Overview

Dataset statistics

Number of variables20
Number of observations35
Missing cells193
Missing cells (%)27.6%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory5.6 KiB
Average record size in memory164.8 B

Variable types

Unsupported1
Text18
DateTime1

Dataset

Description2023-05-25
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201926

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 1 (2.9%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 10:09:58.187362
Analysis finished2024-02-10 10:10:06.867137
Duration8.68 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B

인구이동보고서(1호)
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T10:10:07.167091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10.5
Mean length7.875
Min length5

Characters and Unicode

Total characters126
Distinct characters43
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

Unique16 ?
Unique (%)100.0%

Sample

1st row행정기관 :
2nd row작성기준 :
3rd row시, 군, 구(읍면동)
4th row전월말세대수
5th row전월말인구수
ValueCountFrequency (%)
요 2
 
7.7%
인 2
 
7.7%
2
 
7.7%
금월말거주불명자수 1
 
3.8%
금월말인구수 1
 
3.8%
금월말세대수 1
 
3.8%
거주불명자수증감 1
 
3.8%
인구수증감 1
 
3.8%
세대수증감 1
 
3.8%
소 1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T10:10:08.119682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
수 11
 
8.7%
말 8
 
6.3%
월 8
 
6.3%
인 5
 
4.0%
자 5
 
4.0%
전 4
 
3.2%
감 4
 
3.2%
증 4
 
3.2%
금 4
 
3.2%
Other values (33) 61
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
82.5%
Control 12
 
9.5%
Space Separator 4
 
3.2%
Other Punctuation 4
 
3.2%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 4
 
3.8%
Other values (27) 47
45.2%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
: 2
50.0%
Control
ValueCountFrequency (%)
12
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
82.5%
Common 22
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 4
 
3.8%
Other values (27) 47
45.2%
Common
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
82.5%
ASCII 22
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%
Hangul
ValueCountFrequency (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 4
 
3.8%
Other values (27) 47
45.2%

Unnamed: 2
Text

MISSING 

Distinct9
Distinct (%)81.8%
Missing24
Missing (%)68.6%
Memory size412.0 B
2024-02-10T10:10:08.501769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3636364
Min length2

Characters and Unicode

Total characters26
Distinct characters17
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

Unique7 ?
Unique (%)63.6%

Sample

1st row전 입
2nd row복귀
3rd row출생
4th row등록
5th row국외
ValueCountFrequency (%)
국외 2
15.4%
기타 2
15.4%
전 2
15.4%
입 1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
출 1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T10:10:09.295652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
국 2
 
7.7%
기 2
 
7.7%
타 2
 
7.7%
전 2
 
7.7%
외 2
 
7.7%
출 2
 
7.7%
록 1
 
3.8%
말 1
 
3.8%
망 1
 
3.8%
Other values (7) 7
26.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
84.6%
Control 4
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 1
 
4.5%
Other values (6) 6
27.3%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
84.6%
Common 4
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
84.6%
ASCII 4
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 1
 
4.5%
Other values (6) 6
27.3%

Unnamed: 3
Text

MISSING 

Distinct7
Distinct (%)58.3%
Missing23
Missing (%)65.7%
Memory size412.0 B
2024-02-10T10:10:09.687298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters21
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

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 동구
2nd row2023.04 현재
3rd row계
4th row남자
5th row여자
ValueCountFrequency (%)
계 2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
동구 1
7.1%
2023.04 1
7.1%
현재 1
7.1%
2024-02-10T10:10:10.423932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
 
12.2%
자 4
 
9.8%
도 4
 
9.8%
3
 
7.3%
계 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
광 2
 
4.9%
남 2
 
4.9%
Other values (11) 13
31.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
75.6%
Decimal Number 6
 
14.6%
Space Separator 3
 
7.3%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 2
33.3%
3 1
16.7%
4 1
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
75.6%
Common 10
 
24.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
4 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
75.6%
ASCII 10
 
24.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
4 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T10:10:10.816693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters5
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

Unique0 ?
Unique (%)0.0%

Sample

1st row시군구내
2nd row시군구간
3rd row시군구내
4th row시군구간
ValueCountFrequency (%)
시군구내 2
50.0%
시군구간 2
50.0%
2024-02-10T10:10:11.622362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:12.023727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.0606061
Min length1

Characters and Unicode

Total characters101
Distinct characters15
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

