Overview

Dataset statistics

Number of variables4
Number of observations7592
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory252.2 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://data.incheon.go.kr/findData/publicDataDetail?dataId=15051663&srcSe=7661IVAWM27C61E190

Alerts

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

Reproduction

Analysis started2024-05-17 21:16:07.113614
Analysis finished2024-05-17 21:16:08.623258
Duration1.51 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일자
Categorical

Distinct26
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size59.4 KiB
2023-10-19
 
317
2023-10-11
 
316
2023-10-17
 
314
2023-10-23
 
312
2023-10-31
 
311
Other values (21)
6022 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-02
2nd row2023-10-02
3rd row2023-10-02
4th row2023-10-02
5th row2023-10-02

Common Values

ValueCountFrequency (%)
2023-10-19 317
 
4.2%
2023-10-11 316
 
4.2%
2023-10-17 314
 
4.1%
2023-10-23 312
 
4.1%
2023-10-31 311
 
4.1%
2023-10-12 307
 
4.0%
2023-10-26 305
 
4.0%
2023-10-13 304
 
4.0%
2023-10-27 303
 
4.0%
2023-10-16 302
 
4.0%
Other values (16) 4501
59.3%

Length

2024-05-18T06:16:08.750487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2023-10-19 317
 
4.2%
2023-10-11 316
 
4.2%
2023-10-17 314
 
4.1%
2023-10-23 312
 
4.1%
2023-10-31 311
 
4.1%
2023-10-12 307
 
4.0%
2023-10-26 305
 
4.0%
2023-10-13 304
 
4.0%
2023-10-27 303
 
4.0%
2023-10-16 302
 
4.0%
Other values (16) 4501
59.3%

품목
Text

Distinct544
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Memory size59.4 KiB
2024-05-18T06:16:09.066679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length9.5036881
Min length5

Characters and Unicode

Total characters72152
Distinct characters325
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 (%)1.0%

Sample

1st row가지(가지(일반))
2nd row감귤(기타)
3rd row감귤(하우스감귤)
4th row감자(기타)
5th row감자(수미)
ValueCountFrequency (%)
및 198
 
2.5%
전분 198
 
2.5%
마늘(깐마늘 52
 
0.6%
가지(가지(일반 26
 
0.3%
아욱(아욱(일반 26
 
0.3%
양파(양파(수입 26
 
0.3%
양송이(양송이(일반 26
 
0.3%
양상추(양상추(일반 26
 
0.3%
양배추(양배추(일반 26
 
0.3%
알타리무(총각무(일반 26
 
0.3%
Other values (539) 7431
92.2%
2024-05-18T06:16:09.731928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 10773
 
14.9%
) 10773
 
14.9%
일 2170
 
3.0%
반 2137
 
3.0%
추 1867
 
2.6%
기 1703
 
2.4%
타 1602
 
2.2%
고 1492
 
2.1%
리 1368
 
1.9%
수 929
 
1.3%
Other values (315) 37338
51.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 50047
69.4%
Open Punctuation 10773
 
14.9%
Close Punctuation 10773
 
14.9%
Space Separator 469
 
0.7%
Other Punctuation 57
 
0.1%
Decimal Number 33
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 2170
 
4.3%
반 2137
 
4.3%
추 1867
 
3.7%
기 1703
 
3.4%
타 1602
 
3.2%
고 1492
 
3.0%
리 1368
 
2.7%
수 929
 
1.9%
마 913
 
1.8%
나 903
 
1.8%
Other values (309) 34963
69.9%
Decimal Number
ValueCountFrequency (%)
1 28
84.8%
8 5
 
15.2%
Open Punctuation
ValueCountFrequency (%)
( 10773
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10773
100.0%
Space Separator
ValueCountFrequency (%)
469
100.0%
Other Punctuation
ValueCountFrequency (%)
, 57
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 50047
69.4%
Common 22105
30.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 2170
 
4.3%
반 2137
 
4.3%
추 1867
 
3.7%
기 1703
 
3.4%
타 1602
 
3.2%
고 1492
 
3.0%
리 1368
 
2.7%
수 929
 
1.9%
마 913
 
1.8%
나 903
 
1.8%
Other values (309) 34963
69.9%
Common
ValueCountFrequency (%)
( 10773
48.7%
) 10773
48.7%
469
 
2.1%
, 57
 
0.3%
1 28
 
0.1%
8 5
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 50047
69.4%
ASCII 22105
30.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 10773
48.7%
) 10773
48.7%
469
 
2.1%
, 57
 
0.3%
1 28
 
0.1%
8 5
 
< 0.1%
Hangul
ValueCountFrequency (%)
일 2170
 
4.3%
반 2137
 
4.3%
추 1867
 
3.7%
기 1703
 
3.4%
타 1602
 
3.2%
고 1492
 
3.0%
리 1368
 
2.7%
수 929
 
1.9%
마 913
 
1.8%
나 903
 
1.8%
Other values (309) 34963
69.9%

물량
Real number (ℝ)

