Overview

Dataset statistics

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

Variable types

Unsupported1
Text22
DateTime1

Dataset

Description2023-02-23
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201925

Alerts

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

Reproduction

Analysis started2024-02-10 09:33:03.696910
Analysis finished2024-02-10 09:33:04.972844
Duration1.28 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:33:05.188325image/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%
2024-02-10T09:33:06.122140image/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
2024-02-10T09:33:06.595293image/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%
2024-02-10T09:33:07.495634image/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
2024-02-10T09:33:07.970272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 남구
2nd row2023.01 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%
2023.01 1
7.1%
현재 1
7.1%
2024-02-10T09:33:08.753149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (10) 12
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
75.6%
Decimal Number 6
 
14.6%
Space Separator 3
 
7.3%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
3
9.7%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (4) 4
12.9%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 2
33.3%
1 1
16.7%
3 1
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:33:09.088690image/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%
2024-02-10T09:33:09.890712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:10.421433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.3333333
Min length1

Characters and Unicode

Total characters110
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

Unique25 ?
Unique (%)75.8%

Sample

1st row합 계
2nd row95,868
3rd row212,379
4th row350
5th row150
ValueCountFrequency (%)
0 4
 
11.8%
5 2
 
5.9%
582 2
 
5.9%
778 1
 
2.9%
350 1
 
2.9%
1,064 1
 
2.9%
364 1
 
2.9%
212,028 1
 
2.9%
95,741 1
 
2.9%
14 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:33:11.249728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
14.5%
5 13
11.8%
0 11
10.0%
9 11
10.0%
2 10
9.1%
, 9
8.2%
8 8
7.3%
3 8
7.3%
6 7
6.4%
7 6
 
5.5%
Other values (5) 11
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 95
86.4%
Other Punctuation 9
 
8.2%
Space Separator 2
 
1.8%
Dash Punctuation 2
 
1.8%
Other Letter 2
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
16.8%
5 13
13.7%
0 11
11.6%
9 11
11.6%
2 10
10.5%
8 8
8.4%
3 8
8.4%
6 7
7.4%
7 6
 
6.3%
4 5
 
5.3%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 9
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 108
98.2%
Hangul 2
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
14.8%
5 13
12.0%
0 11
10.2%
9 11
10.2%
2 10
9.3%
, 9
8.3%
8 8
7.4%
3 8
7.4%
6 7
6.5%
7 6
 
5.6%
Other values (3) 9
8.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108
98.2%
Hangul 2
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
14.8%
5 13
12.0%
0 11
10.2%
9 11
10.2%
2 10
9.3%
, 9
8.3%
8 8
7.4%
3 8
7.4%
6 7
6.5%
7 6
 
5.6%
Other values (3) 9
8.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:11.660334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row양림동
2nd row3,116
3rd row6,777
4th row11
5th row5
ValueCountFrequency (%)
0 6
 
18.2%
14 2
 
6.1%
3 2
 
6.1%
35 1
 
3.0%
36 1
 
3.0%
6,750 1
 
3.0%
3,119 1
 
3.0%
27 1
 
3.0%
1 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:33:12.498330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
20.6%
0 10
14.7%
3 10
14.7%
7 7
10.3%
2 7
10.3%
6 5
 
7.4%
, 4
 
5.9%
5 4
 
5.9%
4 2
 
2.9%
1
 
1.5%
Other values (4) 4
 
5.9%

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 (%)
1 14
23.3%
0 10
16.7%
3 10
16.7%
7 7
11.7%
2 7
11.7%
6 5
 
8.3%
5 4
 
6.7%
4 2
 
3.3%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
21.5%
0 10
15.4%
3 10
15.4%
7 7
10.8%
2 7
10.8%
6 5
 
7.7%
, 4
 
6.2%
5 4
 
6.2%
4 2
 
3.1%
- 1
 
1.5%
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 (%)
1 14
21.5%
0 10
15.4%
3 10
15.4%
7 7
10.8%
2 7
10.8%
6 5
 
