Overview

Dataset statistics

Number of variables4
Number of observations243
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory33.5 B

Variable types

Numeric1
Text2
Categorical1

Dataset

Description서대문구 고시원 정보에 대한 데이터로 상호명, 주소를 포함하여 제공합니다. 2020년 1월 1일자 데이터입니다.
Author서울특별시 서대문구
URLhttps://www.data.go.kr/data/15106927/fileData.do

Alerts

업종 has constant value ""Constant
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-19 07:00:12.793008
Analysis finished2024-04-19 07:00:13.152515
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct243
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122
Minimum1
Maximum243
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2024-04-19T16:00:13.221341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile13.1
Q161.5
median122
Q3182.5
95-th percentile230.9
Maximum243
Range242
Interquartile range (IQR)121

Descriptive statistics

Standard deviation70.292247
Coefficient of variation (CV)0.57616596
Kurtosis-1.2
Mean122
Median Absolute Deviation (MAD)61
Skewness0
Sum29646
Variance4941
MonotonicityStrictly increasing
2024-04-19T16:00:13.352210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.4%
154 1
 
0.4%
156 1
 
0.4%
157 1
 
0.4%
158 1
 
0.4%
159 1
 
0.4%
160 1
 
0.4%
161 1
 
0.4%
162 1
 
0.4%
163 1
 
0.4%
Other values (233) 233
95.9%
ValueCountFrequency (%)
1 1
0.4%
2 1
0.4%
3 1
0.4%
4 1
0.4%
5 1
0.4%
6 1
0.4%
7 1
0.4%
8 1
0.4%
9 1
0.4%
10 1
0.4%
ValueCountFrequency (%)
243 1
0.4%
242 1
0.4%
241 1
0.4%
240 1
0.4%
239 1
0.4%
238 1
0.4%
237 1
0.4%
236 1
0.4%
235 1
0.4%
234 1
0.4%

상호
Text

Distinct236
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-19T16:00:13.584905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length6.5679012
Min length2

Characters and Unicode

Total characters1596
Distinct characters248
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique230 ?
Unique (%)94.7%

Sample

1st row쉼터고시텔
2nd row대성고시원
3rd row신형고시원
4th row소호리빙텔(2층)
5th row웰빙텔
ValueCountFrequency (%)
코코리빙텔 3
 
1.1%
웰빙텔 3
 
1.1%
풀하우스 2
 
0.8%
휴레지던스 2
 
0.8%
이화고시텔 2
 
0.8%
엘리트고시원 2
 
0.8%
3층 2
 
0.8%
멀티하우스연대점 2
 
0.8%
탑고시텔 2
 
0.8%
원룸텔 2
 
0.8%
Other values (242) 243
91.7%
2024-04-19T16:00:14.246711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 113
 
7.1%
텔 90
 
5.6%
시 80
 
5.0%
고 78
 
4.9%
원 71
 
4.4%
하 65
 
4.1%
우 55
 
3.4%
리 46
 
2.9%
( 42
 
2.6%
) 42
 
2.6%
Other values (238) 914
57.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1396
87.5%
Open Punctuation 42
 
2.6%
Close Punctuation 42
 
2.6%
Decimal Number 40
 
2.5%
Uppercase Letter 27
 
1.7%
Space Separator 22
 
1.4%
Other Punctuation 15
 
0.9%
Lowercase Letter 6
 
0.4%
Dash Punctuation 3
 
0.2%
Math Symbol 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 113
 
8.1%
텔 90
 
6.4%
시 80
 
5.7%
고 78
 
5.6%
원 71
 
5.1%
하 65
 
4.7%
우 55
 
3.9%
리 46
 
3.3%
빙 40
 
2.9%
이 37
 
2.7%
Other values (201) 721
51.6%
Uppercase Letter
ValueCountFrequency (%)
I 4
14.8%
J 3
11.1%
H 3
11.1%
Y 2
 
