Overview

Dataset statistics

Number of variables18
Number of observations112
Missing cells1247
Missing cells (%)61.9%
Duplicate rows6
Duplicate rows (%)5.4%
Total size in memory15.9 KiB
Average record size in memory145.2 B

Variable types

Text11
Categorical1
Unsupported6

Dataset

Description이 데이터는 2021년 11월 2일 기준으로 남원시 국도 및 지방도에 대한 도로종류, 노선명, 시설명, 총길이, 총폭, 교통량, 준공년도 등에 대한 데이터 입니다.
Author전라북도 남원시
URLhttps://www.data.go.kr/data/3075515/fileData.do

Alerts

Unnamed: 10 has constant value ""Constant
Unnamed: 11 has constant value ""Constant
Unnamed: 12 has constant value ""Constant
Unnamed: 14 has constant value ""Constant
Unnamed: 15 has constant value ""Constant
Unnamed: 16 has constant value ""Constant
Unnamed: 17 has constant value ""Constant
Dataset has 6 (5.4%) duplicate rowsDuplicates
1-2〈개발규제지역면적〉 has 106 (94.6%) missing valuesMissing
Unnamed: 2 has 9 (8.0%) missing valuesMissing
Unnamed: 3 has 7 (6.2%) missing valuesMissing
Unnamed: 4 has 12 (10.7%) missing valuesMissing
Unnamed: 5 has 3 (2.7%) missing valuesMissing
Unnamed: 6 has 2 (1.8%) missing valuesMissing
Unnamed: 7 has 3 (2.7%) missing valuesMissing
Unnamed: 8 has 109 (97.3%) missing valuesMissing
Unnamed: 9 has 110 (98.2%) missing valuesMissing
Unnamed: 10 has 111 (99.1%) missing valuesMissing
Unnamed: 11 has 111 (99.1%) missing valuesMissing
Unnamed: 12 has 111 (99.1%) missing valuesMissing
Unnamed: 13 has 109 (97.3%) missing valuesMissing
Unnamed: 14 has 111 (99.1%) missing valuesMissing
Unnamed: 15 has 111 (99.1%) missing valuesMissing
Unnamed: 16 has 111 (99.1%) missing valuesMissing
Unnamed: 17 has 111 (99.1%) missing valuesMissing
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 08:52:54.707149
Analysis finished2023-12-12 08:52:56.315334
Duration1.61 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

1-2〈개발규제지역면적〉
Text

MISSING 

Distinct6
Distinct (%)100.0%
Missing106
Missing (%)94.6%
Memory size1.0 KiB
2023-12-12T17:52:56.429305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length5.5
Min length1

Characters and Unicode

Total characters33
Distinct characters23
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 (%)100.0%

Sample

1st row종류
2nd row계
3rd row상수원보호구역
4th row자연환경보전지역
5th row문화재보호구역
ValueCountFrequency (%)
종류 1
16.7%
계 1
16.7%
상수원보호구역 1
16.7%
자연환경보전지역 1
16.7%
문화재보호구역 1
16.7%
백두대간보호구역 1
16.7%
2023-12-12T17:52:56.811020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 4
 
12.1%
역 4
 
12.1%
호 3
 
9.1%
구 3
 
9.1%
종 1
 
3.0%
전 1
 
3.0%
대 1
 
3.0%
두 1
 
3.0%
백 1
 
3.0%
재 1
 
3.0%
Other values (13) 13
39.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 4
 
12.1%
역 4
 
12.1%
호 3
 
9.1%
구 3
 
9.1%
종 1
 
3.0%
전 1
 
3.0%
대 1
 
3.0%
두 1
 
3.0%
백 1
 
3.0%
재 1
 
3.0%
Other values (13) 13
39.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 4
 
12.1%
역 4
 
12.1%
호 3
 
9.1%
구 3
 
9.1%
종 1
 
3.0%
전 1
 
3.0%
대 1
 
3.0%
두 1
 
3.0%
백 1
 
3.0%
재 1
 
3.0%
Other values (13) 13
39.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 4
 