Unique25 ?
Unique (%)75.8%

Sample

1st row합 계
2nd row54,507
3rd row106,247
4th row705
5th row106
ValueCountFrequency (%)
0 4
 
11.8%
1 2
 
5.9%
2 2
 
5.9%
290 2
 
5.9%
106 1
 
2.9%
705 1
 
2.9%
562 1
 
2.9%
703 1
 
2.9%
106,443 1
 
2.9%
54,667 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T10:10:12.994850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
14.9%
1 13
12.9%
7 13
12.9%
6 12
11.9%
2 11
10.9%
4 9
8.9%
5 7
6.9%
, 6
 
5.9%
3 5
 
5.0%
9 4
 
4.0%
Other values (5) 6
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 90
89.1%
Other Punctuation 6
 
5.9%
Space Separator 2
 
2.0%
Other Letter 2
 
2.0%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
16.7%
1 13
14.4%
7 13
14.4%
6 12
13.3%
2 11
12.2%
4 9
10.0%
5 7
7.8%
3 5
 
5.6%
9 4
 
4.4%
8 1
 
1.1%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
15.2%
1 13
13.1%
7 13
13.1%
6 12
12.1%
2 11
11.1%
4 9
9.1%
5 7
7.1%
, 6
 
6.1%
3 5
 
5.1%
9 4
 
4.0%
Other values (3) 4
 
4.0%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
15.2%
1 13
13.1%
7 13
13.1%
6 12
12.1%
2 11
11.1%
4 9
9.1%
5 7
7.1%
, 6
 
6.1%
3 5
 
5.1%
9 4
 
4.0%
Other values (3) 4
 
4.0%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:13.334393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters14
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

Unique19 ?
Unique (%)57.6%

Sample

1st row충장동
2nd row4,101
3rd row5,213
4th row37
5th row6
ValueCountFrequency (%)
0 8
24.2%
36 2
 
6.1%
68 2
 
6.1%
6 2
 
6.1%
15 1
 
3.0%
33 1
 
3.0%
4,137 1
 
3.0%
1 1
 
3.0%
47 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:10:14.207717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.9%
6 10
14.5%
3 9
13.0%
1 9
13.0%
4 7
10.1%
5 6
8.7%
, 4
 
5.8%
8 3
 
4.3%
2 3
 
4.3%
7 3
 
4.3%
Other values (4) 4
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
6 10
16.4%
3 9
14.8%
1 9
14.8%
4 7
11.5%
5 6
9.8%
8 3
 
4.9%
2 3
 
4.9%
7 3
 
4.9%
Other Letter
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.7%
6 10
15.2%
3 9
13.6%
1 9
13.6%
4 7
10.6%
5 6
9.1%
, 4
 
6.1%
8 3
 
4.5%
2 3
 
4.5%
7 3
 
4.5%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.7%
6 10
15.2%
3 9
13.6%
1 9
13.6%
4 7
10.6%
5 6
9.1%
, 4
 
6.1%
8 3
 
4.5%
2 3
 
4.5%
7 3
 
4.5%
Hangul
ValueCountFrequency (%)
충 1
33.3%
장 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:14.587570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
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 (%)48.5%

Sample

1st row동명동
2nd row2,447
3rd row3,724
4th row115
5th row7
ValueCountFrequency (%)
0 9
27.3%
29 2
 
6.1%
115 2
 
6.1%
7 2
 
6.1%
17 2
 
6.1%
23 2
 
6.1%
24 1
 
3.0%
32 1
 
3.0%
2,431 1
 
3.0%
16 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T10:10:15.684652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.7%
2 10
14.3%
1 9
12.9%
7 9
12.9%
3 7
10.0%
4 6
8.6%
5 4
 
5.7%
, 4
 
5.7%
9 2
 
2.9%
8 2
 
2.9%
Other values (4) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
87.1%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
2 10
16.4%
1 9
14.8%
7 9
14.8%
3 7
11.5%
4 6
9.8%
5 4
 
6.6%
9 2
 
3.3%
8 2
 
3.3%
6 1
 
1.6%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.4%
2 10
14.9%
1 9
13.4%
7 9
13.4%
3 7
10.4%
4 6
9.0%
5 4
 
6.0%
, 4
 
6.0%
9 2
 
3.0%
8 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 67
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.4%
2 10
14.9%
1 9
13.4%
7 9
13.4%
3 7
10.4%
4 6
9.0%
5 4
 
