Overview

Dataset statistics

Number of variables11
Number of observations2240
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory203.6 KiB
Average record size in memory93.1 B

Variable types

Numeric4
Text2
Categorical4
DateTime1

Dataset

Description대전광역시 서구 상권별 업종별 인허가업소 현황(개방서비스ID, 개방서비스명, 데이터기준일자, 상권코드, 상권명, 행정동코드명, 행정동명, 영업상태코드, 영업상태명, 인허가업소수) 데이터를 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15109021/fileData.do

Alerts

데이터생성일자 has constant value ""Constant
영업상태명 is highly overall correlated with 영업상태코드High correlation
영업상태코드 is highly overall correlated with 영업상태명High correlation
상권코드 is highly overall correlated with 상권명 and 1 other fieldsHigh correlation
행정동코드 is highly overall correlated with 상권명 and 1 other fieldsHigh correlation
상권명 is highly overall correlated with 상권코드 and 2 other fieldsHigh correlation
행정동명 is highly overall correlated with 상권코드 and 2 other fieldsHigh correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:24:44.622862
Analysis finished2023-12-12 20:24:47.993728
Duration3.37 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct2240
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1120.5
Minimum1
Maximum2240
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.8 KiB
2023-12-13T05:24:48.109690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile112.95
Q1560.75
median1120.5
Q31680.25
95-th percentile2128.05
Maximum2240
Range2239
Interquartile range (IQR)1119.5

Descriptive statistics

Standard deviation646.77662
Coefficient of variation (CV)0.57722144
Kurtosis-1.2
Mean1120.5
Median Absolute Deviation (MAD)560
Skewness0
Sum2509920
Variance418320
MonotonicityStrictly increasing
2023-12-13T05:24:48.280337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1498 1
 
< 0.1%
1492 1
 
< 0.1%
1493 1
 
< 0.1%
1494 1
 
< 0.1%
1495 1
 
< 0.1%
1496 1
 
< 0.1%
1497 1
 
< 0.1%
1499 1
 
< 0.1%
1490 1
 
< 0.1%
Other values (2230) 2230
99.6%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
2240 1
< 0.1%
2239 1
< 0.1%
2238 1
< 0.1%
2237 1
< 0.1%
2236 1
< 0.1%
2235 1
< 0.1%
2234 1
< 0.1%
2233 1
< 0.1%
2232 1
< 0.1%
2231 1
< 0.1%

개방서비스아이디
Text

Distinct111
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size17.6 KiB
2023-12-13T05:24:48.652130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters22400
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)0.5%

Sample

1st row02_03_01_P
2nd row10_32_01_P
3rd row01_01_06_P
4th row05_18_01_P
5th row01_01_06_P
ValueCountFrequency (%)
08_26_04_p 97
 
4.3%
11_43_02_p 66
 
2.9%
08_26_02_p 61
 
2.7%
08_26_03_p 57
 
2.5%
07_22_03_p 52
 
2.3%
01_02_03_p 51
 
2.3%
07_24_04_p 49
 
2.2%
03_05_05_p 49
 
2.2%
09_30_12_p 46
 
2.1%
01_01_02_p 46
 
2.1%
Other values (101) 1666
74.4%
2023-12-13T05:24:49.217285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
_ 6720
30.0%
0 4930
22.0%
1 2325
 
10.4%
P 2240
 
10.0%
2 2029
 
9.1%
3 1102
 
4.9%
7 690
 
3.1%
4 682
 
3.0%
5 522
 
2.3%
8 436
 
1.9%
Other values (2) 724
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 13440
60.0%
Connector Punctuation 6720
30.0%
Uppercase Letter 2240
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4930
36.7%
1 2325
17.3%
2 2029
15.1%
3 1102
 
8.2%
7 690
 
5.1%
4 682
 
5.1%
5 522
 
3.9%
8 436
 
3.2%
6 410
 
3.1%
9 314
 
2.3%
Connector Punctuation
ValueCountFrequency (%)
_ 6720
100.0%
Uppercase Letter
ValueCountFrequency (%)
P 2240
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20160
90.0%
Latin 2240
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 6720
33.3%
0 4930
24.5%
1 2325
 
