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

Description2023-11-10
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 09:39:11.533828
Analysis finished2024-02-10 09:39:12.507710
Duration0.97 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:39:12.702384image/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%
2024-02-10T09:39:13.586685image/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
2024-02-10T09:39:13.833141image/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%
2024-02-10T09:39:14.369994image/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
2024-02-10T09:39:14.707538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters20
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 row2023.09 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%
2023.09 1
7.1%
현재 1
7.1%
2024-02-10T09:39:15.423289image/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
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (10) 12
29.3%

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 2
33.3%
0 2
33.3%
9 1
16.7%
3 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 2
20.0%
0 2
20.0%
. 1
 
10.0%
9 1
 
10.0%
3 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 2
20.0%
0 2
20.0%
. 1
 
10.0%
9 1
 
10.0%
3 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:39:15.629146image/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%
2024-02-10T09:39:16.296300image/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 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:16.667335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.0606061
Min length1

Characters and Unicode

Total characters101
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row합 계
2nd row95,603
3rd row210,423
4th row346
5th row149
ValueCountFrequency (%)
0 3
 
8.8%
531 2
 
5.9%
2 2
 
5.9%
1 2
 
5.9%
939 1
 
2.9%
1,819 1
 
2.9%
347 1
 
2.9%
210,329 1
 
2.9%
95,626 1
 
2.9%
94 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:39:17.675380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
16.8%
3 10
9.9%
2 9
8.9%
4 9
8.9%
0 8
7.9%
9 8
7.9%
6 8
7.9%
5 7
6.9%
7 7
6.9%
8 7
6.9%
Other values (5) 11
10.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
18.9%
3 10
11.1%
2 9
10.0%
4 9
10.0%
0 8
8.9%
9 8
8.9%
6 8
8.9%
5 7
7.8%
7 7
7.8%
8 7
7.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
17.2%
3 10
10.1%
2 9
9.1%
4 9
9.1%
0 8
8.1%
9 8
8.1%
6 8
8.1%
5 7
7.1%
7 7
7.1%
8 7
7.1%
Other values (3) 9
9.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
17.2%
3 10
10.1%
2 9
9.1%
4 9
9.1%
0 8
8.1%
9 8
8.1%
6 8
8.1%
5 7
7.1%
7 7
7.1%
8 7
7.1%
Other values (3) 9
9.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:18.014330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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 row양림동
2nd row3,092
3rd row6,667
4th row15
5th row7
ValueCountFrequency (%)
0 8
24.2%
19 3
 
9.1%
7 2
 
6.1%
23 2
 
6.1%
15 2
 
6.1%
39 1
 
3.0%
20 1
 
3.0%
3,088 1
 
3.0%
3 1
 
3.0%
4 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:39:18.908200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
18.5%
1 10
15.4%
3 7
10.8%
9 6
9.2%
6 6
9.2%
7 4
 
6.2%
2 4
 
6.2%
, 4
 
6.2%
5 3
 
4.6%
4 3
 
4.6%
Other values (5) 6
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
87.7%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
21.1%
1 10
17.5%
3 7
12.3%
9 6
10.5%
6 6
10.5%
7 4
 
7.0%
2 4
 
7.0%
5 3
 
5.3%
4 3
 
5.3%
8 2
 
3.5%
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 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
19.4%
1 10
16.1%
3 7
11.3%
9 6
9.7%
6 6
9.7%
7 4
 
6.5%
2 4
 
6.5%
, 4
 
6.5%
5 3
 
4.8%
4 3
 
4.8%
Other values (2) 3
 
4.8%
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 12
19.4%
1 10
16.1%
3 7
11.3%
9 6
9.7%
6 6
9.7%
7 4
 
6.5%
2 4
 
6.5%
, 4
 
6.5%
5 3
 
4.8%
4 3
 
4.8%
Other values (2) 3
 
4.8%
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
2024-02-10T09:39:19.245628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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 row방림1동
2nd row3,083
3rd row6,768
4th row9
5th row6
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
6 2
 
