Overview

Dataset statistics

Number of variables10
Number of observations235
Missing cells354
Missing cells (%)15.1%
Duplicate rows1
Duplicate rows (%)0.4%
Total size in memory19.2 KiB
Average record size in memory83.5 B

Variable types

Text5
Categorical2
Numeric3

Dataset

Description충청북도 시군에 소재하고 있는 공공기관이 운영하는 체육시설에 대한 정보입니다. (시설명, 소재지, 소재지도로명주소, 소재지지번주소, 면적(제곱미터), 규격, 수용인원, 준공년도, 관리기관, 전화번호)의 컬럼 정보를 포함하고 있습니다.
Author충청북도
URLhttps://www.data.go.kr/data/15083343/fileData.do

Alerts

Dataset has 1 (0.4%) duplicate rowsDuplicates
시설명 has 21 (8.9%) missing valuesMissing
소재지도로명주소 has 56 (23.8%) missing valuesMissing
소재지지번주소 has 34 (14.5%) missing valuesMissing
면적(제곱미터) has 26 (11.1%) missing valuesMissing
수용인원(명) has 142 (60.4%) missing valuesMissing
준공년도 has 31 (13.2%) missing valuesMissing
관리기관 has 22 (9.4%) missing valuesMissing
전화번호 has 22 (9.4%) missing valuesMissing

Reproduction

Analysis started2024-03-14 16:03:16.352727
Analysis finished2024-03-14 16:03:21.402561
Duration5.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설명
Text

MISSING 

Distinct208
Distinct (%)97.2%
Missing21
Missing (%)8.9%
Memory size2.0 KiB
2024-03-15T01:03:22.269437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length15
Mean length9.0140187
Min length1

Characters and Unicode

Total characters1929
Distinct characters204
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique203 ?
Unique (%)94.9%

Sample

1st row청주체육관
2nd row남궁유도회관
3rd row청주유도회관
4th row올림픽기념국민생활관
5th row충북스포츠센터
ValueCountFrequency (%)
전천후게이트볼장 12
 
4.1%
축구장 11
 
3.8%
국민체육센터 10
 
3.4%
진천종합스포츠타운 4
 
1.4%
그라운드골프장 4
 
1.4%
풋살장 4
 
1.4%
파크골프장 4
 
1.4%
테니스장 4
 
1.4%
다목적체육관 3
 
1.0%
서충주생활체육공원 3
 
1.0%
Other values (208) 233
79.8%
2024-03-15T01:03:23.601105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 151
 
7.8%
육 82
 
4.3%
체 81
 
4.2%
78
 
4.0%
구 56
 
2.9%
천 52
 
2.7%
스 48
 
2.5%
공 46
 
2.4%
원 44
 
2.3%
생 34
 
1.8%
Other values (194) 1257
65.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1832
95.0%
Space Separator 78
 
4.0%
Uppercase Letter 7
 
0.4%
Decimal Number 4
 
0.2%
Close Punctuation 3
 
0.2%
Open Punctuation 3
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 151
 
8.2%
육 82
 
4.5%
체 81
 
4.4%
구 56
 
3.1%
천 52
 
2.8%
스 48
 
2.6%
공 46
 
2.5%
원 44
 
2.4%
생 34
 
1.9%
트 32
 
1.7%
Other values (182) 1206
65.8%
Uppercase Letter
ValueCountFrequency (%)
B 3
42.9%
A 2
28.6%
M 1
 
14.3%
X 1
 
14.3%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
5 1
25.0%
1 1
25.0%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
* 1
50.0%
Space Separator
ValueCountFrequency (%)
78
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1832
95.0%
Common 90
 
