Overview

Dataset statistics

Number of variables68
Number of observations30
Missing cells30
Missing cells (%)1.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory17.9 KiB
Average record size in memory611.4 B

Variable types

Text2
Categorical5
Numeric60
Unsupported1

Dataset

DescriptionSample
Author(주)어메이징푸드솔루션
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=AFS00000000000000004

Alerts

AD_FD_FOOD_DISH_SIZE has constant value ""Constant
AD_FD_AMOUNT has constant value ""Constant
AD_FD_LST_DML_DT has constant value ""Constant
AD_FD_SEND_DT has 30 (100.0%) missing valuesMissing
AD_FD_FOOD_CD has unique valuesUnique
AD_FD_PROTEIN has unique valuesUnique
AD_FD_POLLEN has unique valuesUnique
AD_FD_BETA_CAROTENE has unique valuesUnique
AD_FD_VITA_K has unique valuesUnique
AD_FD_FOLATE has unique valuesUnique
AD_FD_BIOTIN has unique valuesUnique
AD_FD_CALCIUM has unique valuesUnique
AD_FD_VGT_CALCIUM has unique valuesUnique
AD_FD_PHOSPHORUS has unique valuesUnique
AD_FD_SALT has unique valuesUnique
AD_FD_POTASSIUM has unique valuesUnique
AD_FD_FERRIC has unique valuesUnique
AD_FD_ZINC has unique valuesUnique
AD_FD_SELENIUM has unique valuesUnique
AD_FD_ISOLEUCINE has unique valuesUnique
AD_FD_LEUCINE has unique valuesUnique
AD_FD_LYSINE has unique valuesUnique
AD_FD_METHIONINE has unique valuesUnique
AD_FD_PHENYLALANINE has unique valuesUnique
AD_FD_THREONINE has unique valuesUnique
AD_FD_TRYPTOPHAN has unique valuesUnique
AD_FD_VALINE has unique valuesUnique
AD_FD_HISTIDINE has unique valuesUnique
AD_FD_ARGININE has unique valuesUnique
AD_FD_CAL has unique valuesUnique
AD_FD_CARB has unique valuesUnique
AD_FD_FAT has unique valuesUnique
AD_FD_SEND_DT is an unsupported type, check if it needs cleaning or further analysisUnsupported
AD_FD_ANI_FAT has 11 (36.7%) zerosZeros
AD_FD_ANI_PROTEIN has 11 (36.7%) zerosZeros
AD_FD_VITA_A has 2 (6.7%) zerosZeros
AD_FD_RETINOL has 9 (30.0%) zerosZeros
AD_FD_VITA_D has 14 (46.7%) zerosZeros
AD_FD_VITA_C has 3 (10.0%) zerosZeros
AD_FD_VITA_B1 has 3 (10.0%) zerosZeros
AD_FD_VITA_B2 has 1 (3.3%) zerosZeros
AD_FD_VITA_B6 has 1 (3.3%) zerosZeros
AD_FD_VITA_B12 has 8 (26.7%) zerosZeros
AD_FD_BIOTIN has 1 (3.3%) zerosZeros
AD_FD_ANI_CALCIUM has 11 (36.7%) zerosZeros
AD_FD_CHLORINE has 4 (13.3%) zerosZeros
AD_FD_MAGNESIUM has 2 (6.7%) zerosZeros
AD_FD_ANI_FERRIC has 11 (36.7%) zerosZeros
AD_FD_COPPER has 2 (6.7%) zerosZeros
AD_FD_FLUORINE has 15 (50.0%) zerosZeros
AD_FD_IODINE has 5 (16.7%) zerosZeros
AD_FD_CHOLESTEROL has 6 (20.0%) zerosZeros
AD_FD_TOTAL_FAT_ACID has 1 (3.3%) zerosZeros
AD_FD_SATURATED_FAT_ACID has 2 (6.7%) zerosZeros
AD_FD_MONOSATURATED_FAT_ACID has 2 (6.7%) zerosZeros
AD_FD_POLYSATURATED_FAT_ACID has 1 (3.3%) zerosZeros
AD_FD_TRANS_FAT_ACID has 21 (70.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:17:49.148572
Analysis finished2023-12-10 06:17:49.982571
Duration0.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

AD_FD_FOOD_CD
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T15:17:50.222349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.966667
Min length13

Characters and Unicode

Total characters419
Distinct characters12
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

Unique30 ?
Unique (%)100.0%

Sample

1st rowAF001010160050
2nd rowAF001010160060
3rd rowAF001010170010
4th rowAF001010170020
5th rowAF001010170030
ValueCountFrequency (%)
af001010160050 1
 
3.3%
af001010160060 1
 
3.3%
af004080120750 1
 
3.3%
af004080120740 1
 
3.3%
af004080120730 1
 
3.3%
af004080120720 1
 
3.3%
af00406011003 1
 
3.3%
af004080120700 1
 
3.3%
af004080120690 1
 
3.3%
af004020130070 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T15:17:50.808147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 196
46.8%
1 60
 
14.3%
2 35
 
8.4%
A 30
 
7.2%
F 30
 
7.2%
4 24
 
5.7%
7 13
 
3.1%
3 8
 
1.9%
8 8
 
1.9%
6 7
 
1.7%
Other values (2) 8
 
1.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 359
85.7%
Uppercase Letter 60
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 196
54.6%
1 60
 
16.7%
2 35
 
9.7%
4 24
 
6.7%
7 13
 
3.6%
3 8
 
2.2%
8 8
 
2.2%
6 7
 
1.9%
5 6
 
1.7%
9 2
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
A 30
50.0%
F 30
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 359
85.7%
Latin 60
 
14.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 196
54.6%
1 60
 
16.7%
2 35
 
9.7%
4 24
 
6.7%
7 13
 
3.6%
3 8
 
2.2%
8 8
 
2.2%
6 7
 
1.9%
5 6
 
1.7%
9 2
 
0.6%
Latin
ValueCountFrequency (%)
A 30
50.0%
F 30
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 196
46.8%
1 60
 
14.3%
2 35
 
8.4%
A 30
 
7.2%
F 30
 
7.2%
4 24
 
5.7%
7 13
 
3.1%
3 8
 
1.9%
8 8
 
1.9%
6 7
 
1.7%
Other values (2) 8
 
1.9%

AD_FD_SERVICE_CD
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
AF004
20 
AF001
10 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAF001
2nd rowAF001
3rd rowAF001
4th rowAF001
5th rowAF001

Common Values

ValueCountFrequency (%)
AF004 20
66.7%
AF001 10
33.3%

Length

2023-12-10T15:17:51.051000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:17:51.222368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
af004 20
66.7%
af001 10
33.3%

AD_FD_VGT_FAT
Real number (ℝ)

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8773333
Minimum0.03
Maximum15.46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:51.419329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile0.089
Q10.2025
median0.71
Q33.855
95-th percentile13.5905
Maximum15.46
Range15.43
Interquartile range (IQR)3.6525

Descriptive statistics

Standard deviation4.5566805
Coefficient of variation (CV)1.5836471
Kurtosis2.2552248
Mean2.8773333
Median Absolute Deviation (MAD)0.555
Skewness1.8334726
Sum86.32
Variance20.763337
MonotonicityNot monotonic
2023-12-10T15:17:51.686790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.2 2
 
6.7%
0.11 2
 
6.7%
0.92 2
 
6.7%
12.32 1
 
3.3%
7.05 1
 
3.3%
0.24 1
 
3.3%
0.03 1
 
3.3%
0.69 1
 
3.3%
0.21 1
 
3.3%
2.13 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.03 1
3.3%
0.08 1
3.3%
0.1 1
3.3%
0.11 2
6.7%
0.16 1
3.3%
0.2 2
6.7%
0.21 1
3.3%
0.23 1
3.3%
0.24 1
3.3%
0.32 1
3.3%
ValueCountFrequency (%)
15.46 1
3.3%
14.63 1
3.3%
12.32 1
3.3%
10.6 1
3.3%
7.05 1
3.3%
5.24 1
3.3%
4.96 1
3.3%
4.43 1
3.3%
2.13 1
3.3%
1.27 1
3.3%

AD_FD_ANI_FAT
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7346667
Minimum0
Maximum18.78
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:51.893630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.96
Q36.2075
95-th percentile14.475
Maximum18.78
Range18.78
Interquartile range (IQR)6.2075

Descriptive statistics

Standard deviation5.2439994
Coefficient of variation (CV)1.4041412
Kurtosis1.6414254
Mean3.7346667
Median Absolute Deviation (MAD)0.96
Skewness1.5170613
Sum112.04
Variance27.499529
MonotonicityNot monotonic
2023-12-10T15:17:52.110517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 11
36.7%
0.96 3
 
10.0%
9.1 1
 
3.3%
12.0 1
 
3.3%
4.56 1
 
3.3%
18.78 1
 
3.3%
4.33 1
 
3.3%
16.5 1
 
3.3%
1.96 1
 
3.3%
3.01 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
0.0 11
36.7%
0.18 1
 
3.3%
0.2 1
 
3.3%
0.32 1
 
3.3%
0.96 3
 
10.0%
1.96 1
 
3.3%
3.01 1
 
3.3%
4.33 1
 
3.3%
4.56 1
 
3.3%
4.88 1
 
3.3%
ValueCountFrequency (%)
18.78 1
3.3%
16.5 1
3.3%
12.0 1
3.3%
9.75 1
3.3%
9.52 1
3.3%
9.1 1
3.3%
7.42 1
3.3%
6.65 1
3.3%
4.88 1
3.3%
4.56 1
3.3%

AD_FD_PROTEIN
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.108
Minimum0.98
Maximum72.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:52.322232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.98
5-th percentile3.15
Q14.685
median7.375
Q320.0175
95-th percentile28.7505
Maximum72.86
Range71.88
Interquartile range (IQR)15.3325

Descriptive statistics

Standard deviation14.284007
Coefficient of variation (CV)1.0897167
Kurtosis9.9645237
Mean13.108
Median Absolute Deviation (MAD)2.9
Skewness2.7657554
Sum393.24
Variance204.03285
MonotonicityNot monotonic
2023-12-10T15:17:52.571917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
9.74 1
 
3.3%
3.69 1
 
3.3%
23.45 1
 
3.3%
6.16 1
 
3.3%
29.7 1
 
3.3%
19.77 1
 
3.3%
6.15 1
 
3.3%
10.29 1
 
3.3%
27.07 1
 
3.3%
21.82 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.98 1
3.3%
2.79 1
3.3%
3.59 1
3.3%
3.69 1
3.3%
3.75 1
3.3%
4.49 1
3.3%
4.53 1
3.3%
4.64 1
3.3%
4.82 1
3.3%
5.65 1
3.3%
ValueCountFrequency (%)
72.86 1
3.3%
29.7 1
3.3%
27.59 1
3.3%
27.07 1
3.3%
26.65 1
3.3%
23.45 1
3.3%
21.82 1
3.3%
20.1 1
3.3%
19.77 1
3.3%
10.29 1
3.3%

AD_FD_VGT_PROTEIN
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4316667
Minimum0.58
Maximum29.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:52.831776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.58
5-th percentile0.7975
Q11.315
median3.02
Q35.4825
95-th percentile9.3715
Maximum29.1
Range28.52
Interquartile range (IQR)4.1675

Descriptive statistics

Standard deviation5.3305496
Coefficient of variation (CV)1.2028318
Kurtosis16.270328
Mean4.4316667
Median Absolute Deviation (MAD)2.045
Skewness3.6354138
Sum132.95
Variance28.414759
MonotonicityNot monotonic
2023-12-10T15:17:53.029293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.97 2
 
6.7%
0.98 2
 
6.7%
9.43 1
 
3.3%
3.27 1
 
3.3%
2.72 1
 
3.3%
3.05 1
 
3.3%
5.49 1
 
3.3%
1.5 1
 
3.3%
2.99 1
 
3.3%
9.3 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.58 1
3.3%
0.73 1
3.3%
0.88 1
3.3%
0.97 2
6.7%
0.98 2
6.7%
1.28 1
3.3%
1.42 1
3.3%
1.5 1
3.3%
2.3 1
3.3%
2.72 1
3.3%
ValueCountFrequency (%)
29.1 1
3.3%
9.43 1
3.3%
9.3 1
3.3%
8.1 1
3.3%
7.25 1
3.3%
6.5 1
3.3%
5.86 1
3.3%
5.49 1
3.3%
5.46 1
3.3%
5.15 1
3.3%

AD_FD_ANI_PROTEIN
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.9686667
Minimum0
Maximum24.16
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:53.290134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1.06
Q36.285
95-th percentile19.5365
Maximum24.16
Range24.16
Interquartile range (IQR)6.285

Descriptive statistics

Standard deviation7.5679026
Coefficient of variation (CV)1.5231254
Kurtosis0.63480897
Mean4.9686667
Median Absolute Deviation (MAD)1.06
Skewness1.4666025
Sum149.06
Variance57.27315
MonotonicityNot monotonic
2023-12-10T15:17:53.547027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 11
36.7%
0.96 3
 
10.0%
1.36 2
 
6.7%
7.04 1
 
3.3%
4.02 1
 
3.3%
7.7 1
 
3.3%
1.16 1
 
3.3%
1.18 1
 
3.3%
0.95 1
 
3.3%
15.57 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
0.0 11
36.7%
0.95 1
 
3.3%
0.96 3
 
10.0%
1.16 1
 
3.3%
1.18 1
 
3.3%
1.36 2
 
6.7%
2.86 1
 
3.3%
3.53 1
 
3.3%
4.02 1
 
3.3%
7.04 1
 
3.3%
ValueCountFrequency (%)
24.16 1
3.3%
20.0 1
3.3%
18.97 1
3.3%
18.5 1
3.3%
17.82 1
3.3%
15.57 1
3.3%
7.7 1
3.3%
7.04 1
3.3%
4.02 1
3.3%
3.53 1
3.3%

AD_FD_TOTAL_DIETARY_FIBER
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7456667
Minimum0.78
Maximum13.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:53.754147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.78
5-th percentile1.232
Q12.16
median2.635
Q33.9625
95-th percentile11.881
Maximum13.73
Range12.95
Interquartile range (IQR)1.8025

