Overview

Dataset statistics

Number of variables6
Number of observations367
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory18.0 KiB
Average record size in memory50.4 B

Variable types

Numeric2
Categorical2
Text2

Dataset

Description인천광역시 구별 거리가게 현황에 관한 데이터로 시군구, 유형, 도로명주소, 우편번호, 지번주소의 항목을 제공하겠음.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15048909&srcSe=7661IVAWM27C61E190

Alerts

순번 is highly overall correlated with 구High correlation
우편번호 is highly overall correlated with 구High correlation
구 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique

Reproduction

Analysis started2024-01-28 17:15:08.400680
Analysis finished2024-01-28 17:15:09.130631
Duration0.73 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct367
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean184
Minimum1
Maximum367
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-01-29T02:15:09.450219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.3
Q192.5
median184
Q3275.5
95-th percentile348.7
Maximum367
Range366
Interquartile range (IQR)183

Descriptive statistics

Standard deviation106.08801
Coefficient of variation (CV)0.57656529
Kurtosis-1.2
Mean184
Median Absolute Deviation (MAD)92
Skewness0
Sum67528
Variance11254.667
MonotonicityStrictly increasing
2024-01-29T02:15:09.561682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
243 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
248 1
 
0.3%
247 1
 
0.3%
246 1
 
0.3%
245 1
 
0.3%
Other values (357) 357
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%
363 1
0.3%
362 1
0.3%
361 1
0.3%
360 1
0.3%
359 1
0.3%
358 1
0.3%

구
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
남동구
115 
부평구
76 
미추홀구
55 
중구
50 
연수구
29 
Other values (3)
42 

Length

Max length4
Median length3
Mean length2.9427793
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 115
31.3%
부평구 76
20.7%
미추홀구 55
15.0%
중구 50
13.6%
연수구 29
 
7.9%
서구 25
 
6.8%
계양구 16
 
4.4%
동구 1
 
0.3%

Length

2024-01-29T02:15:09.674951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:15:09.769018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 115
31.3%
부평구 76
20.7%
미추홀구 55
15.0%
중구 50
13.6%
연수구 29
 
7.9%
서구 25
 
6.8%
계양구 16
 
4.4%
동구 1
 
0.3%

유형
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
가로판매대
200 
구두수선대
167 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가로판매대 200
54.5%
구두수선대 167
45.5%

Length

2024-01-29T02:15:09.870232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-29T02:15:09.974153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가로판매대 200
54.5%
구두수선대 167
45.5%

도로명주소
Text

Distinct366
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-01-29T02:15:10.193731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length28
Mean length25.53951
Min length21

Characters and Unicode

Total characters9373
Distinct characters161
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

Unique365 ?
Unique (%)99.5%

Sample

1st row인천광역시 계양구 봉오대로 791-2 (작전동)
2nd row인천광역시 계양구 계양대로 53-2 (작전동)
3rd row인천광역시 계양구 계양대로 82-2 (작전동)
4th row인천광역시 계양구 계양대로 85-2 (작전동)
5th row인천광역시 계양구 계양대로 161-2 (계산동)
ValueCountFrequency (%)
인천광역시 367
 
20.0%
남동구 115
 
6.3%
부평구 76
 
4.1%
논현동 60
 
3.3%
미추홀구 55
 
3.0%
중구 50
 
2.7%
부평동 42
 
2.3%
아암대로 35
 
1.9%
주안동 32
 
1.7%
연수구 29
 
1.6%
Other values (485) 974
53.1%
2024-01-29T02:15:10.642797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1468
 
15.7%
동 503
 
5.4%
인 418
 
4.5%
구 399
 
4.3%
1 396
 
4.2%
역 379
 
4.0%
천 373
 
4.0%
시 372
 
4.0%
광 370
 
3.9%
( 367
 
3.9%
Other values (151) 4328
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5414
57.8%
Space Separator 1468
 
15.7%
Decimal Number 1420
 
15.1%
Open Punctuation 367
 
3.9%
Close Punctuation 367
 
3.9%
Dash Punctuation 337
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 503
 
9.3%
인 418
 
7.7%
구 399
 
7.4%
역 379
 
7.0%
천 373
 
6.9%
시 372
 
6.9%
광 370
 
6.8%
로 366
 
6.8%
부 159
 
2.9%
평 141
 
2.6%
Other values (137) 1934
35.7%
Decimal Number
ValueCountFrequency (%)
1 396
27.9%
2 235
16.5%
3 175
12.3%
4 125
 
8.8%
6 119
 
8.4%
5 88
 
6.2%
0 79
 
5.6%
8 74
 
5.2%
7 72
 
5.1%
9 57
 
4.0%
Space Separator
ValueCountFrequency (%)
1468
100.0%
Open Punctuation
ValueCountFrequency (%)
( 367
100.0%
Close Punctuation
ValueCountFrequency (%)
) 367
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 337
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5414
57.8%
Common 3959
42.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 503
 
