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

Description2024-02-01
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 09:42:57.103819
Analysis finished2024-02-10 09:42:58.335313
Duration1.23 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
2024-02-10T09:42:58.685933image/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%
2024-02-10T09:42:59.691163image/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
2024-02-10T09:43:00.216793image/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%
2024-02-10T09:43:01.099589image/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
2024-02-10T09:43:01.597368image/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 row2023.11 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%
2023.11 1
7.1%
현재 1
7.1%
2024-02-10T09:43:02.611864image/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 (%)
1 2
33.3%
2 2
33.3%
3 1
16.7%
0 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%
1 2
20.0%
2 2
20.0%
3 1
 
10.0%
. 1
 
10.0%
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%
1 2
20.0%
2 2
20.0%
3 1
 
10.0%
. 1
 
10.0%
0 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:43:02.977660image/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%
2024-02-10T09:43:03.612410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:04.023008image/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

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row95,511
3rd row210,027
4th row330
5th row151
ValueCountFrequency (%)
0 4
 
11.8%
659 2
 
5.9%
2,098 1
 
2.9%
368 1
 
2.9%
209,979 1
 
2.9%
95,479 1
 
2.9%
38 1
 
2.9%
48 1
 
2.9%
32 1
 
2.9%
20 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:43:04.958334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 19
17.1%
1 13
11.7%
9 12
10.8%
2 11
9.9%
, 10
9.0%
5 9
8.1%
8 8
7.2%
3 7
 
6.3%
6 6
 
5.4%
7 6
 
5.4%
Other values (5) 10
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 95
85.6%
Other Punctuation 10
 
9.0%
Space Separator 2
 
1.8%
Dash Punctuation 2
 
1.8%
Other Letter 2
 
1.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 19
20.0%
1 13
13.7%
9 12
12.6%
2 11
11.6%
5 9
9.5%
8 8
8.4%
3 7
 
7.4%
6 6
 
6.3%
7 6
 
6.3%
4 4
 
4.2%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 19
17.4%
1 13
11.9%
9 12
11.0%
2 11
10.1%
, 10
9.2%
5 9
8.3%
8 8
7.3%
3 7
 
6.4%
6 6
 
5.5%
7 6
 
5.5%
Other values (3) 8
7.3%
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 (%)
0 19
17.4%
1 13
11.9%
9 12
11.0%
2 11
10.1%
, 10
9.2%
5 9
8.3%
8 8
7.3%
3 7
 
6.4%
6 6
 
5.5%
7 6
 
5.5%
Other values (3) 8
7.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:05.478428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique20 ?
Unique (%)60.6%

Sample

1st row양림동
2nd row3,079
3rd row6,656
4th row9
5th row7
ValueCountFrequency (%)
0 7
21.2%
23 2
 
6.1%
16 2
 
6.1%
7 2
 
6.1%
66 1
 
3.0%
15 1
 
3.0%
14 1
 
3.0%
6,627 1
 
3.0%
3,068 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:43:06.343740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6 12
17.6%
0 9
13.2%
3 8
11.8%
1 8
11.8%
2 6
8.8%
7 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
4 3
 
4.4%
9 3
 
4.4%
Other values (5) 6
8.8%

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 (%)
6 12
20.3%
0 9
15.3%
3 8
13.6%
1 8
13.6%
2 6
10.2%
7 5
8.5%
5 4
 
6.8%
4 3
 
5.1%
9 3
 
5.1%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
6 12
18.5%
0 9
13.8%
3 8
12.3%
1 8
12.3%
2 6
9.2%
7 5
7.7%
, 4
 
6.2%
5 4
 
6.2%
4 3
 
4.6%
9 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
6 12
18.5%
0 9
13.8%
3 8
12.3%
1 8
12.3%
2 6
9.2%
7 5
7.7%
, 4
 
6.2%
5 4
 
6.2%
4 3
 
4.6%
9 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:06.749737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique20 ?
Unique (%)60.6%

Sample

1st row방림1동
2nd row3,084
3rd row6,738
4th row17
5th row6
ValueCountFrequency (%)
0 7
21.2%
17 2
 
6.1%
27 2
 
6.1%
1 2
 
6.1%
42 2
 
6.1%
3,084 1
 
3.0%
23 1
 
3.0%
6 1
 
3.0%
98 1
 
3.0%
16 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:43:07.833842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 10
16.4%
1 10
16.4%
2 7
11.5%
7 6
9.8%
4 6
9.8%
3 6
9.8%
6 5
8.2%
5 5
8.2%
8 4
 
