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://data.incheon.go.kr/findData/publicDataDetail?dataId=3044833&srcSe=7661IVAWM27C61E190

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 44 (22.9%) zerosZeros
(주)부평농산 총금액(원) has 44 (22.9%) zerosZeros
(주)경인농산 총물량(KG) has 34 (17.7%) zerosZeros
(주)경인농산 총금액(원) has 34 (17.7%) zerosZeros
인천원예농협 총물량(KG) has 33 (17.2%) zerosZeros
인천원예농협 총금액(원) has 33 (17.2%) zerosZeros

Reproduction

Analysis started2024-04-21 16:25:34.674772
Analysis finished2024-04-21 16:25:46.514766
Duration11.84 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
39 
과실류
25 
양채류
21 
특용작물류
13 
산채류
13 
Other values (17)
81 

Length

Max length6
Median length5
Mean length3.6875
Min length2

Unique

Unique3 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
엽경채류 39
20.3%
과실류 25
13.0%
양채류 21
10.9%
특용작물류 13
 
6.8%
산채류 13
 
6.8%
조미채소류 11
 
5.7%
농림가공 9
 
4.7%
수실류 8
 
4.2%
두류 7
 
3.6%
버섯류 7
 
3.6%
Other values (12) 39
20.3%

Length

2024-04-22T01:25:46.643606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
엽경채류 39
19.7%
과실류 25
12.6%
양채류 21
10.6%
특용작물류 13
 
6.6%
산채류 13
 
6.6%
조미채소류 11
 
5.6%
농림가공 9
 
4.5%
수실류 8
 
4.0%
두류 7
 
3.5%
버섯류 7
 
3.5%
Other values (13) 45
22.7%

품목명
Text

Distinct184
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size1.6 KiB
2024-04-22T01:25:47.908044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3.0104167
Min length1

Characters and Unicode

Total characters578
Distinct characters218
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

Unique179 ?
Unique (%)93.2%

Sample

1st row다시마
2nd row청각
3rd row사과
4th row배
5th row포도
ValueCountFrequency (%)
기타 5
 
2.6%
호박씨 2
 
1.0%
해바라기씨 2
 
1.0%
다시마 2
 
1.0%
차류 2
 
1.0%
얼갈이배추 1
 
0.5%
콩나물 1
 
0.5%
아욱 1
 
0.5%
양배추 1
 
0.5%
복숭아 1
 
0.5%
Other values (178) 178
90.8%
2024-04-22T01:25:49.422174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
추 19
 
3.3%
리 16
 
2.8%
고 15
 
2.6%
나 14
 
2.4%
기 11
 
1.9%
물 10
 
1.7%
무 9
 
1.6%
( 9
 
1.6%
타 9
 
1.6%
라 9
 
1.6%
Other values (208) 457
79.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 556
96.2%
Open Punctuation 9
 
1.6%
Close Punctuation 9
 
1.6%
Space Separator 4
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
추 19
 
3.4%
리 16
 
2.9%
고 15
 
2.7%
나 14
 
2.5%
기 11
 
2.0%
물 10
 
1.8%
무 9
 
1.6%
타 9
 
1.6%
라 9
 
1.6%
마 9
 
1.6%
Other values (205) 435
78.2%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 556
96.2%
Common 22
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
추 19
 
3.4%
리 16
 
2.9%
고 15
 
2.7%
나 14
 
2.5%
기 11
 
2.0%
물 10
 
1.8%
무 9
 
1.6%
타 9
 
1.6%
라 9
 
1.6%
마 9
 
1.6%
Other values (205) 435
78.2%
Common
ValueCountFrequency (%)
( 9
40.9%
) 9
40.9%
4
18.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 556
96.2%
ASCII 22
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
추 19
 
3.4%
리 16
 
2.9%
고 15
 
2.7%
나 14
 
2.5%
기 11
 
2.0%
물 10
 
1.8%
무 9
 
1.6%
타 9
 
1.6%
라 9
 
1.6%
마 9
 
1.6%
Other values (205) 435
78.2%
ASCII
ValueCountFrequency (%)
( 9
40.9%
) 9
40.9%
4
18.2%

품목별총물량(KG)
Real number (ℝ)

HIGH CORRELATION 

Distinct188
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65096.551
Minimum0.5
Maximum1587328
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:49.667232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.5
5-th percentile15.1
Q1253.25
median2985.95
Q329626.6
95-th percentile323307.85
Maximum1587328
Range1587327.5
Interquartile range (IQR)29373.35

