Overview

Dataset statistics

Number of variables10
Number of observations192
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.6 KiB
Average record size in memory88.7 B

Variable types

Categorical1
Text1
Numeric8

Dataset

Description인천광역시 내 소재한 삼산농산물도매시장 법인별 거래정보(농산물 품목, 거래물량, 거래금액 등) 데이터를 제공합니다.
Author인천광역시
URLhttps://www.data.go.kr/data/3044833/fileData.do

Alerts

품목별총물량(KG) is highly overall correlated with 품목별총금액(원) and 6 other fieldsHigh correlation
품목별총금액(원) is highly overall correlated with 품목별총물량(KG) and 6 other fieldsHigh correlation
(주)부평농산 총물량(KG) is highly overall correlated with 품목별총물량(KG) and 6 other fieldsHigh correlation
(주)부평농산 총금액(원) is highly overall correlated with 품목별총물량(KG) and 6 other fieldsHigh correlation
(주)경인농산 총물량(KG) is highly overall correlated with 품목별총물량(KG) and 6 other fieldsHigh correlation
(주)경인농산 총금액(원) is highly overall correlated with 품목별총물량(KG) and 6 other fieldsHigh correlation
인천원예농협 총물량(KG) is highly overall correlated with 품목별총물량(KG) and 6 other fieldsHigh correlation
인천원예농협 총금액(원) is highly overall correlated with 품목별총물량(KG) and 6 other fieldsHigh correlation
(주)부평농산 총물량(KG) has 38 (19.8%) zerosZeros
(주)부평농산 총금액(원) has 38 (19.8%) zerosZeros
(주)경인농산 총물량(KG) has 34 (17.7%) zerosZeros
(주)경인농산 총금액(원) has 34 (17.7%) zerosZeros
인천원예농협 총물량(KG) has 38 (19.8%) zerosZeros
인천원예농협 총금액(원) has 38 (19.8%) zerosZeros

Reproduction

Analysis started2024-04-21 02:42:48.028964
Analysis finished2024-04-21 02:42:55.646200
Duration7.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

대분류
Categorical

Distinct22
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
엽경채류
37 
양채류
23 
과실류
20 
특용작물류
18 
조미채소류
16 
Other values (17)
78 

Length

Max length6
Median length5
Mean length3.7916667
Min length2

Unique

Unique3 ?
Unique (%)1.6%

Sample

1st row건제품
2nd row과실류
3rd row과실류
4th row과실류
5th row과실류

Common Values

ValueCountFrequency (%)
엽경채류 37
19.3%
양채류 23
12.0%
과실류 20
10.4%
특용작물류 18
9.4%
조미채소류 16
8.3%
산채류 16
8.3%
농림가공 9
 
4.7%
버섯류 8
 
4.2%
수실류 6
 
3.1%
신선 해조류 6
 
3.1%
Other values (12) 33
17.2%

Length

2024-04-21T11:42:55.737854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
엽경채류 37
18.7%
양채류 23
11.6%
과실류 20
10.1%
특용작물류 18
9.1%
조미채소류 16
8.1%
산채류 16
8.1%
농림가공 9
 
4.5%
버섯류 8
 
4.0%
해조류 6
 
3.0%
과일과채류 6
 
3.0%
Other values (13) 39
19.7%

품목명
Text

Distinct172
Distinct (%)89.6%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-21T11:42:56.053760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3
Min length1

Characters and Unicode

Total characters576
Distinct characters207
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

Unique157 ?
Unique (%)81.8%

Sample

1st row다시마
2nd row사과
3rd row배
4th row포도
5th row단감
ValueCountFrequency (%)
기타 7
 
3.6%
고추씨 2
 
1.0%
생강 2
 
1.0%
들깨 2
 
1.0%
건고추 2
 
1.0%
마늘 2
 
1.0%
겨자 2
 
1.0%
참깨 2
 
1.0%
홍고추 2
 
1.0%
땅콩 2
 
1.0%
Other values (166) 171
87.2%
2024-04-21T11:42:56.474918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 24
 
