Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2023-03-09
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 2 (5.7%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 25 has 2 (5.7%) missing valuesMissing
Unnamed: 26 has 2 (5.7%) missing valuesMissing
Unnamed: 27 has 2 (5.7%) missing valuesMissing
Unnamed: 28 has 2 (5.7%) missing valuesMissing
Unnamed: 29 has 2 (5.7%) missing valuesMissing
Unnamed: 30 has 2 (5.7%) missing valuesMissing
Unnamed: 31 has 2 (5.7%) missing valuesMissing
Unnamed: 32 has 2 (5.7%) missing valuesMissing
Unnamed: 33 has 2 (5.7%) missing valuesMissing
Unnamed: 34 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 09:49:04.721260
Analysis finished2024-02-10 09:49:06.764874
Duration2.04 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:49:07.073661image/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%
2024-02-10T09:49:08.214767image/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
2024-02-10T09:49:08.612742image/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%
2024-02-10T09:49:09.588547image/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
2024-02-10T09:49:10.142355image/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 북구
2nd row2023.02 현재
3rd row
4th row남자
5th row여자
ValueCountFrequency (%)
2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
북구 1
7.1%
2023.02 1
7.1%
현재 1
7.1%
2024-02-10T09:49:10.982246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
2 3
 
7.3%
2
 
4.9%
0 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%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
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%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
. 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%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
ASCII
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
. 1
 
10.0%
3 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:49:11.351369image/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%
2024-02-10T09:49:12.197056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:12.674647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4
Min length1

Characters and Unicode

Total characters132
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row합 계
2nd row198,068
3rd row424,326
4th row1,080
5th row231
ValueCountFrequency (%)
0 5
 
14.7%
1,534 2
 
5.9%
231 2
 
5.9%
2,442 1
 
2.9%
2,638 1
 
2.9%
424,013 1
 
2.9%
198,320 1
 
2.9%
38 1
 
2.9%
313 1
 
2.9%
252 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T09:49:13.502301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 18
13.6%
3 16
12.1%
1 16
12.1%
0 15
11.4%
2 15
11.4%
4 14
10.6%
8 10
7.6%
7 7
 
5.3%
5 6
 
4.5%
9 5
 
3.8%
Other values (5) 10
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
81.8%
Other Punctuation 18
 
13.6%
Space Separator 2
 
1.5%
Dash Punctuation 2
 
1.5%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 16
14.8%
1 16
14.8%
0 15
13.9%
2 15
13.9%
4 14
13.0%
8 10
9.3%
7 7
6.5%
5 6
 
5.6%
9 5
 
4.6%
6 4
 
3.7%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 130
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
, 18
13.8%
3 16
12.3%
1 16
12.3%
0 15
11.5%
2 15
11.5%
4 14
10.8%
8 10
7.7%
7 7
 
5.4%
5 6
 
4.6%
9 5
 
3.8%
Other values (3) 8
6.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 130
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 18
13.8%
3 16
12.3%
1 16
12.3%
0 15
11.5%
2 15
11.5%
4 14
10.8%
8 10
7.7%
7 7
 
5.4%
5 6
 
4.6%
9 5
 
3.8%
Other values (3) 8
6.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:13.836337image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row중흥1동
2nd row2,884
3rd row4,540
4th row47
5th row1
ValueCountFrequency (%)
0 7
21.2%
16 2
 
6.1%
17 2
 
6.1%
1 2
 
6.1%
2 2
 
6.1%
18 1
 
3.0%
33 1
 
3.0%
4,524 1
 
3.0%
2,868 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:49:14.586115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
15.7%
4 10
14.3%
2 9
12.9%
0 8
11.4%
8 5
7.1%
6 4
 
5.7%
7 4
 
5.7%
5 4
 
5.7%
, 4
 
5.7%
3 4
 
5.7%
Other values (5) 7
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Other Punctuation 4
 
5.7%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
18.3%
4 10
16.7%
2 9
15.0%
0 8
13.3%
8 5
8.3%
6 4
 
6.7%
7 4
 
6.7%
5 4
 
6.7%
3 4
 
6.7%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
16.4%
4 10
14.9%
2 9
13.4%
0 8
11.9%
8 5
7.5%
6 4
 
6.0%
7 4
 
6.0%
5 4
 
6.0%
, 4
 
6.0%
3 4
 
6.0%
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 (%)
1 11
16.4%
4 10
14.9%
2 9
13.4%
0 8
11.9%
8 5
7.5%
6 4
 
6.0%
7 4
 
6.0%
5 4
 
6.0%
, 4
 
6.0%
3 4
 
6.0%
Other values (2) 4
 
6.0%
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
2024-02-10T09:49:14.909126image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row중흥2동
2nd row4,392
3rd row8,414
4th row38
5th row6
ValueCountFrequency (%)
0 8
24.2%
6 2
 
6.1%
2 2
 
6.1%
78 1
 
3.0%
8,399 1
 
3.0%
4,404 1
 
3.0%
15 1
 
3.0%
12 1
 
3.0%
56 1
 
3.0%
53 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:49:15.697258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
4 8
11.1%
1 7
9.7%
3 7
9.7%
6 6
8.3%
2 6
8.3%
5 5
6.9%
8 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
Other values (5) 9
12.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.5%
4 8
12.7%
1 7
11.1%
3 7
11.1%
6 6
9.5%
2 6
9.5%
5 5
7.9%
8 5
7.9%
9 4
 
