Overview

Dataset statistics

Number of variables35
Number of observations35
Missing cells223
Missing cells (%)18.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.7 KiB
Average record size in memory284.8 B

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2022-08-25
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
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 09:44:14.581536
Analysis finished2024-02-10 09:44:16.067338
Duration1.49 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
2024-02-10T09:44:16.285942image/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%
2024-02-10T09:44:17.232179image/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
2024-02-10T09:44:17.572124image/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%
2024-02-10T09:44:18.356580image/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
2024-02-10T09:44:18.727982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

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

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 북구
2nd row2022.07 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%
2022.07 1
7.1%
현재 1
7.1%
2024-02-10T09:44:19.479183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
2 3
 
7.3%
2
 
4.9%
0 2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (10) 12
29.3%

Most occurring categories

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

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
7 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

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

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
16.1%
4
12.9%
4
12.9%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
2
 
6.5%
1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
7 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 3
30.0%
0 2
20.0%
7 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:44:19.783600image/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%
2024-02-10T09:44:20.320297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:20.675025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.9393939
Min length1

Characters and Unicode

Total characters130
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 row197,373
3rd row426,053
4th row1,267
5th row224
ValueCountFrequency (%)
1 3
 
8.8%
1,534 2
 
5.9%
0 2
 
5.9%
1,136 1
 
2.9%
1,267 1
 
2.9%
224 1
 
2.9%
1,270 1
 
2.9%
425,881 1
 
2.9%
197,542 1
 
2.9%
3 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:44:21.424830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 29
22.3%
, 18
13.8%
2 16
12.3%
3 10
 
7.7%
7 10
 
7.7%
4 9
 
6.9%
6 8
 
6.2%
5 7
 
5.4%
9 7
 
5.4%
0 6
 
4.6%
Other values (5) 10
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107
82.3%
Other Punctuation 18
 
13.8%
Space Separator 2
 
1.5%
Other Letter 2
 
1.5%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 29
27.1%
2 16
15.0%
3 10
 
9.3%
7 10
 
9.3%
4 9
 
8.4%
6 8
 
7.5%
5 7
 
6.5%
9 7
 
6.5%
0 6
 
5.6%
8 5
 
4.7%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 128
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 29
22.7%
, 18
14.1%
2 16
12.5%
3 10
 
7.8%
7 10
 
7.8%
4 9
 
7.0%
6 8
 
6.2%
5 7
 
5.5%
9 7
 
5.5%
0 6
 
4.7%
Other values (3) 8
 
6.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 128
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 29
22.7%
, 18
14.1%
2 16
12.5%
3 10
 
7.8%
7 10
 
7.8%
4 9
 
7.0%
6 8
 
6.2%
5 7
 
5.5%
9 7
 
5.5%
0 6
 
4.7%
Other values (3) 8
 
6.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:21.732390image/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

Unique15 ?
Unique (%)45.5%

Sample

1st row중흥1동
2nd row3,000
3rd row4,724
4th row54
5th row0
ValueCountFrequency (%)
0 10
30.3%
47 2
 
6.1%
17 2
 
6.1%
54 2
 
6.1%
3 2
 
6.1%
15 2
 
6.1%
중흥1동 1
 
3.0%
4,724 1
 
3.0%
24 1
 
3.0%
23 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T09:44:22.348322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.6%
4 10
14.7%
1 8
11.8%
7 8
11.8%
2 7
10.3%
3 5
 
7.4%
5 4
 
5.9%
, 4
 
5.9%
9 2
 
2.9%
- 2
 
2.9%
Other values (4) 4
 
5.9%

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%
4 10
16.9%
1 8
13.6%
7 8
13.6%
2 7
11.9%
3 5
 
8.5%
5 4
 
6.8%
9 2
 
3.4%
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
21.5%
4 10
15.4%
1 8
12.3%
7 8
12.3%
2 7
10.8%
3 5
 
7.7%
5 4
 
6.2%
, 4
 
6.2%
9 2
 
3.1%
- 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%
4 10
15.4%
1 8
12.3%
7 8
12.3%
2 7
10.8%
3 5
 
7.7%
5 4
 
6.2%
, 4
 
6.2%
9 2
 
3.1%
- 2
 
3.1%
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
2024-02-10T09:44:22.677359image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row중흥2동
2nd row4,451
3rd row8,531
4th row61
5th row6
ValueCountFrequency (%)
0 8
24.2%
61 2
 
6.1%
2 2
 
6.1%
6 2
 
6.1%
46 1
 
3.0%
8,531 1
 
3.0%
75 1
 
3.0%
4,449 1
 
3.0%
1 1
 
3.0%
34 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:44:23.318243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13
18.8%
0 9
13.0%
1 8
11.6%
2 8
11.6%
6 6
8.7%
5 5
 
7.2%
3 5
 
7.2%
, 4
 
5.8%
7 3
 
4.3%
8 3
 
4.3%
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 (%)
4 13
21.3%
0 9
14.8%
1 8
13.1%
2 8
13.1%
6 6
9.8%
5 5
 
8.2%
3 5
 
8.2%
7 3
 
4.9%
8 3
 
4.9%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 13
19.7%
0 9
13.6%
1 8
12.1%
2 8
12.1%
6 6
9.1%
5 5
 
