Overview

Dataset statistics

Number of variables67
Number of observations100
Missing cells211
Missing cells (%)3.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory58.6 KiB
Average record size in memory600.3 B

Variable types

Numeric38
Categorical26
Text1
Unsupported2

Dataset

DescriptionSample
Author(주)어메이징푸드솔루션
URLhttps://www.bigdata-telecom.kr/invoke/SOKBP2603/?goodsCode=AFS00000000000000024

Alerts

FD_SVC_CODE has constant value ""Constant
PRCSFD_CTGRY_CODE has constant value ""Constant
BIOTIN_VALUE has constant value ""Constant
CHLOR_VALUE has constant value ""Constant
IDN_VALUE has constant value ""Constant
MUFA_VALUE has constant value ""Constant
PUFA_VALUE has constant value ""Constant
AFAT_VALUE is highly imbalanced (84.9%)Imbalance
APRTN_VALUE is highly imbalanced (86.0%)Imbalance
RTNOL_VALUE is highly imbalanced (73.0%)Imbalance
ACA_VALUE is highly imbalanced (86.0%)Imbalance
AIRON_VALUE is highly imbalanced (86.0%)Imbalance
FLRN_VALUE is highly imbalanced (89.8%)Imbalance
MANG_VALUE is highly imbalanced (82.7%)Imbalance
TRANSFA_VALUE is highly imbalanced (79.9%)Imbalance
ILE_VALUE is highly imbalanced (91.9%)Imbalance
LEU_VALUE is highly imbalanced (91.9%)Imbalance
LYS_VALUE is highly imbalanced (91.9%)Imbalance
METHIO_VALUE is highly imbalanced (91.9%)Imbalance
PHE_VALUE is highly imbalanced (91.9%)Imbalance
THREO_VALUE is highly imbalanced (91.9%)Imbalance
TRYPTO_VALUE is highly imbalanced (91.9%)Imbalance
VALINE_VALUE is highly imbalanced (91.9%)Imbalance
HISTI_VALUE is highly imbalanced (91.9%)Imbalance
ARGI_VALUE is highly imbalanced (91.9%)Imbalance
CHOLE_VALUE has 3 (3.0%) missing valuesMissing
SAFA_VALUE has 2 (2.0%) missing valuesMissing
TOT_CALORIE_VALUE has 2 (2.0%) missing valuesMissing
LAST_UPDT_DT has 100 (100.0%) missing valuesMissing
TRANSMIS_DTTM has 100 (100.0%) missing valuesMissing
FAT_VALUE has 2 (2.0%) missing valuesMissing
PRCSFD_CODE has unique valuesUnique
LAST_UPDT_DT is an unsupported type, check if it needs cleaning or further analysisUnsupported
TRANSMIS_DTTM is an unsupported type, check if it needs cleaning or further analysisUnsupported
PROTN_VALUE has 21 (21.0%) zerosZeros
VPRTN_VALUE has 62 (62.0%) zerosZeros
FIBR_VALUE has 59 (59.0%) zerosZeros
MOIST_VALUE has 58 (58.0%) zerosZeros
ASH_VALUE has 63 (63.0%) zerosZeros
VITA_VALUE has 73 (73.0%) zerosZeros
BCRT_VALUE has 84 (84.0%) zerosZeros
VITD_VALUE has 90 (90.0%) zerosZeros
VITE_VALUE has 61 (61.0%) zerosZeros
VITK_VALUE has 71 (71.0%) zerosZeros
VITC_VALUE has 56 (56.0%) zerosZeros
VITB1_VALUE has 59 (59.0%) zerosZeros
VITB2_VALUE has 58 (58.0%) zerosZeros
NIACN_VALUE has 58 (58.0%) zerosZeros
VITB6_VALUE has 62 (62.0%) zerosZeros
FOLATE_VALUE has 67 (67.0%) zerosZeros
VITB12_VALUE has 87 (87.0%) zerosZeros
PANTO_VALUE has 76 (76.0%) zerosZeros
CA_VALUE has 59 (59.0%) zerosZeros
VCA_VALUE has 62 (62.0%) zerosZeros
PHOSPHO_VALUE has 57 (57.0%) zerosZeros
NA_VALUE has 20 (20.0%) zerosZeros
POTSSM_VALUE has 59 (59.0%) zerosZeros
MGM_VALUE has 88 (88.0%) zerosZeros
IRON_VALUE has 59 (59.0%) zerosZeros
VIRON_VALUE has 60 (60.0%) zerosZeros
ZINC_VALUE has 61 (61.0%) zerosZeros
COPPR_VALUE has 63 (63.0%) zerosZeros
SELEN_VALUE has 64 (64.0%) zerosZeros
CHOLE_VALUE has 90 (90.0%) zerosZeros
TFA_VALUE has 82 (82.0%) zerosZeros
SAFA_VALUE has 76 (76.0%) zerosZeros
CARBO_VALUE has 13 (13.0%) zerosZeros
FAT_VALUE has 17 (17.0%) zerosZeros
VFAT_VALUE has 62 (62.0%) zerosZeros

Reproduction

Analysis started2023-12-10 06:43:08.048124
Analysis finished2023-12-10 06:43:09.607425
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

PRCSFD_CODE
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2991412 × 108
Minimum1.003 × 108
Maximum1.7005 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:09.739349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.003 × 108
5-th percentile1.0540011 × 108
Q11.0902501 × 108
median1.7800002 × 108
Q31.812002 × 108
95-th percentile8.3011005 × 108
Maximum1.7005 × 109
Range1.6002 × 109
Interquartile range (IQR)72175192

Descriptive statistics

Standard deviation3.2574542 × 108
Coefficient of variation (CV)1.4168135
Kurtosis14.448746
Mean2.2991412 × 108
Median Absolute Deviation (MAD)3200330
Skewness3.9423404
Sum2.2991412 × 1010
Variance1.0611008 × 1017
MonotonicityNot monotonic
2023-12-10T15:43:10.004397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
800100053 1
 
1.0%
106300050 1
 
1.0%
111500010 1
 
1.0%
111100010 1
 
1.0%
110300040 1
 
1.0%
110300030 1
 
1.0%
110300020 1
 
1.0%
110300010 1
 
1.0%
109300010 1
 
1.0%
108200010 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
100300003 1
1.0%
100500004 1
1.0%
100500005 1
1.0%
105400090 1
1.0%
105400100 1
1.0%
105400110 1
1.0%
105400120 1
1.0%
105400130 1
1.0%
105400140 1
1.0%
105400150 1
1.0%
ValueCountFrequency (%)
1700500009 1
1.0%
1700400030 1
1.0%
1600900021 1
1.0%
1600300008 1
1.0%
1400300002 1
1.0%
800100053 1
1.0%
300100107 1
1.0%
181200380 1
1.0%
181200370 1
1.0%
181200360 1
1.0%

FD_SVC_CODE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
P004
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowP004
2nd rowP004
3rd rowP004
4th rowP004
5th rowP004

Common Values

ValueCountFrequency (%)
P004 100
100.0%

Length

2023-12-10T15:43:10.380069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:10.588685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
p004 100
100.0%

AFAT_VALUE
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
96 
0.63
 
2
0.9
 
1
4.1
 
1

Length

Max length4
Median length3
Mean length3.02
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 96
96.0%
0.63 2
 
2.0%
0.9 1
 
1.0%
4.1 1
 
1.0%

Length

2023-12-10T15:43:10.784236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:10.957624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 96
96.0%
0.63 2
 
2.0%
0.9 1
 
1.0%
4.1 1
 
1.0%

PROTN_VALUE
Real number (ℝ)

ZEROS 

Distinct61
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5997
Minimum0
Maximum36
Zeros21
Zeros (%)21.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:11.178999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median1
Q36.005
95-th percentile12.048
Maximum36
Range36
Interquartile range (IQR)5.905

Descriptive statistics

Standard deviation5.3036123
Coefficient of variation (CV)1.4733484
Kurtosis13.386905
Mean3.5997
Median Absolute Deviation (MAD)1
Skewness2.9073888
Sum359.97
Variance28.128304
MonotonicityNot monotonic
2023-12-10T15:43:11.474518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 21
21.0%
0.1 7
 
7.0%
1.0 3
 
3.0%
0.55 3
 
3.0%
0.47 3
 
3.0%
0.15 3
 
3.0%
0.2 2
 
2.0%
6.02 2
 
2.0%
1.2 2
 
2.0%
0.4 2
 
2.0%
Other values (51) 52
52.0%
ValueCountFrequency (%)
0.0 21
21.0%
0.08 1
 
1.0%
0.1 7
 
7.0%
0.15 3
 
3.0%
0.2 2
 
2.0%
0.3 1
 
1.0%
0.4 2
 
2.0%
0.47 3
 
3.0%
0.5 1
 
1.0%
0.54 1
 
1.0%
ValueCountFrequency (%)
36.0 1
1.0%
18.11 1
1.0%
15.1 1
1.0%
14.0 1
1.0%
12.96 1
1.0%
12.0 1
1.0%
11.81 1
1.0%
11.66 1
1.0%
10.68 1
1.0%
10.5 1
1.0%

VPRTN_VALUE
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7564
Minimum0
Maximum7.6
Zeros62
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:11.686315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.325
95-th percentile5.17
Maximum7.6
Range7.6
Interquartile range (IQR)0.325

Descriptive statistics

Standard deviation1.7602103
Coefficient of variation (CV)2.3270893
Kurtosis6.1649616
Mean0.7564
Median Absolute Deviation (MAD)0
Skewness2.6400333
Sum75.64
Variance3.0983404
MonotonicityNot monotonic
2023-12-10T15:43:11.911497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 62
62.0%
0.1 7
 
7.0%
0.47 3
 
3.0%
0.15 3
 
3.0%
0.55 2
 
2.0%
0.4 2
 
2.0%
0.2 2
 
2.0%
3.01 2
 
2.0%
2.55 1
 
1.0%
1.85 1
 
1.0%
Other values (15) 15
 
15.0%
ValueCountFrequency (%)
0.0 62
62.0%
0.1 7
 
7.0%
0.15 3
 
3.0%
0.2 2
 
2.0%
0.3 1
 
1.0%
0.4 2
 
2.0%
0.47 3
 
3.0%
0.5 1
 
1.0%
0.55 2
 
2.0%
0.6 1
 
1.0%
ValueCountFrequency (%)
7.6 1
1.0%
7.2 1
1.0%
6.7 1
1.0%
6.6 1
1.0%
6.5 1
1.0%
5.1 1
1.0%
4.5 1
1.0%
4.07 1
1.0%
3.8 1
1.0%
3.01 2
2.0%

APRTN_VALUE
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
97 
3.01
 
2
0.95
 
1

Length

Max length4
Median length3
Mean length3.03
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 97
97.0%
3.01 2
 
