Overview

Dataset statistics

Number of variables43
Number of observations10000
Missing cells58107
Missing cells (%)13.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 MiB
Average record size in memory376.0 B

Variable types

Categorical15
Unsupported5
Numeric15
Text8

Dataset

Description농협 산지 공판장에서 거래되는 농산물들의 경매낙찰가격과 거래되는 상품들에 대한 거래 상세 정보
Author농림수산식품교육문화정보원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220210000000001795

Alerts

DELNG_DE has constant value ""Constant
STD_UNIT_NEW_CODE has constant value ""Constant
STD_UNIT_NEW_NM has constant value ""Constant
STD_SPCIES_NEW_NM is highly imbalanced (96.0%)Imbalance
STD_FRMLC_NEW_CODE is highly imbalanced (60.5%)Imbalance
STD_FRMLC_NEW_NM is highly imbalanced (60.5%)Imbalance
STD_QLITY_NEW_CODE is highly imbalanced (57.9%)Imbalance
STD_QLITY_NEW_NM is highly imbalanced (57.9%)Imbalance
SBID_TIME has 10000 (100.0%) missing valuesMissing
WHSAL_MRKT_NEW_CODE has 10000 (100.0%) missing valuesMissing
WHSAL_MRKT_NEW_NM has 10000 (100.0%) missing valuesMissing
WHSAL_MRKT_CODE has 10000 (100.0%) missing valuesMissing
WHSAL_MRKT_NM has 10000 (100.0%) missing valuesMissing
STD_MTC_NEW_NM has 8037 (80.4%) missing valuesMissing
SBID_TIME is an unsupported type, check if it needs cleaning or further analysisUnsupported
WHSAL_MRKT_NEW_CODE is an unsupported type, check if it needs cleaning or further analysisUnsupported
WHSAL_MRKT_NEW_NM is an unsupported type, check if it needs cleaning or further analysisUnsupported
WHSAL_MRKT_CODE is an unsupported type, check if it needs cleaning or further analysisUnsupported
WHSAL_MRKT_NM is an unsupported type, check if it needs cleaning or further analysisUnsupported
STD_MTC_NEW_CODE has 8037 (80.4%) zerosZeros

Reproduction

Analysis started2023-12-11 03:18:06.859189
Analysis finished2023-12-11 03:18:07.952788
Duration1.09 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

DELNG_DE
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
20200114
10000 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20200114
2nd row20200114
3rd row20200114
4th row20200114
5th row20200114

Common Values

ValueCountFrequency (%)
20200114 10000
100.0%

Length

2023-12-11T12:18:08.003314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:08.071075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20200114 10000
100.0%

SBID_TIME
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

WHSAL_MRKT_NEW_CODE
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

WHSAL_MRKT_NEW_NM
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

CPR_CODE
Real number (ℝ)

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.80899 × 1012
Minimum8.80899 × 1012
Maximum8.8089901 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:08.148111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8.80899 × 1012
5-th percentile8.80899 × 1012
Q18.80899 × 1012
median8.80899 × 1012
Q38.80899 × 1012
95-th percentile8.80899 × 1012
Maximum8.8089901 × 1012
Range53682
Interquartile range (IQR)3319

Descriptive statistics

Standard deviation14728.227
Coefficient of variation (CV)1.6719541 × 10-9
Kurtosis1.0683466
Mean8.80899 × 1012
Median Absolute Deviation (MAD)226
Skewness1.6426417
Sum8.80899 × 1016
Variance2.1692068 × 108
MonotonicityNot monotonic
2023-12-11T12:18:08.255647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
8808990000855 1388
13.9%
8808990000923 777
 
7.8%
8808990001098 709
 
7.1%
8808990000961 643
 
6.4%
8808990001104 631
 
6.3%
8808990000831 630
 
6.3%
8808990000824 543
 
5.4%
8808990001081 518
 
5.2%
8808990004099 506
 
5.1%
8808990001128 396
 
4.0%
Other values (19) 3259
32.6%
ValueCountFrequency (%)
8808990000794 340
 
3.4%
8808990000817 118
 
1.2%
8808990000824 543
 
5.4%
8808990000831 630
6.3%
8808990000855 1388
13.9%
8808990000923 777
7.8%
8808990000961 643
6.4%
8808990001074 88
 
0.9%
8808990001081 518
 
5.2%
8808990001098 709
7.1%
ValueCountFrequency (%)
8808990054476 28
 
0.3%
8808990052090 77
 
0.8%
8808990050799 55
 
0.5%
8808990045580 9
 
0.1%
8808990044866 8
 
0.1%
8808990043517 384
3.8%
8808990040820 284
2.8%
8808990036373 300
3.0%
8808990036342 374
3.7%
8808990030340 157
1.6%

CPR_NM
Categorical

Distinct29
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
가락공판장
1388 
대전공판장
777 
반여공판장
709 
광주공판장
643 
부산공판장
631 
Other values (24)
5852 

Length

Max length15
Median length5
Mean length6.9012
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row북대구공판장
2nd row대전공판장
3rd row반여공판장
4th row강서공판장
5th row안산공판장

Common Values

ValueCountFrequency (%)
가락공판장 1388
13.9%
대전공판장 777
 
7.8%
반여공판장 709
 
7.1%
광주공판장 643
 
6.4%
부산공판장 631
 
6.3%
구리공판장 630
 
6.3%
강서공판장 543
 
5.4%
북대구공판장 518
 
5.2%
인천원예농협삼산공판장 506
 
5.1%
창원공판장 396
 
4.0%
Other values (19) 3259
32.6%

Length

2023-12-11T12:18:08.377870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가락공판장 1388
 
13.0%
대전공판장 777
 
7.3%
반여공판장 709
 
6.6%
광주공판장 643
 
6.0%
부산공판장 631
 
5.9%
구리공판장 630
 
5.9%
강서공판장 543
 
5.1%
북대구공판장 518
 
4.8%
인천원예농협삼산공판장 506
 
4.7%
공판장 448
 
4.2%
Other values (22) 3914
36.6%

AUC_SE_CODE
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
7910 
2
2090 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row2

Common Values

ValueCountFrequency (%)
1 7910
79.1%
2 2090
 
20.9%

Length

2023-12-11T12:18:08.488041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:08.578545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 7910
79.1%
2 2090
 
20.9%

AUC_SE_NM
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
경매
7910 
정가수의
2090 

Length

Max length4
Median length2
Mean length2.418
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경매
2nd row경매
3rd row경매
4th row경매
5th row정가수의

Common Values

ValueCountFrequency (%)
경매 7910
79.1%
정가수의 2090
 
20.9%

Length

2023-12-11T12:18:08.675660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:08.787356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경매 7910
79.1%
정가수의 2090
 
20.9%

WHSAL_MRKT_CODE
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

WHSAL_MRKT_NM
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing10000
Missing (%)100.0%
Memory size166.0 KiB

LEDG_NO
Real number (ℝ)

Distinct1932
Distinct (%)19.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2927.9983
Minimum1
Maximum20002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:08.894800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.95
Q1285
median811
Q32620
95-th percentile20001
Maximum20002
Range20001
Interquartile range (IQR)2335

Descriptive statistics

Standard deviation5280.1582
Coefficient of variation (CV)1.8033338
Kurtosis5.2978402
Mean2927.9983
Median Absolute Deviation (MAD)694
Skewness2.5357662
Sum29279983
Variance27880071
MonotonicityNot monotonic
2023-12-11T12:18:09.030622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20001 565
 
5.7%
20002 180
 
1.8%
1 53
 
0.5%
11 51
 
0.5%
301 47
 
0.5%
411 44
 
0.4%
1381 43
 
0.4%
201 40
 
0.4%
101 36
 
0.4%
2 36
 
0.4%
Other values (1922) 8905
89.0%
ValueCountFrequency (%)
1 53
0.5%
2 36
0.4%
3 24
0.2%
4 25
0.2%
5 32
0.3%
6 14
 
0.1%
7 21
 
0.2%
8 14
 
0.1%
9 13
 
0.1%
10 31
0.3%
ValueCountFrequency (%)
20002 180
 
1.8%
20001 565
5.7%
11215 3
 
< 0.1%
11214 3
 
< 0.1%
11213 4
 
< 0.1%
11210 8
 
0.1%
11209 2
 
< 0.1%
11208 3
 
< 0.1%
11207 2
 
< 0.1%
11204 3
 
< 0.1%

SLE_SEQN
Real number (ℝ)

