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

Description2022-11-16
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 09:47:15.662931
Analysis finished2024-02-10 09:47:17.860424
Duration2.2 seconds
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
2024-02-10T09:47:18.200612image/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%
2024-02-10T09:47:19.267237image/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
2024-02-10T09:47:19.651687image/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%
2024-02-10T09:47:20.785740image/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
2024-02-10T09:47:21.176506image/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 row2022.10 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%
2022.10 1
7.1%
현재 1
7.1%
2024-02-10T09:47:21.996467image/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%
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 3
30.0%
0 2
20.0%
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 3
30.0%
0 2
20.0%
1 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:47:22.486038image/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%
2024-02-10T09:47:23.137144image/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
2024-02-10T09:47:23.660695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.8181818
Min length1

Characters and Unicode

Total characters126
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

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row197,341
3rd row423,743
4th row860
5th row223
ValueCountFrequency (%)
0 4
 
11.8%
2,605 2
 
5.9%
2,571 1
 
2.9%
883 1
 
2.9%
424,720 1
 
2.9%
198,023 1
 
2.9%
23 1
 
2.9%
977 1
 
2.9%
682 1
 
2.9%
2 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:47:24.788293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 23
18.3%
0 17
13.5%
, 16
12.7%
1 12
9.5%
3 10
7.9%
8 10
7.9%
4 9
 
7.1%
9 8
 
6.3%
5 7
 
5.6%
7 6
 
4.8%
Other values (4) 8
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 106
84.1%
Other Punctuation 16
 
12.7%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 23
21.7%
0 17
16.0%
1 12
11.3%
3 10
9.4%
8 10
9.4%
4 9
 
8.5%
9 8
 
7.5%
5 7
 
6.6%
7 6
 
5.7%
6 4
 
3.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 23
18.5%
0 17
13.7%
, 16
12.9%
1 12
9.7%
3 10
8.1%
8 10
8.1%
4 9
 
7.3%
9 8
 
6.5%
5 7
 
5.6%
7 6
 
4.8%
Other values (2) 6
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 23
18.5%
0 17
13.7%
, 16
12.9%
1 12
9.7%
3 10
8.1%
8 10
8.1%
4 9
 
7.3%
9 8
 
6.5%
5 7
 
5.6%
7 6
 
4.8%
Other values (2) 6
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:25.279239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row중흥1동
2nd row2,955
3rd row4,644
4th row38
5th row0
ValueCountFrequency (%)
0 9
27.3%
36 1
 
3.0%
40 1
 
3.0%
4,623 1
 
3.0%
2,947 1
 
3.0%
4 1
 
3.0%
21 1
 
3.0%
8 1
 
3.0%
3 1
 
3.0%
22 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:26.242731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.5%
2 10
14.5%
4 9
13.0%
1 7
10.1%
3 6
8.7%
, 4
 
5.8%
9 4
 
5.8%
5 4
 
5.8%
6 4
 
5.8%
8 3
 
4.3%
Other values (5) 8
11.6%

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%
2 10
16.7%
4 9
15.0%
1 7
11.7%
3 6
10.0%
9 4
 
6.7%
5 4
 
6.7%
6 4
 
6.7%
8 3
 
5.0%
7 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%
2 10
15.2%
4 9
13.6%
1 7
10.6%
3 6
9.1%
, 4
 
6.1%
9 4
 
6.1%
5 4
 
6.1%
6 4
 
6.1%
8 3
 
4.5%
Other values (2) 5
7.6%
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%
2 10
15.2%
4 9
13.6%
1 7
10.6%
3 6
9.1%
, 4
 
6.1%
9 4
 
6.1%
5 4
 
6.1%
6 4
 
6.1%
8 3
 
4.5%
Other values (2) 5
7.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:26.589745image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row중흥2동
2nd row4,444
3rd row8,537
4th row24
5th row6
ValueCountFrequency (%)
0 7
21.2%
6 2
 
6.1%
24 2
 
6.1%
2 2
 
6.1%
81 1
 
3.0%
8,537 1
 
3.0%
96 1
 
3.0%
4,414 1
 
3.0%
59 1
 
3.0%
30 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:47:27.668191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 12
16.9%
0 8
11.3%
2 8
11.3%
9 7
9.9%
6 5
7.0%
1 5
7.0%
8 5
7.0%
5 4
 
5.6%
7 4
 
5.6%
3 4
 
5.6%
Other values (5) 9
12.7%

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 (%)
4 12
19.4%
0 8
12.9%
2 8
12.9%
9 7
11.3%
6 5
8.1%
1 5
8.1%
8 5
8.1%
5 4
 
6.5%
7 4
 
6.5%
3 4
 
6.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
17.6%
0 8
11.8%
2 8
11.8%
9 7
10.3%
6 5
7.4%
1 5
7.4%
8 5
7.4%
5 4
 
5.9%
7 4
 
5.9%
3 4
 
5.9%
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 (%)
4 12
17.6%
0 8
11.8%
2 8
11.8%
9 7
10.3%
6 5
7.4%
1 5
7.4%
8 5
7.4%
5 4
 
5.9%
7 4
 
5.9%
3 4
 
5.9%
Other values (2) 6
8.8%
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
2024-02-10T09:47:28.134857image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row중흥3동
2nd row3,631
3rd row6,579
4th row37
5th row3
ValueCountFrequency (%)
0 6
18.2%
3 3
 
