Overview

Dataset statistics

Number of variables24
Number of observations35
Missing cells201
Missing cells (%)23.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory196.8 B

Variable types

Unsupported1
Text22
DateTime1

Dataset

Description2022-05-19
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201925

Alerts

Unnamed: 12 has constant value ""Constant
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 09:28:12.471898
Analysis finished2024-02-10 09:28:13.504953
Duration1.03 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
2024-02-10T09:28:13.704004image/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%
2024-02-10T09:28:15.030234image/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
2024-02-10T09:28:15.482208image/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%
2024-02-10T09:28:16.386717image/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
2024-02-10T09:28:16.815701image/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 row2022.04 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%
2022.04 1
7.1%
현재 1
7.1%
2024-02-10T09:28:17.570603image/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%
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 (%)
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%
4 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%
4 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:28:17.872618image/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%
2024-02-10T09:28:18.582602image/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
2024-02-10T09:28:18.959772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.1515152
Min length1

Characters and Unicode

Total characters104
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

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row95,963
3rd row215,008
4th row536
5th row151
ValueCountFrequency (%)
0 3
 
8.8%
1 2
 
5.9%
545 2
 
5.9%
790 1
 
2.9%
536 1
 
2.9%
151 1
 
2.9%
537 1
 
2.9%
214,848 1
 
2.9%
96,146 1
 
2.9%
160 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:28:19.967017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 15
14.4%
1 14
13.5%
0 13
12.5%
9 12
11.5%
6 8
7.7%
2 8
7.7%
, 7
6.7%
8 7
6.7%
3 6
 
5.8%
4 5
 
4.8%
Other values (5) 9
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 92
88.5%
Other Punctuation 7
 
6.7%
Space Separator 2
 
1.9%
Other Letter 2
 
1.9%
Dash Punctuation 1
 
1.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 15
16.3%
1 14
15.2%
0 13
14.1%
9 12
13.0%
6 8
8.7%
2 8
8.7%
8 7
7.6%
3 6
 
6.5%
4 5
 
5.4%
7 4
 
4.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 102
98.1%
Hangul 2
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
5 15
14.7%
1 14
13.7%
0 13
12.7%
9 12
11.8%
6 8
7.8%
2 8
7.8%
, 7
6.9%
8 7
6.9%
3 6
 
5.9%
4 5
 
4.9%
Other values (3) 7
6.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 102
98.1%
Hangul 2
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 15
14.7%
1 14
13.7%
0 13
12.7%
9 12
11.8%
6 8
7.8%
2 8
7.8%
, 7
6.9%
8 7
6.9%
3 6
 
5.9%
4 5
 
4.9%
Other values (3) 7
6.9%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:20.295204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique18 ?
Unique (%)54.5%

Sample

1st row양림동
2nd row3,159
3rd row6,948
4th row21
5th row5
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
5 2
 
6.1%
2 2
 
6.1%
21 2
 
6.1%
44 1
 
3.0%
24 1
 
3.0%
3,160 1
 
3.0%
3,159 1
 
3.0%
10 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:28:21.111709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.2%
0 10
15.2%
2 9
13.6%
5 6
9.1%
6 5
 
7.6%
4 5
 
7.6%
3 4
 
6.1%
, 4
 
6.1%
9 3
 
4.5%
8 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 (%)
1 14
23.7%
0 10
16.9%
2 9
15.3%
5 6
10.2%
6 5
 
8.5%
4 5
 
8.5%
3 4
 
6.8%
9 3
 
5.1%
8 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 (%)
1 14
22.2%
0 10
15.9%
2 9
14.3%
5 6
9.5%
6 5
 
7.9%
4 5
 
7.9%
3 4
 
6.3%
, 4
 
6.3%
9 3
 
4.8%
8 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 (%)
1 14
22.2%
0 10
15.9%
2 9
14.3%
5 6
9.5%
6 5
 
