Overview

Dataset statistics

Number of variables25
Number of observations199
Missing cells29
Missing cells (%)0.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.9 KiB
Average record size in memory220.7 B

Variable types

Numeric19
DateTime1
Categorical2
Text3

Alerts

Caffeine is highly imbalanced (92.0%)Imbalance
FoodImage has 29 (14.6%) missing valuesMissing
id has unique valuesUnique
TransFat has 189 (95.0%) zerosZeros
Cholesterol has 104 (52.3%) zerosZeros
Sodium has 15 (7.5%) zerosZeros
Cellulose has 86 (43.2%) zerosZeros
Calcium has 66 (33.2%) zerosZeros
FolicAcid has 80 (40.2%) zerosZeros
Iron has 68 (34.2%) zerosZeros
VitaminA has 109 (54.8%) zerosZeros
VitaminC has 112 (56.3%) zerosZeros
water has 70 (35.2%) zerosZeros
ash has 65 (32.7%) zerosZeros
total_amino_acids has 90 (45.2%) zerosZeros
essential_amino_acid has 94 (47.2%) zerosZeros
Calorie has 3 (1.5%) zerosZeros
CarbonHydrate has 13 (6.5%) zerosZeros
Sugar has 45 (22.6%) zerosZeros
Protein has 10 (5.0%) zerosZeros
SaturatedFattyAcid has 34 (17.1%) zerosZeros

Reproduction

Analysis started2023-12-10 06:35:50.110259
Analysis finished2023-12-10 06:35:50.691545
Duration0.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

id
Real number (ℝ)

UNIQUE 

Distinct199
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean634925.33
Minimum634808
Maximum635031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:50.820902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum634808
5-th percentile634825.9
Q1634874.5
median634926
Q3634977.5
95-th percentile635021.1
Maximum635031
Range223
Interquartile range (IQR)103

Descriptive statistics

Standard deviation62.543147
Coefficient of variation (CV)9.8504729 × 10-5
Kurtosis-1.1144206
Mean634925.33
Median Absolute Deviation (MAD)52
Skewness-0.055268013
Sum1.2635014 × 108
Variance3911.6453
MonotonicityStrictly increasing
2023-12-10T15:35:51.029399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
634808 1
 
0.5%
634966 1
 
0.5%
634955 1
 
0.5%
634956 1
 
0.5%
634957 1
 
0.5%
634958 1
 
0.5%
634959 1
 
0.5%
634960 1
 
0.5%
634961 1
 
0.5%
634963 1
 
0.5%
Other values (189) 189
95.0%
ValueCountFrequency (%)
634808 1
0.5%
634809 1
0.5%
634810 1
0.5%
634811 1
0.5%
634812 1
0.5%
634813 1
0.5%
634814 1
0.5%
634818 1
0.5%
634820 1
0.5%
634825 1
0.5%
ValueCountFrequency (%)
635031 1
0.5%
635030 1
0.5%
635029 1
0.5%
635028 1
0.5%
635027 1
0.5%
635026 1
0.5%
635025 1
0.5%
635024 1
0.5%
635023 1
0.5%
635022 1
0.5%

Time
Date

Distinct112
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
Minimum2019-10-01 00:00:22
Maximum2019-10-01 08:34:53
2023-12-10T15:35:51.275311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T15:35:51.528820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

TransFat
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.042572864
Minimum0
Maximum2.496
Zeros189
Zeros (%)95.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:52.114105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.004
Maximum2.496
Range2.496
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.25768035
Coefficient of variation (CV)6.0526901
Kurtosis58.41607
Mean0.042572864
Median Absolute Deviation (MAD)0
Skewness7.3876151
Sum8.472
Variance0.066399165
MonotonicityNot monotonic
2023-12-10T15:35:52.337412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 189
95.0%
0.2 3
 
1.5%
1.7 2
 
1.0%
0.5 2
 
1.0%
2.496 1
 
0.5%
0.04 1
 
0.5%
0.936 1
 
0.5%
ValueCountFrequency (%)
0.0 189
95.0%
0.04 1
 
0.5%
0.2 3
 
1.5%
0.5 2
 
1.0%
0.936 1
 
0.5%
1.7 2
 
1.0%
2.496 1
 
0.5%
ValueCountFrequency (%)
2.496 1
 
0.5%
1.7 2
 
1.0%
0.936 1
 
0.5%
0.5 2
 
1.0%
0.2 3
 
1.5%
0.04 1
 
0.5%
0.0 189
95.0%

Cholesterol
Real number (ℝ)

ZEROS 

Distinct57
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.484178
Minimum0
Maximum1009.4
Zeros104
Zeros (%)52.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:52.560549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q325.4
95-th percentile223
Maximum1009.4
Range1009.4
Interquartile range (IQR)25.4

Descriptive statistics

Standard deviation123.36408
Coefficient of variation (CV)2.7122417
Kurtosis37.027862
Mean45.484178
Median Absolute Deviation (MAD)0
Skewness5.3990521
Sum9051.3515
Variance15218.697
MonotonicityNot monotonic
2023-12-10T15:35:52.835397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 104
52.3%
223.0 8
 
4.0%
20.0 5
 
2.5%
5.0 5
 
2.5%
10.0 5
 
2.5%
198.2 4
 
2.0%
386.0 3
 
1.5%
18.0 3
 
1.5%
1.9 3
 
1.5%
40.0 3
 
1.5%
Other values (47) 56
28.1%
ValueCountFrequency (%)
0.0 104
52.3%
0.7 1
 
0.5%
0.9 2
 
1.0%
1.0 1
 
0.5%
1.4 2
 
1.0%
1.9 3
 
1.5%
3.9 2
 
1.0%
4.0 2
 
1.0%
5.0 5
 
2.5%
7.49 1
 
0.5%
ValueCountFrequency (%)
1009.4 2
 
1.0%
386.0 3
 
1.5%
255.0 1
 
0.5%
225.0 1
 
0.5%
223.0 8
4.0%
222.0 1
 
0.5%
218.3 1
 
0.5%
198.2 4
2.0%
184.1 1
 
0.5%
112.0 1
 
0.5%

Sodium
Real number (ℝ)