6.6%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:08.169253image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row방림2동
2nd row3,897
3rd row8,216
4th row16
5th row10
ValueCountFrequency (%)
0 7
21.2%
28 2
 
6.1%
1 2
 
6.1%
8,216 1
 
3.0%
16 1
 
3.0%
17 1
 
3.0%
8,188 1
 
3.0%
3,885 1
 
3.0%
12 1
 
3.0%
6 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:08.986452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.7%
8 11
15.3%
2 9
12.5%
0 8
11.1%
6 6
8.3%
3 6
8.3%
5 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
4 2
 
2.8%
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 (%)
1 12
19.0%
8 11
17.5%
2 9
14.3%
0 8
12.7%
6 6
9.5%
3 6
9.5%
5 4
 
6.3%
7 3
 
4.8%
4 2
 
3.2%
9 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 (%)
1 12
17.4%
8 11
15.9%
2 9
13.0%
0 8
11.6%
6 6
8.7%
3 6
8.7%
5 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
4 2
 
2.9%
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 (%)
1 12
17.4%
8 11
15.9%
2 9
13.0%
0 8
11.6%
6 6
8.7%
3 6
8.7%
5 4
 
5.8%
, 4
 
5.8%
7 3
 
4.3%
4 2
 
2.9%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:09.423084image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row봉선1동
2nd row6,447
3rd row12,843
4th row37
5th row12
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
38 2
 
6.1%
12 2
 
6.1%
42 2
 
6.1%
36 2
 
6.1%
6,447 1
 
3.0%
109 1
 
3.0%
61 1
 
3.0%
6,446 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:43:10.331125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
14.9%
1 11
14.9%
0 10
13.5%
3 9
12.2%
6 7
9.5%
2 7
9.5%
8 4
 
5.4%
, 4
 
5.4%
7 3
 
4.1%
5 2
 
2.7%
Other values (5) 6
8.1%

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 (%)
4 11
16.9%
1 11
16.9%
0 10
15.4%
3 9
13.8%
6 7
10.8%
2 7
10.8%
8 4
 
6.2%
7 3
 
4.6%
5 2
 
3.1%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
15.5%
1 11
15.5%
0 10
14.1%
3 9
12.7%
6 7
9.9%
2 7
9.9%
8 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
5 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11
15.5%
1 11
15.5%
0 10
14.1%
3 9
12.7%
6 7
9.9%
2 7
9.9%
8 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
5 2
 
2.8%
Other values (2) 3
 
4.2%
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
2024-02-10T09:43:10.734519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.6176471
Min length1

Characters and Unicode

Total characters89
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row봉선2동
3rd row9,780
4th row27,678
5th row10
ValueCountFrequency (%)
0 5
 
14.3%
2 3
 
8.6%
10 2
 
5.7%
110 2
 
5.7%
출력일자 1
 
2.9%
12 1
 
2.9%
27,710 1
 
2.9%
9,777 1
 
2.9%
32 1
 
2.9%
3 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T09:43:11.802421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
21.3%
0 13
14.6%
2 11
12.4%
7 9
10.1%
3 6
 
6.7%
6 6
 
6.7%
9 4
 
4.5%
, 4
 
4.5%
8 3
 
3.4%
4 2
 
2.2%
Other values (11) 12
13.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
84.3%
Other Letter 7
 
7.9%
Other Punctuation 5
 
5.6%
Space Separator 1
 
1.1%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
25.3%
0 13
17.3%
2 11
14.7%
7 9
12.0%
3 6
 
8.0%
6 6
 
8.0%
9 4
 
5.3%
8 3
 
4.0%
4 2
 
2.7%
5 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
23.2%
0 13
15.9%
2 11
13.4%
7 9
11.0%
3 6
 
7.3%
6 6
 
7.3%
9 4
 
4.9%
, 4
 
4.9%
8 3
 
3.7%
4 2
 
2.4%
Other values (4) 5
 
6.1%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
23.2%
0 13
15.9%
2 11
13.4%
7 9
11.0%
3 6
 
7.3%
6 6
 
7.3%
9 4
 
4.9%
, 4
 
4.9%
8 3
 
3.7%
4 2
 
2.4%
Other values (4) 5
 
6.1%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Unnamed: 11
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:12.244827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row사직동
2nd row2,768
3rd row4,752
4th row30
5th row5
ValueCountFrequency (%)
0 6
18.2%
5 4
 
