Overview

Dataset statistics

Number of variables24
Number of observations30
Missing cells2
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory208.3 B

Variable types

Numeric10
Categorical6
Text8

Dataset

Description경남도내 경기장 현황 데이터입니다. 시군구별 시설명, 소유기관명, 관리주체, 부지면적, 건축면적, 연면적 등의 데이터를 포함하고 있습니다.
Author경상남도
URLhttps://www.data.go.kr/data/3080549/fileData.do

Alerts

시도 has constant value ""Constant
데이터기준일자 has constant value ""Constant
경기장 트랙 주로연장(m) is highly imbalanced (73.5%)Imbalance
지번주소 has 1 (3.3%) missing valuesMissing
우편번호 has 1 (3.3%) missing valuesMissing
연번 has unique valuesUnique
시설명 has unique valuesUnique
부지면적(제곱미터) has unique valuesUnique
건축면적(제곱미터) has unique valuesUnique
연면적(제곱미터) has unique valuesUnique
도로명주소 has unique valuesUnique
건축면적(제곱미터) has 1 (3.3%) zerosZeros
연면적(제곱미터) has 1 (3.3%) zerosZeros
관람석 좌석수 has 1 (3.3%) zerosZeros

Reproduction

Analysis started2024-04-13 13:24:19.120072
Analysis finished2024-04-13 13:24:20.681793
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:20.878032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2024-04-13T22:24:21.289614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

시도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size368.0 B
경상남도
30 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
경상남도 30
100.0%

Length

2024-04-13T22:24:21.701763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:24:22.017760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경상남도 30
100.0%

시군구
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-13T22:24:22.532299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)33.3%

Sample

1st row창원시
2nd row창원시
3rd row진주시
4th row통영시
5th row사천시
ValueCountFrequency (%)
거제시 5
16.7%
고성군 3
 
10.0%
창원시 2
 
6.7%
사천시 2
 
6.7%
김해시 2
 
6.7%
밀양시 2
 
6.7%
함양군 2
 
6.7%
의령군 2
 
6.7%
함안군 1
 
3.3%
남해군 1
 
3.3%
Other values (8) 8
26.7%
2024-04-13T22:24:23.241082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

시설명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-13T22:24:23.901267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length7
Mean length7.4666667
Min length5

Characters and Unicode

Total characters224
Distinct characters56
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row창원종합운동장
2nd row진해공설운동장
3rd row진주종합경기장 주경기장
4th row통영공설운동장
5th row삼천포종합운동장
ValueCountFrequency (%)
주경기장 2
 
5.9%
창원종합운동장 1
 
2.9%
동고성체육공원 1
 
2.9%
부림공설운동장 1
 
2.9%
함안공설운동장 1
 
2.9%
창녕공설운동장 1
 
2.9%
고성군 1
 
2.9%
종합운동장 1
 
2.9%
거류체육공원 1
 
2.9%
남해군공설운동장 1
 
2.9%
Other values (23) 23
67.6%
2024-04-13T22:24:24.938313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 29
 
12.9%
동 27
 
12.1%
운 25
 
11.2%
공 16
 
7.1%
설 13
 
5.8%
합 11
 
4.9%
종 10
 
4.5%
기 4
 
1.8%
육 4
 
1.8%
원 4
 
1.8%
Other values (46) 81
36.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 220
98.2%
Space Separator 4
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 29
 
13.2%
동 27
 
12.3%
운 25
 
11.4%
공 16
 
7.3%
설 13
 
5.9%
합 11
 
5.0%
종 10
 
4.5%
기 4
 
1.8%
육 4
 
1.8%
원 4
 
1.8%
Other values (45) 77
35.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 220
98.2%
Common 4
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 29
 
13.2%
동 27
 
12.3%
운 25
 
11.4%
공 16
 
7.3%
설 13
 
5.9%
합 11
 
5.0%
종 10
 
4.5%
기 4
 
1.8%
육 4
 
1.8%
원 4
 
1.8%
Other values (45) 77
35.0%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 220
98.2%
ASCII 4
 
1.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 29
 
13.2%
동 27
 
12.3%
운 25
 
11.4%
공 16
 
7.3%
설 13
 
5.9%
합 11
 
5.0%
종 10
 
4.5%
기 4
 
1.8%
육 4
 
1.8%
원 4
 
1.8%
Other values (45) 77
35.0%
ASCII
ValueCountFrequency (%)
4
100.0%

소유기관
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-13T22:24:25.437316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters90
Distinct characters29
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)33.3%

Sample

1st row창원시
2nd row창원시
3rd row진주시
4th row통영시
5th row사천시
ValueCountFrequency (%)
거제시 5
16.7%
고성군 3
 
10.0%
창원시 2
 
6.7%
사천시 2
 
6.7%
김해시 2
 
6.7%
밀양시 2
 
6.7%
함양군 2
 
6.7%
의령군 2
 
6.7%
함안군 1
 
3.3%
남해군 1
 
3.3%
Other values (8) 8
26.7%
2024-04-13T22:24:26.133257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 90
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

Most occurring scripts

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 90
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 16
17.8%
군 14
15.6%
거 6
 
6.7%
제 5
 
5.6%
양 5
 
5.6%
창 4
 
4.4%
천 3
 
3.3%
해 3
 
3.3%
함 3
 
3.3%
성 3
 
3.3%
Other values (19) 28
31.1%

관리주체
Text

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-13T22:24:26.787669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length7.3666667
Min length3

Characters and Unicode

Total characters221
Distinct characters44
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

Unique9 ?
Unique (%)30.0%

Sample

1st row시설관리공단
2nd row시설관리공단
3rd row진주시
4th row통영시
5th row사천시
ValueCountFrequency (%)
위탁(거제해양관광개발공사 5
16.7%
시설관리공단 3
10.0%
고성군 3
10.0%
사천시 2
 