6.1%
26 2
 
6.1%
2 2
 
6.1%
9 2
 
6.1%
23 1
 
3.0%
70 1
 
3.0%
3,086 1
 
3.0%
21 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:39:20.143810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
18.5%
6 11
16.9%
2 9
13.8%
3 7
10.8%
8 5
7.7%
1 4
 
6.2%
, 4
 
6.2%
9 3
 
4.6%
7 3
 
4.6%
4 2
 
3.1%
Other values (5) 5
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
87.7%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
21.1%
6 11
19.3%
2 9
15.8%
3 7
12.3%
8 5
8.8%
1 4
 
7.0%
9 3
 
5.3%
7 3
 
5.3%
4 2
 
3.5%
5 1
 
1.8%
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 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
19.4%
6 11
17.7%
2 9
14.5%
3 7
11.3%
8 5
8.1%
1 4
 
6.5%
, 4
 
6.5%
9 3
 
4.8%
7 3
 
4.8%
4 2
 
3.2%
Other values (2) 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 12
19.4%
6 11
17.7%
2 9
14.5%
3 7
11.3%
8 5
8.1%
1 4
 
6.5%
, 4
 
6.5%
9 3
 
4.8%
7 3
 
4.8%
4 2
 
3.2%
Other values (2) 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:20.462949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row방림2동
2nd row3,922
3rd row8,290
4th row17
5th row10
ValueCountFrequency (%)
0 8
24.2%
17 2
 
6.1%
15 2
 
6.1%
10 2
 
6.1%
25 1
 
3.0%
8,290 1
 
3.0%
53 1
 
3.0%
3,907 1
 
3.0%
42 1
 
3.0%
9 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:39:21.506998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
19.4%
2 12
16.7%
1 8
11.1%
3 6
8.3%
8 5
 
6.9%
9 5
 
6.9%
7 4
 
5.6%
5 4
 
5.6%
, 4
 
5.6%
4 3
 
4.2%
Other values (5) 7
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
87.5%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
22.2%
2 12
19.0%
1 8
12.7%
3 6
9.5%
8 5
 
7.9%
9 5
 
7.9%
7 4
 
6.3%
5 4
 
6.3%
4 3
 
4.8%
6 2
 
3.2%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.3%
2 12
17.4%
1 8
11.6%
3 6
8.7%
8 5
 
7.2%
9 5
 
7.2%
7 4
 
5.8%
5 4
 
5.8%
, 4
 
5.8%
4 3
 
4.3%
Other values (2) 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 (%)
0 14
20.3%
2 12
17.4%
1 8
11.6%
3 6
8.7%
8 5
 
7.2%
9 5
 
7.2%
7 4
 
5.8%
5 4
 
5.8%
, 4
 
5.8%
4 3
 
4.3%
Other values (2) 4
 
5.8%
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
2024-02-10T09:39:21.811866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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 row봉선1동
2nd row6,464
3rd row12,879
4th row41
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
31 2
 
6.1%
41 2
 
6.1%
4 1
 
3.0%
37 1
 
3.0%
12,855 1
 
3.0%
6,454 1
 
3.0%
2 1
 
3.0%
24 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:39:22.566317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.3%
0 9
12.0%
4 9
12.0%
3 7
9.3%
5 6
8.0%
2 6
8.0%
6 4
 
5.3%
, 4
 
5.3%
7 4
 
5.3%
9 4
 
5.3%
Other values (5) 9
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
86.7%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
4.0%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
20.0%
0 9
13.8%
4 9
13.8%
3 7
10.8%
5 6
9.2%
2 6
9.2%
6 4
 
6.2%
7 4
 
6.2%
9 4
 
6.2%
8 3
 
4.6%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.1%
0 9
12.5%
4 9
12.5%
3 7
9.7%
5 6
8.3%
2 6
8.3%
6 4
 
5.6%
, 4
 
5.6%
7 4
 
5.6%
9 4
 
5.6%
Other values (2) 6
8.3%
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 13
18.1%
0 9
12.5%
4 9
12.5%
3 7
9.7%
5 6
8.3%
2 6
8.3%
6 4
 
