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

Description2023-04-14
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 09:34:14.208874
Analysis finished2024-02-10 09:34:15.457382
Duration1.25 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
2024-02-10T09:34:15.747687image/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%
2024-02-10T09:34:16.817069image/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
2024-02-10T09:34:17.252452image/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%
2024-02-10T09:34:18.390732image/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
2024-02-10T09:34:18.789654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 남구
2nd row2023.03 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%
2023.03 1
7.1%
현재 1
7.1%
2024-02-10T09:34:19.689524image/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%
3 2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (9) 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 (%)
3 2
33.3%
2 2
33.3%
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 (%)
3
30.0%
3 2
20.0%
2 2
20.0%
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 (%)
3
30.0%
3 2
20.0%
2 2
20.0%
0 2
20.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:34:20.030012image/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%
2024-02-10T09:34:20.806212image/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
2024-02-10T09:34:21.199568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.3636364
Min length1

Characters and Unicode

Total characters111
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row합 계
2nd row95,795
3rd row211,907
4th row356
5th row152
ValueCountFrequency (%)
0 5
 
14.7%
6 2
 
5.9%
656 2
 
5.9%
904 1
 
2.9%
356 1
 
2.9%
152 1
 
2.9%
354 1
 
2.9%
211,563 1
 
2.9%
95,778 1
 
2.9%
2 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T09:34:22.170642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
14.4%
5 13
11.7%
0 11
9.9%
9 11
9.9%
, 10
9.0%
6 9
8.1%
2 9
8.1%
4 9
8.1%
7 6
 
5.4%
8 5
 
4.5%
Other values (5) 12
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 94
84.7%
Other Punctuation 10
 
9.0%
Dash Punctuation 3
 
2.7%
Space Separator 2
 
1.8%
Other Letter 2
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
17.0%
5 13
13.8%
0 11
11.7%
9 11
11.7%
6 9
9.6%
2 9
9.6%
4 9
9.6%
7 6
 
6.4%
8 5
 
5.3%
3 5
 
5.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
14.7%
5 13
11.9%
0 11
10.1%
9 11
10.1%
, 10
9.2%
6 9
8.3%
2 9
8.3%
4 9
8.3%
7 6
 
5.5%
8 5
 
4.6%
Other values (3) 10
9.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
14.7%
5 13
11.9%
0 11
10.1%
9 11
10.1%
, 10
9.2%
6 9
8.3%
2 9
8.3%
4 9
8.3%
7 6
 
5.5%
8 5
 
4.6%
Other values (3) 10
9.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:22.605669image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row양림동
2nd row3,110
3rd row6,733
4th row14
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 2
 
6.1%
29 2
 
6.1%
14 2
 
6.1%
20 1
 
3.0%
18 1
 
3.0%
6,725 1
 
3.0%
3,115 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:34:23.469345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
18.2%
0 11
16.7%
3 7
10.6%
2 6
9.1%
7 5
7.6%
5 5
7.6%
9 4
 
6.1%
6 4
 
6.1%
, 4
 
6.1%
4 2
 
3.0%
Other values (5) 6
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
87.9%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
20.7%
0 11
19.0%
3 7
12.1%
2 6
10.3%
7 5
8.6%
5 5
8.6%
9 4
 
6.9%
6 4
 
6.9%
4 2
 
3.4%
8 2
 
3.4%
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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
19.0%
0 11
17.5%
3 7
11.1%
2 6
9.5%
7 5
7.9%
5 5
7.9%
9 4
 
6.3%
6 4
 
6.3%
, 4
 
6.3%
4 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
19.0%
0 11
17.5%
3 7
11.1%
2 6
9.5%
7 5
7.9%
5 5
7.9%
9 4
 
6.3%
6 4
 
6.3%
, 4
 
6.3%
4 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:23.894399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row방림1동
2nd row3,009
3rd row6,651
4th row12
5th row7
ValueCountFrequency (%)
0 7
21.2%
26 2
 
6.1%
7 2
 
6.1%
6 1
 
3.0%
90 1
 
3.0%
6,677 1
 
3.0%
3,034 1
 
3.0%
1 1
 
3.0%
25 1
 
3.0%
4 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:34:25.049096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.0%
6 9
12.9%
1 8
11.4%
4 8
11.4%
3 6
8.6%
2 5
 
7.1%
5 5
 
7.1%
7 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (4) 4
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
88.6%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
22.6%
6 9
14.5%
1 8
12.9%
4 8
12.9%
3 6
9.7%
2 5
 
