Overview

Dataset statistics

Number of variables6
Number of observations24
Missing cells53
Missing cells (%)36.8%
Duplicate rows1
Duplicate rows (%)4.2%
Total size in memory1.3 KiB
Average record size in memory53.5 B

Variable types

Text5
Categorical1

Dataset

Description전라남도 함평군 체육시설현황에 대한 것으로 시설명, 주소, 주요시설, 사용료, 관중규모 등에 대한 데이터가 제공되고 있습니다.
Author전라남도 함평군
URLhttps://www.data.go.kr/data/15011684/fileData.do

Alerts

Dataset has 1 (4.2%) duplicate rowsDuplicates
구분 has 10 (41.7%) missing valuesMissing
시설명 has 10 (41.7%) missing valuesMissing
주소 has 10 (41.7%) missing valuesMissing
주요시설 has 10 (41.7%) missing valuesMissing
비고 has 13 (54.2%) missing valuesMissing

Reproduction

Analysis started2024-03-23 06:30:36.085003
Analysis finished2024-03-23 06:30:38.242343
Duration2.16 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

MISSING 

Distinct7
Distinct (%)50.0%
Missing10
Missing (%)41.7%
Memory size324.0 B
2024-03-23T06:30:38.441504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length5.1428571
Min length3

Characters and Unicode

Total characters72
Distinct characters22
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

Unique4 ?
Unique (%)28.6%

Sample

1st row운동장 및 체육센터
2nd row운동장 및 체육센터
3rd row운동장 및 체육센터
4th row운동장 및 체육센터
5th row축구장
ValueCountFrequency (%)
운동장 4
18.2%
및 4
18.2%
체육센터 4
18.2%
야구장 4
18.2%
골프장 2
9.1%
축구장 1
 
4.5%
궁도장 1
 
4.5%
테니스장 1
 
4.5%
스포츠텔 1
 
4.5%
2024-03-23T06:30:39.535769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 13
18.1%
8
11.1%
구 5
 
6.9%
운 4
 
5.6%
및 4
 
5.6%
체 4
 
5.6%
육 4
 
5.6%
센 4
 
5.6%
터 4
 
5.6%
야 4
 
5.6%
Other values (12) 18
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64
88.9%
Space Separator 8
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 13
20.3%
구 5
 
7.8%
운 4
 
6.2%
및 4
 
6.2%
체 4
 
6.2%
육 4
 
6.2%
센 4
 
6.2%
터 4
 
6.2%
야 4
 
6.2%
동 4
 
6.2%
Other values (11) 14
21.9%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64
88.9%
Common 8
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 13
20.3%
구 5
 
7.8%
운 4
 
6.2%
및 4
 
6.2%
체 4
 
6.2%
육 4
 
6.2%
센 4
 
6.2%
터 4
 
6.2%
야 4
 
6.2%
동 4
 
6.2%
Other values (11) 14
21.9%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64
88.9%
ASCII 8
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 13
20.3%
구 5
 
7.8%
운 4
 
6.2%
및 4
 
6.2%
체 4
 
6.2%
육 4
 
6.2%
센 4
 
6.2%
터 4
 
6.2%
야 4
 
6.2%
동 4
 
6.2%
Other values (11) 14
21.9%
ASCII
ValueCountFrequency (%)
8
100.0%

시설명
Text

MISSING 

Distinct14
Distinct (%)100.0%
Missing10
Missing (%)41.7%
Memory size324.0 B
2024-03-23T06:30:40.158559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length7.2142857
Min length5

Characters and Unicode

Total characters101
Distinct characters50
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)100.0%

Sample

1st row함평문화체육센터
2nd row함평국민체육센터
3rd row함평공설운동장
4th row함평농어촌복합체육센터
5th row함평축구장
ValueCountFrequency (%)
함평문화체육센터 1
 
