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

Description2022-04-13
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 09:39:45.318029
Analysis finished2024-02-10 09:39:47.232007
Duration1.91 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
2024-02-10T09:39:47.550422image/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%
2024-02-10T09:39:48.795730image/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
2024-02-10T09:39:49.180421image/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%
2024-02-10T09:39:50.307801image/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
2024-02-10T09:39:50.884208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

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

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 북구
2nd row2022.02 현재
3rd row
4th row남자
5th row여자
ValueCountFrequency (%)
2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
북구 1
7.1%
2022.02 1
7.1%
현재 1
7.1%
2024-02-10T09:39:51.965958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
2 4
 
9.8%
4
 
9.8%
4
 
9.8%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (9) 11
26.8%

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 4
66.7%
0 2
33.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

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

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
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 (%)
2 4
40.0%
3
30.0%
0 2
20.0%
. 1
 
10.0%

Most occurring blocks

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

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
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 (%)
2 4
40.0%
3
30.0%
0 2
20.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:39:52.293852image/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%
2024-02-10T09:39:53.091025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:53.577773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.969697
Min length1

Characters and Unicode

Total characters131
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

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row195,811
3rd row426,877
4th row1,298
5th row218
ValueCountFrequency (%)
0 5
 
14.7%
2,379 2
 
5.9%
3,086 1
 
2.9%
2,994 1
 
2.9%
1,280 1
 
2.9%
427,139 1
 
2.9%
196,446 1
 
2.9%
18 1
 
2.9%
262 1
 
2.9%
635 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:39:54.654375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 20
15.3%
, 18
13.7%
1 16
12.2%
0 11
8.4%
6 11
8.4%
8 11
8.4%
3 10
7.6%
9 10
7.6%
4 10
7.6%
7 6
 
4.6%
Other values (5) 8
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 108
82.4%
Other Punctuation 18
 
13.7%
Space Separator 2
 
1.5%
Other Letter 2
 
1.5%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 20
18.5%
1 16
14.8%
0 11
10.2%
6 11
10.2%
8 11
10.2%
3 10
9.3%
9 10
9.3%
4 10
9.3%
7 6
 
5.6%
5 3
 
2.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 129
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 20
15.5%
, 18
14.0%
1 16
12.4%
0 11
8.5%
6 11
8.5%
8 11
8.5%
3 10
7.8%
9 10
7.8%
4 10
7.8%
7 6
 
4.7%
Other values (3) 6
 
4.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 129
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 20
15.5%
, 18
14.0%
1 16
12.4%
0 11
8.5%
6 11
8.5%
8 11
8.5%
3 10
7.8%
9 10
7.8%
4 10
7.8%
7 6
 
4.7%
Other values (3) 6
 
4.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:55.051552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row중흥1동
2nd row3,002
3rd row4,793
4th row59
5th row0
ValueCountFrequency (%)
0 8
24.2%
39 2
 
6.1%
1 2
 
6.1%
2 2
 
6.1%
4,793 1
 
3.0%
28 1
 
3.0%
33 1
 
3.0%
4,791 1
 
3.0%
3,007 1
 
3.0%
5 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:39:56.055016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.6%
3 10
14.7%
2 9
13.2%
7 7
10.3%
9 5
 
7.4%
1 5
 
7.4%
, 4
 
5.9%
8 4
 
5.9%
5 3
 
4.4%
4 2
 
2.9%
Other values (4) 5
 
7.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
23.7%
3 10
16.9%
2 9
15.3%
7 7
11.9%
9 5
 
8.5%
1 5
 
8.5%
8 4
 
6.8%
5 3
 
5.1%
4 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
21.5%
3 10
15.4%
2 9
13.8%
7 7
10.8%
9 5
 
7.7%
1 5
 
7.7%
, 4
 
6.2%
8 4
 
6.2%
5 3
 
4.6%
4 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 14
21.5%
3 10
15.4%
2 9
13.8%
7 7
10.8%
9 5
 
7.7%
1 5
 
7.7%
, 4
 
6.2%
8 4
 
6.2%
5 3
 
4.6%
4 2
 
3.1%
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
2024-02-10T09:39:56.406525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique23 ?
Unique (%)69.7%

Sample

1st row중흥2동
2nd row3,787
3rd row6,858
4th row65
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 2
 
6.1%
97 1
 
3.0%
94 1
 
3.0%
7,569 1
 
3.0%
4,042 1
 
3.0%
2 1
 
3.0%
711 1
 
3.0%
255 1
 
3.0%
5 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:39:57.523248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.3%
4 9
11.7%
6 9
11.7%
7 8
10.4%
5 8
10.4%
9 6
7.8%
1 5
6.5%
3 5
6.5%
, 4
 
5.2%
8 4
 
5.2%
Other values (5) 8
10.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
15.9%
4 9
13.0%
6 9
13.0%
7 8
11.6%
5 8
11.6%
9 6
8.7%
1 5
7.2%
3 5
7.2%
8 4
 
5.8%
2 4
 
5.8%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.9%
4 9
12.2%
6 9
12.2%
7 8
10.8%
5 8
10.8%
9 6
8.1%
1 5
6.8%
3 5
6.8%
, 4
 
5.4%
8 4
 
5.4%
Other values (2) 5
6.8%
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 11
14.9%
4 9
12.2%
6 9
12.2%
7 8
10.8%
5 8
10.8%
9 6
8.1%
1 5
6.8%
3 5
6.8%
, 4
 