Distinct373
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean170.8901
Minimum10
Maximum4390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:09.161627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile10
Q120
median40
Q3100
95-th percentile760
Maximum4390
Range4380
Interquartile range (IQR)80

Descriptive statistics

Standard deviation465.77885
Coefficient of variation (CV)2.7256047
Kurtosis32.97058
Mean170.8901
Median Absolute Deviation (MAD)30
Skewness5.4233295
Sum1708901
Variance216949.94
MonotonicityNot monotonic
2023-12-11T12:18:09.294621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 1624
16.2%
20 1382
13.8%
30 1100
11.0%
40 819
 
8.2%
50 628
 
6.3%
60 521
 
5.2%
70 398
 
4.0%
80 358
 
3.6%
90 291
 
2.9%
100 244
 
2.4%
Other values (363) 2635
26.4%
ValueCountFrequency (%)
10 1624
16.2%
11 37
 
0.4%
12 9
 
0.1%
13 8
 
0.1%
14 7
 
0.1%
15 3
 
< 0.1%
16 2
 
< 0.1%
17 4
 
< 0.1%
18 3
 
< 0.1%
19 2
 
< 0.1%
ValueCountFrequency (%)
4390 1
< 0.1%
4310 1
< 0.1%
4290 1
< 0.1%
4280 1
< 0.1%
4260 1
< 0.1%
4210 1
< 0.1%
4200 1
< 0.1%
4120 1
< 0.1%
4050 1
< 0.1%
4040 1
< 0.1%

CATGORY_NEW_CODE
Real number (ℝ)

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.0702
Minimum0
Maximum93
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:09.421018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6
Q16
median9
Q312
95-th percentile17
Maximum93
Range93
Interquartile range (IQR)6

Descriptive statistics

Standard deviation14.817437
Coefficient of variation (CV)1.2276049
Kurtosis21.1298
Mean12.0702
Median Absolute Deviation (MAD)3
Skewness4.6581639
Sum120702
Variance219.55643
MonotonicityNot monotonic
2023-12-11T12:18:09.521596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
6 3156
31.6%
9 1796
18.0%
10 1715
17.2%
12 893
 
8.9%
17 803
 
8.0%
13 577
 
5.8%
5 312
 
3.1%
91 216
 
2.2%
11 143
 
1.4%
14 138
 
1.4%
Other values (9) 251
 
2.5%
ValueCountFrequency (%)
0 66
 
0.7%
2 1
 
< 0.1%
3 7
 
0.1%
5 312
 
3.1%
6 3156
31.6%
9 1796
18.0%
10 1715
17.2%
11 143
 
1.4%
12 893
 
8.9%
13 577
 
5.8%
ValueCountFrequency (%)
93 8
 
0.1%
91 216
 
2.2%
81 128
 
1.3%
41 1
 
< 0.1%
19 15
 
0.1%
18 1
 
< 0.1%
17 803
8.0%
16 24
 
0.2%
14 138
 
1.4%
13 577
5.8%

CATGORY_NEW_NM
Categorical

Distinct19
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
과실류
3156 
과채류
1796 
엽경채류
1715 
조미채소류
893 
버섯류
803 
Other values (14)
1637 

Length

Max length5
Median length3
Mean length3.3549
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row버섯류
2nd row과채류
3rd row과실류
4th row버섯류
5th row해조류

Common Values

ValueCountFrequency (%)
과실류 3156
31.6%
과채류 1796
18.0%
엽경채류 1715
17.2%
조미채소류 893
 
8.9%
버섯류 803
 
8.0%
양채류 577
 
5.8%
서류 312
 
3.1%
농림가공 216
 
2.2%
근채류 143
 
1.4%
산채류 138
 
1.4%
Other values (9) 251
 
2.5%

Length

2023-12-11T12:18:09.895751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
과실류 3156
31.6%
과채류 1796
18.0%
엽경채류 1715
17.2%
조미채소류 893
 
8.9%
버섯류 803
 
8.0%
양채류 577
 
5.8%
서류 312
 
3.1%
농림가공 216
 
2.2%
근채류 143
 
1.4%
산채류 138
 
1.4%
Other values (9) 251
 
2.5%

CATGORY_CODE
Real number (ℝ)

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.2915
Minimum2
Maximum93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:10.002925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q16
median8
Q312
95-th percentile17
Maximum93
Range91
Interquartile range (IQR)6

Descriptive statistics

Standard deviation9.3329544
Coefficient of variation (CV)0.90686046
Kurtosis44.833993
Mean10.2915
Median Absolute Deviation (MAD)2
Skewness6.3565397
Sum102915
Variance87.104038
MonotonicityNot monotonic
2023-12-11T12:18:10.150427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
6 3341
33.4%
10 1758
17.6%
8 1334
 
13.3%
12 893
 
8.9%
17 805
 
8.1%
13 594
 
5.9%
9 462
 
4.6%
5 312
 
3.1%
11 143
 
1.4%
14 138
 
1.4%
Other values (10) 220
 
2.2%
ValueCountFrequency (%)
2 1
 
< 0.1%
3 7
 
0.1%
5 312
 
3.1%
6 3341
33.4%
7 13
 
0.1%
8 1334
 
13.3%
9 462
 
4.6%
10 1758
17.6%
11 143
 
1.4%
12 893
 
8.9%
ValueCountFrequency (%)
93 8
 
0.1%
91 19
 
0.2%
76 131
 
1.3%
41 1
 
< 0.1%
19 15
 
0.1%
18 1
 
< 0.1%
17 805
8.1%
16 24
 
0.2%
14 138
 
1.4%
13 594
5.9%

CATGORY_NM
Categorical

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
과실류
3341 
엽경채류
1758 
과일과채류
1334 
조미채소류
893 
버섯류
805 
Other values (15)
1869 

Length

Max length7
Median length3
Mean length3.6394
Min length2

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st row버섯류
2nd row과채류
3rd row과실류
4th row버섯류
5th row신선 해조류

Common Values

ValueCountFrequency (%)
과실류 3341
33.4%
엽경채류 1758
17.6%
과일과채류 1334
 
13.3%
조미채소류 893
 
8.9%
버섯류 805
 
8.1%
양채류 594
 
5.9%
과채류 462
 
4.6%
서류 312
 
3.1%
근채류 143
 
1.4%
산채류 138
 
1.4%
Other values (10) 220
 
2.2%

Length

2023-12-11T12:18:10.324581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
과실류 3341
33.0%
엽경채류 1758
17.4%
과일과채류 1334
 
13.2%
조미채소류 893
 
8.8%
버섯류 805
 
7.9%
양채류 594
 
5.9%
과채류 462
 
4.6%
서류 312
 
3.1%
근채류 143
 
1.4%
산채류 138
 
1.4%
Other values (11) 351
 
3.5%

STD_PRDLST_NEW_CODE
Real number (ℝ)

Distinct132
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1215.0261
Minimum0
Maximum9351
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:10.480227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile601
Q1614
median909
Q31203
95-th percentile1711
Maximum9351
Range9351
Interquartile range (IQR)589

Descriptive statistics

Standard deviation1483.1887
Coefficient of variation (CV)1.2207053
Kurtosis21.138486
Mean1215.0261
Median Absolute Deviation (MAD)295
Skewness4.658854
Sum12150261
Variance2199848.9
MonotonicityNot monotonic
2023-12-11T12:18:10.672624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
909 1028
 
10.3%
601 896
 
9.0%
614 729
 
7.3%
602 649
 
6.5%
615 477
 
4.8%
1205 400
 
4.0%
1008 314
 
3.1%
1704 258
 
2.6%
502 236
 
2.4%
902 233
 
2.3%
Other values (122) 4780
47.8%
ValueCountFrequency (%)
0 66
 
0.7%
201 1
 
< 0.1%
301 1
 
< 0.1%
305 6
 
0.1%
501 76
 
0.8%
502 236
 
2.4%
601 896
9.0%
602 649
6.5%
603 48
 
0.5%
605 192
 
1.9%
ValueCountFrequency (%)
9351 8
 
0.1%
9118 197
2.0%
9108 5
 
0.1%
9107 9
 
0.1%
9106 2
 
< 0.1%
9104 3
 
< 0.1%
8113 49
 
0.5%
8109 61
 
0.6%
8108 14
 
0.1%
8105 3
 
< 0.1%

STD_PRDLST_NEW_NM
Text

Distinct131
Distinct (%)1.3%
Missing66
Missing (%)0.7%
Memory size156.2 KiB
2023-12-11T12:18:10.985590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.5144957
Min length1

