
0.5%
277061 1
0.5%
277062 1
0.5%
277063 1
0.5%
277064 1
0.5%
277065 1
0.5%
277066 1
0.5%
277067 1
0.5%
ValueCountFrequency (%)
337288 1
0.5%
335667 1
0.5%
335666 1
0.5%
335469 1
0.5%
335468 1
0.5%
334726 1
0.5%
334666 1
0.5%
334665 1
0.5%
334664 1
0.5%
334663 1
0.5%

Userkey
Text

Distinct69
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:13:21.005219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters12736
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)11.1%

Sample

1st rowc1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a80
2nd rowc1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a80
3rd rowc1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a80
4th rowc1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a80
5th rowc1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a80
ValueCountFrequency (%)
b15186ab97acf9764e301989774de20b8f1a4d5ed9eb52448838f3956aaa92db 11
 
5.5%
e23ec3299eb6671e3f6df9303e04f7336ff57354bbc21a6eb8ef9aebd2783924 10
 
5.0%
31f365fb6cee3ef002181cc8eca0a35bf24f996fa7fb96d0cb3722179c7eda46 9
 
4.5%
35219f05fc1c355632b7650abcb8c094deed09402edbab2ae97413e1f82f156b 8
 
4.0%
37ea70ba6a579e5c8ac57053d348efc0a93e082cf8f698b7f61863a90ffc1b79 7
 
3.5%
4cf2fd5dd0b7755fce8ac3b32f764f7e49b43ac146fe92c366f1fe3602fdf087 7
 
3.5%
adcb181085f06f4de83952f02d5c65e12d5d69fad2a0872cf525bdedb2d4fa38 7
 
3.5%
6e84cfac5c67a72170b7da40d1c00045479b5887818c4b23745fb24e31d39b7b 7
 
3.5%
d19a2e1128acb0c8fd240dcb7faa81a7842a062b9976070c5dd7b2791f631e14 6
 
3.0%
a44429708a6b5609b4c31a1c712bc4d73a0a57476f2cf619754bf5c04ca3755e 6
 
3.0%
Other values (59) 121
60.8%
2023-12-10T15:13:21.542462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 871
 
6.8%
8 849
 
6.7%
7 837
 
6.6%
c 829
 
6.5%
3 826
 
6.5%
b 816
 
6.4%
4 805
 
6.3%
6 803
 
6.3%
a 801
 
6.3%
5 784
 
6.2%
Other values (6) 4515
35.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7918
62.2%
Lowercase Letter 4818
37.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
8 849
10.7%
7 837
10.6%
3 826
10.4%
4 805
10.2%
6 803
10.1%
5 784
9.9%
9 768
9.7%
2 766
9.7%
0 745
9.4%
1 735
9.3%
Lowercase Letter
ValueCountFrequency (%)
f 871
18.1%
c 829
17.2%
b 816
16.9%
a 801
16.6%
d 764
15.9%
e 737
15.3%

Most occurring scripts

ValueCountFrequency (%)
Common 7918
62.2%
Latin 4818
37.8%

Most frequent character per script

Common
ValueCountFrequency (%)
8 849
10.7%
7 837
10.6%
3 826
10.4%
4 805
10.2%
6 803
10.1%
5 784
9.9%
9 768
9.7%
2 766
9.7%
0 745
9.4%
1 735
9.3%
Latin
ValueCountFrequency (%)
f 871
18.1%
c 829
17.2%
b 816
16.9%
a 801
16.6%
d 764
15.9%
e 737
15.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12736
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 871
 
6.8%
8 849
 
6.7%
7 837
 
6.6%
c 829
 
6.5%
3 826
 
6.5%
b 816
 
6.4%
4 805
 
6.3%
6 803
 
6.3%
a 801
 
6.3%
5 784
 
6.2%
Other values (6) 4515
35.5%

Time
Date

Distinct114
Distinct (%)57.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2019-10-01 11:50:00
Maximum2019-10-31 20:18:00
2023-12-10T15:13:21.736552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:13:21.925712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

EatAmount
Real number (ℝ)

Distinct13
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.98739866
Minimum0.208333
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:22.086972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.208333
5-th percentile0.25
Q10.75
median1
Q31
95-th percentile2
Maximum10
Range9.791667
Interquartile range (IQR)0.25

Descriptive statistics

Standard deviation0.79366909
Coefficient of variation (CV)0.80379803
Kurtosis85.076739
Mean0.98739866
Median Absolute Deviation (MAD)0
Skewness7.85412
Sum196.49233
Variance0.62991063
MonotonicityNot monotonic
2023-12-10T15:13:22.243290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
1.0 125
62.8%
0.5 25
 
12.6%
0.25 17
 
8.5%
2.0 12
 
6.0%
0.75 11
 
5.5%
1.5 2
 
1.0%
10.0 1
 
0.5%
3.0 1
 
0.5%
1.55862 1
 
0.5%
4.0 1
 
0.5%
Other values (3) 3
 
1.5%
ValueCountFrequency (%)
0.208333 1
 
0.5%
0.25 17
 
8.5%
0.32538 1
 
0.5%
0.4 1
 
0.5%
0.5 25
 
12.6%
0.75 11
 
5.5%
1.0 125
62.8%
1.5 2
 
1.0%
1.55862 1
 
0.5%
2.0 12
 
6.0%
ValueCountFrequency (%)
10.0 1
 
0.5%
4.0 1
 
0.5%
3.0 1
 
0.5%
2.0 12
 
6.0%
1.55862 1
 
0.5%
1.5 2
 
1.0%
1.0 125
62.8%
0.75 11
 
5.5%
0.5 25
 
12.6%
0.4 1
 
0.5%

Nationality
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
ko
168 
KR
 
16
en
 
13
kr
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowko
2nd rowko
3rd rowko
4th rowko
5th rowko

Common Values

ValueCountFrequency (%)
ko 168
84.4%
KR 16
 
8.0%
en 13
 
6.5%
kr 2
 
1.0%

Length

2023-12-10T15:13:22.410939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:13:22.569903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ko 168
84.4%
kr 18
 
9.0%
en 13
 
6.5%

FoodName
Text

Distinct144
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:13:22.999641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length12
Mean length4.3417085
Min length1

Characters and Unicode

Total characters864
Distinct characters239
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

Unique111 ?
Unique (%)55.8%

Sample

1st row어묵탕
2nd row흑미밥
3rd row배추김치
4th row오이
5th row소불고기
ValueCountFrequency (%)
쌀밥 10
 
4.6%
배추김치 8
 
3.7%
흑미밥 4
 
1.9%
김구이 3
 
1.4%
미숫가루(보리 3
 
1.4%
연근조림 3
 
1.4%
사과 3
 
1.4%
김밥 3
 
1.4%
라면 3
 
1.4%
우유 3
 
1.4%
Other values (148) 173
80.1%
2023-12-10T15:13:23.566070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 28
 
3.2%
밥 27
 
3.1%
치 24
 
2.8%
김 22
 
2.5%
( 20
 
2.3%
) 18
 
2.1%
17
 
2.0%
리 17
 
2.0%
아 16
 
1.9%
추 16
 
1.9%
Other values (229) 659
76.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 809
93.6%
Open Punctuation 20
 
2.3%
Close Punctuation 18
 
2.1%
Space Separator 17
 
2.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 28
 
3.5%
밥 27
 
3.3%
치 24
 
3.0%
김 22
 
2.7%
리 17
 
2.1%
아 16
 
2.0%
추 16
 
2.0%
고 14
 
1.7%
배 13
 
1.6%
스 13
 
1.6%
Other values (226) 619
76.5%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%
Close Punctuation
ValueCountFrequency (%)
) 18
100.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 809
93.6%
Common 55
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 28
 
