Overview

Dataset statistics

Number of variables10
Number of observations49
Missing cells39
Missing cells (%)8.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory85.7 B

Variable types

Text5
Categorical3
Numeric2

Dataset

Description충청북도 축구장 현황에 대한 데이터로서 시설명, 소재지. 면적, 먄수, 수용인원, 준공년도, 관리기관, 전화번호 등에 대한 데이터가 들어 있습니다.
Author충청북도
URLhttps://www.data.go.kr/data/15071044/fileData.do

Alerts

소재지 is highly overall correlated with 관리기관High correlation
관리기관 is highly overall correlated with 소재지High correlation
면수 is highly imbalanced (50.6%)Imbalance
소재지도로명주소 has 18 (36.7%) missing valuesMissing
소재지지번주소 has 2 (4.1%) missing valuesMissing
면적(제곱미터) has 1 (2.0%) missing valuesMissing
수용인원 has 16 (32.7%) missing valuesMissing
준공년도 has 2 (4.1%) missing valuesMissing

Reproduction

Analysis started2023-12-12 14:54:09.470495
Analysis finished2023-12-12 14:54:11.292516
Duration1.82 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

Distinct47
Distinct (%)95.9%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T23:54:11.455437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length9.6122449
Min length4

Characters and Unicode

Total characters471
Distinct characters104
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

Unique45 ?
Unique (%)91.8%

Sample

1st row용정축구공원
2nd row가덕생활체육공원 축구장
3rd row강내생활체육공원 축구장
4th row내수생활체육공원 축구장
5th row흥덕축구공원축구장
ValueCountFrequency (%)
축구장 12
 
17.6%
풋살장 4
 
5.9%
인조잔디구장 2
 
2.9%
축구센터 2
 
2.9%
감곡생활체육공원 2
 
2.9%
대소생활체육공원 2
 
2.9%
서충주생활체육공원 2
 
2.9%
유소년축구장 1
 
1.5%
적성체육공원 1
 
1.5%
용정축구공원 1
 
1.5%
Other values (39) 39
57.4%
2023-12-12T23:54:11.911433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 45
 
9.6%
구 43
 
9.1%
축 31
 
6.6%
원 28
 
5.9%
공 27
 
5.7%
육 23
 
4.9%
체 23
 
4.9%
생 20
 
4.2%
19
 
4.0%
활 19
 
4.0%
Other values (94) 193
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 452
96.0%
Space Separator 19
 
4.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 45
 
10.0%
구 43
 
9.5%
축 31
 
6.9%
원 28
 
6.2%
공 27
 
6.0%
육 23
 
5.1%
체 23
 
5.1%
생 20
 
4.4%
활 19
 
4.2%
살 7
 
1.5%
Other values (93) 186
41.2%
Space Separator
ValueCountFrequency (%)
19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 452
96.0%
Common 19
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 45
 
10.0%
구 43
 
9.5%
축 31
 
6.9%
원 28
 
6.2%
공 27
 
6.0%
육 23
 
5.1%
체 23
 
5.1%
생 20
 
4.4%
활 19
 
4.2%
살 7
 
1.5%
Other values (93) 186
41.2%
Common
ValueCountFrequency (%)
19
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 452
96.0%
ASCII 19
 
4.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 45
 
10.0%
구 43
 
9.5%
축 31
 
6.9%
원 28
 
6.2%
공 27
 
6.0%
육 23
 
5.1%
체 23
 
5.1%
생 20
 
4.4%
활 19
 
4.2%
살 7
 
1.5%
Other values (93) 186
41.2%
ASCII
ValueCountFrequency (%)
19
100.0%

소재지
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Memory size524.0 B
충주시
14 
단양군
7 
음성군
6 
청주시
5 
진천군
5 
Other values (5)
12 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique2 ?
Unique (%)4.1%

Sample

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

Common Values

ValueCountFrequency (%)
충주시 14
28.6%
단양군 7
14.3%
음성군 6
12.2%
청주시 5
 
10.2%
진천군 5
 
10.2%
보은군 4
 
8.2%
제천시 3
 
6.1%
증평군 3
 
6.1%
옥천군 1
 
2.0%
괴산군 1
 
2.0%

Length

2023-12-12T23:54:12.121926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:54:12.275814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
충주시 14
28.6%
단양군 7
14.3%
음성군 6
12.2%
청주시 5
 