Descriptive statistics

Standard deviation200044.03
Coefficient of variation (CV)3.0730358
Kurtosis35.318228
Mean65096.551
Median Absolute Deviation (MAD)2962.45
Skewness5.5275424
Sum12498538
Variance4.0017614 × 1010
MonotonicityNot monotonic
2024-04-22T01:25:49.936445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.0 2
 
1.0%
20.0 2
 
1.0%
8.0 2
 
1.0%
30.0 2
 
1.0%
28971.0 1
 
0.5%
844.5 1
 
0.5%
0.5 1
 
0.5%
1512602.0 1
 
0.5%
250396.0 1
 
0.5%
226.0 1
 
0.5%
Other values (178) 178
92.7%
ValueCountFrequency (%)
0.5 1
0.5%
2.5 1
0.5%
4.0 1
0.5%
6.0 2
1.0%
7.3 1
0.5%
8.0 2
1.0%
10.0 1
0.5%
14.0 1
0.5%
16.0 1
0.5%
17.05 1
0.5%
ValueCountFrequency (%)
1587328.0 1
0.5%
1512602.0 1
0.5%
1145404.0 1
0.5%
636619.2 1
0.5%
545386.0 1
0.5%
463683.0 1
0.5%
432940.0 1
0.5%
426453.0 1
0.5%
335344.0 1
0.5%
331554.0 1
0.5%

품목별총금액(원)
Real number (ℝ)

HIGH CORRELATION 

Distinct191
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.2513763 × 108
Minimum4500
Maximum2.015937 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:50.418882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4500
5-th percentile42250
Q11161750
median9982875
Q381857550
95-th percentile6.6757754 × 108
Maximum2.015937 × 109
Range2.0159325 × 109
Interquartile range (IQR)80695800

Descriptive statistics

Standard deviation2.8382302 × 108
Coefficient of variation (CV)2.2680869
Kurtosis15.380636
Mean1.2513763 × 108
Median Absolute Deviation (MAD)9866875
Skewness3.592472
Sum2.4026425 × 1010
Variance8.0555507 × 1016
MonotonicityNot monotonic
2024-04-22T01:25:50.689604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24000 2
 
1.0%
521000 1
 
0.5%
3334000 1
 
0.5%
7001300 1
 
0.5%
4500 1
 
0.5%
963235820 1
 
0.5%
275316950 1
 
0.5%
348000 1
 
0.5%
519241000 1
 
0.5%
670166000 1
 
0.5%
Other values (181) 181
94.3%
ValueCountFrequency (%)
4500 1
0.5%
8000 1
0.5%
13000 1
0.5%
20000 1
0.5%
24000 2
1.0%
25000 1
0.5%
26000 1
0.5%
30000 1
0.5%
34000 1
0.5%
49000 1
0.5%
ValueCountFrequency (%)
2015937000 1
0.5%
1481268600 1
0.5%
1300592500 1
0.5%
1201534980 1
0.5%
1140242200 1
0.5%
963235820 1
0.5%
889366000 1
0.5%
804088000 1
0.5%
678919020 1
0.5%
670166000 1
0.5%

(주)부평농산 총물량(KG)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct148
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23755.286
Minimum0
Maximum746015
Zeros44
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:50.953616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17.5
median561
Q310072.75
95-th percentile115356.2
Maximum746015
Range746015
Interquartile range (IQR)10065.25

Descriptive statistics

Standard deviation82840.464
Coefficient of variation (CV)3.4872434
Kurtosis52.652913
Mean23755.286
Median Absolute Deviation (MAD)561
Skewness6.7449251
Sum4561014.9
Variance6.8625425 × 109
MonotonicityNot monotonic
2024-04-22T01:25:51.210443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 44
 
22.9%
6.0 2
 
1.0%
22050.5 1
 
0.5%
9665.0 1
 
0.5%
176.25 1
 
0.5%
746015.0 1
 
0.5%
110318.0 1
 
0.5%
111634.0 1
 
0.5%
37538.0 1
 
0.5%
91121.0 1
 
0.5%
Other values (138) 138
71.9%
ValueCountFrequency (%)
0.0 44
22.9%
1.0 1
 
0.5%
4.0 1
 
0.5%
6.0 2
 
1.0%
8.0 1
 
0.5%
10.0 1
 
0.5%
16.0 1
 
0.5%
20.0 1
 
0.5%
21.0 1
 
0.5%
23.0 1
 
0.5%
ValueCountFrequency (%)
746015.0 1
0.5%
695456.0 1
0.5%
298300.0 1
0.5%
235663.2 1
0.5%
194190.0 1
0.5%
170957.0 1
0.5%
138162.0 1
0.5%
136888.0 1
0.5%
122762.0 1
0.5%
116146.0 1
0.5%