5.6%
, 4
 
5.6%
7 4
 
5.6%
9 4
 
5.6%
Other values (2) 6
8.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct27
Distinct (%)79.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:39:22.908321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4705882
Min length1

Characters and Unicode

Total characters84
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 row9,808
4th row27,784
5th row10
ValueCountFrequency (%)
0 6
 
17.1%
10 2
 
5.7%
16 2
 
5.7%
124 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
241 1
 
2.9%
9,793 1
 
2.9%
60 1
 
2.9%
15 1
 
2.9%
Other values (18) 18
51.4%
2024-02-10T09:39:23.932564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
14.3%
7 11
13.1%
0 10
11.9%
9 7
8.3%
4 6
7.1%
2 6
7.1%
5 5
 
6.0%
3 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
Other values (11) 14
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
82.1%
Other Letter 7
 
8.3%
Other Punctuation 5
 
6.0%
Dash Punctuation 2
 
2.4%
Space Separator 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.4%
7 11
15.9%
0 10
14.5%
9 7
10.1%
4 6
8.7%
2 6
8.7%
5 5
7.2%
3 5
7.2%
8 4
 
5.8%
6 3
 
4.3%
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 77
91.7%
Hangul 7
 
8.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
15.6%
7 11
14.3%
0 10
13.0%
9 7
9.1%
4 6
7.8%
2 6
7.8%
5 5
6.5%
3 5
6.5%
, 4
 
5.2%
8 4
 
5.2%
Other values (4) 7
9.1%
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 77
91.7%
Hangul 7
 
8.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
15.6%
7 11
14.3%
0 10
13.0%
9 7
9.1%
4 6
7.8%
2 6
7.8%
5 5
6.5%
3 5
6.5%
, 4
 
5.2%
8 4
 
5.2%
Other values (4) 7
9.1%
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 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:24.303806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique19 ?
Unique (%)57.6%

Sample

1st row사직동
2nd row2,801
3rd row4,773
4th row33
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 2
 
6.1%
33 2
 
6.1%
10 2
 
6.1%
25 2
 
6.1%
23 1
 
3.0%
4,773 1
 
3.0%
24 1
 
3.0%
2,791 1
 
3.0%
14 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:39:25.325078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.9%
1 9
13.4%
2 7
10.4%
3 6
9.0%
4 6
9.0%
5 5
7.5%
7 5
7.5%
9 4
 
6.0%
, 4
 
6.0%
8 2
 
3.0%
Other values (5) 7
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
86.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.7%
1 9
15.5%
2 7
12.1%
3 6
10.3%
4 6
10.3%
5 5
8.6%
7 5
8.6%
9 4
 
6.9%
8 2
 
3.4%
6 2
 
3.4%
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 64
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.8%
1 9
14.1%
2 7
10.9%
3 6
9.4%
4 6
9.4%
5 5
7.8%
7 5
7.8%
9 4
 
6.2%
, 4
 
6.2%
8 2
 
3.1%
Other values (2) 4
 
6.2%
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%
1 9
14.1%
2 7
10.9%
3 6
9.4%
4 6
9.4%
5 5
7.8%
7 5
7.8%
9 4
 
6.2%
, 4
 
6.2%
8 2
 
3.1%
Other values (2) 4
 
6.2%
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
Minimum2023-10-25 00:00:00
Maximum2023-10-25 00:00:00
2024-02-10T09:39:25.682769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:39:26.034108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:26.348172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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 row월산동
2nd row4,505
3rd row8,704
4th row23
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
50 2
 
6.1%
23 2
 
6.1%
46 1
 
3.0%
53 1
 
3.0%
8,649 1
 
3.0%
4,477 1
 
3.0%
1 1
 
3.0%
55 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:39:27.392073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.8%
4 10
14.5%
7 7
10.1%
5 7
10.1%
2 6
8.7%
3 5
 
7.2%
, 4
 
5.8%
8 4
 
5.8%
1 4
 
5.8%
6 3
 
4.3%
Other values (5) 6
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.7%
4 10
16.7%
7 7
11.7%
5 7
11.7%
2 6
10.0%
3 5
 
