Overview

Dataset statistics

Number of variables22
Number of observations77
Missing cells179
Missing cells (%)10.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory14.7 KiB
Average record size in memory195.7 B

Variable types

Categorical5
Text2
Numeric15

Dataset

Description도매시장 통계연보에 수립된 전국의 산지 공판장 현황 정보(소재지명,거래실적,물류장비,시설규모,유통주체현황 등)를 제공합니다.
Author한국농수산식품유통공사
URLhttps://www.data.go.kr/data/15072153/fileData.do

Alerts

전동차 수 is highly imbalanced (68.2%)Imbalance
거래실적(19년도)(백만원) has 3 (3.9%) missing valuesMissing
국비 has 34 (44.2%) missing valuesMissing
지방비 has 41 (53.2%) missing valuesMissing
자부담 has 20 (26.0%) missing valuesMissing
기타 has 63 (81.8%) missing valuesMissing
대지규모(제곱미터) has 6 (7.8%) missing valuesMissing
건물면적(제곱미터) has 3 (3.9%) missing valuesMissing
경매장(제곱미터) has 9 (11.7%) missing valuesMissing
지게차 수 has 23 (29.9%) zerosZeros
콘베이어 수 has 67 (87.0%) zerosZeros
선별기 수 has 52 (67.5%) zerosZeros
경매사 수 has 24 (31.2%) zerosZeros
유통주체(중도매인) 수 has 20 (26.0%) zerosZeros
유통주체(산지유통인) 수 has 57 (74.0%) zerosZeros

Reproduction

Analysis started2023-12-12 20:11:53.481056
Analysis finished2023-12-12 20:11:53.818889
Duration0.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

부류
Categorical

Distinct5
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size748.0 B
청과
47 
임산
24 
화훼
 
4
수산
 
1
약용
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row청과
2nd row청과
3rd row청과
4th row청과
5th row임산

Common Values

ValueCountFrequency (%)
청과 47
61.0%
임산 24
31.2%
화훼 4
 
5.2%
수산 1
 
1.3%
약용 1
 
1.3%

Length

2023-12-13T05:11:53.886045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:54.289622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청과 47
61.0%
임산 24
31.2%
화훼 4
 
5.2%
수산 1
 
1.3%
약용 1
 
1.3%

소재지
Categorical

Distinct9
Distinct (%)11.7%
Missing0
Missing (%)0.0%
Memory size748.0 B
경북
34 
강원
9 
경남
9 
충남
7 
전남
7 
Other values (4)
11 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row충남
2nd row전남
3rd row전남
4th row전북
5th row강원

Common Values

ValueCountFrequency (%)
경북 34
44.2%
강원 9
 
11.7%
경남 9
 
11.7%
충남 7
 
9.1%
전남 7
 
9.1%
전북 5
 
6.5%
충북 4
 
5.2%
제주 1
 
1.3%
서울 1
 
1.3%

Length

2023-12-13T05:11:54.435073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:54.549529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경북 34
44.2%
강원 9
 
11.7%
경남 9
 
11.7%
충남 7
 
9.1%
전남 7
 
9.1%
전북 5
 
6.5%
충북 4
 
5.2%
제주 1
 
1.3%
서울 1
 
1.3%

공판장 명칭
Text

Distinct76
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T05:11:54.792439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length7.8571429
Min length4

Characters and Unicode

Total characters605
Distinct characters115
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

Unique75 ?
Unique (%)97.4%

Sample

1st row공주농협
2nd row목포원예농협
3rd row여수원예농협
4th row군산원예농협
5th row강릉산림조합
ValueCountFrequency (%)
농산물공판장 4
 
3.8%
공판장지점 3
 
2.9%
공판장 3
 
2.9%
용암농협 2
 
1.9%
여수원예농협 2
 
1.9%
신경주농협 1
 
1.0%
풍기인삼공판장 1
 
1.0%
진안산림조합 1
 
1.0%
인제산림조합 1
 
1.0%
성주조공법인 1
 
1.0%
Other values (86) 86
81.9%
2023-12-13T05:11:55.257365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
농 54
 
8.9%
협 47
 
7.8%
산 39
 
6.4%
28
 
4.6%
조 26
 
4.3%
합 25
 
4.1%
림 24
 
4.0%
공 20
 
3.3%
장 18
 
3.0%
판 17
 
2.8%
Other values (105) 307
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 569
94.0%
Space Separator 28
 
