Overview

Dataset statistics

Number of variables9
Number of observations23
Missing cells60
Missing cells (%)29.0%
Duplicate rows1
Duplicate rows (%)4.3%
Total size in memory1.8 KiB
Average record size in memory78.7 B

Variable types

Text6
Categorical2
Unsupported1

Alerts

Dataset has 1 (4.3%) duplicate rowsDuplicates
시군 has 6 (26.1%) missing valuesMissing
승마장명 has 6 (26.1%) missing valuesMissing
주 소 has 7 (30.4%) missing valuesMissing
총면적 has 6 (26.1%) missing valuesMissing
마필수 has 6 (26.1%) missing valuesMissing
마방수 has 6 (26.1%) missing valuesMissing
Unnamed: 8 has 23 (100.0%) missing valuesMissing
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 23:53:11.043990
Analysis finished2024-03-13 23:53:11.645331
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군
Text

MISSING 

Distinct10
Distinct (%)58.8%
Missing6
Missing (%)26.1%
Memory size316.0 B
2024-03-14T08:53:11.729491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.8823529
Min length1

Characters and Unicode

Total characters49
Distinct characters20
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

Unique6 ?
Unique (%)35.3%

Sample

1st row계
2nd row전주시
3rd row익산시
4th row익산시
5th row정읍시
ValueCountFrequency (%)
남원시 3
17.6%
김제시 3
17.6%
장수군 3
17.6%
익산시 2
11.8%
계 1
 
5.9%
전주시 1
 
5.9%
정읍시 1
 
5.9%
순창군 1
 
5.9%
고창군 1
 
5.9%
부안군 1
 
5.9%
2024-03-14T08:53:12.031855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 10
20.4%
군 6
12.2%
남 3
 
6.1%
김 3
 
6.1%
제 3
 
6.1%
장 3
 
6.1%
수 3
 
6.1%
원 3
 
6.1%
익 2
 
4.1%
산 2
 
4.1%
Other values (10) 11
22.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 49
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 10
20.4%
군 6
12.2%
남 3
 
6.1%
김 3
 
6.1%
제 3
 
6.1%
장 3
 
6.1%
수 3
 
6.1%
원 3
 
6.1%
익 2
 
4.1%
산 2
 
4.1%
Other values (10) 11
22.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 49
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 10
20.4%
군 6
12.2%
남 3
 
6.1%
김 3
 
6.1%
제 3
 
6.1%
장 3
 
6.1%
수 3
 
6.1%
원 3
 
6.1%
익 2
 
4.1%
산 2
 
4.1%
Other values (10) 11
22.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 49
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 10
20.4%
군 6
12.2%
남 3
 
6.1%
김 3
 
6.1%
제 3
 
6.1%
장 3
 
6.1%
수 3
 
6.1%
원 3
 
6.1%
익 2
 
4.1%
산 2
 
4.1%
Other values (10) 11
22.4%

승마장명
Text

MISSING 

Distinct17
Distinct (%)100.0%
Missing6
Missing (%)26.1%
Memory size316.0 B
2024-03-14T08:53:12.198541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length13
Mean length7.9411765
Min length5

Characters and Unicode

Total characters135
Distinct characters65
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

Unique17 ?
Unique (%)100.0%

Sample

1st row16(운영 12, 미운영 4)
2nd row전주승마장
3rd row풀잎승마장
4th row익산승마장
5th row웨스턴캠프
ValueCountFrequency (%)
승마클럽 3
 
11.5%
전주승마장 1
 
3.8%
미운영 1
 
3.8%
인디안 1
 
3.8%
아리울승마장 1
 
3.8%
해변승마클럽 1
 
3.8%
금과승마장 1
 
3.8%
장수힐스리조트승마장 1
 
3.8%
장수승마장 1
 
3.8%
장수승마체험장 1
 
3.8%
Other values (14) 14
53.8%
2024-03-14T08:53:12.454958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
마 16
 
11.9%
승 15
 
11.1%
장 13
 
9.6%
9
 
6.7%
클 4
 
3.0%
리 4
 
3.0%
럽 4
 
3.0%
산 3
 
2.2%
수 3
 
2.2%
1 2
 
1.5%
Other values (55) 62
45.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
87.4%
Space Separator 9
 