Descriptive statistics

Standard deviation3.1650142
Coefficient of variation (CV)0.84498022
Kurtosis5.0683881
Mean3.7456667
Median Absolute Deviation (MAD)0.66
Skewness2.3448917
Sum112.37
Variance10.017315
MonotonicityNot monotonic
2023-12-10T15:17:54.022720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
2.66 2
 
6.7%
2.37 2
 
6.7%
2.58 1
 
3.3%
3.94 1
 
3.3%
1.97 1
 
3.3%
10.33 1
 
3.3%
3.13 1
 
3.3%
1.98 1
 
3.3%
3.71 1
 
3.3%
4.28 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.78 1
3.3%
0.98 1
3.3%
1.54 1
3.3%
1.72 1
3.3%
1.97 1
3.3%
1.98 1
3.3%
2.07 1
3.3%
2.11 1
3.3%
2.31 1
3.3%
2.37 2
6.7%
ValueCountFrequency (%)
13.73 1
3.3%
13.15 1
3.3%
10.33 1
3.3%
5.28 1
3.3%
4.91 1
3.3%
4.83 1
3.3%
4.28 1
3.3%
3.97 1
3.3%
3.94 1
3.3%
3.71 1
3.3%

AD_FD_WATER
Real number (ℝ)

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean141.069
Minimum14.06
Maximum864.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:54.279063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14.06
5-th percentile17.024
Q182.945
median137.2
Q3156.88
95-th percentile187.173
Maximum864.84
Range850.78
Interquartile range (IQR)73.935

Descriptive statistics

Standard deviation147.66162
Coefficient of variation (CV)1.0467333
Kurtosis21.256081
Mean141.069
Median Absolute Deviation (MAD)26.45
Skewness4.2335442
Sum4232.07
Variance21803.954
MonotonicityNot monotonic
2023-12-10T15:17:54.459431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
157.15 2
 
6.7%
14.06 1
 
3.3%
186.4 1
 
3.3%
111.46 1
 
3.3%
154.76 1
 
3.3%
111.65 1
 
3.3%
123.3 1
 
3.3%
120.81 1
 
3.3%
183.44 1
 
3.3%
123.28 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
14.06 1
3.3%
14.9 1
3.3%
19.62 1
3.3%
29.14 1
3.3%
37.82 1
3.3%
43.91 1
3.3%
44.66 1
3.3%
79.3 1
3.3%
93.88 1
3.3%
110.04 1
3.3%
ValueCountFrequency (%)
864.84 1
3.3%
187.74 1
3.3%
186.48 1
3.3%
186.4 1
3.3%
183.44 1
3.3%
157.52 1
3.3%
157.15 2
6.7%
156.07 1
3.3%
155.04 1
3.3%
154.76 1
3.3%

AD_FD_POLLEN
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6636667
Minimum0.52
Maximum16.45
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:55.033399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.52
5-th percentile0.6865
Q11.795
median2.155
Q32.745
95-th percentile4.577
Maximum16.45
Range15.93
Interquartile range (IQR)0.95

Descriptive statistics

Standard deviation2.7843671
Coefficient of variation (CV)1.0453136
Kurtosis22.236549
Mean2.6636667
Median Absolute Deviation (MAD)0.545
Skewness4.4423385
Sum79.91
Variance7.7526999
MonotonicityNot monotonic
2023-12-10T15:17:55.266376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2.61 1
 
3.3%
2.08 1
 
3.3%
2.99 1
 
3.3%
2.49 1
 
3.3%
2.79 1
 
3.3%
1.84 1
 
3.3%
2.48 1
 
3.3%
1.24 1
 
3.3%
3.95 1
 
3.3%
3.4 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.52 1
3.3%
0.61 1
3.3%
0.78 1
3.3%
1.06 1
3.3%
1.14 1
3.3%
1.23 1
3.3%
1.24 1
3.3%
1.78 1
3.3%
1.84 1
3.3%
1.85 1
3.3%
ValueCountFrequency (%)
16.45 1
3.3%
5.09 1
3.3%
3.95 1
3.3%
3.4 1
3.3%
3.23 1
3.3%
3.11 1
3.3%
2.99 1
3.3%
2.79 1
3.3%
2.61 1
3.3%
2.49 1
3.3%

AD_FD_VITA_A
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.24167
Minimum0
Maximum881.54
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:55.484949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.252
Q19.0925
median43.235
Q3121.7775
95-th percentile548.8545
Maximum881.54
Range881.54
Interquartile range (IQR)112.685

Descriptive statistics

Standard deviation203.31067
Coefficient of variation (CV)1.597831
Kurtosis6.4650735
Mean127.24167
Median Absolute Deviation (MAD)42.64
Skewness2.5082121
Sum3817.25
Variance41335.23
MonotonicityNot monotonic
2023-12-10T15:17:55.673048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 2
 
6.7%
1.14 1
 
3.3%
0.56 1
 
3.3%
108.96 1
 
3.3%
126.05 1
 
3.3%
99.82 1
 
3.3%
77.9 1
 
3.3%
126.06 1
 
3.3%
189.23 1
 
3.3%
592.05 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0 2
6.7%
0.56 1
3.3%
0.63 1
3.3%
1.14 1
3.3%
3.31 1
3.3%
5.56 1
3.3%
8.59 1
3.3%
10.6 1
3.3%
14.51 1
3.3%
24.37 1
3.3%
ValueCountFrequency (%)
881.54 1
3.3%
592.05 1
3.3%
496.06 1
3.3%
363.01 1
3.3%
224.86 1
3.3%
189.23 1
3.3%
126.06 1
3.3%
126.05 1
3.3%
108.96 1
3.3%
99.82 1
3.3%

AD_FD_RETINOL
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.750333
Minimum0
Maximum118.2
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:55.884826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5.5
Q321.945
95-th percentile45.7205
Maximum118.2
Range118.2
Interquartile range (IQR)21.945

Descriptive statistics

Standard deviation24.348176
Coefficient of variation (CV)1.5458832
Kurtosis10.317724
Mean15.750333
Median Absolute Deviation (MAD)5.5
Skewness2.8161516
Sum472.51
Variance592.83365
MonotonicityNot monotonic
2023-12-10T15:17:56.081207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 9
30.0%
14.2 3
 
10.0%
0.2 2
 
6.7%
28.01 1
 
3.3%
8.0 1
 
3.3%
21.6 1
 
3.3%
1.2 1
 
3.3%
45.0 1
 
3.3%
2.0 1
 
3.3%
22.06 1
 
3.3%
Other values (9) 9
30.0%
ValueCountFrequency (%)
0.0 9
30.0%
0.2 2
 
6.7%
0.86 1
 
3.3%
1.2 1
 
3.3%
2.0 1
 
3.3%
3.0 1
 
3.3%
8.0 1
 
3.3%
13.98 1
 
3.3%
14.2 3
 
10.0%
16.19 1
 
3.3%
ValueCountFrequency (%)
118.2 1
3.3%
46.31 1
3.3%
45.0 1
3.3%
40.3 1
3.3%
34.4 1
3.3%
28.4 1
3.3%
28.01 1
3.3%
22.06 1
3.3%
21.6 1
3.3%
16.19 1
3.3%

AD_FD_FOOD_GRP_CD
Real number (ℝ)

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7333333
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:56.274088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11.25
median3
Q35.5
95-th percentile8
Maximum8
Range7
Interquartile range (IQR)4.25

Descriptive statistics

Standard deviation2.6383555
Coefficient of variation (CV)0.70670236
Kurtosis-0.88145214
Mean3.7333333
Median Absolute Deviation (MAD)2
Skewness0.76859827
Sum112
Variance6.9609195
MonotonicityNot monotonic
2023-12-10T15:17:56.463104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
3 12
40.0%
1 8
26.7%
8 7
23.3%
4 1
 
3.3%
2 1
 
3.3%
6 1
 
3.3%
ValueCountFrequency (%)
1 8
26.7%
2 1
 
3.3%
3 12
40.0%
4 1
 
3.3%
6 1
 
3.3%
8 7
23.3%
ValueCountFrequency (%)
8 7
23.3%
6 1
 
3.3%
4 1
 
3.3%
3 12
40.0%
2 1
 
3.3%
1 8
26.7%

AD_FD_BETA_CAROTENE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean769.55
Minimum3.2
Maximum5122.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:56.670969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2
5-th percentile6.417
Q148.9075
median396.155
Q3756.4825
95-th percentile3262.013
Maximum5122.92
Range5119.72
Interquartile range (IQR)707.575

Descriptive statistics

Standard deviation1185.21
Coefficient of variation (CV)1.5401339
Kurtosis6.2887208
Mean769.55
Median Absolute Deviation (MAD)353.04
Skewness2.4816434
Sum23086.5
Variance1404722.8
MonotonicityNot monotonic
2023-12-10T15:17:56.911772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
282.46 1
 
3.3%
1265.28 1
 
3.3%
605.9 1
 
3.3%
756.34 1
 
3.3%
469.4 1
 
3.3%
460.21 1
 
3.3%
756.53 1
 
3.3%
100.75 1
 
3.3%
865.32 1
 
3.3%
3559.13 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
3.2 1
3.3%
3.6 1
3.3%
9.86 1
3.3%
14.0 1
3.3%
21.5 1
3.3%
38.4 1
3.3%
47.83 1
3.3%
48.86 1
3.3%
49.05 1
3.3%
69.53 1
3.3%
ValueCountFrequency (%)
5122.92 1
3.3%
3559.13 1
3.3%
2898.87 1
3.3%
2178.2 1
3.3%
1265.28 1
3.3%
865.32 1
3.3%
786.35 1
3.3%
756.53 1
3.3%
756.34 1
3.3%
725.93 1
3.3%

AD_FD_VITA_D
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.44833333
Minimum0
Maximum4.39
Zeros14
Zeros (%)46.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:57.118066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.055
Q30.3
95-th percentile2.743
Maximum4.39
Range4.39
Interquartile range (IQR)0.3

Descriptive statistics

Standard deviation1.0370452
Coefficient of variation (CV)2.3131119
Kurtosis9.9955765
Mean0.44833333
Median Absolute Deviation (MAD)0.055
Skewness3.2221415
Sum13.45
Variance1.0754626
MonotonicityNot monotonic
2023-12-10T15:17:57.287603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 14
46.7%
0.3 5
 
16.7%
0.12 2
 
6.7%
0.09 1
 
3.3%
1.5 1
 
3.3%
4.39 1
 
3.3%
3.76 1
 
3.3%
0.02 1
 
3.3%
0.33 1
 
3.3%
0.31 1
 
3.3%
Other values (2) 2
 
6.7%
ValueCountFrequency (%)
0.0 14
46.7%
0.02 1
 
3.3%
0.09 1
 
3.3%
0.12 2
 
6.7%
0.3 5
 
16.7%
0.31 1
 
3.3%
0.33 1
 
3.3%
0.59 1
 
3.3%
0.72 1
 
3.3%
1.5 1
 
3.3%
ValueCountFrequency (%)
4.39 1
 
3.3%
3.76 1
 
3.3%
1.5 1
 
3.3%
0.72 1
 
3.3%
0.59 1
 
3.3%
0.33 1
 
3.3%
0.31 1
 
3.3%
0.3 5
16.7%
0.12 2
 
6.7%
0.09 1
 
3.3%

AD_FD_VITA_E
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1523333
Minimum0.02
Maximum12.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:57.482622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.02
5-th percentile0.0625
Q10.5
median1.615
Q32.1725
95-th percentile7.328
Maximum12.15
Range12.13
Interquartile range (IQR)1.6725

Descriptive statistics

Standard deviation2.6307252
Coefficient of variation (CV)1.2222666
Kurtosis6.922841
Mean2.1523333
Median Absolute Deviation (MAD)1.025
Skewness2.4723785
Sum64.57
Variance6.9207151
MonotonicityNot monotonic
2023-12-10T15:17:57.763091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1.79 2
 
6.7%
1.32 2
 
6.7%
3.17 1
 
3.3%
1.37 1
 
3.3%
1.61 1
 
3.3%
0.37 1
 
3.3%
0.62 1
 
3.3%
1.12 1
 
3.3%
2.22 1
 
3.3%
2.47 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.02 1
3.3%
0.04 1
3.3%
0.09 1
3.3%
0.13 1
3.3%
0.23 1
3.3%
0.28 1
3.3%
0.37 1
3.3%
0.48 1
3.3%
0.56 1
3.3%
0.62 1
3.3%
ValueCountFrequency (%)
12.15 1
3.3%
7.58 1
3.3%
7.02 1
3.3%
4.45 1
3.3%
3.35 1
3.3%
3.17 1
3.3%
2.47 1
3.3%
2.22 1
3.3%
2.03 1
3.3%
1.89 1
3.3%

AD_FD_VITA_K
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.098333
Minimum0.12
Maximum583.86
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:57.965554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.12
5-th percentile0.495
Q12.4625
median8.845
Q314.865
95-th percentile68.1185
Maximum583.86
Range583.74
Interquartile range (IQR)12.4025

Descriptive statistics

Standard deviation105.64128
Coefficient of variation (CV)3.2911766
Kurtosis28.236108
Mean32.098333
Median Absolute Deviation (MAD)6.35
Skewness5.2541486
Sum962.95
Variance11160.081
MonotonicityNot monotonic
2023-12-10T15:17:58.154800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
15.01 1
 
3.3%
11.95 1
 
3.3%
4.89 1
 
3.3%
7.43 1
 
3.3%
14.37 1
 
3.3%
13.79 1
 
3.3%
7.66 1
 
3.3%
40.75 1
 
3.3%
51.91 1
 
3.3%
14.43 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.12 1
3.3%
0.18 1
3.3%
0.88 1
3.3%
0.89 1
3.3%
1.2 1
3.3%
1.22 1
3.3%
2.36 1
3.3%
2.43 1
3.3%
2.56 1
3.3%
3.44 1
3.3%
ValueCountFrequency (%)
583.86 1
3.3%
81.38 1
3.3%
51.91 1
3.3%
40.75 1
3.3%
20.82 1
3.3%
19.27 1
3.3%
15.48 1
3.3%
15.01 1
3.3%
14.43 1
3.3%
14.37 1
3.3%