4.7%
Latin 7
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 151
 
8.2%
육 82
 
4.5%
체 81
 
4.4%
구 56
 
3.1%
천 52
 
2.8%
스 48
 
2.6%
공 46
 
2.5%
원 44
 
2.4%
생 34
 
1.9%
트 32
 
1.7%
Other values (182) 1206
65.8%
Common
ValueCountFrequency (%)
78
86.7%
) 3
 
3.3%
( 3
 
3.3%
2 2
 
2.2%
5 1
 
1.1%
1 1
 
1.1%
· 1
 
1.1%
* 1
 
1.1%
Latin
ValueCountFrequency (%)
B 3
42.9%
A 2
28.6%
M 1
 
14.3%
X 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1832
95.0%
ASCII 96
 
5.0%
None 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 151
 
8.2%
육 82
 
4.5%
체 81
 
4.4%
구 56
 
3.1%
천 52
 
2.8%
스 48
 
2.6%
공 46
 
2.5%
원 44
 
2.4%
생 34
 
1.9%
트 32
 
1.7%
Other values (182) 1206
65.8%
ASCII
ValueCountFrequency (%)
78
81.2%
B 3
 
3.1%
) 3
 
3.1%
( 3
 
3.1%
A 2
 
2.1%
2 2
 
2.1%
5 1
 
1.0%
1 1
 
1.0%
M 1
 
1.0%
X 1
 
1.0%
None
ValueCountFrequency (%)
· 1
100.0%

소재지
Categorical

Distinct13
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
충주시
36 
음성군
33 
보은군
27 
청주시
25 
제천시
24 
Other values (8)
90 

Length

Max length4
Median length3
Mean length3.0978723
Min length3

Unique

Unique1 ?
Unique (%)0.4%

Sample

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

Common Values

ValueCountFrequency (%)
충주시 36
15.3%
음성군 33
14.0%
보은군 27
11.5%
청주시 25
10.6%
제천시 24
10.2%
<NA> 22
9.4%
진천군 17
7.2%
단양군 17
7.2%
증평군 12
 
5.1%
영동군 10
 
4.3%
Other values (3) 12
 
5.1%

Length

2024-03-15T01:03:23.833040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충주시 37
15.7%
음성군 33
14.0%
보은군 27
11.5%
청주시 25
10.6%
제천시 24
10.2%
na 22
9.4%
진천군 17
7.2%
단양군 17
7.2%
증평군 12
 
5.1%
영동군 10
 
4.3%
Other values (2) 11
 
4.7%

소재지도로명주소
Text

MISSING 

Distinct140
Distinct (%)78.2%
Missing56
Missing (%)23.8%
Memory size2.0 KiB
2024-03-15T01:03:25.314133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27
Mean length20.223464
Min length15

Characters and Unicode

Total characters3620
Distinct characters167
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

Unique114 ?
Unique (%)63.7%

Sample

1st row충청북도 청주시 서원구 사직대로 229
2nd row충청북도 청주시 서원구 흥덕로 55
3rd row충청북도 청주시 상당구 1순환로 1514번길 70
4th row충청북도 청주시 서원구 흥덕로 69
5th row충청북도 청주시 서원구 흥덕로 37
ValueCountFrequency (%)
충청북도 179
 
20.8%
음성군 35
 
4.1%
충주시 26
 
3.0%
청주시 25
 
2.9%
보은군 25
 
2.9%
제천시 21
 
2.4%
보은읍 16
 
1.9%
진천군 13
 
1.5%
단양군 11
 
1.3%
군청길 10
 
1.2%
Other values (291) 501
58.1%
2024-03-15T01:03:27.205724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
684
18.9%
청 232
 
6.4%
충 206
 
5.7%
북 184
 
5.1%
도 183
 
5.1%
로 124
 
3.4%
군 122
 
3.4%
1 120
 
3.3%
시 76
 
2.1%
읍 75
 
2.1%
Other values (157) 1614
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2352
65.0%
Space Separator 684
 
18.9%
Decimal Number 544
 
15.0%
Dash Punctuation 38
 
1.0%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 232
 
9.9%
충 206
 
8.8%
북 184
 
7.8%
도 183
 
7.8%
로 124
 
5.3%
군 122
 
5.2%
시 76
 
3.2%
읍 75
 
3.2%
성 61
 
2.6%
천 59
 
2.5%
Other values (143) 1030
43.8%
Decimal Number
ValueCountFrequency (%)
1 120
22.1%
3 71
13.1%
2 62
11.4%
5 50
9.2%
6 50
9.2%
4 45
 