2.0%
0.95 1
 
1.0%

Length

2023-12-10T15:43:12.137562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:12.298949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 97
97.0%
3.01 2
 
2.0%
0.95 1
 
1.0%

FIBR_VALUE
Real number (ℝ)

ZEROS 

Distinct22
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.7351
Minimum0
Maximum17.6
Zeros59
Zeros (%)59.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:12.464847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.8125
95-th percentile2.5
Maximum17.6
Range17.6
Interquartile range (IQR)0.8125

Descriptive statistics

Standard deviation2.0939299
Coefficient of variation (CV)2.8484967
Kurtosis44.267826
Mean0.7351
Median Absolute Deviation (MAD)0
Skewness6.0642663
Sum73.51
Variance4.3845424
MonotonicityNot monotonic
2023-12-10T15:43:12.684659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0.0 59
59.0%
0.1 6
 
6.0%
0.85 3
 
3.0%
0.9 3
 
3.0%
0.75 3
 
3.0%
1.8 3
 
3.0%
2.5 3
 
3.0%
0.78 2
 
2.0%
0.4 2
 
2.0%
0.89 2
 
2.0%
Other values (12) 14
 
14.0%
ValueCountFrequency (%)
0.0 59
59.0%
0.1 6
 
6.0%
0.4 2
 
2.0%
0.45 1
 
1.0%
0.75 3
 
3.0%
0.78 2
 
2.0%
0.8 2
 
2.0%
0.85 3
 
3.0%
0.89 2
 
2.0%
0.9 3
 
3.0%
ValueCountFrequency (%)
17.6 1
 
1.0%
8.0 1
 
1.0%
6.0 1
 
1.0%
5.0 1
 
1.0%
2.5 3
3.0%
1.83 1
 
1.0%
1.8 3
3.0%
1.6 1
 
1.0%
1.43 1
 
1.0%
1.36 1
 
1.0%

MOIST_VALUE
Real number (ℝ)

ZEROS 

Distinct32
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.0835
Minimum0
Maximum139.06
Zeros58
Zeros (%)58.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:12.924846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q341.62
95-th percentile87.9
Maximum139.06
Range139.06
Interquartile range (IQR)41.62

Descriptive statistics

Standard deviation28.792825
Coefficient of variation (CV)1.6854172
Kurtosis3.0804214
Mean17.0835
Median Absolute Deviation (MAD)0
Skewness1.7884278
Sum1708.35
Variance829.02678
MonotonicityNot monotonic
2023-12-10T15:43:13.149767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 58
58.0%
42.4 3
 
3.0%
87.9 3
 
3.0%
41.83 3
 
3.0%
44.2 2
 
2.0%
46.15 2
 
2.0%
41.22 2
 
2.0%
44.3 2
 
2.0%
3.0 2
 
2.0%
41.55 1
 
1.0%
Other values (22) 22
 
22.0%
ValueCountFrequency (%)
0.0 58
58.0%
0.85 1
 
1.0%
1.0 1
 
1.0%
1.22 1
 
1.0%
1.5 1
 
1.0%
1.7 1
 
1.0%
1.74 1
 
1.0%
2.0 1
 
1.0%
3.0 2
 
2.0%
3.1 1
 
1.0%
ValueCountFrequency (%)
139.06 1
 
1.0%
89.0 1
 
1.0%
88.1 1
 
1.0%
87.9 3
3.0%
87.7 1
 
1.0%
65.45 1
 
1.0%
46.75 1
 
1.0%
46.15 2
2.0%
44.75 1
 
1.0%
44.35 1
 
1.0%

ASH_VALUE
Real number (ℝ)

ZEROS 

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2265
Minimum0
Maximum3.7
Zeros63
Zeros (%)63.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:13.378102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.21
95-th percentile1.2145
Maximum3.7
Range3.7
Interquartile range (IQR)0.21

Descriptive statistics

Standard deviation0.54622187
Coefficient of variation (CV)2.4115756
Kurtosis19.199253
Mean0.2265
Median Absolute Deviation (MAD)0
Skewness4.001388
Sum22.65
Variance0.29835833
MonotonicityNot monotonic
2023-12-10T15:43:13.592308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
0.0 63
63.0%
0.1 6
 
6.0%
0.4 3
 
3.0%
0.3 3
 
3.0%
0.29 3
 
3.0%
0.24 2
 
2.0%
0.15 2
 
2.0%
0.2 2
 
2.0%
0.65 2
 
2.0%
0.6 1
 
1.0%
Other values (13) 13
 
13.0%
ValueCountFrequency (%)
0.0 63
63.0%
0.1 6
 
6.0%
0.12 1
 
1.0%
0.15 2
 
2.0%
0.19 1
 
1.0%
0.2 2
 
2.0%
0.24 2
 
2.0%
0.26 1
 
1.0%
0.29 3
 
3.0%
0.3 3
 
3.0%
ValueCountFrequency (%)
3.7 1
1.0%
2.3 1
1.0%
2.2 1
1.0%
1.4 1
1.0%
1.3 1
1.0%
1.21 1
1.0%
1.2 1
1.0%
0.94 1
1.0%
0.8 1
1.0%
0.65 2
2.0%

VITA_VALUE
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.4362
Minimum0
Maximum478.75
Zeros73
Zeros (%)73.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:13.776166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile437
Maximum478.75
Range478.75
Interquartile range (IQR)1

Descriptive statistics

Standard deviation138.18091
Coefficient of variation (CV)2.6352198
Kurtosis4.4770873
Mean52.4362
Median Absolute Deviation (MAD)0
Skewness2.4786841
Sum5243.62
Variance19093.965
MonotonicityNot monotonic
2023-12-10T15:43:13.962930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 73
73.0%
437.0 6
 
6.0%
1.0 4
 
4.0%
478.75 3
 
3.0%
7.33 3
 
3.0%
218.5 2
 
2.0%
3.4 1
 
1.0%
20.0 1
 
1.0%
448.0 1
 
1.0%
173.5 1
 
1.0%
Other values (5) 5
 
5.0%
ValueCountFrequency (%)
0.0 73
73.0%
0.83 1
 
1.0%
1.0 4
 
4.0%
1.25 1
 
1.0%
1.83 1
 
1.0%
3.17 1
 
1.0%
3.4 1
 
1.0%
7.33 3
 
3.0%
20.0 1
 
1.0%
70.4 1
 
1.0%
ValueCountFrequency (%)
478.75 3
3.0%
448.0 1
 
1.0%
437.0 6
6.0%
218.5 2
 
2.0%
173.5 1
 
1.0%
70.4 1
 
1.0%
20.0 1
 
1.0%
7.33 3
3.0%
3.4 1
 
1.0%
3.17 1
 
1.0%

RTNOL_VALUE
Categorical

IMBALANCE 

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
90 
437.0
 
6
218.5
 
2
20.0
 
1
448.0
 
1

Length

Max length5
Median length3
Mean length3.19
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 90
90.0%
437.0 6
 
6.0%
218.5 2
 
2.0%
20.0 1
 
1.0%
448.0 1
 
1.0%

Length

2023-12-10T15:43:14.139378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:14.318572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 90
90.0%
437.0 6
 
6.0%
218.5 2
 
2.0%
20.0 1
 
1.0%
448.0 1
 
1.0%

BCRT_VALUE
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean92.536
Minimum0
Maximum2872.5
Zeros84
Zeros (%)84.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:14.459166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile44
Maximum2872.5
Range2872.5
Interquartile range (IQR)0

Descriptive statistics

Standard deviation493.19557
Coefficient of variation (CV)5.3297698
Kurtosis29.410662
Mean92.536
Median Absolute Deviation (MAD)0
Skewness5.534402
Sum9253.6
Variance243241.87
MonotonicityNot monotonic
2023-12-10T15:43:14.622004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 84
84.0%
2872.5 3
 
3.0%
44.0 3
 
3.0%
4.5 2
 
2.0%
6.0 2
 
2.0%
20.4 1
 
1.0%
420.2 1
 
1.0%
19.0 1
 
1.0%
11.0 1
 
1.0%
5.0 1
 
1.0%
ValueCountFrequency (%)
0.0 84
84.0%
4.5 2
 
2.0%
5.0 1
 
1.0%
6.0 2
 
2.0%
7.5 1
 
1.0%
11.0 1
 
1.0%
19.0 1
 
1.0%
20.4 1
 
1.0%
44.0 3
 
3.0%
420.2 1
 
1.0%
ValueCountFrequency (%)
2872.5 3
3.0%
420.2 1
 
1.0%
44.0 3
3.0%
20.4 1
 
1.0%
19.0 1
 
1.0%
11.0 1
 
1.0%
7.5 1
 
1.0%
6.0 2
2.0%
5.0 1
 
1.0%
4.5 2
2.0%

PRCSFD_NM
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T15:43:14.973110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length22
Mean length13.97
Min length2

Characters and Unicode

Total characters1397
Distinct characters244
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)96.0%

Sample

1st row밴쯔 덤플링
2nd row꽃생차
3rd row(냉)시나몬레이즌베이글
4th rowXtra concentrate(P2-formula| Canada)
5th row낫토균 발효 약콩효소
ValueCountFrequency (%)
시리얼 8
 
4.6%
포스트 7
 
4.0%
풀무원 5
 
2.9%
라면|봉지면 5
 
2.9%
씨비엘 4
 
2.3%
130ml 4
 
2.3%
식물성유산균 4
 
2.3%
환자용식품|환자용식품 4
 
2.3%
그린비아 3
 
1.7%
코코볼 3
 
1.7%
Other values (121) 127
73.0%
2023-12-10T15:43:15.565428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
| 120
 
8.6%
75
 
5.4%
( 47
 
3.4%
) 47
 
3.4%
식 43
 
3.1%
버 30
 
2.1%
거 30
 
2.1%
차 26
 
1.9%
스 24
 
1.7%
형 23
 
1.6%
Other values (234) 932
66.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1009
72.2%
Math Symbol 120
 
8.6%
Space Separator 75
 
5.4%
Decimal Number 51
 
3.7%
Open Punctuation 47
 
3.4%
Close Punctuation 47
 
3.4%
Lowercase Letter 35
 
2.5%
Dash Punctuation 5
 
0.4%
Uppercase Letter 5
 
0.4%
Other Punctuation 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 43
 
4.3%
버 30
 
3.0%
거 30
 
3.0%
차 26
 
2.6%
스 24
 
2.4%
형 23
 
2.3%
면 23
 
2.3%
이 21
 
2.1%
제 21
 
2.1%
고 17
 
1.7%
Other values (205) 751
74.4%
Lowercase Letter
ValueCountFrequency (%)
a 6
17.1%
l 5
14.3%
m 5
14.3%
t 3
8.6%
r 3
8.6%
n 3
8.6%
e 2
 
