Overview

Dataset statistics

Number of variables8
Number of observations4261
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory270.6 KiB
Average record size in memory65.0 B

Variable types

Categorical2
DateTime2
Text3
Numeric1

Dataset

Description서울특별시 양천구의 음식점 업종, 업태, 업소명, 주소지, 전화번호, 영업장면적, 인허가일자 정보를 제공합니다.
Author서울특별시 양천구
URLhttps://www.data.go.kr/data/15035771/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업태명 is highly overall correlated with 업종명High correlation
업종명 is highly overall correlated with 업태명High correlation

Reproduction

Analysis started2023-12-12 01:17:57.092480
Analysis finished2023-12-12 01:17:59.112424
Duration2.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.4 KiB
일반음식점
3177 
휴게음식점
1084 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반음식점 3177
74.6%
휴게음식점 1084
 
25.4%

Length

2023-12-12T10:17:59.207706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:17:59.369525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 3177
74.6%
휴게음식점 1084
 
25.4%

인허가일자
Date

Distinct2804
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Memory size33.4 KiB
Minimum1977-08-20 00:00:00
Maximum2023-09-14 00:00:00
2023-12-12T10:17:59.541625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:17:59.783149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업소명
Text

Distinct4117
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Memory size33.4 KiB
2023-12-12T10:18:00.181241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length26
Mean length7.2128608
Min length1

Characters and Unicode

Total characters30734
Distinct characters946
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks6 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3998 ?
Unique (%)93.8%

Sample

1st row염창식당
2nd row신흥반점
3rd row중화루
4th row홍콩반점
5th row손오공마라탕 목동점
ValueCountFrequency (%)
목동점 169
 
2.9%
신정점 44
 
0.8%
씨유 44
 
0.8%
신월점 39
 
0.7%
세븐일레븐 36
 
0.6%
오목교점 34
 
0.6%
신정네거리역점 25
 
0.4%
지에스25 25
 
0.4%
메가엠지씨커피 25
 
0.4%
카페 23
 
0.4%
Other values (4385) 5273
91.9%
2023-12-12T10:18:01.033513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1480
 
4.8%
점 1315
 
4.3%
동 786
 
2.6%
목 758
 
2.5%
이 622
 
2.0%
스 588
 
1.9%
신 526
 
1.7%
리 454
 
1.5%
) 374
 
1.2%
( 374
 
1.2%
Other values (936) 23457
76.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 26007
84.6%
Space Separator 1480
 
4.8%
Uppercase Letter 870
 
2.8%
Lowercase Letter 830
 
2.7%
Decimal Number 662
 
2.2%
Close Punctuation 374
 
1.2%
Open Punctuation 374
 
1.2%
Other Punctuation 121
 
0.4%
Math Symbol 6
 
< 0.1%
Dash Punctuation 5
 
< 0.1%
Other values (2) 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 1315
 
5.1%
동 786
 
3.0%
목 758
 
2.9%
이 622
 
2.4%
스 588
 
2.3%
신 526
 
2.0%
리 454
 
1.7%
피 328
 
1.3%
정 321
 
1.2%
마 277
 
1.1%
Other values (855) 20032
77.0%
Lowercase Letter
ValueCountFrequency (%)
e 147
17.7%
a 87
10.5%
o 74
 
8.9%
f 57
 
6.9%
c 49
 
5.9%
r 49
 
5.9%
i 44
 
5.3%
s 39
 
4.7%
t 38
 
4.6%
n 37
 
4.5%
Other values (16) 209
25.2%
Uppercase Letter
ValueCountFrequency (%)
C 91
 
10.5%
S 78
 
9.0%
O 69
 
7.9%
A 60
 
6.9%
E 59
 
6.8%
P 51
 
5.9%
B 49
 
5.6%
G 42
 
4.8%
T 37
 
4.3%
N 36
 
4.1%
Other values (16) 298
34.3%
Decimal Number
ValueCountFrequency (%)
2 173
26.1%
5 108
16.3%
1 97
14.7%
4 68
 