9.1%
50 2
 
6.1%
25 2
 
6.1%
29 2
 
6.1%
8 1
 
3.0%
80 1
 
3.0%
6,550 1
 
3.0%
3,634 1
 
3.0%
9 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:47:29.241695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.7%
3 11
15.7%
5 10
14.3%
2 5
7.1%
6 5
7.1%
9 5
7.1%
1 4
 
5.7%
7 4
 
5.7%
, 4
 
5.7%
4 4
 
5.7%
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 (%)
0 11
17.7%
3 11
17.7%
5 10
16.1%
2 5
8.1%
6 5
8.1%
9 5
8.1%
1 4
 
6.5%
7 4
 
6.5%
4 4
 
6.5%
8 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 (%)
0 11
16.4%
3 11
16.4%
5 10
14.9%
2 5
7.5%
6 5
7.5%
9 5
7.5%
1 4
 
6.0%
7 4
 
6.0%
, 4
 
6.0%
4 4
 
6.0%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.4%
3 11
16.4%
5 10
14.9%
2 5
7.5%
6 5
7.5%
9 5
7.5%
1 4
 
6.0%
7 4
 
6.0%
, 4
 
6.0%
4 4
 
6.0%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:29.662615image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row중앙동
2nd row2,354
3rd row4,001
4th row23
5th row5
ValueCountFrequency (%)
0 6
18.2%
4 2
 
6.1%
27 2
 
6.1%
5 2
 
6.1%
36 2
 
6.1%
2 1
 
3.0%
55 1
 
3.0%
2,354 1
 
3.0%
2,337 1
 
3.0%
26 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:47:30.781534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 10
14.5%
2 10
14.5%
0 9
13.0%
5 7
10.1%
1 7
10.1%
4 5
7.2%
7 5
7.2%
6 4
 
5.8%
, 4
 
5.8%
8 2
 
2.9%
Other values (5) 6
8.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 10
16.7%
2 10
16.7%
0 9
15.0%
5 7
11.7%
1 7
11.7%
4 5
8.3%
7 5
8.3%
6 4
 
6.7%
8 2
 
3.3%
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 (%)
3 10
15.2%
2 10
15.2%
0 9
13.6%
5 7
10.6%
1 7
10.6%
4 5
7.6%
7 5
7.6%
6 4
 
6.1%
, 4
 
6.1%
8 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 10
15.2%
2 10
15.2%
0 9
13.6%
5 7
10.6%
1 7
10.6%
4 5
7.6%
7 5
7.6%
6 4
 
6.1%
, 4
 
6.1%
8 2
 
3.0%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct21
Distinct (%)61.8%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:47:31.236773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1764706
Min length1

Characters and Unicode

Total characters74
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)44.1%

Sample

1st row출력일자 :
2nd row임동
3rd row4,611
4th row9,137
5th row26
ValueCountFrequency (%)
0 9
25.7%
26 2
 
5.7%
5 2
 
5.7%
23 2
 
5.7%
57 2
 
5.7%
9,137 2
 
5.7%
1
 
2.9%
2 1
 
2.9%
21 1
 
2.9%
29 1
 
2.9%
Other values (12) 12
34.3%
2024-02-10T09:47:32.069803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
14.9%
1 10
13.5%
0 9
12.2%
3 7
9.5%
5 6
8.1%
7 5
6.8%
6 5
6.8%
, 4
 
5.4%
9 4
 
5.4%
4 4
 
5.4%
Other values (9) 9
12.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
83.8%
Other Letter 6
 
8.1%
Other Punctuation 5
 
6.8%
Space Separator 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
17.7%
1 10
16.1%
0 9
14.5%
3 7
11.3%
5 6
9.7%
7 5
8.1%
6 5
8.1%
9 4
 
6.5%
4 4
 
6.5%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 68
91.9%
Hangul 6
 
8.1%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
16.2%
1 10
14.7%
0 9
13.2%
3 7
10.3%
5 6
8.8%
7 5
7.4%
6 5
7.4%
, 4
 
5.9%
9 4
 
5.9%
4 4
 
5.9%
Other values (3) 3
 
4.4%
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 68
91.9%
Hangul 6
 
8.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
16.2%
1 10
14.7%
0 9
13.2%
3 7
10.3%
5 6
8.8%
7 5
7.4%
6 5
7.4%
, 4
 
5.9%
9 4
 
5.9%
4 4
 
5.9%
Other values (3) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:32.483284image/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 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 row신안동
2nd row7,328
3rd row12,454
4th row62
5th row2
ValueCountFrequency (%)
1 4
 
12.1%
0 4
 
12.1%
2 2
 
6.1%
79 1
 
3.0%
87 1
 
3.0%
12,598 1
 
3.0%
7,469 1
 
3.0%
144 1
 
3.0%
141 1
 
3.0%
9 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:47:33.449752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.5%
6 11
14.3%
4 9
11.7%
2 8
10.4%
0 6
 
7.8%
7 6
 
7.8%
9 5
 
6.5%
, 4
 
5.2%
3 4
 
5.2%
8 3
 
3.9%
Other values (4) 6
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
90.9%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.4%
6 11
15.7%
4 9
12.9%
2 8
11.4%
0 6
 
8.6%
7 6
 
8.6%
9 5
 
7.1%
3 4
 
5.7%
8 3
 
4.3%
5 3
 
4.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.3%
6 11
14.9%
4 9
12.2%
2 8
10.8%
0 6
 
