Overview

Dataset statistics

Number of variables5
Number of observations85
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory45.6 B

Variable types

Categorical2
Numeric3

Dataset

Description국립농산물품질관리원 원산지표시 지역별 적발현황(년도, 시도, 거짓표시 적발실적, 미표시 적발실적, 과태료)
Author국립농산물품질관리원
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20191011000000001215

Alerts

거짓표시 적발실적(개소) is highly overall correlated with 미표시 적발실적(개소) and 1 other fieldsHigh correlation
미표시 적발실적(개소) is highly overall correlated with 거짓표시 적발실적(개소) and 1 other fieldsHigh correlation
과태료(천원) is highly overall correlated with 거짓표시 적발실적(개소) and 1 other fieldsHigh correlation
과태료(천원) has unique valuesUnique

Reproduction

Analysis started2024-03-23 07:49:21.478208
Analysis finished2024-03-23 07:49:24.578512
Duration3.1 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

Distinct5
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size812.0 B
2018
17 
2019
17 
2020
17 
2021
17 
2022
17 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018
2nd row2018
3rd row2018
4th row2018
5th row2018

Common Values

ValueCountFrequency (%)
2018 17
20.0%
2019 17
20.0%
2020 17
20.0%
2021 17
20.0%
2022 17
20.0%

Length

2024-03-23T07:49:24.770408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T07:49:25.101742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 17
20.0%
2019 17
20.0%
2020 17
20.0%
2021 17
20.0%
2022 17
20.0%

시도
Categorical

Distinct34
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Memory size812.0 B
서울
 
4
전북
 
4
강원
 
4
대구
 
4
인천
 
4
Other values (29)
65 

Length

Max length4
Median length2
Mean length2.4
Min length2

Unique

Unique17 ?
Unique (%)20.0%

Sample

1st row서울
2nd row부산
3rd row대구
4th row인천
5th row광주

Common Values

ValueCountFrequency (%)
서울 4
 
4.7%
전북 4
 
4.7%
강원 4
 
4.7%
대구 4
 
4.7%
인천 4
 
4.7%
광주 4
 
4.7%
대전 4
 
4.7%
세종 4
 
4.7%
경기 4
 
4.7%
울산 4
 
4.7%
Other values (24) 45
52.9%

Length

2024-03-23T07:49:25.680800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 5
 
5.9%
울산 5
 
5.9%
제주 5
 
5.9%
경남 5
 
5.9%
경북 5
 
5.9%
전남 5
 
5.9%
충남 5
 
5.9%
충북 5
 
5.9%
경기 5
 
5.9%
전북 5
 
5.9%
Other values (7) 35
41.2%

거짓표시 적발실적(개소)
Real number (ℝ)

HIGH CORRELATION 

Distinct72
Distinct (%)84.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.89412
Minimum10
Maximum390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-03-23T07:49:26.020846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile25.6
Q151
median97
Q3136
95-th percentile261.4
Maximum390
Range380
Interquartile range (IQR)85

Descriptive statistics

Standard deviation73.935787
Coefficient of variation (CV)0.67896952
Kurtosis2.3391824
Mean108.89412
Median Absolute Deviation (MAD)46
Skewness1.3552028
Sum9256
Variance5466.5006
MonotonicityNot monotonic
2024-03-23T07:49:26.303813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
125 2
 
2.4%
68 2
 
2.4%
87 2
 
2.4%
134 2
 
2.4%
28 2
 
2.4%
176 2
 
2.4%
97 2
 
2.4%
171 2
 
2.4%
131 2
 
2.4%
40 2
 
2.4%
Other values (62) 65
76.5%
ValueCountFrequency (%)
10 1
1.2%
14 1
1.2%
16 1
1.2%
21 1
1.2%
25 1
1.2%
28 2
2.4%
30 1
1.2%
31 1
1.2%
34 2
2.4%
37 1
1.2%
ValueCountFrequency (%)
390 1
1.2%
333 1
1.2%
284 1
1.2%
270 1
1.2%
263 1
1.2%
255 1
1.2%
221 1
1.2%
219 1
1.2%
183 1
1.2%
182 1
1.2%

미표시 적발실적(개소)
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean81.905882
Minimum8
Maximum223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-03-23T07:49:26.583174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile16.2
Q147
median77
Q3102
95-th percentile185
Maximum223
Range215
Interquartile range (IQR)55