3.5%
밥 27
 
3.3%
치 24
 
3.0%
김 22
 
2.7%
리 17
 
2.1%
아 16
 
2.0%
추 16
 
2.0%
고 14
 
1.7%
배 13
 
1.6%
스 13
 
1.6%
Other values (226) 619
76.5%
Common
ValueCountFrequency (%)
( 20
36.4%
) 18
32.7%
17
30.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 809
93.6%
ASCII 55
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 28
 
3.5%
밥 27
 
3.3%
치 24
 
3.0%
김 22
 
2.7%
리 17
 
2.1%
아 16
 
2.0%
추 16
 
2.0%
고 14
 
1.7%
배 13
 
1.6%
스 13
 
1.6%
Other values (226) 619
76.5%
ASCII
ValueCountFrequency (%)
( 20
36.4%
) 18
32.7%
17
30.9%

StandardUnit
Categorical

Distinct33
Distinct (%)16.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1접시
52 
1개
25 
1인분
24 
1공기
14 
1컵
11 
Other values (28)
73 

Length

Max length10
Median length3
Mean length3.2864322
Min length2

Unique

Unique11 ?
Unique (%)5.5%

Sample

1st row1인분
2nd row1공기
3rd row1접시
4th row1인분(1/3개)
5th row1인분

Common Values

ValueCountFrequency (%)
1접시 52
26.1%
1개 25
12.6%
1인분 24
12.1%
1공기 14
 
7.0%
1컵 11
 
5.5%
1종지 10
 
5.0%
1잔 7
 
3.5%
1그릇 5
 
2.5%
1대접 5
 
2.5%
1큰술 5
 
2.5%
Other values (23) 41
20.6%

Length

2023-12-10T15:13:23.759904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1접시 52
26.1%
1개 25
12.6%
1인분 24
12.1%
1공기 14
 
7.0%
1컵 11
 
5.5%
1종지 10
 
5.0%
1잔 7
 
3.5%
1대접 5
 
2.5%
1큰술 5
 
2.5%
1그릇 5
 
2.5%
Other values (23) 41
20.6%

TotalGram
Text

Distinct90
Distinct (%)45.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:13:24.046120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length2.6633166
Min length1

Characters and Unicode

Total characters530
Distinct characters17
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

Unique60 ?
Unique (%)30.2%

Sample

1st row600
2nd row210
3rd row40
4th row70
5th row200
ValueCountFrequency (%)
200 16
 
8.0%
40 11
 
5.5%
210 11
 
5.5%
100 10
 
5.0%
70 8
 
4.0%
250 7
 
3.5%
150 7
 
3.5%
30 5
 
2.5%
50 5
 
2.5%
10 5
 
2.5%
Other values (80) 114
57.3%
2023-12-10T15:13:24.620817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 168
31.7%
1 72
13.6%
2 69
13.0%
5 57
 
10.8%
3 30
 
5.7%
4 29
 
5.5%
7 26
 
4.9%
6 22
 
4.2%
9 17
 
3.2%
8 16
 
3.0%
Other values (7) 24
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 506
95.5%
Other Punctuation 16
 
3.0%
Other Letter 6
 
1.1%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 168
33.2%
1 72
14.2%
2 69
13.6%
5 57
 
11.3%
3 30
 
5.9%
4 29
 
5.7%
7 26
 
5.1%
6 22
 
4.3%
9 17
 
3.4%
8 16
 
3.2%
Other Letter
ValueCountFrequency (%)
접 2
33.3%
시 2
33.3%
조 1
16.7%
각 1
16.7%
Other Punctuation
ValueCountFrequency (%)
. 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 524
98.9%
Hangul 6
 
1.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 168
32.1%
1 72
13.7%
2 69
13.2%
5 57
 
10.9%
3 30
 
5.7%
4 29
 
5.5%
7 26
 
5.0%
6 22
 
4.2%
9 17
 
3.2%
8 16
 
3.1%
Other values (3) 18
 
3.4%
Hangul
ValueCountFrequency (%)
접 2
33.3%
시 2
33.3%
조 1
16.7%
각 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 524
98.9%
Hangul 6
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 168
32.1%
1 72
13.7%
2 69
13.2%
5 57
 
10.9%
3 30
 
5.7%
4 29
 
5.5%
7 26
 
5.0%
6 22
 
4.2%
9 17
 
3.2%
8 16
 
3.1%
Other values (3) 18
 
3.4%
Hangul
ValueCountFrequency (%)
접 2
33.3%
시 2
33.3%
조 1
16.7%
각 1
16.7%

Calorie
Real number (ℝ)

Distinct159
Distinct (%)79.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.19811
Minimum0
Maximum959.54
Zeros1
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:24.840651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.92
Q132.33125
median106
Q3246.5125
95-th percentile474.3
Maximum959.54
Range959.54
Interquartile range (IQR)214.18125

Descriptive statistics

Standard deviation176.75844
Coefficient of variation (CV)1.0897688
Kurtosis4.4911246
Mean162.19811
Median Absolute Deviation (MAD)87.865
Skewness1.8585858
Sum32277.423
Variance31243.545
MonotonicityNot monotonic
2023-12-10T15:13:25.187292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
326.7 8
 
4.0%
10.0 7
 
3.5%
500.0 4
 
2.0%
106.0 3
 
1.5%
6.0 3
 
1.5%
122.0 3
 
1.5%
35.82 3
 
1.5%
80.0 3
 
1.5%
126.0 2
 
1.0%
303.53 2
 
1.0%
Other values (149) 161
80.9%
ValueCountFrequency (%)
0.0 1
 
0.5%
1.5 1
 
0.5%
2.5 1
 
0.5%
3.0 1
 
0.5%
3.6 1
 
0.5%
3.8 1
 
0.5%
4.5 1
 
0.5%
5.0 2
1.0%
5.2 1
 
0.5%
6.0 3
1.5%
ValueCountFrequency (%)
959.54 1
 
0.5%
918.0 1
 
0.5%
870.0 1
 
0.5%
782.0 1
 
0.5%
733.75 1
 
0.5%
500.0 4
2.0%
495.0 1
 
0.5%
472.0 1
 
0.5%
467.86 1
 
0.5%
465.0 2
1.0%

CarbonHydrate
Real number (ℝ)

ZEROS 

Distinct152
Distinct (%)76.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.264185
Minimum0
Maximum1680
Zeros8
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:25.408451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.13536
Q12.6645
median9
Q334.5
95-th percentile74.4393
Maximum1680
Range1680
Interquartile range (IQR)31.8355

Descriptive statistics

Standard deviation120.19195
Coefficient of variation (CV)4.1071348
Kurtosis182.18607
Mean29.264185
Median Absolute Deviation (MAD)8.193208
Skewness13.219421
Sum5823.5728
Variance14446.106
MonotonicityNot monotonic
2023-12-10T15:13:25.685405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
4.0%
71.55 8
 