6.0%
, 4
 
6.0%
9 2
 
3.0%
8 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
동 2
66.7%
명 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:16.092126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters15
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

Unique21 ?
Unique (%)63.6%

Sample

1st row계림1동
2nd row5,823
3rd row10,581
4th row77
5th row12
ValueCountFrequency (%)
0 8
24.2%
77 2
 
6.1%
12 2
 
6.1%
39 1
 
3.0%
10,581 1
 
3.0%
78 1
 
3.0%
5,819 1
 
3.0%
14 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:10:17.030545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.0%
1 11
14.7%
7 8
10.7%
8 7
9.3%
4 6
8.0%
5 6
8.0%
2 5
6.7%
6 5
6.7%
, 4
 
5.3%
3 3
 
4.0%
Other values (5) 8
10.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
88.0%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.2%
1 11
16.7%
7 8
12.1%
8 7
10.6%
4 6
9.1%
5 6
9.1%
2 5
7.6%
6 5
7.6%
3 3
 
4.5%
9 3
 
4.5%
Other Letter
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.7%
1 11
15.3%
7 8
11.1%
8 7
9.7%
4 6
8.3%
5 6
8.3%
2 5
6.9%
6 5
6.9%
, 4
 
5.6%
3 3
 
4.2%
Other values (2) 5
6.9%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
96.0%
Hangul 3
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.7%
1 11
15.3%
7 8
11.1%
8 7
9.7%
4 6
8.3%
5 6
8.3%
2 5
6.9%
6 5
6.9%
, 4
 
5.6%
3 3
 
4.2%
Other values (2) 5
6.9%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:17.496821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters14
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

Unique21 ?
Unique (%)63.6%

Sample

1st row계림2동
2nd row5,456
3rd row12,979
4th row28
5th row12
ValueCountFrequency (%)
0 8
24.2%
28 2
 
6.1%
12 2
 
6.1%
38 1
 
3.0%
12,979 1
 
3.0%
111 1
 
3.0%
5,501 1
 
3.0%
91 1
 
3.0%
45 1
 
3.0%
7 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:10:18.233934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.7%
0 13
16.5%
5 10
12.7%
2 9
11.4%
9 6
7.6%
8 5
 
6.3%
4 5
 
6.3%
6 4
 
5.1%
, 4
 
5.1%
3 3
 
3.8%
Other values (4) 6
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
91.1%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
19.4%
0 13
18.1%
5 10
13.9%
2 9
12.5%
9 6
8.3%
8 5
 
6.9%
4 5
 
6.9%
6 4
 
5.6%
3 3
 
4.2%
7 3
 
4.2%
Other Letter
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
18.4%
0 13
17.1%
5 10
13.2%
2 9
11.8%
9 6
7.9%
8 5
 
6.6%
4 5
 
6.6%
6 4
 
5.3%
, 4
 
5.3%
3 3
 
3.9%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
18.4%
0 13
17.1%
5 10
13.2%
2 9
11.8%
9 6
7.9%
8 5
 
6.6%
4 5
 
6.6%
6 4
 
5.3%
, 4
 
5.3%
3 3
 
3.9%
Hangul
ValueCountFrequency (%)
계 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct24
Distinct (%)70.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T10:10:18.583497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2647059
Min length1

Characters and Unicode

Total characters77
Distinct characters21
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

Unique19 ?
Unique (%)55.9%

Sample

1st row출력일자 :
2nd row산수1동
3rd row4,393
4th row8,191
5th row63
ValueCountFrequency (%)
0 7
20.0%
36 2
 
5.7%
52 2
 
5.7%
63 2
 
5.7%
6 2
 
5.7%
104 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
1 1
 
2.9%
4,372 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T10:10:19.405741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
14.3%
0 10
13.0%
1 10
13.0%
6 8
10.4%
4 6
7.8%
8 5
6.5%
2 5
6.5%
, 4
 
5.2%
9 3
 
3.9%
5 3
 
3.9%
Other values (11) 12
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
80.5%
Other Letter 7
 
9.1%
Other Punctuation 5
 
6.5%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
17.7%
0 10
16.1%
1 10
16.1%
6 8
12.9%
4 6
9.7%
8 5
8.1%
2 5
8.1%
9 3
 
4.8%
5 3
 
4.8%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
수 1
14.3%
동 1
14.3%
산 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
90.9%
Hangul 7
 