ZEROS 

Distinct121
Distinct (%)60.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean354.04367
Minimum0
Maximum4000
Zeros15
Zeros (%)7.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:53.104594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q19
median120
Q3390.5
95-th percentile1457.9
Maximum4000
Range4000
Interquartile range (IQR)381.5

Descriptive statistics

Standard deviation603.78899
Coefficient of variation (CV)1.7054082
Kurtosis14.554388
Mean354.04367
Median Absolute Deviation (MAD)118
Skewness3.3844754
Sum70454.691
Variance364561.14
MonotonicityNot monotonic
2023-12-10T15:35:53.594968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 15
 
7.5%
70.0 8
 
4.0%
3.0 6
 
3.0%
1.0 5
 
2.5%
120.0 5
 
2.5%
291.04 4
 
2.0%
170.0 4
 
2.0%
80.0 4
 
2.0%
8.0 4
 
2.0%
2.0 4
 
2.0%
Other values (111) 140
70.4%
ValueCountFrequency (%)
0.0 15
7.5%
0.1 1
 
0.5%
0.6 1
 
0.5%
0.86 1
 
0.5%
1.0 5
 
2.5%
2.0 4
 
2.0%
2.5 1
 
0.5%
3.0 6
 
3.0%
4.0 2
 
1.0%
4.5 1
 
0.5%
ValueCountFrequency (%)
4000.0 2
1.0%
2639.0 2
1.0%
2020.0 2
1.0%
1890.0 2
1.0%
1790.0 2
1.0%
1421.0 1
0.5%
1360.0 1
0.5%
1315.0 1
0.5%
1134.0 2
1.0%
1128.0 1
0.5%

Cellulose
Real number (ℝ)

ZEROS 

Distinct69
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.6499347
Minimum0
Maximum226.2
Zeros86
Zeros (%)43.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:54.116576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.7
Q32.75
95-th percentile7.89
Maximum226.2
Range226.2
Interquartile range (IQR)2.75

Descriptive statistics

Standard deviation16.931336
Coefficient of variation (CV)4.6388052
Kurtosis152.79906
Mean3.6499347
Median Absolute Deviation (MAD)0.7
Skewness11.782394
Sum726.337
Variance286.67014
MonotonicityNot monotonic
2023-12-10T15:35:54.415446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 86
43.2%
0.5 5
 
2.5%
2.9 5
 
2.5%
5.4 5
 
2.5%
4.9 4
 
2.0%
2.7 4
 
2.0%
2.3 4
 
2.0%
1.3 3
 
1.5%
2.1 3
 
1.5%
0.9 3
 
1.5%
Other values (59) 77
38.7%
ValueCountFrequency (%)
0.0 86
43.2%
0.109 1
 
0.5%
0.11 1
 
0.5%
0.1155 1
 
0.5%
0.2 1
 
0.5%
0.203 1
 
0.5%
0.218 1
 
0.5%
0.455 1
 
0.5%
0.5 5
 
2.5%
0.6 1
 
0.5%
ValueCountFrequency (%)
226.2 1
0.5%
45.0 2
1.0%
29.0 2
1.0%
28.0 1
0.5%
16.1 1
0.5%
12.8 1
0.5%
10.5 2
1.0%
7.6 1
0.5%
7.52 2
1.0%
5.81 1
0.5%

Calcium
Real number (ℝ)

ZEROS 

Distinct86
Distinct (%)43.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.106897
Minimum0
Maximum483
Zeros66
Zeros (%)33.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:54.752235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median11.18
Q328
95-th percentile152
Maximum483
Range483
Interquartile range (IQR)28

Descriptive statistics

Standard deviation63.494068
Coefficient of variation (CV)1.9775834
Kurtosis25.474928
Mean32.106897
Median Absolute Deviation (MAD)11.18
Skewness4.409001
Sum6389.2725
Variance4031.4966
MonotonicityNot monotonic
2023-12-10T15:35:55.125816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 66
33.2%
26.0 9
 
4.5%
8.0 8
 
4.0%
27.071 4
 
2.0%
18.0 4
 
2.0%
20.8 4
 
2.0%
5.0 3
 
1.5%
180.0 3
 
1.5%
21.0 3
 
1.5%
15.0 3
 
1.5%
Other values (76) 92
46.2%
ValueCountFrequency (%)
0.0 66
33.2%
0.595 2
 
1.0%
1.0 1
 
0.5%
2.0 1
 
0.5%
2.097 1
 
0.5%
2.45 1
 
0.5%
3.0 2
 
1.0%
3.175 1
 
0.5%
3.8 1
 
0.5%
4.0 1
 
0.5%
ValueCountFrequency (%)
483.0 2
1.0%
240.1 1
 
0.5%
210.0 1
 
0.5%
185.0 1
 
0.5%
180.0 3
1.5%
178.0 1
 
0.5%
152.0 2
1.0%
140.0 2
1.0%
138.0 1
 
0.5%
114.0 1
 
0.5%

FolicAcid
Real number (ℝ)

ZEROS 

Distinct70
Distinct (%)35.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.308347
Minimum0
Maximum216
Zeros80
Zeros (%)40.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:55.393519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q328.5
95-th percentile91.4
Maximum216
Range216
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation33.211431
Coefficient of variation (CV)1.5586113
Kurtosis7.489267
Mean21.308347
Median Absolute Deviation (MAD)6
Skewness2.4034763
Sum4240.361
Variance1102.9991
MonotonicityNot monotonic
2023-12-10T15:35:55.681355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 80
40.2%
69.5 8
 
