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

Description2022-07-08
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 09:43:30.877583
Analysis finished2024-02-10 09:43:32.273794
Duration1.4 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
2024-02-10T09:43:32.490997image/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%
2024-02-10T09:43:33.412723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
11
 
8.7%
8
 
6.3%
8
 
6.3%
5
 
4.0%
5
 
4.0%
4
 
3.2%
4
 
3.2%
4
 
3.2%
4
 
3.2%
Other values (33) 61
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
82.5%
Control 12
 
9.5%
Space Separator 4
 
3.2%
Other Punctuation 4
 
3.2%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%
Other Punctuation
ValueCountFrequency (%)
, 2
50.0%
: 2
50.0%
Control
ValueCountFrequency (%)
12
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
82.5%
Common 22
 
17.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%
Common
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
82.5%
ASCII 22
 
17.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
54.5%
4
 
18.2%
, 2
 
9.1%
: 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%
Hangul
ValueCountFrequency (%)
11
 
10.6%
8
 
7.7%
8
 
7.7%
5
 
4.8%
5
 
4.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
4
 
3.8%
Other values (27) 47
45.2%

Unnamed: 2
Text

MISSING 

Distinct9
Distinct (%)81.8%
Missing24
Missing (%)68.6%
Memory size412.0 B
2024-02-10T09:43:33.746698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.3636364
Min length2

Characters and Unicode

Total characters26
Distinct characters17
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)63.6%

Sample

1st row전 입
2nd row복귀
3rd row출생
4th row등록
5th row국외
ValueCountFrequency (%)
국외 2
15.4%
기타 2
15.4%
2
15.4%
1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T09:43:34.247817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
2
 
7.7%
1
 
3.8%
1
 
3.8%
1
 
3.8%
Other values (7) 7
26.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 22
84.6%
Control 4
 
15.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%
Control
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 22
84.6%
Common 4
 
15.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 22
84.6%
ASCII 4
 
15.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
100.0%
Hangul
ValueCountFrequency (%)
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
2
 
9.1%
1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Other values (6) 6
27.3%

Unnamed: 3
Text

MISSING 

Distinct7
Distinct (%)58.3%
Missing23
Missing (%)65.7%
Memory size412.0 B
2024-02-10T09:43:34.598980image/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 row2022.06 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%
2022.06 1
7.1%
현재 1
7.1%
2024-02-10T09:43:35.285840image/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%
6 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%
6 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%
6 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:43:35.500935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군구내
2nd row시군구간
3rd row시군구내
4th row시군구간
ValueCountFrequency (%)
시군구내 2
50.0%
시군구간 2
50.0%
2024-02-10T09:43:35.940913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:36.368681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4
Min length1

Characters and Unicode

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

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row197,158
3rd row426,329
4th row1,278
5th row222
ValueCountFrequency (%)
0 4
 
11.8%
1,791 2
 
5.9%
2,346 1
 
2.9%
1,267 1
 
2.9%
426,053 1
 
2.9%
197,373 1
 
2.9%
11 1
 
2.9%
276 1
 
2.9%
215 1
 
2.9%
1 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:43:37.357335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 25
18.9%
2 20
15.2%
, 18
13.6%
4 12
9.1%
0 8
 
6.1%
7 8
 
6.1%
9 8
 
6.1%
6 8
 
6.1%
3 7
 
5.3%
5 6
 
4.5%
Other values (5) 12
9.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
23.1%
2 20
18.5%
4 12
11.1%
0 8
 
7.4%
7 8
 
7.4%
9 8
 
7.4%
6 8
 
7.4%
3 7
 
6.5%
5 6
 
5.6%
8 6
 
5.6%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 25
19.2%
2 20
15.4%
, 18
13.8%
4 12
9.2%
0 8
 
6.2%
7 8
 
6.2%
9 8
 
6.2%
6 8
 
6.2%
3 7
 
5.4%
5 6
 
4.6%
Other values (3) 10
 
7.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 25
19.2%
2 20
15.4%
, 18
13.8%
4 12
9.2%
0 8
 
6.2%
7 8
 
6.2%
9 8
 
6.2%
6 8
 
6.2%
3 7
 
5.4%
5 6
 
4.6%
Other values (3) 10
 
7.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:37.712314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
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

Unique16 ?
Unique (%)48.5%

Sample

1st row중흥1동
2nd row3,002
3rd row4,727
4th row55
5th row0
ValueCountFrequency (%)
0 9
27.3%
26 2
 
6.1%
60 2
 
6.1%
19 2
 
6.1%
3 2
 
6.1%
30 2
 
6.1%
3,002 1
 
3.0%
55 1
 
3.0%
34 1
 
3.0%
4,727 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:43:38.524711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
26.1%
3 7
 
10.1%
2 7
 
10.1%
6 6
 
8.7%
1 6
 
8.7%
5 5
 
7.2%
4 5
 
7.2%
, 4
 
5.8%
7 3
 
4.3%
- 3
 
4.3%
Other values (4) 5
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
85.5%
Other Punctuation 4
 
5.8%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
30.5%
3 7
 
11.9%
2 7
 
11.9%
6 6
 
10.2%
1 6
 
10.2%
5 5
 
8.5%
4 5
 
8.5%
7 3
 
5.1%
9 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
27.3%
3 7
 
10.6%
2 7
 
10.6%
6 6
 
9.1%
1 6
 
9.1%
5 5
 
7.6%
4 5
 
7.6%
, 4
 
6.1%
7 3
 
4.5%
- 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 18
27.3%
3 7
 
10.6%
2 7
 
10.6%
6 6
 
9.1%
1 6
 
9.1%
5 5
 
7.6%
4 5
 
7.6%
, 4
 
6.1%
7 3
 
4.5%
- 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:38.852984image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row중흥2동
2nd row4,407
3rd row8,461
4th row62
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
83 2
 
