Overview

Dataset statistics

Number of variables8
Number of observations39
Missing cells4
Missing cells (%)1.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory69.4 B

Variable types

Numeric2
Text4
Categorical2

Dataset

Description인천광역시 군, 구별,실내체육관, 종합경기장, 테니스장, 수영장, 축구장의 (연번 명칭 주소 면적(제곱미터) 주요시설 좌석수 (수용인원) 준공년월 관리주체) 현황을 제공합니다.<br/>
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15055873&srcSe=7661IVAWM27C61E190

Alerts

좌석수 (수용인원) is highly overall correlated with 관리주체High correlation
관리주체 is highly overall correlated with 좌석수 (수용인원)High correlation
면적(제곱미터) has 1 (2.6%) missing valuesMissing
주요시설 has 1 (2.6%) missing valuesMissing
좌석수 (수용인원) has 2 (5.1%) missing valuesMissing
연번 has unique valuesUnique
명칭 has unique valuesUnique

Reproduction

Analysis started2024-03-18 03:12:06.189440
Analysis finished2024-03-18 03:12:08.811166
Duration2.62 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20
Minimum1
Maximum39
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-03-18T12:12:08.868206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.9
Q110.5
median20
Q329.5
95-th percentile37.1
Maximum39
Range38
Interquartile range (IQR)19

Descriptive statistics

Standard deviation11.401754
Coefficient of variation (CV)0.57008771
Kurtosis-1.2
Mean20
Median Absolute Deviation (MAD)10
Skewness0
Sum780
Variance130
MonotonicityStrictly increasing
2024-03-18T12:12:08.972981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
1 1
 
2.6%
2 1
 
2.6%
23 1
 
2.6%
24 1
 
2.6%
25 1
 
2.6%
26 1
 
2.6%
27 1
 
2.6%
28 1
 
2.6%
29 1
 
2.6%
30 1
 
2.6%
Other values (29) 29
74.4%
ValueCountFrequency (%)
1 1
2.6%
2 1
2.6%
3 1
2.6%
4 1
2.6%
5 1
2.6%
6 1
2.6%
7 1
2.6%
8 1
2.6%
9 1
2.6%
10 1
2.6%
ValueCountFrequency (%)
39 1
2.6%
38 1
2.6%
37 1
2.6%
36 1
2.6%
35 1
2.6%
34 1
2.6%
33 1
2.6%
32 1
2.6%
31 1
2.6%
30 1
2.6%

명칭
Text

UNIQUE 

Distinct39
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-03-18T12:12:09.162508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.4615385
Min length5

Characters and Unicode

Total characters291
Distinct characters111
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)100.0%

Sample

1st row문학경기장
2nd row문학야구장
3rd row삼산월드체육관
4th row계산국민체육센터
5th row도원체육관
ValueCountFrequency (%)
문학경기장 1
 
2.6%
열우물테니스경기장 1
 
2.6%
강화고인돌체육관 1
 
2.6%
아시아드bmx경기장 1
 
2.6%
계양체육관 1
 
2.6%
계양아시아드양궁장 1
 
2.6%
계양테니스장 1
 
2.6%
남동체육관 1
 
2.6%
남동아시아드럭비경기장 1
 
2.6%
열우물스쿼시경기장 1
 
2.6%
Other values (29) 29
74.4%
2024-03-18T12:12:09.551450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 27
 
9.3%
기 15
 
5.2%
경 13
 
4.5%
체 11
 
3.8%
육 11
 
3.8%
관 10
 
3.4%
아 8
 
2.7%
학 7
 
2.4%
국 6
 
2.1%
드 6
 
2.1%
Other values (101) 177
60.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 280
96.2%
Uppercase Letter 9
 
3.1%
Open Punctuation 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 27
 
9.6%
기 15
 
5.4%
경 13
 
4.6%
체 11
 
3.9%
육 11
 
3.9%
관 10
 
3.6%
아 8
 
2.9%
학 7
 
2.5%
국 6
 
2.1%
드 6
 
2.1%
Other values (93) 166
59.3%
Uppercase Letter
ValueCountFrequency (%)
G 2
22.2%
N 2
22.2%
L 2
22.2%
B 1
11.1%
M 1
11.1%
X 1
11.1%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 280
96.2%
Latin 9
 