4.6%
Math Symbol 4
 
0.7%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
농 54
 
9.5%
협 47
 
8.3%
산 39
 
6.9%
조 26
 
4.6%
합 25
 
4.4%
림 24
 
4.2%
공 20
 
3.5%
장 18
 
3.2%
판 17
 
3.0%
주 15
 
2.6%
Other values (100) 284
49.9%
Math Symbol
ValueCountFrequency (%)
< 2
50.0%
> 2
50.0%
Space Separator
ValueCountFrequency (%)
28
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 569
94.0%
Common 36
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
농 54
 
9.5%
협 47
 
8.3%
산 39
 
6.9%
조 26
 
4.6%
합 25
 
4.4%
림 24
 
4.2%
공 20
 
3.5%
장 18
 
3.2%
판 17
 
3.0%
주 15
 
2.6%
Other values (100) 284
49.9%
Common
ValueCountFrequency (%)
28
77.8%
) 2
 
5.6%
( 2
 
5.6%
< 2
 
5.6%
> 2
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 569
94.0%
ASCII 36
 
6.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
농 54
 
9.5%
협 47
 
8.3%
산 39
 
6.9%
조 26
 
4.6%
합 25
 
4.4%
림 24
 
4.2%
공 20
 
3.5%
장 18
 
3.2%
판 17
 
3.0%
주 15
 
2.6%
Other values (100) 284
49.9%
ASCII
ValueCountFrequency (%)
28
77.8%
) 2
 
5.6%
( 2
 
5.6%
< 2
 
5.6%
> 2
 
5.6%

주소
Text

Distinct76
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size748.0 B
2023-12-13T05:11:55.724349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length14.285714
Min length9

Characters and Unicode

Total characters1100
Distinct characters146
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique75 ?
Unique (%)97.4%

Sample

1st row공주시 금성길 19
2nd row목포시 영산로 575
3rd row여수시 남산북9길 20
4th row군산시 하포로 29
5th row강릉시 옥가로 27
ValueCountFrequency (%)
중앙로 6
 
2.1%
의성군 5
 
1.8%
성주군 4
 
1.4%
의성읍 3
 
1.1%
64 3
 
1.1%
창녕군 3
 
1.1%
청도군 3
 
1.1%
13 3
 
1.1%
공주시 2
 
0.7%
남문로 2
 
0.7%
Other values (230) 248
87.9%
2023-12-13T05:11:56.286724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219
 
19.9%
로 59
 
5.4%
1 45
 
4.1%
2 43
 
3.9%
군 41
 
3.7%
시 35
 
3.2%
3 31
 
2.8%
읍 28
 
2.5%
성 24
 
2.2%
주 22
 
2.0%
Other values (136) 553
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 630
57.3%
Decimal Number 240
 
21.8%
Space Separator 219
 
19.9%
Dash Punctuation 9
 
0.8%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 59
 
9.4%
군 41
 
6.5%
시 35
 
5.6%
읍 28
 
4.4%
성 24
 
3.8%
주 22
 
3.5%
길 20
 
3.2%
산 19
 
3.0%
면 16
 
2.5%
천 14
 
2.2%
Other values (122) 352
55.9%
Decimal Number
ValueCountFrequency (%)
1 45
18.8%
2 43
17.9%
3 31
12.9%
0 21
8.8%
4 21
8.8%
9 19
7.9%
7 18
 
7.5%
6 17
 
7.1%
5 16
 
6.7%
8 9
 
3.8%
Space Separator
ValueCountFrequency (%)
219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 630
57.3%
Common 470
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 59
 
9.4%
군 41
 
6.5%
시 35
 
5.6%
읍 28
 
4.4%
성 24
 
3.8%
주 22
 
3.5%
길 20
 
3.2%
산 19
 
3.0%
면 16
 
2.5%
천 14
 
2.2%
Other values (122) 352
55.9%
Common
ValueCountFrequency (%)
219
46.6%
1 45
 
9.6%
2 43
 
9.1%
3 31
 
6.6%
0 21
 
4.5%
4 21
 
4.5%
9 19
 
4.0%
7 18
 
3.8%
6 17
 
3.6%
5 16
 
3.4%
Other values (4) 20
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 630
57.3%
ASCII 470
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
46.6%
1 45
 