6.1%
1 2
 
6.1%
6 2
 
6.1%
32 1
 
3.0%
46 1
 
3.0%
8,531 1
 
3.0%
4,451 1
 
3.0%
70 1
 
3.0%
44 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:39.757693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 10
16.1%
0 9
14.5%
1 8
12.9%
5 8
12.9%
6 7
11.3%
8 7
11.3%
3 5
8.1%
2 5
8.1%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
4 10
14.9%
0 9
13.4%
1 8
11.9%
5 8
11.9%
6 7
10.4%
8 7
10.4%
3 5
7.5%
2 5
7.5%
, 4
 
6.0%
7 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 10
14.9%
0 9
13.4%
1 8
11.9%
5 8
11.9%
6 7
10.4%
8 7
10.4%
3 5
7.5%
2 5
7.5%
, 4
 
6.0%
7 2
 
3.0%
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
2024-02-10T09:43:40.090953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.3333333
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row중흥3동
2nd row3,458
3rd row6,324
4th row42
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
42 2
 
6.1%
38 2
 
6.1%
33 1
 
3.0%
6,324 1
 
3.0%
249 1
 
3.0%
6,470 1
 
3.0%
3,564 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:43:40.828293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.9%
3 12
15.6%
4 9
11.7%
1 9
11.7%
2 8
10.4%
6 6
7.8%
8 5
 
6.5%
5 4
 
5.2%
, 4
 
5.2%
9 2
 
2.6%
Other values (5) 5
 
6.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
18.8%
3 12
17.4%
4 9
13.0%
1 9
13.0%
2 8
11.6%
6 6
8.7%
8 5
 
7.2%
5 4
 
5.8%
9 2
 
2.9%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.6%
3 12
16.2%
4 9
12.2%
1 9
12.2%
2 8
10.8%
6 6
8.1%
8 5
 
6.8%
5 4
 
5.4%
, 4
 
5.4%
9 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
17.6%
3 12
16.2%
4 9
12.2%
1 9
12.2%
2 8
10.8%
6 6
8.1%
8 5
 
6.8%
5 4
 
5.4%
, 4
 
5.4%
9 2
 
2.7%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:41.142346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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

Unique17 ?
Unique (%)51.5%

Sample

1st row중앙동
2nd row2,379
3rd row3,982
4th row51
5th row4
ValueCountFrequency (%)
0 9
27.3%
51 3
 
9.1%
57 2
 
6.1%
4 2
 
6.1%
26 1
 
3.0%
3,982 1
 
3.0%
28 1
 
3.0%
2,397 1
 
3.0%
53 1
 
3.0%
18 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:43:41.916399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.2%
5 9
13.2%
1 9
13.2%
2 9
13.2%
9 5
7.4%
3 5
7.4%
7 4
 
5.9%
4 4
 
5.9%
, 4
 
5.9%
8 4
 
5.9%
Other values (4) 4
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
89.7%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
5 9
14.8%
1 9
14.8%
2 9
14.8%
9 5
8.2%
3 5
8.2%
7 4
 
6.6%
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%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.9%
5 9
13.8%
1 9
13.8%
2 9
13.8%
9 5
7.7%
3 5
7.7%
7 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
8 4
 
6.2%
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 11
16.9%
5 9
13.8%
1 9
13.8%
2 9
13.8%
9 5
7.7%
3 5
7.7%
7 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
8 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct24
Distinct (%)70.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:43:42.269737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1470588
Min length1

Characters and Unicode

Total characters73
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

Unique20 ?
Unique (%)58.8%

Sample

1st row출력일자 :
2nd row임동
3rd row4,555
4th row9,166
5th row38
ValueCountFrequency (%)
0 8
22.9%
5 2
 
5.7%
2 2
 
5.7%
38 2
 
5.7%
104 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
4,572 1
 
2.9%
9 1
 
2.9%
17 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T09:43:42.982826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
17.8%
0 10
13.7%
4 6
8.2%
3 6
8.2%
9 5
 
6.8%
1 5
 
6.8%
2 5
 
6.8%
, 4
 
5.5%
6 4
 
5.5%
8 3
 
4.1%
Other values (10) 12
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
82.2%
Other Letter 6
 
8.2%
Other Punctuation 5
 
6.8%
Dash Punctuation 1
 
1.4%
Space Separator 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 13
21.7%
0 10
16.7%
4 6
10.0%
3 6
10.0%
9 5
 
8.3%
1 5
 
8.3%
2 5
 
8.3%
6 4
 
6.7%
8 3
 
5.0%
7 3
 
5.0%
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 67
91.8%
Hangul 6
 
8.2%

Most frequent character per script

Common
ValueCountFrequency (%)
5 13
19.4%
0 10
14.9%
4 6
9.0%
3 6
9.0%
9 5
 
7.5%
1 5
 
7.5%
2 5
 
7.5%
, 4
 
6.0%
6 4
 
6.0%
8 3
 
4.5%
Other values (4) 6
9.0%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 13
19.4%
0 10
14.9%
4 6
9.0%
3 6
9.0%
9 5
 
7.5%
1 5
 
7.5%
2 5
 
7.5%
, 4
 
6.0%
6 4
 
6.0%
8 3
 
4.5%
Other values (4) 6
9.0%
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
2024-02-10T09:43:43.387869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row신안동
2nd row7,244
3rd row12,393
4th row90
5th row2
ValueCountFrequency (%)
0 7
21.2%
2 2
 