7.6%
3 5
 
7.6%
, 4
 
6.1%
7 3
 
4.5%
8 3
 
4.5%
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 (%)
4 13
19.7%
0 9
13.6%
1 8
12.1%
2 8
12.1%
6 6
9.1%
5 5
 
7.6%
3 5
 
7.6%
, 4
 
6.1%
7 3
 
4.5%
8 3
 
4.5%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:23.745969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row중흥3동
2nd row3,564
3rd row6,470
4th row41
5th row3
ValueCountFrequency (%)
0 6
18.2%
3 4
 
12.1%
40 2
 
6.1%
35 1
 
3.0%
41 1
 
3.0%
62 1
 
3.0%
6,530 1
 
3.0%
3,598 1
 
3.0%
1 1
 
3.0%
60 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:44:24.672752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.6%
3 10
14.3%
4 7
10.0%
2 7
10.0%
6 7
10.0%
1 5
 
7.1%
9 5
 
7.1%
5 5
 
7.1%
, 4
 
5.7%
7 3
 
4.3%
Other values (4) 4
 
5.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.6%
3 10
15.9%
4 7
11.1%
2 7
11.1%
6 7
11.1%
1 5
 
7.9%
9 5
 
7.9%
5 5
 
7.9%
7 3
 
4.8%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
19.4%
3 10
14.9%
4 7
10.4%
2 7
10.4%
6 7
10.4%
1 5
 
7.5%
9 5
 
7.5%
5 5
 
7.5%
, 4
 
6.0%
7 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
19.4%
3 10
14.9%
4 7
10.4%
2 7
10.4%
6 7
10.4%
1 5
 
7.5%
9 5
 
7.5%
5 5
 
7.5%
, 4
 
6.0%
7 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:25.321519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique22 ?
Unique (%)66.7%

Sample

1st row중앙동
2nd row2,397
3rd row4,035
4th row51
5th row4
ValueCountFrequency (%)
0 7
21.2%
21 2
 
6.1%
4 2
 
6.1%
5 1
 
3.0%
25 1
 
3.0%
4,054 1
 
3.0%
2,407 1
 
3.0%
2 1
 
3.0%
19 1
 
3.0%
10 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:26.090891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.1%
2 9
13.2%
4 8
11.8%
1 7
10.3%
3 7
10.3%
5 6
8.8%
, 4
 
5.9%
9 4
 
5.9%
7 4
 
5.9%
8 2
 
2.9%
Other values (4) 4
 
5.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.7%
2 9
15.0%
4 8
13.3%
1 7
11.7%
3 7
11.7%
5 6
10.0%
9 4
 
6.7%
7 4
 
6.7%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.0%
2 9
13.8%
4 8
12.3%
1 7
10.8%
3 7
10.8%
5 6
9.2%
, 4
 
6.2%
9 4
 
6.2%
7 4
 
6.2%
8 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 13
20.0%
2 9
13.8%
4 8
12.3%
1 7
10.8%
3 7
10.8%
5 6
9.2%
, 4
 
6.2%
9 4
 
6.2%
7 4
 
6.2%
8 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:44:26.491348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.0882353
Min length1

Characters and Unicode

Total characters71
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row임동
3rd row4,572
4th row9,157
5th row38
ValueCountFrequency (%)
0 7
20.0%
37 3
 
8.6%
5 2
 
5.7%
32 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
44 1
 
2.9%
4,576 1
 
2.9%
1 1
 
2.9%
2 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T09:44:27.511539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 9
12.7%
0 8
11.3%
7 7
9.9%
5 7
9.9%
3 7
9.9%
9 6
8.5%
2 6
8.5%
, 4
 
5.6%
8 3
 
4.2%
1 3
 
4.2%
Other values (10) 11
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
81.7%
Other Letter 6
 
8.5%
Other Punctuation 5
 
7.0%
Dash Punctuation 1
 
1.4%
Space Separator 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9
15.5%
0 8
13.8%
7 7
12.1%
5 7
12.1%
3 7
12.1%
9 6
10.3%
2 6
10.3%
8 3
 
5.2%
1 3
 
5.2%
6 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
91.5%
Hangul 6
 
8.5%

Most frequent character per script

Common
ValueCountFrequency (%)
4 9
13.8%
0 8
12.3%
7 7
10.8%
5 7
10.8%
3 7
10.8%
9 6
9.2%
2 6
9.2%
, 4
6.2%
8 3
 
4.6%
1 3
 
4.6%
Other values (4) 5
7.7%
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 65
91.5%
Hangul 6
 
8.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 9
13.8%
0 8
12.3%
7 7
10.8%
5 7
10.8%
3 7
10.8%
9 6
9.2%
2 6
9.2%
, 4
6.2%
8 3
 
4.6%
1 3
 
4.6%
Other values (4) 5
7.7%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:27.827190image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row신안동
2nd row7,235
3rd row12,364
4th row87
5th row2
ValueCountFrequency (%)
0 7
21.2%
2 3
 
9.1%
1 2
 
6.1%
55 1
 
3.0%
87 1
 
3.0%
12,364 1
 
3.0%
12,353 1
 
3.0%
7,233 1
 
3.0%
11 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:44:28.414711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.7%
1 9
12.5%
2 8
11.1%
0 7
9.7%
6 7
9.7%
8 5
6.9%
5 5
6.9%
4 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
Other values (5) 8
11.1%