7.7%
, 4
 
6.2%
5 4
 
6.2%
4 2
 
3.1%
- 1
 
1.5%
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
2024-02-10T09:33:12.880651image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row방림1동
2nd row2,957
3rd row6,564
4th row11
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
11 2
 
6.1%
3 1
 
3.0%
56 1
 
3.0%
2,988 1
 
3.0%
53 1
 
3.0%
31 1
 
3.0%
2 1
 
3.0%
17 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:33:13.686347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
18.8%
0 10
14.5%
7 8
11.6%
5 7
10.1%
6 7
10.1%
2 6
8.7%
, 4
 
5.8%
3 4
 
5.8%
9 3
 
4.3%
4 2
 
2.9%
Other values (4) 5
 
7.2%

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 (%)
1 13
21.0%
0 10
16.1%
7 8
12.9%
5 7
11.3%
6 7
11.3%
2 6
9.7%
3 4
 
6.5%
9 3
 
4.8%
4 2
 
3.2%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
19.7%
0 10
15.2%
7 8
12.1%
5 7
10.6%
6 7
10.6%
2 6
9.1%
, 4
 
6.1%
3 4
 
6.1%
9 3
 
4.5%
4 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
19.7%
0 10
15.2%
7 8
12.1%
5 7
10.6%
6 7
10.6%
2 6
9.1%
, 4
 
6.1%
3 4
 
6.1%
9 3
 
4.5%
4 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:14.086995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row방림2동
2nd row3,982
3rd row8,492
4th row16
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
15 2
 
6.1%
19 2
 
6.1%
22 2
 
6.1%
21 2
 
6.1%
11 1
 
3.0%
56 1
 
3.0%
30 1
 
3.0%
3,972 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:33:14.927768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.2%
2 13
17.8%
0 11
15.1%
9 5
 
6.8%
3 5
 
6.8%
5 4
 
5.5%
8 4
 
5.5%
, 4
 
5.5%
6 3
 
4.1%
- 3
 
4.1%
Other values (5) 7
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
86.3%
Other Punctuation 4
 
5.5%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
22.2%
2 13
20.6%
0 11
17.5%
9 5
 
7.9%
3 5
 
7.9%
5 4
 
6.3%
8 4
 
6.3%
6 3
 
4.8%
4 2
 
3.2%
7 2
 
3.2%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
20.0%
2 13
18.6%
0 11
15.7%
9 5
 
7.1%
3 5
 
7.1%
5 4
 
5.7%
8 4
 
5.7%
, 4
 
5.7%
6 3
 
4.3%
- 3
 
4.3%
Other values (2) 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 (%)
1 14
20.0%
2 13
18.6%
0 11
15.7%
9 5
 
7.1%
3 5
 
7.1%
5 4
 
5.7%
8 4
 
5.7%
, 4
 
5.7%
6 3
 
4.3%
- 3
 
4.3%
Other values (2) 4
 
5.7%
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
2024-02-10T09:33:15.254616image/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 row6,485
3rd row12,900
4th row49
5th row10
ValueCountFrequency (%)
0 7
21.2%
68 2
 
6.1%
4 2
 
6.1%
45 2
 
6.1%
99 1
 
3.0%
167 1
 
3.0%
12,866 1
 
3.0%
6,474 1
 
3.0%
34 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:33:16.065953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13
17.1%
0 10
13.2%
6 9
11.8%
1 8
10.5%
8 6
7.9%
9 5
 
6.6%
7 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
5 3
 
3.9%
Other values (5) 9
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
86.8%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 13
19.7%
0 10
15.2%
6 9
13.6%
1 8
12.1%
8 6
9.1%
9 5
 
7.6%
7 5
 
7.6%
3 4
 
6.1%
5 3
 
4.5%
2 3
 
4.5%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
4 13
17.8%
0 10
13.7%
6 9
12.3%
1 8
11.0%
8 6
8.2%
9 5
 
6.8%
7 5
 
6.8%
, 4
 
5.5%
3 4
 
5.5%
5 3
 
4.1%
Other values (2) 6
8.2%
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 (%)
4 13
17.8%
0 10
13.7%
6 9
12.3%
1 8
11.0%
8 6
8.2%
9 5
 