4.2%
리 18
 
3.1%
고 18
 
3.1%
기 14
 
2.4%
나 13
 
2.3%
타 11
 
1.9%
마 11
 
1.9%
양 9
 
1.6%
배 9
 
1.6%
) 9
 
1.6%
Other values (197) 440
76.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 554
96.2%
Close Punctuation 9
 
1.6%
Open Punctuation 9
 
1.6%
Space Separator 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 24
 
4.3%
리 18
 
3.2%
고 18
 
3.2%
기 14
 
2.5%
나 13
 
2.3%
타 11
 
2.0%
마 11
 
2.0%
양 9
 
1.6%
배 9
 
1.6%
물 9
 
1.6%
Other values (194) 418
75.5%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 554
96.2%
Common 22
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 24
 
4.3%
리 18
 
3.2%
고 18
 
3.2%
기 14
 
2.5%
나 13
 
2.3%
타 11
 
2.0%
마 11
 
2.0%
양 9
 
1.6%
배 9
 
1.6%
물 9
 
1.6%
Other values (194) 418
75.5%
Common
ValueCountFrequency (%)
) 9
40.9%
( 9
40.9%
4
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 554
96.2%
ASCII 22
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 24
 
4.3%
리 18
 
3.2%
고 18
 
3.2%
기 14
 
2.5%
나 13
 
2.3%
타 11
 
2.0%
마 11
 
2.0%
양 9
 
1.6%
배 9
 
1.6%
물 9
 
1.6%
Other values (194) 418
75.5%
ASCII
ValueCountFrequency (%)
) 9
40.9%
( 9
40.9%
4
18.2%

품목별총물량(KG)
Real number (ℝ)

HIGH CORRELATION 

Distinct184
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53634.274
Minimum0.5
Maximum1235646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:56.604190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile10
Q1305
median2772.25
Q327205.15
95-th percentile270432.63
Maximum1235646
Range1235645.5
Interquartile range (IQR)26900.15

Descriptive statistics

Standard deviation155497.01
Coefficient of variation (CV)2.8992097
Kurtosis31.851002
Mean53634.274
Median Absolute Deviation (MAD)2758.5
Skewness5.2161089
Sum10297781
Variance2.417932 × 1010
MonotonicityNot monotonic
2024-04-21T11:42:56.747916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 4
 
2.1%
3969.0 2
 
1.0%
12.0 2
 
1.0%
4.0 2
 
1.0%
201.0 2
 
1.0%
24.0 2
 
1.0%
89029.0 1
 
0.5%
46845.4 1
 
0.5%
74426.4 1
 
0.5%
39254.8 1
 
0.5%
Other values (174) 174
90.6%
ValueCountFrequency (%)
0.5 1
 
0.5%
1.5 1
 
0.5%
1.6 1
 
0.5%
3.0 1
 
0.5%
4.0 2
1.0%
8.0 1
 
0.5%
10.0 4
2.1%
12.0 2
1.0%
13.0 1
 
0.5%
14.5 1
 
0.5%
ValueCountFrequency (%)
1235646.0 1
0.5%
1114042.0 1
0.5%
859167.0 1
0.5%
557624.3 1
0.5%
487565.0 1
0.5%
391536.0 1
0.5%
337842.1 1
0.5%
329798.0 1
0.5%
277666.0 1
0.5%
273968.8 1
0.5%

품목별총금액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct190
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4565778 × 108
Minimum2000
Maximum2.1255718 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:56.868097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile39100
Q11605500
median11328200
Q31.0415922 × 108
95-th percentile7.6552007 × 108
Maximum2.1255718 × 109
Range2.1255698 × 109
Interquartile range (IQR)1.0255372 × 108

Descriptive statistics

Standard deviation3.2832215 × 108
Coefficient of variation (CV)2.2540653
Kurtosis14.735363
Mean1.4565778 × 108
Median Absolute Deviation (MAD)11222450
Skewness3.5525188
Sum2.7966294 × 1010
Variance1.0779543 × 1017
MonotonicityNot monotonic
2024-04-21T11:42:56.986791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18000 2
 