5.7%
o 2
 
5.7%
c 2
 
5.7%
f 1
 
2.9%
Other values (3) 3
8.6%
Decimal Number
ValueCountFrequency (%)
2 15
29.4%
1 14
27.5%
3 11
21.6%
0 8
15.7%
6 2
 
3.9%
5 1
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
C 2
40.0%
P 1
20.0%
X 1
20.0%
M 1
20.0%
Math Symbol
ValueCountFrequency (%)
| 120
100.0%
Space Separator
ValueCountFrequency (%)
75
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
& 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1009
72.2%
Common 348
 
24.9%
Latin 40
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 43
 
4.3%
버 30
 
3.0%
거 30
 
3.0%
차 26
 
2.6%
스 24
 
2.4%
형 23
 
2.3%
면 23
 
2.3%
이 21
 
2.1%
제 21
 
2.1%
고 17
 
1.7%
Other values (205) 751
74.4%
Latin
ValueCountFrequency (%)
a 6
15.0%
l 5
12.5%
m 5
12.5%
t 3
7.5%
r 3
7.5%
n 3
7.5%
C 2
 
5.0%
e 2
 
5.0%
o 2
 
5.0%
c 2
 
5.0%
Other values (7) 7
17.5%
Common
ValueCountFrequency (%)
| 120
34.5%
75
21.6%
( 47
 
13.5%
) 47
 
13.5%
2 15
 
4.3%
1 14
 
4.0%
3 11
 
3.2%
0 8
 
2.3%
- 5
 
1.4%
& 3
 
0.9%
Other values (2) 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1009
72.2%
ASCII 388
 
27.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
| 120
30.9%
75
19.3%
( 47
 
12.1%
) 47
 
12.1%
2 15
 
3.9%
1 14
 
3.6%
3 11
 
2.8%
0 8
 
2.1%
a 6
 
1.5%
l 5
 
1.3%
Other values (19) 40
 
10.3%
Hangul
ValueCountFrequency (%)
식 43
 
4.3%
버 30
 
3.0%
거 30
 
3.0%
차 26
 
2.6%
스 24
 
2.4%
형 23
 
2.3%
면 23
 
2.3%
이 21
 
2.1%
제 21
 
2.1%
고 17
 
1.7%
Other values (205) 751
74.4%

VITD_VALUE
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2693
Minimum0
Maximum3.58
Zeros90
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:15.780032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3.336
Maximum3.58
Range3.58
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.86745565
Coefficient of variation (CV)3.2211498
Kurtosis8.9091365
Mean0.2693
Median Absolute Deviation (MAD)0
Skewness3.1951281
Sum26.93
Variance0.7524793
MonotonicityNot monotonic
2023-12-10T15:43:15.989584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 90
90.0%
3.45 4
 
4.0%
3.33 1
 
1.0%
3.58 1
 
1.0%
1.83 1
 
1.0%
0.91 1
 
1.0%
1.73 1
 
1.0%
1.75 1
 
1.0%
ValueCountFrequency (%)
0.0 90
90.0%
0.91 1
 
1.0%
1.73 1
 
1.0%
1.75 1
 
1.0%
1.83 1
 
1.0%
3.33 1
 
1.0%
3.45 4
 
4.0%
3.58 1
 
1.0%
ValueCountFrequency (%)
3.58 1
 
1.0%
3.45 4
 
4.0%
3.33 1
 
1.0%
1.83 1
 
1.0%
1.75 1
 
1.0%
1.73 1
 
1.0%
0.91 1
 
1.0%
0.0 90
90.0%

VITE_VALUE
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6383
Minimum0
Maximum8.3
Zeros61
Zeros (%)61.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:16.261831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.2075
95-th percentile5.8
Maximum8.3
Range8.3
Interquartile range (IQR)0.2075

Descriptive statistics

Standard deviation1.7321786
Coefficient of variation (CV)2.7137374
Kurtosis9.4614486
Mean0.6383
Median Absolute Deviation (MAD)0
Skewness3.1804708
Sum63.83
Variance3.0004425
MonotonicityNot monotonic
2023-12-10T15:43:16.479495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 61
61.0%
0.26 5
 
5.0%
5.8 5
 
5.0%
0.05 3
 
3.0%
0.3 3
 
3.0%
1.0 3
 
3.0%
2.9 3
 
3.0%
0.09 2
 
2.0%
8.3 2
 
2.0%
0.06 2
 
2.0%
Other values (9) 11
 
11.0%
ValueCountFrequency (%)
0.0 61
61.0%
0.04 1
 
1.0%
0.05 3
 
3.0%
0.06 2
 
2.0%
0.08 1
 
1.0%
0.09 2
 
2.0%
0.14 2
 
2.0%
0.15 1
 
1.0%
0.19 2
 
2.0%
0.26 5
 
5.0%
ValueCountFrequency (%)
8.3 2
 
2.0%
5.8 5
5.0%
2.9 3
3.0%
1.3 1
 
1.0%
1.0 3
3.0%
0.9 1
 
1.0%
0.46 1
 
1.0%
0.3 3
3.0%
0.29 1
 
1.0%
0.26 5
5.0%

VITK_VALUE
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5581
Minimum0
Maximum7.2
Zeros71
Zeros (%)71.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:16.694586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.525
95-th percentile3.4
Maximum7.2
Range7.2
Interquartile range (IQR)0.525

Descriptive statistics

Standard deviation1.30963
Coefficient of variation (CV)2.3465866
Kurtosis13.016072
Mean0.5581
Median Absolute Deviation (MAD)0
Skewness3.3898178
Sum55.81
Variance1.7151307
MonotonicityNot monotonic
2023-12-10T15:43:16.893143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 71
71.0%
2.3 3
 
3.0%
1.6 3
 
3.0%
0.7 2
 
2.0%
1.2 2
 
2.0%
0.25 2
 
2.0%
1.75 2
 
2.0%
0.6 2
 
2.0%
3.4 2
 
2.0%
7.2 2
 
2.0%
Other values (9) 9
 
9.0%
ValueCountFrequency (%)
0.0 71
71.0%
0.25 2
 
2.0%
0.4 1
 
1.0%
0.5 1
 
1.0%
0.6 2
 
2.0%
0.7 2
 
2.0%
0.75 1
 
1.0%
0.9 1
 
1.0%
0.99 1
 
1.0%
1.0 1
 
1.0%
ValueCountFrequency (%)
7.2 2
2.0%
4.4 1
 
1.0%
3.95 1
 
1.0%
3.4 2
2.0%
2.3 3
3.0%
1.75 2
2.0%
1.6 3
3.0%
1.2 2
2.0%
1.02 1
 
1.0%
1.0 1
 
1.0%

VITC_VALUE
Real number (ℝ)

ZEROS 

Distinct37
Distinct (%)37.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.7371
Minimum0
Maximum254
Zeros56
Zeros (%)56.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:17.102864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q312.6625
95-th percentile75.55
Maximum254
Range254
Interquartile range (IQR)12.6625

Descriptive statistics

Standard deviation39.613199
Coefficient of variation (CV)2.5171854
Kurtosis17.864295
Mean15.7371
Median Absolute Deviation (MAD)0
Skewness3.9817228
Sum1573.71
Variance1569.2055
MonotonicityNot monotonic
2023-12-10T15:43:17.334084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0.0 56
56.0%
23.05 3
 
3.0%
0.35 2
 
2.0%
1.05 2
 
2.0%
19.15 2
 
2.0%
2.85 2
 
2.0%
33.8 2
 
2.0%
12.25 2
 
2.0%
2.2 1
 
1.0%
63.6 1
 
1.0%
Other values (27) 27
27.0%
ValueCountFrequency (%)
0.0 56
56.0%
0.2 1
 
1.0%
0.35 2
 
2.0%
0.52 1
 
1.0%
0.62 1
 
1.0%
1.05 2
 
2.0%
1.8 1
 
1.0%
2.1 1
 
1.0%
2.2 1
 
1.0%
2.85 2
 
2.0%
ValueCountFrequency (%)
254.0 1
1.0%
183.0 1
1.0%
172.0 1
1.0%
127.0 1
1.0%
86.0 1
1.0%
75.0 1
1.0%
63.6 1
1.0%
58.5 1
1.0%
57.0 1
1.0%
46.0 1
1.0%

VITB1_VALUE
Real number (ℝ)

ZEROS 

Distinct15
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1074
Minimum0
Maximum1.45
Zeros59
Zeros (%)59.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:17.512965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.01
95-th percentile0.8
Maximum1.45
Range1.45
Interquartile range (IQR)0.01

Descriptive statistics

Standard deviation0.28946352
Coefficient of variation (CV)2.6951911
Kurtosis7.7563434
Mean0.1074
Median Absolute Deviation (MAD)0
Skewness2.8772853
Sum10.74
Variance0.083789131
MonotonicityNot monotonic
2023-12-10T15:43:17.705749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
0.0 59
59.0%
0.01 23
 
23.0%
0.02 4
 
4.0%
0.8 3
 
3.0%
0.41 1
 
1.0%
0.76 1
 
1.0%
1.24 1
 
1.0%
1.45 1
 
1.0%
0.85 1
 
1.0%
0.73 1
 
1.0%
Other values (5) 5
 
5.0%
ValueCountFrequency (%)
0.0 59
59.0%
0.01 23
 
23.0%
0.02 4
 
4.0%
0.04 1
 
1.0%
0.4 1
 
1.0%
0.41 1
 
1.0%
0.43 1
 
1.0%
0.69 1
 
1.0%
0.73 1
 
1.0%
0.76 1
 
1.0%
ValueCountFrequency (%)
1.45 1
 
1.0%
1.24 1
 
1.0%
1.03 1
 
1.0%
0.85 1
 
1.0%
0.8 3
3.0%
0.76 1
 
1.0%
0.73 1
 
1.0%
0.69 1
 
1.0%
0.43 1
 
1.0%
0.41 1
 
1.0%

VITB2_VALUE
Real number (ℝ)

ZEROS 

Distinct18
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1118
Minimum0
Maximum1.44
Zeros58
Zeros (%)58.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:17.888210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.02
95-th percentile0.95
Maximum1.44
Range1.44
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.2944791
Coefficient of variation (CV)2.6339812
Kurtosis7.1996348
Mean0.1118
Median Absolute Deviation (MAD)0
Skewness2.8466409
Sum11.18
Variance0.086717939
MonotonicityNot monotonic
2023-12-10T15:43:18.081049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 58
58.0%
0.02 13
 
