Overview

Dataset statistics

Number of variables24
Number of observations35
Missing cells201
Missing cells (%)23.9%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory6.7 KiB
Average record size in memory196.8 B

Variable types

Unsupported1
Text22
DateTime1

Dataset

Description2022-11-16
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201925

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: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 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 09:32:26.306018
Analysis finished2024-02-10 09:32:27.586267
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:32:27.940172image/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 (%)
2
 
7.7%
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%
1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T09:32:29.129931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
11
 
8.7%
8
 
6.3%
8
 
6.3%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
4
 
3.2%
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 (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
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 (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
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 (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
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
2024-02-10T09:32:29.699011image/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%
2
15.4%
1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T09:32:30.690851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
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 (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
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 (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
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 (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
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
2024-02-10T09:32:31.087472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters19
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 남구
2nd row2022.10 현재
3rd row
4th row남자
5th row여자
ValueCountFrequency (%)
2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
남구 1
7.1%
2022.10 1
7.1%
현재 1
7.1%
2024-02-10T09:32:32.036744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
3
 
7.3%
2 3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (9) 11
26.8%

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 (%)
5
16.1%
4
12.9%
4
12.9%
3
9.7%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (4) 4
12.9%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
1 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 (%)
5
16.1%
4
12.9%
4
12.9%
3
9.7%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (4) 4
12.9%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
. 1
 
10.0%
1 1
 
10.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
3
9.7%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (4) 4
12.9%
ASCII
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
. 1
 
10.0%
1 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:32:32.342549image/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%
2024-02-10T09:32:33.069643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
4
25.0%
4
25.0%
4
25.0%
2
12.5%
2
12.5%

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:33.606972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.3636364
Min length1

Characters and Unicode

Total characters111
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

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row96,295
3rd row213,653
4th row309
5th row147
ValueCountFrequency (%)
0 4
 
11.8%
554 2
 
5.9%
1,040 1
 
2.9%
307 1
 
2.9%
213,079 1
 
2.9%
96,133 1
 
2.9%
2 1
 
2.9%
574 1
 
2.9%
162 1
 
2.9%
1 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:32:34.464203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
16.2%
0 12
10.8%
5 11
9.9%
2 10
9.0%
, 9
8.1%
6 9
8.1%
4 8
7.2%
9 8
7.2%
3 8
7.2%
7 8
7.2%
Other values (5) 10
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 95
85.6%
Other Punctuation 9
 
8.1%
Dash Punctuation 3
 
2.7%
Space Separator 2
 
1.8%
Other Letter 2
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
18.9%
0 12
12.6%
5 11
11.6%
2 10
10.5%
6 9
9.5%
4 8
8.4%
9 8
8.4%
3 8
8.4%
7 8
8.4%
8 3
 
3.2%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 109
98.2%
Hangul 2
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
16.5%
0 12
11.0%
5 11
10.1%
2 10
9.2%
, 9
8.3%
6 9
8.3%
4 8
7.3%
9 8
7.3%
3 8
7.3%
7 8
7.3%
Other values (3) 8
7.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 109
98.2%
Hangul 2
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
16.5%
0 12
11.0%
5 11
10.1%
2 10
9.2%
, 9
8.3%
6 9
8.3%
4 8
7.3%
9 8
7.3%
3 8
7.3%
7 8
7.3%
Other values (3) 8
7.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:34.890555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique19 ?
Unique (%)57.6%

Sample

1st row양림동
2nd row3,147
3rd row6,859
4th row13
5th row5
ValueCountFrequency (%)
0 6
18.2%
11 2
 
6.1%
1 2
 
6.1%
13 2
 
6.1%
5 2
 
6.1%
36 2
 
6.1%
14 1
 
3.0%
43 1
 
3.0%
3,131 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:32:35.658168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
21.4%
3 11
15.7%
0 8
11.4%
6 6
 
8.6%
2 5
 
7.1%
5 4
 
5.7%
, 4
 
5.7%
4 4
 
5.7%
9 3
 
4.3%
- 3
 
4.3%
Other values (5) 7
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Other Punctuation 4
 
