Overview

Dataset statistics

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

Variable types

Unsupported1
Text33
DateTime1

Dataset

Description2024-01-26
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201927

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 2 (5.7%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 25 has 2 (5.7%) missing valuesMissing
Unnamed: 26 has 2 (5.7%) missing valuesMissing
Unnamed: 27 has 2 (5.7%) missing valuesMissing
Unnamed: 28 has 2 (5.7%) missing valuesMissing
Unnamed: 29 has 2 (5.7%) missing valuesMissing
Unnamed: 30 has 2 (5.7%) missing valuesMissing
Unnamed: 31 has 2 (5.7%) missing valuesMissing
Unnamed: 32 has 2 (5.7%) missing valuesMissing
Unnamed: 33 has 2 (5.7%) missing valuesMissing
Unnamed: 34 has 2 (5.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 09:57:50.896527
Analysis finished2024-02-10 09:57:52.396669
Duration1.5 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
2024-02-10T09:57:52.673074image/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%
2024-02-10T09:57:53.593909image/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
2024-02-10T09:57:53.938318image/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%
2024-02-10T09:57:54.797222image/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
2024-02-10T09:57:55.142067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 북구
2nd row2023.10 현재
3rd row
4th row남자
5th row여자
ValueCountFrequency (%)
2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
북구 1
7.1%
2023.10 1
7.1%
현재 1
7.1%
2024-02-10T09:57:55.943241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
 
12.2%
4
 
9.8%
4
 
9.8%
3
 
7.3%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
2
 
4.9%
Other values (11) 13
31.7%

Most occurring categories

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

Most frequent character per category

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

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:57:56.257279image/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%
2024-02-10T09:57:57.113544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:57:57.521705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.969697
Min length1

Characters and Unicode

Total characters131
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row199,404
3rd row422,776
4th row1,004
5th row243
ValueCountFrequency (%)
0 5
 
14.7%
1,667 2
 
5.9%
19 2
 
5.9%
2,096 1
 
2.9%
985 1
 
2.9%
422,567 1
 
2.9%
199,373 1
 
2.9%
209 1
 
2.9%
31 1
 
2.9%
39 1
 
2.9%
Other values (18) 18
52.9%
2024-02-10T09:57:58.569696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
13.0%
, 17
13.0%
9 15
11.5%
2 15
11.5%
0 14
10.7%
7 11
8.4%
4 11
8.4%
3 9
6.9%
6 8
6.1%
8 5
 
3.8%
Other values (5) 9
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 107
81.7%
Other Punctuation 17
 
13.0%
Dash Punctuation 3
 
2.3%
Space Separator 2
 
1.5%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
15.9%
9 15
14.0%
2 15
14.0%
0 14
13.1%
7 11
10.3%
4 11
10.3%
3 9
8.4%
6 8
7.5%
8 5
 
4.7%
5 2
 
1.9%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 17
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
13.2%
, 17
13.2%
9 15
11.6%
2 15
11.6%
0 14
10.9%
7 11
8.5%
4 11
8.5%
3 9
7.0%
6 8
6.2%
8 5
 
3.9%
Other values (3) 7
5.4%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
13.2%
, 17
13.2%
9 15
11.6%
2 15
11.6%
0 14
10.9%
7 11
8.5%
4 11
8.5%
3 9
7.0%
6 8
6.2%
8 5
 
3.9%
Other values (3) 7
5.4%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:57:58.950293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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 row중흥1동
2nd row2,906
3rd row4,525
4th row45
5th row1
ValueCountFrequency (%)
0 7
21.2%
1 4
 
12.1%
45 2
 
6.1%
44 2
 
6.1%
19 2
 
6.1%
49 1
 
3.0%
4,481 1
 
3.0%
2,887 1
 
3.0%
2 1
 
3.0%
16 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:57:59.933334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.9%
4 12
16.9%
0 8
11.3%
2 8
11.3%
8 6
8.5%
5 5
7.0%
9 5
7.0%
, 4
 
5.6%
- 3
 
4.2%
6 2
 
2.8%
Other values (5) 6
8.5%

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 (%)
1 12
19.7%
4 12
19.7%
0 8
13.1%
2 8
13.1%
8 6
9.8%
5 5
8.2%
9 5
8.2%
6 2
 
3.3%
3 2
 
3.3%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.6%
4 12
17.6%
0 8
11.8%
2 8
11.8%
8 6
8.8%
5 5
7.4%
9 5
7.4%
, 4
 
5.9%
- 3
 
4.4%
6 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.6%
4 12
17.6%
0 8
11.8%
2 8
11.8%
8 6
8.8%
5 5
7.4%
9 5
7.4%
, 4
 
5.9%
- 3
 
4.4%
6 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:00.283763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row중흥2동
2nd row4,438
3rd row8,401
4th row31
5th row7
ValueCountFrequency (%)
0 7
21.2%
31 3
 
9.1%
7 2
 
6.1%
28 2
 
6.1%
33 1
 
3.0%
34 1
 
3.0%
8,383 1
 
3.0%
4,421 1
 
3.0%
1 1
 
3.0%
18 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:58:01.491719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.9%
3 10
13.9%
1 9
12.5%
4 9
12.5%
8 8
11.1%
2 7
9.7%
7 5
6.9%
, 4
 
5.6%
- 3
 
4.2%
5 2
 
2.8%
Other values (5) 5
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
86.1%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.1%
3 10
16.1%
1 9
14.5%
4 9
14.5%
8 8
12.9%
2 7
11.3%
7 5
8.1%
5 2
 
