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

Description2022-11-03
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 09:38:20.972548
Analysis finished2024-02-10 09:38:23.177793
Duration2.21 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
2024-02-10T09:38:23.618062image/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%
2024-02-10T09:38:25.083000image/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
2024-02-10T09:38:25.540702image/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%
2024-02-10T09:38:26.670072image/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
2024-02-10T09:38:27.094520image/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 row2022.09 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%
2022.09 1
7.1%
현재 1
7.1%
2024-02-10T09:38:27.999270image/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%
9 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%
9 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%
9 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:38:28.293410image/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%
2024-02-10T09:38:29.015353image/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
2024-02-10T09:38:29.429679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.0606061
Min length1

Characters and Unicode

Total characters134
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row197,556
3rd row424,715
4th row1,268
5th row220
ValueCountFrequency (%)
0 3
 
8.8%
5 2
 
5.9%
1,388 2
 
5.9%
1,617 1
 
2.9%
1,268 1
 
2.9%
220 1
 
2.9%
860 1
 
2.9%
423,743 1
 
2.9%
197,341 1
 
2.9%
408 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T09:38:30.271708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
14.9%
2 20
14.9%
, 17
12.7%
4 14
10.4%
3 11
8.2%
7 11
8.2%
9 9
6.7%
0 7
 
5.2%
8 7
 
5.2%
5 7
 
5.2%
Other values (5) 11
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 110
82.1%
Other Punctuation 17
 
12.7%
Dash Punctuation 3
 
2.2%
Space Separator 2
 
1.5%
Other Letter 2
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
18.2%
2 20
18.2%
4 14
12.7%
3 11
10.0%
7 11
10.0%
9 9
8.2%
0 7
 
6.4%
8 7
 
6.4%
5 7
 
6.4%
6 4
 
3.6%
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 132
98.5%
Hangul 2
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
15.2%
2 20
15.2%
, 17
12.9%
4 14
10.6%
3 11
8.3%
7 11
8.3%
9 9
6.8%
0 7
 
5.3%
8 7
 
5.3%
5 7
 
5.3%
Other values (3) 9
6.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 132
98.5%
Hangul 2
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
15.2%
2 20
15.2%
, 17
12.9%
4 14
10.6%
3 11
8.3%
7 11
8.3%
9 9
6.8%
0 7
 
5.3%
8 7
 
5.3%
5 7
 
5.3%
Other values (3) 9
6.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:30.614793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique19 ?
Unique (%)57.6%

Sample

1st row중흥1동
2nd row2,974
3rd row4,674
4th row53
5th row0
ValueCountFrequency (%)
0 8
24.2%
15 3
 
9.1%
31 2
 
6.1%
2 2
 
6.1%
19 2
 
6.1%
30 2
 
6.1%
50 1
 
3.0%
53 1
 
3.0%
21 1
 
3.0%
4,644 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:38:31.410837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.4%
0 11
15.1%
5 8
11.0%
4 8
11.0%
3 7
9.6%
2 5
6.8%
, 4
 
5.5%
9 4
 
5.5%
6 3
 
4.1%
7 3
 
4.1%
Other values (5) 8
11.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
19.0%
0 11
17.5%
5 8
12.7%
4 8
12.7%
3 7
11.1%
2 5
7.9%
9 4
 
6.3%
6 3
 
4.8%
7 3
 
4.8%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
17.1%
0 11
15.7%
5 8
11.4%
4 8
11.4%
3 7
10.0%
2 5
7.1%
, 4
 
5.7%
9 4
 
5.7%
6 3
 
4.3%
7 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.1%
0 11
15.7%
5 8
11.4%
4 8
11.4%
3 7
10.0%
2 5
7.1%
, 4
 
5.7%
9 4
 
5.7%
6 3
 
4.3%
7 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:31.773110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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 row중흥2동
2nd row4,463
3rd row8,548
4th row62
5th row6
ValueCountFrequency (%)
0 5
 
15.2%
6 3
 
9.1%
29 2
 
6.1%
38 2
 
6.1%
45 1
 
3.0%
99 1
 
3.0%
8,537 1
 
3.0%
4,444 1
 
3.0%
11 1
 
3.0%
19 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:38:32.696885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 12
18.8%
2 8
12.5%
5 8
12.5%
6 7
10.9%
9 7
10.9%
3 6
9.4%
0 5
7.8%
8 5
7.8%
1 5
7.8%
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 71
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
4 12
16.9%
2 8
11.3%
5 8
11.3%
6 7
9.9%
9 7
9.9%
3 6
8.5%
0 5
7.0%
8 5
7.0%
1 5
7.0%
, 4
 
5.6%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 12
16.9%
2 8
11.3%
5 8
11.3%
6 7
9.9%
9 7
9.9%
3 6
8.5%
0 5
7.0%
8 5
7.0%
1 5
7.0%
, 4
 
5.6%
Other values (2) 4
 
5.6%
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
2024-02-10T09:38:33.013880image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row중흥3동
2nd row3,626
3rd row6,579
4th row52
5th row3
ValueCountFrequency (%)
0 6
18.2%
3 2
 
6.1%
6,579 2
 
6.1%
52 2
 
6.1%
5 2
 
6.1%
28 1
 
3.0%
100 1
 
3.0%
3,631 1
 
3.0%
15 1
 
3.0%
14 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:38:33.807662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 9
14.5%
3 9
14.5%
0 8
12.9%
4 8
12.9%
6 7
11.3%
2 7
11.3%
7 5
8.1%
1 5
8.1%
9 3
 