1.0%
40000 2
 
1.0%
932000 1
 
0.5%
69237100 1
 
0.5%
270815550 1
 
0.5%
435267000 1
 
0.5%
261682950 1
 
0.5%
437854500 1
 
0.5%
400969100 1
 
0.5%
71122200 1
 
0.5%
Other values (180) 180
93.8%
ValueCountFrequency (%)
2000 1
0.5%
2500 1
0.5%
7000 1
0.5%
9500 1
0.5%
10000 1
0.5%
13000 1
0.5%
18000 2
1.0%
28000 1
0.5%
38000 1
0.5%
40000 2
1.0%
ValueCountFrequency (%)
2125571800 1
0.5%
2028939500 1
0.5%
1572114000 1
0.5%
1281552000 1
0.5%
1255265550 1
0.5%
1196647200 1
0.5%
915096500 1
0.5%
914461000 1
0.5%
820262660 1
0.5%
781235500 1
0.5%

(주)부평농산 총물량(KG)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct144
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19068.688
Minimum0
Maximum648978
Zeros38
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:57.103306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median766
Q38871
95-th percentile91919.5
Maximum648978
Range648978
Interquartile range (IQR)8851

Descriptive statistics

Standard deviation64276.188
Coefficient of variation (CV)3.3707715
Kurtosis57.727085
Mean19068.688
Median Absolute Deviation (MAD)766
Skewness6.9129302
Sum3661188
Variance4.1314283 × 109
MonotonicityNot monotonic
2024-04-21T11:42:57.235805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 38
 
19.8%
24.0 4
 
2.1%
20.0 3
 
1.6%
76.0 3
 
1.6%
190.0 2
 
1.0%
10.0 2
 
1.0%
722.0 2
 
1.0%
60.0 2
 
1.0%
457.0 1
 
0.5%
4835.0 1
 
0.5%
Other values (134) 134
69.8%
ValueCountFrequency (%)
0.0 38
19.8%
2.0 1
 
0.5%
6.0 1
 
0.5%
8.0 1
 
0.5%
10.0 2
 
1.0%
11.0 1
 
0.5%
12.0 1
 
0.5%
13.0 1
 
0.5%
20.0 3
 
1.6%
21.0 1
 
0.5%
ValueCountFrequency (%)
648978.0 1
0.5%
434050.0 1
0.5%
260476.0 1
0.5%
174587.0 1
0.5%
150302.0 1
0.5%
144087.8 1
0.5%
130780.0 1
0.5%
109566.0 1
0.5%
98121.0 1
0.5%
97062.0 1
0.5%

(주)부평농산 총금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct155
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49999193
Minimum0
Maximum1.048746 × 109
Zeros38
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:57.392398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1113250
median2984800
Q330489000
95-th percentile2.8231719 × 108
Maximum1.048746 × 109
Range1.048746 × 109
Interquartile range (IQR)30375750

Descriptive statistics

Standard deviation1.1830507 × 108
Coefficient of variation (CV)2.3661397
Kurtosis28.15282
Mean49999193
Median Absolute Deviation (MAD)2984800
Skewness4.4373687
Sum9.5998452 × 109
Variance1.3996091 × 1016
MonotonicityNot monotonic
2024-04-21T11:42:57.529372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
 
19.8%
18574200 1
 
0.5%
84360400 1
 
0.5%
140952500 1
 
0.5%
87695750 1
 
0.5%
166682900 1
 
0.5%
102211500 1
 
0.5%
177925500 1
 
0.5%
111844000 1
 
0.5%
2181000 1
 
0.5%
Other values (145) 145
75.5%
ValueCountFrequency (%)
0 38
19.8%
12000 1
 
0.5%
26000 1
 
0.5%
30000 1
 
0.5%
38000 1
 
0.5%
40000 1
 
0.5%
46000 1
 
0.5%
69000 1
 
0.5%
74000 1
 
0.5%
88000 1
 
0.5%
ValueCountFrequency (%)
1048746000 1
0.5%
515866900 1
0.5%
404207500 1
0.5%
393702500 1
0.5%
372315200 1
0.5%
365080200 1
0.5%
360775000 1
0.5%
342389000 1
0.5%
328902900 1
0.5%
295976500 1
0.5%