(주)부평농산 총금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct148
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43970199
Minimum0
Maximum7.70649 × 108
Zeros44
Zeros (%)22.9%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:51.474383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q148250
median2165250
Q333575000
95-th percentile2.3208771 × 108
Maximum7.70649 × 108
Range7.70649 × 108
Interquartile range (IQR)33526750

Descriptive statistics

Standard deviation1.0559776 × 108
Coefficient of variation (CV)2.4015758
Kurtosis18.40715
Mean43970199
Median Absolute Deviation (MAD)2165250
Skewness3.9433834
Sum8.4422782 × 109
Variance1.1150888 × 1016
MonotonicityNot monotonic
2024-04-22T01:25:51.745363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 44
 
22.9%
383000 2
 
1.0%
8895100 1
 
0.5%
1538500 1
 
0.5%
484893640 1
 
0.5%
99481850 1
 
0.5%
141703500 1
 
0.5%
173224500 1
 
0.5%
54585300 1
 
0.5%
104358500 1
 
0.5%
Other values (138) 138
71.9%
ValueCountFrequency (%)
0 44
22.9%
5000 1
 
0.5%
8000 1
 
0.5%
24000 1
 
0.5%
34000 1
 
0.5%
53000 1
 
0.5%
60000 1
 
0.5%
80000 1
 
0.5%
88000 1
 
0.5%
88500 1
 
0.5%
ValueCountFrequency (%)
770649000 1
0.5%
597697300 1
0.5%
484893640 1
0.5%
463386000 1
0.5%
422358300 1
0.5%
385876000 1
0.5%
314009000 1
0.5%
299693500 1
0.5%
291833600 1
0.5%
233585000 1
0.5%

(주)경인농산 총물량(KG)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct150
Distinct (%)78.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19075.934
Minimum0
Maximum476889
Zeros34
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:52.010289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q120
median644
Q37024.75
95-th percentile89713.725
Maximum476889
Range476889
Interquartile range (IQR)7004.75

Descriptive statistics

Standard deviation58819.927
Coefficient of variation (CV)3.0834625
Kurtosis30.937979
Mean19075.934
Median Absolute Deviation (MAD)644
Skewness5.1667484
Sum3662579.3
Variance3.4597838 × 109
MonotonicityNot monotonic
2024-04-22T01:25:52.270357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 34
 
17.7%
20.0 4
 
2.1%
120.0 2
 
1.0%
16.0 2
 
1.0%
200.0 2
 
1.0%
138.0 2
 
1.0%
849.0 2
 
1.0%
30.0 2
 
1.0%
7387.0 1
 
0.5%
983.0 1
 
0.5%
Other values (140) 140
72.9%
ValueCountFrequency (%)
0.0 34
17.7%
0.5 1
 
0.5%
2.0 1
 
0.5%
2.5 1
 
0.5%
4.0 1
 
0.5%
5.0 1
 
0.5%
8.0 1
 
0.5%
10.0 1
 
0.5%
12.0 1
 
0.5%
13.45 1
 
0.5%
ValueCountFrequency (%)
476889.0 1
0.5%
373599.0 1
0.5%
351654.0 1
0.5%
199210.0 1
0.5%
174225.0 1
0.5%
172450.0 1
0.5%
169935.0 1
0.5%
162461.0 1
0.5%
113710.0 1
0.5%
92981.0 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%
Mean37774344
Minimum0
Maximum7.43266 × 108
Zeros34
Zeros (%)17.7%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:52.519490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q193800
median1710750
Q319567312
95-th percentile2.13438 × 108
Maximum7.43266 × 108
Range7.43266 × 108
Interquartile range (IQR)19473512

Descriptive statistics

Standard deviation94405629
Coefficient of variation (CV)2.4991997
Kurtosis21.28064
Mean37774344
Median Absolute Deviation (MAD)1710750
Skewness4.116592
Sum7.252674 × 109
Variance8.9124227 × 1015
MonotonicityNot monotonic
2024-04-22T01:25:52.781825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34
 