4.8%
8 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
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 (%)
5 9
13.4%
3 9
13.4%
0 8
11.9%
4 8
11.9%
6 7
10.4%
2 7
10.4%
7 5
7.5%
1 5
7.5%
, 4
6.0%
9 3
 
4.5%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 9
13.4%
3 9
13.4%
0 8
11.9%
4 8
11.9%
6 7
10.4%
2 7
10.4%
7 5
7.5%
1 5
7.5%
, 4
6.0%
9 3
 
4.5%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:34.195767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique23 ?
Unique (%)69.7%

Sample

1st row중앙동
2nd row2,389
3rd row4,045
4th row50
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
19 2
 
6.1%
26 2
 
6.1%
39 1
 
3.0%
32 1
 
3.0%
23 1
 
3.0%
4,001 1
 
3.0%
2,354 1
 
3.0%
27 1
 
3.0%
44 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:38:35.028616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
15.3%
0 10
13.9%
4 10
13.9%
3 8
11.1%
1 6
8.3%
5 6
8.3%
9 4
 
5.6%
, 4
 
5.6%
6 3
 
4.2%
- 3
 
4.2%
Other values (5) 7
9.7%

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 (%)
2 11
17.7%
0 10
16.1%
4 10
16.1%
3 8
12.9%
1 6
9.7%
5 6
9.7%
9 4
 
6.5%
6 3
 
4.8%
7 2
 
3.2%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 10
Text

MISSING 

Distinct28
Distinct (%)82.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:38:35.410032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2647059
Min length1

Characters and Unicode

Total characters77
Distinct characters19
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

Unique25 ?
Unique (%)73.5%

Sample

1st row출력일자 :
2nd row임동
3rd row4,574
4th row9,125
5th row36
ValueCountFrequency (%)
0 5
 
14.3%
5 2
 
5.7%
10 2
 
5.7%
70 2
 
5.7%
54 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
62 1
 
2.9%
9,137 1
 
2.9%
4,611 1
 
2.9%
Other values (18) 18
51.4%
2024-02-10T09:38:36.342747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
83.1%
Other Letter 6
 
7.8%
Other Punctuation 5
 
6.5%
Dash Punctuation 1
 
1.3%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.8%
1 12
18.8%
6 7
10.9%
4 7
10.9%
5 6
9.4%
3 6
9.4%
7 5
7.8%
2 5
7.8%
9 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
92.2%
Hangul 6
 
7.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.9%
1 12
16.9%
6 7
9.9%
4 7
9.9%
5 6
8.5%
3 6
8.5%
7 5
7.0%
2 5
7.0%
9 4
 
5.6%
, 4
 
5.6%
Other values (3) 3
 
4.2%
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 71
92.2%
Hangul 6
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.9%
1 12
16.9%
6 7
9.9%
4 7
9.9%
5 6
8.5%
3 6
8.5%
7 5
7.0%
2 5
7.0%
9 4
 
5.6%
, 4
 
5.6%
Other values (3) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%
1
16.7%

Unnamed: 11
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:36.837589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3939394
Min length1

Characters and Unicode

Total characters79
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row신안동
2nd row7,248
3rd row12,353
4th row86
5th row1
ValueCountFrequency (%)
0 5
 
15.2%
1 2
 
6.1%
63 1
 
3.0%
62 1
 
3.0%
12,454 1
 
3.0%
7,328 1
 
3.0%
24 1
 
3.0%
101 1
 
3.0%
80 1
 
3.0%
20 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T09:38:37.601776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
13.9%
1 11
13.9%
2 11
13.9%
4 9
11.4%
3 8
10.1%
8 7
8.9%
6 7
8.9%
, 4
 
5.1%
5 4
 
5.1%
7 3
 
3.8%
Other values (4) 4
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
89.9%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
15.5%
1 11
15.5%
2 11
15.5%
4 9
12.7%
3 8
11.3%
8 7
9.9%
6 7
9.9%
5 4
 
5.6%
7 3
 
4.2%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.5%
1 11
14.5%
2 11
14.5%
4 9
11.8%
3 8
10.5%
8 7
9.2%
6 7
9.2%
, 4
 
5.3%
5 4
 
5.3%
7 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
14.5%
1 11
14.5%
2 11
14.5%
4 9
11.8%
3 8
10.5%
8 7
9.2%
6 7
9.2%
, 4
 
5.3%
5 4
 
5.3%
7 3
 
3.9%
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
Minimum2022-10-11 00:00:00
Maximum2022-10-11 00:00:00
2024-02-10T09:38:38.035629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:38:38.311099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:38.655745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7575758
Min length1

Characters and Unicode

Total characters91
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row용봉동
2nd row17,882
3rd row37,986
4th row123
5th row20
ValueCountFrequency (%)
0 5
 
15.2%
20 2
 
6.1%
233 1
 
3.0%
37,907 1
 
3.0%
17,873 1
 
3.0%
43 1
 
3.0%
79 1
 
3.0%
9 1
 
3.0%
41 1
 
3.0%
11 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T09:38:39.430082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
18.7%
3 13
14.3%
0 11
12.1%
7 9
9.9%
8 9
9.9%
2 6
 