(주)경인농산 총물량(KG)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct152
Distinct (%)79.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16442.998
Minimum0
Maximum492679
Zeros34
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:57.667965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q119
median721
Q36411.25
95-th percentile81109.25
Maximum492679
Range492679
Interquartile range (IQR)6392.25

Descriptive statistics

Standard deviation51465.046
Coefficient of variation (CV)3.1299064
Kurtosis44.368132
Mean16442.998
Median Absolute Deviation (MAD)721
Skewness5.9516893
Sum3157055.7
Variance2.6486509 × 109
MonotonicityNot monotonic
2024-04-21T11:42:57.802600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 34
 
17.7%
20.0 3
 
1.6%
12.0 2
 
1.0%
4.0 2
 
1.0%
10.0 2
 
1.0%
95.0 2
 
1.0%
30.0 2
 
1.0%
4558.0 1
 
0.5%
146648.0 1
 
0.5%
66391.0 1
 
0.5%
Other values (142) 142
74.0%
ValueCountFrequency (%)
0.0 34
17.7%
0.3 1
 
0.5%
1.2 1
 
0.5%
1.6 1
 
0.5%
3.0 1
 
0.5%
4.0 2
 
1.0%
6.0 1
 
0.5%
7.5 1
 
0.5%
10.0 2
 
1.0%
11.0 1
 
0.5%
ValueCountFrequency (%)
492679.0 1
0.5%
272514.0 1
0.5%
270262.3 1
0.5%
186070.0 1
0.5%
146648.0 1
0.5%
145200.0 1
0.5%
128770.0 1
0.5%
82967.1 1
0.5%
82350.0 1
0.5%
81640.0 1
0.5%

(주)경인농산 총금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct157
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43993527
Minimum0
Maximum8.766924 × 108
Zeros34
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:57.926519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1117500
median2247950
Q329372750
95-th percentile2.1036647 × 108
Maximum8.766924 × 108
Range8.766924 × 108
Interquartile range (IQR)29255250

Descriptive statistics

Standard deviation1.1313169 × 108
Coefficient of variation (CV)2.5715531
Kurtosis23.750115
Mean43993527
Median Absolute Deviation (MAD)2247950
Skewness4.4131957
Sum8.4467571 × 109
Variance1.2798779 × 1016
MonotonicityNot monotonic
2024-04-21T11:42:58.051229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34
 
17.7%
18000 2
 
1.0%
840000 2
 
1.0%
932000 1
 
0.5%
1091000 1
 
0.5%
83811400 1
 
0.5%
121761050 1
 
0.5%
102038600 1
 
0.5%
134349100 1
 
0.5%
168192000 1
 
0.5%
Other values (147) 147
76.6%
ValueCountFrequency (%)
0 34
17.7%
9500 1
 
0.5%
15000 1
 
0.5%
16000 1
 
0.5%
18000 2
 
1.0%
27000 1
 
0.5%
36000 1
 
0.5%
39000 1
 
0.5%
40000 1
 
0.5%
60000 1
 
0.5%
ValueCountFrequency (%)
876692400 1
0.5%
713048000 1
0.5%
561499500 1
0.5%
416249000 1
0.5%
379999300 1
0.5%
360318000 1
0.5%
337098000 1
0.5%
276365000 1
0.5%
262095000 1
0.5%
212718000 1
0.5%

인천원예농협 총물량(KG)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct151
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18122.588
Minimum0
Maximum360887
Zeros38
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:58.396030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q126.5
median1005
Q311223.875
95-th percentile90964.525
Maximum360887
Range360887
Interquartile range (IQR)11197.375

Descriptive statistics

Standard deviation47357.991
Coefficient of variation (CV)2.6132024
Kurtosis24.714278
Mean18122.588
Median Absolute Deviation (MAD)1005
Skewness4.5525042
Sum3479537
Variance2.2427793 × 109
MonotonicityNot monotonic
2024-04-21T11:42:58.514247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 38
 