4.0%
2.0 4
 
2.0%
18.0 4
 
2.0%
1.76 4
 
2.0%
21.0 3
 
1.5%
10.0 3
 
1.5%
79.0 3
 
1.5%
6.8553 3
 
1.5%
8.0 3
 
1.5%
Other values (142) 156
78.4%
ValueCountFrequency (%)
0.0 8
4.0%
0.0624999 1
 
0.5%
0.0936 1
 
0.5%
0.14 1
 
0.5%
0.225 1
 
0.5%
0.31125 1
 
0.5%
0.44 1
 
0.5%
0.4752 1
 
0.5%
0.6 1
 
0.5%
0.608025 1
 
0.5%
ValueCountFrequency (%)
1680.0 1
 
0.5%
115.5 1
 
0.5%
83.0 1
 
0.5%
81.38 1
 
0.5%
80.0 1
 
0.5%
79.0 3
 
1.5%
75.6635 1
 
0.5%
74.4393 2
 
1.0%
71.55 8
4.0%
71.0 1
 
0.5%

Sugar
Real number (ℝ)

ZEROS 

Distinct116
Distinct (%)58.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5671608
Minimum0
Maximum42.924
Zeros55
Zeros (%)27.6%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:25.915690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.0426
Q34
95-th percentile17.062
Maximum42.924
Range42.924
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.3995544
Coefficient of variation (CV)1.7940191
Kurtosis11.513772
Mean3.5671608
Median Absolute Deviation (MAD)1.0426
Skewness3.0500794
Sum709.86499
Variance40.954297
MonotonicityNot monotonic
2023-12-10T15:13:26.154014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 55
27.6%
2.0 6
 
3.0%
2.4 4
 
2.0%
4.0 4
 
2.0%
3.0 4
 
2.0%
0.0954 3
 
1.5%
16.0 2
 
1.0%
0.1403 2
 
1.0%
0.11 2
 
1.0%
1.0426 2
 
1.0%
Other values (106) 115
57.8%
ValueCountFrequency (%)
0.0 55
27.6%
0.003525 1
 
0.5%
0.0047 2
 
1.0%
0.047 1
 
0.5%
0.078752 1
 
0.5%
0.0954 3
 
1.5%
0.10785 1
 
0.5%
0.11 2
 
1.0%
0.1403 2
 
1.0%
0.15 1
 
0.5%
ValueCountFrequency (%)
42.924 1
0.5%
36.6 1
0.5%
27.0 1
0.5%
24.0 1
0.5%
22.28 1
0.5%
21.0 1
0.5%
20.0 1
0.5%
19.0 1
0.5%
18.06 1
0.5%
17.62 1
0.5%

Protein
Real number (ℝ)

ZEROS 

Distinct144
Distinct (%)72.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8216352
Minimum0
Maximum115
Zeros8
Zeros (%)4.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:26.430187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0705
Q10.804
median3.6
Q37.3
95-th percentile20.17
Maximum115
Range115
Interquartile range (IQR)6.496

Descriptive statistics

Standard deviation13.113169
Coefficient of variation (CV)1.9222911
Kurtosis35.490933
Mean6.8216352
Median Absolute Deviation (MAD)2.9775
Skewness5.3630544
Sum1357.5054
Variance171.9552
MonotonicityNot monotonic
2023-12-10T15:13:26.691182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 8
 
4.0%
5.76 8
 
4.0%
4.0 5
 
2.5%
0.56 4
 
2.0%
0.6 4
 
2.0%
10.0 4
 
2.0%
5.0 4
 
2.0%
5.6 3
 
1.5%
7.3 3
 
1.5%
0.3 3
 
1.5%
Other values (134) 153
76.9%
ValueCountFrequency (%)
0.0 8
4.0%
0.0155 1
 
0.5%
0.03 1
 
0.5%
0.075 1
 
0.5%
0.1 1
 
0.5%
0.14 1
 
0.5%
0.143 1
 
0.5%
0.15 1
 
0.5%
0.2 1
 
0.5%
0.243 1
 
0.5%
ValueCountFrequency (%)
115.0 1
0.5%
95.93 1
0.5%
59.4 1
0.5%
56.875 1
0.5%
49.8 1
0.5%
34.5 1
0.5%
30.0 2
1.0%
24.0 1
0.5%
21.7 1
0.5%
20.0 1
0.5%

LoseWeight
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.16582915
Minimum-69
Maximum26
Zeros94
Zeros (%)47.2%
Negative25
Negative (%)12.6%
Memory size1.9 KiB
2023-12-10T15:13:26.917268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-69
5-th percentile-1.1
Q10
median0
Q31
95-th percentile6
Maximum26
Range95
Interquartile range (IQR)1

Descriptive statistics

Standard deviation9.325085
Coefficient of variation (CV)56.233088
Kurtosis45.162192
Mean0.16582915
Median Absolute Deviation (MAD)1
Skewness-5.8958085
Sum33
Variance86.95721
MonotonicityNot monotonic
2023-12-10T15:13:27.116820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 94
47.2%
1 32
 
16.1%
2 18
 
9.0%
-1 15
 
7.5%
6 10
 
5.0%
3 8
 
4.0%
4 6
 
3.0%
-4 4
 
2.0%
26 3
 
1.5%
-2 3
 
1.5%
Other values (4) 6
 
3.0%
ValueCountFrequency (%)
-69 3
 
1.5%
-4 4
 
2.0%
-2 3
 
1.5%
-1 15
 
7.5%
0 94
47.2%
1 32
 
16.1%
2 18
 
9.0%
3 8
 
4.0%
4 6
 
3.0%
5 1
 
0.5%
ValueCountFrequency (%)
26 3
 
1.5%
10 1
 
0.5%
8 1
 
0.5%
6 10
 
5.0%
5 1
 
0.5%
4 6
 
3.0%
3 8
 
4.0%
2 18
 
9.0%
1 32
 
16.1%
0 94
47.2%

SaturatedFattyAcid
Real number (ℝ)

ZEROS 

Distinct138
Distinct (%)69.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3627216
Minimum0
Maximum143.4
Zeros28
Zeros (%)14.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:27.293898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0295
median0.26525
Q31.982
95-th percentile9
Maximum143.4
Range143.4
Interquartile range (IQR)1.9525

Descriptive statistics

Standard deviation10.439616
Coefficient of variation (CV)4.4184709
Kurtosis170.41147
Mean2.3627216
Median Absolute Deviation (MAD)0.26525
Skewness12.613394
Sum470.1816
Variance108.98559
MonotonicityNot monotonic
2023-12-10T15:13:27.498813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 28
 
14.1%
0.126 8
 
4.0%
9.0 4
 
2.0%
2.0 3
 
1.5%
0.004 3
 
1.5%
4.34 3
 
1.5%
0.0972 3
 
1.5%
0.75 3
 
1.5%
0.15 2
 
1.0%
0.7687 2
 
1.0%
Other values (128) 140
70.4%
ValueCountFrequency (%)
0.0 28
14.1%
0.0005 2
 
1.0%
0.004 3
 
1.5%
0.00478309 1
 
0.5%
0.005 1
 
0.5%
0.009 1
 
0.5%
0.01 1
 
0.5%
0.0105 1
 
0.5%
0.011 1
 
0.5%
0.012 1
 
0.5%
ValueCountFrequency (%)
143.4 1
 
0.5%
16.48 1
 
0.5%
12.6405 1
 
0.5%
12.469 1
 
0.5%
10.76 1
 
0.5%
10.335 1
 
0.5%
10.0 1
 
0.5%
9.0 4
2.0%
8.8 1
 
0.5%
8.0 1
 
0.5%

TransFat
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.17975377
Minimum0
Maximum24.96
Zeros193
Zeros (%)97.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:27.678282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum24.96
Range24.96
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.8608722
Coefficient of variation (CV)10.35234
Kurtosis162.45179
Mean0.17975377
Median Absolute Deviation (MAD)0
Skewness12.455327
Sum35.771
Variance3.4628452
MonotonicityNot monotonic
2023-12-10T15:13:27.832199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 193
97.0%
0.5 2
 