3.2%
6 1
 
1.6%
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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.5%
3 10
14.5%
1 9
13.0%
4 9
13.0%
8 8
11.6%
2 7
10.1%
7 5
7.2%
, 4
 
5.8%
- 3
 
4.3%
5 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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.5%
3 10
14.5%
1 9
13.0%
4 9
13.0%
8 8
11.6%
2 7
10.1%
7 5
7.2%
, 4
 
5.8%
- 3
 
4.3%
5 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:01.847793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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 row중흥3동
2nd row3,681
3rd row6,558
4th row43
5th row3
ValueCountFrequency (%)
0 7
21.2%
50 2
 
6.1%
5 2
 
6.1%
3 2
 
6.1%
56 1
 
3.0%
62 1
 
3.0%
6,545 1
 
3.0%
3,676 1
 
3.0%
2 1
 
3.0%
13 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:58:02.829219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 13
18.3%
3 11
15.5%
0 10
14.1%
6 8
11.3%
1 6
8.5%
8 4
 
5.6%
, 4
 
5.6%
4 4
 
5.6%
2 3
 
4.2%
9 2
 
2.8%
Other values (5) 6
8.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 13
21.0%
3 11
17.7%
0 10
16.1%
6 8
12.9%
1 6
9.7%
8 4
 
6.5%
4 4
 
6.5%
2 3
 
4.8%
9 2
 
3.2%
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 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
5 13
19.1%
3 11
16.2%
0 10
14.7%
6 8
11.8%
1 6
8.8%
8 4
 
5.9%
, 4
 
5.9%
4 4
 
5.9%
2 3
 
4.4%
9 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 13
19.1%
3 11
16.2%
0 10
14.7%
6 8
11.8%
1 6
8.8%
8 4
 
5.9%
, 4
 
5.9%
4 4
 
5.9%
2 3
 
4.4%
9 2
 
2.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:03.298888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique17 ?
Unique (%)51.5%

Sample

1st row중앙동
2nd row2,240
3rd row3,865
4th row32
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 2
 
6.1%
35 2
 
6.1%
22 2
 
6.1%
32 2
 
6.1%
15 1
 
3.0%
72 1
 
3.0%
2,224 1
 
3.0%
17 1
 
3.0%
16 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:58:04.338734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
20.3%
0 10
14.5%
3 10
14.5%
5 7
10.1%
1 6
8.7%
, 4
 
5.8%
4 3
 
4.3%
8 3
 
4.3%
6 3
 
4.3%
7 3
 
4.3%
Other values (5) 6
8.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
23.3%
0 10
16.7%
3 10
16.7%
5 7
11.7%
1 6
10.0%
4 3
 
5.0%
8 3
 
5.0%
6 3
 
5.0%
7 3
 
5.0%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
21.2%
0 10
15.2%
3 10
15.2%
5 7
10.6%
1 6
9.1%
, 4
 
6.1%
4 3
 
4.5%
8 3
 
4.5%
6 3
 
4.5%
7 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 (%)
2 14
21.2%
0 10
15.2%
3 10
15.2%
5 7
10.6%
1 6
9.1%
, 4
 
6.1%
4 3
 
4.5%
8 3
 
4.5%
6 3
 
4.5%
7 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct27
Distinct (%)79.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:58:04.719217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length2.2352941
Min length1

Characters and Unicode

Total characters76
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)70.6%

Sample

1st row출력일자 :
2nd row임동
3rd row4,580
4th row9,099
5th row27
ValueCountFrequency (%)
0 6
 
17.1%
5 2
 
5.7%
32 2
 
5.7%
11 2
 
5.7%
39 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
43 1
 
2.9%
17 1
 
2.9%
9,067 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T09:58:06.021704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.8%
1 8
10.5%
9 7
9.2%
3 7
9.2%
7 6
7.9%
4 5
 
6.6%
2 5
 
6.6%
, 4
 
5.3%
8 4
 
5.3%
5 4
 
5.3%
Other values (10) 14
18.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
19.7%
1 8
13.1%
9 7
11.5%
3 7
11.5%
7 6
9.8%
4 5
8.2%
2 5
8.2%
8 4
 
6.6%
5 4
 
6.6%
6 3
 
4.9%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
1 8
11.4%
9 7
10.0%
3 7
10.0%
7 6
8.6%
4 5
7.1%
2 5
7.1%
, 4
 
5.7%
8 4
 
5.7%
5 4
 
5.7%
Other values (4) 8
11.4%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.1%
1 8
11.4%
9 7
10.0%
3 7
10.0%
7 6
8.6%
4 5
7.1%
2 5
7.1%
, 4
 
5.7%
8 4
 
5.7%
5 4
 
5.7%
Other values (4) 8
11.4%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:06.548828image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row신안동
2nd row7,392
3rd row12,287
4th row72
5th row1
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
63 2
 
6.1%
1 2
 
6.1%
21 2
 
6.1%
69 1
 
3.0%
148 1
 
3.0%
87 1
 
3.0%
12,266 1
 
3.0%
7,371 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:58:07.760764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.7%
1 11
14.7%
2 9
12.0%
7 9
12.0%
6 9
12.0%
3 5
6.7%
9 4
 
5.3%
, 4
 
5.3%
- 3
 
4.0%
8 3
 
4.0%
Other values (5) 7
9.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.9%
1 11
16.9%
2 9
13.8%
7 9
13.8%
6 9
13.8%
3 5
7.7%
9 4
 