8.1%
7 6
 
8.1%
9 5
 
6.8%
, 4
 
5.4%
3 4
 
5.4%
8 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 (%)
1 15
20.3%
6 11
14.9%
4 9
12.2%
2 8
10.8%
0 6
 
8.1%
7 6
 
8.1%
9 5
 
6.8%
, 4
 
5.4%
3 4
 
5.4%
8 3
 
4.1%
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
Minimum2022-11-07 00:00:00
Maximum2022-11-07 00:00:00
2024-02-10T09:47:33.811560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:47:34.125642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:34.423191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
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 row용봉동
2nd row17,873
3rd row37,907
4th row80
5th row20
ValueCountFrequency (%)
0 7
21.2%
122 2
 
6.1%
20 2
 
6.1%
171 2
 
6.1%
144 2
 
6.1%
260 1
 
3.0%
80 1
 
3.0%
349 1
 
3.0%
37,736 1
 
3.0%
17,831 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:47:35.452170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
16.9%
2 13
14.6%
0 12
13.5%
7 10
11.2%
3 9
10.1%
4 6
 
6.7%
8 6
 
6.7%
6 4
 
4.5%
9 4
 
4.5%
, 4
 
4.5%
Other values (5) 6
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
89.9%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
18.8%
2 13
16.2%
0 12
15.0%
7 10
12.5%
3 9
11.2%
4 6
 
7.5%
8 6
 
7.5%
6 4
 
5.0%
9 4
 
5.0%
5 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 86
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
17.4%
2 13
15.1%
0 12
14.0%
7 10
11.6%
3 9
10.5%
4 6
 
7.0%
8 6
 
7.0%
6 4
 
4.7%
9 4
 
4.7%
, 4
 
4.7%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
17.4%
2 13
15.1%
0 12
14.0%
7 10
11.6%
3 9
10.5%
4 6
 
7.0%
8 6
 
7.0%
6 4
 
4.7%
9 4
 
4.7%
, 4
 
4.7%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:35.868723image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row운암1동
2nd row7,445
3rd row19,064
4th row17
5th row18
ValueCountFrequency (%)
0 7
21.2%
18 3
 
9.1%
63 2
 
6.1%
89 2
 
6.1%
7,445 1
 
3.0%
17 1
 
3.0%
91 1
 
3.0%
7,429 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:47:36.805280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.8%
4 10
13.2%
0 8
10.5%
8 7
9.2%
9 7
9.2%
6 5
6.6%
2 5
6.6%
7 5
6.6%
3 4
 
5.3%
5 4
 
5.3%
Other values (5) 9
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
88.2%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
17.9%
4 10
14.9%
0 8
11.9%
8 7
10.4%
9 7
10.4%
6 5
7.5%
2 5
7.5%
7 5
7.5%
3 4
 
6.0%
5 4
 
6.0%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.4%
4 10
13.7%
0 8
11.0%
8 7
9.6%
9 7
9.6%
6 5
6.8%
2 5
6.8%
7 5
6.8%
3 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 12
16.4%
4 10
13.7%
0 8
11.0%
8 7
9.6%
9 7
9.6%
6 5
6.8%
2 5
6.8%
7 5
6.8%
3 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: 15
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:37.134425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row운암2동
2nd row6,068
3rd row11,629
4th row56
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
53 3
 
9.1%
9 2
 
6.1%
1 1
 
3.0%
80 1
 
3.0%
11,600 1
 
3.0%
6,038 1
 
3.0%
4 1
 
3.0%
29 1
 
3.0%
30 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:37.943494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.0%
1 9
12.0%
3 8
10.7%
6 8
10.7%
5 6
8.0%
9 6
8.0%
2 6
8.0%
8 5
6.7%
, 4
 
5.3%
7 3
 
4.0%
Other values (5) 8
10.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.5%
1 9
13.8%
3 8
12.3%
6 8
12.3%
5 6
9.2%
9 6
9.2%
2 6
9.2%
8 5
7.7%
7 3
 
4.6%
4 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 12
16.7%
1 9
12.5%
3 8
11.1%
6 8
11.1%
5 6
8.3%
9 6
8.3%
2 6
8.3%
8 5
6.9%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 5
6.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.7%
1 9
12.5%
3 8
11.1%
6 8
11.1%
5 6
8.3%
9 6
8.3%
2 6
8.3%
8 5
6.9%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 5
6.9%
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
2024-02-10T09:47:38.465290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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 row운암3동
2nd row5,430
3rd row13,317
4th row21
5th row15
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
43 1
 
3.0%
13,368 1
 
3.0%
5,452 1
 
3.0%
1 1
 
3.0%
51 1
 
3.0%
22 1
 
3.0%
5 1
 
3.0%
33 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:47:39.292614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
1 10
13.5%
5 9
12.2%
3 9
12.2%
2 8
10.8%
4 7
9.5%
, 4
 
5.4%
7 4
 
5.4%
6 4
 
5.4%
9 3
 
4.1%
Other values (5) 5
6.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.7%
1 10
15.2%
5 9
13.6%
3 9
13.6%
2 8
12.1%
4 7
10.6%
7 4
 
6.1%
6 4
 
6.1%
9 3
 
4.5%
8 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.5%
1 10
14.1%
5 9
12.7%
3 9
12.7%
2 8
11.3%
4 7
9.9%
, 4
 
