Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2023-05-25
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 1 (2.9%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 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 09:50:48.032039
Analysis finished2024-02-10 09:50:49.710987
Duration1.68 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
2024-02-10T09:50:49.968804image/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%
2024-02-10T09:50:51.032695image/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
2024-02-10T09:50:51.581710image/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%
2024-02-10T09:50:52.368271image/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
2024-02-10T09:50:52.833555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters21
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 row2023.04 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%
2023.04 1
7.1%
현재 1
7.1%
2024-02-10T09:50:53.539742image/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
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (11) 13
31.7%

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 2
33.3%
0 2
33.3%
3 1
16.7%
4 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
4 1
 
10.0%
. 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 (%)
3
30.0%
2 2
20.0%
0 2
20.0%
3 1
 
10.0%
4 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:50:53.915061image/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%
2024-02-10T09:50:54.496394image/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
2024-02-10T09:50:54.975865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.8787879
Min length1

Characters and Unicode

Total characters128
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

Unique23 ?
Unique (%)69.7%

Sample

1st row합 계
2nd row198,569
3rd row423,723
4th row1,024
5th row232
ValueCountFrequency (%)
0 4
 
11.8%
1,169 2
 
5.9%
1 2
 
5.9%
1,024 2
 
5.9%
1,719 1
 
2.9%
3,556 1
 
2.9%
423,338 1
 
2.9%
198,611 1
 
2.9%
385 1
 
2.9%
42 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T09:50:55.895639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
18.8%
, 18
14.1%
3 15
11.7%
2 13
10.2%
8 11
8.6%
0 10
7.8%
5 8
 
6.2%
6 7
 
5.5%
4 6
 
4.7%
9 6
 
4.7%
Other values (5) 10
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105
82.0%
Other Punctuation 18
 
14.1%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
22.9%
3 15
14.3%
2 13
12.4%
8 11
10.5%
0 10
9.5%
5 8
 
7.6%
6 7
 
6.7%
4 6
 
5.7%
9 6
 
5.7%
7 5
 
4.8%
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 126
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
19.0%
, 18
14.3%
3 15
11.9%
2 13
10.3%
8 11
8.7%
0 10
7.9%
5 8
 
6.3%
6 7
 
5.6%
4 6
 
4.8%
9 6
 
4.8%
Other values (3) 8
 
6.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 126
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
19.0%
, 18
14.3%
3 15
11.9%
2 13
10.3%
8 11
8.7%
0 10
7.9%
5 8
 
6.3%
6 7
 
5.6%
4 6
 
4.8%
9 6
 
4.8%
Other values (3) 8
 
6.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:56.307467image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row중흥1동
2nd row2,863
3rd row4,503
4th row42
5th row1
ValueCountFrequency (%)
0 9
27.3%
1 2
 
6.1%
27 2
 
6.1%
42 2
 
6.1%
16 2
 
6.1%
17 1
 
3.0%
58 1
 
3.0%
2,849 1
 
3.0%
14 1
 
3.0%
2 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:50:57.306887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
17.1%
0 11
15.7%
4 10
14.3%
2 10
14.3%
7 4
 
5.7%
, 4
 
5.7%
8 4
 
5.7%
6 3
 
4.3%
3 3
 
4.3%
5 2
 
2.9%
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 (%)
1 12
19.7%
0 11
18.0%
4 10
16.4%
2 10
16.4%
7 4
 
6.6%
8 4
 
6.6%
6 3
 
4.9%
3 3
 
4.9%
5 2
 
3.3%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.9%
0 11
16.4%
4 10
14.9%
2 10
14.9%
7 4
 
6.0%
, 4
 
6.0%
8 4
 
6.0%
6 3
 
4.5%
3 3
 
4.5%
5 2
 
3.0%
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 12
17.9%
0 11
16.4%
4 10
14.9%
2 10
14.9%
7 4
 
6.0%
, 4
 
6.0%
8 4
 
6.0%
6 3
 
4.5%
3 3
 
4.5%
5 2
 
3.0%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:57.708181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row중흥2동
2nd row4,419
3rd row8,407
4th row34
5th row5
ValueCountFrequency (%)
0 6
18.2%
5 4
 
12.1%
34 2
 
6.1%
95 2
 
6.1%
39 1
 
3.0%
32 1
 
3.0%
8,402 1
 
3.0%
4,412 1
 
3.0%
2 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:50:58.728051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
15.9%
0 10
14.5%
5 9
13.0%
3 8
11.6%
2 7
10.1%
1 6
8.7%
9 4
 
5.8%
, 4
 
5.8%
8 2
 
2.9%
7 2
 
2.9%
Other values (5) 6
8.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
18.3%
0 10
16.7%
5 9
15.0%
3 8
13.3%
2 7
11.7%
1 6
10.0%
9 4
 
6.7%
8 2
 
3.3%
7 2
 
3.3%
6 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 11
16.7%
0 10
15.2%
5 9
13.6%
3 8
12.1%
2 7
10.6%
1 6
9.1%
9 4
 
6.1%
, 4
 
6.1%
8 2
 
3.0%
7 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 11
16.7%
0 10
15.2%
5 9
13.6%
3 8
12.1%
2 7
10.6%
1 6
9.1%
9 4
 
6.1%
, 4
 
6.1%
8 2
 
3.0%
7 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:50:59.136922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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