10.2%
진천군 5
 
10.2%
보은군 4
 
8.2%
제천시 3
 
6.1%
증평군 3
 
6.1%
옥천군 1
 
2.0%
괴산군 1
 
2.0%

소재지도로명주소
Text

MISSING 

Distinct26
Distinct (%)83.9%
Missing18
Missing (%)36.7%
Memory size524.0 B
2023-12-12T23:54:12.616520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length23
Mean length19.967742
Min length11

Characters and Unicode

Total characters619
Distinct characters96
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

Unique21 ?
Unique (%)67.7%

Sample

1st row충청북도 청주시 상당구 1순환로 1594번길 42
2nd row충청북도 청주시 상당구 가덕면 인차3길 51-2
3rd row충청북도 청주시 흥덕구 강내면 석화사인길 13-45
4th row충청북도 청주시 청원구 초정약수로 55
5th row충청북도 청주시 흥덕구 휴암동 산65-1
ValueCountFrequency (%)
충청북도 29
 
19.9%
충주시 9
 
6.2%
단양군 5
 
3.4%
청주시 5
 
3.4%
음성군 4
 
2.7%
제천시 3
 
2.1%
기업도시로 2
 
1.4%
42 2
 
1.4%
보은읍 2
 
1.4%
보은군 2
 
1.4%
Other values (70) 83
56.8%
2023-12-12T23:54:13.119013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
116
18.7%
충 39
 
6.3%
청 37
 
6.0%
북 31
 
5.0%
도 31
 
5.0%
로 23
 
3.7%
시 19
 
3.1%
1 16
 
2.6%
군 15
 
2.4%
주 15
 
2.4%
Other values (86) 277
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
64.1%
Space Separator 116
 
18.7%
Decimal Number 97
 
15.7%
Dash Punctuation 9
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 39
 
9.8%
청 37
 
9.3%
북 31
 
7.8%
도 31
 
7.8%
로 23
 
5.8%
시 19
 
4.8%
군 15
 
3.8%
주 15
 
3.8%
면 11
 
2.8%
성 11
 
2.8%
Other values (74) 165
41.6%
Decimal Number
ValueCountFrequency (%)
1 16
16.5%
2 12
12.4%
4 12
12.4%
5 12
12.4%
6 11
11.3%
3 8
8.2%
9 8
8.2%
7 7
7.2%
0 7
7.2%
8 4
 
4.1%
Space Separator
ValueCountFrequency (%)
116
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 397
64.1%
Common 222
35.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 39
 
9.8%
청 37
 
9.3%
북 31
 
7.8%
도 31
 
7.8%
로 23
 
5.8%
시 19
 
4.8%
군 15
 
3.8%
주 15
 
3.8%
면 11
 
2.8%
성 11
 
2.8%
Other values (74) 165
41.6%
Common
ValueCountFrequency (%)
116
52.3%
1 16
 
7.2%
2 12
 
5.4%
4 12
 
5.4%
5 12
 
5.4%
6 11
 
5.0%
- 9
 
4.1%
3 8
 
3.6%
9 8
 
3.6%
7 7
 
3.2%
Other values (2) 11
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 397
64.1%
ASCII 222
35.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
116
52.3%
1 16
 
7.2%
2 12
 
5.4%
4 12
 
5.4%
5 12
 
5.4%
6 11
 
5.0%
- 9
 
4.1%
3 8
 
3.6%
9 8
 
3.6%
7 7
 
3.2%
Other values (2) 11
 
5.0%
Hangul
ValueCountFrequency (%)
충 39
 
9.8%
청 37
 
9.3%
북 31
 
7.8%
도 31
 
7.8%
로 23
 
5.8%
시 19
 
4.8%
군 15
 
3.8%
주 15
 
3.8%
면 11
 
2.8%
성 11
 
2.8%
Other values (74) 165
41.6%

소재지지번주소
Text

MISSING 

Distinct42
Distinct (%)89.4%
Missing2
Missing (%)4.1%
Memory size524.0 B
2023-12-12T23:54:13.520233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length26
Mean length20.361702
Min length14

Characters and Unicode

Total characters957
Distinct characters105
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

Unique37 ?
Unique (%)78.7%

Sample

1st row충청북도 청주시 상당구 용정동 460
2nd row충청북도 청주시 상당구 가덕면 인차리 산 25-1
3rd row충청북도 청주시 흥덕구 강내면 탑연리 251-1
4th row충청북도 청주시 내수읍 내수리 108-2
5th row충청북도 청주시 흥덕구 휴암동 산65-1
ValueCountFrequency (%)
충청북도 44
 
