Overview

Dataset statistics

Number of variables24
Number of observations35
Missing cells201
Missing cells (%)23.9%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory6.7 KiB
Average record size in memory196.8 B

Variable types

Unsupported1
Text22
DateTime1

Dataset

Description2022-04-13
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201925

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 2 (5.7%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 09:26:59.255193
Analysis finished2024-02-10 09:27:00.304061
Duration1.05 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
2024-02-10T09:27:00.586307image/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%
2024-02-10T09:27:01.644854image/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
2024-02-10T09:27:02.079235image/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%
2024-02-10T09:27:03.118313image/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
2024-02-10T09:27:03.601076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters18
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 row2022.02 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%
2022.02 1
7.1%
현재 1
7.1%
2024-02-10T09:27:04.361231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
4
 
9.8%
4
 
9.8%
2 4
 
9.8%
3
 
7.3%
3
 
7.3%
2
 
4.9%
0 2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (8) 10
24.4%

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 4
66.7%
0 2
33.3%
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 (%)
2 4
40.0%
3
30.0%
0 2
20.0%
. 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 (%)
2 4
40.0%
3
30.0%
0 2
20.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:27:04.804717image/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%
2024-02-10T09:27:05.568667image/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 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:06.109751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.5757576
Min length1

Characters and Unicode

Total characters118
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 row95,849
3rd row215,739
4th row542
5th row150
ValueCountFrequency (%)
0 5
 
14.7%
721 2
 
5.9%
150 2
 
5.9%
1,559 1
 
2.9%
1,452 1
 
2.9%
215,454 1
 
2.9%
95,954 1
 
2.9%
11 1
 
2.9%
285 1
 
2.9%
105 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T09:27:07.266472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
19.5%
5 16
13.6%
2 14
11.9%
, 13
11.0%
0 12
10.2%
9 9
 
7.6%
7 7
 
5.9%
4 7
 
5.9%
8 5
 
4.2%
3 4
 
3.4%
Other values (5) 8
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 99
83.9%
Other Punctuation 13
 
11.0%
Space Separator 2
 
1.7%
Dash Punctuation 2
 
1.7%
Other Letter 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
23.2%
5 16
16.2%
2 14
14.1%
0 12
12.1%
9 9
 
9.1%
7 7
 
7.1%
4 7
 
7.1%
8 5
 
5.1%
3 4
 
4.0%
6 2
 
2.0%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 116
98.3%
Hangul 2
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
19.8%
5 16
13.8%
2 14
12.1%
, 13
11.2%
0 12
10.3%
9 9
 
7.8%
7 7
 
6.0%
4 7
 
6.0%
8 5
 
4.3%
3 4
 
3.4%
Other values (3) 6
 
5.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 116
98.3%
Hangul 2
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
19.8%
5 16
13.8%
2 14
12.1%
, 13
11.2%
0 12
10.3%
9 9
 
7.8%
7 7
 
6.0%
4 7
 
6.0%
8 5
 
4.3%
3 4
 
3.4%
Other values (3) 6
 
5.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:07.677832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row양림동
2nd row3,164
3rd row7,003
4th row21
5th row5
ValueCountFrequency (%)
0 8
24.2%
21 3
 
9.1%
5 2
 
6.1%
50 1
 
3.0%
7,003 1
 
3.0%
3,164 1
 
3.0%
3,160 1
 
3.0%
49 1
 
3.0%
4 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:27:08.837990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.3%
2 8
11.6%
1 7
10.1%
3 7
10.1%
5 6
8.7%
7 5
 
7.2%
4 5
 
7.2%
9 4
 
5.8%
6 4
 
5.8%
, 4
 
5.8%
Other values (4) 5
 
7.2%

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 14
23.3%
2 8
13.3%
1 7
11.7%
3 7
11.7%
5 6
10.0%
7 5
 
8.3%
4 5
 
8.3%
9 4
 
6.7%
6 4
 
6.7%
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 14
21.2%
2 8
12.1%
1 7
10.6%
3 7
10.6%
5 6
9.1%
7 5
 