5.7%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
25.0%
3 11
18.3%
0 8
13.3%
6 6
 
10.0%
2 5
 
8.3%
5 4
 
6.7%
4 4
 
6.7%
9 3
 
5.0%
8 2
 
3.3%
7 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
22.4%
3 11
16.4%
0 8
11.9%
6 6
 
9.0%
2 5
 
7.5%
5 4
 
6.0%
, 4
 
6.0%
4 4
 
6.0%
9 3
 
4.5%
- 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
22.4%
3 11
16.4%
0 8
11.9%
6 6
 
9.0%
2 5
 
7.5%
5 4
 
6.0%
, 4
 
6.0%
4 4
 
6.0%
9 3
 
4.5%
- 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:36.068402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2
Min length1

Characters and Unicode

Total characters66
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 row방림1동
2nd row2,886
3rd row6,393
4th row8
5th row6
ValueCountFrequency (%)
0 8
24.2%
8 2
 
6.1%
6 2
 
6.1%
17 1
 
3.0%
6,393 1
 
3.0%
29 1
 
3.0%
2,904 1
 
3.0%
30 1
 
3.0%
18 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:32:36.922851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.7%
3 9
13.6%
6 7
10.6%
1 7
10.6%
4 7
10.6%
2 6
9.1%
8 5
7.6%
9 4
 
6.1%
, 4
 
6.1%
5 2
 
3.0%
Other values (4) 4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
89.4%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.6%
3 9
15.3%
6 7
11.9%
1 7
11.9%
4 7
11.9%
2 6
10.2%
8 5
8.5%
9 4
 
6.8%
5 2
 
3.4%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.5%
3 9
14.3%
6 7
11.1%
1 7
11.1%
4 7
11.1%
2 6
9.5%
8 5
7.9%
9 4
 
6.3%
, 4
 
6.3%
5 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.5%
3 9
14.3%
6 7
11.1%
1 7
11.1%
4 7
11.1%
2 6
9.5%
8 5
7.9%
9 4
 
6.3%
, 4
 
6.3%
5 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:37.306107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique17 ?
Unique (%)51.5%

Sample

1st row방림2동
2nd row4,004
3rd row8,586
4th row15
5th row9
ValueCountFrequency (%)
0 7
21.2%
16 3
 
9.1%
15 3
 
9.1%
9 2
 
6.1%
1 2
 
6.1%
4 1
 
3.0%
54 1
 
3.0%
48 1
 
3.0%
3,988 1
 
3.0%
35 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:32:38.445606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
14.3%
5 10
14.3%
0 9
12.9%
8 8
11.4%
6 5
7.1%
2 5
7.1%
4 5
7.1%
3 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (5) 7
10.0%

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 (%)
1 10
16.4%
5 10
16.4%
0 9
14.8%
8 8
13.1%
6 5
8.2%
2 5
8.2%
4 5
8.2%
3 4
 
6.6%
9 3
 
4.9%
7 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
1 10
14.9%
5 10
14.9%
0 9
13.4%
8 8
11.9%
6 5
7.5%
2 5
7.5%
4 5
7.5%
3 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
14.9%
5 10
14.9%
0 9
13.4%
8 8
11.9%
6 5
7.5%
2 5
7.5%
4 5
7.5%
3 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:38.793227image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row봉선1동
2nd row6,590
3rd row13,074
4th row37
5th row11
ValueCountFrequency (%)
0 6
18.2%
43 2
 
6.1%
40 2
 
6.1%
48 2
 
6.1%
3 2
 
6.1%
11 2
 
6.1%
96 1
 
3.0%
98 1
 
3.0%
6,547 1
 
3.0%
84 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:32:39.674206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.0%
1 9
12.0%
4 9
12.0%
7 8
10.7%
3 7
9.3%
9 7
9.3%
8 4
 
5.3%
, 4
 
5.3%
6 4
 
5.3%
5 4
 
5.3%
Other values (5) 7
9.3%

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 9
13.6%
4 9
13.6%
7 8
12.1%
3 7
10.6%
9 7
10.6%
8 4
 