6.6%
4 5
 
5.5%
9 5
 
5.5%
, 4
 
4.4%
6 3
 
3.3%
Other values (5) 9
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
89.0%
Other Punctuation 4
 
4.4%
Dash Punctuation 3
 
3.3%
Other Letter 3
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.0%
3 13
16.0%
0 11
13.6%
7 9
11.1%
8 9
11.1%
2 6
 
7.4%
4 5
 
6.2%
9 5
 
6.2%
6 3
 
3.7%
5 3
 
3.7%
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 88
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
19.3%
3 13
14.8%
0 11
12.5%
7 9
10.2%
8 9
10.2%
2 6
 
6.8%
4 5
 
5.7%
9 5
 
5.7%
, 4
 
4.5%
6 3
 
3.4%
Other values (2) 6
 
6.8%
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 17
19.3%
3 13
14.8%
0 11
12.5%
7 9
10.2%
8 9
10.2%
2 6
 
6.8%
4 5
 
5.7%
9 5
 
5.7%
, 4
 
4.5%
6 3
 
3.4%
Other values (2) 6
 
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:39.831952image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row운암1동
2nd row7,466
3rd row19,099
4th row27
5th row18
ValueCountFrequency (%)
0 6
 
18.2%
18 2
 
6.1%
10 2
 
6.1%
77 1
 
3.0%
19,064 1
 
3.0%
7,445 1
 
3.0%
35 1
 
3.0%
21 1
 
3.0%
8 1
 
3.0%
59 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:38:40.774109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.2%
0 11
13.9%
7 10
12.7%
4 7
8.9%
5 6
7.6%
6 6
7.6%
9 6
7.6%
, 4
 
5.1%
2 4
 
5.1%
3 4
 
5.1%
Other values (5) 9
11.4%

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 12
17.4%
0 11
15.9%
7 10
14.5%
4 7
10.1%
5 6
8.7%
6 6
8.7%
9 6
8.7%
2 4
 
5.8%
3 4
 
5.8%
8 3
 
4.3%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
15.8%
0 11
14.5%
7 10
13.2%
4 7
9.2%
5 6
7.9%
6 6
7.9%
9 6
7.9%
, 4
 
5.3%
2 4
 
5.3%
3 4
 
5.3%
Other values (2) 6
7.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
15.8%
0 11
14.5%
7 10
13.2%
4 7
9.2%
5 6
7.9%
6 6
7.9%
9 6
7.9%
, 4
 
5.3%
2 4
 
5.3%
3 4
 
5.3%
Other values (2) 6
7.9%
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
2024-02-10T09:38:41.143965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row운암2동
2nd row6,080
3rd row11,688
4th row56
5th row8
ValueCountFrequency (%)
0 8
24.2%
56 2
 
6.1%
55 2
 
6.1%
54 1
 
3.0%
11,688 1
 
3.0%
89 1
 
3.0%
11,629 1
 
3.0%
6,068 1
 
3.0%
59 1
 
3.0%
12 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:38:42.344519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.3%
5 10
13.3%
1 10
13.3%
6 9
12.0%
8 8
10.7%
9 6
8.0%
, 4
 
5.3%
2 4
 
5.3%
4 3
 
4.0%
3 2
 
2.7%
Other values (5) 6
8.0%

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 13
19.7%
5 10
15.2%
1 10
15.2%
6 9
13.6%
8 8
12.1%
9 6
9.1%
2 4
 
6.1%
4 3
 
4.5%
3 2
 
3.0%
7 1
 
1.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.1%
5 10
13.9%
1 10
13.9%
6 9
12.5%
8 8
11.1%
9 6
8.3%
, 4
 
5.6%
2 4
 
5.6%
4 3
 
4.2%
3 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.1%
5 10
13.9%
1 10
13.9%
6 9
12.5%
8 8
11.1%
9 6
8.3%
, 4
 
5.6%
2 4
 
5.6%
4 3
 
4.2%
3 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:42.900182image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row운암3동
2nd row5,423
3rd row13,317
4th row30
5th row15
ValueCountFrequency (%)
0 7
21.2%
38 2
 
6.1%
66 2
 
6.1%
4 2
 
6.1%
13,317 2
 
6.1%
9 2
 
6.1%
15 2
 
6.1%
7 1
 
3.0%
142 1
 
3.0%
29 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:38:43.903457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
16.4%
0 10
13.7%
1 10
13.7%
6 7
9.6%
4 7
9.6%
7 5
6.8%
2 5
6.8%
5 4
 
5.5%
, 4
 
5.5%
9 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 (%)
3 12
18.5%
0 10
15.4%
1 10
15.4%
6 7
10.8%
4 7
10.8%
7 5
7.7%
2 5
7.7%
5 4
 
6.2%
9 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 (%)
3 12
17.1%
0 10
14.3%
1 10
14.3%
6 7
10.0%
4 7
10.0%
7 5
7.1%
2 5
7.1%
5 4
 
5.7%
, 4
 
5.7%
9 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 (%)
3 12
17.1%
0 10
14.3%
1 10
14.3%
6 7
10.0%
4 7
10.0%
7 5
7.1%
2 5
7.1%
5 4
 
5.7%
, 4
 
5.7%
9 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:44.353046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row동림동
2nd row9,918
3rd row23,032
4th row53
5th row8
ValueCountFrequency (%)
0 5
 