AD_FD_VITA_C
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.333667
Minimum0
Maximum71.04
Zeros3
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:58.338377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q16.145
median13.77
Q333.41
95-th percentile53.13
Maximum71.04
Range71.04
Interquartile range (IQR)27.265

Descriptive statistics

Standard deviation19.119944
Coefficient of variation (CV)0.94030969
Kurtosis0.20595584
Mean20.333667
Median Absolute Deviation (MAD)11.535
Skewness0.98373211
Sum610.01
Variance365.57225
MonotonicityNot monotonic
2023-12-10T15:17:58.533414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 3
 
10.0%
0.21 1
 
3.3%
71.04 1
 
3.3%
10.36 1
 
3.3%
49.61 1
 
3.3%
41.85 1
 
3.3%
25.14 1
 
3.3%
49.4 1
 
3.3%
12.08 1
 
3.3%
33.42 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.0 3
10.0%
0.21 1
 
3.3%
2.07 1
 
3.3%
2.7 1
 
3.3%
5.58 1
 
3.3%
5.85 1
 
3.3%
7.03 1
 
3.3%
7.07 1
 
3.3%
7.7 1
 
3.3%
8.94 1
 
3.3%
ValueCountFrequency (%)
71.04 1
3.3%
56.01 1
3.3%
49.61 1
3.3%
49.4 1
3.3%
41.85 1
3.3%
35.59 1
3.3%
33.87 1
3.3%
33.42 1
3.3%
33.38 1
3.3%
32.62 1
3.3%

AD_FD_VITA_B1
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.22633333
Minimum0
Maximum1.02
Zeros3
Zeros (%)10.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:58.748890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0825
median0.15
Q30.2525
95-th percentile0.7355
Maximum1.02
Range1.02
Interquartile range (IQR)0.17

Descriptive statistics

Standard deviation0.24313305
Coefficient of variation (CV)1.0742255
Kurtosis3.6799283
Mean0.22633333
Median Absolute Deviation (MAD)0.08
Skewness1.9275788
Sum6.79
Variance0.059113678
MonotonicityNot monotonic
2023-12-10T15:17:58.924646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 3
 
10.0%
0.15 3
 
10.0%
0.12 3
 
10.0%
0.18 2
 
6.7%
0.2 2
 
6.7%
0.07 2
 
6.7%
0.05 1
 
3.3%
0.26 1
 
3.3%
0.39 1
 
3.3%
0.62 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
0.0 3
10.0%
0.01 1
 
3.3%
0.05 1
 
3.3%
0.07 2
6.7%
0.08 1
 
3.3%
0.09 1
 
3.3%
0.11 1
 
3.3%
0.12 3
10.0%
0.13 1
 
3.3%
0.15 3
10.0%
ValueCountFrequency (%)
1.02 1
3.3%
0.83 1
3.3%
0.62 1
3.3%
0.53 1
3.3%
0.42 1
3.3%
0.39 1
3.3%
0.31 1
3.3%
0.26 1
3.3%
0.23 1
3.3%
0.2 2
6.7%

AD_FD_VITA_B2
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.24566667
Minimum0
Maximum1.6
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:59.196021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.02
Q10.09
median0.135
Q30.3425
95-th percentile0.5825
Maximum1.6
Range1.6
Interquartile range (IQR)0.2525

Descriptive statistics

Standard deviation0.30744423
Coefficient of variation (CV)1.251469
Kurtosis12.901634
Mean0.24566667
Median Absolute Deviation (MAD)0.095
Skewness3.1741393
Sum7.37
Variance0.094521954
MonotonicityNot monotonic
2023-12-10T15:17:59.429863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.09 3
 
10.0%
0.02 2
 
6.7%
0.1 2
 
6.7%
0.03 2
 
6.7%
0.45 2
 
6.7%
0.05 2
 
6.7%
0.0 1
 
3.3%
0.5 1
 
3.3%
0.14 1
 
3.3%
0.32 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
0.0 1
 
3.3%
0.02 2
6.7%
0.03 2
6.7%
0.05 2
6.7%
0.09 3
10.0%
0.1 2
6.7%
0.11 1
 
3.3%
0.12 1
 
3.3%
0.13 1
 
3.3%
0.14 1
 
3.3%
ValueCountFrequency (%)
1.6 1
3.3%
0.65 1
3.3%
0.5 1
3.3%
0.45 2
6.7%
0.42 1
3.3%
0.41 1
3.3%
0.35 1
3.3%
0.32 1
3.3%
0.29 1
3.3%
0.22 1
3.3%

AD_FD_NIACIN
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8516667
Minimum0.15
Maximum14.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:17:59.654172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.15
5-th percentile0.474
Q11.005
median1.855
Q32.9925
95-th percentile7.615
Maximum14.92
Range14.77
Interquartile range (IQR)1.9875

Descriptive statistics

Standard deviation3.0361069
Coefficient of variation (CV)1.0646781
Kurtosis8.0298766
Mean2.8516667
Median Absolute Deviation (MAD)0.885
Skewness2.5518764
Sum85.55
Variance9.2179454
MonotonicityNot monotonic
2023-12-10T15:17:59.891569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
1.0 2
 
6.7%
4.78 2
 
6.7%
0.85 1
 
3.3%
6.68 1
 
3.3%
1.86 1
 
3.3%
8.38 1
 
3.3%
4.22 1
 
3.3%
1.87 1
 
3.3%
0.54 1
 
3.3%
2.41 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.15 1
3.3%
0.42 1
3.3%
0.54 1
3.3%
0.75 1
3.3%
0.85 1
3.3%
0.95 1
3.3%
1.0 2
6.7%
1.02 1
3.3%
1.06 1
3.3%
1.12 1
3.3%
ValueCountFrequency (%)
14.92 1
3.3%
8.38 1
3.3%
6.68 1
3.3%
6.34 1
3.3%
4.78 2
6.7%
4.22 1
3.3%
3.0 1
3.3%
2.97 1
3.3%
2.72 1
3.3%
2.68 1
3.3%

AD_FD_VITA_B6
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.23366667
Minimum0
Maximum1.49
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:00.153966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0235
Q10.1025
median0.13
Q30.215
95-th percentile0.5475
Maximum1.49
Range1.49
Interquartile range (IQR)0.1125

Descriptive statistics

Standard deviation0.285506
Coefficient of variation (CV)1.2218517
Kurtosis12.83946
Mean0.23366667
Median Absolute Deviation (MAD)0.045
Skewness3.2220337
Sum7.01
Variance0.081513678
MonotonicityNot monotonic
2023-12-10T15:18:00.396254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.13 3
 
10.0%
0.12 3
 
10.0%
0.14 2
 
6.7%
0.1 2
 
6.7%
0.11 2
 
6.7%
0.06 1
 
3.3%
0.43 1
 
3.3%
0.52 1
 
3.3%
0.49 1
 
3.3%
0.0 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
0.0 1
 
3.3%
0.01 1
 
3.3%
0.04 1
 
3.3%
0.06 1
 
3.3%
0.07 1
 
3.3%
0.09 1
 
3.3%
0.1 2
6.7%
0.11 2
6.7%
0.12 3
10.0%
0.13 3
10.0%
ValueCountFrequency (%)
1.49 1
3.3%
0.57 1
3.3%
0.52 1
3.3%
0.51 1
3.3%
0.49 1
3.3%
0.43 1
3.3%
0.37 1
3.3%
0.22 1
3.3%
0.2 1
3.3%
0.18 1
3.3%

AD_FD_FOLATE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean66.158
Minimum13.24
Maximum236.42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:00.617727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.24
5-th percentile25.1425
Q134.395
median46.45
Q380.8075
95-th percentile151.4525
Maximum236.42
Range223.18
Interquartile range (IQR)46.4125

Descriptive statistics

Standard deviation48.869292
Coefficient of variation (CV)0.73867547
Kurtosis4.0989877
Mean66.158
Median Absolute Deviation (MAD)15.82
Skewness1.8960488
Sum1984.74
Variance2388.2077
MonotonicityNot monotonic
2023-12-10T15:18:00.811952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
32.01 1
 
3.3%
54.74 1
 
3.3%
88.24 1
 
3.3%
33.58 1
 
3.3%
135.53 1
 
3.3%
82.06 1
 
3.3%
32.88 1
 
3.3%
29.25 1
 
3.3%
77.05 1
 
3.3%
39.83 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
13.24 1
3.3%
24.58 1
3.3%
25.83 1
3.3%
29.25 1
3.3%
32.01 1
3.3%
32.88 1
3.3%
33.58 1
3.3%
34.09 1
3.3%
35.31 1
3.3%
36.6 1
3.3%
ValueCountFrequency (%)
236.42 1
3.3%
164.48 1
3.3%
135.53 1
3.3%
117.94 1
3.3%
116.52 1
3.3%
113.74 1
3.3%
88.24 1
3.3%
82.06 1
3.3%
77.05 1
3.3%
67.7 1
3.3%

AD_FD_FOOD_GRP_NM
Categorical

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
죽| 스프류
12 
밥류
8 
볶음류
7 
국| 탕류
 
1
면| 만두류
 
1

Length

Max length6
Median length5
Mean length4.1
Min length2

Unique

Unique3 ?
Unique (%)10.0%

Sample

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

Common Values

ValueCountFrequency (%)
죽| 스프류 12
40.0%
밥류 8
26.7%
볶음류 7
23.3%
국| 탕류 1
 
3.3%
면| 만두류 1
 
3.3%
구이류 1
 
3.3%

Length

2023-12-10T15:18:01.040169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:18:01.261742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
죽 12
27.3%
스프류 12
27.3%
밥류 8
18.2%
볶음류 7
15.9%
국 1
 
2.3%
탕류 1
 
2.3%
면 1
 
2.3%
만두류 1
 
2.3%
구이류 1
 
2.3%

AD_FD_VITA_B12
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.51633333
Minimum0
Maximum2.82
Zeros8
Zeros (%)26.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:01.480616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.01
median0.145
Q30.4775
95-th percentile2.462
Maximum2.82
Range2.82
Interquartile range (IQR)0.4675

Descriptive statistics

Standard deviation0.80858106
Coefficient of variation (CV)1.5660059
Kurtosis2.7676038
Mean0.51633333
Median Absolute Deviation (MAD)0.145
Skewness1.9605244
Sum15.49
Variance0.65380333
MonotonicityNot monotonic
2023-12-10T15:18:01.685597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0.0 8
26.7%
0.12 3
 
10.0%
0.04 2
 
6.7%
0.17 1
 
3.3%
1.0 1
 
3.3%
0.48 1
 
3.3%
1.92 1
 
3.3%
0.44 1
 
3.3%
0.6 1
 
3.3%
0.41 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
0.0 8
26.7%
0.04 2
 
6.7%
0.09 1
 
3.3%
0.12 3
 
10.0%
0.14 1
 
3.3%
0.15 1
 
3.3%
0.16 1
 
3.3%
0.17 1
 
3.3%
0.41 1
 
3.3%
0.44 1
 
3.3%
ValueCountFrequency (%)
2.82 1
3.3%
2.48 1
3.3%
2.44 1
3.3%
1.92 1
3.3%
1.0 1
3.3%
0.83 1
3.3%
0.6 1
3.3%
0.48 1
3.3%
0.47 1
3.3%
0.45 1
3.3%

AD_FD_PANTOTHENIC_ACID
Real number (ℝ)

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.82233333
Minimum0.09
Maximum2.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:01.895794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.09
5-th percentile0.1325
Q10.295
median0.645
Q31.2575
95-th percentile1.83
Maximum2.39
Range2.3
Interquartile range (IQR)0.9625

Descriptive statistics

Standard deviation0.63964798
Coefficient of variation (CV)0.77784513
Kurtosis-0.43600077
Mean0.82233333
Median Absolute Deviation (MAD)0.45
Skewness0.77614103
Sum24.67
Variance0.40914954
MonotonicityNot monotonic
2023-12-10T15:18:02.132670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.34 2
 
6.7%
1.26 2
 
6.7%
0.75 2
 
6.7%
1.11 1
 
3.3%
0.49 1
 
3.3%
1.71 1
 
3.3%
1.92 1
 
3.3%
0.74 1
 
3.3%
0.26 1
 
3.3%
1.72 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.09 1
3.3%
0.11 1
3.3%
0.16 1
3.3%
0.19 1
3.3%
0.2 1
3.3%
0.24 1
3.3%
0.26 1
3.3%
0.28 1
3.3%
0.34 2
6.7%
0.35 1
3.3%
ValueCountFrequency (%)
2.39 1
3.3%
1.92 1
3.3%
1.72 1
3.3%
1.71 1
3.3%
1.7 1
3.3%
1.61 1
3.3%
1.26 2
6.7%
1.25 1
3.3%
1.2 1
3.3%
1.11 1
3.3%

AD_FD_BIOTIN
Real number (ℝ)

UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.736
Minimum0
Maximum16.09
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:02.320389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1155
Q10.5975
median1.485
Q33.4975
95-th percentile10.331
Maximum16.09
Range16.09
Interquartile range (IQR)2.9

Descriptive statistics

Standard deviation3.7757992
Coefficient of variation (CV)1.3800436
Kurtosis8.1338329
Mean2.736
Median Absolute Deviation (MAD)1.045
Skewness2.8154982
Sum82.08
Variance14.256659
MonotonicityNot monotonic
2023-12-10T15:18:02.553987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2.55 1
 
3.3%
1.63 1
 
3.3%
1.23 1
 
3.3%
1.25 1
 
3.3%
4.2 1
 
3.3%
1.89 1
 
3.3%
0.96 1
 
3.3%
0.03 1
 
3.3%
0.74 1
 
3.3%
2.86 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.0 1
3.3%
0.03 1
3.3%
0.22 1
3.3%
0.25 1
3.3%
0.33 1
3.3%
0.47 1
3.3%
0.5 1
3.3%
0.55 1
3.3%
0.74 1
3.3%
0.89 1
3.3%
ValueCountFrequency (%)
16.09 1
3.3%
15.02 1
3.3%
4.6 1
3.3%
4.58 1
3.3%
4.2 1
3.3%
4.18 1
3.3%
4.05 1
3.3%
3.71 1
3.3%
2.86 1
3.3%
2.55 1
3.3%