5.4%
8 4
 
5.4%
Other values (2) 5
6.8%
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
2024-02-10T09:39:57.950222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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 row중흥3동
2nd row2,847
3rd row4,818
4th row43
5th row3
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
2 2
 
6.1%
3 2
 
6.1%
34 1
 
3.0%
43 1
 
3.0%
64 1
 
3.0%
5,508 1
 
3.0%
3,133 1
 
3.0%
690 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:39:59.069060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 14
17.9%
0 10
12.8%
4 10
12.8%
1 8
10.3%
8 8
10.3%
6 5
 
6.4%
2 5
 
6.4%
7 4
 
5.1%
5 4
 
5.1%
, 4
 
5.1%
Other values (5) 6
7.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 14
20.0%
0 10
14.3%
4 10
14.3%
1 8
11.4%
8 8
11.4%
6 5
 
7.1%
2 5
 
7.1%
7 4
 
5.7%
5 4
 
5.7%
9 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 14
18.7%
0 10
13.3%
4 10
13.3%
1 8
10.7%
8 8
10.7%
6 5
 
6.7%
2 5
 
6.7%
7 4
 
5.3%
5 4
 
5.3%
, 4
 
5.3%
Other values (2) 3
 
4.0%
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 (%)
3 14
18.7%
0 10
13.3%
4 10
13.3%
1 8
10.7%
8 8
10.7%
6 5
 
6.7%
2 5
 
6.7%
7 4
 
5.3%
5 4
 
5.3%
, 4
 
5.3%
Other values (2) 3
 
4.0%
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
2024-02-10T09:39:59.457627image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row중앙동
2nd row2,030
3rd row3,051
4th row53
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 3
 
9.1%
53 2
 
6.1%
47 2
 
6.1%
21 1
 
3.0%
85 1
 
3.0%
2,015 1
 
3.0%
15 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:40:00.482610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.4%
3 9
13.4%
4 8
11.9%
5 8
11.9%
1 7
10.4%
2 6
9.0%
, 4
 
6.0%
8 3
 
4.5%
7 2
 
3.0%
6 2
 
3.0%
Other values (5) 5
 
7.5%

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 (%)
0 13
22.0%
3 9
15.3%
4 8
13.6%
5 8
13.6%
1 7
11.9%
2 6
10.2%
8 3
 
5.1%
7 2
 
3.4%
6 2
 
3.4%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.3%
3 9
14.1%
4 8
12.5%
5 8
12.5%
1 7
10.9%
2 6
9.4%
, 4
 
6.2%
8 3
 
4.7%
7 2
 
3.1%
6 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 64
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
20.3%
3 9
14.1%
4 8
12.5%
5 8
12.5%
1 7
10.9%
2 6
9.4%
, 4
 
6.2%
8 3
 
4.7%
7 2
 
3.1%
6 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct22
Distinct (%)64.7%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:40:00.923314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1470588
Min length1

Characters and Unicode

Total characters73
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)52.9%

Sample

1st row출력일자 :
2nd row임동
3rd row4,478
4th row9,179
5th row37
ValueCountFrequency (%)
0 8
22.9%
5 4
 
11.4%
86 2
 
5.7%
37 2
 
5.7%
88 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
4,564 1
 
2.9%
35 1
 
2.9%
31 1
 
2.9%
Other values (13) 13
37.1%
2024-02-10T09:40:02.029119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 10
13.7%
0 8
11.0%
8 8
11.0%
3 7
9.6%
4 7
9.6%
9 7
9.6%
6 5
6.8%
1 4
 
5.5%
, 4
 
5.5%
7 4
 
5.5%
Other values (9) 9
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
83.6%
Other Letter 6
 
8.2%
Other Punctuation 5
 
6.8%
Space Separator 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 10
16.4%
0 8
13.1%
8 8
13.1%
3 7
11.5%
4 7
11.5%
9 7
11.5%
6 5
8.2%
1 4
 
6.6%
7 4
 
6.6%
2 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%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 67
91.8%
Hangul 6
 
8.2%

Most frequent character per script

Common
ValueCountFrequency (%)
5 10
14.9%
0 8
11.9%
8 8
11.9%
3 7
10.4%
4 7
10.4%
9 7
10.4%
6 5
7.5%
1 4
 
6.0%
, 4
 
6.0%
7 4
 
6.0%
Other values (3) 3
 
4.5%
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 67
91.8%
Hangul 6
 
8.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 10
14.9%
0 8
11.9%
8 8
11.9%
3 7
10.4%
4 7
10.4%
9 7
10.4%
6 5
7.5%
1 4
 
6.0%
, 4
 
6.0%
7 4
 
6.0%
Other values (3) 3
 
4.5%
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
2024-02-10T09:40:02.502030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
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 row7,224
3rd row12,389
4th row85
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 3
 
9.1%
72 2
 
6.1%
139 1
 
3.0%
130 1
 
3.0%
12,361 1
 
3.0%
7,216 1
 
3.0%
28 1
 
3.0%
8 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:03.404670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.0%
2 11
13.9%
0 10
12.7%
9 8
10.1%
3 6
 
7.6%
8 6
 
7.6%
7 5
 
6.3%
6 5
 
6.3%
, 4
 
5.1%
- 3
 
3.8%
Other values (5) 6
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
87.3%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.7%
2 11
15.9%
0 10
14.5%
9 8
11.6%
3 6
 
8.7%
8 6
 
8.7%
7 5
 
7.2%
6 5
 
7.2%
4 2
 
2.9%
5 1
 
1.4%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.7%
2 11
14.5%
0 10
13.2%
9 8
10.5%
3 6
 