8.3%
8 4
 
6.7%
1 4
 
6.7%
6 3
 
5.0%
9 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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
19.7%
4 10
15.2%
7 7
10.6%
5 7
10.6%
2 6
9.1%
3 5
 
7.6%
, 4
 
6.1%
8 4
 
6.1%
1 4
 
6.1%
6 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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
19.7%
4 10
15.2%
7 7
10.6%
5 7
10.6%
2 6
9.1%
3 5
 
7.6%
, 4
 
6.1%
8 4
 
6.1%
1 4
 
6.1%
6 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:27.884412image/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 row월산4동
2nd row4,740
3rd row8,162
4th row30
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 3
 
9.1%
19 2
 
6.1%
13 2
 
6.1%
55 1
 
3.0%
30 1
 
3.0%
44 1
 
3.0%
8,142 1
 
3.0%
4,737 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:39:28.861227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.7%
1 9
12.9%
4 9
12.9%
3 8
11.4%
5 5
7.1%
7 5
7.1%
2 5
7.1%
8 4
 
5.7%
, 4
 
5.7%
9 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 (%)
0 11
18.3%
1 9
15.0%
4 9
15.0%
3 8
13.3%
5 5
8.3%
7 5
8.3%
2 5
8.3%
8 4
 
6.7%
9 3
 
5.0%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.4%
1 9
13.4%
4 9
13.4%
3 8
11.9%
5 5
7.5%
7 5
7.5%
2 5
7.5%
8 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 (%)
0 11
16.4%
1 9
13.4%
4 9
13.4%
3 8
11.9%
5 5
7.5%
7 5
7.5%
2 5
7.5%
8 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: 15
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:29.232811image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row월산5동
2nd row3,452
3rd row6,027
4th row10
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
16 2
 
6.1%
1 2
 
6.1%
10 2
 
6.1%
23 1
 
3.0%
33 1
 
3.0%
6,003 1
 
3.0%
3,437 1
 
3.0%
24 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:39:30.118414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
18.8%
0 12
17.4%
3 11
15.9%
2 6
8.7%
6 5
 
7.2%
5 5
 
7.2%
7 4
 
5.8%
, 4
 
5.8%
4 3
 
4.3%
- 2
 
2.9%
Other values (4) 4
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
21.7%
0 12
20.0%
3 11
18.3%
2 6
10.0%
6 5
 
8.3%
5 5
 
8.3%
7 4
 
6.7%
4 3
 
5.0%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
19.7%
0 12
18.2%
3 11
16.7%
2 6
9.1%
6 5
 
7.6%
5 5
 
7.6%
7 4
 
6.1%
, 4
 
6.1%
4 3
 
4.5%
- 2
 
3.0%
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 (%)
1 13
19.7%
0 12
18.2%
3 11
16.7%
2 6
9.1%
6 5
 
7.6%
5 5
 
7.6%
7 4
 
6.1%
, 4
 
6.1%
4 3
 
4.5%
- 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:30.522996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row백운1동
2nd row5,144
3rd row11,739
4th row14
5th row15
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
15 3
 
9.1%
40 2
 
6.1%
12 1
 
3.0%
5,151 1
 
3.0%
1 1
 
3.0%
7 1
 
3.0%
22 1
 
3.0%
32 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:39:31.280351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
21.4%
0 10
14.3%
3 9
12.9%
4 8
11.4%
5 6
 
8.6%
2 6
 
8.6%
7 5
 
7.1%
, 4
 
5.7%
9 2
 
2.9%
6 2
 
2.9%
Other values (3) 3
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
90.0%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
23.8%
0 10
15.9%
3 9
14.3%
4 8
12.7%
5 6
 
9.5%
2 6
 
9.5%
7 5
 
7.9%
9 2
 
3.2%
6 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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%
0 10
14.9%
3 9
13.4%
4 8
11.9%
5 6
 