13.0%
0.01 7
 
7.0%
0.03 3
 
3.0%
0.04 3
 
3.0%
0.9 2
 
2.0%
0.95 2
 
2.0%
0.07 2
 
2.0%
0.45 1
 
1.0%
0.58 1
 
1.0%
Other values (8) 8
 
8.0%
ValueCountFrequency (%)
0.0 58
58.0%
0.01 7
 
7.0%
0.02 13
 
13.0%
0.03 3
 
3.0%
0.04 3
 
3.0%
0.07 2
 
2.0%
0.09 1
 
1.0%
0.1 1
 
1.0%
0.45 1
 
1.0%
0.48 1
 
1.0%
ValueCountFrequency (%)
1.44 1
1.0%
1.11 1
1.0%
1.0 1
1.0%
0.99 1
1.0%
0.95 2
2.0%
0.9 2
2.0%
0.58 1
1.0%
0.56 1
1.0%
0.48 1
1.0%
0.45 1
1.0%

NIACN_VALUE
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3837
Minimum0
Maximum20.7
Zeros58
Zeros (%)58.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:18.582976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.2025
95-th percentile10.2075
Maximum20.7
Range20.7
Interquartile range (IQR)0.2025

Descriptive statistics

Standard deviation3.6989853
Coefficient of variation (CV)2.6732567
Kurtosis10.544582
Mean1.3837
Median Absolute Deviation (MAD)0
Skewness3.1718683
Sum138.37
Variance13.682492
MonotonicityNot monotonic
2023-12-10T15:43:18.902390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0.0 58
58.0%
0.2 4
 
4.0%
0.09 3
 
3.0%
0.82 3
 
3.0%
0.03 3
 
3.0%
0.23 2
 
2.0%
0.3 2
 
2.0%
1.25 2
 
2.0%
10.0 2
 
2.0%
0.05 1
 
1.0%
Other values (20) 20
 
20.0%
ValueCountFrequency (%)
0.0 58
58.0%
0.02 1
 
1.0%
0.03 3
 
3.0%
0.05 1
 
1.0%
0.06 1
 
1.0%
0.07 1
 
1.0%
0.09 3
 
3.0%
0.11 1
 
1.0%
0.12 1
 
1.0%
0.13 1
 
1.0%
ValueCountFrequency (%)
20.7 1
1.0%
16.8 1
1.0%
10.8 1
1.0%
10.6 1
1.0%
10.35 1
1.0%
10.2 1
1.0%
10.0 2
2.0%
8.12 1
1.0%
6.06 1
1.0%
5.78 1
1.0%

VITB6_VALUE
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.0967
Minimum0
Maximum1.3
Zeros62
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:19.189808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.02
95-th percentile0.8
Maximum1.3
Range1.3
Interquartile range (IQR)0.02

Descriptive statistics

Standard deviation0.25982922
Coefficient of variation (CV)2.6869619
Kurtosis9.8760405
Mean0.0967
Median Absolute Deviation (MAD)0
Skewness3.1606813
Sum9.67
Variance0.067511222
MonotonicityNot monotonic
2023-12-10T15:43:19.973880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 62
62.0%
0.02 8
 
8.0%
0.01 7
 
7.0%
0.8 5
 
5.0%
0.05 3
 
3.0%
0.03 3
 
3.0%
0.04 3
 
3.0%
0.4 3
 
3.0%
1.3 2
 
2.0%
0.41 1
 
1.0%
Other values (3) 3
 
3.0%
ValueCountFrequency (%)
0.0 62
62.0%
0.01 7
 
7.0%
0.02 8
 
8.0%
0.03 3
 
3.0%
0.04 3
 
3.0%
0.05 3
 
3.0%
0.12 1
 
1.0%
0.18 1
 
1.0%
0.4 3
 
3.0%
0.41 1
 
1.0%
ValueCountFrequency (%)
1.3 2
 
2.0%
0.8 5
5.0%
0.57 1
 
1.0%
0.41 1
 
1.0%
0.4 3
3.0%
0.18 1
 
1.0%
0.12 1
 
1.0%
0.05 3
3.0%
0.04 3
3.0%
0.03 3
3.0%

FOLATE_VALUE
Real number (ℝ)

ZEROS 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.6266
Minimum0
Maximum19
Zeros67
Zeros (%)67.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:20.270257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.5
95-th percentile19
Maximum19
Range19
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation5.1749779
Coefficient of variation (CV)1.9702193
Kurtosis4.6343717
Mean2.6266
Median Absolute Deviation (MAD)0
Skewness2.3207358
Sum262.66
Variance26.780396
MonotonicityNot monotonic
2023-12-10T15:43:20.630754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
0.0 67
67.0%
19.0 7
 
7.0%
1.5 4
 
4.0%
5.0 4
 
4.0%
3.5 4
 
4.0%
9.5 3
 
3.0%
7.5 2
 
2.0%
8.0 2
 
2.0%
3.0 2
 
2.0%
4.0 2
 
2.0%
Other values (3) 3
 
3.0%
ValueCountFrequency (%)
0.0 67
67.0%
1.5 4
 
4.0%
3.0 2
 
2.0%
3.12 1
 
1.0%
3.5 4
 
4.0%
4.0 2
 
2.0%
5.0 4
 
4.0%
6.24 1
 
1.0%
6.8 1
 
1.0%
7.5 2
 
2.0%
ValueCountFrequency (%)
19.0 7
7.0%
9.5 3
3.0%
8.0 2
 
2.0%
7.5 2
 
2.0%
6.8 1
 
1.0%
6.24 1
 
1.0%
5.0 4
4.0%
4.0 2
 
2.0%
3.5 4
4.0%
3.12 1
 
1.0%

VITB12_VALUE
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.5668
Minimum0
Maximum20.7
Zeros87
Zeros (%)87.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:20.847494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.0085
Maximum20.7
Range20.7
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.3646764
Coefficient of variation (CV)4.1719768
Kurtosis54.101862
Mean0.5668
Median Absolute Deviation (MAD)0
Skewness6.7520333
Sum56.68
Variance5.5916947
MonotonicityNot monotonic
2023-12-10T15:43:21.012745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0.0 87
87.0%
5.17 3
 
3.0%
2.59 2
 
2.0%
0.04 1
 
1.0%
20.7 1
 
1.0%
5.0 1
 
1.0%
5.36 1
 
1.0%
2.73 1
 
1.0%
1.37 1
 
1.0%
0.74 1
 
1.0%
ValueCountFrequency (%)
0.0 87
87.0%
0.04 1
 
1.0%
0.05 1
 
1.0%
0.74 1
 
1.0%
1.37 1
 
1.0%
2.59 2
 
2.0%
2.73 1
 
1.0%
5.0 1
 
1.0%
5.17 3
 
3.0%
5.36 1
 
1.0%
ValueCountFrequency (%)
20.7 1
 
1.0%
5.36 1
 
1.0%
5.17 3
3.0%
5.0 1
 
1.0%
2.73 1
 
1.0%
2.59 2
2.0%
1.37 1
 
1.0%
0.74 1
 
1.0%
0.05 1
 
1.0%
0.04 1
 
1.0%

PRCSFD_CTGRY_CODE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
AF001
100 

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 (%)
AF001 100
100.0%

Length

2023-12-10T15:43:21.175249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:21.331179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
af001 100
100.0%

PANTO_VALUE
Real number (ℝ)

ZEROS 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3787
Minimum0
Maximum34.9
Zeros76
Zeros (%)76.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:21.471889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.2
Maximum34.9
Range34.9
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.4877629
Coefficient of variation (CV)9.2098308
Kurtosis99.909844
Mean0.3787
Median Absolute Deviation (MAD)0
Skewness9.9933381
Sum37.87
Variance12.16449
MonotonicityNot monotonic
2023-12-10T15:43:21.672286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0.0 76
76.0%
0.08 5
 
5.0%
0.2 3
 
3.0%
0.12 3
 
3.0%
0.07 3
 
3.0%
0.06 3
 
3.0%
0.05 2
 
2.0%
0.39 1
 
1.0%
0.44 1
 
1.0%
34.9 1
 
1.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
0.0 76
76.0%
0.05 2
 
2.0%
0.06 3
 
3.0%
0.07 3
 
3.0%
0.08 5
 
5.0%
0.11 1
 
1.0%
0.12 3
 
3.0%
0.18 1
 
1.0%
0.2 3
 
3.0%
0.39 1
 
1.0%
ValueCountFrequency (%)
34.9 1
 
1.0%
0.44 1
 
1.0%
0.39 1
 
1.0%
0.2 3
3.0%
0.18 1
 
1.0%
0.12 3
3.0%
0.11 1
 
1.0%
0.08 5
5.0%
0.07 3
3.0%
0.06 3
3.0%

BIOTIN_VALUE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

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 (%)
0 100
100.0%

Length

2023-12-10T15:43:21.891539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:22.036069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

CA_VALUE
Real number (ℝ)

ZEROS 

Distinct25
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.6661
Minimum0
Maximum221
Zeros59
Zeros (%)59.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:22.186919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q34.5
95-th percentile33.05
Maximum221
Range221
Interquartile range (IQR)4.5

Descriptive statistics

Standard deviation29.508227
Coefficient of variation (CV)3.405018
Kurtosis37.944202
Mean8.6661
Median Absolute Deviation (MAD)0
Skewness5.9325781
Sum866.61
Variance870.73545
MonotonicityNot monotonic
2023-12-10T15:43:22.385078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
0.0 59
59.0%
2.0 7
 
7.0%
2.5 4
 
4.0%
12.0 3
 
3.0%
7.0 3
 
3.0%
4.0 3
 
3.0%
11.0 2
 
2.0%
3.0 2
 
2.0%
33.0 1
 
1.0%
221.0 1
 
1.0%
Other values (15) 15
 
15.0%
ValueCountFrequency (%)
0.0 59
59.0%
2.0 7
 
7.0%
2.5 4
 
4.0%
3.0 2
 
2.0%
4.0 3
 
3.0%
6.0 1
 
1.0%
6.2 1
 
1.0%
7.0 3
 
3.0%
8.0 1
 
1.0%
9.35 1
 
1.0%
ValueCountFrequency (%)
221.0 1
1.0%
179.66 1
1.0%
61.0 1
1.0%
48.0 1
1.0%
34.0 1
1.0%
33.0 1
1.0%
31.9 1
1.0%
26.0 1
1.0%
23.0 1
1.0%
21.0 1
1.0%

VCA_VALUE
Real number (ℝ)

ZEROS 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.4311
Minimum0
Maximum221
Zeros62
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:22.551669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33.25
95-th percentile26.295
Maximum221
Range221
Interquartile range (IQR)3.25

Descriptive statistics

Standard deviation28.782086
Coefficient of variation (CV)3.8731932
Kurtosis43.228755
Mean7.4311
Median Absolute Deviation (MAD)0
Skewness6.4351751
Sum743.11
Variance828.40847
MonotonicityNot monotonic
2023-12-10T15:43:22.721084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
0.0 62
62.0%
2.0 7
 