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 (%)
3 12
19.0%
1 9
14.3%
2 8
12.7%
0 7
11.1%
6 7
11.1%
8 5
7.9%
5 5
7.9%
4 4
 
6.3%
9 3
 
4.8%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
17.4%
1 9
13.0%
2 8
11.6%
0 7
10.1%
6 7
10.1%
8 5
7.2%
5 5
7.2%
4 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
7.2%
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 (%)
3 12
17.4%
1 9
13.0%
2 8
11.6%
0 7
10.1%
6 7
10.1%
8 5
7.2%
5 5
7.2%
4 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
7.2%
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
Minimum2022-08-19 00:00:00
Maximum2022-08-19 00:00:00
2024-02-10T09:44:28.637492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:44:28.946767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:29.226669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6363636
Min length1

Characters and Unicode

Total characters87
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 row용봉동
2nd row17,840
3rd row38,077
4th row123
5th row20
ValueCountFrequency (%)
0 6
 
18.2%
12 2
 
6.1%
20 2
 
6.1%
138 1
 
3.0%
123 1
 
3.0%
211 1
 
3.0%
38,047 1
 
3.0%
17,847 1
 
3.0%
1 1
 
3.0%
30 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:44:29.922280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.5%
0 13
14.9%
7 10
11.5%
8 10
11.5%
2 8
9.2%
4 7
8.0%
3 7
8.0%
, 4
 
4.6%
6 3
 
3.4%
9 3
 
3.4%
Other values (5) 5
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
90.8%
Other Punctuation 4
 
4.6%
Other Letter 3
 
3.4%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.5%
0 13
16.5%
7 10
12.7%
8 10
12.7%
2 8
10.1%
4 7
8.9%
3 7
8.9%
6 3
 
3.8%
9 3
 
3.8%
5 1
 
1.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
20.2%
0 13
15.5%
7 10
11.9%
8 10
11.9%
2 8
9.5%
4 7
8.3%
3 7
8.3%
, 4
 
4.8%
6 3
 
3.6%
9 3
 
3.6%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
20.2%
0 13
15.5%
7 10
11.9%
8 10
11.9%
2 8
9.5%
4 7
8.3%
3 7
8.3%
, 4
 
4.8%
6 3
 
3.6%
9 3
 
3.6%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:30.294525image/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 row운암1동
2nd row7,459
3rd row19,180
4th row27
5th row17
ValueCountFrequency (%)
0 7
21.2%
4 3
 
9.1%
27 3
 
9.1%
52 2
 
6.1%
40 2
 
6.1%
151 1
 
3.0%
19,140 1
 
3.0%
7,463 1
 
3.0%
72 1
 
3.0%
82 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:44:30.878999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.2%
1 12
16.2%
2 8
10.8%
4 8
10.8%
7 7
9.5%
5 5
6.8%
8 5
6.8%
, 4
 
5.4%
9 4
 
5.4%
3 3
 
4.1%
Other values (5) 6
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
89.2%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.2%
1 12
18.2%
2 8
12.1%
4 8
12.1%
7 7
10.6%
5 5
7.6%
8 5
7.6%
9 4
 
6.1%
3 3
 
4.5%
6 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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.9%
1 12
16.9%
2 8
11.3%
4 8
11.3%
7 7
9.9%
5 5
7.0%
8 5
7.0%
, 4
 
5.6%
9 4
 
5.6%
3 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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.9%
1 12
16.9%
2 8
11.3%
4 8
11.3%
7 7
9.9%
5 5
7.0%
8 5
7.0%
, 4
 
5.6%
9 4
 
5.6%
3 3
 
4.2%
Other values (2) 3
 
4.2%
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
2024-02-10T09:44:31.142307image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row운암2동
2nd row6,093
3rd row11,785
4th row57
5th row7
ValueCountFrequency (%)
0 5
 
15.2%
1 3
 
9.1%
57 2
 
6.1%
66 1
 
3.0%
128 1
 
3.0%
11,743 1
 
3.0%
6,087 1
 
3.0%
42 1
 
3.0%
6 1
 
3.0%
12 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:44:31.928763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
14.3%
0 8
11.4%
7 8
11.4%
3 8
11.4%
6 7
10.0%
2 6
8.6%
5 5
7.1%
8 5
7.1%
4 5
7.1%
, 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 (%)
1 10
14.3%
0 8
11.4%
7 8
11.4%
3 8
11.4%
6 7
10.0%
2 6
8.6%
5 5
7.1%
8 5
7.1%
4 5
7.1%
, 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:32.243330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row운암3동
2nd row5,225
3rd row12,847
4th row29
5th row15
ValueCountFrequency (%)
0 8
24.2%
29 2
 
6.1%
15 2
 
6.1%
42 1
 
3.0%
12,847 1
 
3.0%
52 1
 
3.0%
5,364 1
 
3.0%
311 1
 
3.0%
139 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:44:32.884302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.2%
1 12
15.0%
5 11
13.8%
2 11
13.8%
3 10
12.5%
4 5
 
6.2%
9 4
 
5.0%
, 4
 
5.0%
7 3
 
3.8%
8 3
 
3.8%
Other values (4) 4
 
5.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
17.8%
1 12
16.4%
5 11
15.1%
2 11
15.1%
3 10
13.7%
4 5
 
