Overview

Dataset statistics

Number of variables3
Number of observations617
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.4 KiB
Average record size in memory27.2 B

Variable types

Numeric3

Dataset

Description- 제주특별자치도에 위치한 일반, 휴게 음식점의 사업장명, 인허가일자, 영업상태, 소재지주소 등의 정보를 제공합니다. - 원본 파일의 좌표가 중부원점 TM(EPSH:2097) 좌표계를 따르고 있는데 위경도(WGS84) 좌표계로 변환 시 정확하게 변환이 되지 않아 파일에서 좌표 정보는 제외하였습니다. 데이터 제공 사이트로 가시면 원본 좌표를 확인하실 수 있습니다. - 인포그래픽을 제공함에 따라 인허가일에 따른 영업 및 폐업 음식점 수 파일도 함께 제공합니다. - 데이터 제공처: LOCALDATA
Author제주데이터허브
URLhttps://www.jejudatahub.net/data/view/data/780

Alerts

인허가연월 is highly overall correlated with 영업 and 1 other fieldsHigh correlation
영업 is highly overall correlated with 인허가연월 and 1 other fieldsHigh correlation
폐업 is highly overall correlated with 인허가연월 and 1 other fieldsHigh correlation
인허가연월 has unique valuesUnique
영업 has 66 (10.7%) zerosZeros
폐업 has 18 (2.9%) zerosZeros

Reproduction

Analysis started2023-12-11 20:01:08.177387
Analysis finished2023-12-11 20:01:09.458467
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

인허가연월
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct617
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean199726.92
Minimum196001
Maximum202309
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T05:01:09.537430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum196001
5-th percentile197106.4
Q1198503
median199801
Q3201011
95-th percentile202102.2
Maximum202309
Range6308
Interquartile range (IQR)2508

Descriptive statistics

Standard deviation1545.6129
Coefficient of variation (CV)0.0077386311
Kurtosis-0.9869374
Mean199726.92
Median Absolute Deviation (MAD)1297
Skewness-0.13820996
Sum1.2323151 × 108
Variance2388919.3
MonotonicityStrictly increasing
2023-12-12T05:01:09.676797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
196001 1
 
0.2%
200611 1
 
0.2%
200604 1
 
0.2%
200605 1
 
0.2%
200606 1
 
0.2%
200607 1
 
0.2%
200608 1
 
0.2%
200609 1
 
0.2%
200610 1
 
0.2%
200612 1
 
0.2%
Other values (607) 607
98.4%
ValueCountFrequency (%)
196001 1
0.2%
196002 1
0.2%
196310 1
0.2%
196401 1
0.2%
196403 1
0.2%
196501 1
0.2%
196509 1
0.2%
196608 1
0.2%
196704 1
0.2%
196710 1
0.2%
ValueCountFrequency (%)
202309 1
0.2%
202308 1
0.2%
202307 1
0.2%
202306 1
0.2%
202305 1
0.2%
202304 1
0.2%
202303 1
0.2%
202302 1
0.2%
202301 1
0.2%
202212 1
0.2%

영업
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct134
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.833063
Minimum0
Maximum202
Zeros66
Zeros (%)10.7%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T05:01:09.789995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median15
Q337
95-th percentile150
Maximum202
Range202
Interquartile range (IQR)35

Descriptive statistics

Standard deviation47.592081
Coefficient of variation (CV)1.4066737
Kurtosis2.3828077
Mean33.833063
Median Absolute Deviation (MAD)14
Skewness1.8256846
Sum20875
Variance2265.0062
MonotonicityNot monotonic
2023-12-12T05:01:09.904104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66
 
10.7%
1 58
 
9.4%
2 37
 
6.0%
3 29
 
4.7%
4 25
 
4.1%
10 14
 
2.3%
28 14
 
2.3%
16 14
 
2.3%
12 12
 
1.9%
13 12
 
1.9%
Other values (124) 336
54.5%
ValueCountFrequency (%)
0 66
10.7%
1 58
9.4%
2 37
6.0%
3 29
4.7%
4 25
 
4.1%
5 10
 
1.6%
6 8
 
1.3%
7 9
 
1.5%
8 8
 
1.3%
9 6
 
1.0%
ValueCountFrequency (%)
202 1
0.2%
201 1
0.2%
196 2
0.3%
194 1
0.2%
191 1
0.2%
186 1
0.2%
185 1
0.2%
182 2
0.3%
178 1
0.2%
177 1
0.2%

폐업
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct122
Distinct (%)19.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43.26094
Minimum0
Maximum135
Zeros18
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2023-12-12T05:01:10.017344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q110
median42
Q368
95-th percentile103
Maximum135
Range135
Interquartile range (IQR)58

Descriptive statistics

Standard deviation34.056222
Coefficient of variation (CV)0.78722798
Kurtosis-0.85780496
Mean43.26094
Median Absolute Deviation (MAD)30
Skewness0.39388357
Sum26692
Variance1159.8263
MonotonicityNot monotonic
2023-12-12T05:01:10.140244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 42
 
6.8%
6 20
 
3.2%
0 18
 
2.9%
3 13
 
2.1%
2 13
 
2.1%
4 13
 
2.1%
14 13
 
2.1%
5 12
 
1.9%
10 11
 
1.8%
55 10
 
1.6%
Other values (112) 452
73.3%
ValueCountFrequency (%)
0 18
2.9%
1 42
6.8%
2 13
 
2.1%
3 13
 
2.1%
4 13
 
2.1%
5 12
 
1.9%
6 20
3.2%
7 10
 
1.6%
8 7
 
1.1%
9 6
 
1.0%
ValueCountFrequency (%)
135 2
0.3%
132 1
0.2%
128 1
0.2%
127 1
0.2%
121 2
0.3%
119 1
0.2%
117 1
0.2%
116 2
0.3%
115 1
0.2%
114 2
0.3%

Interactions

2023-12-12T05:01:08.992133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:08.276964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:08.626857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:09.104350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:08.386780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:08.735679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:09.208437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:08.519483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T05:01:08.868915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T05:01:10.227257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가연월영업폐업
인허가연월1.0000.8780.785
영업0.8781.0000.627
폐업0.7850.6271.000
2023-12-12T05:01:10.306082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인허가연월영업폐업
인허가연월1.0000.9570.670
영업0.9571.0000.702
폐업0.6700.7021.000

Missing values

2023-12-12T05:01:09.340281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T05:01:09.425352image/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

인허가연월영업폐업
019600101
119600201
219631001
319640110
419640302
519650101
619650901
719660801
819670410
919671021
인허가연월영업폐업
6072022121509
6082023011303
60920230216311
61020230320124
61120230419411
6122023051826
61320230618216
6142023071509
6152023081776
6162023091746