Overview

Dataset statistics

Number of variables7
Number of observations35
Missing cells15
Missing cells (%)6.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory61.8 B

Variable types

Numeric2
Text4
Categorical1

Dataset

Description인천광역시 중구 문화공간에 대한 정보입니다.
Author인천광역시
URLhttps://www.incheon.go.kr/data/DATA010201/view?docId=15074639

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 15 (42.9%) missing valuesMissing
연번 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-01-28 08:28:42.117282
Analysis finished2024-01-28 08:28:42.814418
Duration0.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T17:28:42.867060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.7
Q19.5
median18
Q326.5
95-th percentile33.3
Maximum35
Range34
Interquartile range (IQR)17

Descriptive statistics

Standard deviation10.246951
Coefficient of variation (CV)0.56927504
Kurtosis-1.2
Mean18
Median Absolute Deviation (MAD)9
Skewness0
Sum630
Variance105
MonotonicityStrictly increasing
2024-01-28T17:28:42.977235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
1 1
 
2.9%
2 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
26 1
 
2.9%
27 1
 
2.9%
28 1
 
2.9%
Other values (25) 25
71.4%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
35 1
2.9%
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
26 1
2.9%

사업장명
Text

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-01-28T17:28:43.159409image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length15
Mean length8.0857143
Min length2

Characters and Unicode

Total characters283
Distinct characters114
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)94.3%

Sample

1st row인천중구문화회관
2nd row인천학생교육문화회관
3rd row무의도아트센터플렛폼
4th row다락소극장
5th row씨사이드파크 하늘구름광장야외무대
ValueCountFrequency (%)
갤러리 3
 
5.6%
서담재 2
 
3.7%
인천학생교육문화회관 2
 
3.7%
채림아뜨리에 1
 
1.9%
선광미술관 1
 
1.9%
우현문갤러리 1
 
1.9%
프로젝트룸 1
 
1.9%
신포 1
 
1.9%
팟지 1
 
1.9%
스페이스 1
 
1.9%
Other values (40) 40
74.1%
2024-01-28T17:28:43.461640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19
 
6.7%
리 11
 
3.9%
스 9
 
3.2%
갤 9
 
3.2%
러 9
 
3.2%
장 8
 
2.8%
이 8
 
2.8%
관 8
 
2.8%
공 6
 
2.1%
화 6
 
2.1%
Other values (104) 190
67.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 261
92.2%
Space Separator 19
 
6.7%
Uppercase Letter 3
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 11
 
4.2%
스 9
 
3.4%
갤 9
 
3.4%
러 9
 
3.4%
장 8
 
3.1%
이 8
 
3.1%
관 8
 
3.1%
공 6
 
2.3%
화 6
 
2.3%
인 6
 
2.3%
Other values (100) 181
69.3%
Uppercase Letter
ValueCountFrequency (%)
V 1
33.3%
G 1
33.3%
C 1
33.3%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 261
92.2%
Common 19
 
6.7%
Latin 3
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 11
 
4.2%
스 9
 
3.4%
갤 9
 
3.4%
러 9
 
3.4%
장 8
 
3.1%
이 8
 
3.1%
관 8
 
3.1%
공 6
 
2.3%
화 6
 
2.3%
인 6
 
2.3%
Other values (100) 181
69.3%
Latin
ValueCountFrequency (%)
V 1
33.3%
G 1
33.3%
C 1
33.3%
Common
ValueCountFrequency (%)
19
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 261
92.2%
ASCII 22
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19
86.4%
V 1
 
4.5%
G 1
 
4.5%
C 1
 
4.5%
Hangul
ValueCountFrequency (%)
리 11
 
4.2%
스 9
 
3.4%
갤 9
 
3.4%
러 9
 
3.4%
장 8
 
3.1%
이 8
 
3.1%
관 8
 
3.1%
공 6
 
2.3%
화 6
 
2.3%
인 6
 
2.3%
Other values (100) 181
69.3%

도로명주소
Text

UNIQUE 

Distinct35
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-01-28T17:28:43.668676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length20.8
Min length14

Characters and Unicode

Total characters728
Distinct characters75
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