6.7%
Decimal Number 5
 
3.7%
Open Punctuation 1
 
0.7%
Other Punctuation 1
 
0.7%
Close Punctuation 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 16
 
13.6%
승 15
 
12.7%
장 13
 
11.0%
클 4
 
3.4%
리 4
 
3.4%
럽 4
 
3.4%
산 3
 
2.5%
수 3
 
2.5%
운 2
 
1.7%
영 2
 
1.7%
Other values (47) 52
44.1%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
4 1
20.0%
6 1
20.0%
2 1
20.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
87.4%
Common 17
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 16
 
13.6%
승 15
 
12.7%
장 13
 
11.0%
클 4
 
3.4%
리 4
 
3.4%
럽 4
 
3.4%
산 3
 
2.5%
수 3
 
2.5%
운 2
 
1.7%
영 2
 
1.7%
Other values (47) 52
44.1%
Common
ValueCountFrequency (%)
9
52.9%
1 2
 
11.8%
4 1
 
5.9%
6 1
 
5.9%
( 1
 
5.9%
2 1
 
5.9%
, 1
 
5.9%
) 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
87.4%
ASCII 17
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
마 16
 
13.6%
승 15
 
12.7%
장 13
 
11.0%
클 4
 
3.4%
리 4
 
3.4%
럽 4
 
3.4%
산 3
 
2.5%
수 3
 
2.5%
운 2
 
1.7%
영 2
 
1.7%
Other values (47) 52
44.1%
ASCII
ValueCountFrequency (%)
9
52.9%
1 2
 
11.8%
4 1
 
5.9%
6 1
 
5.9%
( 1
 
5.9%
2 1
 
5.9%
, 1
 
5.9%
) 1
 
5.9%

주 소
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing7
Missing (%)30.4%
Memory size316.0 B
2024-03-14T08:53:12.653767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18.5
Mean length16.5625
Min length14

Characters and Unicode

Total characters265
Distinct characters74
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

Unique16 ?
Unique (%)100.0%

Sample

1st row덕진구 호성동 호성로 19
2nd row익산시 금마면 갈산리 242-20
3rd row익산시 삼기면 용연리 산21-1
4th row정읍시 송산1길 142-101
5th row남원시 운봉읍 준향리 477-1
ValueCountFrequency (%)
남원시 3
 
4.8%
김제시 3
 
4.8%
장수군 3
 
4.8%
익산시 2
 
3.2%
천천면 2
 
3.2%
월곡리 2
 
3.2%
산92-1 1
 
1.6%
용지면 1
 
1.6%
부교리 1
 
1.6%
181-5 1
 
1.6%
Other values (43) 43
69.4%
2024-03-14T08:53:12.951176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
46
 
17.4%
1 13
 
4.9%
- 13
 
4.9%
리 13
 
4.9%
2 12
 
4.5%
면 11
 
4.2%
시 9
 
3.4%
4 8
 
3.0%
산 8
 
3.0%
8 7
 
2.6%
Other values (64) 125
47.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 146
55.1%
Decimal Number 60
22.6%
Space Separator 46
 
17.4%
Dash Punctuation 13
 
4.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 13
 
8.9%
면 11
 
7.5%
시 9
 
6.2%
산 8
 
5.5%
군 6
 
4.1%
천 5
 
3.4%
장 5
 
3.4%
읍 4
 
2.7%
수 4
 
2.7%
상 3
 
2.1%
Other values (52) 78
53.4%
Decimal Number
ValueCountFrequency (%)
1 13
21.7%
2 12
20.0%
4 8
13.3%
8 7
11.7%
7 5
 
8.3%
6 3
 
5.0%
3 3
 
5.0%
5 3
 
5.0%
0 3
 
5.0%
9 3
 
5.0%
Space Separator
ValueCountFrequency (%)
46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 146
55.1%
Common 119
44.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 13
 