7.6%
4 5
 
7.6%
9 4
 
6.1%
6 4
 
6.1%
, 4
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
21.2%
2 8
12.1%
1 7
10.6%
3 7
10.6%
5 6
9.1%
7 5
 
7.6%
4 5
 
7.6%
9 4
 
6.1%
6 4
 
6.1%
, 4
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:09.406686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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 row방림1동
2nd row2,931
3rd row6,640
4th row19
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 2
 
6.1%
19 2
 
6.1%
25 2
 
6.1%
18 1
 
3.0%
6,640 1
 
3.0%
36 1
 
3.0%
2,937 1
 
3.0%
12 1
 
3.0%
6 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:27:10.690507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.9%
2 8
11.9%
1 7
10.4%
9 6
9.0%
4 6
9.0%
3 6
9.0%
6 6
9.0%
5 5
7.5%
7 4
 
6.0%
, 4
 
6.0%
Other values (4) 5
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
89.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
2 8
13.3%
1 7
11.7%
9 6
10.0%
4 6
10.0%
3 6
10.0%
6 6
10.0%
5 5
8.3%
7 4
 
6.7%
8 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.6%
2 8
12.5%
1 7
10.9%
9 6
9.4%
4 6
9.4%
3 6
9.4%
6 6
9.4%
5 5
7.8%
7 4
 
6.2%
, 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 10
15.6%
2 8
12.5%
1 7
10.9%
9 6
9.4%
4 6
9.4%
3 6
9.4%
6 6
9.4%
5 5
7.8%
7 4
 
6.2%
, 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:11.268775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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 row4,078
3rd row8,891
4th row38
5th row10
ValueCountFrequency (%)
0 6
18.2%
10 3
 
9.1%
23 2
 
6.1%
27 2
 
6.1%
1 2
 
6.1%
32 1
 
3.0%
77 1
 
3.0%
8,881 1
 
3.0%
4,090 1
 
3.0%
12 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:27:12.518631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.1%
2 11
15.3%
1 8
11.1%
3 7
9.7%
8 7
9.7%
7 6
8.3%
4 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
5 2
 
2.8%
Other values (5) 6
8.3%

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 13
20.6%
2 11
17.5%
1 8
12.7%
3 7
11.1%
8 7
11.1%
7 6
9.5%
4 4
 
6.3%
9 4
 
6.3%
5 2
 
3.2%
6 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.8%
2 11
15.9%
1 8
11.6%
3 7
10.1%
8 7
10.1%
7 6
8.7%
4 4
 
5.8%
, 4
 
5.8%
9 4
 
5.8%
5 2
 
2.9%
Other values (2) 3
 
4.3%
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 13
18.8%
2 11
15.9%
1 8
11.6%
3 7
10.1%
8 7
10.1%
7 6
8.7%
4 4
 
5.8%
, 4
 
5.8%
9 4
 
5.8%
5 2
 
2.9%
Other values (2) 3
 
4.3%
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
2024-02-10T09:27:12.946298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
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 row6,677
3rd row13,460
4th row46
5th row11
ValueCountFrequency (%)
0 7
21.2%
85 2
 
6.1%
1 2
 
6.1%
11 2
 
6.1%
37 1
 
3.0%
98 1
 
3.0%
13,425 1
 
3.0%
6,678 1
 
3.0%
35 1
 
3.0%
14 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:27:13.879653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.8%
0 9
11.8%
6 9
11.8%
5 8
10.5%
4 7
9.2%
8 6
7.9%
3 6
7.9%
7 5
6.6%
, 4
 
5.3%
2 3
 
3.9%
Other values (5) 7
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
88.2%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.9%
0 9
13.4%
6 9
13.4%
5 8
11.9%
4 7
10.4%
8 6
9.0%
3 6
9.0%
7 5
7.5%
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 (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.4%
0 9
12.3%
6 9
12.3%
5 8
11.0%
4 7
9.6%
8 6
8.2%
3 6
8.2%
7 5
6.8%
, 4
 