5.6%
7 4
 
5.6%
6 4
 
5.6%
9 3
 
4.2%
Other values (2) 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.5%
1 10
14.1%
5 9
12.7%
3 9
12.7%
2 8
11.3%
4 7
9.9%
, 4
 
5.6%
7 4
 
5.6%
6 4
 
5.6%
9 3
 
4.2%
Other values (2) 2
 
2.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:39.626147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row동림동
2nd row9,885
3rd row22,942
4th row25
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
61 2
 
6.1%
7 2
 
6.1%
104 1
 
3.0%
212 1
 
3.0%
22,881 1
 
3.0%
9,890 1
 
3.0%
5 1
 
3.0%
12 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:40.604655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.0%
2 11
14.7%
0 10
13.3%
8 9
12.0%
4 7
9.3%
6 7
9.3%
7 4
 
5.3%
9 4
 
5.3%
, 4
 
5.3%
5 3
 
4.0%
Other values (3) 4
 
5.3%

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 12
17.9%
2 11
16.4%
0 10
14.9%
8 9
13.4%
4 7
10.4%
6 7
10.4%
7 4
 
6.0%
9 4
 
6.0%
5 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 (%)
1 12
16.7%
2 11
15.3%
0 10
13.9%
8 9
12.5%
4 7
9.7%
6 7
9.7%
7 4
 
5.6%
9 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
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 (%)
1 12
16.7%
2 11
15.3%
0 10
13.9%
8 9
12.5%
4 7
9.7%
6 7
9.7%
7 4
 
5.6%
9 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:40.963453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.7575758
Min length1

Characters and Unicode

Total characters91
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

Unique25 ?
Unique (%)75.8%

Sample

1st row우산동
2nd row5,619
3rd row10,189
4th row44
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
59 1
 
3.0%
115 1
 
3.0%
12,437 1
 
3.0%
6,493 1
 
3.0%
1 1
 
3.0%
2,248 1
 
3.0%
874 1
 
3.0%
11 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:47:41.740808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
22.0%
, 10
11.0%
4 10
11.0%
0 8
 
8.8%
2 8
 
8.8%
8 7
 
7.7%
7 6
 
6.6%
5 5
 
5.5%
6 5
 
5.5%
9 5
 
5.5%
Other values (4) 7
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
85.7%
Other Punctuation 10
 
11.0%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
25.6%
4 10
12.8%
0 8
 
10.3%
2 8
 
10.3%
8 7
 
9.0%
7 6
 
7.7%
5 5
 
6.4%
6 5
 
6.4%
9 5
 
6.4%
3 4
 
5.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
22.7%
, 10
11.4%
4 10
11.4%
0 8
 
9.1%
2 8
 
9.1%
8 7
 
8.0%
7 6
 
6.8%
5 5
 
5.7%
6 5
 
5.7%
9 5
 
5.7%
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 20
22.7%
, 10
11.4%
4 10
11.4%
0 8
 
9.1%
2 8
 
9.1%
8 7
 
8.0%
7 6
 
6.8%
5 5
 
5.7%
6 5
 
5.7%
9 5
 
5.7%
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
2024-02-10T09:47:42.101585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row풍향동
2nd row2,753
3rd row5,574
4th row14
5th row2
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
2 2
 
6.1%
5 1
 
3.0%
121 1
 
3.0%
5,506 1
 
3.0%
2,729 1
 
3.0%
68 1
 
3.0%
24 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:43.142040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
15.7%
1 10
14.3%
0 8
11.4%
5 8
11.4%
3 7
10.0%
7 5
7.1%
, 4
 
5.7%
6 4
 
5.7%
4 3
 
4.3%
8 3
 
4.3%
Other values (5) 7
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
87.1%
Other Punctuation 4
 
5.7%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
18.0%
1 10
16.4%
0 8
13.1%
5 8
13.1%
3 7
11.5%
7 5
8.2%
6 4
 
6.6%
4 3
 
4.9%
8 3
 
4.9%
9 2
 
3.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
16.4%
1 10
14.9%
0 8
11.9%
5 8
11.9%
3 7
10.4%
7 5
7.5%
, 4
 
6.0%
6 4
 
6.0%
4 3
 
4.5%
8 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
16.4%
1 10
14.9%
0 8
11.9%
5 8
11.9%
3 7
10.4%
7 5
7.5%
, 4
 
6.0%
6 4
 
6.0%
4 3
 
4.5%
8 3
 
4.5%
Other values (2) 4
 
6.0%
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
2024-02-10T09:47:43.551853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row문화동
2nd row9,662
3rd row20,439
4th row31
5th row8
ValueCountFrequency (%)
0 7
21.2%
8 2
 
6.1%
31 2
 
6.1%
10 1
 
3.0%
277 1
 
3.0%
9,629 1
 
3.0%
115 1
 
3.0%
33 1
 
3.0%
11 1
 
3.0%
60 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:44.359362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.5%
1 12
15.2%
2 9
11.4%
3 8
10.1%
6 7
8.9%
9 6
7.6%
8 4
 
5.1%
, 4
 
5.1%
4 4
 
5.1%
5 4
 
5.1%
Other values (5) 8
10.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
18.6%
1 12
17.1%
2 9
12.9%
3 8
11.4%
6 7
10.0%
9 6
8.6%
8 4
 
