Overview

Dataset statistics

Number of variables5
Number of observations32
Missing cells13
Missing cells (%)8.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 KiB
Average record size in memory45.1 B

Variable types

Numeric1
Text3
Categorical1

Dataset

Description인천광역시 중구 헬스장에 대한 정보입니다.파일명 인천광역시 중구 헬스장내용 상호, 시설주소(도로명), 시설전화번호 등
Author인천광역시 중구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15074854&srcSe=7661IVAWM27C61E190

Alerts

데이터기준일자 has constant value ""Constant
시설전화번호 has 13 (40.6%) missing valuesMissing
순번 has unique valuesUnique
상호 has unique valuesUnique
시설주소(도로명) has unique valuesUnique

Reproduction

Analysis started2024-01-28 09:16:23.779235
Analysis finished2024-01-28 09:16:24.135200
Duration0.36 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.5
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size420.0 B
2024-01-28T18:16:24.490569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.55
Q18.75
median16.5
Q324.25
95-th percentile30.45
Maximum32
Range31
Interquartile range (IQR)15.5

Descriptive statistics

Standard deviation9.3808315
Coefficient of variation (CV)0.56853524
Kurtosis-1.2
Mean16.5
Median Absolute Deviation (MAD)8
Skewness0
Sum528
Variance88
MonotonicityStrictly increasing
2024-01-28T18:16:24.587023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
1 1
 
3.1%
18 1
 
3.1%
32 1
 
3.1%
31 1
 
3.1%
30 1
 
3.1%
29 1
 
3.1%
28 1
 
3.1%
27 1
 
3.1%
26 1
 
3.1%
25 1
 
3.1%
Other values (22) 22
68.8%
ValueCountFrequency (%)
1 1
3.1%
2 1
3.1%
3 1
3.1%
4 1
3.1%
5 1
3.1%
6 1
3.1%
7 1
3.1%
8 1
3.1%
9 1
3.1%
10 1
3.1%
ValueCountFrequency (%)
32 1
3.1%
31 1
3.1%
30 1
3.1%
29 1
3.1%
28 1
3.1%
27 1
3.1%
26 1
3.1%
25 1
3.1%
24 1
3.1%
23 1
3.1%

상호
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-28T18:16:24.760150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.34375
Min length2

Characters and Unicode

Total characters235
Distinct characters99
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row명성헬스타운
2nd row토크짐
3rd row(주)하프짐휘트니스
4th row마린휘트니스클럽
5th rowJD휘트니스짐
ValueCountFrequency (%)
클럽올림푸스 2
 
4.5%
피트니스 2
 
4.5%
명성헬스타운 1
 
2.3%
바디프로필gym 1
 
2.3%
센터 1
 
2.3%
혁짐 1
 
2.3%
lhu 1
 
2.3%
트레이닝센터 1
 
2.3%
gym201 1
 
2.3%
팀스카이 1
 
2.3%
Other values (32) 32
72.7%
2024-01-28T18:16:25.053819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 25
 
10.6%
트 15
 
6.4%
12
 
5.1%
니 9
 
3.8%
이 9
 
3.8%
짐 7
 
3.0%
피 6
 
2.6%
클 5
 
2.1%
럽 4
 
1.7%
터 4
 
1.7%
Other values (89) 139
59.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 201
85.5%
Uppercase Letter 14
 
6.0%
Space Separator 12
 
5.1%
Decimal Number 6
 
2.6%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 25
 
12.4%
트 15
 
7.5%
니 9
 
4.5%
이 9
 
4.5%
짐 7
 
3.5%
피 6
 
3.0%
클 5
 
2.5%
럽 4
 
2.0%
터 4
 
2.0%
휘 4
 
2.0%
Other values (74) 113
56.2%
Uppercase Letter
ValueCountFrequency (%)
L 2
14.3%
Y 2
14.3%
G 2
14.3%
M 2
14.3%
J 2
14.3%
D 2
14.3%
U 1
7.1%
H 1
7.1%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
2 2
33.3%
0 1
16.7%
7 1
16.7%
Space Separator
ValueCountFrequency (%)
12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 201
85.5%
Common 20
 
8.5%
Latin 14
 
6.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 25
 
12.4%
트 15
 
7.5%
니 9
 
4.5%
이 9
 
4.5%
짐 7
 
3.5%
피 6
 
3.0%
클 5
 
2.5%
럽 4
 
2.0%
터 4
 
2.0%
휘 4
 
2.0%
Other values (74) 113
56.2%
Latin
ValueCountFrequency (%)
L 2
14.3%
Y 2
14.3%
G 2
14.3%
M 2
14.3%
J 2
14.3%
D 2
14.3%
U 1
7.1%
H 1
7.1%
Common
ValueCountFrequency (%)
12
60.0%
1 2
 