1.0%
24.96 1
 
0.5%
0.675 1
 
0.5%
8.2 1
 
0.5%
0.936 1
 
0.5%
ValueCountFrequency (%)
0.0 193
97.0%
0.5 2
 
1.0%
0.675 1
 
0.5%
0.936 1
 
0.5%
8.2 1
 
0.5%
24.96 1
 
0.5%
ValueCountFrequency (%)
24.96 1
 
0.5%
8.2 1
 
0.5%
0.936 1
 
0.5%
0.675 1
 
0.5%
0.5 2
 
1.0%
0.0 193
97.0%

Cholesterol
Real number (ℝ)

ZEROS 

Distinct71
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.011198
Minimum0
Maximum472
Zeros112
Zeros (%)56.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:28.005075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q317.02275
95-th percentile167.7935
Maximum472
Range472
Interquartile range (IQR)17.02275

Descriptive statistics

Standard deviation76.702431
Coefficient of variation (CV)2.5557937
Kurtosis15.125828
Mean30.011198
Median Absolute Deviation (MAD)0
Skewness3.7035148
Sum5972.2284
Variance5883.2629
MonotonicityNot monotonic
2023-12-10T15:13:28.209888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 112
56.3%
0.9 5
 
2.5%
5.0 3
 
1.5%
0.45 3
 
1.5%
18.0 3
 
1.5%
107.9 2
 
1.0%
10.0 2
 
1.0%
1.9 2
 
1.0%
235.0 2
 
1.0%
98.649 2
 
1.0%
Other values (61) 63
31.7%
ValueCountFrequency (%)
0.0 112
56.3%
0.025 1
 
0.5%
0.225 1
 
0.5%
0.425 1
 
0.5%
0.45 3
 
1.5%
0.5 1
 
0.5%
0.7 2
 
1.0%
0.9 5
 
2.5%
0.95 1
 
0.5%
1.4 1
 
0.5%
ValueCountFrequency (%)
472.0 1
0.5%
453.8 1
0.5%
398.0 1
0.5%
396.4 1
0.5%
289.5 1
0.5%
255.0 1
0.5%
235.0 2
1.0%
210.0 1
0.5%
198.2 1
0.5%
164.415 1
0.5%

Sodium
Real number (ℝ)

ZEROS 

Distinct146
Distinct (%)73.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean355.59398
Minimum0
Maximum2856
Zeros7
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:28.724500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.576
Q17.2
median170
Q3428.8725
95-th percentile1479.7
Maximum2856
Range2856
Interquartile range (IQR)421.6725

Descriptive statistics

Standard deviation518.20558
Coefficient of variation (CV)1.4572957
Kurtosis6.5259481
Mean355.59398
Median Absolute Deviation (MAD)164.6
Skewness2.4179137
Sum70763.201
Variance268537.02
MonotonicityNot monotonic
2023-12-10T15:13:29.038085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.2 8
 
4.0%
0.0 7
 
3.5%
3.0 5
 
2.5%
85.0 5
 
2.5%
80.0 4
 
2.0%
6.0 4
 
2.0%
92.8 4
 
2.0%
1.0 3
 
1.5%
2.0 3
 
1.5%
1790.0 3
 
1.5%
Other values (136) 153
76.9%
ValueCountFrequency (%)
0.0 7
3.5%
0.18 1
 
0.5%
0.2 1
 
0.5%
0.36 1
 
0.5%
0.6 1
 
0.5%
1.0 3
1.5%
1.02 1
 
0.5%
1.44 1
 
0.5%
1.62 1
 
0.5%
2.0 3
1.5%
ValueCountFrequency (%)
2856.0 1
 
0.5%
2631.2 1
 
0.5%
2600.0 1
 
0.5%
2064.0 1
 
0.5%
1860.0 1
 
0.5%
1790.0 3
1.5%
1776.0 1
 
0.5%
1540.0 1
 
0.5%
1473.0 1
 
0.5%
1468.14 1
 
0.5%

Cellulose
Real number (ℝ)

ZEROS 

Distinct93
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.278476
Minimum0
Maximum2262
Zeros70
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:29.292125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.7
Q32.1725
95-th percentile8.145
Maximum2262
Range2262
Interquartile range (IQR)2.1725

Descriptive statistics

Standard deviation160.25525
Coefficient of variation (CV)12.068798
Kurtosis198.78569
Mean13.278476
Median Absolute Deviation (MAD)0.7
Skewness14.095445
Sum2642.4167
Variance25681.744
MonotonicityNot monotonic
2023-12-10T15:13:29.504285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 70
35.2%
0.9 10
 
5.0%
0.7 5
 
2.5%
0.4 4
 
2.0%
2.4 3
 
1.5%
1.3 3
 
1.5%
3.5 3
 
1.5%
2.8 3
 
1.5%
2.5 3
 
1.5%
2.17 2
 
1.0%
Other values (83) 93
46.7%
ValueCountFrequency (%)
0.0 70
35.2%
0.086625 1
 
0.5%
0.1 2
 
1.0%
0.15 1
 
0.5%
0.1516 1
 
0.5%
0.25 1
 
0.5%
0.325 1
 
0.5%
0.32825 1
 
0.5%
0.33 1
 
0.5%
0.370875 1
 
0.5%
ValueCountFrequency (%)
2262.0 1
0.5%
28.0 1
0.5%
19.2 1
0.5%
19.0 1
0.5%
16.8 1
0.5%
15.0 1
0.5%
14.0 1
0.5%
13.6 1
0.5%
9.8 1
0.5%
9.45 1
0.5%

Calcium
Real number (ℝ)

ZEROS 

Distinct117
Distinct (%)58.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.579492
Minimum0
Maximum550
Zeros52
Zeros (%)26.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:29.725070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median8
Q337.5
95-th percentile154.2
Maximum550
Range550
Interquartile range (IQR)37.5

Descriptive statistics

Standard deviation62.70181
Coefficient of variation (CV)1.985523
Kurtosis30.988697
Mean31.579492
Median Absolute Deviation (MAD)8
Skewness4.7752127
Sum6284.319
Variance3931.517
MonotonicityNot monotonic
2023-12-10T15:13:29.938123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 52
26.1%
6.3 8
 
4.0%
2.0 7
 
3.5%
180.0 4
 
2.0%
25.6 4
 
2.0%
4.0 3
 
1.5%
39.0 2
 
1.0%
16.8 2
 
1.0%
18.0 2
 
1.0%
6.37 2
 
1.0%
Other values (107) 113
56.8%
ValueCountFrequency (%)
0.0 52
26.1%
0.525 1
 
0.5%
0.6 1
 
0.5%
0.75 1
 
0.5%
0.8 1
 
0.5%
1.25 1
 
0.5%
1.3975 1
 
0.5%
1.5 1
 
0.5%
2.0 7
 
3.5%
3.0 1
 
0.5%
ValueCountFrequency (%)
550.0 1
 
0.5%
426.0 1
 
0.5%
210.0 1
 
0.5%
180.0 4
2.0%
168.0 1
 
0.5%
157.5 1
 
0.5%
156.0 1
 
0.5%
154.0 1
 
0.5%
151.48 1
 
0.5%
138.0 1
 
0.5%

FolicAcid
Real number (ℝ)

ZEROS 

Distinct96
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.323176
Minimum0
Maximum300
Zeros71
Zeros (%)35.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:30.153106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q322.875
95-th percentile103.12
Maximum300
Range300
Interquartile range (IQR)22.875