AD_FD_CALCIUM
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.654667
Minimum6.4
Maximum822.25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:02.795486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6.4
5-th percentile9.952
Q129.3825
median50.24
Q385.9
95-th percentile216.2455
Maximum822.25
Range815.85
Interquartile range (IQR)56.5175

Descriptive statistics

Standard deviation148.98561
Coefficient of variation (CV)1.661772
Kurtosis21.577898
Mean89.654667
Median Absolute Deviation (MAD)24.95
Skewness4.417466
Sum2689.64
Variance22196.712
MonotonicityNot monotonic
2023-12-10T15:18:03.031654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
95.56 1
 
3.3%
68.35 1
 
3.3%
23.4 1
 
3.3%
13.56 1
 
3.3%
51.88 1
 
3.3%
44.02 1
 
3.3%
14.05 1
 
3.3%
141.75 1
 
3.3%
50.84 1
 
3.3%
91.75 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
6.4 1
3.3%
7.0 1
3.3%
13.56 1
3.3%
14.05 1
3.3%
15.3 1
3.3%
23.4 1
3.3%
24.24 1
3.3%
26.34 1
3.3%
38.51 1
3.3%
39.37 1
3.3%
ValueCountFrequency (%)
822.25 1
3.3%
268.63 1
3.3%
152.22 1
3.3%
149.6 1
3.3%
141.75 1
3.3%
108.05 1
3.3%
95.56 1
3.3%
91.75 1
3.3%
68.35 1
3.3%
67.55 1
3.3%

AD_FD_VGT_CALCIUM
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.370333
Minimum2.41
Maximum216.84
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:03.259196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.41
5-th percentile4.496
Q110.7
median13.925
Q333.2175
95-th percentile109.692
Maximum216.84
Range214.43
Interquartile range (IQR)22.5175

Descriptive statistics

Standard deviation44.96587
Coefficient of variation (CV)1.3891074
Kurtosis9.6891094
Mean32.370333
Median Absolute Deviation (MAD)7.225
Skewness2.9189141
Sum971.11
Variance2021.9295
MonotonicityNot monotonic
2023-12-10T15:18:03.469812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
89.76 1
 
3.3%
28.25 1
 
3.3%
10.97 1
 
3.3%
11.05 1
 
3.3%
36.85 1
 
3.3%
34.5 1
 
3.3%
11.75 1
 
3.3%
126.0 1
 
3.3%
41.12 1
 
3.3%
71.98 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
2.41 1
3.3%
3.83 1
3.3%
5.31 1
3.3%
6.4 1
3.3%
7.0 1
3.3%
7.21 1
3.3%
10.23 1
3.3%
10.61 1
3.3%
10.97 1
3.3%
11.05 1
3.3%
ValueCountFrequency (%)
216.84 1
3.3%
126.0 1
3.3%
89.76 1
3.3%
71.98 1
3.3%
69.95 1
3.3%
41.12 1
3.3%
36.85 1
3.3%
34.5 1
3.3%
29.37 1
3.3%
28.25 1
3.3%

AD_FD_ANI_CALCIUM
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.766667
Minimum0
Maximum139.93
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:03.664358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median10.265
Q331.5
95-th percentile92.3255
Maximum139.93
Range139.93
Interquartile range (IQR)31.5

Descriptive statistics

Standard deviation34.810887
Coefficient of variation (CV)1.5290287
Kurtosis6.8990873
Mean22.766667
Median Absolute Deviation (MAD)10.265
Skewness2.5525214
Sum683
Variance1211.7978
MonotonicityNot monotonic
2023-12-10T15:18:03.960670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 11
36.7%
31.5 3
 
10.0%
39.3 1
 
3.3%
10.0 1
 
3.3%
13.33 1
 
3.3%
4.6 1
 
3.3%
9.5 1
 
3.3%
1.0 1
 
3.3%
135.62 1
 
3.3%
139.93 1
 
3.3%
Other values (8) 8
26.7%
ValueCountFrequency (%)
0.0 11
36.7%
1.0 1
 
3.3%
4.6 1
 
3.3%
9.5 1
 
3.3%
10.0 1
 
3.3%
10.53 1
 
3.3%
13.33 1
 
3.3%
15.4 1
 
3.3%
26.95 1
 
3.3%
28.37 1
 
3.3%
ValueCountFrequency (%)
139.93 1
 
3.3%
135.62 1
 
3.3%
39.41 1
 
3.3%
39.3 1
 
3.3%
38.56 1
 
3.3%
38.1 1
 
3.3%
37.9 1
 
3.3%
31.5 3
10.0%
28.37 1
 
3.3%
26.95 1
 
3.3%

AD_FD_PHOSPHORUS
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean214.55867
Minimum16.71
Maximum1221.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:04.189935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16.71
5-th percentile67.112
Q1111.9675
median143.035
Q3239.1425
95-th percentile534.5575
Maximum1221.21
Range1204.5
Interquartile range (IQR)127.175

Descriptive statistics

Standard deviation227.39347
Coefficient of variation (CV)1.0598196
Kurtosis13.675477
Mean214.55867
Median Absolute Deviation (MAD)48.23
Skewness3.4260235
Sum6436.76
Variance51707.791
MonotonicityNot monotonic
2023-12-10T15:18:04.879529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
147.14 1
 
3.3%
82.71 1
 
3.3%
244.25 1
 
3.3%
113.98 1
 
3.3%
262.11 1
 
3.3%
223.82 1
 
3.3%
113.46 1
 
3.3%
161.6 1
 
3.3%
367.63 1
 
3.3%
267.76 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
16.71 1
3.3%
54.35 1
3.3%
82.71 1
3.3%
89.07 1
3.3%
91.21 1
3.3%
98.4 1
3.3%
103.1 1
3.3%
111.47 1
3.3%
113.46 1
3.3%
113.98 1
3.3%
ValueCountFrequency (%)
1221.21 1
3.3%
662.2 1
3.3%
378.55 1
3.3%
367.63 1
3.3%
294.49 1
3.3%
267.76 1
3.3%
262.11 1
3.3%
244.25 1
3.3%
223.82 1
3.3%
200.64 1
3.3%

AD_FD_SALT
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean447.446
Minimum4.6
Maximum3710.34
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:05.088098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.6
5-th percentile5.735
Q1187.115
median357.26
Q3447.3825
95-th percentile771.661
Maximum3710.34
Range3705.74
Interquartile range (IQR)260.2675

Descriptive statistics

Standard deviation651.52414
Coefficient of variation (CV)1.4560956
Kurtosis23.399342
Mean447.446
Median Absolute Deviation (MAD)144.03
Skewness4.5849307
Sum13423.38
Variance424483.71
MonotonicityNot monotonic
2023-12-10T15:18:05.299948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
638.62 1
 
3.3%
351.82 1
 
3.3%
436.08 1
 
3.3%
405.92 1
 
3.3%
297.29 1
 
3.3%
134.84 1
 
3.3%
406.03 1
 
3.3%
7.0 1
 
3.3%
803.53 1
 
3.3%
451.15 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4.6 1
3.3%
4.7 1
3.3%
7.0 1
3.3%
10.32 1
3.3%
74.03 1
3.3%
134.84 1
3.3%
168.55 1
3.3%
170.65 1
3.3%
236.51 1
3.3%
257.24 1
3.3%
ValueCountFrequency (%)
3710.34 1
3.3%
803.53 1
3.3%
732.71 1
3.3%
638.62 1
3.3%
638.49 1
3.3%
527.77 1
3.3%
524.57 1
3.3%
451.15 1
3.3%
436.08 1
3.3%
407.2 1
3.3%

AD_FD_CHLORINE
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.551
Minimum0
Maximum125.69
Zeros4
Zeros (%)13.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:05.585663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14.3475
median9.965
Q342.675
95-th percentile66.2645
Maximum125.69
Range125.69
Interquartile range (IQR)38.3275

Descriptive statistics

Standard deviation30.204177
Coefficient of variation (CV)1.1821133
Kurtosis2.5625988
Mean25.551
Median Absolute Deviation (MAD)9.965
Skewness1.5084921
Sum766.53
Variance912.2923
MonotonicityNot monotonic
2023-12-10T15:18:05.801624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0 4
 
13.3%
6.05 1
 
3.3%
11.14 1
 
3.3%
62.64 1
 
3.3%
6.83 1
 
3.3%
28.08 1
 
3.3%
60.74 1
 
3.3%
9.93 1
 
3.3%
21.31 1
 
3.3%
4.67 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.0 4
13.3%
0.3 1
 
3.3%
0.44 1
 
3.3%
3.8 1
 
3.3%
4.24 1
 
3.3%
4.67 1
 
3.3%
4.74 1
 
3.3%
4.86 1
 
3.3%
5.29 1
 
3.3%
6.05 1
 
3.3%
ValueCountFrequency (%)
125.69 1
3.3%
69.23 1
3.3%
62.64 1
3.3%
62.4 1
3.3%
61.54 1
3.3%
60.74 1
3.3%
49.94 1
3.3%
43.55 1
3.3%
40.05 1
3.3%
34.84 1
3.3%

AD_FD_POTASSIUM
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean509.77133
Minimum116.28
Maximum2070.21
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:06.050315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum116.28
5-th percentile166.28
Q1315.1575
median425.39
Q3584.765
95-th percentile1079.3915
Maximum2070.21
Range1953.93
Interquartile range (IQR)269.6075

Descriptive statistics

Standard deviation382.94307
Coefficient of variation (CV)0.75120557
Kurtosis9.5283381
Mean509.77133
Median Absolute Deviation (MAD)149.275
Skewness2.7475811
Sum15293.14
Variance146645.39
MonotonicityNot monotonic
2023-12-10T15:18:06.269227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
196.51 1
 
3.3%
391.55 1
 
3.3%
746.02 1
 
3.3%
584.69 1
 
3.3%
718.98 1
 
3.3%
564.64 1
 
3.3%
584.79 1
 
3.3%
219.25 1
 
3.3%
691.66 1
 
3.3%
723.17 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
116.28 1
3.3%
147.2 1
3.3%
189.6 1
3.3%
196.51 1
3.3%
219.25 1
3.3%
257.01 1
3.3%
295.22 1
3.3%
314.94 1
3.3%
315.81 1
3.3%
326.4 1
3.3%
ValueCountFrequency (%)
2070.21 1
3.3%
1352.15 1
3.3%
746.02 1
3.3%
723.17 1
3.3%
718.98 1
3.3%
691.66 1
3.3%
592.28 1
3.3%
584.79 1
3.3%
584.69 1
3.3%
564.64 1
3.3%

AD_FD_FOOD_NM
Text

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T15:18:06.631840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10.5
Mean length8.6333333
Min length4

Characters and Unicode

Total characters259
Distinct characters95
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)73.3%

Sample

1st row유부초밥_8
2nd row조밥_1
3rd row견과영양밥(초등)_C5
4th row떡볶이와 주먹밥_C4
5th row오색주먹밥(초등)_C5
ValueCountFrequency (%)
콘스프_1 2
 
6.5%
양송이스프_1 2
 
6.5%
토마토크림스프_1 2
 
6.5%
감자베이컨볶음_1 2
 
6.5%
유부초밥_8 1
 
3.2%
닭다리살그린빈스볶음_1 1
 
3.2%
떡갈비채소볶음_1 1
 
3.2%
두부채소구이_1 1
 
3.2%
닭고기캐슈넛볶음_1 1
 
3.2%
돈육양파고추장볶음_1 1
 
3.2%
Other values (17) 17
54.8%
2023-12-10T15:18:07.268183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 30
 
11.6%
1 24
 
9.3%
스 13
 
5.0%
프 8
 
3.1%
초 8
 
3.1%
밥 8
 
3.1%
볶 7
 
2.7%
이 6
 
2.3%
음 6
 
2.3%
고 5
 
1.9%
Other values (85) 144
55.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 188
72.6%
Connector Punctuation 30
 
11.6%
Decimal Number 30
 
11.6%
Uppercase Letter 4
 
1.5%
Open Punctuation 3
 
1.2%
Close Punctuation 3
 
1.2%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 13
 
6.9%
프 8
 
4.3%
초 8
 
4.3%
밥 8
 
4.3%
볶 7
 
3.7%
이 6
 
3.2%
음 6
 
3.2%
고 5
 
2.7%
파 4
 
2.1%
토 4
 
2.1%
Other values (75) 119
63.3%
Decimal Number
ValueCountFrequency (%)
1 24
80.0%
5 3
 
10.0%
4 1
 
3.3%
2 1
 
3.3%
8 1
 
3.3%
Connector Punctuation
ValueCountFrequency (%)
_ 30
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 188
72.6%
Common 67
 
25.9%
Latin 4
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 13
 
6.9%
프 8
 
4.3%
초 8
 
4.3%
밥 8
 
4.3%
볶 7
 
3.7%
이 6
 
3.2%
음 6
 
3.2%
고 5
 
2.7%
파 4
 
2.1%
토 4
 
2.1%
Other values (75) 119
63.3%
Common
ValueCountFrequency (%)
_ 30
44.8%
1 24
35.8%
5 3
 
4.5%
( 3
 
4.5%
) 3
 
4.5%
1
 
1.5%
4 1
 
1.5%
2 1
 
1.5%
8 1
 
1.5%
Latin
ValueCountFrequency (%)
C 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 188
72.6%
ASCII 71
 
27.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 30
42.3%
1 24
33.8%
C 4
 
5.6%
5 3
 
4.2%
( 3
 
4.2%
) 3
 
4.2%
1
 
1.4%
4 1
 
1.4%
2 1
 
1.4%
8 1
 
1.4%
Hangul
ValueCountFrequency (%)
스 13
 
6.9%
프 8
 
4.3%
초 8
 
4.3%
밥 8
 
4.3%
볶 7
 
3.7%
이 6
 
3.2%
음 6
 
3.2%
고 5
 
2.7%
파 4
 
2.1%
토 4
 
2.1%
Other values (75) 119
63.3%

AD_FD_MAGNESIUM
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.591667
Minimum0
Maximum277.66
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:07.480427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0315
Q19.9325
median22.58
Q333.925
95-th percentile110.3095
Maximum277.66
Range277.66
Interquartile range (IQR)23.9925