7.9%
8 6
 
7.9%
7 5
 
6.6%
6 5
 
6.6%
, 4
 
5.3%
- 3
 
3.9%
Other values (2) 3
 
3.9%
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 (%)
1 15
19.7%
2 11
14.5%
0 10
13.2%
9 8
10.5%
3 6
 
7.9%
8 6
 
7.9%
7 5
 
6.6%
6 5
 
6.6%
, 4
 
5.3%
- 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-03-09 00:00:00
Maximum2022-03-09 00:00:00
2024-02-10T09:40:03.917436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:40:04.342775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:04.747665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7272727
Min length1

Characters and Unicode

Total characters90
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 row용봉동
2nd row17,818
3rd row38,573
4th row124
5th row18
ValueCountFrequency (%)
0 7
21.2%
22 2
 
6.1%
18 2
 
6.1%
364 1
 
3.0%
124 1
 
3.0%
38,573 1
 
3.0%
38,475 1
 
3.0%
17,853 1
 
3.0%
1 1
 
3.0%
98 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:40:05.560540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
14.4%
0 12
13.3%
8 12
13.3%
3 10
11.1%
2 9
10.0%
4 8
8.9%
7 6
6.7%
5 5
 
5.6%
6 4
 
4.4%
, 4
 
4.4%
Other values (5) 7
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
91.1%
Other Punctuation 4
 
4.4%
Other Letter 3
 
3.3%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
15.9%
0 12
14.6%
8 12
14.6%
3 10
12.2%
2 9
11.0%
4 8
9.8%
7 6
7.3%
5 5
 
6.1%
6 4
 
4.9%
9 3
 
3.7%
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 87
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
14.9%
0 12
13.8%
8 12
13.8%
3 10
11.5%
2 9
10.3%
4 8
9.2%
7 6
6.9%
5 5
 
5.7%
6 4
 
4.6%
, 4
 
4.6%
Other values (2) 4
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 87
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
14.9%
0 12
13.8%
8 12
13.8%
3 10
11.5%
2 9
10.3%
4 8
9.2%
7 6
6.9%
5 5
 
5.7%
6 4
 
4.6%
, 4
 
4.6%
Other values (2) 4
 
4.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:06.141934image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row운암1동
2nd row7,442
3rd row19,345
4th row30
5th row18
ValueCountFrequency (%)
0 6
 
18.2%
12 2
 
6.1%
18 2
 
6.1%
56 1
 
3.0%
30 1
 
3.0%
102 1
 
3.0%
19,332 1
 
3.0%
7,454 1
 
3.0%
2 1
 
3.0%
13 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:40:07.263154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
22.2%
0 10
12.3%
2 8
9.9%
4 7
 
8.6%
3 6
 
7.4%
5 6
 
7.4%
8 5
 
6.2%
9 4
 
4.9%
7 4
 
4.9%
6 4
 
4.9%
Other values (5) 9
11.1%

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 18
25.0%
0 10
13.9%
2 8
11.1%
4 7
 
9.7%
3 6
 
8.3%
5 6
 
8.3%
8 5
 
6.9%
9 4
 
5.6%
7 4
 
5.6%
6 4
 
5.6%
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 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
23.1%
0 10
12.8%
2 8
10.3%
4 7
 
9.0%
3 6
 
7.7%
5 6
 
7.7%
8 5
 
6.4%
9 4
 
5.1%
7 4
 
5.1%
6 4
 
5.1%
Other values (2) 6
 
7.7%
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 18
23.1%
0 10
12.8%
2 8
10.3%
4 7
 
9.0%
3 6
 
7.7%
5 6
 
7.7%
8 5
 
6.4%
9 4
 
5.1%
7 4
 
5.1%
6 4
 
5.1%
Other values (2) 6
 
7.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:07.665543image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row운암2동
2nd row6,116
3rd row12,025
4th row58
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
58 2
 
6.1%
156 1
 
3.0%
75 1
 
3.0%
12,000 1
 
3.0%
6,131 1
 
3.0%
2 1
 
3.0%
25 1
 
3.0%
15 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:40:08.490943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
17.6%
0 12
16.2%
1 11
14.9%
2 7
9.5%
6 6
8.1%
7 5
 
6.8%
, 4
 
5.4%
8 3
 
4.1%
3 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 (%)
5 13
20.0%
0 12
18.5%
1 11
16.9%
2 7
10.8%
6 6
9.2%
7 5
 
7.7%
8 3
 
4.6%
3 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 (%)
5 13
18.3%
0 12
16.9%
1 11
15.5%
2 7
9.9%
6 6
8.5%
7 5
 
7.0%
, 4
 
5.6%
8 3
 
4.2%
3 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 (%)
5 13
18.3%
0 12
16.9%
1 11
15.5%
2 7
9.9%
6 6
8.5%
7 5
 
7.0%
, 4
 
5.6%
8 3
 
4.2%
3 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: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:09.011038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row운암3동
2nd row5,076
3rd row12,661
4th row31
5th row14
ValueCountFrequency (%)
0 8
24.2%
69 2
 
6.1%
31 2
 
6.1%
5 2
 
6.1%
20 1
 
3.0%
14 1
 
3.0%
73 1
 
3.0%
12,648 1
 
3.0%
5,086 1
 
3.0%
13 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:40:09.753926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.3%
1 13
17.3%
6 9
12.0%
5 7
9.3%
3 7
9.3%
2 5
 