Descriptive statistics

Standard deviation43.499869
Coefficient of variation (CV)1.9486416
Kurtosis13.978397
Mean22.323176
Median Absolute Deviation (MAD)6
Skewness3.4239804
Sum4442.312
Variance1892.2386
MonotonicityNot monotonic
2023-12-10T15:13:30.357901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 71
35.7%
11.0 9
 
4.5%
4.0 8
 
4.0%
17.0 4
 
2.0%
6.0 3
 
1.5%
5.5 2
 
1.0%
25.1 2
 
1.0%
101.0 2
 
1.0%
31.0 2
 
1.0%
40.5 2
 
1.0%
Other values (86) 94
47.2%
ValueCountFrequency (%)
0.0 71
35.7%
0.25 1
 
0.5%
0.5 1
 
0.5%
1.2125 1
 
0.5%
1.5 1
 
0.5%
2.0 1
 
0.5%
2.1046 1
 
0.5%
2.2425 1
 
0.5%
2.55 1
 
0.5%
2.8 1
 
0.5%
ValueCountFrequency (%)
300.0 1
0.5%
233.6 1
0.5%
224.0 1
0.5%
179.6 1
0.5%
162.0 1
0.5%
150.0 1
0.5%
147.0 2
1.0%
120.0 1
0.5%
106.0 1
0.5%
102.8 1
0.5%

Iron
Real number (ℝ)

ZEROS 

Distinct113
Distinct (%)56.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5513683
Minimum0
Maximum190
Zeros53
Zeros (%)26.6%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:30.564985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.3
Q31.1322
95-th percentile4.065
Maximum190
Range190
Interquartile range (IQR)1.1322

Descriptive statistics

Standard deviation14.759807
Coefficient of variation (CV)5.7850554
Kurtosis134.83947
Mean2.5513683
Median Absolute Deviation (MAD)0.3
Skewness11.046848
Sum507.7223
Variance217.8519
MonotonicityNot monotonic
2023-12-10T15:13:30.758170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 53
26.6%
1.17 8
 
4.0%
0.1 5
 
2.5%
0.32 4
 
2.0%
1.0 3
 
1.5%
0.4 3
 
1.5%
0.3 3
 
1.5%
2.85226 2
 
1.0%
0.8 2
 
1.0%
0.16 2
 
1.0%
Other values (103) 114
57.3%
ValueCountFrequency (%)
0.0 53
26.6%
0.003 1
 
0.5%
0.02 1
 
0.5%
0.025 1
 
0.5%
0.033 1
 
0.5%
0.04 1
 
0.5%
0.045 2
 
1.0%
0.047775 1
 
0.5%
0.05 1
 
0.5%
0.051875 1
 
0.5%
ValueCountFrequency (%)
190.0 1
0.5%
69.3 1
0.5%
38.0 1
0.5%
33.0 1
0.5%
21.0 1
0.5%
11.4 1
0.5%
11.25 1
0.5%
7.5 1
0.5%
4.2 2
1.0%
4.05 1
0.5%

VitaminA
Real number (ℝ)

ZEROS 

Distinct64
Distinct (%)32.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.383166
Minimum0
Maximum1876
Zeros106
Zeros (%)53.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:30.939708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q319
95-th percentile241
Maximum1876
Range1876
Interquartile range (IQR)19

Descriptive statistics

Standard deviation162.53138
Coefficient of variation (CV)3.7464159
Kurtosis84.053926
Mean43.383166
Median Absolute Deviation (MAD)0
Skewness8.1982033
Sum8633.25
Variance26416.45
MonotonicityNot monotonic
2023-12-10T15:13:31.156977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 106
53.3%
1.0 10
 
5.0%
19.0 4
 
2.0%
90.0 3
 
1.5%
44.0 3
 
1.5%
104.0 3
 
1.5%
3.0 2
 
1.0%
6.0 2
 
1.0%
43.0 2
 
1.0%
241.0 2
 
1.0%
Other values (54) 62
31.2%
ValueCountFrequency (%)
0.0 106
53.3%
0.4 1
 
0.5%
0.5 2
 
1.0%
0.75 1
 
0.5%
1.0 10
 
5.0%
1.25 1
 
0.5%
1.5 1
 
0.5%
2.0 2
 
1.0%
3.0 2
 
1.0%
3.75 1
 
0.5%
ValueCountFrequency (%)
1876.0 1
0.5%
662.0 1
0.5%
652.0 1
0.5%
482.0 1
0.5%
469.0 1
0.5%
450.0 1
0.5%
292.0 2
1.0%
290.0 1
0.5%
241.0 2
1.0%
154.0 1
0.5%

VitaminC
Real number (ℝ)

ZEROS 

Distinct81
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4794835
Minimum0
Maximum230.344
Zeros95
Zeros (%)47.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:31.397238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.192475
Q32.91
95-th percentile25.46669
Maximum230.344
Range230.344
Interquartile range (IQR)2.91

Descriptive statistics

Standard deviation25.180704
Coefficient of variation (CV)3.886221
Kurtosis62.507014
Mean6.4794835
Median Absolute Deviation (MAD)0.192475
Skewness7.4628478
Sum1289.4172
Variance634.06788
MonotonicityNot monotonic
2023-12-10T15:13:31.578544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 95
47.7%
2.8 4
 
2.0%
2.0 3
 
1.5%
4.0 3
 
1.5%
0.7 3
 
1.5%
0.5 3
 
1.5%
1.58 3
 
1.5%
60.0 2
 
1.0%
1.4 2
 
1.0%
6.0 2
 
1.0%
Other values (71) 79
39.7%
ValueCountFrequency (%)
0.0 95
47.7%
0.02965 1
 
0.5%
0.0375 1
 
0.5%
0.079 1
 
0.5%
0.1186 1
 
0.5%
0.192475 1
 
0.5%
0.222 1
 
0.5%
0.245025 1
 
0.5%
0.2571 2
 
1.0%
0.336 1
 
0.5%
ValueCountFrequency (%)
230.344 1
0.5%
230.0 1
0.5%
69.0 2
1.0%
60.0 2
1.0%
50.0 1
0.5%
43.86 1
0.5%
42.0 1
0.5%
29.0 1
0.5%
25.0741 1
0.5%
25.0 1
0.5%

DayOfDiet
Real number (ℝ)

ZEROS 

Distinct49
Distinct (%)24.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean676.17588
Minimum0
Maximum18198
Zeros17
Zeros (%)8.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:31.770876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13
median9
Q339
95-th percentile252.7
Maximum18198
Range18198
Interquartile range (IQR)36

Descriptive statistics

Standard deviation3354.4952
Coefficient of variation (CV)4.9609803
Kurtosis24.077104
Mean676.17588
Median Absolute Deviation (MAD)8
Skewness5.0818134
Sum134559
Variance11252638
MonotonicityNot monotonic
2023-12-10T15:13:31.984601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
0 17
 
8.5%
2 15
 
7.5%
3 15
 
7.5%
1 14
 
7.0%
9 11
 
5.5%
8 10
 
5.0%
7 8
 
4.0%
5 7
 
3.5%
132 6
 
3.0%
6 6
 
3.0%
Other values (39) 90
45.2%
ValueCountFrequency (%)
0 17
8.5%
1 14
7.0%
2 15
7.5%
3 15
7.5%
4 6
 