8.3%
9 42
 
7.7%
7 40
 
7.4%
0 36
 
6.6%
8 28
 
5.1%
Space Separator
ValueCountFrequency (%)
684
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2352
65.0%
Common 1268
35.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 232
 
9.9%
충 206
 
8.8%
북 184
 
7.8%
도 183
 
7.8%
로 124
 
5.3%
군 122
 
5.2%
시 76
 
3.2%
읍 75
 
3.2%
성 61
 
2.6%
천 59
 
2.5%
Other values (143) 1030
43.8%
Common
ValueCountFrequency (%)
684
53.9%
1 120
 
9.5%
3 71
 
5.6%
2 62
 
4.9%
5 50
 
3.9%
6 50
 
3.9%
4 45
 
3.5%
9 42
 
3.3%
7 40
 
3.2%
- 38
 
3.0%
Other values (4) 66
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2352
65.0%
ASCII 1268
35.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
684
53.9%
1 120
 
9.5%
3 71
 
5.6%
2 62
 
4.9%
5 50
 
3.9%
6 50
 
3.9%
4 45
 
3.5%
9 42
 
3.3%
7 40
 
3.2%
- 38
 
3.0%
Other values (4) 66
 
5.2%
Hangul
ValueCountFrequency (%)
청 232
 
9.9%
충 206
 
8.8%
북 184
 
7.8%
도 183
 
7.8%
로 124
 
5.3%
군 122
 
5.2%
시 76
 
3.2%
읍 75
 
3.2%
성 61
 
2.6%
천 59
 
2.5%
Other values (143) 1030
43.8%

소재지지번주소
Text

MISSING 

Distinct161
Distinct (%)80.1%
Missing34
Missing (%)14.5%
Memory size2.0 KiB
2024-03-15T01:03:28.745832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length21.273632
Min length14

Characters and Unicode

Total characters4276
Distinct characters148
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)66.7%

Sample

1st row충청북도 청주시 서원구 사직동 119-1
2nd row충청북도 청주시 서원구 사직동 808
3rd row충청북도 청주시 상당구 용정동 241
4th row충청북도 청주시 서원구 사직동 788
5th row충청북도 청주시 서원구 사직동 808-6
ValueCountFrequency (%)
충청북도 201
 
20.0%
음성군 31
 
3.1%
충주시 29
 
2.9%
보은군 27
 
2.7%
제천시 24
 
2.4%
청주시 24
 
2.4%
진천군 17
 
1.7%
보은읍 17
 
1.7%
단양군 15
 
1.5%
증평읍 12
 
1.2%
Other values (328) 609
60.5%
2024-03-15T01:03:30.898135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
808
18.9%
청 234
 
5.5%
충 230
 
5.4%
도 204
 
4.8%
북 202
 
4.7%
리 156
 
3.6%
1 138
 
3.2%
군 121
 
2.8%
- 106
 
2.5%
2 105
 
2.5%
Other values (138) 1972
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2651
62.0%
Space Separator 808
 
18.9%
Decimal Number 709
 
16.6%
Dash Punctuation 106
 
2.5%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 234
 
8.8%
충 230
 
8.7%
도 204
 
7.7%
북 202
 
7.6%
리 156
 
5.9%
군 121
 
4.6%
읍 98
 
3.7%
천 78
 
2.9%
시 77
 
2.9%
동 76
 
2.9%
Other values (125) 1175
44.3%
Decimal Number
ValueCountFrequency (%)
1 138
19.5%
2 105
14.8%
4 82
11.6%
3 68
9.6%
5 61
8.6%
6 58
8.2%
8 57
8.0%
7 49
 
6.9%
9 48
 
6.8%
0 43
 
6.1%
Space Separator
ValueCountFrequency (%)
808
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 106
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2651
62.0%
Common 1625
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 234
 