6.8%
7 5
 
6.8%
, 4
 
5.5%
3 4
 
5.5%
5 3
 
4.1%
Other values (2) 6
8.2%
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
2024-02-10T09:33:16.548451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6470588
Min length1

Characters and Unicode

Total characters90
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

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row봉선2동
3rd row9,837
4th row28,183
5th row10
ValueCountFrequency (%)
0 6
 
17.1%
16 2
 
5.7%
1 2
 
5.7%
10 2
 
5.7%
출력일자 1
 
2.9%
9,823 1
 
2.9%
85 1
 
2.9%
14 1
 
2.9%
15 1
 
2.9%
152 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T09:33:17.722630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
17.8%
0 12
13.3%
2 12
13.3%
8 9
10.0%
3 7
7.8%
, 4
 
4.4%
9 4
 
4.4%
6 4
 
4.4%
7 4
 
4.4%
5 4
 
4.4%
Other values (11) 14
15.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
83.3%
Other Letter 7
 
7.8%
Other Punctuation 5
 
5.6%
Dash Punctuation 2
 
2.2%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.3%
0 12
16.0%
2 12
16.0%
8 9
12.0%
3 7
9.3%
9 4
 
5.3%
6 4
 
5.3%
7 4
 
5.3%
5 4
 
5.3%
4 3
 
4.0%
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 83
92.2%
Hangul 7
 
7.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.3%
0 12
14.5%
2 12
14.5%
8 9
10.8%
3 7
8.4%
, 4
 
4.8%
9 4
 
4.8%
6 4
 
4.8%
7 4
 
4.8%
5 4
 
4.8%
Other values (4) 7
8.4%
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 83
92.2%
Hangul 7
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.3%
0 12
14.5%
2 12
14.5%
8 9
10.8%
3 7
8.4%
, 4
 
4.8%
9 4
 
4.8%
6 4
 
4.8%
7 4
 
4.8%
5 4
 
4.8%
Other values (4) 7
8.4%
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 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:18.124457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row사직동
2nd row2,864
3rd row4,928
4th row43
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
43 2
 
6.1%
1 1
 
3.0%
74 1
 
3.0%
2,849 1
 
3.0%
30 1
 
3.0%
15 1
 
3.0%
3 1
 
3.0%
21 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:33:19.391026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
15.9%
0 9
13.0%
2 9
13.0%
1 7
10.1%
3 6
8.7%
8 6
8.7%
6 5
7.2%
, 4
 
5.8%
9 4
 
5.8%
7 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 (%)
4 11
18.3%
0 9
15.0%
2 9
15.0%
1 7
11.7%
3 6
10.0%
8 6
10.0%
6 5
8.3%
9 4
 
6.7%
7 2
 
3.3%
5 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
16.7%
0 9
13.6%
2 9
13.6%
1 7
10.6%
3 6
9.1%
8 6
9.1%
6 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
7 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 (%)
4 11
16.7%
0 9
13.6%
2 9
13.6%
1 7
10.6%
3 6
9.1%
8 6
9.1%
6 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
7 2
 
3.0%
Other values (2) 3
 
4.5%
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
Minimum2023-02-09 00:00:00
Maximum2023-02-09 00:00:00
2024-02-10T09:33:19.796021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:33:20.067751image/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
2024-02-10T09:33:20.536306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row월산동
2nd row4,561
3rd row8,818
4th row30
5th row7
ValueCountFrequency (%)
0 7
21.2%
37 2
 
6.1%
7 2
 
6.1%
8 1
 
3.0%
45 1
 
3.0%
8,795 1
 
3.0%
4,552 1
 
3.0%
1 1
 
3.0%
23 1
 
3.0%
9 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:33:21.524198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
13.6%
8 7
11.9%
4 7
11.9%
2 7
11.9%
7 6
10.2%
3 6
10.2%
9 5
8.5%
5 5
8.5%
1 5
8.5%
6 3
 