7.1%
함평국민체육센터 1
 
7.1%
함평공설운동장 1
 
7.1%
함평농어촌복합체육센터 1
 
7.1%
함평축구장 1
 
7.1%
전남야구장 1
 
7.1%
함평야구장 1
 
7.1%
함평리틀야구장 1
 
7.1%
함평베이스타운 1
 
7.1%
함평파크골프장 1
 
7.1%
Other values (4) 4
28.6%
2024-03-23T06:30:41.469825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
함 13
 
12.9%
평 13
 
12.9%
장 9
 
8.9%
구 5
 
5.0%
터 3
 
3.0%
야 3
 
3.0%
스 3
 
3.0%
센 3
 
3.0%
육 3
 
3.0%
체 3
 
3.0%
Other values (40) 43
42.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 99
98.0%
Open Punctuation 1
 
1.0%
Close Punctuation 1
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
함 13
 
13.1%
평 13
 
13.1%
장 9
 
9.1%
구 5
 
5.1%
터 3
 
3.0%
야 3
 
3.0%
스 3
 
3.0%
센 3
 
3.0%
육 3
 
3.0%
체 3
 
3.0%
Other values (38) 41
41.4%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 99
98.0%
Common 2
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
함 13
 
13.1%
평 13
 
13.1%
장 9
 
9.1%
구 5
 
5.1%
터 3
 
3.0%
야 3
 
3.0%
스 3
 
3.0%
센 3
 
3.0%
육 3
 
3.0%
체 3
 
3.0%
Other values (38) 41
41.4%
Common
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 99
98.0%
ASCII 2
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
함 13
 
13.1%
평 13
 
13.1%
장 9
 
9.1%
구 5
 
5.1%
터 3
 
3.0%
야 3
 
3.0%
스 3
 
3.0%
센 3
 
3.0%
육 3
 
3.0%
체 3
 
3.0%
Other values (38) 41
41.4%
ASCII
ValueCountFrequency (%)
( 1
50.0%
) 1
50.0%

주소
Text

MISSING 

Distinct7
Distinct (%)50.0%
Missing10
Missing (%)41.7%
Memory size324.0 B
2024-03-23T06:30:42.519341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length21.571429
Min length19

Characters and Unicode

Total characters302
Distinct characters41
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

Unique5 ?
Unique (%)35.7%

Sample

1st row전라남도 함평군 대동면 함장로 1377
2nd row전라남도 함평군 대동면 함장로 1377
3rd row전라남도 함평군 대동면 함장로 1377
4th row전라남도 함평군 함평읍 들샘길 36
5th row전라남도 함평군 대동면 함장로 1377
ValueCountFrequency (%)
전라남도 14
19.7%
함평군 14
19.7%
대동면 11
15.5%
함장로 6
8.5%
1377 6
8.5%
올림픽로 3
 
4.2%
281-20 3
 
4.2%
함평읍 3
 
4.2%
생태습지 1
 
1.4%
내대화길 1
 
1.4%
Other values (9) 9
12.7%
2024-03-23T06:30:44.520019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
57
18.9%
함 23
 
7.6%
평 17
 
5.6%
7 15
 
5.0%
전 14
 
4.6%
군 14
 
4.6%
라 14
 
4.6%
도 14
 
4.6%
남 14
 
4.6%
대 12
 
4.0%
Other values (31) 108
35.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 193
63.9%
Space Separator 57
 
18.9%
Decimal Number 49
 
16.2%
Dash Punctuation 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
함 23
11.9%
평 17
 
8.8%
전 14
 
7.3%
군 14
 
7.3%
라 14
 
7.3%
도 14
 
7.3%
남 14
 
7.3%
대 12
 
6.2%
동 12
 
6.2%
면 11
 
5.7%
Other values (20) 48
24.9%
Decimal Number
ValueCountFrequency (%)
7 15
30.6%
1 10
20.4%
3 8
16.3%
2 6
 