17.7%
32000 2
 
1.0%
122000 2
 
1.0%
83996500 1
 
0.5%
220063060 1
 
0.5%
138878700 1
 
0.5%
258000 1
 
0.5%
208017500 1
 
0.5%
304601000 1
 
0.5%
26056600 1
 
0.5%
Other values (147) 147
76.6%
ValueCountFrequency (%)
0 34
17.7%
4500 1
 
0.5%
6000 1
 
0.5%
8000 1
 
0.5%
15000 1
 
0.5%
20500 1
 
0.5%
25000 1
 
0.5%
32000 2
 
1.0%
34000 1
 
0.5%
36000 1
 
0.5%
ValueCountFrequency (%)
743266000 1
0.5%
518871500 1
0.5%
385238000 1
0.5%
378233500 1
0.5%
360775100 1
0.5%
304601000 1
0.5%
292830200 1
0.5%
244952700 1
0.5%
235305400 1
0.5%
220063060 1
0.5%

인천원예농협 총물량(KG)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct156
Distinct (%)81.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22265.332
Minimum0
Maximum518273
Zeros33
Zeros (%)17.2%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:53.047828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q139.5
median1116.675
Q310556.25
95-th percentile120899.7
Maximum518273
Range518273
Interquartile range (IQR)10516.75

Descriptive statistics

Standard deviation63562.14
Coefficient of variation (CV)2.8547583
Kurtosis30.946686
Mean22265.332
Median Absolute Deviation (MAD)1116.675
Skewness5.1179905
Sum4274943.7
Variance4.0401456 × 109
MonotonicityNot monotonic
2024-04-22T01:25:53.304780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 33
 
17.2%
700.0 2
 
1.0%
10.0 2
 
1.0%
108.0 2
 
1.0%
51.0 2
 
1.0%
50.0 1
 
0.5%
164.8 1
 
0.5%
47097.0 1
 
0.5%
70.0 1
 
0.5%
144884.0 1
 
0.5%
Other values (146) 146
76.0%
ValueCountFrequency (%)
0.0 33
17.2%
2.5 1
 
0.5%
4.0 1
 
0.5%
7.05 1
 
0.5%
7.3 1
 
0.5%
10.0 2
 
1.0%
13.0 1
 
0.5%
14.0 1
 
0.5%
15.0 1
 
0.5%
17.05 1
 
0.5%
ValueCountFrequency (%)
518273.0 1
0.5%
414933.0 1
0.5%
370215.0 1
0.5%
201746.0 1
0.5%
200685.0 1
0.5%
188735.0 1
0.5%
144884.0 1
0.5%
135040.0 1
0.5%
130097.0 1
0.5%
121662.0 1
0.5%

인천원예농협 총금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct159
Distinct (%)82.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43393089
Minimum0
Maximum5.02022 × 108
Zeros33
Zeros (%)17.2%
Negative0
Negative (%)0.0%
Memory size1.8 KiB
2024-04-22T01:25:53.560203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1131750
median3774250
Q330763125
95-th percentile2.5690195 × 108
Maximum5.02022 × 108
Range5.02022 × 108
Interquartile range (IQR)30631375

Descriptive statistics

Standard deviation91662985
Coefficient of variation (CV)2.1123867
Kurtosis9.5000506
Mean43393089
Median Absolute Deviation (MAD)3774250
Skewness2.9929541
Sum8.331473 × 109
Variance8.4021028 × 1015
MonotonicityNot monotonic
2024-04-22T01:25:53.817198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33
 
17.2%
15000 2
 
1.0%
927000 1
 
0.5%
36956400 1
 
0.5%
90000 1
 
0.5%
169520000 1
 
0.5%
192340500 1
 
0.5%
33381000 1
 
0.5%
18421800 1
 
0.5%
109471500 1
 
0.5%
Other values (149) 149
77.6%
ValueCountFrequency (%)
0 33
17.2%
5000 1
 
0.5%
13000 1
 
0.5%
14300 1
 
0.5%
15000 2
 
1.0%
20000 1
 
0.5%
24000 1
 
0.5%
26000 1
 
0.5%
27000 1
 
0.5%
48500 1
 
0.5%
ValueCountFrequency (%)
502022000 1
0.5%
498333300 1
0.5%
458973000 1
0.5%
382969980 1
0.5%
357108800 1
0.5%
325746000 1
0.5%
267201000 1
0.5%
262633900 1
0.5%
258279120 1
0.5%
257180600 1
0.5%