4.0%
6.0 7
 
3.5%
4.0 6
 
3.0%
60.0 4
 
2.0%
11.0 4
 
2.0%
40.5 4
 
2.0%
12.0 3
 
1.5%
40.0 3
 
1.5%
25.0 3
 
1.5%
Other values (60) 77
38.7%
ValueCountFrequency (%)
0.0 80
40.2%
0.32 1
 
0.5%
1.5 1
 
0.5%
2.0 1
 
0.5%
2.55 1
 
0.5%
2.82 1
 
0.5%
2.99 1
 
0.5%
3.0 1
 
0.5%
4.0 6
 
3.0%
4.8 2
 
1.0%
ValueCountFrequency (%)
216.0 1
0.5%
147.0 1
0.5%
136.0 1
0.5%
129.0 2
1.0%
104.55 2
1.0%
102.8 1
0.5%
101.0 1
0.5%
95.0 1
0.5%
91.0 1
0.5%
70.0 2
1.0%

Iron
Real number (ℝ)

ZEROS 

Distinct79
Distinct (%)39.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.5778129
Minimum0
Maximum63
Zeros68
Zeros (%)34.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:55.891197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.3
Q31.148
95-th percentile12.61
Maximum63
Range63
Interquartile range (IQR)1.148

Descriptive statistics

Standard deviation9.2445728
Coefficient of variation (CV)3.5862078
Kurtosis31.051296
Mean2.5778129
Median Absolute Deviation (MAD)0.3
Skewness5.4644174
Sum512.98478
Variance85.462127
MonotonicityNot monotonic
2023-12-10T15:35:56.106278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 68
34.2%
0.885 8
 
4.0%
0.2 6
 
3.0%
1.3 5
 
2.5%
0.9168 4
 
2.0%
1.0 4
 
2.0%
0.6 4
 
2.0%
0.8 3
 
1.5%
0.1 3
 
1.5%
1.1 3
 
1.5%
Other values (69) 91
45.7%
ValueCountFrequency (%)
0.0 68
34.2%
0.02 1
 
0.5%
0.022 1
 
0.5%
0.068975 1
 
0.5%
0.1 3
 
1.5%
0.105 1
 
0.5%
0.1103 1
 
0.5%
0.129 1
 
0.5%
0.132 1
 
0.5%
0.144 1
 
0.5%
ValueCountFrequency (%)
63.0 2
1.0%
58.8 2
1.0%
32.1 1
0.5%
20.0 2
1.0%
19.6 2
1.0%
19.0 1
0.5%
11.9 1
0.5%
7.6 1
0.5%
5.4 1
0.5%
4.8 1
0.5%

VitaminA
Real number (ℝ)

ZEROS 

Distinct44
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.43409
Minimum0
Maximum889
Zeros109
Zeros (%)54.8%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:56.337064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q320
95-th percentile123.2
Maximum889
Range889
Interquartile range (IQR)20

Descriptive statistics

Standard deviation89.259991
Coefficient of variation (CV)3.1391892
Kurtosis49.503296
Mean28.43409
Median Absolute Deviation (MAD)0
Skewness6.2609361
Sum5658.384
Variance7967.346
MonotonicityNot monotonic
2023-12-10T15:35:56.553244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
0.0 109
54.8%
1.0 11
 
5.5%
20.0 9
 
4.5%
2.0 5
 
2.5%
22.0 5
 
2.5%
44.0 5
 
2.5%
3.0 3
 
1.5%
104.0 3
 
1.5%
19.0 3
 
1.5%
7.0 3
 
1.5%
Other values (34) 43
 
21.6%
ValueCountFrequency (%)
0.0 109
54.8%
0.1 2
 
1.0%
0.224 1
 
0.5%
0.4 1
 
0.5%
0.6 1
 
0.5%
0.96 1
 
0.5%
1.0 11
 
5.5%
2.0 5
 
2.5%
3.0 3
 
1.5%
5.0 1
 
0.5%
ValueCountFrequency (%)
889.0 1
0.5%
482.0 1
0.5%
469.0 1
0.5%
290.0 1
0.5%
242.0 1
0.5%
241.0 1
0.5%
205.0 1
0.5%
202.0 1
0.5%
200.0 1
0.5%
170.0 1
0.5%

VitaminC
Real number (ℝ)

ZEROS 

Distinct57
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.9752348
Minimum0
Maximum220
Zeros112
Zeros (%)56.3%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:56.776035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile25
Maximum220
Range220
Interquartile range (IQR)3

Descriptive statistics

Standard deviation19.886372
Coefficient of variation (CV)3.3281323
Kurtosis72.099559
Mean5.9752348
Median Absolute Deviation (MAD)0
Skewness7.576663
Sum1189.0717
Variance395.46779
MonotonicityNot monotonic
2023-12-10T15:35:57.071094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 112
56.3%
25.0 6
 
3.0%
2.82 5
 
2.5%
2.0 4
 
2.0%
3.0 4
 
2.0%
6.0 3
 
1.5%
1.58 3
 
1.5%
0.64 2
 
1.0%
0.336 2
 
1.0%
15.0 2
 
1.0%
Other values (47) 56
28.1%
ValueCountFrequency (%)
0.0 112
56.3%
0.000395 1
 
0.5%
0.0668 1
 
0.5%
0.104375 1
 
0.5%
0.1186 2
 
1.0%
0.3267 1
 
0.5%
0.336 2
 
1.0%
0.64 2
 
1.0%
0.66 1
 
0.5%
0.86 1
 
0.5%
ValueCountFrequency (%)
220.0 1
 
0.5%
108.0 1
 
0.5%
80.0 1
 
0.5%
69.0 1
 
0.5%
42.0 1
 
0.5%
38.71 1
 
0.5%
34.0 1
 
0.5%
29.06 1
 
0.5%
25.0 6
3.0%
24.1768 1
 
0.5%

Caffeine
Categorical

IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
0.0
196 
1.258
 
2
3.064
 
1

Length

Max length5
Median length3
Mean length3.0301508
Min length3

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 196
98.5%
1.258 2
 
1.0%
3.064 1
 
0.5%

Length

2023-12-10T15:35:57.307193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:35:57.494125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 196
98.5%
1.258 2
 
1.0%
3.064 1
 
0.5%

FoodName
Text

Distinct151
Distinct (%)75.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:35:57.867819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length5.3065327
Min length1

Characters and Unicode

Total characters1056
Distinct characters273
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique121 ?
Unique (%)60.8%