8.9%
면 11
 
7.5%
시 9
 
6.2%
산 8
 
5.5%
군 6
 
4.1%
천 5
 
3.4%
장 5
 
3.4%
읍 4
 
2.7%
수 4
 
2.7%
상 3
 
2.1%
Other values (52) 78
53.4%
Common
ValueCountFrequency (%)
46
38.7%
1 13
 
10.9%
- 13
 
10.9%
2 12
 
10.1%
4 8
 
6.7%
8 7
 
5.9%
7 5
 
4.2%
6 3
 
2.5%
3 3
 
2.5%
5 3
 
2.5%
Other values (2) 6
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 146
55.1%
ASCII 119
44.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
46
38.7%
1 13
 
10.9%
- 13
 
10.9%
2 12
 
10.1%
4 8
 
6.7%
8 7
 
5.9%
7 5
 
4.2%
6 3
 
2.5%
3 3
 
2.5%
5 3
 
2.5%
Other values (2) 6
 
5.0%
Hangul
ValueCountFrequency (%)
리 13
 
8.9%
면 11
 
7.5%
시 9
 
6.2%
산 8
 
5.5%
군 6
 
4.1%
천 5
 
3.4%
장 5
 
3.4%
읍 4
 
2.7%
수 4
 
2.7%
상 3
 
2.1%
Other values (52) 78
53.4%

개설년도
Categorical

Distinct8
Distinct (%)34.8%
Missing0
Missing (%)0.0%
Memory size316.0 B
<NA>
6 
2013
4 
2008
4 
2010
3 
-
2 
Other values (3)
4 

Length

Max length4
Median length4
Mean length3.7391304
Min length1

Unique

Unique2 ?
Unique (%)8.7%

Sample

1st row-
2nd row2010
3rd row2012
4th row2013
5th row2001

Common Values

ValueCountFrequency (%)
<NA> 6
26.1%
2013 4
17.4%
2008 4
17.4%
2010 3
13.0%
- 2
 
8.7%
2012 2
 
8.7%
2001 1
 
4.3%
2009 1
 
4.3%

Length

2024-03-14T08:53:13.054423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:53:13.145398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 6
26.1%
2013 4
17.4%
2008 4
17.4%
2010 3
13.0%
2
 
8.7%
2012 2
 
8.7%
2001 1
 
4.3%
2009 1
 
4.3%

신고구분
Categorical

Distinct4
Distinct (%)17.4%
Missing0
Missing (%)0.0%
Memory size316.0 B
체육시설업
13 
<NA>
6 
농어촌형 승마시설
3 
체:13.농:3
 
1

Length

Max length9
Median length5
Mean length5.3913043
Min length4

Unique

Unique1 ?
Unique (%)4.3%

Sample

1st row체:13.농:3
2nd row체육시설업
3rd row체육시설업
4th row체육시설업
5th row체육시설업

Common Values

ValueCountFrequency (%)
체육시설업 13
56.5%
<NA> 6
26.1%
농어촌형 승마시설 3
 
13.0%
체:13.농:3 1
 
4.3%

Length

2024-03-14T08:53:13.515955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:53:13.595501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
체육시설업 13
50.0%
na 6
23.1%
농어촌형 3
 
11.5%
승마시설 3
 
11.5%
체:13.농:3 1
 
3.8%

총면적
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing6
Missing (%)26.1%
Memory size316.0 B
2024-03-14T08:53:13.718669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.7647059
Min length1

Characters and Unicode

Total characters98
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)88.2%

Sample

1st row-
2nd row23,484㎡
3rd row1,130㎡
4th row4,500㎡
5th row60,000㎡
ValueCountFrequency (%)
2
 
11.8%
11,570 1
 
5.9%
18,060㎡ 1
 
5.9%
512㎡ 1
 
5.9%
174.4㎡ 1
 
5.9%
26,110㎡ 1
 
5.9%
165,314㎡ 1
 
5.9%
31.361㎡ 1
 
5.9%
23,484㎡ 1
 
5.9%
3,835㎡ 1
 
5.9%
Other values (6) 6
35.3%
2024-03-14T08:53:14.004924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
14.3%
㎡ 14
14.3%
, 12
12.2%
0 11
11.2%
3 9
9.2%
5 7
7.1%
6 7
7.1%
2 7
7.1%
4 7
7.1%
7 3
 