Unique18 ?
Unique (%)54.5%

Sample

1st row중흥3동
2nd row3,661
3rd row6,532
4th row39
5th row2
ValueCountFrequency (%)
0 7
21.2%
37 2
 
6.1%
23 2
 
6.1%
31 2
 
6.1%
2 2
 
6.1%
5 1
 
3.0%
9 1
 
3.0%
6,553 1
 
3.0%
3,677 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:51:00.086833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
89.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 13
21.7%
2 9
15.0%
0 8
13.3%
7 6
10.0%
1 6
10.0%
6 6
10.0%
5 5
 
8.3%
4 4
 
6.7%
9 2
 
3.3%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 13
20.3%
2 9
14.1%
0 8
12.5%
7 6
9.4%
1 6
9.4%
6 6
9.4%
5 5
 
7.8%
, 4
 
6.2%
4 4
 
6.2%
9 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 (%)
3 13
20.3%
2 9
14.1%
0 8
12.5%
7 6
9.4%
1 6
9.4%
6 6
9.4%
5 5
 
7.8%
, 4
 
6.2%
4 4
 
6.2%
9 2
 
3.1%
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
2024-02-10T09:51:00.481882image/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 row2,280
3rd row3,956
4th row39
5th row6
ValueCountFrequency (%)
0 7
21.2%
1 3
 
9.1%
10 2
 
6.1%
9 1
 
3.0%
26 1
 
3.0%
36 1
 
3.0%
3,955 1
 
3.0%
2,278 1
 
3.0%
3 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:01.400003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.4%
3 11
16.4%
2 8
11.9%
1 7
10.4%
5 6
9.0%
, 4
 
6.0%
9 4
 
6.0%
6 4
 
6.0%
8 3
 
4.5%
- 3
 
4.5%
Other values (5) 6
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
85.1%
Other Punctuation 4
 
6.0%
Dash Punctuation 3
 
4.5%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
19.3%
3 11
19.3%
2 8
14.0%
1 7
12.3%
5 6
10.5%
9 4
 
7.0%
6 4
 
7.0%
8 3
 
5.3%
4 2
 
3.5%
7 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.2%
3 11
17.2%
2 8
12.5%
1 7
10.9%
5 6
9.4%
, 4
 
6.2%
9 4
 
6.2%
6 4
 
6.2%
8 3
 
4.7%
- 3
 
4.7%
Other values (2) 3
 
4.7%
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 11
17.2%
3 11
17.2%
2 8
12.5%
1 7
10.9%
5 6
9.4%
, 4
 
6.2%
9 4
 
6.2%
6 4
 
6.2%
8 3
 
4.7%
- 3
 
4.7%
Other values (2) 3
 
4.7%
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
2024-02-10T09:51:01.957455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0588235
Min length1

Characters and Unicode

Total characters70
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

Unique17 ?
Unique (%)50.0%

Sample

1st row출력일자 :
2nd row임동
3rd row4,595
4th row9,136
5th row29
ValueCountFrequency (%)
0 8
22.9%
5 3
 
8.6%
29 2
 
5.7%
35 2
 
5.7%
4 2
 
5.7%
73 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
4,599 1
 
2.9%
6 1
 
2.9%
Other values (13) 13
37.1%
2024-02-10T09:51:03.057022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 10
14.3%
0 9
12.9%
4 8
11.4%
9 7
10.0%
3 7
10.0%
2 6
8.6%
1 5
7.1%
, 4
 
5.7%
8 3
 
4.3%
6 2
 
2.9%
Other values (9) 9
12.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
82.9%
Other Letter 6
 
8.6%
Other Punctuation 5
 
7.1%
Space Separator 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 10
17.2%
0 9
15.5%
4 8
13.8%
9 7
12.1%
3 7
12.1%
2 6
10.3%
1 5
8.6%
8 3
 
5.2%
6 2
 
3.4%
7 1
 
1.7%
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 64
91.4%
Hangul 6
 
8.6%

Most frequent character per script

Common
ValueCountFrequency (%)
5 10
15.6%
0 9
14.1%
4 8
12.5%
9 7
10.9%
3 7
10.9%
2 6
9.4%
1 5
7.8%
, 4
 
6.2%
8 3
 
4.7%
6 2
 
3.1%
Other values (3) 3
 
4.7%
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 64
91.4%
Hangul 6
 
8.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 10
15.6%
0 9
14.1%
4 8
12.5%
9 7
10.9%
3 7
10.9%
2 6
9.4%
1 5
7.8%
, 4
 
6.2%
8 3
 
4.7%
6 2
 
3.1%
Other values (3) 3
 
4.7%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:03.409418image/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 row신안동
2nd row7,506
3rd row12,503
4th row74
5th row1
ValueCountFrequency (%)
0 6
18.2%
1 4
 
12.1%
51 2
 
6.1%
38 2
 
6.1%
5 1
 
3.0%
74 1
 
3.0%
65 1
 
3.0%
12,467 1
 
3.0%
7,497 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:51:04.241414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
15.3%
0 10
13.9%
7 9
12.5%
5 7
9.7%
6 7
9.7%
4 6
8.3%
2 5
6.9%
3 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 (%)
1 11
17.5%
0 10
15.9%
7 9
14.3%
5 7
11.1%
6 7
11.1%
4 6
9.5%
2 5
7.9%
3 4
 