5.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
12.1%
8 7
10.6%
4 7
10.6%
2 7
10.6%
7 6
9.1%
3 6
9.1%
9 5
7.6%
5 5
7.6%
1 5
7.6%
, 4
6.1%
Other values (2) 6
9.1%
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 8
12.1%
8 7
10.6%
4 7
10.6%
2 7
10.6%
7 6
9.1%
3 6
9.1%
9 5
7.6%
5 5
7.6%
1 5
7.6%
, 4
6.1%
Other values (2) 6
9.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:21.992829image/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 row4,798
3rd row8,362
4th row31
5th row5
ValueCountFrequency (%)
0 8
24.2%
31 3
 
9.1%
5 2
 
6.1%
30 1
 
3.0%
8,362 1
 
3.0%
62 1
 
3.0%
4,786 1
 
3.0%
12 1
 
3.0%
7 1
 
3.0%
34 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:33:22.922007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.5%
1 10
14.1%
4 10
14.1%
3 9
12.7%
8 5
7.0%
2 5
7.0%
7 4
 
5.6%
6 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
Other values (5) 6
8.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.7%
1 10
16.1%
4 10
16.1%
3 9
14.5%
8 5
8.1%
2 5
8.1%
7 4
 
6.5%
6 4
 
6.5%
5 3
 
4.8%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.2%
1 10
14.7%
4 10
14.7%
3 9
13.2%
8 5
7.4%
2 5
7.4%
7 4
 
5.9%
6 4
 
5.9%
, 4
 
5.9%
5 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 (%)
0 11
16.2%
1 10
14.7%
4 10
14.7%
3 9
13.2%
8 5
7.4%
2 5
7.4%
7 4
 
5.9%
6 4
 
5.9%
, 4
 
5.9%
5 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:23.377510image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row월산5동
2nd row3,506
3rd row6,205
4th row17
5th row4
ValueCountFrequency (%)
0 8
24.2%
3,506 2
 
6.1%
4 2
 
6.1%
36 2
 
6.1%
31 1
 
3.0%
17 1
 
3.0%
37 1
 
3.0%
6,191 1
 
3.0%
1 1
 
3.0%
14 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:33:24.273462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.4%
1 9
13.0%
6 8
11.6%
3 7
10.1%
2 6
8.7%
5 5
7.2%
4 5
7.2%
, 4
 
5.8%
7 4
 
5.8%
8 2
 
2.9%
Other values (5) 7
10.1%

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 12
20.0%
1 9
15.0%
6 8
13.3%
3 7
11.7%
2 6
10.0%
5 5
8.3%
4 5
8.3%
7 4
 
6.7%
8 2
 
3.3%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.2%
1 9
13.6%
6 8
12.1%
3 7
10.6%
2 6
9.1%
5 5
7.6%
4 5
7.6%
, 4
 
6.1%
7 4
 
6.1%
8 2
 
3.0%
Other values (2) 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 12
18.2%
1 9
13.6%
6 8
12.1%
3 7
10.6%
2 6
9.1%
5 5
7.6%
4 5
7.6%
, 4
 
6.1%
7 4
 
6.1%
8 2
 
3.0%
Other values (2) 4
 
6.1%
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
2024-02-10T09:33:24.666662image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row백운1동
2nd row5,177
3rd row11,919
4th row12
5th row14
ValueCountFrequency (%)
0 6
18.2%
14 3
 
9.1%
1 2
 
6.1%
36 2
 
6.1%
2 1
 
3.0%
39 1
 
3.0%
11,889 1
 
3.0%
5,167 1
 
3.0%
30 1
 
3.0%
10 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:33:25.550591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
23.0%
0 8
10.8%
3 6
 
8.1%
9 6
 
8.1%
4 5
 
6.8%
6 5
 
6.8%
7 5
 
6.8%
2 5
 
6.8%
8 4
 
5.4%
5 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 17
26.2%
0 8
12.3%
3 6
 