6.2%
8 3
 
4.6%
4 2
 
3.1%
5 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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.3%
1 11
15.3%
2 9
12.5%
7 9
12.5%
6 9
12.5%
3 5
6.9%
9 4
 
5.6%
, 4
 
5.6%
- 3
 
4.2%
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%
1 11
15.3%
2 9
12.5%
7 9
12.5%
6 9
12.5%
3 5
6.9%
9 4
 
5.6%
, 4
 
5.6%
- 3
 
4.2%
8 3
 
4.2%
Other values (2) 4
 
5.6%
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
Minimum2024-01-09 00:00:00
Maximum2024-01-09 00:00:00
2024-02-10T09:58:08.205310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:58:08.478217image/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
2024-02-10T09:58:08.900974image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row용봉동
2nd row17,984
3rd row37,264
4th row81
5th row22
ValueCountFrequency (%)
0 5
 
15.2%
145 2
 
6.1%
2 2
 
6.1%
1 2
 
6.1%
22 2
 
6.1%
85 1
 
3.0%
183 1
 
3.0%
37,230 1
 
3.0%
17,986 1
 
3.0%
34 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:58:09.777565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
23.3%
0 8
 
9.3%
2 8
 
9.3%
3 8
 
9.3%
4 7
 
8.1%
8 7
 
8.1%
6 6
 
7.0%
7 6
 
7.0%
, 4
 
4.7%
9 4
 
4.7%
Other values (5) 8
 
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
89.5%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
26.0%
0 8
 
10.4%
2 8
 
10.4%
3 8
 
10.4%
4 7
 
9.1%
8 7
 
9.1%
6 6
 
7.8%
7 6
 
7.8%
9 4
 
5.2%
5 3
 
3.9%
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 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
24.1%
0 8
 
9.6%
2 8
 
9.6%
3 8
 
9.6%
4 7
 
8.4%
8 7
 
8.4%
6 6
 
7.2%
7 6
 
7.2%
, 4
 
4.8%
9 4
 
4.8%
Other values (2) 5
 
6.0%
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 20
24.1%
0 8
 
9.6%
2 8
 
9.6%
3 8
 
9.6%
4 7
 
8.4%
8 7
 
8.4%
6 6
 
7.2%
7 6
 
7.2%
, 4
 
4.8%
9 4
 
4.8%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:10.134583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
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

Unique24 ?
Unique (%)72.7%

Sample

1st row운암1동
2nd row7,366
3rd row18,554
4th row20
5th row22
ValueCountFrequency (%)
0 7
21.2%
22 2
 
6.1%
65 1
 
3.0%
18,606 1
 
3.0%
7,382 1
 
3.0%
11 1
 
3.0%
52 1
 
3.0%
16 1
 
3.0%
7 1
 
3.0%
56 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:58:11.240909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.7%
6 11
14.7%
1 10
13.3%
2 7
9.3%
3 6
8.0%
5 6
8.0%
7 5
6.7%
8 5
6.7%
, 4
 
5.3%
4 4
 
5.3%
Other values (4) 6
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
90.7%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.2%
6 11
16.2%
1 10
14.7%
2 7
10.3%
3 6
8.8%
5 6
8.8%
7 5
7.4%
8 5
7.4%
4 4
 
5.9%
9 3
 
4.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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%
6 11
15.3%
1 10
13.9%
2 7
9.7%
3 6
8.3%
5 6
8.3%
7 5
6.9%
8 5
6.9%
, 4
 
5.6%
4 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%
6 11
15.3%
1 10
13.9%
2 7
9.7%
3 6
8.3%
5 6
8.3%
7 5
6.9%
8 5
6.9%
, 4
 
5.6%
4 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:11.697594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row운암2동
2nd row5,969
3rd row11,359
4th row52
5th row8
ValueCountFrequency (%)
0 8
24.2%
34 2
 
6.1%
5,969 2
 
6.1%
30 1
 
3.0%
11,359 1
 
3.0%
55 1
 
3.0%
51 1
 
3.0%
11,370 1
 
3.0%
1 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:58:12.519771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.4%
5 12
16.4%
1 11
15.1%
3 7
9.6%
9 6
8.2%
, 4
 
5.5%
6 4
 
5.5%
4 4
 
5.5%
7 4
 
5.5%
2 3
 
4.1%
Other values (5) 6
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.5%
5 12
18.5%
1 11
16.9%
3 7
10.8%
9 6
9.2%
6 4
 
6.2%
4 4
 
6.2%
7 4
 
6.2%
2 3
 
4.6%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
5 12
17.1%
1 11
15.7%
3 7
10.0%
9 6
8.6%
, 4
 
5.7%
6 4
 
5.7%
4 4
 
5.7%
7 4
 
5.7%
2 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.1%
5 12
17.1%
1 11
15.7%
3 7
10.0%
9 6
8.6%
, 4
 
5.7%
6 4
 
5.7%
4 4
 
5.7%
7 4
 
5.7%
2 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:12.963526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row운암3동
2nd row5,499
3rd row13,297
4th row31
5th row17
ValueCountFrequency (%)
0 8
24.2%
17 2
 
6.1%
31 2
 
6.1%
36 2
 
6.1%
30 1
 
3.0%
13,297 1
 
3.0%
48 1
 
3.0%
5,504 1
 
3.0%
2 1
 
3.0%
5 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:58:13.783572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
15.3%
0 10
13.9%
3 9
12.5%
5 7
9.7%
4 7
9.7%
6 6
8.3%
9 6
8.3%
, 4
 
