Overview

Dataset statistics

Number of variables4
Number of observations609
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.8 KiB
Average record size in memory33.2 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description서울특별시 양천구 담배소매인 지정 목록으로 총 652개소의 상호와 도로명주소(상세주소)를 제공합니다.예)담배판매, 상세주소
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15039323/fileData.do

Alerts

데이터기준일 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 16:39:13.133677
Analysis finished2024-03-14 16:39:14.426155
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct609
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean305
Minimum1
Maximum609
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-03-15T01:39:14.636615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31.4
Q1153
median305
Q3457
95-th percentile578.6
Maximum609
Range608
Interquartile range (IQR)304

Descriptive statistics

Standard deviation175.94744
Coefficient of variation (CV)0.57687684
Kurtosis-1.2
Mean305
Median Absolute Deviation (MAD)152
Skewness0
Sum185745
Variance30957.5
MonotonicityStrictly increasing
2024-03-15T01:39:15.050413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
410 1
 
0.2%
403 1
 
0.2%
404 1
 
0.2%
405 1
 
0.2%
406 1
 
0.2%
407 1
 
0.2%
408 1
 
0.2%
409 1
 
0.2%
411 1
 
0.2%
Other values (599) 599
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
609 1
0.2%
608 1
0.2%
607 1
0.2%
606 1
0.2%
605 1
0.2%
604 1
0.2%
603 1
0.2%
602 1
0.2%
601 1
0.2%
600 1
0.2%

상호명
Text

Distinct598
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-03-15T01:39:16.031087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length15
Mean length8.5993432
Min length2

Characters and Unicode

Total characters5237
Distinct characters405
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique592 ?
Unique (%)97.2%

Sample

1st rowGS25 신정중앙점
2nd row지에스25 목동낙원점
3rd row지에스25 양천보람점
4th row씨유 신월정성점
5th row지에스25 신정로점
ValueCountFrequency (%)
씨유 72
 
7.8%
지에스25 42
 
4.5%
주)코리아세븐 31
 
3.4%
이마트24 27
 
2.9%
gs25 26
 
2.8%
세븐일레븐 20
 
2.2%
cu 7
 
0.8%
지에스(gs)25 6
 
0.6%
주식회사 6
 
0.6%
목동점 5
 
0.5%
Other values (637) 682
73.8%
2024-03-15T01:39:17.184257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 336
 
6.4%
316
 
6.0%
목 176
 
3.4%
동 170
 
3.2%
신 167
 
3.2%
2 144
 
2.7%
트 131
 
2.5%
스 130
 
2.5%
마 126
 
2.4%
5 112
 
2.1%
Other values (395) 3429
65.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4211
80.4%
Decimal Number 348
 
6.6%
Space Separator 316
 
6.0%
Uppercase Letter 176
 
3.4%
Open Punctuation 81
 
1.5%
Close Punctuation 81
 
1.5%
Lowercase Letter 15
 
0.3%
Other Punctuation 6
 
0.1%
Dash Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 336
 
8.0%
목 176
 
4.2%
동 170
 
4.0%
신 167
 
4.0%
트 131
 
3.1%
스 130
 
3.1%
마 126
 
3.0%
지 104
 
2.5%
유 98
 
2.3%
븐 90
 
2.1%
Other values (352) 2683
63.7%
Uppercase Letter
ValueCountFrequency (%)
S 70
39.8%
G 56
31.8%
C 13
 
7.4%
U 11
 
6.2%
R 5
 
2.8%
O 4
 
2.3%
T 3
 
1.7%
B 3
 
1.7%
A 2
 
1.1%
D 2
 
1.1%
Other values (7) 7
 
4.0%
Decimal Number
ValueCountFrequency (%)
2 144
41.4%
5 112
32.2%
4 36
 
10.3%
1 20
 
5.7%
3 13
 
3.7%
0 6
 
1.7%
6 6
 
1.7%
7 5
 
1.4%
9 3
 
0.9%
8 3
 
0.9%
Lowercase Letter
ValueCountFrequency (%)
e 4
26.7%
p 2
13.3%
s 2
13.3%
r 2
13.3%
v 1
 
6.7%
y 1
 
6.7%
o 1
 
6.7%
t 1
 
6.7%
a 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 5
83.3%
& 1
 
16.7%
Space Separator
ValueCountFrequency (%)
316
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4212
80.4%
Common 834
 
15.9%
Latin 191
 
3.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 336
 
8.0%
목 176
 
4.2%
동 170
 
4.0%
신 167
 
4.0%
트 131
 
3.1%
스 130
 
3.1%
마 126
 
3.0%
지 104
 
2.5%
유 98
 
2.3%
븐 90
 
2.1%
Other values (353) 2684
63.7%
Latin
ValueCountFrequency (%)
S 70
36.6%
G 56
29.3%
C 13
 