12.1%
역 4
 
12.1%
호 3
 
9.1%
구 3
 
9.1%
종 1
 
3.0%
전 1
 
3.0%
대 1
 
3.0%
두 1
 
3.0%
백 1
 
3.0%
재 1
 
3.0%
Other values (13) 13
39.4%

Unnamed: 1
Categorical

Distinct8
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.0 KiB
국가지정
30 
문화재자료
30 
시도지정
28 
<NA>
19 
소 계
 
2
Other values (3)
 
3

Length

Max length5
Median length4
Mean length4.25
Min length2

Unique

Unique3 ?
Unique (%)2.7%

Sample

1st row<NA>
2nd row구분
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
국가지정 30
26.8%
문화재자료 30
26.8%
시도지정 28
25.0%
<NA> 19
17.0%
소 계 2
 
1.8%
구분 1
 
0.9%
핵심구역 1
 
0.9%
완충구역 1
 
0.9%

Length

2023-12-12T17:52:57.066866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:52:57.225562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국가지정 30
26.3%
문화재자료 30
26.3%
시도지정 28
24.6%
na 19
16.7%
소 2
 
1.8%
계 2
 
1.8%
구분 1
 
0.9%
핵심구역 1
 
0.9%
완충구역 1
 
0.9%

Unnamed: 2
Text

MISSING 

Distinct95
Distinct (%)92.2%
Missing9
Missing (%)8.0%
Memory size1.0 KiB
2023-12-12T17:52:57.549997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length7.3106796
Min length3

Characters and Unicode

Total characters753
Distinct characters160
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique88 ?
Unique (%)85.4%

Sample

1st row보호구역명칭
2nd row상수원보호구역
3rd row자연환경보전
4th row소 계
5th row 백장암 삼층석탑
ValueCountFrequency (%)
실상사 9
 
4.8%
석불입상 6
 
3.2%
남원 6
 
3.2%
만복사지 5
 
2.6%
사 4
 
2.1%
정 3
 
1.6%
계 3
 
1.6%
선원사 3
 
1.6%
삼층석탑 3
 
1.6%
소 3
 
1.6%
Other values (126) 144
76.2%
2023-12-12T17:52:58.009024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
90
 
12.0%
  79
 
10.5%
사 35
 
4.6%
상 31
 
4.1%
석 24
 
3.2%
원 19
 
2.5%
리 16
 
2.1%
암 12
 
1.6%
산 12
 
1.6%
지 12
 
1.6%
Other values (150) 423
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 580
77.0%
Space Separator 169
 
22.4%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 35
 
6.0%
상 31
 
5.3%
석 24
 
4.1%
원 19
 
3.3%
리 16
 
2.8%
암 12
 
2.1%
산 12
 
2.1%
지 12
 
2.1%
실 11
 
1.9%
불 11
 
1.9%
Other values (146) 397
68.4%
Space Separator
ValueCountFrequency (%)
90
53.3%
  79
46.7%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 580
77.0%
Common 173
 
23.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 35
 
6.0%
상 31
 
5.3%
석 24
 
4.1%
원 19
 
3.3%
리 16
 
2.8%
암 12
 
2.1%
산 12
 
2.1%
지 12
 
2.1%
실 11
 
1.9%
불 11
 
1.9%
Other values (146) 397
68.4%
Common
ValueCountFrequency (%)
90
52.0%
  79
45.7%
( 2
 
1.2%
) 2
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 580
77.0%
ASCII 94
 
12.5%
None 79
 
10.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
90
95.7%
( 2
 
2.1%
) 2
 
2.1%
None
ValueCountFrequency (%)
  79
100.0%
Hangul
ValueCountFrequency (%)
사 35
 
6.0%
상 31
 
5.3%
석 24
 
4.1%
원 19
 
3.3%
리 16
 
2.8%
암 12
 
2.1%
산 12
 
2.1%
지 12
 
2.1%
실 11
 
1.9%
불 11
 
1.9%
Other values (146) 397
68.4%

Unnamed: 3
Text

MISSING 

Distinct89
Distinct (%)84.8%
Missing7
Missing (%)6.2%
Memory size1.0 KiB
2023-12-12T17:52:58.430523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length10.171429
Min length3

