Overview

Dataset statistics

Number of variables7
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory59.9 B

Variable types

Categorical1
Text6

Reproduction

Analysis started2024-03-14 02:46:56.711919
Analysis finished2024-03-14 02:46:57.093434
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct11
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size404.0 B
개발진흥지구
7 
시설보호지구
5 
경관지구
4 
미관지구
4 
보존지구
4 
Other values (6)
10 

Length

Max length8
Median length4
Mean length4.7647059
Min length2

Unique

Unique4 ?
Unique (%)11.8%

Sample

1st row총계
2nd row경관지구
3rd row경관지구
4th row경관지구
5th row경관지구

Common Values

ValueCountFrequency (%)
개발진흥지구 7
20.6%
시설보호지구 5
14.7%
경관지구 4
11.8%
미관지구 4
11.8%
보존지구 4
11.8%
고도지구 3
8.8%
취락지구 3
8.8%
총계 1
 
2.9%
방화지구 1
 
2.9%
방재지구 1
 
2.9%

Length

2024-03-14T11:46:57.144657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
개발진흥지구 7
20.6%
시설보호지구 5
14.7%
경관지구 4
11.8%
미관지구 4
11.8%
보존지구 4
11.8%
고도지구 3
8.8%
취락지구 3
8.8%
총계 1
 
2.9%
방화지구 1
 
2.9%
방재지구 1
 
2.9%

연도
Text

Distinct25
Distinct (%)73.5%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:46:57.256945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.5294118
Min length1

Characters and Unicode

Total characters86
Distinct characters52
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)64.7%

Sample

1st row(단위:㎢)
2nd row소계
3rd row자연
4th row수변
5th row시가지
ValueCountFrequency (%)
소계 7
20.6%
3
 
8.8%
자연 2
 
5.9%
공용시설 1
 
2.9%
단위:㎢ 1
 
2.9%
학교시설 1
 
2.9%
복합 1
 
2.9%
관광 1
 
2.9%
유통 1
 
2.9%
산업 1
 
2.9%
Other values (15) 15
44.1%
2024-03-14T11:46:57.525026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
계 8
 
9.3%
소 7
 
8.1%
시 6
 
7.0%
설 5
 
5.8%
- 3
 
3.5%
자 3
 
3.5%
연 2
 
2.3%
중 2
 
2.3%
화 2
 
2.3%
공 2
 
2.3%
Other values (42) 46
53.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 79
91.9%
Dash Punctuation 3
 
3.5%
Open Punctuation 1
 
1.2%
Other Punctuation 1
 
1.2%
Other Symbol 1
 
1.2%
Close Punctuation 1
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
계 8
 
10.1%
소 7
 
8.9%
시 6
 
7.6%
설 5
 
6.3%
자 3
 
3.8%
연 2
 
2.5%
중 2
 
2.5%
화 2
 
2.5%
공 2
 
2.5%
최 2
 
2.5%
Other values (37) 40
50.6%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Other Punctuation
ValueCountFrequency (%)
: 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎢ 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 79
91.9%
Common 7
 
8.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
계 8
 
10.1%
소 7
 
8.9%
시 6
 
7.6%
설 5
 
6.3%
자 3
 
3.8%
연 2
 
2.5%
중 2
 
2.5%
화 2
 
2.5%
공 2
 
2.5%
최 2
 
2.5%
Other values (37) 40
50.6%
Common
ValueCountFrequency (%)
- 3
42.9%
( 1
 
14.3%
: 1
 
14.3%
㎢ 1
 
14.3%
) 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 79
91.9%
ASCII 6
 
7.0%
CJK Compat 1
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
계 8
 
10.1%
소 7
 
8.9%
시 6
 
7.6%
설 5
 
6.3%
자 3
 
3.8%
연 2
 
2.5%
중 2
 
2.5%
화 2
 
2.5%
공 2
 
2.5%
최 2
 
2.5%
Other values (37) 40
50.6%
ASCII
ValueCountFrequency (%)
- 3
50.0%
( 1
 
16.7%
: 1
 
16.7%
) 1
 
16.7%
CJK Compat
ValueCountFrequency (%)
㎢ 1
100.0%

2009
Text

Distinct24
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:46:57.682892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.3235294
Min length1