3.1%
Other values (3) 7
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
69.4%
Other Symbol 14
 
14.3%
Other Punctuation 14
 
14.3%
Dash Punctuation 2
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.6%
0 11
16.2%
3 9
13.2%
5 7
10.3%
6 7
10.3%
2 7
10.3%
4 7
10.3%
7 3
 
4.4%
8 3
 
4.4%
Other Punctuation
ValueCountFrequency (%)
, 12
85.7%
. 2
 
14.3%
Other Symbol
ValueCountFrequency (%)
㎡ 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
14.3%
㎡ 14
14.3%
, 12
12.2%
0 11
11.2%
3 9
9.2%
5 7
7.1%
6 7
7.1%
2 7
7.1%
4 7
7.1%
7 3
 
3.1%
Other values (3) 7
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
85.7%
CJK Compat 14
 
14.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
16.7%
, 12
14.3%
0 11
13.1%
3 9
10.7%
5 7
8.3%
6 7
8.3%
2 7
8.3%
4 7
8.3%
7 3
 
3.6%
8 3
 
3.6%
Other values (2) 4
 
4.8%
CJK Compat
ValueCountFrequency (%)
㎡ 14
100.0%

마필수
Text

MISSING 

Distinct15
Distinct (%)88.2%
Missing6
Missing (%)26.1%
Memory size316.0 B
2024-03-14T08:53:14.169287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.6470588
Min length1

Characters and Unicode

Total characters28
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

Unique13 ?
Unique (%)76.5%

Sample

1st row220
2nd row19
3rd row11
4th row5
5th row12
ValueCountFrequency (%)
12 2
 
11.8%
2
 
11.8%
220 1
 
5.9%
19 1
 
5.9%
11 1
 
5.9%
5 1
 
5.9%
31 1
 
5.9%
8 1
 
5.9%
50 1
 
5.9%
17 1
 
5.9%
Other values (5) 5
29.4%
2024-03-14T08:53:14.441931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 8
28.6%
2 5
17.9%
3 3
 
10.7%
- 2
 
7.1%
0 2
 
7.1%
9 2
 
7.1%
5 2
 
7.1%
8 1
 
3.6%
7 1
 
3.6%
4 1
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 26
92.9%
Dash Punctuation 2
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 8
30.8%
2 5
19.2%
3 3
 
11.5%
0 2
 
7.7%
9 2
 
7.7%
5 2
 
7.7%
8 1
 
3.8%
7 1
 
3.8%
4 1
 
3.8%
6 1
 
3.8%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 8
28.6%
2 5
17.9%
3 3
 
10.7%
- 2
 
7.1%
0 2
 
7.1%
9 2
 
7.1%
5 2
 
7.1%
8 1
 
3.6%
7 1
 
3.6%
4 1
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 8
28.6%
2 5
17.9%
3 3
 
10.7%
- 2
 
7.1%
0 2
 
7.1%
9 2
 
7.1%
5 2
 
7.1%
8 1
 
3.6%
7 1
 
3.6%
4 1
 
3.6%

마방수
Text

MISSING 

Distinct16
Distinct (%)94.1%
Missing6
Missing (%)26.1%
Memory size316.0 B
2024-03-14T08:53:14.553196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length2
Mean length1.8823529
Min length1

Characters and Unicode

Total characters32
Distinct characters10
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

Unique15 ?
Unique (%)88.2%

Sample

1st row536
2nd row68
3rd row12
4th row17
5th row38
ValueCountFrequency (%)
2
 
11.8%
536 1
 
5.9%
12 1
 
5.9%
17 1
 
5.9%
38 1
 
5.9%
16 1
 
5.9%
10 1
 
5.9%
68 1
 
5.9%
20 1
 
5.9%
184 1
 
5.9%
Other values (6) 6
35.3%
2024-03-14T08:53:14.778021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6
18.8%
8 5
15.6%
6 4
12.5%
4 4
12.5%
3 3
9.4%
0 3
9.4%
- 2
 
6.2%
2 2
 
6.2%
7 2
 
6.2%
5 1
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
93.8%
Dash Punctuation 2
 