9.2%
9 6
 
9.2%
4 5
 
7.7%
6 5
 
7.7%
7 5
 
7.7%
2 5
 
7.7%
8 4
 
6.2%
5 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 17
23.9%
0 8
11.3%
3 6
 
8.5%
9 6
 
8.5%
4 5
 
7.0%
6 5
 
7.0%
7 5
 
7.0%
2 5
 
7.0%
8 4
 
5.6%
5 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 17
23.9%
0 8
11.3%
3 6
 
8.5%
9 6
 
8.5%
4 5
 
7.0%
6 5
 
7.0%
7 5
 
7.0%
2 5
 
7.0%
8 4
 
5.6%
5 4
 
5.6%
Other values (2) 6
 
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:25.967956image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row백운2동
2nd row3,274
3rd row6,210
4th row21
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 2
 
6.1%
8 2
 
6.1%
3,274 2
 
6.1%
36 1
 
3.0%
6,210 1
 
3.0%
55 1
 
3.0%
6,202 1
 
3.0%
5 1
 
3.0%
38 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:33:26.920155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.4%
3 9
13.0%
2 9
13.0%
1 7
10.1%
5 6
8.7%
7 5
7.2%
4 5
7.2%
6 5
7.2%
, 4
 
5.8%
8 3
 
4.3%
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 12
19.7%
3 9
14.8%
2 9
14.8%
1 7
11.5%
5 6
9.8%
7 5
8.2%
4 5
8.2%
6 5
8.2%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.2%
3 9
13.6%
2 9
13.6%
1 7
10.6%
5 6
9.1%
7 5
7.6%
4 5
7.6%
6 5
7.6%
, 4
 
6.1%
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 (%)
0 12
18.2%
3 9
13.6%
2 9
13.6%
1 7
10.6%
5 6
9.1%
7 5
7.6%
4 5
7.6%
6 5
7.6%
, 4
 
6.1%
8 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:27.420364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row주월1동
2nd row9,599
3rd row21,462
4th row19
5th row13
ValueCountFrequency (%)
0 8
24.2%
13 4
 
12.1%
9,599 2
 
6.1%
19 2
 
6.1%
82 2
 
6.1%
112 1
 
3.0%
1 1
 
3.0%
11 1
 
3.0%
79 1
 
3.0%
51 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:33:28.203430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
25.6%
2 11
14.1%
0 10
12.8%
9 10
12.8%
3 7
 
9.0%
, 4
 
5.1%
7 4
 
5.1%
5 3
 
3.8%
8 2
 
2.6%
6 2
 
2.6%
Other values (4) 5
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
91.0%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
28.2%
2 11
15.5%
0 10
14.1%
9 10
14.1%
3 7
 
9.9%
7 4
 
5.6%
5 3
 
4.2%
8 2
 
2.8%
6 2
 
2.8%
4 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
26.7%
2 11
14.7%
0 10
13.3%
9 10
13.3%
3 7
 
9.3%
, 4
 
5.3%
7 4
 
5.3%
5 3
 
4.0%
8 2
 
2.7%
6 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 20
26.7%
2 11
14.7%
0 10
13.3%
9 10
13.3%
3 7
 
9.3%
, 4
 
5.3%
7 4
 
5.3%
5 3
 
4.0%
8 2
 
2.7%
6 2
 
2.7%
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
2024-02-10T09:33:28.610792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row주월2동
2nd row4,011
3rd row7,807
4th row29
5th row6
ValueCountFrequency (%)
0 6
18.2%
6 3
 
9.1%
31 3
 
9.1%
2 2
 
6.1%
22 2
 
6.1%
52 1
 
3.0%
29 1
 
3.0%
79 1
 
3.0%
3,989 1
 
3.0%
32 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:33:29.643842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
18.6%
1 11
15.7%
0 9
12.9%
7 7
10.0%
3 5
 
7.1%
9 5
 
7.1%
6 4
 
5.7%
, 4
 
5.7%
8 3
 
4.3%
5 3
 
4.3%
Other values (5) 6
8.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
87.1%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
21.3%
1 11
18.0%
0 9
14.8%
7 7
11.5%
3 5
 