6.8%
9 4
 
5.5%
7 3
 
4.1%
8 3
 
4.1%
6 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
16.9%
1 12
15.6%
5 11
14.3%
2 11
14.3%
3 10
13.0%
4 5
 
6.5%
9 4
 
5.2%
, 4
 
5.2%
7 3
 
3.9%
8 3
 
3.9%
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 13
16.9%
1 12
15.6%
5 11
14.3%
2 11
14.3%
3 10
13.0%
4 5
 
6.5%
9 4
 
5.2%
, 4
 
5.2%
7 3
 
3.9%
8 3
 
3.9%
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
2024-02-10T09:44:33.159981image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row동림동
2nd row9,883
3rd row23,036
4th row54
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
81 1
 
3.0%
23,071 1
 
3.0%
9,903 1
 
3.0%
1 1
 
3.0%
35 1
 
3.0%
20 1
 
3.0%
7 1
 
3.0%
47 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:44:33.865448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 66
89.2%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.7%
1 8
12.1%
5 8
12.1%
3 8
12.1%
2 7
10.6%
8 6
9.1%
9 6
9.1%
7 5
 
7.6%
4 3
 
4.5%
6 2
 
3.0%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
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%
1 8
11.3%
5 8
11.3%
3 8
11.3%
2 7
9.9%
8 6
8.5%
9 6
8.5%
7 5
 
7.0%
, 4
 
5.6%
4 3
 
4.2%
Other values (2) 3
 
4.2%
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%
1 8
11.3%
5 8
11.3%
3 8
11.3%
2 7
9.9%
8 6
8.5%
9 6
8.5%
7 5
 
7.0%
, 4
 
5.6%
4 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:34.270561image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row우산동
2nd row5,606
3rd row10,172
4th row61
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
61 2
 
6.1%
2 1
 
3.0%
80 1
 
3.0%
5,610 1
 
3.0%
11 1
 
3.0%
4 1
 
3.0%
6 1
 
3.0%
22 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:35.099853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
21.7%
1 13
18.8%
6 7
10.1%
7 5
 
7.2%
3 5
 
7.2%
2 5
 
7.2%
, 4
 
5.8%
5 3
 
4.3%
4 3
 
4.3%
8 3
 
4.3%
Other values (5) 6
 
8.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
24.6%
1 13
21.3%
6 7
11.5%
7 5
 
8.2%
3 5
 
8.2%
2 5
 
8.2%
5 3
 
4.9%
4 3
 
4.9%
8 3
 
4.9%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
22.7%
1 13
19.7%
6 7
10.6%
7 5
 
7.6%
3 5
 
7.6%
2 5
 
7.6%
, 4
 
6.1%
5 3
 
4.5%
4 3
 
4.5%
8 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
22.7%
1 13
19.7%
6 7
10.6%
7 5
 
7.6%
3 5
 
7.6%
2 5
 
7.6%
, 4
 
6.1%
5 3
 
4.5%
4 3
 
4.5%
8 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:35.441649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

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

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row풍향동
2nd row2,773
3rd row5,658
4th row25
5th row2
ValueCountFrequency (%)
0 7
21.2%
2 5
15.2%
23 2
 
6.1%
18 2
 
6.1%
2,773 2
 
6.1%
7 2
 
6.1%
26 1
 
3.0%
22 1
 
3.0%
5 1
 
3.0%
9 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T09:44:36.304674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
21.5%
0 8
12.3%
5 7
10.8%
1 6
9.2%
7 6
9.2%
3 5
 
7.7%
, 4
 
6.2%
8 3
 
4.6%
6 3
 
4.6%
9 2
 
3.1%
Other values (5) 7
10.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
86.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%
Dash Punctuation 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
25.0%
0 8
14.3%
5 7
12.5%
1 6
10.7%
7 6
10.7%
3 5
 
8.9%
8 3
 
5.4%
6 3
 
5.4%
9 2
 
3.6%
4 2
 
3.6%
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 62
95.4%
Hangul 3
 
4.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
22.6%
0 8
12.9%
5 7
11.3%
1 6
9.7%
7 6
9.7%
3 5
 
8.1%
, 4
 
6.5%
8 3
 
4.8%
6 3
 
4.8%
9 2
 
3.2%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
22.6%
0 8
12.9%
5 7
11.3%
1 6
9.7%
7 6
9.7%
3 5
 
8.1%
, 4
 
6.5%
8 3
 
4.8%
6 3
 
4.8%
9 2
 
3.2%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:36.700767image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row문화동
2nd row9,691
3rd row20,644
4th row55
5th row7
ValueCountFrequency (%)
0 8
24.2%
55 2
 
6.1%
7 2
 
6.1%
59 1
 
3.0%
20,644 1
 
3.0%
85 1
 
3.0%
9,695 1
 
3.0%
25 1
 
3.0%
4 1
 
3.0%
12 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:44:37.709512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
5 11
15.3%
4 9
12.5%
6 7
9.7%
9 7
9.7%
1 5
6.9%
2 5
6.9%
7 4
 
5.6%
, 4
 
5.6%
3 3
 
4.2%
Other values (5) 6
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
5 11
17.2%
4 9
14.1%
6 7
10.9%
9 7
10.9%
1 5
7.8%
2 5
7.8%
7 4
 