6.3%
7 4
 
6.3%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
4 8
11.6%
1 7
10.1%
3 7
10.1%
6 6
8.7%
2 6
8.7%
5 5
7.2%
8 5
7.2%
, 4
 
5.8%
9 4
 
5.8%
Other values (2) 6
8.7%
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%
4 8
11.6%
1 7
10.1%
3 7
10.1%
6 6
8.7%
2 6
8.7%
5 5
7.2%
8 5
7.2%
, 4
 
5.8%
9 4
 
5.8%
Other values (2) 6
8.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:16.015960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row중흥3동
2nd row3,641
3rd row6,535
4th row42
5th row2
ValueCountFrequency (%)
0 7
21.2%
42 3
 
9.1%
2 2
 
6.1%
62 1
 
3.0%
6,535 1
 
3.0%
133 1
 
3.0%
3,664 1
 
3.0%
17 1
 
3.0%
23 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:49:16.835878image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 9
14.3%
3 9
14.3%
0 8
12.7%
4 8
12.7%
1 7
11.1%
6 7
11.1%
5 7
11.1%
7 4
6.3%
8 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%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 9
13.4%
3 9
13.4%
0 8
11.9%
4 8
11.9%
1 7
10.4%
6 7
10.4%
5 7
10.4%
7 4
6.0%
, 4
6.0%
8 3
 
4.5%
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
2024-02-10T09:49:17.154255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row중앙동
2nd row2,286
3rd row3,934
4th row43
5th row6
ValueCountFrequency (%)
0 7
21.2%
28 2
 
6.1%
3 2
 
6.1%
1 2
 
6.1%
6 2
 
6.1%
26 1
 
3.0%
54 1
 
3.0%
3,941 1
 
3.0%
2,285 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:49:18.146755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
14.9%
3 9
13.4%
0 8
11.9%
6 7
10.4%
1 7
10.4%
4 6
9.0%
8 4
 
6.0%
, 4
 
6.0%
5 3
 
4.5%
9 2
 
3.0%
Other values (5) 7
10.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
17.2%
3 9
15.5%
0 8
13.8%
6 7
12.1%
1 7
12.1%
4 6
10.3%
8 4
 
6.9%
5 3
 
5.2%
9 2
 
3.4%
7 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
15.6%
3 9
14.1%
0 8
12.5%
6 7
10.9%
1 7
10.9%
4 6
9.4%
8 4
 
6.2%
, 4
 
6.2%
5 3
 
4.7%
9 2
 
3.1%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
15.6%
3 9
14.1%
0 8
12.5%
6 7
10.9%
1 7
10.9%
4 6
9.4%
8 4
 
6.2%
, 4
 
6.2%
5 3
 
4.7%
9 2
 
3.1%
Other values (2) 4
 
6.2%
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
2024-02-10T09:49:18.460378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2352941
Min length1

Characters and Unicode

Total characters76
Distinct characters20
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

Unique23 ?
Unique (%)67.6%

Sample

1st row출력일자 :
2nd row임동
3rd row4,623
4th row9,170
5th row34
ValueCountFrequency (%)
0 6
 
17.1%
5 3
 
8.6%
19 2
 
5.7%
1
 
2.9%
1 1
 
2.9%
9,149 1
 
2.9%
4,603 1
 
2.9%
4 1
 
2.9%
21 1
 
2.9%
20 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T09:49:19.195142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.5%
4 10
13.2%
9 7
9.2%
3 7
9.2%
1 7
9.2%
2 5
6.6%
5 5
6.6%
6 4
 
5.3%
, 4
 
5.3%
7 4
 
5.3%
Other values (10) 12
15.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
80.3%
Other Letter 6
 
7.9%
Other Punctuation 5
 
6.6%
Dash Punctuation 3
 
3.9%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
4 10
16.4%
9 7
11.5%
3 7
11.5%
1 7
11.5%
2 5
8.2%
5 5
8.2%
6 4
 
6.6%
7 4
 
6.6%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70
92.1%
Hangul 6
 
7.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
4 10
14.3%
9 7
10.0%
3 7
10.0%
1 7
10.0%
2 5
7.1%
5 5
7.1%
6 4
 
5.7%
, 4
 
5.7%
7 4
 
5.7%
Other values (4) 6
8.6%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70
92.1%
Hangul 6
 
7.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.7%
4 10
14.3%
9 7
10.0%
3 7
10.0%
1 7
10.0%
2 5
7.1%
5 5
7.1%
6 4
 
5.7%
, 4
 
5.7%
7 4
 
5.7%
Other values (4) 6
8.6%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:19.524504image/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 row신안동
2nd row7,461
3rd row12,479
4th row77
5th row1
ValueCountFrequency (%)
0 6
 
18.2%
1 3
 
9.1%
75 2
 
6.1%
10 1
 
3.0%
210 1
 
3.0%
7,477 1
 
3.0%
2 1
 
3.0%
8 1
 
3.0%
16 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:49:20.351771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
22.4%
0 11
14.5%
7 11
14.5%
2 7
9.2%
5 6
 
7.9%
4 6
 
7.9%
, 4
 
5.3%
8 4
 
5.3%
9 3
 
3.9%
6 2
 
2.6%
Other values (5) 5
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
89.5%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
25.0%
0 11
16.2%
7 11
16.2%
2 7
10.3%
5 6
 
8.8%
4 6
 
8.8%
8 4
 
5.9%
9 3
 
4.4%
6 2
 
2.9%
3 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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
23.3%
0 11
15.1%
7 11
15.1%
2 7
9.6%
5 6
 