6.3%
8 2
 
3.2%
9 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.9%
0 10
14.5%
7 9
13.0%
5 7
10.1%
6 7
10.1%
4 6
8.7%
2 5
7.2%
3 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 (%)
1 11
15.9%
0 10
14.5%
7 9
13.0%
5 7
10.1%
6 7
10.1%
4 6
8.7%
2 5
7.2%
3 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: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-05-22 00:00:00
Maximum2023-05-22 00:00:00
2024-02-10T09:51:04.647285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:51:05.010227image/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
2024-02-10T09:51:05.357839image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row용봉동
2nd row18,005
3rd row37,619
4th row84
5th row20
ValueCountFrequency (%)
0 6
 
18.2%
85 2
 
6.1%
1 2
 
6.1%
169 2
 
6.1%
120 1
 
3.0%
362 1
 
3.0%
37,568 1
 
3.0%
18,009 1
 
3.0%
51 1
 
3.0%
4 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:51:06.337387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.4%
0 13
15.5%
9 8
9.5%
8 8
9.5%
3 7
 
8.3%
5 6
 
7.1%
6 5
 
6.0%
, 4
 
4.8%
4 4
 
4.8%
2 4
 
4.8%
Other values (5) 7
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
90.5%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
23.7%
0 13
17.1%
9 8
10.5%
8 8
10.5%
3 7
 
9.2%
5 6
 
7.9%
6 5
 
6.6%
4 4
 
5.3%
2 4
 
5.3%
7 3
 
3.9%
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 81
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.2%
0 13
16.0%
9 8
9.9%
8 8
9.9%
3 7
 
8.6%
5 6
 
7.4%
6 5
 
6.2%
, 4
 
4.9%
4 4
 
4.9%
2 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 18
22.2%
0 13
16.0%
9 8
9.9%
8 8
9.9%
3 7
 
8.6%
5 6
 
7.4%
6 5
 
6.2%
, 4
 
4.9%
4 4
 
4.9%
2 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:06.666618image/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 row운암1동
2nd row7,398
3rd row18,769
4th row20
5th row21
ValueCountFrequency (%)
0 7
21.2%
40 2
 
6.1%
21 2
 
6.1%
140 1
 
3.0%
78 1
 
3.0%
18,730 1
 
3.0%
7,386 1
 
3.0%
2 1
 
3.0%
39 1
 
3.0%
12 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:51:07.474869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.2%
1 12
15.6%
2 10
13.0%
3 8
10.4%
8 7
9.1%
6 5
 
6.5%
7 5
 
6.5%
, 4
 
5.2%
4 3
 
3.9%
9 3
 
3.9%
Other values (5) 6
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
88.3%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
20.6%
1 12
17.6%
2 10
14.7%
3 8
11.8%
8 7
10.3%
6 5
 
7.4%
7 5
 
7.4%
4 3
 
4.4%
9 3
 
4.4%
5 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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
18.9%
1 12
16.2%
2 10
13.5%
3 8
10.8%
8 7
9.5%
6 5
 
6.8%
7 5
 
6.8%
, 4
 
5.4%
4 3
 
4.1%
9 3
 
4.1%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
18.9%
1 12
16.2%
2 10
13.5%
3 8
10.8%
8 7
9.5%
6 5
 
6.8%
7 5
 
6.8%
, 4
 
5.4%
4 3
 
4.1%
9 3
 
4.1%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:07.830348image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row운암2동
2nd row5,989
3rd row11,409
4th row52
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 2
 
6.1%
63 1
 
3.0%
11,373 1
 
3.0%
5,978 1
 
3.0%
1 1
 
3.0%
36 1
 
3.0%
11 1
 
3.0%
6 1
 
3.0%
45 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:51:08.576702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.9%
0 10
13.5%
3 8
10.8%
5 7
9.5%
9 6
8.1%
4 6
8.1%
2 5
6.8%
7 4
 
5.4%
, 4
 
5.4%
8 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 (%)
1 11
17.2%
0 10
15.6%
3 8
12.5%
5 7
10.9%
9 6
9.4%
4 6
9.4%
2 5
7.8%
7 4
 
6.2%
8 4
 
6.2%
6 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 (%)
1 11
15.5%
0 10
14.1%
3 8
11.3%
5 7
9.9%
9 6
8.5%
4 6
8.5%
2 5
7.0%
7 4
 
5.6%
, 4
 
5.6%
8 4
 
5.6%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
15.5%
0 10
14.1%
3 8
11.3%
5 7
9.9%
9 6
8.5%
4 6
8.5%
2 5
7.0%
7 4
 
5.6%
, 4
 
5.6%
8 4
 
5.6%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:08.890387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique15 ?
Unique (%)45.5%

Sample

1st row운암3동
2nd row5,483
3rd row13,368
4th row33
5th row17
ValueCountFrequency (%)
0 8
24.2%
40 2
 
6.1%
28 2
 
6.1%
33 2
 
6.1%
13,368 2
 
6.1%
17 2
 
6.1%
6 1
 
3.0%
81 1
 
3.0%
5,491 1
 
3.0%
1 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:51:09.824945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
18.3%
0 11
15.5%
1 9
12.7%
4 8
11.3%
8 8
11.3%
2 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
6 3
 
4.2%
9 2
 
2.8%
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 (%)
3 13
20.6%
0 11
17.5%
1 9
14.3%
4 8
12.7%
8 8
12.7%
2 4
 
6.3%
7 3
 
4.8%
6 3
 
4.8%
9 2
 
3.2%
5 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 (%)
3 13
19.1%
0 11
16.2%
1 9
13.2%
4 8
11.8%
8 8
11.8%
2 4
 