9.3%
인 418
 
7.7%
구 399
 
7.4%
역 379
 
7.0%
천 373
 
6.9%
시 372
 
6.9%
광 370
 
6.8%
로 366
 
6.8%
부 159
 
2.9%
평 141
 
2.6%
Other values (137) 1934
35.7%
Common
ValueCountFrequency (%)
1468
37.1%
1 396
 
10.0%
( 367
 
9.3%
) 367
 
9.3%
- 337
 
8.5%
2 235
 
5.9%
3 175
 
4.4%
4 125
 
3.2%
6 119
 
3.0%
5 88
 
2.2%
Other values (4) 282
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5414
57.8%
ASCII 3959
42.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1468
37.1%
1 396
 
10.0%
( 367
 
9.3%
) 367
 
9.3%
- 337
 
8.5%
2 235
 
5.9%
3 175
 
4.4%
4 125
 
3.2%
6 119
 
3.0%
5 88
 
2.2%
Other values (4) 282
 
7.1%
Hangul
ValueCountFrequency (%)
동 503
 
9.3%
인 418
 
7.7%
구 399
 
7.4%
역 379
 
7.0%
천 373
 
6.9%
시 372
 
6.9%
광 370
 
6.8%
로 366
 
6.8%
부 159
 
2.9%
평 141
 
2.6%
Other values (137) 1934
35.7%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct211
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21829.837
Minimum21013
Maximum22832
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-01-29T02:15:10.775078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21013
5-th percentile21311.9
Q121480.5
median21673
Q322202
95-th percentile22778
Maximum22832
Range1819
Interquartile range (IQR)721.5

Descriptive statistics

Standard deviation444.18222
Coefficient of variation (CV)0.020347483
Kurtosis-0.64035799
Mean21829.837
Median Absolute Deviation (MAD)284
Skewness0.45735644
Sum8011550
Variance197297.85
MonotonicityNot monotonic
2024-01-29T02:15:10.903103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21672 20
 
5.4%
21673 19
 
5.2%
22322 13
 
3.5%
21674 13
 
3.5%
21404 9
 
2.5%
21394 8
 
2.2%
21389 6
 
1.6%
21393 5
 
1.4%
22348 5
 
1.4%
22316 4
 
1.1%
Other values (201) 265
72.2%
ValueCountFrequency (%)
21013 1
0.3%
21027 1
0.3%
21034 1
0.3%
21039 1
0.3%
21047 1
0.3%
21049 1
0.3%
21054 1
0.3%
21056 1
0.3%
21057 1
0.3%
21060 1
0.3%
ValueCountFrequency (%)
22832 1
0.3%
22818 1
0.3%
22817 1
0.3%
22814 2
0.5%
22811 1
0.3%
22810 1
0.3%
22809 1
0.3%
22807 1
0.3%
22800 1
0.3%
22795 1
0.3%

지번주소
Text

Distinct219
Distinct (%)59.7%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-01-29T02:15:11.144227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length18.697548
Min length14

Characters and Unicode

Total characters6862
Distinct characters87
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

Unique173 ?
Unique (%)47.1%

Sample

1st row인천광역시 계양구 작전동 941
2nd row인천광역시 계양구 작전동 878
3rd row인천광역시 계양구 작전동 878
4th row인천광역시 계양구 작전동 878
5th row인천광역시 계양구 계산동 1034
ValueCountFrequency (%)
인천광역시 367
24.8%
남동구 115
 
7.8%
부평구 76
 
5.1%
논현동 60
 
4.1%
미추홀구 55
 
3.7%
중구 50
 
3.4%
부평동 42
 
2.8%
126-10 35
 
2.4%
주안동 32
 
2.2%
연수구 29
 
2.0%
Other values (274) 617
41.7%
2024-01-29T02:15:11.555230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1111
16.2%
동 492
 
7.2%
구 388
 
5.7%
인 372
 
5.4%
천 372
 
5.4%
시 367
 
5.3%
역 367
 
5.3%
광 367
 
5.3%
1 352
 
5.1%
- 227
 
3.3%
Other values (77) 2447
35.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4025
58.7%
Decimal Number 1489
 
21.7%
Space Separator 1111
 
16.2%
Dash Punctuation 227
 
3.3%
Other Punctuation 10
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 492
12.2%
구 388
9.6%
인 372
 
9.2%
천 372
 
9.2%
시 367
 
9.1%
역 367
 
9.1%
광 367
 
9.1%
부 125
 
3.1%
남 121
 
3.0%
평 119
 
3.0%
Other values (64) 935
23.2%
Decimal Number
ValueCountFrequency (%)
1 352
23.6%
2 183
12.3%
3 150
10.1%
7 133
 