8.2%
4 6
 
8.2%
, 4
 
5.5%
8 4
 
5.5%
9 3
 
4.1%
6 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
23.3%
0 11
15.1%
7 11
15.1%
2 7
9.6%
5 6
 
8.2%
4 6
 
8.2%
, 4
 
5.5%
8 4
 
5.5%
9 3
 
4.1%
6 2
 
2.7%
Other values (2) 2
 
2.7%
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
Minimum2023-03-07 00:00:00
Maximum2023-03-07 00:00:00
2024-02-10T09:49:20.563962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:49:20.929445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:21.284300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6666667
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row용봉동
2nd row17,821
3rd row37,583
4th row82
5th row20
ValueCountFrequency (%)
0 6
 
18.2%
20 2
 
6.1%
294 1
 
3.0%
552 1
 
3.0%
37,615 1
 
3.0%
17,927 1
 
3.0%
1 1
 
3.0%
32 1
 
3.0%
106 1
 
3.0%
11 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:49:22.021794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
20.5%
2 14
15.9%
0 9
10.2%
4 7
 
8.0%
7 7
 
8.0%
8 6
 
6.8%
3 6
 
6.8%
5 6
 
6.8%
, 4
 
4.5%
6 4
 
4.5%
Other values (5) 7
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
90.9%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
22.5%
2 14
17.5%
0 9
11.2%
4 7
 
8.8%
7 7
 
8.8%
8 6
 
7.5%
3 6
 
7.5%
5 6
 
7.5%
6 4
 
5.0%
9 3
 
3.8%
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 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
21.2%
2 14
16.5%
0 9
10.6%
4 7
 
8.2%
7 7
 
8.2%
8 6
 
7.1%
3 6
 
7.1%
5 6
 
7.1%
, 4
 
4.7%
6 4
 
4.7%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
21.2%
2 14
16.5%
0 9
10.6%
4 7
 
8.2%
7 7
 
8.2%
8 6
 
7.1%
3 6
 
7.1%
5 6
 
7.1%
, 4
 
4.7%
6 4
 
4.7%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:22.364735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row운암1동
2nd row7,407
3rd row18,843
4th row23
5th row20
ValueCountFrequency (%)
0 6
 
18.2%
109 2
 
6.1%
1 2
 
6.1%
22 1
 
3.0%
18,806 1
 
3.0%
7,405 1
 
3.0%
37 1
 
3.0%
2 1
 
3.0%
9 1
 
3.0%
85 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:49:23.171515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.7%
1 10
12.8%
8 10
12.8%
2 8
10.3%
9 6
7.7%
7 5
 
6.4%
4 5
 
6.4%
3 5
 
6.4%
, 4
 
5.1%
5 3
 
3.8%
Other values (5) 9
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.1%
1 10
14.7%
8 10
14.7%
2 8
11.8%
9 6
8.8%
7 5
 
7.4%
4 5
 
7.4%
3 5
 
7.4%
5 3
 
4.4%
6 3
 
4.4%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.3%
1 10
13.3%
8 10
13.3%
2 8
10.7%
9 6
8.0%
7 5
 
6.7%
4 5
 
6.7%
3 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
Other values (2) 6
8.0%
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 (%)
0 13
17.3%
1 10
13.3%
8 10
13.3%
2 8
10.7%
9 6
8.0%
7 5
 
6.7%
4 5
 
6.7%
3 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:23.489610image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row운암2동
2nd row5,988
3rd row11,472
4th row52
5th row9
ValueCountFrequency (%)
0 8
24.2%
52 2
 
6.1%
9 2
 
6.1%
39 1
 
3.0%
11,472 1
 
3.0%
71 1
 
3.0%
5,984 1
 
3.0%
37 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:49:24.200824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
1 9
12.3%
2 8
11.0%
4 8
11.0%
5 6
8.2%
9 5
6.8%
3 5
6.8%
8 4
 
5.5%
6 4
 
5.5%
, 4
 
5.5%
Other values (5) 9
12.3%

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 11
17.2%
1 9
14.1%
2 8
12.5%
4 8
12.5%
5 6
9.4%
9 5
7.8%
3 5
7.8%
8 4
 
6.2%
6 4
 
6.2%
7 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
1 9
12.9%
2 8
11.4%
4 8
11.4%
5 6
8.6%
9 5
7.1%
3 5
7.1%
8 4
 
5.7%
6 4
 
5.7%
, 4
 
5.7%
Other values (2) 6
8.6%
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 11
15.7%
1 9
12.9%
2 8
11.4%
4 8
11.4%
5 6
8.6%
9 5
7.1%
3 5
7.1%
8 4
 
5.7%
6 4
 
5.7%
, 4
 
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:24.563407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row운암3동
2nd row5,454
3rd row13,370
4th row36
5th row16
ValueCountFrequency (%)
0 7
21.2%
61 3
 
9.1%
16 2
 
6.1%
32 2
 
6.1%
34 1
 
3.0%
65 1
 
3.0%
13,344 1
 
3.0%
5,456 1
 
3.0%
1 1
 
3.0%
26 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:49:25.317466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
17.3%
6 11
14.7%
1 11
14.7%
0 9
12.0%
4 7
9.3%
2 6
8.0%
5 6
8.0%
, 4
 
5.3%
9 2
 
2.7%
- 2
 
2.7%
Other values (4) 4
 
5.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 13
19.7%
6 11
16.7%
1 11
16.7%
0 9
13.6%
4 7
10.6%
2 6
9.1%
5 6
9.1%
9 2
 