6.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6
20.0%
8 5
16.7%
6 4
13.3%
4 4
13.3%
3 3
10.0%
0 3
10.0%
2 2
 
6.7%
7 2
 
6.7%
5 1
 
3.3%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 32
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6
18.8%
8 5
15.6%
6 4
12.5%
4 4
12.5%
3 3
9.4%
0 3
9.4%
- 2
 
6.2%
2 2
 
6.2%
7 2
 
6.2%
5 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6
18.8%
8 5
15.6%
6 4
12.5%
4 4
12.5%
3 3
9.4%
0 3
9.4%
- 2
 
6.2%
2 2
 
6.2%
7 2
 
6.2%
5 1
 
3.1%

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing23
Missing (%)100.0%
Memory size339.0 B

Correlations

2024-03-14T08:53:14.856883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군승마장명주 소개설년도신고구분총면적마필수마방수
시군1.0001.0001.0000.6710.8940.8820.7570.962
승마장명1.0001.0001.0001.0001.0001.0001.0001.000
주 소1.0001.0001.0001.0001.0001.0001.0001.000
개설년도0.6711.0001.0001.0000.3311.0000.0000.890
신고구분0.8941.0001.0000.3311.0000.0001.0001.000
총면적0.8821.0001.0001.0000.0001.0000.9540.988
마필수0.7571.0001.0000.0001.0000.9541.0000.976
마방수0.9621.0001.0000.8901.0000.9880.9761.000
2024-03-14T08:53:14.950612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개설년도신고구분
개설년도1.0000.126
신고구분0.1261.000
2024-03-14T08:53:15.018011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개설년도신고구분
개설년도1.0000.126
신고구분0.1261.000

Missing values

2024-03-14T08:53:11.361082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T08:53:11.463510image/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.
2024-03-14T08:53:11.568307image/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

시군승마장명주 소개설년도신고구분총면적마필수마방수Unnamed: 8
0계16(운영 12, 미운영 4)<NA>-체:13.농:3-220536<NA>
1전주시전주승마장덕진구 호성동 호성로 192010체육시설업23,484㎡1968<NA>
2익산시풀잎승마장익산시 금마면 갈산리 242-202012체육시설업1,130㎡1112<NA>
3익산시익산승마장익산시 삼기면 용연리 산21-12013체육시설업4,500㎡517<NA>
4정읍시웨스턴캠프정읍시 송산1길 142-1012001체육시설업60,000㎡1238<NA>
5남원시한국경마축산고 승마클럽남원시 운봉읍 준향리 477-12010체육시설업5,637㎡3116<NA>
6남원시남원춘향그랑프리 승마랜드남원시 주천면 중송길 772012체육시설업1,642㎡810<NA>
7남원시지리산푸른언덕 승마클럽남원시 인월면 상우리 106-22008체육시설업3,835㎡12-<NA>
8김제시기전대 재활승마장김제시 용지면부교리 84-52013체육시설업22,532㎡5064<NA>
9김제시인디안 승마장김제시 만경읍 장산리 288-22008체육시설업11,5701748<NA>
시군승마장명주 소개설년도신고구분총면적마필수마방수Unnamed: 8
13장수군장수힐스리조트승마장장수군 천천면 월곡리 산92-12013농어촌형 승마시설26,110㎡330<NA>
14순창군금과승마장순창군 금과면 방축리 산33-82009체육시설업174.4㎡-7<NA>
15고창군해변승마클럽고창군 상하면 명사십리로 282-92013농어촌형 승마시설512㎡44<NA>
16부안군아리울승마장부안군 상서면 가오리 734-42008체육시설업18,060㎡1618<NA>
17<NA><NA><NA><NA><NA><NA><NA><NA><NA>
18<NA><NA><NA><NA><NA><NA><NA><NA><NA>
19<NA><NA><NA><NA><NA><NA><NA><NA><NA>
20<NA><NA><NA><NA><NA><NA><NA><NA><NA>
21<NA><NA><NA><NA><NA><NA><NA><NA><NA>
22<NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시군승마장명주 소개설년도신고구분총면적마필수마방수# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA>6