8.8%
충 230
 
8.7%
도 204
 
7.7%
북 202
 
7.6%
리 156
 
5.9%
군 121
 
4.6%
읍 98
 
3.7%
천 78
 
2.9%
시 77
 
2.9%
동 76
 
2.9%
Other values (125) 1175
44.3%
Common
ValueCountFrequency (%)
808
49.7%
1 138
 
8.5%
- 106
 
6.5%
2 105
 
6.5%
4 82
 
5.0%
3 68
 
4.2%
5 61
 
3.8%
6 58
 
3.6%
8 57
 
3.5%
7 49
 
3.0%
Other values (3) 93
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2651
62.0%
ASCII 1625
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
808
49.7%
1 138
 
8.5%
- 106
 
6.5%
2 105
 
6.5%
4 82
 
5.0%
3 68
 
4.2%
5 61
 
3.8%
6 58
 
3.6%
8 57
 
3.5%
7 49
 
3.0%
Other values (3) 93
 
5.7%
Hangul
ValueCountFrequency (%)
청 234
 
8.8%
충 230
 
8.7%
도 204
 
7.7%
북 202
 
7.6%
리 156
 
5.9%
군 121
 
4.6%
읍 98
 
3.7%
천 78
 
2.9%
시 77
 
2.9%
동 76
 
2.9%
Other values (125) 1175
44.3%

면적(제곱미터)
Real number (ℝ)

MISSING 

Distinct193
Distinct (%)92.3%
Missing26
Missing (%)11.1%
Infinite0
Infinite (%)0.0%
Mean9777.5789
Minimum9
Maximum134296
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-15T01:03:31.299672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile379.2
Q11480
median3965
Q38970
95-th percentile50892.8
Maximum134296
Range134287
Interquartile range (IQR)7490

Descriptive statistics

Standard deviation17827
Coefficient of variation (CV)1.823253
Kurtosis16.9101
Mean9777.5789
Median Absolute Deviation (MAD)2979
Skewness3.7401579
Sum2043514
Variance3.1780193 × 108
MonotonicityNot monotonic
2024-03-15T01:03:31.575391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4000 3
 
1.3%
8970 3
 
1.3%
1000 2
 
0.9%
14280 2
 
0.9%
51454 2
 
0.9%
3994 2
 
0.9%
3500 2
 
0.9%
7140 2
 
0.9%
74541 2
 
0.9%
300 2
 
0.9%
Other values (183) 187
79.6%
(Missing) 26
 
11.1%
ValueCountFrequency (%)
9 1
0.4%
146 1
0.4%
261 1
0.4%
300 2
0.9%
342 1
0.4%
351 2
0.9%
352 1
0.4%
374 1
0.4%
376 1
0.4%
384 1
0.4%
ValueCountFrequency (%)
134296 1
0.4%
99494 1
0.4%
81623 1
0.4%
74541 2
0.9%
71159 1
0.4%
61144 1
0.4%
52417 1
0.4%
51582 1
0.4%
51454 2
0.9%
50051 1
0.4%

규격
Categorical

Distinct48
Distinct (%)20.4%
Missing0
Missing (%)0.0%
Memory size2.0 KiB
<NA>
75 
일반건물식
40 
1
32 
2
11 
4
8 
Other values (43)
69 

Length

Max length19
Median length16
Mean length4.0595745
Min length1

Unique

Unique34 ?
Unique (%)14.5%

Sample

1st row돔형
2nd row아치형
3rd row일반건물식
4th row아치형
5th row일반건물식

Common Values

ValueCountFrequency (%)
<NA> 75
31.9%
일반건물식 40
17.0%
1 32
13.6%
2 11
 
4.7%
4 8
 
3.4%
22m×17m×6m 8
 
3.4%
돔형 7
 
3.0%
6 4
 
1.7%
트랙200미터 4
 
1.7%
3 3
 
1.3%
Other values (38) 43
18.3%

Length

2024-03-15T01:03:32.180911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 75
29.3%
일반건물식 40
15.6%
1 32
12.5%
2 11
 