7.0%
7.0 3
 
3.0%
4.0 3
 
3.0%
11.0 2
 
2.0%
12.0 2
 
2.0%
3.0 2
 
2.0%
1.25 2
 
2.0%
2.5 2
 
2.0%
16.5 1
 
1.0%
Other values (14) 14
 
14.0%
ValueCountFrequency (%)
0.0 62
62.0%
1.25 2
 
2.0%
2.0 7
 
7.0%
2.5 2
 
2.0%
3.0 2
 
2.0%
4.0 3
 
3.0%
6.0 1
 
1.0%
6.2 1
 
1.0%
7.0 3
 
3.0%
8.0 1
 
1.0%
ValueCountFrequency (%)
221.0 1
1.0%
179.66 1
1.0%
34.0 1
1.0%
33.0 1
1.0%
31.9 1
1.0%
26.0 1
1.0%
23.0 1
1.0%
21.0 1
1.0%
16.5 1
1.0%
12.0 2
2.0%

ACA_VALUE
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
97 
1.25
 
2
12.0
 
1

Length

Max length4
Median length3
Mean length3.03
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 97
97.0%
1.25 2
 
2.0%
12.0 1
 
1.0%

Length

2023-12-10T15:43:22.917761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:23.061343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 97
97.0%
1.25 2
 
2.0%
12.0 1
 
1.0%

PHOSPHO_VALUE
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.5075
Minimum0
Maximum648
Zeros57
Zeros (%)57.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:23.206627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q310
95-th percentile93.68
Maximum648
Range648
Interquartile range (IQR)10

Descriptive statistics

Standard deviation73.509429
Coefficient of variation (CV)3.4178509
Kurtosis54.565682
Mean21.5075
Median Absolute Deviation (MAD)0
Skewness6.7939758
Sum2150.75
Variance5403.6361
MonotonicityNot monotonic
2023-12-10T15:43:23.410635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
0.0 57
57.0%
6.0 4
 
4.0%
46.5 3
 
3.0%
14.0 3
 
3.0%
10.0 3
 
3.0%
12.0 3
 
3.0%
3.5 3
 
3.0%
7.5 3
 
3.0%
4.0 2
 
2.0%
5.0 2
 
2.0%
Other values (17) 17
 
17.0%
ValueCountFrequency (%)
0.0 57
57.0%
3.0 1
 
1.0%
3.5 3
 
3.0%
4.0 2
 
2.0%
5.0 2
 
2.0%
5.4 1
 
1.0%
6.0 4
 
4.0%
7.5 3
 
3.0%
7.7 1
 
1.0%
10.0 3
 
3.0%
ValueCountFrequency (%)
648.0 1
1.0%
223.0 1
1.0%
187.0 1
1.0%
153.4 1
1.0%
106.6 1
1.0%
93.0 1
1.0%
81.0 1
1.0%
76.0 1
1.0%
68.85 1
1.0%
54.0 1
1.0%

NA_VALUE
Real number (ℝ)

ZEROS 

Distinct63
Distinct (%)63.6%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean287.48152
Minimum0
Maximum4129.92
Zeros20
Zeros (%)20.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:23.637340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.25
median18.5
Q3208.1
95-th percentile1755.648
Maximum4129.92
Range4129.92
Interquartile range (IQR)206.85

Descriptive statistics

Standard deviation639.40756
Coefficient of variation (CV)2.2241693
Kurtosis14.230015
Mean287.48152
Median Absolute Deviation (MAD)18.5
Skewness3.4031831
Sum28460.67
Variance408842.03
MonotonicityNot monotonic
2023-12-10T15:43:23.877439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 20
 
20.0%
2.0 5
 
5.0%
1.0 5
 
5.0%
135.0 3
 
3.0%
1758.24 3
 
3.0%
3.0 3
 
3.0%
18.5 2
 
2.0%
23.0 2
 
2.0%
14.0 2
 
2.0%
1380.0 1
 
1.0%
Other values (53) 53
53.0%
ValueCountFrequency (%)
0.0 20
20.0%
1.0 5
 
5.0%
1.5 1
 
1.0%
1.55 1
 
1.0%
2.0 5
 
5.0%
3.0 3
 
3.0%
3.1 1
 
1.0%
4.0 1
 
1.0%
6.9 1
 
1.0%
7.5 1
 
1.0%
ValueCountFrequency (%)
4129.92 1
 
1.0%
2415.0 1
 
1.0%
1758.24 3
3.0%
1755.36 1
 
1.0%
1714.0 1
 
1.0%
1504.0 1
 
1.0%
1380.0 1
 
1.0%
1376.0 1
 
1.0%
878.0 1
 
1.0%
737.14 1
 
1.0%

CHLOR_VALUE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

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 (%)
0 100
100.0%

Length

2023-12-10T15:43:24.102093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:24.279408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

POTSSM_VALUE
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.8538
Minimum0
Maximum764
Zeros59
Zeros (%)59.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:24.435995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q366
95-th percentile146.3
Maximum764
Range764
Interquartile range (IQR)66

Descriptive statistics

Standard deviation113.86694
Coefficient of variation (CV)2.3307694
Kurtosis30.410588
Mean48.8538
Median Absolute Deviation (MAD)0
Skewness5.1396958
Sum4885.38
Variance12965.68
MonotonicityNot monotonic
2023-12-10T15:43:24.652216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
0.0 59
59.0%
97.5 3
 
3.0%
65.0 3
 
3.0%
93.5 2
 
2.0%
35.5 2
 
2.0%
98.0 2
 
2.0%
764.0 2
 
2.0%
40.0 1
 
1.0%
75.9 1
 
1.0%
101.0 1
 
1.0%
Other values (24) 24
24.0%
ValueCountFrequency (%)
0.0 59
59.0%
17.5 1
 
1.0%
32.5 1
 
1.0%
35.5 2
 
2.0%
38.5 1
 
1.0%
40.0 1
 
1.0%
42.5 1
 
1.0%
49.0 1
 
1.0%
56.5 1
 
1.0%
57.0 1
 
1.0%
ValueCountFrequency (%)
764.0 2
2.0%
199.94 1
1.0%
181.0 1
1.0%
171.0 1
1.0%
145.0 1
1.0%
130.0 1
1.0%
129.0 1
1.0%
118.5 1
1.0%
115.0 1
1.0%
113.5 1
1.0%

MGM_VALUE
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3672
Minimum0
Maximum53.56
Zeros88
Zeros (%)88.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:24.832164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4.5
Maximum53.56
Range53.56
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.5689472
Coefficient of variation (CV)4.8046717
Kurtosis48.646188
Mean1.3672
Median Absolute Deviation (MAD)0
Skewness6.7862256
Sum136.72
Variance43.151067
MonotonicityNot monotonic
2023-12-10T15:43:24.989385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0.0 88
88.0%
3.5 3
 
3.0%
4.5 2
 
2.0%
8.0 2
 
2.0%
4.0 2
 
2.0%
3.0 1
 
1.0%
36.66 1
 
1.0%
53.56 1
 
1.0%
ValueCountFrequency (%)
0.0 88
88.0%
3.0 1
 
1.0%
3.5 3
 
3.0%
4.0 2
 
2.0%
4.5 2
 
2.0%
8.0 2
 
2.0%
36.66 1
 
1.0%
53.56 1
 
1.0%
ValueCountFrequency (%)
53.56 1
 
1.0%
36.66 1
 
1.0%
8.0 2
 
2.0%
4.5 2
 
2.0%
4.0 2
 
2.0%
3.5 3
 
3.0%
3.0 1
 
1.0%
0.0 88
88.0%

ENTRPS_NM
Categorical

Distinct23
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
거버
31 
동서식품
14 
씨제이제일제당
7 
정식품
7 
풀무원
6 
Other values (18)
35 

Length

Max length10
Median length9
Mean length3.71
Min length2

Unique

Unique10 ?
Unique (%)10.0%

Sample

1st row(주)서원푸드
2nd row(주)경신바이오
3rd row㈜ 에이피홀딩스
4th row(주)네이처텍
5th row(주)네이처텍

Common Values

ValueCountFrequency (%)
거버 31
31.0%
동서식품 14
14.0%
씨제이제일제당 7
 
7.0%
정식품 7
 
7.0%
풀무원 6
 
6.0%
동원산업 5
 
5.0%
삼양식품 5
 
5.0%
빙그레 4
 
4.0%
일양약품 3
 
3.0%
삼강 2
 
2.0%
Other values (13) 16
16.0%

Length

2023-12-10T15:43:25.177314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
거버 31
30.1%
동서식품 14
13.6%
씨제이제일제당 7
 
6.8%
정식품 7
 
6.8%
풀무원 6
 
5.8%
동원산업 5
 
4.9%
삼양식품 5
 
4.9%
빙그레 4
 
3.9%
일양약품 3
 
2.9%
주)네이처텍 2
 
1.9%
Other values (15) 19
18.4%

IRON_VALUE
Real number (ℝ)

ZEROS 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9072
Minimum0
Maximum12.35
Zeros59
Zeros (%)59.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:25.370243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.1925
95-th percentile6.41
Maximum12.35
Range12.35
Interquartile range (IQR)0.1925

Descriptive statistics

Standard deviation2.3951846
Coefficient of variation (CV)2.6401947
Kurtosis11.245405
Mean0.9072
Median Absolute Deviation (MAD)0
Skewness3.3049022
Sum90.72
Variance5.7369093
MonotonicityNot monotonic
2023-12-10T15:43:25.571217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
0.0 59
59.0%
0.12 4
 
4.0%
0.11 3
 
3.0%
0.1 3
 
3.0%
0.25 2
 
2.0%
1.4 2
 
2.0%
0.49 2
 
2.0%
0.19 2
 
2.0%
0.14 2
 
2.0%
0.15 2
 
2.0%
Other values (18) 19
 
19.0%
ValueCountFrequency (%)
0.0 59
59.0%
0.1 3
 
3.0%
0.11 3
 
3.0%
0.12 4
 
4.0%
0.14 2
 
2.0%
0.15 2
 
2.0%
0.19 2
 
2.0%
0.2 1
 
1.0%
0.24 1
 
1.0%
0.25 2
 
2.0%
ValueCountFrequency (%)
12.35 2
2.0%
9.35 1
1.0%
6.9 1
1.0%
6.6 1
1.0%
6.4 1
1.0%
6.3 1
1.0%
5.0 1
1.0%
3.7 1
1.0%
3.45 1
1.0%
3.4 1
1.0%

VIRON_VALUE
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)26.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8998
Minimum0
Maximum12.35
Zeros60
Zeros (%)60.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:25.774617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.19
95-th percentile6.41
Maximum12.35
Range12.35
Interquartile range (IQR)0.19