Characters and Unicode

Total characters1068
Distinct characters106
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

Unique78 ?
Unique (%)74.3%

Sample

1st row위치(소재지)
2nd row1개소
3rd row남원시 도통동 574
4th row1개소
5th row남원시 운봉읍등 관내일원
ValueCountFrequency (%)
산내 15
 
5.4%
남원시 14
 
5.1%
일원 13
 
4.7%
입석 10
 
3.6%
주생 9
 
3.2%
왕정동 7
 
2.5%
57 6
 
2.2%
도통동 5
 
1.8%
이백 5
 
1.8%
수지 4
 
1.4%
Other values (146) 189
68.2%
2023-12-12T17:52:59.029589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
174
 
16.3%
  79
 
7.4%
1 63
 
5.9%
동 46
 
4.3%
산 45
 
4.2%
- 42
 
3.9%
외 32
 
3.0%
2 31
 
2.9%
5 29
 
2.7%
4 28
 
2.6%
Other values (96) 499
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 493
46.2%
Decimal Number 278
26.0%
Space Separator 253
23.7%
Dash Punctuation 42
 
3.9%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 46
 
9.3%
산 45
 
9.1%
외 32
 
6.5%
원 28
 
5.7%
내 20
 
4.1%
주 15
 
3.0%
남 14
 
2.8%
시 14
 
2.8%
일 14
 
2.8%
면 13
 
2.6%
Other values (81) 252
51.1%
Decimal Number
ValueCountFrequency (%)
1 63
22.7%
2 31
11.2%
5 29
10.4%
4 28
10.1%
6 28
10.1%
3 27
9.7%
7 24
 
8.6%
9 18
 
6.5%
8 17
 
6.1%
0 13
 
4.7%
Space Separator
ValueCountFrequency (%)
174
68.8%
  79
31.2%
Dash Punctuation
ValueCountFrequency (%)
- 42
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 575
53.8%
Hangul 493
46.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 46
 
9.3%
산 45
 
9.1%
외 32
 
6.5%
원 28
 
5.7%
내 20
 
4.1%
주 15
 
3.0%
남 14
 
2.8%
시 14
 
2.8%
일 14
 
2.8%
면 13
 
2.6%
Other values (81) 252
51.1%
Common
ValueCountFrequency (%)
174
30.3%
  79
13.7%
1 63
 
11.0%
- 42
 
7.3%
2 31
 
5.4%
5 29
 
5.0%
4 28
 
4.9%
6 28
 
4.9%
3 27
 
4.7%
7 24
 
4.2%
Other values (5) 50
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 496
46.4%
Hangul 493
46.2%
None 79
 
7.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
174
35.1%
1 63
 
12.7%
- 42
 
8.5%
2 31
 
6.2%
5 29
 
5.8%
4 28
 
5.6%
6 28
 
5.6%
3 27
 
5.4%
7 24
 
4.8%
9 18
 
3.6%
Other values (4) 32
 
6.5%
None
ValueCountFrequency (%)
  79
100.0%
Hangul
ValueCountFrequency (%)
동 46
 
9.3%
산 45
 
9.1%
외 32
 
6.5%
원 28
 
5.7%
내 20
 
4.1%
주 15
 
3.0%
남 14
 
2.8%
시 14
 
2.8%
일 14
 
2.8%
면 13
 
2.6%
Other values (81) 252
51.1%

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing12
Missing (%)10.7%
Memory size1.0 KiB

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)2.7%
Memory size1.0 KiB

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)1.8%
Memory size1.0 KiB

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)2.7%
Memory size1.0 KiB

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing109
Missing (%)97.3%
Memory size1.0 KiB

Unnamed: 9
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing110
Missing (%)98.2%
Memory size1.0 KiB
2023-12-12T17:52:59.259067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length9.5
Mean length9.5
Min length1