3.1%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 27
 
9.6%
기 15
 
5.4%
경 13
 
4.6%
체 11
 
3.9%
육 11
 
3.9%
관 10
 
3.6%
아 8
 
2.9%
학 7
 
2.5%
국 6
 
2.1%
드 6
 
2.1%
Other values (93) 166
59.3%
Latin
ValueCountFrequency (%)
G 2
22.2%
N 2
22.2%
L 2
22.2%
B 1
11.1%
M 1
11.1%
X 1
11.1%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 280
96.2%
ASCII 11
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 27
 
9.6%
기 15
 
5.4%
경 13
 
4.6%
체 11
 
3.9%
육 11
 
3.9%
관 10
 
3.6%
아 8
 
2.9%
학 7
 
2.5%
국 6
 
2.1%
드 6
 
2.1%
Other values (93) 166
59.3%
ASCII
ValueCountFrequency (%)
G 2
18.2%
N 2
18.2%
L 2
18.2%
B 1
9.1%
M 1
9.1%
X 1
9.1%
( 1
9.1%
) 1
9.1%

주소
Text

Distinct23
Distinct (%)59.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2024-03-18T12:12:09.755824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length18.076923
Min length15

Characters and Unicode

Total characters705
Distinct characters71
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)35.9%

Sample

1st row인천광역시 남구 매소홀로 618
2nd row인천광역시 남구 매소홀로 618
3rd row인천광역시 부평구 체육관로 60
4th row인천광역시 계양구 주부토로 580
5th row인천광역시 중구 샛골로41번길 10
ValueCountFrequency (%)
인천광역시 39
24.5%
연수구 11
 
6.9%
남구 7
 
4.4%
경원대로 5
 
3.1%
526 5
 
3.1%
계양구 5
 
3.1%
봉오대로 4
 
2.5%
855 4
 
2.5%
남동구 4
 
2.5%
서구 3
 
1.9%
Other values (46) 72
45.3%
2024-03-18T12:12:10.046693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
17.0%
인 41
 
5.8%
천 41
 
5.8%
광 39
 
5.5%
역 39
 
5.5%
시 39
 
5.5%
구 38
 
5.4%
로 38
 
5.4%
6 20
 
2.8%
5 20
 
2.8%
Other values (61) 270
38.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 462
65.5%
Decimal Number 123
 
17.4%
Space Separator 120
 
17.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 41
 
8.9%
천 41
 
8.9%
광 39
 
8.4%
역 39
 
8.4%
시 39
 
8.4%
구 38
 
8.2%
로 38
 
8.2%
대 16
 
3.5%
수 15
 
3.2%
연 11
 
2.4%
Other values (50) 145
31.4%
Decimal Number
ValueCountFrequency (%)
6 20
16.3%
5 20
16.3%
1 17
13.8%
2 14
11.4%
0 14
11.4%
4 11
8.9%
8 10
8.1%
9 7
 
5.7%
3 7
 
5.7%
7 3
 
2.4%
Space Separator
ValueCountFrequency (%)
120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 462
65.5%
Common 243
34.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 41
 
8.9%
천 41
 
8.9%
광 39
 
8.4%
역 39
 
8.4%
시 39
 
8.4%
구 38
 
8.2%
로 38
 
8.2%
대 16
 
3.5%
수 15
 
3.2%
연 11
 
2.4%
Other values (50) 145
31.4%
Common
ValueCountFrequency (%)
120
49.4%
6 20
 
8.2%
5 20
 
8.2%
1 17
 
7.0%
2 14
 
5.8%
0 14
 
5.8%
4 11
 
4.5%
8 10
 
4.1%
9 7
 
2.9%
3 7
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 462
65.5%
ASCII 243
34.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
49.4%
6 20
 
8.2%
5 20
 
8.2%
1 17
 
7.0%
2 14
 
5.8%
0 14
 
5.8%
4 11
 
4.5%
8 10
 
4.1%
9 7
 
2.9%
3 7
 
2.9%
Hangul
ValueCountFrequency (%)
인 41
 
8.9%
천 41
 
8.9%
광 39
 
8.4%
역 39
 
8.4%
시 39
 
8.4%
구 38
 
8.2%
로 38
 
8.2%
대 16
 
3.5%
수 15
 
3.2%
연 11
 
2.4%
Other values (50) 145
31.4%

면적(제곱미터)
Text

MISSING 

Distinct36
Distinct (%)94.7%
Missing1
Missing (%)2.6%
Memory size444.0 B
2024-03-18T12:12:10.207477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length18.5
Mean length13.973684
Min length4