Descriptive statistics

Standard deviation2.3971119
Coefficient of variation (CV)2.6640497
Kurtosis11.242054
Mean0.8998
Median Absolute Deviation (MAD)0
Skewness3.3057153
Sum89.98
Variance5.7461454
MonotonicityNot monotonic
2023-12-10T15:43:26.006588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
0.0 60
60.0%
0.25 4
 
4.0%
0.12 4
 
4.0%
0.1 3
 
3.0%
0.11 3
 
3.0%
0.15 2
 
2.0%
0.14 2
 
2.0%
0.19 2
 
2.0%
12.35 2
 
2.0%
1.4 2
 
2.0%
Other values (16) 16
 
16.0%
ValueCountFrequency (%)
0.0 60
60.0%
0.1 3
 
3.0%
0.11 3
 
3.0%
0.12 4
 
4.0%
0.14 2
 
2.0%
0.15 2
 
2.0%
0.19 2
 
2.0%
0.2 1
 
1.0%
0.24 1
 
1.0%
0.25 4
 
4.0%
ValueCountFrequency (%)
12.35 2
2.0%
9.35 1
1.0%
6.9 1
1.0%
6.6 1
1.0%
6.4 1
1.0%
6.3 1
1.0%
5.0 1
1.0%
3.7 1
1.0%
3.45 1
1.0%
3.4 1
1.0%

AIRON_VALUE
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
97 
0.25
 
2
0.26
 
1

Length

Max length4
Median length3
Mean length3.03
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 97
97.0%
0.25 2
 
2.0%
0.26 1
 
1.0%

Length

2023-12-10T15:43:26.232471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:26.401848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 97
97.0%
0.25 2
 
2.0%
0.26 1
 
1.0%

ZINC_VALUE
Real number (ℝ)

ZEROS 

Distinct21
Distinct (%)21.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.3966
Minimum0
Maximum5.7
Zeros61
Zeros (%)61.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:26.560773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.065
95-th percentile3.1705
Maximum5.7
Range5.7
Interquartile range (IQR)0.065

Descriptive statistics

Standard deviation1.1737475
Coefficient of variation (CV)2.9595248
Kurtosis11.973278
Mean0.3966
Median Absolute Deviation (MAD)0
Skewness3.4942456
Sum39.66
Variance1.3776833
MonotonicityNot monotonic
2023-12-10T15:43:26.752376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
0.0 61
61.0%
0.08 4
 
4.0%
0.02 4
 
4.0%
0.1 3
 
3.0%
0.04 3
 
3.0%
5.7 3
 
3.0%
0.06 3
 
3.0%
0.01 2
 
2.0%
0.11 2
 
2.0%
0.03 2
 
2.0%
Other values (11) 13
 
13.0%
ValueCountFrequency (%)
0.0 61
61.0%
0.01 2
 
2.0%
0.02 4
 
4.0%
0.03 2
 
2.0%
0.04 3
 
3.0%
0.06 3
 
3.0%
0.08 4
 
4.0%
0.1 3
 
3.0%
0.11 2
 
2.0%
0.15 1
 
1.0%
ValueCountFrequency (%)
5.7 3
3.0%
3.37 2
2.0%
3.16 1
 
1.0%
2.85 2
2.0%
1.58 1
 
1.0%
1.11 1
 
1.0%
1.0 1
 
1.0%
0.56 1
 
1.0%
0.51 1
 
1.0%
0.39 1
 
1.0%

COPPR_VALUE
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.1027
Minimum0
Maximum67.5
Zeros63
Zeros (%)63.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:26.944010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.0325
95-th percentile0.708
Maximum67.5
Range67.5
Interquartile range (IQR)0.0325

Descriptive statistics

Standard deviation7.5233374
Coefficient of variation (CV)6.8226511
Kurtosis65.940994
Mean1.1027
Median Absolute Deviation (MAD)0
Skewness7.9442244
Sum110.27
Variance56.600606
MonotonicityNot monotonic
2023-12-10T15:43:27.137891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 63
63.0%
0.04 7
 
7.0%
0.03 6
 
6.0%
0.02 5
 
5.0%
0.07 5
 
5.0%
2.0 3
 
3.0%
0.14 1
 
1.0%
0.09 1
 
1.0%
34.0 1
 
1.0%
67.5 1
 
1.0%
Other values (7) 7
 
7.0%
ValueCountFrequency (%)
0.0 63
63.0%
0.01 1
 
1.0%
0.02 5
 
5.0%
0.03 6
 
6.0%
0.04 7
 
7.0%
0.05 1
 
1.0%
0.07 5
 
5.0%
0.08 1
 
1.0%
0.09 1
 
1.0%
0.13 1
 
1.0%
ValueCountFrequency (%)
67.5 1
 
1.0%
34.0 1
 
1.0%
2.0 3
3.0%
0.64 1
 
1.0%
0.5 1
 
1.0%
0.22 1
 
1.0%
0.14 1
 
1.0%
0.13 1
 
1.0%
0.09 1
 
1.0%
0.08 1
 
1.0%

FLRN_VALUE
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
98 
5.1
 
1
0.5
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 98
98.0%
5.1 1
 
1.0%
0.5 1
 
1.0%

Length

2023-12-10T15:43:27.345764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:27.606122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 98
98.0%
5.1 1
 
1.0%
0.5 1
 
1.0%

MANG_VALUE
Categorical

IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
96 
0.02
 
3
4.22
 
1

Length

Max length4
Median length3
Mean length3.04
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0.0 96
96.0%
0.02 3
 
3.0%
4.22 1
 
1.0%

Length

2023-12-10T15:43:27.812333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:27.977899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 96
96.0%
0.02 3
 
3.0%
4.22 1
 
1.0%

IDN_VALUE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

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 (%)
0 100
100.0%

Length

2023-12-10T15:43:28.181081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:28.387883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

SELEN_VALUE
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.8869
Minimum0
Maximum16.1
Zeros64
Zeros (%)64.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:28.550301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.2
95-th percentile5.1
Maximum16.1
Range16.1
Interquartile range (IQR)0.2

Descriptive statistics

Standard deviation2.8574449
Coefficient of variation (CV)3.2218344
Kurtosis20.049107
Mean0.8869
Median Absolute Deviation (MAD)0
Skewness4.3916009
Sum88.69
Variance8.1649913
MonotonicityNot monotonic
2023-12-10T15:43:28.812824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 64
64.0%
0.2 4
 
4.0%
5.1 4
 
4.0%
0.15 4
 
4.0%
0.35 3
 
3.0%
0.4 3
 
3.0%
0.1 3
 
3.0%
0.05 3
 
3.0%
0.3 2
 
2.0%
15.4 2
 
2.0%
Other values (7) 8
 
8.0%
ValueCountFrequency (%)
0.0 64
64.0%
0.05 3
 
3.0%
0.1 3
 
3.0%
0.15 4
 
4.0%
0.2 4
 
4.0%
0.3 2
 
2.0%
0.35 3
 
3.0%
0.4 3
 
3.0%
0.5 1
 
1.0%
1.45 1
 
1.0%
ValueCountFrequency (%)
16.1 1
 
1.0%
15.4 2
2.0%
5.1 4
4.0%
4.1 1
 
1.0%
3.02 2
2.0%
2.55 1
 
1.0%
2.05 1
 
1.0%
1.45 1
 
1.0%
0.5 1
 
1.0%
0.4 3
3.0%

CHOLE_VALUE
Real number (ℝ)

MISSING  ZEROS 

Distinct7
Distinct (%)7.2%
Missing3
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean1.393299
Minimum0
Maximum51
Zeros90
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:29.034961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5.71
Maximum51
Range51
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.8501316
Coefficient of variation (CV)4.9164837
Kurtosis37.811966
Mean1.393299
Median Absolute Deviation (MAD)0
Skewness5.9729069
Sum135.15
Variance46.924304
MonotonicityNot monotonic
2023-12-10T15:43:29.188031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0.0 90
90.0%
13.75 2
 
2.0%
51.0 1
 
1.0%
39.0 1
 
1.0%
0.5 1
 
1.0%
13.35 1
 
1.0%
3.8 1
 
1.0%
(Missing) 3
 
3.0%
ValueCountFrequency (%)
0.0 90
90.0%
0.5 1
 
1.0%
3.8 1
 
1.0%
13.35 1
 
1.0%
13.75 2
 
2.0%
39.0 1
 
1.0%
51.0 1
 
1.0%
ValueCountFrequency (%)
51.0 1
 
1.0%
39.0 1
 
1.0%
13.75 2
 
2.0%
13.35 1
 
1.0%
3.8 1
 
1.0%
0.5 1
 
1.0%
0.0 90
90.0%

QNT_VALUE
Real number (ℝ)

Distinct22
Distinct (%)22.2%
Missing1
Missing (%)1.0%
Infinite0
Infinite (%)0.0%
Mean106.78384
Minimum2
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:29.399521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5
Q150
median100
Q3120
95-th percentile212.1
Maximum1000
Range998
Interquartile range (IQR)70

Descriptive statistics

Standard deviation141.70241
Coefficient of variation (CV)1.3270024
Kurtosis31.276754
Mean106.78384
Median Absolute Deviation (MAD)50
Skewness5.2207539
Sum10571.6
Variance20079.573
MonotonicityNot monotonic
2023-12-10T15:43:29.644928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
100.0 26
26.0%
50.0 25
25.0%
5.0 7
 
7.0%
130.0 6
 
6.0%
200.0 5
 
5.0%
120.0 5
 
5.0%
80.0 4
 
4.0%
30.0 4
 
4.0%
26.0 2
 
2.0%
1000.0 2
 
2.0%
Other values (12) 13
13.0%
ValueCountFrequency (%)
2.0 1
 
1.0%
4.0 1
 
1.0%
5.0 7
 
7.0%
26.0 2
 
2.0%
29.6 1
 
1.0%
30.0 4
 
4.0%
40.0 1
 
1.0%
50.0 25
25.0%
80.0 4
 
4.0%
100.0 26
26.0%
ValueCountFrequency (%)
1000.0 2
 
2.0%
300.0 1
 
1.0%
267.0 1
 
1.0%
231.0 1
 
1.0%
210.0 1
 
1.0%
200.0 5
5.0%
170.0 1
 
1.0%
151.0 1
 
1.0%
150.0 2
 
2.0%
130.0 6
6.0%

TFA_VALUE
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2417
Minimum0
Maximum3.3
Zeros82
Zeros (%)82.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:29.878010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.025
Maximum3.3
Range3.3
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.73071026
Coefficient of variation (CV)3.0232117
Kurtosis10.470975
Mean0.2417
Median Absolute Deviation (MAD)0
Skewness3.3639342
Sum24.17
Variance0.53393748
MonotonicityNot monotonic
2023-12-10T15:43:30.112674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0.0 82
82.0%
3.2 3
 