Sample

1st row불닭볶음면 큰컵
2nd row테라 맥주
3rd row크래미
4th row소고기볶음(숙주)
5th row날치알볶음밥
ValueCountFrequency (%)
삶은계란 8
 
3.1%
사과 6
 
2.3%
고구마(찐것 4
 
1.6%
흑미밥 4
 
1.6%
계란후라이 4
 
1.6%
우유 4
 
1.6%
라떼 4
 
1.6%
계란 3
 
1.2%
토스트 3
 
1.2%
아이스 3
 
1.2%
Other values (185) 213
83.2%
2023-12-10T15:35:58.448375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57
 
5.4%
이 29
 
2.7%
( 22
 
2.1%
스 21
 
2.0%
) 20
 
1.9%
밥 18
 
1.7%
계 17
 
1.6%
란 17
 
1.6%
음 16
 
1.5%
고 16
 
1.5%
Other values (263) 823
77.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 934
88.4%
Space Separator 57
 
5.4%
Open Punctuation 22
 
2.1%
Close Punctuation 20
 
1.9%
Decimal Number 13
 
1.2%
Lowercase Letter 5
 
0.5%
Other Punctuation 3
 
0.3%
Uppercase Letter 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 29
 
3.1%
스 21
 
2.2%
밥 18
 
1.9%
계 17
 
1.8%
란 17
 
1.8%
음 16
 
1.7%
고 16
 
1.7%
볶 16
 
1.7%
라 15
 
1.6%
드 15
 
1.6%
Other values (247) 754
80.7%
Decimal Number
ValueCountFrequency (%)
0 6
46.2%
1 3
23.1%
9 1
 
7.7%
3 1
 
7.7%
8 1
 
7.7%
5 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
m 2
40.0%
l 2
40.0%
v 1
20.0%
Other Punctuation
ValueCountFrequency (%)
% 2
66.7%
& 1
33.3%
Uppercase Letter
ValueCountFrequency (%)
T 1
50.0%
G 1
50.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Close Punctuation
ValueCountFrequency (%)
) 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 934
88.4%
Common 115
 
10.9%
Latin 7
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 29
 
3.1%
스 21
 
2.2%
밥 18
 
1.9%
계 17
 
1.8%
란 17
 
1.8%
음 16
 
1.7%
고 16
 
1.7%
볶 16
 
1.7%
라 15
 
1.6%
드 15
 
1.6%
Other values (247) 754
80.7%
Common
ValueCountFrequency (%)
57
49.6%
( 22
 
19.1%
) 20
 
17.4%
0 6
 
5.2%
1 3
 
2.6%
% 2
 
1.7%
9 1
 
0.9%
3 1
 
0.9%
8 1
 
0.9%
& 1
 
0.9%
Latin
ValueCountFrequency (%)
m 2
28.6%
l 2
28.6%
T 1
14.3%
G 1
14.3%
v 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 934
88.4%
ASCII 122
 
11.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57
46.7%
( 22
 
18.0%
) 20
 
16.4%
0 6
 
4.9%
1 3
 
2.5%
m 2
 
1.6%
l 2
 
1.6%
% 2
 
1.6%
9 1
 
0.8%
T 1
 
0.8%
Other values (6) 6
 
4.9%
Hangul
ValueCountFrequency (%)
이 29
 
3.1%
스 21
 
2.2%
밥 18
 
1.9%
계 17
 
1.8%
란 17
 
1.8%
음 16
 
1.7%
고 16
 
1.7%
볶 16
 
1.7%
라 15
 
1.6%
드 15
 
1.6%
Other values (247) 754
80.7%

water
Real number (ℝ)

ZEROS 

Distinct96
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.700067
Minimum0
Maximum361.05
Zeros70
Zeros (%)35.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:58.685888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median35.56
Q368.58255
95-th percentile174.98
Maximum361.05
Range361.05
Interquartile range (IQR)68.58255

Descriptive statistics

Standard deviation64.133947
Coefficient of variation (CV)1.2904197
Kurtosis3.8075824
Mean49.700067
Median Absolute Deviation (MAD)35.56
Skewness1.8047754
Sum9890.3133
Variance4113.1632
MonotonicityNot monotonic
2023-12-10T15:35:58.923137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 70
35.2%
37.5 8
 
4.0%
170.4 5
 
2.5%
85.8 4
 
2.0%
38.0228 4
 
2.0%
174.8 3
 
1.5%
37.12 2
 
1.0%
51.119 2
 
1.0%
113.449 2
 
1.0%
85.5 2
 
1.0%
Other values (86) 97
48.7%
ValueCountFrequency (%)
0.0 70
35.2%
0.2318 1
 
0.5%
0.405 1
 
0.5%
2.0032 1
 
0.5%
2.4 1
 
0.5%
4.8 2
 
1.0%
8.3305 1
 
0.5%
8.955 1
 
0.5%
10.749 1
 
0.5%
11.49 1
 
0.5%
ValueCountFrequency (%)
361.05 1
 
0.5%
303.18 1
 
0.5%
249.577 2
1.0%
216.489 1
 
0.5%
187.8 1
 
0.5%
184.6 1
 
0.5%
180.0 1
 
0.5%
179.6 1
 
0.5%
176.6 1
 
0.5%
174.8 3
1.5%

ash
Real number (ℝ)

ZEROS 

Distinct97
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2702356
Minimum0
Maximum70.96
Zeros65
Zeros (%)32.7%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:35:59.161470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.58
Q31.4256
95-th percentile5.3366
Maximum70.96
Range70.96
Interquartile range (IQR)1.4256

Descriptive statistics

Standard deviation8.7888193
Coefficient of variation (CV)3.8713248
Kurtosis47.401798
Mean2.2702356
Median Absolute Deviation (MAD)0.58
Skewness6.7851546
Sum451.77688
Variance77.243345
MonotonicityNot monotonic
2023-12-10T15:35:59.426052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 65
32.7%
0.45 9
 