6.7%
김해시도시개발공사 2
 
6.7%
밀양시시설관리공단(위탁 2
 
6.7%
시설관리사업소 2
 
6.7%
함양군 2
 
6.7%
하동군(문화체육과 1
 
3.3%
거창군 1
 
3.3%
Other values (7) 7
23.3%
2024-04-13T22:24:27.846547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 20
 
9.0%
사 13
 
5.9%
관 13
 
5.9%
공 13
 
5.9%
설 10
 
4.5%
군 10
 
4.5%
( 9
 
4.1%
양 9
 
4.1%
) 9
 
4.1%
위 8
 
3.6%
Other values (34) 107
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 203
91.9%
Open Punctuation 9
 
4.1%
Close Punctuation 9
 
4.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 20
 
9.9%
사 13
 
6.4%
관 13
 
6.4%
공 13
 
6.4%
설 10
 
4.9%
군 10
 
4.9%
양 9
 
4.4%
위 8
 
3.9%
리 8
 
3.9%
탁 8
 
3.9%
Other values (32) 91
44.8%
Open Punctuation
ValueCountFrequency (%)
( 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 203
91.9%
Common 18
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 20
 
9.9%
사 13
 
6.4%
관 13
 
6.4%
공 13
 
6.4%
설 10
 
4.9%
군 10
 
4.9%
양 9
 
4.4%
위 8
 
3.9%
리 8
 
3.9%
탁 8
 
3.9%
Other values (32) 91
44.8%
Common
ValueCountFrequency (%)
( 9
50.0%
) 9
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 203
91.9%
ASCII 18
 
8.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 20
 
9.9%
사 13
 
6.4%
관 13
 
6.4%
공 13
 
6.4%
설 10
 
4.9%
군 10
 
4.9%
양 9
 
4.4%
위 8
 
3.9%
리 8
 
3.9%
탁 8
 
3.9%
Other values (32) 91
44.8%
ASCII
ValueCountFrequency (%)
( 9
50.0%
) 9
50.0%

부지면적(제곱미터)
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean79757.967
Minimum15000
Maximum369924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:28.223489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15000
5-th percentile24168.6
Q137577.25
median56541
Q388541.5
95-th percentile206140.3
Maximum369924
Range354924
Interquartile range (IQR)50964.25

Descriptive statistics

Standard deviation74017.227
Coefficient of variation (CV)0.928023
Kurtosis7.6075802
Mean79757.967
Median Absolute Deviation (MAD)22000
Skewness2.5410117
Sum2392739
Variance5.4785499 × 109
MonotonicityNot monotonic
2024-04-13T22:24:28.633225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
369924 1
 
3.3%
51200 1
 
3.3%
46651 1
 
3.3%
206049 1
 
3.3%
15000 1
 
3.3%
31795 1
 
3.3%
72775 1
 
3.3%
96288 1
 
3.3%
28106 1
 
3.3%
56130 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
15000 1
3.3%
22509 1
3.3%
26197 1
3.3%
28106 1
3.3%
29693 1
3.3%
31795 1
3.3%
32486 1
3.3%
36960 1
3.3%
39429 1
3.3%
42037 1
3.3%
ValueCountFrequency (%)
369924 1
3.3%
206215 1
3.3%
206049 1
3.3%
168704 1
3.3%
134596 1
3.3%
98505 1
3.3%
96288 1
3.3%
92560 1
3.3%
76486 1
3.3%
73500 1
3.3%

건축면적(제곱미터)
Real number (ℝ)

UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5000.634
Minimum0
Maximum33496
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:29.017912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile57.25
Q1336.25
median1060
Q36435.5
95-th percentile20520.6
Maximum33496
Range33496
Interquartile range (IQR)6099.25

Descriptive statistics

Standard deviation7878.7353
Coefficient of variation (CV)1.5755473
Kurtosis5.3856388
Mean5000.634
Median Absolute Deviation (MAD)999.5
Skewness2.2703695
Sum150019.02
Variance62074471
MonotonicityNot monotonic
2024-04-13T22:24:29.431113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
19370.0 1
 
3.3%
383.12 1
 
3.3%
705.0 1
 
3.3%
7317.0 1
 
3.3%
0.0 1
 
3.3%
5468.0 1
 
3.3%
367.0 1
 
3.3%
695.0 1
 
3.3%
1329.0 1
 
3.3%
28.0 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.0 1
3.3%
28.0 1
3.3%
93.0 1
3.3%
125.0 1
3.3%
140.0 1
3.3%
160.0 1
3.3%
186.0 1
3.3%
326.0 1
3.3%
367.0 1
3.3%
383.12 1
3.3%
ValueCountFrequency (%)
33496.0 1
3.3%
21462.0 1
3.3%
19370.0 1
3.3%
14536.0 1
3.3%
10520.0 1
3.3%
9106.0 1
3.3%
7317.0 1
3.3%
6758.0 1
3.3%
5468.0 1
3.3%
5229.0 1
3.3%

연면적(제곱미터)
Real number (ℝ)

UNIQUE  ZEROS 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5687.9337
Minimum0
Maximum41160
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:29.829502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile102.45
Q1493.2
median1319.5
Q36648
95-th percentile25296.25
Maximum41160
Range41160
Interquartile range (IQR)6154.8

Descriptive statistics

Standard deviation9627.2817
Coefficient of variation (CV)1.6925798
Kurtosis6.7287633
Mean5687.9337
Median Absolute Deviation (MAD)1169.5
Skewness2.5639054
Sum170638.01
Variance92684552
MonotonicityNot monotonic
2024-04-13T22:24:30.222684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
30820.0 1
 