15.2%
7 2
 
6.1%
116 1
 
3.0%
22,942 1
 
3.0%
9,885 1
 
3.0%
28 1
 
3.0%
90 1
 
3.0%
33 1
 
3.0%
30 1
 
3.0%
13 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T09:38:45.382468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
14.3%
2 9
12.9%
1 9
12.9%
8 9
12.9%
3 8
11.4%
9 6
8.6%
6 6
8.6%
7 5
7.1%
4 4
 
5.7%
5 4
 
5.7%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
13.0%
2 9
11.7%
1 9
11.7%
8 9
11.7%
3 8
10.4%
9 6
7.8%
6 6
7.8%
7 5
6.5%
4 4
 
5.2%
, 4
 
5.2%
Other values (2) 7
9.1%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
13.0%
2 9
11.7%
1 9
11.7%
8 9
11.7%
3 8
10.4%
9 6
7.8%
6 6
7.8%
7 5
6.5%
4 4
 
5.2%
, 4
 
5.2%
Other values (2) 7
9.1%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:45.920951image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row우산동
2nd row5,603
3rd row10,102
4th row62
5th row7
ValueCountFrequency (%)
0 4
 
12.1%
35 3
 
9.1%
7 2
 
6.1%
28 2
 
6.1%
2 2
 
6.1%
18 2
 
6.1%
3 1
 
3.0%
211 1
 
3.0%
112 1
 
3.0%
10,189 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:38:46.895103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
18.7%
0 9
12.0%
2 9
12.0%
8 8
10.7%
3 6
8.0%
9 6
8.0%
5 5
 
6.7%
6 5
 
6.7%
, 4
 
5.3%
7 3
 
4.0%
Other values (5) 6
8.0%

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 14
20.9%
0 9
13.4%
2 9
13.4%
8 8
11.9%
3 6
9.0%
9 6
9.0%
5 5
 
7.5%
6 5
 
7.5%
7 3
 
4.5%
4 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.4%
0 9
12.5%
2 9
12.5%
8 8
11.1%
3 6
8.3%
9 6
8.3%
5 5
 
6.9%
6 5
 
6.9%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.4%
0 9
12.5%
2 9
12.5%
8 8
11.1%
3 6
8.3%
9 6
8.3%
5 5
 
6.9%
6 5
 
6.9%
, 4
 
5.6%
7 3
 
4.2%
Other values (2) 3
 
4.2%
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
2024-02-10T09:38:47.299999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

Total characters70
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

Unique21 ?
Unique (%)63.6%

Sample

1st row풍향동
2nd row2,771
3rd row5,607
4th row22
5th row2
ValueCountFrequency (%)
0 5
 
15.2%
2 3
 
9.1%
10 2
 
6.1%
1 2
 
6.1%
8 2
 
6.1%
62 1
 
3.0%
22 1
 
3.0%
47 1
 
3.0%
5,574 1
 
3.0%
2,753 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:38:48.193088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
85.7%
Other Punctuation 4
 
5.7%
Dash Punctuation 3
 
4.3%
Other Letter 3
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
2 10
16.7%
1 8
13.3%
7 7
11.7%
4 6
10.0%
8 5
8.3%
3 5
8.3%
5 5
8.3%
6 4
 
6.7%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.9%
2 10
14.9%
1 8
11.9%
7 7
10.4%
4 6
9.0%
8 5
7.5%
3 5
7.5%
5 5
7.5%
6 4
 
6.0%
, 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 10
14.9%
2 10
14.9%
1 8
11.9%
7 7
10.4%
4 6
9.0%
8 5
7.5%
3 5
7.5%
5 5
7.5%
6 4
 
6.0%
, 4
 
6.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:48.680771image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row문화동
2nd row9,688
3rd row20,526
4th row52
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
21 3
 
9.1%
8 2
 
6.1%
89 1
 
3.0%
114 1
 
3.0%
20,439 1
 
3.0%
9,662 1
 
3.0%
87 1
 
3.0%
26 1
 
3.0%
62 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:38:49.522591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
15.2%
0 10
12.7%
6 10
12.7%
1 8
10.1%
8 7
8.9%
3 6
7.6%
9 5
6.3%
, 4
 
5.1%
4 4
 
5.1%
7 4
 
5.1%
Other values (5) 9
11.4%

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 (%)
2 12
17.4%
0 10
14.5%
6 10
14.5%
1 8
11.6%
8 7
10.1%
3 6
8.7%
9 5
7.2%
4 4
 
5.8%
7 4
 
5.8%
5 3
 
4.3%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
2 12
15.8%
0 10
13.2%
6 10
13.2%
1 8
10.5%
8 7
9.2%
3 6
7.9%
9 5
6.6%
, 4
 
5.3%
4 4
 
5.3%
7 4
 
5.3%
Other values (2) 6
7.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 12
15.8%
0 10
13.2%
6 10
13.2%
1 8
10.5%
8 7
9.2%
3 6
7.9%
9 5
6.6%
, 4
 
5.3%
4 4
 
5.3%
7 4
 
5.3%
Other values (2) 6
7.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:49.909842image/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 row문흥1동
2nd row6,465
3rd row15,609
4th row27
5th row9
ValueCountFrequency (%)
0 5
 