10.3%
0 51
 
7.7%
3 50
 
7.6%
7 39
 
5.9%
8 30
 
4.5%
9 27
 
4.1%
6 19
 
2.9%
Other Punctuation
ValueCountFrequency (%)
& 56
46.3%
. 32
26.4%
, 14
 
11.6%
' 7
 
5.8%
· 5
 
4.1%
: 3
 
2.5%
! 2
 
1.7%
# 1
 
0.8%
% 1
 
0.8%
Math Symbol
ValueCountFrequency (%)
× 4
66.7%
~ 1
 
16.7%
+ 1
 
16.7%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
Space Separator
ValueCountFrequency (%)
1480
100.0%
Close Punctuation
ValueCountFrequency (%)
) 374
100.0%
Open Punctuation
ValueCountFrequency (%)
( 374
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 25988
84.6%
Common 3024
 
9.8%
Latin 1703
 
5.5%
Han 19
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 1315
 
5.1%
동 786
 
3.0%
목 758
 
2.9%
이 622
 
2.4%
스 588
 
2.3%
신 526
 
2.0%
리 454
 
1.7%
피 328
 
1.3%
정 321
 
1.2%
마 277
 
1.1%
Other values (841) 20013
77.0%
Latin
ValueCountFrequency (%)
e 147
 
8.6%
C 91
 
5.3%
a 87
 
5.1%
S 78
 
4.6%
o 74
 
4.3%
O 69
 
4.1%
A 60
 
3.5%
E 59
 
3.5%
f 57
 
3.3%
P 51
 
3.0%
Other values (44) 930
54.6%
Common
ValueCountFrequency (%)
1480
48.9%
) 374
 
12.4%
( 374
 
12.4%
2 173
 
5.7%
5 108
 
3.6%
1 97
 
3.2%
4 68
 
2.2%
& 56
 
1.9%
0 51
 
1.7%
3 50
 
1.7%
Other values (17) 193
 
6.4%
Han
ValueCountFrequency (%)
家 3
15.8%
酒 2
10.5%
松 2
10.5%
木 2
10.5%
火 1
 
5.3%
蘊 1
 
5.3%
金 1
 
5.3%
一 1
 
5.3%
品 1
 
5.3%
情 1
 
5.3%
Other values (4) 4
21.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 25988
84.6%
ASCII 4715
 
15.3%
CJK 17
 
0.1%
None 9
 
< 0.1%
Number Forms 3
 
< 0.1%
CJK Compat Ideographs 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1480
31.4%
) 374
 
7.9%
( 374
 
7.9%
2 173
 
3.7%
e 147
 
3.1%
5 108
 
2.3%
1 97
 
2.1%
C 91
 
1.9%
a 87
 
1.8%
S 78
 
1.7%
Other values (67) 1706
36.2%
Hangul
ValueCountFrequency (%)
점 1315
 
5.1%
동 786
 
3.0%
목 758
 
2.9%
이 622
 
2.4%
스 588
 
2.3%
신 526
 
2.0%
리 454
 
1.7%
피 328
 
1.3%
정 321
 
1.2%
마 277
 
1.1%
Other values (841) 20013
77.0%
None
ValueCountFrequency (%)
· 5
55.6%
× 4
44.4%
CJK
ValueCountFrequency (%)
家 3
17.6%
酒 2
11.8%
松 2
11.8%
木 2
11.8%
火 1
 
5.9%
蘊 1
 
5.9%
一 1
 
5.9%
品 1
 
5.9%
情 1
 
5.9%
林 1
 
5.9%
Other values (2) 2
11.8%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
66.7%
Ⅰ 1
33.3%
CJK Compat Ideographs
ValueCountFrequency (%)
金 1
50.0%
李 1
50.0%

소재지(도로명)
Text

Distinct3932
Distinct (%)92.3%
Missing2
Missing (%)< 0.1%
Memory size33.4 KiB
2023-12-12T10:18:01.418702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length61
Mean length33.830711
Min length21

Characters and Unicode

Total characters144085
Distinct characters368
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3710 ?
Unique (%)87.1%

Sample

1st row서울특별시 양천구 목동중앙북로 97, 1층 (목동)
2nd row서울특별시 양천구 목동중앙북로16길 32, 1층 (목동)
3rd row서울특별시 양천구 화곡로3길 1 (신월동)
4th row서울특별시 양천구 곰달래로 9-1, 1층 (신월동)
5th row서울특별시 양천구 오목로50길 1 (신정동)
ValueCountFrequency (%)
서울특별시 4259
 
