Overview

Dataset statistics

Number of variables4
Number of observations6749
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory224.2 KiB
Average record size in memory34.0 B

Variable types

Categorical1
Text1
Numeric2

Dataset

Description인천광역시 남촌농산물도매시장에서 거래되는 농산물에 대한 경매 가격 정보로 거래일자, 품목, 물량, 금액 등을 볼 수 있습니다
Author인천광역시
URLhttps://www.data.go.kr/data/15051663/fileData.do

Alerts

물량 is highly overall correlated with 금액High correlation
금액 is highly overall correlated with 물량High correlation

Reproduction

Analysis started2024-04-21 01:18:42.580214
Analysis finished2024-04-21 01:18:44.449716
Duration1.87 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Categorical

Distinct26
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
2024-03-05 00:00
 
278
2024-03-18 00:00
 
276
2024-03-25 00:00
 
275
2024-03-29 00:00
 
275
2024-03-19 00:00
 
272
Other values (21)
5373 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-03-01 00:00
2nd row2024-03-01 00:00
3rd row2024-03-01 00:00
4th row2024-03-01 00:00
5th row2024-03-01 00:00

Common Values

ValueCountFrequency (%)
2024-03-05 00:00 278
 
4.1%
2024-03-18 00:00 276
 
4.1%
2024-03-25 00:00 275
 
4.1%
2024-03-29 00:00 275
 
4.1%
2024-03-19 00:00 272
 
4.0%
2024-03-28 00:00 271
 
4.0%
2024-03-15 00:00 270
 
4.0%
2024-03-26 00:00 269
 
4.0%
2024-03-01 00:00 266
 
3.9%
2024-03-14 00:00 266
 
3.9%
Other values (16) 4031
59.7%

Length

2024-04-21T10:18:44.522864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
00:00 6749
50.0%
2024-03-05 278
 
2.1%
2024-03-18 276
 
2.0%
2024-03-25 275
 
2.0%
2024-03-29 275
 
2.0%
2024-03-19 272
 
2.0%
2024-03-28 271
 
2.0%
2024-03-15 270
 
2.0%
2024-03-26 269
 
2.0%
2024-03-01 266
 
2.0%
Other values (17) 4297
31.8%

품목
Text

Distinct452
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
2024-04-21T10:18:44.722918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length18
Mean length9.8979108
Min length5

Characters and Unicode

Total characters66801
Distinct characters303
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

Unique54 ?
Unique (%)0.8%

Sample

1st row가지(가지(일반))
2nd row감귤(비가림감귤)
3rd row감귤(천헤향)
4th row감자(기타)
5th row감자(대지)
ValueCountFrequency (%)
및 202
 
2.8%
전분 202
 
2.8%
마늘(깐마늘 53
 
0.7%
브로코리(녹색꽃양배추)(브로코리(일반 26
 
0.4%
상추(기타 26
 
0.4%
사과(후지 26
 
0.4%
상추(포기찹 26
 
0.4%
사과(미시마 26
 
0.4%
브로코리(녹색꽃양배추)(브로코리(수입 26
 
0.4%
상추(꽃적상추 26
 
0.4%
Other values (446) 6571
91.1%
2024-04-21T10:18:45.052566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 9925
 
14.9%
) 9925
 
14.9%
일 2040
 
3.1%
반 1994
 
3.0%
추 1624
 
2.4%
기 1518
 
2.3%
리 1387
 
2.1%
타 1324
 
2.0%
고 1223
 
1.8%
나 1010
 
1.5%
Other values (293) 34831
52.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 46406
69.5%
Open Punctuation 9925
 
14.9%
Close Punctuation 9925
 
14.9%
Space Separator 461
 
0.7%
Other Punctuation 55
 
0.1%
Decimal Number 29
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 2040
 
4.4%
반 1994
 
4.3%
추 1624
 
3.5%
기 1518
 
3.3%
리 1387
 
3.0%
타 1324
 
2.9%
고 1223
 
2.6%
나 1010
 
2.2%
수 997
 
2.1%
마 865
 
1.9%
Other values (288) 32424
69.9%
Open Punctuation
ValueCountFrequency (%)
( 9925
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9925
100.0%
Space Separator
ValueCountFrequency (%)
461
100.0%
Other Punctuation
ValueCountFrequency (%)
, 55
100.0%
Decimal Number
ValueCountFrequency (%)
1 29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 46406
69.5%
Common 20395
30.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 2040
 
4.4%
반 1994
 
4.3%
추 1624
 
3.5%
기 1518
 
3.3%
리 1387
 
3.0%
타 1324
 
2.9%
고 1223
 
2.6%
나 1010
 
2.2%
수 997
 
2.1%
마 865
 
1.9%
Other values (288) 32424
69.9%
Common
ValueCountFrequency (%)
( 9925
48.7%
) 9925
48.7%
461
 
2.3%
, 55
 
0.3%
1 29
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 46406
69.5%
ASCII 20395
30.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 9925
48.7%
) 9925
48.7%
461
 
2.3%
, 55
 
0.3%
1 29
 
0.1%
Hangul
ValueCountFrequency (%)
일 2040
 
4.4%
반 1994
 
4.3%
추 1624
 
3.5%
기 1518
 
3.3%
리 1387
 
3.0%
타 1324
 
2.9%
고 1223
 
2.6%
나 1010
 
2.2%
수 997
 
2.1%
마 865
 
1.9%
Other values (288) 32424
69.9%

물량
Real number (ℝ)