5.9%
, 4
 
5.9%
7 3
 
4.4%
6 3
 
4.4%
9 2
 
2.9%
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 (%)
3 13
19.1%
0 11
16.2%
1 9
13.2%
4 8
11.8%
8 8
11.8%
2 4
 
5.9%
, 4
 
5.9%
7 3
 
4.4%
6 3
 
4.4%
9 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:10.300883image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row동림동
2nd row9,900
3rd row22,742
4th row35
5th row7
ValueCountFrequency (%)
0 7
21.2%
82 2
 
6.1%
32 2
 
6.1%
3 2
 
6.1%
7 2
 
6.1%
47 1
 
3.0%
22,710 1
 
3.0%
9,903 1
 
3.0%
12 1
 
3.0%
50 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:51:11.130114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.6%
2 10
13.5%
1 7
9.5%
9 7
9.5%
4 7
9.5%
3 7
9.5%
7 5
 
6.8%
8 4
 
5.4%
, 4
 
5.4%
5 3
 
4.1%
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 (%)
0 13
20.0%
2 10
15.4%
1 7
10.8%
9 7
10.8%
4 7
10.8%
3 7
10.8%
7 5
 
7.7%
8 4
 
6.2%
5 3
 
4.6%
6 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 (%)
0 13
18.3%
2 10
14.1%
1 7
9.9%
9 7
9.9%
4 7
9.9%
3 7
9.9%
7 5
 
7.0%
8 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
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 (%)
0 13
18.3%
2 10
14.1%
1 7
9.9%
9 7
9.9%
4 7
9.9%
3 7
9.9%
7 5
 
7.0%
8 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:11.558962image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row우산동
2nd row7,541
3rd row15,207
4th row53
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 2
 
6.1%
53 2
 
6.1%
39 2
 
6.1%
38 1
 
3.0%
15,207 1
 
3.0%
61 1
 
3.0%
7,580 1
 
3.0%
101 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:51:12.755173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.9%
0 13
17.6%
5 10
13.5%
3 9
12.2%
8 5
 
6.8%
7 5
 
6.8%
9 4
 
5.4%
, 4
 
5.4%
2 3
 
4.1%
4 3
 
4.1%
Other values (4) 4
 
5.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.9%
0 13
19.4%
5 10
14.9%
3 9
13.4%
8 5
 
7.5%
7 5
 
7.5%
9 4
 
6.0%
2 3
 
4.5%
4 3
 
4.5%
6 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.7%
0 13
18.3%
5 10
14.1%
3 9
12.7%
8 5
 
7.0%
7 5
 
7.0%
9 4
 
5.6%
, 4
 
5.6%
2 3
 
4.2%
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 (%)
1 14
19.7%
0 13
18.3%
5 10
14.1%
3 9
12.7%
8 5
 
7.0%
7 5
 
7.0%
9 4
 
5.6%
, 4
 
5.6%
2 3
 
4.2%
4 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:13.123015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row풍향동
2nd row2,686
3rd row5,411
4th row21
5th row2
ValueCountFrequency (%)
0 7
21.2%
2 3
 
9.1%
32 2
 
6.1%
12 2
 
6.1%
30 1
 
3.0%
23 1
 
3.0%
5,420 1
 
3.0%
2,694 1
 
3.0%
3 1
 
3.0%
9 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:51:14.119952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
23.4%
0 9
14.1%
1 7
10.9%
3 6
 
9.4%
4 5
 
7.8%
, 4
 
6.2%
6 4
 
6.2%
5 4
 
6.2%
9 3
 
4.7%
8 2
 
3.1%
Other values (4) 5
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
89.1%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
26.3%
0 9
15.8%
1 7
12.3%
3 6
 
10.5%
4 5
 
8.8%
6 4
 
7.0%
5 4
 
7.0%
9 3
 
5.3%
8 2
 
3.5%
7 2
 
3.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
24.6%
0 9
14.8%
1 7
11.5%
3 6
 
9.8%
4 5
 
8.2%
, 4
 
6.6%
6 4
 
6.6%
5 4
 
6.6%
9 3
 
4.9%
8 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15
24.6%
0 9
14.8%
1 7
11.5%
3 6
 
9.8%
4 5
 
8.2%
, 4
 
6.6%
6 4
 
6.6%
5 4
 
6.6%
9 3
 
4.9%
8 2
 
3.3%
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
2024-02-10T09:51:14.627393image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row문화동
2nd row9,593
3rd row20,090
4th row34
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
92 1
 
3.0%
20,081 1
 
3.0%
9,590 1
 
3.0%
2 1
 
3.0%
9 1
 
3.0%
3 1
 
3.0%
13 1
 
3.0%
67 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:51:15.669279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.8%
9 11
15.1%
8 7
9.6%
1 7
9.6%
3 7
9.6%
7 5
 
6.8%
5 4
 
5.5%
, 4
 
5.5%
2 4
 
5.5%
4 3
 
4.1%
Other values (5) 8
11.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.3%
9 11
17.2%
8 7
10.9%
1 7
10.9%
3 7
10.9%
7 5
 
7.8%
5 4
 
6.2%
2 4
 
6.2%
4 3
 
4.7%
6 3
 
4.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.6%
9 11
15.7%
8 7
10.0%
1 7
10.0%
3 7
10.0%
7 5
 