8.2%
9 5
 
8.2%
6 4
 
6.6%
8 3
 
4.9%
5 3
 
4.9%
4 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
19.4%
1 11
16.4%
0 9
13.4%
7 7
10.4%
3 5
 
7.5%
9 5
 
7.5%
6 4
 
6.0%
, 4
 
6.0%
8 3
 
4.5%
5 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
19.4%
1 11
16.4%
0 9
13.4%
7 7
10.4%
3 5
 
7.5%
9 5
 
7.5%
6 4
 
6.0%
, 4
 
6.0%
8 3
 
4.5%
5 3
 
4.5%
Other values (2) 3
 
4.5%
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
2024-02-10T09:33:30.031213image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row진월동
2nd row11,416
3rd row28,578
4th row34
5th row24
ValueCountFrequency (%)
0 7
21.2%
155 1
 
3.0%
132 1
 
3.0%
33 1
 
3.0%
28,504 1
 
3.0%
11,390 1
 
3.0%
1 1
 
3.0%
74 1
 
3.0%
26 1
 
3.0%
13 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:33:30.942151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.2%
0 11
12.9%
2 10
11.8%
8 9
10.6%
4 6
 
7.1%
3 6
 
7.1%
5 5
 
5.9%
7 5
 
5.9%
, 4
 
4.7%
6 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 18
24.0%
0 11
14.7%
2 10
13.3%
8 9
12.0%
4 6
 
8.0%
3 6
 
8.0%
5 5
 
6.7%
7 5
 
6.7%
6 4
 
5.3%
9 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 18
22.0%
0 11
13.4%
2 10
12.2%
8 9
11.0%
4 6
 
7.3%
3 6
 
7.3%
5 5
 
6.1%
7 5
 
6.1%
, 4
 
4.9%
6 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 18
22.0%
0 11
13.4%
2 10
12.2%
8 9
11.0%
4 6
 
7.3%
3 6
 
7.3%
5 5
 
6.1%
7 5
 
6.1%
, 4
 
4.9%
6 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
2024-02-10T09:33:31.304869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row효덕동
2nd row7,559
3rd row15,834
4th row2
5th row8
ValueCountFrequency (%)
0 6
18.2%
8 3
 
9.1%
69 2
 
6.1%
10 2
 
6.1%
6 1
 
3.0%
72 1
 
3.0%
7,535 1
 
3.0%
37 1
 
3.0%
24 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:33:32.448189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.7%
7 8
11.0%
9 7
9.6%
1 7
9.6%
5 7
9.6%
8 6
8.2%
3 6
8.2%
6 5
6.8%
2 5
6.8%
, 4
 
5.5%
Other values (5) 8
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
87.7%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.6%
7 8
12.5%
9 7
10.9%
1 7
10.9%
5 7
10.9%
8 6
9.4%
3 6
9.4%
6 5
7.8%
2 5
7.8%
4 3
 
4.7%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.3%
7 8
11.4%
9 7
10.0%
1 7
10.0%
5 7
10.0%
8 6
8.6%
3 6
8.6%
6 5
7.1%
2 5
7.1%
, 4
 
5.7%
Other values (2) 5
7.1%
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 10
14.3%
7 8
11.4%
9 7
10.0%
1 7
10.0%
5 7
10.0%
8 6
8.6%
3 6
8.6%
6 5
7.1%
2 5
7.1%
, 4
 
5.7%
Other values (2) 5
7.1%
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
2024-02-10T09:33:32.840989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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 row송암동
2nd row8,593
3rd row21,170
4th row10
5th row8
ValueCountFrequency (%)
0 7
21.2%
115 2
 
6.1%
13 2
 
6.1%
송암동 1
 
3.0%
230 1
 
3.0%
21,183 1
 
3.0%
8,592 1
 
3.0%
3 1
 
3.0%
1 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:33:33.903533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
22.1%
0 13
16.9%
2 8
10.4%
3 7
9.1%
5 7
9.1%
8 6
 