14.9%
양천구 4259
 
14.9%
1층 2376
 
8.3%
목동 1566
 
5.5%
신정동 1397
 
4.9%
신월동 1099
 
3.8%
목동동로 416
 
1.5%
지상1층 398
 
1.4%
오목로 351
 
1.2%
목동서로 292
 
1.0%
Other values (2235) 12258
42.8%
2023-12-12T10:18:02.114468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
24417
 
16.9%
1 8029
 
5.6%
동 7288
 
5.1%
, 4985
 
3.5%
서 4695
 
3.3%
양 4461
 
3.1%
로 4455
 
3.1%
목 4424
 
3.1%
( 4420
 
3.1%
) 4420
 
3.1%
Other values (358) 72491
50.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 82419
57.2%
Space Separator 24417
 
16.9%
Decimal Number 22482
 
15.6%
Other Punctuation 4994
 
3.5%
Open Punctuation 4420
 
3.1%
Close Punctuation 4420
 
3.1%
Dash Punctuation 601
 
0.4%
Uppercase Letter 202
 
0.1%
Math Symbol 107
 
0.1%
Lowercase Letter 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 7288
 
8.8%
서 4695
 
5.7%
양 4461
 
5.4%
로 4455
 
5.4%
목 4424
 
5.4%
시 4339
 
5.3%
천 4305
 
5.2%
구 4275
 
5.2%
울 4271
 
5.2%
별 4262
 
5.2%
Other values (318) 35644
43.2%
Uppercase Letter
ValueCountFrequency (%)
B 81
40.1%
A 51
25.2%
M 11
 
5.4%
S 9
 
4.5%
C 9
 
4.5%
R 5
 
2.5%
E 5
 
2.5%
U 4
 
2.0%
T 4
 
2.0%
O 4
 
2.0%
Other values (9) 19
 
9.4%
Decimal Number
ValueCountFrequency (%)
1 8029
35.7%
2 3036
 
13.5%
3 2280
 
10.1%
0 2235
 
9.9%
5 1485
 
6.6%
4 1427
 
6.3%
7 1142
 
5.1%
6 1109
 
4.9%
9 921
 
4.1%
8 818
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 4985
99.8%
. 6
 
0.1%
& 2
 
< 0.1%
/ 1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
24417
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4420
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4420
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 601
100.0%
Math Symbol
ValueCountFrequency (%)
~ 107
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 14
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 82419
57.2%
Common 61441
42.6%
Latin 225
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 7288
 
8.8%
서 4695
 
5.7%
양 4461
 
5.4%
로 4455
 
5.4%
목 4424
 
5.4%
시 4339
 
5.3%
천 4305
 
5.2%
구 4275
 
5.2%
울 4271
 
5.2%
별 4262
 
5.2%
Other values (318) 35644
43.2%
Latin
ValueCountFrequency (%)
B 81
36.0%
A 51
22.7%
l 14
 
6.2%
M 11
 
4.9%
Ⅰ 9
 
4.0%
S 9
 
4.0%
C 9
 
4.0%
R 5
 
2.2%
E 5
 
2.2%
U 4
 
1.8%
Other values (11) 27
 
12.0%
Common
ValueCountFrequency (%)
24417
39.7%
1 8029
 
13.1%
, 4985
 
8.1%
( 4420
 
7.2%
) 4420
 
7.2%
2 3036
 
4.9%
3 2280
 
3.7%
0 2235
 
3.6%
5 1485
 
2.4%
4 1427
 
2.3%
Other values (9) 4707
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 82419
57.2%
ASCII 61657
42.8%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
24417
39.6%
1 8029
 
13.0%
, 4985
 
8.1%
( 4420
 
7.2%
) 4420
 
7.2%
2 3036
 
4.9%
3 2280
 
3.7%
0 2235
 
3.6%
5 1485
 
2.4%
4 1427
 
2.3%
Other values (29) 4923
 
8.0%
Hangul
ValueCountFrequency (%)
동 7288
 
8.8%
서 4695
 
5.7%
양 4461
 
5.4%
로 4455
 
5.4%
목 4424
 
5.4%
시 4339
 
5.3%
천 4305
 
5.2%
구 4275
 
5.2%
울 4271
 
5.2%
별 4262
 
5.2%
Other values (318) 35644
43.2%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
100.0%

소재지(지번)
Text

Distinct3557
Distinct (%)83.5%
Missing0
Missing (%)0.0%
Memory size33.4 KiB
2023-12-12T10:18:02.673274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length50
Mean length26.275992
Min length17