7.1%
5 4
 
5.7%
, 4
 
5.7%
2 4
 
5.7%
4 3
 
4.3%
Other values (2) 5
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.6%
9 11
15.7%
8 7
10.0%
1 7
10.0%
3 7
10.0%
7 5
 
7.1%
5 4
 
5.7%
, 4
 
5.7%
2 4
 
5.7%
4 3
 
4.3%
Other values (2) 5
 
7.1%
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
2024-02-10T09:51:16.156712image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row문흥1동
2nd row6,568
3rd row15,469
4th row19
5th row9
ValueCountFrequency (%)
0 7
21.2%
123 2
 
6.1%
54 2
 
6.1%
9 2
 
6.1%
3 1
 
3.0%
35 1
 
3.0%
15,606 1
 
3.0%
6,690 1
 
3.0%
1 1
 
3.0%
137 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:16.954710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.7%
0 11
14.1%
6 10
12.8%
5 8
10.3%
2 7
9.0%
9 5
 
6.4%
3 5
 
6.4%
4 5
 
6.4%
, 4
 
5.1%
8 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 (%)
1 13
18.6%
0 11
15.7%
6 10
14.3%
5 8
11.4%
2 7
10.0%
9 5
 
7.1%
3 5
 
7.1%
4 5
 
7.1%
8 4
 
5.7%
7 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 (%)
1 13
17.3%
0 11
14.7%
6 10
13.3%
5 8
10.7%
2 7
9.3%
9 5
 
6.7%
3 5
 
6.7%
4 5
 
6.7%
, 4
 
5.3%
8 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 (%)
1 13
17.3%
0 11
14.7%
6 10
13.3%
5 8
10.7%
2 7
9.3%
9 5
 
6.7%
3 5
 
6.7%
4 5
 
6.7%
, 4
 
5.3%
8 4
 
5.3%
Other values (2) 3
 
4.0%
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
2024-02-10T09:51:17.371256image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row문흥2동
2nd row7,379
3rd row15,172
4th row21
5th row5
ValueCountFrequency (%)
0 6
18.2%
28 2
 
6.1%
21 2
 
6.1%
5 2
 
6.1%
1 2
 
6.1%
46 1
 
3.0%
89 1
 
3.0%
7,364 1
 
3.0%
47 1
 
3.0%
15 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:18.352607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.2%
2 10
13.5%
4 9
12.2%
5 8
10.8%
0 7
9.5%
6 5
6.8%
7 5
6.8%
3 4
 
5.4%
, 4
 
5.4%
8 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 (%)
1 12
18.5%
2 10
15.4%
4 9
13.8%
5 8
12.3%
0 7
10.8%
6 5
7.7%
7 5
7.7%
3 4
 
6.2%
8 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 (%)
1 12
16.9%
2 10
14.1%
4 9
12.7%
5 8
11.3%
0 7
9.9%
6 5
7.0%
7 5
7.0%
3 4
 
5.6%
, 4
 
5.6%
8 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 (%)
1 12
16.9%
2 10
14.1%
4 9
12.7%
5 8
11.3%
0 7
9.9%
6 5
7.0%
7 5
7.0%
3 4
 
5.6%
, 4
 
5.6%
8 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:18.768469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row두암1동
2nd row3,952
3rd row7,401
4th row12
5th row9
ValueCountFrequency (%)
0 9
27.3%
9 2
 
6.1%
11 2
 
6.1%
12 2
 
6.1%
19 1
 
3.0%
28 1
 
3.0%
3,945 1
 
3.0%
26 1
 
3.0%
7 1
 
3.0%
8 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:51:19.753206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.9%
1 10
14.5%
2 9
13.0%
7 7
10.1%
9 5
7.2%
5 5
7.2%
3 5
7.2%
, 4
 
5.8%
4 4
 
5.8%
6 2
 
2.9%
Other values (5) 7
10.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.3%
1 10
16.7%
2 9
15.0%
7 7
11.7%
9 5
8.3%
5 5
8.3%
3 5
8.3%
4 4
 
6.7%
6 2
 
3.3%
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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.7%
1 10
15.2%
2 9
13.6%
7 7
10.6%
9 5
7.6%
5 5
7.6%
3 5
7.6%
, 4
 
6.1%
4 4
 
6.1%
6 2
 
3.0%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.7%
1 10
15.2%
2 9
13.6%
7 7
10.6%
9 5
7.6%
5 5
7.6%
3 5
7.6%
, 4
 
6.1%
4 4
 
6.1%
6 2
 
3.0%
Other values (2) 4
 
6.1%
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
2024-02-10T09:51:20.299417image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row두암2동
2nd row7,612
3rd row15,414
4th row49
5th row9
ValueCountFrequency (%)
0 7
21.2%
71 2
 
6.1%
1 2
 
6.1%
9 2
 
6.1%
62 1
 
3.0%
73 1
 
3.0%
15,386 1
 
3.0%
7,606 1
 
3.0%
28 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:21.284973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.0%
0 8
10.7%
4 8
10.7%
7 6
8.0%
6 6
8.0%
2 6
8.0%
3 6
8.0%
5 5
6.7%
9 4
 
5.3%
, 4
 
5.3%
Other values (5) 10
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
86.7%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
4.0%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.5%
0 8
12.3%
4 8
12.3%
7 6
9.2%
6 6
9.2%
2 6
9.2%
3 6
9.2%
5 5
7.7%
9 4
 