19.5%
충주시 14
 
6.2%
단양군 7
 
3.1%
음성군 6
 
2.7%
청주시 5
 
2.2%
보은군 4
 
1.8%
주덕읍 3
 
1.3%
증평읍 3
 
1.3%
송산리 3
 
1.3%
제천시 3
 
1.3%
Other values (112) 134
59.3%
2023-12-12T23:54:14.042509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
18.7%
충 58
 
6.1%
청 50
 
5.2%
북 44
 
4.6%
도 44
 
4.6%
리 40
 
4.2%
1 29
 
3.0%
2 28
 
2.9%
주 24
 
2.5%
군 24
 
2.5%
Other values (95) 437
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 592
61.9%
Space Separator 179
 
18.7%
Decimal Number 163
 
17.0%
Dash Punctuation 23
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
충 58
 
9.8%
청 50
 
8.4%
북 44
 
7.4%
도 44
 
7.4%
리 40
 
6.8%
주 24
 
4.1%
군 24
 
4.1%
시 22
 
3.7%
면 19
 
3.2%
읍 18
 
3.0%
Other values (83) 249
42.1%
Decimal Number
ValueCountFrequency (%)
1 29
17.8%
2 28
17.2%
4 18
11.0%
5 18
11.0%
3 17
10.4%
6 16
9.8%
0 11
 
6.7%
9 11
 
6.7%
7 10
 
6.1%
8 5
 
3.1%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 592
61.9%
Common 365
38.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
충 58
 
9.8%
청 50
 
8.4%
북 44
 
7.4%
도 44
 
7.4%
리 40
 
6.8%
주 24
 
4.1%
군 24
 
4.1%
시 22
 
3.7%
면 19
 
3.2%
읍 18
 
3.0%
Other values (83) 249
42.1%
Common
ValueCountFrequency (%)
179
49.0%
1 29
 
7.9%
2 28
 
7.7%
- 23
 
6.3%
4 18
 
4.9%
5 18
 
4.9%
3 17
 
4.7%
6 16
 
4.4%
0 11
 
3.0%
9 11
 
3.0%
Other values (2) 15
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 592
61.9%
ASCII 365
38.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
49.0%
1 29
 
7.9%
2 28
 
7.7%
- 23
 
6.3%
4 18
 
4.9%
5 18
 
4.9%
3 17
 
4.7%
6 16
 
4.4%
0 11
 
3.0%
9 11
 
3.0%
Other values (2) 15
 
4.1%
Hangul
ValueCountFrequency (%)
충 58
 
9.8%
청 50
 
8.4%
북 44
 
7.4%
도 44
 
7.4%
리 40
 
6.8%
주 24
 
4.1%
군 24
 
4.1%
시 22
 
3.7%
면 19
 
3.2%
읍 18
 
3.0%
Other values (83) 249
42.1%

면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct44
Distinct (%)91.7%
Missing1
Missing (%)2.0%
Infinite0
Infinite (%)0.0%
Mean16081.604
Minimum864
Maximum99494
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T23:54:14.252381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum864
5-th percentile1423.3
Q16576
median8955
Q315126.75
95-th percentile58089.55
Maximum99494
Range98630
Interquartile range (IQR)8550.75

Descriptive statistics

Standard deviation20068.619
Coefficient of variation (CV)1.2479239
Kurtosis6.9492527
Mean16081.604
Median Absolute Deviation (MAD)3272.5
Skewness2.5782837
Sum771917
Variance4.0274946 × 108
MonotonicityNot monotonic
2023-12-12T23:54:14.416666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
8970 3
 
6.1%
7140 2
 
4.1%
4000 2
 
4.1%
52417 1
 
2.0%
8940 1
 
2.0%
14208 1
 
2.0%
4988 1
 
2.0%
7089 1
 
2.0%
61144 1
 
2.0%
9272 1
 
2.0%
Other values (34) 34
69.4%
ValueCountFrequency (%)
864 1
2.0%
1269 1
2.0%
1312 1
2.0%
1630 1
2.0%
2440 1
2.0%
2660 1
2.0%
4000 2
4.1%
4988 1
2.0%
5510 1
2.0%
5855 1
2.0%
ValueCountFrequency (%)
99494 1
2.0%
74541 1
2.0%
61144 1
2.0%
52417 1
2.0%
51454 1
2.0%
32203 1
2.0%
31619 1
2.0%
29451 1
2.0%
21181 1
2.0%
19830 1
2.0%