Characters and Unicode

Total characters24979
Distinct characters169
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)0.1%

Sample

1st row양송이
2nd row호박
3rd row사과
4th row표고버섯
5th row미역류
ValueCountFrequency (%)
딸기 1028
 
10.3%
사과 896
 
9.0%
감귤 729
 
7.3%
배 649
 
6.5%
만감 477
 
4.8%
고추 400
 
4.0%
시금치 314
 
3.2%
표고버섯 258
 
2.6%
고구마 236
 
2.4%
호박 233
 
2.3%
Other values (123) 4718
47.5%
2023-12-11T12:18:11.475058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
감 1673
 
6.7%
추 1327
 
5.3%
배 1113
 
4.5%
기 1029
 
4.1%
딸 1028
 
4.1%
고 999
 
4.0%
사 935
 
3.7%
과 896
 
3.6%
귤 729
 
2.9%
이 663
 
2.7%
Other values (159) 14587
58.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24303
97.3%
Open Punctuation 336
 
1.3%
Close Punctuation 336
 
1.3%
Space Separator 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
감 1673
 
6.9%
추 1327
 
5.5%
배 1113
 
4.6%
기 1029
 
4.2%
딸 1028
 
4.2%
고 999
 
4.1%
사 935
 
3.8%
과 896
 
3.7%
귤 729
 
3.0%
이 663
 
2.7%
Other values (156) 13911
57.2%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Close Punctuation
ValueCountFrequency (%)
) 336
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24303
97.3%
Common 676
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
감 1673
 
6.9%
추 1327
 
5.5%
배 1113
 
4.6%
기 1029
 
4.2%
딸 1028
 
4.2%
고 999
 
4.1%
사 935
 
3.8%
과 896
 
3.7%
귤 729
 
3.0%
이 663
 
2.7%
Other values (156) 13911
57.2%
Common
ValueCountFrequency (%)
( 336
49.7%
) 336
49.7%
4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24303
97.3%
ASCII 676
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
감 1673
 
6.9%
추 1327
 
5.5%
배 1113
 
4.6%
기 1029
 
4.2%
딸 1028
 
4.2%
고 999
 
4.1%
사 935
 
3.8%
과 896
 
3.7%
귤 729
 
3.0%
이 663
 
2.7%
Other values (156) 13911
57.2%
ASCII
ValueCountFrequency (%)
( 336
49.7%
) 336
49.7%
4
 
0.6%

STD_PRDLST_CODE
Real number (ℝ)

Distinct141
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1036.8156
Minimum201
Maximum9304
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:11.640511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum201
5-th percentile601
Q1614
median806
Q31202
95-th percentile1704
Maximum9304
Range9103
Interquartile range (IQR)588

Descriptive statistics

Standard deviation933.75831
Coefficient of variation (CV)0.9006021
Kurtosis44.778867
Mean1036.8156
Median Absolute Deviation (MAD)204
Skewness6.3510352
Sum10368156
Variance871904.58
MonotonicityNot monotonic
2023-12-11T12:18:11.783724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
804 1028
 
10.3%
601 896
 
9.0%
614 729
 
7.3%
602 649
 
6.5%
615 477
 
4.8%
1008 314
 
3.1%
1205 305
 
3.0%
1704 258
 
2.6%
502 236
 
2.4%
902 233
 
2.3%
Other values (131) 4875
48.8%
ValueCountFrequency (%)
201 1
 
< 0.1%
301 1
 
< 0.1%
305 6
 
0.1%
501 76
 
0.8%
502 236
 
2.4%
601 896
9.0%
602 649
6.5%
603 48
 
0.5%
605 175
 
1.8%
606 17
 
0.2%
ValueCountFrequency (%)
9304 8
 
0.1%
9108 5
 
0.1%
9107 9
 
0.1%
9106 2
 
< 0.1%
9104 3
 
< 0.1%
7699 3
 
< 0.1%
7610 49
0.5%
7609 14
 
0.1%
7607 61
0.6%
7603 3
 
< 0.1%

STD_PRDLST_NM
Text

Distinct137
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:12.098017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.5998
Min length1

Characters and Unicode

Total characters25998
Distinct characters178
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

Unique12 ?
Unique (%)0.1%

Sample

1st row양송이
2nd row호박
3rd row사과
4th row표고버섯
5th row미역
ValueCountFrequency (%)
딸기 1028
 
10.3%
사과 896
 
9.0%
감귤 729
 
7.3%
배 649
 
6.5%
만감 477
 
4.8%
시금치 314
 
3.1%
풋고추 305
 
3.0%
표고버섯 258
 
2.6%
고구마 236
 
2.4%
호박 233
 
2.3%
Other values (129) 4879
48.8%
2023-12-11T12:18:12.615857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
감 1673
 
6.4%
추 1327
 
5.1%
배 1113
 
4.3%
기 1096
 
4.2%
딸 1028
 
4.0%
고 999
 
3.8%
사 949
 
3.7%
과 896
 
3.4%
귤 729
 
2.8%
이 724
 
2.8%
Other values (168) 15464
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25306
97.3%
Close Punctuation 336
 
1.3%
Open Punctuation 336
 
1.3%
Other Punctuation 16
 
0.1%
Space Separator 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
감 1673
 
6.6%
추 1327
 
5.2%
배 1113
 
4.4%
기 1096
 
4.3%
딸 1028
 
4.1%
고 999
 
3.9%
사 949
 
3.8%
과 896
 
3.5%
귤 729
 
2.9%
이 724
 
2.9%
Other values (164) 14772
58.4%
Close Punctuation
ValueCountFrequency (%)
) 336
100.0%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25306
97.3%
Common 692
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
감 1673
 
6.6%
추 1327
 
5.2%
배 1113
 
4.4%
기 1096
 
4.3%
딸 1028
 
4.1%
고 999
 
3.9%
사 949
 
3.8%
과 896
 
3.5%
귤 729
 
2.9%
이 724
 
2.9%
Other values (164) 14772
58.4%
Common
ValueCountFrequency (%)
) 336
48.6%
( 336
48.6%
, 16
 
2.3%
4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25306
97.3%
ASCII 692
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
감 1673
 
6.6%
추 1327
 
5.2%
배 1113
 
4.4%
기 1096
 
4.3%
딸 1028
 
4.1%
고 999
 
3.9%
사 949
 
3.8%
과 896
 
3.5%
귤 729
 
2.9%
이 724
 
2.9%
Other values (164) 14772
58.4%
ASCII
ValueCountFrequency (%)
) 336
48.6%
( 336
48.6%
, 16
 
2.3%
4
 
0.6%

STD_SPCIES_NEW_CODE
Real number (ℝ)

Distinct276
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121525.11
Minimum0
Maximum935199
Zeros66
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:12.770153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile60103
Q161401
median90913
Q3120302
95-th percentile171101
Maximum935199
Range935199
Interquartile range (IQR)58901

Descriptive statistics

Standard deviation148326.05
Coefficient of variation (CV)1.2205383
Kurtosis21.138955
Mean121525.11
Median Absolute Deviation (MAD)29512
Skewness4.6589203
Sum1.2152511 × 109
Variance2.2000618 × 1010
MonotonicityNot monotonic
2023-12-11T12:18:12.909750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
90913 958
 
9.6%
60103 675
 
6.8%
60201 646
 
6.5%
61401 346
 
3.5%
61504 269
 
2.7%
61499 228
 
2.3%
100801 214
 
2.1%
61599 208
 
2.1%
120501 190
 
1.9%
171101 174
 
1.7%
Other values (266) 6092
60.9%
ValueCountFrequency (%)
0 66
0.7%
20199 1
 
< 0.1%
30199 1
 
< 0.1%
30501 6
 
0.1%
50101 47
0.5%
50103 1
 
< 0.1%
50114 5
 
0.1%
50199 23
 
0.2%
50201 38
0.4%
50204 38
0.4%
ValueCountFrequency (%)
935199 8
 
0.1%
911899 135
1.4%
911801 62
0.6%
910829 5
 
0.1%
910791 9
 
0.1%
910699 1
 
< 0.1%
910651 1
 
< 0.1%
910499 3
 
< 0.1%
811399 45
 
0.4%
811303 2
 
< 0.1%

STD_SPCIES_NEW_NM
Categorical

IMBALANCE 

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
<NA>
9872 
미역(신선/냉장)(미가공)
 