12.2%
0 3
 
6.1%
8 3
 
6.1%
4 2
 
4.1%
6 1
 
2.0%
9 1
 
2.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 193
63.9%
Common 109
36.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
함 23
11.9%
평 17
 
8.8%
전 14
 
7.3%
군 14
 
7.3%
라 14
 
7.3%
도 14
 
7.3%
남 14
 
7.3%
대 12
 
6.2%
동 12
 
6.2%
면 11
 
5.7%
Other values (20) 48
24.9%
Common
ValueCountFrequency (%)
57
52.3%
7 15
 
13.8%
1 10
 
9.2%
3 8
 
7.3%
2 6
 
5.5%
- 3
 
2.8%
0 3
 
2.8%
8 3
 
2.8%
4 2
 
1.8%
6 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 193
63.9%
ASCII 109
36.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
57
52.3%
7 15
 
13.8%
1 10
 
9.2%
3 8
 
7.3%
2 6
 
5.5%
- 3
 
2.8%
0 3
 
2.8%
8 3
 
2.8%
4 2
 
1.8%
6 1
 
0.9%
Hangul
ValueCountFrequency (%)
함 23
11.9%
평 17
 
8.8%
전 14
 
7.3%
군 14
 
7.3%
라 14
 
7.3%
도 14
 
7.3%
남 14
 
7.3%
대 12
 
6.2%
동 12
 
6.2%
면 11
 
5.7%
Other values (20) 48
24.9%

주요시설
Text

MISSING 

Distinct13
Distinct (%)92.9%
Missing10
Missing (%)41.7%
Memory size324.0 B
2024-03-23T06:30:45.169267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length24
Mean length20.142857
Min length3

Characters and Unicode

Total characters282
Distinct characters88
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
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 row실내체육관, 기계실, 방송실, 무대, 관람석 등
2nd row실내체육관, 기계실, 방송실, 무대, 관람석 등
3rd row공설운동장, 육상트랙
4th row찜질방, 운동실, 탈의실, 샤워실
5th row경기장
ValueCountFrequency (%)
등 7
 
10.9%
야구장 3
 
4.7%
실내체육관 2
 
3.1%
경기장 2
 
3.1%
휴게실 2
 
3.1%
기계실 2
 
3.1%
객실 2
 
3.1%
화장실 2
 
3.1%
기록실 2
 
3.1%
방송실 2
 
3.1%
Other values (36) 38
59.4%
2024-03-23T06:30:46.208810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
50
 
17.7%
, 37
 
13.1%
실 22
 
7.8%
장 12
 
4.3%
기 8
 
2.8%
등 7
 
2.5%
관 6
 
2.1%
1 5
 
1.8%
2 4
 
1.4%
야 4
 
1.4%
Other values (78) 127
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 168
59.6%
Space Separator 50
 
17.7%
Other Punctuation 37
 
13.1%
Decimal Number 20
 
7.1%
Open Punctuation 2
 
0.7%
Other Symbol 2
 
0.7%
Close Punctuation 2
 
0.7%
Lowercase Letter 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
실 22
 
13.1%
장 12
 
7.1%
기 8
 
4.8%
등 7
 
4.2%
관 6
 
3.6%
야 4
 
2.4%
석 4
 
2.4%
내 3
 
1.8%
선 3
 
1.8%
동 3
 
1.8%
Other values (64) 96
57.1%
Decimal Number
ValueCountFrequency (%)
1 5
25.0%
2 4
20.0%
0 3
15.0%
7 2
 
10.0%
6 2
 
10.0%
4 2
 
10.0%
3 1
 
5.0%
8 1
 
5.0%
Space Separator
ValueCountFrequency (%)
50
100.0%
Other Punctuation
ValueCountFrequency (%)
, 37
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
m 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 168
59.6%
Common 113
40.1%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
실 22
 