8.1%
5 5
 
8.1%
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%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.9%
6 9
13.4%
1 8
11.9%
4 8
11.9%
3 6
9.0%
2 5
 
7.5%
5 5
 
7.5%
7 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
20.9%
6 9
13.4%
1 8
11.9%
4 8
11.9%
3 6
9.0%
2 5
 
7.5%
5 5
 
7.5%
7 4
 
6.0%
, 4
 
6.0%
9 3
 
4.5%
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
2024-02-10T09:34:25.427172image/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 row3,975
3rd row8,473
4th row14
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
3 2
 
6.1%
35 2
 
6.1%
37 1
 
3.0%
14 1
 
3.0%
34 1
 
3.0%
8,438 1
 
3.0%
3,962 1
 
3.0%
13 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:34:26.631815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.3%
0 10
13.9%
1 8
11.1%
2 7
9.7%
5 6
8.3%
7 5
6.9%
9 5
6.9%
4 5
6.9%
8 4
 
5.6%
, 4
 
5.6%
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 (%)
3 11
17.5%
0 10
15.9%
1 8
12.7%
2 7
11.1%
5 6
9.5%
7 5
7.9%
9 5
7.9%
4 5
7.9%
8 4
 
6.3%
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 (%)
3 11
15.9%
0 10
14.5%
1 8
11.6%
2 7
10.1%
5 6
8.7%
7 5
7.2%
9 5
7.2%
4 5
7.2%
8 4
 
5.8%
, 4
 
5.8%
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 (%)
3 11
15.9%
0 10
14.5%
1 8
11.6%
2 7
10.1%
5 6
8.7%
7 5
7.2%
9 5
7.2%
4 5
7.2%
8 4
 
5.8%
, 4
 
5.8%
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
2024-02-10T09:34:27.048618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row봉선1동
2nd row6,500
3rd row12,939
4th row42
5th row10
ValueCountFrequency (%)
0 7
21.2%
12,939 2
 
6.1%
42 2
 
6.1%
10 2
 
6.1%
165 1
 
3.0%
83 1
 
3.0%
6,508 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:34:28.052104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.2%
1 9
13.6%
4 7
10.6%
8 7
10.6%
2 6
9.1%
9 6
9.1%
6 6
9.1%
3 5
7.6%
5 5
7.6%
7 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
1 9
12.9%
4 7
10.0%
8 7
10.0%
2 6
8.6%
9 6
8.6%
6 6
8.6%
3 5
7.1%
5 5
7.1%
, 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.1%
1 9
12.9%
4 7
10.0%
8 7
10.0%
2 6
8.6%
9 6
8.6%
6 6
8.6%
3 5
7.1%
5 5
7.1%
, 4
 
5.7%
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
2024-02-10T09:34:28.505735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6764706
Min length1

Characters and Unicode

Total characters91
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 row9,830
4th row28,066
5th row10
ValueCountFrequency (%)
0 6
 
17.1%
1 2
 
5.7%
10 2
 
5.7%
150 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
27,957 1
 
2.9%
9,811 1
 
2.9%
109 1
 
2.9%
19 1
 
2.9%
Other values (18) 18
51.4%
2024-02-10T09:34:29.403369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
22.0%
0 15
16.5%
2 8
 
8.8%
3 6
 
6.6%
7 6
 
6.6%
9 5
 
5.5%
8 5
 
5.5%
6 5
 
5.5%
, 4
 
4.4%
4 3
 
3.3%
Other values (11) 14
15.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
83.5%
Other Letter 7
 
7.7%
Other Punctuation 5
 
5.5%
Dash Punctuation 2
 
2.2%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
26.3%
0 15
19.7%
2 8
 
10.5%
3 6
 
7.9%
7 6
 
7.9%
9 5
 
6.6%
8 5
 
6.6%
6 5
 
6.6%
4 3
 
3.9%
5 3
 
3.9%
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 84
92.3%
Hangul 7
 
7.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
23.8%
0 15
17.9%
2 8
 
9.5%
3 6
 
7.1%
7 6
 
7.1%
9 5
 
6.0%
8 5
 
6.0%
6 5
 
6.0%
, 4
 
4.8%
4 3
 
3.6%
Other values (4) 7
 
8.3%
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 84
92.3%
Hangul 7
 
7.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
23.8%
0 15
17.9%
2 8
 
9.5%
3 6
 
7.1%
7 6
 
7.1%
9 5
 
6.0%
8 5
 
6.0%
6 5
 
6.0%
, 4
 
4.8%
4 3
 
3.6%
Other values (4) 7
 
8.3%
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 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:29.786830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row사직동
2nd row2,851
3rd row4,884
4th row41
5th row6
ValueCountFrequency (%)
0 7
21.2%
15 3
 