6.1%
6 4
 
6.1%
5 4
 
6.1%
2 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 9
12.5%
4 9
12.5%
7 8
11.1%
3 7
9.7%
9 7
9.7%
8 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
5 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 9
12.5%
4 9
12.5%
7 8
11.1%
3 7
9.7%
9 7
9.7%
8 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
5 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:32:40.095638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5588235
Min length1

Characters and Unicode

Total characters87
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

Unique24 ?
Unique (%)70.6%

Sample

1st row출력일자 :
2nd row봉선2동
3rd row9,919
4th row28,339
5th row10
ValueCountFrequency (%)
0 8
22.9%
10 2
 
5.7%
261 1
 
2.9%
8 1
 
2.9%
28,238 1
 
2.9%
9,898 1
 
2.9%
101 1
 
2.9%
21 1
 
2.9%
13 1
 
2.9%
85 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T09:32:40.998285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
17.2%
0 11
12.6%
8 9
10.3%
2 9
10.3%
9 8
9.2%
3 7
8.0%
, 4
 
4.6%
6 4
 
4.6%
5 4
 
4.6%
7 3
 
3.4%
Other values (11) 13
14.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
82.8%
Other Letter 7
 
8.0%
Other Punctuation 5
 
5.7%
Dash Punctuation 2
 
2.3%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.8%
0 11
15.3%
8 9
12.5%
2 9
12.5%
9 8
11.1%
3 7
9.7%
6 4
 
5.6%
5 4
 
5.6%
7 3
 
4.2%
4 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
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 80
92.0%
Hangul 7
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
18.8%
0 11
13.8%
8 9
11.2%
2 9
11.2%
9 8
10.0%
3 7
8.8%
, 4
 
5.0%
6 4
 
5.0%
5 4
 
5.0%
7 3
 
3.8%
Other values (4) 6
 
7.5%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
92.0%
Hangul 7
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
18.8%
0 11
13.8%
8 9
11.2%
2 9
11.2%
9 8
10.0%
3 7
8.8%
, 4
 
5.0%
6 4
 
5.0%
5 4
 
5.0%
7 3
 
3.8%
Other values (4) 6
 
7.5%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Unnamed: 11
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:41.343255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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 row사직동
2nd row2,906
3rd row5,013
4th row35
5th row6
ValueCountFrequency (%)
0 7
21.2%
18 4
 
12.1%
6 2
 
6.1%
1 2
 
6.1%
35 2
 
6.1%
67 1
 
3.0%
30 1
 
3.0%
2,887 1
 
3.0%
32 1
 
3.0%
19 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:32:42.153489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.2%
1 11
16.2%
8 9
13.2%
3 8
11.8%
2 5
7.4%
6 4
 
5.9%
5 4
 
5.9%
, 4
 
5.9%
9 3
 
4.4%
7 3
 
4.4%
Other values (5) 6
8.8%

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 11
18.6%
1 11
18.6%
8 9
15.3%
3 8
13.6%
2 5
8.5%
6 4
 
6.8%
5 4
 
6.8%
9 3
 
5.1%
7 3
 
5.1%
4 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 11
16.9%
1 11
16.9%
8 9
13.8%
3 8
12.3%
2 5
7.7%
6 4
 
6.2%
5 4
 
6.2%
, 4
 
6.2%
9 3
 
4.6%
7 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.9%
1 11
16.9%
8 9
13.8%
3 8
12.3%
2 5
7.7%
6 4
 
6.2%
5 4
 
6.2%
, 4
 
6.2%
9 3
 
4.6%
7 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-11-07 00:00:00
Maximum2022-11-07 00:00:00
2024-02-10T09:32:42.644868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:32:43.103789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:43.388588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique15 ?
Unique (%)45.5%

Sample

1st row월산동
2nd row4,592
3rd row8,899
4th row25
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 3
 
9.1%
15 3
 
9.1%
30 2
 
6.1%
25 2
 
6.1%
9 2
 
6.1%
18 1
 
3.0%
4,583 1
 
3.0%
12 1
 
3.0%
33 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T09:32:44.604270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.7%
3 9
13.2%
5 8
11.8%
8 7
10.3%
1 6
8.8%
9 6
8.8%
2 5
7.4%
7 4
 
