Overview

Dataset statistics

Number of variables5
Number of observations102
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.4 KiB
Average record size in memory44.3 B

Variable types

Numeric3
Categorical1
Text1

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)High correlation
미표시 적발실적(개소) is highly overall correlated with 거짓표시 적발실적(개소)High correlation
과태료(천원) has unique valuesUnique

Reproduction

Analysis started2024-03-23 07:50:06.372718
Analysis finished2024-03-23 07:50:09.745514
Duration3.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Real number (ℝ)

Distinct6
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2020.5
Minimum2018
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-23T07:50:09.978916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2018
5-th percentile2018
Q12019
median2020.5
Q32022
95-th percentile2023
Maximum2023
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7162589
Coefficient of variation (CV)0.00084942286
Kurtosis-1.271813
Mean2020.5
Median Absolute Deviation (MAD)1.5
Skewness0
Sum206091
Variance2.9455446
MonotonicityIncreasing
2024-03-23T07:50:10.377672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2018 17
16.7%
2019 17
16.7%
2020 17
16.7%
2021 17
16.7%
2022 17
16.7%
2023 17
16.7%
ValueCountFrequency (%)
2018 17
16.7%
2019 17
16.7%
2020 17
16.7%
2021 17
16.7%
2022 17
16.7%
2023 17
16.7%
ValueCountFrequency (%)
2023 17
16.7%
2022 17
16.7%
2021 17
16.7%
2020 17
16.7%
2019 17
16.7%
2018 17
16.7%

시도
Categorical

Distinct34
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size948.0 B
서울
 
5
전북
 
5
강원
 
5
대구
 
5
인천
 
5
Other values (29)
77 

Length

Max length4
Median length2
Mean length2.3333333
Min length2

Unique

Unique17 ?
Unique (%)16.7%

Sample

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

Common Values

ValueCountFrequency (%)
서울 5
 
4.9%
전북 5
 
4.9%
강원 5
 
4.9%
대구 5
 
4.9%
인천 5
 
4.9%
광주 5
 
4.9%
대전 5
 
4.9%
세종 5
 
4.9%
경기 5
 
4.9%
울산 5
 
4.9%
Other values (24) 52
51.0%

Length

2024-03-23T07:50:10.774720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 6
 
5.9%
울산 6
 
5.9%
제주 6
 
5.9%
경남 6
 
5.9%
경북 6
 
5.9%
전남 6
 
5.9%
충남 6
 
5.9%
충북 6
 
5.9%
경기 6
 
5.9%
전북 6
 
5.9%
Other values (7) 42
41.2%

거짓표시 적발실적(개소)
Real number (ℝ)

HIGH CORRELATION 

Distinct82
Distinct (%)80.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean110.05882
Minimum9
Maximum390
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-23T07:50:11.199142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile21.2
Q157.5
median98.5
Q3136
95-th percentile269.65
Maximum390
Range381
Interquartile range (IQR)78.5

Descriptive statistics

Standard deviation73.914163
Coefficient of variation (CV)0.6715878
Kurtosis2.2172541
Mean110.05882
Median Absolute Deviation (MAD)40
Skewness1.3499419
Sum11226
Variance5463.3034
MonotonicityNot monotonic
2024-03-23T07:50:11.663304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
102 3
 
2.9%
34 3
 
2.9%
176 2
 
2.0%
136 2
 
2.0%
39 2
 
2.0%
134 2
 
2.0%
106 2
 
2.0%
28 2
 
2.0%
68 2
 
2.0%
94 2
 
2.0%
Other values (72) 80
78.4%
ValueCountFrequency (%)
9 1
 
1.0%
11 1
 
1.0%
14 1
 
1.0%
15 1
 
1.0%
17 1
 
1.0%
21 1
 
1.0%
25 1
 
1.0%
28 2
2.0%
33 1
 
1.0%
34 3
2.9%
ValueCountFrequency (%)
390 1
1.0%
333 1
1.0%
310 1
1.0%
284 1
1.0%
277 1
1.0%
270 1
1.0%
263 1
1.0%
255 1
1.0%
221 1
1.0%
219 1
1.0%