5.6%
2 4
 
5.6%
7 3
 
4.2%
Other values (4) 5
6.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
90.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.9%
0 10
15.4%
3 9
13.8%
5 7
10.8%
4 7
10.8%
6 6
9.2%
9 6
9.2%
2 4
 
6.2%
7 3
 
4.6%
8 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
15.9%
0 10
14.5%
3 9
13.0%
5 7
10.1%
4 7
10.1%
6 6
8.7%
9 6
8.7%
, 4
 
5.8%
2 4
 
5.8%
7 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 (%)
1 11
15.9%
0 10
14.5%
3 9
13.0%
5 7
10.1%
4 7
10.1%
6 6
8.7%
9 6
8.7%
, 4
 
5.8%
2 4
 
5.8%
7 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:14.208627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row동림동
2nd row10,091
3rd row22,856
4th row32
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
32 2
 
6.1%
108 1
 
3.0%
200 1
 
3.0%
22,801 1
 
3.0%
10,096 1
 
3.0%
55 1
 
3.0%
5 1
 
3.0%
2 1
 
3.0%
14 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:58:15.007907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
19.7%
2 10
13.2%
1 8
10.5%
3 7
9.2%
5 7
9.2%
6 5
 
6.6%
, 4
 
5.3%
9 4
 
5.3%
8 4
 
5.3%
4 4
 
5.3%
Other values (4) 8
10.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
22.1%
2 10
14.7%
1 8
11.8%
3 7
10.3%
5 7
10.3%
6 5
 
7.4%
9 4
 
5.9%
8 4
 
5.9%
4 4
 
5.9%
7 4
 
5.9%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
20.5%
2 10
13.7%
1 8
11.0%
3 7
9.6%
5 7
9.6%
6 5
 
6.8%
, 4
 
5.5%
9 4
 
5.5%
8 4
 
5.5%
4 4
 
5.5%
Other values (2) 5
 
6.8%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
20.5%
2 10
13.7%
1 8
11.0%
3 7
9.6%
5 7
9.6%
6 5
 
6.8%
, 4
 
5.5%
9 4
 
5.5%
8 4
 
5.5%
4 4
 
5.5%
Other values (2) 5
 
6.8%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:15.472813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row우산동
2nd row7,756
3rd row15,570
4th row51
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
51 3
 
9.1%
8 2
 
6.1%
5 1
 
3.0%
95 1
 
3.0%
7,809 1
 
3.0%
102 1
 
3.0%
53 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:58:16.297796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
20.3%
5 14
18.9%
1 11
14.9%
7 7
9.5%
8 5
 
6.8%
3 4
 
5.4%
, 4
 
5.4%
2 4
 
5.4%
4 3
 
4.1%
6 2
 
2.7%
Other values (4) 5
 
6.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
22.4%
5 14
20.9%
1 11
16.4%
7 7
10.4%
8 5
 
7.5%
3 4
 
6.0%
2 4
 
6.0%
4 3
 
4.5%
6 2
 
3.0%
9 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
21.1%
5 14
19.7%
1 11
15.5%
7 7
9.9%
8 5
 
7.0%
3 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
4 3
 
4.2%
6 2
 
2.8%
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 15
21.1%
5 14
19.7%
1 11
15.5%
7 7
9.9%
8 5
 
7.0%
3 4
 
5.6%
, 4
 
5.6%
2 4
 
5.6%
4 3
 
4.2%
6 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:16.634974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row풍향동
2nd row2,639
3rd row5,292
4th row21
5th row2
ValueCountFrequency (%)
0 7
21.2%
20 2
 
6.1%
5 2
 
6.1%
2 2
 
6.1%
25 1
 
3.0%
39 1
 
3.0%
5,256 1
 
3.0%
2,616 1
 
3.0%
36 1
 
3.0%
23 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:58:17.584041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
22.1%
0 10
14.7%
6 8
11.8%
3 6
 
8.8%
5 6
 
8.8%
, 4
 
5.9%
1 4
 
5.9%
4 4
 
5.9%
9 3
 
4.4%
- 3
 
4.4%
Other values (5) 5
 
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
85.3%
Other Punctuation 4
 
5.9%
Dash Punctuation 3
 
4.4%
Other Letter 3
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
25.9%
0 10
17.2%
6 8
13.8%
3 6
 
10.3%
5 6
 
10.3%
1 4
 
6.9%
4 4
 
6.9%
9 3
 
5.2%
8 1
 
1.7%
7 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
23.1%
0 10
15.4%
6 8
12.3%
3 6
 
9.2%
5 6
 
9.2%
, 4
 
6.2%
1 4
 
6.2%
4 4
 
6.2%
9 3
 
4.6%
- 3
 
4.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15
23.1%
0 10
15.4%
6 8
12.3%
3 6
 
9.2%
5 6
 
9.2%
, 4
 
6.2%
1 4
 
6.2%
4 4
 
6.2%
9 3
 
4.6%
- 3
 
4.6%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:18.076973image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row문화동
2nd row10,521
3rd row22,184
4th row34
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
102 1
 
3.0%
115 1
 
3.0%
22,473 1
 
3.0%
10,666 1
 
3.0%
1 1
 
3.0%
289 1
 
3.0%
145 1
 
3.0%
22 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:58:18.809635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.8%
0 14
16.3%
2 14
16.3%
4 6
 