5.9%
, 4
 
5.9%
4 3
 
4.4%
Other values (5) 6
8.8%

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 10
16.9%
3 9
15.3%
5 8
13.6%
8 7
11.9%
1 6
10.2%
9 6
10.2%
2 5
8.5%
7 4
 
6.8%
4 3
 
5.1%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 10
15.4%
3 9
13.8%
5 8
12.3%
8 7
10.8%
1 6
9.2%
9 6
9.2%
2 5
7.7%
7 4
 
6.2%
, 4
 
6.2%
4 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.4%
3 9
13.8%
5 8
12.3%
8 7
10.8%
1 6
9.2%
9 6
9.2%
2 5
7.7%
7 4
 
6.2%
, 4
 
6.2%
4 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:45.161893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
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 row월산4동
2nd row4,801
3rd row8,421
4th row28
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
28 2
 
6.1%
1 2
 
6.1%
57 1
 
3.0%
8,421 1
 
3.0%
79 1
 
3.0%
4,790 1
 
3.0%
39 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:32:45.979745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
15.5%
1 10
14.1%
0 9
12.7%
8 7
9.9%
4 7
9.9%
5 5
7.0%
3 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
87.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
17.7%
1 10
16.1%
0 9
14.5%
8 7
11.3%
4 7
11.3%
5 5
8.1%
3 4
 
6.5%
7 4
 
6.5%
9 4
 
6.5%
6 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
16.2%
1 10
14.7%
0 9
13.2%
8 7
10.3%
4 7
10.3%
5 5
7.4%
3 4
 
5.9%
7 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 68
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
16.2%
1 10
14.7%
0 9
13.2%
8 7
10.3%
4 7
10.3%
5 5
7.4%
3 4
 
5.9%
7 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:46.487310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique23 ?
Unique (%)69.7%

Sample

1st row월산5동
2nd row3,530
3rd row6,267
4th row8
5th row4
ValueCountFrequency (%)
0 6
18.2%
24 2
 
6.1%
1 2
 
6.1%
26 2
 
6.1%
4 2
 
6.1%
67 1
 
3.0%
33 1
 
3.0%
6,241 1
 
3.0%
3,520 1
 
3.0%
10 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:32:47.526480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
15.9%
0 9
13.0%
1 9
13.0%
4 8
11.6%
6 8
11.6%
3 6
8.7%
, 4
 
5.8%
7 4
 
5.8%
5 3
 
4.3%
- 3
 
4.3%
Other values (4) 4
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
85.5%
Other Punctuation 4
 
5.8%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
18.6%
0 9
15.3%
1 9
15.3%
4 8
13.6%
6 8
13.6%
3 6
10.2%
7 4
 
6.8%
5 3
 
5.1%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
16.7%
0 9
13.6%
1 9
13.6%
4 8
12.1%
6 8
12.1%
3 6
9.1%
, 4
 
6.1%
7 4
 
6.1%
5 3
 
4.5%
- 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
16.7%
0 9
13.6%
1 9
13.6%
4 8
12.1%
6 8
12.1%
3 6
9.1%
, 4
 
6.1%
7 4
 
6.1%
5 3
 
4.5%
- 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:47.836943image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row백운1동
2nd row5,186
3rd row12,013
4th row12
5th row14
ValueCountFrequency (%)
0 6
18.2%
1 4
 
12.1%
14 2
 
6.1%
65 2
 
6.1%
40 1
 
3.0%
12 1
 
3.0%
111 1
 
3.0%
11,982 1
 
3.0%
5,187 1
 
3.0%
31 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:32:48.750294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
28.0%
0 8
 