3.3%
721.8 1
 
3.3%
1025.0 1
 
3.3%
9708.0 1
 
3.3%
0.0 1
 
3.3%
6318.0 1
 
3.3%
763.0 1
 
3.3%
1111.0 1
 
3.3%
1329.0 1
 
3.3%
228.21 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
0.0 1
3.3%
84.0 1
3.3%
125.0 1
3.3%
140.0 1
3.3%
160.0 1
3.3%
228.21 1
3.3%
262.0 1
3.3%
417.0 1
3.3%
721.8 1
3.3%
763.0 1
3.3%
ValueCountFrequency (%)
41160.0 1
3.3%
30820.0 1
3.3%
18545.0 1
3.3%
17061.0 1
3.3%
9708.0 1
3.3%
9505.0 1
3.3%
7981.0 1
3.3%
6758.0 1
3.3%
6318.0 1
3.3%
3512.0 1
3.3%

경기장 트랙 바닥재료
Categorical

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size368.0 B
우레탄
19 
몬도
4 
합성탄성고무
2 
시트형탄성
 
1
플러버
 
1
Other values (3)
3 

Length

Max length7
Median length3
Mean length3.2666667
Min length2

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row우레탄
2nd row몬도
3rd row몬도
4th row우레탄
5th row시트형탄성

Common Values

ValueCountFrequency (%)
우레탄 19
63.3%
몬도 4
 
13.3%
합성탄성고무 2
 
6.7%
시트형탄성 1
 
3.3%
플러버 1
 
3.3%
토사 1
 
3.3%
탄성고무 1
 
3.3%
몬도(우레탄) 1
 
3.3%

Length

2024-04-13T22:24:30.763694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:24:31.109008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
우레탄 19
63.3%
몬도 4
 
13.3%
합성탄성고무 2
 
6.7%
시트형탄성 1
 
3.3%
플러버 1
 
3.3%
토사 1
 
3.3%
탄성고무 1
 
3.3%
몬도(우레탄 1
 
3.3%

경기장 트랙 주로연장(m)
Categorical

IMBALANCE 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size368.0 B
400
28 
360
 
1
100
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row400
2nd row400
3rd row400
4th row400
5th row400

Common Values

ValueCountFrequency (%)
400 28
93.3%
360 1
 
3.3%
100 1
 
3.3%

Length

2024-04-13T22:24:31.522318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:24:31.859547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
400 28
93.3%
360 1
 
3.3%
100 1
 
3.3%

경기장 트랙 주로수
Categorical

Distinct5
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size368.0 B
8
20 
4
6 
6
 
2
2
 
1
9
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row8
2nd row8
3rd row8
4th row8
5th row8

Common Values

ValueCountFrequency (%)
8 20
66.7%
4 6
 
20.0%
6 2
 
6.7%
2 1
 
3.3%
9 1
 
3.3%

Length

2024-04-13T22:24:32.217020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:24:32.547091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
8 20
66.7%
4 6
 
20.0%
6 2
 
6.7%
2 1
 
3.3%
9 1
 
3.3%

경기장 필드 바닥재료
Categorical

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size368.0 B
천연잔디
16 
인조잔디
12 
토사
 
1
우레탄
 
1

Length

Max length4
Median length4
Mean length3.9
Min length2

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row천연잔디
2nd row인조잔디
3rd row천연잔디
4th row천연잔디
5th row천연잔디

Common Values

ValueCountFrequency (%)
천연잔디 16
53.3%
인조잔디 12
40.0%
토사 1
 
3.3%
우레탄 1
 
3.3%

Length

2024-04-13T22:24:32.946096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:24:33.250482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
천연잔디 16
53.3%
인조잔디 12
40.0%
토사 1
 
3.3%
우레탄 1
 
3.3%

경기장 필드 폭(m)
Real number (ℝ)

Distinct9
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.633333
Minimum65
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:33.418302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile66.9
Q168
median70
Q372.75
95-th percentile75
Maximum80
Range15
Interquartile range (IQR)4.75

Descriptive statistics

Standard deviation3.1784114
Coefficient of variation (CV)0.044998745
Kurtosis1.2622361
Mean70.633333
Median Absolute Deviation (MAD)2
Skewness0.90524757
Sum2119
Variance10.102299
MonotonicityNot monotonic
2024-04-13T22:24:33.612686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
70 10
33.3%
68 7
23.3%
75 4
 
13.3%
73 3
 
10.0%
72 2
 
6.7%
66 1
 
3.3%
80 1
 
3.3%
69 1
 
3.3%
65 1
 
3.3%
ValueCountFrequency (%)
65 1
 
3.3%
66 1
 
3.3%
68 7
23.3%
69 1
 
3.3%
70 10
33.3%
72 2
 
6.7%
73 3
 
10.0%
75 4
 
13.3%
80 1
 
3.3%
ValueCountFrequency (%)
80 1
 
3.3%
75 4
 
13.3%
73 3
 
10.0%
72 2
 
6.7%
70 10
33.3%
69 1
 
3.3%
68 7
23.3%
66 1
 
3.3%
65 1
 
3.3%

경기장 필드 길이(m)
Real number (ℝ)

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.86667
Minimum100
Maximum157
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:33.800474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile102.45
Q1105
median105
Q3109
95-th percentile110
Maximum157
Range57
Interquartile range (IQR)4

Descriptive statistics

Standard deviation9.6373316
Coefficient of variation (CV)0.089344854
Kurtosis25.353638
Mean107.86667
Median Absolute Deviation (MAD)0
Skewness4.8492986
Sum3236
Variance92.878161
MonotonicityNot monotonic
2024-04-13T22:24:33.983311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
105 16
53.3%
110 5
 