6.1%
9 2
 
6.1%
3 2
 
6.1%
78 2
 
6.1%
7,244 1
 
3.0%
179 1
 
3.0%
86 1
 
3.0%
12,364 1
 
3.0%
7,235 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:43:44.048296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 9
12.3%
0 8
11.0%
2 8
11.0%
9 7
9.6%
3 7
9.6%
6 7
9.6%
4 5
6.8%
8 4
 
5.5%
, 4
 
5.5%
1 4
 
5.5%
Other values (5) 10
13.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
86.3%
Other Punctuation 4
 
5.5%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 9
14.3%
0 8
12.7%
2 8
12.7%
9 7
11.1%
3 7
11.1%
6 7
11.1%
4 5
7.9%
8 4
6.3%
1 4
6.3%
5 4
6.3%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
7 9
12.9%
0 8
11.4%
2 8
11.4%
9 7
10.0%
3 7
10.0%
6 7
10.0%
4 5
7.1%
8 4
5.7%
, 4
5.7%
1 4
5.7%
Other values (2) 7
10.0%
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 (%)
7 9
12.9%
0 8
11.4%
2 8
11.4%
9 7
10.0%
3 7
10.0%
6 7
10.0%
4 5
7.1%
8 4
5.7%
, 4
5.7%
1 4
5.7%
Other values (2) 7
10.0%
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
Minimum2022-07-05 00:00:00
Maximum2022-07-05 00:00:00
2024-02-10T09:43:44.377393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:43:44.633646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:44.833066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7575758
Min length1

Characters and Unicode

Total characters91
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 row17,847
3rd row38,187
4th row120
5th row20
ValueCountFrequency (%)
0 6
 
18.2%
110 3
 
9.1%
20 2
 
6.1%
245 1
 
3.0%
460 1
 
3.0%
38,077 1
 
3.0%
17,840 1
 
3.0%
3 1
 
3.0%
7 1
 
3.0%
21 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:45.422657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
24.2%
0 16
17.6%
7 10
11.0%
2 8
 
8.8%
3 8
 
8.8%
8 6
 
6.6%
, 4
 
4.4%
4 4
 
4.4%
6 4
 
4.4%
5 3
 
3.3%
Other values (5) 6
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
90.1%
Other Punctuation 4
 
4.4%
Other Letter 3
 
3.3%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
26.8%
0 16
19.5%
7 10
12.2%
2 8
 
9.8%
3 8
 
9.8%
8 6
 
7.3%
4 4
 
4.9%
6 4
 
4.9%
5 3
 
3.7%
9 1
 
1.2%
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 88
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
25.0%
0 16
18.2%
7 10
11.4%
2 8
 
9.1%
3 8
 
9.1%
8 6
 
6.8%
, 4
 
4.5%
4 4
 
4.5%
6 4
 
4.5%
5 3
 
3.4%
Other values (2) 3
 
3.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 88
96.7%
Hangul 3
 
3.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
25.0%
0 16
18.2%
7 10
11.4%
2 8
 
9.1%
3 8
 
9.1%
8 6
 
6.8%
, 4
 
4.5%
4 4
 
4.5%
6 4
 
4.5%
5 3
 
3.4%
Other values (2) 3
 
3.4%
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
2024-02-10T09:43:45.772800image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row운암1동
2nd row7,458
3rd row19,213
4th row26
5th row17
ValueCountFrequency (%)
0 7
21.2%
82 2
 
6.1%
63 2
 
6.1%
26 2
 
6.1%
17 2
 
6.1%
1 2
 
6.1%
50 1
 
3.0%
124 1
 
3.0%
51 1
 
3.0%
19,180 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:43:46.418288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
20.0%
0 9
12.0%
2 8
10.7%
6 7
9.3%
4 6
 
8.0%
3 5
 
6.7%
7 5
 
6.7%
5 5
 
6.7%
8 4
 
5.3%
, 4
 
5.3%
Other values (5) 7
9.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
22.4%
0 9
13.4%
2 8
11.9%
6 7
10.4%
4 6
 
9.0%
3 5
 
7.5%
7 5
 
7.5%
5 5
 
7.5%
8 4
 
6.0%
9 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.8%
0 9
12.5%
2 8
11.1%
6 7
9.7%
4 6
 
8.3%
3 5
 
6.9%
7 5
 
6.9%
5 5
 
6.9%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
20.8%
0 9
12.5%
2 8
11.1%
6 7
9.7%
4 6
 
8.3%
3 5
 
6.9%
7 5
 
6.9%
5 5
 
6.9%
8 4
 
5.6%
, 4
 
5.6%
Other values (2) 4
 
5.6%
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
2024-02-10T09:43:46.777770image/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 row6,104
3rd row11,849
4th row55
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
95 1
 
3.0%
57 1
 
3.0%
11,785 1
 
3.0%
6,093 1
 
3.0%
2 1
 
3.0%
64 1
 
3.0%
11 1
 
3.0%
39 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:47.580388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.9%
0 9
12.2%
6 8
10.8%
3 6
8.1%
9 6
8.1%
5 6
8.1%
8 5
6.8%
7 5
6.8%
4 5
6.8%
, 4
 
