Overview

Dataset statistics

Number of variables10
Number of observations24
Missing cells89
Missing cells (%)37.1%
Duplicate rows1
Duplicate rows (%)4.2%
Total size in memory2.0 KiB
Average record size in memory87.3 B

Variable types

Text7
Numeric2
Categorical1

Dataset

Description충청북도 내에 소재하고 있는 종합운동장에 대한 정보를 제공합니다. (시설명, 소재지, 소재지도로명주소, 소재지지번주소, 면적(제곱미터), 규격, 수용인원, 준공년도, 관리기관, 전화번호)
Author충청북도
URLhttps://www.data.go.kr/data/15071033/fileData.do

Alerts

Dataset has 1 (4.2%) duplicate rowsDuplicates
시설명 has 10 (41.7%) missing valuesMissing
소재지 has 10 (41.7%) missing valuesMissing
소재지도로명주소 has 10 (41.7%) missing valuesMissing
소재지지번주소 has 10 (41.7%) missing valuesMissing
면적(제곱미터) has 10 (41.7%) missing valuesMissing
수용인원 has 9 (37.5%) missing valuesMissing
준공년도 has 10 (41.7%) missing valuesMissing
관리기관 has 10 (41.7%) missing valuesMissing
전화번호 has 10 (41.7%) missing valuesMissing

Reproduction

Analysis started2024-03-14 15:40:49.323471
Analysis finished2024-03-14 15:40:51.999777
Duration2.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

MISSING 

Distinct10
Distinct (%)71.4%
Missing10
Missing (%)41.7%
Memory size320.0 B
2024-03-15T00:40:52.452128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length6.5
Min length5

Characters and Unicode

Total characters91
Distinct characters34
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

Unique8 ?
Unique (%)57.1%

Sample

1st row종합경기장
2nd row충주종합운동장
3rd row종합운동장
4th row청풍공설운동장
5th row공설운동장
ValueCountFrequency (%)
공설운동장 4
28.6%
종합운동장 2
14.3%
종합경기장 1
 
7.1%
충주종합운동장 1
 
7.1%
청풍공설운동장 1
 
7.1%
전천후보조육상경기장 1
 
7.1%
스포츠파크주경기장 1
 
7.1%
군민운동장 1
 
7.1%
생거진천종합운동장 1
 
7.1%
금왕체육공원운동장 1
 
7.1%
2024-03-15T00:40:53.481544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 14
15.4%
운 11
12.1%
동 11
12.1%
공 6
 
6.6%
종 5
 
5.5%
합 5
 
5.5%
설 5
 
5.5%
경 3
 
3.3%
기 3
 
3.3%
주 2
 
2.2%
Other values (24) 26
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 91
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 14
15.4%
운 11
12.1%
동 11
12.1%
공 6
 
6.6%
종 5
 
5.5%
합 5
 
5.5%
설 5
 
5.5%
경 3
 
3.3%
기 3
 
3.3%
주 2
 
2.2%
Other values (24) 26
28.6%

Most occurring scripts

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 14
15.4%
운 11
12.1%
동 11
12.1%
공 6
 
6.6%
종 5
 
5.5%
합 5
 
5.5%
설 5
 
5.5%
경 3
 
3.3%
기 3
 
3.3%
주 2
 
2.2%
Other values (24) 26
28.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 91
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 14
15.4%
운 11
12.1%
동 11
12.1%
공 6
 
6.6%
종 5
 
5.5%
합 5
 
5.5%
설 5
 
5.5%
경 3
 
3.3%
기 3
 
3.3%
주 2
 
2.2%
Other values (24) 26
28.6%

소재지
Text

MISSING 

Distinct10
Distinct (%)71.4%
Missing10
Missing (%)41.7%
Memory size320.0 B
2024-03-15T00:40:53.975383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters42
Distinct characters19
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