16.7%
109 4
 
13.3%
100 1
 
3.3%
108 1
 
3.3%
157 1
 
3.3%
102 1
 
3.3%
103 1
 
3.3%
ValueCountFrequency (%)
100 1
 
3.3%
102 1
 
3.3%
103 1
 
3.3%
105 16
53.3%
108 1
 
3.3%
109 4
 
13.3%
110 5
 
16.7%
157 1
 
3.3%
ValueCountFrequency (%)
157 1
 
3.3%
110 5
 
16.7%
109 4
 
13.3%
108 1
 
3.3%
105 16
53.3%
103 1
 
3.3%
102 1
 
3.3%
100 1
 
3.3%

관람석 좌석수
Real number (ℝ)

ZEROS 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6942.8667
Minimum0
Maximum27085
Zeros1
Zeros (%)3.3%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:34.195656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile129.1
Q11170
median5653.5
Q310000
95-th percentile21152.2
Maximum27085
Range27085
Interquartile range (IQR)8830

Descriptive statistics

Standard deviation6858.6541
Coefficient of variation (CV)0.98787064
Kurtosis1.8079026
Mean6942.8667
Median Absolute Deviation (MAD)4346.5
Skewness1.3729208
Sum208286
Variance47041137
MonotonicityNot monotonic
2024-04-13T22:24:34.415280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
10000 3
 
10.0%
3000 3
 
10.0%
27085 1
 
3.3%
200 1
 
3.3%
6627 1
 
3.3%
11000 1
 
3.3%
0 1
 
3.3%
15000 1
 
3.3%
7924 1
 
3.3%
390 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
0 1
 
3.3%
112 1
 
3.3%
150 1
 
3.3%
162 1
 
3.3%
200 1
 
3.3%
280 1
 
3.3%
390 1
 
3.3%
560 1
 
3.3%
3000 3
10.0%
3915 1
 
3.3%
ValueCountFrequency (%)
27085 1
 
3.3%
22000 1
 
3.3%
20116 1
 
3.3%
15000 1
 
3.3%
11476 1
 
3.3%
11000 1
 
3.3%
10000 3
10.0%
7924 1
 
3.3%
7500 1
 
3.3%
6847 1
 
3.3%

관람석 수용인원
Real number (ℝ)

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11974.1
Minimum162
Maximum35000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:34.611565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum162
5-th percentile1965
Q16030.25
median10000
Q311500
95-th percentile30000
Maximum35000
Range34838
Interquartile range (IQR)5469.75

Descriptive statistics

Standard deviation8981.1697
Coefficient of variation (CV)0.75004967
Kurtosis1.006848
Mean11974.1
Median Absolute Deviation (MAD)3646.5
Skewness1.3110729
Sum359223
Variance80661410
MonotonicityNot monotonic
2024-04-13T22:24:34.814837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
10000 12
40.0%
5000 4
 
13.3%
30000 3
 
10.0%
5707 1
 
3.3%
22000 1
 
3.3%
20000 1
 
3.3%
35000 1
 
3.3%
4000 1
 
3.3%
162 1
 
3.3%
7000 1
 
3.3%
Other values (4) 4
 
13.3%
ValueCountFrequency (%)
162 1
 
3.3%
300 1
 
3.3%
4000 1
 
3.3%
5000 4
 
13.3%
5707 1
 
3.3%
7000 1
 
3.3%
8054 1
 
3.3%
10000 12
40.0%
12000 1
 
3.3%
15000 1
 
3.3%
ValueCountFrequency (%)
35000 1
 
3.3%
30000 3
 
10.0%
22000 1
 
3.3%
20000 1
 
3.3%
15000 1
 
3.3%
12000 1
 
3.3%
10000 12
40.0%
8054 1
 
3.3%
7000 1
 
3.3%
5707 1
 
3.3%

준공연도
Real number (ℝ)

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1997.5667
Minimum1963
Maximum2020
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:35.028950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1963
5-th percentile1975.4
Q11991.25
median1998.5
Q32005.75
95-th percentile2013.1
Maximum2020
Range57
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation12.386543
Coefficient of variation (CV)0.0062008156
Kurtosis1.2825097
Mean1997.5667
Median Absolute Deviation (MAD)7.5
Skewness-0.84261213
Sum59927
Variance153.42644
MonotonicityNot monotonic
2024-04-13T22:24:35.231742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
1993 3
 
10.0%
1999 2
 
6.7%
2003 2
 
6.7%
1998 2
 
6.7%
2006 2
 
6.7%
1991 2
 
6.7%
2002 1
 
3.3%
1990 1
 
3.3%
2009 1
 
3.3%
2011 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
1963 1
 
3.3%
1970 1
 
3.3%
1982 1
 
3.3%
1986 1
 
3.3%
1987 1
 
3.3%
1990 1
 
3.3%
1991 2
6.7%
1992 1
 
3.3%
1993 3
10.0%
1997 1
 
3.3%
ValueCountFrequency (%)
2020 1
3.3%
2014 1
3.3%
2012 1
3.3%
2011 1
3.3%
2010 1
3.3%
2009 1
3.3%
2006 2
6.7%
2005 1
3.3%
2004 1
3.3%
2003 2
6.7%

도로명주소
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-13T22:24:35.823770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23.5
Mean length19.166667
Min length12

Characters and Unicode

Total characters575
Distinct characters103
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row경남 창원시 성산구 원이대로 450
2nd row경남 창원시 진해구 충무로 4
3rd row경남 진주시 동진로 415
4th row경상남도 통영시?북문2길?25?(북신동)
5th row경남 사천시 주공로 32(벌리동)
ValueCountFrequency (%)
경남 19
 
15.2%
경상남도 7
 
5.6%
거제시 5
 
4.0%
창원시 2
 
1.6%
고성군 2
 
1.6%
김해시 2
 
1.6%
공설운동장 2
 
1.6%
거창읍 1
 
0.8%
305 1
 
0.8%
합천군 1
 
0.8%
Other values (83) 83
66.4%
2024-04-13T22:24:36.979813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
95
 