4.5%
0.42 5
 
2.5%
1.56 4
 
2.0%
1.0314 4
 
2.0%
0.7 3
 
1.5%
1.34 3
 
1.5%
0.63 3
 
1.5%
0.9 2
 
1.0%
66.555 2
 
1.0%
Other values (87) 99
49.7%
ValueCountFrequency (%)
0.0 65
32.7%
0.028 1
 
0.5%
0.04 1
 
0.5%
0.161 1
 
0.5%
0.172 1
 
0.5%
0.19 1
 
0.5%
0.23 2
 
1.0%
0.3 1
 
0.5%
0.357 1
 
0.5%
0.36 2
 
1.0%
ValueCountFrequency (%)
70.96 1
0.5%
66.555 2
1.0%
31.68 1
0.5%
30.66 1
0.5%
6.2109 1
0.5%
5.8897 1
0.5%
5.4771 2
1.0%
5.3366 2
1.0%
4.80445 1
0.5%
3.91885 2
1.0%

total_amino_acids
Real number (ℝ)

ZEROS 

Distinct81
Distinct (%)40.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2074.5461
Minimum0
Maximum16606
Zeros90
Zeros (%)45.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:36:00.103050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median137.93
Q32389.15
95-th percentile11254.5
Maximum16606
Range16606
Interquartile range (IQR)2389.15

Descriptive statistics

Standard deviation3623.6713
Coefficient of variation (CV)1.7467297
Kurtosis3.6445295
Mean2074.5461
Median Absolute Deviation (MAD)137.93
Skewness2.0354744
Sum412834.68
Variance13130994
MonotonicityNot monotonic
2023-12-10T15:36:00.364318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 90
45.2%
6083.5 8
 
4.0%
378.0 5
 
2.5%
6255.5 4
 
2.0%
6066.0 3
 
1.5%
0.646 2
 
1.0%
177.0 2
 
1.0%
15673.6 2
 
1.0%
3978.84 2
 
1.0%
3012.1 2
 
1.0%
Other values (71) 79
39.7%
ValueCountFrequency (%)
0.0 90
45.2%
0.128 1
 
0.5%
0.41 1
 
0.5%
0.5895 1
 
0.5%
0.646 2
 
1.0%
1.08 1
 
0.5%
46.7 1
 
0.5%
83.13 1
 
0.5%
137.93 2
 
1.0%
138.737 1
 
0.5%
ValueCountFrequency (%)
16606.0 1
0.5%
15673.6 2
1.0%
14194.2 1
0.5%
12917.2 1
0.5%
11889.1 1
0.5%
11844.6 1
0.5%
11664.8 1
0.5%
11324.8 1
0.5%
11254.5 2
1.0%
10601.1 1
0.5%

essential_amino_acid
Real number (ℝ)

ZEROS 

Distinct77
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean978.65358
Minimum0
Maximum12177.9
Zeros94
Zeros (%)47.2%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:36:00.638389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median62.36
Q3950.45
95-th percentile4579.302
Maximum12177.9
Range12177.9
Interquartile range (IQR)950.45

Descriptive statistics

Standard deviation1811.4698
Coefficient of variation (CV)1.8509816
Kurtosis8.7608609
Mean978.65358
Median Absolute Deviation (MAD)62.36
Skewness2.6050155
Sum194752.06
Variance3281422.9
MonotonicityNot monotonic
2023-12-10T15:36:00.986824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 94
47.2%
2911.5 8
 
4.0%
106.0 5
 
2.5%
3143.0 4
 
2.0%
2762.0 3
 
1.5%
2276.3 2
 
1.0%
74.0 2
 
1.0%
6264.13 2
 
1.0%
1751.94 2
 
1.0%
932.05 2
 
1.0%
Other values (67) 75
37.7%
ValueCountFrequency (%)
0.0 94
47.2%
0.14 1
 
0.5%
14.7 1
 
0.5%
34.17 1
 
0.5%
58.8515 1
 
0.5%
62.36 2
 
1.0%
74.0 2
 
1.0%
77.29 1
 
0.5%
78.05 1
 
0.5%
94.355 1
 
0.5%
ValueCountFrequency (%)
12177.9 1
0.5%
7881.08 1
0.5%
7124.34 1
0.5%
6264.13 2
1.0%
5956.36 1
0.5%
5795.73 1
0.5%
5605.6 1
0.5%
5326.93 1
0.5%
4776.24 1
0.5%
4557.42 1
0.5%

FoodImage
Text

MISSING 

Distinct95
Distinct (%)55.9%
Missing29
Missing (%)14.6%
Memory size1.7 KiB
2023-12-10T15:36:01.467626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length36
Mean length35.1
Min length1

Characters and Unicode

Total characters5967
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)39.4%

Sample

1st row49d47f14007f4323b6ff295565157aa4.png
2nd row0
3rd rowed933906632942e1b580701c43a3b271.png
4th row33abd4e887954fb1ad7cab55744e0cb5.png
5th row5adf1aff2fda4c34ae7656e89eb30025.png
ValueCountFrequency (%)
6c020604da264361970f710e7815da96.png 13
 
7.6%
80f5be879d104cef803fc8df62600c9d.png 10
 
5.9%
0550f4394316416f80c369d25f606f09.png 7
 
4.1%
42bdd218d6074c47ae80b14feaac2e40.png 6
 
3.5%
ca4952d216bf41c19cc09bea829303e9.png 5
 
2.9%
f0efe2243ac54f4b9695d8e66f84e1eb.png 5
 
2.9%
805316b392e242619462f0caca45a24e.png 5
 
2.9%
a4d166aaa96341fc84b4aa37850ae6fa.png 4
 
2.4%
5adf1aff2fda4c34ae7656e89eb30025.png 3
 
1.8%
6a856bce567f487b8b924c1ae239848d.png 3
 
1.8%
Other values (85) 109
64.1%
2023-12-10T15:36:02.081154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 462
 