7.9%
4 5
 
7.9%
3 4
 
6.3%
, 4
 
6.3%
9 3
 
4.8%
8 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:21.449356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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 row방림1동
2nd row2,925
3rd row6,600
4th row19
5th row7
ValueCountFrequency (%)
0 8
24.2%
19 3
 
9.1%
30 2
 
6.1%
7 2
 
6.1%
37 2
 
6.1%
46 1
 
3.0%
6,600 1
 
3.0%
51 1
 
3.0%
2,927 1
 
3.0%
2 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:28:22.351686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.9%
2 9
13.4%
1 7
10.4%
9 7
10.4%
3 7
10.4%
6 6
9.0%
7 5
7.5%
, 4
 
6.0%
5 3
 
4.5%
4 2
 
3.0%
Other values (5) 5
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
88.1%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.3%
2 9
15.3%
1 7
11.9%
9 7
11.9%
3 7
11.9%
6 6
10.2%
7 5
8.5%
5 3
 
5.1%
4 2
 
3.4%
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 (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.8%
2 9
14.1%
1 7
10.9%
9 7
10.9%
3 7
10.9%
6 6
9.4%
7 5
7.8%
, 4
 
6.2%
5 3
 
4.7%
4 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
18.8%
2 9
14.1%
1 7
10.9%
9 7
10.9%
3 7
10.9%
6 6
9.4%
7 5
7.8%
, 4
 
6.2%
5 3
 
4.7%
4 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:22.677875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique19 ?
Unique (%)57.6%

Sample

1st row방림2동
2nd row4,085
3rd row8,835
4th row36
5th row10
ValueCountFrequency (%)
0 8
24.2%
10 2
 
6.1%
15 2
 
6.1%
36 2
 
6.1%
46 1
 
3.0%
49 1
 
3.0%
4,060 1
 
3.0%
71 1
 
3.0%
25 1
 
3.0%
13 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:28:23.432099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.9%
1 9
12.2%
8 7
9.5%
3 6
8.1%
5 6
8.1%
2 6
8.1%
4 6
8.1%
6 5
 
6.8%
, 4
 
5.4%
7 3
 
4.1%
Other values (5) 8
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
87.8%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
21.5%
1 9
13.8%
8 7
10.8%
3 6
9.2%
5 6
9.2%
2 6
9.2%
4 6
9.2%
6 5
 
7.7%
7 3
 
4.6%
9 3
 
4.6%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
19.7%
1 9
12.7%
8 7
9.9%
3 6
8.5%
5 6
8.5%
2 6
8.5%
4 6
8.5%
6 5
 
7.0%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 5
 
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
19.7%
1 9
12.7%
8 7
9.9%
3 6
8.5%
5 6
8.5%
2 6
8.5%
4 6
8.5%
6 5
 
7.0%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 5
 
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:23.781476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique22 ?
Unique (%)66.7%

Sample

1st row봉선1동
2nd row6,675
3rd row13,390
4th row47
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
8 2
 
6.1%
47 2
 
6.1%
77 1
 
3.0%
57 1
 
3.0%
6,683 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
41 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:28:24.716861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.2%
4 10
13.5%
3 9
12.2%
0 8
10.8%
6 8
10.8%
7 7
9.5%
, 4
 
5.4%
8 4
 
5.4%
5 3
 
4.1%
2 3
 
4.1%
Other values (5) 6
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
89.2%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.2%
4 10
15.2%
3 9
13.6%
0 8
12.1%
6 8
12.1%
7 7
10.6%
8 4
 
6.1%
5 3
 
4.5%
2 3
 
4.5%
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 (%)
- 1
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%
4 10
14.1%
3 9
12.7%
0 8
11.3%
6 8
11.3%
7 7
9.9%
, 4
 
5.6%
8 4
 
5.6%
5 3
 
4.2%
2 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
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%
4 10
14.1%
3 9
12.7%
0 8
11.3%
6 8
11.3%
7 7
9.9%
, 4
 