7.0%
3 6
 
7.0%
7 5
 
5.8%
5 5
 
5.8%
, 4
 
4.7%
8 4
 
4.7%
6 4
 
4.7%
Other values (5) 7
8.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
90.7%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.8%
0 14
17.9%
2 14
17.9%
4 6
 
7.7%
3 6
 
7.7%
7 5
 
6.4%
5 5
 
6.4%
8 4
 
5.1%
6 4
 
5.1%
9 3
 
3.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
20.5%
0 14
16.9%
2 14
16.9%
4 6
 
7.2%
3 6
 
7.2%
7 5
 
6.0%
5 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
6 4
 
4.8%
Other values (2) 4
 
4.8%
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%
2 14
16.9%
4 6
 
7.2%
3 6
 
7.2%
7 5
 
6.0%
5 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
6 4
 
4.8%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:19.177261image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row문흥1동
2nd row6,719
3rd row15,545
4th row20
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
1 3
 
9.1%
15,545 1
 
3.0%
80 1
 
3.0%
19 1
 
3.0%
15,516 1
 
3.0%
6,720 1
 
3.0%
29 1
 
3.0%
11 1
 
3.0%
44 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:58:20.132076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
0 11
14.7%
4 8
10.7%
5 7
9.3%
2 6
8.0%
6 6
8.0%
9 5
 
6.7%
3 4
 
5.3%
, 4
 
5.3%
7 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 (%)
1 14
21.2%
0 11
16.7%
4 8
12.1%
5 7
10.6%
2 6
9.1%
6 6
9.1%
9 5
 
7.6%
3 4
 
6.1%
7 3
 
4.5%
8 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 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%
0 11
15.3%
4 8
11.1%
5 7
9.7%
2 6
8.3%
6 6
8.3%
9 5
 
6.9%
3 4
 
5.6%
, 4
 
5.6%
7 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 (%)
1 14
19.4%
0 11
15.3%
4 8
11.1%
5 7
9.7%
2 6
8.3%
6 6
8.3%
9 5
 
6.9%
3 4
 
5.6%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:20.576537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)84.8%

Sample

1st row문흥2동
2nd row7,355
3rd row14,921
4th row23
5th row6
ValueCountFrequency (%)
0 5
 
15.2%
22 2
 
6.1%
1 2
 
6.1%
166 1
 
3.0%
80 1
 
3.0%
14,879 1
 
3.0%
7,333 1
 
3.0%
42 1
 
3.0%
3 1
 
3.0%
8 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:58:21.520756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.7%
2 11
16.7%
0 8
12.1%
3 7
10.6%
6 7
10.6%
4 6
9.1%
8 5
7.6%
7 4
 
6.1%
5 4
 
6.1%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
15.1%
2 11
15.1%
0 8
11.0%
3 7
9.6%
6 7
9.6%
4 6
8.2%
8 5
6.8%
7 4
 
5.5%
, 4
 
5.5%
5 4
 
5.5%
Other values (2) 6
8.2%
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
2024-02-10T09:58:21.988518image/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 row3,934
3rd row7,304
4th row12
5th row9
ValueCountFrequency (%)
0 8
24.2%
9 2
 
6.1%
14 2
 
6.1%
3 2
 
6.1%
12 2
 
6.1%
36 1
 
3.0%
35 1
 
3.0%
3,931 1
 
3.0%
29 1
 
3.0%
6 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:58:22.882526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.5%
1 10
14.5%
3 10
14.5%
2 7
10.1%
9 6
8.7%
4 6
8.7%
, 4
 
5.8%
7 4
 
5.8%
6 4
 
5.8%
5 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 10
16.7%
1 10
16.7%
3 10
16.7%
2 7
11.7%
9 6
10.0%
4 6
10.0%
7 4
 
6.7%
6 4
 
6.7%
5 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 10
15.2%
1 10
15.2%
3 10
15.2%
2 7
10.6%
9 6
9.1%
4 6
9.1%
, 4
 
6.1%
7 4
 
6.1%
6 4
 
6.1%
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 10
15.2%
1 10
15.2%
3 10
15.2%
2 7
10.6%
9 6
9.1%
4 6
9.1%
, 4
 
6.1%
7 4
 
6.1%
6 4
 
6.1%
5 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
2024-02-10T09:58:23.320617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row두암2동
2nd row7,582
3rd row15,227
4th row47
5th row9
ValueCountFrequency (%)
0 7
21.2%
49 2
 
6.1%
9 2
 
6.1%
3 1
 
3.0%
78 1
 
3.0%
15,178 1
 
3.0%
7,571 1
 
3.0%
1 1
 
3.0%
11 1
 
3.0%
14 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:58:24.280783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.8%
7 12
15.8%
0 9
11.8%
4 7
9.2%
9 6
7.9%
5 6
7.9%
2 5
6.6%
3 5
6.6%
, 4
 
5.3%
8 3
 
3.9%
Other values (5) 7
9.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
18.2%
7 12
18.2%
0 9
13.6%
4 7
10.6%
9 6
9.1%
5 6
9.1%
2 5
7.6%
3 5
7.6%
8 3
 
4.5%
6 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.4%
7 12
16.4%
0 9
12.3%
4 7
9.6%
9 6
8.2%
5 6
8.2%
2 5
6.8%
3 5
6.8%
, 4
 
5.5%
8 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
16.4%
7 12
16.4%
0 9
12.3%
4 7
9.6%
9 6
8.2%
5 6
8.2%
2 5
6.8%
3 5
6.8%
, 4
 