3.0%
7 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 13
18.1%
6 11
15.3%
1 11
15.3%
0 9
12.5%
4 7
9.7%
2 6
8.3%
5 6
8.3%
, 4
 
5.6%
9 2
 
2.8%
- 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 13
18.1%
6 11
15.3%
1 11
15.3%
0 9
12.5%
4 7
9.7%
2 6
8.3%
5 6
8.3%
, 4
 
5.6%
9 2
 
2.8%
- 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:25.634229image/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 categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row동림동
2nd row9,888
3rd row22,811
4th row35
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
34 2
 
6.1%
108 1
 
3.0%
191 1
 
3.0%
22,769 1
 
3.0%
9,894 1
 
3.0%
42 1
 
3.0%
6 1
 
3.0%
9 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:49:26.324219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
13.5%
8 10
13.5%
0 7
9.5%
3 7
9.5%
4 7
9.5%
9 7
9.5%
2 6
8.1%
7 5
6.8%
, 4
 
5.4%
6 4
 
5.4%
Other values (4) 7
9.5%

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 10
15.4%
8 10
15.4%
0 7
10.8%
3 7
10.8%
4 7
10.8%
9 7
10.8%
2 6
9.2%
7 5
7.7%
6 4
 
6.2%
5 2
 
3.1%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 10
14.1%
8 10
14.1%
0 7
9.9%
3 7
9.9%
4 7
9.9%
9 7
9.9%
2 6
8.5%
7 5
7.0%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
14.1%
8 10
14.1%
0 7
9.9%
3 7
9.9%
4 7
9.9%
9 7
9.9%
2 6
8.5%
7 5
7.0%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:26.664728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
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

Unique25 ?
Unique (%)75.8%

Sample

1st row우산동
2nd row7,371
3rd row14,722
4th row57
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
8 2
 
6.1%
75 1
 
3.0%
143 1
 
3.0%
15,087 1
 
3.0%
7,503 1
 
3.0%
2 1
 
3.0%
365 1
 
3.0%
132 1
 
3.0%
6 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:49:27.402714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.2%
5 12
15.2%
1 9
11.4%
7 9
11.4%
3 7
8.9%
2 7
8.9%
8 6
7.6%
6 5
6.3%
, 4
 
5.1%
4 4
 
5.1%
Other values (4) 4
 
5.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
16.9%
5 12
16.9%
1 9
12.7%
7 9
12.7%
3 7
9.9%
2 7
9.9%
8 6
8.5%
6 5
7.0%
4 4
 
5.6%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
15.8%
5 12
15.8%
1 9
11.8%
7 9
11.8%
3 7
9.2%
2 7
9.2%
8 6
7.9%
6 5
6.6%
, 4
 
5.3%
4 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
15.8%
5 12
15.8%
1 9
11.8%
7 9
11.8%
3 7
9.2%
2 7
9.2%
8 6
7.9%
6 5
6.6%
, 4
 
5.3%
4 4
 
5.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:27.748619image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row풍향동
2nd row2,674
3rd row5,393
4th row22
5th row2
ValueCountFrequency (%)
0 8
24.2%
2 2
 
6.1%
40 1
 
3.0%
49 1
 
3.0%
5,405 1
 
3.0%
2,683 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
9 1
 
3.0%
4 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:49:28.702920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.6%
2 11
16.2%
3 8
11.8%
5 7
10.3%
4 6
8.8%
9 5
7.4%
1 5
7.4%
, 4
 
5.9%
6 3
 
4.4%
8 2
 
2.9%
Other values (5) 5
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
88.2%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.0%
2 11
18.3%
3 8
13.3%
5 7
11.7%
4 6
10.0%
9 5
8.3%
1 5
8.3%
6 3
 
5.0%
8 2
 
3.3%
7 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 (%)
0 12
18.5%
2 11
16.9%
3 8
12.3%
5 7
10.8%
4 6
9.2%
9 5
7.7%
1 5
7.7%
, 4
 
6.2%
6 3
 
4.6%
8 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
18.5%
2 11
16.9%
3 8
12.3%
5 7
10.8%
4 6
9.2%
9 5
7.7%
1 5
7.7%
, 4
 
6.2%
6 3
 
4.6%
8 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:29.022442image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row문화동
2nd row9,584
3rd row20,122
4th row33
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 3
 
9.1%
33 2
 
6.1%
106 1
 
3.0%
20,122 1
 
3.0%
9,584 1
 
3.0%
9,604 1
 
3.0%
9 1
 
3.0%
20 1
 
3.0%
73 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:49:29.749833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.9%
1 13
17.6%
3 8
10.8%
2 7
9.5%
8 6
8.1%
9 5
 
6.8%
6 4
 
5.4%
7 4
 
5.4%
, 4
 
5.4%
4 3
 
4.1%
Other values (4) 6
8.1%

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 (%)
0 14
20.9%
1 13
19.4%
3 8
11.9%
2 7
10.4%
8 6
9.0%
9 5
 
7.5%
6 4
 
6.0%
7 4
 
6.0%
4 3
 
4.5%
5 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
19.7%
1 13
18.3%
3 8
11.3%
2 7
9.9%
8 6
8.5%
9 5
 
7.0%
6 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
4 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 (%)
0 14
19.7%
1 13
18.3%
3 8
11.3%
2 7
9.9%
8 6
8.5%
9 5
 
7.0%
6 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
4 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:30.267299image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row문흥1동
2nd row6,386
3rd row15,315
4th row22
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
2 2
 