11.5%
2 2029
 
10.1%
3 1102
 
5.5%
7 690
 
3.4%
4 682
 
3.4%
5 522
 
2.6%
8 436
 
2.2%
6 410
 
2.0%
Latin
ValueCountFrequency (%)
P 2240
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 22400
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 6720
30.0%
0 4930
22.0%
1 2325
 
10.4%
P 2240
 
10.0%
2 2029
 
9.1%
3 1102
 
4.9%
7 690
 
3.1%
4 682
 
3.0%
5 522
 
2.3%
8 436
 
1.9%
Other values (2) 724
 
3.2%

개방서비스명
Text

Distinct111
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size17.6 KiB
2023-12-13T05:24:49.604822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length6.2580357
Min length2

Characters and Unicode

Total characters14018
Distinct characters160
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)0.5%

Sample

1st row동물병원
2nd row당구장업
3rd row약국
4th row미용업
5th row약국
ValueCountFrequency (%)
통신판매업 97
 
4.3%
담배소매업 66
 
2.9%
방문판매업 61
 
2.7%
전화권유판매업 57
 
2.5%
건강기능식품일반판매업 52
 
2.3%
의료기기판매(임대)업 51
 
2.2%
일반음식점 49
 
2.1%
인터넷컴퓨터게임시설제공업 49
 
2.1%
수질오염원설치시설(기타 46
 
2.0%
의원 46
 
2.0%
Other values (102) 1706
74.8%
2023-12-13T05:24:50.123557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 1779
 
12.7%
매 678
 
4.8%
판 643
 
4.6%
식 371
 
2.6%
기 362
 
2.6%
소 330
 
2.4%
제 321
 
2.3%
물 255
 
1.8%
품 247
 
1.8%
공 237
 
1.7%
Other values (150) 8795
62.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 13714
97.8%
Close Punctuation 126
 
0.9%
Open Punctuation 126
 
0.9%
Space Separator 40
 
0.3%
Other Punctuation 12
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1779
 
13.0%
매 678
 
4.9%
판 643
 
4.7%
식 371
 
2.7%
기 362
 
2.6%
소 330
 
2.4%
제 321
 
2.3%
물 255
 
1.9%
품 247
 
1.8%
공 237
 
1.7%
Other values (146) 8491
61.9%
Close Punctuation
ValueCountFrequency (%)
) 126
100.0%
Open Punctuation
ValueCountFrequency (%)
( 126
100.0%
Space Separator
ValueCountFrequency (%)
40
100.0%
Other Punctuation
ValueCountFrequency (%)
. 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 13714
97.8%
Common 304
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1779
 
13.0%
매 678
 
4.9%
판 643
 
4.7%
식 371
 
2.7%
기 362
 
2.6%
소 330
 
2.4%
제 321
 
2.3%
물 255
 
1.9%
품 247
 
1.8%
공 237
 
1.7%
Other values (146) 8491
61.9%
Common
ValueCountFrequency (%)
) 126
41.4%
( 126
41.4%
40
 
13.2%
. 12
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 13714
97.8%
ASCII 304
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 1779
 
13.0%
매 678
 
4.9%
판 643
 
4.7%
식 371
 
2.7%
기 362
 
2.6%
소 330
 
2.4%
제 321
 
2.3%
물 255
 
1.9%
품 247
 
1.8%
공 237
 
1.7%
Other values (146) 8491
61.9%
ASCII
ValueCountFrequency (%)
) 126
41.4%
( 126
41.4%
40
 
13.2%
. 12
 
3.9%

상권코드
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.3290179
Minimum1
Maximum14
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.8 KiB
2023-12-13T05:24:50.297218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1.95
Q14
median7
Q311
95-th percentile14
Maximum14
Range13
Interquartile range (IQR)7

Descriptive statistics

Standard deviation4.1217792
Coefficient of variation (CV)0.56239175
Kurtosis-1.3863341
Mean7.3290179
Median Absolute Deviation (MAD)4
Skewness0.1164353
Sum16417
Variance16.989064
MonotonicityNot monotonic
2023-12-13T05:24:50.453192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
3 261
11.7%
12 223
10.0%
5 218
9.7%
13 187
8.3%
2 186
8.3%
4 183
8.2%
9 163
 