7.4%
A 2
 
7.4%
P 2
 
7.4%
S 2
 
7.4%
T 1
 
3.7%
W 1
 
3.7%
R 1
 
3.7%
Other values (6) 6
22.2%
Decimal Number
ValueCountFrequency (%)
3 8
20.0%
2 7
17.5%
4 7
17.5%
6 5
12.5%
5 5
12.5%
1 4
10.0%
0 2
 
5.0%
8 1
 
2.5%
9 1
 
2.5%
Other Punctuation
ValueCountFrequency (%)
. 8
53.3%
, 4
26.7%
! 2
 
13.3%
& 1
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
a 4
66.7%
h 2
33.3%
Math Symbol
ValueCountFrequency (%)
~ 2
66.7%
+ 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 42
100.0%
Close Punctuation
ValueCountFrequency (%)
) 42
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1396
87.5%
Common 167
 
10.5%
Latin 33
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 113
 
8.1%
텔 90
 
6.4%
시 80
 
5.7%
고 78
 
5.6%
원 71
 
5.1%
하 65
 
4.7%
우 55
 
3.9%
리 46
 
3.3%
빙 40
 
2.9%
이 37
 
2.7%
Other values (201) 721
51.6%
Common
ValueCountFrequency (%)
( 42
25.1%
) 42
25.1%
22
13.2%
3 8
 
4.8%
. 8
 
4.8%
2 7
 
4.2%
4 7
 
4.2%
6 5
 
3.0%
5 5
 
3.0%
1 4
 
2.4%
Other values (9) 17
10.2%
Latin
ValueCountFrequency (%)
a 4
12.1%
I 4
12.1%
J 3
 
9.1%
H 3
 
9.1%
Y 2
 
6.1%
A 2
 
6.1%
h 2
 
6.1%
P 2
 
6.1%
S 2
 
6.1%
T 1
 
3.0%
Other values (8) 8
24.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1396
87.5%
ASCII 200
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 113
 
8.1%
텔 90
 
6.4%
시 80
 
5.7%
고 78
 
5.6%
원 71
 
5.1%
하 65
 
4.7%
우 55
 
3.9%
리 46
 
3.3%
빙 40
 
2.9%
이 37
 
2.7%
Other values (201) 721
51.6%
ASCII
ValueCountFrequency (%)
( 42
21.0%
) 42
21.0%
22
11.0%
3 8
 
4.0%
. 8
 
4.0%
2 7
 
3.5%
4 7
 
3.5%
6 5
 
2.5%
5 5
 
2.5%
a 4
 
2.0%
Other values (27) 50
25.0%

업종
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
고시원업
243 

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 243
100.0%

Length

2024-04-19T16:00:14.386819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-19T16:00:14.479532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
고시원업 243
100.0%

법정동 주소
Text

Distinct226
Distinct (%)93.0%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
2024-04-19T16:00:14.807484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length20.168724
Min length18

Characters and Unicode

Total characters4901
Distinct characters43
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

Unique215 ?
Unique (%)88.5%

Sample

1st row서울특별시 서대문구 북아현동 220-14
2nd row서울특별시 서대문구 북아현동 3-130
3rd row서울특별시 서대문구 창천동 97-82
4th row서울특별시 서대문구 북아현동 752-1
5th row서울특별시 서대문구 창천동 52-134
ValueCountFrequency (%)
서울특별시 243
25.0%
서대문구 243
25.0%
창천동 89
 
9.2%
연희동 41
 
4.2%
대현동 33
 
3.4%
남가좌동 17
 
1.7%
홍은동 13
 
1.3%
북아현동 10
 
1.0%
북가좌동 9
 
0.9%
충정로3가 6
 
0.6%
Other values (232) 268
27.6%
2024-04-19T16:00:15.286874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
729
14.9%
서 486
 
9.9%
대 279
 
5.7%
특 243
 
5.0%
별 243
 
5.0%
시 243
 
5.0%
문 243
 
5.0%
구 243
 
5.0%
울 243
 
5.0%
동 231
 
4.7%
Other values (33) 1718
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2962
60.4%
Decimal Number 989
 