Characters and Unicode

Total characters111962
Distinct characters364
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3171 ?
Unique (%)74.4%

Sample

1st row서울특별시 양천구 목동 514-15 1층
2nd row서울특별시 양천구 목동 535-18 1층
3rd row서울특별시 양천구 신월동 28-4
4th row서울특별시 양천구 신월동 126-22 1층
5th row서울특별시 양천구 신정동 994-8
ValueCountFrequency (%)
서울특별시 4261
19.1%
양천구 4261
19.1%
목동 1686
 
7.6%
신정동 1466
 
6.6%
1층 1308
 
5.9%
신월동 1174
 
5.3%
지상1층 340
 
1.5%
2층 127
 
0.6%
101호 115
 
0.5%
지하1층 111
 
0.5%
Other values (3437) 7481
33.5%
2023-12-12T10:18:03.437713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
21686
19.4%
1 7308
 
6.5%
동 4904
 
4.4%
시 4339
 
3.9%
양 4328
 
3.9%
서 4302
 
3.8%
천 4298
 
3.8%
구 4277
 
3.8%
울 4272
 
3.8%
별 4264
 
3.8%
Other values (354) 47984
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 60684
54.2%
Decimal Number 24978
22.3%
Space Separator 21686
 
19.4%
Dash Punctuation 3877
 
3.5%
Other Punctuation 177
 
0.2%
Close Punctuation 168
 
0.2%
Open Punctuation 168
 
0.2%
Uppercase Letter 136
 
0.1%
Math Symbol 65
 
0.1%
Lowercase Letter 14
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 4904
 
8.1%
시 4339
 
7.2%
양 4328
 
7.1%
서 4302
 
7.1%
천 4298
 
7.1%
구 4277
 
7.0%
울 4272
 
7.0%
별 4264
 
7.0%
특 4263
 
7.0%
신 2837
 
4.7%
Other values (314) 18600
30.7%
Uppercase Letter
ValueCountFrequency (%)
B 43
31.6%
A 30
22.1%
M 11
 
8.1%
S 8
 
5.9%
C 8
 
5.9%
T 5
 
3.7%
E 4
 
2.9%
P 4
 
2.9%
O 4
 
2.9%
Y 3
 
2.2%
Other values (9) 16
 
11.8%
Decimal Number
ValueCountFrequency (%)
1 7308
29.3%
2 3051
12.2%
0 2685
 
10.7%
9 2284
 
9.1%
3 1928
 
7.7%
4 1762
 
7.1%
5 1568
 
6.3%
6 1562
 
6.3%
7 1557
 
6.2%
8 1273
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 168
94.9%
. 6
 
3.4%
& 2
 
1.1%
/ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
21686
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3877
100.0%
Close Punctuation
ValueCountFrequency (%)
) 168
100.0%
Open Punctuation
ValueCountFrequency (%)
( 168
100.0%
Math Symbol
ValueCountFrequency (%)
~ 65
100.0%
Lowercase Letter
ValueCountFrequency (%)
l 14
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 60684
54.2%
Common 51119
45.7%
Latin 159
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 4904
 
8.1%
시 4339
 
7.2%
양 4328
 
7.1%
서 4302
 
7.1%
천 4298
 
7.1%
구 4277
 
7.0%
울 4272
 
7.0%
별 4264
 
7.0%
특 4263
 
7.0%
신 2837
 
4.7%
Other values (314) 18600
30.7%
Latin
ValueCountFrequency (%)
B 43
27.0%
A 30
18.9%
l 14
 
8.8%
M 11
 
6.9%
Ⅰ 9
 
5.7%
S 8
 
5.0%
C 8
 
5.0%
T 5
 
3.1%
E 4
 
2.5%
P 4
 
2.5%
Other values (11) 23
14.5%
Common
ValueCountFrequency (%)
21686
42.4%
1 7308
 
14.3%
- 3877
 
7.6%
2 3051
 
6.0%
0 2685
 
5.3%
9 2284
 
4.5%
3 1928
 
3.8%
4 1762
 
3.4%
5 1568
 
3.1%
6 1562
 
3.1%
Other values (9) 3408
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 60684
54.2%
ASCII 51269
45.8%
Number Forms 9
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21686
42.3%
1 7308
 