Characters and Unicode

Total characters147
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)58.8%

Sample

1st row103.76
2nd row1.14
3rd row1.14
4th row-
5th row-
ValueCountFrequency (%)
8
23.5%
1.14 2
 
5.9%
22.38 2
 
5.9%
0.64 2
 
5.9%
0.00 1
 
2.9%
103.76 1
 
2.9%
0.25 1
 
2.9%
0.27 1
 
2.9%
18.92 1
 
2.9%
0.03 1
 
2.9%
Other values (14) 14
41.2%
2024-03-14T11:46:57.923837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 26
17.7%
26
17.7%
0 17
11.6%
1 12
8.2%
2 10
 
6.8%
4 9
 
6.1%
3 9
 
6.1%
- 8
 
5.4%
6 7
 
4.8%
7 7
 
4.8%
Other values (3) 16
10.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87
59.2%
Other Punctuation 26
 
17.7%
Space Separator 26
 
17.7%
Dash Punctuation 8
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
19.5%
1 12
13.8%
2 10
11.5%
4 9
10.3%
3 9
10.3%
6 7
8.0%
7 7
8.0%
8 6
 
6.9%
5 6
 
6.9%
9 4
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 147
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 26
17.7%
26
17.7%
0 17
11.6%
1 12
8.2%
2 10
 
6.8%
4 9
 
6.1%
3 9
 
6.1%
- 8
 
5.4%
6 7
 
4.8%
7 7
 
4.8%
Other values (3) 16
10.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 26
17.7%
26
17.7%
0 17
11.6%
1 12
8.2%
2 10
 
6.8%
4 9
 
6.1%
3 9
 
6.1%
- 8
 
5.4%
6 7
 
4.8%
7 7
 
4.8%
Other values (3) 16
10.9%

2010
Text

Distinct24
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:46:58.054455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.3235294
Min length1

Characters and Unicode

Total characters147
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)58.8%

Sample

1st row109.80
2nd row1.13
3rd row1.13
4th row-
5th row-
ValueCountFrequency (%)
8
23.5%
1.13 2
 
5.9%
33.43 2
 
5.9%
0.64 2
 
5.9%
0.00 1
 
2.9%
109.80 1
 
2.9%
0.25 1
 
2.9%
0.86 1
 
2.9%
19.97 1
 
2.9%
0.03 1
 
2.9%
Other values (14) 14
41.2%
2024-03-14T11:46:58.290792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 26
17.7%
26
17.7%
0 19
12.9%
3 15
10.2%
1 14
9.5%
4 10
 
6.8%
- 8
 
5.4%
9 7
 
4.8%
6 6
 
4.1%
8 5
 
3.4%
Other values (3) 11
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 87
59.2%
Other Punctuation 26
 
17.7%
Space Separator 26
 
17.7%
Dash Punctuation 8
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
21.8%
3 15
17.2%
1 14
16.1%
4 10
11.5%
9 7
 
8.0%
6 6
 
6.9%
8 5
 
5.7%
7 5
 
5.7%
2 3
 
3.4%
5 3
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 147
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 26
17.7%
26
17.7%
0 19
12.9%
3 15
10.2%
1 14
9.5%
4 10
 
6.8%
- 8
 
5.4%
9 7
 
4.8%
6 6
 
4.1%
8 5
 
3.4%
Other values (3) 11
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 147
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 26
17.7%
26
17.7%
0 19
12.9%
3 15
10.2%
1 14
9.5%
4 10
 