20.2%
Space Separator 729
 
14.9%
Dash Punctuation 221
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 486
16.4%
대 279
9.4%
특 243
8.2%
별 243
8.2%
시 243
8.2%
문 243
8.2%
구 243
8.2%
울 243
8.2%
동 231
7.8%
천 96
 
3.2%
Other values (21) 412
13.9%
Decimal Number
ValueCountFrequency (%)
1 180
18.2%
3 153
15.5%
2 143
14.5%
4 109
11.0%
5 101
10.2%
7 73
7.4%
0 65
 
6.6%
6 62
 
6.3%
9 58
 
5.9%
8 45
 
4.6%
Space Separator
ValueCountFrequency (%)
729
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2962
60.4%
Common 1939
39.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 486
16.4%
대 279
9.4%
특 243
8.2%
별 243
8.2%
시 243
8.2%
문 243
8.2%
구 243
8.2%
울 243
8.2%
동 231
7.8%
천 96
 
3.2%
Other values (21) 412
13.9%
Common
ValueCountFrequency (%)
729
37.6%
- 221
 
11.4%
1 180
 
9.3%
3 153
 
7.9%
2 143
 
7.4%
4 109
 
5.6%
5 101
 
5.2%
7 73
 
3.8%
0 65
 
3.4%
6 62
 
3.2%
Other values (2) 103
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2962
60.4%
ASCII 1939
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
729
37.6%
- 221
 
11.4%
1 180
 
9.3%
3 153
 
7.9%
2 143
 
7.4%
4 109
 
5.6%
5 101
 
5.2%
7 73
 
3.8%
0 65
 
3.4%
6 62
 
3.2%
Other values (2) 103
 
5.3%
Hangul
ValueCountFrequency (%)
서 486
16.4%
대 279
9.4%
특 243
8.2%
별 243
8.2%
시 243
8.2%
문 243
8.2%
구 243
8.2%
울 243
8.2%
동 231
7.8%
천 96
 
3.2%
Other values (21) 412
13.9%

Interactions

2024-04-19T16:00:12.954721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-04-19T16:00:13.048491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-19T16:00:13.123575image/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

연번상호업종법정동 주소
01쉼터고시텔고시원업서울특별시 서대문구 북아현동 220-14
12대성고시원고시원업서울특별시 서대문구 북아현동 3-130
23신형고시원고시원업서울특별시 서대문구 창천동 97-82
34소호리빙텔(2층)고시원업서울특별시 서대문구 북아현동 752-1
45웰빙텔고시원업서울특별시 서대문구 창천동 52-134
56네오스페이스고시원업서울특별시 서대문구 연희동 136-29
67코코레지던스(이대점)고시원업서울특별시 서대문구 대현동 110-25
78청호고시원고시원업서울특별시 서대문구 대현동 110-42
89더 하우스고시원업서울특별시 서대문구 북가좌동 291-2
910가나고시원고시원업서울특별시 서대문구 충정로2가 184-13
연번상호업종법정동 주소
233234인중고시원고시원업서울특별시 서대문구 남가좌동 3-2
234235소호리빙텔(연대점)고시원업서울특별시 서대문구 창천동 57-13
235236심플하우스(창천)고시원업서울특별시 서대문구 창천동 53-91
236237금용주택고시원업서울특별시 서대문구 창천동 53-78
237238한흥빌딩(신촌리빙텔)고시원업서울특별시 서대문구 창천동 53-34
238239신촌원룸텔(구.선정고시텔)고시원업서울특별시 서대문구 창천동 52-139
239240신촌고시원고시원업서울특별시 서대문구 창천동 52-107
240241해피하우스고시원업서울특별시 서대문구 대현동 101-11
241242리빙고시텔고시원업서울특별시 서대문구 남가좌동 342-29
242243에이플러스리빙텔고시원업서울특별시 서대문구 북아현동 827