Overview

Dataset statistics

Number of variables9
Number of observations5214
Missing cells2
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory376.9 KiB
Average record size in memory74.0 B

Variable types

Numeric2
Text4
Categorical2
DateTime1

Dataset

Description서울특별시 다중이용업소 중 고시원 정보에 대한 데이터로 상호명, 업종명, 법정동 주소 등을 포함하여 제공합니다.2023년 1월 1일자 데이터입니다.
Author서울특별시
URLhttps://www.data.go.kr/data/15112717/fileData.do

Alerts

업종 has constant value ""Constant
연번 is highly overall correlated with 관할소방서High correlation
관할소방서 is highly overall correlated with 연번High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:49:21.395534
Analysis finished2023-12-12 13:49:23.193709
Duration1.8 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct5214
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2607.5
Minimum1
Maximum5214
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.0 KiB
2023-12-12T22:49:23.272868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile261.65
Q11304.25
median2607.5
Q33910.75
95-th percentile4953.35
Maximum5214
Range5213
Interquartile range (IQR)2606.5

Descriptive statistics

Standard deviation1505.2965
Coefficient of variation (CV)0.57729491
Kurtosis-1.2
Mean2607.5
Median Absolute Deviation (MAD)1303.5
Skewness0
Sum13595505
Variance2265917.5
MonotonicityStrictly increasing
2023-12-12T22:49:23.413613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
3465 1
 
< 0.1%
3483 1
 
< 0.1%
3482 1
 
< 0.1%
3481 1
 
< 0.1%
3480 1
 
< 0.1%
3479 1
 
< 0.1%
3478 1
 
< 0.1%
3477 1
 
< 0.1%
3476 1
 
< 0.1%
Other values (5204) 5204
99.8%
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 (%)
5214 1
< 0.1%
5213 1
< 0.1%
5212 1
< 0.1%
5211 1
< 0.1%
5210 1
< 0.1%
5209 1
< 0.1%
5208 1
< 0.1%
5207 1
< 0.1%
5206 1
< 0.1%
5205 1
< 0.1%

상호명
Text

Distinct4108
Distinct (%)78.8%
Missing0
Missing (%)0.0%
Memory size40.9 KiB
2023-12-12T22:49:23.713723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length6.0464135
Min length2

Characters and Unicode

Total characters31526
Distinct characters667
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3625 ?
Unique (%)69.5%

Sample

1st row마이홈리빙텔
2nd row심플하우스 원룸텔
3rd row서울고시원
4th row숭문산업
5th row로얄팰리스
ValueCountFrequency (%)
고시원 67
 
1.1%
원룸텔 52
 
0.9%
오픈하우스 44
 
0.8%
고시텔 35
 
0.6%
레지던스 34
 
0.6%
하우스 25
 
0.4%
심플하우스 24
 
0.4%
해피하우스 23
 
0.4%
코코리빙텔 20
 
0.3%
스테이 20
 
0.3%
Other values (4134) 5501
94.1%
2023-12-12T22:49:24.249830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 2186
 
6.9%
시 2140
 
6.8%
고 2110
 
6.7%
스 1833
 
5.8%
텔 1251
 
4.0%
우 997
 
3.2%
하 991
 
3.1%
리 648
 
2.1%
이 636
 
2.0%
632
 
2.0%
Other values (657) 18102
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28688
91.0%
Space Separator 632
 
2.0%
Uppercase Letter 560
 
1.8%
Open Punctuation 398
 
1.3%
Close Punctuation 396
 
1.3%
Decimal Number 390
 
1.2%
Other Punctuation 210
 
0.7%
Lowercase Letter 185
 
0.6%
Dash Punctuation 49
 
0.2%
Letter Number 9
 
< 0.1%
Other values (2) 9
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 2186
 
7.6%
시 2140
 
7.5%
고 2110
 
7.4%
스 1833
 
6.4%
텔 1251
 
4.4%
우 997
 
3.5%
하 991
 
3.5%
리 648
 
2.3%
이 636
 
2.2%
빌 537
 
1.9%
Other values (583) 15359
53.5%
Uppercase Letter
ValueCountFrequency (%)
S 61
 
10.9%
I 50
 
8.9%
J 40
 
7.1%
A 32
 
5.7%
H 31
 
5.5%
O 30
 
5.4%
K 26
 
4.6%
M 24
 
4.3%
E 24
 
4.3%
T 24
 
4.3%
Other values (15) 218
38.9%
Lowercase Letter
ValueCountFrequency (%)
e 46
24.9%
s 17
 