6.8%
U 11
 
5.8%
R 5
 
2.6%
e 4
 
2.1%
O 4
 
2.1%
T 3
 
1.6%
B 3
 
1.6%
p 2
 
1.0%
Other values (16) 20
 
10.5%
Common
ValueCountFrequency (%)
316
37.9%
2 144
17.3%
5 112
 
13.4%
( 81
 
9.7%
) 81
 
9.7%
4 36
 
4.3%
1 20
 
2.4%
3 13
 
1.6%
0 6
 
0.7%
6 6
 
0.7%
Other values (6) 19
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4211
80.4%
ASCII 1025
 
19.6%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 336
 
8.0%
목 176
 
4.2%
동 170
 
4.0%
신 167
 
4.0%
트 131
 
3.1%
스 130
 
3.1%
마 126
 
3.0%
지 104
 
2.5%
유 98
 
2.3%
븐 90
 
2.1%
Other values (352) 2683
63.7%
ASCII
ValueCountFrequency (%)
316
30.8%
2 144
14.0%
5 112
 
10.9%
( 81
 
7.9%
) 81
 
7.9%
S 70
 
6.8%
G 56
 
5.5%
4 36
 
3.5%
1 20
 
2.0%
3 13
 
1.3%
Other values (32) 96
 
9.4%
None
ValueCountFrequency (%)
㈜ 1
100.0%

주소
Text

Distinct602
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-03-15T01:39:18.246604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length71
Median length56
Mean length32.660099
Min length1

Characters and Unicode

Total characters19890
Distinct characters269
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique599 ?
Unique (%)98.4%

Sample

1st row서울특별시 양천구 은행정로 14 (신정동)
2nd row서울특별시 양천구 목동중앙본로7가길 65. 1층 (목동)
3rd row서울특별시 양천구 곰달래로7길 10. 1층 (신월동)
4th row서울특별시 양천구 월정로17길 25 (신월동)
5th row서울특별시 양천구 목동로19길 11. 1층 (신정동)
ValueCountFrequency (%)
서울특별시 603
 
15.8%
양천구 603
 
15.8%
1층 198
 
5.2%
신월동 178
 
4.7%
신정동 175
 
4.6%
목동 155
 
4.1%
목동동로 43
 
1.1%
목동서로 40
 
1.0%
오목로 40
 
1.0%
101호 30
 
0.8%
Other values (897) 1751
45.9%
2024-03-15T01:39:19.585797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3252
 
16.3%
1 1064
 
5.3%
동 1007
 
5.1%
서 661
 
3.3%
양 634
 
3.2%
시 632
 
3.2%
로 624
 
3.1%
천 613
 
3.1%
구 607
 
3.1%
) 605
 
3.0%
Other values (259) 10191
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11313
56.9%
Decimal Number 3377
 
17.0%
Space Separator 3252
 
16.3%
Close Punctuation 605
 
3.0%
Open Punctuation 605
 
3.0%
Other Punctuation 555
 
2.8%
Dash Punctuation 119
 
0.6%
Uppercase Letter 49
 
0.2%
Lowercase Letter 9
 
< 0.1%
Math Symbol 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 1007
 
8.9%
서 661
 
5.8%
양 634
 
5.6%
시 632
 
5.6%
로 624
 
5.5%
천 613
 
5.4%
구 607
 
5.4%
울 605
 
5.3%
별 603
 
5.3%
특 603
 
5.3%
Other values (222) 4724
41.8%
Uppercase Letter
ValueCountFrequency (%)
B 20
40.8%
A 10
20.4%
S 6
 
12.2%
C 5
 
10.2%
K 2
 
4.1%
O 1
 
2.0%
T 1
 
2.0%
P 1
 
2.0%
X 1
 
2.0%
M 1
 
2.0%
Decimal Number
ValueCountFrequency (%)
1 1064
31.5%
0 402
 
11.9%
2 395
 
11.7%
3 333
 
9.9%
5 250
 
7.4%
4 250
 
7.4%
6 195
 
5.8%
7 188
 
5.6%
9 154
 
4.6%
8 146
 
4.3%
Lowercase Letter
ValueCountFrequency (%)
p 2
22.2%
l 2
22.2%
e 1
11.1%
i 1
11.1%
v 1
11.1%
y 1
11.1%
a 1
11.1%
Other Punctuation
ValueCountFrequency (%)
. 545
98.2%
@ 8
 
1.4%
· 1
 
0.2%
/ 1
 
0.2%
Space Separator
ValueCountFrequency (%)
3252
100.0%
Close Punctuation
ValueCountFrequency (%)
) 605
100.0%
Open Punctuation
ValueCountFrequency (%)
( 605
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 119
100.0%
Math Symbol
ValueCountFrequency (%)
~ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11313
56.9%
Common 8519
42.8%
Latin 58
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 1007
 