9.0%
2 6
 
9.0%
7 5
 
7.5%
, 4
 
6.0%
9 2
 
3.0%
6 2
 
3.0%
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%
0 10
14.9%
3 9
13.4%
4 8
11.9%
5 6
 
9.0%
2 6
 
9.0%
7 5
 
7.5%
, 4
 
6.0%
9 2
 
3.0%
6 2
 
3.0%
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
2024-02-10T09:39:31.643501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
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 row백운2동
2nd row3,410
3rd row6,427
4th row26
5th row2
ValueCountFrequency (%)
0 8
24.2%
2 2
 
6.1%
26 2
 
6.1%
3 2
 
6.1%
34 1
 
3.0%
6,427 1
 
3.0%
38 1
 
3.0%
3,532 1
 
3.0%
211 1
 
3.0%
122 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:39:32.453755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
16.2%
0 11
14.9%
3 10
13.5%
1 8
10.8%
4 8
10.8%
6 6
8.1%
8 5
6.8%
, 4
 
5.4%
5 3
 
4.1%
7 2
 
2.7%
Other values (4) 5
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
90.5%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
17.9%
0 11
16.4%
3 10
14.9%
1 8
11.9%
4 8
11.9%
6 6
9.0%
8 5
7.5%
5 3
 
4.5%
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%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
16.9%
0 11
15.5%
3 10
14.1%
1 8
11.3%
4 8
11.3%
6 6
8.5%
8 5
7.0%
, 4
 
5.6%
5 3
 
4.2%
7 2
 
2.8%
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 (%)
2 12
16.9%
0 11
15.5%
3 10
14.1%
1 8
11.3%
4 8
11.3%
6 6
8.5%
8 5
7.0%
, 4
 
5.6%
5 3
 
4.2%
7 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:32.875164image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row주월1동
2nd row9,584
3rd row21,299
4th row22
5th row13
ValueCountFrequency (%)
0 6
 
18.2%
13 3
 
9.1%
92 2
 
6.1%
8 1
 
3.0%
197 1
 
3.0%
21,293 1
 
3.0%
9,575 1
 
3.0%
3 1
 
3.0%
6 1
 
3.0%
9 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:39:33.741507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.9%
9 10
13.0%
0 9
11.7%
2 9
11.7%
3 8
10.4%
5 8
10.4%
, 4
 
5.2%
7 4
 
5.2%
8 3
 
3.9%
4 2
 
2.6%
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%
9 10
14.7%
0 9
13.2%
2 9
13.2%
3 8
11.8%
5 8
11.8%
7 4
 
5.9%
8 3
 
4.4%
4 2
 
2.9%
6 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%
9 10
13.5%
0 9
12.2%
2 9
12.2%
3 8
10.8%
5 8
10.8%
, 4
 
5.4%
7 4
 
5.4%
8 3
 
4.1%
4 2
 
2.7%
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%
9 10
13.5%
0 9
12.2%
2 9
12.2%
3 8
10.8%
5 8
10.8%
, 4
 
5.4%
7 4
 
5.4%
8 3
 
4.1%
4 2
 
2.7%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:34.070660image/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 row주월2동
2nd row3,907
3rd row7,612
4th row30
5th row5
ValueCountFrequency (%)
0 7
21.2%
29 2
 
6.1%
5 2
 
6.1%
25 2
 
6.1%
22 2
 
6.1%
28 1
 
3.0%
30 1
 
3.0%
56 1
 
3.0%
3,895 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:39:34.857836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
21.1%
0 9
12.7%
5 8
11.3%
7 6
 
8.5%
1 6
 
8.5%
3 5
 
7.0%
9 4
 
5.6%
, 4
 
5.6%
8 4
 
5.6%
- 3
 
4.2%
Other values (5) 7
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
24.6%
0 9
14.8%
5 8
13.1%
7 6
 
9.8%
1 6
 
9.8%
3 5
 
8.2%
9 4
 
6.6%
8 4
 
6.6%
4 2
 
3.3%
6 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 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
22.1%
0 9
13.2%
5 8
11.8%
7 6
 