9.6%
2 43
 
9.1%
3 31
 
6.6%
0 21
 
4.5%
4 21
 
4.5%
9 19
 
4.0%
7 18
 
3.8%
6 17
 
3.6%
5 16
 
3.4%
Other values (4) 20
 
4.3%
Hangul
ValueCountFrequency (%)
로 59
 
9.4%
군 41
 
6.5%
시 35
 
5.6%
읍 28
 
4.4%
성 24
 
3.8%
주 22
 
3.5%
길 20
 
3.2%
산 19
 
3.0%
면 16
 
2.5%
천 14
 
2.2%
Other values (122) 352
55.9%

개장년도
Real number (ℝ)

Distinct38
Distinct (%)49.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1997.1688
Minimum1957
Maximum2019
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:56.469045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1957
5-th percentile1969.4
Q11990
median1998
Q32011
95-th percentile2016
Maximum2019
Range62
Interquartile range (IQR)21

Descriptive statistics

Standard deviation14.742886
Coefficient of variation (CV)0.0073818929
Kurtosis-0.10718466
Mean1997.1688
Median Absolute Deviation (MAD)11
Skewness-0.6373951
Sum153782
Variance217.3527
MonotonicityIncreasing
2023-12-13T05:11:56.622603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1999 8
 
10.4%
2011 6
 
7.8%
2016 5
 
6.5%
1997 4
 
5.2%
1995 4
 
5.2%
2008 3
 
3.9%
2015 3
 
3.9%
1991 3
 
3.9%
2001 2
 
2.6%
2006 2
 
2.6%
Other values (28) 37
48.1%
ValueCountFrequency (%)
1957 1
1.3%
1963 1
1.3%
1965 1
1.3%
1967 1
1.3%
1970 2
2.6%
1974 1
1.3%
1975 1
1.3%
1979 2
2.6%
1980 1
1.3%
1981 1
1.3%
ValueCountFrequency (%)
2019 1
 
1.3%
2017 2
 
2.6%
2016 5
6.5%
2015 3
3.9%
2014 1
 
1.3%
2013 1
 
1.3%
2012 1
 
1.3%
2011 6
7.8%
2009 1
 
1.3%
2008 3
3.9%

거래실적(19년도)(백만원)
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)98.6%
Missing3
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean11370.419
Minimum4
Maximum68348
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:56.776456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile205.85
Q11269
median4689.5
Q314587
95-th percentile45552.8
Maximum68348
Range68344
Interquartile range (IQR)13318

Descriptive statistics

Standard deviation15809.716
Coefficient of variation (CV)1.3904251
Kurtosis4.388226
Mean11370.419
Median Absolute Deviation (MAD)4326.5
Skewness2.127992
Sum841411
Variance2.4994713 × 108
MonotonicityNot monotonic
2023-12-13T05:11:56.911393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35728 2
 
2.6%
6120 1
 
1.3%
698 1
 
1.3%
184 1
 
1.3%
838 1
 
1.3%
59910 1
 
1.3%
4753 1
 
1.3%
3084 1
 
1.3%
11765 1
 
1.3%
1855 1
 
1.3%
Other values (63) 63
81.8%
(Missing) 3
 
3.9%
ValueCountFrequency (%)
4 1
1.3%
165 1
1.3%
184 1
1.3%
187 1
1.3%
216 1
1.3%
276 1
1.3%
282 1
1.3%
304 1
1.3%
422 1
1.3%
669 1
1.3%
ValueCountFrequency (%)
68348 1
1.3%
62656 1
1.3%
61999 1
1.3%
59910 1
1.3%
37822 1
1.3%
35728 2
2.6%
32188 1
1.3%
29413 1
1.3%
25407 1
1.3%
25013 1
1.3%

국비
Real number (ℝ)

MISSING 

Distinct38
Distinct (%)88.4%
Missing34
Missing (%)44.2%
Infinite0
Infinite (%)0.0%
Mean1274.1163
Minimum39
Maximum7595
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:57.040614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile90
Q1360
median630
Q31589
95-th percentile4770
Maximum7595
Range7556
Interquartile range (IQR)1229

Descriptive statistics

Standard deviation1576.6297
Coefficient of variation (CV)1.23743
Kurtosis6.4778271
Mean1274.1163
Median Absolute Deviation (MAD)480
Skewness2.4291399
Sum54787
Variance2485761.3
MonotonicityNot monotonic
2023-12-13T05:11:57.158383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
500 4
 