16.5%
남 31
 
5.4%
경 29
 
5.0%
로 22
 
3.8%
1 20
 
3.5%
2 15
 
2.6%
시 14
 
2.4%
? 13
 
2.3%
5 13
 
2.3%
3 12
 
2.1%
Other values (93) 311
54.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 349
60.7%
Decimal Number 103
 
17.9%
Space Separator 95
 
16.5%
Other Punctuation 13
 
2.3%
Dash Punctuation 9
 
1.6%
Close Punctuation 3
 
0.5%
Open Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 31
 
8.9%
경 29
 
8.3%
로 22
 
6.3%
시 14
 
4.0%
군 12
 
3.4%
동 11
 
3.2%
거 10
 
2.9%
읍 10
 
2.9%
도 9
 
2.6%
상 9
 
2.6%
Other values (78) 192
55.0%
Decimal Number
ValueCountFrequency (%)
1 20
19.4%
2 15
14.6%
5 13
12.6%
3 12
11.7%
6 11
10.7%
4 8
 
7.8%
7 6
 
5.8%
9 6
 
5.8%
8 6
 
5.8%
0 6
 
5.8%
Space Separator
ValueCountFrequency (%)
95
100.0%
Other Punctuation
ValueCountFrequency (%)
? 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 349
60.7%
Common 226
39.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 31
 
8.9%
경 29
 
8.3%
로 22
 
6.3%
시 14
 
4.0%
군 12
 
3.4%
동 11
 
3.2%
거 10
 
2.9%
읍 10
 
2.9%
도 9
 
2.6%
상 9
 
2.6%
Other values (78) 192
55.0%
Common
ValueCountFrequency (%)
95
42.0%
1 20
 
8.8%
2 15
 
6.6%
? 13
 
5.8%
5 13
 
5.8%
3 12
 
5.3%
6 11
 
4.9%
- 9
 
4.0%
4 8
 
3.5%
7 6
 
2.7%
Other values (5) 24
 
10.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 349
60.7%
ASCII 226
39.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
95
42.0%
1 20
 
8.8%
2 15
 
6.6%
? 13
 
5.8%
5 13
 
5.8%
3 12
 
5.3%
6 11
 
4.9%
- 9
 
4.0%
4 8
 
3.5%
7 6
 
2.7%
Other values (5) 24
 
10.6%
Hangul
ValueCountFrequency (%)
남 31
 
8.9%
경 29
 
8.3%
로 22
 
6.3%
시 14
 
4.0%
군 12
 
3.4%
동 11
 
3.2%
거 10
 
2.9%
읍 10
 
2.9%
도 9
 
2.6%
상 9
 
2.6%
Other values (78) 192
55.0%

지번주소
Text

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Memory size368.0 B
2024-04-13T22:24:37.975193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length25
Mean length22.586207
Min length13

Characters and Unicode

Total characters655
Distinct characters106
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

Unique29 ?
Unique (%)100.0%

Sample

1st row경상남도 창원시 성산구 중앙동 1
2nd row경상남도 창원시 진해구 태평동 11-7
3rd row경남 진주시 충무공동 8
4th row통영시 북신동 77-2번지
5th row경상남도 사천시 벌리동 2 삼천포종합운동장
ValueCountFrequency (%)
경상남도 25
 
16.9%
거제시 4
 
2.7%
경남 3
 
2.0%
밀양시 2
 
1.4%
김해시 2
 
1.4%
함양군 2
 
1.4%
사천시 2
 
1.4%
고성군 2
 
1.4%
창원시 2
 
1.4%
의령군 2
 
1.4%
Other values (101) 102
68.9%
2024-04-13T22:24:39.182197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
119
 
18.2%
남 31
 
4.7%
경 28
 
4.3%
도 26
 
4.0%
동 26
 
4.0%
상 25
 
3.8%
1 21
 
3.2%
시 16
 
2.4%
리 16
 
2.4%
2 14
 
2.1%
Other values (96) 333
50.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 435
66.4%
Space Separator 119
 
18.2%
Decimal Number 91
 
13.9%
Dash Punctuation 10
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
남 31
 
7.1%
경 28
 
6.4%
도 26
 
6.0%
동 26
 
6.0%
상 25
 
5.7%
시 16
 
3.7%
리 16
 
3.7%
군 13
 
3.0%
장 13
 
3.0%
운 13
 
3.0%
Other values (84) 228
52.4%
Decimal Number
ValueCountFrequency (%)
1 21
23.1%
2 14
15.4%
6 9
9.9%
4 9
9.9%
8 8
 
8.8%
3 8
 
8.8%
0 7
 
7.7%
5 5
 
5.5%
9 5
 
5.5%
7 5
 
5.5%
Space Separator
ValueCountFrequency (%)
119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 435
66.4%
Common 220
33.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
남 31
 
7.1%
경 28
 
6.4%
도 26
 
6.0%
동 26
 
6.0%
상 25
 
5.7%
시 16
 
3.7%
리 16
 
3.7%
군 13
 
3.0%
장 13
 
3.0%
운 13
 
3.0%
Other values (84) 228
52.4%
Common
ValueCountFrequency (%)
119
54.1%
1 21
 
9.5%
2 14
 
6.4%
- 10
 
4.5%
6 9
 
4.1%
4 9
 
4.1%
8 8
 
3.6%
3 8
 
3.6%
0 7
 
3.2%
5 5
 
2.3%
Other values (2) 10
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 435
66.4%
ASCII 220
33.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
119
54.1%
1 21
 