19.8%
30.0 3
 
1.6%
10.0 2
 
1.0%
4.0 2
 
1.0%
861.0 1
 
0.5%
25435.0 1
 
0.5%
12800.4 1
 
0.5%
56.0 1
 
0.5%
8095.0 1
 
0.5%
1796.0 1
 
0.5%
Other values (141) 141
73.4%
ValueCountFrequency (%)
0.0 38
19.8%
0.5 1
 
0.5%
1.5 1
 
0.5%
3.0 1
 
0.5%
4.0 2
 
1.0%
10.0 2
 
1.0%
11.0 1
 
0.5%
14.5 1
 
0.5%
16.0 1
 
0.5%
30.0 3
 
1.6%
ValueCountFrequency (%)
360887.0 1
0.5%
314154.0 1
0.5%
239047.0 1
0.5%
192063.0 1
0.5%
157176.0 1
0.5%
143274.2 1
0.5%
127976.8 1
0.5%
116275.0 1
0.5%
103966.0 1
0.5%
93964.5 1
0.5%

인천원예농협 총금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct154
Distinct (%)80.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51665063
Minimum0
Maximum6.363802 × 108
Zeros38
Zeros (%)19.8%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-21T11:42:58.642063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1134500
median4835850
Q336952375
95-th percentile2.6514267 × 108
Maximum6.363802 × 108
Range6.363802 × 108
Interquartile range (IQR)36817875

Descriptive statistics

Standard deviation1.1149709 × 108
Coefficient of variation (CV)2.1580751
Kurtosis10.967053
Mean51665063
Median Absolute Deviation (MAD)4835850
Skewness3.2028336
Sum9.9196922 × 109
Variance1.24316 × 1016
MonotonicityNot monotonic
2024-04-21T11:42:58.797601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 38
 
19.8%
2192000 2
 
1.0%
184505000 1
 
0.5%
146823050 1
 
0.5%
57432850 1
 
0.5%
125579900 1
 
0.5%
120933100 1
 
0.5%
24559500 1
 
0.5%
5340000 1
 
0.5%
14122500 1
 
0.5%
Other values (144) 144
75.0%
ValueCountFrequency (%)
0 38
19.8%
2000 1
 
0.5%
2500 1
 
0.5%
7000 1
 
0.5%
10000 1
 
0.5%
13000 1
 
0.5%
30000 1
 
0.5%
39000 1
 
0.5%
95000 1
 
0.5%
101500 1
 
0.5%
ValueCountFrequency (%)
636380200 1
0.5%
604124850 1
0.5%
515326300 1
0.5%
504528000 1
0.5%
493985800 1
0.5%
464014000 1
0.5%
396339000 1
0.5%
345323000 1
0.5%
295607720 1
0.5%
279698500 1
0.5%