9.2%
a 16
 
8.6%
t 12
 
6.5%
i 12
 
6.5%
o 11
 
5.9%
l 10
 
5.4%
u 10
 
5.4%
h 9
 
4.9%
y 9
 
4.9%
Other values (13) 33
17.8%
Decimal Number
ValueCountFrequency (%)
2 110
28.2%
1 83
21.3%
3 65
16.7%
4 48
12.3%
5 20
 
5.1%
0 15
 
3.8%
9 15
 
3.8%
6 13
 
3.3%
7 11
 
2.8%
8 10
 
2.6%
Other Punctuation
ValueCountFrequency (%)
. 160
76.2%
, 36
 
17.1%
& 9
 
4.3%
@ 2
 
1.0%
! 2
 
1.0%
' 1
 
0.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
66.7%
Ⅲ 2
 
22.2%
Ⅰ 1
 
11.1%
Math Symbol
ValueCountFrequency (%)
~ 7
87.5%
+ 1
 
12.5%
Space Separator
ValueCountFrequency (%)
632
100.0%
Open Punctuation
ValueCountFrequency (%)
( 398
100.0%
Close Punctuation
ValueCountFrequency (%)
) 396
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28685
91.0%
Common 2084
 
6.6%
Latin 754
 
2.4%
Han 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 2186
 
7.6%
시 2140
 
7.5%
고 2110
 
7.4%
스 1833
 
6.4%
텔 1251
 
4.4%
우 997
 
3.5%
하 991
 
3.5%
리 648
 
2.3%
이 636
 
2.2%
빌 537
 
1.9%
Other values (580) 15356
53.5%
Latin
ValueCountFrequency (%)
S 61
 
8.1%
I 50
 
6.6%
e 46
 
6.1%
J 40
 
5.3%
A 32
 
4.2%
H 31
 
4.1%
O 30
 
4.0%
K 26
 
3.4%
M 24
 
3.2%
E 24
 
3.2%
Other values (41) 390
51.7%
Common
ValueCountFrequency (%)
632
30.3%
( 398
19.1%
) 396
19.0%
. 160
 
7.7%
2 110
 
5.3%
1 83
 
4.0%
3 65
 
3.1%
- 49
 
2.4%
4 48
 
2.3%
, 36
 
1.7%
Other values (13) 107
 
5.1%
Han
ValueCountFrequency (%)
家 1
33.3%
舊 1
33.3%
秀 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28683
91.0%
ASCII 2829
 
9.0%
Number Forms 9
 
< 0.1%
CJK 3
 
< 0.1%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 2186
 
7.6%
시 2140
 
7.5%
고 2110
 
7.4%
스 1833
 
6.4%
텔 1251
 
4.4%
우 997
 
3.5%
하 991
 
3.5%
리 648
 
2.3%
이 636
 
2.2%
빌 537
 
1.9%
Other values (578) 15354
53.5%
ASCII
ValueCountFrequency (%)
632
22.3%
( 398
14.1%
) 396
14.0%
. 160
 
5.7%
2 110
 
3.9%
1 83
 
2.9%
3 65
 
2.3%
S 61
 
2.2%
I 50
 
1.8%
- 49
 
1.7%
Other values (61) 825
29.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
66.7%
Ⅲ 2
 
22.2%
Ⅰ 1
 
11.1%
CJK
ValueCountFrequency (%)
家 1
33.3%
舊 1
33.3%
秀 1
33.3%
Compat Jamo
ValueCountFrequency (%)
ㄴ 1
50.0%
ㄱ 1
50.0%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size40.9 KiB
고시원업
5214 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고시원업 5214
100.0%

Length

2023-12-12T22:49:24.397453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:49:24.497490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고시원업 5214
100.0%

완비증명 발급일
Date

Distinct2431
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Memory size40.9 KiB
Minimum1992-10-13 00:00:00
Maximum2022-12-30 00:00:00
2023-12-12T22:49:24.599175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:24.771930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지번 주소
Text

Distinct4930
Distinct (%)94.6%
Missing0
Missing (%)0.0%
Memory size40.9 KiB
2023-12-12T22:49:25.118106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length19.771385
Min length14

Characters and Unicode

Total characters103088
Distinct characters195
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4680 ?
Unique (%)89.8%