7.3%
11 142
 
6.3%
14 131
 
5.8%
6 119
 
5.3%
Other values (4) 427
19.1%
ValueCountFrequency (%)
1 112
5.0%
2 186
8.3%
3 261
11.7%
4 183
8.2%
5 218
9.7%
6 119
5.3%
7 108
4.8%
8 91
 
4.1%
9 163
7.3%
10 116
5.2%
ValueCountFrequency (%)
14 131
5.8%
13 187
8.3%
12 223
10.0%
11 142
6.3%
10 116
5.2%
9 163
7.3%
8 91
4.1%
7 108
4.8%
6 119
5.3%
5 218
9.7%

상권명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size17.6 KiB
롯데백화점 주변 상권
261 
세이디에스탄방점 주변 상권
223 
이마트 둔산점 주변 상권
218 
대전시청역 주변 상권
187 
한민시장 주변 상권
186 
Other values (9)
1165 

Length

Max length23
Median length19
Mean length13.175446
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row한민시장 주변 상권
2nd row한민시장 주변 상권
3rd row도마큰시장 주변 상권
4th row대주프라자 주변 상권
5th row롯데백화점 주변 상권

Common Values

ValueCountFrequency (%)
롯데백화점 주변 상권 261
11.7%
세이디에스탄방점 주변 상권 223
10.0%
이마트 둔산점 주변 상권 218
9.7%
대전시청역 주변 상권 187
8.3%
한민시장 주변 상권 186
8.3%
갤러리아백화점 주변 상권 183
8.2%
둔산3동상점가 주변 상권 163
 
7.3%
이마트 트레이더스 월평점 주변 상권 142
 
6.3%
서구 보건소 주변 상권 131
 
5.8%
사학연금회관 뒤편(토요코인호텔) 주변 상권 119
 
5.3%
Other values (4) 427
19.1%

Length

2023-12-13T05:24:50.609232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
상권 2240
30.0%
주변 2240
30.0%
이마트 360
 
4.8%
롯데백화점 261
 
3.5%
세이디에스탄방점 223
 
3.0%
둔산점 218
 
2.9%
대전시청역 187
 
2.5%
한민시장 186
 
2.5%
갤러리아백화점 183
 
2.4%
둔산3동상점가 163
 
2.2%
Other values (10) 1211
16.2%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170593 × 109
Minimum3.017051 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.8 KiB
2023-12-13T05:24:50.742841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017051 × 109
5-th percentile3.017052 × 109
Q13.017056 × 109
median3.017059 × 109
Q33.017063 × 109
95-th percentile3.017065 × 109
Maximum3.017066 × 109
Range15000
Interquartile range (IQR)7000

Descriptive statistics

Standard deviation3642.9189
Coefficient of variation (CV)1.2074403 × 10-6
Kurtosis-1.1128469
Mean3.0170593 × 109
Median Absolute Deviation (MAD)3500
Skewness-0.15304361
Sum6.7582129 × 1012
Variance13270858
MonotonicityNot monotonic
2023-12-13T05:24:50.881191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
3017063000 731
32.6%
3017055500 322
14.4%
3017058600 224
 
10.0%
3017056000 212
 
9.5%
3017059600 202
 
9.0%
3017065000 123
 
5.5%
3017059000 116
 
5.2%
3017052000 115
 
5.1%
3017057000 74
 
3.3%
3017055000 63
 
2.8%
Other values (8) 58
 
2.6%
ValueCountFrequency (%)
3017051000 1
 
< 0.1%
3017052000 115
 
5.1%
3017053500 3
 
0.1%
3017054000 8
 
0.4%
3017055000 63
 
2.8%
3017055500 322
14.4%
3017056000 212
9.5%
3017057000 74
 
3.3%
3017057500 21
 
0.9%
3017058100 12
 
0.5%
ValueCountFrequency (%)
3017066000 9
 
0.4%
3017065000 123
 
5.5%
3017064000 2
 
0.1%
3017063000 731
32.6%
3017059600 202
 
9.0%
3017059000 116
 
5.2%
3017058800 2
 
0.1%
3017058600 224
 
10.0%
3017058100 12
 
0.5%
3017057500 21
 
0.9%

행정동명
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size17.6 KiB
둔산1동
731 
탄방동
322 
월평1동
224 
괴정동
212 
관저1동
202 
Other values (13)
549 