5.4%
Other values (5) 9
12.2%

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 11
16.9%
0 9
13.8%
6 8
12.3%
3 6
9.2%
9 6
9.2%
5 6
9.2%
8 5
7.7%
7 5
7.7%
4 5
7.7%
2 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.5%
0 9
12.7%
6 8
11.3%
3 6
8.5%
9 6
8.5%
5 6
8.5%
8 5
7.0%
7 5
7.0%
4 5
7.0%
, 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 9
12.7%
6 8
11.3%
3 6
8.5%
9 6
8.5%
5 6
8.5%
8 5
7.0%
7 5
7.0%
4 5
7.0%
, 4
 
5.6%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:47.905730image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row운암3동
2nd row5,059
3rd row12,487
4th row29
5th row15
ValueCountFrequency (%)
0 6
 
18.2%
15 2
 
6.1%
29 2
 
6.1%
58 1
 
3.0%
105 1
 
3.0%
5,225 1
 
3.0%
360 1
 
3.0%
166 1
 
3.0%
1 1
 
3.0%
8 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:43:48.715515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
15.0%
0 10
12.5%
5 10
12.5%
1 9
11.2%
4 8
10.0%
7 6
7.5%
8 5
6.2%
6 5
6.2%
9 4
 
5.0%
3 4
 
5.0%
Other values (4) 7
8.8%

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 (%)
2 12
16.4%
0 10
13.7%
5 10
13.7%
1 9
12.3%
4 8
11.0%
7 6
8.2%
8 5
6.8%
6 5
6.8%
9 4
 
5.5%
3 4
 
5.5%
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 (%)
2 12
15.6%
0 10
13.0%
5 10
13.0%
1 9
11.7%
4 8
10.4%
7 6
7.8%
8 5
6.5%
6 5
6.5%
9 4
 
5.2%
3 4
 
5.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
15.6%
0 10
13.0%
5 10
13.0%
1 9
11.7%
4 8
10.4%
7 6
7.8%
8 5
6.5%
6 5
6.5%
9 4
 
5.2%
3 4
 
5.2%
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
2024-02-10T09:43:49.046364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row동림동
2nd row9,850
3rd row23,058
4th row54
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
54 2
 
6.1%
16 1
 
3.0%
218 1
 
3.0%
9,883 1
 
3.0%
22 1
 
3.0%
33 1
 
3.0%
11 1
 
3.0%
57 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:50.041202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.7%
8 9
12.0%
1 8
10.7%
9 8
10.7%
3 8
10.7%
5 7
9.3%
2 6
8.0%
, 4
 
5.3%
6 4
 
5.3%
4 3
 
4.0%
Other values (4) 7
9.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.4%
8 9
13.4%
1 8
11.9%
9 8
11.9%
3 8
11.9%
5 7
10.4%
2 6
9.0%
6 4
 
6.0%
4 3
 
4.5%
7 3
 
4.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.3%
8 9
12.5%
1 8
11.1%
9 8
11.1%
3 8
11.1%
5 7
9.7%
2 6
8.3%
, 4
 
5.6%
6 4
 
5.6%
4 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
2
66.7%
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%
8 9
12.5%
1 8
11.1%
9 8
11.1%
3 8
11.1%
5 7
9.7%
2 6
8.3%
, 4
 
5.6%
6 4
 
5.6%
4 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:50.449543image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row우산동
2nd row5,613
3rd row10,180
4th row62
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
25 2
 
6.1%
1 2
 
6.1%
39 1
 
3.0%
51 1
 
3.0%
10,172 1
 
3.0%
5,606 1
 
3.0%
8 1
 
3.0%
11 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:43:51.294932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.9%
1 12
16.9%
2 7
9.9%
5 6
8.5%
7 5
7.0%
6 5
7.0%
9 4
 
5.6%
, 4
 
5.6%
4 4
 
5.6%
3 3
 
4.2%
Other values (5) 9
12.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
19.7%
1 12
19.7%
2 7
11.5%
5 6
9.8%
7 5
8.2%
6 5
8.2%
9 4
 
6.6%
4 4
 
6.6%
3 3
 
4.9%
8 3
 
4.9%
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 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.6%
1 12
17.6%
2 7
10.3%
5 6
8.8%
7 5
7.4%
6 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
4 4
 
5.9%
3 3
 
4.4%
Other values (2) 6
8.8%
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%
1 12
17.6%
2 7
10.3%
5 6
8.8%
7 5
7.4%
6 5
7.4%
9 4
 
5.9%
, 4
 
5.9%
4 4
 
5.9%
3 3
 
4.4%
Other values (2) 6
8.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:51.713781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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 row풍향동
2nd row2,758
3rd row5,662
4th row23
5th row2
ValueCountFrequency (%)
0 7
21.2%
2 3
 
9.1%
15 2
 
6.1%
1 2
 
6.1%
25 2
 
6.1%
23 2
 
6.1%
17 1
 
3.0%
68 1
 
3.0%
37 1
 
3.0%
31 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:43:52.669723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
18.6%
0 8
13.6%
5 8
13.6%
3 7
11.9%
1 6
10.2%
7 6
10.2%
6 6
10.2%
4 4
 
6.8%
8 3
 
5.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
17.2%
0 8
12.5%
5 8
12.5%
3 7
10.9%
1 6
9.4%
7 6
9.4%
6 6
9.4%
4 4
 
6.2%
, 4
 
6.2%
8 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 (%)
2 11
17.2%
0 8
12.5%
5 8
12.5%
3 7
10.9%
1 6
9.4%
7 6
9.4%
6 6
9.4%
4 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
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
2024-02-10T09:43:53.060281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

Total characters77
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 row문화동
2nd row9,694
3rd row20,694
4th row56
5th row7
ValueCountFrequency (%)
0 7
21.2%
55 2
 