5.2%
360 2
 
2.6%
90 2
 
2.6%
3600 1
 
1.3%
853 1
 
1.3%
295 1
 
1.3%
1800 1
 
1.3%
1548 1
 
1.3%
1630 1
 
1.3%
7595 1
 
1.3%
Other values (28) 28
36.4%
(Missing) 34
44.2%
ValueCountFrequency (%)
39 1
1.3%
43 1
1.3%
90 2
2.6%
150 1
1.3%
158 1
1.3%
191 1
1.3%
200 1
1.3%
202 1
1.3%
295 1
1.3%
360 2
2.6%
ValueCountFrequency (%)
7595 1
1.3%
5600 1
1.3%
4900 1
1.3%
3600 1
1.3%
3054 1
1.3%
2517 1
1.3%
2034 1
1.3%
1800 1
1.3%
1700 1
1.3%
1656 1
1.3%

지방비
Real number (ℝ)

MISSING 

Distinct30
Distinct (%)83.3%
Missing41
Missing (%)53.2%
Infinite0
Infinite (%)0.0%
Mean906.41667
Minimum12
Maximum6696
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:57.297975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12
5-th percentile80
Q1178.75
median275.5
Q3724.5
95-th percentile3712
Maximum6696
Range6684
Interquartile range (IQR)545.75

Descriptive statistics

Standard deviation1544.1677
Coefficient of variation (CV)1.7035959
Kurtosis7.8268838
Mean906.41667
Median Absolute Deviation (MAD)170
Skewness2.8090968
Sum32631
Variance2384453.9
MonotonicityNot monotonic
2023-12-13T05:11:57.422747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
200 4
 
5.2%
180 3
 
3.9%
2800 2
 
2.6%
221 1
 
1.3%
170 1
 
1.3%
175 1
 
1.3%
6696 1
 
1.3%
679 1
 
1.3%
2940 1
 
1.3%
370 1
 
1.3%
Other values (20) 20
26.0%
(Missing) 41
53.2%
ValueCountFrequency (%)
12 1
 
1.3%
50 1
 
1.3%
90 1
 
1.3%
105 1
 
1.3%
106 1
 
1.3%
121 1
 
1.3%
142 1
 
1.3%
170 1
 
1.3%
175 1
 
1.3%
180 3
3.9%
ValueCountFrequency (%)
6696 1
1.3%
6028 1
1.3%
2940 1
1.3%
2800 2
2.6%
1500 1
1.3%
1027 1
1.3%
900 1
1.3%
774 1
1.3%
708 1
1.3%
679 1
1.3%

자부담
Real number (ℝ)

MISSING 

Distinct56
Distinct (%)98.2%
Missing20
Missing (%)26.0%
Infinite0
Infinite (%)0.0%
Mean2310.2105
Minimum1
Maximum45296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:57.580333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile22.4
Q1300
median1091
Q31890
95-th percentile5885
Maximum45296
Range45295
Interquartile range (IQR)1590

Descriptive statistics

Standard deviation6333.2639
Coefficient of variation (CV)2.7414228
Kurtosis39.765727
Mean2310.2105
Median Absolute Deviation (MAD)791
Skewness6.0553181
Sum131682
Variance40110232
MonotonicityNot monotonic
2023-12-13T05:11:57.716254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300 2
 
2.6%
5814 1
 
1.3%
332 1
 
1.3%
1453 1
 
1.3%
90 1
 
1.3%
53 1
 
1.3%
793 1
 
1.3%
2053 1
 
1.3%
1190 1
 
1.3%
1189 1
 
1.3%
Other values (46) 46
59.7%
(Missing) 20
26.0%
ValueCountFrequency (%)
1 1
1.3%
5 1
1.3%
20 1
1.3%
23 1
1.3%
42 1
1.3%
53 1
1.3%
75 1
1.3%
90 1
1.3%
96 1
1.3%
120 1
1.3%
ValueCountFrequency (%)
45296 1
1.3%
17948 1
1.3%
6169 1
1.3%
5814 1
1.3%
3674 1
1.3%
3184 1
1.3%
2847 1
1.3%
2605 1
1.3%
2427 1
1.3%
2404 1
1.3%

기타
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)100.0%
Missing63
Missing (%)81.8%
Infinite0
Infinite (%)0.0%
Mean2043.8571
Minimum20
Maximum22099
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:57.851436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile21.95
Q170
median188
Q3833.25
95-th percentile9554.65
Maximum22099
Range22079
Interquartile range (IQR)763.25

