Overview

Dataset statistics

Number of variables12
Number of observations206
Missing cells1399
Missing cells (%)56.6%
Duplicate rows1
Duplicate rows (%)0.5%
Total size in memory19.4 KiB
Average record size in memory96.6 B

Variable types

Categorical5
Text7

Alerts

Dataset has 1 (0.5%) duplicate rowsDuplicates
Unnamed: 5 is highly overall correlated with 시도High correlation
시가화조정구역 is highly overall correlated with 시도High correlation
개발제한구역 is highly overall correlated with 시도High correlation
Unnamed: 3 is highly overall correlated with 시도High correlation
시도 is highly overall correlated with 개발제한구역 and 3 other fieldsHigh correlation
시도 is highly imbalanced (87.3%)Imbalance
개발제한구역 is highly imbalanced (83.7%)Imbalance
Unnamed: 3 is highly imbalanced (83.7%)Imbalance
시가화조정구역 is highly imbalanced (83.7%)Imbalance
Unnamed: 5 is highly imbalanced (83.7%)Imbalance
시군구 has 201 (97.6%) missing valuesMissing
수자원보호구역 has 198 (96.1%) missing valuesMissing
Unnamed: 7 has 198 (96.1%) missing valuesMissing
도시자연공원구역 has 198 (96.1%) missing valuesMissing
Unnamed: 9 has 198 (96.1%) missing valuesMissing
입지규제최소구역 has 203 (98.5%) missing valuesMissing
Unnamed: 11 has 203 (98.5%) missing valuesMissing

Reproduction

Analysis started2024-03-14 01:07:34.360342
Analysis finished2024-03-14 01:07:35.152081
Duration0.79 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
199 
전라북도
 
5
전라북도 소계
 
1
총계 :
 
1

Length

Max length7
Median length4
Mean length4.0194175
Min length4

Unique

Unique2 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 199
96.6%
전라북도 5
 
2.4%
전라북도 소계 1
 
0.5%
총계 : 1
 
0.5%

Length

2024-03-14T10:07:35.205340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:07:35.292788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 199
95.7%
전라북도 6
 
2.9%
소계 1
 
0.5%
총계 1
 
0.5%
1
 
0.5%

시군구
Text

MISSING 

Distinct5
Distinct (%)100.0%
Missing201
Missing (%)97.6%
Memory size1.7 KiB
2024-03-14T10:07:35.531460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters15
Distinct characters12
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

Unique5 ?
Unique (%)100.0%

Sample

1st row정읍시
2nd row장수군
3rd row임실군
4th row고창군
5th row부안군
ValueCountFrequency (%)
정읍시 1
20.0%
장수군 1
20.0%
임실군 1
20.0%
고창군 1
20.0%
부안군 1
20.0%
2024-03-14T10:07:35.957839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
군 4
26.7%
정 1
 
6.7%
읍 1
 
6.7%
시 1
 
6.7%
장 1
 
6.7%
수 1
 
6.7%
임 1
 
6.7%
실 1
 
6.7%
고 1
 
6.7%
창 1
 
6.7%
Other values (2) 2
13.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 4
26.7%
정 1
 
6.7%
읍 1
 
6.7%
시 1
 
6.7%
장 1
 
6.7%
수 1
 
6.7%
임 1
 
6.7%
실 1
 
6.7%
고 1
 
6.7%
창 1
 
6.7%
Other values (2) 2
13.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 4
26.7%
정 1
 
6.7%
읍 1
 
6.7%
시 1
 
6.7%
장 1
 
6.7%
수 1
 
6.7%
임 1
 
6.7%
실 1
 
6.7%
고 1
 
6.7%
창 1
 
6.7%
Other values (2) 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
군 4
26.7%
정 1
 
6.7%
읍 1
 
6.7%
시 1
 
6.7%
장 1
 
6.7%
수 1
 
6.7%
임 1
 
6.7%
실 1
 
6.7%
고 1
 
6.7%
창 1
 
6.7%
Other values (2) 2
13.3%

개발제한구역
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
198 
0
 
7
개소
 
1

Length

Max length4
Median length4
Mean length3.8883495
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row개소
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 198
96.1%
0 7
 