14.3%
- 3877
 
7.6%
2 3051
 
6.0%
0 2685
 
5.2%
9 2284
 
4.5%
3 1928
 
3.8%
4 1762
 
3.4%
5 1568
 
3.1%
6 1562
 
3.0%
Other values (29) 3558
 
6.9%
Hangul
ValueCountFrequency (%)
동 4904
 
8.1%
시 4339
 
7.2%
양 4328
 
7.1%
서 4302
 
7.1%
천 4298
 
7.1%
구 4277
 
7.0%
울 4272
 
7.0%
별 4264
 
7.0%
특 4263
 
7.0%
신 2837
 
4.7%
Other values (314) 18600
30.7%
Number Forms
ValueCountFrequency (%)
Ⅰ 9
100.0%

건물내부면적
Real number (ℝ)

Distinct2212
Distinct (%)51.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.090509
Minimum0
Maximum2175
Zeros5
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size37.6 KiB
2023-12-12T10:18:03.646575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.6
Q126.4
median41.25
Q370.63
95-th percentile167.38
Maximum2175
Range2175
Interquartile range (IQR)44.23

Descriptive statistics

Standard deviation85.561349
Coefficient of variation (CV)1.3780101
Kurtosis159.06171
Mean62.090509
Median Absolute Deviation (MAD)18.92
Skewness9.4900798
Sum264567.66
Variance7320.7444
MonotonicityNot monotonic
2023-12-12T10:18:03.868017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.3 135
 
3.2%
33.0 121
 
2.8%
6.6 86
 
2.0%
30.0 79
 
1.9%
26.4 55
 
1.3%
66.0 45
 
1.1%
29.7 42
 
1.0%
25.0 38
 
0.9%
40.0 34
 
0.8%
20.0 34
 
0.8%
Other values (2202) 3592
84.3%
ValueCountFrequency (%)
0.0 5
 
0.1%
1.5 1
 
< 0.1%
2.64 1
 
< 0.1%
3.0 3
 
0.1%
3.3 135
3.2%
3.62 1
 
< 0.1%
3.68 1
 
< 0.1%
5.0 6
 
0.1%
5.29 1
 
< 0.1%
5.48 1
 
< 0.1%
ValueCountFrequency (%)
2175.0 1
< 0.1%
1688.62 1
< 0.1%
1474.88 1
< 0.1%
1113.8 1
< 0.1%
1074.73 1
< 0.1%
872.0 1
< 0.1%
853.71 1
< 0.1%
843.91 1
< 0.1%
803.18 1
< 0.1%
795.45 1
< 0.1%

업태명
Categorical

HIGH CORRELATION 

Distinct36
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size33.4 KiB
한식
1228 
기타
568 
커피숍
436 
호프/통닭
390 
분식
230 
Other values (31)
1409 

Length

Max length15
Median length2
Mean length3.3062661
Min length2

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row한식
2nd row중국식
3rd row중국식
4th row중국식
5th row중국식

Common Values

ValueCountFrequency (%)
한식 1228
28.8%
기타 568
13.3%
커피숍 436
 
10.2%
호프/통닭 390
 
9.2%
분식 230
 
5.4%
편의점 199
 
4.7%
기타 휴게음식점 194
 
4.6%
일반조리판매 147
 
3.4%
일식 128
 
3.0%
중국식 126
 
3.0%
Other values (26) 615
14.4%

Length

2023-12-12T10:18:04.052515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 1228
27.6%
기타 762
17.1%
커피숍 436
 
9.8%
호프/통닭 390
 
8.8%
분식 230
 
5.2%
편의점 199
 
4.5%
휴게음식점 194
 
4.4%
일반조리판매 147
 
3.3%
일식 128
 
2.9%
중국식 126
 
2.8%
Other values (26) 615
13.8%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size33.4 KiB
Minimum2023-09-20 00:00:00
Maximum2023-09-20 00:00:00
2023-12-12T10:18:04.179123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:18:04.276745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T10:17:58.693706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:18:04.370940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종명건물내부면적업태명
업종명1.0000.0251.000
건물내부면적0.0251.0000.556
업태명1.0000.5561.000
2023-12-12T10:18:04.498175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태명업종명
업태명1.0000.990
업종명0.9901.000
2023-12-12T10:18:04.594210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건물내부면적업종명업태명
건물내부면적1.0000.0250.219
업종명0.0251.0000.990
업태명0.2190.9901.000

Missing values

2023-12-12T10:17:58.862005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:17:59.031734image/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