6.1%
9 2
 
6.1%
89 1
 
3.0%
154 1
 
3.0%
15,290 1
 
3.0%
6,396 1
 
3.0%
25 1
 
3.0%
10 1
 
3.0%
5 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:49:31.267468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
2 9
12.2%
5 9
12.2%
6 8
10.8%
1 8
10.8%
9 6
8.1%
, 4
 
5.4%
3 4
 
5.4%
8 4
 
5.4%
4 4
 
5.4%
Other values (5) 7
9.5%

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 (%)
0 11
16.9%
2 9
13.8%
5 9
13.8%
6 8
12.3%
1 8
12.3%
9 6
9.2%
3 4
 
6.2%
8 4
 
6.2%
4 4
 
6.2%
7 2
 
3.1%
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 (%)
0 11
15.5%
2 9
12.7%
5 9
12.7%
6 8
11.3%
1 8
11.3%
9 6
8.5%
, 4
 
5.6%
3 4
 
5.6%
8 4
 
5.6%
4 4
 
5.6%
Other values (2) 4
 
5.6%
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 (%)
0 11
15.5%
2 9
12.7%
5 9
12.7%
6 8
11.3%
1 8
11.3%
9 6
8.5%
, 4
 
5.6%
3 4
 
5.6%
8 4
 
5.6%
4 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:31.635727image/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 row문흥2동
2nd row7,381
3rd row15,203
4th row21
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 3
 
9.1%
21 2
 
6.1%
89 1
 
3.0%
15,203 1
 
3.0%
7,381 1
 
3.0%
7,375 1
 
3.0%
26 1
 
3.0%
6 1
 
3.0%
9 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:49:32.426401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.4%
7 11
15.1%
5 9
12.3%
1 8
11.0%
2 6
8.2%
8 6
8.2%
6 4
 
5.5%
3 4
 
5.5%
, 4
 
5.5%
9 3
 
4.1%
Other values (5) 6
8.2%

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 12
18.8%
7 11
17.2%
5 9
14.1%
1 8
12.5%
2 6
9.4%
8 6
9.4%
6 4
 
6.2%
3 4
 
6.2%
9 3
 
4.7%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
7 11
15.7%
5 9
12.9%
1 8
11.4%
2 6
8.6%
8 6
8.6%
6 4
 
5.7%
3 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.1%
7 11
15.7%
5 9
12.9%
1 8
11.4%
2 6
8.6%
8 6
8.6%
6 4
 
5.7%
3 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:32.788554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
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 row두암1동
2nd row3,943
3rd row7,435
4th row13
5th row9
ValueCountFrequency (%)
0 7
21.2%
45 2
 
6.1%
1 2
 
6.1%
9 2
 
6.1%
49 1
 
3.0%
58 1
 
3.0%
7,405 1
 
3.0%
3,947 1
 
3.0%
30 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:49:33.657478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.9%
0 11
15.5%
4 9
12.7%
1 8
11.3%
9 5
7.0%
5 5
7.0%
2 5
7.0%
, 4
 
5.6%
8 4
 
5.6%
7 3
 
4.2%
Other values (4) 5
7.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
19.4%
0 11
17.7%
4 9
14.5%
1 8
12.9%
9 5
8.1%
5 5
8.1%
2 5
8.1%
8 4
 
6.5%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
17.6%
0 11
16.2%
4 9
13.2%
1 8
11.8%
9 5
7.4%
5 5
7.4%
2 5
7.4%
, 4
 
5.9%
8 4
 
5.9%
7 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 (%)
3 12
17.6%
0 11
16.2%
4 9
13.2%
1 8
11.8%
9 5
7.4%
5 5
7.4%
2 5
7.4%
, 4
 
5.9%
8 4
 
5.9%
7 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:34.017324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row두암2동
2nd row7,619
3rd row15,482
4th row50
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
50 3
 
9.1%
9 2
 
6.1%
103 1
 
3.0%
71 1
 
3.0%
15,430 1
 
3.0%
7,608 1
 
3.0%
2 1
 
3.0%
52 1
 
3.0%
11 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:49:34.762250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.2%
1 11
14.3%
5 7
9.1%
6 7
9.1%
7 6
7.8%
4 5
 
6.5%
2 5
 
6.5%
9 4
 
5.2%
, 4
 
5.2%
8 4
 
5.2%
Other values (5) 10
13.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
87.0%
Other Punctuation 4
 
5.2%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
20.9%
1 11
16.4%
5 7
10.4%
6 7
10.4%
7 6
9.0%
4 5
 
7.5%
2 5
 
7.5%
9 4
 
6.0%
8 4
 
6.0%
3 4
 
6.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
18.9%
1 11
14.9%
5 7
9.5%
6 7
9.5%
7 6
8.1%
4 5
 
6.8%
2 5
 
6.8%
9 4
 
5.4%
, 4
 
5.4%
8 4
 
5.4%
Other values (2) 7
9.5%
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 (%)
0 14
18.9%
1 11
14.9%
5 7
9.5%
6 7
9.5%
7 6
8.1%
4 5
 
6.8%
2 5
 
6.8%
9 4
 
5.4%
, 4
 
5.4%
8 4
 
5.4%
Other values (2) 7
9.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:35.150738image/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 row두암3동
2nd row7,653
3rd row12,796
4th row40
5th row8
ValueCountFrequency (%)
0 6
18.2%
2 3
 
9.1%
53 3
 
9.1%
8 2
 
6.1%
38 2
 
6.1%
7,653 2
 
6.1%
1 1
 
3.0%
123 1
 
3.0%
81 1
 
3.0%
18 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:49:35.907976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
17.6%
1 10
13.5%
0 8
10.8%
8 7
9.5%
2 7
9.5%
5 6
8.1%
7 6
8.1%
, 4
 