12.1%
20 2
 
6.1%
38 1
 
3.0%
30 1
 
3.0%
69 1
 
3.0%
4,730 1
 
3.0%
2,757 1
 
3.0%
22 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:43:13.295252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.9%
2 11
15.9%
5 8
11.6%
1 7
10.1%
7 6
8.7%
3 5
7.2%
4 4
 
5.8%
, 4
 
5.8%
8 3
 
4.3%
9 3
 
4.3%
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 11
18.3%
2 11
18.3%
5 8
13.3%
1 7
11.7%
7 6
10.0%
3 5
8.3%
4 4
 
6.7%
8 3
 
5.0%
9 3
 
5.0%
6 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.7%
2 11
16.7%
5 8
12.1%
1 7
10.6%
7 6
9.1%
3 5
7.6%
4 4
 
6.1%
, 4
 
6.1%
8 3
 
4.5%
9 3
 
4.5%
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 11
16.7%
2 11
16.7%
5 8
12.1%
1 7
10.6%
7 6
9.1%
3 5
7.6%
4 4
 
6.1%
, 4
 
6.1%
8 3
 
4.5%
9 3
 
4.5%
Other values (2) 4
 
6.1%
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
Minimum2023-12-28 00:00:00
Maximum2023-12-28 00:00:00
2024-02-10T09:43:13.721120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:43:14.074669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:14.454427image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row월산동
2nd row4,456
3rd row8,592
4th row24
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 3
 
9.1%
24 2
 
6.1%
139 1
 
3.0%
63 1
 
3.0%
8,531 1
 
3.0%
4,432 1
 
3.0%
2 1
 
3.0%
61 1
 
3.0%
1 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:15.509118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 (%)
4 9
14.8%
6 8
13.1%
0 7
11.5%
2 7
11.5%
3 7
11.5%
1 7
11.5%
7 6
9.8%
8 5
8.2%
5 3
 
4.9%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 9
13.4%
6 8
11.9%
0 7
10.4%
2 7
10.4%
3 7
10.4%
1 7
10.4%
7 6
9.0%
8 5
7.5%
, 4
6.0%
5 3
 
4.5%
Other values (2) 4
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 9
13.4%
6 8
11.9%
0 7
10.4%
2 7
10.4%
3 7
10.4%
1 7
10.4%
7 6
9.0%
8 5
7.5%
, 4
6.0%
5 3
 
4.5%
Other values (2) 4
6.0%
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
2024-02-10T09:43:15.976508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row월산4동
2nd row4,750
3rd row8,166
4th row27
5th row5
ValueCountFrequency (%)
0 5
 
15.2%
51 2
 
6.1%
21 2
 
6.1%
1 2
 
6.1%
5 2
 
6.1%
84 1
 
3.0%
19 1
 
3.0%
31 1
 
3.0%
8,174 1
 
3.0%
4,748 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:17.099137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
16.4%
1 10
14.9%
0 6
9.0%
5 6
9.0%
7 6
9.0%
8 6
9.0%
2 5
7.5%
, 4
 
6.0%
3 3
 
4.5%
9 3
 
4.5%
Other values (5) 7
10.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
18.6%
1 10
16.9%
0 6
10.2%
5 6
10.2%
7 6
10.2%
8 6
10.2%
2 5
8.5%
3 3
 
5.1%
9 3
 
5.1%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
17.2%
1 10
15.6%
0 6
9.4%
5 6
9.4%
7 6
9.4%
8 6
9.4%
2 5
7.8%
, 4
 
6.2%
3 3
 
4.7%
9 3
 
4.7%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11
17.2%
1 10
15.6%
0 6
9.4%
5 6
9.4%
7 6
9.4%
8 6
9.4%
2 5
7.8%
, 4
 
6.2%
3 3
 
4.7%
9 3
 
4.7%
Other values (2) 4
 
6.2%
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
2024-02-10T09:43:17.582555image/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 row3,434
3rd row5,994
4th row11
5th row3
ValueCountFrequency (%)
0 8
24.2%
34 2
 
6.1%
13 2
 
6.1%
3 2
 
6.1%
20 1
 
3.0%
32 1
 
3.0%
5,972 1
 
3.0%
3,426 1
 
3.0%
1 1
 
3.0%
22 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:43:18.788714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
17.4%
0 9
13.0%
2 9
13.0%
4 7
10.1%
1 6
8.7%
9 5
7.2%
7 4
 