6.7%
9 4
 
5.3%
4 4
 
5.3%
, 4
 
5.3%
7 3
 
4.0%
Other values (5) 6
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.4%
1 13
19.4%
6 9
13.4%
5 7
10.4%
3 7
10.4%
2 5
 
7.5%
9 4
 
6.0%
4 4
 
6.0%
7 3
 
4.5%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.1%
1 13
18.1%
6 9
12.5%
5 7
9.7%
3 7
9.7%
2 5
 
6.9%
9 4
 
5.6%
4 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.1%
1 13
18.1%
6 9
12.5%
5 7
9.7%
3 7
9.7%
2 5
 
6.9%
9 4
 
5.6%
4 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:10.109482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters14
Distinct 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 row동림동
2nd row9,865
3rd row23,332
4th row56
5th row9
ValueCountFrequency (%)
0 7
21.2%
56 2
 
6.1%
132 1
 
3.0%
23,231 1
 
3.0%
9,842 1
 
3.0%
101 1
 
3.0%
23 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
81 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:40:11.059865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
14.1%
1 11
14.1%
0 9
11.5%
9 7
9.0%
3 7
9.0%
4 6
7.7%
8 6
7.7%
6 5
6.4%
5 4
 
5.1%
, 4
 
5.1%
Other values (4) 8
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
88.5%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
15.9%
1 11
15.9%
0 9
13.0%
9 7
10.1%
3 7
10.1%
4 6
8.7%
8 6
8.7%
6 5
7.2%
5 4
 
5.8%
7 3
 
4.3%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
14.7%
1 11
14.7%
0 9
12.0%
9 7
9.3%
3 7
9.3%
4 6
8.0%
8 6
8.0%
6 5
6.7%
5 4
 
5.3%
, 4
 
5.3%
Other values (2) 5
6.7%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
14.7%
1 11
14.7%
0 9
12.0%
9 7
9.3%
3 7
9.3%
4 6
8.0%
8 6
8.0%
6 5
6.7%
5 4
 
5.3%
, 4
 
5.3%
Other values (2) 5
6.7%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:11.440756image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row우산동
2nd row5,638
3rd row10,271
4th row63
5th row9
ValueCountFrequency (%)
0 8
24.2%
63 3
 
9.1%
9 3
 
9.1%
64 1
 
3.0%
2 1
 
3.0%
5,634 1
 
3.0%
32 1
 
3.0%
4 1
 
3.0%
43 1
 
3.0%
23 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:40:12.327027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.7%
3 11
15.3%
6 7
9.7%
1 7
9.7%
2 7
9.7%
4 6
8.3%
9 5
6.9%
5 4
 
5.6%
, 4
 
5.6%
8 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 (%)
0 12
19.0%
3 11
17.5%
6 7
11.1%
1 7
11.1%
2 7
11.1%
4 6
9.5%
9 5
7.9%
5 4
 
6.3%
8 2
 
3.2%
7 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.4%
3 11
15.9%
6 7
10.1%
1 7
10.1%
2 7
10.1%
4 6
8.7%
9 5
7.2%
5 4
 
5.8%
, 4
 
5.8%
8 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 (%)
0 12
17.4%
3 11
15.9%
6 7
10.1%
1 7
10.1%
2 7
10.1%
4 6
8.7%
9 5
7.2%
5 4
 
5.8%
, 4
 
5.8%
8 2
 
2.9%
Other values (2) 4
 
5.8%
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
2024-02-10T09:40:12.743704image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row풍향동
2nd row2,768
3rd row5,731
4th row22
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 3
 
9.1%
54 1
 
3.0%
119 1
 
3.0%
5,699 1
 
3.0%
2,755 1
 
3.0%
2 1
 
3.0%
32 1
 
3.0%
13 1
 
3.0%
41 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:40:13.552351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
15.7%
3 10
14.3%
5 9
12.9%
0 7
10.0%
7 5
7.1%
6 5
7.1%
1 5
7.1%
, 4
 
5.7%
4 4
 
5.7%
9 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 (%)
2 11
18.0%
3 10
16.4%
5 9
14.8%
0 7
11.5%
7 5
8.2%
6 5
8.2%
1 5
8.2%
4 4
 
6.6%
9 3
 
4.9%
8 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 (%)
2 11
16.4%
3 10
14.9%
5 9
13.4%
0 7
10.4%
7 5
7.5%
6 5
7.5%
1 5
7.5%
, 4
 
6.0%
4 4
 
6.0%
9 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 (%)
2 11
16.4%
3 10
14.9%
5 9
13.4%
0 7
10.4%
7 5
7.5%
6 5
7.5%
1 5
7.5%
, 4
 
6.0%
4 4
 
6.0%
9 3
 
4.5%
Other values (2) 4
 
6.0%
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
2024-02-10T09:40:14.014727image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row문화동
2nd row9,757
3rd row20,939
4th row61
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
58 2
 
6.1%
7 2
 
6.1%
162 1
 
3.0%
138 1
 
3.0%
9,735 1
 
3.0%
3 1
 
3.0%
91 1
 
3.0%
22 1
 
3.0%
1 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:40:15.011560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.3%
1 11
13.6%
2 10
12.3%
9 7
8.6%
7 6
7.4%
5 6
7.4%
8 6
7.4%
3 6
7.4%
, 4
 
4.9%
4 3
 
3.7%
Other values (5) 8
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
87.7%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
19.7%
1 11
15.5%
2 10
14.1%
9 7
9.9%
7 6
8.5%
5 6
8.5%
8 6
8.5%
3 6
8.5%
4 3
 