5.4%
6 3
 
4.1%
4 3
 
4.1%
Other values (5) 7
9.5%

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 (%)
3 13
20.0%
1 10
15.4%
0 8
12.3%
8 7
10.8%
2 7
10.8%
5 6
9.2%
7 6
9.2%
6 3
 
4.6%
4 3
 
4.6%
9 2
 
3.1%
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 (%)
3 13
18.3%
1 10
14.1%
0 8
11.3%
8 7
9.9%
2 7
9.9%
5 6
8.5%
7 6
8.5%
, 4
 
5.6%
6 3
 
4.2%
4 3
 
4.2%
Other values (2) 4
 
5.6%
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 (%)
3 13
18.3%
1 10
14.1%
0 8
11.3%
8 7
9.9%
2 7
9.9%
5 6
8.5%
7 6
8.5%
, 4
 
5.6%
6 3
 
4.2%
4 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:36.263722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row삼각동
2nd row5,983
3rd row13,589
4th row29
5th row4
ValueCountFrequency (%)
0 8
24.2%
29 2
 
6.1%
4 2
 
6.1%
65 1
 
3.0%
13,589 1
 
3.0%
89 1
 
3.0%
5,994 1
 
3.0%
1 1
 
3.0%
11 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:49:37.018323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 11
15.7%
5 10
14.3%
0 9
12.9%
1 8
11.4%
3 6
8.6%
4 5
7.1%
2 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
7 3
 
4.3%
Other values (4) 6
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 11
17.5%
5 10
15.9%
0 9
14.3%
1 8
12.7%
3 6
9.5%
4 5
7.9%
2 4
 
6.3%
6 4
 
6.3%
7 3
 
4.8%
8 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
9 11
16.4%
5 10
14.9%
0 9
13.4%
1 8
11.9%
3 6
9.0%
4 5
7.5%
2 4
 
6.0%
, 4
 
6.0%
6 4
 
6.0%
7 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 (%)
9 11
16.4%
5 10
14.9%
0 9
13.4%
1 8
11.9%
3 6
9.0%
4 5
7.5%
2 4
 
6.0%
, 4
 
6.0%
6 4
 
6.0%
7 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:37.450280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row일곡동
2nd row11,461
3rd row28,829
4th row24
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 2
 
6.1%
24 2
 
6.1%
9 2
 
6.1%
170 1
 
3.0%
28,829 1
 
3.0%
259 1
 
3.0%
11,470 1
 
3.0%
85 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:49:38.316667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.1%
0 11
13.4%
2 11
13.4%
4 9
11.0%
9 6
7.3%
8 6
7.3%
7 5
 
6.1%
3 5
 
6.1%
5 4
 
4.9%
, 4
 
4.9%
Other values (5) 7
8.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
18.9%
0 11
14.9%
2 11
14.9%
4 9
12.2%
9 6
8.1%
8 6
8.1%
7 5
 
6.8%
3 5
 
6.8%
5 4
 
5.4%
6 3
 
4.1%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.7%
0 11
13.9%
2 11
13.9%
4 9
11.4%
9 6
7.6%
8 6
7.6%
7 5
 
6.3%
3 5
 
6.3%
5 4
 
5.1%
, 4
 
5.1%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
17.7%
0 11
13.9%
2 11
13.9%
4 9
11.4%
9 6
7.6%
8 6
7.6%
7 5
 
6.3%
3 5
 
6.3%
5 4
 
5.1%
, 4
 
5.1%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:38.679989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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 row매곡동
2nd row5,489
3rd row13,538
4th row14
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
80 1
 
3.0%
15 1
 
3.0%
13,530 1
 
3.0%
5,498 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
9 1
 
3.0%
3 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:49:39.811360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 12
17.1%
0 10
14.3%
1 8
11.4%
4 7
10.0%
3 6
8.6%
8 5
7.1%
7 4
 
5.7%
2 4
 
5.7%
, 4
 
5.7%
9 4
 
5.7%
Other values (5) 6
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 12
19.4%
0 10
16.1%
1 8
12.9%
4 7
11.3%
3 6
9.7%
8 5
8.1%
7 4
 
6.5%
2 4
 
6.5%
9 4
 
6.5%
6 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 12
17.9%
0 10
14.9%
1 8
11.9%
4 7
10.4%
3 6
9.0%
8 5
7.5%
7 4
 
6.0%
2 4
 
6.0%
, 4
 
6.0%
9 4
 
6.0%
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 (%)
5 12
17.9%
0 10
14.9%
1 8
11.9%
4 7
10.4%
3 6
9.0%
8 5
7.5%
7 4
 
6.0%
2 4
 
6.0%
, 4
 
6.0%
9 4
 
6.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:40.396453image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row오치1동
2nd row5,377
3rd row10,423
4th row59
5th row10
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
10 2
 
6.1%
70 1
 
3.0%
72 1
 
3.0%
10,400 1
 
3.0%
5,388 1
 
3.0%
23 1
 
3.0%
11 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:49:41.107705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
19.7%
1 10
13.2%
5 8
10.5%
3 8
10.5%
4 6
 
7.9%
2 6
 
7.9%
7 6
 
7.9%
, 4
 
5.3%
6 4
 
5.3%
9 2
 
2.6%
Other values (5) 7
9.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
22.4%
1 10
14.9%
5 8
11.9%
3 8
11.9%
4 6
 