HIGH CORRELATION 

Distinct2610
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1724.6173
Minimum0.03
Maximum96025
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.4 KiB
2024-04-21T10:18:45.173628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile6
Q154
median285
Q31236
95-th percentile8449
Maximum96025
Range96024.97
Interquartile range (IQR)1182

Descriptive statistics

Standard deviation4791.8785
Coefficient of variation (CV)2.778517
Kurtosis73.075889
Mean1724.6173
Median Absolute Deviation (MAD)271
Skewness6.9571813
Sum11639442
Variance22962099
MonotonicityNot monotonic
2024-04-21T10:18:45.294179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 155
 
2.3%
20.0 150
 
2.2%
4.0 101
 
1.5%
40.0 90
 
1.3%
30.0 86
 
1.3%
50.0 85
 
1.3%
2.0 82
 
1.2%
8.0 77
 
1.1%
80.0 68
 
1.0%
60.0 61
 
0.9%
Other values (2600) 5794
85.8%
ValueCountFrequency (%)
0.03 1
 
< 0.1%
0.04 1
 
< 0.1%
0.05 1
 
< 0.1%
0.08 1
 
< 0.1%
0.1 2
 
< 0.1%
0.2 4
0.1%
0.3 2
 
< 0.1%
0.35 1
 
< 0.1%
0.5 2
 
< 0.1%
0.6 6
0.1%
ValueCountFrequency (%)
96025.0 1
< 0.1%
76800.0 1
< 0.1%
68941.0 1
< 0.1%
66310.0 1
< 0.1%
59970.0 1
< 0.1%
59065.0 1
< 0.1%
55730.0 1
< 0.1%
54700.0 1
< 0.1%
54170.0 1
< 0.1%
52700.0 1
< 0.1%

금액
Real number (ℝ)

HIGH CORRELATION 

Distinct4326
Distinct (%)64.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5141980.7
Minimum1500
Maximum1.718765 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size59.4 KiB
2024-04-21T10:18:45.407027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1500
5-th percentile22200
Q1195800
median1048000
Q34500000
95-th percentile23884800
Maximum1.718765 × 108
Range1.71875 × 108
Interquartile range (IQR)4304200

Descriptive statistics

Standard deviation11859283
Coefficient of variation (CV)2.3063648
Kurtosis38.634063
Mean5141980.7
Median Absolute Deviation (MAD)996000
Skewness5.2957267
Sum3.4703227 × 1010
Variance1.406426 × 1014
MonotonicityNot monotonic
2024-04-21T10:18:45.527451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000 48
 
0.7%
40000 41
 
0.6%
30000 36
 
0.5%
60000 36
 
0.5%
120000 28
 
0.4%
24000 28
 
0.4%
50000 27
 
0.4%
100000 26
 
0.4%
150000 24
 
0.4%
15000 24
 
0.4%
Other values (4316) 6431
95.3%
ValueCountFrequency (%)
1500 3
 
< 0.1%
2000 3
 
< 0.1%
2500 1
 
< 0.1%
3000 16
0.2%
3500 1
 
< 0.1%
4000 8
0.1%
4500 4
 
0.1%
5000 8
0.1%
6000 18
0.3%
7000 10
0.1%
ValueCountFrequency (%)
171876500 1
< 0.1%
144643600 1
< 0.1%
125508000 1
< 0.1%
125504600 1
< 0.1%
124650000 1
< 0.1%
124579300 1
< 0.1%
122672000 1
< 0.1%
120057100 1
< 0.1%
118708000 1
< 0.1%
116664000 1
< 0.1%

Interactions

2024-04-21T10:18:44.127158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:18:43.897003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:18:44.210904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T10:18:44.040020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T10:18:45.615306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자물량금액
일자1.0000.0000.000
물량0.0001.0000.554
금액0.0000.5541.000
2024-04-21T10:18:45.700632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
물량금액일자
물량1.0000.9360.000
금액0.9361.0000.000
일자0.0000.0001.000

Missing values

2024-04-21T10:18:44.319009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T10:18:44.405953image/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

일자품목물량금액
02024-03-01 00:00가지(가지(일반))1605.010101500
12024-03-01 00:00감귤(비가림감귤)460.02009000
22024-03-01 00:00감귤(천헤향)2441.016094500
32024-03-01 00:00감자(기타)320.0678000
42024-03-01 00:00감자(대지)5060.011103000
52024-03-01 00:00감자(돼지감자)78.0100000
62024-03-01 00:00감자(두백)240.0405000
72024-03-01 00:00감자(수미)15040.033919000
82024-03-01 00:00건고추(건고추(일반))50.0710000
92024-03-01 00:00겨자(적겨자)36.0110000
일자품목물량금액
67392024-03-30 00:00풋고추(오이맛고추)829.03571100
67402024-03-30 00:00풋고추(청양)2589.524634650
67412024-03-30 00:00피망(단고추)(반홍피망)30.077000
67422024-03-30 00:00피망(단고추)(청피망)300.01283000
67432024-03-30 00:00피망(단고추)(피망(일반))100.0300000
67442024-03-30 00:00피망(단고추)(홍피망)35.065000
67452024-03-30 00:00호박(단호박(수입))640.0768000
67462024-03-30 00:00호박(애호박)2792.010122000
67472024-03-30 00:00호박(쥬키니호박)590.01580000
67482024-03-30 00:00홍고추(홍고추(일반))280.02416000