Unique35 ?
Unique (%)100.0%

Sample

1st row인천광역시 중구 축항대로296번길 81
2nd row인천광역시 중구 자유공원로 12
3rd row인천광역시 중구 용유동 하나개로 151-6
4th row인천광역시 중구 중앙동4가 1-1
5th row인천광역시 중구 영종동 하늘달빛로 2번길 6
ValueCountFrequency (%)
인천광역시 35
22.3%
중구 35
22.3%
운서동 4
 
2.5%
2층 3
 
1.9%
공항로 2
 
1.3%
자유공원로 2
 
1.3%
3층 2
 
1.3%
참외전로 2
 
1.3%
1-6 2
 
1.3%
15 2
 
1.3%
Other values (64) 68
43.3%
2024-01-28T17:28:44.014050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
122
16.8%
중 40
 
5.5%
인 37
 
5.1%
천 36
 
4.9%
광 35
 
4.8%
역 35
 
4.8%
시 35
 
4.8%
구 35
 
4.8%
1 32
 
4.4%
로 28
 
3.8%
Other values (65) 293
40.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 451
62.0%
Decimal Number 137
 
18.8%
Space Separator 122
 
16.8%
Dash Punctuation 17
 
2.3%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
중 40
 
8.9%
인 37
 
8.2%
천 36
 
8.0%
광 35
 
7.8%
역 35
 
7.8%
시 35
 
7.8%
구 35
 
7.8%
로 28
 
6.2%
동 16
 
3.5%
번 14
 
3.1%
Other values (52) 140
31.0%
Decimal Number
ValueCountFrequency (%)
1 32
23.4%
2 27
19.7%
6 15
10.9%
3 15
10.9%
5 14
10.2%
0 9
 
6.6%
9 7
 
5.1%
8 7
 
5.1%
4 7
 
5.1%
7 4
 
2.9%
Space Separator
ValueCountFrequency (%)
122
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 451
62.0%
Common 277
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
중 40
 
8.9%
인 37
 
8.2%
천 36
 
8.0%
광 35
 
7.8%
역 35
 
7.8%
시 35
 
7.8%
구 35
 
7.8%
로 28
 
6.2%
동 16
 
3.5%
번 14
 
3.1%
Other values (52) 140
31.0%
Common
ValueCountFrequency (%)
122
44.0%
1 32
 
11.6%
2 27
 
9.7%
- 17
 
6.1%
6 15
 
5.4%
3 15
 
5.4%
5 14
 
5.1%
0 9
 
3.2%
9 7
 
2.5%
8 7
 
2.5%
Other values (3) 12
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 451
62.0%
ASCII 277
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
122
44.0%
1 32
 
11.6%
2 27
 
9.7%
- 17
 
6.1%
6 15
 
5.4%
3 15
 
5.4%
5 14
 
5.1%
0 9
 
3.2%
9 7
 
2.5%
8 7
 
2.5%
Other values (3) 12
 
4.3%
Hangul
ValueCountFrequency (%)
중 40
 
8.9%
인 37
 
8.2%
천 36
 
8.0%
광 35
 
7.8%
역 35
 
7.8%
시 35
 
7.8%
구 35
 
7.8%
로 28
 
6.2%
동 16
 
3.5%
번 14
 
3.1%
Other values (52) 140
31.0%

전화번호
Text

MISSING 

Distinct19
Distinct (%)95.0%
Missing15
Missing (%)42.9%
Memory size412.0 B
2024-01-28T17:28:44.179769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.55
Min length9

Characters and Unicode

Total characters231
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

Unique18 ?
Unique (%)90.0%

Sample

1st row032-760-6426
2nd row032-760-3400
3rd row070-4419-1959
4th row032-456-2973
5th row032-760-7863
ValueCountFrequency (%)
032-773-3013 2
 
10.0%
032-773-1177 1
 
5.0%
032-760-6426 1
 
5.0%
032-617-7177 1
 
5.0%
032-772-9417 1
 
5.0%
032-766-8660 1
 
5.0%
070-4142-0897 1
 
5.0%
032-207-7752 1
 
5.0%
032-772-7502 1
 
5.0%
1544-8855 1
 
5.0%
Other values (9) 9
45.0%
2024-01-28T17:28:44.447550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37
16.0%
- 36
15.6%
7 34
14.7%
2 26
11.3%
3 24
10.4%
1 18
7.8%
4 16
6.9%
6 14
 