9.0%
2 6
 
9.0%
7 6
 
9.0%
6 4
 
6.0%
9 2
 
3.0%
8 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
20.5%
1 10
13.7%
5 8
11.0%
3 8
11.0%
4 6
 
8.2%
2 6
 
8.2%
7 6
 
8.2%
, 4
 
5.5%
6 4
 
5.5%
9 2
 
2.7%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
20.5%
1 10
13.7%
5 8
11.0%
3 8
11.0%
4 6
 
8.2%
2 6
 
8.2%
7 6
 
8.2%
, 4
 
5.5%
6 4
 
5.5%
9 2
 
2.7%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:41.540992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row오치2동
2nd row6,887
3rd row11,997
4th row34
5th row10
ValueCountFrequency (%)
0 6
18.2%
37 2
 
6.1%
1 2
 
6.1%
48 2
 
6.1%
10 2
 
6.1%
62 1
 
3.0%
139 1
 
3.0%
11,949 1
 
3.0%
6,866 1
 
3.0%
21 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:49:42.590100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.7%
0 9
11.5%
3 9
11.5%
7 6
7.7%
6 6
7.7%
4 6
7.7%
2 6
7.7%
8 5
 
6.4%
9 5
 
6.4%
, 4
 
5.1%
Other values (5) 9
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.1%
0 9
13.2%
3 9
13.2%
7 6
8.8%
6 6
8.8%
4 6
8.8%
2 6
8.8%
8 5
 
7.4%
9 5
 
7.4%
5 3
 
4.4%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.3%
0 9
12.0%
3 9
12.0%
7 6
8.0%
6 6
8.0%
4 6
8.0%
2 6
8.0%
8 5
 
6.7%
9 5
 
6.7%
, 4
 
5.3%
Other values (2) 6
8.0%
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 13
17.3%
0 9
12.0%
3 9
12.0%
7 6
8.0%
6 6
8.0%
4 6
8.0%
2 6
8.0%
8 5
 
6.7%
9 5
 
6.7%
, 4
 
5.3%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:42.938911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8787879
Min length1

Characters and Unicode

Total characters62
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

Unique14 ?
Unique (%)42.4%

Sample

1st row석곡동
2nd row1,338
3rd row2,400
4th row10
5th row3
ValueCountFrequency (%)
0 7
21.2%
5 4
12.1%
3 3
 
9.1%
1 3
 
9.1%
10 2
 
6.1%
9 2
 
6.1%
13 1
 
3.0%
11 1
 
3.0%
1,335 1
 
3.0%
8 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T09:49:43.785602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
21.0%
0 11
17.7%
3 9
14.5%
5 6
9.7%
, 4
 
6.5%
8 4
 
6.5%
2 4
 
6.5%
- 3
 
4.8%
9 2
 
3.2%
6 1
 
1.6%
Other values (5) 5
 
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
83.9%
Other Punctuation 4
 
6.5%
Dash Punctuation 3
 
4.8%
Other Letter 3
 
4.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
25.0%
0 11
21.2%
3 9
17.3%
5 6
11.5%
8 4
 
7.7%
2 4
 
7.7%
9 2
 
3.8%
6 1
 
1.9%
4 1
 
1.9%
7 1
 
1.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 59
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
22.0%
0 11
18.6%
3 9
15.3%
5 6
10.2%
, 4
 
6.8%
8 4
 
6.8%
2 4
 
6.8%
- 3
 
5.1%
9 2
 
3.4%
6 1
 
1.7%
Other values (2) 2
 
3.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 59
95.2%
Hangul 3
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
22.0%
0 11
18.6%
3 9
15.3%
5 6
10.2%
, 4
 
6.8%
8 4
 
6.8%
2 4
 
6.8%
- 3
 
5.1%
9 2
 
3.4%
6 1
 
1.7%
Other values (2) 2
 
3.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:44.144465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
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

Unique25 ?
Unique (%)75.8%

Sample

1st row건국동
2nd row9,002
3rd row21,739
4th row57
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
10 2
 
6.1%
16 2
 
6.1%
1 2
 
6.1%
9,002 1
 
3.0%
102 1
 
3.0%
228 1
 
3.0%
21,726 1
 
3.0%
8,986 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:49:44.852014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
19.3%
1 16
19.3%
2 10
12.0%
6 7
8.4%
7 5
 
6.0%
3 5
 
6.0%
5 5
 
6.0%
8 5
 
6.0%
9 4
 
4.8%
, 4
 
4.8%
Other values (4) 6
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
88.0%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
21.9%
1 16
21.9%
2 10
13.7%
6 7
9.6%
7 5
 
6.8%
3 5
 
6.8%
5 5
 
6.8%
8 5
 
6.8%
9 4
 
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 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
20.0%
1 16
20.0%
2 10
12.5%
6 7
8.8%
7 5
 
6.2%
3 5
 
6.2%
5 5
 
6.2%
8 5
 
6.2%
9 4
 
5.0%
, 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
20.0%
1 16
20.0%
2 10
12.5%
6 7
8.8%
7 5
 
6.2%
3 5
 
6.2%
5 5
 
6.2%
8 5
 
6.2%
9 4
 
5.0%
, 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:45.173493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6666667
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row양산동
2nd row16,280
3rd row36,961
4th row69
5th row16
ValueCountFrequency (%)
0 7
21.2%
18 2
 