6.2%
8 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.7%
0 8
11.1%
4 8
11.1%
7 6
8.3%
6 6
8.3%
2 6
8.3%
3 6
8.3%
5 5
6.9%
9 4
 
5.6%
, 4
 
5.6%
Other values (2) 7
9.7%
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 (%)
1 12
16.7%
0 8
11.1%
4 8
11.1%
7 6
8.3%
6 6
8.3%
2 6
8.3%
3 6
8.3%
5 5
6.9%
9 4
 
5.6%
, 4
 
5.6%
Other values (2) 7
9.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:21.806673image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row두암3동
2nd row7,629
3rd row12,729
4th row36
5th row8
ValueCountFrequency (%)
0 7
21.2%
26 2
 
6.1%
8 2
 
6.1%
35 2
 
6.1%
49 1
 
3.0%
36 1
 
3.0%
72 1
 
3.0%
7,634 1
 
3.0%
1 1
 
3.0%
20 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:22.838329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
18.3%
0 9
12.7%
3 8
11.3%
7 7
9.9%
9 6
8.5%
6 5
 
7.0%
8 4
 
5.6%
4 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
Other values (5) 8
11.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
21.0%
0 9
14.5%
3 8
12.9%
7 7
11.3%
9 6
9.7%
6 5
 
8.1%
8 4
 
6.5%
4 4
 
6.5%
5 3
 
4.8%
1 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 (%)
2 13
19.1%
0 9
13.2%
3 8
11.8%
7 7
10.3%
9 6
8.8%
6 5
 
7.4%
8 4
 
5.9%
4 4
 
5.9%
, 4
 
5.9%
5 3
 
4.4%
Other values (2) 5
 
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
19.1%
0 9
13.2%
3 8
11.8%
7 7
10.3%
9 6
8.8%
6 5
 
7.4%
8 4
 
5.9%
4 4
 
5.9%
, 4
 
5.9%
5 3
 
4.4%
Other values (2) 5
 
7.4%
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
2024-02-10T09:51:23.190106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row삼각동
2nd row5,991
3rd row13,537
4th row27
5th row4
ValueCountFrequency (%)
0 6
18.2%
27 3
 
9.1%
4 2
 
6.1%
28 2
 
6.1%
90 1
 
3.0%
29 1
 
3.0%
5,997 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:23.990273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

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

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
18.2%
0 8
12.1%
5 8
12.1%
7 6
9.1%
3 6
9.1%
9 6
9.1%
1 6
9.1%
4 4
 
6.1%
8 4
 
6.1%
, 4
 
6.1%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
18.2%
0 8
12.1%
5 8
12.1%
7 6
9.1%
3 6
9.1%
9 6
9.1%
1 6
9.1%
4 4
 
6.1%
8 4
 
6.1%
, 4
 
6.1%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:24.331908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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 row일곡동
2nd row11,464
3rd row28,646
4th row24
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
12 2
 
6.1%
9 2
 
6.1%
216 1
 
3.0%
28,592 1
 
3.0%
11,455 1
 
3.0%
2 1
 
3.0%
54 1
 
3.0%
96 1
 
3.0%
56 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:51:25.193643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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%
6 10
14.5%
0 8
11.6%
4 8
11.6%
5 6
 
8.7%
8 5
 
7.2%
9 4
 
5.8%
3 2
 
2.9%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

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

Unnamed: 28
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:25.545272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row매곡동
2nd row5,516
3rd row13,507
4th row14
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 3
 
9.1%
36 3
 
9.1%
31 2
 
6.1%
41 1
 
3.0%
14 1
 
3.0%
72 1
 
3.0%
13,485 1
 
3.0%
5,517 1
 
3.0%
2 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:51:26.258171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
15.9%
0 9
13.0%
3 9
13.0%
2 8
11.6%
5 7
10.1%
6 6
8.7%
4 6
8.7%
, 4
 
5.8%
7 3
 
4.3%
1
 
1.4%
Other values (5) 5
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
88.4%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
18.0%
0 9
14.8%
3 9
14.8%
2 8
13.1%
5 7
11.5%
6 6
9.8%
4 6
9.8%
7 3
 
4.9%
9 1
 
1.6%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
16.7%
0 9
13.6%
3 9
13.6%
2 8
12.1%
5 7
10.6%
6 6
9.1%
4 6
9.1%
, 4
 
6.1%
7 3
 
4.5%
9 1
 
1.5%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
16.7%
0 9
13.6%
3 9
13.6%
2 8
12.1%
5 7
10.6%
6 6
9.1%
4 6
9.1%
, 4
 
6.1%
7 3
 
4.5%
9 1
 
1.5%
Other values (2) 2
 
3.0%
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
2024-02-10T09:51:26.711284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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 row오치1동
2nd row5,377
3rd row10,344
4th row52
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
46 2
 
6.1%
30 2
 
6.1%
1 2
 
6.1%
7 2
 
6.1%
10 2
 
6.1%
51 1
 
3.0%
71 1
 
3.0%
5,370 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:27.443862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.3%
1 13
17.3%
3 10
13.3%
7 8
10.7%
4 7
9.3%
2 5
 
6.7%
5 4
 
5.3%
, 4
 
5.3%
6 3
 
4.0%
- 3
 
4.0%
Other values (5) 5
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
86.7%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
4.0%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.0%
1 13
20.0%
3 10
15.4%
7 8
12.3%
4 7
10.8%
2 5
 