5.6%
8 4
 
5.6%
5 3
 
4.2%
2 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct28
Distinct (%)82.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:28:25.060612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6176471
Min length1

Characters and Unicode

Total characters89
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

Unique25 ?
Unique (%)73.5%

Sample

1st row출력일자 :
2nd row봉선2동
3rd row10,033
4th row28,830
5th row27
ValueCountFrequency (%)
1 5
 
14.3%
0 3
 
8.6%
17 2
 
5.7%
18 2
 
5.7%
7 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
28,765 1
 
2.9%
10,015 1
 
2.9%
65 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T09:28:25.867503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
22.5%
0 13
14.6%
7 8
 
9.0%
2 8
 
9.0%
8 8
 
9.0%
3 5
 
5.6%
5 5
 
5.6%
6 4
 
4.5%
, 4
 
4.5%
- 3
 
3.4%
Other values (11) 11
12.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
82.0%
Other Letter 7
 
7.9%
Other Punctuation 5
 
5.6%
Dash Punctuation 3
 
3.4%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
27.4%
0 13
17.8%
7 8
 
11.0%
2 8
 
11.0%
8 8
 
11.0%
3 5
 
6.8%
5 5
 
6.8%
6 4
 
5.5%
9 1
 
1.4%
4 1
 
1.4%
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 (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
92.1%
Hangul 7
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
24.4%
0 13
15.9%
7 8
 
9.8%
2 8
 
9.8%
8 8
 
9.8%
3 5
 
6.1%
5 5
 
6.1%
6 4
 
4.9%
, 4
 
4.9%
- 3
 
3.7%
Other values (4) 4
 
4.9%
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 82
92.1%
Hangul 7
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
24.4%
0 13
15.9%
7 8
 
9.8%
2 8
 
9.8%
8 8
 
9.8%
3 5
 
6.1%
5 5
 
6.1%
6 4
 
4.9%
, 4
 
4.9%
- 3
 
3.7%
Other values (4) 4
 
4.9%
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 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:26.242646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
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

Unique17 ?
Unique (%)51.5%

Sample

1st row사직동
2nd row2,946
3rd row5,143
4th row49
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 3
 
9.1%
23 2
 
6.1%
13 2
 
6.1%
24 2
 
6.1%
1 1
 
3.0%
50 1
 
3.0%
7 1
 
3.0%
5,144 1
 
3.0%
2,952 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:28:27.143480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
15.6%
4 9
14.1%
0 8
12.5%
3 7
10.9%
1 7
10.9%
5 5
7.8%
6 4
 
6.2%
, 4
 
6.2%
9 3
 
4.7%
7 3
 
4.7%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
89.1%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
17.5%
4 9
15.8%
0 8
14.0%
3 7
12.3%
1 7
12.3%
5 5
8.8%
6 4
 
7.0%
9 3
 
5.3%
7 3
 
5.3%
8 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61
95.3%
Hangul 3
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
16.4%
4 9
14.8%
0 8
13.1%
3 7
11.5%
1 7
11.5%
5 5
8.2%
6 4
 
6.6%
, 4
 
6.6%
9 3
 
4.9%
7 3
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
95.3%
Hangul 3
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
16.4%
4 9
14.8%
0 8
13.1%
3 7
11.5%
1 7
11.5%
5 5
8.2%
6 4
 
6.6%
, 4
 
6.6%
9 3
 
4.9%
7 3
 
4.9%
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
Minimum2022-05-12 00:00:00
Maximum2022-05-12 00:00:00
2024-02-10T09:28:27.581784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:28:27.854856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:28.178292image/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

Unique15 ?
Unique (%)45.5%

Sample

1st row월산동
2nd row4,630
3rd row8,975
4th row51
5th row6
ValueCountFrequency (%)
0 5
15.2%
2 3
 