면수
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
1
38 
2
6 
4
 
2
3
 
2
<NA>
 
1

Length

Max length4
Median length1
Mean length1.0612245
Min length1

Unique

Unique1 ?
Unique (%)2.0%

Sample

1st row4
2nd row1
3rd row1
4th row1
5th row3

Common Values

ValueCountFrequency (%)
1 38
77.6%
2 6
 
12.2%
4 2
 
4.1%
3 2
 
4.1%
<NA> 1
 
2.0%

Length

2023-12-12T23:54:14.595894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:54:14.690816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 38
77.6%
2 6
 
12.2%
4 2
 
4.1%
3 2
 
4.1%
na 1
 
2.0%

수용인원
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing16
Missing (%)32.7%
Memory size524.0 B
2023-12-12T23:54:14.822963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length4.1818182
Min length3

Characters and Unicode

Total characters138
Distinct characters10
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

Unique12 ?
Unique (%)36.4%

Sample

1st row1500
2nd row200
3rd row1500
4th row400
5th row150
ValueCountFrequency (%)
500 7
21.2%
200 3
 
9.1%
50 3
 
9.1%
1500 2
 
6.1%
100 2
 
6.1%
1300 2
 
6.1%
400 2
 
6.1%
150 1
 
3.0%
1000 1
 
3.0%
700 1
 
3.0%
Other values (9) 9
27.3%
2023-12-12T23:54:15.128036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 59
42.8%
32
23.2%
5 17
 
12.3%
1 10
 
7.2%
2 7
 
5.1%
3 7
 
5.1%
4 2
 
1.4%
8 2
 
1.4%
7 1
 
0.7%
, 1
 
0.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105
76.1%
Space Separator 32
 
23.2%
Other Punctuation 1
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 59
56.2%
5 17
 
16.2%
1 10
 
9.5%
2 7
 
6.7%
3 7
 
6.7%
4 2
 
1.9%
8 2
 
1.9%
7 1
 
1.0%
Space Separator
ValueCountFrequency (%)
32
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 138
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 59
42.8%
32
23.2%
5 17
 
12.3%
1 10
 
7.2%
2 7
 
5.1%
3 7
 
5.1%
4 2
 
1.4%
8 2
 
1.4%
7 1
 
0.7%
, 1
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 138
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 59
42.8%
32
23.2%
5 17
 
12.3%
1 10
 
7.2%
2 7
 
5.1%
3 7
 
5.1%
4 2
 
1.4%
8 2
 
1.4%
7 1
 
0.7%
, 1
 
0.7%

준공년도
Real number (ℝ)

MISSING 

Distinct22
Distinct (%)46.8%
Missing2
Missing (%)4.1%
Infinite0
Infinite (%)0.0%
Mean2011.1489
Minimum1988
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size573.0 B
2023-12-12T23:54:15.324678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1988
5-th percentile1998.9
Q12008
median2011
Q32016
95-th percentile2020.7
Maximum2022
Range34
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.9469378
Coefficient of variation (CV)0.0034542135
Kurtosis2.4190289
Mean2011.1489
Median Absolute Deviation (MAD)4
Skewness-1.1935164
Sum94524
Variance48.259944
MonotonicityNot monotonic
2023-12-12T23:54:15.478065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2011 7
14.3%
2008 4
 
8.2%
2016 4
 
8.2%
2014 4
 
8.2%
2017 3
 
6.1%
2012 3
 
6.1%
2009 3
 
6.1%
2022 2
 
4.1%
2015 2
 
4.1%
2020 2
 
4.1%
Other values (12) 13
26.5%
ValueCountFrequency (%)
1988 1
 
2.0%
1992 1
 
2.0%
1998 1
 
2.0%
2001 1
 
2.0%
2003 1
 
2.0%
2005 2
4.1%
2006 1
 
2.0%
2007 1
 
2.0%
2008 4
8.2%
2009 3
6.1%
ValueCountFrequency (%)
2022 2
4.1%
2021 1
 
2.0%
2020 2
4.1%
2018 1
 
2.0%
2017 3
6.1%
2016 4
8.2%
2015 2
4.1%
2014 4
8.2%
2013 1
 
2.0%
2012 3
6.1%

관리기관
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)49.0%
Missing0
Missing (%)0.0%
Memory size524.0 B
시설관리사업소
6 
진천군체육진흥지원단
5 
청주시시설관리공단
4 
충주시축구협회
4 
보은군청 스포츠산업과
4 
Other values (19)
26 