9.5%
2 14
 
6.4%
- 10
 
4.5%
6 9
 
4.1%
4 9
 
4.1%
8 8
 
3.6%
3 8
 
3.6%
0 7
 
3.2%
5 5
 
2.3%
Other values (2) 10
 
4.5%
Hangul
ValueCountFrequency (%)
남 31
 
7.1%
경 28
 
6.4%
도 26
 
6.0%
동 26
 
6.0%
상 25
 
5.7%
시 16
 
3.7%
리 16
 
3.7%
군 13
 
3.0%
장 13
 
3.0%
운 13
 
3.0%
Other values (84) 228
52.4%

우편번호
Real number (ℝ)

MISSING 

Distinct29
Distinct (%)100.0%
Missing1
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean51830.759
Minimum50043
Maximum53310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size398.0 B
2024-04-13T22:24:39.408916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50043
5-th percentile50081.6
Q150619
median52152
Q352915
95-th percentile53273.8
Maximum53310
Range3267
Interquartile range (IQR)2296

Descriptive statistics

Standard deviation1163.4424
Coefficient of variation (CV)0.022446949
Kurtosis-1.4814142
Mean51830.759
Median Absolute Deviation (MAD)895
Skewness-0.32401867
Sum1503092
Variance1353598.2
MonotonicityNot monotonic
2024-04-13T22:24:39.628493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
51411 1
 
3.3%
51677 1
 
3.3%
50229 1
 
3.3%
50126 1
 
3.3%
50052 1
 
3.3%
50043 1
 
3.3%
52215 1
 
3.3%
52333 1
 
3.3%
52426 1
 
3.3%
52915 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
50043 1
3.3%
50052 1
3.3%
50126 1
3.3%
50229 1
3.3%
50334 1
3.3%
50420 1
3.3%
50436 1
3.3%
50619 1
3.3%
50832 1
3.3%
50860 1
3.3%
ValueCountFrequency (%)
53310 1
3.3%
53285 1
3.3%
53257 1
3.3%
53217 1
3.3%
53047 1
3.3%
52931 1
3.3%
52926 1
3.3%
52915 1
3.3%
52830 1
3.3%
52550 1
3.3%

기관연락처
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-13T22:24:40.252867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length12
Mean length12.833333
Min length12

Characters and Unicode

Total characters385
Distinct characters12
Distinct categories3 ?
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 (%)60.0%

Sample

1st row055-712-0581
2nd row055-712-0621
3rd row055-749-7438
4th row055-643-6839 6840
5th row055-831-5632
ValueCountFrequency (%)
055-639-8130 3
 
8.6%
055-670-2114 3
 
8.6%
055-831-5632 2
 
5.7%
055-639-8360 2
 
5.7%
8361 2
 
5.7%
8362 2
 
5.7%
055-570-2832 2
 
5.7%
055-880-6777 1
 
2.9%
055-712-0581 1
 
2.9%
055-532-9537 1
 
2.9%
Other values (16) 16
45.7%
2024-04-13T22:24:41.082370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 72
18.7%
0 64
16.6%
- 60
15.6%
3 38
9.9%
6 32
8.3%
8 26
 
6.8%
1 21
 
5.5%
2 19
 
4.9%
9 17
 
4.4%
7 17
 
4.4%
Other values (2) 19
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 320
83.1%
Dash Punctuation 60
 
15.6%
Space Separator 5
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 72
22.5%
0 64
20.0%
3 38
11.9%
6 32
10.0%
8 26
 
8.1%
1 21
 
6.6%
2 19
 
5.9%
9 17
 
5.3%
7 17
 
5.3%
4 14
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 385
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 72
18.7%
0 64
16.6%
- 60
15.6%
3 38
9.9%
6 32
8.3%
8 26
 
6.8%
1 21
 
5.5%
2 19
 
4.9%
9 17
 
4.4%
7 17
 
4.4%
Other values (2) 19
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 385
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 72
18.7%
0 64
16.6%
- 60
15.6%
3 38
9.9%
6 32
8.3%
8 26
 
6.8%
1 21
 
5.5%
2 19
 
4.9%
9 17
 
4.4%
7 17
 
4.4%
Other values (2) 19
 
4.9%

홈페이지
Text

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-13T22:24:41.658009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length193
Median length66
Mean length65.133333
Min length33

Characters and Unicode

Total characters1954
Distinct characters57
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)83.3%

Sample

1st rowhttps://www.cwsisul.or.kr/_chsports/_sub01/sub01_01.html
2nd rowhttps://www.cwsisul.or.kr/_jhpuground/_sub01/sub01_01.html
3rd rowhttps://www.jinju.go.kr/yeyak/08871/09151/09172.web
4th rowhttps://sportspark2015.ttdc.kr/sub/playground.asp
5th rowhttp://scsports.or.kr/%EC%B2%B4%EC%9C%A1%ED%9A%8C-%EC%86%8C%EA%B0%9C/%EC%B2%B4%EC%9C%A1%EC%8B%9C%EC%84%A4%EC%95%88%EB%82%B4/
ValueCountFrequency (%)
https://www.goseong.go.kr/index.goseong?menucd=dom_000000105010000000 3
 
10.0%
http://scsports.or.kr/%ec%b2%b4%ec%9c%a1%ed%9a%8c-%ec%86%8c%ea%b0%9c/%ec%b2%b4%ec%9c%a1%ec%8b%9c%ec%84%a4%ec%95%88%eb%82%b4 2
 
6.7%
https://www.uiryeong.go.kr/index.uiryeong?menucd=dom_000000204006003007 1
 
3.3%
https://www.cwsisul.or.kr/_chsports/_sub01/sub01_01.html 1
 
3.3%
https://www.yssisul.or.kr/stms/sc 1
 
3.3%
http://www.geochang.go.kr/sports/index.do?c=sp0201020100 1
 
3.3%
https://www.hygn.go.kr/04485/04487.web?amode=view&fcd=s009&cpage=6 1
 
3.3%
https://www.hygn.go.kr/04485/04486.web 1
 
3.3%
https://www.sancheong.go.kr/www/contents.do?key=234 1
 
3.3%
https://www.hadong.go.kr/specialty/00225/00522.web 1
 
3.3%
Other values (17) 17
56.7%
2024-04-13T22:24:42.493340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 150
 