15.2%
9 3
 
9.1%
40 2
 
6.1%
64 1
 
3.0%
146 1
 
3.0%
15,534 1
 
3.0%
6,442 1
 
3.0%
8 1
 
3.0%
75 1
 
3.0%
23 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:38:50.712419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
13.5%
4 9
12.2%
5 9
12.2%
0 8
10.8%
2 7
9.5%
6 6
8.1%
9 5
6.8%
3 4
 
5.4%
, 4
 
5.4%
8 4
 
5.4%
Other values (5) 8
10.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 10
15.6%
4 9
14.1%
5 9
14.1%
0 8
12.5%
2 7
10.9%
6 6
9.4%
9 5
7.8%
3 4
 
6.2%
8 4
 
6.2%
7 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 10
14.1%
4 9
12.7%
5 9
12.7%
0 8
11.3%
2 7
9.9%
6 6
8.5%
9 5
7.0%
3 4
 
5.6%
, 4
 
5.6%
8 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 (%)
1 10
14.1%
4 9
12.7%
5 9
12.7%
0 8
11.3%
2 7
9.9%
6 6
8.5%
9 5
7.0%
3 4
 
5.6%
, 4
 
5.6%
8 4
 
5.6%
Other values (2) 5
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:51.244946image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row문흥2동
2nd row7,386
3rd row15,451
4th row33
5th row4
ValueCountFrequency (%)
0 5
 
15.2%
4 3
 
9.1%
103 1
 
3.0%
87 1
 
3.0%
15,366 1
 
3.0%
7,381 1
 
3.0%
11 1
 
3.0%
85 1
 
3.0%
5 1
 
3.0%
12 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:38:52.191367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.6%
5 9
11.7%
0 8
10.4%
3 8
10.4%
2 7
9.1%
4 6
7.8%
7 5
6.5%
6 5
6.5%
, 4
 
5.2%
8 4
 
5.2%
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 12
17.9%
5 9
13.4%
0 8
11.9%
3 8
11.9%
2 7
10.4%
4 6
9.0%
7 5
7.5%
6 5
7.5%
8 4
 
6.0%
9 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.2%
5 9
12.2%
0 8
10.8%
3 8
10.8%
2 7
9.5%
4 6
8.1%
7 5
6.8%
6 5
6.8%
, 4
 
5.4%
8 4
 
5.4%
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 12
16.2%
5 9
12.2%
0 8
10.8%
3 8
10.8%
2 7
9.5%
4 6
8.1%
7 5
6.8%
6 5
6.8%
, 4
 
5.4%
8 4
 
5.4%
Other values (2) 6
8.1%
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
2024-02-10T09:38:52.630125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique16 ?
Unique (%)48.5%

Sample

1st row두암1동
2nd row4,011
3rd row7,624
4th row21
5th row8
ValueCountFrequency (%)
0 5
15.2%
15 3
 
9.1%
10 2
 
6.1%
22 2
 
6.1%
1 2
 
6.1%
8 2
 
6.1%
27 2
 
6.1%
26 1
 
3.0%
64 1
 
3.0%
41 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:38:53.638012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.2%
0 9
12.3%
2 9
12.3%
7 6
8.2%
4 6
8.2%
8 5
 
6.8%
5 4
 
5.5%
, 4
 
5.5%
6 4
 
5.5%
3 3
 
4.1%
Other values (5) 9
12.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
22.2%
0 9
14.3%
2 9
14.3%
7 6
9.5%
4 6
9.5%
8 5
 
7.9%
5 4
 
6.3%
6 4
 
6.3%
3 3
 
4.8%
9 3
 
4.8%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
20.0%
0 9
12.9%
2 9
12.9%
7 6
8.6%
4 6
8.6%
8 5
 
7.1%
5 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
3 3
 
4.3%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
20.0%
0 9
12.9%
2 9
12.9%
7 6
8.6%
4 6
8.6%
8 5
 
7.1%
5 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
3 3
 
4.3%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:54.374948image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row두암2동
2nd row7,685
3rd row15,734
4th row56
5th row9
ValueCountFrequency (%)
0 5
 
15.2%
9 3
 
9.1%
48 3
 
9.1%
5 1
 
3.0%
147 1
 
3.0%
7,670 1
 
3.0%
8 1
 
3.0%
47 1
 
3.0%
15 1
 
3.0%
12 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:38:55.617758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 10
13.2%
0 8
10.5%
7 8
10.5%
5 8
10.5%
8 7
9.2%
1 7
9.2%
6 6
7.9%
9 5
6.6%
2 4
 
5.3%
, 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 (%)
4 10
15.2%
0 8
12.1%
7 8
12.1%
5 8
12.1%
8 7
10.6%
1 7
10.6%
6 6
9.1%
9 5
7.6%
2 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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 10
13.7%
0 8
11.0%
7 8
11.0%
5 8
11.0%
8 7
9.6%
1 7
9.6%
6 6
8.2%
9 5
6.8%
2 4
 
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 (%)
4 10
13.7%
0 8
11.0%
7 8
11.0%
5 8
11.0%
8 7
9.6%
1 7
9.6%
6 6
8.2%
9 5
6.8%
2 4
 
5.5%
, 4
 
5.5%
Other values (2) 6
8.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 25
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:38:56.085056image/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 row두암3동
2nd row7,734
3rd row13,002
4th row46
5th row8
ValueCountFrequency (%)
0 5
 