Length

Max length15
Median length11
Mean length8.877551
Min length3

Unique

Unique15 ?
Unique (%)30.6%

Sample

1st row청주시시설관리공단
2nd row청주시시설관리공단
3rd row강내면
4th row청주시시설관리공단
5th row청주시시설관리공단

Common Values

ValueCountFrequency (%)
시설관리사업소 6
12.2%
진천군체육진흥지원단 5
 
10.2%
청주시시설관리공단 4
 
8.2%
충주시축구협회 4
 
8.2%
보은군청 스포츠산업과 4
 
8.2%
충주시 체육진흥과 4
 
8.2%
증평군 체육진흥과 3
 
6.1%
단양군청 문화체육과 2
 
4.1%
제천시시설관리사업소 2
 
4.1%
산턱면사무소 1
 
2.0%
Other values (14) 14
28.6%

Length

2023-12-12T23:54:15.667362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충주시 8
 
10.7%
시설관리사업소 7
 
9.3%
체육진흥과 7
 
9.3%
진천군체육진흥지원단 5
 
6.7%
단양군 5
 
6.7%
스포츠산업과 4
 
5.3%
보은군청 4
 
5.3%
충주시축구협회 4
 
5.3%
청주시시설관리공단 4
 
5.3%
증평군 3
 
4.0%
Other values (21) 24
32.0%

전화번호
Text

Distinct29
Distinct (%)59.2%
Missing0
Missing (%)0.0%
Memory size524.0 B
2023-12-12T23:54:15.924564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length12
Mean length12.102041
Min length12

Characters and Unicode

Total characters593
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

Unique19 ?
Unique (%)38.8%

Sample

1st row043-270-8513
2nd row043-270-8513
3rd row043-201-7575
4th row043-270-8513
5th row043-270-8513
ValueCountFrequency (%)
043-270-8513 4
 
8.2%
043-540-3742 4
 
8.2%
043-854-9009 4
 
8.2%
043-850-3905 4
 
8.2%
043-539-7695 3
 
6.1%
043-835-4923 3
 
6.1%
043-641-4897 2
 
4.1%
043-420-3105 2
 
4.1%
043-871-5915 2
 
4.1%
043-871-5919 2
 
4.1%
Other values (19) 19
38.8%
2023-12-12T23:54:16.319186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 98
16.5%
- 98
16.5%
3 91
15.3%
4 85
14.3%
5 51
8.6%
8 37
 
6.2%
9 37
 
6.2%
2 31
 
5.2%
7 31
 
5.2%
1 22
 
3.7%
Other values (2) 12
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 494
83.3%
Dash Punctuation 98
 
16.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 98
19.8%
3 91
18.4%
4 85
17.2%
5 51
10.3%
8 37
 
7.5%
9 37
 
7.5%
2 31
 
6.3%
7 31
 
6.3%
1 22
 
4.5%
6 11
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 98
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 593
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 98
16.5%
- 98
16.5%
3 91
15.3%
4 85
14.3%
5 51
8.6%
8 37
 
6.2%
9 37
 
6.2%
2 31
 
5.2%
7 31
 
5.2%
1 22
 
3.7%
Other values (2) 12
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 593
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 98
16.5%
- 98
16.5%
3 91
15.3%
4 85
14.3%
5 51
8.6%
8 37
 
6.2%
9 37
 
6.2%
2 31
 
5.2%
7 31
 
5.2%
1 22
 
3.7%
Other values (2) 12
 
2.0%

Interactions

2023-12-12T23:54:10.643699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:54:10.126139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:54:10.730767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T23:54:10.551480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T23:54:16.460629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)면수수용인원준공년도관리기관전화번호
시설명1.0001.0000.9830.9540.0000.9020.9721.0001.0001.000
소재지1.0001.0001.0001.0000.3320.0000.9090.3151.0001.000
소재지도로명주소0.9831.0001.0001.0000.8240.0000.7001.0001.0001.000
소재지지번주소0.9541.0001.0001.0000.9960.0000.6811.0001.0001.000
면적(제곱미터)0.0000.3320.8240.9961.0000.7560.9210.0000.0000.000
면수0.9020.0000.0000.0000.7561.0000.4970.0000.0000.000
수용인원0.9720.9090.7000.6810.9210.4971.0000.0000.7330.640
준공년도1.0000.3151.0001.0000.0000.0000.0001.0000.7770.789
관리기관1.0001.0001.0001.0000.0000.0000.7330.7771.0001.000
전화번호1.0001.0001.0001.0000.0000.0000.6400.7891.0001.000
2023-12-12T23:54:16.638494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지관리기관면수
소재지1.0000.8010.000
관리기관0.8011.0000.000
면수0.0000.0001.000
2023-12-12T23:54:16.753375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)준공년도소재지면수관리기관
면적(제곱미터)1.000-0.1770.1550.4050.000
준공년도-0.1771.0000.0780.0000.311
소재지0.1550.0781.0000.0000.801
면수0.4050.0000.0001.0000.000
관리기관0.0000.3110.8010.0001.000