3.0%
5 7
3.5%
6 6
 
3.0%
7 8
4.0%
8 10
5.0%
9 11
5.5%
ValueCountFrequency (%)
18198 1
 
0.5%
18197 6
3.0%
322 1
 
0.5%
304 2
 
1.0%
247 4
2.0%
206 2
 
1.0%
168 1
 
0.5%
161 1
 
0.5%
156 2
 
1.0%
153 1
 
0.5%

Caffeine
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0
199 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 199
100.0%

Length

2023-12-10T15:13:32.249874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:13:32.384523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 199
100.0%

water
Real number (ℝ)

ZEROS 

Distinct127
Distinct (%)63.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.745301
Minimum0
Maximum585.589
Zeros50
Zeros (%)25.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:32.547374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.03
median24.4665
Q367.70255
95-th percentile174.8
Maximum585.589
Range585.589
Interquartile range (IQR)67.67255

Descriptive statistics

Standard deviation75.171059
Coefficient of variation (CV)1.5111188
Kurtosis17.099543
Mean49.745301
Median Absolute Deviation (MAD)24.4665
Skewness3.3843924
Sum9899.3148
Variance5650.6881
MonotonicityNot monotonic
2023-12-10T15:13:32.791308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 50
25.1%
12.06 8
 
4.0%
37.12 4
 
2.0%
51.119 3
 
1.5%
0.18 3
 
1.5%
174.8 3
 
1.5%
69.251 2
 
1.0%
50.3289 2
 
1.0%
18.56 2
 
1.0%
24.6735 2
 
1.0%
Other values (117) 120
60.3%
ValueCountFrequency (%)
0.0 50
25.1%
0.06 1
 
0.5%
0.06825 1
 
0.5%
0.17385 1
 
0.5%
0.174 1
 
0.5%
0.18 3
 
1.5%
0.204 1
 
0.5%
0.2318 2
 
1.0%
0.816 1
 
0.5%
1.4755 1
 
0.5%
ValueCountFrequency (%)
585.589 1
 
0.5%
443.7 1
 
0.5%
373.176 1
 
0.5%
234.08 1
 
0.5%
212.503 1
 
0.5%
184.6 1
 
0.5%
181.0 1
 
0.5%
180.525 1
 
0.5%
180.0 1
 
0.5%
174.8 3
1.5%

ash
Real number (ℝ)

ZEROS 

Distinct128
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6807702
Minimum0
Maximum306.6
Zeros48
Zeros (%)24.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:33.055698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.035
median0.493165
Q31.4451
95-th percentile3.85399
Maximum306.6
Range306.6
Interquartile range (IQR)1.4101

Descriptive statistics

Standard deviation21.802471
Coefficient of variation (CV)8.132913
Kurtosis193.53516
Mean2.6807702
Median Absolute Deviation (MAD)0.493165
Skewness13.830365
Sum533.47327
Variance475.34773
MonotonicityNot monotonic
2023-12-10T15:13:33.305910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 48
 
24.1%
0.36 8
 
4.0%
0.48 4
 
2.0%
0.1647 3
 
1.5%
1.34 3
 
1.5%
2.8888 3
 
1.5%
0.7 2
 
1.0%
1.1 2
 
1.0%
0.6916 2
 
1.0%
0.24 2
 
1.0%
Other values (118) 122
61.3%
ValueCountFrequency (%)
0.0 48
24.1%
0.0185 1
 
0.5%
0.03 1
 
0.5%
0.04 1
 
0.5%
0.045 1
 
0.5%
0.08 1
 
0.5%
0.09 1
 
0.5%
0.090675 1
 
0.5%
0.1032 1
 
0.5%
0.105 1
 
0.5%
ValueCountFrequency (%)
306.6 1
0.5%
31.68 1
0.5%
10.354 1
0.5%
5.1276 1
0.5%
4.80445 2
1.0%
4.65817 1
0.5%
4.6415 1
0.5%
4.3908 1
0.5%
3.88 1
0.5%
3.8511 1
0.5%

total_amino_acids
Real number (ℝ)

ZEROS 

Distinct108
Distinct (%)54.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1839.8912
Minimum0
Maximum21008.9
Zeros79
Zeros (%)39.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:33.537927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median245.94
Q31549.8
95-th percentile11687.23
Maximum21008.9
Range21008.9
Interquartile range (IQR)1549.8

Descriptive statistics

Standard deviation3614.5783
Coefficient of variation (CV)1.9645609
Kurtosis7.8599519
Mean1839.8912
Median Absolute Deviation (MAD)245.94
Skewness2.7503511
Sum366138.34
Variance13065176
MonotonicityNot monotonic
2023-12-10T15:13:33.778227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 79
39.7%
15673.6 3
 
1.5%
1185.75 3
 
1.5%
6066.0 3
 
1.5%
830.83 2
 
1.0%
870.3 2
 
1.0%
6255.5 2
 
1.0%
1549.8 2
 
1.0%
3772.39 2
 
1.0%
0.41 2
 
1.0%
Other values (98) 99
49.7%
ValueCountFrequency (%)
0.0 79
39.7%
0.3075 1
 
0.5%
0.41 2
 
1.0%
0.5895 1
 
0.5%
2.0 1
 
0.5%
10.4 1
 
0.5%
10.8 1
 
0.5%
19.5 1
 
0.5%
43.9875 1
 
0.5%
59.0 1
 
0.5%
ValueCountFrequency (%)
21008.9 1
 
0.5%
15673.6 3
1.5%
14354.7 1
 
0.5%
13727.4 1
 
0.5%
12511.0 1
 
0.5%
12454.5 1
 
0.5%
11920.0 1
 
0.5%
11889.1 1
 
0.5%
11664.8 1
 
0.5%
8866.25 1
 
0.5%

essential_amino_acid
Real number (ℝ)

ZEROS 

Distinct104
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean872.46132
Minimum0
Maximum12177.9
Zeros83
Zeros (%)41.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:34.025945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median85.1025
Q3698.6
95-th percentile5807.238
Maximum12177.9
Range12177.9
Interquartile range (IQR)698.6

Descriptive statistics

Standard deviation1838.8494
Coefficient of variation (CV)2.1076572
Kurtosis11.774328
Mean872.46132
Median Absolute Deviation (MAD)85.1025
Skewness3.1779392
Sum173619.8
Variance3381367
MonotonicityNot monotonic
2023-12-10T15:13:34.685181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 83
41.7%
496.17 3
 
1.5%
2762.0 3
 
1.5%
6264.13 3
 
1.5%
371.4 2
 
1.0%
418.6 2
 
1.0%
3143.0 2
 
1.0%
698.6 2
 
1.0%
1892.62 2
 
1.0%
0.14 2
 
1.0%
Other values (94) 95
47.7%
ValueCountFrequency (%)
0.0 83
41.7%
0.105 1
 
0.5%
0.14 2
 
1.0%
2.0 1
 
0.5%
3.0 1
 
0.5%
4.5 1
 
0.5%
8.925 1
 
0.5%
18.0 1
 
0.5%
26.5 1
 
0.5%
33.8981 1
 
0.5%
ValueCountFrequency (%)
12177.9 1
 
0.5%
10170.6 1
 
0.5%
6987.83 1
 
0.5%
6802.52 1
 
0.5%
6286.0 1
 
0.5%
6264.13 3
1.5%
5956.36 1
 
0.5%
5910.81 1
 
0.5%
5795.73 1
 
0.5%
4941.81 1
 
0.5%

FoodImage
Text

MISSING 

Distinct95
Distinct (%)61.3%
Missing44
Missing (%)22.1%
Memory size1.7 KiB
2023-12-10T15:13:35.089484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length35.587097
Min length1

Characters and Unicode

Total characters5516
Distinct characters20
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