4.3%
4 8
 
3.1%
22m×17m×6m 8
 
3.1%
돔형 7
 
2.7%
6 4
 
1.6%
트랙200미터 4
 
1.6%
회관식 3
 
1.2%
Other values (56) 64
25.0%

수용인원(명)
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)35.5%
Missing142
Missing (%)60.4%
Infinite0
Infinite (%)0.0%
Mean1389.1613
Minimum50
Maximum12000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-15T01:03:32.618235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile77.6
Q1200
median500
Q31500
95-th percentile6100
Maximum12000
Range11950
Interquartile range (IQR)1300

Descriptive statistics

Standard deviation2122.884
Coefficient of variation (CV)1.5281767
Kurtosis8.4623221
Mean1389.1613
Median Absolute Deviation (MAD)380
Skewness2.7659151
Sum129192
Variance4506636.4
MonotonicityNot monotonic
2024-03-15T01:03:33.116714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
500 11
 
4.7%
200 11
 
4.7%
1000 6
 
2.6%
50 5
 
2.1%
1500 5
 
2.1%
300 5
 
2.1%
100 4
 
1.7%
150 4
 
1.7%
2000 4
 
1.7%
400 3
 
1.3%
Other values (23) 35
 
14.9%
(Missing) 142
60.4%
ValueCountFrequency (%)
50 5
2.1%
96 1
 
0.4%
100 4
 
1.7%
150 4
 
1.7%
200 11
4.7%
250 3
 
1.3%
300 5
2.1%
338 1
 
0.4%
350 2
 
0.9%
400 3
 
1.3%
ValueCountFrequency (%)
12000 1
 
0.4%
8000 3
1.3%
7000 1
 
0.4%
5500 1
 
0.4%
5000 2
0.9%
4000 2
0.9%
3300 1
 
0.4%
3000 3
1.3%
2500 1
 
0.4%
2000 4
1.7%

준공년도
Real number (ℝ)

MISSING 

Distinct34
Distinct (%)16.7%
Missing31
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean2010.8578
Minimum1974
Maximum2024
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.2 KiB
2024-03-15T01:03:33.563564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1974
5-th percentile1992.45
Q12006
median2011
Q32018
95-th percentile2022
Maximum2024
Range50
Interquartile range (IQR)12

Descriptive statistics

Standard deviation8.9246648
Coefficient of variation (CV)0.0044382376
Kurtosis1.4577296
Mean2010.8578
Median Absolute Deviation (MAD)6
Skewness-0.98336991
Sum410215
Variance79.649643
MonotonicityNot monotonic
2024-03-15T01:03:34.015668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
2022 16
 
6.8%
2020 14
 
6.0%
2017 12
 
5.1%
2011 12
 
5.1%
2010 11
 
4.7%
2012 11
 
4.7%
2005 11
 
4.7%
2008 10
 
4.3%
2007 10
 
4.3%
2016 9
 
3.8%
Other values (24) 88
37.4%
(Missing) 31
 
13.2%
ValueCountFrequency (%)
1974 1
 
0.4%
1979 1
 
0.4%
1988 2
0.9%
1990 3
1.3%
1992 4
1.7%
1995 3
1.3%
1996 1
 
0.4%
1997 2
0.9%
1998 2
0.9%
1999 3
1.3%
ValueCountFrequency (%)
2024 1
 
0.4%
2023 7
3.0%
2022 16
6.8%
2021 4
 
1.7%
2020 14
6.0%
2019 3
 
1.3%
2018 8
3.4%
2017 12
5.1%
2016 9
3.8%
2015 3
 
1.3%

관리기관
Text

MISSING 

Distinct54
Distinct (%)25.4%
Missing22
Missing (%)9.4%
Memory size2.0 KiB
2024-03-15T01:03:35.211773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length9.4366197
Min length3

Characters and Unicode

Total characters2010
Distinct characters98
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)14.6%