8.9%
서 661
 
5.8%
양 634
 
5.6%
시 632
 
5.6%
로 624
 
5.5%
천 613
 
5.4%
구 607
 
5.4%
울 605
 
5.3%
별 603
 
5.3%
특 603
 
5.3%
Other values (222) 4724
41.8%
Common
ValueCountFrequency (%)
3252
38.2%
1 1064
 
12.5%
) 605
 
7.1%
( 605
 
7.1%
. 545
 
6.4%
0 402
 
4.7%
2 395
 
4.6%
3 333
 
3.9%
5 250
 
2.9%
4 250
 
2.9%
Other values (9) 818
 
9.6%
Latin
ValueCountFrequency (%)
B 20
34.5%
A 10
17.2%
S 6
 
10.3%
C 5
 
8.6%
p 2
 
3.4%
l 2
 
3.4%
K 2
 
3.4%
O 1
 
1.7%
T 1
 
1.7%
P 1
 
1.7%
Other values (8) 8
 
13.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11313
56.9%
ASCII 8576
43.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3252
37.9%
1 1064
 
12.4%
) 605
 
7.1%
( 605
 
7.1%
. 545
 
6.4%
0 402
 
4.7%
2 395
 
4.6%
3 333
 
3.9%
5 250
 
2.9%
4 250
 
2.9%
Other values (26) 875
 
10.2%
Hangul
ValueCountFrequency (%)
동 1007
 
8.9%
서 661
 
5.8%
양 634
 
5.6%
시 632
 
5.6%
로 624
 
5.5%
천 613
 
5.4%
구 607
 
5.4%
울 605
 
5.3%
별 603
 
5.3%
특 603
 
5.3%
Other values (222) 4724
41.8%
None
ValueCountFrequency (%)
· 1
100.0%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
2024-01-20
609 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-20
2nd row2024-01-20
3rd row2024-01-20
4th row2024-01-20
5th row2024-01-20

Common Values

ValueCountFrequency (%)
2024-01-20 609
100.0%

Length

2024-03-15T01:39:19.917518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T01:39:20.178048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-20 609
100.0%

Interactions

2024-03-15T01:39:13.682739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-15T01:39:14.025752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:39:14.314127image/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

연번상호명주소데이터기준일
01GS25 신정중앙점서울특별시 양천구 은행정로 14 (신정동)2024-01-20
12지에스25 목동낙원점서울특별시 양천구 목동중앙본로7가길 65. 1층 (목동)2024-01-20
23지에스25 양천보람점서울특별시 양천구 곰달래로7길 10. 1층 (신월동)2024-01-20
34씨유 신월정성점서울특별시 양천구 월정로17길 25 (신월동)2024-01-20
45지에스25 신정로점서울특별시 양천구 목동로19길 11. 1층 (신정동)2024-01-20
56(주)코리아세븐 목동역점서울특별시 양천구 신정중앙로 88 (신정동)2024-01-20
67지에스25 신월베스트점서울특별시 양천구 가로공원로69길 8. 1층 (신월동)2024-01-20
78씨유 양천중앙점서울특별시 양천구 중앙로48길 6. 1층 (신정동)2024-01-20
89세븐일레븐 목동13단지점서울특별시 양천구 목동동로 100. A동 113. 114호 (신정동. 목동신시가지아파트13단지)2024-01-20
910씨유 목동11단지점서울특별시 양천구 목동동로 10. 상가A동 1층 101호 (신정동. 목동신시가지아파트11단지)2024-01-20
연번상호명주소데이터기준일
599600현대스토아서울특별시 양천구 목동중앙북로8나길 11 (목동)2024-01-20
600601서울쌀상회서울특별시 양천구 화곡로3가길 7-8 (신월동)2024-01-20
601602서부매점서울특별시 양천구 신정로 167. C동 1층 1104호 (신정동. 서부트럭터미널)2024-01-20
602603길훈슈퍼서울특별시 양천구 지양로 101. 1호 (신월동.길훈아파트 상가7동 1층)2024-01-20
603604프로세탁소서울특별시 양천구 화곡로8길 21 (신월동)2024-01-20
604605민속떡집서울특별시 양천구 월정로7길 14 (신월동)2024-01-20
605606정일부동산서울특별시 양천구 오목로3길 24 (신월동.108호)2024-01-20
606607미도슈퍼서울특별시 양천구 은행정로 70 (신정동)2024-01-20
607608(주)이마트에브리데이목동점서울특별시 양천구 목동서로 130 (목5동904 목동@4단지 관리동상가 105호)2024-01-20
608609세븐일레븐 신월2호점서울특별시 양천구 오목로 19 (신월동)2024-01-20