5.7%
4 4
 
5.7%
5 4
 
5.7%
7 3
 
4.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.1%
1 12
15.8%
2 9
11.8%
3 8
10.5%
6 7
9.2%
9 6
7.9%
8 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
5 4
 
5.3%
Other values (2) 5
 
6.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
17.1%
1 12
15.8%
2 9
11.8%
3 8
10.5%
6 7
9.2%
9 6
7.9%
8 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
5 4
 
5.3%
Other values (2) 5
 
6.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:44.798907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row문흥1동
2nd row6,442
3rd row15,534
4th row19
5th row9
ValueCountFrequency (%)
0 7
21.2%
19 3
 
9.1%
9 2
 
6.1%
58 2
 
6.1%
115 1
 
3.0%
96 1
 
3.0%
6,432 1
 
3.0%
75 1
 
3.0%
10 1
 
3.0%
5 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:47:45.612320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
5 11
14.7%
9 10
13.3%
0 8
10.7%
3 7
9.3%
4 6
8.0%
, 4
 
5.3%
8 3
 
4.0%
6 3
 
4.0%
2 2
 
2.7%
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%
5 11
16.7%
9 10
15.2%
0 8
12.1%
3 7
10.6%
4 6
9.1%
8 3
 
4.5%
6 3
 
4.5%
2 2
 
3.0%
7 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%
5 11
15.3%
9 10
13.9%
0 8
11.1%
3 7
9.7%
4 6
8.3%
, 4
 
5.6%
8 3
 
4.2%
6 3
 
4.2%
2 2
 
2.8%
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%
5 11
15.3%
9 10
13.9%
0 8
11.1%
3 7
9.7%
4 6
8.3%
, 4
 
5.6%
8 3
 
4.2%
6 3
 
4.2%
2 2
 
2.8%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:45.955323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row문흥2동
2nd row7,381
3rd row15,366
4th row22
5th row4
ValueCountFrequency (%)
0 8
24.2%
22 2
 
6.1%
115 1
 
3.0%
214 1
 
3.0%
15,272 1
 
3.0%
7,371 1
 
3.0%
94 1
 
3.0%
10 1
 
3.0%
11 1
 
3.0%
52 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:46.959756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 12
17.6%
1 12
17.6%
0 10
14.7%
3 7
10.3%
7 6
8.8%
5 6
8.8%
6 4
 
5.9%
4 4
 
5.9%
9 4
 
5.9%
8 3
 
4.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
16.2%
1 12
16.2%
0 10
13.5%
3 7
9.5%
7 6
8.1%
5 6
8.1%
, 4
 
5.4%
6 4
 
5.4%
4 4
 
5.4%
9 4
 
5.4%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
16.2%
1 12
16.2%
0 10
13.5%
3 7
9.5%
7 6
8.1%
5 6
8.1%
, 4
 
5.4%
6 4
 
5.4%
4 4
 
5.4%
9 4
 
5.4%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:47.264891image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row두암1동
2nd row3,996
3rd row7,598
4th row10
5th row8
ValueCountFrequency (%)
0 9
27.3%
24 2
 
6.1%
10 2
 
6.1%
8 2
 
6.1%
22 2
 
6.1%
15 2
 
6.1%
66 1
 
3.0%
65 1
 
3.0%
3,974 1
 
3.0%
83 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:47:48.315526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.5%
1 9
12.7%
5 7
9.9%
2 7
9.9%
8 6
8.5%
3 5
7.0%
9 5
7.0%
6 5
7.0%
4 4
 
5.6%
, 4
 
5.6%
Other values (5) 8
11.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.7%
1 9
14.5%
5 7
11.3%
2 7
11.3%
8 6
9.7%
3 5
8.1%
9 5
8.1%
6 5
8.1%
4 4
 
6.5%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.2%
1 9
13.2%
5 7
10.3%
2 7
10.3%
8 6
8.8%
3 5
7.4%
9 5
7.4%
6 5
7.4%
4 4
 
5.9%
, 4
 
5.9%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.2%
1 9
13.2%
5 7
10.3%
2 7
10.3%
8 6
8.8%
3 5
7.4%
9 5
7.4%
6 5
7.4%
4 4
 
5.9%
, 4
 
5.9%
Other values (2) 5
7.4%
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
2024-02-10T09:47:48.740348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

Total characters78
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row두암2동
2nd row7,670
3rd row15,687
4th row48
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 3
 
9.1%
108 1
 
3.0%
107 1
 
3.0%
15,605 1
 
3.0%
7,661 1
 
3.0%
1 1
 
3.0%
82 1
 
3.0%
14 1
 
3.0%
54 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:49.776019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.4%
1 11
14.1%
7 9
11.5%
5 7
9.0%
4 7
9.0%
6 6
7.7%
8 5
6.4%
2 4
 
5.1%
, 4
 
5.1%
3 4
 
5.1%
Other values (5) 9
11.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
87.2%
Other Punctuation 4
 
5.1%
Dash Punctuation 3
 
3.8%
Other Letter 3
 
3.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
17.6%
1 11
16.2%
7 9
13.2%
5 7
10.3%
4 7
10.3%
6 6
8.8%
8 5
7.4%
2 4
 
5.9%
3 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%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.0%
1 11
14.7%
7 9
12.0%
5 7
9.3%
4 7
9.3%
6 6
8.0%
8 5
6.7%
2 4
 