6.1%
7 2
 
6.1%
50 2
 
6.1%
79 2
 
6.1%
216 1
 
3.0%
11 1
 
3.0%
110 1
 
3.0%
9,691 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:43:54.046169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.9%
1 11
14.3%
9 9
11.7%
6 9
11.7%
5 7
9.1%
7 6
7.8%
4 6
7.8%
2 5
 
6.5%
, 4
 
5.2%
- 3
 
3.9%
Other values (4) 4
 
5.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.4%
1 11
16.4%
9 9
13.4%
6 9
13.4%
5 7
10.4%
7 6
9.0%
4 6
9.0%
2 5
 
7.5%
3 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.6%
1 11
14.9%
9 9
12.2%
6 9
12.2%
5 7
9.5%
7 6
8.1%
4 6
8.1%
2 5
 
6.8%
, 4
 
5.4%
- 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 13
17.6%
1 11
14.9%
9 9
12.2%
6 9
12.2%
5 7
9.5%
7 6
8.1%
4 6
8.1%
2 5
 
6.8%
, 4
 
5.4%
- 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:54.360329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row문흥1동
2nd row6,475
3rd row15,709
4th row29
5th row9
ValueCountFrequency (%)
0 7
21.2%
39 2
 
6.1%
9 2
 
6.1%
4 1
 
3.0%
153 1
 
3.0%
15,648 1
 
3.0%
6,462 1
 
3.0%
1 1
 
3.0%
61 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:55.084296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.2%
1 8
10.8%
5 8
10.8%
9 7
9.5%
3 7
9.5%
6 6
8.1%
4 6
8.1%
7 6
8.1%
, 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 (%)
0 9
14.1%
1 8
12.5%
5 8
12.5%
9 7
10.9%
3 7
10.9%
6 6
9.4%
4 6
9.4%
7 6
9.4%
8 4
6.2%
2 3
 
4.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
12.7%
1 8
11.3%
5 8
11.3%
9 7
9.9%
3 7
9.9%
6 6
8.5%
4 6
8.5%
7 6
8.5%
, 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 (%)
0 9
12.7%
1 8
11.3%
5 8
11.3%
9 7
9.9%
3 7
9.9%
6 6
8.5%
4 6
8.5%
7 6
8.5%
, 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: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:55.404238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row문흥2동
2nd row7,382
3rd row15,535
4th row32
5th row4
ValueCountFrequency (%)
0 6
18.2%
4 3
 
9.1%
32 2
 
6.1%
69 2
 
6.1%
1 1
 
3.0%
88 1
 
3.0%
7,375 1
 
3.0%
43 1
 
3.0%
7 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:43:56.041399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
12.3%
3 9
12.3%
4 7
9.6%
8 7
9.6%
5 7
9.6%
2 6
8.2%
9 5
6.8%
7 5
6.8%
1 5
6.8%
6 4
5.5%
Other values (5) 9
12.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
14.1%
3 9
14.1%
4 7
10.9%
8 7
10.9%
5 7
10.9%
2 6
9.4%
9 5
7.8%
7 5
7.8%
1 5
7.8%
6 4
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
12.9%
3 9
12.9%
4 7
10.0%
8 7
10.0%
5 7
10.0%
2 6
8.6%
9 5
7.1%
7 5
7.1%
1 5
7.1%
6 4
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
12.9%
3 9
12.9%
4 7
10.0%
8 7
10.0%
5 7
10.0%
2 6
8.6%
9 5
7.1%
7 5
7.1%
1 5
7.1%
6 4
5.7%
Other values (2) 6
8.6%
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
2024-02-10T09:43:56.357711image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row두암1동
2nd row4,011
3rd row7,692
4th row23
5th row7
ValueCountFrequency (%)
0 8
24.2%
33 2
 
6.1%
37 2
 
6.1%
1 2
 
6.1%
23 2
 
6.1%
14 1
 
3.0%
43 1
 
3.0%
7,673 1
 
3.0%
4,010 1
 
3.0%
19 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:43:57.198055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.8%
3 10
14.5%
1 9
13.0%
2 6
8.7%
7 6
8.7%
6 5
 
7.2%
8 4
 
5.8%
4 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (4) 5
 
7.2%

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 13
21.7%
3 10
16.7%
1 9
15.0%
2 6
10.0%
7 6
10.0%
6 5
 
8.3%
8 4
 
6.7%
4 4
 
6.7%
9 3
 
5.0%
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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
19.7%
3 10
15.2%
1 9
13.6%
2 6
9.1%
7 6
9.1%
6 5
 
7.6%
8 4
 
6.1%
4 4
 
6.1%
, 4
 
6.1%
9 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 13
19.7%
3 10
15.2%
1 9
13.6%
2 6
9.1%
7 6
9.1%
6 5
 
7.6%
8 4
 
6.1%
4 4
 
6.1%
, 4
 
6.1%
9 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:43:57.525967image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row두암2동
2nd row7,691
3rd row15,893
4th row56
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
2 3
 
9.1%
9 2
 
6.1%
76 1
 
3.0%
56 1
 
3.0%
101 1
 
3.0%
15,862 1
 
3.0%
7,693 1
 
3.0%
31 1
 
3.0%
17 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:43:58.262029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.7%
5 9
12.0%
2 8
10.7%
6 8
10.7%
0 7
9.3%
9 6
8.0%
7 6
8.0%
3 5
6.7%
4 4
 
5.3%
, 4
 
5.3%
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 (%)
1 11
16.7%
5 9
13.6%
2 8
12.1%
6 8
12.1%
0 7
10.6%
9 6
9.1%
7 6
9.1%
3 5
7.6%
4 4
 