Characters and Unicode

Total characters531
Distinct characters21
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)89.5%

Sample

1st row95226(지하1층 지상5층)
2nd row41901(지하3층 지상4층)
3rd row43029(지하2층 지상3층)
4th row4814(지하1층 지상3층)
5th row1639(지상3층)
ValueCountFrequency (%)
지상3층 17
25.0%
지상2층 5
 
7.4%
지상4층 3
 
4.4%
113619.95(지하 2
 
2.9%
9707 2
 
2.9%
2층 2
 
2.9%
지상5층 2
 
2.9%
6909(지하1층 1
 
1.5%
95226(지하1층 1
 
1.5%
7175(지상1층 1
 
1.5%
Other values (32) 32
47.1%
2024-03-18T12:12:10.474881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 61
11.5%
층 61
11.5%
1 47
 
8.9%
상 34
 
6.4%
3 34
 
6.4%
2 34
 
6.4%
( 33
 
6.2%
) 33
 
6.2%
30
 
5.6%
9 28
 
5.3%
Other values (11) 136
25.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 242
45.6%
Other Letter 186
35.0%
Open Punctuation 33
 
6.2%
Close Punctuation 33
 
6.2%
Space Separator 30
 
5.6%
Other Punctuation 7
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 47
19.4%
3 34
14.0%
2 34
14.0%
9 28
11.6%
4 19
7.9%
5 18
 
7.4%
6 16
 
6.6%
0 16
 
6.6%
7 15
 
6.2%
8 15
 
6.2%
Other Letter
ValueCountFrequency (%)
지 61
32.8%
층 61
32.8%
상 34
18.3%
하 27
14.5%
스 1
 
0.5%
탠 1
 
0.5%
드 1
 
0.5%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Other Punctuation
ValueCountFrequency (%)
. 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 345
65.0%
Hangul 186
35.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 47
13.6%
3 34
9.9%
2 34
9.9%
( 33
9.6%
) 33
9.6%
30
8.7%
9 28
8.1%
4 19
 
5.5%
5 18
 
5.2%
6 16
 
4.6%
Other values (4) 53
15.4%
Hangul
ValueCountFrequency (%)
지 61
32.8%
층 61
32.8%
상 34
18.3%
하 27
14.5%
스 1
 
0.5%
탠 1
 
0.5%
드 1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 345
65.0%
Hangul 186
35.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 61
32.8%
층 61
32.8%
상 34
18.3%
하 27
14.5%
스 1
 
0.5%
탠 1
 
0.5%
드 1
 
0.5%
ASCII
ValueCountFrequency (%)
1 47
13.6%
3 34
9.9%
2 34
9.9%
( 33
9.6%
) 33
9.6%
30
8.7%
9 28
8.1%
4 19
 
5.5%
5 18
 
5.2%
6 16
 
4.6%
Other values (4) 53
15.4%

주요시설
Text

MISSING 

Distinct33
Distinct (%)86.8%
Missing1
Missing (%)2.6%
Memory size444.0 B
2024-03-18T12:12:10.685923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length32
Mean length15.473684
Min length6

Characters and Unicode

Total characters588
Distinct characters107
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)81.6%

Sample

1st row/ 육상경기장, 축구경기장
2nd row/ 야구경기장
3rd row/ 주경기장/ 보조경기장/ 생활체육시설/ 야외구장
4th row/수영장, 체육관
5th row/ 실내체육관
ValueCountFrequency (%)
37
27.4%
실내체육관 8
 
5.9%
1면 7
 
5.2%
수영장 3
 
2.2%
축구경기장 3
 
2.2%
실내 2
 
1.5%
80사대 2
 
1.5%
14면 2
 
1.5%
탁구장 2
 
1.5%
체육관 2
 
1.5%
Other values (65) 67
49.6%
2024-03-18T12:12:10.989825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
108
 