51
기타파래류(신선/냉장)(미가공)
 
45
톳(신선/냉장)(미가공)
 
14
기타미역류(신선/냉장)(미가공)
 
10
Other values (4)
 
8

Length

Max length18
Median length4
Mean length4.1449
Min length4

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row미역(신선/냉장)(미가공)

Common Values

ValueCountFrequency (%)
<NA> 9872
98.7%
미역(신선/냉장)(미가공) 51
 
0.5%
기타파래류(신선/냉장)(미가공) 45
 
0.4%
톳(신선/냉장)(미가공) 14
 
0.1%
기타미역류(신선/냉장)(미가공) 10
 
0.1%
기타다시마류(신선/냉장)(미가공) 3
 
< 0.1%
홑파래(신선/냉장)(미가공) 2
 
< 0.1%
매생이(신선/냉장)(미가공) 2
 
< 0.1%
꼬시래기(신선/냉장)(미가공) 1
 
< 0.1%

Length

2023-12-11T12:18:13.044529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:13.160494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 9872
98.7%
미역(신선/냉장)(미가공 51
 
0.5%
기타파래류(신선/냉장)(미가공 45
 
0.4%
톳(신선/냉장)(미가공 14
 
0.1%
기타미역류(신선/냉장)(미가공 10
 
0.1%
기타다시마류(신선/냉장)(미가공 3
 
< 0.1%
홑파래(신선/냉장)(미가공 2
 
< 0.1%
매생이(신선/냉장)(미가공 2
 
< 0.1%
꼬시래기(신선/냉장)(미가공 1
 
< 0.1%

STD_SPCIES_CODE
Real number (ℝ)

Distinct293
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103702.78
Minimum20199
Maximum930499
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:13.314318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20199
5-th percentile60103
Q161401
median80603
Q3120201
95-th percentile170499
Maximum930499
Range910300
Interquartile range (IQR)58800

Descriptive statistics

Standard deviation93378.872
Coefficient of variation (CV)0.90044716
Kurtosis44.782422
Mean103702.78
Median Absolute Deviation (MAD)20402
Skewness6.3513902
Sum1.0370278 × 109
Variance8.7196138 × 109
MonotonicityNot monotonic
2023-12-11T12:18:13.446515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
80413 958
 
9.6%
60103 675
 
6.8%
60201 646
 
6.5%
61401 346
 
3.5%
61504 269
 
2.7%
61499 228
 
2.3%
100801 214
 
2.1%
61599 208
 
2.1%
120501 190
 
1.9%
171101 174
 
1.7%
Other values (283) 6092
60.9%
ValueCountFrequency (%)
20199 1
 
< 0.1%
30199 1
 
< 0.1%
30501 6
 
0.1%
50101 47
 
0.5%
50103 1
 
< 0.1%
50114 5
 
0.1%
50199 23
 
0.2%
50201 38
 
0.4%
50204 38
 
0.4%
50299 160
1.6%
ValueCountFrequency (%)
930499 8
 
0.1%
910829 5
 
0.1%
910791 9
 
0.1%
910699 1
 
< 0.1%
910651 1
 
< 0.1%
910499 3
 
< 0.1%
769999 3
 
< 0.1%
761099 45
0.4%
761003 2
 
< 0.1%
761002 2
 
< 0.1%

STD_SPCIES_NM
Text

Distinct137
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:13.722174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.5998
Min length1

Characters and Unicode

Total characters25998
Distinct characters178
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

Unique12 ?
Unique (%)0.1%

Sample

1st row양송이
2nd row호박
3rd row사과
4th row표고버섯
5th row미역
ValueCountFrequency (%)
딸기 1028
 
10.3%
사과 896
 
9.0%
감귤 729
 
7.3%
배 649
 
6.5%
만감 477
 
4.8%
시금치 314
 
3.1%
풋고추 305
 
3.0%
표고버섯 258
 
2.6%
고구마 236
 
2.4%
호박 233
 
2.3%
Other values (129) 4879
48.8%
2023-12-11T12:18:14.135080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
감 1673
 
6.4%
추 1327
 
5.1%
배 1113
 
4.3%
기 1096
 
4.2%
딸 1028
 
4.0%
고 999
 
3.8%
사 949
 
3.7%
과 896
 
3.4%
귤 729
 
2.8%
이 724
 
2.8%
Other values (168) 15464
59.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25306
97.3%
Close Punctuation 336
 
1.3%
Open Punctuation 336
 
1.3%
Other Punctuation 16
 
0.1%
Space Separator 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
감 1673
 
6.6%
추 1327
 
5.2%
배 1113
 
4.4%
기 1096
 
4.3%
딸 1028
 
4.1%
고 999
 
3.9%
사 949
 
3.8%
과 896
 
3.5%
귤 729
 
2.9%
이 724
 
2.9%
Other values (164) 14772
58.4%
Close Punctuation
ValueCountFrequency (%)
) 336
100.0%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25306
97.3%
Common 692
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
감 1673
 
6.6%
추 1327
 
5.2%
배 1113
 
4.4%
기 1096
 
4.3%
딸 1028
 
4.1%
고 999
 
3.9%
사 949
 
3.8%
과 896
 
3.5%
귤 729
 
2.9%
이 724
 
2.9%
Other values (164) 14772
58.4%
Common
ValueCountFrequency (%)
) 336
48.6%
( 336
48.6%
, 16
 
2.3%
4
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25306
97.3%
ASCII 692
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
감 1673
 
6.6%
추 1327
 
5.2%
배 1113
 
4.4%
기 1096
 
4.3%
딸 1028
 
4.1%
고 999
 
3.9%
사 949
 
3.8%
과 896
 
3.5%
귤 729
 
2.9%
이 724
 
2.9%
Other values (164) 14772
58.4%
ASCII
ValueCountFrequency (%)
) 336
48.6%
( 336
48.6%
, 16
 
2.3%
4
 
0.6%

DELNG_PRUT
Real number (ℝ)

Distinct118
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.19572
Minimum0.1
Maximum40
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:14.281710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile1
Q12
median5
Q310
95-th percentile15
Maximum40
Range39.9
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.6282526
Coefficient of variation (CV)0.74700802
Kurtosis0.95975676
Mean6.19572
Median Absolute Deviation (MAD)3
Skewness1.0213281
Sum61957.2
Variance21.420722
MonotonicityNot monotonic
2023-12-11T12:18:14.420098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 1927
19.3%
5.0 1738
17.4%
2.0 1323
13.2%
4.0 1055
10.5%
1.0 930
9.3%
7.5 501
 
5.0%
8.0 490
 
4.9%
15.0 396
 
4.0%
3.0 287
 
2.9%
20.0 245
 
2.5%
Other values (108) 1108
11.1%
ValueCountFrequency (%)
0.1 41
 
0.4%
0.2 53
 
0.5%
0.3 24
 
0.2%
0.4 56
 
0.6%
0.5 197
 
2.0%
0.6 22
 
0.2%
0.7 11
 
0.1%
0.8 27
 
0.3%
0.9 7
 
0.1%
1.0 930
9.3%
ValueCountFrequency (%)
40.0 1
 
< 0.1%
25.0 1
 
< 0.1%
24.0 2
< 0.1%
23.0 4
< 0.1%
22.5 2
< 0.1%
22.1 1
 
< 0.1%
21.0 1
 
< 0.1%
20.8 1
 
< 0.1%
20.2 1
 
< 0.1%
20.1 1
 
< 0.1%

STD_UNIT_NEW_CODE
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
12
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12

Common Values

ValueCountFrequency (%)
12 10000
100.0%

Length

2023-12-11T12:18:14.572145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:14.668568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 10000
100.0%

STD_UNIT_NEW_NM
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
kg
10000 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
kg 10000
100.0%

Length

2023-12-11T12:18:14.781021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:14.884177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
kg 10000
100.0%

STD_FRMLC_NEW_CODE
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
101
7828 
107
 