6.2%
3 3
 
4.7%
8 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
5 11
15.9%
4 9
13.0%
6 7
10.1%
9 7
10.1%
1 5
7.2%
2 5
7.2%
7 4
 
5.8%
, 4
 
5.8%
3 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.9%
5 11
15.9%
4 9
13.0%
6 7
10.1%
9 7
10.1%
1 5
7.2%
2 5
7.2%
7 4
 
5.8%
, 4
 
5.8%
3 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:38.076300image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row문흥1동
2nd row6,462
3rd row15,648
4th row28
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 2
 
6.1%
46 2
 
6.1%
39 2
 
6.1%
28 2
 
6.1%
2 1
 
3.0%
60 1
 
3.0%
15,635 1
 
3.0%
6,464 1
 
3.0%
1 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:44:38.718199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
6 10
13.9%
4 8
11.1%
1 7
9.7%
2 6
8.3%
5 6
8.3%
9 5
6.9%
3 5
6.9%
8 4
 
5.6%
, 4
 
5.6%
Other values (5) 6
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.5%
6 10
15.9%
4 8
12.7%
1 7
11.1%
2 6
9.5%
5 6
9.5%
9 5
7.9%
3 5
7.9%
8 4
 
6.3%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.9%
6 10
14.5%
4 8
11.6%
1 7
10.1%
2 6
8.7%
5 6
8.7%
9 5
7.2%
3 5
7.2%
8 4
 
5.8%
, 4
 
5.8%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.9%
6 10
14.5%
4 8
11.6%
1 7
10.1%
2 6
8.7%
5 6
8.7%
9 5
7.2%
3 5
7.2%
8 4
 
5.8%
, 4
 
5.8%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:38.975023image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row문흥2동
2nd row7,375
3rd row15,492
4th row32
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 2
 
6.1%
49 2
 
6.1%
7,375 2
 
6.1%
32 2
 
6.1%
57 1
 
3.0%
15,492 1
 
3.0%
152 1
 
3.0%
21 1
 
3.0%
8 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:44:39.730576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
14.1%
2 8
12.5%
4 8
12.5%
3 7
10.9%
1 7
10.9%
7 6
9.4%
5 6
9.4%
6 6
9.4%
9 4
6.2%
8 3
 
4.7%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
13.0%
2 8
11.6%
4 8
11.6%
3 7
10.1%
1 7
10.1%
7 6
8.7%
5 6
8.7%
6 6
8.7%
9 4
5.8%
, 4
5.8%
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 9
13.0%
2 8
11.6%
4 8
11.6%
3 7
10.1%
1 7
10.1%
7 6
8.7%
5 6
8.7%
6 6
8.7%
9 4
5.8%
, 4
5.8%
Other values (2) 4
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:39.963417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row두암1동
2nd row4,010
3rd row7,673
4th row23
5th row8
ValueCountFrequency (%)
0 8
24.2%
8 3
 
9.1%
22 2
 
6.1%
37 1
 
3.0%
23 1
 
3.0%
7,673 1
 
3.0%
4,013 1
 
3.0%
1 1
 
3.0%
11 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:44:40.736226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.0%
3 9
15.0%
1 8
13.3%
2 7
11.7%
7 7
11.7%
8 6
10.0%
4 6
10.0%
6 4
 
6.7%
5 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.2%
3 9
13.6%
1 8
12.1%
2 7
10.6%
7 7
10.6%
8 6
9.1%
4 6
9.1%
6 4
 
6.1%
, 4
 
6.1%
- 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 (%)
0 12
18.2%
3 9
13.6%
1 8
12.1%
2 7
10.6%
7 7
10.6%
8 6
9.1%
4 6
9.1%
6 4
 
6.1%
, 4
 
6.1%
- 2
 
3.0%
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
2024-02-10T09:44:41.054348image/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 row두암2동
2nd row7,693
3rd row15,862
4th row54
5th row9
ValueCountFrequency (%)
0 7
21.2%
47 2
 
6.1%
2 2
 
6.1%
8 2
 
6.1%
9 2
 
6.1%
49 1
 
3.0%
54 1
 
3.0%
121 1
 
3.0%
15,817 1
 
3.0%
7,685 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:44:41.749344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.3%
7 8
11.0%
5 8
11.0%
8 7
9.6%
6 7
9.6%
1 7
9.6%
2 6
8.2%
4 5
6.8%
9 4
5.5%
, 4
5.5%
Other values (5) 8
11.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
14.1%
7 8
12.5%
5 8
12.5%
8 7
10.9%
6 7
10.9%
1 7
10.9%
2 6
9.4%
4 5
7.8%
9 4
6.2%
3 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 9
12.9%
7 8
11.4%
5 8
11.4%
8 7
10.0%
6 7
10.0%
1 7
10.0%
2 6
8.6%
4 5
7.1%
9 4
5.7%
, 4
5.7%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
12.9%
7 8
11.4%
5 8
11.4%
8 7
10.0%
6 7
10.0%
1 7
10.0%
2 6
8.6%
4 5
7.1%
9 4
5.7%
, 4
5.7%
Other values (2) 5
7.1%
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
2024-02-10T09:44:42.081249image/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 row두암3동
2nd row7,752
3rd row13,136
4th row46
5th row8
ValueCountFrequency (%)
0 7
21.2%
46 4
 