5.5%
2 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
96.1%
Hangul 3
 
3.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.4%
0 9
12.3%
6 9
12.3%
5 8
11.0%
4 7
9.6%
8 6
8.2%
3 6
8.2%
7 5
6.8%
, 4
 
5.5%
2 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:27:14.218519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.7058824
Min length1

Characters and Unicode

Total characters92
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

Unique23 ?
Unique (%)67.6%

Sample

1st row출력일자 :
2nd row봉선2동
3rd row9,998
4th row28,848
5th row26
ValueCountFrequency (%)
0 7
20.0%
10 2
 
5.7%
16 2
 
5.7%
1
 
2.9%
28,955 1
 
2.9%
10,027 1
 
2.9%
1 1
 
2.9%
107 1
 
2.9%
29 1
 
2.9%
209 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T09:27:15.058399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
15.2%
2 13
14.1%
1 11
12.0%
9 11
12.0%
6 8
8.7%
8 5
 
5.4%
7 5
 
5.4%
5 5
 
5.4%
4 4
 
4.3%
, 4
 
4.3%
Other values (10) 12
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
85.9%
Other Letter 7
 
7.6%
Other Punctuation 5
 
5.4%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
17.7%
2 13
16.5%
1 11
13.9%
9 11
13.9%
6 8
10.1%
8 5
 
6.3%
7 5
 
6.3%
5 5
 
6.3%
4 4
 
5.1%
3 3
 
3.8%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85
92.4%
Hangul 7
 
7.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
16.5%
2 13
15.3%
1 11
12.9%
9 11
12.9%
6 8
9.4%
8 5
 
5.9%
7 5
 
5.9%
5 5
 
5.9%
4 4
 
4.7%
, 4
 
4.7%
Other values (3) 5
 
5.9%
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 85
92.4%
Hangul 7
 
7.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
16.5%
2 13
15.3%
1 11
12.9%
9 11
12.9%
6 8
9.4%
8 5
 
5.9%
7 5
 
5.9%
5 5
 
5.9%
4 4
 
4.7%
, 4
 
4.7%
Other values (3) 5
 
5.9%
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 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:15.459163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique23 ?
Unique (%)69.7%

Sample

1st row사직동
2nd row2,967
3rd row5,215
4th row49
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
27 2
 
6.1%
1 2
 
6.1%
6 2
 
6.1%
29 1
 
3.0%
57 1
 
3.0%
5,157 1
 
3.0%
2,949 1
 
3.0%
58 1
 
3.0%
18 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:27:16.334314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
14.1%
0 9
12.7%
2 9
12.7%
5 9
12.7%
7 6
8.5%
9 5
7.0%
6 4
 
5.6%
, 4
 
5.6%
4 3
 
4.2%
3 3
 
4.2%
Other values (5) 9
12.7%

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 (%)
1 10
16.4%
0 9
14.8%
2 9
14.8%
5 9
14.8%
7 6
9.8%
9 5
8.2%
6 4
 
6.6%
4 3
 
4.9%
3 3
 
4.9%
8 3
 
4.9%
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 (%)
1 10
14.7%
0 9
13.2%
2 9
13.2%
5 9
13.2%
7 6
8.8%
9 5
7.4%
6 4
 
5.9%
, 4
 
5.9%
4 3
 
4.4%
3 3
 
4.4%
Other values (2) 6
8.8%
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 (%)
1 10
14.7%
0 9
13.2%
2 9
13.2%
5 9
13.2%
7 6
8.8%
9 5
7.4%
6 4
 
5.9%
, 4
 
5.9%
4 3
 
4.4%
3 3
 
4.4%
Other values (2) 6
8.8%
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
Minimum2022-03-04 00:00:00
Maximum2022-03-04 00:00:00
2024-02-10T09:27:16.775527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:27:17.081337image/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
2024-02-10T09:27:17.412242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters14
Distinct categories3 ?
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 row월산동
2nd row4,611
3rd row8,898
4th row50
5th row5
ValueCountFrequency (%)
0 7
21.2%
23 2
 