Characters and Unicode

Total characters19
Distinct characters18
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

Unique2 ?
Unique (%)100.0%

Sample

1st row타 개발규제지역과 중복면적(천㎡)
2nd row계
ValueCountFrequency (%)
타 1
25.0%
개발규제지역과 1
25.0%
중복면적(천㎡ 1
25.0%
계 1
25.0%
2023-12-12T17:52:59.628612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
 
10.5%
타 1
 
5.3%
) 1
 
5.3%
㎡ 1
 
5.3%
천 1
 
5.3%
( 1
 
5.3%
적 1
 
5.3%
면 1
 
5.3%
복 1
 
5.3%
중 1
 
5.3%
Other values (8) 8
42.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14
73.7%
Space Separator 2
 
10.5%
Close Punctuation 1
 
5.3%
Other Symbol 1
 
5.3%
Open Punctuation 1
 
5.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
타 1
 
7.1%
천 1
 
7.1%
적 1
 
7.1%
면 1
 
7.1%
복 1
 
7.1%
중 1
 
7.1%
과 1
 
7.1%
역 1
 
7.1%
지 1
 
7.1%
제 1
 
7.1%
Other values (4) 4
28.6%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎡ 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14
73.7%
Common 5
 
26.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
타 1
 
7.1%
천 1
 
7.1%
적 1
 
7.1%
면 1
 
7.1%
복 1
 
7.1%
중 1
 
7.1%
과 1
 
7.1%
역 1
 
7.1%
지 1
 
7.1%
제 1
 
7.1%
Other values (4) 4
28.6%
Common
ValueCountFrequency (%)
2
40.0%
) 1
20.0%
㎡ 1
20.0%
( 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14
73.7%
ASCII 4
 
21.1%
CJK Compat 1
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
50.0%
) 1
25.0%
( 1
25.0%
Hangul
ValueCountFrequency (%)
타 1
 
7.1%
천 1
 
7.1%
적 1
 
7.1%
면 1
 
7.1%
복 1
 
7.1%
중 1
 
7.1%
과 1
 
7.1%
역 1
 
7.1%
지 1
 
7.1%
제 1
 
7.1%
Other values (4) 4
28.6%
CJK Compat
ValueCountFrequency (%)
㎡ 1
100.0%

Unnamed: 10
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing111
Missing (%)99.1%
Memory size1.0 KiB
2023-12-12T17:52:59.785297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length9
Min length9

Characters and Unicode

Total characters9
Distinct characters9
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

Unique1 ?
Unique (%)100.0%

Sample

1st row군사시설 보호구역
ValueCountFrequency (%)
군사시설 1
50.0%
보호구역 1
50.0%
2023-12-12T17:53:00.101941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 1
11.1%
사 1
11.1%
시 1
11.1%
설 1
11.1%
1
11.1%
보 1
11.1%
호 1
11.1%
구 1
11.1%
역 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
88.9%
Control 1
 
11.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 1
12.5%
사 1
12.5%
시 1
12.5%
설 1
12.5%
보 1
12.5%
호 1
12.5%
구 1
12.5%
역 1
12.5%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
88.9%
Common 1
 
11.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 1
12.5%
사 1
12.5%
시 1
12.5%
설 1
12.5%
보 1
12.5%
호 1
12.5%
구 1
12.5%
역 1
12.5%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
88.9%
ASCII 1
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 1
12.5%
사 1
12.5%
시 1
12.5%
설 1
12.5%
보 1
12.5%
호 1
12.5%
구 1
12.5%
역 1
12.5%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing111
Missing (%)99.1%
Memory size1.0 KiB
2023-12-12T17:53:00.282890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
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