업종명인허가일자업소명소재지(도로명)소재지(지번)건물내부면적업태명데이터기준일자
0일반음식점1977-08-20염창식당서울특별시 양천구 목동중앙북로 97, 1층 (목동)서울특별시 양천구 목동 514-15 1층71.04한식2023-09-20
1일반음식점1980-04-17신흥반점서울특별시 양천구 목동중앙북로16길 32, 1층 (목동)서울특별시 양천구 목동 535-18 1층20.19중국식2023-09-20
2일반음식점1980-09-16중화루서울특별시 양천구 화곡로3길 1 (신월동)서울특별시 양천구 신월동 28-429.4중국식2023-09-20
3일반음식점1980-05-26홍콩반점서울특별시 양천구 곰달래로 9-1, 1층 (신월동)서울특별시 양천구 신월동 126-22 1층9.92중국식2023-09-20
4일반음식점1981-06-19손오공마라탕 목동점서울특별시 양천구 오목로50길 1 (신정동)서울특별시 양천구 신정동 994-878.62중국식2023-09-20
5일반음식점1982-04-22하림맥시칸신정점서울특별시 양천구 중앙로29길 5, 1층 (신정동)서울특별시 양천구 신정동 1148-1 1층28.08통닭(치킨)2023-09-20
6일반음식점1983-05-18신도리서울특별시 양천구 신정중앙로 100, 1층 (신정동)서울특별시 양천구 신정동 902-7 1층37.75일식2023-09-20
7일반음식점1983-12-12도채가비서울특별시 양천구 목동중앙북로7가길 55, 1층 (목동)서울특별시 양천구 목동 612-652.26정종/대포집/소주방2023-09-20
8일반음식점1983-12-20서울꽃삼 신월직영점서울특별시 양천구 곰달래로 20 (신월동,1층)서울특별시 양천구 신월동 225-17 1층41.0한식2023-09-20
9일반음식점1984-08-02전국식당서울특별시 양천구 신정로 167, B동 지하1층 11,12호 (신정동)서울특별시 양천구 신정동 1315-9 지하1층 B동 11,12호96.06한식2023-09-20
업종명인허가일자업소명소재지(도로명)소재지(지번)건물내부면적업태명데이터기준일자
4251휴게음식점2023-09-06달콤왕가탕후루 신정네거리역점서울특별시 양천구 중앙로 269, 1층 (신정동)서울특별시 양천구 신정동 1190-6 1층37.42기타 휴게음식점2023-09-20
4252휴게음식점2023-09-07브이요거트(V!YOGURT) 목동점서울특별시 양천구 은행정로18길 11, 1층 (신정동)서울특별시 양천구 신정동 904-2 1층26.5기타 휴게음식점2023-09-20
4253휴게음식점2023-09-07플러스82 양천점서울특별시 양천구 목동남로4길 51, 1층 (신정동)서울특별시 양천구 신정동 207-1233.0커피숍2023-09-20
4254휴게음식점2023-09-07지에스25 목동역7단지점서울특별시 양천구 목동로 216, 1층 (목동)서울특별시 양천구 목동 808-313.0편의점2023-09-20
4255휴게음식점2023-09-07오랑사삭서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)서울특별시 양천구 목동 916 현대하이페리온 지하2층16.5패스트푸드2023-09-20
4256휴게음식점2023-09-11쥬스쿨(JUSCHOOL)서울특별시 양천구 지양로 74, 1층 2호 (신월동)서울특별시 양천구 신월동 961-533.0커피숍2023-09-20
4257휴게음식점2023-09-11더플랫로스터스(the flat roasters)서울특별시 양천구 신월로10길 5, 1층 (신월동)서울특별시 양천구 신월동 549-1010.8커피숍2023-09-20
4258휴게음식점2023-09-13오엑스피씨 목동역점서울특별시 양천구 신정중앙로 92, 지하1층 (신정동)서울특별시 양천구 신정동 902-216.0일반조리판매2023-09-20
4259휴게음식점2023-09-13영양사의 반찬가게서울특별시 양천구 목동동로 257, 지하2층 (목동, 현대하이페리온)서울특별시 양천구 목동 916 현대하이페리온0.0백화점2023-09-20
4260휴게음식점2023-09-14공차 양천구청점서울특별시 양천구 목동서로 383, 105호 (신정동)서울특별시 양천구 신정동 323-6 105호42.2커피숍2023-09-20