6.1%
5 2
 
6.1%
6 1
 
3.0%
83 1
 
3.0%
8,971 1
 
3.0%
4,634 1
 
3.0%
2 1
 
3.0%
73 1
 
3.0%
10 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:27:18.233751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.7%
5 8
12.9%
3 8
12.9%
8 8
12.9%
2 6
9.7%
1 6
9.7%
4 4
 
6.5%
6 4
 
6.5%
7 4
 
6.5%
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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 14
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:18.637403image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row월산4동
2nd row4,799
3rd row8,502
4th row44
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 3
 
9.1%
1 2
 
6.1%
17 2
 
6.1%
41 2
 
6.1%
51 1
 
3.0%
8,503 1
 
3.0%
4,816 1
 
3.0%
2 1
 
3.0%
29 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:27:19.693639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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%
4 9
15.0%
5 8
13.3%
1 8
13.3%
2 8
13.3%
7 4
 
6.7%
9 4
 
6.7%
8 4
 
6.7%
6 3
 
5.0%
3 2
 
3.3%
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%
4 9
13.8%
5 8
12.3%
1 8
12.3%
2 8
12.3%
7 4
 
6.2%
, 4
 
6.2%
9 4
 
6.2%
8 4
 
6.2%
6 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.4%
4 9
13.8%
5 8
12.3%
1 8
12.3%
2 8
12.3%
7 4
 
6.2%
, 4
 
6.2%
9 4
 
6.2%
8 4
 
6.2%
6 3
 
4.6%
Other values (2) 3
 
4.6%
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
2024-02-10T09:27:20.282373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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 row월산5동
2nd row3,551
3rd row6,430
4th row21
5th row5
ValueCountFrequency (%)
0 7
21.2%
25 3
 
9.1%
1 2
 
6.1%
5 2
 
6.1%
74 1
 
3.0%
36 1
 
3.0%
21 1
 
3.0%
38 1
 
3.0%
6,416 1
 
3.0%
3,554 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:27:21.200558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 10
14.5%
0 9
13.0%
2 9
13.0%
1 9
13.0%
3 7
10.1%
4 6
8.7%
6 5
7.2%
, 4
 
5.8%
7 2
 
2.9%
9 2
 
2.9%
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 (%)
5 10
16.7%
0 9
15.0%
2 9
15.0%
1 9
15.0%
3 7
11.7%
4 6
10.0%
6 5
8.3%
7 2
 
3.3%
9 2
 
3.3%
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 (%)
5 10
15.2%
0 9
13.6%
2 9
13.6%
1 9
13.6%
3 7
10.6%
4 6
9.1%
6 5
7.6%
, 4
 
6.1%
7 2
 
3.0%
9 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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 10
15.2%
0 9
13.6%
2 9
13.6%
1 9
13.6%
3 7
10.6%
4 6
9.1%
6 5
7.6%
, 4
 
6.1%
7 2
 
3.0%
9 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:21.678873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row백운1동
2nd row5,190
3rd row12,237
4th row22
5th row13
ValueCountFrequency (%)
0 8
24.2%
13 2
 
6.1%
42 2
 
6.1%
22 2
 
6.1%
37 1
 
3.0%
59 1
 
3.0%
5,191 1
 
3.0%
18 1
 
3.0%
1 1
 
3.0%
14 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:27:22.599846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
21.3%
2 13
17.3%
0 9
12.0%
4 6
 
8.0%
5 6
 
8.0%
9 6
 
8.0%
3 5
 
6.7%
, 4
 
5.3%
7 3
 
4.0%
6 2
 
2.7%
Other values (5) 5
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
89.3%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
23.9%
2 13
19.4%
0 9
13.4%
4 6
 
9.0%
5 6
 
9.0%
9 6
 
9.0%
3 5
 
7.5%
7 3
 
4.5%
6 2
 
3.0%
8 1
 
1.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
22.2%
2 13
18.1%
0 9
12.5%
4 6
 
8.3%
5 6
 
8.3%
9 6
 
8.3%
3 5
 
6.9%
, 4
 
5.6%
7 3
 
4.2%
6 2
 
2.8%
Other values (2) 2
 
2.8%
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 16
22.2%
2 13
18.1%
0 9
12.5%
4 6
 