4.2%
6 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
17.9%
1 11
14.1%
2 10
12.8%
9 7
9.0%
7 6
7.7%
5 6
7.7%
8 6
7.7%
3 6
7.7%
, 4
 
5.1%
4 3
 
3.8%
Other values (2) 5
 
6.4%
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 (%)
0 14
17.9%
1 11
14.1%
2 10
12.8%
9 7
9.0%
7 6
7.7%
5 6
7.7%
8 6
7.7%
3 6
7.7%
, 4
 
5.1%
4 3
 
3.8%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:15.438971image/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 row문흥1동
2nd row6,490
3rd row15,974
4th row29
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
29 2
 
6.1%
68 2
 
6.1%
90 1
 
3.0%
15,974 1
 
3.0%
121 1
 
3.0%
6,493 1
 
3.0%
70 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:16.397196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.4%
9 12
16.4%
1 8
11.0%
2 7
9.6%
6 5
6.8%
8 5
6.8%
4 5
6.8%
, 4
 
5.5%
3 4
 
5.5%
7 4
 
5.5%
Other values (5) 7
9.6%

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 (%)
0 12
18.5%
9 12
18.5%
1 8
12.3%
2 7
10.8%
6 5
7.7%
8 5
7.7%
4 5
7.7%
3 4
 
6.2%
7 4
 
6.2%
5 3
 
4.6%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
9 12
17.1%
1 8
11.4%
2 7
10.0%
6 5
7.1%
8 5
7.1%
4 5
7.1%
, 4
 
5.7%
3 4
 
5.7%
7 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.1%
9 12
17.1%
1 8
11.4%
2 7
10.0%
6 5
7.1%
8 5
7.1%
4 5
7.1%
, 4
 
5.7%
3 4
 
5.7%
7 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:16.754833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row문흥2동
2nd row7,370
3rd row15,736
4th row32
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
32 2
 
6.1%
3 2
 
6.1%
160 1
 
3.0%
15,736 1
 
3.0%
226 1
 
3.0%
7,372 1
 
3.0%
88 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:17.545086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
18.8%
1 12
15.0%
2 9
11.2%
3 8
10.0%
4 7
8.8%
5 7
8.8%
6 5
 
6.2%
7 5
 
6.2%
, 4
 
5.0%
8 3
 
3.8%
Other values (5) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
90.0%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
20.8%
1 12
16.7%
2 9
12.5%
3 8
11.1%
4 7
9.7%
5 7
9.7%
6 5
 
6.9%
7 5
 
6.9%
8 3
 
4.2%
9 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
19.5%
1 12
15.6%
2 9
11.7%
3 8
10.4%
4 7
9.1%
5 7
9.1%
6 5
 
6.5%
7 5
 
6.5%
, 4
 
5.2%
8 3
 
3.9%
Other values (2) 2
 
2.6%
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 (%)
0 15
19.5%
1 12
15.6%
2 9
11.7%
3 8
10.4%
4 7
9.1%
5 7
9.1%
6 5
 
6.5%
7 5
 
6.5%
, 4
 
5.2%
8 3
 
3.9%
Other values (2) 2
 
2.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:17.982348image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row두암1동
2nd row4,031
3rd row7,773
4th row23
5th row7
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
7 2
 
6.1%
49 1
 
3.0%
57 1
 
3.0%
7,759 1
 
3.0%
4,022 1
 
3.0%
14 1
 
3.0%
9 1
 
3.0%
3 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:40:18.794386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.3%
7 10
14.3%
4 9
12.9%
3 7
10.0%
1 6
8.6%
2 6
8.6%
9 5
7.1%
, 4
 
5.7%
6 3
 
4.3%
- 3
 
4.3%
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 (%)
0 10
16.7%
7 10
16.7%
4 9
15.0%
3 7
11.7%
1 6
10.0%
2 6
10.0%
9 5
8.3%
6 3
 
5.0%
8 2
 
3.3%
5 2
 
3.3%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.9%
7 10
14.9%
4 9
13.4%
3 7
10.4%
1 6
9.0%
2 6
9.0%
9 5
7.5%
, 4
 
6.0%
6 3
 
4.5%
- 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 (%)
0 10
14.9%
7 10
14.9%
4 9
13.4%
3 7
10.4%
1 6
9.0%
2 6
9.0%
9 5
7.5%
, 4
 
6.0%
6 3
 
4.5%
- 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:19.130834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row두암2동
2nd row7,685
3rd row16,030
4th row52
5th row9
ValueCountFrequency (%)
0 8
24.2%
52 2
 
6.1%
9 2
 
6.1%
67 1
 
3.0%
16,030 1
 
3.0%
104 1
 
3.0%
7,711 1
 
3.0%
28 1
 
3.0%
26 1
 
3.0%
12 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:19.778253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.7%
2 8
10.7%
1 8
10.7%
9 7
9.3%
8 6
8.0%
6 6
8.0%
7 6
8.0%
5 4
 
5.3%
3 4
 
5.3%
4 4
 
5.3%
Other values (5) 8
10.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
20.9%
2 8
11.9%
1 8
11.9%
9 7
10.4%
8 6
9.0%
6 6
9.0%
7 6
9.0%
5 4
 
6.0%
3 4
 
6.0%
4 4
 
6.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
19.4%
2 8
11.1%
1 8
11.1%
9 7
9.7%
8 6
8.3%
6 6
8.3%
7 6
8.3%
5 4
 