7.7%
/ 130
 
6.7%
. 112
 
5.7%
w 98
 
5.0%
s 88
 
4.5%
t 86
 
4.4%
% 81
 
4.1%
o 77
 
3.9%
e 72
 
3.7%
g 58
 
3.0%
Other values (47) 1002
51.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1010
51.7%
Other Punctuation 384
 
19.7%
Decimal Number 368
 
18.8%
Uppercase Letter 129
 
6.6%
Connector Punctuation 32
 
1.6%
Math Symbol 29
 
1.5%
Dash Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 98
 
9.7%
s 88
 
8.7%
t 86
 
8.5%
o 77
 
7.6%
e 72
 
7.1%
g 58
 
5.7%
r 55
 
5.4%
p 55
 
5.4%
h 54
 
5.3%
n 40
 
4.0%
Other values (14) 327
32.4%
Uppercase Letter
ValueCountFrequency (%)
C 37
28.7%
E 28
21.7%
B 20
15.5%
A 15
11.6%
D 7
 
5.4%
M 6
 
4.7%
O 5
 
3.9%
S 3
 
2.3%
W 2
 
1.6%
G 2
 
1.6%
Other values (4) 4
 
3.1%
Decimal Number
ValueCountFrequency (%)
0 150
40.8%
2 42
 
11.4%
1 39
 
10.6%
4 34
 
9.2%
8 29
 
7.9%
9 25
 
6.8%
5 21
 
5.7%
3 10
 
2.7%
6 10
 
2.7%
7 8
 
2.2%
Other Punctuation
ValueCountFrequency (%)
/ 130
33.9%
. 112
29.2%
% 81
21.1%
: 30
 
7.8%
& 17
 
4.4%
? 14
 
3.6%
Connector Punctuation
ValueCountFrequency (%)
_ 32
100.0%
Math Symbol
ValueCountFrequency (%)
= 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1139
58.3%
Common 815
41.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 98
 
8.6%
s 88
 
7.7%
t 86
 
7.6%
o 77
 
6.8%
e 72
 
6.3%
g 58
 
5.1%
r 55
 
4.8%
p 55
 
4.8%
h 54
 
4.7%
n 40
 
3.5%
Other values (28) 456
40.0%
Common
ValueCountFrequency (%)
0 150
18.4%
/ 130
16.0%
. 112
13.7%
% 81
9.9%
2 42
 
5.2%
1 39
 
4.8%
4 34
 
4.2%
_ 32
 
3.9%
: 30
 
3.7%
8 29
 
3.6%
Other values (9) 136
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1954
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 150
 
7.7%
/ 130
 
6.7%
. 112
 
5.7%
w 98
 
5.0%
s 88
 
4.5%
t 86
 
4.4%
% 81
 
4.1%
o 77
 
3.9%
e 72
 
3.7%
g 58
 
3.0%
Other values (47) 1002
51.3%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size368.0 B
2024-04-08
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-04-08
2nd row2024-04-08
3rd row2024-04-08
4th row2024-04-08
5th row2024-04-08

Common Values

ValueCountFrequency (%)
2024-04-08 30
100.0%

Length

2024-04-13T22:24:42.702842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T22:24:42.868323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-04-08 30
100.0%