9.1%
6 3
 
9.1%
49 2
 
6.1%
26 2
 
6.1%
36 2
 
6.1%
51 2
 
6.1%
46 1
 
3.0%
85 1
 
3.0%
8,975 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:28:29.060263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 (%)
6 11
18.3%
0 8
13.3%
2 7
11.7%
1 7
11.7%
4 6
10.0%
9 5
8.3%
3 5
8.3%
5 5
8.3%
8 4
 
6.7%
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 (%)
6 11
16.4%
0 8
11.9%
2 7
10.4%
1 7
10.4%
4 6
9.0%
9 5
7.5%
3 5
7.5%
5 5
7.5%
, 4
 
6.0%
8 4
 
6.0%
Other values (2) 5
7.5%
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 (%)
6 11
16.4%
0 8
11.9%
2 7
10.4%
1 7
10.4%
4 6
9.0%
9 5
7.5%
3 5
7.5%
5 5
7.5%
, 4
 
6.0%
8 4
 
6.0%
Other values (2) 5
7.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:29.427063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique25 ?
Unique (%)75.8%

Sample

1st row월산4동
2nd row4,828
3rd row8,512
4th row41
5th row5
ValueCountFrequency (%)
0 6
 
18.2%
5 2
 
6.1%
2 2
 
6.1%
3 2
 
6.1%
8,512 1
 
3.0%
55 1
 
3.0%
103 1
 
3.0%
8,509 1
 
3.0%
4,826 1
 
3.0%
1 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:28:30.277094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.3%
4 9
12.9%
5 8
11.4%
8 8
11.4%
1 7
10.0%
2 7
10.0%
3 6
8.6%
, 4
 
5.7%
6 3
 
4.3%
9 3
 
4.3%
Other values (4) 5
7.1%

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 10
16.4%
4 9
14.8%
5 8
13.1%
8 8
13.1%
1 7
11.5%
2 7
11.5%
3 6
9.8%
6 3
 
4.9%
9 3
 
4.9%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.9%
4 9
13.4%
5 8
11.9%
8 8
11.9%
1 7
10.4%
2 7
10.4%
3 6
9.0%
, 4
 
6.0%
6 3
 
4.5%
9 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 10
14.9%
4 9
13.4%
5 8
11.9%
8 8
11.9%
1 7
10.4%
2 7
10.4%
3 6
9.0%
, 4
 
6.0%
6 3
 
4.5%
9 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:30.719400image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row월산5동
2nd row3,552
3rd row6,409
4th row21
5th row5
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
26 2
 
6.1%
36 2
 
6.1%
44 1
 
3.0%
5 1
 
3.0%
71 1
 
3.0%
22 1
 
3.0%
6,369 1
 
3.0%
3,550 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:28:31.649783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.3%
3 10
14.3%
5 8
11.4%
1 7
10.0%
2 7
10.0%
6 7
10.0%
4 6
8.6%
, 4
 
5.7%
9 3
 
4.3%
8 2
 
2.9%
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 10
16.4%
3 10
16.4%
5 8
13.1%
1 7
11.5%
2 7
11.5%
6 7
11.5%
4 6
9.8%
9 3
 
4.9%
8 2
 
3.3%
7 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 10
14.9%
3 10
14.9%
5 8
11.9%
1 7
10.4%
2 7
10.4%
6 7
10.4%
4 6
9.0%
, 4
 
6.0%
9 3
 
4.5%
8 2
 
3.0%
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 10
14.9%
3 10
14.9%
5 8
11.9%
1 7
10.4%
2 7
10.4%
6 7
10.4%
4 6
9.0%
, 4
 
6.0%
9 3
 
4.5%
8 2
 
3.0%
Other values (2) 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
2024-02-10T09:28:32.164791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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 row백운1동
2nd row5,183
3rd row12,168
4th row21
5th row15
ValueCountFrequency (%)
0 8
24.2%
21 2
 