Descriptive statistics

Standard deviation5819.7445
Coefficient of variation (CV)2.8474321
Kurtosis13.431082
Mean2043.8571
Median Absolute Deviation (MAD)161.5
Skewness3.6411047
Sum28614
Variance33869426
MonotonicityNot monotonic
2023-12-13T05:11:57.957602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
94 1
 
1.3%
100 1
 
1.3%
221 1
 
1.3%
62 1
 
1.3%
2800 1
 
1.3%
50 1
 
1.3%
20 1
 
1.3%
853 1
 
1.3%
23 1
 
1.3%
155 1
 
1.3%
Other values (4) 4
 
5.2%
(Missing) 63
81.8%
ValueCountFrequency (%)
20 1
1.3%
23 1
1.3%
50 1
1.3%
62 1
1.3%
94 1
1.3%
100 1
1.3%
155 1
1.3%
221 1
1.3%
346 1
1.3%
774 1
1.3%
ValueCountFrequency (%)
22099 1
1.3%
2800 1
1.3%
1017 1
1.3%
853 1
1.3%
774 1
1.3%
346 1
1.3%
221 1
1.3%
155 1
1.3%
100 1
1.3%
94 1
1.3%

대지규모(제곱미터)
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)98.6%
Missing6
Missing (%)7.8%
Infinite0
Infinite (%)0.0%
Mean9570.3803
Minimum31
Maximum50545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:58.089607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile383.5
Q12239
median7448
Q313291.5
95-th percentile28046
Maximum50545
Range50514
Interquartile range (IQR)11052.5

Descriptive statistics

Standard deviation9780.6642
Coefficient of variation (CV)1.0219724
Kurtosis3.8546739
Mean9570.3803
Median Absolute Deviation (MAD)5212
Skewness1.7325476
Sum679497
Variance95661392
MonotonicityNot monotonic
2023-12-13T05:11:58.225279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18474 2
 
2.6%
34818 1
 
1.3%
467 1
 
1.3%
367 1
 
1.3%
8394 1
 
1.3%
2242 1
 
1.3%
23684 1
 
1.3%
4324 1
 
1.3%
10083 1
 
1.3%
703 1
 
1.3%
Other values (60) 60
77.9%
(Missing) 6
 
7.8%
ValueCountFrequency (%)
31 1
1.3%
334 1
1.3%
361 1
1.3%
367 1
1.3%
400 1
1.3%
467 1
1.3%
495 1
1.3%
500 1
1.3%
592 1
1.3%
703 1
1.3%
ValueCountFrequency (%)
50545 1
1.3%
34818 1
1.3%
34091 1
1.3%
30340 1
1.3%
25752 1
1.3%
23850 1
1.3%
23684 1
1.3%
20956 1
1.3%
19737 1
1.3%
18474 2
2.6%

건물면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct73
Distinct (%)98.6%
Missing3
Missing (%)3.9%
Infinite0
Infinite (%)0.0%
Mean3490.973
Minimum31
Maximum44863
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:58.362049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile195.9
Q1770.5
median1843
Q33823
95-th percentile9261.45
Maximum44863
Range44832
Interquartile range (IQR)3052.5

Descriptive statistics

Standard deviation6369.919
Coefficient of variation (CV)1.824683
Kurtosis27.627279
Mean3490.973
Median Absolute Deviation (MAD)1345
Skewness4.904323
Sum258332
Variance40575868
MonotonicityNot monotonic
2023-12-13T05:11:58.500056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3693 2
 
2.6%
1723 1
 
1.3%
1426 1
 
1.3%
467 1
 
1.3%
310 1
 
1.3%
1750 1
 
1.3%
695 1
 
1.3%
3097 1
 
1.3%
6606 1
 
1.3%
1087 1
 
1.3%
Other values (63) 63
81.8%
(Missing) 3
 
3.9%
ValueCountFrequency (%)
31 1
1.3%
33 1
1.3%
170 1
1.3%
192 1
1.3%
198 1
1.3%
310 1
1.3%
330 1
1.3%
349 1
1.3%
352 1
1.3%
354 1
1.3%
ValueCountFrequency (%)
44863 1
1.3%
29258 1
1.3%
15127 1
1.3%
14193 1
1.3%
6606 1
1.3%
6513 1
1.3%
6213 1
1.3%
5943 1
1.3%
5344 1
1.3%
5165 1
1.3%