10.7%
4 7
 
9.3%
5 7
 
9.3%
6 5
 
6.7%
8 5
 
6.7%
3 5
 
6.7%
2 4
 
5.3%
, 4
 
5.3%
7 2
 
2.7%
Other values (5) 7
 
9.3%

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 (%)
1 21
31.8%
0 8
 
12.1%
4 7
 
10.6%
5 7
 
10.6%
6 5
 
7.6%
8 5
 
7.6%
3 5
 
7.6%
2 4
 
6.1%
7 2
 
3.0%
9 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
1 21
29.2%
0 8
 
11.1%
4 7
 
9.7%
5 7
 
9.7%
6 5
 
6.9%
8 5
 
6.9%
3 5
 
6.9%
2 4
 
5.6%
, 4
 
5.6%
7 2
 
2.8%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
29.2%
0 8
 
11.1%
4 7
 
9.7%
5 7
 
9.7%
6 5
 
6.9%
8 5
 
6.9%
3 5
 
6.9%
2 4
 
5.6%
, 4
 
5.6%
7 2
 
2.8%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:49.084476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique19 ?
Unique (%)57.6%

Sample

1st row백운2동
2nd row3,329
3rd row6,288
4th row20
5th row2
ValueCountFrequency (%)
0 8
24.2%
20 3
 
9.1%
2 3
 
9.1%
35 2
 
6.1%
17 2
 
6.1%
51 1
 
3.0%
6,288 1
 
3.0%
49 1
 
3.0%
3,312 1
 
3.0%
3 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:32:50.121754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
20.0%
0 12
17.1%
3 8
11.4%
5 6
8.6%
1 6
8.6%
6 4
 
5.7%
9 4
 
5.7%
, 4
 
5.7%
4 3
 
4.3%
7 2
 
2.9%
Other values (5) 7
10.0%

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 (%)
2 14
23.0%
0 12
19.7%
3 8
13.1%
5 6
9.8%
1 6
9.8%
6 4
 
6.6%
9 4
 
6.6%
4 3
 
4.9%
7 2
 
3.3%
8 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 (%)
2 14
20.9%
0 12
17.9%
3 8
11.9%
5 6
9.0%
1 6
9.0%
6 4
 
6.0%
9 4
 
6.0%
, 4
 
6.0%
4 3
 
4.5%
7 2
 
3.0%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
20.9%
0 12
17.9%
3 8
11.9%
5 6
9.0%
1 6
9.0%
6 4
 
6.0%
9 4
 
6.0%
, 4
 
6.0%
4 3
 
4.5%
7 2
 
3.0%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:50.489078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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

Unique25 ?
Unique (%)75.8%

Sample

1st row주월1동
2nd row9,694
3rd row21,729
4th row18
5th row13
ValueCountFrequency (%)
0 6
 
18.2%
77 2
 
6.1%
13 2
 
6.1%
108 1
 
3.0%
238 1
 
3.0%
21,652 1
 
3.0%
9,670 1
 
3.0%
1 1
 
3.0%
24 1
 
3.0%
12 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:32:51.335869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.0%
0 12
14.8%
7 9
11.1%
2 8
9.9%
3 7
8.6%
6 6
7.4%
8 6
7.4%
9 4
 
4.9%
, 4
 
4.9%
5 4
 
4.9%
Other values (5) 8
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
87.7%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
18.3%
0 12
16.9%
7 9
12.7%
2 8
11.3%
3 7
9.9%
6 6
8.5%
8 6
8.5%
9 4
 
5.6%
5 4
 
5.6%
4 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
16.7%
0 12
15.4%
7 9
11.5%
2 8
10.3%
3 7
9.0%
6 6
7.7%
8 6
7.7%
9 4
 
5.1%
, 4
 
5.1%
5 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
16.7%
0 12
15.4%
7 9
11.5%
2 8
10.3%
3 7
9.0%
6 6
7.7%
8 6
7.7%
9 4
 
5.1%
, 4
 
5.1%
5 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:51.689547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique19 ?
Unique (%)57.6%

Sample

1st row주월2동
2nd row4,037
3rd row7,868
4th row29
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 3
 
9.1%
29 2
 
6.1%
1 2
 
6.1%
13 2
 
6.1%
37 1
 
3.0%
7,868 1
 
3.0%
39 1
 
3.0%
4,024 1
 
3.0%
42 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:32:52.764555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.9%
2 9
12.9%
1 8
11.4%
4 8
11.4%
6 7
10.0%
3 7
10.0%
7 5
7.1%
8 4
5.7%
, 4
5.7%
9 3
 