5.5%
8 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:24.701142image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row두암3동
2nd row7,563
3rd row12,582
4th row34
5th row8
ValueCountFrequency (%)
0 8
24.2%
32 2
 
6.1%
45 2
 
6.1%
17 2
 
6.1%
8 2
 
6.1%
39 1
 
3.0%
89 1
 
3.0%
42 1
 
3.0%
12,543 1
 
3.0%
7,551 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:58:25.500201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
13.5%
0 9
12.2%
3 9
12.2%
4 8
10.8%
5 8
10.8%
2 7
9.5%
7 5
6.8%
8 4
 
5.4%
, 4
 
5.4%
6 3
 
4.1%
Other values (5) 7
9.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
87.8%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%
Dash Punctuation 2
 
2.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
15.4%
0 9
13.8%
3 9
13.8%
4 8
12.3%
5 8
12.3%
2 7
10.8%
7 5
7.7%
8 4
 
6.2%
6 3
 
4.6%
9 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
14.1%
0 9
12.7%
3 9
12.7%
4 8
11.3%
5 8
11.3%
2 7
9.9%
7 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
6 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 10
14.1%
0 9
12.7%
3 9
12.7%
4 8
11.3%
5 8
11.3%
2 7
9.9%
7 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
6 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:26.015989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row삼각동
2nd row5,990
3rd row13,389
4th row25
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
25 2
 
6.1%
39 2
 
6.1%
75 1
 
3.0%
13,389 1
 
3.0%
131 1
 
3.0%
5,992 1
 
3.0%
13 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:58:26.792630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 9
14.3%
1 9
14.3%
0 8
12.7%
9 7
11.1%
5 7
11.1%
7 7
11.1%
2 6
9.5%
4 4
6.3%
6 4
6.3%
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 (%)
3 9
13.2%
1 9
13.2%
0 8
11.8%
9 7
10.3%
5 7
10.3%
7 7
10.3%
2 6
8.8%
4 4
5.9%
6 4
5.9%
, 4
5.9%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 9
13.2%
1 9
13.2%
0 8
11.8%
9 7
10.3%
5 7
10.3%
7 7
10.3%
2 6
8.8%
4 4
5.9%
6 4
5.9%
, 4
5.9%
Other values (2) 3
 
4.4%
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
2024-02-10T09:58:27.218368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row일곡동
2nd row11,442
3rd row28,366
4th row28
5th row14
ValueCountFrequency (%)
0 6
 
18.2%
14 3
 
9.1%
222 1
 
3.0%
28,335 1
 
3.0%
11,435 1
 
3.0%
1 1
 
3.0%
31 1
 
3.0%
7 1
 
3.0%
87 1
 
3.0%
39 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:58:28.243861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
20.7%
2 12
14.6%
0 9
11.0%
3 8
9.8%
4 7
8.5%
7 5
 
6.1%
, 4
 
4.9%
8 4
 
4.9%
6 4
 
4.9%
9 4
 
4.9%
Other values (5) 8
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
87.8%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.6%
2 12
16.7%
0 9
12.5%
3 8
11.1%
4 7
9.7%
7 5
 
6.9%
8 4
 
5.6%
6 4
 
5.6%
9 4
 
5.6%
5 2
 
2.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
21.5%
2 12
15.2%
0 9
11.4%
3 8
10.1%
4 7
8.9%
7 5
 
6.3%
, 4
 
5.1%
8 4
 
5.1%
6 4
 
5.1%
9 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
21.5%
2 12
15.2%
0 9
11.4%
3 8
10.1%
4 7
8.9%
7 5
 
6.3%
, 4
 
5.1%
8 4
 
5.1%
6 4
 
5.1%
9 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:28.633060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row매곡동
2nd row5,480
3rd row13,339
4th row18
5th row5
ValueCountFrequency (%)
0 8
24.2%
7 2
 
6.1%
52 2
 
6.1%
33 2
 
6.1%
18 2
 
6.1%
5 2
 
6.1%
매곡동 1
 
3.0%
121 1
 
3.0%
69 1
 
3.0%
61 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:58:29.425925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
15.7%
0 10
14.3%
3 10
14.3%
5 9
12.9%
2 5
7.1%
7 4
 
5.7%
, 4
 
5.7%
9 4
 
5.7%
8 3
 
4.3%
4 3
 
4.3%
Other values (5) 7
10.0%

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 (%)
1 11
17.7%
0 10
16.1%
3 10
16.1%
5 9
14.5%
2 5
8.1%
7 4
 
6.5%
9 4
 
6.5%
8 3
 
4.8%
4 3
 
4.8%
6 3
 
4.8%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
16.4%
0 10
14.9%
3 10
14.9%
5 9
13.4%
2 5
7.5%
7 4
 
6.0%
, 4
 
6.0%
9 4
 
6.0%
8 3
 
4.5%
4 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:29.729498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.3030303
Min length1

Characters and Unicode

Total characters76
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row오치1동
2nd row5,414
3rd row10,324
4th row44
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
2 2
 
6.1%
57 1
 
3.0%
105 1
 
3.0%
10,340 1
 
3.0%
5,425 1
 
3.0%
16 1
 
3.0%
11 1
 
3.0%
29 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:58:30.667639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
18.4%
1 12
15.8%
2 11
14.5%
4 11
14.5%
5 6
7.9%
, 4
 
5.3%
6 4
 
5.3%
3 3
 
3.9%
7 3
 
3.9%
9 2
 
2.6%
Other values (5) 6
7.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
20.6%
1 12
17.6%
2 11
16.2%
4 11
16.2%
5 6
8.8%
6 4
 