Unique1 ?
Unique (%)100.0%

Sample

1st row상수원 보호구역
ValueCountFrequency (%)
상수원 1
50.0%
보호구역 1
50.0%
2023-12-12T17:53:00.578028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
상 1
12.5%
수 1
12.5%
원 1
12.5%
1
12.5%
보 1
12.5%
호 1
12.5%
구 1
12.5%
역 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
87.5%
Control 1
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 1
14.3%
수 1
14.3%
원 1
14.3%
보 1
14.3%
호 1
14.3%
구 1
14.3%
역 1
14.3%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
87.5%
Common 1
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 1
14.3%
수 1
14.3%
원 1
14.3%
보 1
14.3%
호 1
14.3%
구 1
14.3%
역 1
14.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
87.5%
ASCII 1
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
상 1
14.3%
수 1
14.3%
원 1
14.3%
보 1
14.3%
호 1
14.3%
구 1
14.3%
역 1
14.3%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing111
Missing (%)99.1%
Memory size1.0 KiB
2023-12-12T17:53:00.727044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
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

Unique1 ?
Unique (%)100.0%

Sample

1st row개발제한 구역
ValueCountFrequency (%)
개발제한 1
50.0%
구역 1
50.0%
2023-12-12T17:53:01.033754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
개 1
14.3%
발 1
14.3%
제 1
14.3%
한 1
14.3%
1
14.3%
구 1
14.3%
역 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6
85.7%
Control 1
 
14.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 1
16.7%
발 1
16.7%
제 1
16.7%
한 1
16.7%
구 1
16.7%
역 1
16.7%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6
85.7%
Common 1
 
14.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 1
16.7%
발 1
16.7%
제 1
16.7%
한 1
16.7%
구 1
16.7%
역 1
16.7%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6
85.7%
ASCII 1
 
14.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
개 1
16.7%
발 1
16.7%
제 1
16.7%
한 1
16.7%
구 1
16.7%
역 1
16.7%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing109
Missing (%)97.3%
Memory size1.0 KiB

Unnamed: 14
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing111
Missing (%)99.1%
Memory size1.0 KiB
2023-12-12T17:53:01.169324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters8
Distinct characters8
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

Unique1 ?
Unique (%)100.0%

Sample

1st row문화재 보호구역
ValueCountFrequency (%)
문화재 1
50.0%
보호구역 1
50.0%
2023-12-12T17:53:01.503055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
문 1
12.5%
화 1
12.5%
재 1
12.5%
1
12.5%
보 1
12.5%
호 1
12.5%
구 1
12.5%
역 1
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
87.5%
Control 1
 
12.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
문 1
14.3%
화 1
14.3%
재 1
14.3%
보 1
14.3%
호 1
14.3%
구 1
14.3%
역 1
14.3%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
87.5%
Common 1
 
12.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
문 1
14.3%
화 1
14.3%
재 1
14.3%
보 1
14.3%
호 1
14.3%
구 1
14.3%
역 1
14.3%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
87.5%
ASCII 1
 
12.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
문 1
14.3%
화 1
14.3%
재 1
14.3%
보 1
14.3%
호 1
14.3%
구 1
14.3%
역 1
14.3%
ASCII
ValueCountFrequency (%)
1
100.0%

Unnamed: 15
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing111
Missing (%)99.1%
Memory size1.0 KiB
2023-12-12T17:53:01.612136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
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

Unique1 ?
Unique (%)100.0%

Sample

1st row수변
ValueCountFrequency (%)
수변 1
100.0%
2023-12-12T17:53:01.941433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
수 1
50.0%
변 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 1
50.0%
변 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 1
50.0%
변 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
수 1
50.0%
변 1
50.0%

Unnamed: 16
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing111
Missing (%)99.1%
Memory size1.0 KiB
2023-12-12T17:53:02.136187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
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

Unique1 ?
Unique (%)100.0%

Sample

1st row백두대간
ValueCountFrequency (%)
백두대간 1
100.0%
2023-12-12T17:53:02.528751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
백 1
25.0%
두 1
25.0%
대 1
25.0%
간 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
백 1
25.0%
두 1
25.0%
대 1
25.0%
간 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
백 1
25.0%
두 1
25.0%
대 1
25.0%
간 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
백 1
25.0%
두 1
25.0%
대 1
25.0%
간 1
25.0%