Length

Max length4
Median length4
Mean length3.6178571
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row괴정동
2nd row괴정동
3rd row도마1동
4th row관저1동
5th row탄방동

Common Values

ValueCountFrequency (%)
둔산1동 731
32.6%
탄방동 322
14.4%
월평1동 224
 
10.0%
괴정동 212
 
9.5%
관저1동 202
 
9.0%
만년동 123
 
5.5%
가수원동 116
 
5.2%
도마1동 115
 
5.1%
가장동 74
 
3.3%
용문동 63
 
2.8%
Other values (8) 58
 
2.6%

Length

2023-12-13T05:24:51.060285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
둔산1동 731
32.6%
탄방동 322
14.4%
월평1동 224
 
10.0%
괴정동 212
 
9.5%
관저1동 202
 
9.0%
만년동 123
 
5.5%
가수원동 116
 
5.2%
도마1동 115
 
5.1%
가장동 74
 
3.3%
용문동 63
 
2.8%
Other values (8) 58
 
2.6%

영업상태코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.6 KiB
1
1014 
3
986 
4
215 
2
 
25

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 1014
45.3%
3 986
44.0%
4 215
 
9.6%
2 25
 
1.1%

Length

2023-12-13T05:24:51.226974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:51.368980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 1014
45.3%
3 986
44.0%
4 215
 
9.6%
2 25
 
1.1%

영업상태명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size17.6 KiB
영업/정상
1014 
폐업
986 
취소/말소/만료/정지/중지
215 
휴업
 
25

Length

Max length14
Median length5
Mean length4.5098214
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row폐업
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
영업/정상 1014
45.3%
폐업 986
44.0%
취소/말소/만료/정지/중지 215
 
9.6%
휴업 25
 
1.1%

Length

2023-12-13T05:24:51.514859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:24:51.640455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 1014
45.3%
폐업 986
44.0%
취소/말소/만료/정지/중지 215
 
9.6%
휴업 25
 
1.1%

인허가업소수
Real number (ℝ)

Distinct120
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.80625
Minimum1
Maximum1168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size19.8 KiB
2023-12-13T05:24:51.793800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q36
95-th percentile48
Maximum1168
Range1167
Interquartile range (IQR)5

Descriptive statistics

Standard deviation45.756223
Coefficient of variation (CV)3.8755933
Kurtosis259.36569
Mean11.80625
Median Absolute Deviation (MAD)1
Skewness13.4794
Sum26446
Variance2093.6319
MonotonicityNot monotonic
2023-12-13T05:24:51.970637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 816
36.4%
2 372
16.6%
3 197
 
8.8%
4 133
 
5.9%
5 90
 
4.0%
6 78
 
3.5%
7 61
 
2.7%
8 43
 
1.9%
10 35
 
1.6%
9 32
 
1.4%
Other values (110) 383
17.1%
ValueCountFrequency (%)
1 816
36.4%
2 372
16.6%
3 197
 
8.8%
4 133
 
5.9%
5 90
 
4.0%
6 78
 
3.5%
7 61
 
2.7%
8 43
 
1.9%
9 32
 
1.4%
10 35
 
1.6%
ValueCountFrequency (%)
1168 1
< 0.1%
781 1
< 0.1%
726 1
< 0.1%
492 1
< 0.1%
450 1
< 0.1%
396 1
< 0.1%
330 1
< 0.1%
294 1
< 0.1%
273 1
< 0.1%
262 1
< 0.1%