9.1%
20 2
 
6.1%
6 2
 
6.1%
35 1
 
3.0%
38 1
 
3.0%
4,848 1
 
3.0%
2,836 1
 
3.0%
2 1
 
3.0%
36 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:34:30.793357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 9
15.0%
1 8
13.3%
8 8
13.3%
5 6
10.0%
2 6
10.0%
4 6
10.0%
3 6
10.0%
6 4
6.7%
7 4
6.7%
9 3
 
5.0%
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 9
13.4%
1 8
11.9%
8 8
11.9%
5 6
9.0%
2 6
9.0%
4 6
9.0%
3 6
9.0%
6 4
6.0%
7 4
6.0%
, 4
6.0%
Other values (2) 6
9.0%
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 9
13.4%
1 8
11.9%
8 8
11.9%
5 6
9.0%
2 6
9.0%
4 6
9.0%
3 6
9.0%
6 4
6.0%
7 4
6.0%
, 4
6.0%
Other values (2) 6
9.0%
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
Minimum2023-04-11 00:00:00
Maximum2023-04-11 00:00:00
2024-02-10T09:34:31.142372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:34:31.532676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:31.923831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row월산동
2nd row4,541
3rd row8,773
4th row28
5th row7
ValueCountFrequency (%)
0 8
24.2%
28 2
 
6.1%
7 2
 
6.1%
17 1
 
3.0%
8,773 1
 
3.0%
39 1
 
3.0%
4,553 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
8 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:34:32.970350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 10
15.2%
3 9
13.6%
0 8
12.1%
8 8
12.1%
2 6
9.1%
4 6
9.1%
1 6
9.1%
, 4
 
6.1%
5 3
 
4.5%
9 2
 
3.0%
Other values (4) 4
 
6.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 10
16.9%
3 9
15.3%
0 8
13.6%
8 8
13.6%
2 6
10.2%
4 6
10.2%
1 6
10.2%
5 3
 
5.1%
9 2
 
3.4%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
7 10
15.9%
3 9
14.3%
0 8
12.7%
8 8
12.7%
2 6
9.5%
4 6
9.5%
1 6
9.5%
, 4
 
6.3%
5 3
 
4.8%
9 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
7 10
15.9%
3 9
14.3%
0 8
12.7%
8 8
12.7%
2 6
9.5%
4 6
9.5%
1 6
9.5%
, 4
 
6.3%
5 3
 
4.8%
9 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:33.304549image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row월산4동
2nd row4,769
3rd row8,295
4th row31
5th row5
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
30 2
 
6.1%
5 2
 
6.1%
51 1
 
3.0%
31 1
 
3.0%
53 1
 
3.0%
4,771 1
 
3.0%
13 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:34:34.260708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.9%
0 9
12.7%
5 8
11.3%
3 8
11.3%
4 7
9.9%
6 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
9 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 (%)
1 12
19.4%
0 9
14.5%
5 8
12.9%
3 8
12.9%
4 7
11.3%
6 4
 
6.5%
7 4
 
6.5%
2 4
 
6.5%
9 3
 
4.8%
8 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 (%)
1 12
17.6%
0 9
13.2%
5 8
11.8%
3 8
11.8%
4 7
10.3%
6 4
 
5.9%
7 4
 
5.9%
, 4
 
5.9%
2 4
 
5.9%
9 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 (%)
1 12
17.6%
0 9
13.2%
5 8
11.8%
3 8
11.8%
4 7
10.3%
6 4
 
5.9%
7 4
 
5.9%
, 4
 
5.9%
2 4
 
5.9%
9 3
 
4.4%
Other values (2) 5
7.4%
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
2024-02-10T09:34:34.720064image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row월산5동
2nd row3,501
3rd row6,176
4th row14
5th row4
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
13 2
 
6.1%
27 2
 
6.1%
14 2
 
6.1%
4 2
 
6.1%
7 1
 
3.0%
60 1
 
3.0%
18 1
 
3.0%
3,487 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:34:35.680177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 12
19.7%
0 10
16.4%
4 10
16.4%
3 8
13.1%
6 6
9.8%
7 5
8.2%
5 4
 