18.4%
/ 49
 
8.3%
장 41
 
7.0%
면 20
 
3.4%
경 18
 
3.1%
기 17
 
2.9%
, 17
 
2.9%
1 15
 
2.6%
구 14
 
2.4%
실 13
 
2.2%
Other values (97) 276
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 326
55.4%
Space Separator 108
 
18.4%
Other Punctuation 66
 
11.2%
Decimal Number 59
 
10.0%
Open Punctuation 8
 
1.4%
Close Punctuation 8
 
1.4%
Lowercase Letter 7
 
1.2%
Uppercase Letter 6
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 41
 
12.6%
면 20
 
6.1%
경 18
 
5.5%
기 17
 
5.2%
구 14
 
4.3%
실 13
 
4.0%
육 13
 
4.0%
체 12
 
3.7%
내 11
 
3.4%
관 10
 
3.1%
Other values (78) 157
48.2%
Decimal Number
ValueCountFrequency (%)
1 15
25.4%
0 10
16.9%
5 9
15.3%
2 7
11.9%
6 5
 
8.5%
4 4
 
6.8%
9 4
 
6.8%
8 3
 
5.1%
3 2
 
3.4%
Uppercase Letter
ValueCountFrequency (%)
M 4
66.7%
B 1
 
16.7%
X 1
 
16.7%
Other Punctuation
ValueCountFrequency (%)
/ 49
74.2%
, 17
 
25.8%
Lowercase Letter
ValueCountFrequency (%)
ｍ 5
71.4%
m 2
 
28.6%
Space Separator
ValueCountFrequency (%)
108
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 326
55.4%
Common 249
42.3%
Latin 13
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 41
 
12.6%
면 20
 
6.1%
경 18
 
5.5%
기 17
 
5.2%
구 14
 
4.3%
실 13
 
4.0%
육 13
 
4.0%
체 12
 
3.7%
내 11
 
3.4%
관 10
 
3.1%
Other values (78) 157
48.2%
Common
ValueCountFrequency (%)
108
43.4%
/ 49
19.7%
, 17
 
6.8%
1 15
 
6.0%
0 10
 
4.0%
5 9
 
3.6%
( 8
 
3.2%
) 8
 
3.2%
2 7
 
2.8%
6 5
 
2.0%
Other values (4) 13
 
5.2%
Latin
ValueCountFrequency (%)
ｍ 5
38.5%
M 4
30.8%
m 2
 
15.4%
B 1
 
7.7%
X 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 325
55.3%
ASCII 257
43.7%
None 5
 
0.9%
Compat Jamo 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
108
42.0%
/ 49
19.1%
, 17
 
6.6%
1 15
 
5.8%
0 10
 
3.9%
5 9
 
3.5%
( 8
 
3.1%
) 8
 
3.1%
2 7
 
2.7%
6 5
 
1.9%
Other values (8) 21
 
8.2%
Hangul
ValueCountFrequency (%)
장 41
 
12.6%
면 20
 
6.2%
경 18
 
5.5%
기 17
 
5.2%
구 14
 
4.3%
실 13
 
4.0%
육 13
 
4.0%
체 12
 
3.7%
내 11
 
3.4%
관 10
 
3.1%
Other values (77) 156
48.0%
None
ValueCountFrequency (%)
ｍ 5
100.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 1
100.0%

좌석수 (수용인원)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct33
Distinct (%)89.2%
Missing2
Missing (%)5.1%
Infinite0
Infinite (%)0.0%
Mean5642.4054
Minimum20
Maximum48590
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size483.0 B
2024-03-18T12:12:11.092052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile50
Q1460
median2353
Q34974
95-th percentile28546.4
Maximum48590
Range48570
Interquartile range (IQR)4514

Descriptive statistics

Standard deviation10203.786
Coefficient of variation (CV)1.8084107
Kurtosis9.2513345
Mean5642.4054
Median Absolute Deviation (MAD)2177
Skewness2.9764832
Sum208769
Variance1.0411726 × 108
MonotonicityNot monotonic
2024-03-18T12:12:11.190705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
100 4
 