5.3%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 6
8.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.0%
1 11
14.7%
7 9
12.0%
5 7
9.3%
4 7
9.3%
6 6
8.0%
8 5
6.7%
2 4
 
5.3%
, 4
 
5.3%
3 4
 
5.3%
Other values (2) 6
8.0%
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
2024-02-10T09:47:50.160491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row두암3동
2nd row7,703
3rd row12,950
4th row24
5th row8
ValueCountFrequency (%)
0 8
24.2%
24 2
 
6.1%
8 2
 
6.1%
61 1
 
3.0%
12,950 1
 
3.0%
81 1
 
3.0%
7,694 1
 
3.0%
57 1
 
3.0%
9 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:47:50.967596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.2%
1 10
13.5%
3 8
10.8%
8 6
8.1%
5 6
8.1%
7 6
8.1%
2 5
6.8%
4 5
6.8%
, 4
 
5.4%
9 4
 
5.4%
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 (%)
0 12
18.5%
1 10
15.4%
3 8
12.3%
8 6
9.2%
5 6
9.2%
7 6
9.2%
2 5
7.7%
4 5
7.7%
9 4
 
6.2%
6 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 (%)
0 12
16.9%
1 10
14.1%
3 8
11.3%
8 6
8.5%
5 6
8.5%
7 6
8.5%
2 5
7.0%
4 5
7.0%
, 4
 
5.6%
9 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 12
16.9%
1 10
14.1%
3 8
11.3%
8 6
8.5%
5 6
8.5%
7 6
8.5%
2 5
7.0%
4 5
7.0%
, 4
 
5.6%
9 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:51.359049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
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 row삼각동
2nd row6,056
3rd row13,792
4th row21
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
4 2
 
6.1%
24 2
 
6.1%
13,736 1
 
3.0%
6,032 1
 
3.0%
3 1
 
3.0%
56 1
 
3.0%
9 1
 
3.0%
39 1
 
3.0%
31 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:47:52.329412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 11
17.2%
1 9
14.1%
6 9
14.1%
3 8
12.5%
9 7
10.9%
2 6
9.4%
4 5
7.8%
5 5
7.8%
7 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 11
15.7%
1 9
12.9%
6 9
12.9%
3 8
11.4%
9 7
10.0%
2 6
8.6%
4 5
7.1%
5 5
7.1%
, 4
 
5.7%
7 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.7%
1 9
12.9%
6 9
12.9%
3 8
11.4%
9 7
10.0%
2 6
8.6%
4 5
7.1%
5 5
7.1%
, 4
 
5.7%
7 4
 
5.7%
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
2024-02-10T09:47:52.712126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique21 ?
Unique (%)63.6%

Sample

1st row일곡동
2nd row11,533
3rd row29,119
4th row24
5th row12
ValueCountFrequency (%)
0 7
21.2%
12 3
 
9.1%
24 2
 
6.1%
135 1
 
3.0%
29,119 1
 
3.0%
122 1
 
3.0%
11,507 1
 
3.0%
103 1
 
3.0%
26 1
 
3.0%
14 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:47:53.527746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
19.3%
2 14
16.9%
0 11
13.3%
6 7
8.4%
5 7
8.4%
3 6
 
7.2%
4 4
 
4.8%
9 4
 
4.8%
, 4
 
4.8%
8 3
 
3.6%
Other values (5) 7
8.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
21.6%
2 14
18.9%
0 11
14.9%
6 7
9.5%
5 7
9.5%
3 6
 
8.1%
4 4
 
5.4%
9 4
 
5.4%
8 3
 
4.1%
7 2
 
2.7%
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 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.0%
2 14
17.5%
0 11
13.8%
6 7
8.8%
5 7
8.8%
3 6
 
7.5%
4 4
 
5.0%
9 4
 
5.0%
, 4
 
5.0%
8 3
 
3.8%
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 16
20.0%
2 14
17.5%
0 11
13.8%
6 7
8.8%
5 7
8.8%
3 6
 
7.5%
4 4
 
5.0%
9 4
 
5.0%
, 4
 
5.0%
8 3
 
3.8%
Other values (2) 4
 
5.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:53.968639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
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

Unique18 ?
Unique (%)54.5%

Sample

1st row매곡동
2nd row5,495
3rd row13,645
4th row11
5th row5
ValueCountFrequency (%)
0 7
21.2%
24 2
 
6.1%
1 2
 
6.1%
11 2
 
6.1%
4 2
 
6.1%
68 2
 
6.1%
5 1
 
3.0%
136 1
 
3.0%
13,621 1
 
3.0%
5,496 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:47:54.779352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
18.3%
0 9
12.7%
5 9
12.7%
6 8
11.3%
4 7
9.9%
3 6
8.5%
2 5
 
7.0%
8 4
 
5.6%
, 4
 
5.6%
9 2
 
2.8%
Other values (4) 4
 
5.6%

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 (%)
1 13
20.6%
0 9
14.3%
5 9
14.3%
6 8
12.7%
4 7
11.1%
3 6
9.5%
2 5
 
7.9%
8 4
 
6.3%
9 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
19.1%
0 9
13.2%
5 9
13.2%
6 8
11.8%
4 7
10.3%
3 6
8.8%
2 5
 
7.4%
8 4
 
5.9%
, 4
 
5.9%
9 2
 
2.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
19.1%
0 9
13.2%
5 9
13.2%
6 8
11.8%
4 7
10.3%
3 6
8.8%
2 5
 