513
111
 
469
108
 
334
1ZZ
 
331
Other values (6)
 
525

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row101
2nd row101
3rd row101
4th row101
5th row101

Common Values

ValueCountFrequency (%)
101 7828
78.3%
107 513
 
5.1%
111 469
 
4.7%
108 334
 
3.3%
1ZZ 331
 
3.3%
105 174
 
1.7%
102 149
 
1.5%
112 100
 
1.0%
110 72
 
0.7%
103 18
 
0.2%

Length

2023-12-11T12:18:14.982690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
101 7828
78.3%
107 513
 
5.1%
111 469
 
4.7%
108 334
 
3.3%
1zz 331
 
3.3%
105 174
 
1.7%
102 149
 
1.5%
112 100
 
1.0%
110 72
 
0.7%
103 18
 
0.2%

STD_FRMLC_NEW_NM
Categorical

IMBALANCE 

Distinct11
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
상자
7828 
파렛트
 
513
단
 
469
봉지
 
334
기타
 
331
Other values (6)
 
525

Length

Max length5
Median length2
Mean length2.0715
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상자 7828
78.3%
파렛트 513
 
5.1%
단 469
 
4.7%
봉지 334
 
3.3%
기타 331
 
3.3%
그물망 174
 
1.7%
P-BOX 149
 
1.5%
개 100
 
1.0%
접시용기 72
 
0.7%
PE대 18
 
0.2%

Length

2023-12-11T12:18:15.106412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상자 7828
78.3%
파렛트 513
 
5.1%
단 469
 
4.7%
봉지 334
 
3.3%
기타 331
 
3.3%
그물망 174
 
1.7%
p-box 149
 
1.5%
개 100
 
1.0%
접시용기 72
 
0.7%
pe대 18
 
0.2%

STD_MG_NEW_CODE
Text

Distinct57
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:15.268248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters30000
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row1ZZ
2nd row1ZZ
3rd row123
4th row1ZZ
5th row1ZZ
ValueCountFrequency (%)
1zz 5542
55.4%
124 649
 
6.5%
110 435
 
4.3%
101 420
 
4.2%
125 362
 
3.6%
123 357
 
3.6%
112 275
 
2.8%
113 202
 
2.0%
120 155
 
1.6%
116 98
 
1.0%
Other values (47) 1505
 
15.0%
2023-12-11T12:18:15.555816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11997
40.0%
Z 11084
36.9%
2 2253
 
7.5%
0 1581
 
5.3%
4 903
 
3.0%
3 795
 
2.6%
5 503
 
1.7%
6 391
 
1.3%
8 254
 
0.8%
9 128
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 18916
63.1%
Uppercase Letter 11084
36.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11997
63.4%
2 2253
 
11.9%
0 1581
 
8.4%
4 903
 
4.8%
3 795
 
4.2%
5 503
 
2.7%
6 391
 
2.1%
8 254
 
1.3%
9 128
 
0.7%
7 111
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
Z 11084
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 18916
63.1%
Latin 11084
36.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 11997
63.4%
2 2253
 
11.9%
0 1581
 
8.4%
4 903
 
4.8%
3 795
 
4.2%
5 503
 
2.7%
6 391
 
2.1%
8 254
 
1.3%
9 128
 
0.7%
7 111
 
0.6%
Latin
ValueCountFrequency (%)
Z 11084
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 30000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11997
40.0%
Z 11084
36.9%
2 2253
 
7.5%
0 1581
 
5.3%
4 903
 
3.0%
3 795
 
2.6%
5 503
 
1.7%
6 391
 
1.3%
8 254
 
0.8%
9 128
 
0.4%

STD_MG_NEW_NM
Text

Distinct57
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:15.751755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0918
Min length1

Characters and Unicode

Total characters20918
Distinct characters19
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row기타
2nd row기타
3rd row30내
4th row기타
5th row기타
ValueCountFrequency (%)
기타 5542
55.4%
40내 649
 
6.5%
10 435
 
4.3%
1 420
 
4.2%
50내 362
 
3.6%
30내 357
 
3.6%
12 275
 
2.8%
13 202
 
2.0%
20 155
 
1.6%
16 98
 
1.0%
Other values (47) 1505
 
15.0%
2023-12-11T12:18:16.085481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 5542
26.5%
타 5542
26.5%
0 2422
11.6%
1 2075
 
9.9%
내 1785
 
8.5%
4 837
 
4.0%
2 714
 
3.4%
3 661
 
3.2%
5 518
 
2.5%
6 279
 
1.3%
Other values (9) 543
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13040
62.3%
Decimal Number 7878
37.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2422
30.7%
1 2075
26.3%
4 837
 
10.6%
2 714
 
9.1%
3 661
 
8.4%
5 518
 
6.6%
6 279
 
3.5%
8 143
 
1.8%
9 122
 
1.5%
7 107
 
1.4%
Other Letter
ValueCountFrequency (%)
기 5542
42.5%
타 5542
42.5%
내 1785
 
13.7%
대 60
 
0.5%
특 46
 
0.4%
소 36
 
0.3%
중 17
 
0.1%
이 6
 
< 0.1%
상 6
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13040
62.3%
Common 7878
37.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2422
30.7%
1 2075
26.3%
4 837
 
10.6%
2 714
 
9.1%
3 661
 
8.4%
5 518
 
6.6%
6 279
 
3.5%
8 143
 
1.8%
9 122
 
1.5%
7 107
 
1.4%
Hangul
ValueCountFrequency (%)
기 5542
42.5%
타 5542
42.5%
내 1785
 
13.7%
대 60
 
0.5%
특 46
 
0.4%
소 36
 
0.3%
중 17
 
0.1%
이 6
 
< 0.1%
상 6
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13040
62.3%
ASCII 7878
37.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 5542
42.5%
타 5542
42.5%
내 1785
 
13.7%
대 60
 
0.5%
특 46
 
0.4%
소 36
 
0.3%
중 17
 
0.1%
이 6
 
< 0.1%
상 6
 
< 0.1%
ASCII
ValueCountFrequency (%)
0 2422
30.7%
1 2075
26.3%
4 837
 
10.6%
2 714
 
9.1%
3 661
 
8.4%
5 518
 
6.6%
6 279
 
3.5%
8 143
 
1.8%
9 122
 
1.5%
7 107
 
1.4%

STD_QLITY_NEW_CODE
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
11
7307 
1Z
1186 
12
773 
13
 
375
19
 
141
Other values (5)
 
218

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row12
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 7307
73.1%
1Z 1186
 
11.9%
12 773
 
7.7%
13 375
 
3.8%
19 141
 
1.4%
15 108
 
1.1%
14 73
 
0.7%
16 32
 
0.3%
17 4
 
< 0.1%
18 1
 
< 0.1%

Length

2023-12-11T12:18:16.228801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:16.366395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 7307
73.1%
1z 1186
 
11.9%
12 773
 
7.7%
13 375
 
3.8%
19 141
 
1.4%
15 108
 
1.1%
14 73
 
0.7%
16 32
 
0.3%
17 4
 
< 0.1%
18 1
 
< 0.1%

STD_QLITY_NEW_NM
Categorical

IMBALANCE 

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
특
7307 
무등급
1186 
상
773 
보통
 
375
등외
 
141
Other values (5)
 
218

Length

Max length3
Median length1
Mean length1.3106
Min length1

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row상
2nd row특
3rd row특
4th row특
5th row특

Common Values

ValueCountFrequency (%)
특 7307
73.1%
무등급 1186
 
11.9%
상 773
 
7.7%
보통 375
 
3.8%
등외 141
 
1.4%
5등 108
 
1.1%
4등 73
 
0.7%
6등 32
 
0.3%
7등 4
 
< 0.1%
8등 1
 
< 0.1%

Length

2023-12-11T12:18:16.523199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:16.659185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
특 7307
73.1%
무등급 1186
 
11.9%
상 773
 
7.7%
보통 375
 
3.8%
등외 141
 
1.4%
5등 108
 
1.1%
4등 73
 
0.7%
6등 32
 
0.3%
7등 4
 
< 0.1%
8등 1
 
< 0.1%

CPR_USE_PRDLST_CODE
Real number (ℝ)

Distinct366
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3793544 × 109
Minimum1.002001 × 109
Maximum1.2003101 × 1011
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:16.827283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.002001 × 109
5-th percentile2.001001 × 109
Q12.001014 × 109
median3.001003 × 109
Q33.005002 × 109
95-th percentile4.002003 × 109
Maximum1.2003101 × 1011
Range1.1902901 × 1011
Interquartile range (IQR)1.003988 × 109