Descriptive statistics

Standard deviation53.256681
Coefficient of variation (CV)1.455432
Kurtosis14.861115
Mean36.591667
Median Absolute Deviation (MAD)12.5
Skewness3.5626608
Sum1097.75
Variance2836.2741
MonotonicityNot monotonic
2023-12-10T15:18:07.715775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 2
 
6.7%
19.0 1
 
3.3%
34.81 1
 
3.3%
27.78 1
 
3.3%
100.8 1
 
3.3%
35.93 1
 
3.3%
27.87 1
 
3.3%
7.75 1
 
3.3%
118.09 1
 
3.3%
31.27 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0 2
6.7%
0.07 1
3.3%
4.61 1
3.3%
7.75 1
3.3%
7.78 1
3.3%
9.07 1
3.3%
9.14 1
3.3%
12.31 1
3.3%
14.65 1
3.3%
17.55 1
3.3%
ValueCountFrequency (%)
277.66 1
3.3%
118.09 1
3.3%
100.8 1
3.3%
76.71 1
3.3%
58.33 1
3.3%
35.93 1
3.3%
35.35 1
3.3%
34.81 1
3.3%
31.27 1
3.3%
29.57 1
3.3%

AD_FD_FERRIC
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.234
Minimum0.37
Maximum9.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:08.008669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.37
5-th percentile0.6645
Q11.1425
median1.62
Q32.8725
95-th percentile5.6125
Maximum9.93
Range9.56
Interquartile range (IQR)1.73

Descriptive statistics

Standard deviation2.0002976
Coefficient of variation (CV)0.89538835
Kurtosis8.0988838
Mean2.234
Median Absolute Deviation (MAD)0.765
Skewness2.6523461
Sum67.02
Variance4.0011903
MonotonicityNot monotonic
2023-12-10T15:18:08.244505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
2.49 1
 
3.3%
1.35 1
 
3.3%
3.18 1
 
3.3%
0.87 1
 
3.3%
3.33 1
 
3.3%
2.94 1
 
3.3%
0.86 1
 
3.3%
1.74 1
 
3.3%
3.22 1
 
3.3%
3.32 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.37 1
3.3%
0.57 1
3.3%
0.78 1
3.3%
0.83 1
3.3%
0.85 1
3.3%
0.86 1
3.3%
0.87 1
3.3%
1.13 1
3.3%
1.18 1
3.3%
1.2 1
3.3%
ValueCountFrequency (%)
9.93 1
3.3%
7.48 1
3.3%
3.33 1
3.3%
3.32 1
3.3%
3.22 1
3.3%
3.19 1
3.3%
3.18 1
3.3%
2.94 1
3.3%
2.67 1
3.3%
2.49 1
3.3%

AD_FD_VGT_FERRIC
Real number (ℝ)

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.257
Minimum0.17
Maximum5.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:08.497329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.17
5-th percentile0.2645
Q10.595
median1.09
Q31.515
95-th percentile2.345
Maximum5.92
Range5.75
Interquartile range (IQR)0.92

Descriptive statistics

Standard deviation1.0839237
Coefficient of variation (CV)0.86231006
Kurtosis11.497442
Mean1.257
Median Absolute Deviation (MAD)0.485
Skewness2.8668497
Sum37.71
Variance1.1748907
MonotonicityNot monotonic
2023-12-10T15:18:08.718022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.59 2
 
6.7%
1.41 2
 
6.7%
2.39 1
 
3.3%
0.68 1
 
3.3%
1.03 1
 
3.3%
0.77 1
 
3.3%
2.11 1
 
3.3%
1.06 1
 
3.3%
0.76 1
 
3.3%
1.5 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
0.17 1
3.3%
0.26 1
3.3%
0.27 1
3.3%
0.29 1
3.3%
0.42 1
3.3%
0.49 1
3.3%
0.59 2
6.7%
0.61 1
3.3%
0.68 1
3.3%
0.72 1
3.3%
ValueCountFrequency (%)
5.92 1
3.3%
2.39 1
3.3%
2.29 1
3.3%
2.15 1
3.3%
2.11 1
3.3%
1.73 1
3.3%
1.58 1
3.3%
1.52 1
3.3%
1.5 1
3.3%
1.47 1
3.3%

AD_FD_ANI_FERRIC
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.46166667
Minimum0
Maximum2.49
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:08.918487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.07
Q30.7075
95-th percentile1.919
Maximum2.49
Range2.49
Interquartile range (IQR)0.7075

Descriptive statistics

Standard deviation0.70493865
Coefficient of variation (CV)1.5269429
Kurtosis1.7069658
Mean0.46166667
Median Absolute Deviation (MAD)0.07
Skewness1.6347761
Sum13.85
Variance0.49693851
MonotonicityNot monotonic
2023-12-10T15:18:09.145691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.0 11
36.7%
0.03 3
 
10.0%
0.07 2
 
6.7%
0.13 2
 
6.7%
0.52 1
 
3.3%
0.77 1
 
3.3%
0.91 1
 
3.3%
0.32 1
 
3.3%
2.49 1
 
3.3%
0.29 1
 
3.3%
Other values (6) 6
20.0%
ValueCountFrequency (%)
0.0 11
36.7%
0.03 3
 
10.0%
0.07 2
 
6.7%
0.13 2
 
6.7%
0.29 1
 
3.3%
0.32 1
 
3.3%
0.41 1
 
3.3%
0.52 1
 
3.3%
0.77 1
 
3.3%
0.91 1
 
3.3%
ValueCountFrequency (%)
2.49 1
3.3%
2.0 1
3.3%
1.82 1
3.3%
1.7 1
3.3%
1.21 1
3.3%
0.92 1
3.3%
0.91 1
3.3%
0.77 1
3.3%
0.52 1
3.3%
0.41 1
3.3%

AD_FD_ZINC
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0466667
Minimum0.27
Maximum10.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:09.365799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.27
5-th percentile0.3675
Q10.905
median1.13
Q32.4725
95-th percentile5.5225
Maximum10.89
Range10.62
Interquartile range (IQR)1.5675

Descriptive statistics

Standard deviation2.1746063
Coefficient of variation (CV)1.0625112
Kurtosis8.9832007
Mean2.0466667
Median Absolute Deviation (MAD)0.465
Skewness2.7151194
Sum61.4
Variance4.7289126
MonotonicityNot monotonic
2023-12-10T15:18:09.597959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1.9 1
 
3.3%
1.0 1
 
3.3%
5.95 1
 
3.3%
0.92 1
 
3.3%
3.31 1
 
3.3%
3.48 1
 
3.3%
0.9 1
 
3.3%
1.2 1
 
3.3%
4.03 1
 
3.3%
2.55 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.27 1
3.3%
0.3 1
3.3%
0.45 1
3.3%
0.67 1
3.3%
0.71 1
3.3%
0.78 1
3.3%
0.79 1
3.3%
0.9 1
3.3%
0.92 1
3.3%
1.0 1
3.3%
ValueCountFrequency (%)
10.89 1
3.3%
5.95 1
3.3%
5.0 1
3.3%
4.03 1
3.3%
3.48 1
3.3%
3.31 1
3.3%
2.88 1
3.3%
2.55 1
3.3%
2.24 1
3.3%
1.9 1
3.3%

AD_FD_COPPER
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.283
Minimum0
Maximum1.25
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:09.817647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.018
Q10.1125
median0.17
Q30.3875
95-th percentile0.7995
Maximum1.25
Range1.25
Interquartile range (IQR)0.275

Descriptive statistics

Standard deviation0.28622574
Coefficient of variation (CV)1.0113984
Kurtosis3.457805
Mean0.283
Median Absolute Deviation (MAD)0.09
Skewness1.8046888
Sum8.49
Variance0.081925172
MonotonicityNot monotonic
2023-12-10T15:18:10.090946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.16 2
 
6.7%
0.12 2
 
6.7%
0.0 2
 
6.7%
0.08 2
 
6.7%
0.13 1
 
3.3%
0.24 1
 
3.3%
0.65 1
 
3.3%
0.18 1
 
3.3%
0.11 1
 
3.3%
0.21 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0.0 2
6.7%
0.04 1
3.3%
0.05 1
3.3%
0.08 2
6.7%
0.09 1
3.3%
0.11 1
3.3%
0.12 2
6.7%
0.13 1
3.3%
0.14 1
3.3%
0.15 1
3.3%
ValueCountFrequency (%)
1.25 1
3.3%
0.84 1
3.3%
0.75 1
3.3%
0.65 1
3.3%
0.56 1
3.3%
0.53 1
3.3%
0.44 1
3.3%
0.41 1
3.3%
0.32 1
3.3%
0.26 1
3.3%

AD_FD_FLUORINE
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.898
Minimum0
Maximum22.24
Zeros15
Zeros (%)50.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:10.373552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.045
Q31.4
95-th percentile21.611
Maximum22.24
Range22.24
Interquartile range (IQR)1.4

Descriptive statistics

Standard deviation6.6563661
Coefficient of variation (CV)2.2968827
Kurtosis5.0434421
Mean2.898
Median Absolute Deviation (MAD)0.045
Skewness2.5153423
Sum86.94
Variance44.30721
MonotonicityNot monotonic
2023-12-10T15:18:10.613430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 15
50.0%
0.3 2
 
6.7%
1.72 1
 
3.3%
1.1 1
 
3.3%
0.21 1
 
3.3%
0.09 1
 
3.3%
21.6 1
 
3.3%
21.62 1
 
3.3%
2.9 1
 
3.3%
1.5 1
 
3.3%
Other values (5) 5
 
16.7%
ValueCountFrequency (%)
0.0 15
50.0%
0.09 1
 
3.3%
0.21 1
 
3.3%
0.25 1
 
3.3%
0.3 2
 
6.7%
0.6 1
 
3.3%
1.1 1
 
3.3%
1.5 1
 
3.3%
1.72 1
 
3.3%
2.9 1
 
3.3%
ValueCountFrequency (%)
22.24 1
3.3%
21.62 1
3.3%
21.6 1
3.3%
8.95 1
3.3%
3.56 1
3.3%
2.9 1
3.3%
1.72 1
3.3%
1.5 1
3.3%
1.1 1
3.3%
0.6 1
3.3%

AD_FD_MANGANESE
Real number (ℝ)

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.72166667
Minimum0.06
Maximum3.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:10.808830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.06
5-th percentile0.0745
Q10.275
median0.385
Q30.6875
95-th percentile3.1085
Maximum3.94
Range3.88
Interquartile range (IQR)0.4125

Descriptive statistics

Standard deviation0.94094261
Coefficient of variation (CV)1.3038466
Kurtosis6.2535068
Mean0.72166667
Median Absolute Deviation (MAD)0.23
Skewness2.6151966
Sum21.65
Variance0.88537299
MonotonicityNot monotonic
2023-12-10T15:18:11.030354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.32 2
 
6.7%
0.38 2
 
6.7%
0.33 2
 
6.7%
0.27 2
 
6.7%
0.09 1
 
3.3%
0.39 1
 
3.3%
0.47 1
 
3.3%
0.69 1
 
3.3%
0.62 1
 
3.3%
0.08 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0.06 1
3.3%
0.07 1
3.3%
0.08 1
3.3%
0.09 1
3.3%
0.16 1
3.3%
0.23 1
3.3%
0.27 2
6.7%
0.29 1
3.3%
0.32 2
6.7%
0.33 2
6.7%
ValueCountFrequency (%)
3.94 1
3.3%
3.41 1
3.3%
2.74 1
3.3%
0.98 1
3.3%
0.85 1
3.3%
0.78 1
3.3%
0.74 1
3.3%
0.69 1
3.3%
0.68 1
3.3%
0.66 1
3.3%

AD_FD_IODINE
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5783333
Minimum0
Maximum46.14
Zeros5
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:11.298221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.0325
median4.31
Q37.68
95-th percentile32.748
Maximum46.14
Range46.14
Interquartile range (IQR)7.6475

Descriptive statistics

Standard deviation11.53252
Coefficient of variation (CV)1.5217753
Kurtosis4.3927009
Mean7.5783333
Median Absolute Deviation (MAD)4.21
Skewness2.1742295
Sum227.35
Variance132.99902
MonotonicityNot monotonic
2023-12-10T15:18:11.517415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 5
 
16.7%
7.09 3
 
10.0%
0.02 2
 
6.7%
0.15 1
 
3.3%
7.9 1
 
3.3%
0.05 1
 
3.3%
0.03 1
 
3.3%
2.37 1
 
3.3%
7.71 1
 
3.3%
12.36 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
0.0 5
16.7%
0.02 2
 
6.7%
0.03 1
 
3.3%
0.04 1
 
3.3%
0.05 1
 
3.3%
0.15 1
 
3.3%
0.54 1
 
3.3%
1.13 1
 
3.3%
2.37 1
 
3.3%
3.32 1
 
3.3%
ValueCountFrequency (%)
46.14 1
3.3%
36.33 1
3.3%
28.37 1
3.3%
25.38 1
3.3%
12.36 1
3.3%
7.9 1
3.3%
7.82 1
3.3%
7.71 1
3.3%
7.59 1
3.3%
7.18 1
3.3%

AD_FD_SELENIUM
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.100333
Minimum0.36
Maximum117.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:11.740587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.36
5-th percentile2.418
Q13.215
median9.78
Q318.8225
95-th percentile35.912
Maximum117.66
Range117.3
Interquartile range (IQR)15.6075

Descriptive statistics

Standard deviation21.792733
Coefficient of variation (CV)1.4431955
Kurtosis17.619681
Mean15.100333
Median Absolute Deviation (MAD)7.03
Skewness3.8447793
Sum453.01
Variance474.92322
MonotonicityNot monotonic
2023-12-10T15:18:11.994252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
18.23 1
 