Unique7 ?
Unique (%)50.0%

Sample

1st row청주시
2nd row충주시
3rd row제천시
4th row제천시
5th row보은군
ValueCountFrequency (%)
보은군 3
21.4%
제천시 2
14.3%
음성군 2
14.3%
청주시 1
 
7.1%
충주시 1
 
7.1%
옥천군 1
 
7.1%
영동군 1
 
7.1%
진천군 1
 
7.1%
괴산군 1
 
7.1%
단양군 1
 
7.1%
2024-03-15T00:40:54.950273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 10
23.8%
천 4
 
9.5%
시 4
 
9.5%
보 3
 
7.1%
은 3
 
7.1%
성 2
 
4.8%
주 2
 
4.8%
음 2
 
4.8%
제 2
 
4.8%
청 1
 
2.4%
Other values (9) 9
21.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 42
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 10
23.8%
천 4
 
9.5%
시 4
 
9.5%
보 3
 
7.1%
은 3
 
7.1%
성 2
 
4.8%
주 2
 
4.8%
음 2
 
4.8%
제 2
 
4.8%
청 1
 
2.4%
Other values (9) 9
21.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 42
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 10
23.8%
천 4
 
9.5%
시 4
 
9.5%
보 3
 
7.1%
은 3
 
7.1%
성 2
 
4.8%
주 2
 
4.8%
음 2
 
4.8%
제 2
 
4.8%
청 1
 
2.4%
Other values (9) 9
21.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 42
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 10
23.8%
천 4
 
9.5%
시 4
 
9.5%
보 3
 
7.1%
은 3
 
7.1%
성 2
 
4.8%
주 2
 
4.8%
음 2
 
4.8%
제 2
 
4.8%
청 1
 
2.4%
Other values (9) 9
21.4%

소재지도로명주소
Text

MISSING 

Distinct13
Distinct (%)92.9%
Missing10
Missing (%)41.7%
Memory size320.0 B
2024-03-15T00:40:55.788635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length19.071429
Min length15

Characters and Unicode

Total characters267
Distinct characters58
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

Unique12 ?
Unique (%)85.7%

Sample

1st row충청북도 청주시 서원구 사직대로229
2nd row충청북도 충주시 대림로 85
3rd row충청북도 제천시 숭의로 101
4th row충청북도 제천시 문화재길 160
5th row충청북도 보은군 보은읍 군청길 40
ValueCountFrequency (%)
충청북도 14
21.5%
보은읍 3
 
4.6%
군청길 3
 
4.6%
보은군 3
 
4.6%
40 2
 
3.1%
제천시 2
 
3.1%
음성군 2
 
3.1%
음성읍 1
 
1.5%
진천읍 1
 
1.5%
문화로69-11 1
 
1.5%
Other values (33) 33
50.8%
2024-03-15T00:40:56.797005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
51
19.1%
청 18
 
6.7%
충 15
 
5.6%
도 14
 
5.2%
북 14
 
5.2%
군 13
 
4.9%
읍 10
 
3.7%
로 8
 
3.0%
1 8
 
3.0%
천 7
 
2.6%
Other values (48) 109
40.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 178
66.7%
Space Separator 51
 
19.1%
Decimal Number 37
 
13.9%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 18
 
10.1%
충 15
 
8.4%
도 14
 
7.9%
북 14
 
7.9%
군 13
 
7.3%
읍 10
 
5.6%
로 8
 
4.5%
천 7
 
3.9%
보 6
 
3.4%
은 6
 
3.4%
Other values (36) 67
37.6%
Decimal Number
ValueCountFrequency (%)
1 8
21.6%
0 5
13.5%
7 4
10.8%
6 4
10.8%
2 4
10.8%
3 3
 
8.1%
9 3
 
8.1%
4 3
 
8.1%
5 2
 
5.4%
8 1
 
2.7%
Space Separator
ValueCountFrequency (%)
51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 178
66.7%
Common 89
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 18
 