6.8%
- 8
 
5.4%
9 7
 
4.8%
6 6
 
4.1%
8 5
 
3.4%
Other values (3) 11
7.5%

2011
Text

Distinct26
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:46:58.431695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length4.5
Min length1

Characters and Unicode

Total characters153
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)67.6%

Sample

1st row138.09
2nd row13.81
3rd row1.13
4th row12.68
5th row-
ValueCountFrequency (%)
7
20.6%
0.64 2
 
5.9%
38.86 2
 
5.9%
138.09 1
 
2.9%
0.00 1
 
2.9%
0.07 1
 
2.9%
19.03 1
 
2.9%
0.09 1
 
2.9%
9.09 1
 
2.9%
10.21 1
 
2.9%
Other values (16) 16
47.1%
2024-03-14T11:46:58.689942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 27
17.6%
27
17.6%
0 20
13.1%
1 14
9.2%
3 12
7.8%
8 12
7.8%
9 10
 
6.5%
- 7
 
4.6%
6 6
 
3.9%
4 6
 
3.9%
Other values (3) 12
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92
60.1%
Other Punctuation 27
 
17.6%
Space Separator 27
 
17.6%
Dash Punctuation 7
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 20
21.7%
1 14
15.2%
3 12
13.0%
8 12
13.0%
9 10
10.9%
6 6
 
6.5%
4 6
 
6.5%
2 6
 
6.5%
7 4
 
4.3%
5 2
 
2.2%
Other Punctuation
ValueCountFrequency (%)
. 27
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 153
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 27
17.6%
27
17.6%
0 20
13.1%
1 14
9.2%
3 12
7.8%
8 12
7.8%
9 10
 
6.5%
- 7
 
4.6%
6 6
 
3.9%
4 6
 
3.9%
Other values (3) 12
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 153
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 27
17.6%
27
17.6%
0 20
13.1%
1 14
9.2%
3 12
7.8%
8 12
7.8%
9 10
 
6.5%
- 7
 
4.6%
6 6
 
3.9%
4 6
 
3.9%
Other values (3) 12
7.8%

2012
Text

Distinct24
Distinct (%)70.6%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:46:58.826813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length4.3529412
Min length1

Characters and Unicode

Total characters148
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)58.8%

Sample

1st row138.36
2nd row13.93
3rd row1.25
4th row12.68
5th row-
ValueCountFrequency (%)
8
23.5%
0.31 2
 
5.9%
0.64 2
 
5.9%
50.43 2
 
5.9%
8.20 1
 
2.9%
138.36 1
 
2.9%
18.26 1
 
2.9%
9.41 1
 
2.9%
9.58 1
 
2.9%
37.63 1
 
2.9%
Other values (14) 14
41.2%
2024-03-14T11:46:59.053032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 26
17.6%
26
17.6%
0 17
11.5%
3 14
9.5%
1 12
8.1%
8 10
 
6.8%
- 8
 
5.4%
4 7
 
4.7%
6 7
 
4.7%
2 7
 
4.7%
Other values (3) 14
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 88
59.5%
Other Punctuation 26
 
17.6%
Space Separator 26
 
17.6%
Dash Punctuation 8
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
19.3%
3 14
15.9%
1 12
13.6%
8 10
11.4%
4 7
8.0%
6 7
8.0%
2 7
8.0%
5 6
 
6.8%
9 5
 
5.7%
7 3
 
3.4%
Other Punctuation
ValueCountFrequency (%)
. 26
100.0%
Space Separator
ValueCountFrequency (%)
26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 148
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 26
17.6%
26
17.6%
0 17
11.5%
3 14
9.5%
1 12
8.1%
8 10
 
6.8%
- 8
 
5.4%
4 7
 
4.7%
6 7
 
4.7%
2 7
 
4.7%
Other values (3) 14
9.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 26
17.6%
26
17.6%
0 17
11.5%
3 14
9.5%
1 12
8.1%
8 10
 