Descriptive statistics

Standard deviation6.9804621 × 109
Coefficient of variation (CV)2.06562
Kurtosis172.27518
Mean3.3793544 × 109
Median Absolute Deviation (MAD)9.9799897 × 108
Skewness11.916553
Sum3.3793544 × 1013
Variance4.8726851 × 1019
MonotonicityNot monotonic
2023-12-11T12:18:17.001044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2003004030 958
 
9.6%
2001001048 675
 
6.8%
2001002010 646
 
6.5%
2001014010 322
 
3.2%
2001017004 269
 
2.7%
3005005004 190
 
1.9%
4002003003 188
 
1.9%
3003008001 188
 
1.9%
2001014999 179
 
1.8%
4002010001 173
 
1.7%
Other values (356) 6212
62.1%
ValueCountFrequency (%)
1002001017 1
 
< 0.1%
1003001999 1
 
< 0.1%
1003005001 1
 
< 0.1%
2001001035 4
 
< 0.1%
2001001048 675
6.8%
2001001055 45
 
0.4%
2001001056 135
 
1.4%
2001001087 1
 
< 0.1%
2001001100 2
 
< 0.1%
2001001104 4
 
< 0.1%
ValueCountFrequency (%)
120031011099 2
 
< 0.1%
120030010012 2
 
< 0.1%
120030010011 2
 
< 0.1%
120030010010 2
 
< 0.1%
120029010010 8
 
0.1%
120014010016 5
 
0.1%
41005999999 30
0.3%
41005999001 4
 
< 0.1%
41005010001 7
 
0.1%
41005007002 17
0.2%

CPR_USE_PRDLST_NM
Text

Distinct147
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
2023-12-11T12:18:17.321177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length2
Mean length2.6289
Min length1

Characters and Unicode

Total characters26289
Distinct characters183
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.2%

Sample

1st row양송이
2nd row호박
3rd row사과
4th row표고버섯
5th row미역
ValueCountFrequency (%)
딸기 1028
 
10.3%
사과 896
 
9.0%
배 649
 
6.5%
감귤 602
 
6.0%
만감 508
 
5.1%
시금치 314
 
3.1%
풋고추 305
 
3.0%
표고버섯 258
 
2.6%
고구마 236
 
2.4%
호박 233
 
2.3%
Other values (137) 4971
49.7%
2023-12-11T12:18:17.860437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
감 1577
 
6.0%
추 1357
 
5.2%
기 1173
 
4.5%
고 1088
 
4.1%
배 1043
 
4.0%
딸 1028
 
3.9%
사 934
 
3.6%
과 904
 
3.4%
이 725
 
2.8%
귤 604
 
2.3%
Other values (173) 15856
60.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 25515
97.1%
Close Punctuation 387
 
1.5%
Open Punctuation 387
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
감 1577
 
6.2%
추 1357
 
5.3%
기 1173
 
4.6%
고 1088
 
4.3%
배 1043
 
4.1%
딸 1028
 
4.0%
사 934
 
3.7%
과 904
 
3.5%
이 725
 
2.8%
귤 604
 
2.4%
Other values (171) 15082
59.1%
Close Punctuation
ValueCountFrequency (%)
) 387
100.0%
Open Punctuation
ValueCountFrequency (%)
( 387
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25515
97.1%
Common 774
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
감 1577
 
6.2%
추 1357
 
5.3%
기 1173
 
4.6%
고 1088
 
4.3%
배 1043
 
4.1%
딸 1028
 
4.0%
사 934
 
3.7%
과 904
 
3.5%
이 725
 
2.8%
귤 604
 
2.4%
Other values (171) 15082
59.1%
Common
ValueCountFrequency (%)
) 387
50.0%
( 387
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25515
97.1%
ASCII 774
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
감 1577
 
6.2%
추 1357
 
5.3%
기 1173
 
4.6%
고 1088
 
4.3%
배 1043
 
4.1%
딸 1028
 
4.0%
사 934
 
3.7%
과 904
 
3.5%
이 725
 
2.8%
귤 604
 
2.4%
Other values (171) 15082
59.1%
ASCII
ValueCountFrequency (%)
) 387
50.0%
( 387
50.0%

SBID_PRIC
Real number (ℝ)

Distinct1265
Distinct (%)12.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19604.152
Minimum244
Maximum357000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:18.018461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum244
5-th percentile2200
Q18000
median15200
Q324500
95-th percentile54000
Maximum357000
Range356756
Interquartile range (IQR)16500

Descriptive statistics

Standard deviation19056.61
Coefficient of variation (CV)0.97207008
Kurtosis37.571804
Mean19604.152
Median Absolute Deviation (MAD)8045
Skewness4.1007833
Sum1.9604152 × 108
Variance3.6315437 × 108
MonotonicityNot monotonic
2023-12-11T12:18:18.174083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15000 226
 
2.3%
10000 225
 
2.2%
18000 221
 
2.2%
16000 202
 
2.0%
12000 187
 
1.9%
20000 184
 
1.8%
17000 181
 
1.8%
13000 176
 
1.8%
14000 164
 
1.6%
5000 159
 
1.6%
Other values (1255) 8075
80.8%
ValueCountFrequency (%)
244 1
 
< 0.1%
250 1
 
< 0.1%
261 1
 
< 0.1%
263 2
< 0.1%
264 1
 
< 0.1%
265 3
< 0.1%
270 3
< 0.1%
272 1
 
< 0.1%
273 2
< 0.1%
280 3
< 0.1%
ValueCountFrequency (%)
357000 1
< 0.1%
340000 1
< 0.1%
280000 1
< 0.1%
273420 1
< 0.1%
246840 1
< 0.1%
233750 1
< 0.1%
229500 1
< 0.1%
212000 1
< 0.1%
184500 1
< 0.1%
180000 1
< 0.1%

SHIPMNT_SE_CODE
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
3
6570 
2
2064 
4
1291 
1
 
75

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3
2nd row3
3rd row3
4th row2
5th row4

Common Values

ValueCountFrequency (%)
3 6570
65.7%
2 2064
 
20.6%
4 1291
 
12.9%
1 75
 
0.8%

Length

2023-12-11T12:18:18.684232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:18.816522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 6570
65.7%
2 2064
 
20.6%
4 1291
 
12.9%
1 75
 
0.8%

SHIPMNT_SE_NM
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
개별
6570 
계통
2064 
상인
1291 
협동
 
75

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개별
2nd row개별
3rd row개별
4th row계통
5th row상인

Common Values

ValueCountFrequency (%)
개별 6570
65.7%
계통 2064
 
20.6%
상인 1291
 
12.9%
협동 75
 
0.8%

Length

2023-12-11T12:18:18.935734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:18:19.057929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개별 6570
65.7%
계통 2064
 
20.6%
상인 1291
 
12.9%
협동 75
 
0.8%

STD_MTC_NEW_CODE
Real number (ℝ)

ZEROS 

Distinct91
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12879.66
Minimum0
Maximum99000
Zeros8037
Zeros (%)80.4%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:19.220291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile90200
Maximum99000
Range99000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation28809.559
Coefficient of variation (CV)2.2368261
Kurtosis2.7349555
Mean12879.66
Median Absolute Deviation (MAD)0
Skewness2.0686554
Sum1.287966 × 108
Variance8.2999071 × 108
MonotonicityNot monotonic
2023-12-11T12:18:19.391266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 8037
80.4%
90100 326
 
3.3%
99000 165
 
1.7%
90600 80
 
0.8%
59000 57
 
0.6%
80100 52
 
0.5%
90200 50
 
0.5%
98000 48
 
0.5%
31700 47
 
0.5%
95000 42
 
0.4%
Other values (81) 1096
 
11.0%
ValueCountFrequency (%)
0 8037
80.4%
10000 5
 
0.1%
11400 2
 
< 0.1%
12000 13
 
0.1%
12500 27
 
0.3%
12600 28
 
0.3%
12700 9
 
0.1%
12900 4
 
< 0.1%
13900 5
 
0.1%
15200 12
 
0.1%
ValueCountFrequency (%)
99000 165
1.7%
98000 48
 
0.5%
97000 24
 
0.2%
96000 4
 
< 0.1%
95000 42
 
0.4%
94000 25
 
0.2%
93000 19
 
0.2%
91000 8
 
0.1%
90700 1
 
< 0.1%
90600 80
0.8%

STD_MTC_NEW_NM
Text

MISSING 

Distinct90
Distinct (%)4.6%
Missing8037
Missing (%)80.4%
Memory size156.2 KiB
2023-12-11T12:18:19.696364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length6.5568008
Min length3