Sample

1st row서울특별시 종로구 운니동 14
2nd row서울특별시 종로구 낙원동 143
3rd row서울특별시 종로구 명륜4가 188-12
4th row서울특별시 종로구 숭인동 165
5th row서울특별시 종로구 숭인동 181-25
ValueCountFrequency (%)
서울특별시 5214
25.0%
관악구 824
 
4.0%
신림동 619
 
3.0%
동작구 414
 
2.0%
강남구 350
 
1.7%
동대문구 309
 
1.5%
영등포구 296
 
1.4%
성북구 291
 
1.4%
송파구 221
 
1.1%
서대문구 194
 
0.9%
Other values (4905) 12124
58.1%
2023-12-12T22:49:25.642432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15642
 
15.2%
동 6199
 
6.0%
서 5861
 
5.7%
구 5514
 
5.3%
시 5227
 
5.1%
별 5214
 
5.1%
특 5214
 
5.1%
울 5214
 
5.1%
1 5054
 
4.9%
- 4828
 
4.7%
Other values (185) 39121
37.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 58761
57.0%
Decimal Number 23857
23.1%
Space Separator 15642
 
15.2%
Dash Punctuation 4828
 
4.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 6199
 
10.5%
서 5861
 
10.0%
구 5514
 
9.4%
시 5227
 
8.9%
별 5214
 
8.9%
특 5214
 
8.9%
울 5214
 
8.9%
신 861
 
1.5%
관 860
 
1.5%
악 824
 
1.4%
Other values (173) 17773
30.2%
Decimal Number
ValueCountFrequency (%)
1 5054
21.2%
2 3348
14.0%
3 2742
11.5%
5 2305
9.7%
4 2288
9.6%
6 2052
8.6%
0 1625
 
6.8%
7 1553
 
6.5%
9 1489
 
6.2%
8 1401
 
5.9%
Space Separator
ValueCountFrequency (%)
15642
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 4828
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 58761
57.0%
Common 44327
43.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 6199
 
10.5%
서 5861
 
10.0%
구 5514
 
9.4%
시 5227
 
8.9%
별 5214
 
8.9%
특 5214
 
8.9%
울 5214
 
8.9%
신 861
 
1.5%
관 860
 
1.5%
악 824
 
1.4%
Other values (173) 17773
30.2%
Common
ValueCountFrequency (%)
15642
35.3%
1 5054
 
11.4%
- 4828
 
10.9%
2 3348
 
7.6%
3 2742
 
6.2%
5 2305
 
5.2%
4 2288
 
5.2%
6 2052
 
4.6%
0 1625
 
3.7%
7 1553
 
3.5%
Other values (2) 2890
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 58761
57.0%
ASCII 44327
43.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15642
35.3%
1 5054
 
11.4%
- 4828
 
10.9%
2 3348
 
7.6%
3 2742
 
6.2%
5 2305
 
5.2%
4 2288
 
5.2%
6 2052
 
4.6%
0 1625
 
3.7%
7 1553
 
3.5%
Other values (2) 2890
 
6.5%
Hangul
ValueCountFrequency (%)
동 6199
 
10.5%
서 5861
 
10.0%
구 5514
 
9.4%
시 5227
 
8.9%
별 5214
 
8.9%
특 5214
 
8.9%
울 5214
 
8.9%
신 861
 
1.5%
관 860
 
1.5%
악 824
 
1.4%
Other values (173) 17773
30.2%

도로명 주소
Text

Distinct4926
Distinct (%)94.5%
Missing0
Missing (%)0.0%
Memory size40.9 KiB
2023-12-12T22:49:26.098846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length19.256041
Min length14

Characters and Unicode

Total characters100401
Distinct characters265
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4671 ?
Unique (%)89.6%

Sample

1st row서울특별시 종로구 율곡로6길 11
2nd row서울특별시 종로구 수표로 118
3rd row서울특별시 종로구 창경궁로 224
4th row서울특별시 종로구 종로 375
5th row서울특별시 종로구 종로65길 37
ValueCountFrequency (%)
서울특별시 5214
25.0%
관악구 824
 
4.0%
동작구 414
 
2.0%
강남구 350
 
1.7%
동대문구 309
 
1.5%
영등포구 296
 
1.4%
성북구 291
 
1.4%
송파구 221
 
1.1%
서대문구 194
 
0.9%
서초구 187
 
0.9%
Other values (3647) 12556
60.2%
2023-12-12T22:49:27.039834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15643
 