Descriptive statistics

Standard deviation51.062899
Coefficient of variation (CV)0.62343384
Kurtosis0.50863505
Mean81.905882
Median Absolute Deviation (MAD)30
Skewness0.90243124
Sum6962
Variance2607.4196
MonotonicityNot monotonic
2024-03-23T07:49:27.080542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56 3
 
3.5%
53 3
 
3.5%
84 3
 
3.5%
95 2
 
2.4%
35 2
 
2.4%
34 2
 
2.4%
71 2
 
2.4%
124 2
 
2.4%
81 2
 
2.4%
91 2
 
2.4%
Other values (57) 62
72.9%
ValueCountFrequency (%)
8 1
1.2%
9 1
1.2%
12 1
1.2%
15 1
1.2%
16 1
1.2%
17 1
1.2%
19 2
2.4%
20 1
1.2%
24 1
1.2%
26 2
2.4%
ValueCountFrequency (%)
223 1
1.2%
219 1
1.2%
211 1
1.2%
203 1
1.2%
188 1
1.2%
173 1
1.2%
171 1
1.2%
166 1
1.2%
160 1
1.2%
149 1
1.2%

과태료(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23880.259
Minimum2200
Maximum85113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2024-03-23T07:49:27.584723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2200
5-th percentile3901.6
Q111393
median18601
Q331920
95-th percentile60519.2
Maximum85113
Range82913
Interquartile range (IQR)20527

Descriptive statistics

Standard deviation18290.023
Coefficient of variation (CV)0.76590557
Kurtosis1.6548968
Mean23880.259
Median Absolute Deviation (MAD)10006
Skewness1.363066
Sum2029822
Variance3.3452495 × 108
MonotonicityNot monotonic
2024-03-23T07:49:28.075519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24907 1
 
1.2%
11393 1
 
1.2%
23833 1
 
1.2%
59099 1
 
1.2%
17519 1
 
1.2%
69149 1
 
1.2%
2550 1
 
1.2%
5450 1
 
1.2%
8328 1
 
1.2%
17068 1
 
1.2%
Other values (75) 75
88.2%
ValueCountFrequency (%)
2200 1
1.2%
2550 1
1.2%
2700 1
1.2%
3500 1
1.2%
3857 1
1.2%
4080 1
1.2%
4369 1
1.2%
4400 1
1.2%
5450 1
1.2%
5495 1
1.2%
ValueCountFrequency (%)
85113 1
1.2%
75121 1
1.2%
74579 1
1.2%
69149 1
1.2%
60570 1
1.2%
60316 1
1.2%
59099 1
1.2%
52569 1
1.2%
52542 1
1.2%
48064 1
1.2%

Interactions

2024-03-23T07:49:23.166719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:21.802935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:22.485952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:23.444716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:22.046799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:22.702641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:23.834059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:22.247745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:49:22.939626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:49:28.337863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도시도거짓표시 적발실적(개소)미표시 적발실적(개소)과태료(천원)
년도1.0000.0000.1670.0000.000
시도0.0001.0000.5320.7920.787
거짓표시 적발실적(개소)0.1670.5321.0000.9060.849
미표시 적발실적(개소)0.0000.7920.9061.0000.898
과태료(천원)0.0000.7870.8490.8981.000
2024-03-23T07:49:28.592974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도시도
년도1.0000.000
시도0.0001.000
2024-03-23T07:49:28.831028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거짓표시 적발실적(개소)미표시 적발실적(개소)과태료(천원)년도시도
거짓표시 적발실적(개소)1.0000.8170.7060.0830.158
미표시 적발실적(개소)0.8171.0000.9180.0000.342
과태료(천원)0.7060.9181.0000.0000.330
년도0.0830.0000.0001.0000.000
시도0.1580.3420.3300.0001.000

Missing values

2024-03-23T07:49:24.143350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T07:49:24.455695image/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

년도시도거짓표시 적발실적(개소)미표시 적발실적(개소)과태료(천원)
02018서울2637824907
12018부산1366916454
22018대구1025617121
32018인천69458595
42018광주847212464
52018대전1154911423
62018울산41314080
72018세종25164369
82018경기39018852569
92018강원15516052542
년도시도거짓표시 적발실적(개소)미표시 적발실적(개소)과태료(천원)
752022세종1692700
762022경기18314960316
772022강원608630168
782022충북709533661
792022충남856817988
802022전북654911355
812022전남825628563
822022경북937322944
832022경남879019039
842022제주103511901