Missing values

2023-12-12T23:54:10.883587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:54:11.055244image/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.
2023-12-12T23:54:11.205398image/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

시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)면수수용인원준공년도관리기관전화번호
0용정축구공원청주시충청북도 청주시 상당구 1순환로 1594번길 42충청북도 청주시 상당구 용정동 46052417415002009청주시시설관리공단043-270-8513
1가덕생활체육공원 축구장청주시충청북도 청주시 상당구 가덕면 인차3길 51-2충청북도 청주시 상당구 가덕면 인차리 산 25-17454112002012청주시시설관리공단043-270-8513
2강내생활체육공원 축구장청주시충청북도 청주시 흥덕구 강내면 석화사인길 13-45충청북도 청주시 흥덕구 강내면 탑연리 251-1102241<NA>2012강내면043-201-7575
3내수생활체육공원 축구장청주시충청북도 청주시 청원구 초정약수로 55충청북도 청주시 내수읍 내수리 108-271401<NA>2021청주시시설관리공단043-270-8513
4흥덕축구공원축구장청주시충청북도 청주시 흥덕구 휴암동 산65-1충청북도 청주시 흥덕구 휴암동 산65-119790315002015청주시시설관리공단043-270-8513
5서충주생활체육공원 축구장충주시충청북도 충주시 기업도시로 150충청북도 충주시 주덕읍 화곡리 1191916114002018충주시 체육진흥과043-850-3905
6서충주생활체육공원 풋살장충주시충청북도 충주시 기업도시로 150충청북도 충주시 주덕읍 화곡리 1191<NA><NA><NA><NA>충주시 체육진흥과043-850-3905
7주덕다목적구장충주시충청북도 충주시 주덕읍 창전길 216충청북도 충주시 주덕읍 삼청리 223821411502014충주시 주덕읍043-850-2302
8앙성생활체육공원 축구장충주시충청북도 충주시 앙성면 하너미로 755충청북도 충주시 앙성면 용대리 212-21153614002014충주시 앙성면043-850-2362
9탄금풋살장충주시충청북도 충주시 남한강로 8충청북도 충주시 칠금동 40526603<NA><NA>충주시축구협회043-854-9009
시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)면수수용인원준공년도관리기관전화번호
39대소생활체육공원 풋살장음성군충청북도 음성군 대소면 대성로 43충청북도 음성군 대소면 태생리 39013121502016시설관리사업소043-871-5915
40감곡생활체육공원 축구장음성군<NA>충청북도 음성군 감곡면 오향리 320551013302017시설관리사업소043-871-5919
41감곡생활체육공원 풋살장음성군<NA>충청북도 음성군 감곡면 오향리 3208641302017시설관리사업소043-871-5919
42매포생활체육공원축구장단양군충청북도 단양군 매포읍 평동4로 91충청북도 단양군 매포읍 평동리 462792015002006단양군 매포읍사무소043-420-3604
43단성생활체육공원축구장단양군<NA>충청북도 단양군 단성면 하방리 162-2715015002005단양군 단성면사무소043-420-3704
44대강생활체육공원축구장단양군충청북도 단양군 대강면 사인암로 760-9충청북도 단양군 대강면 두음리 527825015002005단양군 대강면사무소043-420-3752
45별곡지구생활체육공원축구장단양군<NA>충청북도 단양군 단양읍 별곡리 113800015002011단양군청 문화체육과043-420-3105
46적성체육공원 축구장단양군충청북도 단양군 적성면 적성로 232-20충청북도 단양군 적성면 소야리 20590415002015단양군 적성면사무소043-420-3953
47영춘체육공원 축구장단양군충청북도 단양군 영춘면 강변로 464충청북도 단양군 하리 435-885101<NA>2020단양군 영춘면사무소043-420-3854
48공설운동장 축구장단양군충청북도 단양군 단양읍 별곡6길 26충청북도 단양군 단양읍 별곡리 15-67490112,0001988단양군청 문화체육과043-420-3105