9.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
15.7%
0 10
14.3%
1 10
14.3%
6 8
11.4%
4 6
8.6%
8 5
7.1%
2 5
7.1%
, 4
 
5.7%
9 3
 
4.3%
5 3
 
4.3%
Other values (4) 5
7.1%
Hangul
ValueCountFrequency (%)
수 1
14.3%
동 1
14.3%
산 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
90.9%
Hangul 7
 
9.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 11
15.7%
0 10
14.3%
1 10
14.3%
6 8
11.4%
4 6
8.6%
8 5
7.1%
2 5
7.1%
, 4
 
5.7%
9 3
 
4.3%
5 3
 
4.3%
Other values (4) 5
7.1%
Hangul
ValueCountFrequency (%)
수 1
14.3%
동 1
14.3%
산 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:19.739906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
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

Unique18 ?
Unique (%)54.5%

Sample

1st row산수2동
2nd row4,725
3rd row10,012
4th row29
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
18 2
 
6.1%
26 2
 
6.1%
29 2
 
6.1%
83 1
 
3.0%
35 1
 
3.0%
4,715 1
 
3.0%
3 1
 
3.0%
16 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:10:20.531192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
1 9
12.5%
2 7
9.7%
9 6
8.3%
6 6
8.3%
8 6
8.3%
4 5
6.9%
3 5
6.9%
, 4
 
5.6%
5 4
 
5.6%
Other values (5) 9
12.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
86.1%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.7%
1 9
14.5%
2 7
11.3%
9 6
9.7%
6 6
9.7%
8 6
9.7%
4 5
8.1%
3 5
8.1%
5 4
 
6.5%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
1 9
13.0%
2 7
10.1%
9 6
8.7%
6 6
8.7%
8 6
8.7%
4 5
7.2%
3 5
7.2%
, 4
 
5.8%
5 4
 
5.8%
Other values (2) 6
8.7%
Hangul
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.9%
1 9
13.0%
2 7
10.1%
9 6
8.7%
6 6
8.7%
8 6
8.7%
4 5
7.2%
3 5
7.2%
, 4
 
5.8%
5 4
 
5.8%
Other values (2) 6
8.7%
Hangul
ValueCountFrequency (%)
산 1
33.3%
수 1
33.3%
동 1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-05-03 00:00:00
Maximum2023-05-03 00:00:00
2024-02-10T10:10:21.059286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T10:10:21.440027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:21.716284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
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 (%)48.5%

Sample

1st row지산1동
2nd row2,446
3rd row4,150
4th row41
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
18 3
 
9.1%
1 2
 
6.1%
16 2
 
6.1%
33 1
 
3.0%
34 1
 
3.0%
41 1
 
3.0%
4,150 1
 
3.0%
7 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T10:10:22.550956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
17.6%
3 9
13.2%
4 9
13.2%
0 8
11.8%
2 8
11.8%
8 5
7.4%
, 4
 
5.9%
6 3
 
4.4%
5 3
 
4.4%
- 2
 
2.9%
Other values (5) 5
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
86.8%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
20.3%
3 9
15.3%
4 9
15.3%
0 8
13.6%
2 8
13.6%
8 5
8.5%
6 3
 
5.1%
5 3
 
5.1%
9 1
 
1.7%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
18.5%
3 9
13.8%
4 9
13.8%
0 8
12.3%
2 8
12.3%
8 5
7.7%
, 4
 
6.2%
6 3
 
4.6%
5 3
 
4.6%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
95.6%
Hangul 3
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
18.5%
3 9
13.8%
4 9
13.8%
0 8
12.3%
2 8
12.3%
8 5
7.7%
, 4
 
6.2%
6 3
 
4.6%
5 3
 
4.6%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:22.893520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
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

Unique20 ?
Unique (%)60.6%

Sample

1st row지산2동
2nd row2,381
3rd row4,350
4th row9
5th row6
ValueCountFrequency (%)
0 8
24.2%
18 3
 
9.1%
6 2
 
6.1%
28 1
 
3.0%
13 1
 
3.0%
4,336 1
 
3.0%
2,379 1
 
3.0%
1 1
 
3.0%
14 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:10:23.749474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.6%
1 10
14.7%
3 8
11.8%
2 8
11.8%
8 6
8.8%
, 4
 