6.6%
2 3
 
4.9%
8 2
 
3.3%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.6%
0 10
14.7%
4 10
14.7%
3 8
11.8%
6 6
8.8%
7 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
2 3
 
4.4%
- 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.6%
0 10
14.7%
4 10
14.7%
3 8
11.8%
6 6
8.8%
7 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
2 3
 
4.4%
- 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:36.027467image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row백운1동
2nd row5,171
3rd row11,899
4th row13
5th row14
ValueCountFrequency (%)
0 7
21.2%
13 3
 
9.1%
14 2
 
6.1%
68 1
 
3.0%
11,899 1
 
3.0%
147 1
 
3.0%
5,162 1
 
3.0%
49 1
 
3.0%
9 1
 
3.0%
45 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:34:36.748789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
23.7%
0 10
13.2%
4 9
11.8%
5 9
11.8%
3 5
 
6.6%
9 5
 
6.6%
, 4
 
5.3%
8 4
 
5.3%
6 3
 
3.9%
7 3
 
3.9%
Other values (5) 6
 
7.9%

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 18
26.9%
0 10
14.9%
4 9
13.4%
5 9
13.4%
3 5
 
7.5%
9 5
 
7.5%
8 4
 
6.0%
6 3
 
4.5%
7 3
 
4.5%
2 1
 
1.5%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
24.7%
0 10
13.7%
4 9
12.3%
5 9
12.3%
3 5
 
6.8%
9 5
 
6.8%
, 4
 
5.5%
8 4
 
5.5%
6 3
 
4.1%
7 3
 
4.1%
Other values (2) 3
 
4.1%
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 18
24.7%
0 10
13.7%
4 9
12.3%
5 9
12.3%
3 5
 
6.8%
9 5
 
6.8%
, 4
 
5.5%
8 4
 
5.5%
6 3
 
4.1%
7 3
 
4.1%
Other values (2) 3
 
4.1%
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
2024-02-10T09:34:37.093034image/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 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 row3,304
3rd row6,253
4th row26
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
26 2
 
6.1%
77 2
 
6.1%
28 1
 
3.0%
6,253 1
 
3.0%
34 1
 
3.0%
3,334 1
 
3.0%
30 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:34:37.998147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 (%)
3 13
21.0%
0 10
16.1%
2 8
12.9%
7 7
11.3%
1 6
9.7%
4 6
9.7%
6 5
 
8.1%
9 3
 
4.8%
8 3
 
4.8%
5 1
 
1.6%
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 (%)
3 13
19.7%
0 10
15.2%
2 8
12.1%
7 7
10.6%
1 6
9.1%
4 6
9.1%
6 5
 
7.6%
, 4
 
6.1%
9 3
 
4.5%
8 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 (%)
3 13
19.7%
0 10
15.2%
2 8
12.1%
7 7
10.6%
1 6
9.1%
4 6
9.1%
6 5
 
7.6%
, 4
 
6.1%
9 3
 
4.5%
8 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:38.393886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row주월1동
2nd row9,599
3rd row21,429
4th row19
5th row13
ValueCountFrequency (%)
0 8
24.2%
13 3
 
9.1%
19 2
 
6.1%
96 2
 
6.1%
78 1
 
3.0%
275 1
 
3.0%
9,592 1
 
3.0%
31 1
 
3.0%
7 1
 
3.0%
14 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:34:39.265390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.5%
9 11
13.6%
0 10
12.3%
3 9
11.1%
2 6
 
7.4%
8 6
 
7.4%
5 5
 
6.2%
7 5
 
6.2%
, 4
 
4.9%
4 3
 
3.7%
Other values (5) 7
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.8%
9 11
15.3%
0 10
13.9%
3 9
12.5%
2 6
 
8.3%
8 6
 
8.3%
5 5
 
6.9%
7 5
 
6.9%
4 3
 
4.2%
6 2
 
2.8%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.2%
9 11
14.1%
0 10
12.8%
3 9
11.5%
2 6
 
7.7%
8 6
 
7.7%
5 5
 
6.4%
7 5
 
6.4%
, 4
 
5.1%
4 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.2%
9 11
14.1%
0 10
12.8%
3 9
11.5%
2 6
 