8.9%
6 129
 
8.7%
0 127
 
8.5%
5 107
 
7.2%
4 105
 
7.1%
9 103
 
6.9%
8 100
 
6.7%
Space Separator
ValueCountFrequency (%)
1111
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 227
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4025
58.7%
Common 2837
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 492
12.2%
구 388
9.6%
인 372
 
9.2%
천 372
 
9.2%
시 367
 
9.1%
역 367
 
9.1%
광 367
 
9.1%
부 125
 
3.1%
남 121
 
3.0%
평 119
 
3.0%
Other values (64) 935
23.2%
Common
ValueCountFrequency (%)
1111
39.2%
1 352
 
12.4%
- 227
 
8.0%
2 183
 
6.5%
3 150
 
5.3%
7 133
 
4.7%
6 129
 
4.5%
0 127
 
4.5%
5 107
 
3.8%
4 105
 
3.7%
Other values (3) 213
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4025
58.7%
ASCII 2837
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1111
39.2%
1 352
 
12.4%
- 227
 
8.0%
2 183
 
6.5%
3 150
 
5.3%
7 133
 
4.7%
6 129
 
4.5%
0 127
 
4.5%
5 107
 
3.8%
4 105
 
3.7%
Other values (3) 213
 
7.5%
Hangul
ValueCountFrequency (%)
동 492
12.2%
구 388
9.6%
인 372
 
9.2%
천 372
 
9.2%
시 367
 
9.1%
역 367
 
9.1%
광 367
 
9.1%
부 125
 
3.1%
남 121
 
3.0%
평 119
 
3.0%
Other values (64) 935
23.2%

Interactions

2024-01-29T02:15:08.842578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:15:08.675964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:15:08.918197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-29T02:15:08.762039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-29T02:15:11.632927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구유형우편번호
순번1.0000.9140.4800.956
구0.9141.0000.5470.974
유형0.4800.5471.0000.569
우편번호0.9560.9740.5691.000
2024-01-29T02:15:11.710990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구유형
구1.0000.410
유형0.4101.000
2024-01-29T02:15:11.786994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호구유형
순번1.0000.4880.7540.365
우편번호0.4881.0000.9150.437
구0.7540.9151.0000.410
유형0.3650.4370.4101.000

Missing values

2024-01-29T02:15:09.018664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-29T02:15:09.097894image/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

순번구유형도로명주소우편번호지번주소
01계양구구두수선대인천광역시 계양구 봉오대로 791-2 (작전동)21080인천광역시 계양구 작전동 941
12계양구구두수선대인천광역시 계양구 계양대로 53-2 (작전동)21110인천광역시 계양구 작전동 878
23계양구구두수선대인천광역시 계양구 계양대로 82-2 (작전동)21091인천광역시 계양구 작전동 878
34계양구구두수선대인천광역시 계양구 계양대로 85-2 (작전동)21047인천광역시 계양구 작전동 878
45계양구구두수선대인천광역시 계양구 계양대로 161-2 (계산동)21054인천광역시 계양구 계산동 1034
56계양구구두수선대인천광역시 계양구 계양대로 216-2 (계산동)21049인천광역시 계양구 계산동 1014
67계양구가로판매대인천광역시 계양구 경명대로 1053-2 (계산동)21039인천광역시 계양구 계산동 1014
78계양구구두수선대인천광역시 계양구 경명대로 1142-2 (계산동)21057인천광역시 계양구 계산동 1054
89계양구구두수선대인천광역시 계양구 새벌로 94-2 (효성동)21114인천광역시 계양구 효성동 217
910계양구구두수선대인천광역시 계양구 안남로 472-2 (효성동)21113인천광역시 계양구 효성동 313
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357358중구가로판매대인천광역시 중구 우현로35번길 7-2 (신포동)22322인천광역시 중구 신포동 18-16
358359중구가로판매대인천광역시 중구 우현로35번길 9 (신포동)22322인천광역시 중구 신포동 18-16
359360중구가로판매대인천광역시 중구 우현로35번길 9-1 (신포동)22322인천광역시 중구 신포동 18-16
360361중구가로판매대인천광역시 중구 우현로35번길 9-2 (신포동)22322인천광역시 중구 신포동 18-16
361362중구가로판매대인천광역시 중구 우현로35번길 9-3 (신포동)22322인천광역시 중구 신포동 18-16
362363중구가로판매대인천광역시 중구 우현로35번길 9-4 (신포동)22322인천광역시 중구 신포동 18-16
363364중구구두수선대인천광역시 중구 우현로67번길 1-2 (내동)22316인천광역시 중구 내동 188-2
364365중구구두수선대인천광역시 중구 인중로182번길 8 (사동)22313인천광역시 중구 사동 26-19
365366중구구두수선대인천광역시 중구 제물량로166번길 1-5 (신생동)22322인천광역시 중구 신생동 11-53, 2-44
366367중구구두수선대인천광역시 중구 축항대로86번길 34-1 (항동7가)22348인천광역시 중구 항동7가 58-2