7.8%
7 5
 
6.5%
, 4
 
5.2%
6 4
 
5.2%
9 2
 
2.6%
Other values (4) 4
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
89.6%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
24.6%
0 13
18.8%
2 8
11.6%
3 7
10.1%
5 7
10.1%
8 6
 
8.7%
7 5
 
7.2%
6 4
 
5.8%
9 2
 
2.9%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
23.0%
0 13
17.6%
2 8
10.8%
3 7
9.5%
5 7
9.5%
8 6
 
8.1%
7 5
 
6.8%
, 4
 
5.4%
6 4
 
5.4%
9 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
23.0%
0 13
17.6%
2 8
10.8%
3 7
9.5%
5 7
9.5%
8 6
 
8.1%
7 5
 
6.8%
, 4
 
5.4%
6 4
 
5.4%
9 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:33:34.222043image/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

Unique15 ?
Unique (%)45.5%

Sample

1st row대촌동
2nd row4,133
3rd row8,170
4th row5
5th row4
ValueCountFrequency (%)
0 7
21.2%
34 3
 
9.1%
7 2
 
6.1%
5 2
 
6.1%
4 2
 
6.1%
16 2
 
6.1%
8 2
 
6.1%
62 1
 
3.0%
4,126 1
 
3.0%
1 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:33:35.180929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
14.1%
1 9
14.1%
3 7
10.9%
4 7
10.9%
8 6
9.4%
6 5
7.8%
7 5
7.8%
, 4
6.2%
2 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 (%)
0 9
16.1%
1 9
16.1%
3 7
12.5%
4 7
12.5%
8 6
10.7%
6 5
8.9%
7 5
8.9%
2 4
7.1%
5 3
 
5.4%
9 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 (%)
0 9
14.8%
1 9
14.8%
3 7
11.5%
4 7
11.5%
8 6
9.8%
6 5
8.2%
7 5
8.2%
, 4
6.6%
2 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 (%)
0 9
14.8%
1 9
14.8%
3 7
11.5%
4 7
11.5%
8 6
9.8%
6 5
8.2%
7 5
8.2%
, 4
6.6%
2 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>2023.02.09<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.01 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>95,8683,1162,9573,9826,4859,8372,864<NA>4,5614,7983,5065,1773,2749,5994,01111,4167,5598,5934,133
4<NA>전월말인구수<NA><NA><NA>212,3796,7776,5648,49212,90028,1834,928<NA>8,8188,3626,20511,9196,21021,4627,80728,57815,83421,1708,170
5<NA>전월말거주불명자수<NA><NA><NA>350111116491043<NA>30311712211929342105
6<NA>전월말재외국민등록자수<NA><NA><NA>150571010166<NA>75414313624884
7<NA>증 가 요 인전 입<NA>1,951531075613724344<NA>648164651072225021813823270
8<NA><NA><NA>남자<NA>9432257356412020<NA>274136295091311076911034
9<NA><NA><NA>여자<NA>1,0083150217312324<NA>3740283657131191116912236
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>5100010<NA>00010000101
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>0000000<NA>00000000000
28<NA>세대수증감<NA><NA><NA>-127331-10-11-14-15<NA>-9-120-1000-22-26-24-1-7
29<NA>인구수증감<NA><NA><NA>-351-2753-11-34-85-30<NA>-23-31-14-30-811-32-74-37138
30<NA>거주불명자수증감<NA><NA><NA>1430-1-400<NA>-10-11502-1830
31<NA>금월말세대수<NA><NA><NA>95,7413,1192,9883,9726,4749,8232,849<NA>4,5524,7863,5065,1673,2749,5993,98911,3907,5358,5924,126
32<NA>금월말인구수<NA><NA><NA>212,0286,7506,6178,48112,86628,0984,898<NA>8,7958,3316,19111,8896,20221,4737,77528,50415,79721,1838,178
33<NA>금월말거주불명자수<NA><NA><NA>364141115451043<NA>293116132619313310135
34<NA>금월말재외국민등록자수<NA><NA><NA>15177109166<NA>75414313625874

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>기타<NA><NA>0000000<NA>000000000002