15.6%
서 5975
 
6.0%
구 5437
 
5.4%
시 5310
 
5.3%
울 5228
 
5.2%
특 5214
 
5.2%
별 5214
 
5.2%
로 5178
 
5.2%
1 4259
 
4.2%
길 3760
 
3.7%
Other values (255) 39183
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64266
64.0%
Decimal Number 19207
 
19.1%
Space Separator 15643
 
15.6%
Dash Punctuation 1285
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 5975
 
9.3%
구 5437
 
8.5%
시 5310
 
8.3%
울 5228
 
8.1%
특 5214
 
8.1%
별 5214
 
8.1%
로 5178
 
8.1%
길 3760
 
5.9%
동 1362
 
2.1%
대 1227
 
1.9%
Other values (243) 20361
31.7%
Decimal Number
ValueCountFrequency (%)
1 4259
22.2%
2 2851
14.8%
3 2275
11.8%
4 1885
9.8%
5 1609
 
8.4%
6 1530
 
8.0%
7 1375
 
7.2%
8 1219
 
6.3%
9 1119
 
5.8%
0 1085
 
5.6%
Space Separator
ValueCountFrequency (%)
15643
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64266
64.0%
Common 36135
36.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 5975
 
9.3%
구 5437
 
8.5%
시 5310
 
8.3%
울 5228
 
8.1%
특 5214
 
8.1%
별 5214
 
8.1%
로 5178
 
8.1%
길 3760
 
5.9%
동 1362
 
2.1%
대 1227
 
1.9%
Other values (243) 20361
31.7%
Common
ValueCountFrequency (%)
15643
43.3%
1 4259
 
11.8%
2 2851
 
7.9%
3 2275
 
6.3%
4 1885
 
5.2%
5 1609
 
4.5%
6 1530
 
4.2%
7 1375
 
3.8%
- 1285
 
3.6%
8 1219
 
3.4%
Other values (2) 2204
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64266
64.0%
ASCII 36135
36.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15643
43.3%
1 4259
 
11.8%
2 2851
 
7.9%
3 2275
 
6.3%
4 1885
 
5.2%
5 1609
 
4.5%
6 1530
 
4.2%
7 1375
 
3.8%
- 1285
 
3.6%
8 1219
 
3.4%
Other values (2) 2204
 
6.1%
Hangul
ValueCountFrequency (%)
서 5975
 
9.3%
구 5437
 
8.5%
시 5310
 
8.3%
울 5228
 
8.1%
특 5214
 
8.1%
별 5214
 
8.1%
로 5178
 
8.1%
길 3760
 
5.9%
동 1362
 
2.1%
대 1227
 
1.9%
Other values (243) 20361
31.7%

영업장 면적
Real number (ℝ)

Distinct4706
Distinct (%)90.3%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean400.25496
Minimum0
Maximum3085.18
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size46.0 KiB
2023-12-12T22:49:27.228025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile139.617
Q1254.685
median352.01
Q3480.0225
95-th percentile873.807
Maximum3085.18
Range3085.18
Interquartile range (IQR)225.3375

Descriptive statistics

Standard deviation226.3979
Coefficient of variation (CV)0.56563421
Kurtosis10.42853
Mean400.25496
Median Absolute Deviation (MAD)110.405
Skewness2.1281886
Sum2086128.8
Variance51256.008
MonotonicityNot monotonic
2023-12-12T22:49:27.393585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
330.0 8
 
0.2%
264.0 6
 
0.1%
237.0 5
 
0.1%
326.0 5
 
0.1%
297.0 5
 
0.1%
303.0 5
 
0.1%
214.2 5
 
0.1%
478.8 4
 
0.1%
396.0 4
 
0.1%
300.0 4
 
0.1%
Other values (4696) 5161
99.0%
ValueCountFrequency (%)
0.0 1
< 0.1%
29.24 1
< 0.1%
38.13 1
< 0.1%
49.5 1
< 0.1%
50.31 1
< 0.1%
50.38 1
< 0.1%
50.43 1
< 0.1%
51.6 1
< 0.1%
52.92 1
< 0.1%
54.45 1
< 0.1%
ValueCountFrequency (%)
3085.18 1
< 0.1%
2515.7 1
< 0.1%
2252.61 1
< 0.1%
2131.25 1
< 0.1%
2084.05 1
< 0.1%
2019.68 1
< 0.1%
1883.42 1
< 0.1%
1816.78 1
< 0.1%
1800.84 1
< 0.1%
1754.22 1
< 0.1%