10.3%
50 2
 
5.1%
3206 1
 
2.6%
1337 1
 
2.6%
2353 1
 
2.6%
31224 1
 
2.6%
8115 1
 
2.6%
2014 1
 
2.6%
5802 1
 
2.6%
4974 1
 
2.6%
Other values (23) 23
59.0%
(Missing) 2
 
5.1%
ValueCountFrequency (%)
20 1
 
2.6%
50 2
5.1%
100 4
10.3%
150 1
 
2.6%
176 1
 
2.6%
460 1
 
2.6%
680 1
 
2.6%
1010 1
 
2.6%
1067 1
 
2.6%
1181 1
 
2.6%
ValueCountFrequency (%)
48590 1
2.6%
31224 1
2.6%
27877 1
2.6%
20376 1
2.6%
8828 1
2.6%
8115 1
2.6%
7822 1
2.6%
5802 1
2.6%
5009 1
2.6%
4974 1
2.6%

준공년월
Categorical

Distinct16
Distinct (%)41.0%
Missing0
Missing (%)0.0%
Memory size444.0 B
2021-01
6 
2021-09
5 
2021-12
4 
<NA>
4 
2021-02
3 
Other values (11)
17 

Length

Max length7
Median length7
Mean length6.6923077
Min length4

Unique

Unique7 ?
Unique (%)17.9%

Sample

1st row2021-02
2nd row2021-02
3rd row2021-09
4th row2021-01
5th row1975-09

Common Values

ValueCountFrequency (%)
2021-01 6
15.4%
2021-09 5
12.8%
2021-12 4
10.3%
<NA> 4
10.3%
2021-02 3
7.7%
2021-04 3
7.7%
2021-06 3
7.7%
1980-05 2
 
5.1%
2021-07 2
 
5.1%
1975-09 1
 
2.6%
Other values (6) 6
15.4%

Length

2024-03-18T12:12:11.297933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2021-01 6
15.4%
2021-09 5
12.8%
2021-12 4
10.3%
na 4
10.3%
2021-02 3
7.7%
2021-04 3
7.7%
2021-06 3
7.7%
1980-05 2
 
5.1%
2021-07 2
 
5.1%
1975-09 1
 
2.6%
Other values (6) 6
15.4%

관리주체
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size444.0 B
인천광역시체육회
19 
인천광역시시설관리공단
7 
<NA>
4 
㈜신세계야구단
2 
인천유나이티드FC
2 
Other values (4)
5 

Length

Max length11
Median length9
Mean length7.8974359
Min length3

Unique

Unique3 ?
Unique (%)7.7%

Sample

1st row㈜신세계야구단
2nd row㈜신세계야구단
3rd row인천광역시시설관리공단
4th row인천광역시시설관리공단
5th row인천광역시체육회

Common Values

ValueCountFrequency (%)
인천광역시체육회 19
48.7%
인천광역시시설관리공단 7
 
17.9%
<NA> 4
 
10.3%
㈜신세계야구단 2
 
5.1%
인천유나이티드FC 2
 
5.1%
인천광역시장애인체육회 2
 
5.1%
계양구 1
 
2.6%
연수구 1
 
2.6%
남동구 1
 
2.6%

Length

2024-03-18T12:12:11.407794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-18T12:12:11.524649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
인천광역시체육회 19
48.7%
인천광역시시설관리공단 7
 
17.9%
na 4
 
10.3%
㈜신세계야구단 2
 
5.1%
인천유나이티드fc 2
 
5.1%
인천광역시장애인체육회 2
 
5.1%
계양구 1
 
2.6%
연수구 1
 
2.6%
남동구 1
 
2.6%

Interactions

2024-03-18T12:12:08.375709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:12:08.164894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:12:08.463777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-18T12:12:08.292442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-18T12:12:11.630133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번명칭주소면적(제곱미터)주요시설좌석수 (수용인원)준공년월관리주체
연번1.0001.0000.9060.9690.8020.5770.3260.738
명칭1.0001.0001.0001.0001.0001.0001.0001.000
주소0.9061.0001.0001.0000.9510.0000.9540.000
면적(제곱미터)0.9691.0001.0001.0000.9860.0001.0001.000
주요시설0.8021.0000.9510.9861.0000.0000.9620.000
좌석수 (수용인원)0.5771.0000.0000.0000.0001.0000.5870.745
준공년월0.3261.0000.9541.0000.9620.5871.0000.000
관리주체0.7381.0000.0001.0000.0000.7450.0001.000
2024-03-18T12:12:11.785441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
준공년월관리주체
준공년월1.0000.000
관리주체0.0001.000
2024-03-18T12:12:11.859664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번좌석수 (수용인원)준공년월관리주체
연번1.000-0.1560.0000.405
좌석수 (수용인원)-0.1561.0000.2380.513
준공년월0.0000.2381.0000.000
관리주체0.4050.5130.0001.000