3.3%
2.64 1
 
3.3%
24.74 1
 
3.3%
3.88 1
 
3.3%
17.96 1
 
3.3%
26.14 1
 
3.3%
3.95 1
 
3.3%
10.44 1
 
3.3%
21.63 1
 
3.3%
30.28 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.36 1
3.3%
2.4 1
3.3%
2.44 1
3.3%
2.54 1
3.3%
2.64 1
3.3%
2.86 1
3.3%
3.04 1
3.3%
3.19 1
3.3%
3.29 1
3.3%
3.73 1
3.3%
ValueCountFrequency (%)
117.66 1
3.3%
40.52 1
3.3%
30.28 1
3.3%
26.14 1
3.3%
24.74 1
3.3%
21.63 1
3.3%
20.19 1
3.3%
19.02 1
3.3%
18.23 1
3.3%
17.96 1
3.3%

AD_FD_FOOD_DISH_SIZE
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
30 

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 30
100.0%

Length

2023-12-10T15:18:12.233377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:18:12.432663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 30
100.0%

AD_FD_CHOLESTEROL
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.469667
Minimum0
Maximum312.87
Zeros6
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:12.614089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.7825
median10.87
Q342.3225
95-th percentile137.1565
Maximum312.87
Range312.87
Interquartile range (IQR)40.54

Descriptive statistics

Standard deviation64.85547
Coefficient of variation (CV)1.7783401
Kurtosis11.536151
Mean36.469667
Median Absolute Deviation (MAD)10.87
Skewness3.1524905
Sum1094.09
Variance4206.232
MonotonicityNot monotonic
2023-12-10T15:18:12.839316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 6
20.0%
3.3 3
 
10.0%
11.5 2
 
6.7%
60.0 2
 
6.7%
42.33 1
 
3.3%
71.0 1
 
3.3%
96.0 1
 
3.3%
83.0 1
 
3.3%
6.54 1
 
3.3%
10.24 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
0.0 6
20.0%
0.22 1
 
3.3%
1.35 1
 
3.3%
3.08 1
 
3.3%
3.3 3
10.0%
6.54 1
 
3.3%
8.36 1
 
3.3%
10.24 1
 
3.3%
11.5 2
 
6.7%
13.28 1
 
3.3%
ValueCountFrequency (%)
312.87 1
3.3%
170.83 1
3.3%
96.0 1
3.3%
83.0 1
3.3%
71.0 1
3.3%
60.0 2
6.7%
42.33 1
3.3%
42.3 1
3.3%
32.03 1
3.3%
26.65 1
3.3%

AD_FD_TOTAL_FAT_ACID
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.5413333
Minimum0
Maximum60.62
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:13.089316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0595
Q11.2175
median3.48
Q311.0275
95-th percentile19.5805
Maximum60.62
Range60.62
Interquartile range (IQR)9.81

Descriptive statistics

Standard deviation11.679292
Coefficient of variation (CV)1.5487039
Kurtosis14.936147
Mean7.5413333
Median Absolute Deviation (MAD)2.42
Skewness3.488352
Sum226.24
Variance136.40587
MonotonicityNot monotonic
2023-12-10T15:18:13.326281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
3.48 2
 
6.7%
5.68 1
 
3.3%
4.55 1
 
3.3%
15.06 1
 
3.3%
15.21 1
 
3.3%
13.71 1
 
3.3%
5.38 1
 
3.3%
4.46 1
 
3.3%
13.6 1
 
3.3%
18.86 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
0.0 1
3.3%
0.01 1
3.3%
0.12 1
3.3%
0.44 1
3.3%
0.66 1
3.3%
0.97 1
3.3%
1.15 1
3.3%
1.21 1
3.3%
1.24 1
3.3%
1.36 1
3.3%
ValueCountFrequency (%)
60.62 1
3.3%
20.17 1
3.3%
18.86 1
3.3%
15.21 1
3.3%
15.06 1
3.3%
13.71 1
3.3%
13.6 1
3.3%
12.1 1
3.3%
7.81 1
3.3%
5.68 1
3.3%

AD_FD_SATURATED_FAT_ACID
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2613333
Minimum0
Maximum9.02
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:13.538183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0135
Q10.665
median0.92
Q33.255
95-th percentile7.741
Maximum9.02
Range9.02
Interquartile range (IQR)2.59

Descriptive statistics

Standard deviation2.6204997
Coefficient of variation (CV)1.1588295
Kurtosis0.89443752
Mean2.2613333
Median Absolute Deviation (MAD)0.675
Skewness1.414725
Sum67.84
Variance6.8670189
MonotonicityNot monotonic
2023-12-10T15:18:13.746840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.92 2
 
6.7%
0.7 2
 
6.7%
6.25 2
 
6.7%
0.68 2
 
6.7%
0.0 2
 
6.7%
8.38 1
 
3.3%
1.49 1
 
3.3%
4.69 1
 
3.3%
1.46 1
 
3.3%
3.39 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
0.0 2
6.7%
0.03 1
3.3%
0.2 1
3.3%
0.29 1
3.3%
0.31 1
3.3%
0.41 1
3.3%
0.66 1
3.3%
0.68 2
6.7%
0.7 2
6.7%
0.78 1
3.3%
ValueCountFrequency (%)
9.02 1
3.3%
8.38 1
3.3%
6.96 1
3.3%
6.25 2
6.7%
4.69 1
3.3%
3.39 1
3.3%
3.31 1
3.3%
3.09 1
3.3%
2.32 1
3.3%
1.8 1
3.3%

AD_FD_MONOSATURATED_FAT_ACID
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.7846667
Minimum0
Maximum38.71
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:13.956189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.009
Q10.28
median1.37
Q34.67
95-th percentile9.2975
Maximum38.71
Range38.71
Interquartile range (IQR)4.39

Descriptive statistics

Standard deviation7.2748441
Coefficient of variation (CV)1.9221889
Kurtosis19.271629
Mean3.7846667
Median Absolute Deviation (MAD)1.09
Skewness4.0825996
Sum113.54
Variance52.923357
MonotonicityNot monotonic
2023-12-10T15:18:14.182721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.28 3
 
10.0%
0.0 2
 
6.7%
2.23 1
 
3.3%
38.71 1
 
3.3%
7.98 1
 
3.3%
2.13 1
 
3.3%
7.84 1
 
3.3%
8.13 1
 
3.3%
2.14 1
 
3.3%
1.0 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0.0 2
6.7%
0.02 1
 
3.3%
0.05 1
 
3.3%
0.1 1
 
3.3%
0.27 1
 
3.3%
0.28 3
10.0%
0.38 1
 
3.3%
0.53 1
 
3.3%
0.91 1
 
3.3%
1.0 1
 
3.3%
ValueCountFrequency (%)
38.71 1
3.3%
9.68 1
3.3%
8.83 1
3.3%
8.13 1
3.3%
7.98 1
3.3%
7.84 1
3.3%
6.21 1
3.3%
5.44 1
3.3%
2.36 1
3.3%
2.23 1
3.3%

AD_FD_POLYSATURATED_FAT_ACID
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.896
Minimum0
Maximum13.49
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:14.424647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.019
Q10.1025
median0.62
Q32.745
95-th percentile5.0315
Maximum13.49
Range13.49
Interquartile range (IQR)2.6425

Descriptive statistics

Standard deviation2.7544893
Coefficient of variation (CV)1.4527897
Kurtosis10.282154
Mean1.896
Median Absolute Deviation (MAD)0.615
Skewness2.7739681
Sum56.88
Variance7.587211
MonotonicityNot monotonic
2023-12-10T15:18:15.214698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.18 3
 
10.0%
0.06 2
 
6.7%
0.08 2
 
6.7%
0.03 2
 
6.7%
13.49 1
 
3.3%
0.83 1
 
3.3%
1.64 1
 
3.3%
2.8 1
 
3.3%
4.14 1
 
3.3%
1.65 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
0.0 1
 
3.3%
0.01 1
 
3.3%
0.03 2
6.7%
0.06 2
6.7%
0.08 2
6.7%
0.17 1
 
3.3%
0.18 3
10.0%
0.23 1
 
3.3%
0.25 1
 
3.3%
0.41 1
 
3.3%
ValueCountFrequency (%)
13.49 1
3.3%
5.09 1
3.3%
4.96 1
3.3%
4.26 1
3.3%
4.14 1
3.3%
3.62 1
3.3%
3.34 1
3.3%
2.8 1
3.3%
2.58 1
3.3%
2.54 1
3.3%

AD_FD_TRANS_FAT_ACID
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.026666667
Minimum0
Maximum0.49
Zeros21
Zeros (%)70.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:15.462358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.0175
95-th percentile0.106
Maximum0.49
Range0.49
Interquartile range (IQR)0.0175

Descriptive statistics

Standard deviation0.092487961
Coefficient of variation (CV)3.4682985
Kurtosis23.569688
Mean0.026666667
Median Absolute Deviation (MAD)0
Skewness4.7369715
Sum0.8
Variance0.008554023
MonotonicityNot monotonic
2023-12-10T15:18:15.700958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 21
70.0%
0.02 5
 
16.7%
0.49 1
 
3.3%
0.16 1
 
3.3%
0.04 1
 
3.3%
0.01 1
 
3.3%
ValueCountFrequency (%)
0.0 21
70.0%
0.01 1
 
3.3%
0.02 5
 
16.7%
0.04 1
 
3.3%
0.16 1
 
3.3%
0.49 1
 
3.3%
ValueCountFrequency (%)
0.49 1
 
3.3%
0.16 1
 
3.3%
0.04 1
 
3.3%
0.02 5
 
16.7%
0.01 1
 
3.3%
0.0 21
70.0%

AD_FD_ISOLEUCINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean414.12
Minimum12.79
Maximum3367.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:15.922301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.79
5-th percentile42.5325
Q193.5725
median190.705
Q3331.2875
95-th percentile1187.4375
Maximum3367.32
Range3354.53
Interquartile range (IQR)237.715

Descriptive statistics

Standard deviation659.39554
Coefficient of variation (CV)1.5922813
Kurtosis14.013428
Mean414.12
Median Absolute Deviation (MAD)101.995
Skewness3.4405617
Sum12423.6
Variance434802.48
MonotonicityNot monotonic
2023-12-10T15:18:16.134765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
252.01 1
 
3.3%
90.88 1
 
3.3%
1101.61 1
 
3.3%
191.28 1
 
3.3%
259.48 1
 
3.3%
58.44 1
 
3.3%
190.13 1
 
3.3%
338.25 1
 
3.3%
1257.66 1
 
3.3%
125.29 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
12.79 1
3.3%
36.48 1
3.3%
49.93 1
3.3%
51.98 1
3.3%
58.44 1
3.3%
87.13 1
3.3%
90.29 1
3.3%
90.88 1
3.3%
101.65 1
3.3%
108.66 1
3.3%
ValueCountFrequency (%)
3367.32 1
3.3%
1257.66 1
3.3%
1101.61 1
3.3%
1099.0 1
3.3%
1005.53 1
3.3%
757.87 1
3.3%
342.0 1
3.3%
338.25 1
3.3%
310.4 1
3.3%
259.48 1
3.3%

AD_FD_LEUCINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean704.19167
Minimum17.78
Maximum5527.39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:16.355939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.78
5-th percentile81.0685
Q1158.6025
median321.51
Q3616.8125
95-th percentile2064.0745
Maximum5527.39
Range5509.61
Interquartile range (IQR)458.21

Descriptive statistics

Standard deviation1090.7334
Coefficient of variation (CV)1.5489155
Kurtosis13.206987
Mean704.19167
Median Absolute Deviation (MAD)182.72
Skewness3.3292028
Sum21125.75
Variance1189699.4
MonotonicityNot monotonic
2023-12-10T15:18:16.558166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
463.83 1
 
3.3%
157.99 1
 
3.3%
1859.24 1
 
3.3%
322.36 1
 
3.3%
424.26 1
 
3.3%
98.11 1
 
3.3%
320.66 1
 
3.3%
598.55 1
 
3.3%
2143.09 1
 
3.3%
128.34 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
17.78 1
3.3%
70.21 1
3.3%
94.34 1
3.3%
95.84 1
3.3%
98.11 1
3.3%
128.34 1
3.3%
149.24 1
3.3%
157.99 1
3.3%
160.44 1
3.3%
162.37 1
3.3%
ValueCountFrequency (%)
5527.39 1
3.3%
2143.09 1
3.3%
1967.5 1
3.3%
1859.24 1
3.3%
1570.63 1
3.3%
1337.63 1
3.3%
689.6 1
3.3%
622.9 1
3.3%
598.55 1
3.3%
463.83 1
3.3%

AD_FD_LYSINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean508.37333
Minimum23.16
Maximum3361.15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:16.769879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23.16
5-th percentile48.738
Q195.0025
median154.3
Q3419.775
95-th percentile2038.532
Maximum3361.15
Range3337.99
Interquartile range (IQR)324.7725

Descriptive statistics

Standard deviation785.6352
Coefficient of variation (CV)1.5453903
Kurtosis5.5588179
Mean508.37333
Median Absolute Deviation (MAD)102.86
Skewness2.3680069
Sum15251.2
Variance617222.67
MonotonicityNot monotonic
2023-12-10T15:18:16.985383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
209.09 1
 
3.3%
95.92 1
 
3.3%
2031.91 1
 
3.3%
431.95 1
 
3.3%
383.25 1
 
3.3%
59.04 1
 
3.3%
432.32 1
 
3.3%
334.5 1
 
3.3%
2043.95 1
 
3.3%
94.77 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
23.16 1
3.3%
47.64 1
3.3%
50.08 1
3.3%
52.8 1
3.3%
59.04 1
3.3%
59.81 1
3.3%
91.32 1
3.3%
94.77 1
3.3%
95.7 1
3.3%
95.92 1
3.3%
ValueCountFrequency (%)
3361.15 1
3.3%
2043.95 1
3.3%
2031.91 1
3.3%
1704.6 1
3.3%
1030.24 1
3.3%
1006.99 1
3.3%
432.32 1
3.3%
431.95 1
3.3%
383.25 1
3.3%
344.7 1
3.3%

AD_FD_METHIONINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean189.09467
Minimum3.45
Maximum1683.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:17.298320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.45
5-th percentile17.8885
Q136.2675
median60.54
Q3150.575
95-th percentile630.2005
Maximum1683.41
Range1679.96
Interquartile range (IQR)114.3075