Interactions

2024-04-21T11:42:54.739743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:49.881711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.616236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.252761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.901474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.552285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.199131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.843719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.826018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.015728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.692594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.341677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.981658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.641644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.278453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.143588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.911888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.099880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.759925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.417188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.052380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.717401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.353987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.226262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.998648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.184239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.847718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.502056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.138269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.793043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.442220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.311755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:55.090539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.269683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.930500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.581734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.215370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.864195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.519007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.390787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:55.186891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.363280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.010470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.657289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.293206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.942373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.595000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.471110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:55.261924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.450199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.085866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.731356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.366552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.025205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.666653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.547726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:55.350442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:50.537427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.167058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:51.813895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:52.453580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.116165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:53.756639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T11:42:54.648654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T11:42:58.890260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
대분류품목별총물량(KG)품목별총금액(원)(주)부평농산 총물량(KG)(주)부평농산 총금액(원)(주)경인농산 총물량(KG)(주)경인농산 총금액(원)인천원예농협 총물량(KG)인천원예농협 총금액(원)
대분류1.0000.0500.3660.0000.4250.2270.4910.3580.572
품목별총물량(KG)0.0501.0000.7980.8800.8110.9250.8390.9320.795
품목별총금액(원)0.3660.7981.0000.8680.8850.8500.9240.9400.911
(주)부평농산 총물량(KG)0.0000.8800.8681.0000.8480.9820.8050.9790.740
(주)부평농산 총금액(원)0.4250.8110.8850.8481.0000.8470.9160.7960.900
(주)경인농산 총물량(KG)0.2270.9250.8500.9820.8471.0000.8230.9830.747
(주)경인농산 총금액(원)0.4910.8390.9240.8050.9160.8231.0000.8330.906
인천원예농협 총물량(KG)0.3580.9320.9400.9790.7960.9830.8331.0000.798
인천원예농협 총금액(원)0.5720.7950.9110.7400.9000.7470.9060.7981.000
2024-04-21T11:42:59.008590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목별총물량(KG)품목별총금액(원)(주)부평농산 총물량(KG)(주)부평농산 총금액(원)(주)경인농산 총물량(KG)(주)경인농산 총금액(원)인천원예농협 총물량(KG)인천원예농협 총금액(원)대분류
품목별총물량(KG)1.0000.9720.9050.8750.9190.9040.9490.9220.000
품목별총금액(원)0.9721.0000.8980.9090.8790.9040.9280.9430.146
(주)부평농산 총물량(KG)0.9050.8981.0000.9790.8210.8250.8260.8030.000
(주)부평농산 총금액(원)0.8750.9090.9791.0000.7870.8210.7990.8080.199
(주)경인농산 총물량(KG)0.9190.8790.8210.7871.0000.9800.8810.8420.098
(주)경인농산 총금액(원)0.9040.9040.8250.8210.9801.0000.8620.8520.214
인천원예농협 총물량(KG)0.9490.9280.8260.7990.8810.8621.0000.9790.140
인천원예농협 총금액(원)0.9220.9430.8030.8080.8420.8520.9791.0000.242
대분류0.0000.1460.0000.1990.0980.2140.1400.2421.000

Missing values

2024-04-21T11:42:55.463225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:42:55.589212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

대분류품목명품목별총물량(KG)품목별총금액(원)(주)부평농산 총물량(KG)(주)부평농산 총금액(원)(주)경인농산 총물량(KG)(주)경인농산 총금액(원)인천원예농협 총물량(KG)인천원예농협 총금액(원)
0건제품다시마209.09320000.00209.09320000.00
1과실류사과250555.0128155200057060.036077500077220.0416249000116275.0504528000
2과실류배57345.032102900024930.01329300002160.01236300030255.0175736000
3과실류포도80359.054580500036836.626202950015951.211383900027571.2169936500
4과실류단감1980.09814000480.012200000.001500.08594000
5과실류참다래(키위)5978.6371240001805.013015000373.627240003800.021385000
6과실류바나나337842.1752662000174587.039370250082967.118279300080288.0176166500
7과실류파인애플58482.011441950035328.0737930006514.01139200016640.029234500
8과실류감귤72523.944117630040687.12520855004870.02930300026966.8159787800
9과실류만감26830.212471800018086.2837190001206.047820007538.036217000
대분류품목명품목별총물량(KG)품목별총금액(원)(주)부평농산 총물량(KG)(주)부평농산 총금액(원)(주)경인농산 총물량(KG)(주)경인농산 총금액(원)인천원예농협 총물량(KG)인천원예농협 총금액(원)
182조미채소류기타20.023000020.02300000.000.00
183특용작물류참깨1497.091590001290.07739000207.014200000.00
184특용작물류들깨841.563042000.00172.51561000669.04743200
185특용작물류땅콩1817.07803000617.02763000500.02100000700.02940000
186특용작물류피마자10.0180000.0010.0180000.00
187특용작물류유채14.51015000.000.0014.5101500
188특용작물류고추씨105.03399000.0030.010000075.0239900
189특용작물류호박씨60.038300060.03830000.000.00
190특용작물류차류678.024290000.0020.036000658.02393000
191특용작물류해바라기씨24.08800024.0880000.000.00