Sample

1st row청주시시설관리공단
2nd row충북유도회
3rd row충북유도회
4th row청주시시설관리공단
5th row충청북도
ValueCountFrequency (%)
시설관리사업소 38
 
11.6%
음성군 33
 
10.1%
보은군청 27
 
8.3%
스포츠산업과 27
 
8.3%
체육진흥과 20
 
6.1%
충주시 18
 
5.5%
제천시시설관리사업소 16
 
4.9%
진천군체육진흥지원단 15
 
4.6%
증평군 12
 
3.7%
청주시시설관리공단 11
 
3.4%
Other values (50) 110
33.6%
2024-03-15T01:03:36.362447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 159
 
7.9%
131
 
6.5%
군 125
 
6.2%
업 98
 
4.9%
설 86
 
4.3%
소 79
 
3.9%
사 78
 
3.9%
관 77
 
3.8%
리 76
 
3.8%
육 65
 
3.2%
Other values (88) 1036
51.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1876
93.3%
Space Separator 131
 
6.5%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 159
 
8.5%
군 125
 
6.7%
업 98
 
5.2%
설 86
 
4.6%
소 79
 
4.2%
사 78
 
4.2%
관 77
 
4.1%
리 76
 
4.1%
육 65
 
3.5%
체 65
 
3.5%
Other values (84) 968
51.6%
Space Separator
ValueCountFrequency (%)
131
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1877
93.4%
Common 133
 
6.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 159
 
8.5%
군 125
 
6.7%
업 98
 
5.2%
설 86
 
4.6%
소 79
 
4.2%
사 78
 
4.2%
관 77
 
4.1%
리 76
 
4.0%
육 65
 
3.5%
체 65
 
3.5%
Other values (85) 969
51.6%
Common
ValueCountFrequency (%)
131
98.5%
) 1
 
0.8%
( 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1876
93.3%
ASCII 133
 
6.6%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 159
 
8.5%
군 125
 
6.7%
업 98
 
5.2%
설 86
 
4.6%
소 79
 
4.2%
사 78
 
4.2%
관 77
 
4.1%
리 76
 
4.1%
육 65
 
3.5%
체 65
 
3.5%
Other values (84) 968
51.6%
ASCII
ValueCountFrequency (%)
131
98.5%
) 1
 
0.8%
( 1
 
0.8%
None
ValueCountFrequency (%)
㈜ 1
100.0%

전화번호
Text

MISSING 

Distinct71
Distinct (%)33.3%
Missing22
Missing (%)9.4%
Memory size2.0 KiB
2024-03-15T01:03:37.228706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters2556
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

Unique44 ?
Unique (%)20.7%

Sample

1st row043-270-8513
2nd row043-284-7300
3rd row043-284-7300
4th row043-270-8513
5th row043-220-9514
ValueCountFrequency (%)
043-540-3742 27
 
12.7%
043-871-2483 20
 
9.4%
043-641-5597 15
 
7.0%
043-270-8513 14
 
6.6%
043-740-5993 10
 
4.7%
043-835-4923 9
 
4.2%
043-420-3105 8
 
3.8%
043-539-7697 7
 
3.3%
043-850-3905 5
 
2.3%
043-850-9276 5
 
2.3%
Other values (61) 93
43.7%
2024-03-15T01:03:38.268016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 426
16.7%
3 396
15.5%
4 383
15.0%
0 377
14.7%
5 203
7.9%
7 166
 
6.5%
8 154
 
6.0%
2 138
 
5.4%
9 136
 
5.3%
1 113
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2130
83.3%
Dash Punctuation 426
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 396
18.6%
4 383
18.0%
0 377
17.7%
5 203
9.5%
7 166
7.8%
8 154
 
7.2%
2 138
 
6.5%
9 136
 
6.4%
1 113
 
5.3%
6 64
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 426
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2556
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 426
16.7%
3 396
15.5%
4 383
15.0%
0 377
14.7%
5 203
7.9%
7 166
 