Descriptive statistics

Standard deviation330.23604
Coefficient of variation (CV)1.7464059
Kurtosis14.793501
Mean189.09467
Median Absolute Deviation (MAD)35.02
Skewness3.5719678
Sum5672.84
Variance109055.84
MonotonicityNot monotonic
2023-12-10T15:18:17.516739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
128.51 1
 
3.3%
41.7 1
 
3.3%
496.89 1
 
3.3%
118.3 1
 
3.3%
145.4 1
 
3.3%
33.45 1
 
3.3%
116.76 1
 
3.3%
71.65 1
 
3.3%
676.06 1
 
3.3%
29.98 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
3.45 1
3.3%
12.88 1
3.3%
24.01 1
3.3%
27.03 1
3.3%
29.98 1
3.3%
33.45 1
3.3%
34.16 1
3.3%
35.29 1
3.3%
39.2 1
3.3%
41.7 1
3.3%
ValueCountFrequency (%)
1683.41 1
3.3%
676.06 1
3.3%
574.15 1
3.3%
496.89 1
3.3%
322.4 1
3.3%
322.35 1
3.3%
184.8 1
3.3%
152.3 1
3.3%
145.4 1
3.3%
128.51 1
3.3%

AD_FD_AMOUNT
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
0
30 

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 30
100.0%

Length

2023-12-10T15:18:17.726727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:18:17.932368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 30
100.0%

AD_FD_PHENYLALANINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean405.25133
Minimum11
Maximum3152.01
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:18.071777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile38.967
Q193.1675
median172.35
Q3375.625
95-th percentile1198.1715
Maximum3152.01
Range3141.01
Interquartile range (IQR)282.4575

Descriptive statistics

Standard deviation626.99018
Coefficient of variation (CV)1.5471638
Kurtosis12.640581
Mean405.25133
Median Absolute Deviation (MAD)100.57
Skewness3.2524001
Sum12157.54
Variance393116.69
MonotonicityNot monotonic
2023-12-10T15:18:18.368783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
289.81 1
 
3.3%
94.03 1
 
3.3%
975.19 1
 
3.3%
138.85 1
 
3.3%
226.25 1
 
3.3%
60.06 1
 
3.3%
138.32 1
 
3.3%
377.5 1
 
3.3%
1125.5 1
 
3.3%
84.79 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
11.0 1
3.3%
30.75 1
3.3%
49.01 1
3.3%
49.53 1
3.3%
60.06 1
3.3%
83.5 1
3.3%
84.79 1
3.3%
92.88 1
3.3%
94.03 1
3.3%
99.67 1
3.3%
ValueCountFrequency (%)
3152.01 1
3.3%
1257.63 1
3.3%
1125.5 1
3.3%
1073.55 1
3.3%
975.19 1
3.3%
736.91 1
3.3%
397.1 1
3.3%
377.5 1
3.3%
370.0 1
3.3%
289.81 1
3.3%

AD_FD_THREONINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean346.73867
Minimum12.15
Maximum2282.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:18.639076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.15
5-th percentile35.766
Q176.765
median175.5
Q3301.325
95-th percentile1111.5355
Maximum2282.1
Range2269.95
Interquartile range (IQR)224.56

Descriptive statistics

Standard deviation491.97761
Coefficient of variation (CV)1.4188715
Kurtosis7.60088
Mean346.73867
Median Absolute Deviation (MAD)108.625
Skewness2.5768275
Sum10402.16
Variance242041.97
MonotonicityNot monotonic
2023-12-10T15:18:18.886202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
228.33 1
 
3.3%
75.9 1
 
3.3%
1023.08 1
 
3.3%
228.22 1
 
3.3%
212.72 1
 
3.3%
51.41 1
 
3.3%
227.51 1
 
3.3%
318.15 1
 
3.3%
1145.56 1
 
3.3%
79.36 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
12.15 1
3.3%
32.49 1
3.3%
39.77 1
3.3%
40.36 1
3.3%
51.41 1
3.3%
62.45 1
3.3%
65.55 1
3.3%
75.9 1
3.3%
79.36 1
3.3%
84.56 1
3.3%
ValueCountFrequency (%)
2282.1 1
3.3%
1145.56 1
3.3%
1069.95 1
3.3%
1023.08 1
3.3%
872.76 1
3.3%
708.3 1
3.3%
318.15 1
3.3%
307.5 1
3.3%
282.8 1
3.3%
228.33 1
3.3%

AD_FD_TRYPTOPHAN
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean95.305333
Minimum9.83
Maximum441.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:19.098457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.83
5-th percentile11.2425
Q123.7775
median48.1
Q391.725
95-th percentile368.465
Maximum441.02
Range431.19
Interquartile range (IQR)67.9475

Descriptive statistics

Standard deviation119.84589
Coefficient of variation (CV)1.257494
Kurtosis2.41047
Mean95.305333
Median Absolute Deviation (MAD)27.45
Skewness1.8336614
Sum2859.16
Variance14363.037
MonotonicityNot monotonic
2023-12-10T15:18:19.340410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
74.19 1
 
3.3%
20.55 1
 
3.3%
240.18 1
 
3.3%
50.31 1
 
3.3%
61.21 1
 
3.3%
13.87 1
 
3.3%
49.52 1
 
3.3%
84.0 1
 
3.3%
323.2 1
 
3.3%
25.61 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
9.83 1
3.3%
10.68 1
3.3%
11.93 1
3.3%
13.43 1
3.3%
13.87 1
3.3%
20.55 1
3.3%
20.75 1
3.3%
23.35 1
3.3%
25.06 1
3.3%
25.61 1
3.3%
ValueCountFrequency (%)
441.02 1
3.3%
405.5 1
3.3%
323.2 1
3.3%
248.16 1
3.3%
240.18 1
3.3%
222.85 1
3.3%
104.8 1
3.3%
94.3 1
3.3%
84.0 1
3.3%
74.19 1
3.3%

AD_FD_VALINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean470.56
Minimum15.86
Maximum4091.11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:19.697174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15.86
5-th percentile56.334
Q1107.365
median242.295
Q3364.535
95-th percentile1291.881
Maximum4091.11
Range4075.25
Interquartile range (IQR)257.17

Descriptive statistics

Standard deviation776.91526
Coefficient of variation (CV)1.651044
Kurtosis16.856954
Mean470.56
Median Absolute Deviation (MAD)133.665
Skewness3.8109976
Sum14116.8
Variance603597.33
MonotonicityNot monotonic
2023-12-10T15:18:20.006289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
251.24 1
 
3.3%
111.16 1
 
3.3%
1137.9 1
 
3.3%
242.93 1
 
3.3%
275.73 1
 
3.3%
81.05 1
 
3.3%
241.66 1
 
3.3%
388.04 1
 
3.3%
1416.72 1
 
3.3%
103.53 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
15.86 1
3.3%
53.76 1
3.3%
59.48 1
3.3%
61.13 1
3.3%
81.05 1
3.3%
103.53 1
3.3%
103.99 1
3.3%
106.1 1
3.3%
111.16 1
3.3%
135.62 1
3.3%
ValueCountFrequency (%)
4091.11 1
3.3%
1416.72 1
3.3%
1139.3 1
3.3%
1137.9 1
3.3%
1070.69 1
3.3%
726.17 1
3.3%
388.04 1
3.3%
368.88 1
3.3%
351.5 1
3.3%
330.8 1
3.3%

AD_FD_HISTIDINE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean252.48467
Minimum9.98
Maximum1855.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:20.278516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9.98
5-th percentile34.3385
Q173.06
median121.695
Q3165.845
95-th percentile851.3335
Maximum1855.02
Range1845.04
Interquartile range (IQR)92.785

Descriptive statistics

Standard deviation381.90923
Coefficient of variation (CV)1.5126037
Kurtosis10.475625
Mean252.48467
Median Absolute Deviation (MAD)48
Skewness3.0220826
Sum7574.54
Variance145854.66
MonotonicityNot monotonic
2023-12-10T15:18:20.596937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
125.14 1
 
3.3%
75.01 1
 
3.3%
797.23 1
 
3.3%
122.41 1
 
3.3%
168.41 1
 
3.3%
55.6 1
 
3.3%
120.98 1
 
3.3%
150.83 1
 
3.3%
895.6 1
 
3.3%
63.55 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
9.98 1
3.3%
23.03 1
3.3%
48.16 1
3.3%
48.58 1
3.3%
51.17 1
3.3%
55.6 1
3.3%
63.55 1
3.3%
72.41 1
3.3%
75.01 1
3.3%
81.19 1
3.3%
ValueCountFrequency (%)
1855.02 1
3.3%
895.6 1
3.3%
797.23 1
3.3%
709.3 1
3.3%
542.48 1
3.3%
433.58 1
3.3%
177.2 1
3.3%
168.41 1
3.3%
158.15 1
3.3%
153.2 1
3.3%

AD_FD_ARGININE
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean641.024
Minimum13.69
Maximum3961.57
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:20.861304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.69
5-th percentile45.306
Q1117.485
median246.165
Q3580.81
95-th percentile2136.0975
Maximum3961.57
Range3947.88
Interquartile range (IQR)463.325

Descriptive statistics

Standard deviation905.7784
Coefficient of variation (CV)1.4130179
Kurtosis5.3476965
Mean641.024
Median Absolute Deviation (MAD)163.15
Skewness2.2485141
Sum19230.72
Variance820434.5
MonotonicityNot monotonic
2023-12-10T15:18:21.142383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
590.28 1
 
3.3%
113.62 1
 
3.3%
1668.13 1
 
3.3%
226.24 1
 
3.3%
345.84 1
 
3.3%
283.67 1
 
3.3%
225.54 1
 
3.3%
402.86 1
 
3.3%
2136.3 1
 
3.3%
196.26 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
13.69 1
3.3%
29.7 1
3.3%
64.38 1
3.3%
71.9 1
3.3%
76.56 1
3.3%
93.19 1
3.3%
113.62 1
3.3%
115.1 1
3.3%
124.64 1
3.3%
172.3 1
3.3%
ValueCountFrequency (%)
3961.57 1
3.3%
2136.3 1
3.3%
2135.85 1
3.3%
1977.9 1
3.3%
1668.13 1
3.3%
1563.37 1
3.3%
679.7 1
3.3%
590.28 1
3.3%
552.4 1
3.3%
451.59 1
3.3%

AD_FD_LST_DML_DT
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2020-06-18 16:00:45
30 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020-06-18 16:00:45
2nd row2020-06-18 16:00:45
3rd row2020-06-18 16:00:45
4th row2020-06-18 16:00:45
5th row2020-06-18 16:00:45

Common Values

ValueCountFrequency (%)
2020-06-18 16:00:45 30
100.0%

Length

2023-12-10T15:18:21.374920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:18:21.559524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020-06-18 30
50.0%
16:00:45 30
50.0%

AD_FD_SEND_DT
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing30
Missing (%)100.0%
Memory size402.0 B

AD_FD_CAL
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean344.06933
Minimum43.45
Maximum2214.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:21.727498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum43.45
5-th percentile107.859
Q1141.7675
median228.955
Q3367.7475
95-th percentile833.635
Maximum2214.2
Range2170.75
Interquartile range (IQR)225.98

Descriptive statistics

Standard deviation404.27278
Coefficient of variation (CV)1.1749748
Kurtosis16.66052
Mean344.06933
Median Absolute Deviation (MAD)106.395
Skewness3.8333838
Sum10322.08
Variance163436.48
MonotonicityNot monotonic
2023-12-10T15:18:21.932838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
460.65 1
 
3.3%
194.16 1
 
3.3%
284.87 1
 
3.3%
141.59 1
 
3.3%
235.94 1
 
3.3%
369.35 1
 
3.3%
140.93 1
 
3.3%
142.3 1
 
3.3%
362.94 1
 
3.3%
373.39 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
43.45 1
3.3%
103.71 1
3.3%
112.93 1
3.3%
121.63 1
3.3%
123.49 1
3.3%
134.76 1
3.3%
140.93 1
3.3%
141.59 1
3.3%
142.3 1
3.3%
183.2 1
3.3%
ValueCountFrequency (%)
2214.2 1
3.3%
1102.6 1
3.3%
504.9 1
3.3%
460.65 1
3.3%
456.61 1
3.3%
386.42 1
3.3%
373.39 1
3.3%
369.35 1
3.3%
362.94 1
3.3%
357.0 1
3.3%

AD_FD_CARB
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.724667
Minimum4.53
Maximum383.32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:22.134076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4.53
5-th percentile8.125
Q116.1275
median18.375
Q367.635
95-th percentile90.565
Maximum383.32
Range378.79
Interquartile range (IQR)51.5075

Descriptive statistics

Standard deviation69.538354
Coefficient of variation (CV)1.5208061
Kurtosis20.281208
Mean45.724667
Median Absolute Deviation (MAD)7.285
Skewness4.2019655
Sum1371.74
Variance4835.5826
MonotonicityNot monotonic
2023-12-10T15:18:22.395477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
77.13 1
 
3.3%
15.57 1
 
3.3%
18.15 1
 
3.3%
17.81 1
 
3.3%
17.78 1
 
3.3%
17.71 1
 
3.3%
17.64 1
 
3.3%
4.53 1
 
3.3%
16.82 1
 
3.3%
16.72 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
4.53 1
3.3%
5.38 1
3.3%
11.48 1
3.3%
11.77 1
3.3%
11.98 1
3.3%
14.5 1
3.3%
15.57 1
3.3%
15.93 1
3.3%
16.72 1
3.3%
16.82 1
3.3%
ValueCountFrequency (%)
383.32 1
3.3%
91.69 1
3.3%
89.19 1
3.3%
78.0 1
3.3%
77.13 1
3.3%
77.04 1
3.3%
75.0 1
3.3%
70.38 1
3.3%
59.4 1
3.3%
35.25 1
3.3%

AD_FD_FAT
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.322667
Minimum0.2
Maximum72.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T15:18:22.612577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.01
Q15.39
median8.265
Q313.3675
95-th percentile33.123
Maximum72.02
Range71.82
Interquartile range (IQR)7.9775