5.9%
3 3
 
4.4%
7 3
 
4.4%
9 2
 
2.9%
8 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
19.2%
1 12
16.4%
2 11
15.1%
4 11
15.1%
5 6
8.2%
, 4
 
5.5%
6 4
 
5.5%
3 3
 
4.1%
7 3
 
4.1%
9 2
 
2.7%
Other values (2) 3
 
4.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
19.2%
1 12
16.4%
2 11
15.1%
4 11
15.1%
5 6
8.2%
, 4
 
5.5%
6 4
 
5.5%
3 3
 
4.1%
7 3
 
4.1%
9 2
 
2.7%
Other values (2) 3
 
4.1%
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
2024-02-10T09:58:30.996632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique25 ?
Unique (%)75.8%

Sample

1st row오치2동
2nd row6,790
3rd row11,690
4th row32
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
12 2
 
6.1%
66 1
 
3.0%
57 1
 
3.0%
31 1
 
3.0%
11,649 1
 
3.0%
6,765 1
 
3.0%
41 1
 
3.0%
25 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:58:31.897480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.2%
0 9
11.7%
2 9
11.7%
6 8
10.4%
3 7
9.1%
9 5
 
6.5%
4 5
 
6.5%
, 4
 
5.2%
5 4
 
5.2%
7 3
 
3.9%
Other values (5) 9
11.7%

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 (%)
1 14
20.9%
0 9
13.4%
2 9
13.4%
6 8
11.9%
3 7
10.4%
9 5
 
7.5%
4 5
 
7.5%
5 4
 
6.0%
7 3
 
4.5%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
18.9%
0 9
12.2%
2 9
12.2%
6 8
10.8%
3 7
9.5%
9 5
 
6.8%
4 5
 
6.8%
, 4
 
5.4%
5 4
 
5.4%
7 3
 
4.1%
Other values (2) 6
8.1%
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 (%)
1 14
18.9%
0 9
12.2%
2 9
12.2%
6 8
10.8%
3 7
9.5%
9 5
 
6.8%
4 5
 
6.8%
, 4
 
5.4%
5 4
 
5.4%
7 3
 
4.1%
Other values (2) 6
8.1%
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
2024-02-10T09:58:32.331367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8181818
Min length1

Characters and Unicode

Total characters60
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

Unique13 ?
Unique (%)39.4%

Sample

1st row석곡동
2nd row1,316
3rd row2,337
4th row8
5th row3
ValueCountFrequency (%)
0 9
27.3%
3 3
 
9.1%
8 3
 
9.1%
14 2
 
6.1%
9 2
 
6.1%
10 2
 
6.1%
23 1
 
3.0%
29 1
 
3.0%
15 1
 
3.0%
11 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T09:58:33.251539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
20.0%
0 11
18.3%
3 11
18.3%
8 4
 
6.7%
, 4
 
6.7%
2 4
 
6.7%
4 3
 
5.0%
9 3
 
5.0%
5 2
 
3.3%
6 1
 
1.7%
Other values (5) 5
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
86.7%
Other Punctuation 4
 
6.7%
Other Letter 3
 
5.0%
Dash Punctuation 1
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
23.1%
0 11
21.2%
3 11
21.2%
8 4
 
7.7%
2 4
 
7.7%
4 3
 
5.8%
9 3
 
5.8%
5 2
 
3.8%
6 1
 
1.9%
7 1
 
1.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 57
95.0%
Hangul 3
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
21.1%
0 11
19.3%
3 11
19.3%
8 4
 
7.0%
, 4
 
7.0%
2 4
 
7.0%
4 3
 
5.3%
9 3
 
5.3%
5 2
 
3.5%
6 1
 
1.8%
Other values (2) 2
 
3.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
95.0%
Hangul 3
 
5.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
21.1%
0 11
19.3%
3 11
19.3%
8 4
 
7.0%
, 4
 
7.0%
2 4
 
7.0%
4 3
 
5.3%
9 3
 
5.3%
5 2
 
3.5%
6 1
 
1.8%
Other values (2) 2
 
3.5%
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
2024-02-10T09:58:33.670803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row건국동
2nd row8,864
3rd row21,314
4th row53
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
127 1
 
3.0%
21,257 1
 
3.0%
8,820 1
 
3.0%
1 1
 
3.0%
57 1
 
3.0%
44 1
 
3.0%
19 1
 
3.0%
73 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:58:34.870026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.5%
0 11
13.9%
2 8
10.1%
5 8
10.1%
4 6
7.6%
6 5
 
6.3%
8 5
 
6.3%
7 5
 
6.3%
, 4
 
5.1%
3 4
 
5.1%
Other values (5) 10
12.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
18.8%
0 11
15.9%
2 8
11.6%
5 8
11.6%
4 6
8.7%
6 5
 
7.2%
8 5
 
7.2%
7 5
 
7.2%
3 4
 
5.8%
9 4
 
5.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
17.1%
0 11
14.5%
2 8
10.5%
5 8
10.5%
4 6
7.9%
6 5
 
6.6%
8 5
 
6.6%
7 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 7
9.2%
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 13
17.1%
0 11
14.5%
2 8
10.5%
5 8
10.5%
4 6
7.9%
6 5
 
6.6%
8 5
 
6.6%
7 5
 
6.6%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 7
9.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:58:35.260325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6363636
Min length1

Characters and Unicode

Total characters87
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row양산동
2nd row16,170
3rd row36,288
4th row76
5th row17
ValueCountFrequency (%)
0 6
 