6.1%
15 2
 
6.1%
25 1
 
3.0%
12,168 1
 
3.0%
47 1
 
3.0%
5,186 1
 
3.0%
41 1
 
3.0%
3 1
 
3.0%
12 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:28:32.946943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
23.3%
0 9
12.3%
2 9
12.3%
5 7
9.6%
3 7
9.6%
4 4
 
5.5%
8 4
 
5.5%
, 4
 
5.5%
9 3
 
4.1%
6 3
 
4.1%
Other values (5) 6
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
26.2%
0 9
13.8%
2 9
13.8%
5 7
10.8%
3 7
10.8%
4 4
 
6.2%
8 4
 
6.2%
9 3
 
4.6%
6 3
 
4.6%
7 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
24.3%
0 9
12.9%
2 9
12.9%
5 7
10.0%
3 7
10.0%
4 4
 
5.7%
8 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
6 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
24.3%
0 9
12.9%
2 9
12.9%
5 7
10.0%
3 7
10.0%
4 4
 
5.7%
8 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
6 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:33.360070image/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 row3,349
3rd row6,378
4th row26
5th row2
ValueCountFrequency (%)
0 8
24.2%
26 2
 
6.1%
32 2
 
6.1%
5 2
 
6.1%
2 2
 
6.1%
105 1
 
3.0%
52 1
 
3.0%
6,378 1
 
3.0%
53 1
 
3.0%
3,344 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:28:34.428761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
18.6%
2 12
17.1%
0 11
15.7%
5 7
10.0%
6 6
8.6%
4 5
 
7.1%
, 4
 
5.7%
1 2
 
2.9%
7 2
 
2.9%
8 2
 
2.9%
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 (%)
3 13
21.3%
2 12
19.7%
0 11
18.0%
5 7
11.5%
6 6
9.8%
4 5
 
8.2%
1 2
 
3.3%
7 2
 
3.3%
8 2
 
3.3%
9 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 (%)
3 13
19.4%
2 12
17.9%
0 11
16.4%
5 7
10.4%
6 6
9.0%
4 5
 
7.5%
, 4
 
6.0%
1 2
 
3.0%
7 2
 
3.0%
8 2
 
3.0%
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 (%)
3 13
19.4%
2 12
17.9%
0 11
16.4%
5 7
10.4%
6 6
9.0%
4 5
 
7.5%
, 4
 
6.0%
1 2
 
3.0%
7 2
 
3.0%
8 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:34.816303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
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 row주월1동
2nd row9,683
3rd row21,964
4th row48
5th row14
ValueCountFrequency (%)
0 7
21.2%
14 3
 
9.1%
64 2
 
6.1%
73 2
 
6.1%
16 1
 
3.0%
48 1
 
3.0%
90 1
 
3.0%
22,031 1
 
3.0%
9,736 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:28:35.685142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.0%
3 11
13.8%
0 10
12.5%
4 9
11.2%
6 8
10.0%
2 6
7.5%
7 5
6.2%
9 5
6.2%
, 4
 
5.0%
8 3
 
3.8%
Other values (5) 7
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
90.0%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
16.7%
3 11
15.3%
0 10
13.9%
4 9
12.5%
6 8
11.1%
2 6
8.3%
7 5
6.9%
9 5
6.9%
8 3
 
4.2%
5 3
 
4.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
15.6%
3 11
14.3%
0 10
13.0%
4 9
11.7%
6 8
10.4%
2 6
7.8%
7 5
6.5%
9 5
6.5%
, 4
 
5.2%
8 3
 
3.9%
Other values (2) 4
 
5.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
15.6%
3 11
14.3%
0 10
13.0%
4 9
11.7%
6 8
10.4%
2 6
7.8%
7 5
6.5%
9 5
6.5%
, 4
 
5.2%
8 3
 
3.9%
Other values (2) 4
 
5.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:36.014592image/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