6.1%
5 11
 
4.8%
9 8
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 195
84.4%
Dash Punctuation 36
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 37
19.0%
7 34
17.4%
2 26
13.3%
3 24
12.3%
1 18
9.2%
4 16
8.2%
6 14
 
7.2%
5 11
 
5.6%
9 8
 
4.1%
8 7
 
3.6%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 231
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 37
16.0%
- 36
15.6%
7 34
14.7%
2 26
11.3%
3 24
10.4%
1 18
7.8%
4 16
6.9%
6 14
 
6.1%
5 11
 
4.8%
9 8
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 231
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 37
16.0%
- 36
15.6%
7 34
14.7%
2 26
11.3%
3 24
10.4%
1 18
7.8%
4 16
6.9%
6 14
 
6.1%
5 11
 
4.8%
9 8
 
3.5%

경도
Real number (ℝ)

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.469427
Minimum37.38552
Maximum37.493556
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size447.0 B
2024-01-28T17:28:44.563146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.38552
5-th percentile37.445383
Q137.470715
median37.472846
Q337.474738
95-th percentile37.490626
Maximum37.493556
Range0.1080356
Interquartile range (IQR)0.0040231

Descriptive statistics

Standard deviation0.018356547
Coefficient of variation (CV)0.00048990734
Kurtosis12.758584
Mean37.469427
Median Absolute Deviation (MAD)0.0020885
Skewness-3.0207089
Sum1311.4299
Variance0.00033696283
MonotonicityNot monotonic
2024-01-28T17:28:44.923253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
37.4757211 2
 
5.7%
37.4720468 1
 
2.9%
37.4742275 1
 
2.9%
37.4746741 1
 
2.9%
37.4722367 1
 
2.9%
37.4722324 1
 
2.9%
37.4500431 1
 
2.9%
37.4747747 1
 
2.9%
37.4727423 1
 
2.9%
37.4375305 1
 
2.9%
Other values (24) 24
68.6%
ValueCountFrequency (%)
37.38552 1
2.9%
37.4375305 1
2.9%
37.448749 1
2.9%
37.4500431 1
2.9%
37.4557648 1
2.9%
37.4598228 1
2.9%
37.469179 1
2.9%
37.4704023 1
2.9%
37.4706718 1
2.9%
37.4707579 1
2.9%
ValueCountFrequency (%)
37.4935556 1
2.9%
37.492619 1
2.9%
37.4897719 1
2.9%
37.4882052 1
2.9%
37.476378 1
2.9%
37.4757211 2
5.7%
37.4757147 1
2.9%
37.4747747 1
2.9%
37.4747012 1
2.9%
37.4746741 1
2.9%

위도
Text

Distinct34
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size412.0 B
2024-01-28T17:28:45.090536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.028571
Min length11

Characters and Unicode

Total characters386
Distinct characters12
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

Unique33 ?
Unique (%)94.3%

Sample

1st row126.6250312
2nd row126.6275085
3rd row126.4092234
4th row126.6245068
5th row126.5262623
ValueCountFrequency (%)
126.6275085 2
 
5.7%
126.6232341 1
 
2.9%
126.6240574 1
 
2.9%
126.6191307 1
 
2.9%
126.6208422 1
 
2.9%
126.6206503 1
 
2.9%
126.4898929 1
 
2.9%
126.6157493 1
 
2.9%
126.6175704 1
 
2.9%
126.4378815 1
 
2.9%
Other values (24) 24
68.6%
2024-01-28T17:28:45.377004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 82
21.2%
2 71
18.4%
1 60
15.5%
. 35
9.1%
5 26
 
6.7%
4 23
 
6.0%
7 21
 
5.4%
0 18
 
4.7%
3 18
 
4.7%
8 17
 
4.4%
Other values (2) 15
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 350
90.7%
Other Punctuation 36
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 82
23.4%
2 71
20.3%
1 60
17.1%
5 26
 
7.4%
4 23
 
6.6%
7 21
 
6.0%
0 18
 
5.1%
3 18
 
5.1%
8 17
 
4.9%
9 14
 
4.0%
Other Punctuation
ValueCountFrequency (%)
. 35
97.2%
, 1
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
Common 386
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
6 82
21.2%
2 71
18.4%
1 60
15.5%
. 35
9.1%
5 26
 