5.6%
3 4
 
5.6%
4 4
 
5.6%
Other values (2) 5
 
6.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
19.4%
2 8
11.1%
1 8
11.1%
9 7
9.7%
8 6
8.3%
6 6
8.3%
7 6
8.3%
5 4
 
5.6%
3 4
 
5.6%
4 4
 
5.6%
Other values (2) 5
 
6.9%
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
2024-02-10T09:40:20.093583image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row두암3동
2nd row7,806
3rd row13,365
4th row49
5th row7
ValueCountFrequency (%)
0 8
24.2%
53 3
 
9.1%
49 2
 
6.1%
7 2
 
6.1%
74 1
 
3.0%
13,365 1
 
3.0%
123 1
 
3.0%
7,805 1
 
3.0%
52 1
 
3.0%
1 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:40:21.069885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.2%
3 11
14.9%
1 8
10.8%
5 6
8.1%
7 6
8.1%
6 6
8.1%
4 5
6.8%
8 5
6.8%
, 4
 
5.4%
2 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 12
18.5%
3 11
16.9%
1 8
12.3%
5 6
9.2%
7 6
9.2%
6 6
9.2%
4 5
7.7%
8 5
7.7%
2 4
 
6.2%
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 (%)
0 12
16.9%
3 11
15.5%
1 8
11.3%
5 6
8.5%
7 6
8.5%
6 6
8.5%
4 5
7.0%
8 5
7.0%
, 4
 
5.6%
2 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 12
16.9%
3 11
15.5%
1 8
11.3%
5 6
8.5%
7 6
8.5%
6 6
8.5%
4 5
7.0%
8 5
7.0%
, 4
 
5.6%
2 4
 
5.6%
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
2024-02-10T09:40:21.390163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row삼각동
2nd row6,074
3rd row14,104
4th row28
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
72 2
 
6.1%
28 2
 
6.1%
6 1
 
3.0%
119 1
 
3.0%
14,040 1
 
3.0%
6,066 1
 
3.0%
1 1
 
3.0%
64 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:22.180531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
20.0%
1 11
14.7%
4 8
10.7%
2 7
9.3%
6 7
9.3%
8 5
 
6.7%
7 5
 
6.7%
, 4
 
5.3%
9 4
 
5.3%
5 3
 
4.0%
Other values (5) 6
 
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
22.7%
1 11
16.7%
4 8
12.1%
2 7
10.6%
6 7
10.6%
8 5
 
7.6%
7 5
 
7.6%
9 4
 
6.1%
5 3
 
4.5%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
20.8%
1 11
15.3%
4 8
11.1%
2 7
9.7%
6 7
9.7%
8 5
 
6.9%
7 5
 
6.9%
, 4
 
5.6%
9 4
 
5.6%
5 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
20.8%
1 11
15.3%
4 8
11.1%
2 7
9.7%
6 7
9.7%
8 5
 
6.9%
7 5
 
6.9%
, 4
 
5.6%
9 4
 
5.6%
5 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:22.539642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
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 row일곡동
2nd row11,559
3rd row29,922
4th row35
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
11,559 2
 
6.1%
6 1
 
3.0%
173 1
 
3.0%
29,827 1
 
3.0%
2 1
 
3.0%
95 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:40:23.231589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.3%
9 9
10.8%
2 9
10.8%
0 8
9.6%
5 7
8.4%
3 7
8.4%
7 6
 
7.2%
4 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
Other values (5) 8
9.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
89.2%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.6%
9 9
12.2%
2 9
12.2%
0 8
10.8%
5 7
9.5%
3 7
9.5%
7 6
 
8.1%
4 5
 
6.8%
8 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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.0%
9 9
11.2%
2 9
11.2%
0 8
10.0%
5 7
8.8%
3 7
8.8%
7 6
 
7.5%
4 5
 
6.2%
, 4
 
5.0%
8 4
 
5.0%
Other values (2) 5
 
6.2%
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 (%)
1 16
20.0%
9 9
11.2%
2 9
11.2%
0 8
10.0%
5 7
8.8%
3 7
8.8%
7 6
 
7.5%
4 5
 
6.2%
, 4
 
5.0%
8 4
 
5.0%
Other values (2) 5
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:23.563361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row매곡동
2nd row5,501
3rd row13,857
4th row21
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 3
 
9.1%
68 2
 
6.1%
21 2
 
6.1%
75 2
 
6.1%
25 1
 
3.0%
74 1
 
3.0%
5,525 1
 
3.0%
24 1
 
3.0%
2 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:40:24.553271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 14
19.7%
0 8
11.3%
1 8
11.3%
2 7
9.9%
4 6
8.5%
7 5
 
7.0%
3 5
 
7.0%
6 4
 
5.6%
8 4
 
5.6%
, 4
 
5.6%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
88.7%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 14
22.2%
0 8
12.7%
1 8
12.7%
2 7
11.1%
4 6
9.5%
7 5
 
7.9%
3 5
 
7.9%
6 4
 
6.3%
8 4
 
6.3%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 14
20.6%
0 8
11.8%
1 8
11.8%
2 7
10.3%
4 6
8.8%
7 5
 
7.4%
3 5
 
7.4%
6 4
 
5.9%
8 4
 
5.9%
, 4
 
5.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 14
20.6%
0 8
11.8%
1 8
11.8%
2 7
10.3%
4 6
8.8%
7 5
 