8.3%
5 6
 
8.3%
9 6
 
8.3%
3 5
 
6.9%
, 4
 
5.6%
7 3
 
4.2%
6 2
 
2.8%
Other values (2) 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:23.099134image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row백운2동
2nd row3,342
3rd row6,381
4th row28
5th row2
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
2 2
 
6.1%
57 1
 
3.0%
53 1
 
3.0%
6,375 1
 
3.0%
3,359 1
 
3.0%
6 1
 
3.0%
17 1
 
3.0%
40 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:27:24.048860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.9%
0 10
14.1%
2 9
12.7%
1 7
9.9%
5 6
8.5%
7 5
7.0%
, 4
 
5.6%
4 4
 
5.6%
6 3
 
4.2%
8 3
 
4.2%
Other values (5) 8
11.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
19.4%
0 10
16.1%
2 9
14.5%
1 7
11.3%
5 6
9.7%
7 5
8.1%
4 4
 
6.5%
6 3
 
4.8%
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%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
17.6%
0 10
14.7%
2 9
13.2%
1 7
10.3%
5 6
8.8%
7 5
7.4%
, 4
 
5.9%
4 4
 
5.9%
6 3
 
4.4%
8 3
 
4.4%
Other values (2) 5
7.4%
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 (%)
3 12
17.6%
0 10
14.7%
2 9
13.2%
1 7
10.3%
5 6
8.8%
7 5
7.4%
, 4
 
5.9%
4 4
 
5.9%
6 3
 
4.4%
8 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:24.410059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
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 row주월1동
2nd row9,635
3rd row21,923
4th row42
5th row14
ValueCountFrequency (%)
0 7
21.2%
14 2
 
6.1%
42 2
 
6.1%
156 2
 
6.1%
87 1
 
3.0%
21,923 1
 
3.0%
296 1
 
3.0%
9,639 1
 
3.0%
35 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:27:25.283773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.3%
0 10
12.2%
3 9
11.0%
2 8
9.8%
4 7
8.5%
5 6
 
7.3%
6 6
 
7.3%
9 6
 
7.3%
8 6
 
7.3%
, 4
 
4.9%
Other values (5) 5
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
90.2%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.3%
0 10
13.5%
3 9
12.2%
2 8
10.8%
4 7
9.5%
5 6
 
8.1%
6 6
 
8.1%
9 6
 
8.1%
8 6
 
8.1%
7 1
 
1.4%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.0%
0 10
12.7%
3 9
11.4%
2 8
10.1%
4 7
8.9%
5 6
 
7.6%
6 6
 
7.6%
9 6
 
7.6%
8 6
 
7.6%
, 4
 
5.1%
Other values (2) 2
 
2.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 79
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.0%
0 10
12.7%
3 9
11.4%
2 8
10.1%
4 7
8.9%
5 6
 
7.6%
6 6
 
7.6%
9 6
 
7.6%
8 6
 
7.6%
, 4
 
5.1%
Other values (2) 2
 
2.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:25.719038image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row주월2동
2nd row4,033
3rd row8,022
4th row31
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 2
 
6.1%
31 2
 
6.1%
24 2
 
6.1%
18 1
 
3.0%
8,022 1
 
3.0%
41 1
 
3.0%
4,057 1
 
3.0%
12 1
 
3.0%
9 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:27:26.536575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.8%
2 9
13.0%
4 9
13.0%
8 8
11.6%
3 8
11.6%
1 7
10.1%
7 5
 
7.2%
, 4
 
5.8%
1
 
1.4%
1
 
1.4%
Other values (4) 4
 
5.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.3%
2 9
14.8%
4 9
14.8%
8 8
13.1%
3 8
13.1%
1 7
11.5%
7 5
 
8.2%
9 1
 
1.6%
5 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
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%
2 9
13.6%
4 9
13.6%
8 8
12.1%
3 8
12.1%
1 7
10.6%
7 5
 