7.7%
0 424
 
7.1%
6 407
 
6.8%
9 355
 
5.9%
a 349
 
5.8%
1 349
 
5.8%
2 329
 
5.5%
f 320
 
5.4%
8 315
 
5.3%
e 312
 
5.2%
Other values (10) 2345
39.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3469
58.1%
Lowercase Letter 2329
39.0%
Other Punctuation 169
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 462
13.3%
0 424
12.2%
6 407
11.7%
9 355
10.2%
1 349
10.1%
2 329
9.5%
8 315
9.1%
3 280
8.1%
5 274
7.9%
7 274
7.9%
Lowercase Letter
ValueCountFrequency (%)
a 349
15.0%
f 320
13.7%
e 312
13.4%
d 289
12.4%
c 283
12.2%
b 281
12.1%
p 165
7.1%
n 165
7.1%
g 165
7.1%
Other Punctuation
ValueCountFrequency (%)
. 169
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3638
61.0%
Latin 2329
39.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 462
12.7%
0 424
11.7%
6 407
11.2%
9 355
9.8%
1 349
9.6%
2 329
9.0%
8 315
8.7%
3 280
7.7%
5 274
7.5%
7 274
7.5%
Latin
ValueCountFrequency (%)
a 349
15.0%
f 320
13.7%
e 312
13.4%
d 289
12.4%
c 283
12.2%
b 281
12.1%
p 165
7.1%
n 165
7.1%
g 165
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5967
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 462
 
7.7%
0 424
 
7.1%
6 407
 
6.8%
9 355
 
5.9%
a 349
 
5.8%
1 349
 
5.8%
2 329
 
5.5%
f 320
 
5.4%
8 315
 
5.3%
e 312
 
5.2%
Other values (10) 2345
39.3%

StandardUnit
Categorical

Distinct39
Distinct (%)19.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
1개
40 
1접시
38 
1인분
21 
1컵
16 
1공기
12 
Other values (34)
72 

Length

Max length11
Median length9
Mean length3
Min length2

Unique

Unique19 ?
Unique (%)9.5%

Sample

1st row1컵
2nd row1병
3rd row1회제공량
4th row1접시
5th row1인분

Common Values

ValueCountFrequency (%)
1개 40
20.1%
1접시 38
19.1%
1인분 21
10.6%
1컵 16
 
8.0%
1공기 12
 
6.0%
1대접 7
 
3.5%
1팩 6
 
3.0%
1잔 5
 
2.5%
1병 5
 
2.5%
1그릇 4
 
2.0%
Other values (29) 45
22.6%

Length

2023-12-10T15:36:02.310197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1개 40
20.1%
1접시 38
19.1%
1인분 21
10.6%
1컵 16
 
8.0%
1공기 12
 
6.0%
1대접 7
 
3.5%
1팩 6
 
3.0%
1잔 5
 
2.5%
1병 5
 
2.5%
1그릇 4
 
2.0%
Other values (29) 45
22.6%

TotalGram
Text

Distinct60
Distinct (%)30.2%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-10T15:36:02.707170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length2.6884422
Min length1

Characters and Unicode

Total characters535
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)14.6%

Sample

1st row105
2nd row500
3rd row30
4th row100
5th row430
ValueCountFrequency (%)
100 28
 
14.1%
200 23
 
11.6%
50 10
 
5.0%
210 10
 
5.0%
150 8
 
4.0%
40 8
 
4.0%
70 8
 
4.0%
130 7
 
3.5%
230 6
 
3.0%
53 5
 
2.5%
Other values (50) 86
43.2%
2023-12-10T15:36:03.301919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 222
41.5%
1 90
16.8%
2 54
 
10.1%
5 51
 
9.5%
3 40
 
7.5%
4 21
 
3.9%
8 16
 
3.0%
7 15
 
2.8%
9 6
 
1.1%
. 5
 
0.9%
Other values (8) 15
 
2.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 518
96.8%
Other Letter 10
 
1.9%
Other Punctuation 5
 
0.9%
Open Punctuation 1
 
0.2%
Close Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 222
42.9%
1 90
17.4%
2 54
 
10.4%
5 51
 
9.8%
3 40
 
7.7%
4 21
 
4.1%
8 16
 
3.1%
7 15
 
2.9%
9 6
 
1.2%
6 3
 
0.6%
Other Letter
ValueCountFrequency (%)
시 3
30.0%
접 3
30.0%
개 2
20.0%
조 1
 
10.0%
각 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 525
98.1%
Hangul 10
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 222
42.3%
1 90
17.1%
2 54
 
10.3%
5 51
 
9.7%
3 40
 
7.6%
4 21
 
4.0%
8 16
 
3.0%
7 15
 
2.9%
9 6
 
1.1%
. 5
 
1.0%
Other values (3) 5
 
1.0%
Hangul
ValueCountFrequency (%)
시 3
30.0%
접 3
30.0%
개 2
20.0%
조 1
 
10.0%
각 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 525
98.1%
Hangul 10
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 222
42.3%
1 90
17.1%
2 54
 
10.3%
5 51
 
9.7%
3 40
 
7.6%
4 21
 
4.0%
8 16
 
3.0%
7 15
 
2.9%
9 6
 
1.1%
. 5
 
1.0%
Other values (3) 5
 
1.0%
Hangul
ValueCountFrequency (%)
시 3
30.0%
접 3
30.0%
개 2
20.0%
조 1
 
10.0%
각 1
 
10.0%

Calorie
Real number (ℝ)

ZEROS 

Distinct128
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean153.95849
Minimum0
Maximum688
Zeros3
Zeros (%)1.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:36:03.542963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10.90175
Q151.5
median99
Q3186.5
95-th percentile462.31
Maximum688
Range688
Interquartile range (IQR)135

Descriptive statistics

Standard deviation145.92253
Coefficient of variation (CV)0.94780435
Kurtosis1.4984263
Mean153.95849
Median Absolute Deviation (MAD)59
Skewness1.4243918
Sum30637.741
Variance21293.385
MonotonicityNot monotonic
2023-12-10T15:36:03.787115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.5 8
 