6.1%
8 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.3%
5 9
12.5%
2 8
11.1%
6 8
11.1%
0 7
9.7%
9 6
8.3%
7 6
8.3%
3 5
6.9%
4 4
 
5.6%
, 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
15.3%
5 9
12.5%
2 8
11.1%
6 8
11.1%
0 7
9.7%
9 6
8.3%
7 6
8.3%
3 5
6.9%
4 4
 
5.6%
, 4
 
5.6%
Other values (2) 4
 
5.6%
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
2024-02-10T09:43:58.617697image/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 row두암3동
2nd row7,769
3rd row13,171
4th row46
5th row8
ValueCountFrequency (%)
0 6
18.2%
52 2
 
6.1%
46 2
 
6.1%
8 2
 
6.1%
1 2
 
6.1%
41 1
 
3.0%
102 1
 
3.0%
7,752 1
 
3.0%
35 1
 
3.0%
17 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:43:59.415001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.6%
3 11
14.9%
0 8
10.8%
5 7
9.5%
7 7
9.5%
2 5
 
6.8%
6 5
 
6.8%
, 4
 
5.4%
4 3
 
4.1%
8 3
 
4.1%
Other values (5) 8
10.8%

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 13
20.0%
3 11
16.9%
0 8
12.3%
5 7
10.8%
7 7
10.8%
2 5
 
7.7%
6 5
 
7.7%
4 3
 
4.6%
8 3
 
4.6%
9 3
 
4.6%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.3%
3 11
15.5%
0 8
11.3%
5 7
9.9%
7 7
9.9%
2 5
 
7.0%
6 5
 
7.0%
, 4
 
5.6%
4 3
 
4.2%
8 3
 
4.2%
Other values (2) 5
 
7.0%
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 13
18.3%
3 11
15.5%
0 8
11.3%
5 7
9.9%
7 7
9.9%
2 5
 
7.0%
6 5
 
7.0%
, 4
 
5.6%
4 3
 
4.2%
8 3
 
4.2%
Other values (2) 5
 
7.0%
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
2024-02-10T09:43:59.655293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row삼각동
2nd row6,052
3rd row13,871
4th row31
5th row4
ValueCountFrequency (%)
0 7
21.2%
2 2
 
6.1%
4 2
 
6.1%
6 1
 
3.0%
150 1
 
3.0%
13,856 1
 
3.0%
6,050 1
 
3.0%
15 1
 
3.0%
5 1
 
3.0%
45 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:00.284835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.8%
1 8
11.0%
3 8
11.0%
5 7
9.6%
7 7
9.6%
4 6
8.2%
2 6
8.2%
6 5
 
6.8%
, 4
 
5.5%
- 3
 
4.1%
Other values (5) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
86.3%
Other Punctuation 4
 
5.5%
Dash Punctuation 3
 
4.1%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.6%
1 8
12.7%
3 8
12.7%
5 7
11.1%
7 7
11.1%
4 6
9.5%
2 6
9.5%
6 5
 
7.9%
8 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 (%)
- 3
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%
1 8
11.4%
3 8
11.4%
5 7
10.0%
7 7
10.0%
4 6
8.6%
2 6
8.6%
6 5
 
7.1%
, 4
 
5.7%
- 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.6%
1 8
11.4%
3 8
11.4%
5 7
10.0%
7 7
10.0%
4 6
8.6%
2 6
8.6%
6 5
 
7.1%
, 4
 
5.7%
- 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 27
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:00.721504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4242424
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row일곡동
2nd row11,549
3rd row29,495
4th row33
5th row11
ValueCountFrequency (%)
0 8
24.2%
33 2
 
6.1%
11 2
 
6.1%
87 1
 
3.0%
29,495 1
 
3.0%
129 1
 
3.0%
29,446 1
 
3.0%
11,560 1
 
3.0%
49 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:44:01.515916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.0%
0 10
12.5%
9 10
12.5%
3 7
8.8%
2 7
8.8%
4 7
8.8%
5 5
 
6.2%
8 5
 
6.2%
, 4
 
5.0%
6 3
 
3.8%
Other values (5) 6
 
7.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.2%
0 10
13.9%
9 10
13.9%
3 7
9.7%
2 7
9.7%
4 7
9.7%
5 5
 
6.9%
8 5
 
6.9%
6 3
 
4.2%
7 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.8%
0 10
13.0%
9 10
13.0%
3 7
9.1%
2 7
9.1%
4 7
9.1%
5 5
 
6.5%
8 5
 
6.5%
, 4
 
5.2%
6 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
20.8%
0 10
13.0%
9 10
13.0%
3 7
9.1%
2 7
9.1%
4 7
9.1%
5 5
 
6.5%
8 5
 
6.5%
, 4
 
5.2%
6 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:01.848417image/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 row매곡동
2nd row5,516
3rd row13,756
4th row24
5th row5
ValueCountFrequency (%)
0 7
21.2%
24 3
 
9.1%
5 2
 
6.1%
65 1
 
3.0%
129 1
 
3.0%
5,504 1
 
3.0%
12 1
 
3.0%
3 1
 
3.0%
30 1
 
3.0%
39 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:44:02.618542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.9%
5 9
12.5%
2 8
11.1%
1 8
11.1%
4 7
9.7%
3 7
9.7%
6 6
8.3%
, 4
 