데이터생성일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size17.6 KiB
Minimum2022-11-15 00:00:00
Maximum2022-11-15 00:00:00
2023-12-13T05:24:52.103934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:52.206096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T05:24:47.012519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:45.401558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:45.922706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:46.469713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:47.147482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:45.525659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:46.057091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:46.617175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:47.302689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:45.651289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:46.190092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:46.738626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:47.438978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:45.806662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:46.325838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T05:24:46.881450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:24:52.283490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상권코드상권명행정동코드행정동명영업상태코드영업상태명인허가업소수
순번1.0000.1050.0710.0000.0000.0730.0730.000
상권코드0.1051.0001.0000.7810.8970.0000.0000.000
상권명0.0711.0001.0000.8920.9280.0000.0000.000
행정동코드0.0000.7810.8921.0001.0000.0000.0000.000
행정동명0.0000.8970.9281.0001.0000.0820.0820.000
영업상태코드0.0730.0000.0000.0000.0821.0001.0000.000
영업상태명0.0730.0000.0000.0000.0821.0001.0000.000
인허가업소수0.0000.0000.0000.0000.0000.0000.0001.000
2023-12-13T05:24:52.406545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명영업상태코드상권명행정동명
영업상태명1.0001.0000.0000.045
영업상태코드1.0001.0000.0000.045
상권명0.0000.0001.0000.656
행정동명0.0450.0450.6561.000
2023-12-13T05:24:52.496663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상권코드행정동코드인허가업소수상권명행정동명영업상태코드영업상태명
순번1.000-0.010-0.0370.0210.0280.0000.0440.044
상권코드-0.0101.0000.2300.0340.9990.6290.0000.000
행정동코드-0.0370.2301.0000.0650.6580.9980.0000.000
인허가업소수0.0210.0340.0651.0000.0000.0000.0000.000
상권명0.0280.9990.6580.0001.0000.6560.0000.000
행정동명0.0000.6290.9980.0000.6561.0000.0450.045
영업상태코드0.0440.0000.0000.0000.0000.0451.0001.000
영업상태명0.0440.0000.0000.0000.0000.0451.0001.000

Missing values

2023-12-13T05:24:47.652593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:24:47.896764image/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

순번개방서비스아이디개방서비스명상권코드상권명행정동코드행정동명영업상태코드영업상태명인허가업소수데이터생성일자
0102_03_01_P동물병원2한민시장 주변 상권3017056000괴정동1영업/정상12022-11-15
1210_32_01_P당구장업2한민시장 주변 상권3017056000괴정동3폐업42022-11-15
2301_01_06_P약국10도마큰시장 주변 상권3017052000도마1동3폐업42022-11-15
3405_18_01_P미용업7대주프라자 주변 상권3017059600관저1동3폐업252022-11-15
4501_01_06_P약국3롯데백화점 주변 상권3017055500탄방동3폐업72022-11-15
5601_02_03_P의료기기판매(임대)업8마치광장골목형상점가 주변 상권3017059600관저1동1영업/정상72022-11-15
6703_12_02_P국내외여행업2한민시장 주변 상권3017056000괴정동3폐업12022-11-15
7803_05_05_P인터넷컴퓨터게임시설제공업8마치광장골목형상점가 주변 상권3017059600관저1동3폐업22022-11-15
8908_26_03_P전화권유판매업5이마트 둔산점 주변 상권3017059600관저1동3폐업12022-11-15
91007_22_10_P식품자동판매기업13대전시청역 주변 상권3017063000둔산1동3폐업232022-11-15
순번개방서비스아이디개방서비스명상권코드상권명행정동코드행정동명영업상태코드영업상태명인허가업소수데이터생성일자
2230223106_20_01_P세탁업12세이디에스탄방점 주변 상권3017055500탄방동1영업/정상12022-11-15
2231223207_22_03_P건강기능식품일반판매업5이마트 둔산점 주변 상권3017063000둔산1동1영업/정상252022-11-15
2232223304_16_01_P인쇄사10도마큰시장 주변 상권3017052000도마1동1영업/정상22022-11-15
2233223403_10_02_P비디오물배급업13대전시청역 주변 상권3017063000둔산1동1영업/정상12022-11-15
2234223509_30_04_P건물위생관리업14서구 보건소 주변 상권3017065000만년동3폐업122022-11-15
2235223607_24_05_P휴게음식점9둔산3동상점가 주변 상권3017063000둔산1동1영업/정상132022-11-15
2236223707_24_05_P휴게음식점4갤러리아백화점 주변 상권3017063000둔산1동3폐업2542022-11-15
2237223806_20_01_P세탁업13대전시청역 주변 상권3017063000둔산1동1영업/정상12022-11-15
2238223907_24_05_P휴게음식점9둔산3동상점가 주변 상권3017055500탄방동1영업/정상72022-11-15
2239224002_03_06_P동물생산업5이마트 둔산점 주변 상권3017063000둔산1동4취소/말소/만료/정지/중지142022-11-15