4.0%
106.0 5
 
2.5%
140.0 5
 
2.5%
169.0 4
 
2.0%
86.3 4
 
2.0%
330.0 4
 
2.0%
40.0 3
 
1.5%
55.0 3
 
1.5%
130.0 3
 
1.5%
45.0 3
 
1.5%
Other values (118) 157
78.9%
ValueCountFrequency (%)
0.0 3
1.5%
5.2 1
 
0.5%
6.0 1
 
0.5%
8.4 1
 
0.5%
10.0 3
1.5%
10.67 1
 
0.5%
10.9275 1
 
0.5%
11.0 1
 
0.5%
12.8 2
1.0%
13.196 1
 
0.5%
ValueCountFrequency (%)
688.0 2
1.0%
620.0 1
 
0.5%
500.0 2
1.0%
482.0 3
1.5%
480.0 1
 
0.5%
475.0 1
 
0.5%
460.9 1
 
0.5%
445.0 1
 
0.5%
440.872 1
 
0.5%
426.0 3
1.5%

CarbonHydrate
Real number (ℝ)

ZEROS 

Distinct124
Distinct (%)62.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.111672
Minimum0
Maximum168
Zeros13
Zeros (%)6.5%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:36:04.045956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12.99325
median10.37
Q330.5
95-th percentile81.0623
Maximum168
Range168
Interquartile range (IQR)27.50675

Descriptive statistics

Standard deviation28.964287
Coefficient of variation (CV)1.253232
Kurtosis2.957763
Mean23.111672
Median Absolute Deviation (MAD)8.6518
Skewness1.7006912
Sum4599.2228
Variance838.92995
MonotonicityNot monotonic
2023-12-10T15:36:04.274048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 13
 
6.5%
1.095 8
 
4.0%
10.0 6
 
3.0%
28.72 5
 
2.5%
71.0 4
 
2.0%
40.69 4
 
2.0%
1.7182 4
 
2.0%
9.0 4
 
2.0%
2.0 4
 
2.0%
13.0 3
 
1.5%
Other values (114) 144
72.4%
ValueCountFrequency (%)
0.0 13
6.5%
0.128 1
 
0.5%
0.216 1
 
0.5%
0.50045 1
 
0.5%
0.715 1
 
0.5%
0.8 1
 
0.5%
0.8107 1
 
0.5%
1.05 1
 
0.5%
1.095 8
4.0%
1.4 1
 
0.5%
ValueCountFrequency (%)
168.0 1
0.5%
102.0 1
0.5%
101.0 2
1.0%
94.0 1
0.5%
90.839 1
0.5%
86.0 2
1.0%
84.0 1
0.5%
83.0 1
0.5%
80.847 1
0.5%
79.3 1
0.5%

Sugar
Real number (ℝ)

ZEROS 

Distinct96
Distinct (%)48.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2053937
Minimum0
Maximum59
Zeros45
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:36:04.534828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.01005
median1.6935
Q36.605
95-th percentile22.28
Maximum59
Range59
Interquartile range (IQR)6.59495

Descriptive statistics

Standard deviation8.6761312
Coefficient of variation (CV)1.6667579
Kurtosis11.41732
Mean5.2053937
Median Absolute Deviation (MAD)1.6935
Skewness2.958622
Sum1035.8734
Variance75.275253
MonotonicityNot monotonic
2023-12-10T15:36:04.750253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 45
22.6%
0.085 8
 
4.0%
3.0 6
 
3.0%
5.0 5
 
2.5%
22.28 5
 
2.5%
10.0 5
 
2.5%
9.0 4
 
2.0%
0.11 4
 
2.0%
7.0 4
 
2.0%
2.1 3
 
1.5%
Other values (86) 110
55.3%
ValueCountFrequency (%)
0.0 45
22.6%
0.0047 2
 
1.0%
0.0094 3
 
1.5%
0.0107 1
 
0.5%
0.085 8
 
4.0%
0.09185 1
 
0.5%
0.11 4
 
2.0%
0.1447 1
 
0.5%
0.176 1
 
0.5%
0.2 1
 
0.5%
ValueCountFrequency (%)
59.0 1
 
0.5%
49.733 1
 
0.5%
37.0 1
 
0.5%
35.0 1
 
0.5%
28.657 1
 
0.5%
27.0 1
 
0.5%
23.2 1
 
0.5%
23.0 1
 
0.5%
22.28 5
2.5%
22.0 1
 
0.5%

Protein
Real number (ℝ)

ZEROS 

Distinct114
Distinct (%)57.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4719911
Minimum0
Maximum66.5
Zeros10
Zeros (%)5.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:36:04.962227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.0504
Q11.138
median5
Q38.45
95-th percentile21.05
Maximum66.5
Range66.5
Interquartile range (IQR)7.312

Descriptive statistics

Standard deviation8.329903
Coefficient of variation (CV)1.2870696
Kurtosis26.182726
Mean6.4719911
Median Absolute Deviation (MAD)3.824
Skewness4.207754
Sum1287.9262
Variance69.387283
MonotonicityNot monotonic
2023-12-10T15:36:05.201151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 10
 
5.0%
6.97 8
 
4.0%
0.4 6
 
3.0%
9.0 5
 
2.5%
3.0 5
 
2.5%
11.0 5
 
2.5%
6.5 5
 
2.5%
2.0 4
 
2.0%
5.0 4
 
2.0%
1.0 4
 
2.0%
Other values (104) 143
71.9%
ValueCountFrequency (%)
0.0 10
5.0%
0.056 1
 
0.5%
0.213895 1
 
0.5%
0.23 2
 
1.0%
0.258 1
 
0.5%
0.2695 1
 
0.5%
0.3 1
 
0.5%
0.3585 1
 
0.5%
0.4 6
3.0%
0.5 1
 
0.5%
ValueCountFrequency (%)
66.5 2
1.0%
28.0 2
1.0%
25.5 1
 
0.5%
24.0 1
 
0.5%
22.0 1
 
0.5%
21.5 3
1.5%
21.0 1
 
0.5%
19.7 1
 
0.5%
15.072 1
 
0.5%
15.0 1
 
0.5%

SaturatedFattyAcid
Real number (ℝ)

ZEROS 

Distinct114
Distinct (%)57.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8742077
Minimum0
Maximum56
Zeros34
Zeros (%)17.1%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-10T15:36:05.413414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median0.616
Q32
95-th percentile6.38
Maximum56
Range56
Interquartile range (IQR)1.98