13.1%
장 12
 
7.1%
기 8
 
4.8%
등 7
 
4.2%
관 6
 
3.6%
야 4
 
2.4%
석 4
 
2.4%
내 3
 
1.8%
선 3
 
1.8%
동 3
 
1.8%
Other values (64) 96
57.1%
Common
ValueCountFrequency (%)
50
44.2%
, 37
32.7%
1 5
 
4.4%
2 4
 
3.5%
0 3
 
2.7%
( 2
 
1.8%
7 2
 
1.8%
6 2
 
1.8%
4 2
 
1.8%
㎡ 2
 
1.8%
Other values (3) 4
 
3.5%
Latin
ValueCountFrequency (%)
m 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 168
59.6%
ASCII 112
39.7%
CJK Compat 2
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
50
44.6%
, 37
33.0%
1 5
 
4.5%
2 4
 
3.6%
0 3
 
2.7%
( 2
 
1.8%
7 2
 
1.8%
6 2
 
1.8%
4 2
 
1.8%
) 2
 
1.8%
Other values (3) 3
 
2.7%
Hangul
ValueCountFrequency (%)
실 22
 
13.1%
장 12
 
7.1%
기 8
 
4.8%
등 7
 
4.2%
관 6
 
3.6%
야 4
 
2.4%
석 4
 
2.4%
내 3
 
1.8%
선 3
 
1.8%
동 3
 
1.8%
Other values (64) 96
57.1%
CJK Compat
ValueCountFrequency (%)
㎡ 2
100.0%

사용료
Categorical

Distinct3
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size324.0 B
유료
10 
<NA>
10 
무료
4 

Length

Max length4
Median length2
Mean length2.8333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유료
2nd row유료
3rd row유료
4th row무료
5th row유료

Common Values

ValueCountFrequency (%)
유료 10
41.7%
<NA> 10
41.7%
무료 4
 
16.7%

Length

2024-03-23T06:30:46.753348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T06:30:47.089449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유료 10
41.7%
na 10
41.7%
무료 4
 
16.7%

비고
Text

MISSING 

Distinct10
Distinct (%)90.9%
Missing13
Missing (%)54.2%
Memory size324.0 B
2024-03-23T06:30:47.464045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length11.272727
Min length6

Characters and Unicode

Total characters124
Distinct characters33
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

Unique9 ?
Unique (%)81.8%

Sample

1st row1000여명(관중석) 수용
2nd row1000여명 수용
3rd row9000여명(관중석) 수용
4th row인조잔디구장
5th row150석(관중석)
ValueCountFrequency (%)
수용 3
13.6%
150석(관중석 2
 
9.1%
동시 2
 
9.1%
수용가능 2
 
9.1%
가능(조명시설 2
 
9.1%
설치 2
 
9.1%
1000여명(관중석 1
 
4.5%
1000여명 1
 
4.5%
9000여명(관중석 1
 
4.5%
인조잔디구장 1
 
4.5%
Other values (5) 5
22.7%
2024-03-23T06:30:48.535536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
 
10.5%
11
 
8.9%
명 7
 
5.6%
용 7
 
5.6%
석 6
 
4.8%
( 6
 
4.8%
) 6
 
4.8%
수 5
 
4.0%
1 5
 
4.0%
여 5
 
4.0%
Other values (23) 53
42.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 78
62.9%
Decimal Number 23
 
18.5%
Space Separator 11
 
8.9%
Open Punctuation 6
 
4.8%
Close Punctuation 6
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
명 7
 
9.0%
용 7
 
9.0%
석 6
 
7.7%
수 5
 
6.4%
여 5
 
6.4%
시 4
 
5.1%
중 4
 
5.1%
관 4
 
5.1%
설 4
 
5.1%
능 4
 
5.1%
Other values (15) 28
35.9%
Decimal Number
ValueCountFrequency (%)
0 13
56.5%
1 5
 
21.7%
5 3
 
13.0%
9 1
 
4.3%
8 1
 
4.3%
Space Separator
ValueCountFrequency (%)
11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 78
62.9%
Common 46
37.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
명 7
 