10.1%
충 15
 
8.4%
도 14
 
7.9%
북 14
 
7.9%
군 13
 
7.3%
읍 10
 
5.6%
로 8
 
4.5%
천 7
 
3.9%
보 6
 
3.4%
은 6
 
3.4%
Other values (36) 67
37.6%
Common
ValueCountFrequency (%)
51
57.3%
1 8
 
9.0%
0 5
 
5.6%
7 4
 
4.5%
6 4
 
4.5%
2 4
 
4.5%
3 3
 
3.4%
9 3
 
3.4%
4 3
 
3.4%
5 2
 
2.2%
Other values (2) 2
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 178
66.7%
ASCII 89
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
51
57.3%
1 8
 
9.0%
0 5
 
5.6%
7 4
 
4.5%
6 4
 
4.5%
2 4
 
4.5%
3 3
 
3.4%
9 3
 
3.4%
4 3
 
3.4%
5 2
 
2.2%
Other values (2) 2
 
2.2%
Hangul
ValueCountFrequency (%)
청 18
 
10.1%
충 15
 
8.4%
도 14
 
7.9%
북 14
 
7.9%
군 13
 
7.3%
읍 10
 
5.6%
로 8
 
4.5%
천 7
 
3.9%
보 6
 
3.4%
은 6
 
3.4%
Other values (36) 67
37.6%

소재지지번주소
Text

MISSING 

Distinct13
Distinct (%)92.9%
Missing10
Missing (%)41.7%
Memory size320.0 B
2024-03-15T00:40:57.513056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length24
Mean length20.428571
Min length14

Characters and Unicode

Total characters286
Distinct characters63
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

Unique12 ?
Unique (%)85.7%

Sample

1st row충청북도 청주시 서원구 사직동 808
2nd row충청북도 충주시 호암동 627-1
3rd row충청북도 제천시 화산동 1
4th row충청북도 제천시 청풍면 물태리 103
5th row충청북도 보은군 보은읍 이평리 40-2
ValueCountFrequency (%)
충청북도 14
 
20.0%
보은읍 3
 
4.3%
이평리 3
 
4.3%
보은군 3
 
4.3%
음성군 2
 
2.9%
40-2 2
 
2.9%
제천시 2
 
2.9%
진천군 1
 
1.4%
진천읍 1
 
1.4%
교성리 1
 
1.4%
Other values (38) 38
54.3%
2024-03-15T00:40:58.471730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
56
19.6%
청 16
 
5.6%
충 15
 
5.2%
북 14
 
4.9%
도 14
 
4.9%
리 11
 
3.8%
읍 11
 
3.8%
군 10
 
3.5%
1 9
 
3.1%
0 7
 
2.4%
Other values (53) 123
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 182
63.6%
Space Separator 56
 
19.6%
Decimal Number 42
 
14.7%
Dash Punctuation 6
 
2.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 16
 
8.8%
충 15
 
8.2%
북 14
 
7.7%
도 14
 
7.7%
리 11
 
6.0%
읍 11
 
6.0%
군 10
 
5.5%
천 7
 
3.8%
은 6
 
3.3%
보 6
 
3.3%
Other values (41) 72
39.6%
Decimal Number
ValueCountFrequency (%)
1 9
21.4%
0 7
16.7%
4 5
11.9%
2 4
9.5%
3 4
9.5%
6 3
 
7.1%
9 3
 
7.1%
7 3
 
7.1%
8 3
 
7.1%
5 1
 
2.4%
Space Separator
ValueCountFrequency (%)
56
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 182
63.6%
Common 104
36.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 16
 
8.8%
충 15
 
8.2%
북 14
 
7.7%
도 14
 
7.7%
리 11
 
6.0%
읍 11
 
6.0%
군 10
 
5.5%
천 7
 
3.8%
은 6
 
3.3%
보 6
 
3.3%
Other values (41) 72
39.6%
Common
ValueCountFrequency (%)
56
53.8%
1 9
 
8.7%
0 7
 
6.7%
- 6
 
5.8%
4 5
 
4.8%
2 4
 
3.8%
3 4
 
3.8%
6 3
 
2.9%
9 3
 
2.9%
7 3
 
2.9%
Other values (2) 4
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 182
63.6%
ASCII 104
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
56
53.8%
1 9
 