5.9%
4 4
 
5.9%
6 3
 
4.4%
5 3
 
4.4%
9 3
 
4.4%
Other values (5) 7
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
86.8%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.3%
1 10
16.9%
3 8
13.6%
2 8
13.6%
8 6
10.2%
4 4
 
6.8%
6 3
 
5.1%
5 3
 
5.1%
9 3
 
5.1%
7 2
 
3.4%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.5%
1 10
15.4%
3 8
12.3%
2 8
12.3%
8 6
9.2%
, 4
 
6.2%
4 4
 
6.2%
6 3
 
4.6%
5 3
 
4.6%
9 3
 
4.6%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
95.6%
Hangul 3
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
18.5%
1 10
15.4%
3 8
12.3%
2 8
12.3%
8 6
9.2%
, 4
 
6.2%
4 4
 
6.2%
6 3
 
4.6%
5 3
 
4.6%
9 3
 
4.6%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
지 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:24.100447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters15
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 (%)48.5%

Sample

1st row서남동
2nd row2,243
3rd row2,959
4th row54
5th row3
ValueCountFrequency (%)
0 9
27.3%
3 3
 
9.1%
13 3
 
9.1%
2,243 2
 
6.1%
17 1
 
3.0%
2,953 1
 
3.0%
1 1
 
3.0%
6 1
 
3.0%
11 1
 
3.0%
24 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T10:10:24.952445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
18.2%
0 10
15.2%
1 10
15.2%
2 7
10.6%
4 5
7.6%
, 4
 
6.1%
5 4
 
6.1%
9 3
 
4.5%
7 3
 
4.5%
6 2
 
3.0%
Other values (5) 6
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
86.4%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
21.1%
0 10
17.5%
1 10
17.5%
2 7
12.3%
4 5
8.8%
5 4
 
7.0%
9 3
 
5.3%
7 3
 
5.3%
6 2
 
3.5%
8 1
 
1.8%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
19.0%
0 10
15.9%
1 10
15.9%
2 7
11.1%
4 5
7.9%
, 4
 
6.3%
5 4
 
6.3%
9 3
 
4.8%
7 3
 
4.8%
6 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 12
19.0%
0 10
15.9%
1 10
15.9%
2 7
11.1%
4 5
7.9%
, 4
 
6.3%
5 4
 
6.3%
9 3
 
4.8%
7 3
 
4.8%
6 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
서 1
33.3%
남 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:25.393872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters13
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

Unique17 ?
Unique (%)51.5%

Sample

1st row학동
2nd row3,529
3rd row7,411
4th row77
5th row9
ValueCountFrequency (%)
0 6
18.2%
2 3
 
9.1%
1 2
 
6.1%
41 2
 
6.1%
77 2
 
6.1%
9 2
 
6.1%
6 1
 
3.0%
36 1
 
3.0%
7,409 1
 
3.0%
3,530 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T10:10:26.585963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.8%
1 8
12.3%
7 8
12.3%
3 8
12.3%
9 7
10.8%
2 7
10.8%
4 5
7.7%
, 4
6.2%
6 3
 
4.6%
5 3
 
4.6%
Other values (3) 3
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 2
 
3.1%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.5%
1 8
13.8%
7 8
13.8%
3 8
13.8%
9 7
12.1%
2 7
12.1%
4 5
8.6%
6 3
 
5.2%
5 3
 
5.2%
Other Letter
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
14.3%
1 8
12.7%
7 8
12.7%
3 8
12.7%
9 7
11.1%
2 7
11.1%
4 5
7.9%
, 4
6.3%
6 3
 
4.8%
5 3
 
4.8%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
14.3%
1 8
12.7%
7 8
12.7%
3 8
12.7%
9 7
11.1%
2 7
11.1%
4 5
7.9%
, 4
6.3%
6 3
 
4.8%
5 3
 
4.8%
Hangul
ValueCountFrequency (%)
학 1
50.0%
동 1
50.0%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:26.929826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
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

Unique23 ?
Unique (%)69.7%

Sample

1st row학운동
2nd row5,208
3rd row11,176
4th row45
5th row21
ValueCountFrequency (%)
0 8
24.2%
21 2
 
6.1%
38 2
 
6.1%
31 1
 
3.0%
52 1
 
3.0%
44 1
 
3.0%
11,155 1
 
3.0%
5,192 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:10:27.997067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.2%
0 11
14.9%
2 11
14.9%
3 6
8.1%
5 6
8.1%
8 5
6.8%
, 4
 
