Overview

Dataset statistics

Number of variables6
Number of observations344
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory16.9 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://www.data.go.kr/data/15048909/fileData.do

Alerts

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

Reproduction

Analysis started2024-03-14 21:03:25.080107
Analysis finished2024-03-14 21:03:26.690712
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct344
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean172.5
Minimum1
Maximum344
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-15T06:03:26.838373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile18.15
Q186.75
median172.5
Q3258.25
95-th percentile326.85
Maximum344
Range343
Interquartile range (IQR)171.5

Descriptive statistics

Standard deviation99.448479
Coefficient of variation (CV)0.57651292
Kurtosis-1.2
Mean172.5
Median Absolute Deviation (MAD)86
Skewness0
Sum59340
Variance9890
MonotonicityStrictly increasing
2024-03-15T06:03:27.283879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
228 1
 
0.3%
236 1
 
0.3%
235 1
 
0.3%
234 1
 
0.3%
233 1
 
0.3%
232 1
 
0.3%
231 1
 
0.3%
230 1
 
0.3%
229 1
 
0.3%
Other values (334) 334
97.1%
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 (%)
344 1
0.3%
343 1
0.3%
342 1
0.3%
341 1
0.3%
340 1
0.3%
339 1
0.3%
338 1
0.3%
337 1
0.3%
336 1
0.3%
335 1
0.3%

구
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
남동구
114 
부평구
73 
미추홀구
53 
중구
34 
연수구
29 
Other values (3)
41 

Length

Max length4
Median length3
Mean length2.9796512
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
남동구 114
33.1%
부평구 73
21.2%
미추홀구 53
15.4%
중구 34
 
9.9%
연수구 29
 
8.4%
서구 25
 
7.3%
계양구 15
 
4.4%
동구 1
 
0.3%

Length

2024-03-15T06:03:27.551842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:03:27.836221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남동구 114
33.1%
부평구 73
21.2%
미추홀구 53
15.4%
중구 34
 
9.9%
연수구 29
 
8.4%
서구 25
 
7.3%
계양구 15
 
4.4%
동구 1
 
0.3%

유형
Categorical

Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
가로판매대
179 
구두수선대
165 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
가로판매대 179
52.0%
구두수선대 165
48.0%

Length

2024-03-15T06:03:28.330205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:03:28.670919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가로판매대 179
52.0%
구두수선대 165
48.0%

도로명주소
Text

UNIQUE 

Distinct344
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-03-15T06:03:30.392499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length25.581395
Min length21

Characters and Unicode

Total characters8800
Distinct characters159
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

Unique344 ?
Unique (%)100.0%

Sample

1st row인천광역시 중구 우현로67번길 1-2 (내동)
2nd row인천광역시 중구 우현로 53-1 (내동)
3rd row인천광역시 중구 제물량로 142 (답동)
4th row인천광역시 중구 참외전로 248 (도원동)
5th row인천광역시 중구 월미로 312 (북성동1가)
ValueCountFrequency (%)
인천광역시 344
 
20.0%
남동구 114
 
6.6%
부평구 73
 
4.2%
논현동 60
 
3.5%
미추홀구 53
 
3.1%
부평동 40
 
2.3%
아암대로 35
 
2.0%
중구 34
 
2.0%
주안동 31
 
1.8%
연수구 29
 
1.7%
Other values (459) 907
52.7%
2024-03-15T06:03:32.332713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1376
 
15.6%
동 479
 
5.4%
인 393
 
4.5%
1 380
 
4.3%
구 376
 
4.3%
역 356
 
4.0%
천 350
 
4.0%
광 347
 
3.9%
시 347
 
3.9%
) 344
 
3.9%
Other values (149) 4052
46.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5081
57.7%
Space Separator 1376
 
15.6%
Decimal Number 1334
 
15.2%
Close Punctuation 344
 
3.9%
Open Punctuation 344
 
3.9%
Dash Punctuation 321
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 479
 
9.4%
인 393
 
7.7%
구 376
 
7.4%
역 356
 
7.0%
천 350
 
6.9%
광 347
 
6.8%
시 347
 
6.8%
로 343
 
6.8%
부 154
 
3.0%
남 138
 
2.7%
Other values (135) 1798
35.4%
Decimal Number
ValueCountFrequency (%)
1 380
28.5%
2 222
16.6%
3 158
11.8%
4 117
 
8.8%
6 113
 
8.5%
0 78
 
5.8%
5 76
 
5.7%
8 72
 
5.4%
7 67
 
5.0%
9 51
 
3.8%
Space Separator
ValueCountFrequency (%)
1376
100.0%
Close Punctuation
ValueCountFrequency (%)
) 344
100.0%
Open Punctuation
ValueCountFrequency (%)
( 344
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 321
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5081
57.7%
Common 3719
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 479
 