8.7%
0 7
 
6.7%
- 6
 
5.8%
4 5
 
4.8%
2 4
 
3.8%
3 4
 
3.8%
6 3
 
2.9%
9 3
 
2.9%
7 3
 
2.9%
Other values (2) 4
 
3.8%
Hangul
ValueCountFrequency (%)
청 16
 
8.8%
충 15
 
8.2%
북 14
 
7.7%
도 14
 
7.7%
리 11
 
6.0%
읍 11
 
6.0%
군 10
 
5.5%
천 7
 
3.8%
은 6
 
3.3%
보 6
 
3.3%
Other values (41) 72
39.6%

면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct14
Distinct (%)100.0%
Missing10
Missing (%)41.7%
Infinite0
Infinite (%)0.0%
Mean39961.857
Minimum2672
Maximum69620
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-15T00:40:58.813288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2672
5-th percentile5576.2
Q133984.25
median43081.5
Q352865.25
95-th percentile66061.25
Maximum69620
Range66948
Interquartile range (IQR)18881

Descriptive statistics

Standard deviation20071.881
Coefficient of variation (CV)0.50227597
Kurtosis-0.3155818
Mean39961.857
Median Absolute Deviation (MAD)10573
Skewness-0.48599614
Sum559466
Variance4.028804 × 108
MonotonicityNot monotonic
2024-03-15T00:40:59.052655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
33917 1
 
4.2%
46272 1
 
4.2%
55063 1
 
4.2%
69620 1
 
4.2%
44812 1
 
4.2%
2672 1
 
4.2%
7140 1
 
4.2%
34186 1
 
4.2%
64145 1
 
4.2%
61144 1
 
4.2%
Other values (4) 4
 
16.7%
(Missing) 10
41.7%
ValueCountFrequency (%)
2672 1
4.2%
7140 1
4.2%
18623 1
4.2%
33917 1
4.2%
34186 1
4.2%
35709 1
4.2%
42000 1
4.2%
44163 1
4.2%
44812 1
4.2%
46272 1
4.2%
ValueCountFrequency (%)
69620 1
4.2%
64145 1
4.2%
61144 1
4.2%
55063 1
4.2%
46272 1
4.2%
44812 1
4.2%
44163 1
4.2%
42000 1
4.2%
35709 1
4.2%
34186 1
4.2%

규격
Categorical

Distinct5
Distinct (%)20.8%
Missing0
Missing (%)0.0%
Memory size320.0 B
400×8코스
10 
<NA>
10 
공인2종
2 
100×6코스
 
1
400×6코스
 
1

Length

Max length7
Median length5.5
Mean length5.5
Min length4

Unique

Unique2 ?
Unique (%)8.3%

Sample

1st row400×8코스
2nd row400×8코스
3rd row공인2종
4th row400×8코스
5th row공인2종

Common Values

ValueCountFrequency (%)
400×8코스 10
41.7%
<NA> 10
41.7%
공인2종 2
 
8.3%
100×6코스 1
 
4.2%
400×6코스 1
 
4.2%

Length

2024-03-15T00:40:59.571118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T00:40:59.845219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
400×8코스 10
41.7%
na 10
41.7%
공인2종 2
 
8.3%
100×6코스 1
 
4.2%
400×6코스 1
 
4.2%

수용인원
Text

MISSING 

Distinct15
Distinct (%)100.0%
Missing9
Missing (%)37.5%
Memory size320.0 B
2024-03-15T00:41:00.550229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length9.8
Min length1

Characters and Unicode

Total characters147
Distinct characters14
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

Unique15 ?
Unique (%)100.0%

Sample

1st row17608석, 30000명
2nd row14946석, 20000명
3rd row25000석, 35000명
4th row1300명
5th row6000석, 8000명
ValueCountFrequency (%)
8000명 2
 