5.4%
4 4
 
5.4%
9 3
 
4.1%
7 3
 
4.1%
Other values (5) 9
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.8%
0 11
17.2%
2 11
17.2%
3 6
9.4%
5 6
9.4%
8 5
7.8%
4 4
 
6.2%
9 3
 
4.7%
7 3
 
4.7%
6 3
 
4.7%
Other Letter
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.9%
0 11
15.5%
2 11
15.5%
3 6
8.5%
5 6
8.5%
8 5
7.0%
, 4
 
5.6%
4 4
 
5.6%
9 3
 
4.2%
7 3
 
4.2%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.9%
0 11
15.5%
2 11
15.5%
3 6
8.5%
5 6
8.5%
8 5
7.0%
, 4
 
5.6%
4 4
 
5.6%
9 3
 
4.2%
7 3
 
4.2%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
학 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:28.377510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters13
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

Unique21 ?
Unique (%)63.6%

Sample

1st row지원1동
2nd row4,211
3rd row9,020
4th row21
5th row8
ValueCountFrequency (%)
0 8
24.2%
21 2
 
6.1%
8 2
 
6.1%
36 1
 
3.0%
9,020 1
 
3.0%
43 1
 
3.0%
4,231 1
 
3.0%
35 1
 
3.0%
20 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T10:10:29.366642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.3%
2 10
14.5%
1 8
11.6%
3 8
11.6%
5 6
8.7%
4 5
 
7.2%
8 4
 
5.8%
9 4
 
5.8%
, 4
 
5.8%
6 3
 
4.3%
Other values (3) 3
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
89.9%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
22.6%
2 10
16.1%
1 8
12.9%
3 8
12.9%
5 6
9.7%
4 5
 
8.1%
8 4
 
6.5%
9 4
 
6.5%
6 3
 
4.8%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
21.2%
2 10
15.2%
1 8
12.1%
3 8
12.1%
5 6
9.1%
4 5
 
7.6%
8 4
 
6.1%
9 4
 
6.1%
, 4
 
6.1%
6 3
 
4.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
21.2%
2 10
15.2%
1 8
12.1%
3 8
12.1%
5 6
9.1%
4 5
 
7.6%
8 4
 
6.1%
9 4
 
6.1%
, 4
 
6.1%
6 3
 
4.5%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T10:10:29.787035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
Distinct characters14
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

Unique18 ?
Unique (%)54.5%

Sample

1st row지원2동
2nd row7,544
3rd row16,481
4th row109
5th row7
ValueCountFrequency (%)
0 7
21.2%
50 2
 
6.1%
109 2
 
6.1%
7 2
 
6.1%
67 2
 
6.1%
1 1
 
3.0%
130 1
 
3.0%
7,684 1
 
3.0%
181 1
 
3.0%
140 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T10:10:30.607961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
22.5%
0 14
17.5%
6 10
12.5%
7 9
11.2%
4 6
 
7.5%
5 4
 
5.0%
3 4
 
5.0%
, 4
 
5.0%
9 3
 
3.8%
8 3
 
3.8%
Other values (4) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
91.2%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
24.7%
0 14
19.2%
6 10
13.7%
7 9
12.3%
4 6
 
8.2%
5 4
 
5.5%
3 4
 
5.5%
9 3
 
4.1%
8 3
 
4.1%
2 2
 
2.7%
Other Letter
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 77
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
23.4%
0 14
18.2%
6 10
13.0%
7 9
11.7%
4 6
 
7.8%
5 4
 
5.2%
3 4
 
5.2%
, 4
 
5.2%
9 3
 
3.9%
8 3
 
3.9%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 77
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
23.4%
0 14
18.2%
6 10
13.0%
7 9
11.7%
4 6
 