9.4%
인 393
 
7.7%
구 376
 
7.4%
역 356
 
7.0%
천 350
 
6.9%
광 347
 
6.8%
시 347
 
6.8%
로 343
 
6.8%
부 154
 
3.0%
남 138
 
2.7%
Other values (135) 1798
35.4%
Common
ValueCountFrequency (%)
1376
37.0%
1 380
 
10.2%
) 344
 
9.2%
( 344
 
9.2%
- 321
 
8.6%
2 222
 
6.0%
3 158
 
4.2%
4 117
 
3.1%
6 113
 
3.0%
0 78
 
2.1%
Other values (4) 266
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5081
57.7%
ASCII 3719
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1376
37.0%
1 380
 
10.2%
) 344
 
9.2%
( 344
 
9.2%
- 321
 
8.6%
2 222
 
6.0%
3 158
 
4.2%
4 117
 
3.1%
6 113
 
3.0%
0 78
 
2.1%
Other values (4) 266
 
7.2%
Hangul
ValueCountFrequency (%)
동 479
 
9.4%
인 393
 
7.7%
구 376
 
7.4%
역 356
 
7.0%
천 350
 
6.9%
광 347
 
6.8%
시 347
 
6.8%
로 343
 
6.8%
부 154
 
3.0%
남 138
 
2.7%
Other values (135) 1798
35.4%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct206
Distinct (%)59.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21812.067
Minimum21013
Maximum22832
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-15T06:03:32.619569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum21013
5-th percentile21311.45
Q121452
median21673
Q322155.75
95-th percentile22778
Maximum22832
Range1819
Interquartile range (IQR)703.75

Descriptive statistics

Standard deviation441.03192
Coefficient of variation (CV)0.02021963
Kurtosis-0.43723637
Mean21812.067
Median Absolute Deviation (MAD)280.5
Skewness0.5793253
Sum7503351
Variance194509.16
MonotonicityNot monotonic
2024-03-15T06:03:33.102319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21672 20
 
5.8%
21673 19
 
5.5%
21674 13
 
3.8%
21404 9
 
2.6%
21394 7
 
2.0%
21389 6
 
1.7%
22348 5
 
1.5%
21393 5
 
1.5%
22316 4
 
1.2%
22322 4
 
1.2%
Other values (196) 252
73.3%
ValueCountFrequency (%)
21013 1
0.3%
21027 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%
21080 1
0.3%
ValueCountFrequency (%)
22832 1
0.3%
22818 1
0.3%
22817 1
0.3%
22814 2
0.6%
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

Distinct210
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
2024-03-15T06:03:34.166111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length24
Mean length18.68314
Min length14

Characters and Unicode

Total characters6427
Distinct characters84
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

Unique166 ?
Unique (%)48.3%

Sample

1st row인천광역시 중구 내동 188-2
2nd row인천광역시 중구 내동 209-7
3rd row인천광역시 중구 답동 65-1, 21
4th row인천광역시 중구 도원동 73-2
5th row인천광역시 중구 북성동1가 102-45
ValueCountFrequency (%)
인천광역시 344
24.9%
남동구 114
 
8.2%
부평구 73
 
5.3%
논현동 60
 
4.3%
미추홀구 53
 
3.8%
부평동 40
 
2.9%
중구 34
 
2.5%
126-10 33
 
2.4%
주안동 31
 
2.2%
연수구 29
 
2.1%
Other values (260) 571
41.3%
2024-03-15T06:03:35.614739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1038
16.2%
동 468
 
7.3%
구 365
 
5.7%
인 349
 
5.4%
천 349
 
5.4%
광 344
 
5.4%
역 344
 
5.4%
시 344
 
5.4%
1 321
 
5.0%
- 205
 
3.2%
Other values (74) 2300
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3787
58.9%
Decimal Number 1391
 
21.6%
Space Separator 1038
 
16.2%
Dash Punctuation 205
 
3.2%
Other Punctuation 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 468
12.4%
구 365
9.6%
인 349
9.2%
천 349
9.2%
광 344
 
9.1%
역 344
 
9.1%
시 344
 
9.1%
남 120
 
3.2%
부 120
 
3.2%
평 114
 
3.0%
Other values (61) 870
23.0%
Decimal Number
ValueCountFrequency (%)
1 321
23.1%
2 174
12.5%
3 143
10.3%
7 128
 
9.2%
0 120
 
8.6%
6 116
 
8.3%
5 103
 
7.4%
9 99
 
7.1%
4 95
 
6.8%
8 92
 
6.6%
Space Separator
ValueCountFrequency (%)
1038
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 205
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3787
58.9%
Common 2640
41.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 468
12.4%
구 365
9.6%
인 349
9.2%
천 349
9.2%
광 344
 