5.8%
, 4
 
5.8%
5 4
 
5.8%
6 3
 
4.3%
Other values (5) 6
8.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
20.0%
0 9
15.0%
2 9
15.0%
4 7
11.7%
1 6
10.0%
9 5
8.3%
7 4
 
6.7%
5 4
 
6.7%
6 3
 
5.0%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 16
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:19.291701image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row백운1동
2nd row5,140
3rd row11,718
4th row15
5th row14
ValueCountFrequency (%)
0 7
21.2%
26 2
 
6.1%
5,140 2
 
6.1%
2 1
 
3.0%
47 1
 
3.0%
18 1
 
3.0%
11,688 1
 
3.0%
3 1
 
3.0%
30 1
 
3.0%
1 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:20.214207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
21.9%
0 12
16.4%
3 7
9.6%
4 6
 
8.2%
6 6
 
8.2%
8 6
 
8.2%
5 5
 
6.8%
, 4
 
5.5%
2 3
 
4.1%
7 3
 
4.1%
Other values (5) 5
 
6.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
24.6%
0 12
18.5%
3 7
10.8%
4 6
 
9.2%
6 6
 
9.2%
8 6
 
9.2%
5 5
 
7.7%
2 3
 
4.6%
7 3
 
4.6%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
22.9%
0 12
17.1%
3 7
10.0%
4 6
 
8.6%
6 6
 
8.6%
8 6
 
8.6%
5 5
 
7.1%
, 4
 
5.7%
2 3
 
4.3%
7 3
 
4.3%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
22.9%
0 12
17.1%
3 7
10.0%
4 6
 
8.6%
6 6
 
8.6%
8 6
 
8.6%
5 5
 
7.1%
, 4
 
5.7%
2 3
 
4.3%
7 3
 
4.3%
Other values (2) 2
 
2.9%
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
2024-02-10T09:43:20.652460image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row백운2동
2nd row3,556
3rd row6,696
4th row26
5th row2
ValueCountFrequency (%)
0 6
18.2%
2 3
 
9.1%
26 2
 
6.1%
7 2
 
6.1%
22 2
 
6.1%
39 1
 
3.0%
45 1
 
3.0%
3,563 1
 
3.0%
4 1
 
3.0%
24 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:43:21.596124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
23.2%
6 10
14.5%
0 8
11.6%
3 8
11.6%
5 5
 
7.2%
4 5
 
7.2%
, 4
 
5.8%
9 4
 
5.8%
7 3
 
4.3%
1
 
1.4%
Other values (5) 5
 
7.2%

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 (%)
2 16
26.2%
6 10
16.4%
0 8
13.1%
3 8
13.1%
5 5
 
8.2%
4 5
 
8.2%
9 4
 
6.6%
7 3
 
4.9%
1 1
 
1.6%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 16
24.2%
6 10
15.2%
0 8
12.1%
3 8
12.1%
5 5
 
7.6%
4 5
 
7.6%
, 4
 
6.1%
9 4
 
6.1%
7 3
 
4.5%
1 1
 
1.5%
Other values (2) 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 (%)
2 16
24.2%
6 10
15.2%
0 8
12.1%
3 8
12.1%
5 5
 
7.6%
4 5
 
7.6%
, 4
 
6.1%
9 4
 
6.1%
7 3
 
4.5%
1 1
 
1.5%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:22.017319image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row주월1동
2nd row9,566
3rd row21,193
4th row22
5th row13
ValueCountFrequency (%)
0 6
18.2%
95 2
 
6.1%
10 2
 
6.1%
22 2
 
6.1%
13 2
 
6.1%
75 1
 
3.0%
115 1
 
3.0%
21,174 1
 
3.0%
9,544 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:43:22.890389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
21.0%
2 10
12.3%
0 9
11.1%
9 9
11.1%
3 7
8.6%
5 7
8.6%
6 5
 
6.2%
, 4
 
4.9%
8 3
 
3.7%
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 17
23.6%
2 10
13.9%
0 9
12.5%
9 9
12.5%
3 7
9.7%
5 7
9.7%
6 5
 
6.9%
8 3
 
4.2%
4 3
 
4.2%
7 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 17
21.8%
2 10
12.8%
0 9
11.5%
9 9
11.5%
3 7
9.0%
5 7
9.0%
6 5
 
6.4%
, 4
 
5.1%
8 3
 
3.8%
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 17
21.8%
2 10
12.8%
0 9
11.5%
9 9
11.5%
3 7
9.0%
5 7
9.0%
6 5
 