15.2%
1 2
 
6.1%
8 2
 
6.1%
129 1
 
3.0%
61 1
 
3.0%
12,950 1
 
3.0%
7,703 1
 
3.0%
22 1
 
3.0%
52 1
 
3.0%
31 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:38:57.579279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.1%
1 11
14.1%
3 9
11.5%
2 9
11.5%
4 7
9.0%
6 5
6.4%
7 5
6.4%
5 5
6.4%
, 4
 
5.1%
8 3
 
3.8%
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 11
16.2%
1 11
16.2%
3 9
13.2%
2 9
13.2%
4 7
10.3%
6 5
7.4%
7 5
7.4%
5 5
7.4%
8 3
 
4.4%
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 11
14.7%
1 11
14.7%
3 9
12.0%
2 9
12.0%
4 7
9.3%
6 5
6.7%
7 5
6.7%
5 5
6.7%
, 4
 
5.3%
8 3
 
4.0%
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 11
14.7%
1 11
14.7%
3 9
12.0%
2 9
12.0%
4 7
9.3%
6 5
6.7%
7 5
6.7%
5 5
6.7%
, 4
 
5.3%
8 3
 
4.0%
Other values (2) 6
8.0%
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
2024-02-10T09:38:57.962813image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row삼각동
2nd row6,054
3rd row13,801
4th row30
5th row4
ValueCountFrequency (%)
0 6
18.2%
9 3
 
9.1%
40 2
 
6.1%
58 2
 
6.1%
4 2
 
6.1%
35 1
 
3.0%
121 1
 
3.0%
43 1
 
3.0%
13,792 1
 
3.0%
6,056 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:38:58.920264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.3%
5 8
11.3%
1 8
11.3%
4 6
8.5%
6 6
8.5%
3 6
8.5%
8 5
 
7.0%
2 5
 
7.0%
9 4
 
5.6%
, 4
 
5.6%
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 (%)
0 13
21.0%
5 8
12.9%
1 8
12.9%
4 6
9.7%
6 6
9.7%
3 6
9.7%
8 5
 
8.1%
2 5
 
8.1%
9 4
 
6.5%
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 (%)
0 13
19.1%
5 8
11.8%
1 8
11.8%
4 6
8.8%
6 6
8.8%
3 6
8.8%
8 5
 
7.4%
2 5
 
7.4%
9 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 (%)
0 13
19.1%
5 8
11.8%
1 8
11.8%
4 6
8.8%
6 6
8.8%
3 6
8.8%
8 5
 
7.4%
2 5
 
7.4%
9 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
2024-02-10T09:38:59.314394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique23 ?
Unique (%)69.7%

Sample

1st row일곡동
2nd row11,541
3rd row29,201
4th row33
5th row12
ValueCountFrequency (%)
0 5
 
15.2%
12 3
 
9.1%
71 2
 
6.1%
73 1
 
3.0%
105 1
 
3.0%
29,119 1
 
3.0%
11,533 1
 
3.0%
9 1
 
3.0%
82 1
 
3.0%
8 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:39:00.260103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
26.8%
2 10
12.2%
0 8
 
9.8%
3 7
 
8.5%
7 6
 
7.3%
5 5
 
6.1%
, 4
 
4.9%
4 4
 
4.9%
9 4
 
4.9%
8 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 22
30.6%
2 10
13.9%
0 8
 
11.1%
3 7
 
9.7%
7 6
 
8.3%
5 5
 
6.9%
4 4
 
5.6%
9 4
 
5.6%
8 4
 
5.6%
6 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 22
27.8%
2 10
12.7%
0 8
 
10.1%
3 7
 
8.9%
7 6
 
7.6%
5 5
 
6.3%
, 4
 
5.1%
4 4
 
5.1%
9 4
 
5.1%
8 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 22
27.8%
2 10
12.7%
0 8
 
10.1%
3 7
 
8.9%
7 6
 
7.6%
5 5
 
6.3%
, 4
 
5.1%
4 4
 
5.1%
9 4
 
5.1%
8 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 28
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:00.785158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row매곡동
2nd row5,503
3rd row13,678
4th row22
5th row5
ValueCountFrequency (%)
0 6
18.2%
5 3
 
9.1%
27 2
 
6.1%
11 2
 
6.1%
31 1
 
3.0%
13,645 1
 
3.0%
5,495 1
 
3.0%
33 1
 
3.0%
8 1
 
3.0%
10 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:39:01.704687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 10
13.7%
3 10
13.7%
0 9
12.3%
1 9
12.3%
7 6
8.2%
2 5
6.8%
4 4
 
5.5%
, 4
 
5.5%
6 4
 
5.5%
9 4
 
5.5%
Other values (5) 8
11.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 10
15.9%
3 10
15.9%
0 9
14.3%
1 9
14.3%
7 6
9.5%
2 5
7.9%
4 4
 
6.3%
6 4
 
6.3%
9 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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
5 10
14.3%
3 10
14.3%
0 9
12.9%
1 9
12.9%
7 6
8.6%
2 5
7.1%
4 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
9 4
 
5.7%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 10
14.3%
3 10
14.3%
0 9
12.9%
1 9
12.9%
7 6
8.6%
2 5
7.1%
4 4
 
5.7%
, 4
 
5.7%
6 4
 
5.7%
9 4
 
5.7%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 29
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:02.146600image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row오치1동
2nd row5,477
3rd row10,616
4th row40
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
57 2
 