18.2%
17 2
 
6.1%
176 1
 
3.0%
342 1
 
3.0%
36,217 1
 
3.0%
16,147 1
 
3.0%
2 1
 
3.0%
71 1
 
3.0%
23 1
 
3.0%
16 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:58:36.022621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
21.8%
7 11
12.6%
2 10
11.5%
6 9
10.3%
0 8
9.2%
4 7
 
8.0%
3 6
 
6.9%
8 6
 
6.9%
, 4
 
4.6%
- 3
 
3.4%
Other values (4) 4
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
88.5%
Other Punctuation 4
 
4.6%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
24.7%
7 11
14.3%
2 10
13.0%
6 9
11.7%
0 8
10.4%
4 7
 
9.1%
3 6
 
7.8%
8 6
 
7.8%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
22.6%
7 11
13.1%
2 10
11.9%
6 9
10.7%
0 8
9.5%
4 7
 
8.3%
3 6
 
7.1%
8 6
 
7.1%
, 4
 
4.8%
- 3
 
3.6%
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 19
22.6%
7 11
13.1%
2 10
11.9%
6 9
10.7%
0 8
9.5%
4 7
 
8.3%
3 6
 
7.1%
8 6
 
7.1%
, 4
 
4.8%
- 3
 
3.6%
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
2024-02-10T09:58:36.444253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row신용동
2nd row11,723
3rd row29,039
4th row12
5th row11
ValueCountFrequency (%)
0 6
 
18.2%
11 3
 
9.1%
12 2
 
6.1%
2 1
 
3.0%
113 1
 
3.0%
11,713 1
 
3.0%
1 1
 
3.0%
18 1
 
3.0%
10 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:58:37.489454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
28.9%
2 14
16.9%
0 9
 
10.8%
3 6
 
7.2%
9 5
 
6.0%
8 5
 
6.0%
, 4
 
4.8%
7 4
 
4.8%
- 3
 
3.6%
4 2
 
2.4%
Other values (5) 7
 
8.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
32.9%
2 14
19.2%
0 9
 
12.3%
3 6
 
8.2%
9 5
 
6.8%
8 5
 
6.8%
7 4
 
5.5%
4 2
 
2.7%
6 2
 
2.7%
5 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
30.0%
2 14
17.5%
0 9
 
11.2%
3 6
 
7.5%
9 5
 
6.2%
8 5
 
6.2%
, 4
 
5.0%
7 4
 
5.0%
- 3
 
3.8%
4 2
 
2.5%
Other values (2) 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
30.0%
2 14
17.5%
0 9
 
11.2%
3 6
 
7.5%
9 5
 
6.2%
8 5
 
6.2%
, 4
 
5.0%
7 4
 
5.0%
- 3
 
3.8%
4 2
 
2.5%
Other values (2) 4
 
5.0%
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>2024.01.09<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.10 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>199,4042,9064,4383,6812,2404,5807,392<NA>17,9847,3665,9695,49910,0917,7562,63910,5216,7197,3553,9347,5827,5635,99011,4425,4805,4146,7901,3168,86416,17011,723
4<NA>전월말인구수<NA><NA><NA>422,7764,5258,4016,5583,8659,09912,287<NA>37,26418,55411,35913,29722,85615,5705,29222,18415,54514,9217,30415,22712,58213,38928,36613,33910,32411,6902,33721,31436,28829,039
5<NA>전월말거주불명자수<NA><NA><NA>1,004453143322772<NA>8120523132512134202312473425281844328537612
6<NA>전월말재외국민등록자수<NA><NA><NA>243173551<NA>2222817982109699841451012361711
7<NA>증 가 요 인전 입<NA>4,07745771095771148<NA>3161841531181452054451812212550119891311921211298929198271222
8<NA><NA><NA>남자<NA>2,079234659353787<NA>1719473547210520247576131704573906963431510214493
9<NA><NA><NA>여자<NA>1,998223150223461<NA>14590806473100242716564194944581025266461496127129
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>390000110<NA>10150215003000100000000
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>-31-19-17-5-16-9-21<NA>21605553-231451-22-3-11-122-7-111-25-3-44-23-10
29<NA>인구수증감<NA><NA><NA>-209-44-18-13-17-32-21<NA>-3452112-55102-36289-29-42-29-49-39-13-31716-411-57-71-18
30<NA>거주불명자수증감<NA><NA><NA>-19-1-120-10-2<NA>-111-1000-5-1-1-10-110-10-2-10-1-2-1
31<NA>금월말세대수<NA><NA><NA>199,3732,8874,4213,6762,2244,5717,371<NA>17,9867,3825,9695,50410,0967,8092,61610,6666,7207,3333,9317,5717,5515,99211,4355,4795,4256,7651,3138,82016,14711,713
32<NA>금월말인구수<NA><NA><NA>422,5674,4818,3836,5453,8489,06712,266<NA>37,23018,60611,37013,29922,80115,6725,25622,47315,51614,8797,27515,17812,54313,37628,33513,34610,34011,6492,33821,25736,21729,021
33<NA>금월말거주불명자수<NA><NA><NA>985443045321770<NA>8031513132511633192212463525271842318527411
34<NA>금월말재외국민등록자수<NA><NA><NA>242173561<NA>22229177821010599841451011361711

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34# duplicates
0<NA>국외<NA><NA>0000000<NA>00000000000000000000002
1<NA>기타<NA><NA>0000000<NA>00000000000000000000002