6.8%
- 8
 
5.4%
4 7
 
4.7%
6 7
 
4.7%
2 7
 
4.7%
Other values (3) 14
9.5%

2013
Text

Distinct26
Distinct (%)76.5%
Missing0
Missing (%)0.0%
Memory size404.0 B
2024-03-14T11:46:59.176020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.4705882
Min length1

Characters and Unicode

Total characters152
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)67.6%

Sample

1st row146.51
2nd row13.81
3rd row1.13
4th row12.68
5th row-
ValueCountFrequency (%)
7
20.6%
0.64 2
 
5.9%
59.66 2
 
5.9%
146.51 1
 
2.9%
0.00 1
 
2.9%
0.07 1
 
2.9%
17.57 1
 
2.9%
0.05 1
 
2.9%
9.83 1
 
2.9%
8.57 1
 
2.9%
Other values (16) 16
47.1%
2024-03-14T11:46:59.404079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 27
17.8%
27
17.8%
0 15
9.9%
1 15
9.9%
6 11
7.2%
3 10
 
6.6%
5 9
 
5.9%
8 8
 
5.3%
- 7
 
4.6%
4 7
 
4.6%
Other values (3) 16
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 91
59.9%
Other Punctuation 27
 
17.8%
Space Separator 27
 
17.8%
Dash Punctuation 7
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
16.5%
1 15
16.5%
6 11
12.1%
3 10
11.0%
5 9
9.9%
8 8
8.8%
4 7
7.7%
7 7
7.7%
9 5
 
5.5%
2 4
 
4.4%
Other Punctuation
ValueCountFrequency (%)
. 27
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 152
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
. 27
17.8%
27
17.8%
0 15
9.9%
1 15
9.9%
6 11
7.2%
3 10
 
6.6%
5 9
 
5.9%
8 8
 
5.3%
- 7
 
4.6%
4 7
 
4.6%
Other values (3) 16
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 27
17.8%
27
17.8%
0 15
9.9%
1 15
9.9%
6 11
7.2%
3 10
 
6.6%
5 9
 
5.9%
8 8
 
5.3%
- 7
 
4.6%
4 7
 
4.6%
Other values (3) 16
10.5%

Correlations

2024-03-14T11:46:59.483204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분연도20092010201120122013
구분1.0000.0000.6670.6670.0000.4380.000
연도0.0001.0000.8140.8140.8080.4640.808
20090.6670.8141.0001.0000.9960.9981.000
20100.6670.8141.0001.0000.9960.9981.000
20110.0000.8080.9960.9961.0000.9961.000
20120.4380.4640.9980.9980.9961.0001.000
20130.0000.8081.0001.0001.0001.0001.000

Missing values

2024-03-14T11:46:56.978111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:46:57.061460image/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.

Sample

구분연도20092010201120122013
0총계(단위:㎢)103.76109.80138.09138.36146.51
1경관지구소계1.141.1313.8113.9313.81
2경관지구자연1.141.131.131.251.13
3경관지구수변--12.6812.6812.68
4경관지구시가지-----
5미관지구소계7.927.949.849.869.81
6미관지구중심0.540.540.570.570.57
7미관지구역사문화0.010.011.281.281.28
8미관지구일반7.377.397.998.017.96
9고도지구소계14.7014.6914.3914.3914.61
구분연도20092010201120122013
24취락지구자연22.3833.4338.8650.4359.66
25취락지구집단-----
26개발진흥지구소계45.2540.5638.8637.6336.53
27개발진흥지구주거16.4811.9110.219.588.57
28개발진흥지구산업7.567.329.099.419.83
29개발진흥지구유통0.030.030.09-0.05
30개발진흥지구관광18.9219.9719.0318.2617.57
31개발진흥지구복합0.270.860.070.070.07
32개발진흥지구특정1.990.470.370.310.44
33특정용도제한지구------