Sample

연번시도시군구시설명소유기관관리주체부지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)경기장 트랙 바닥재료경기장 트랙 주로연장(m)경기장 트랙 주로수경기장 필드 바닥재료경기장 필드 폭(m)경기장 필드 길이(m)관람석 좌석수관람석 수용인원준공연도도로명주소지번주소우편번호기관연락처홈페이지데이터기준일자
01경상남도창원시창원종합운동장창원시시설관리공단36992419370.030820.0우레탄4008천연잔디7511027085300001993경남 창원시 성산구 원이대로 450경상남도 창원시 성산구 중앙동 151411055-712-0581https://www.cwsisul.or.kr/_chsports/_sub01/sub01_01.html2024-04-08
12경상남도창원시진해공설운동장창원시시설관리공단618336758.06758.0몬도4008인조잔디68105570757071963경남 창원시 진해구 충무로 4경상남도 창원시 진해구 태평동 11-751677055-712-0621https://www.cwsisul.or.kr/_jhpuground/_sub01/sub01_01.html2024-04-08
23경상남도진주시진주종합경기장 주경기장진주시진주시20621533496.041160.0몬도4008천연잔디6810520116220002010경남 진주시 동진로 415경남 진주시 충무공동 852830055-749-7438https://www.jinju.go.kr/yeyak/08871/09151/09172.web2024-04-08
34경상남도통영시통영공설운동장통영시통영시32486789.01045.0우레탄4008천연잔디751055600200001970경상남도 통영시?북문2길?25?(북신동)통영시 북신동 77-2번지53047055-643-6839 6840https://sportspark2015.ttdc.kr/sub/playground.asp2024-04-08
45경상남도사천시삼천포종합운동장사천시사천시1345965229.07981.0시트형탄성4008천연잔디751106847100001986경남 사천시 주공로 32(벌리동)경상남도 사천시 벌리동 2 삼천포종합운동장52550055-831-5632http://scsports.or.kr/%EC%B2%B4%EC%9C%A1%ED%9A%8C-%EC%86%8C%EA%B0%9C/%EC%B2%B4%EC%9C%A1%EC%8B%9C%EC%84%A4%EC%95%88%EB%82%B4/2024-04-08
56경상남도사천시사천종합운동장사천시사천시420372162.92372.0우레탄4008천연잔디751104868100001982경남 사천읍 구암두문로 85경상남도 사천시 사천읍 정의리 7 사천종합운동장52516055-831-5632http://scsports.or.kr/%EC%B2%B4%EC%9C%A1%ED%9A%8C-%EC%86%8C%EA%B0%9C/%EC%B2%B4%EC%9C%A1%EC%8B%9C%EC%84%A4%EC%95%88%EB%82%B4/2024-04-08
67경상남도김해시김해운동장김해시김해시도시개발공사611273496.03512.0몬도4008천연잔디6610011476350002004경남 김해시 구산동 660번지경상남도 김해시 구산동 660 김해운동장50832055-323-7313https://www.gimhae.go.kr/00954/01200/02448.web?sno=154&amode=view&2024-04-08
78경상남도김해시진영공설운동장 육상경기장김해시김해시도시개발공사73500742.01310.0플러버4008인조잔디801103915100001999경남 김해시 진영읍 김해대로 257경상남도 김해시 진영읍 진영리 134050860055-346-2100https://www.gimhae.go.kr/00204/00291/00293.web?amode=view&idx=4812024-04-08
89경상남도밀양시밀양종합운동장밀양시밀양시시설관리공단(위탁)643182504.03073.0우레탄4008천연잔디7010510000100001997경상남도 밀양대로 2057-21(교동)경상남도 밀양시 교동 1111 밀양공설운동장50420055-359-4600https://www.myfmc.or.kr/sub/02_02_01.php2024-04-08
910경상남도밀양시삼문공설운동장밀양시밀양시시설관리공단(위탁)2250993.084.0토사4006토사70105300040002003경상남도 밀양시 삼문송림길 25경상남도 밀양시 삼문동 232-2 밀양문화체육회관50436055-359-4640https://www.myfmc.or.kr/sub/02_13_01.php2024-04-08
연번시도시군구시설명소유기관관리주체부지면적(제곱미터)건축면적(제곱미터)연면적(제곱미터)경기장 트랙 바닥재료경기장 트랙 주로연장(m)경기장 트랙 주로수경기장 필드 바닥재료경기장 필드 폭(m)경기장 필드 길이(m)관람석 좌석수관람석 수용인원준공연도도로명주소지번주소우편번호기관연락처홈페이지데이터기준일자
2021경상남도고성군고성군 종합운동장고성군고성군9256010520.018545.0우레탄4008천연잔디701056465100001998경남 고성읍 송학고분로 193경상남도 고성군 고성읍 기월리 61152931055-670-2114https://www.goseong.go.kr/index.goseong?menuCd=DOM_0000001050100000002024-04-08
2122경상남도고성군거류체육공원고성군고성군29693140.0140.0우레탄4004인조잔디7210956050002006경상남도 고성군 거류면?안정로?1268-36경상남도 거류면 신용리 888 일원52926055-670-2114https://www.goseong.go.kr/index.goseong?menuCd=DOM_0000001050100000002024-04-08
2223경상남도고성군동고성체육공원고성군고성군5613028.0228.21우레탄4004인조잔디7010539050002020경남 고성군 회화면 배둔리 1336경상남도 고성군 회화면 배둔리 133652915055-670-2114https://www.goseong.go.kr/index.goseong?menuCd=DOM_0000001050100000002024-04-08
2324경상남도남해군남해군공설운동장남해군체육시설사업소281061329.01329.0우레탄4008천연잔디7011010000100001987경남 남해군 남해읍 망운로 9번길 42-17경상남도 남해군 남해읍 서변리 212 남해공설운동장52426055-860-8681https://www.namhae.go.kr/search/totalSearch.do?section=all&pageCd=WW0900000000&siteGubun=portal&asection=all&keyword=%EA%B3%B5%EC%84%A4%EC%9A%B4%EB%8F%99%EC%9E%A5&viewMoreGb=&keyword2=&menuAll=2024-04-08
2425경상남도하동군하동공설운동장하동군하동군(문화체육과)96288695.01111.0우레탄4008천연잔디70105792480541993경상남도 하동군 적량면 공설운동장로 207경상남도 하동군 적량면 고절리 1209-152333055-880-6777https://www.hadong.go.kr/specialty/00225/00522.web2024-04-08
2526경상남도산청군산청공설운동장산청군산청군72775367.0763.0우레탄4006인조잔디68105300050001992경상남도 산청군 금서면?친환경로2631번길?35경남 산청군 금서면 매촌리 152215055-970-6000https://www.sancheong.go.kr/www/contents.do?key=2342024-04-08
2627경상남도함양군함양종합운동장함양군함양군317955468.06318.0몬도(우레탄)4008천연잔디7015715000150001991경남 함양읍 대실곰실로 9경상남도 함양군 함양읍 백연리 449 공설운동장50043055-960-4620https://www.hygn.go.kr/04485/04486.web2024-04-08
2728경상남도함양군휴천공설운동장함양군함양군150000.00.0우레탄1002인조잔디6510203002011경상남도 함양군 휴천면 휴천로 460-1경상남도 함양군 휴천면 목현리 480-250052055-960-8560https://www.hygn.go.kr/04485/04487.web?amode=view&fcd=S009&cpage=62024-04-08
2829경상남도거창군거창종합운동장거창군거창군2060497317.09708.0몬도4008천연잔디7310911000120002009경남 거창군 거창읍 심소정길 39-36경남 거창군 거창읍 양평리 116050126055-940-8720http://www.geochang.go.kr/sports/Index.do?c=SP02010201002024-04-08
2930경상남도합천군합천공설운동장합천군합천군46651705.01025.0우레탄4009천연잔디731036627100001990경남 합천군 합천읍 장수로 1-1경상남도 합천군 합천읍 합천리 931 합천공설운동장50229055-930-4933https://www.hc.go.kr/05756/06121/06128.web?&cpage=5572024-04-08