미표시 적발실적(개소)
Real number (ℝ)

HIGH CORRELATION 

Distinct80
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean86.745098
Minimum8
Maximum223
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-03-23T07:50:12.114551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile16.05
Q147.25
median80
Q3120.5
95-th percentile202.25
Maximum223
Range215
Interquartile range (IQR)73.25

Descriptive statistics

Standard deviation53.642876
Coefficient of variation (CV)0.61839663
Kurtosis0.13159298
Mean86.745098
Median Absolute Deviation (MAD)35
Skewness0.7773799
Sum8848
Variance2877.5581
MonotonicityNot monotonic
2024-03-23T07:50:12.599209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56 3
 
2.9%
53 3
 
2.9%
84 3
 
2.9%
26 3
 
2.9%
81 3
 
2.9%
77 2
 
2.0%
91 2
 
2.0%
129 2
 
2.0%
24 2
 
2.0%
69 2
 
2.0%
Other values (70) 77
75.5%
ValueCountFrequency (%)
8 1
1.0%
9 1
1.0%
10 1
1.0%
12 1
1.0%
15 1
1.0%
16 1
1.0%
17 1
1.0%
19 1
1.0%
20 1
1.0%
22 1
1.0%
ValueCountFrequency (%)
223 1
1.0%
221 1
1.0%
219 1
1.0%
217 1
1.0%
211 1
1.0%
203 1
1.0%
188 1
1.0%
185 1
1.0%
173 1
1.0%
171 1
1.0%

과태료(천원)
Text

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2024-03-23T07:50:13.342483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.6372549
Min length4

Characters and Unicode

Total characters575
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)100.0%

Sample

1st row24907
2nd row16454
3rd row17121
4th row8595
5th row12464
ValueCountFrequency (%)
24907 1
 
1.0%
19,705 1
 
1.0%
78,171 1
 
1.0%
12,884 1
 
1.0%
8,826 1
 
1.0%
57,488 1
 
1.0%
14,628 1
 
1.0%
36,892 1
 
1.0%
5,495 1
 
1.0%
29,900 1
 
1.0%
Other values (92) 92
90.2%
2024-03-23T07:50:14.450201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 85
14.8%
1 67
11.7%
2 64
11.1%
0 57
9.9%
4 53
9.2%
3 52
9.0%
5 44
7.7%
6 44
7.7%
8 40
7.0%
9 37
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 490
85.2%
Other Punctuation 85
 
14.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 67
13.7%
2 64
13.1%
0 57
11.6%
4 53
10.8%
3 52
10.6%
5 44
9.0%
6 44
9.0%
8 40
8.2%
9 37
7.6%
7 32
6.5%
Other Punctuation
ValueCountFrequency (%)
, 85
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
, 85
14.8%
1 67
11.7%
2 64
11.1%
0 57
9.9%
4 53
9.2%
3 52
9.0%
5 44
7.7%
6 44
7.7%
8 40
7.0%
9 37
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 85
14.8%
1 67
11.7%
2 64
11.1%
0 57
9.9%
4 53
9.2%
3 52
9.0%
5 44
7.7%
6 44
7.7%
8 40
7.0%
9 37
6.4%

Interactions

2024-03-23T07:50:08.267825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:06.656370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:07.381710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:08.517313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:06.908372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:07.634281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:08.853622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:07.163513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T07:50:07.909424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T07:50:14.710650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도시도거짓표시 적발실적(개소)미표시 적발실적(개소)
년도1.0000.0000.1270.000
시도0.0001.0000.7150.819
거짓표시 적발실적(개소)0.1270.7151.0000.872
미표시 적발실적(개소)0.0000.8190.8721.000
2024-03-23T07:50:14.973563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
년도거짓표시 적발실적(개소)미표시 적발실적(개소)시도
년도1.000-0.306-0.0080.000
거짓표시 적발실적(개소)-0.3061.0000.8090.290
미표시 적발실적(개소)-0.0080.8091.0000.395
시도0.0000.2900.3951.000

Missing values

2024-03-23T07:50:09.130639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/