7.8%
5 4
 
5.2%
3 4
 
5.2%
, 4
 
5.2%
9 3
 
3.9%
8 3
 
3.9%
Hangul
ValueCountFrequency (%)
지 1
33.3%
원 1
33.3%
동 1
33.3%

Correlations

2024-02-10T10:10:30.967102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
인구이동보고서(1호)1.0000.0001.000NaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 20.0001.000NaNNaN0.9471.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.925
Unnamed: 31.000NaN1.000NaN1.0001.0001.0001.0001.0000.7720.7900.6760.7900.5831.0001.0001.0000.790
Unnamed: 4NaNNaNNaN1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Unnamed: 51.0000.9471.0001.0001.0000.9910.9900.9920.9920.9820.9940.9940.9910.9930.9910.9920.9920.986
Unnamed: 61.0001.0001.0001.0000.9911.0000.9920.9900.9900.9900.9960.9810.9980.9880.9950.9940.9900.988
Unnamed: 71.0001.0001.0001.0000.9900.9921.0001.0001.0000.9880.9850.9910.9940.9570.9840.9921.0000.988
Unnamed: 81.0001.0001.0001.0000.9920.9901.0001.0001.0000.9950.9910.9840.9870.9820.9880.9871.0000.995
Unnamed: 91.0001.0001.0001.0000.9920.9901.0001.0001.0000.9950.9910.9840.9870.9820.9880.9871.0000.995
Unnamed: 101.0001.0000.7721.0000.9820.9900.9880.9950.9951.0000.9930.9650.9860.9600.9910.9750.9950.996
Unnamed: 111.0001.0000.7901.0000.9940.9960.9850.9910.9910.9931.0000.9770.9950.9730.9930.9850.9910.993
Unnamed: 131.0001.0000.6761.0000.9940.9810.9910.9840.9840.9650.9771.0000.9900.9780.9740.9900.9840.959
Unnamed: 141.0001.0000.7901.0000.9910.9980.9940.9870.9870.9860.9950.9901.0000.9830.9930.9960.9870.986
Unnamed: 151.0001.0000.5831.0000.9930.9880.9570.9820.9820.9600.9730.9780.9831.0000.9750.9960.9820.960
Unnamed: 161.0001.0001.0001.0000.9910.9950.9840.9880.9880.9910.9930.9740.9930.9751.0000.9830.9880.987
Unnamed: 171.0001.0001.0001.0000.9920.9940.9920.9870.9870.9750.9850.9900.9960.9960.9831.0000.9870.975
Unnamed: 181.0001.0001.0001.0000.9920.9901.0001.0001.0000.9950.9910.9840.9870.9820.9880.9871.0000.995
Unnamed: 191.0000.9250.7901.0000.9860.9880.9880.9950.9950.9960.9930.9590.9860.9600.9870.9750.9951.000

Missing values

2024-02-10T10:10:04.149672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-02-10T10:10:05.389100image/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.
2024-02-10T10:10:06.100780image/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

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
0<NA>행정기관 :<NA>광주광역시 동구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2023.05.03<NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.04 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계충장동동명동계림1동계림2동산수1동산수2동<NA>지산1동지산2동서남동학동학운동지원1동지원2동
3<NA>전월말세대수<NA><NA><NA>54,5074,1012,4475,8235,4564,3934,725<NA>2,4462,3812,2433,5295,2084,2117,544
4<NA>전월말인구수<NA><NA><NA>106,2475,2133,72410,58112,9798,19110,012<NA>4,1504,3502,9597,41111,1769,02016,481
5<NA>전월말거주불명자수<NA><NA><NA>7053711577286329<NA>41954774521109
6<NA>전월말재외국민등록자수<NA><NA><NA>10667121266<NA>36392187
7<NA>증 가 요 인전 입계<NA>1,461134541342956870<NA>3447347778119317
8<NA><NA><NA>남자<NA>7406829741413629<NA>162918414069150
9<NA><NA><NA>여자<NA>7216625601543241<NA>181816363850167
Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19
25<NA><NA>말소<NA><NA>2000000<NA>1001000
26<NA><NA>국외<NA><NA>0000000<NA>0000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000
28<NA>세대수증감<NA><NA><NA>16036-16-445-21-10<NA>-13-201-1620140
29<NA>인구수증감<NA><NA><NA>19647-17-1491-40-16<NA>-28-14-6-2-2135181
30<NA>거주불명자수증감<NA><NA><NA>-2-10000-3<NA>11-12-100
31<NA>금월말세대수<NA><NA><NA>54,6674,1372,4315,8195,5014,3724,715<NA>2,4332,3792,2433,5305,1924,2317,684
32<NA>금월말인구수<NA><NA><NA>106,4435,2603,70710,56713,0708,1519,996<NA>4,1224,3362,9537,40911,1559,05516,662
33<NA>금월말거주불명자수<NA><NA><NA>7033611577286326<NA>421053794421109
34<NA>금월말재외국민등록자수<NA><NA><NA>10767121266<NA>36392287

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19# duplicates
0<NA>기타<NA><NA>0000000<NA>00000002