Descriptive statistics

Standard deviation4.6795845
Coefficient of variation (CV)2.4968334
Kurtosis91.42984
Mean1.8742077
Median Absolute Deviation (MAD)0.616
Skewness8.3912442
Sum372.96734
Variance21.898511
MonotonicityNot monotonic
2023-12-10T15:36:05.653568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 34
 
17.1%
1.36 8
 
4.0%
0.02 6
 
3.0%
0.3 4
 
2.0%
1.5724 4
 
2.0%
1.5 4
 
2.0%
3.5 3
 
1.5%
0.149 3
 
1.5%
4.34 3
 
1.5%
3.93 3
 
1.5%
Other values (104) 127
63.8%
ValueCountFrequency (%)
0.0 34
17.1%
0.0005 1
 
0.5%
0.002 1
 
0.5%
0.00566 1
 
0.5%
0.0079 1
 
0.5%
0.0086 1
 
0.5%
0.01 1
 
0.5%
0.0105 1
 
0.5%
0.015 1
 
0.5%
0.016 1
 
0.5%
ValueCountFrequency (%)
56.0 1
0.5%
16.0 1
0.5%
14.34 1
0.5%
12.98 2
1.0%
12.6405 1
0.5%
9.511 1
0.5%
9.0 2
1.0%
8.0 1
0.5%
6.2 1
0.5%
5.588 1
0.5%

Sample

idTimeTransFatCholesterolSodiumCelluloseCalciumFolicAcidIronVitaminAVitaminCCaffeineFoodNamewaterashtotal_amino_acidsessential_amino_acidFoodImageStandardUnitTotalGramCalorieCarbonHydrateSugarProteinSaturatedFattyAcid
06348082019-10-01 00:00:220.00.0950.00.00.00.00.00.00.00.0불닭볶음면 큰컵0.00.00.00.0<NA>1컵105425.063.08.09.08.0
16348092019-10-01 00:00:220.00.00.00.00.00.00.00.00.00.0테라 맥주0.00.00.00.0<NA>1병50069.7512.60.00.00.0
26348102019-10-01 00:11:360.05.0230.00.00.00.00.00.00.00.0크래미0.00.00.00.0<NA>1회제공량3025.03.01.03.00.0
36348112019-10-01 00:32:540.037.9204.00.919.019.01.72.05.00.0소고기볶음(숙주)78.95861.0705210601.1388.406<NA>1접시100140.05.53.014.11.786
46348122019-10-01 00:37:340.025.2750.01.923.049.01.8170.04.00.0날치알볶음밥56.0112.347768.93311.58<NA>1인분430426.067.81.51347.74754.942
56348132019-10-01 00:38:060.07.49853.080.00.00.00.00.00.00.0떡볶이0.00.00.00.0<NA>1인분200303.5360.486.837.610.75
66348142019-10-01 00:40:230.00.0393.01.540.00.011.90.05.00.0김말이튀김52.21.30.00.0<NA>100g100251.032.10.02.40.0
76348182019-10-01 00:59:470.00.0840.00.00.00.00.00.00.00.0케이준치킨샐러드0.00.00.00.049d47f14007f4323b6ff295565157aa4.png1그릇230445.00.010.011.02.9
86348202019-10-01 01:12:202.4960.067.2226.20.015.019.00.9623.00.0닭고기(통닭0.030.661.080.00튀김)1접시(2조각)87.0168.03.660.014.34
96348252019-10-01 01:20:140.00.02.00.04.00.00.020.00.00.0사이다180.00.040.00.0<NA>1컵20080.019.9617.620.00.0
idTimeTransFatCholesterolSodiumCelluloseCalciumFolicAcidIronVitaminAVitaminCCaffeineFoodNamewaterashtotal_amino_acidsessential_amino_acidFoodImageStandardUnitTotalGramCalorieCarbonHydrateSugarProteinSaturatedFattyAcid
1896350222019-10-01 08:32:430.05.050.00.00.00.00.00.00.00.0쵸코하임0.00.00.00.088ef18e155944174a56a2904af6a1d6d.png1인분(2봉지)32170.018.010.03.05.0
1906350232019-10-01 08:32:570.00.03.02.15.023.00.80.034.00.0감자(삶은것)103.740.9622195.7782.6b50c1d322f044255b577ad516c101e5c.png1개13086.018.52.14.20.0
1916350242019-10-01 08:33:180.00.0180.61.29.112.250.211.00.00.0식빵12.180.563012.1932.05be95ac4cbef8416098951180eb005c9d.png1장3599.017.92.12.90.287
1926350252019-10-01 08:33:320.0223.070.00.026.069.50.88520.00.00.0삶은계란37.50.456083.52911.52c0535f9cbdb49cf8794d8ee62f153f0.png1개5071.51.0950.0856.971.36
1936350262019-10-01 08:33:510.00.011.05.731.555.00.18917.06.00.0양배추62.790.434956.2242.29b5f4c152f0e4ad1a2ecd0d86671b362.png1접시7023.15.5443.3531.1760.021
1946350272019-10-01 08:34:020.00.08.00.015.00.04.00.00.00.0포도즙85.50.23177.074.03664212dc749441a86b61c414f2f9084.png1포10051.014.036.510.230.0
1956350282019-10-01 08:34:140.00.00.10.111.06.00.0220.02.0320.0딸기잼2.40.02846.714.7a37432a9a9ca4a04a29496bcde35afce.png1큰술1025.06.35.3210.0560.002
1966350292019-10-01 08:34:330.00.08.00.015.00.04.00.00.00.0포도즙85.50.23177.074.0092d145073c24741a101b5ca050ef4a2.png1포10051.014.036.510.230.0
1976350302019-10-01 08:34:340.00.01.02.721.0129.02.37.00.00.0옥수수(찐것)65.70.90.00.0e8c5922791fa438e8ad8f5e30198154e.png1개100132.025.40.06.60.0
1986350312019-10-01 08:34:530.018.080.02.8180.04.00.1104.01.580.0우유174.81.346066.02762.01b182837a9bb446dbf2d2f7874026b5e.png1컵200122.010.00.05.64.34