Unique15 ?
Unique (%)45.5%

Sample

1st row주월2동
2nd row4,057
3rd row7,989
4th row32
5th row6
ValueCountFrequency (%)
0 8
24.2%
24 2
 
6.1%
42 2
 
6.1%
32 2
 
6.1%
6 2
 
6.1%
23 2
 
6.1%
주월2동 1
 
3.0%
84 1
 
3.0%
7,989 1
 
3.0%
37 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:28:36.902998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
88.2%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
2 10
16.7%
4 10
16.7%
3 8
13.3%
8 5
8.3%
1 5
8.3%
7 5
8.3%
6 3
 
5.0%
9 3
 
5.0%
5 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
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%
2 10
15.4%
4 10
15.4%
3 8
12.3%
8 5
7.7%
1 5
7.7%
7 5
7.7%
, 4
 
6.2%
6 3
 
4.6%
9 3
 
4.6%
Other values (2) 2
 
3.1%
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%
2 10
15.4%
4 10
15.4%
3 8
12.3%
8 5
7.7%
1 5
7.7%
7 5
7.7%
, 4
 
6.2%
6 3
 
4.6%
9 3
 
4.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:37.284349image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row진월동
2nd row11,476
3rd row29,112
4th row52
5th row26
ValueCountFrequency (%)
0 7
21.2%
78 2
 
6.1%
26 2
 
6.1%
63 2
 
6.1%
52 2
 
6.1%
125 1
 
3.0%
11,470 1
 
3.0%
6 1
 
3.0%
1 1
 
3.0%
23 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:28:38.147827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
16.0%
1 12
14.8%
0 11
13.6%
6 7
8.6%
4 6
7.4%
5 5
 
6.2%
9 5
 
6.2%
8 5
 
6.2%
3 4
 
4.9%
, 4
 
4.9%
Other values (5) 9
11.1%

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 (%)
2 13
18.1%
1 12
16.7%
0 11
15.3%
6 7
9.7%
4 6
8.3%
5 5
 
6.9%
9 5
 
6.9%
8 5
 
6.9%
3 4
 
5.6%
7 4
 
5.6%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
16.7%
1 12
15.4%
0 11
14.1%
6 7
9.0%
4 6
7.7%
5 5
 
6.4%
9 5
 
6.4%
8 5
 
6.4%
3 4
 
5.1%
, 4
 
5.1%
Other values (2) 6
7.7%
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 (%)
2 13
16.7%
1 12
15.4%
0 11
14.1%
6 7
9.0%
4 6
7.7%
5 5
 
6.4%
9 5
 
6.4%
8 5
 
6.4%
3 4
 
5.1%
, 4
 
5.1%
Other values (2) 6
7.7%
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
2024-02-10T09:28:38.484030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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 row효덕동
2nd row7,481
3rd row16,015
4th row2
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
2 2
 
6.1%
140 2
 
6.1%
72 1
 
3.0%
16,015 1
 
3.0%
7,481 1
 
3.0%
7,523 1
 
3.0%
3 1
 
3.0%
42 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:28:39.298952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.3%
1 11
15.5%
4 8
11.3%
2 6
8.5%
6 6
8.5%
7 6
8.5%
3 6
8.5%
, 4
 
5.6%
5 3
 
4.2%
9 2
 
2.8%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
88.7%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.6%
1 11
17.5%
4 8
12.7%
2 6
9.5%
6 6
9.5%
7 6
9.5%
3 6
9.5%
5 3
 
4.8%
9 2
 
3.2%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
19.1%
1 11
16.2%
4 8
11.8%
2 6
8.8%
6 6
8.8%
7 6
8.8%
3 6
8.8%
, 4
 
5.9%
5 3
 
4.4%
9 2
 
2.9%
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 (%)
0 13
19.1%
1 11
16.2%
4 8
11.8%
2 6
8.8%
6 6
8.8%
7 6
8.8%
3 6
8.8%
, 4
 