9.1%
역 344
 
9.1%
시 344
 
9.1%
남 120
 
3.2%
부 120
 
3.2%
평 114
 
3.0%
Other values (61) 870
23.0%
Common
ValueCountFrequency (%)
1038
39.3%
1 321
 
12.2%
- 205
 
7.8%
2 174
 
6.6%
3 143
 
5.4%
7 128
 
4.8%
0 120
 
4.5%
6 116
 
4.4%
5 103
 
3.9%
9 99
 
3.8%
Other values (3) 193
 
7.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3787
58.9%
ASCII 2640
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1038
39.3%
1 321
 
12.2%
- 205
 
7.8%
2 174
 
6.6%
3 143
 
5.4%
7 128
 
4.8%
0 120
 
4.5%
6 116
 
4.4%
5 103
 
3.9%
9 99
 
3.8%
Other values (3) 193
 
7.3%
Hangul
ValueCountFrequency (%)
동 468
12.4%
구 365
9.6%
인 349
9.2%
천 349
9.2%
광 344
 
9.1%
역 344
 
9.1%
시 344
 
9.1%
남 120
 
3.2%
부 120
 
3.2%
평 114
 
3.0%
Other values (61) 870
23.0%

Interactions

2024-03-15T06:03:25.941433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:03:25.454272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:03:26.213996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:03:25.670273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T06:03:35.771274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번구유형우편번호
순번1.0000.9070.5560.953
구0.9071.0000.5620.975
유형0.5560.5621.0000.584
우편번호0.9530.9750.5841.000
2024-03-15T06:03:36.017494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
유형구
유형1.0000.420
구0.4201.000
2024-03-15T06:03:36.238786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호구유형
순번1.000-0.5330.7390.424
우편번호-0.5331.0000.9190.449
구0.7390.9191.0000.420
유형0.4240.4490.4201.000

Missing values

2024-03-15T06:03:26.432858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:03:26.618541image/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
01중구구두수선대인천광역시 중구 우현로67번길 1-2 (내동)22316인천광역시 중구 내동 188-2
12중구구두수선대인천광역시 중구 우현로 53-1 (내동)22322인천광역시 중구 내동 209-7
23중구구두수선대인천광역시 중구 제물량로 142 (답동)22321인천광역시 중구 답동 65-1, 21
34중구가로판매대인천광역시 중구 참외전로 248 (도원동)22328인천광역시 중구 도원동 73-2
45중구가로판매대인천광역시 중구 월미로 312 (북성동1가)22304인천광역시 중구 북성동1가 102-45
56중구가로판매대인천광역시 중구 제물량로 273 (북성동1가)22307인천광역시 중구 북성동1가 3-61, 7-64
67중구가로판매대인천광역시 중구 월미로 486 (북성동1가)22305인천광역시 중구 북성동1가 75-11
78중구가로판매대인천광역시 중구 월미문화로 96 (북성동1가)22304인천광역시 중구 북성동1가 98-13
89중구가로판매대인천광역시 중구 월미로 217 (북성동1가)22302인천광역시 중구 북성동1가 98-35
910중구가로판매대인천광역시 중구 제물량로 165-3 (사동)22313인천광역시 중구 사동 26-19
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334335서구구두수선대인천광역시 서구 건지로 407-1 (가좌동)22807인천광역시 서구 가좌동 산141-8
335336서구구두수선대인천광역시 서구 도요지로 220-1 (검암동)22699인천광역시 서구 검암동 740
336337서구구두수선대인천광역시 서구 여우재로 114-1 (가좌동)22811인천광역시 서구 가좌동 401
337338서구구두수선대인천광역시 서구 율도로 27-1 (신현동)22780인천광역시 서구 신현동 산23-11
338339서구구두수선대인천광역시 서구 탁옥로 34-1 (심곡동)22727인천광역시 서구 심곡동 269
339340서구구두수선대인천광역시 서구 탁옥로 110-1 (심곡동)22711인천광역시 서구 심곡동 311
340341서구구두수선대인천광역시 서구 가정로293번길 2-1 (석남동)22785인천광역시 서구 석남동 454-4
341342서구구두수선대인천광역시 서구 거북로119번길 1-1 (석남동)22791인천광역시 서구 석남동 620
342343서구구두수선대인천광역시 서구 승학로495번길 4-22 (검암동)22695인천광역시 서구 검암동 688
343344서구구두수선대인천광역시 서구 신진말로28번길 17-1 (가좌동)22817인천광역시 서구 가좌동 211