Missing values

2024-03-18T12:12:08.560144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T12:12:08.664658image/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.
2024-03-18T12:12:08.755008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번명칭주소면적(제곱미터)주요시설좌석수 (수용인원)준공년월관리주체
01문학경기장인천광역시 남구 매소홀로 61895226(지하1층 지상5층)/ 육상경기장, 축구경기장485902021-02㈜신세계야구단
12문학야구장인천광역시 남구 매소홀로 61841901(지하3층 지상4층)/ 야구경기장278772021-02㈜신세계야구단
23삼산월드체육관인천광역시 부평구 체육관로 6043029(지하2층 지상3층)/ 주경기장/ 보조경기장/ 생활체육시설/ 야외구장78222021-09인천광역시시설관리공단
34계산국민체육센터인천광역시 계양구 주부토로 5804814(지하1층 지상3층)/수영장, 체육관34002021-01인천광역시시설관리공단
45도원체육관인천광역시 중구 샛골로41번길 101639(지상3층)/ 실내체육관26151975-09인천광역시체육회
56도원수영장인천광역시 중구 샛골로41번길 221050(지하1층지상4층)/ 수영장(50M 8코스)10671980-05인천광역시체육회
67올림픽기념국민생활관인천광역시 남동구 구월로 2516619(지하2층 지상3층)/ 수영장, 체육관/ 헬스장, 탁구장33001992-09인천광역시체육회
78동춘롤러경기장인천광역시 연수구 능허대로 4993485(지하1층 지상2층)/ 롤러경기장 1면1501999-07인천광역시체육회
89가좌테니스장인천광역시 서구 가좌로11번길 711129(지하1층 지상2층)/ 테니스장(16면)1761999-10인천광역시체육회
910수봉궁도장(무덕정)인천광역시 남구 수봉로95번길 327250(지상2층)/ 궁도장(149M 과녁 3개)1001980-05인천광역시체육회
연번명칭주소면적(제곱미터)주요시설좌석수 (수용인원)준공년월관리주체
2930선학체육관인천광역시 연수구 경원대로 5263777.12(지하1층 지상3층)/ 실내체육관20142021-01연수구
3031선학하키경기장인천광역시 연수구 경원대로 5266175.38(지하1층 지상3층)/ 하키경기장81152021-01인천광역시체육회
3132선학파크골프장인천광역시 연수구 경원대로 52618518/ 골프장9홀502021-12인천광역시체육회
3233인천아시아드주경기장인천광역시 서구 봉수대로 806113619.95(지하 2층 지상3층)/ 육상경기장, 축구경기장312242021-01인천광역시시설관리공단
3334연희크리켓경기장인천광역시 서구 봉수대로 806113619.95(지하 2층 지상3층)/ 크리켓경기장23532021-01인천광역시시설관리공단
3435옥련국제사격장인천광역시 연수구 독배로 172번길 1429999(지상1층 지상4층)/ 10ｍ 80사대, 25ｍ 60사대 50ｍ 80사대, 런닝(10ｍ) 3사대13372021-06인천광역시체육회
3536선학국제빙상경기장인천광역시 연수구 경원대로 5266938.48(지하1층 지상3층)/ 아이스링크 2면(주ㆍ보조)/ 컬링링크 1면32062021-01인천광역시체육회
3637남동다목적실내체육관인천광역시 남동구 소래로 5402260(지하1층)/ 배드민턴 14면, 탁구장1002021-04남동구
3738장애인국민체육센터인천광역시 연수구 경원대로 5263908.56(지하1층 지상3층)/ 실내체육관, 인조잔디축구장6802021-06인천광역시장애인체육회
3839장애인체육관인천광역시 연수구 앵고개로 130954(지하1층 지상3층)/ 실내체육관, 체력단련실1002021-12인천광역시장애인체육회