경매장(제곱미터)
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)97.1%
Missing9
Missing (%)11.7%
Infinite0
Infinite (%)0.0%
Mean1848.8088
Minimum33
Maximum14893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:58.636724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile114.2
Q1461
median1279.5
Q32390.5
95-th percentile5539.5
Maximum14893
Range14860
Interquartile range (IQR)1929.5

Descriptive statistics

Standard deviation2258.0931
Coefficient of variation (CV)1.2213773
Kurtosis16.507039
Mean1848.8088
Median Absolute Deviation (MAD)914
Skewness3.4342338
Sum125719
Variance5098984.3
MonotonicityNot monotonic
2023-12-13T05:11:58.776221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2600 2
 
2.6%
990 2
 
2.6%
258 1
 
1.3%
1918 1
 
1.3%
4779 1
 
1.3%
14893 1
 
1.3%
620 1
 
1.3%
1750 1
 
1.3%
1718 1
 
1.3%
3358 1
 
1.3%
Other values (56) 56
72.7%
(Missing) 9
 
11.7%
ValueCountFrequency (%)
33 1
1.3%
52 1
1.3%
100 1
1.3%
110 1
1.3%
122 1
1.3%
130 1
1.3%
170 1
1.3%
227 1
1.3%
253 1
1.3%
258 1
1.3%
ValueCountFrequency (%)
14893 1
1.3%
7967 1
1.3%
6171 1
1.3%
5949 1
1.3%
4779 1
1.3%
4186 1
1.3%
4146 1
1.3%
3633 1
1.3%
3358 1
1.3%
3269 1
1.3%

지게차 수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4935065
Minimum0
Maximum8
Zeros23
Zeros (%)29.9%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:58.908170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q32
95-th percentile4
Maximum8
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4565946
Coefficient of variation (CV)0.97528507
Kurtosis4.2695932
Mean1.4935065
Median Absolute Deviation (MAD)1
Skewness1.5212453
Sum115
Variance2.1216678
MonotonicityNot monotonic
2023-12-13T05:11:59.024152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 23
29.9%
2 22
28.6%
1 18
23.4%
3 9
 
11.7%
5 2
 
2.6%
4 2
 
2.6%
8 1
 
1.3%
ValueCountFrequency (%)
0 23
29.9%
1 18
23.4%
2 22
28.6%
3 9
 
11.7%
4 2
 
2.6%
5 2
 
2.6%
8 1
 
1.3%
ValueCountFrequency (%)
8 1
 
1.3%
5 2
 
2.6%
4 2
 
2.6%
3 9
 
11.7%
2 22
28.6%
1 18
23.4%
0 23
29.9%

전동차 수
Categorical

IMBALANCE 

Distinct4
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size748.0 B
0
68 
1
7 
2
 
1
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)2.6%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 68
88.3%
1 7
 
9.1%
2 1
 
1.3%
3 1
 
1.3%

Length

2023-12-13T05:11:59.166826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:59.263565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 68
88.3%
1 7
 
9.1%
2 1
 
1.3%
3 1
 
1.3%

콘베이어 수
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.31168831
Minimum0
Maximum6
Zeros67
Zeros (%)87.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:11:59.356542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation0.9768335
Coefficient of variation (CV)3.1340075
Kurtosis17.490421
Mean0.31168831
Median Absolute Deviation (MAD)0
Skewness3.940001
Sum24
Variance0.95420369
MonotonicityNot monotonic
2023-12-13T05:11:59.464213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 67
87.0%
2 4
 
5.2%
1 3
 
3.9%
6 1
 
1.3%
3 1
 
1.3%
4 1
 
1.3%
ValueCountFrequency (%)
0 67
87.0%
1 3
 
3.9%
2 4
 
5.2%
3 1
 
1.3%
4 1
 
1.3%
6 1
 
1.3%
ValueCountFrequency (%)
6 1
 
1.3%
4 1
 
1.3%
3 1
 
1.3%
2 4
 
5.2%
1 3
 
3.9%
0 67
87.0%

순화수집트럭 수
Categorical

Distinct4
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size748.0 B
0
39 
1
23 
2
12 
3
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row2
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 39
50.6%
1 23
29.9%
2 12
 
15.6%
3 3
 
3.9%

Length

2023-12-13T05:11:59.614662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:59.724599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 39
50.6%
1 23
29.9%
2 12
 
15.6%
3 3
 
3.9%

냉장탑차 수
Categorical

Distinct4
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size748.0 B
0
59 
1
14 
2
 