7.6%
, 4
 
6.1%
9 1
 
1.5%
- 1
 
1.5%
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%
2 9
13.6%
4 9
13.6%
8 8
12.1%
3 8
12.1%
1 7
10.6%
7 5
 
7.6%
, 4
 
6.1%
9 1
 
1.5%
- 1
 
1.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:26.889893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6666667
Min length1

Characters and Unicode

Total characters88
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row진월동
2nd row11,495
3rd row29,374
4th row59
5th row26
ValueCountFrequency (%)
0 6
 
18.2%
6 2
 
6.1%
26 2
 
6.1%
273 1
 
3.0%
206 1
 
3.0%
29,261 1
 
3.0%
11,486 1
 
3.0%
113 1
 
3.0%
9 1
 
3.0%
1 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:27:27.896468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.2%
2 14
15.9%
0 10
11.4%
6 9
10.2%
9 6
 
6.8%
3 6
 
6.8%
4 5
 
5.7%
7 5
 
5.7%
5 5
 
5.7%
, 4
 
4.5%
Other values (5) 8
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
88.6%
Other Punctuation 4
 
4.5%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.5%
2 14
17.9%
0 10
12.8%
6 9
11.5%
9 6
 
7.7%
3 6
 
7.7%
4 5
 
6.4%
7 5
 
6.4%
5 5
 
6.4%
8 2
 
2.6%
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 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
18.8%
2 14
16.5%
0 10
11.8%
6 9
10.6%
9 6
 
7.1%
3 6
 
7.1%
4 5
 
5.9%
7 5
 
5.9%
5 5
 
5.9%
, 4
 
4.7%
Other values (2) 5
 
5.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
18.8%
2 14
16.5%
0 10
11.8%
6 9
10.6%
9 6
 
7.1%
3 6
 
7.1%
4 5
 
5.9%
7 5
 
5.9%
5 5
 
5.9%
, 4
 
4.7%
Other values (2) 5
 
5.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:28.252386image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row효덕동
2nd row7,498
3rd row16,131
4th row2
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 2
 
6.1%
2 2
 
6.1%
123 2
 
6.1%
75 1
 
3.0%
16,131 1
 
3.0%
7,498 1
 
3.0%
7,479 1
 
3.0%
91 1
 
3.0%
19 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:27:28.942008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.6%
0 11
14.9%
9 7
9.5%
2 6
8.1%
6 6
8.1%
4 5
 
6.8%
8 5
 
6.8%
3 4
 
5.4%
5 4
 
5.4%
7 4
 
5.4%
Other values (5) 9
12.2%

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 (%)
1 13
20.0%
0 11
16.9%
9 7
10.8%
2 6
9.2%
6 6
9.2%
4 5
 
7.7%
8 5
 
7.7%
3 4
 
6.2%
5 4
 
6.2%
7 4
 
6.2%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.3%
0 11
15.5%
9 7
9.9%
2 6
8.5%
6 6
8.5%
4 5
 
7.0%
8 5
 
7.0%
3 4
 
5.6%
5 4
 
5.6%
7 4
 
5.6%
Other values (2) 6
8.5%
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 13
18.3%
0 11
15.5%
9 7
9.9%
2 6
8.5%
6 6
8.5%
4 5
 
7.0%
8 5
 
7.0%
3 4
 
5.6%
5 4
 
5.6%
7 4
 
5.6%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:27:29.364535image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row송암동
2nd row8,592
3rd row21,489
4th row18
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
18 2
 
6.1%
15 2
 
6.1%
185 1
 
3.0%
21,489 1
 
3.0%
301 1
 
3.0%
8,607 1
 
3.0%
39 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:27:30.158158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.2%
0 12
15.0%
5 8
10.0%
8 7
8.8%
7 5
 
6.2%
3 5
 
6.2%
2 5
 
6.2%
4 5
 
6.2%
9 5
 
6.2%
, 4
 
5.0%
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 17
23.6%
0 12
16.7%
5 8
11.1%
8 7
9.7%
7 5
 