Descriptive statistics

Standard deviation14.14668
Coefficient of variation (CV)1.148021
Kurtosis10.926905
Mean12.322667
Median Absolute Deviation (MAD)4.95
Skewness2.9923247
Sum369.68
Variance200.12855
MonotonicityNot monotonic
2023-12-10T15:18:22.869772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
12.33 1
 
3.3%
13.62 1
 
3.3%
13.24 1
 
3.3%
5.54 1
 
3.3%
5.34 1
 
3.3%
24.23 1
 
3.3%
5.55 1
 
3.3%
10.66 1
 
3.3%
22.46 1
 
3.3%
24.29 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.2 1
3.3%
0.92 1
3.3%
1.12 1
3.3%
1.32 1
3.3%
2.71 1
3.3%
3.11 1
3.3%
4.4 1
3.3%
5.34 1
3.3%
5.54 1
3.3%
5.55 1
3.3%
ValueCountFrequency (%)
72.02 1
3.3%
40.35 1
3.3%
24.29 1
3.3%
24.23 1
3.3%
22.46 1
3.3%
13.65 1
3.3%
13.62 1
3.3%
13.41 1
3.3%
13.24 1
3.3%
13.19 1
3.3%

Sample

AD_FD_FOOD_CDAD_FD_SERVICE_CDAD_FD_VGT_FATAD_FD_ANI_FATAD_FD_PROTEINAD_FD_VGT_PROTEINAD_FD_ANI_PROTEINAD_FD_TOTAL_DIETARY_FIBERAD_FD_WATERAD_FD_POLLENAD_FD_VITA_AAD_FD_RETINOLAD_FD_FOOD_GRP_CDAD_FD_BETA_CAROTENEAD_FD_VITA_DAD_FD_VITA_EAD_FD_VITA_KAD_FD_VITA_CAD_FD_VITA_B1AD_FD_VITA_B2AD_FD_NIACINAD_FD_VITA_B6AD_FD_FOLATEAD_FD_FOOD_GRP_NMAD_FD_VITA_B12AD_FD_PANTOTHENIC_ACIDAD_FD_BIOTINAD_FD_CALCIUMAD_FD_VGT_CALCIUMAD_FD_ANI_CALCIUMAD_FD_PHOSPHORUSAD_FD_SALTAD_FD_CHLORINEAD_FD_POTASSIUMAD_FD_FOOD_NMAD_FD_MAGNESIUMAD_FD_FERRICAD_FD_VGT_FERRICAD_FD_ANI_FERRICAD_FD_ZINCAD_FD_COPPERAD_FD_FLUORINEAD_FD_MANGANESEAD_FD_IODINEAD_FD_SELENIUMAD_FD_FOOD_DISH_SIZEAD_FD_CHOLESTEROLAD_FD_TOTAL_FAT_ACIDAD_FD_SATURATED_FAT_ACIDAD_FD_MONOSATURATED_FAT_ACIDAD_FD_POLYSATURATED_FAT_ACIDAD_FD_TRANS_FAT_ACIDAD_FD_ISOLEUCINEAD_FD_LEUCINEAD_FD_LYSINEAD_FD_METHIONINEAD_FD_AMOUNTAD_FD_PHENYLALANINEAD_FD_THREONINEAD_FD_TRYPTOPHANAD_FD_VALINEAD_FD_HISTIDINEAD_FD_ARGININEAD_FD_LST_DML_DTAD_FD_SEND_DTAD_FD_CALAD_FD_CARBAD_FD_FAT
0AF001010160050AF00112.320.09.749.430.02.0744.662.611.140.01282.460.03.1715.010.210.110.021.00.1432.01밥류0.01.112.5595.5689.760.0147.14638.626.05196.51유부초밥_819.02.492.390.01.90.320.00.980.1518.2310.05.680.862.232.580.0252.01463.83209.09128.510289.81228.3374.19251.24125.14590.282020-06-18 16:00:45<NA>460.6577.1312.33
1AF001010160060AF0010.920.06.56.50.01.7214.060.520.560.013.20.00.560.180.00.120.021.020.1236.6밥류0.01.22.47.07.00.098.44.60.0147.2조밥_10.01.581.580.01.740.260.00.740.012.6210.00.00.00.00.00.0310.4689.6222.0184.80370.0282.8104.8330.8153.2552.42020-06-18 16:00:45<NA>357.078.00.92
2AF001010170010AF0014.960.07.53.570.02.3729.141.7810.60.01249.690.091.791.25.850.180.192.720.139.91밥류0.00.21.3426.3413.880.0171.35257.244.86337.15견과영양밥(초등)_C523.431.490.590.00.710.151.720.850.544.2510.225.240.72.12.440.0227.64351.82125.6150.290236.8132.329.75311.6117.24451.592020-06-18 16:00:45<NA>327.2859.46.66
3AF001010170020AF00115.469.7572.8629.115.5713.73864.8416.45496.06118.212898.871.57.5815.4835.590.831.614.921.49236.42밥류2.481.6115.02822.25216.8428.371221.213710.34125.692070.21떡볶이와 주먹밥_C476.719.935.922.4910.890.841.13.9436.33117.661312.8720.179.026.214.960.493367.325527.393361.151683.4103152.012282.1441.024091.111855.023961.572020-06-18 16:00:45<NA>2214.2383.3240.35
4AF001010170030AF0014.430.08.373.970.01.5437.821.1488.010.01602.270.01.7919.277.030.20.093.00.0924.58밥류0.00.090.4739.3729.370.0200.6474.034.74295.22오색주먹밥(초등)_C54.611.570.490.01.110.050.210.570.048.4210.03.40.71.331.550.0237.55384.1559.8157.520216.5465.5525.78368.8881.19320.882020-06-18 16:00:45<NA>456.6189.196.22
5AF001040120050AF0010.920.24.493.540.952.8379.33.23363.010.042178.20.01.71583.8614.320.080.10.950.1117.94국| 탕류0.830.160.0108.0569.9538.191.21732.710.3365.15근대된장국_158.332.061.730.320.790.120.02.745.33.0418.360.010.00.00.010.0208.31343.18262.8363.560213.57178.4948.76245.94123.5266.092020-06-18 16:00:45<NA>43.455.381.12
6AF001010120010AF0010.20.07.257.250.04.8314.90.610.630.013.60.00.484.020.00.130.031.00.1367.7밥류0.01.254.1815.315.30.0103.14.70.0326.4강남콩밥_10.02.152.150.01.60.190.00.780.014.2710.00.120.030.020.080.0342.0622.9344.7152.30397.1307.594.3351.5177.2679.72020-06-18 16:00:45<NA>350.677.040.2
7AF001010170040AF0015.240.3227.595.467.042.43156.073.115.5628.41332.14.397.0214.25.580.230.222.320.1366.28밥류2.822.394.0561.9812.2826.95378.55638.495.29559.62잡탕밥_129.453.191.520.912.880.560.00.6846.1440.521170.837.811.82.363.620.021099.01967.51704.6574.1501073.551069.95405.51139.3709.32135.852020-06-18 16:00:45<NA>504.975.08.81
8AF001010170050AF0010.320.1820.15.154.022.11110.042.0585.083.01786.353.761.892.5615.370.150.11.850.243.44밥류2.441.72.5138.5110.6115.4294.49285.680.44400.15해물덮밥_227.92.671.410.522.240.530.00.660.020.19142.30.660.20.050.410.0757.871337.631006.99322.350736.91708.3222.85726.17433.581563.372020-06-18 16:00:45<NA>386.4270.381.32
9AF001020110020AF0010.26.6510.10.977.72.4593.882.0296.380.862574.160.023.3510.0356.010.420.352.680.3734.09면| 만두류0.450.40.8952.0612.0110.53138.93368.523.8330.2고추잡채_129.571.770.610.771.330.140.00.336.3312.76126.6512.13.315.443.340.0290.29149.24109.1535.29092.8884.5625.06106.148.58183.572020-06-18 16:00:45<NA>204.7811.7713.19
AD_FD_FOOD_CDAD_FD_SERVICE_CDAD_FD_VGT_FATAD_FD_ANI_FATAD_FD_PROTEINAD_FD_VGT_PROTEINAD_FD_ANI_PROTEINAD_FD_TOTAL_DIETARY_FIBERAD_FD_WATERAD_FD_POLLENAD_FD_VITA_AAD_FD_RETINOLAD_FD_FOOD_GRP_CDAD_FD_BETA_CAROTENEAD_FD_VITA_DAD_FD_VITA_EAD_FD_VITA_KAD_FD_VITA_CAD_FD_VITA_B1AD_FD_VITA_B2AD_FD_NIACINAD_FD_VITA_B6AD_FD_FOLATEAD_FD_FOOD_GRP_NMAD_FD_VITA_B12AD_FD_PANTOTHENIC_ACIDAD_FD_BIOTINAD_FD_CALCIUMAD_FD_VGT_CALCIUMAD_FD_ANI_CALCIUMAD_FD_PHOSPHORUSAD_FD_SALTAD_FD_CHLORINEAD_FD_POTASSIUMAD_FD_FOOD_NMAD_FD_MAGNESIUMAD_FD_FERRICAD_FD_VGT_FERRICAD_FD_ANI_FERRICAD_FD_ZINCAD_FD_COPPERAD_FD_FLUORINEAD_FD_MANGANESEAD_FD_IODINEAD_FD_SELENIUMAD_FD_FOOD_DISH_SIZEAD_FD_CHOLESTEROLAD_FD_TOTAL_FAT_ACIDAD_FD_SATURATED_FAT_ACIDAD_FD_MONOSATURATED_FAT_ACIDAD_FD_POLYSATURATED_FAT_ACIDAD_FD_TRANS_FAT_ACIDAD_FD_ISOLEUCINEAD_FD_LEUCINEAD_FD_LYSINEAD_FD_METHIONINEAD_FD_AMOUNTAD_FD_PHENYLALANINEAD_FD_THREONINEAD_FD_TRYPTOPHANAD_FD_VALINEAD_FD_HISTIDINEAD_FD_ARGININEAD_FD_LST_DML_DTAD_FD_SEND_DTAD_FD_CALAD_FD_CARBAD_FD_FAT
20AF004020130050AF0040.441.963.590.732.862.66155.040.7833.4422.06369.530.02.0381.3819.990.180.180.750.1825.83죽| 스프류0.410.110.33149.613.97135.62111.4710.320.0116.28블루베리가스파초_17.780.830.420.411.080.00.00.5525.382.5416.541.910.311.410.180.0108.66209.97107.0348.2099.6788.2444.94135.62127.4571.92020-06-18 16:00:45<NA>183.235.254.4
21AF004020130070AF0040.110.00.980.980.02.61123.281.233.310.0321.50.01.323.8413.220.00.00.150.1449.46죽| 스프류0.00.194.66.46.40.016.71170.654.67257.01애플비트가스파초_19.141.181.180.00.270.043.560.080.00.3610.02.480.411.840.230.012.7917.7823.163.45011.012.1513.4315.869.9813.692020-06-18 16:00:45<NA>103.7121.72.71
22AF004080120690AF0040.8916.521.822.7418.55.28183.443.4592.052.083559.130.04.4514.4332.621.020.426.340.5739.83볶음류0.60.852.8691.7571.981.0267.76451.1521.31723.17돈육양파고추장볶음_131.273.321.411.72.550.230.60.6212.3630.28160.018.866.969.685.090.01125.29128.3494.7729.98084.7979.3625.61103.5363.55196.262020-06-18 16:00:45<NA>373.3916.7224.29
23AF004080120700AF00414.634.3327.078.118.974.28120.813.95189.2345.08865.320.02.4751.9133.420.310.412.410.5177.05볶음류0.441.720.7450.8441.129.5367.63803.539.93691.66닭고기캐슈넛볶음_1118.093.222.290.924.030.750.00.270.0221.63183.013.63.398.834.260.01257.662143.092043.95676.0601125.51145.56323.21416.72895.62136.32020-06-18 16:00:45<NA>362.9416.8222.46
24AF00406011003AF00410.60.010.299.30.03.71123.31.240.00.06100.750.01.3240.7512.080.010.030.540.029.25구이류0.00.260.03141.75126.00.0161.67.00.0219.25두부채소구이_17.751.741.50.01.20.210.00.690.010.4410.04.460.921.02.540.0338.25598.55334.571.650377.5318.1584.0388.04150.83402.862020-06-18 16:00:45<NA>142.34.5310.66
25AF004080120720AF0042.130.06.152.990.01.98111.652.48126.060.28756.530.122.227.6649.40.150.131.870.1132.88볶음류0.040.340.9614.0511.750.0113.46406.0360.74584.79감자베이컨볶음_127.870.860.760.00.90.110.30.380.023.95111.55.381.462.141.650.02190.13320.66432.32116.760138.32227.5149.52241.66120.98225.542020-06-18 16:00:45<NA>140.9317.645.55
26AF004080120730AF0040.2118.7819.771.517.823.13154.761.8477.91.28460.210.01.1213.7925.140.620.294.220.4982.06볶음류1.920.741.8944.0234.54.6223.82134.8428.08564.64떡갈비채소볶음_135.932.941.061.823.480.188.950.477.7126.14160.013.716.258.134.140.058.4498.1159.0433.45060.0651.4113.8781.0555.6283.672020-06-18 16:00:45<NA>369.3517.7124.23
27AF004080120740AF0040.694.5629.75.4924.1610.33157.152.7999.8221.68469.40.00.6214.3741.850.390.328.380.52135.53볶음류0.481.924.251.8836.8513.33262.11297.296.83718.98닭다리살그린빈스볶음_1100.83.332.111.213.310.650.00.322.3717.96196.015.214.697.842.80.0259.48424.26383.25145.40226.25212.7261.21275.73168.41345.842020-06-18 16:00:45<NA>235.9417.785.34
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29AF004080120760AF0040.2412.023.452.7220.03.94186.42.99108.968.08605.90.721.614.8910.360.260.56.680.4388.24볶음류1.01.711.2323.410.9710.0244.25436.0811.14746.02쇠고기버섯불고기_134.813.181.032.05.950.2422.240.380.0524.74171.015.066.257.980.830.01101.611859.242031.91496.890975.191023.08240.181137.9797.231668.132020-06-18 16:00:45<NA>284.8718.1513.24