5.6%
9 4
 
5.6%
7 2
 
2.8%
Other values (5) 7
9.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.9%
5 9
14.3%
2 8
12.7%
1 8
12.7%
4 7
11.1%
3 7
11.1%
6 6
9.5%
9 4
 
6.3%
7 2
 
3.2%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.5%
5 9
13.0%
2 8
11.6%
1 8
11.6%
4 7
10.1%
3 7
10.1%
6 6
8.7%
, 4
 
5.8%
9 4
 
5.8%
7 2
 
2.9%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.5%
5 9
13.0%
2 8
11.6%
1 8
11.6%
4 7
10.1%
3 7
10.1%
6 6
8.7%
, 4
 
5.8%
9 4
 
5.8%
7 2
 
2.9%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:02.959239image/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 row오치1동
2nd row5,510
3rd row10,767
4th row49
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
76 1
 
3.0%
10,709 1
 
3.0%
5,483 1
 
3.0%
3 1
 
3.0%
58 1
 
3.0%
27 1
 
3.0%
5 1
 
3.0%
45 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:44:03.984622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.6%
5 9
12.2%
4 8
10.8%
8 6
8.1%
1 6
8.1%
7 6
8.1%
2 5
 
6.8%
3 5
 
6.8%
, 4
 
5.4%
6 4
 
5.4%
Other values (5) 8
10.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.3%
5 9
14.1%
4 8
12.5%
8 6
9.4%
1 6
9.4%
7 6
9.4%
2 5
 
7.8%
3 5
 
7.8%
6 4
 
6.2%
9 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.3%
5 9
12.7%
4 8
11.3%
8 6
8.5%
1 6
8.5%
7 6
8.5%
2 5
 
7.0%
3 5
 
7.0%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 5
 
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.3%
5 9
12.7%
4 8
11.3%
8 6
8.5%
1 6
8.5%
7 6
8.5%
2 5
 
7.0%
3 5
 
7.0%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 5
 
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:04.366194image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row오치2동
2nd row6,993
3rd row12,351
4th row36
5th row9
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
6,993 1
 
3.0%
37 1
 
3.0%
12,320 1
 
3.0%
6,983 1
 
3.0%
1 1
 
3.0%
31 1
 
3.0%
7 1
 
3.0%
48 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:44:05.016999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.0%
1 11
14.7%
6 8
10.7%
3 8
10.7%
2 7
9.3%
7 6
8.0%
4 5
6.7%
, 4
 
5.3%
9 4
 
5.3%
5 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 12
18.2%
1 11
16.7%
6 8
12.1%
3 8
12.1%
2 7
10.6%
7 6
9.1%
4 5
7.6%
9 4
 
6.1%
5 3
 
4.5%
8 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.7%
1 11
15.3%
6 8
11.1%
3 8
11.1%
2 7
9.7%
7 6
8.3%
4 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
5 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 12
16.7%
1 11
15.3%
6 8
11.1%
3 8
11.1%
2 7
9.7%
7 6
8.3%
4 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
5 3
 
4.2%
Other values (2) 4
 
5.6%
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
2024-02-10T09:44:05.315659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7272727
Min length1

Characters and Unicode

Total characters57
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

Unique13 ?
Unique (%)39.4%

Sample

1st row석곡동
2nd row1,386
3rd row2,499
4th row22
5th row3
ValueCountFrequency (%)
0 9
27.3%
2 3
 
9.1%
3 3
 
9.1%
8 2
 
6.1%
22 2
 
6.1%
9 2
 
6.1%
6 2
 
6.1%
1 1
 
3.0%
1,384 1
 
3.0%
7 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T09:44:06.036654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
17.5%
0 9
15.8%
3 6
10.5%
9 5
8.8%
1 5
8.8%
8 4
 
7.0%
, 4
 
7.0%
4 4
 
7.0%
6 3
 
5.3%
7 2
 
3.5%
Other values (4) 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 10
20.8%
0 9
18.8%
3 6
12.5%
9 5
10.4%
1 5
10.4%
8 4
 
8.3%
4 4
 
8.3%
6 3
 
6.2%
7 2
 
4.2%
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 54
94.7%
Hangul 3
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
18.5%
0 9
16.7%
3 6
11.1%
9 5
9.3%
1 5
9.3%
8 4
 
7.4%
, 4
 
7.4%
4 4
 
7.4%
6 3
 
5.6%
7 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 10
18.5%
0 9
16.7%
3 6
11.1%
9 5
9.3%
1 5
9.3%
8 4
 
7.4%
, 4
 
7.4%
4 4
 
7.4%
6 3
 
5.6%
7 2
 
3.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 32
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:06.365072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row건국동
2nd row9,165
3rd row22,060
4th row62
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
65 2
 
6.1%
12 2
 
6.1%
1 2
 
6.1%
111 1
 
3.0%
238 1
 
3.0%
22,012 1
 
3.0%
9,133 1
 
3.0%
48 1
 
3.0%
32 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:07.211720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.0%
2 12
15.0%
0 10
12.5%
6 7
8.8%
3 7
8.8%
8 7
8.8%
5 6
 
7.5%
, 4
 
5.0%
- 3
 
3.8%
9 2
 
2.5%
Other values (5) 6
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
87.5%
Other Punctuation 4
 
5.0%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.9%
2 12
17.1%
0 10
14.3%
6 7
10.0%
3 7
10.0%
8 7
10.0%
5 6
 
8.6%
9 2
 
2.9%
7 2
 
2.9%
4 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.8%
2 12
15.6%
0 10
13.0%
6 7
9.1%
3 7
9.1%
8 7
9.1%
5 6
 