3
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)1.3%

Sample

1st row0
2nd row0
3rd row0
4th row1
5th row0

Common Values

ValueCountFrequency (%)
0 59
76.6%
1 14
 
18.2%
2 3
 
3.9%
3 1
 
1.3%

Length

2023-12-13T05:11:59.845719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:11:59.968458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 59
76.6%
1 14
 
18.2%
2 3
 
3.9%
3 1
 
1.3%

선별기 수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.81818182
Minimum0
Maximum10
Zeros52
Zeros (%)67.5%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:12:00.082027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile4
Maximum10
Range10
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.6441865
Coefficient of variation (CV)2.0095613
Kurtosis12.602185
Mean0.81818182
Median Absolute Deviation (MAD)0
Skewness3.0894585
Sum63
Variance2.7033493
MonotonicityNot monotonic
2023-12-13T05:12:00.196143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 52
67.5%
1 10
 
13.0%
2 5
 
6.5%
3 5
 
6.5%
5 2
 
2.6%
4 2
 
2.6%
10 1
 
1.3%
ValueCountFrequency (%)
0 52
67.5%
1 10
 
13.0%
2 5
 
6.5%
3 5
 
6.5%
4 2
 
2.6%
5 2
 
2.6%
10 1
 
1.3%
ValueCountFrequency (%)
10 1
 
1.3%
5 2
 
2.6%
4 2
 
2.6%
3 5
 
6.5%
2 5
 
6.5%
1 10
 
13.0%
0 52
67.5%

경매사 수
Real number (ℝ)

ZEROS 

Distinct7
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.5844156
Minimum0
Maximum6
Zeros24
Zeros (%)31.2%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:12:00.322891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q32
95-th percentile5
Maximum6
Range6
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.4721149
Coefficient of variation (CV)0.92912171
Kurtosis0.46232411
Mean1.5844156
Median Absolute Deviation (MAD)1
Skewness0.85902456
Sum122
Variance2.1671224
MonotonicityNot monotonic
2023-12-13T05:12:00.436422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
2 24
31.2%
0 24
31.2%
1 13
16.9%
3 9
 
11.7%
5 4
 
5.2%
4 2
 
2.6%
6 1
 
1.3%
ValueCountFrequency (%)
0 24
31.2%
1 13
16.9%
2 24
31.2%
3 9
 
11.7%
4 2
 
2.6%
5 4
 
5.2%
6 1
 
1.3%
ValueCountFrequency (%)
6 1
 
1.3%
5 4
 
5.2%
4 2
 
2.6%
3 9
 
11.7%
2 24
31.2%
1 13
16.9%
0 24
31.2%

유통주체(중도매인) 수
Real number (ℝ)

ZEROS 

Distinct37
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.480519
Minimum0
Maximum118
Zeros20
Zeros (%)26.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:12:00.637110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median12
Q325
95-th percentile53.2
Maximum118
Range118
Interquartile range (IQR)25

Descriptive statistics

Standard deviation20.691093
Coefficient of variation (CV)1.1836658
Kurtosis7.1895961
Mean17.480519
Median Absolute Deviation (MAD)12
Skewness2.249893
Sum1346
Variance428.12133
MonotonicityNot monotonic
2023-12-13T05:12:00.798751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 20
26.0%
17 4
 
5.2%
9 3
 
3.9%
25 3
 
3.9%
13 3
 
3.9%
14 3
 
3.9%
12 3
 
3.9%
1 2
 
2.6%
10 2
 
2.6%
35 2
 
2.6%
Other values (27) 32
41.6%
ValueCountFrequency (%)
0 20
26.0%
1 2
 
2.6%
3 1
 
1.3%
5 1
 
1.3%
6 2
 
2.6%
7 1
 
1.3%
8 2
 
2.6%
9 3
 
3.9%
10 2
 
2.6%
11 2
 
2.6%
ValueCountFrequency (%)
118 1
1.3%
78 1
1.3%
70 1
1.3%
62 1
1.3%
51 1
1.3%
46 2
2.6%
40 1
1.3%
39 1
1.3%
35 2
2.6%
34 1
1.3%

유통주체(산지유통인) 수
Real number (ℝ)

ZEROS 

Distinct14
Distinct (%)18.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.584416
Minimum0
Maximum732
Zeros57
Zeros (%)74.0%
Negative0
Negative (%)0.0%
Memory size825.0 B
2023-12-13T05:12:01.219148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile56.4
Maximum732
Range732
Interquartile range (IQR)1