4.3%
Other values (5) 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 9
14.8%
2 9
14.8%
1 8
13.1%
4 8
13.1%
6 7
11.5%
3 7
11.5%
7 5
8.2%
8 4
6.6%
9 3
 
4.9%
5 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 9
13.4%
2 9
13.4%
1 8
11.9%
4 8
11.9%
6 7
10.4%
3 7
10.4%
7 5
7.5%
8 4
6.0%
, 4
6.0%
9 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
13.4%
2 9
13.4%
1 8
11.9%
4 8
11.9%
6 7
10.4%
3 7
10.4%
7 5
7.5%
8 4
6.0%
, 4
6.0%
9 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:53.102469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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 row진월동
2nd row11,430
3rd row28,669
4th row34
5th row24
ValueCountFrequency (%)
0 6
 
18.2%
24 2
 
6.1%
52 2
 
6.1%
34 2
 
6.1%
121 1
 
3.0%
234 1
 
3.0%
11,408 1
 
3.0%
22 1
 
3.0%
1 1
 
3.0%
14 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:32:53.955493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.3%
2 12
14.8%
0 9
11.1%
4 8
9.9%
8 7
8.6%
3 6
7.4%
6 5
 
6.2%
, 4
 
4.9%
7 4
 
4.9%
5 4
 
4.9%
Other values (5) 8
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
88.9%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
19.4%
2 12
16.7%
0 9
12.5%
4 8
11.1%
8 7
9.7%
3 6
8.3%
6 5
 
6.9%
7 4
 
5.6%
5 4
 
5.6%
9 3
 
4.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.9%
2 12
15.4%
0 9
11.5%
4 8
10.3%
8 7
9.0%
3 6
7.7%
6 5
 
6.4%
, 4
 
5.1%
7 4
 
5.1%
5 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
17.9%
2 12
15.4%
0 9
11.5%
4 8
10.3%
8 7
9.0%
3 6
7.7%
6 5
 
6.4%
, 4
 
5.1%
7 4
 
5.1%
5 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:54.365281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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

Unique20 ?
Unique (%)60.6%

Sample

1st row효덕동
2nd row7,512
3rd row15,838
4th row2
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
2 2
 
6.1%
62 2
 
6.1%
83 1
 
3.0%
15,838 1
 
3.0%
185 1
 
3.0%
7,569 1
 
3.0%
35 1
 
3.0%
57 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:32:55.320526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.0%
5 9
13.0%
8 8
11.6%
7 7
10.1%
1 7
10.1%
6 5
7.2%
2 5
7.2%
9 5
7.2%
, 4
5.8%
3 4
5.8%
Other values (4) 6
8.7%

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 9
14.5%
5 9
14.5%
8 8
12.9%
7 7
11.3%
1 7
11.3%
6 5
8.1%
2 5
8.1%
9 5
8.1%
3 4
6.5%
4 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
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 9
13.6%
5 9
13.6%
8 8
12.1%
7 7
10.6%
1 7
10.6%
6 5
7.6%
2 5
7.6%
9 5
7.6%
, 4
6.1%
3 4
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
13.6%
5 9
13.6%
8 8
12.1%
7 7
10.6%
1 7
10.6%
6 5
7.6%
2 5
7.6%
9 5
7.6%
, 4
6.1%
3 4
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:55.710392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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

Unique19 ?
Unique (%)57.6%

Sample

1st row송암동
2nd row8,599
3rd row21,297
4th row10
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 2
 
6.1%
57 2
 
6.1%
10 2
 
6.1%
56 1
 
3.0%
112 1
 
3.0%
8,578 1
 
3.0%
87 1
 
3.0%
21 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:32:56.386998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.9%
0 12
15.6%
7 9
11.7%
2 9
11.7%
5 7
9.1%
8 6
7.8%
, 4
 
5.2%
3 4
 
5.2%
9 3
 
3.9%
6 3
 
3.9%
Other values (5) 7
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
88.3%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.1%
0 12
17.6%
7 9
13.2%
2 9
13.2%
5 7
10.3%
8 6
8.8%
3 4
 
5.9%
9 3
 
4.4%
6 3
 
4.4%
4 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.6%
0 12
16.2%
7 9
12.2%
2 9
12.2%
5 7
9.5%
8 6
8.1%
, 4
 