7.4%
3 5
 
7.4%
6 4
 
5.9%
8 4
 
5.9%
, 4
 
5.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:24.943045image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row오치1동
2nd row5,535
3rd row10,946
4th row47
5th row8
ValueCountFrequency (%)
0 6
18.2%
3 3
 
9.1%
76 2
 
6.1%
8 2
 
6.1%
50 1
 
3.0%
47 1
 
3.0%
5,535 1
 
3.0%
10,912 1
 
3.0%
5,532 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:26.166138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.5%
5 9
12.2%
4 9
12.2%
3 7
9.5%
1 7
9.5%
7 6
8.1%
6 5
6.8%
8 4
 
5.4%
, 4
 
5.4%
2 4
 
5.4%
Other values (5) 9
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.6%
5 9
14.1%
4 9
14.1%
3 7
10.9%
1 7
10.9%
7 6
9.4%
6 5
7.8%
8 4
 
6.2%
2 4
 
6.2%
9 3
 
4.7%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.1%
5 9
12.7%
4 9
12.7%
3 7
9.9%
1 7
9.9%
7 6
8.5%
6 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.1%
5 9
12.7%
4 9
12.7%
3 7
9.9%
1 7
9.9%
7 6
8.5%
6 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:26.576390image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row오치2동
2nd row7,013
3rd row12,497
4th row35
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 3
 
9.1%
34 2
 
6.1%
90 1
 
3.0%
35 1
 
3.0%
82 1
 
3.0%
7,008 1
 
3.0%
1 1
 
3.0%
49 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:40:27.539905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.6%
8 9
12.2%
1 9
12.2%
4 7
9.5%
3 6
8.1%
6 6
8.1%
2 5
 
6.8%
, 4
 
5.4%
5 3
 
4.1%
7 3
 
4.1%
Other values (5) 9
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
86.5%
Other Punctuation 4
 
5.4%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.3%
8 9
14.1%
1 9
14.1%
4 7
10.9%
3 6
9.4%
6 6
9.4%
2 5
 
7.8%
5 3
 
4.7%
7 3
 
4.7%
9 3
 
4.7%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.3%
8 9
12.7%
1 9
12.7%
4 7
9.9%
3 6
8.5%
6 6
8.5%
2 5
 
7.0%
, 4
 
5.6%
5 3
 
4.2%
7 3
 
4.2%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.3%
8 9
12.7%
1 9
12.7%
4 7
9.9%
3 6
8.5%
6 6
8.5%
2 5
 
7.0%
, 4
 
5.6%
5 3
 
4.2%
7 3
 
4.2%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:28.007239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.9090909
Min length1

Characters and Unicode

Total characters63
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 row석곡동
2nd row1,392
3rd row2,514
4th row21
5th row3
ValueCountFrequency (%)
0 9
27.3%
8 2
 
6.1%
6 2
 
6.1%
21 2
 
6.1%
3 2
 
6.1%
14 2
 
6.1%
7 1
 
3.0%
1,384 1
 
3.0%
11 1
 
3.0%
1 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:40:29.020192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
22.2%
0 11
17.5%
2 8
12.7%
3 6
9.5%
8 5
 
7.9%
4 4
 
6.3%
, 4
 
6.3%
6 2
 
3.2%
5 2
 
3.2%
- 2
 
3.2%
Other values (5) 5
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
85.7%
Other Punctuation 4
 
6.3%
Other Letter 3
 
4.8%
Dash Punctuation 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
25.9%
0 11
20.4%
2 8
14.8%
3 6
11.1%
8 5
 
9.3%
4 4
 
7.4%
6 2
 
3.7%
5 2
 
3.7%
9 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 (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 60
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
23.3%
0 11
18.3%
2 8
13.3%
3 6
10.0%
8 5
 
8.3%
4 4
 
6.7%
, 4
 
6.7%
6 2
 
3.3%
5 2
 
3.3%
- 2
 
3.3%
Other values (2) 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
95.2%
Hangul 3
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
23.3%
0 11
18.3%
2 8
13.3%
3 6
10.0%
8 5
 
8.3%
4 4
 
6.7%
, 4
 
6.7%
6 2
 
3.3%
5 2
 
3.3%
- 2
 
3.3%
Other values (2) 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:29.482912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique22 ?
Unique (%)66.7%

Sample

1st row건국동
2nd row9,262
3rd row22,339
4th row64
5th row14
ValueCountFrequency (%)
0 7
21.2%
118 2
 
6.1%
14 2
 
6.1%
16 1
 
3.0%
157 1
 
3.0%
22,274 1
 
3.0%
9,245 1
 
3.0%
1 1
 
3.0%
65 1
 
3.0%
17 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:40:30.271924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
17.9%
2 12
14.3%
0 10
11.9%
4 6
 
7.1%
8 6
 
7.1%
5 6
 
7.1%
6 6
 
7.1%
3 5
 
6.0%
9 4
 
4.8%
, 4
 
4.8%
Other values (5) 10
11.9%

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 15
20.3%
2 12
16.2%
0 10
13.5%
4 6
 
8.1%
8 6
 
8.1%
5 6
 
8.1%
6 6
 
8.1%
3 5
 
6.8%
9 4
 
5.4%
7 4
 
5.4%
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 81
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
18.5%
2 12
14.8%
0 10
12.3%
4 6
 
7.4%
8 6
 
7.4%
5 6
 
7.4%
6 6
 
7.4%
3 5
 
6.2%
9 4
 
4.9%
, 4
 
4.9%
Other values (2) 7
8.6%
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 15
18.5%
2 12
14.8%
0 10
12.3%
4 6
 