6.1%
16 2
 
6.1%
209 1
 
3.0%
69 1
 
3.0%
36,961 1
 
3.0%
36,815 1
 
3.0%
16,258 1
 
3.0%
1 1
 
3.0%
146 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:49:46.027504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
20.5%
0 11
12.5%
6 11
12.5%
8 10
11.4%
2 8
9.1%
9 8
9.1%
4 4
 
4.5%
, 4
 
4.5%
3 4
 
4.5%
5 3
 
3.4%
Other values (5) 7
 
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
23.1%
0 11
14.1%
6 11
14.1%
8 10
12.8%
2 8
10.3%
9 8
10.3%
4 4
 
5.1%
3 4
 
5.1%
5 3
 
3.8%
7 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 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
21.2%
0 11
12.9%
6 11
12.9%
8 10
11.8%
2 8
9.4%
9 8
9.4%
4 4
 
4.7%
, 4
 
4.7%
3 4
 
4.7%
5 3
 
3.5%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
21.2%
0 11
12.9%
6 11
12.9%
8 10
11.8%
2 8
9.4%
9 8
9.4%
4 4
 
4.7%
, 4
 
4.7%
3 4
 
4.7%
5 3
 
3.5%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:49:46.367211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row신용동
2nd row11,795
3rd row29,231
4th row17
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
10 2
 
6.1%
6 2
 
6.1%
339 1
 
3.0%
29,148 1
 
3.0%
11,789 1
 
3.0%
4 1
 
3.0%
83 1
 
3.0%
163 1
 
3.0%
90 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:49:47.253695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.8%
0 10
11.9%
9 8
 
9.5%
6 8
 
9.5%
2 7
 
8.3%
3 6
 
7.1%
8 6
 
7.1%
, 4
 
4.8%
7 4
 
4.8%
4 3
 
3.6%
Other values (5) 8
 
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
88.1%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
27.0%
0 10
13.5%
9 8
 
10.8%
6 8
 
10.8%
2 7
 
9.5%
3 6
 
8.1%
8 6
 
8.1%
7 4
 
5.4%
4 3
 
4.1%
5 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
24.7%
0 10
12.3%
9 8
 
9.9%
6 8
 
9.9%
2 7
 
8.6%
3 6
 
7.4%
8 6
 
7.4%
, 4
 
4.9%
7 4
 
4.9%
4 3
 
3.7%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
24.7%
0 10
12.3%
9 8
 
9.9%
6 8
 
9.9%
2 7
 
8.6%
3 6
 
7.4%
8 6
 
7.4%
, 4
 
4.9%
7 4
 
4.9%
4 3
 
3.7%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
0<NA>행정기관 :<NA>광주광역시 북구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2023.03.07<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.02 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><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 계중흥1동중흥2동중흥3동중앙동임동신안동<NA>용봉동운암1동운암2동운암3동동림동우산동풍향동문화동문흥1동문흥2동두암1동두암2동두암3동삼각동일곡동매곡동오치1동오치2동석곡동건국동양산동신용동
3<NA>전월말세대수<NA><NA><NA>198,0682,8844,3923,6412,2864,6237,461<NA>17,8217,4075,9885,4549,8887,3712,6749,5846,3867,3813,9437,6197,6535,98311,4615,4895,3776,8871,3389,00216,28011,795
4<NA>전월말인구수<NA><NA><NA>424,3264,5408,4146,5353,9349,17012,479<NA>37,58318,84311,47213,37022,81114,7225,39320,12215,31515,2037,43515,48212,79613,58928,82913,53810,42311,9972,40021,73936,96129,231
5<NA>전월말거주불명자수<NA><NA><NA>1,080473842433477<NA>82235236355722332221135040292414593410576917
6<NA>전월말재외국민등록자수<NA><NA><NA>231162651<NA>2020916872895998412510103101610
7<NA>증 가 요 인전 입<NA>4,779411371476383212<NA>5821851081031445051052131261658313612315425914212010115210268249
8<NA><NA><NA>남자<NA>2,4401971873644117<NA>27196624275250551168078386652791257563535107149129
9<NA><NA><NA>여자<NA>2,339226660273995<NA>31189466169255509746874570717513467574810103119120
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: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
25<NA><NA>말소<NA><NA>5000000<NA>0100000000011020000000
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>252-161223-1-2016<NA>106-2-42613292010-64-110119911-21-3-16-22-6
29<NA>인구수증감<NA><NA><NA>-313-16-15177-218<NA>32-37-37-26-42365129-25-26-30-52-181-85-8-23-48-13-13-146-83
30<NA>거주불명자수증감<NA><NA><NA>-38-2-20-3-4-2<NA>-1-10-1-1-2-10-20-1-2-2001-4-1-1-1-1-4
31<NA>금월말세대수<NA><NA><NA>198,3202,8684,4043,6642,2854,6037,477<NA>17,9277,4055,9845,4569,8947,5032,6839,6046,3967,3753,9477,6087,6535,99411,4705,4985,3886,8661,3358,98616,25811,789
32<NA>금월말인구수<NA><NA><NA>424,0134,5248,3996,5523,9419,14912,487<NA>37,61518,80611,43513,34422,76915,0875,40520,13115,29015,1777,40515,43012,77813,59028,74413,53010,40011,9492,38721,72636,81529,148
33<NA>금월말거주불명자수<NA><NA><NA>1,042453642403075<NA>8122523534552133202112483829241555339566813
34<NA>금월말재외국민등록자수<NA><NA><NA>231162651<NA>2021916782895998412410103101610

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: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34# duplicates
0<NA>국외<NA><NA>0000000<NA>00000000000000000000002
1<NA>기타<NA><NA>0000000<NA>00000000000000000000002