8.3%
17608석 1
 
4.2%
6000명 1
 
4.2%
9000석 1
 
4.2%
3000명 1
 
4.2%
1404석 1
 
4.2%
7000명 1
 
4.2%
6500명 1
 
4.2%
6128석 1
 
4.2%
6400석 1
 
4.2%
Other values (13) 13
54.2%
2024-03-15T00:41:01.689419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 56
38.1%
명 13
 
8.8%
석 11
 
7.5%
11
 
7.5%
, 10
 
6.8%
1 8
 
5.4%
6 8
 
5.4%
4 6
 
4.1%
5 6
 
4.1%
8 5
 
3.4%
Other values (4) 13
 
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
69.4%
Other Letter 24
 
16.3%
Space Separator 11
 
7.5%
Other Punctuation 10
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 56
54.9%
1 8
 
7.8%
6 8
 
7.8%
4 6
 
5.9%
5 6
 
5.9%
8 5
 
4.9%
3 4
 
3.9%
2 4
 
3.9%
7 3
 
2.9%
9 2
 
2.0%
Other Letter
ValueCountFrequency (%)
명 13
54.2%
석 11
45.8%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 123
83.7%
Hangul 24
 
16.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 56
45.5%
11
 
8.9%
, 10
 
8.1%
1 8
 
6.5%
6 8
 
6.5%
4 6
 
4.9%
5 6
 
4.9%
8 5
 
4.1%
3 4
 
3.3%
2 4
 
3.3%
Other values (2) 5
 
4.1%
Hangul
ValueCountFrequency (%)
명 13
54.2%
석 11
45.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 123
83.7%
Hangul 24
 
16.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 56
45.5%
11
 
8.9%
, 10
 
8.1%
1 8
 
6.5%
6 8
 
6.5%
4 6
 
4.9%
5 6
 
4.9%
8 5
 
4.1%
3 4
 
3.3%
2 4
 
3.3%
Other values (2) 5
 
4.1%
Hangul
ValueCountFrequency (%)
명 13
54.2%
석 11
45.8%

준공년도
Real number (ℝ)

MISSING 

Distinct10
Distinct (%)71.4%
Missing10
Missing (%)41.7%
Infinite0
Infinite (%)0.0%
Mean1999.8571
Minimum1979
Maximum2017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size344.0 B
2024-03-15T00:41:02.054986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1979
5-th percentile1984.85
Q11990
median2002
Q32007.75
95-th percentile2017
Maximum2017
Range38
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation11.979837
Coefficient of variation (CV)0.0059903462
Kurtosis-1.1798689
Mean1999.8571
Median Absolute Deviation (MAD)10.5
Skewness-0.095227646
Sum27998
Variance143.51648
MonotonicityNot monotonic
2024-03-15T00:41:02.429310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2017 2
 
8.3%
1988 2
 
8.3%
2006 2
 
8.3%
1990 2
 
8.3%
1979 1
 
4.2%
1993 1
 
4.2%
2011 1
 
4.2%
1998 1
 
4.2%
2007 1
 
4.2%
2008 1
 
4.2%
(Missing) 10
41.7%
ValueCountFrequency (%)
1979 1
4.2%
1988 2
8.3%
1990 2
8.3%
1993 1
4.2%
1998 1
4.2%
2006 2
8.3%
2007 1
4.2%
2008 1
4.2%
2011 1
4.2%
2017 2
8.3%
ValueCountFrequency (%)
2017 2
8.3%
2011 1
4.2%
2008 1
4.2%
2007 1
4.2%
2006 2
8.3%
1998 1
4.2%
1993 1
4.2%
1990 2
8.3%
1988 2
8.3%
1979 1
4.2%

관리기관
Text

MISSING 

Distinct10
Distinct (%)71.4%
Missing10
Missing (%)41.7%
Memory size320.0 B
2024-03-15T00:41:03.139274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.0714286
Min length4