Unique58 ?
Unique (%)37.4%

Sample

1st roweb5eb82f3fdf42139b3497ab23da6bbb.png
2nd roweb5eb82f3fdf42139b3497ab23da6bbb.png
3rd roweb5eb82f3fdf42139b3497ab23da6bbb.png
4th roweb5eb82f3fdf42139b3497ab23da6bbb.png
5th roweb5eb82f3fdf42139b3497ab23da6bbb.png
ValueCountFrequency (%)
9da362ae8ab141af8857a9feccb9761c.png 6
 
3.9%
eb5eb82f3fdf42139b3497ab23da6bbb.png 6
 
3.9%
b381c6b4602b4287aa47c683345f216c.png 5
 
3.2%
240bb067c921432999b3d055ad9bf19e.png 4
 
2.6%
2e02727581574a55b643adca6c2575ff.png 4
 
2.6%
cfc02b5c0f9a41fb8a86473683de7e62.png 4
 
2.6%
8bd09a4baf3a47218abacf32da0fdf34.png 4
 
2.6%
c50280ebbc42462e9a5ce8b92272237b.png 3
 
1.9%
0c28480254cc486da4805b2fa9933563.png 3
 
1.9%
9a6d4aded47e4eb49a20f61512be525f.png 3
 
1.9%
Other values (85) 113
72.9%
2023-12-10T15:13:35.730087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 407
 
7.4%
b 369
 
6.7%
a 347
 
6.3%
8 338
 
6.1%
7 319
 
5.8%
2 317
 
5.7%
3 298
 
5.4%
0 290
 
5.3%
e 290
 
5.3%
9 287
 
5.2%
Other values (10) 2254
40.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3086
55.9%
Lowercase Letter 2276
41.3%
Other Punctuation 154
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 407
13.2%
8 338
11.0%
7 319
10.3%
2 317
10.3%
3 298
9.7%
0 290
9.4%
9 287
9.3%
1 283
9.2%
6 280
9.1%
5 267
8.7%
Lowercase Letter
ValueCountFrequency (%)
b 369
16.2%
a 347
15.2%
e 290
12.7%
d 282
12.4%
c 276
12.1%
f 253
11.1%
p 153
6.7%
n 153
6.7%
g 153
6.7%
Other Punctuation
ValueCountFrequency (%)
. 154
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3240
58.7%
Latin 2276
41.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 407
12.6%
8 338
10.4%
7 319
9.8%
2 317
9.8%
3 298
9.2%
0 290
9.0%
9 287
8.9%
1 283
8.7%
6 280
8.6%
5 267
8.2%
Latin
ValueCountFrequency (%)
b 369
16.2%
a 347
15.2%
e 290
12.7%
d 282
12.4%
c 276
12.1%
f 253
11.1%
p 153
6.7%
n 153
6.7%
g 153
6.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 407
 
7.4%
b 369
 
6.7%
a 347
 
6.3%
8 338
 
6.1%
7 319
 
5.8%
2 317
 
5.7%
3 298
 
5.4%
0 290
 
5.3%
e 290
 
5.3%
9 287
 
5.2%
Other values (10) 2254
40.9%

Sex
Categorical

Distinct2
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1
150 
0
49 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 150
75.4%
0 49
 
24.6%

Length

2023-12-10T15:13:35.964460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:13:36.114425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 150
75.4%
0 49
 
24.6%

Age
Real number (ℝ)

Distinct8
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.39196
Minimum17
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:36.239156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile17
Q117
median31
Q345
95-th percentile75
Maximum75
Range58
Interquartile range (IQR)28

Descriptive statistics

Standard deviation15.496729
Coefficient of variation (CV)0.45059163
Kurtosis0.56842604
Mean34.39196
Median Absolute Deviation (MAD)14
Skewness0.87548876
Sum6844
Variance240.14862
MonotonicityNot monotonic
2023-12-10T15:13:36.394974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
17 53
26.6%
38 35
17.6%
45 34
17.1%
31 31
15.6%
24 20
 
10.1%
75 12
 
6.0%
52 12
 
6.0%
59 2
 
1.0%
ValueCountFrequency (%)
17 53
26.6%
24 20
 
10.1%
31 31
15.6%
38 35
17.6%
45 34
17.1%
52 12
 
6.0%
59 2
 
1.0%
75 12
 
6.0%
ValueCountFrequency (%)
75 12
 
6.0%
59 2
 
1.0%
52 12
 
6.0%
45 34
17.1%
38 35
17.6%
31 31
15.6%
24 20
 
10.1%
17 53
26.6%

Height
Real number (ℝ)

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163.42714
Minimum152
Maximum188
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:36.544943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum152
5-th percentile158
Q1158
median164
Q3164
95-th percentile176
Maximum188
Range36
Interquartile range (IQR)6

Descriptive statistics

Standard deviation7.0991156
Coefficient of variation (CV)0.043439026
Kurtosis3.3943579
Mean163.42714
Median Absolute Deviation (MAD)6
Skewness1.5541127
Sum32522
Variance50.397442
MonotonicityNot monotonic
2023-12-10T15:13:36.688184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
164 77
38.7%
158 73
36.7%
170 28
 
14.1%
152 8
 
4.0%
188 7
 
3.5%
176 4
 
2.0%
182 2
 
1.0%
ValueCountFrequency (%)
152 8
 
4.0%
158 73
36.7%
164 77
38.7%
170 28
 
14.1%
176 4
 
2.0%
182 2
 
1.0%
188 7
 
3.5%
ValueCountFrequency (%)
188 7
 
3.5%
182 2
 
1.0%
176 4
 
2.0%
170 28
 
14.1%
164 77
38.7%
158 73
36.7%
152 8
 
4.0%

Weight
Real number (ℝ)

Distinct37
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.135678
Minimum45
Maximum109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:13:36.868949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile46
Q154
median58
Q369
95-th percentile95
Maximum109
Range64
Interquartile range (IQR)15

Descriptive statistics

Standard deviation14.676535
Coefficient of variation (CV)0.23246025
Kurtosis1.242539
Mean63.135678
Median Absolute Deviation (MAD)6
Skewness1.2992916
Sum12564
Variance215.40069
MonotonicityNot monotonic
2023-12-10T15:13:37.059209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
54 29
 
14.6%
58 19
 
9.5%
57 14
 
7.0%
45 9
 
4.5%
72 9
 
4.5%
50 8
 
4.0%
62 8
 
4.0%
64 8
 
4.0%
48 7
 
3.5%
84 6
 
3.0%
Other values (27) 82
41.2%
ValueCountFrequency (%)
45 9
 
4.5%
46 4
 
2.0%
48 7
 
3.5%
49 5
 
2.5%
50 8
 
4.0%
52 4
 
2.0%
53 4
 
2.0%
54 29
14.6%
55 2
 
1.0%
56 4
 
2.0%
ValueCountFrequency (%)
109 4
2.0%
104 1
 
0.5%
101 2
 
1.0%
98 2
 
1.0%
95 3
1.5%
90 4
2.0%
86 4
2.0%
84 6
3.0%
82 3
1.5%
80 1
 
0.5%

ActivityLevel
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1
107 
2
59 
0
29 
3
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
1 107
53.8%
2 59
29.6%
0 29
 
14.6%
3 4
 
2.0%

Length

2023-12-10T15:13:37.237700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:13:37.462370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 107
53.8%
2 59
29.6%
0 29
 
14.6%
3 4
 
2.0%

EatType
Categorical

Distinct4
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1
64 
0
56 
2
51 
3
28 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 64
32.2%
0 56
28.1%
2 51
25.6%
3 28
14.1%