3.0%
0.22 1
 
1.0%
0.8 1
 
1.0%
0.31 1
 
1.0%
0.23 1
 
1.0%
0.39 1
 
1.0%
0.34 1
 
1.0%
0.28 1
 
1.0%
0.21 1
 
1.0%
Other values (7) 7
 
7.0%
ValueCountFrequency (%)
0.0 82
82.0%
0.04 1
 
1.0%
0.21 1
 
1.0%
0.22 1
 
1.0%
0.23 1
 
1.0%
0.28 1
 
1.0%
0.31 1
 
1.0%
0.34 1
 
1.0%
0.39 1
 
1.0%
0.8 1
 
1.0%
ValueCountFrequency (%)
3.3 1
 
1.0%
3.2 3
3.0%
2.5 1
 
1.0%
2.0 1
 
1.0%
1.8 1
 
1.0%
1.25 1
 
1.0%
0.9 1
 
1.0%
0.8 1
 
1.0%
0.39 1
 
1.0%
0.34 1
 
1.0%

SAFA_VALUE
Real number (ℝ)

MISSING  ZEROS 

Distinct18
Distinct (%)18.4%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean0.33193878
Minimum0
Maximum6.2
Zeros76
Zeros (%)76.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:30.331146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2.605
Maximum6.2
Range6.2
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.9651544
Coefficient of variation (CV)2.9076278
Kurtosis15.993806
Mean0.33193878
Median Absolute Deviation (MAD)0
Skewness3.7438662
Sum32.53
Variance0.93152301
MonotonicityNot monotonic
2023-12-10T15:43:31.026662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
0.0 76
76.0%
3.2 3
 
3.0%
0.2 2
 
2.0%
2.0 2
 
2.0%
0.28 2
 
2.0%
0.21 1
 
1.0%
0.8 1
 
1.0%
0.23 1
 
1.0%
0.39 1
 
1.0%
0.34 1
 
1.0%
Other values (8) 8
 
8.0%
(Missing) 2
 
2.0%
ValueCountFrequency (%)
0.0 76
76.0%
0.01 1
 
1.0%
0.04 1
 
1.0%
0.2 2
 
2.0%
0.21 1
 
1.0%
0.23 1
 
1.0%
0.28 2
 
2.0%
0.34 1
 
1.0%
0.39 1
 
1.0%
0.8 1
 
1.0%
ValueCountFrequency (%)
6.2 1
 
1.0%
3.3 1
 
1.0%
3.2 3
3.0%
2.5 1
 
1.0%
2.0 2
2.0%
1.8 1
 
1.0%
1.25 1
 
1.0%
0.9 1
 
1.0%
0.8 1
 
1.0%
0.39 1
 
1.0%

MUFA_VALUE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

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 (%)
0 100
100.0%

Length

2023-12-10T15:43:31.230714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:31.379714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

PUFA_VALUE
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
100 

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 (%)
0 100
100.0%

Length

2023-12-10T15:43:31.559170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:31.712798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 100
100.0%

TRANSFA_VALUE
Categorical

IMBALANCE 

Distinct4
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0.0
94 
<NA>
 
4
0.03
 
1
0.02
 
1

Length

Max length4
Median length3
Mean length3.06
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row0.0
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row0.0

Common Values

ValueCountFrequency (%)
0.0 94
94.0%
<NA> 4
 
4.0%
0.03 1
 
1.0%
0.02 1
 
1.0%

Length

2023-12-10T15:43:31.884089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:32.085382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0.0 94
94.0%
na 4
 
4.0%
0.03 1
 
1.0%
0.02 1
 
1.0%

ILE_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
290
 
1

Length

Max length3
Median length1
Mean length1.02
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
290 1
 
1.0%

Length

2023-12-10T15:43:32.331161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:32.517495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
290 1
 
1.0%

LEU_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
1200
 
1

Length

Max length4
Median length1
Mean length1.03
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
1200 1
 
1.0%

Length

2023-12-10T15:43:32.684823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:32.858578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
1200 1
 
1.0%

LYS_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
67
 
1

Length

Max length2
Median length1
Mean length1.01
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
67 1
 
1.0%

Length

2023-12-10T15:43:33.035437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:33.197495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
67 1
 
1.0%

METHIO_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
150
 
1

Length

Max length3
Median length1
Mean length1.02
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
150 1
 
1.0%

Length

2023-12-10T15:43:33.406492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:33.571275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
150 1
 
1.0%

PHE_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
420
 
1

Length

Max length3
Median length1
Mean length1.02
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
420 1
 
1.0%

Length

2023-12-10T15:43:33.729728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:33.898147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
420 1
 
1.0%

TOT_CALORIE_VALUE
Real number (ℝ)

MISSING 

Distinct74
Distinct (%)75.5%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean166.69367
Minimum2.25
Maximum970
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:34.041991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.25
5-th percentile17.75
Q134.605
median65
Q3257.57
95-th percentile605.664
Maximum970
Range967.75
Interquartile range (IQR)222.965

Descriptive statistics

Standard deviation191.58048
Coefficient of variation (CV)1.1492967
Kurtosis2.9979298
Mean166.69367
Median Absolute Deviation (MAD)43.75
Skewness1.7188738
Sum16335.98
Variance36703.081
MonotonicityNot monotonic
2023-12-10T15:43:34.280387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
45.0 7
 
7.0%
47.0 4
 
4.0%
32.5 4
 
4.0%
200.0 4
 
4.0%
100.0 3
 
3.0%
21.0 2
 
2.0%
374.0 2
 
2.0%
13.5 2
 
2.0%
65.0 2
 
2.0%
31.0 2
 
2.0%
Other values (64) 66
66.0%
ValueCountFrequency (%)
2.25 1
1.0%
8.0 1
1.0%
13.0 1
1.0%
13.5 2
2.0%
18.5 1
1.0%
20.5 2
2.0%
21.0 2
2.0%
21.5 1
1.0%
23.5 1
1.0%
24.52 1
1.0%
ValueCountFrequency (%)
970.0 1
1.0%
666.72 1
1.0%
665.28 1
1.0%
635.04 1
1.0%
610.56 1
1.0%
604.8 1
1.0%
596.4 1
1.0%
482.0 1
1.0%
406.0 1
1.0%
404.0 1
1.0%

THREO_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
240
 
1

Length

Max length3
Median length1
Mean length1.02
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
240 1
 
1.0%

Length

2023-12-10T15:43:34.551171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:34.748617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
240 1
 
1.0%

TRYPTO_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
41
 
1

Length

Max length2
Median length1
Mean length1.01
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
41 1
 
1.0%

Length

2023-12-10T15:43:34.935661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:35.112871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
41 1
 
1.0%

VALINE_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
360
 
1

Length

Max length3
Median length1
Mean length1.02
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
360 1
 
1.0%

Length

2023-12-10T15:43:35.306824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:35.482244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
360 1
 
1.0%

HISTI_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
220
 
1

Length

Max length3
Median length1
Mean length1.02
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
220 1
 
1.0%

Length

2023-12-10T15:43:35.647138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:35.840541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
220 1
 
1.0%

ARGI_VALUE
Categorical

IMBALANCE 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
0
99 
130
 
1

Length

Max length3
Median length1
Mean length1.02
Min length1

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
0 99
99.0%
130 1
 
1.0%

Length

2023-12-10T15:43:36.016798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T15:43:36.162875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 99
99.0%
130 1
 
1.0%

LAST_UPDT_DT
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

TRANSMIS_DTTM
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing100
Missing (%)100.0%
Memory size1.0 KiB

CARBO_VALUE
Real number (ℝ)

ZEROS 

Distinct76
Distinct (%)76.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean30.4418
Minimum0
Maximum134.4
Zeros13
Zeros (%)13.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:36.346393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15.3375
median11.78
Q345.5
95-th percentile101.66
Maximum134.4
Range134.4
Interquartile range (IQR)40.1625

Descriptive statistics

Standard deviation35.013748
Coefficient of variation (CV)1.1501865
Kurtosis0.20638553
Mean30.4418
Median Absolute Deviation (MAD)11.78
Skewness1.17019
Sum3044.18
Variance1225.9625
MonotonicityNot monotonic
2023-12-10T15:43:36.582735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 13
 
13.0%
5.4 4
 
4.0%
7.24 3
 
3.0%
101.66 2
 
2.0%
32.0 2
 
2.0%
16.5 2
 
2.0%
3.0 2
 
2.0%
11.86 2
 
2.0%
1.22 2
 
2.0%
1.0 2
 
2.0%
Other values (66) 66
66.0%
ValueCountFrequency (%)
0.0 13
13.0%
0.59 1
 
1.0%
1.0 2
 
2.0%
1.22 2
 
2.0%
1.84 1
 
1.0%
2.62 1
 
1.0%
3.0 2
 
2.0%
3.55 1
 
1.0%
5.0 1
 
1.0%
5.15 1
 
1.0%
ValueCountFrequency (%)
134.4 1
1.0%
122.0 1
1.0%
108.0 1
1.0%
102.1 1
1.0%
101.66 2
2.0%
98.78 1
1.0%
97.04 1
1.0%
91.6 1
1.0%
88.1 1
1.0%
86.4 1
1.0%

FAT_VALUE
Real number (ℝ)

MISSING  ZEROS 

Distinct47
Distinct (%)48.0%
Missing2
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean3.15
Minimum0
Maximum36
Zeros17
Zeros (%)17.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:36.773714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.1
median0.41
Q33.4
95-th percentile19.6025
Maximum36
Range36
Interquartile range (IQR)3.3

Descriptive statistics

Standard deviation6.3162771
Coefficient of variation (CV)2.0051673
Kurtosis10.916177
Mean3.15
Median Absolute Deviation (MAD)0.41
Skewness3.1936583
Sum308.7
Variance39.895357
MonotonicityNot monotonic
2023-12-10T15:43:36.958239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=47)
ValueCountFrequency (%)
0.0 17
17.0%
0.1 15
 
15.0%
5.0 6
 
6.0%
0.2 4
 
4.0%
0.05 4
 
4.0%
4.3 3
 
3.0%
0.17 3
 
3.0%
6.0 2
 
2.0%
3.5 2
 
2.0%
3.0 2
 
2.0%
Other values (37) 40
40.0%
ValueCountFrequency (%)
0.0 17
17.0%
0.05 4
 
4.0%
0.1 15
15.0%
0.15 1
 
1.0%
0.17 3
 
3.0%
0.2 4
 
4.0%
0.25 1
 
1.0%
0.3 1
 
1.0%
0.37 1
 
1.0%
0.39 1
 
1.0%
ValueCountFrequency (%)
36.0 1
1.0%
25.78 1
1.0%
24.91 1
1.0%
24.77 1
1.0%
19.73 1
1.0%
19.58 1
1.0%
11.46 1
1.0%
10.68 1
1.0%
9.22 1
1.0%
8.77 1
1.0%