7.7%
8 6
 
7.7%
5 5
 
6.4%
7 5
 
6.4%
, 4
 
5.1%
4 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:39.782600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row주월2동
2nd row3,976
3rd row7,750
4th row28
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 3
 
9.1%
25 3
 
9.1%
36 2
 
6.1%
28 2
 
6.1%
21 1
 
3.0%
71 1
 
3.0%
3,971 1
 
3.0%
9 1
 
3.0%
6 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:34:40.901830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.2%
2 9
13.2%
5 9
13.2%
7 7
10.3%
3 6
8.8%
6 6
8.8%
1 5
7.4%
, 4
5.9%
9 4
5.9%
8 2
 
2.9%
Other values (5) 7
10.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.3%
2 9
15.3%
5 9
15.3%
7 7
11.9%
3 6
10.2%
6 6
10.2%
1 5
8.5%
9 4
6.8%
8 2
 
3.4%
4 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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
13.8%
2 9
13.8%
5 9
13.8%
7 7
10.8%
3 6
9.2%
6 6
9.2%
1 5
7.7%
, 4
6.2%
9 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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
13.8%
2 9
13.8%
5 9
13.8%
7 7
10.8%
3 6
9.2%
6 6
9.2%
1 5
7.7%
, 4
6.2%
9 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: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:41.320913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5757576
Min length1

Characters and Unicode

Total characters85
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 row진월동
2nd row11,398
3rd row28,452
4th row36
5th row26
ValueCountFrequency (%)
0 7
21.2%
26 2
 
6.1%
125 1
 
3.0%
28,377 1
 
3.0%
11,392 1
 
3.0%
1 1
 
3.0%
75 1
 
3.0%
6 1
 
3.0%
12 1
 
3.0%
137 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:34:42.296896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.8%
2 12
14.1%
0 9
10.6%
3 9
10.6%
5 7
8.2%
7 6
 
7.1%
6 5
 
5.9%
9 5
 
5.9%
8 5
 
5.9%
, 4
 
4.7%
Other values (5) 7
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
88.2%
Other Punctuation 4
 
4.7%
Dash Punctuation 3
 
3.5%
Other Letter 3
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.3%
2 12
16.0%
0 9
12.0%
3 9
12.0%
5 7
9.3%
7 6
 
8.0%
6 5
 
6.7%
9 5
 
6.7%
8 5
 
6.7%
4 1
 
1.3%
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 82
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.5%
2 12
14.6%
0 9
11.0%
3 9
11.0%
5 7
8.5%
7 6
 
7.3%
6 5
 
6.1%
9 5
 
6.1%
8 5
 
6.1%
, 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.5%
2 12
14.6%
0 9
11.0%
3 9
11.0%
5 7
8.5%
7 6
 
7.3%
6 5
 
6.1%
9 5
 
6.1%
8 5
 
6.1%
, 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:42.804364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row효덕동
2nd row7,528
3rd row15,738
4th row10
5th row8
ValueCountFrequency (%)
0 8
24.2%
10 2
 
6.1%
67 2
 
6.1%
8 2
 
6.1%
38 1
 
3.0%
15,738 1
 
3.0%
85 1
 
3.0%
7,508 1
 
3.0%
20 1
 
3.0%
11 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:34:43.698604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.3%
1 11
14.7%
8 9
12.0%
5 9
12.0%
7 7
9.3%
3 4
 
5.3%
6 4
 
5.3%
4 4
 
5.3%
2 4
 
5.3%
, 4
 
5.3%
Other values (5) 6
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.7%
1 11
16.7%
8 9
13.6%
5 9
13.6%
7 7
10.6%
3 4
 
6.1%
6 4
 
6.1%
4 4
 
6.1%
2 4
 
6.1%
9 1
 
1.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.1%
1 11
15.3%
8 9
12.5%
5 9
12.5%
7 7
9.7%
3 4
 
5.6%
6 4
 
5.6%
4 4
 
5.6%
2 4
 
5.6%
, 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.1%
1 11
15.3%
8 9
12.5%
5 9
12.5%
7 7
9.7%
3 4
 
5.6%
6 4
 
5.6%
4 4
 
5.6%
2 4
 
5.6%
, 4
 
5.6%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:44.263132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
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 row송암동
2nd row8,617
3rd row21,211
4th row13
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
13 2
 
6.1%
10 1
 
3.0%
114 1
 
3.0%
21,227 1
 
3.0%
8,630 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
4 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:34:45.195451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
23.1%
0 11
14.1%
2 11
14.1%
3 6
 