3.4%
개소 1
 
0.5%

Length

2024-03-14T10:07:36.056526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:07:36.137696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
96.1%
0 7
 
3.4%
개소 1
 
0.5%

Unnamed: 3
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
198 
0
 
7
면적
 
1

Length

Max length4
Median length4
Mean length3.8883495
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row면적
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 198
96.1%
0 7
 
3.4%
면적 1
 
0.5%

Length

2024-03-14T10:07:36.226354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:07:36.309850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
96.1%
0 7
 
3.4%
면적 1
 
0.5%

시가화조정구역
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
198 
0
 
7
개소
 
1

Length

Max length4
Median length4
Mean length3.8883495
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row개소
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 198
96.1%
0 7
 
3.4%
개소 1
 
0.5%

Length

2024-03-14T10:07:36.404111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:07:36.502005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
96.1%
0 7
 
3.4%
개소 1
 
0.5%

Unnamed: 5
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
<NA>
198 
0
 
7
면적
 
1

Length

Max length4
Median length4
Mean length3.8883495
Min length1

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row면적
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
<NA> 198
96.1%
0 7
 
3.4%
면적 1
 
0.5%

Length

2024-03-14T10:07:36.606217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:07:36.687784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 198
96.1%
0 7
 
3.4%
면적 1
 
0.5%

수자원보호구역
Text

MISSING 

Distinct4
Distinct (%)50.0%
Missing198
Missing (%)96.1%
Memory size1.7 KiB
2024-03-14T10:07:36.758502image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.125
Min length1

Characters and Unicode

Total characters9
Distinct characters5
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 (%)12.5%

Sample

1st row개소
2nd row1
3rd row0
4th row1
5th row0
ValueCountFrequency (%)
0 3
37.5%
1 2
25.0%
2 2
25.0%
개소 1
 
12.5%
2024-03-14T10:07:36.944148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
33.3%
1 2
22.2%
2 2
22.2%
개 1
 
11.1%
소 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
77.8%
Other Letter 2
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
42.9%
1 2
28.6%
2 2
28.6%
Other Letter
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
77.8%
Hangul 2
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
42.9%
1 2
28.6%
2 2
28.6%
Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
77.8%
Hangul 2
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
42.9%
1 2
28.6%
2 2
28.6%
Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Unnamed: 7
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing198
Missing (%)96.1%
Memory size1.7 KiB
2024-03-14T10:07:37.053905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length5.5
Min length1

Characters and Unicode

Total characters44
Distinct characters12
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

Unique3 ?
Unique (%)37.5%

Sample

1st row면적
2nd row5,938,000
3rd row0
4th row14,601,000
5th row0
ValueCountFrequency (%)
0 3
37.5%
20,539,000 2
25.0%
면적 1
 
12.5%
5,938,000 1
 
12.5%
14,601,000 1
 
12.5%
2024-03-14T10:07:37.282380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
40.9%
, 8
18.2%
5 3
 
6.8%
3 3
 
6.8%
9 3
 
6.8%
2 2
 
4.5%
1 2
 
4.5%
면 1
 
2.3%
적 1
 
2.3%
8 1
 
2.3%
Other values (2) 2
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 34
77.3%
Other Punctuation 8
 
18.2%
Other Letter 2
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
52.9%
5 3
 
8.8%
3 3
 
8.8%
9 3
 
8.8%
2 2
 
5.9%
1 2
 
5.9%
8 1
 
2.9%
4 1
 
2.9%
6 1
 
2.9%
Other Letter
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 42
95.5%
Hangul 2
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
42.9%
, 8
19.0%
5 3
 
7.1%
3 3
 
7.1%
9 3
 
7.1%
2 2
 
4.8%
1 2
 
4.8%
8 1
 
2.4%
4 1
 
2.4%
6 1
 
2.4%
Hangul
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 42
95.5%
Hangul 2
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
42.9%
, 8
19.0%
5 3
 
7.1%
3 3
 
7.1%
9 3
 
7.1%
2 2
 
4.8%
1 2
 
4.8%
8 1
 
2.4%
4 1
 
2.4%
6 1
 
2.4%
Hangul
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%

도시자연공원구역
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing198
Missing (%)96.1%
Memory size1.7 KiB
2024-03-14T10:07:37.383116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.125
Min length1