7.8%
, 4
 
5.2%
- 3
 
3.9%
9 2
 
2.6%
Other values (2) 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 (%)
1 16
20.8%
2 12
15.6%
0 10
13.0%
6 7
9.1%
3 7
9.1%
8 7
9.1%
5 6
 
7.8%
, 4
 
5.2%
- 3
 
3.9%
9 2
 
2.6%
Other values (2) 3
 
3.9%
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
2024-02-10T09:44:07.608861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7272727
Min length1

Characters and Unicode

Total characters90
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row양산동
2nd row16,413
3rd row37,551
4th row63
5th row19
ValueCountFrequency (%)
0 5
 
15.2%
2 2
 
6.1%
19 2
 
6.1%
221 1
 
3.0%
228 1
 
3.0%
37,420 1
 
3.0%
16,376 1
 
3.0%
131 1
 
3.0%
37 1
 
3.0%
1 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:44:08.410625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
24.4%
0 9
10.0%
2 9
10.0%
3 8
 
8.9%
4 7
 
7.8%
7 7
 
7.8%
6 6
 
6.7%
5 6
 
6.7%
9 4
 
4.4%
, 4
 
4.4%
Other values (5) 8
 
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
88.9%
Other Punctuation 4
 
4.4%
Dash Punctuation 3
 
3.3%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
27.5%
0 9
11.2%
2 9
11.2%
3 8
 
10.0%
4 7
 
8.8%
7 7
 
8.8%
6 6
 
7.5%
5 6
 
7.5%
9 4
 
5.0%
8 2
 
2.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
25.3%
0 9
10.3%
2 9
10.3%
3 8
 
9.2%
4 7
 
8.0%
7 7
 
8.0%
6 6
 
6.9%
5 6
 
6.9%
9 4
 
4.6%
, 4
 
4.6%
Other values (2) 5
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
25.3%
0 9
10.3%
2 9
10.3%
3 8
 
9.2%
4 7
 
8.0%
7 7
 
8.0%
6 6
 
6.9%
5 6
 
6.9%
9 4
 
4.6%
, 4
 
4.6%
Other values (2) 5
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:44:08.747863image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row신용동
2nd row11,818
3rd row29,596
4th row9
5th row10
ValueCountFrequency (%)
0 7
21.2%
1 2
 
6.1%
10 2
 
6.1%
109 1
 
3.0%
122 1
 
3.0%
29,574 1
 
3.0%
11,819 1
 
3.0%
22 1
 
3.0%
4 1
 
3.0%
84 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:44:09.328978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.5%
0 12
15.4%
9 9
11.5%
2 8
10.3%
8 8
10.3%
5 5
 
6.4%
, 4
 
5.1%
6 4
 
5.1%
4 3
 
3.8%
3 2
 
2.6%
Other values (5) 7
9.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
23.2%
0 12
17.4%
9 9
13.0%
2 8
11.6%
8 8
11.6%
5 5
 
7.2%
6 4
 
5.8%
4 3
 
4.3%
3 2
 
2.9%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.3%
0 12
16.0%
9 9
12.0%
2 8
10.7%
8 8
10.7%
5 5
 
6.7%
, 4
 
5.3%
6 4
 
5.3%
4 3
 
4.0%
3 2
 
2.7%
Other values (2) 4
 
5.3%
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 16
21.3%
0 12
16.0%
9 9
12.0%
2 8
10.7%
8 8
10.7%
5 5
 
6.7%
, 4
 
5.3%
6 4
 
5.3%
4 3
 
4.0%
3 2
 
2.7%
Other values (2) 4
 
5.3%
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>2022.07.05<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>2022.06 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>197,1583,0024,4073,4582,3794,5557,244<NA>17,8477,4586,1045,0599,8505,6132,7589,6946,4757,3824,0117,6917,7696,05211,5495,5165,5106,9931,3869,16516,41311,818
4<NA>전월말인구수<NA><NA><NA>426,3294,7278,4616,3243,9829,16612,393<NA>38,18719,21311,84912,48723,05810,1805,66220,69415,70915,5357,69215,89313,17113,87129,49513,75610,76712,3512,49922,06037,55129,596
5<NA>전월말거주불명자수<NA><NA><NA>1,278556242513890<NA>12026552954622356293223564631332449362262639
6<NA>전월말재외국민등록자수<NA><NA><NA>222063452<NA>20178158727947984115893121910
7<NA>증 가 요 인전 입<NA>4,2866016824910895156<NA>35312411146719092681719513866146102134199998511612183301198
8<NA><NA><NA>남자<NA>2,1643485123515078<NA>19063622279645379258693371526486414264310115592
9<NA><NA><NA>여자<NA>2,1222683126574578<NA>163614924094473179376933755070113584352982146106
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>0001000002001000000000
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>1000000<NA>0000000000000000000010
28<NA>세대수증감<NA><NA><NA>215-2441061817-9<NA>-71-1116633-715-3-13-7-12-17-211-12-27-10-2-32-371
29<NA>인구수증감<NA><NA><NA>-276-37014653-9-29<NA>-110-33-64360-22-8-4-50-61-43-19-31-35-15-49-24-58-31-6-48-131-22
30<NA>거주불명자수증감<NA><NA><NA>-11-1-1-100-3<NA>31200-12-1-100-20-200-310-1-2-1
31<NA>금월말세대수<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
32<NA>금월말인구수<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
33<NA>금월말거주불명자수<NA><NA><NA>1,267546141513887<NA>12327572954612555283223544629332446372261618
34<NA>금월말재외국민등록자수<NA><NA><NA>224063452<NA>201771587279489841258103121910

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