7.7%
5 4
 
6.2%
6 3
 
4.6%
9 1
 
1.5%
8 1
 
1.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.1%
1 13
18.1%
3 10
13.9%
7 8
11.1%
4 7
9.7%
2 5
 
6.9%
5 4
 
5.6%
, 4
 
5.6%
6 3
 
4.2%
- 3
 
4.2%
Other values (2) 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 (%)
0 13
18.1%
1 13
18.1%
3 10
13.9%
7 8
11.1%
4 7
9.7%
2 5
 
6.9%
5 4
 
5.6%
, 4
 
5.6%
6 3
 
4.2%
- 3
 
4.2%
Other values (2) 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:27.772985image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row오치2동
2nd row6,872
3rd row11,960
4th row34
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
34 2
 
6.1%
113 1
 
3.0%
51 1
 
3.0%
11,911 1
 
3.0%
6,859 1
 
3.0%
1 1
 
3.0%
49 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:51:28.742050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
0 10
13.3%
3 10
13.3%
9 7
9.3%
6 5
 
6.7%
2 5
 
6.7%
4 4
 
5.3%
, 4
 
5.3%
5 4
 
5.3%
8 3
 
4.0%
Other values (5) 9
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
86.7%
Other Punctuation 4
 
5.3%
Dash Punctuation 3
 
4.0%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.5%
0 10
15.4%
3 10
15.4%
9 7
10.8%
6 5
 
7.7%
2 5
 
7.7%
4 4
 
6.2%
5 4
 
6.2%
8 3
 
4.6%
7 3
 
4.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.4%
0 10
13.9%
3 10
13.9%
9 7
9.7%
6 5
 
6.9%
2 5
 
6.9%
4 4
 
5.6%
, 4
 
5.6%
5 4
 
5.6%
8 3
 
4.2%
Other values (2) 6
8.3%
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 (%)
1 14
19.4%
0 10
13.9%
3 10
13.9%
9 7
9.7%
6 5
 
6.9%
2 5
 
6.9%
4 4
 
5.6%
, 4
 
5.6%
5 4
 
5.6%
8 3
 
4.2%
Other values (2) 6
8.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:29.177145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7575758
Min length1

Characters and Unicode

Total characters58
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row석곡동
2nd row1,324
3rd row2,374
4th row8
5th row3
ValueCountFrequency (%)
0 9
27.3%
8 4
12.1%
3 3
 
9.1%
4 2
 
6.1%
석곡동 1
 
3.0%
2,374 1
 
3.0%
14 1
 
3.0%
6 1
 
3.0%
1,324 1
 
3.0%
7 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T09:51:30.184690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
17.2%
3 9
15.5%
1 8
13.8%
4 5
8.6%
2 5
8.6%
8 4
 
6.9%
, 4
 
6.9%
5 2
 
3.4%
9 2
 
3.4%
- 2
 
3.4%
Other values (5) 7
12.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
84.5%
Other Punctuation 4
 
6.9%
Other Letter 3
 
5.2%
Dash Punctuation 2
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
20.4%
3 9
18.4%
1 8
16.3%
4 5
10.2%
2 5
10.2%
8 4
 
8.2%
5 2
 
4.1%
9 2
 
4.1%
7 2
 
4.1%
6 2
 
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 55
94.8%
Hangul 3
 
5.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
18.2%
3 9
16.4%
1 8
14.5%
4 5
9.1%
2 5
9.1%
8 4
 
7.3%
, 4
 
7.3%
5 2
 
3.6%
9 2
 
3.6%
- 2
 
3.6%
Other values (2) 4
 
7.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
94.8%
Hangul 3
 
5.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
18.2%
3 9
16.4%
1 8
14.5%
4 5
9.1%
2 5
9.1%
8 4
 
7.3%
, 4
 
7.3%
5 2
 
3.6%
9 2
 
3.6%
- 2
 
3.6%
Other values (2) 4
 
7.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:30.584500image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row건국동
2nd row8,977
3rd row21,684
4th row54
5th row9
ValueCountFrequency (%)
0 5
 
15.2%
48 2
 
6.1%
11 2
 
6.1%
37 2
 
6.1%
1 2
 
6.1%
54 1
 
3.0%
9 1
 
3.0%
79 1
 
3.0%
53 1
 
3.0%
21,647 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:51:31.608343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.5%
7 9
11.8%
4 8
10.5%
8 7
9.2%
6 6
7.9%
3 6
7.9%
0 5
6.6%
9 5
6.6%
2 5
6.6%
5 4
 
5.3%
Other values (5) 10
13.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.7%
7 9
13.6%
4 8
12.1%
8 7
10.6%
6 6
9.1%
3 6
9.1%
0 5
7.6%
9 5
7.6%
2 5
7.6%
5 4
 
6.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.1%
7 9
12.3%
4 8
11.0%
8 7
9.6%
6 6
8.2%
3 6
8.2%
0 5
6.8%
9 5
6.8%
2 5
6.8%
5 4
 
5.5%
Other values (2) 7
9.6%
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 11
15.1%
7 9
12.3%
4 8
11.0%
8 7
9.6%
6 6
8.2%
3 6
8.2%
0 5
6.8%
9 5
6.8%
2 5
6.8%
5 4
 
5.5%
Other values (2) 7
9.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:31.983654image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row양산동
2nd row16,233
3rd row36,717
4th row73
5th row18
ValueCountFrequency (%)
0 5
 