5.4%
3 4
 
5.4%
9 3
 
4.1%
6 3
 
4.1%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
17.6%
0 12
16.2%
7 9
12.2%
2 9
12.2%
5 7
9.5%
8 6
8.1%
, 4
 
5.4%
3 4
 
5.4%
9 3
 
4.1%
6 3
 
4.1%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:32:57.034166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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

Unique16 ?
Unique (%)48.5%

Sample

1st row대촌동
2nd row4,133
3rd row8,100
4th row5
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 3
 
9.1%
49 2
 
6.1%
29 2
 
6.1%
5 2
 
6.1%
7 1
 
3.0%
20 1
 
3.0%
4,137 1
 
3.0%
50 1
 
3.0%
11 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:32:57.879509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
21.5%
4 8
12.3%
1 8
12.3%
2 7
10.8%
5 7
10.8%
9 4
 
6.2%
3 4
 
6.2%
, 4
 
6.2%
8 3
 
4.6%
7 2
 
3.1%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
24.1%
4 8
13.8%
1 8
13.8%
2 7
12.1%
5 7
12.1%
9 4
 
6.9%
3 4
 
6.9%
8 3
 
5.2%
7 2
 
3.4%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
22.6%
4 8
12.9%
1 8
12.9%
2 7
11.3%
5 7
11.3%
9 4
 
6.5%
3 4
 
6.5%
, 4
 
6.5%
8 3
 
4.8%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
22.6%
4 8
12.9%
1 8
12.9%
2 7
11.3%
5 7
11.3%
9 4
 
6.5%
3 4
 
6.5%
, 4
 
6.5%
8 3
 
4.8%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23
0<NA>행정기관 :<NA>광주광역시 남구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.11.07<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.10 현재<NA><NA><NA><NA><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 계양림동방림1동방림2동봉선1동봉선2동사직동<NA>월산동월산4동월산5동백운1동백운2동주월1동주월2동진월동효덕동송암동대촌동
3<NA>전월말세대수<NA><NA><NA>96,2953,1472,8864,0046,5909,9192,906<NA>4,5924,8013,5305,1863,3299,6944,03711,4307,5128,5994,133
4<NA>전월말인구수<NA><NA><NA>213,6536,8596,3938,58613,07428,3395,013<NA>8,8998,4216,26712,0136,28821,7297,86828,66915,83821,2978,100
5<NA>전월말거주불명자수<NA><NA><NA>30913815371035<NA>2528812201829342105
6<NA>전월말재외국민등록자수<NA><NA><NA>14756911156<NA>75414213624884
7<NA>증 가 요 인전 입<NA>1,6654390549616538<NA>5379461116016347186185146103
8<NA><NA><NA>남자<NA>791204626487720<NA>1932224535772677907655
9<NA><NA><NA>여자<NA>874234428488818<NA>34472466258621109957048
Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23
25<NA><NA>말소<NA><NA>3001000<NA>00000001100
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>1000000<NA>00100000000
28<NA>세대수증감<NA><NA><NA>-162-1618-16-43-21-19<NA>-9-11-101-17-24-13-2257-214
29<NA>인구수증감<NA><NA><NA>-574-3630-35-84-101-32<NA>-12-39-26-31-35-77-42-5235-8750
30<NA>거주불명자수증감<NA><NA><NA>-2-200300<NA>00-1-10-100000
31<NA>금월말세대수<NA><NA><NA>96,1333,1312,9043,9886,5479,8982,887<NA>4,5834,7903,5205,1873,3129,6704,02411,4087,5698,5784,137
32<NA>금월말인구수<NA><NA><NA>213,0796,8236,4238,55112,99028,2384,981<NA>8,8878,3826,24111,9826,25321,6527,82628,61715,87321,2108,150
33<NA>금월말거주불명자수<NA><NA><NA>30711815401035<NA>2528711201729342105
34<NA>금월말재외국민등록자수<NA><NA><NA>14956911176<NA>75414213624884

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: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23# duplicates
0<NA>국외<NA><NA>0000000<NA>000000000002