6.7%
4 23
 
6.0%
7 21
 
5.4%
0 18
 
4.7%
3 18
 
4.7%
8 17
 
4.4%
Other values (2) 15
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 386
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 82
21.2%
2 71
18.4%
1 60
15.5%
. 35
9.1%
5 26
 
6.7%
4 23
 
6.0%
7 21
 
5.4%
0 18
 
4.7%
3 18
 
4.7%
8 17
 
4.4%
Other values (2) 15
 
3.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size412.0 B
2021-07-20
35 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-07-20
2nd row2021-07-20
3rd row2021-07-20
4th row2021-07-20
5th row2021-07-20

Common Values

ValueCountFrequency (%)
2021-07-20 35
100.0%

Length

2024-01-28T17:28:45.500254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-28T17:28:45.597167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-07-20 35
100.0%

Interactions

2024-01-28T17:28:42.529562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:28:42.372582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:28:42.607444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-28T17:28:42.452659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-28T17:28:45.652877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업장명도로명주소전화번호경도위도
연번1.0000.9251.0000.8860.1090.944
사업장명0.9251.0001.0001.0000.7650.993
도로명주소1.0001.0001.0001.0001.0001.000
전화번호0.8861.0001.0001.0000.8661.000
경도0.1090.7651.0000.8661.0001.000
위도0.9440.9931.0001.0001.0001.000
2024-01-28T17:28:45.747333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번경도
연번1.0000.072
경도0.0721.000

Missing values

2024-01-28T17:28:42.691477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:28:42.779740image/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

연번사업장명도로명주소전화번호경도위도데이터기준일자
01인천중구문화회관인천광역시 중구 축항대로296번길 81032-760-642637.437531126.62503122021-07-20
12인천학생교육문화회관인천광역시 중구 자유공원로 12032-760-340037.475721126.62750852021-07-20
23무의도아트센터플렛폼인천광역시 중구 용유동 하나개로 151-6<NA>37.38552126.40922342021-07-20
34다락소극장인천광역시 중구 중앙동4가 1-1070-4419-195937.471364126.62450682021-07-20
45씨사이드파크 하늘구름광장야외무대인천광역시 중구 영종동 하늘달빛로 2번길 6032-456-297337.473773126.52626232021-07-20
56한중문화관 공연장인천광역시 중구 항동1가 1-2032-760-786337.473464126.61861382021-07-20
67월미테마파크 학무대인천광역시 중구 북성동 월미문화로 81<NA>37.471322126.59409832021-07-20
78인천학생교육문화회관 대공연장인천광역시 중구 인현동 5<NA>37.475715126.62732612021-07-20
89하늘문화센터 대강장인천광역시 중구 운서동 영종해안북로 1000-26032-456-294037.488205126.42579912021-07-20
910인천국제공항 야외공연장인천광역시 중구 공항로 2721577-260037.459823126.43788152021-07-20
연번사업장명도로명주소전화번호경도위도데이터기준일자
2526관동갤러리인천광역시 중구 신포로31번길 38032-766-866037.472742126.62153512021-07-20
2627이일이 갤러리인천광역시 중구 제물량로166번길 1-6 3층, 4층<NA>37.470402126.62323412021-07-20
2728가온갤러리인천광역시 중구 자유공원로 12 2층<NA>37.475721126.62750852021-07-20
2829한지그램갤러리 지우인천광역시 중구 차이나타운로 56-15<NA>37.474701126.61574932021-07-20
2930채림아뜨리에인천광역시 중구 운서로63번길 3-3 101호<NA>37.493556126.48989292021-07-20
3031갤러리지오인천광역시 중구 제물량로206번길 36-1<NA>37.472846126.62065032021-07-20
3132파랑관선인천광역시 중구 개항로53번길 24032-772-941737.469179126.62084222021-07-20
3233스페이스 아도인천광역시 중구 신포로23번길 80 중앙빌딩 2층070-8823-019137.473164126.61913072021-07-20
3334팟지인천광역시 중구 우현로39번길 15<NA>37.470758126.62405742021-07-20
3435선농원화랑인천광역시 중구 참외전로 148 서원상사<NA>37.473633126.63072682021-07-20