9.0%
용 7
 
9.0%
석 6
 
7.7%
수 5
 
6.4%
여 5
 
6.4%
시 4
 
5.1%
중 4
 
5.1%
관 4
 
5.1%
설 4
 
5.1%
능 4
 
5.1%
Other values (15) 28
35.9%
Common
ValueCountFrequency (%)
0 13
28.3%
11
23.9%
( 6
13.0%
) 6
13.0%
1 5
 
10.9%
5 3
 
6.5%
9 1
 
2.2%
8 1
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 78
62.9%
ASCII 46
37.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
28.3%
11
23.9%
( 6
13.0%
) 6
13.0%
1 5
 
10.9%
5 3
 
6.5%
9 1
 
2.2%
8 1
 
2.2%
Hangul
ValueCountFrequency (%)
명 7
 
9.0%
용 7
 
9.0%
석 6
 
7.7%
수 5
 
6.4%
여 5
 
6.4%
시 4
 
5.1%
중 4
 
5.1%
관 4
 
5.1%
설 4
 
5.1%
능 4
 
5.1%
Other values (15) 28
35.9%

Correlations

2024-03-23T06:30:48.813946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분시설명주소주요시설사용료비고
구분1.0001.0000.8051.0000.4521.000
시설명1.0001.0001.0001.0001.0001.000
주소0.8051.0001.0001.0000.6491.000
주요시설1.0001.0001.0001.0001.0000.950
사용료0.4521.0000.6491.0001.0001.000
비고1.0001.0001.0000.9501.0001.000

Missing values

2024-03-23T06:30:37.076374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T06:30:37.639498image/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.
2024-03-23T06:30:38.003478image/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

구분시설명주소주요시설사용료비고
0운동장 및 체육센터함평문화체육센터전라남도 함평군 대동면 함장로 1377실내체육관, 기계실, 방송실, 무대, 관람석 등유료1000여명(관중석) 수용
1운동장 및 체육센터함평국민체육센터전라남도 함평군 대동면 함장로 1377실내체육관, 기계실, 방송실, 무대, 관람석 등유료1000여명 수용
2운동장 및 체육센터함평공설운동장전라남도 함평군 대동면 함장로 1377공설운동장, 육상트랙유료9000여명(관중석) 수용
3운동장 및 체육센터함평농어촌복합체육센터전라남도 함평군 함평읍 들샘길 36찜질방, 운동실, 탈의실, 샤워실무료<NA>
4축구장함평축구장전라남도 함평군 대동면 함장로 1377경기장유료인조잔디구장
5야구장전남야구장전라남도 함평군 대동면 올림픽로 281-20야구장, 기록실, 선수대기실 등유료150석(관중석)
6야구장함평야구장전라남도 함평군 대동면 올림픽로 281-20야구장, 사무실, 기록실, 심판실, 화장실, 조괄판, 조명시설 등유료150석(관중석)
7야구장함평리틀야구장전라남도 함평군 대동면 올림픽로 281-20야구장, 덕아웃 등유료<NA>
8야구장함평베이스타운전라남도 함평군 대동면 학동로 934객실, 실내연습장, 야외연습장 등유료150여명 동시 수용가능
9골프장함평파크골프장전라남도 함평군 함평읍 내교리 생태습지 내페어웨이 11,874㎡, 그 외 20,426㎡무료천연잔디구장
구분시설명주소주요시설사용료비고
14<NA><NA><NA><NA><NA><NA>
15<NA><NA><NA><NA><NA><NA>
16<NA><NA><NA><NA><NA><NA>
17<NA><NA><NA><NA><NA><NA>
18<NA><NA><NA><NA><NA><NA>
19<NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA>
22<NA><NA><NA><NA><NA><NA>
23<NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

구분시설명주소주요시설사용료비고# duplicates
0<NA><NA><NA><NA><NA><NA>10