Descriptive statistics

Standard deviation103.96474
Coefficient of variation (CV)5.050653
Kurtosis37.534259
Mean20.584416
Median Absolute Deviation (MAD)0
Skewness6.0924988
Sum1585
Variance10808.667
MonotonicityNot monotonic
2023-12-13T05:12:01.331746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
0 57
74.0%
2 4
 
5.2%
10 3
 
3.9%
5 2
 
2.6%
4 2
 
2.6%
11 1
 
1.3%
90 1
 
1.3%
50 1
 
1.3%
82 1
 
1.3%
1 1
 
1.3%
Other values (4) 4
 
5.2%
ValueCountFrequency (%)
0 57
74.0%
1 1
 
1.3%
2 4
 
5.2%
4 2
 
2.6%
5 2
 
2.6%
7 1
 
1.3%
8 1
 
1.3%
10 3
 
3.9%
11 1
 
1.3%
50 1
 
1.3%
ValueCountFrequency (%)
732 1
 
1.3%
548 1
 
1.3%
90 1
 
1.3%
82 1
 
1.3%
50 1
 
1.3%
11 1
 
1.3%
10 3
3.9%
8 1
 
1.3%
7 1
 
1.3%
5 2
2.6%

Sample

부류소재지공판장 명칭주소개장년도거래실적(19년도)(백만원)국비지방비자부담기타대지규모(제곱미터)건물면적(제곱미터)경매장(제곱미터)지게차 수전동차 수콘베이어 수순화수집트럭 수냉장탑차 수선별기 수경매사 수유통주체(중도매인) 수유통주체(산지유통인) 수
0청과충남공주농협공주시 금성길 19195713105401802605<NA>9587846001121022130
1청과전남목포원예농협목포시 영산로 575196325407<NA><NA>17948<NA>20956258479671011005310
2청과전남여수원예농협여수시 남산북9길 2019659826<NA><NA>1494<NA>1815181512721002002120
3청과전북군산원예농협군산시 하포로 291967294131183<NA>205994180154146414620111052311
4임산강원강릉산림조합강릉시 옥가로 271970276<NA><NA><NA><NA>1443298852000000000
5임산강원고성산림조합고성군 간성읍 간성북로 31970891<NA><NA><NA><NA><NA><NA>297000000000
6청과강원동두천농협동두천시 중앙로 20719741267<NA><NA>435<NA>410511421142000000160
7청과경북청도농협 공판장청도군 청도읍 한내길 17019751333620020018410045838338333001122300
8청과경남통영농협통영시 새터길 719794647<NA><NA>1890<NA>59235230000000021290
9청과전남나주배원예농협나주시 청동길 3219791226717004502847<NA>23850651332692001012220
부류소재지공판장 명칭주소개장년도거래실적(19년도)(백만원)국비지방비자부담기타대지규모(제곱미터)건물면적(제곱미터)경매장(제곱미터)지게차 수전동차 수콘베이어 수순화수집트럭 수냉장탑차 수선별기 수경매사 수유통주체(중도매인) 수유통주체(산지유통인) 수
67화훼충북한국화훼농협 음성화훼유통센터음성군 금왕읍 대금로 1278번길 4020152099525176696<NA><NA>257524804418613031031180
68임산강원양양속초산림조합양양군 양양읍 남문로 1320151889<NA><NA><NA><NA><NA>354253000000000
69임산전남진도산림조합진도군 운림산방로 1622016216<NA>17575<NA>495198130000010000
70임산경북예천산림조합예천군 예천읍 양궁로 572016422<NA><NA><NA><NA>1665490262000000000
71임산경북울진산림조합울진군 울진읍 온양리 437-120161728500200300<NA>3438762227100013000
72임산충남부여산림조합부여군 구룡면 성충로 140720161858<NA><NA><NA><NA>74483865<NA>200013000
73임산경북청도산림조합청도군 각남면 각남로 32520161475<NA><NA><NA><NA><NA><NA>100000000000
74청과경북군위농협공판장군위권 군위읍 도군로 26952017<NA><NA>170<NA><NA>1759220731560200003254
75임산경북상주산림조합상주군 영남제일로 17852017304<NA><NA><NA><NA><NA>33<NA>000000005
76청과경북농업회사법인 산지애(주)청송군 주왕산면 주왕산로 44820191275<NA><NA><NA><NA>1602241939904000041170