12.1%
1 2
 
6.1%
8 2
 
6.1%
37 2
 
6.1%
73 1
 
3.0%
7,756 1
 
3.0%
4 1
 
3.0%
5 1
 
3.0%
56 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:44:42.772730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.1%
4 8
11.3%
3 8
11.3%
6 7
9.9%
1 7
9.9%
7 7
9.9%
5 7
9.9%
, 4
 
5.6%
9 4
 
5.6%
2 3
 
4.2%
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 (%)
0 10
15.9%
4 8
12.7%
3 8
12.7%
6 7
11.1%
1 7
11.1%
7 7
11.1%
5 7
11.1%
9 4
 
6.3%
2 3
 
4.8%
8 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 (%)
0 10
14.7%
4 8
11.8%
3 8
11.8%
6 7
10.3%
1 7
10.3%
7 7
10.3%
5 7
10.3%
, 4
 
5.9%
9 4
 
5.9%
2 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
4 8
11.8%
3 8
11.8%
6 7
10.3%
1 7
10.3%
7 7
10.3%
5 7
10.3%
, 4
 
5.9%
9 4
 
5.9%
2 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:43.147373image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row삼각동
2nd row6,050
3rd row13,856
4th row29
5th row4
ValueCountFrequency (%)
0 6
18.2%
4 2
 
6.1%
68 2
 
6.1%
30 2
 
6.1%
3 2
 
6.1%
142 1
 
3.0%
6,053 1
 
3.0%
1 1
 
3.0%
6 1
 
3.0%
52 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:44:43.819561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.9%
3 8
11.3%
6 8
11.3%
5 8
11.3%
2 7
9.9%
4 6
8.5%
1 6
8.5%
8 5
7.0%
, 4
 
5.6%
7 2
 
2.8%
Other values (5) 5
7.0%

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 (%)
0 12
19.0%
3 8
12.7%
6 8
12.7%
5 8
12.7%
2 7
11.1%
4 6
9.5%
1 6
9.5%
8 5
7.9%
7 2
 
3.2%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.6%
3 8
11.8%
6 8
11.8%
5 8
11.8%
2 7
10.3%
4 6
8.8%
1 6
8.8%
8 5
7.4%
, 4
 
5.9%
7 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.6%
3 8
11.8%
6 8
11.8%
5 8
11.8%
2 7
10.3%
4 6
8.8%
1 6
8.8%
8 5
7.4%
, 4
 
5.9%
7 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:44.184368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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 row일곡동
2nd row11,560
3rd row29,446
4th row33
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
12 2
 
6.1%
126 1
 
3.0%
248 1
 
3.0%
29,356 1
 
3.0%
11,561 1
 
3.0%
90 1
 
3.0%
8 1
 
3.0%
93 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:44:44.780009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.7%
2 10
12.8%
0 9
11.5%
5 8
10.3%
6 7
9.0%
3 7
9.0%
4 6
7.7%
8 5
 
6.4%
, 4
 
5.1%
9 4
 
5.1%
Other values (5) 5
 
6.4%

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%
2 10
14.3%
0 9
12.9%
5 8
11.4%
6 7
10.0%
3 7
10.0%
4 6
8.6%
8 5
 
7.1%
9 4
 
5.7%
7 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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.3%
2 10
13.3%
0 9
12.0%
5 8
10.7%
6 7
9.3%
3 7
9.3%
4 6
8.0%
8 5
 
6.7%
, 4
 
5.3%
9 4
 
5.3%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
17.3%
2 10
13.3%
0 9
12.0%
5 8
10.7%
6 7
9.3%
3 7
9.3%
4 6
8.0%
8 5
 
6.7%
, 4
 
5.3%
9 4
 
5.3%
Other values (2) 2
 
2.7%
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
2024-02-10T09:44:45.092884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters13
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 row5,504
3rd row13,732
4th row24
5th row5
ValueCountFrequency (%)
0 8
24.2%
24 3
 
9.1%
5 2
 
6.1%
55 2
 
6.1%
14 1
 
3.0%
107 1
 
3.0%
5,506 1
 
3.0%
10 1
 
3.0%
2 1
 
3.0%
6 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:44:45.788470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
19.7%
5 13
18.3%
2 9
12.7%
4 7
9.9%
1 7
9.9%
3 5
 
7.0%
, 4
 
5.6%
7 4
 
5.6%
6 4
 
5.6%
1
 
1.4%
Other values (3) 3
 
4.2%

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 (%)
0 14
22.2%
5 13
20.6%
2 9
14.3%
4 7
11.1%
1 7
11.1%
3 5
 
7.9%
7 4
 
6.3%
6 4
 
6.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.6%
5 13
19.1%
2 9
13.2%
4 7
10.3%
1 7
10.3%
3 5
 
7.4%
, 4
 
5.9%
7 4
 
5.9%
6 4
 
5.9%
- 1
 
1.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
20.6%
5 13
19.1%
2 9
13.2%
4 7
10.3%
1 7
10.3%
3 5
 
7.4%
, 4
 
5.9%
7 4
 
5.9%
6 4
 
5.9%
- 1
 
1.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:46.134604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row오치1동
2nd row5,483
3rd row10,709
4th row46
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
8 3
 