HIGH CORRELATION 

Distinct2948
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2030.0946
Minimum0.01
Maximum87230
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size66.9 KiB
2024-05-18T06:16:09.985607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile8
Q152
median275
Q31313.25
95-th percentile10500
Maximum87230
Range87229.99
Interquartile range (IQR)1261.25

Descriptive statistics

Standard deviation5393.9855
Coefficient of variation (CV)2.657012
Kurtosis48.212856
Mean2030.0946
Median Absolute Deviation (MAD)261
Skewness5.7568244
Sum15412478
Variance29095080
MonotonicityNot monotonic
2024-05-18T06:16:10.407872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 184
 
2.4%
20.0 157
 
2.1%
40.0 106
 
1.4%
4.0 101
 
1.3%
8.0 94
 
1.2%
60.0 90
 
1.2%
30.0 89
 
1.2%
50.0 78
 
1.0%
2.0 73
 
1.0%
80.0 69
 
0.9%
Other values (2938) 6551
86.3%
ValueCountFrequency (%)
0.01 1
< 0.1%
0.02 1
< 0.1%
0.05 1
< 0.1%
0.06 1
< 0.1%
0.1 2
< 0.1%
0.12 1
< 0.1%
0.13 1
< 0.1%
0.14 1
< 0.1%
0.2 1
< 0.1%
0.3 1
< 0.1%
ValueCountFrequency (%)
87230.0 1
< 0.1%
82296.0 1
< 0.1%
80542.0 1
< 0.1%
74260.0 1
< 0.1%
63390.0 1
< 0.1%
62815.0 1
< 0.1%
59675.0 1
< 0.1%
53815.0 1
< 0.1%
49660.0 1
< 0.1%
47314.0 1
< 0.1%

금액
Real number (ℝ)

HIGH CORRELATION 

Distinct4627
Distinct (%)60.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4275876.2
Minimum500
Maximum2.136805 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size66.9 KiB
2024-05-18T06:16:10.699949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum500
5-th percentile24000
Q1157375
median848750
Q33877075
95-th percentile19921400
Maximum2.136805 × 108
Range2.1368 × 108
Interquartile range (IQR)3719700

Descriptive statistics

Standard deviation10275595
Coefficient of variation (CV)2.4031555
Kurtosis102.19169
Mean4275876.2
Median Absolute Deviation (MAD)798750
Skewness7.7701046
Sum3.2462452 × 1010
Variance1.0558786 × 1014
MonotonicityNot monotonic
2024-05-18T06:16:10.952907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40000 49
 
0.6%
120000 43
 
0.6%
20000 42
 
0.6%
10000 40
 
0.5%
100000 39
 
0.5%
60000 37
 
0.5%
30000 35
 
0.5%
36000 33
 
0.4%
140000 31
 
0.4%
80000 31
 
0.4%
Other values (4617) 7212
95.0%
ValueCountFrequency (%)
500 1
 
< 0.1%
1000 5
 
0.1%
1500 1
 
< 0.1%
2000 4
 
0.1%
3000 7
 
0.1%
3900 1
 
< 0.1%
4000 7
 
0.1%
5000 14
0.2%
6000 20
0.3%
6500 1
 
< 0.1%
ValueCountFrequency (%)
213680500 1
< 0.1%
212964000 1
< 0.1%
179957000 1
< 0.1%
165563000 1
< 0.1%
161346000 1
< 0.1%
160867500 1
< 0.1%
156971500 1
< 0.1%
124871000 1
< 0.1%
104577500 1
< 0.1%
101872500 1
< 0.1%

Interactions

2024-05-18T06:16:08.011911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:07.707397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:08.169938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T06:16:07.856623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T06:16:11.114022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일자물량금액
일자1.0000.0240.000
물량0.0241.0000.638
금액0.0000.6381.000
2024-05-18T06:16:11.269331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
물량금액일자
물량1.0000.9360.009
금액0.9361.0000.000
일자0.0090.0001.000

Missing values

2024-05-18T06:16:08.408146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T06:16:08.561135image/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
02023-10-02가지(가지(일반))10205.011285700
12023-10-02감귤(기타)840.01827500
22023-10-02감귤(하우스감귤)4383.021041800
32023-10-02감자(기타)22040.035077000
42023-10-02감자(수미)16100.028817000
52023-10-02갓(돌산갓)596.0503200
62023-10-02강낭콩(강낭콩(일반))422.02040000
72023-10-02건고추(기타)14.0280000
82023-10-02건고추(청양건고추)2.556000
92023-10-02겨자(겨자(일반))14.0170000
일자품목물량금액
75822023-10-31피망(단고추)(청피망)655.02382000
75832023-10-31피망(단고추)(피망(일반))209.0561000
75842023-10-31피망(단고추)(홍피망)120.0436000
75852023-10-31호박(늙은호박)1444.0363300
75862023-10-31호박(단호박)2404.04278000
75872023-10-31호박(애호박)7158.011850400
75882023-10-31호박(쥬키니호박)1630.01318500
75892023-10-31호박잎(생호박잎)20.065000
75902023-10-31홍고추(홍고추(일반))1427.04774000
75912023-10-31홍고추(홍청양)169.0995000