Characters and Unicode

Total characters12871
Distinct characters82
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)0.4%

Sample

1st row전라남도
2nd row서울특별시
3rd row충청남도 부여군
4th row경기도 하남시
5th row대전광역시
ValueCountFrequency (%)
서울특별시 326
 
10.9%
전라남도 303
 
10.1%
경상남도 218
 
7.3%
제주특별자치도 165
 
5.5%
충청남도 155
 
5.2%
경상북도 142
 
4.7%
경기도 133
 
4.4%
충청북도 125
 
4.2%
광주광역시 80
 
2.7%
전라북도 75
 
2.5%
Other values (82) 1279
42.6%
2023-12-11T12:18:20.172383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
도 1423
 
11.1%
1038
 
8.1%
군 868
 
6.7%
남 778
 
6.0%
시 741
 
5.8%
경 493
 
3.8%
특 491
 
3.8%
별 491
 
3.8%
전 419
 
3.3%
라 378
 
2.9%
Other values (72) 5751
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11833
91.9%
Space Separator 1038
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 1423
 
12.0%
군 868
 
7.3%
남 778
 
6.6%
시 741
 
6.3%
경 493
 
4.2%
특 491
 
4.1%
별 491
 
4.1%
전 419
 
3.5%
라 378
 
3.2%
상 360
 
3.0%
Other values (71) 5391
45.6%
Space Separator
ValueCountFrequency (%)
1038
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11833
91.9%
Common 1038
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 1423
 
12.0%
군 868
 
7.3%
남 778
 
6.6%
시 741
 
6.3%
경 493
 
4.2%
특 491
 
4.1%
별 491
 
4.1%
전 419
 
3.5%
라 378
 
3.2%
상 360
 
3.0%
Other values (71) 5391
45.6%
Common
ValueCountFrequency (%)
1038
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11833
91.9%
ASCII 1038
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
도 1423
 
12.0%
군 868
 
7.3%
남 778
 
6.6%
시 741
 
6.3%
경 493
 
4.2%
특 491
 
4.1%
별 491
 
4.1%
전 419
 
3.5%
라 378
 
3.2%
상 360
 
3.0%
Other values (71) 5391
45.6%
ASCII
ValueCountFrequency (%)
1038
100.0%

CPR_MTC_CODE
Real number (ℝ)

Distinct910
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean560517.91
Minimum50106
Maximum990000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:20.348437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50106
5-th percentile138701
Q1373800
median627705
Q3697600
95-th percentile902000
Maximum990000
Range939894
Interquartile range (IQR)323800

Descriptive statistics

Standard deviation212173.25
Coefficient of variation (CV)0.37853073
Kurtosis-0.50477489
Mean560517.91
Median Absolute Deviation (MAD)110705
Skewness-0.30207344
Sum5.6051791 × 109
Variance4.5017489 × 1010
MonotonicityNot monotonic
2023-12-11T12:18:20.520349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
138701 622
 
6.2%
901000 326
 
3.3%
697600 243
 
2.4%
990000 165
 
1.7%
138160 160
 
1.6%
697815 148
 
1.5%
690600 147
 
1.5%
695842 127
 
1.3%
690811 105
 
1.1%
714850 105
 
1.1%
Other values (900) 7852
78.5%
ValueCountFrequency (%)
50106 3
 
< 0.1%
130060 2
 
< 0.1%
130863 4
 
< 0.1%
131140 1
 
< 0.1%
138050 4
 
< 0.1%
138160 160
 
1.6%
138701 622
6.2%
157290 4
 
< 0.1%
157740 5
 
0.1%
200140 11
 
0.1%
ValueCountFrequency (%)
990000 165
1.7%
980000 48
 
0.5%
970000 24
 
0.2%
960000 4
 
< 0.1%
950000 42
 
0.4%
940000 25
 
0.2%
930000 19
 
0.2%
910000 8
 
0.1%
907000 1
 
< 0.1%
906000 80
0.8%

CPR_MTC_NM
Text

Distinct229
Distinct (%)2.3%
Missing4
Missing (%)< 0.1%
Memory size156.2 KiB
2023-12-11T12:18:20.879069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length6
Mean length5.7663065
Min length2

Characters and Unicode

Total characters57640
Distinct characters128
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 (%)0.3%

Sample

1st row대구 달성군
2nd row전남 구례군
3rd row경남 밀양시
4th row전남
5th row서울
ValueCountFrequency (%)
경남 1703
 
9.0%
제주 1528
 
8.0%
서울 1107
 
5.8%
충남 1059
 
5.6%
전남 969
 
5.1%
경북 881
 
4.6%
송파구 769
 
4.0%
충북 675
 
3.5%
서귀포시 630
 
3.3%
경기 424
 
2.2%
Other values (205) 9281
48.8%
2023-12-11T12:18:21.457217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9030
15.7%
시 4309
 
7.5%
남 4236
 
7.3%
주 3979
 
6.9%
군 3221
 
5.6%
경 3105
 
5.4%
제 2333
 
4.0%
북 2210
 
3.8%
서 2094
 
3.6%
충 1980
 
3.4%
Other values (118) 21143
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48564
84.3%
Space Separator 9030
 
15.7%
Other Punctuation 28
 
< 0.1%
Decimal Number 9
 
< 0.1%
Open Punctuation 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4309
 
8.9%
남 4236
 
8.7%
주 3979
 
8.2%
군 3221
 
6.6%
경 3105
 
6.4%
제 2333
 
4.8%
북 2210
 
4.6%
서 2094
 
4.3%
충 1980
 
4.1%
구 1957
 
4.0%
Other values (114) 19140
39.4%
Space Separator
ValueCountFrequency (%)
9030
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 28
100.0%
Decimal Number
ValueCountFrequency (%)
2 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48564
84.3%
Common 9076
 
15.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4309
 
8.9%
남 4236
 
8.7%
주 3979
 
8.2%
군 3221
 
6.6%
경 3105
 
6.4%
제 2333
 
4.8%
북 2210
 
4.6%
서 2094
 
4.3%
충 1980
 
4.1%
구 1957
 
4.0%
Other values (114) 19140
39.4%
Common
ValueCountFrequency (%)
9030
99.5%
/ 28
 
0.3%
2 9
 
0.1%
( 9
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48564
84.3%
ASCII 9076
 
15.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9030
99.5%
/ 28
 
0.3%
2 9
 
0.1%
( 9
 
0.1%
Hangul
ValueCountFrequency (%)
시 4309
 
8.9%
남 4236
 
8.7%
주 3979
 
8.2%
군 3221
 
6.6%
경 3105
 
6.4%
제 2333
 
4.8%
북 2210
 
4.6%
서 2094
 
4.3%
충 1980
 
4.1%
구 1957
 
4.0%
Other values (114) 19140
39.4%

DELNG_QY
Real number (ℝ)

Distinct229
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.8282
Minimum1
Maximum900
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-11T12:18:21.625335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median12
Q335
95-th percentile108
Maximum900
Range899
Interquartile range (IQR)31

Descriptive statistics

Standard deviation60.027899
Coefficient of variation (CV)1.8859973
Kurtosis39.972888
Mean31.8282
Median Absolute Deviation (MAD)10
Skewness5.3333994
Sum318282
Variance3603.3486
MonotonicityNot monotonic
2023-12-11T12:18:21.796681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1010
 
10.1%
2 669
 
6.7%
10 589
 
5.9%
5 573
 
5.7%
3 528
 
5.3%
4 410
 
4.1%
20 391
 
3.9%
6 297
 
3.0%
8 261
 
2.6%
7 250
 
2.5%
Other values (219) 5022
50.2%
ValueCountFrequency (%)
1 1010
10.1%
2 669
6.7%
3 528
5.3%
4 410
4.1%
5 573
5.7%
6 297
 