7.4%
8 6
 
7.4%
5 6
 
7.4%
6 6
 
7.4%
3 5
 
6.2%
9 4
 
4.9%
, 4
 
4.9%
Other values (2) 7
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:30.636148image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row양산동
2nd row16,415
3rd row37,949
4th row67
5th row19
ValueCountFrequency (%)
0 7
21.2%
19 2
 
6.1%
237 1
 
3.0%
37,855 1
 
3.0%
16,419 1
 
3.0%
3 1
 
3.0%
94 1
 
3.0%
4 1
 
3.0%
13 1
 
3.0%
173 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:40:31.517993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
20.5%
0 13
14.8%
4 10
11.4%
3 10
11.4%
7 8
9.1%
9 6
 
6.8%
6 5
 
5.7%
, 4
 
4.5%
5 4
 
4.5%
2 3
 
3.4%
Other values (5) 7
 
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
89.8%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
22.8%
0 13
16.5%
4 10
12.7%
3 10
12.7%
7 8
10.1%
9 6
 
7.6%
6 5
 
6.3%
5 4
 
5.1%
2 3
 
3.8%
8 2
 
2.5%
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 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
21.2%
0 13
15.3%
4 10
11.8%
3 10
11.8%
7 8
9.4%
9 6
 
7.1%
6 5
 
5.9%
, 4
 
4.7%
5 4
 
4.7%
2 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 13
15.3%
4 10
11.8%
3 10
11.8%
7 8
9.4%
9 6
 
7.1%
6 5
 
5.9%
, 4
 
4.7%
5 4
 
4.7%
2 3
 
3.5%
Other values (2) 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:40:31.918618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row신용동
2nd row11,830
3rd row29,906
4th row8
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 4
 
12.1%
200 1
 
3.0%
393 1
 
3.0%
29,781 1
 
3.0%
11,838 1
 
3.0%
125 1
 
3.0%
7 1
 
3.0%
155 1
 
3.0%
103 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:40:33.030252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.5%
1 14
17.5%
8 8
10.0%
3 8
10.0%
9 8
10.0%
2 7
8.8%
5 6
7.5%
7 5
 
6.2%
, 4
 
5.0%
4 1
 
1.2%
Other values (5) 5
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
90.0%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
19.4%
1 14
19.4%
8 8
11.1%
3 8
11.1%
9 8
11.1%
2 7
9.7%
5 6
8.3%
7 5
 
6.9%
4 1
 
1.4%
6 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
18.2%
1 14
18.2%
8 8
10.4%
3 8
10.4%
9 8
10.4%
2 7
9.1%
5 6
7.8%
7 5
 
6.5%
, 4
 
5.2%
4 1
 
1.3%
Other values (2) 2
 
2.6%
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 (%)
0 14
18.2%
1 14
18.2%
8 8
10.4%
3 8
10.4%
9 8
10.4%
2 7
9.1%
5 6
7.8%
7 5
 
6.5%
, 4
 
5.2%
4 1
 
1.3%
Other values (2) 2
 
2.6%
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>2022.03.09<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>2022.02 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>195,8113,0023,7872,8472,0304,4787,224<NA>17,8187,4426,1165,0769,8655,6382,7689,7576,4907,3704,0317,6857,8066,07411,5595,5015,5357,0131,3929,26216,41511,830
4<NA>전월말인구수<NA><NA><NA>426,8774,7936,8584,8183,0519,17912,389<NA>38,57319,34512,02512,66123,33210,2715,73120,93915,97415,7367,77316,03013,36514,10429,92213,85710,94612,4972,51422,33937,94929,906
5<NA>전월말거주불명자수<NA><NA><NA>1,298596543533785<NA>12430583156632261293223524928352147352164678
6<NA>전월말재외국민등록자수<NA><NA><NA>218043451<NA>1818714993794797411588314198
7<NA>증 가 요 인전 입<NA>6,3717790781788185239<NA>610195135129171102832121212269418312315925914312412118249350251
8<NA><NA><NA>남자<NA>3,109394333784789123<NA>30479746084483610068112469853831326867606131170121
9<NA><NA><NA>여자<NA>3,262384744394196116<NA>3061166169875447112531144885707612775576112118180130
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>12100000<NA>0000100103000012300000
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>6355255286-1586-8<NA>35121510-23-4-13-2232-926-1-8024-3-5-8-1748
29<NA>인구수증감<NA><NA><NA>262-2711690486-28<NA>-98-13-25-13-101-32-32-91-70-88-14-28-52-64-95-5-34-49-11-65-94-125
30<NA>거주불명자수증감<NA><NA><NA>-18-1-2-200-1<NA>1-2-20002-300-1001-20-1-10-1-30
31<NA>금월말세대수<NA><NA><NA>196,4463,0074,0423,1332,0154,5647,216<NA>17,8537,4546,1315,0869,8425,6342,7559,7356,4937,3724,0227,7117,8056,06611,5595,5255,5327,0081,3849,24516,41911,838
32<NA>금월말인구수<NA><NA><NA>427,1394,7917,5695,5083,0559,26512,361<NA>38,47519,33212,00012,64823,23110,2395,69920,84815,90415,6487,75916,00213,31314,04029,82713,85210,91212,4482,50322,27437,85529,781
33<NA>금월말거주불명자수<NA><NA><NA>1,280586341533784<NA>12528563156632458293222524929332146342163648
34<NA>금월말재외국민등록자수<NA><NA><NA>219043451<NA>1818715893794797411588314199

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