15.2%
1 2
 
6.1%
147 1
 
3.0%
76 1
 
3.0%
36,626 1
 
3.0%
16,201 1
 
3.0%
3 1
 
3.0%
91 1
 
3.0%
32 1
 
3.0%
21 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T09:51:32.951453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.7%
2 10
12.0%
7 10
12.0%
0 8
9.6%
6 8
9.6%
3 7
 
8.4%
8 6
 
7.2%
, 4
 
4.8%
9 3
 
3.6%
4 3
 
3.6%
Other values (5) 6
 
7.2%

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 18
24.3%
2 10
13.5%
7 10
13.5%
0 8
10.8%
6 8
10.8%
3 7
 
9.5%
8 6
 
8.1%
9 3
 
4.1%
4 3
 
4.1%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.5%
2 10
12.5%
7 10
12.5%
0 8
10.0%
6 8
10.0%
3 7
 
8.8%
8 6
 
7.5%
, 4
 
5.0%
9 3
 
3.8%
4 3
 
3.8%
Other values (2) 3
 
3.8%
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 18
22.5%
2 10
12.5%
7 10
12.5%
0 8
10.0%
6 8
10.0%
3 7
 
8.8%
8 6
 
7.5%
, 4
 
5.0%
9 3
 
3.8%
4 3
 
3.8%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:51:33.351626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique21 ?
Unique (%)63.6%

Sample

1st row신용동
2nd row11,756
3rd row29,117
4th row12
5th row10
ValueCountFrequency (%)
0 8
24.2%
12 2
 
6.1%
10 2
 
6.1%
50 1
 
3.0%
29,117 1
 
3.0%
106 1
 
3.0%
11,745 1
 
3.0%
5 1
 
3.0%
11 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:51:34.337041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
27.8%
0 13
16.5%
2 9
11.4%
5 7
 
8.9%
7 6
 
7.6%
9 4
 
5.1%
8 4
 
5.1%
, 4
 
5.1%
6 3
 
3.8%
4 2
 
2.5%
Other values (5) 5
 
6.3%

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 (%)
1 22
31.0%
0 13
18.3%
2 9
12.7%
5 7
 
9.9%
7 6
 
8.5%
9 4
 
5.6%
8 4
 
5.6%
6 3
 
4.2%
4 2
 
2.8%
3 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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
28.9%
0 13
17.1%
2 9
11.8%
5 7
 
9.2%
7 6
 
7.9%
9 4
 
5.3%
8 4
 
5.3%
, 4
 
5.3%
6 3
 
3.9%
4 2
 
2.6%
Other values (2) 2
 
2.6%
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 22
28.9%
0 13
17.1%
2 9
11.8%
5 7
 
9.2%
7 6
 
7.9%
9 4
 
5.3%
8 4
 
5.3%
, 4
 
5.3%
6 3
 
3.9%
4 2
 
2.6%
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>2023.05.22<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>2023.04 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>198,5692,8634,4193,6612,2804,5957,506<NA>18,0057,3985,9895,4839,9007,5412,6869,5936,5687,3793,9527,6127,6295,99111,4645,5165,3776,8721,3248,97716,23311,756
4<NA>전월말인구수<NA><NA><NA>423,7234,5038,4076,5323,9569,13612,503<NA>37,61918,76911,40913,36822,74215,2075,41120,09015,46915,1727,40115,41412,72913,53728,64613,50710,34411,9602,37421,68436,71729,117
5<NA>전월말거주불명자수<NA><NA><NA>1,024423439392974<NA>8420523335532134192112493627241452348547312
6<NA>전월말재외국민등록자수<NA><NA><NA>232152651<NA>202191778289599841241010391810
7<NA>증 가 요 인전 입<NA>3,2454495745380107<NA>3081038584151215571782468947128728216472776814134207211
8<NA><NA><NA>남자<NA>1,657245237304546<NA>16940484082111259112345255743458136462987211196
9<NA><NA><NA>여자<NA>1,588204337233561<NA>13963374469104328712344227129378336313966296115
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>7000000<NA>0000000001000200100210
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>1000000<NA>0000000000000000000010
28<NA>세대수증감<NA><NA><NA>42-14-716-24-9<NA>4-12-1183398-3122-15-7-656-91-7-13-5-11-32-11
29<NA>인구수증감<NA><NA><NA>-385-16-521-16-36<NA>-51-39-360-321019-9137-47-26-28-20-12-54-22-42-49-11-37-915
30<NA>거주불명자수증감<NA><NA><NA>0023-302<NA>12-1-1-3032-100-1-11-22-6-10-130
31<NA>금월말세대수<NA><NA><NA>198,6112,8494,4123,6772,2784,5997,497<NA>18,0097,3865,9785,4919,9037,5802,6949,5906,6907,3643,9457,6067,6345,99711,4555,5175,3706,8591,3198,96616,20111,745
32<NA>금월말인구수<NA><NA><NA>423,3384,4878,4026,5533,9559,14212,467<NA>37,56818,73011,37313,36822,71015,3085,42020,08115,60615,1257,37515,38612,70913,52528,59213,48510,30211,9112,36321,64736,62629,122
33<NA>금월말거주불명자수<NA><NA><NA>1,024423642362976<NA>8522513232532436182112483528221646338537612
34<NA>금월말재외국민등록자수<NA><NA><NA>228152551<NA>192191778289599841241010381710

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