6.1%
16 2
 
6.1%
61 1
 
3.0%
24 1
 
3.0%
10,577 1
 
3.0%
5,462 1
 
3.0%
39 1
 
3.0%
15 1
 
3.0%
5 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:39:03.234405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.6%
0 11
14.3%
6 9
11.7%
5 8
10.4%
7 7
9.1%
2 7
9.1%
4 6
7.8%
, 4
 
5.2%
9 3
 
3.9%
- 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 (%)
1 12
17.9%
0 11
16.4%
6 9
13.4%
5 8
11.9%
7 7
10.4%
2 7
10.4%
4 6
9.0%
9 3
 
4.5%
8 2
 
3.0%
3 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 (%)
1 12
16.2%
0 11
14.9%
6 9
12.2%
5 8
10.8%
7 7
9.5%
2 7
9.5%
4 6
8.1%
, 4
 
5.4%
9 3
 
4.1%
- 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 (%)
1 12
16.2%
0 11
14.9%
6 9
12.2%
5 8
10.8%
7 7
9.5%
2 7
9.5%
4 6
8.1%
, 4
 
5.4%
9 3
 
4.1%
- 3
 
4.1%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 30
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:03.642568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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 row오치2동
2nd row6,962
3rd row12,219
4th row40
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
10 2
 
6.1%
54 2
 
6.1%
12 2
 
6.1%
40 2
 
6.1%
29 1
 
3.0%
74 1
 
3.0%
12,173 1
 
3.0%
6,942 1
 
3.0%
46 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:39:04.442887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.0%
2 13
16.5%
0 10
12.7%
4 9
11.4%
9 7
8.9%
6 5
 
6.3%
, 4
 
5.1%
7 4
 
5.1%
3 3
 
3.8%
- 3
 
3.8%
Other values (5) 6
 
7.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.7%
2 13
18.8%
0 10
14.5%
4 9
13.0%
9 7
10.1%
6 5
 
7.2%
7 4
 
5.8%
3 3
 
4.3%
5 2
 
2.9%
8 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.7%
2 13
17.1%
0 10
13.2%
4 9
11.8%
9 7
9.2%
6 5
 
6.6%
, 4
 
5.3%
7 4
 
5.3%
3 3
 
3.9%
- 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.7%
2 13
17.1%
0 10
13.2%
4 9
11.8%
9 7
9.2%
6 5
 
6.6%
, 4
 
5.3%
7 4
 
5.3%
3 3
 
3.9%
- 3
 
3.9%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 31
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:04.837877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.969697
Min length1

Characters and Unicode

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

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row석곡동
2nd row1,379
3rd row2,478
4th row22
5th row3
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
12 2
 
6.1%
3 2
 
6.1%
8 2
 
6.1%
5 2
 
6.1%
14 1
 
3.0%
1,360 1
 
3.0%
34 1
 
3.0%
19 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:39:05.818176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.9%
1 11
16.9%
2 8
12.3%
4 7
10.8%
3 6
9.2%
, 4
 
6.2%
8 3
 
4.6%
7 3
 
4.6%
9 3
 
4.6%
- 3
 
4.6%
Other values (5) 6
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
84.6%
Other Punctuation 4
 
6.2%
Dash Punctuation 3
 
4.6%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
20.0%
1 11
20.0%
2 8
14.5%
4 7
12.7%
3 6
10.9%
8 3
 
5.5%
7 3
 
5.5%
9 3
 
5.5%
5 2
 
3.6%
6 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.7%
1 11
17.7%
2 8
12.9%
4 7
11.3%
3 6
9.7%
, 4
 
6.5%
8 3
 
4.8%
7 3
 
4.8%
9 3
 
4.8%
- 3
 
4.8%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.7%
1 11
17.7%
2 8
12.9%
4 7
11.3%
3 6
9.7%
, 4
 
6.5%
8 3
 
4.8%
7 3
 
4.8%
9 3
 
4.8%
- 3
 
4.8%
Other values (2) 3
 
4.8%
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
2024-02-10T09:39:06.289380image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row건국동
2nd row9,085
3rd row21,932
4th row61
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
9 3
 
9.1%
11 2
 
6.1%
88 1
 
3.0%
90 1
 
3.0%
21,889 1
 
3.0%
9,070 1
 
3.0%
43 1
 
3.0%
15 1
 
3.0%
12 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:39:07.279469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
15.6%
0 11
14.3%
9 8
10.4%
8 7
9.1%
5 6
7.8%
2 6
7.8%
4 6
7.8%
7 5
6.5%
, 4
 
5.2%
3 4
 
5.2%
Other values (5) 8
10.4%

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 12
17.9%
0 11
16.4%
9 8
11.9%
8 7
10.4%
5 6
9.0%
2 6
9.0%
4 6
9.0%
7 5
7.5%
3 4
 
6.0%
6 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
16.2%
0 11
14.9%
9 8
10.8%
8 7
9.5%
5 6
8.1%
2 6
8.1%
4 6
8.1%
7 5
6.8%
, 4
 
5.4%
3 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 (%)
1 12
16.2%
0 11
14.9%
9 8
10.8%
8 7
9.5%
5 6
8.1%
2 6
8.1%
4 6
8.1%
7 5
6.8%
, 4
 
5.4%
3 4
 
5.4%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 33
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:07.622759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6666667
Min length1

Characters and Unicode

Total characters88
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row양산동
2nd row16,340
3rd row37,226
4th row64
5th row17
ValueCountFrequency (%)
0 5
 