Length

2023-12-10T15:13:37.715579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:13:37.884811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 64
32.2%
0 56
28.1%
2 51
25.6%
3 28
14.1%

Sample

idUserkeyTimeEatAmountNationalityFoodNameStandardUnitTotalGramCalorieCarbonHydrateSugarProteinLoseWeightSaturatedFattyAcidTransFatCholesterolSodiumCelluloseCalciumFolicAcidIronVitaminAVitaminCDayOfDietCaffeinewaterashtotal_amino_acidsessential_amino_acidFoodImageSexAgeHeightWeightActivityLevelEatType
0329455c1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a802019-10-22 12:591.0ko어묵탕1인분600251.034.22.418.601.560.024.62064.019.296.00.021.00.00.00085.7433.2889245.94111.38eb5eb82f3fdf42139b3497ab23da6bbb.png0751585021
1329456c1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a802019-10-22 12:591.0ko흑미밥1공기210330.071.00.06.500.30.00.0170.00.00.00.00.00.00.0000.00.00.00.0eb5eb82f3fdf42139b3497ab23da6bbb.png0751585021
2329457c1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a802019-10-22 12:591.0ko배추김치1접시4010.01.760.00.5600.00.00.992.80.025.617.00.3219.02.80037.120.480.00.0eb5eb82f3fdf42139b3497ab23da6bbb.png0751585021
3329458c1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a802019-10-22 12:591.0ko오이1인분(1/3개)708.02.1350.9660.600.0160.00.02.10.612.618.00.55.07.8750066.640.357466.2149.8eb5eb82f3fdf42139b3497ab23da6bbb.png0751585021
4329459c1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a802019-10-22 12:591.0ko소불고기1인분200177.018.23.412.801.5460.041.4892.03.632.013.022.15750.02.00095.20451.829411664.85795.73eb5eb82f3fdf42139b3497ab23da6bbb.png0751585021
5329460c1f8b0717defc9c7ca209b7cdcd240f758cda311c86a7c856c422b8f44a68a802019-10-22 12:591.0ko감자조림1접시3540.05.00.70.800.20.00.0200.00.00.00.00.00.00.0000.00.00.00.0eb5eb82f3fdf42139b3497ab23da6bbb.png0751585021
6298085a44429708a6b5609b4c31a1c712bc4d73a0a57476f2cf619754bf5c04ca3755e2019-10-02 12:351.0ko육개장(소고기)1인분700340.021.00.721.707.2730.0142.82856.016.8154.00.069.30.00.070163.8223.63282485.061022.869da362ae8ab141af8857a9feccb9761c.png0751646211
7298086a44429708a6b5609b4c31a1c712bc4d73a0a57476f2cf619754bf5c04ca3755e2019-10-02 12:350.25ko깍두기1접시103.80.7540.3550.14300.0040.00.050.10.434.16.00.0333.752.0708.890.19492.734.09da362ae8ab141af8857a9feccb9761c.png0751646211
8298087a44429708a6b5609b4c31a1c712bc4d73a0a57476f2cf619754bf5c04ca3755e2019-10-02 12:350.25ko멸치볶음1종지7.520.961.32430.751.7424500.1587250.016.2705159.1370.32534.58.750.250.00.02965702.687250.576651857.47931.5359da362ae8ab141af8857a9feccb9761c.png0751646211
9298088a44429708a6b5609b4c31a1c712bc4d73a0a57476f2cf619754bf5c04ca3755e2019-10-02 12:351.0ko쌀밥1공기210326.771.550.05.7600.1260.00.07.20.96.311.01.171.00.07012.060.360.00.09da362ae8ab141af8857a9feccb9761c.png0751646211
idUserkeyTimeEatAmountNationalityFoodNameStandardUnitTotalGramCalorieCarbonHydrateSugarProteinLoseWeightSaturatedFattyAcidTransFatCholesterolSodiumCelluloseCalciumFolicAcidIronVitaminAVitaminCDayOfDietCaffeinewaterashtotal_amino_acidsessential_amino_acidFoodImageSexAgeHeightWeightActivityLevelEatType
18928429703f4b67b553b0aa438d3892c98023b161606dc6dcb9d74759b87260c97b0dc962019-10-07 20:251.0ko아이스 라떼1컵340108.00.07.06.003.80.00.085.00.00.00.00.00.00.07800.00.00.00.04b7add72c0364f61a17b530c60759d09.png1381645803
190322721ce147889c647c0acb74685ad165315ead0de8aa46000ff804f76b491e76e5f342019-10-28 6:050.5ko양배추1접시3511.552.7721.67650.58810.01050.00.05.52.8515.7527.50.09458.53.011031.3950.217478.1121.19c7dd30fe38c4bc7874a884428b7410c.png1311644920
191309632fa08272039db75128d6d6ffb59bfffd94378012021647fb1c5d2fdd9da0c40d72019-10-20 18:541.0ko잡곡밥1공기210329.0568.67950.3937.310.1490.00.07.02.318.025.01.5391.00.33614011.9450.632126.2950.45b5ddb912b6414ed696d707430d04a9af.png0451707322
192293699a165642710239dfc732e4706aaf4ad8588a2705e81bde6a280d481813c2235d32019-10-10 11:300.75ko비빔밥1인분300465.070.57.271718.082.75250.0163.7251065.755.785.5162.04.050.018.1326230162.3674.6581712454.55910.8180abb4660b4d46edb2688a3892a1918f.png1381586201
1932852519d213c94cf557d10ece8d185161097cb782703c6358830d578d1a5d9f2d3f78b2019-10-10 6:511.0ko닭고기(가슴삶은것)1접시45.083.00.00.0-6912.64050.9360.033.828.00.06.01.00.411.06700.031.680.589512177.96085.350521646920
194306316c27cc35cb7128cf2be8f414952d26f4f33ff0f791bc4e0bcbfc79fe89683a98c2019-10-05 16:280.75ko우유(저지방)1컵15054.06.95.3855.14500.60.06.0153.00.0157.50.00.04515.00.40520135.151.0654618.52097.00dc9056644fa4f98bf165c5869d5f98b.png1311524812
19532892558254f8704f66800a4673a15fd3207a2d90183e2590db394c56ab32c4e8285a32019-10-26 8:031.0en바나나1개10080.021.013.31331.00100.10.00.01.02.56.3716.00.49.05.40545069.2510.6916830.83418.670a74ae7ed8b4d28875e583a7cd10264.png03118210120
19628429803f4b67b553b0aa438d3892c98023b161606dc6dcb9d74759b87260c97b0dc962019-10-08 8:032.0ko식빵1장70198.035.84.25.800.5740.00.0361.22.418.224.50.422.00.079024.361.126024.21864.1adf7e2aeddd04c0cb539c2596788ae53.png1381645800
197298444c59f02160bf53c92c4683932028ec62228c47d75aad4f988b1f40523ad2c2c0b2019-10-10 12:111.0ko곤약1인분(2/5봉지)10010.03.00.00.040.00.00.05.00.00.00.00.00.00.01500.00.00.00.0c355eb3e0f994254848820a5bb6276ea.png1311708200
1982801217750b630675289d90d236f73393ca8378f87a914f731c0ef9e3fcd4864a8853f2019-10-30 13:431.0ko방울토마토1인분(16개)20035.08.07.782.020.050.00.010.04.228.070.00.74482.042.01610184.61.11770.0468.0f84196b983e3475eb0226f7e3aaafcc7.png1521585501