7.4%
8 4
 
5.9%
, 4
 
5.9%
9 2
 
2.9%
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
2024-02-10T09:47:55.108774image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row오치1동
2nd row5,462
3rd row10,577
4th row24
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
9 3
 
9.1%
5 2
 
6.1%
77 1
 
3.0%
24 1
 
3.0%
72 1
 
3.0%
10,567 1
 
3.0%
5,453 1
 
3.0%
1 1
 
3.0%
10 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:47:56.138002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
1 9
12.2%
2 9
12.2%
5 8
10.8%
7 7
9.5%
4 5
6.8%
3 5
6.8%
8 4
 
5.4%
, 4
 
5.4%
9 3
 
4.1%
Other values (5) 9
12.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
1 9
14.1%
2 9
14.1%
5 8
12.5%
7 7
10.9%
4 5
7.8%
3 5
7.8%
8 4
 
6.2%
9 3
 
4.7%
6 3
 
4.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.5%
1 9
12.7%
2 9
12.7%
5 8
11.3%
7 7
9.9%
4 5
7.0%
3 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.5%
1 9
12.7%
2 9
12.7%
5 8
11.3%
7 7
9.9%
4 5
7.0%
3 5
7.0%
8 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
Other values (2) 6
8.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:47:56.611223image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row오치2동
2nd row6,942
3rd row12,173
4th row28
5th row10
ValueCountFrequency (%)
0 7
21.2%
81 2
 
6.1%
26 2
 
6.1%
10 2
 
6.1%
155 1
 
3.0%
6,922 1
 
3.0%
2 1
 
3.0%
20 1
 
3.0%
13 1
 
3.0%
33 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:47:57.470655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
16.9%
0 12
15.6%
1 11
14.3%
3 7
9.1%
4 6
7.8%
6 5
 
6.5%
9 5
 
6.5%
, 4
 
5.2%
8 4
 
5.2%
- 3
 
3.9%
Other values (5) 7
9.1%

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 (%)
2 13
19.4%
0 12
17.9%
1 11
16.4%
3 7
10.4%
4 6
9.0%
6 5
 
7.5%
9 5
 
7.5%
8 4
 
6.0%
7 2
 
3.0%
5 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
17.6%
0 12
16.2%
1 11
14.9%
3 7
9.5%
4 6
8.1%
6 5
 
6.8%
9 5
 
6.8%
, 4
 
5.4%
8 4
 
5.4%
- 3
 
4.1%
Other values (2) 4
 
5.4%
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 (%)
2 13
17.6%
0 12
16.2%
1 11
14.9%
3 7
9.5%
4 6
8.1%
6 5
 
6.8%
9 5
 
6.8%
, 4
 
5.4%
8 4
 
5.4%
- 3
 
4.1%
Other values (2) 4
 
5.4%
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
2024-02-10T09:47:57.912689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8484848
Min length1

Characters and Unicode

Total characters61
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

Unique14 ?
Unique (%)42.4%

Sample

1st row석곡동
2nd row1,360
3rd row2,444
4th row10
5th row3
ValueCountFrequency (%)
0 8
24.2%
1 4
12.1%
3 3
 
9.1%
13 2
 
6.1%
10 2
 
6.1%
6 2
 
6.1%
9 1
 
3.0%
17 1
 
3.0%
14 1
 
3.0%
2,444 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T09:47:59.046929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
23.0%
0 11
18.0%
3 9
14.8%
4 5
 
8.2%
, 4
 
6.6%
2 4
 
6.6%
6 3
 
4.9%
8 2
 
3.3%
- 2
 
3.3%
7 2
 
3.3%
Other values (5) 5
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 52
85.2%
Other Punctuation 4
 
6.6%
Other Letter 3
 
4.9%
Dash Punctuation 2
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
26.9%
0 11
21.2%
3 9
17.3%
4 5
 
9.6%
2 4
 
7.7%
6 3
 
5.8%
8 2
 
3.8%
7 2
 
3.8%
5 1
 
1.9%
9 1
 
1.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 58
95.1%
Hangul 3
 
4.9%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
24.1%
0 11
19.0%
3 9
15.5%
4 5
 
8.6%
, 4
 
6.9%
2 4
 
6.9%
6 3
 
5.2%
8 2
 
3.4%
- 2
 
3.4%
7 2
 
3.4%
Other values (2) 2
 
3.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 58
95.1%
Hangul 3
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
24.1%
0 11
19.0%
3 9
15.5%
4 5
 
8.6%
, 4
 
6.9%
2 4
 
6.9%
6 3
 
5.2%
8 2
 
3.4%
- 2
 
3.4%
7 2
 
3.4%
Other values (2) 2
 
3.4%
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
2024-02-10T09:47:59.537000image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row건국동
2nd row9,070
3rd row21,889
4th row50
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 3
 
9.1%
50 2
 
6.1%
106 1
 
3.0%
101 1
 
3.0%
21,839 1
 
3.0%
9,061 1
 
3.0%
2 1
 
3.0%
7 1
 
3.0%
49 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:48:00.508528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
22.7%
9 9
13.6%
1 8
12.1%
2 7
10.6%
5 6
 
9.1%
7 5
 
7.6%
4 5
 
7.6%
8 4
 
6.1%
6 4
 
6.1%
3 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 33
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:48:00.978190image/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 row양산동
2nd row16,337
3rd row37,141
4th row62
5th row17
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
17 2
 