15.2%
17 2
 
6.1%
217 1
 
3.0%
37,141 1
 
3.0%
16,337 1
 
3.0%
2 1
 
3.0%
85 1
 
3.0%
3 1
 
3.0%
11 1
 
3.0%
10 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T09:39:08.394633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 20
22.7%
0 10
11.4%
7 9
10.2%
2 8
 
9.1%
3 7
 
8.0%
8 7
 
8.0%
6 7
 
8.0%
, 4
 
4.5%
4 4
 
4.5%
5 3
 
3.4%
Other values (5) 9
10.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
88.6%
Other Punctuation 4
 
4.5%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 20
25.6%
0 10
12.8%
7 9
11.5%
2 8
 
10.3%
3 7
 
9.0%
8 7
 
9.0%
6 7
 
9.0%
4 4
 
5.1%
5 3
 
3.8%
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 (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 20
23.5%
0 10
11.8%
7 9
10.6%
2 8
 
9.4%
3 7
 
8.2%
8 7
 
8.2%
6 7
 
8.2%
, 4
 
4.7%
4 4
 
4.7%
5 3
 
3.5%
Other values (2) 6
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 20
23.5%
0 10
11.8%
7 9
10.6%
2 8
 
9.4%
3 7
 
8.2%
8 7
 
8.2%
6 7
 
8.2%
, 4
 
4.7%
4 4
 
4.7%
5 3
 
3.5%
Other values (2) 6
 
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 34
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:39:08.738879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row신용동
2nd row11,829
3rd row29,463
4th row9
5th row9
ValueCountFrequency (%)
0 6
18.2%
9 5
 
15.2%
1 2
 
6.1%
26 1
 
3.0%
11,836 1
 
3.0%
48 1
 
3.0%
7 1
 
3.0%
79 1
 
3.0%
102 1
 
3.0%
56 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:39:09.336538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.3%
9 10
13.3%
0 9
12.0%
2 9
12.0%
6 6
8.0%
7 5
 
6.7%
5 5
 
6.7%
, 4
 
5.3%
8 4
 
5.3%
4 3
 
4.0%
Other values (5) 7
9.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.4%
9 10
14.9%
0 9
13.4%
2 9
13.4%
6 6
9.0%
7 5
 
7.5%
5 5
 
7.5%
8 4
 
6.0%
4 3
 
4.5%
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 (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.1%
9 10
13.9%
0 9
12.5%
2 9
12.5%
6 6
8.3%
7 5
 
6.9%
5 5
 
6.9%
, 4
 
5.6%
8 4
 
5.6%
4 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 13
18.1%
9 10
13.9%
0 9
12.5%
2 9
12.5%
6 6
8.3%
7 5
 
6.9%
5 5
 
6.9%
, 4
 
5.6%
8 4
 
5.6%
4 3
 
4.2%
Other values (2) 4
 
5.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24Unnamed: 25Unnamed: 26Unnamed: 27Unnamed: 28Unnamed: 29Unnamed: 30Unnamed: 31Unnamed: 32Unnamed: 33Unnamed: 34
0<NA>행정기관 :<NA>광주광역시 북구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.10.11<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>2022.09 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>197,5562,9744,4633,6262,3894,5747,248<NA>17,8827,4666,0805,4239,9185,6032,7719,6886,4657,3864,0117,6857,7346,05411,5415,5035,4776,9621,3799,08516,34011,829
4<NA>전월말인구수<NA><NA><NA>424,7154,6748,5486,5794,0459,12512,353<NA>37,98619,09911,68813,31723,03210,1025,60720,52615,60915,4517,62415,73413,00213,80129,20113,67810,61612,2192,47821,93237,22629,463
5<NA>전월말거주불명자수<NA><NA><NA>1,268536252503686<NA>12327563053622252273321564630332240402261649
6<NA>전월말재외국민등록자수<NA><NA><NA>220063451<NA>2018815872894898412581039179
7<NA>증 가 요 인전 입<NA>3,7255012510054140263<NA>373133106142181211641428111964114112121142751029710145287172
8<NA><NA><NA>남자<NA>1,9323159562670143<NA>2086155668711228774159276065637139455487216980
9<NA><NA><NA>여자<NA>1,7931966442870120<NA>165725176949936654060375447587136574327311892
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>41415381426920<NA>4110093018821912109219121016111212111
26<NA><NA>국외<NA><NA>0000000<NA>0000000000000000000000
27<NA><NA>기타<NA><NA>5000000<NA>0000032000000000000000
28<NA>세대수증감<NA><NA><NA>-215-19-195-353780<NA>-9-21-127-3316-18-26-23-5-15-15-312-8-8-15-20-19-15-37
29<NA>인구수증감<NA><NA><NA>-972-30-110-4412101<NA>-79-35-590-9087-33-87-75-85-26-47-52-9-82-33-39-46-34-43-85-48
30<NA>거주불명자수증감<NA><NA><NA>-408-15-38-15-27-10-24<NA>-43-100-9-28-18-8-21-8-11-11-8-22-9-9-11-16-12-12-11-20
31<NA>금월말세대수<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
32<NA>금월말인구수<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
33<NA>금월말거주불명자수<NA><NA><NA>860382437232662<NA>8017562125441431192210482421241124281050629
34<NA>금월말재외국민등록자수<NA><NA><NA>223063552<NA>2018915772894898412591039179

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