6.4%
, 4
 
5.1%
8 3
 
3.8%
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
2024-02-10T09:43:23.236917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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

Unique16 ?
Unique (%)48.5%

Sample

1st row주월2동
2nd row3,874
3rd row7,559
4th row28
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 3
 
9.1%
2 2
 
6.1%
3,874 2
 
6.1%
30 2
 
6.1%
22 1
 
3.0%
7,561 1
 
3.0%
3 1
 
3.0%
9 1
 
3.0%
31 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:43:24.015792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
15.4%
2 10
15.4%
3 10
15.4%
5 7
10.8%
7 5
7.7%
9 5
7.7%
, 4
 
6.2%
1 4
 
6.2%
8 3
 
4.6%
4 2
 
3.1%
Other values (4) 5
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
17.2%
2 10
17.2%
3 10
17.2%
5 7
12.1%
7 5
8.6%
9 5
8.6%
1 4
 
6.9%
8 3
 
5.2%
4 2
 
3.4%
6 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
16.1%
2 10
16.1%
3 10
16.1%
5 7
11.3%
7 5
8.1%
9 5
8.1%
, 4
 
6.5%
1 4
 
6.5%
8 3
 
4.8%
4 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
16.1%
2 10
16.1%
3 10
16.1%
5 7
11.3%
7 5
8.1%
9 5
8.1%
, 4
 
6.5%
1 4
 
6.5%
8 3
 
4.8%
4 2
 
3.2%
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
2024-02-10T09:43:24.340855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
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

Unique24 ?
Unique (%)72.7%

Sample

1st row진월동
2nd row11,458
3rd row28,225
4th row35
5th row28
ValueCountFrequency (%)
0 7
21.2%
28 2
 
6.1%
94 1
 
3.0%
28,284 1
 
3.0%
11,473 1
 
3.0%
4 1
 
3.0%
59 1
 
3.0%
15 1
 
3.0%
11 1
 
3.0%
76 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:25.125757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.8%
2 9
11.2%
8 9
11.2%
0 8
10.0%
6 7
8.8%
4 6
 
7.5%
5 6
 
7.5%
9 6
 
7.5%
, 4
 
5.0%
3 4
 
5.0%
Other values (4) 6
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
91.2%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.5%
2 9
12.3%
8 9
12.3%
0 8
11.0%
6 7
9.6%
4 6
 
8.2%
5 6
 
8.2%
9 6
 
8.2%
3 4
 
5.5%
7 3
 
4.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.5%
2 9
11.7%
8 9
11.7%
0 8
10.4%
6 7
9.1%
4 6
 
7.8%
5 6
 
7.8%
9 6
 
7.8%
, 4
 
5.2%
3 4
 
5.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.5%
2 9
11.7%
8 9
11.7%
0 8
10.4%
6 7
9.1%
4 6
 
7.8%
5 6
 
7.8%
9 6
 
7.8%
, 4
 
5.2%
3 4
 
5.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:25.474555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row효덕동
2nd row7,481
3rd row15,568
4th row10
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
5 3
 
9.1%
15,568 1
 
3.0%
10 1
 
3.0%
15,547 1
 
3.0%
7,500 1
 
3.0%
4 1
 
3.0%
21 1
 
3.0%
19 1
 
3.0%
2 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:26.218184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
88.9%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
5 9
14.1%
7 9
14.1%
1 9
14.1%
4 6
9.4%
6 5
7.8%
8 5
7.8%
9 4
 
6.2%
2 4
 
6.2%
3 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
5 9
13.0%
7 9
13.0%
1 9
13.0%
4 6
8.7%
6 5
7.2%
8 5
7.2%
9 4
 
5.8%
2 4
 
5.8%
, 4
 
5.8%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.9%
5 9
13.0%
7 9
13.0%
1 9
13.0%
4 6
8.7%
6 5
7.2%
8 5
7.2%
9 4
 
5.8%
2 4
 
5.8%
, 4
 
5.8%
Other values (2) 3
 
4.3%
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
2024-02-10T09:43:26.772345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row송암동
2nd row8,651
3rd row21,209
4th row7
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
101 1
 
3.0%
110 1
 
3.0%
21,238 1
 
3.0%
8,662 1
 
3.0%
1 1
 
3.0%
29 1
 
3.0%
11 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:27.670171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
21.6%
0 12
16.2%
2 11
14.9%
8 8
10.8%
6 7
9.5%
7 5
 