6.5%
8 154
 
6.0%
2 138
 
5.4%
9 136
 
5.3%
1 113
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2556
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 426
16.7%
3 396
15.5%
4 383
15.0%
0 377
14.7%
5 203
7.9%
7 166
 
6.5%
8 154
 
6.0%
2 138
 
5.4%
9 136
 
5.3%
1 113
 
4.4%

Interactions

2024-03-15T01:03:19.260273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:17.442703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:18.229124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:19.517961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:17.721522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:18.483823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:19.764821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:17.977253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T01:03:19.017461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T01:03:38.440004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지면적(제곱미터)규격수용인원(명)준공년도관리기관전화번호
소재지1.0000.0000.4220.4820.1181.0000.997
면적(제곱미터)0.0001.0000.3550.7440.0000.0000.917
규격0.4220.3551.0000.1190.6180.0000.000
수용인원(명)0.4820.7440.1191.0000.4530.0000.000
준공년도0.1180.0000.6180.4531.0000.6540.512
관리기관1.0000.0000.0000.0000.6541.0000.996
전화번호0.9970.9170.0000.0000.5120.9961.000
2024-03-15T01:03:38.623763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소재지규격
소재지1.0000.125
규격0.1251.000
2024-03-15T01:03:38.764090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면적(제곱미터)수용인원(명)준공년도소재지규격
면적(제곱미터)1.0000.2370.0850.0000.122
수용인원(명)0.2371.000-0.3660.2440.000
준공년도0.085-0.3661.0000.0820.171
소재지0.0000.2440.0821.0000.125
규격0.1220.0000.1710.1251.000

Missing values

2024-03-15T01:03:20.100765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T01:03:20.578912image/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.
2024-03-15T01:03:21.120572image/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)규격수용인원(명)준공년도관리기관전화번호
0청주체육관청주시충청북도 청주시 서원구 사직대로 229충청북도 청주시 서원구 사직동 119-15025돔형80001974청주시시설관리공단043-270-8513
1남궁유도회관청주시충청북도 청주시 서원구 흥덕로 55충청북도 청주시 서원구 사직동 808710아치형7001979충북유도회043-284-7300
2청주유도회관청주시충청북도 청주시 상당구 1순환로 1514번길 70충청북도 청주시 상당구 용정동 2411805일반건물식6002004충북유도회043-284-7300
3올림픽기념국민생활관청주시충청북도 청주시 서원구 흥덕로 69충청북도 청주시 서원구 사직동 7882386아치형25001990청주시시설관리공단043-270-8513
4충북스포츠센터청주시충청북도 청주시 서원구 흥덕로 37충청북도 청주시 서원구 사직동 808-61704일반건물식3502004충청북도043-220-9514
5배드민턴·태권도장청주시충청북도 청주시 서원구 사직대로 229충청북도 청주시 서원구 사직동 8082144일반건물식5002009청주시시설관리공단043-270-8513
6충북체육회관청주시충청북도 청주시 상당구 단재로317번길 59-9(방서동)충청북도 청주시 상당구 방서동 38-11140일반건물식2001995충청북도체육회043-220-9514
7내수국민체육센터청주시충청북도 청주시 청원구 내수읍 청암로 91-4충청북도 청주시 청원구 내수읍 학평리 141-28986일반건물식2002005학교법인주성학원043-218-6566
8오창스포츠센터청주시충청북도 청주시 청원구 오창읍 두릉유리로 1141-12충청북도 청주시 청원구 오창읍 장대리 324-51060일반건물식5002007오창읍043-201-8976
9장애인스포츠센터 및 근대5종훈련장청주시충청북도 청주시 청원구 사천로18번길 81충청북도 청주시 청원구 사천동 89-35537일반건물식6002016청주시장애인체육회043-211-4508
시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)규격수용인원(명)준공년도관리기관전화번호
225<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
226<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
227<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
228<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
229<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
230<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
231<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
232<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
233<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
234*<NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시설명소재지소재지도로명주소소재지지번주소면적(제곱미터)규격수용인원(명)준공년도관리기관전화번호# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>21