Unnamed: 17
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing111
Missing (%)99.1%
Memory size1.0 KiB
2023-12-12T17:53:02.705522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters4
Distinct characters4
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

Unique1 ?
Unique (%)100.0%

Sample

1st row일반지역
ValueCountFrequency (%)
일반지역 1
100.0%
2023-12-12T17:53:03.015405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
일 1
25.0%
반 1
25.0%
지 1
25.0%
역 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 1
25.0%
반 1
25.0%
지 1
25.0%
역 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 1
25.0%
반 1
25.0%
지 1
25.0%
역 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
일 1
25.0%
반 1
25.0%
지 1
25.0%
역 1
25.0%

Correlations

2023-12-12T17:53:03.133326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
1-2〈개발규제지역면적〉Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 9
1-2〈개발규제지역면적〉1.000NaNNaN1.000NaN
Unnamed: 1NaN1.0000.0000.000NaN
Unnamed: 2NaN0.0001.0001.000NaN
Unnamed: 31.0000.0001.0001.000NaN
Unnamed: 9NaNNaNNaNNaN1.000

Missing values

2023-12-12T17:52:55.213999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:52:55.463590image/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.
2023-12-12T17:52:56.078542image/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

1-2〈개발규제지역면적〉Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
0<NA><NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
1종류구분보호구역명칭위치(소재지)지정일행정구역\n면적\n(천㎡)지정면적\n (천㎡)NaNNaN타 개발규제지역과 중복면적(천㎡)<NA><NA><NA>NaN<NA><NA><NA><NA>
2<NA><NA><NA><NA>NaNNaN계육지해양계군사시설 보호구역상수원 보호구역개발제한 구역자연환경\n보전지역문화재 보호구역수변백두대간일반지역
3계<NA><NA><NA>NaNNaNNaNNaNNaN<NA><NA><NA><NA>57084<NA><NA><NA><NA>
4상수원보호구역<NA><NA>1개소NaN7526404154150<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
5<NA><NA>상수원보호구역남원시 도통동 5742008.12.12752640415415NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
6자연환경보전지역<NA><NA>1개소NaN7526401079951079950<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
7<NA><NA>자연환경보전남원시 운봉읍등 관내일원2010. 8. 13752640107995107995NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
8문화재보호구역<NA><NA><NA>NaN24187.4581462.15121462.1512NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
9<NA>국가지정소 계<NA>NaN19916.645606.6025606.6025NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
1-2〈개발규제지역면적〉Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17
102<NA><NA>이백면남원시 이백면 일원05.9.94359912641264NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
103<NA><NA>아영면남원시 아영면 일원05.9.93548027112711NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
104<NA><NA>산내면남원시 산내면 일원05.9.91034544074540745NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
105<NA>소 계<NA>6개면NaN3604571455414554NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
106<NA>완충구역운봉읍남원시 운봉읍 일원05.9.96949015981598NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
107<NA><NA>주천면남원시 주천면 일원05.9.95464958865886NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
108<NA><NA>산동면남원시 산동면 일원05.9.95378534043404NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
109<NA><NA>이백면남원시 이백면 일원05.9.94359915891589NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
110<NA><NA>아영면남원시 아영면 일원05.9.93548020772077NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>
111<NA><NA>산내면남원시 산내면 일원05.9.910345400NaN<NA><NA><NA><NA>NaN<NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

1-2〈개발규제지역면적〉Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17# duplicates
0<NA>소 계<NA>6개면<NA><NA><NA><NA><NA><NA><NA><NA>2
1<NA><NA>산내면남원시 산내면 일원<NA><NA><NA><NA><NA><NA><NA><NA>2
2<NA><NA>산동면남원시 산동면 일원<NA><NA><NA><NA><NA><NA><NA><NA>2
3<NA><NA>아영면남원시 아영면 일원<NA><NA><NA><NA><NA><NA><NA><NA>2
4<NA><NA>이백면남원시 이백면 일원<NA><NA><NA><NA><NA><NA><NA><NA>2
5<NA><NA>주천면남원시 주천면 일원<NA><NA><NA><NA><NA><NA><NA><NA>2