10.0%
2 2
 
10.0%
0 1
 
5.0%
7 1
 
5.0%
( 1
 
5.0%
) 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 201
85.5%
ASCII 34
 
14.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 25
 
12.4%
트 15
 
7.5%
니 9
 
4.5%
이 9
 
4.5%
짐 7
 
3.5%
피 6
 
3.0%
클 5
 
2.5%
럽 4
 
2.0%
터 4
 
2.0%
휘 4
 
2.0%
Other values (74) 113
56.2%
ASCII
ValueCountFrequency (%)
12
35.3%
L 2
 
5.9%
Y 2
 
5.9%
G 2
 
5.9%
1 2
 
5.9%
M 2
 
5.9%
2 2
 
5.9%
J 2
 
5.9%
D 2
 
5.9%
0 1
 
2.9%
Other values (5) 5
14.7%

시설주소(도로명)
Text

UNIQUE 

Distinct32
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size388.0 B
2024-01-28T18:16:25.243403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length59
Median length41
Mean length34.9375
Min length24

Characters and Unicode

Total characters1118
Distinct characters116
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)100.0%

Sample

1st row인천광역시 중구 연안부두로33번길 36 (항동7가)
2nd row인천광역시 중구 신도시남로 28, 5층 (운서동, 영종에어포트2)
3rd row인천광역시 중구 홍예문로 90 (인현동, 뉴코아타운아파트)
4th row인천광역시 중구 서해대로 342 (신흥동3가)
5th row인천광역시 중구 신포로27번길 3 (중앙동4가, 불칸,페미니스트,신포관,제이디휘트니스)
ValueCountFrequency (%)
인천광역시 32
 
15.5%
중구 32
 
15.5%
운서동 16
 
7.7%
2층 5
 
2.4%
중산동 5
 
2.4%
운남동 4
 
1.9%
인현동 3
 
1.4%
3층 3
 
1.4%
영종해안남로321번길 3
 
1.4%
12 2
 
1.0%
Other values (92) 102
49.3%
2024-01-28T18:16:25.551041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
175
 
15.7%
중 39
 
3.5%
, 39
 
3.5%
1 38
 
3.4%
인 37
 
3.3%
시 37
 
3.3%
2 35
 
3.1%
천 34
 
3.0%
동 34
 
3.0%
( 32
 
2.9%
Other values (106) 618
55.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 627
56.1%
Decimal Number 202
 
18.1%
Space Separator 175
 
15.7%
Other Punctuation 39
 
3.5%
Open Punctuation 32
 
2.9%
Close Punctuation 32
 
2.9%
Uppercase Letter 6
 
0.5%
Math Symbol 3
 
0.3%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 39
 
6.2%
인 37
 
5.9%
시 37
 
5.9%
천 34
 
5.4%
동 34
 
5.4%
광 32
 
5.1%
역 32
 
5.1%
구 32
 
5.1%
로 32
 
5.1%
운 23
 
3.7%
Other values (87) 295
47.0%
Decimal Number
ValueCountFrequency (%)
1 38
18.8%
2 35
17.3%
0 31
15.3%
3 20
9.9%
7 18
8.9%
4 16
7.9%
6 14
 
6.9%
5 11
 
5.4%
9 10
 
5.0%
8 9
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
A 3
50.0%
B 2
33.3%
M 1
 
16.7%
Space Separator
ValueCountFrequency (%)
175
100.0%
Other Punctuation
ValueCountFrequency (%)
, 39
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 627
56.1%
Common 485
43.4%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 39
 
6.2%
인 37
 
5.9%
시 37
 
5.9%
천 34
 
5.4%
동 34
 
5.4%
광 32
 
5.1%
역 32
 
5.1%
구 32
 
5.1%
로 32
 
5.1%
운 23
 
3.7%
Other values (87) 295
47.0%
Common
ValueCountFrequency (%)
175
36.1%
, 39
 
8.0%
1 38
 
7.8%
2 35
 
7.2%
( 32
 
6.6%
) 32
 
6.6%
0 31
 
6.4%
3 20
 
4.1%
7 18
 
3.7%
4 16
 
3.3%
Other values (6) 49
 
10.1%
Latin
ValueCountFrequency (%)
A 3
50.0%
B 2
33.3%
M 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 627
56.1%
ASCII 491
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
175
35.6%
, 39
 
7.9%
1 38
 
7.7%
2 35
 
7.1%
( 32
 
6.5%
) 32
 
6.5%
0 31
 
6.3%
3 20
 
4.1%
7 18
 
3.7%
4 16
 
3.3%
Other values (9) 55
 
11.2%
Hangul
ValueCountFrequency (%)
중 39
 
6.2%
인 37
 
5.9%
시 37
 
5.9%
천 34
 
5.4%
동 34
 
5.4%
광 32
 
5.1%
역 32
 
5.1%
구 32
 
5.1%
로 32
 
5.1%
운 23
 
3.7%
Other values (87) 295
47.0%

시설전화번호
Text

MISSING 

Distinct19
Distinct (%)100.0%
Missing13
Missing (%)40.6%
Memory size388.0 B
2024-01-28T18:16:25.710711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters228
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)100.0%

Sample

1st row032-887-1128
2nd row032-752-5000
3rd row032-777-6969
4th row032-884-7989
5th row032-764-9011
ValueCountFrequency (%)
032-887-1128 1
 