영업장 층
Text

Distinct171
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size40.9 KiB
2023-12-12T22:49:27.600321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length28
Mean length7.1601458
Min length3

Characters and Unicode

Total characters37333
Distinct characters22
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

Unique83 ?
Unique (%)1.6%

Sample

1st row지상2,3
2nd row지상4,5
3rd row지상4
4th row지상5
5th row지하1/지상1,2,3
ValueCountFrequency (%)
지상2,3 480
 
9.2%
지상2,3,4 441
 
8.5%
지상3,4 402
 
7.7%
지상3 397
 
7.6%
지상2 361
 
6.9%
지상4 297
 
5.7%
지상1,2,3,4 282
 
5.4%
지하1/지상1,2,3,4 266
 
5.1%
지상1,2,3 204
 
3.9%
지상4,5 188
 
3.6%
Other values (162) 1898
36.4%
2023-12-12T22:49:28.029249image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 9195
24.6%
지 5910
15.8%
상 5156
13.8%
3 3762
10.1%
2 3284
 
8.8%
4 3048
 
8.2%
1 2400
 
6.4%
5 1472
 
3.9%
/ 801
 
2.1%
하 754
 
2.0%
Other values (12) 1551
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 15302
41.0%
Other Letter 12028
32.2%
Other Punctuation 9999
26.8%
Dash Punctuation 2
 
< 0.1%
Space Separator 2
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 3762
24.6%
2 3284
21.5%
4 3048
19.9%
1 2400
15.7%
5 1472
 
9.6%
6 682
 
4.5%
7 360
 
2.4%
8 189
 
1.2%
9 67
 
0.4%
0 38
 
0.2%
Other Letter
ValueCountFrequency (%)
지 5910
49.1%
상 5156
42.9%
하 754
 
6.3%
옥 102
 
0.8%
탑 102
 
0.8%
월 2
 
< 0.1%
일 2
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 9195
92.0%
/ 801
 
8.0%
. 3
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25305
67.8%
Hangul 12028
32.2%

Most frequent character per script

Common
ValueCountFrequency (%)
, 9195
36.3%
3 3762
14.9%
2 3284
 
13.0%
4 3048
 
12.0%
1 2400
 
9.5%
5 1472
 
5.8%
/ 801
 
3.2%
6 682
 
2.7%
7 360
 
1.4%
8 189
 
0.7%
Other values (5) 112
 
0.4%
Hangul
ValueCountFrequency (%)
지 5910
49.1%
상 5156
42.9%
하 754
 
6.3%
옥 102
 
0.8%
탑 102
 
0.8%
월 2
 
< 0.1%
일 2
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25305
67.8%
Hangul 12028
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 9195
36.3%
3 3762
14.9%
2 3284
 
13.0%
4 3048
 
12.0%
1 2400
 
9.5%
5 1472
 
5.8%
/ 801
 
3.2%
6 682
 
2.7%
7 360
 
1.4%
8 189
 
0.7%
Other values (5) 112
 
0.4%
Hangul
ValueCountFrequency (%)
지 5910
49.1%
상 5156
42.9%
하 754
 
6.3%
옥 102
 
0.8%
탑 102
 
0.8%
월 2
 
< 0.1%
일 2
 
< 0.1%

관할소방서
Categorical

HIGH CORRELATION 

Distinct25
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size40.9 KiB
관악소방서
824 
동작소방서
414 
강남소방서
350 
동대문소방서
309 
영등포소방서
 
296
Other values (20)
3021 

Length

Max length6
Median length5
Mean length5.1532413
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
관악소방서 824
15.8%
동작소방서 414
 
7.9%
강남소방서 350
 
6.7%
동대문소방서 309
 
5.9%
영등포소방서 296
 
5.7%
성북소방서 291
 
5.6%
송파소방서 221
 
4.2%
서대문소방서 194
 
3.7%
서초소방서 187
 
3.6%
광진소방서 183
 
3.5%
Other values (15) 1945
37.3%

Length

2023-12-12T22:49:28.182932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관악소방서 824
15.8%
동작소방서 414
 