8.8%
1 6
 
8.8%
3 5
 
7.4%
9 4
 
5.9%
, 4
 
5.9%
8 4
 
5.9%
- 3
 
4.4%
Other values (2) 4
 
5.9%
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 15
22.1%
0 9
13.2%
5 8
11.8%
7 6
 
8.8%
1 6
 
8.8%
3 5
 
7.4%
9 4
 
5.9%
, 4
 
5.9%
8 4
 
5.9%
- 3
 
4.4%
Other values (2) 4
 
5.9%
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
2024-02-10T09:39:35.227167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
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 row11,453
3rd row28,287
4th row36
5th row28
ValueCountFrequency (%)
0 6
 
18.2%
28 2
 
6.1%
36 2
 
6.1%
109 1
 
3.0%
204 1
 
3.0%
11,471 1
 
3.0%
25 1
 
3.0%
18 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:39:36.118621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.5%
2 11
13.9%
0 8
10.1%
8 8
10.1%
6 7
8.9%
4 6
7.6%
5 6
7.6%
3 5
 
6.3%
7 5
 
6.3%
, 4
 
5.1%
Other values (5) 6
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
89.9%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
18.3%
2 11
15.5%
0 8
11.3%
8 8
11.3%
6 7
9.9%
4 6
8.5%
5 6
8.5%
3 5
 
7.0%
7 5
 
7.0%
9 2
 
2.8%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.1%
2 11
14.5%
0 8
10.5%
8 8
10.5%
6 7
9.2%
4 6
7.9%
5 6
7.9%
3 5
 
6.6%
7 5
 
6.6%
, 4
 
5.3%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
17.1%
2 11
14.5%
0 8
10.5%
8 8
10.5%
6 7
9.2%
4 6
7.9%
5 6
7.9%
3 5
 
6.6%
7 5
 
6.6%
, 4
 
5.3%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:36.581462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique15 ?
Unique (%)45.5%

Sample

1st row효덕동
2nd row7,492
3rd row15,593
4th row10
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
5 2
 
6.1%
38 2
 
6.1%
61 2
 
6.1%
10 2
 
6.1%
효덕동 1
 
3.0%
122 1
 
3.0%
15,593 1
 
3.0%
41 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:39:37.416432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
18.6%
0 11
15.7%
5 8
11.4%
3 6
8.6%
4 6
8.6%
7 5
 
7.1%
6 4
 
5.7%
, 4
 
5.7%
2 4
 
5.7%
8 3
 
4.3%
Other values (4) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
90.0%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
20.6%
0 11
17.5%
5 8
12.7%
3 6
9.5%
4 6
9.5%
7 5
 
7.9%
6 4
 
6.3%
2 4
 
6.3%
8 3
 
4.8%
9 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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
19.4%
0 11
16.4%
5 8
11.9%
3 6
9.0%
4 6
9.0%
7 5
 
7.5%
6 4
 
6.0%
, 4
 
6.0%
2 4
 
6.0%
8 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 (%)
1 13
19.4%
0 11
16.4%
5 8
11.9%
3 6
9.0%
4 6
9.0%
7 5
 
7.5%
6 4
 
6.0%
, 4
 
6.0%
2 4
 
6.0%
8 3
 
4.5%
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
2024-02-10T09:39:37.962838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row송암동
2nd row8,638
3rd row21,173
4th row14
5th row5
ValueCountFrequency (%)
0 8
24.2%
60 2
 
6.1%
14 2
 
6.1%
1 2
 
6.1%
47 1
 
3.0%
5 1
 
3.0%
83 1
 
3.0%
21,172 1
 
3.0%
8,637 1
 
3.0%
8,638 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:39:38.825887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
18.1%
0 10
13.9%
7 8
11.1%
6 7
9.7%
8 6
8.3%
3 5
 
6.9%
2 4
 
5.6%
9 4
 
5.6%
, 4
 
5.6%
4 3
 
4.2%
Other values (5) 8
11.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
87.5%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
20.6%
0 10
15.9%
7 8
12.7%
6 7
11.1%
8 6
9.5%
3 5
 