9.1%
2 2
 
6.1%
78 1
 
3.0%
146 1
 
3.0%
10,674 1
 
3.0%
5,475 1
 
3.0%
35 1
 
3.0%
4 1
 
3.0%
30 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:46.768695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.2%
4 8
10.8%
1 8
10.8%
8 6
8.1%
5 6
8.1%
3 6
8.1%
6 6
8.1%
2 4
 
5.4%
, 4
 
5.4%
7 4
 
5.4%
Other values (5) 10
13.5%

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 12
18.8%
4 8
12.5%
1 8
12.5%
8 6
9.4%
5 6
9.4%
3 6
9.4%
6 6
9.4%
2 4
 
6.2%
7 4
 
6.2%
9 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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.9%
4 8
11.3%
1 8
11.3%
8 6
8.5%
5 6
8.5%
3 6
8.5%
6 6
8.5%
2 4
 
5.6%
, 4
 
5.6%
7 4
 
5.6%
Other values (2) 7
9.9%
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%
4 8
11.3%
1 8
11.3%
8 6
8.5%
5 6
8.5%
3 6
8.5%
6 6
8.5%
2 4
 
5.6%
, 4
 
5.6%
7 4
 
5.6%
Other values (2) 7
9.9%
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
2024-02-10T09:44:47.133993image/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 row오치2동
2nd row6,983
3rd row12,320
4th row37
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
10 2
 
6.1%
62 2
 
6.1%
37 2
 
6.1%
25 1
 
3.0%
74 1
 
3.0%
12,288 1
 
3.0%
6,977 1
 
3.0%
7 1
 
3.0%
32 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:47.938057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.7%
2 11
16.7%
3 8
12.1%
1 8
12.1%
7 7
10.6%
6 7
10.6%
4 5
7.6%
9 4
 
6.1%
8 3
 
4.5%
5 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.3%
2 11
15.3%
3 8
11.1%
1 8
11.1%
7 7
9.7%
6 7
9.7%
4 5
6.9%
, 4
 
5.6%
9 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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.3%
2 11
15.3%
3 8
11.1%
1 8
11.1%
7 7
9.7%
6 7
9.7%
4 5
6.9%
, 4
 
5.6%
9 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: 31
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:48.173716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7272727
Min length1

Characters and Unicode

Total characters57
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

Unique11 ?
Unique (%)33.3%

Sample

1st row석곡동
2nd row1,384
3rd row2,493
4th row22
5th row3
ValueCountFrequency (%)
0 8
24.2%
4 3
 
9.1%
3 3
 
9.1%
5 3
 
9.1%
1 2
 
6.1%
2 2
 
6.1%
22 2
 
6.1%
14 1
 
3.0%
7 1
 
3.0%
2,493 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T09:44:48.930121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 9
15.8%
0 8
14.0%
1 8
14.0%
4 7
12.3%
3 6
10.5%
, 4
7.0%
5 3
 
5.3%
8 3
 
5.3%
9 2
 
3.5%
- 2
 
3.5%
Other values (5) 5
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
84.2%
Other Punctuation 4
 
7.0%
Other Letter 3
 
5.3%
Dash Punctuation 2
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 9
18.8%
0 8
16.7%
1 8
16.7%
4 7
14.6%
3 6
12.5%
5 3
 
6.2%
8 3
 
6.2%
9 2
 
4.2%
6 1
 
2.1%
7 1
 
2.1%
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 54
94.7%
Hangul 3
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 9
16.7%
0 8
14.8%
1 8
14.8%
4 7
13.0%
3 6
11.1%
, 4
7.4%
5 3
 
5.6%
8 3
 
5.6%
9 2
 
3.7%
- 2
 
3.7%
Other values (2) 2
 
3.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
94.7%
Hangul 3
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 9
16.7%
0 8
14.8%
1 8
14.8%
4 7
13.0%
3 6
11.1%
, 4
7.4%
5 3
 
5.6%
8 3
 
5.6%
9 2
 
3.7%
- 2
 
3.7%
Other values (2) 2
 
3.7%
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
2024-02-10T09:44:49.191654image/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 row건국동
2nd row9,133
3rd row22,012
4th row61
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
12 2
 
6.1%
71 2
 
6.1%
61 2
 
6.1%
63 1
 
3.0%
95 1
 
3.0%
21,985 1
 
3.0%
9,110 1
 
3.0%
27 1
 
3.0%
23 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:49.895770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
2 9
12.0%
0 8
10.7%
3 7
9.3%
6 6
8.0%
5 6
8.0%
9 5
 
6.7%
7 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
Other values (5) 8
10.7%

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 (%)
1 14
21.2%
2 9
13.6%
0 8
12.1%
3 7
10.6%
6 6
9.1%
5 6
9.1%
9 5
 
7.6%
7 4
 
6.1%
4 4
 
6.1%
8 3
 
4.5%
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 (%)
1 14
19.4%
2 9
12.5%
0 8
11.1%
3 7
9.7%
6 6
8.3%
5 6
8.3%
9 5
 
6.9%
7 4
 
5.6%
, 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 (%)
1 14
19.4%
2 9
12.5%
0 8
11.1%
3 7
9.7%
6 6
8.3%
5 6
8.3%
9 5
 
6.9%
7 4
 
5.6%
, 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: 33
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:50.264398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
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 row16,376
3rd row37,420
4th row61
5th row19
ValueCountFrequency (%)
0 5
 