7.9%
강남소방서 350
 
6.7%
동대문소방서 309
 
5.9%
영등포소방서 296
 
5.7%
성북소방서 291
 
5.6%
송파소방서 221
 
4.2%
서대문소방서 194
 
3.7%
서초소방서 187
 
3.6%
광진소방서 183
 
3.5%
Other values (15) 1945
37.3%

Interactions

2023-12-12T22:49:22.645535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:22.426723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:22.754881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:49:22.538726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:49:28.286916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번영업장 면적관할소방서
연번1.0000.2350.990
영업장 면적0.2351.0000.293
관할소방서0.9900.2931.000
2023-12-12T22:49:28.381985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번영업장 면적관할소방서
연번1.0000.0900.905
영업장 면적0.0901.0000.107
관할소방서0.9050.1071.000

Missing values

2023-12-12T22:49:22.933059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:49:23.126267image/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

연번상호명업종완비증명 발급일지번 주소도로명 주소영업장 면적영업장 층관할소방서
01마이홈리빙텔고시원업2022-10-06서울특별시 종로구 운니동 14서울특별시 종로구 율곡로6길 11246.76지상2,3종로소방서
12심플하우스 원룸텔고시원업2022-10-05서울특별시 종로구 낙원동 143서울특별시 종로구 수표로 118414.74지상4,5종로소방서
23서울고시원고시원업2022-07-11서울특별시 종로구 명륜4가 188-12서울특별시 종로구 창경궁로 224174.49지상4종로소방서
34숭문산업고시원업2022-07-01서울특별시 종로구 숭인동 165서울특별시 종로구 종로 375367.69지상5종로소방서
45로얄팰리스고시원업2022-01-17서울특별시 종로구 숭인동 181-25서울특별시 종로구 종로65길 37428.39지하1/지상1,2,3종로소방서
56레지던스Q고시원업2021-12-21서울특별시 종로구 관철동 18-3서울특별시 종로구 우정국로2길 41225.36지상4,5종로소방서
67노탐고시원업2021-11-02서울특별시 종로구 낙원동 6서울특별시 종로구 삼일대로 440446.91지상6,7,8종로소방서
78미르빌딩고시원업2021-10-07서울특별시 종로구 낙원동 15서울특별시 종로구 삼일대로 446-34384.28지상3,4종로소방서
89수안재고시원업2021-09-15서울특별시 종로구 명륜1가 101-1서울특별시 종로구 성균관로 34277.28지상3,4종로소방서
910예일고시원고시원업2021-01-22서울특별시 종로구 숭인동 177-2서울특별시 종로구 종로 377-3151.54지상2종로소방서
연번상호명업종완비증명 발급일지번 주소도로명 주소영업장 면적영업장 층관할소방서
52045205코지하우스고시원업2012-04-17서울특별시 금천구 독산동 1006-173서울특별시 금천구 범안로16길 8-12423.76지상1,2,3,4금천소방서
52055206동경빌딩 고시원고시원업2013-07-10서울특별시 금천구 독산동 330-41서울특별시 금천구 두산로10길 20910.26지상4,5,6,7금천소방서
52065207종인고시원고시원업2013-03-21서울특별시 금천구 독산동 901-6서울특별시 금천구 남부순환로 1426493.61지상5,6금천소방서
52075208한양고시원고시원업2013-04-01서울특별시 금천구 시흥동 114-9서울특별시 금천구 시흥대로63길 29167.5지상2금천소방서
52085209선진고시텔고시원업2013-06-19서울특별시 금천구 가산동 145-15서울특별시 금천구 남부순환로108길 27379.23지상4금천소방서
52095210엘린하우스고시원업2018-10-05서울특별시 금천구 가산동 146-2서울특별시 금천구 남부순환로 1298353.72지상2,3금천소방서
52105211금천고시원(현.승우)고시원업2010-05-11서울특별시 금천구 독산동 144-1서울특별시 금천구 시흥대로153길 17812.16지상2,3,4금천소방서
52115212남문고시원고시원업2007-10-24서울특별시 금천구 독산동 985-3서울특별시 금천구 시흥대로144길 27261.0지상3금천소방서
52125213해피씨티빌고시원고시원업2007-11-19서울특별시 금천구 가산동 145-26서울특별시 금천구 가산로 132-1189.29지상2금천소방서
52135214지성고시원고시원업2007-09-17서울특별시 금천구 시흥동 870-8서울특별시 금천구 시흥대로 270190.0지상4금천소방서