Characters and Unicode

Total characters9
Distinct characters6
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

Unique3 ?
Unique (%)37.5%

Sample

1st row개소
2nd row0
3rd row1
4th row0
5th row4
ValueCountFrequency (%)
0 3
37.5%
5 2
25.0%
개소 1
 
12.5%
1 1
 
12.5%
4 1
 
12.5%
2024-03-14T10:07:37.579017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 3
33.3%
5 2
22.2%
개 1
 
11.1%
소 1
 
11.1%
1 1
 
11.1%
4 1
 
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 7
77.8%
Other Letter 2
 
22.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
42.9%
5 2
28.6%
1 1
 
14.3%
4 1
 
14.3%
Other Letter
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Common 7
77.8%
Hangul 2
 
22.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
42.9%
5 2
28.6%
1 1
 
14.3%
4 1
 
14.3%
Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7
77.8%
Hangul 2
 
22.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
42.9%
5 2
28.6%
1 1
 
14.3%
4 1
 
14.3%
Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Unnamed: 9
Text

MISSING 

Distinct5
Distinct (%)62.5%
Missing198
Missing (%)96.1%
Memory size1.7 KiB
2024-03-14T10:07:37.777580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.875
Min length1

Characters and Unicode

Total characters39
Distinct characters11
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

Unique3 ?
Unique (%)37.5%

Sample

1st row면적
2nd row0
3rd row108,535
4th row0
5th row1,033,900
ValueCountFrequency (%)
0 3
37.5%
1,142,435 2
25.0%
면적 1
 
12.5%
108,535 1
 
12.5%
1,033,900 1
 
12.5%
2024-03-14T10:07:38.011293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 7
17.9%
, 7
17.9%
1 6
15.4%
3 5
12.8%
4 4
10.3%
5 4
10.3%
2 2
 
5.1%
면 1
 
2.6%
적 1
 
2.6%
8 1
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 30
76.9%
Other Punctuation 7
 
17.9%
Other Letter 2
 
5.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7
23.3%
1 6
20.0%
3 5
16.7%
4 4
13.3%
5 4
13.3%
2 2
 
6.7%
8 1
 
3.3%
9 1
 
3.3%
Other Letter
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37
94.9%
Hangul 2
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 7
18.9%
, 7
18.9%
1 6
16.2%
3 5
13.5%
4 4
10.8%
5 4
10.8%
2 2
 
5.4%
8 1
 
2.7%
9 1
 
2.7%
Hangul
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37
94.9%
Hangul 2
 
5.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 7
18.9%
, 7
18.9%
1 6
16.2%
3 5
13.5%
4 4
10.8%
5 4
10.8%
2 2
 
5.4%
8 1
 
2.7%
9 1
 
2.7%
Hangul
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%

입지규제최소구역
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing203
Missing (%)98.5%
Memory size1.7 KiB
2024-03-14T10:07:38.094151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.3333333
Min length1

Characters and Unicode

Total characters4
Distinct characters3
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 (%)33.3%

Sample

1st row개소
2nd row0
3rd row0
ValueCountFrequency (%)
0 2
66.7%
개소 1
33.3%
2024-03-14T10:07:38.269494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
50.0%
개 1
25.0%
소 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
50.0%
Other Letter 2
50.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%
Decimal Number
ValueCountFrequency (%)
0 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
50.0%
Hangul 2
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%
Common
ValueCountFrequency (%)
0 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
50.0%
Hangul 2
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
100.0%
Hangul
ValueCountFrequency (%)
개 1
50.0%
소 1
50.0%

Unnamed: 11
Text

MISSING 

Distinct2
Distinct (%)66.7%
Missing203
Missing (%)98.5%
Memory size1.7 KiB
2024-03-14T10:07:38.347681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.3333333
Min length1

Characters and Unicode

Total characters4
Distinct characters3
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 (%)33.3%