VFAT_VALUE
Real number (ℝ)

ZEROS 

Distinct19
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2643
Minimum0
Maximum4.3
Zeros62
Zeros (%)62.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T15:43:37.146699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.1
95-th percentile1.7505
Maximum4.3
Range4.3
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.72360804
Coefficient of variation (CV)2.7378284
Kurtosis15.13155
Mean0.2643
Median Absolute Deviation (MAD)0
Skewness3.7550895
Sum26.43
Variance0.5236086
MonotonicityNot monotonic
2023-12-10T15:43:37.341547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0.0 62
62.0%
0.1 14
 
14.0%
0.05 4
 
4.0%
0.17 3
 
3.0%
0.2 2
 
2.0%
0.63 2
 
2.0%
1.75 1
 
1.0%
1.27 1
 
1.0%
1.09 1
 
1.0%
1.76 1
 
1.0%
Other values (9) 9
 
9.0%
ValueCountFrequency (%)
0.0 62
62.0%
0.05 4
 
4.0%
0.1 14
 
14.0%
0.15 1
 
1.0%
0.17 3
 
3.0%
0.2 2
 
2.0%
0.3 1
 
1.0%
0.63 2
 
2.0%
0.9 1
 
1.0%
1.09 1
 
1.0%
ValueCountFrequency (%)
4.3 1
1.0%
3.5 1
1.0%
3.1 1
1.0%
2.15 1
1.0%
1.76 1
1.0%
1.75 1
1.0%
1.27 1
1.0%
1.2 1
1.0%
1.19 1
1.0%
1.09 1
1.0%

Sample

PRCSFD_CODEFD_SVC_CODEAFAT_VALUEPROTN_VALUEVPRTN_VALUEAPRTN_VALUEFIBR_VALUEMOIST_VALUEASH_VALUEVITA_VALUERTNOL_VALUEBCRT_VALUEPRCSFD_NMVITD_VALUEVITE_VALUEVITK_VALUEVITC_VALUEVITB1_VALUEVITB2_VALUENIACN_VALUEVITB6_VALUEFOLATE_VALUEVITB12_VALUEPRCSFD_CTGRY_CODEPANTO_VALUEBIOTIN_VALUECA_VALUEVCA_VALUEACA_VALUEPHOSPHO_VALUENA_VALUECHLOR_VALUEPOTSSM_VALUEMGM_VALUEENTRPS_NMIRON_VALUEVIRON_VALUEAIRON_VALUEZINC_VALUECOPPR_VALUEFLRN_VALUEMANG_VALUEIDN_VALUESELEN_VALUECHOLE_VALUEQNT_VALUETFA_VALUESAFA_VALUEMUFA_VALUEPUFA_VALUETRANSFA_VALUEILE_VALUELEU_VALUELYS_VALUEMETHIO_VALUEPHE_VALUETOT_CALORIE_VALUETHREO_VALUETRYPTO_VALUEVALINE_VALUEHISTI_VALUEARGI_VALUELAST_UPDT_DTTRANSMIS_DTTMCARBO_VALUEFAT_VALUEVFAT_VALUE
0800100053P0040.036.00.00.00.00.00.00.00.00.0밴쯔 덤플링0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.01380.000.00.0(주)서원푸드0.00.00.00.00.00.00.000.051.0<NA>0.06.2000.000000970.000000<NA><NA>122.036.00.0
11600300008P0040.01.20.00.00.00.00.00.00.00.0꽃생차0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.020.400.00.0(주)경신바이오0.00.00.00.00.00.00.000.0<NA>100.00.00.0100<NA>00000369.2900000<NA><NA>97.040.370.0
2300100107P0040.010.00.00.00.00.00.00.00.00.0(냉)시나몬레이즌베이글0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.0410.000.00.0㈜ 에이피홀딩스0.00.00.00.00.00.00.000.0<NA>100.00.0<NA>00<NA>00000280.000000<NA><NA>61.01.00.0
31600900021P0040.01.00.00.00.00.00.00.00.00.0Xtra concentrate(P2-formula| Canada)0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.0<NA>00.00.0(주)네이처텍0.00.00.00.00.00.00.000.0<NA>29.60.0<NA>00<NA>0000025.000000<NA><NA>5.0<NA>0.0
41700400030P0040.01.00.00.00.00.00.00.00.00.0낫토균 발효 약콩효소0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.00.000.00.0(주)네이처텍0.00.00.00.00.00.00.000.00.02.00.00.0000.000000<NA>00000<NA><NA>1.00.00.0
51400300002P0040.00.00.00.00.00.00.00.00.00.0까로망 마이레몬0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.00.000.00.0(주)예담에프엔비0.00.00.00.00.00.00.000.00.040.00.00.000<NA>00000105.200000<NA><NA>26.00.00.0
6100500004P0040.04.20.00.00.00.00.00.00.00.0맛나랑 참 떡볶이0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.0135.000.00.0(유)성지 에프앤디0.00.00.00.00.00.00.000.00.01000.00.00.0000.000000217.000000<NA><NA>49.80.10.0
7100300003P0040.012.00.00.00.00.00.00.00.00.0삼색 수제비0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.0396.000.00.0(유)성지 에프앤디0.00.00.00.00.00.00.000.00.01000.00.00.0000.000000482.000000<NA><NA>108.00.00.0
8100500005P0040.07.50.00.00.00.00.00.00.00.0가마솥 현미 누룽지0.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.06.900.00.0(유)큰바위식품0.00.00.00.00.00.00.000.00.0300.00.00.2000.000000<NA>00000<NA><NA>86.10.60.0
91700500009P0040.014.00.00.00.00.00.00.00.00.0100.00.00.00.00.00.00.00.00.00.0AF0010.000.00.00.00.0312.000.00.0(주)다솜푸드0.00.00.00.00.00.00.000.039.0231.00.02.0000.000000352.000000<NA><NA>52.0<NA>0.0
PRCSFD_CODEFD_SVC_CODEAFAT_VALUEPROTN_VALUEVPRTN_VALUEAPRTN_VALUEFIBR_VALUEMOIST_VALUEASH_VALUEVITA_VALUERTNOL_VALUEBCRT_VALUEPRCSFD_NMVITD_VALUEVITE_VALUEVITK_VALUEVITC_VALUEVITB1_VALUEVITB2_VALUENIACN_VALUEVITB6_VALUEFOLATE_VALUEVITB12_VALUEPRCSFD_CTGRY_CODEPANTO_VALUEBIOTIN_VALUECA_VALUEVCA_VALUEACA_VALUEPHOSPHO_VALUENA_VALUECHLOR_VALUEPOTSSM_VALUEMGM_VALUEENTRPS_NMIRON_VALUEVIRON_VALUEAIRON_VALUEZINC_VALUECOPPR_VALUEFLRN_VALUEMANG_VALUEIDN_VALUESELEN_VALUECHOLE_VALUEQNT_VALUETFA_VALUESAFA_VALUEMUFA_VALUEPUFA_VALUETRANSFA_VALUEILE_VALUELEU_VALUELYS_VALUEMETHIO_VALUEPHE_VALUETOT_CALORIE_VALUETHREO_VALUETRYPTO_VALUEVALINE_VALUEHISTI_VALUEARGI_VALUELAST_UPDT_DTTRANSMIS_DTTMCARBO_VALUEFAT_VALUEVFAT_VALUE
90181200290P0040.00.10.10.00.941.40.11.830.011.0사과|블루베리|고형분포함(거버)0.00.144.46.950.010.020.050.021.50.0AF0010.0802.52.50.03.53.1057.00.0거버0.250.250.00.020.030.00.000.20.050.00.00.0000.00000031.000000<NA><NA>8.30.10.1
91181200300P0040.00.10.10.00.941.550.10.830.05.0사과|블루베리|으깬형태(거버)0.00.061.7513.90.010.020.060.021.50.0AF0010.0802.02.00.04.01.55056.50.0거버0.10.10.00.020.030.00.000.20.050.00.00.0000.00000030.500000<NA><NA>8.150.10.1
92181200310P0040.00.00.00.00.8544.750.10.00.00.0사과소스|고형분포함|3차식(거버)0.00.30.018.90.010.010.030.010.00.0AF0010.0602.52.50.03.01.0038.50.0거버0.110.110.00.020.020.00.000.150.050.00.00.0000.00000018.500000<NA><NA>5.150.00.0
93181200320P0040.00.10.10.00.943.450.121.250.07.5사과소스|살구|고형분포함(거버)0.00.061.758.950.010.020.070.020.00.0AF0010.0803.03.00.05.01.5049.00.0거버0.330.330.00.020.020.00.000.150.050.00.00.0000.00000023.500000<NA><NA>6.20.10.1
94181200330P0040.00.10.10.00.8544.30.11.00.06.0사과소스|으깬형태|1차식(거버)0.00.30.2519.150.010.010.030.021.50.0AF0010.0602.02.00.03.51.0035.50.0거버0.110.110.00.010.020.00.000.150.050.00.00.0000.00000020.500000<NA><NA>5.40.10.1
95181200340P0040.00.10.10.00.8544.30.11.00.06.0사과소스|으깬형태|2차식(거버)0.00.30.2519.150.010.010.030.020.00.0AF0010.0602.02.00.03.51.0035.50.0거버0.110.110.00.010.020.00.000.150.050.00.00.0000.00000020.500000<NA><NA>5.40.10.1
96181200350P0040.636.023.013.010.041.220.290.00.00.0쇠고기|고형분포함|3차식(거버)0.00.190.01.050.010.071.250.020.00.0AF0010.002.51.251.2546.523.0093.50.0거버0.490.250.251.00.00.00.000.013.7550.00.00.0000.00000040.500000<NA><NA>1.221.260.63
97181200360P0040.636.023.013.010.041.220.290.00.00.0쇠고기|으깬형태|2차식(거버)0.00.190.41.050.010.071.250.020.00.74AF0010.1802.51.251.2546.523.0093.50.0거버0.490.250.251.110.020.00.001.4513.7550.00.00.0000.00000040.500000<NA><NA>1.221.260.63
98181200370P0040.02.262.260.00.781.220.650.00.00.0쌀|바나나|분말(거버)0.00.080.990.521.030.996.060.183.120.05AF0010.00179.66179.660.0106.624.960199.9436.66거버12.3512.350.00.390.070.00.003.020.026.00.00.0000.000000105.0400000<NA><NA>20.771.091.09
99181200380P0040.01.851.850.00.781.740.940.00.00.0쌀|분말(거버)0.01.30.00.620.690.588.120.126.240.0AF0010.00221.0221.00.0153.48.320100.153.56거버12.3512.350.00.510.090.00.003.020.026.00.00.0000.000000101.6600000<NA><NA>20.181.271.27