7.7%
7 6
 
7.7%
4 6
 
7.7%
8 6
 
7.7%
, 4
 
5.1%
6 3
 
3.8%
5 2
 
2.6%
Other values (5) 5
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
89.7%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
25.7%
0 11
15.7%
2 11
15.7%
3 6
 
8.6%
7 6
 
8.6%
4 6
 
8.6%
8 6
 
8.6%
6 3
 
4.3%
5 2
 
2.9%
9 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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
24.0%
0 11
14.7%
2 11
14.7%
3 6
 
8.0%
7 6
 
8.0%
4 6
 
8.0%
8 6
 
8.0%
, 4
 
5.3%
6 3
 
4.0%
5 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
96.2%
Hangul 3
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
24.0%
0 11
14.7%
2 11
14.7%
3 6
 
8.0%
7 6
 
8.0%
4 6
 
8.0%
8 6
 
8.0%
, 4
 
5.3%
6 3
 
4.0%
5 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:45.611206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
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 row대촌동
2nd row4,116
3rd row8,185
4th row5
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 3
 
9.1%
33 3
 
9.1%
5 2
 
6.1%
12 2
 
6.1%
24 1
 
3.0%
2 1
 
3.0%
4,112 1
 
3.0%
9 1
 
3.0%
6 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:34:46.653521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 9
14.1%
4 9
14.1%
1 9
14.1%
0 7
10.9%
2 6
9.4%
9 4
6.2%
, 4
6.2%
6 4
6.2%
8 4
6.2%
5 3
 
4.7%
Other values (5) 5
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
87.5%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.7%
Dash Punctuation 1
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 9
16.1%
4 9
16.1%
1 9
16.1%
0 7
12.5%
2 6
10.7%
9 4
7.1%
6 4
7.1%
8 4
7.1%
5 3
 
5.4%
7 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 61
95.3%
Hangul 3
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
3 9
14.8%
4 9
14.8%
1 9
14.8%
0 7
11.5%
2 6
9.8%
9 4
6.6%
, 4
6.6%
6 4
6.6%
8 4
6.6%
5 3
 
4.9%
Other values (2) 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 9
14.8%
4 9
14.8%
1 9
14.8%
0 7
11.5%
2 6
9.8%
9 4
6.6%
, 4
6.6%
6 4
6.6%
8 4
6.6%
5 3
 
4.9%
Other values (2) 2
 
3.3%
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>2023.04.11<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.03 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>95,7953,1103,0093,9756,5009,8302,851<NA>4,5414,7693,5015,1713,3049,5993,97611,3987,5288,6174,116
4<NA>전월말인구수<NA><NA><NA>211,9076,7336,6518,47312,93928,0664,884<NA>8,7738,2956,17611,8996,25321,4297,75028,45215,73821,2118,185
5<NA>전월말거주불명자수<NA><NA><NA>356141214421041<NA>283114132619283610135
6<NA>전월말재외국민등록자수<NA><NA><NA>152771010166<NA>75414313526874
7<NA>증 가 요 인전 입<NA>2,190601145917622047<NA>83105601061722456522913124474
8<NA><NA><NA>남자<NA>1,0923154248910329<NA>4756335591115361235611931
9<NA><NA><NA>여자<NA>1,0982960358711718<NA>3649275181130291067512543
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>6000410<NA>00001000000
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>0000000<NA>00000000000
28<NA>세대수증감<NA><NA><NA>-17525-138-19-15<NA>122-14-930-7-5-6-2013-4
29<NA>인구수증감<NA><NA><NA>-344-826-350-109-36<NA>1-13-41-4977-31-9-75-67169
30<NA>거주불명자수증감<NA><NA><NA>-21-1310-2<NA>0-1-10000-10-10
31<NA>금월말세대수<NA><NA><NA>95,7783,1153,0343,9626,5089,8112,836<NA>4,5534,7713,4875,1623,3349,5923,97111,3927,5088,6304,112
32<NA>금월말인구수<NA><NA><NA>211,5636,7256,6778,43812,93927,9574,848<NA>8,7748,2826,13511,8506,33021,3987,74128,37715,67121,2278,194
33<NA>금월말거주불명자수<NA><NA><NA>354151117431039<NA>283013132619283510125
34<NA>금월말재외국민등록자수<NA><NA><NA>151771010156<NA>75414313526874

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