6.1%
176 1
 
3.0%
355 1
 
3.0%
37,121 1
 
3.0%
16,327 1
 
3.0%
20 1
 
3.0%
10 1
 
3.0%
5 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:48:01.899285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
24.4%
0 10
11.6%
7 10
11.6%
3 9
10.5%
2 8
 
9.3%
6 7
 
8.1%
5 5
 
5.8%
, 4
 
4.7%
8 3
 
3.5%
4 2
 
2.3%
Other values (5) 7
 
8.1%

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 21
27.3%
0 10
13.0%
7 10
13.0%
3 9
11.7%
2 8
 
10.4%
6 7
 
9.1%
5 5
 
6.5%
8 3
 
3.9%
4 2
 
2.6%
9 2
 
2.6%
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 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
25.3%
0 10
12.0%
7 10
12.0%
3 9
10.8%
2 8
 
9.6%
6 7
 
8.4%
5 5
 
6.0%
, 4
 
4.8%
8 3
 
3.6%
4 2
 
2.4%
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 21
25.3%
0 10
12.0%
7 10
12.0%
3 9
10.8%
2 8
 
9.6%
6 7
 
8.4%
5 5
 
6.0%
, 4
 
4.8%
8 3
 
3.6%
4 2
 
2.4%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:48:02.234825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
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

Unique18 ?
Unique (%)54.5%

Sample

1st row신용동
2nd row11,836
3rd row29,415
4th row9
5th row9
ValueCountFrequency (%)
0 7
21.2%
9 4
 
12.1%
62 2
 
6.1%
59 2
 
6.1%
27 1
 
3.0%
130 1
 
3.0%
11,814 1
 
3.0%
57 1
 
3.0%
22 1
 
3.0%
6 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:48:03.073272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 12
15.6%
1 12
15.6%
0 10
13.0%
2 9
11.7%
6 6
7.8%
5 6
7.8%
8 5
6.5%
, 4
 
5.2%
3 3
 
3.9%
4 3
 
3.9%
Other values (5) 7
9.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 12
17.6%
1 12
17.6%
0 10
14.7%
2 9
13.2%
6 6
8.8%
5 6
8.8%
8 5
7.4%
3 3
 
4.4%
4 3
 
4.4%
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 74
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
9 12
16.2%
1 12
16.2%
0 10
13.5%
2 9
12.2%
6 6
8.1%
5 6
8.1%
8 5
6.8%
, 4
 
5.4%
3 3
 
4.1%
4 3
 
4.1%
Other values (2) 4
 
5.4%
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 (%)
9 12
16.2%
1 12
16.2%
0 10
13.5%
2 9
12.2%
6 6
8.1%
5 6
8.1%
8 5
6.8%
, 4
 
5.4%
3 3
 
4.1%
4 3
 
4.1%
Other values (2) 4
 
5.4%
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>2022.11.07<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>2022.10 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>197,3412,9554,4443,6312,3544,6117,328<NA>17,8737,4456,0685,4309,8855,6192,7539,6626,4427,3813,9967,6707,7036,05611,5335,4955,4626,9421,3609,07016,33711,836
4<NA>전월말인구수<NA><NA><NA>423,7434,6448,5376,5794,0019,13712,454<NA>37,90719,06411,62913,31722,94210,1895,57420,43915,53415,3667,59815,68712,95013,79229,11913,64510,57712,1732,44421,88937,14129,415
5<NA>전월말거주불명자수<NA><NA><NA>860382437232662<NA>8017562125441431192210482421241124281050629
6<NA>전월말재외국민등록자수<NA><NA><NA>223063552<NA>2018915772894898412591039179
7<NA>증 가 요 인전 입<NA>5,988579610455121316<NA>349891431461482,36851162111123541441031051551111288317152317180
8<NA><NA><NA>남자<NA>3,0002847542759176<NA>171447170681,18733725860227352596955804037416484
9<NA><NA><NA>여자<NA>2,9882949502862140<NA>178457276801,181189053633271514686564843147815396
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>1000001<NA>0000000000000000000000
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>2000101<NA>0000000000000000000000
28<NA>세대수증감<NA><NA><NA>682-8-303-1723141<NA>-42-16-30225874-24-33-10-10-22-9-9-24-261-9-20-7-9-10-22
29<NA>인구수증감<NA><NA><NA>977-21-59-29-260144<NA>-171-89-2951-612,248-68-115-75-94-83-82-57-56-103-24-10-81-6-50-20-57
30<NA>거주불명자수증감<NA><NA><NA>23409401<NA>11-4-11130000-10300-1-21210
31<NA>금월말세대수<NA><NA><NA>198,0232,9474,4143,6342,3374,6347,469<NA>17,8317,4296,0385,4529,8906,4932,7299,6296,4327,3713,9747,6617,6946,03211,5075,4965,4536,9221,3539,06116,32711,814
32<NA>금월말인구수<NA><NA><NA>424,7204,6238,4786,5503,9759,13712,598<NA>37,73618,97511,60013,36822,88112,4375,50620,32415,45915,2727,51515,60512,89313,73629,01613,62110,56712,0922,43821,83937,12129,358
33<NA>금월말거주불명자수<NA><NA><NA>883422446272663<NA>8118522026451731192210472424241123261152639
34<NA>금월말재외국민등록자수<NA><NA><NA>224063551<NA>2018915772895898412691039179

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