5.3%
032-745-2222 1
 
5.3%
032-751-4860 1
 
5.3%
032-746-9668 1
 
5.3%
032-729-2110 1
 
5.3%
032-751-9682 1
 
5.3%
032-746-2010 1
 
5.3%
032-751-0069 1
 
5.3%
032-888-8100 1
 
5.3%
032-752-0199 1
 
5.3%
Other values (9) 9
47.4%
2024-01-28T18:16:25.964897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 38
16.7%
- 38
16.7%
2 33
14.5%
7 22
9.6%
3 20
8.8%
1 16
7.0%
9 15
 
6.6%
8 14
 
6.1%
5 12
 
5.3%
6 11
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 190
83.3%
Dash Punctuation 38
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 38
20.0%
2 33
17.4%
7 22
11.6%
3 20
10.5%
1 16
8.4%
9 15
 
7.9%
8 14
 
7.4%
5 12
 
6.3%
6 11
 
5.8%
4 9
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 228
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 38
16.7%
- 38
16.7%
2 33
14.5%
7 22
9.6%
3 20
8.8%
1 16
7.0%
9 15
 
6.6%
8 14
 
6.1%
5 12
 
5.3%
6 11
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 228
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 38
16.7%
- 38
16.7%
2 33
14.5%
7 22
9.6%
3 20
8.8%
1 16
7.0%
9 15
 
6.6%
8 14
 
6.1%
5 12
 
5.3%
6 11
 
4.8%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size388.0 B
2023-09-20
32 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-09-20
2nd row2023-09-20
3rd row2023-09-20
4th row2023-09-20
5th row2023-09-20

Common Values

ValueCountFrequency (%)
2023-09-20 32
100.0%

Length

2024-01-28T18:16:26.077827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T18:16:26.153278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-09-20 32
100.0%

Interactions

2024-01-28T18:16:23.939330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T18:16:26.202132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번상호시설주소(도로명)시설전화번호
순번1.0001.0001.0001.000
상호1.0001.0001.0001.000
시설주소(도로명)1.0001.0001.0001.000
시설전화번호1.0001.0001.0001.000

Missing values

2024-01-28T18:16:24.032851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T18:16:24.107044image/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

순번상호시설주소(도로명)시설전화번호데이터기준일자
01명성헬스타운인천광역시 중구 연안부두로33번길 36 (항동7가)032-887-11282023-09-20
12토크짐인천광역시 중구 신도시남로 28, 5층 (운서동, 영종에어포트2)032-752-50002023-09-20
23(주)하프짐휘트니스인천광역시 중구 홍예문로 90 (인현동, 뉴코아타운아파트)032-777-69692023-09-20
34마린휘트니스클럽인천광역시 중구 서해대로 342 (신흥동3가)032-884-79892023-09-20
45JD휘트니스짐인천광역시 중구 신포로27번길 3 (중앙동4가, 불칸,페미니스트,신포관,제이디휘트니스)032-764-90112023-09-20
56웨스트타워 클럽올림푸스인천광역시 중구 영종해안남로321번길 190 (운서동)032-745-12342023-09-20
67이유휘트니스인천광역시 중구 하늘별빛로 59, 3층 (중산동, 비젼프라자)032-752-80502023-09-20
78크로스핏영종인천광역시 중구 신도시남로142번길 15, B01호 (운서동)<NA>2023-09-20
89JDL 마스터짐인천광역시 중구 신도시남로149번길 7, 에어릴렉스호텔 지하 1층 (운서동)032-746-99792023-09-20
910머슬피플인천광역시 중구 신도시남로141번길 5-8, 천지인프라자 6층 602호 (운서동)032-751-00092023-09-20
순번상호시설주소(도로명)시설전화번호데이터기준일자
2223예스비피트니스인천광역시 중구 햇내로28번길 10, 더예스클라우드 A동 2층 A204, A205호 (운서동)<NA>2023-09-20
2324바디프로필GYM인천광역시 중구 관창로 2, 2,3층 (운남동)<NA>2023-09-20
2425주식회사파라다이스세가사미인천광역시 중구 영종해안남로321번길 186 (운서동)032-729-21102023-09-20
2526더베럴 피트니스인천광역시 중구 하늘중앙로225번길 3, 영종M타워 7층 701호 (중산동)<NA>2023-09-20
2627토크스퀘어인천광역시 중구 영종대로 94, 두림타워 901~904호 (운서동)<NA>2023-09-20
2728팀혁짐인천광역시 중구 하늘별빛로65번길 8-21, 303~304호 (중산동)032-746-96682023-09-20
2829갱스터짐인천광역시 중구 하늘별빛로65번길 21, 701~704호 (중산동)<NA>2023-09-20
2930머슬카페피트니스인천광역시 중구 영종대로 184, 영종예스타워복합상영관 602호 (운서동)<NA>2023-09-20
3031피트니스 127인천광역시 중구 흰바위로 262, 럭키프라자 7층 701,702호 (운남동)032-751-12702023-09-20
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