Sample

1st row면적
2nd row0
3rd row0
ValueCountFrequency (%)
0 2
66.7%
면적 1
33.3%
2024-03-14T10:07:38.523078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2
50.0%
면 1
25.0%
적 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2
50.0%
Other Letter 2
50.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%
Decimal Number
ValueCountFrequency (%)
0 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2
50.0%
Hangul 2
50.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%
Common
ValueCountFrequency (%)
0 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2
50.0%
Hangul 2
50.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2
100.0%
Hangul
ValueCountFrequency (%)
면 1
50.0%
적 1
50.0%

Correlations

2024-03-14T10:07:38.619469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도시군구개발제한구역Unnamed: 3시가화조정구역Unnamed: 5수자원보호구역Unnamed: 7도시자연공원구역Unnamed: 9입지규제최소구역Unnamed: 11
시도1.000NaNNaNNaNNaNNaN0.8600.3640.3640.364NaNNaN
시군구NaN1.000NaNNaNNaNNaN1.0001.0001.0001.000NaNNaN
개발제한구역NaNNaN1.0000.3960.3960.3961.0001.0001.0001.0000.0000.000
Unnamed: 3NaNNaN0.3961.0000.3960.3961.0001.0001.0001.0000.0000.000
시가화조정구역NaNNaN0.3960.3961.0000.3961.0001.0001.0001.0000.0000.000
Unnamed: 5NaNNaN0.3960.3960.3961.0001.0001.0001.0001.0000.0000.000
수자원보호구역0.8601.0001.0001.0001.0001.0001.0001.0000.8250.8250.0000.000
Unnamed: 70.3641.0001.0001.0001.0001.0001.0001.0000.8390.8390.0000.000
도시자연공원구역0.3641.0001.0001.0001.0001.0000.8250.8391.0001.0000.0000.000
Unnamed: 90.3641.0001.0001.0001.0001.0000.8250.8391.0001.0000.0000.000
입지규제최소구역NaNNaN0.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
Unnamed: 11NaNNaN0.0000.0000.0000.0000.0000.0000.0000.0000.0001.000
2024-03-14T10:07:38.742606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 5시가화조정구역개발제한구역Unnamed: 3시도
Unnamed: 51.0000.2180.2180.2181.000
시가화조정구역0.2181.0000.2180.2181.000
개발제한구역0.2180.2181.0000.2181.000
Unnamed: 30.2180.2180.2181.0001.000
시도1.0001.0001.0001.0001.000
2024-03-14T10:07:38.825123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도개발제한구역Unnamed: 3시가화조정구역Unnamed: 5
시도1.0001.0001.0001.0001.000
개발제한구역1.0001.0000.2180.2180.218
Unnamed: 31.0000.2181.0000.2180.218
시가화조정구역1.0000.2180.2181.0000.218
Unnamed: 51.0000.2180.2180.2181.000

Missing values

2024-03-14T10:07:34.765578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:07:34.896567image/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.
2024-03-14T10:07:35.031937image/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

시도시군구개발제한구역Unnamed: 3시가화조정구역Unnamed: 5수자원보호구역Unnamed: 7도시자연공원구역Unnamed: 9입지규제최소구역Unnamed: 11
0<NA><NA>개소면적개소면적개소면적개소면적개소면적
1전라북도정읍시000015,938,00000<NA><NA>
2전라북도장수군0000001108,535<NA><NA>
3전라북도임실군0000114,601,00000<NA><NA>
4전라북도고창군00000041,033,900<NA><NA>
5전라북도부안군00000000<NA><NA>
6전라북도 소계<NA>0000220,539,00051,142,43500
7총계 :<NA>0000220,539,00051,142,43500
8<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
9<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
시도시군구개발제한구역Unnamed: 3시가화조정구역Unnamed: 5수자원보호구역Unnamed: 7도시자연공원구역Unnamed: 9입지규제최소구역Unnamed: 11
196<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
197<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
198<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
199<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
200<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
201<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
202<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
203<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
204<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
205<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>

Duplicate rows

Most frequently occurring

시도시군구개발제한구역Unnamed: 3시가화조정구역Unnamed: 5수자원보호구역Unnamed: 7도시자연공원구역Unnamed: 9입지규제최소구역Unnamed: 11# duplicates
0<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>198