15.2%
96 2
 
6.1%
170 1
 
3.0%
60 1
 
3.0%
37,396 1
 
3.0%
16,370 1
 
3.0%
1 1
 
3.0%
24 1
 
3.0%
6 1
 
3.0%
2 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T09:44:50.949782image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.8%
0 14
16.3%
7 10
11.6%
6 9
10.5%
3 9
10.5%
9 6
 
7.0%
4 5
 
5.8%
, 4
 
4.7%
2 4
 
4.7%
- 3
 
3.5%
Other values (5) 5
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
88.4%
Other Punctuation 4
 
4.7%
Dash Punctuation 3
 
3.5%
Other Letter 3
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
22.4%
0 14
18.4%
7 10
13.2%
6 9
11.8%
3 9
11.8%
9 6
 
7.9%
4 5
 
6.6%
2 4
 
5.3%
5 1
 
1.3%
8 1
 
1.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
20.5%
0 14
16.9%
7 10
12.0%
6 9
10.8%
3 9
10.8%
9 6
 
7.2%
4 5
 
6.0%
, 4
 
4.8%
2 4
 
4.8%
- 3
 
3.6%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
20.5%
0 14
16.9%
7 10
12.0%
6 9
10.8%
3 9
10.8%
9 6
 
7.2%
4 5
 
6.0%
, 4
 
4.8%
2 4
 
4.8%
- 3
 
3.6%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:51.284587image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row신용동
2nd row11,819
3rd row29,574
4th row8
5th row10
ValueCountFrequency (%)
0 7
21.2%
60 2
 
6.1%
8 2
 
6.1%
15 1
 
3.0%
247 1
 
3.0%
29,527 1
 
3.0%
11,814 1
 
3.0%
47 1
 
3.0%
5 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:51.994626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
22.8%
0 11
13.9%
9 6
 
7.6%
5 6
 
7.6%
7 6
 
7.6%
4 6
 
7.6%
8 5
 
6.3%
2 5
 
6.3%
, 4
 
5.1%
3 4
 
5.1%
Other values (5) 8
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
88.6%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
25.7%
0 11
15.7%
9 6
 
8.6%
5 6
 
8.6%
7 6
 
8.6%
4 6
 
8.6%
8 5
 
7.1%
2 5
 
7.1%
3 4
 
5.7%
6 3
 
4.3%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
23.7%
0 11
14.5%
9 6
 
7.9%
5 6
 
7.9%
7 6
 
7.9%
4 6
 
7.9%
8 5
 
6.6%
2 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 5
 
6.6%
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 18
23.7%
0 11
14.5%
9 6
 
7.9%
5 6
 
7.9%
7 6
 
7.9%
4 6
 
7.9%
8 5
 
6.6%
2 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 5
 
6.6%
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>2022.08.19<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>2022.07 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>197,3733,0004,4513,5642,3974,5727,235<NA>17,8407,4596,0935,2259,8835,6062,7739,6916,4627,3754,0107,6937,7526,05011,5605,5045,4836,9831,3849,13316,37611,819
4<NA>전월말인구수<NA><NA><NA>426,0534,7248,5316,4704,0359,15712,364<NA>38,07719,18011,78512,84723,03610,1725,65820,64415,64815,4927,67315,86213,13613,85629,44613,73210,70912,3202,49322,01237,42029,574
5<NA>전월말거주불명자수<NA><NA><NA>1,267546141513887<NA>12327572954612555283223544629332446372261618
6<NA>전월말재외국민등록자수<NA><NA><NA>224063452<NA>201771587279489841258103121910
7<NA>증 가 요 인전 입<NA>3,827471211607094131<NA>3711109441720270391429813280121951101581001121107135304197
8<NA><NA><NA>남자<NA>1,966246799374969<NA>1835856208904021734669335350548355596357115794
9<NA><NA><NA>여자<NA>1,861235461334562<NA>188523820911230186952634768455675455347264147103
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>4000000<NA>0000000000000000000220
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>1000000<NA>0010000000000000000000
28<NA>세대수증감<NA><NA><NA>169-3-234104-2<NA>74-613920404203-84312-8-6-3-23-6-5
29<NA>인구수증감<NA><NA><NA>-172-1160192-11<NA>-30-40-4231135-11-7-25-13-21-11-45-37-30-90-10-35-32-11-27-24-47
30<NA>거주불명자수증감<NA><NA><NA>3001-2-11<NA>1000-10-20-10-120110-2700-10
31<NA>금월말세대수<NA><NA><NA>197,5422,9974,4493,5982,4074,5767,233<NA>17,8477,4636,0875,3649,9035,6102,7739,6956,4647,3754,0137,6857,7566,05311,5615,5065,4756,9771,3819,11016,37011,814
32<NA>금월말인구수<NA><NA><NA>425,8814,7238,5326,5304,0549,15912,353<NA>38,04719,14011,74313,15823,07110,1615,65120,61915,63515,4717,66215,81713,09913,82629,35613,72210,67412,2882,48221,98537,39629,527
33<NA>금월말거주불명자수<NA><NA><NA>1,270546142493788<NA>12427572953612355273222564630342444442261608
34<NA>금월말재외국민등록자수<NA><NA><NA>221063452<NA>2018815872794898412581039189