Characters and Unicode

Total characters127
Distinct characters35
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

Unique7 ?
Unique (%)50.0%

Sample

1st row청주시체육시설과
2nd row충주시
3rd row제천시시설관리사업소
4th row제천시시설관리사업소
5th row보은군청 스포츠산업과
ValueCountFrequency (%)
보은군청 3
15.0%
스포츠산업과 3
15.0%
시설관리사업소 3
15.0%
제천시시설관리사업소 2
10.0%
청주시체육시설과 1
 
5.0%
충주시 1
 
5.0%
옥천군 1
 
5.0%
체육사업소 1
 
5.0%
영동군시설사업소 1
 
5.0%
진천군체육진흥지원단 1
 
5.0%
Other values (3) 3
15.0%
2024-03-15T00:41:04.044357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 11
 
8.7%
업 10
 
7.9%
군 8
 
6.3%
사 7
 
5.5%
7
 
5.5%
소 7
 
5.5%
설 7
 
5.5%
리 5
 
3.9%
청 5
 
3.9%
과 5
 
3.9%
Other values (25) 55
43.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 120
94.5%
Space Separator 7
 
5.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 11
 
9.2%
업 10
 
8.3%
군 8
 
6.7%
사 7
 
5.8%
소 7
 
5.8%
설 7
 
5.8%
리 5
 
4.2%
청 5
 
4.2%
과 5
 
4.2%
관 5
 
4.2%
Other values (24) 50
41.7%
Space Separator
ValueCountFrequency (%)
7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 120
94.5%
Common 7
 
5.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 11
 
9.2%
업 10
 
8.3%
군 8
 
6.7%
사 7
 
5.8%
소 7
 
5.8%
설 7
 
5.8%
리 5
 
4.2%
청 5
 
4.2%
과 5
 
4.2%
관 5
 
4.2%
Other values (24) 50
41.7%
Common
ValueCountFrequency (%)
7
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 120
94.5%
ASCII 7
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 11
 
9.2%
업 10
 
8.3%
군 8
 
6.7%
사 7
 
5.8%
소 7
 
5.8%
설 7
 
5.8%
리 5
 
4.2%
청 5
 
4.2%
과 5
 
4.2%
관 5
 
4.2%
Other values (24) 50
41.7%
ASCII
ValueCountFrequency (%)
7
100.0%

전화번호
Text

MISSING 

Distinct12
Distinct (%)85.7%
Missing10
Missing (%)41.7%
Memory size320.0 B
2024-03-15T00:41:04.645871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters168
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

Unique11 ?
Unique (%)78.6%

Sample

1st row043-201-2374
2nd row043-850-0412
3rd row043-641-5599
4th row043-641-5597
5th row043-540-3742
ValueCountFrequency (%)
043-540-3742 3
21.4%
043-201-2374 1
 
7.1%
043-850-0412 1
 
7.1%
043-641-5599 1
 
7.1%
043-641-5597 1
 
7.1%
043-730-4863 1
 
7.1%
043-740-5995 1
 
7.1%
043-539-7695 1
 
7.1%
043-830-3810 1
 
7.1%
043-871-5910 1
 
7.1%
Other values (2) 2
14.3%
2024-03-15T00:41:05.731468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 28
16.7%
0 27
16.1%
4 27
16.1%
3 24
14.3%
5 15
8.9%
7 10
 
6.0%
1 10
 
6.0%
9 9
 
5.4%
2 8
 
4.8%
8 6
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 140
83.3%
Dash Punctuation 28
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 27
19.3%
4 27
19.3%
3 24
17.1%
5 15
10.7%
7 10
 
7.1%
1 10
 
7.1%
9 9
 
6.4%
2 8
 
5.7%
8 6
 
4.3%
6 4
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 168
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 28
16.7%
0 27
16.1%
4 27
16.1%
3 24
14.3%
5 15
8.9%
7 10
 