6.8%
, 4
 
5.4%
3 3
 
4.1%
5 2
 
2.7%
9 2
 
2.7%
Other values (4) 4
 
5.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
23.9%
0 12
17.9%
2 11
16.4%
8 8
11.9%
6 7
10.4%
7 5
 
7.5%
3 3
 
4.5%
5 2
 
3.0%
9 2
 
3.0%
4 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
22.5%
0 12
16.9%
2 11
15.5%
8 8
11.3%
6 7
9.9%
7 5
 
7.0%
, 4
 
5.6%
3 3
 
4.2%
5 2
 
2.8%
9 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
22.5%
0 12
16.9%
2 11
15.5%
8 8
11.3%
6 7
9.9%
7 5
 
7.0%
, 4
 
5.6%
3 3
 
4.2%
5 2
 
2.8%
9 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:28.021663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row대촌동
2nd row4,090
3rd row8,224
4th row6
5th row4
ValueCountFrequency (%)
0 5
15.2%
4 4
 
12.1%
6 2
 
6.1%
32 2
 
6.1%
2 2
 
6.1%
9 2
 
6.1%
1 2
 
6.1%
71 1
 
3.0%
17 1
 
3.0%
4,089 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:43:28.992431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
15.4%
0 8
12.3%
4 7
10.8%
9 6
9.2%
3 5
7.7%
1 5
7.7%
6 4
 
6.2%
, 4
 
6.2%
8 4
 
6.2%
5 3
 
4.6%
Other values (5) 9
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
84.6%
Other Punctuation 4
 
6.2%
Dash Punctuation 3
 
4.6%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
18.2%
0 8
14.5%
4 7
12.7%
9 6
10.9%
3 5
9.1%
1 5
9.1%
6 4
 
7.3%
8 4
 
7.3%
5 3
 
5.5%
7 3
 
5.5%
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 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
16.1%
0 8
12.9%
4 7
11.3%
9 6
9.7%
3 5
8.1%
1 5
8.1%
6 4
 
6.5%
, 4
 
6.5%
8 4
 
6.5%
5 3
 
4.8%
Other values (2) 6
9.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
95.4%
Hangul 3
 
4.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
16.1%
0 8
12.9%
4 7
11.3%
9 6
9.7%
3 5
8.1%
1 5
8.1%
6 4
 
6.5%
, 4
 
6.5%
8 4
 
6.5%
5 3
 
4.8%
Other values (2) 6
9.7%
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>2023.12.28<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.11 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>95,5113,0793,0843,8976,4479,7802,768<NA>4,4564,7503,4345,1403,5569,5663,87411,4587,4818,6514,090
4<NA>전월말인구수<NA><NA><NA>210,0276,6566,7388,21612,84327,6784,752<NA>8,5928,1665,99411,7186,69621,1937,55928,22515,56821,2098,224
5<NA>전월말거주불명자수<NA><NA><NA>33091716371030<NA>24271115262228351076
6<NA>전월말재외국민등록자수<NA><NA><NA>151761012165<NA>75314213528774
7<NA>증 가 요 인전 입<NA>2,09946986610928247<NA>789863811222186226916023268
8<NA><NA><NA>남자<NA>1,0012346354213628<NA>384729356099301118612036
9<NA><NA><NA>여자<NA>1,0982352316714619<NA>4051344662119321587411232
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>20200020<NA>13017000202
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>0000000<NA>00000000000
28<NA>세대수증감<NA><NA><NA>-32-1111-12-1-3-11<NA>-24-2-807-220151911-1
29<NA>인구수증감<NA><NA><NA>-48-2942-28-332-22<NA>-618-22-3024-19259-2129-9
30<NA>거주불명자수증감<NA><NA><NA>385-11525<NA>2413-435441-2
31<NA>금월말세대수<NA><NA><NA>95,4793,0683,0953,8856,4469,7772,757<NA>4,4324,7483,4265,1403,5639,5443,87411,4737,5008,6624,089
32<NA>금월말인구수<NA><NA><NA>209,9796,6276,7808,18812,84027,7104,730<NA>8,5318,1745,97211,6886,72021,1747,56128,28415,54721,2388,215
33<NA>금월말거주불명자수<NA><NA><NA>368141617421235<NA>26311218222533391484
34<NA>금월말재외국민등록자수<NA><NA><NA>148651112155<NA>77313213528574

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