7.9%
2 4
 
6.3%
9 4
 
6.3%
4 3
 
4.8%
5 3
 
4.8%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.8%
0 10
14.5%
7 8
11.6%
6 7
10.1%
8 6
8.7%
3 5
 
7.2%
2 4
 
5.8%
9 4
 
5.8%
, 4
 
5.8%
4 3
 
4.3%
Other values (2) 5
 
7.2%
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 13
18.8%
0 10
14.5%
7 8
11.6%
6 7
10.1%
8 6
8.7%
3 5
 
7.2%
2 4
 
5.8%
9 4
 
5.8%
, 4
 
5.8%
4 3
 
4.3%
Other values (2) 5
 
7.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:39.224882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)39.4%

Sample

1st row대촌동
2nd row4,108
3rd row8,239
4th row6
5th row4
ValueCountFrequency (%)
0 7
21.2%
6 3
 
9.1%
17 2
 
6.1%
4 2
 
6.1%
24 2
 
6.1%
25 2
 
6.1%
34 2
 
6.1%
5 1
 
3.0%
67 1
 
3.0%
4,091 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:39:40.082041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.6%
4 9
13.6%
2 9
13.6%
1 8
12.1%
3 5
7.6%
8 5
7.6%
6 4
6.1%
, 4
6.1%
7 3
 
4.5%
5 3
 
4.5%
Other values (5) 7
10.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.8%
4 9
15.8%
2 9
15.8%
1 8
14.0%
3 5
8.8%
8 5
8.8%
6 4
7.0%
7 3
 
5.3%
5 3
 
5.3%
9 2
 
3.5%
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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
14.3%
4 9
14.3%
2 9
14.3%
1 8
12.7%
3 5
7.9%
8 5
7.9%
6 4
6.3%
, 4
6.3%
7 3
 
4.8%
5 3
 
4.8%
Other values (2) 4
6.3%
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 9
14.3%
4 9
14.3%
2 9
14.3%
1 8
12.7%
3 5
7.9%
8 5
7.9%
6 4
6.3%
, 4
6.3%
7 3
 
4.8%
5 3
 
4.8%
Other values (2) 4
6.3%
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>2023.10.25<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.09 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>95,6033,0923,0833,9226,4649,8082,801<NA>4,5054,7403,4525,1443,4109,5843,90711,4537,4928,6384,108
4<NA>전월말인구수<NA><NA><NA>210,4236,6676,7688,29012,87927,7844,773<NA>8,7048,1626,02711,7396,42721,2997,61228,28715,59321,1738,239
5<NA>전월말거주불명자수<NA><NA><NA>34615917411033<NA>233010142622303610146
6<NA>전월말재외국민등록자수<NA><NA><NA>149761011165<NA>75315213528754
7<NA>증 가 요 인전 입<NA>1,7584666467717740<NA>507133762931955618512217748
8<NA><NA><NA>남자<NA>884234026428321<NA>273121361471032974619624
9<NA><NA><NA>여자<NA>874232620359419<NA>234012401469227111618124
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>2000000<NA>00000001100
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>1000010<NA>00000000000
28<NA>세대수증감<NA><NA><NA>23-43-15-10-15-10<NA>-28-3-157122-9-121812-1-17
29<NA>인구수증감<NA><NA><NA>-943-3-42-24-60-14<NA>-55-20-243211-6-25-255-1-17
30<NA>거주불명자수증감<NA><NA><NA>1000-200<NA>1-21103-10000
31<NA>금월말세대수<NA><NA><NA>95,6263,0883,0863,9076,4549,7932,791<NA>4,4774,7373,4375,1513,5329,5753,89511,4717,5048,6374,091
32<NA>금월말인구수<NA><NA><NA>210,3296,6706,7658,24812,85527,7244,759<NA>8,6498,1426,00311,7426,63821,2937,58728,26215,59821,1728,222
33<NA>금월말거주불명자수<NA><NA><NA>34715917391033<NA>242811152625293610146
34<NA>금월말재외국민등록자수<NA><NA><NA>151761011165<NA>75315213528774