Interactions

2024-04-22T01:25:44.827946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:35.335246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:36.691319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:38.049196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:39.381564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:40.927042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:42.199967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:43.531621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:44.997077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:35.509892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:36.868388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:38.227980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:39.557135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:41.095301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:42.390238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:43.701908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:45.162951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:35.687525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:37.044487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:38.405246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:39.735241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:41.263523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:42.565815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:43.878398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:45.323383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:35.860465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:37.221662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:38.567528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:39.906394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:41.423156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:42.730007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:44.042254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:45.485333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:36.038884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:37.397210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:38.749037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:40.079381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:41.591845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:42.902250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:44.206896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:45.633604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:36.197945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:37.557358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:38.899257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:40.443823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:41.733810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:43.053740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:44.350586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:45.791825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:36.371549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:37.732981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:39.069364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:40.614651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:41.900801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:43.224497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:44.519152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:45.940064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:36.528683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:37.891738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:39.220516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:40.771499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:42.044839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:43.379107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-22T01:25:44.675763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T01:25:53.993207image/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)
대분류1.0000.0000.0000.0000.2150.5390.0000.4260.387
품목별총물량(KG)0.0001.0000.8670.9340.8270.9920.8650.9780.794
품목별총금액(원)0.0000.8671.0000.9180.9790.8190.9270.8320.966
(주)부평농산 총물량(KG)0.0000.9340.9181.0000.8400.9180.8350.8590.873
(주)부평농산 총금액(원)0.2150.8270.9790.8401.0000.8010.8850.8050.937
(주)경인농산 총물량(KG)0.5390.9920.8190.9180.8011.0000.8480.9730.794
(주)경인농산 총금액(원)0.0000.8650.9270.8350.8850.8481.0000.8190.848
인천원예농협 총물량(KG)0.4260.9780.8320.8590.8050.9730.8191.0000.807
인천원예농협 총금액(원)0.3870.7940.9660.8730.9370.7940.8480.8071.000
2024-04-22T01:25:54.221486image/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)1.0000.9700.8840.8570.9120.8880.9460.9260.000
품목별총금액(원)0.9701.0000.8850.8980.8820.8920.9110.9340.000
(주)부평농산 총물량(KG)0.8840.8851.0000.9800.7940.7810.7980.7950.000
(주)부평농산 총금액(원)0.8570.8980.9801.0000.7690.7800.7710.7980.078
(주)경인농산 총물량(KG)0.9120.8820.7940.7691.0000.9830.8660.8400.252
(주)경인농산 총금액(원)0.8880.8920.7810.7800.9831.0000.8370.8370.000
인천원예농협 총물량(KG)0.9460.9110.7980.7710.8660.8371.0000.9790.187
인천원예농협 총금액(원)0.9260.9340.7950.7980.8400.8370.9791.0000.153
대분류0.0000.0000.0000.0780.2520.0000.1870.1531.000

Missing values

2024-04-22T01:25:46.142671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T01:25:46.404713image/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)
0건제품다시마154.05640000.00154.05640000.00
1건제품청각10.0200000.000.0010.020000
2과실류사과316561.01481268600114710.059769730086810.0385238000115041.0498333300
3과실류배109450.027634100043395.010919750010505.02570150055550.0141442000
4과실류포도463683.02015937000170957.0770649000172450.0743266000120276.0502022000
5과실류복숭아1884.0119690000.001672.010961000212.01008000
6과실류단감335344.0889366000138162.038587600067085.0177744000130097.0325746000
7과실류자두1190.042680000.001190.042680000.00
8과실류모과2302.037265000.00110.01060002192.03620500
9과실류참다래(키위)12058.4954265004127.6359690001248.2109640006682.648493500
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)
182특용작물류유채5557.298470001889.034080001508.024045002160.24034500
183특용작물류고추씨70.04032000.0020.010400050.0299200
184특용작물류호박씨26.020500026.02050000.000.00
185특용작물류수세미285.01440000.000.00285.0144000
186특용작물류차류8.0250000.008.0250000.00
187특용작물류해바라기씨8.0340008.0340000.000.00
188특용작물류기타71.03000000.000.0071.0300000
189특용작물류호박씨60.038300060.03830000.000.00
190특용작물류차류678.024290000.0020.036000658.02393000
191특용작물류해바라기씨24.08800024.0880000.000.00