3.0%
7 250
 
2.5%
8 261
 
2.6%
9 169
 
1.7%
10 589
5.9%
ValueCountFrequency (%)
900 1
 
< 0.1%
800 2
< 0.1%
795 1
 
< 0.1%
720 1
 
< 0.1%
700 1
 
< 0.1%
625 2
< 0.1%
620 1
 
< 0.1%
600 3
< 0.1%
580 1
 
< 0.1%
560 2
< 0.1%

Sample

DELNG_DESBID_TIMEWHSAL_MRKT_NEW_CODEWHSAL_MRKT_NEW_NMCPR_CODECPR_NMAUC_SE_CODEAUC_SE_NMWHSAL_MRKT_CODEWHSAL_MRKT_NMLEDG_NOSLE_SEQNCATGORY_NEW_CODECATGORY_NEW_NMCATGORY_CODECATGORY_NMSTD_PRDLST_NEW_CODESTD_PRDLST_NEW_NMSTD_PRDLST_CODESTD_PRDLST_NMSTD_SPCIES_NEW_CODESTD_SPCIES_NEW_NMSTD_SPCIES_CODESTD_SPCIES_NMDELNG_PRUTSTD_UNIT_NEW_CODESTD_UNIT_NEW_NMSTD_FRMLC_NEW_CODESTD_FRMLC_NEW_NMSTD_MG_NEW_CODESTD_MG_NEW_NMSTD_QLITY_NEW_CODESTD_QLITY_NEW_NMCPR_USE_PRDLST_CODECPR_USE_PRDLST_NMSBID_PRICSHIPMNT_SE_CODESHIPMNT_SE_NMSTD_MTC_NEW_CODESTD_MTC_NEW_NMCPR_MTC_CODECPR_MTC_NMDELNG_QY
1727420200114<NA><NA><NA>8808990001081북대구공판장1경매<NA><NA>9634017버섯류17버섯류1702양송이1702양송이170299<NA>170299양송이2.012kg101상자1ZZ기타12상4002002010양송이130003개별0<NA>711821대구 달성군2
1021120200114<NA><NA><NA>8808990000923대전공판장1경매<NA><NA>1001409과채류9과채류902호박902호박90201<NA>90201호박8.012kg101상자1ZZ기타11특3002002016호박376003개별0<NA>542802전남 구례군5
1855020200114<NA><NA><NA>8808990001098반여공판장1경매<NA><NA>3360406과실류6과실류601사과601사과60103<NA>60103사과10.012kg101상자12330내11특2001001048사과150003개별0<NA>627830경남 밀양시2
205820200114<NA><NA><NA>8808990000824강서공판장1경매<NA><NA>47219017버섯류17버섯류1704표고버섯1704표고버섯170401<NA>170401표고버섯4.012kg101상자1ZZ기타11특4002003003표고버섯400002계통95000전라남도950000전남2
8420200114<NA><NA><NA>8808990000794안산공판장2정가수의<NA><NA>12430081해조류76신선 해조류8109미역류7607미역810901미역(신선/냉장)(미가공)760702미역4.012kg101상자1ZZ기타11특41005004016미역150004상인90100서울특별시901000서울2
1744720200114<NA><NA><NA>8808990001098반여공판장2정가수의<NA><NA>20001182010엽경채류10엽경채류1031청경채1031청경채103101<NA>103101청경채4.012kg101상자106611특3003031001청경채198963개별0<NA>138701서울 송파구20
1668720200114<NA><NA><NA>8808990001081북대구공판장1경매<NA><NA>7473012조미채소류12조미채소류1203쪽파1203쪽파120302<NA>120302쪽파1.012kg111단1ZZ기타11특3005003001쪽파32003개별0<NA>695835제주 북제주군20
2494020200114<NA><NA><NA>8808990004099인천원예농협삼산공판장2정가수의<NA><NA>306506과실류6과실류615만감615만감61504<NA>61504만감5.012kg101상자1ZZ기타11특2001017004만감180004상인0<NA>697600제주 서귀포시20
1120620200114<NA><NA><NA>8808990000923대전공판장1경매<NA><NA>21085013양채류13양채류1307케일1307케일130706<NA>130706케일1.012kg101상자1ZZ기타1Z무등급3006008005케일100002계통0<NA>306010대전 대덕구5
2484220200114<NA><NA><NA>8808990004099인천원예농협삼산공판장1경매<NA><NA>2311009과채류8과일과채류909딸기804딸기90913<NA>80413딸기2.012kg101상자101111특2003004030딸기80003개별0<NA>667890경남 하동군11
DELNG_DESBID_TIMEWHSAL_MRKT_NEW_CODEWHSAL_MRKT_NEW_NMCPR_CODECPR_NMAUC_SE_CODEAUC_SE_NMWHSAL_MRKT_CODEWHSAL_MRKT_NMLEDG_NOSLE_SEQNCATGORY_NEW_CODECATGORY_NEW_NMCATGORY_CODECATGORY_NMSTD_PRDLST_NEW_CODESTD_PRDLST_NEW_NMSTD_PRDLST_CODESTD_PRDLST_NMSTD_SPCIES_NEW_CODESTD_SPCIES_NEW_NMSTD_SPCIES_CODESTD_SPCIES_NMDELNG_PRUTSTD_UNIT_NEW_CODESTD_UNIT_NEW_NMSTD_FRMLC_NEW_CODESTD_FRMLC_NEW_NMSTD_MG_NEW_CODESTD_MG_NEW_NMSTD_QLITY_NEW_CODESTD_QLITY_NEW_NMCPR_USE_PRDLST_CODECPR_USE_PRDLST_NMSBID_PRICSHIPMNT_SE_CODESHIPMNT_SE_NMSTD_MTC_NEW_CODESTD_MTC_NEW_NMCPR_MTC_CODECPR_MTC_NMDELNG_QY
327120200114<NA><NA><NA>8808990000824강서공판장1경매<NA><NA>8512406과실류6과실류601사과601사과60103<NA>60103사과5.012kg101상자1131311특2001001048사과90003개별94000충청북도940000충북22
1802820200114<NA><NA><NA>8808990001098반여공판장1경매<NA><NA>2501806과실류6과실류615만감615만감61504<NA>61504만감5.012kg101상자1121211특2001017004만감230004상인0<NA>697600제주 서귀포시26
1923620200114<NA><NA><NA>8808990001098반여공판장1경매<NA><NA>5043011근채류11근채류1101무1101무110199<NA>110199무23.012kg108봉지1131311특3004001012무125003개별0<NA>695841제주 북제주군45
2847920200114<NA><NA><NA>8808990028323춘천원예농업협동조합2정가수의<NA><NA>5221010엽경채류10엽경채류1008시금치1008시금치100803<NA>100803시금치0.312kg111단1ZZ기타11특3003008005시금치17004상인0<NA>138160서울 송파구25
1456820200114<NA><NA><NA>8808990000961광주공판장1경매<NA><NA>805206과실류6과실류602배602배60201<NA>60201배7.512kg1ZZ기타1121211특2001002010배145003개별0<NA>520820전남 나주시95
1407820200114<NA><NA><NA>8808990000961광주공판장1경매<NA><NA>51231013양채류13양채류1302피망(단고추)1302피망(단고추)130205<NA>130205피망(단고추)8.012kg1ZZ기타1ZZ기타1Z무등급3006003001피망(단고추)50003개별0<NA>520951전남 나주시1
712620200114<NA><NA><NA>8808990000855가락공판장1경매<NA><NA>157606과실류6과실류614감귤614감귤61401<NA>61401감귤10.012kg101상자1ZZ기타19등외2001014010감귤50003개별0<NA>690072제주 제주시1
373520200114<NA><NA><NA>8808990000831구리공판장1경매<NA><NA>2172010엽경채류10엽경채류1004양배추1004양배추100401<NA>100401양배추10.012kg101상자109911특3003004008양배추30003개별0<NA>356980충남 서산시2
607920200114<NA><NA><NA>8808990000855가락공판장1경매<NA><NA>11121109과채류9과채류902호박902호박90201<NA>90201호박8.012kg101상자1ZZ기타12상3002002006호박280003개별0<NA>678960경남 합천군15
594120200114<NA><NA><NA>8808990000855가락공판장1경매<NA><NA>1092609과채류9과채류902호박902호박90201<NA>90201호박8.012kg101상자1ZZ기타13보통3002002006호박210003개별0<NA>660380경남 진주시1