6.0%
1 10
 
6.0%
9 9
 
5.4%
2 8
 
4.8%
8 6
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 28
16.7%
0 27
16.1%
4 27
16.1%
3 24
14.3%
5 15
8.9%
7 10
 
6.0%
1 10
 
6.0%
9 9
 
5.4%
2 8
 
4.8%
8 6
 
3.6%

Interactions

2024-03-15T00:40:50.404437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:40:49.868459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:40:50.671071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T00:40:50.139006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T00:41:06.004092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)규격수용인원준공년도관리기관전화번호
시설명1.0000.6630.9190.9190.7610.7401.0000.9720.6630.779
소재지0.6631.0001.0001.0000.3610.0001.0000.0001.0001.000
소재지도로명주소0.9191.0001.0001.0001.0000.0001.0000.7901.0001.000
소재지지번주소0.9191.0001.0001.0001.0000.0001.0000.7901.0001.000
면적(제곱미터)0.7610.3611.0001.0001.0000.8191.0000.0000.3610.879
규격0.7400.0000.0000.0000.8191.0001.0000.6200.0000.000
수용인원1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
준공년도0.9720.0000.7900.7900.0000.6201.0001.0000.0000.000
관리기관0.6631.0001.0001.0000.3610.0001.0000.0001.0001.000
전화번호0.7791.0001.0001.0000.8790.0001.0000.0001.0001.000
2024-03-15T00:41:06.320408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)준공년도규격
면적(제곱미터)1.000-0.2230.000
준공년도-0.2231.0000.268
규격0.0000.2681.000

Missing values

2024-03-15T00:40:50.913567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T00:40:51.301418image/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.
2024-03-15T00:40:51.706250image/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)규격수용인원준공년도관리기관전화번호
0종합경기장청주시충청북도 청주시 서원구 사직대로229충청북도 청주시 서원구 사직동 80833917400×8코스17608석, 30000명1979청주시체육시설과043-201-2374
1충주종합운동장충주시충청북도 충주시 대림로 85충청북도 충주시 호암동 627-146272400×8코스14946석, 20000명2017충주시043-850-0412
2종합운동장제천시충청북도 제천시 숭의로 101충청북도 제천시 화산동 155063공인2종25000석, 35000명1988제천시시설관리사업소043-641-5599
3청풍공설운동장제천시충청북도 제천시 문화재길 160충청북도 제천시 청풍면 물태리 10369620400×8코스1300명1993제천시시설관리사업소043-641-5597
4공설운동장보은군충청북도 보은군 보은읍 군청길 40충청북도 보은군 보은읍 이평리 40-244812공인2종6000석, 8000명2006보은군청 스포츠산업과043-540-3742
5전천후보조육상경기장보은군충청북도 보은군 보은읍 군청길 40충청북도 보은군 보은읍 이평리 40-22672100×6코스100명2011보은군청 스포츠산업과043-540-3742
6스포츠파크주경기장보은군충청북도 보은군 보은읍 군청길 71충청북도 보은군 보은읍 이평리 13-37140400×6코스5507석2017보은군청 스포츠산업과043-540-3742
7공설운동장옥천군충청북도 옥천군 옥천읍 관성로 53충청북도 옥천군 옥천읍 문정리 39034186400×8코스864석, 6000명1990옥천군 체육사업소043-730-4863
8군민운동장영동군충청북도 영동군 영동읍 영동황간로 123충청북도 영동군 영동읍 매천리 110-1 외 2필지64145400×8코스5000석, 10000명1998영동군시설사업소043-740-5995
9생거진천종합운동장진천군충청북도 진천군 진천읍 문화로69-11충청북도 진천군 진천읍 교성리 7461144400×8코스6400석, 8000명2007진천군체육진흥지원단043-539-7695
시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)규격수용인원준공년도관리기관전화번호
14<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
16<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
17<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
18<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
19<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
22<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
23<NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)규격수용인원준공년도관리기관전화번호# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9