5.9%
5 3
 
4.4%
9 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:39.767400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
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 row송암동
2nd row8,608
3rd row21,442
4th row18
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
19 2
 
6.1%
7 2
 
6.1%
83 1
 
3.0%
18 1
 
3.0%
97 1
 
3.0%
8,622 1
 
3.0%
4 1
 
3.0%
14 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:28:40.643864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
90.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.9%
0 9
13.8%
7 9
13.8%
4 7
10.8%
8 6
9.2%
2 6
9.2%
9 5
7.7%
6 5
7.7%
5 4
 
6.2%
3 3
 
4.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 23
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:41.058195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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

Unique19 ?
Unique (%)57.6%

Sample

1st row대촌동
2nd row3,293
3rd row6,298
4th row25
5th row1
ValueCountFrequency (%)
0 8
24.2%
3 2
 
6.1%
25 2
 
6.1%
29 2
 
6.1%
4 1
 
3.0%
1 1
 
3.0%
3,293 1
 
3.0%
3,413 1
 
3.0%
176 1
 
3.0%
120 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:28:41.992099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
15.1%
1 11
15.1%
0 10
13.7%
3 9
12.3%
6 6
8.2%
4 6
8.2%
9 5
6.8%
5 4
 
5.5%
, 4
 
5.5%
8 2
 
2.7%
Other values (4) 5
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
90.4%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
16.7%
1 11
16.7%
0 10
15.2%
3 9
13.6%
6 6
9.1%
4 6
9.1%
9 5
7.6%
5 4
 
6.1%
8 2
 
3.0%
7 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
15.7%
1 11
15.7%
0 10
14.3%
3 9
12.9%
6 6
8.6%
4 6
8.6%
9 5
7.1%
5 4
 
5.7%
, 4
 
5.7%
8 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
15.7%
1 11
15.7%
0 10
14.3%
3 9
12.9%
6 6
8.6%
4 6
8.6%
9 5
7.1%
5 4
 
5.7%
, 4
 
5.7%
8 2
 
2.9%
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>2022.05.12<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.04 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>95,9633,1592,9254,0856,67510,0332,946<NA>4,6304,8283,5525,1833,3499,6834,05711,4767,4818,6083,293
4<NA>전월말인구수<NA><NA><NA>215,0086,9486,6008,83513,39028,8305,143<NA>8,9758,5126,40912,1686,37821,9647,98929,11216,01521,4426,298
5<NA>전월말거주불명자수<NA><NA><NA>536211936472749<NA>514121212648325221825
6<NA>전월말재외국민등록자수<NA><NA><NA>151571011166<NA>65515214626971
7<NA>증 가 요 인전 입<NA>1,96256514813617050<NA>8510471696224284180140173241
8<NA><NA><NA>남자<NA>992223027648032<NA>495838343012342887377125
9<NA><NA><NA>여자<NA>970342121729018<NA>364633353211942926796116
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>7200110<NA>10100001000
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>2000010<NA>00000000010
28<NA>세대수증감<NA><NA><NA>18312-258-186<NA>-12-2-23-5534-64214120
29<NA>인구수증감<NA><NA><NA>-1602-37-71-8-651<NA>-15-3-40-41-4267-7-78-34176
30<NA>거주불명자수증감<NA><NA><NA>10000-13<NA>-22100-300010
31<NA>금월말세대수<NA><NA><NA>96,1463,1602,9274,0606,68310,0152,952<NA>4,6184,8263,5505,1863,3449,7364,06111,4707,5238,6223,413
32<NA>금월말인구수<NA><NA><NA>214,8486,9506,5638,76413,38228,7655,144<NA>8,9608,5096,36912,1276,33622,0317,98229,03416,01221,4466,474
33<NA>금월말거주불명자수<NA><NA><NA>537211936472652<NA>494322212645325221925
34<NA>금월말재외국민등록자수<NA><NA><NA>153571011176<NA>65415214626973