6.9%
3 5
 
6.9%
2 5
 
6.9%
4 5
 
6.9%
9 5
 
6.9%
6 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 17
22.1%
0 12
15.6%
5 8
10.4%
8 7
9.1%
7 5
 
6.5%
3 5
 
6.5%
2 5
 
6.5%
4 5
 
6.5%
9 5
 
6.5%
, 4
 
5.2%
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 17
22.1%
0 12
15.6%
5 8
10.4%
8 7
9.1%
7 5
 
6.5%
3 5
 
6.5%
2 5
 
6.5%
4 5
 
6.5%
9 5
 
6.5%
, 4
 
5.2%
Other values (2) 4
 
5.2%
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
2024-02-10T09:27:30.555534image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row대촌동
2nd row3,288
3rd row6,295
4th row26
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 4
 
12.1%
25 2
 
6.1%
29 2
 
6.1%
3,288 1
 
3.0%
26 1
 
3.0%
12 1
 
3.0%
3,291 1
 
3.0%
2 1
 
3.0%
3 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:27:31.490452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
18.5%
3 8
12.3%
0 7
10.8%
1 7
10.8%
9 6
9.2%
8 5
7.7%
6 5
7.7%
5 4
 
6.2%
, 4
 
6.2%
7 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 (%)
2 12
21.1%
3 8
14.0%
0 7
12.3%
1 7
12.3%
9 6
10.5%
8 5
8.8%
6 5
8.8%
5 4
 
7.0%
7 2
 
3.5%
4 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 (%)
2 12
19.4%
3 8
12.9%
0 7
11.3%
1 7
11.3%
9 6
9.7%
8 5
8.1%
6 5
8.1%
5 4
 
6.5%
, 4
 
6.5%
7 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 (%)
2 12
19.4%
3 8
12.9%
0 7
11.3%
1 7
11.3%
9 6
9.7%
8 5
8.1%
6 5
8.1%
5 4
 
6.5%
, 4
 
6.5%
7 2
 
3.2%
Other values (2) 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23
0<NA>행정기관 :<NA>광주광역시 남구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.03.04<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.02 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>95,8493,1642,9314,0786,6779,9982,967<NA>4,6114,7993,5515,1903,3429,6354,03311,4957,4988,5923,288
4<NA>전월말인구수<NA><NA><NA>215,7397,0036,6408,89113,46028,8485,215<NA>8,8988,5026,43012,2376,38121,9238,02229,37416,13121,4896,295
5<NA>전월말거주불명자수<NA><NA><NA>542211938462649<NA>504421222842315921826
6<NA>전월말재외국민등록자수<NA><NA><NA>150571011166<NA>55513214826971
7<NA>증 가 요 인전 입<NA>2,77959896915953653<NA>16092611251022967837215230175
8<NA><NA><NA>남자<NA>1,3283345398524027<NA>7140295647140341708315633
9<NA><NA><NA>여자<NA>1,4512644307429626<NA>8952326955156442026914542
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>6000002<NA>00000301000
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>0000000<NA>00000000000
28<NA>세대수증감<NA><NA><NA>105-4612129-18<NA>23173117424-9-19153
29<NA>인구수증감<NA><NA><NA>-285-4912-10-35107-58<NA>731-14-18-6-35-12-113-91-392
30<NA>거주불명자수증감<NA><NA><NA>-1100-1-11-1<NA>2-2-10-100-600-1
31<NA>금월말세대수<NA><NA><NA>95,9543,1602,9374,0906,67810,0272,949<NA>4,6344,8163,5545,1913,3599,6394,05711,4867,4798,6073,291
32<NA>금월말인구수<NA><NA><NA>215,4546,9546,6528,88113,42528,9555,157<NA>8,9718,5036,41612,2196,37521,8888,01029,26116,04021,4506,297
33<NA>금월말거주불명자수<NA><NA><NA>531211937452748<NA>524220222742315321825
34<NA>금월말재외국민등록자수<NA><NA><NA>150571011166<NA>55513214826971

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23# duplicates
0<NA>국외<NA><NA>0000000<NA>000000000002
1<NA>기타<NA><NA>0000000<NA>000000000002