Overview

Dataset statistics

Number of variables25
Number of observations35
Missing cells203
Missing cells (%)23.2%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory7.0 KiB
Average record size in memory204.8 B

Variable types

Unsupported1
Text23
DateTime1

Dataset

Description2022-12-16
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201928

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: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 07:10:37.776205
Analysis finished2024-02-10 07:10:38.849096
Duration1.07 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing35
Missing (%)100.0%
Memory size447.0 B
Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T07:10:39.058500image/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%
2024-02-10T07:10:40.194522image/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
2024-02-10T07:10:40.728921image/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%
2024-02-10T07:10:42.066696image/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
2024-02-10T07:10:43.035395image/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 서구
2nd row2022.11 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%
서구 1
7.1%
2022.11 1
7.1%
현재 1
7.1%
2024-02-10T07:10:44.553516image/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%
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%
1 2
33.3%
0 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%
1 2
20.0%
0 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%
1 2
20.0%
0 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:10:45.014852image/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%
2024-02-10T07:10:46.054340image/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
2024-02-10T07:10:46.631124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.6969697
Min length1

Characters and Unicode

Total characters122
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row합 계
2nd row133,602
3rd row287,720
4th row652
5th row147
ValueCountFrequency (%)
0 4
 
11.8%
1,049 2
 
5.9%
3,178 1
 
2.9%
666 1
 
2.9%
287,607 1
 
2.9%
133,548 1
 
2.9%
14 1
 
2.9%
113 1
 
2.9%
54 1
 
2.9%
3 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T07:10:47.524399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
18.0%
, 14
11.5%
0 12
9.8%
6 11
9.0%
4 10
8.2%
2 9
7.4%
3 9
7.4%
8 9
7.4%
7 8
 
6.6%
5 8
 
6.6%
Other values (5) 10
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
83.6%
Other Punctuation 14
 
11.5%
Space Separator 2
 
1.6%
Dash Punctuation 2
 
1.6%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
21.6%
0 12
11.8%
6 11
10.8%
4 10
9.8%
2 9
8.8%
3 9
8.8%
8 9
8.8%
7 8
 
7.8%
5 8
 
7.8%
9 4
 
3.9%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 120
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
18.3%
, 14
11.7%
0 12
10.0%
6 11
9.2%
4 10
8.3%
2 9
7.5%
3 9
7.5%
8 9
7.5%
7 8
 
6.7%
5 8
 
6.7%
Other values (3) 8
 
6.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 120
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
18.3%
, 14
11.7%
0 12
10.0%
6 11
9.2%
4 10
8.3%
2 9
7.5%
3 9
7.5%
8 9
7.5%
7 8
 
6.7%
5 8
 
6.7%
Other values (3) 8
 
6.7%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:10:48.043202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
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 row양동
2nd row2,010
3rd row3,479
4th row16
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 5
15.2%
16 2
 
6.1%
21 2
 
6.1%
46 1
 
3.0%
20 1
 
3.0%
1,989 1
 
3.0%
28 1
 
3.0%
6 1
 
3.0%
9 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:10:48.880756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
18.5%
1 12
18.5%
3 8
12.3%
2 7
10.8%
6 5
7.7%
, 4
 
6.2%
4 4
 
6.2%
9 4
 
6.2%
5 2
 
3.1%
- 2
 
3.1%
Other values (4) 5
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
87.7%
Other Punctuation 4
 
6.2%
Dash Punctuation 2
 
3.1%
Other Letter 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
21.1%
1 12
21.1%
3 8
14.0%
2 7
12.3%
6 5
8.8%
4 4
 
7.0%
9 4
 
7.0%
5 2
 
3.5%
8 2
 
3.5%
7 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
19.0%
1 12
19.0%
3 8
12.7%
2 7
11.1%
6 5
7.9%
, 4
 
6.3%
4 4
 
6.3%
9 4
 
6.3%
5 2
 
3.2%
- 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
19.0%
1 12
19.0%
3 8
12.7%
2 7
11.1%
6 5
7.9%
, 4
 
6.3%
4 4
 
6.3%
9 4
 
6.3%
5 2
 
3.2%
- 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 7
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:10:49.249507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row양3동
2nd row2,169
3rd row4,461
4th row31
5th row1
ValueCountFrequency (%)
0 8
24.2%
1 3
 
9.1%
31 2
 
6.1%
20 2
 
6.1%
7 1
 
3.0%
26 1
 
3.0%
2,158 1
 
3.0%
22 1
 
3.0%
11 1
 
3.0%
6 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:10:50.386708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
19.4%
0 10
14.9%
2 9
13.4%
3 5
 
7.5%
4 5
 
7.5%
9 5
 
7.5%
5 4
 
6.0%
, 4
 
6.0%
6 4
 
6.0%
7 2
 
3.0%
Other values (4) 6
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
88.1%
Other Punctuation 4
 
6.0%
Dash Punctuation 2
 
3.0%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
22.0%
0 10
16.9%
2 9
15.3%
3 5
 
8.5%
4 5
 
8.5%
9 5
 
8.5%
5 4
 
6.8%
6 4
 
6.8%
7 2
 
3.4%
8 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 65
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
20.0%
0 10
15.4%
2 9
13.8%
3 5
 
7.7%
4 5
 
7.7%
9 5
 
7.7%
5 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
7 2
 
3.1%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 65
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
20.0%
0 10
15.4%
2 9
13.8%
3 5
 
7.7%
4 5
 
7.7%
9 5
 
7.7%
5 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
7 2
 
3.1%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:10:50.811839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories3 ?
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 row농성1동
2nd row6,334
3rd row11,117
4th row37
5th row4
ValueCountFrequency (%)
0 7
21.2%
79 2
 
6.1%
4 2
 
6.1%
38 2
 
6.1%
11,117 1
 
3.0%
37 1
 
3.0%
240 1
 
3.0%
6,373 1
 
3.0%
1 1
 
3.0%
64 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:10:51.692312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
21.3%
0 10
13.3%
3 9
12.0%
7 7
9.3%
9 7
9.3%
4 6
 
8.0%
5 4
 
5.3%
6 4
 
5.3%
, 4
 
5.3%
8 3
 
4.0%
Other values (4) 5
 
6.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
23.5%
0 10
14.7%
3 9
13.2%
7 7
10.3%
9 7
10.3%
4 6
 
8.8%
5 4
 
5.9%
6 4
 
5.9%
8 3
 
4.4%
2 2
 
2.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
22.2%
0 10
13.9%
3 9
12.5%
7 7
9.7%
9 7
9.7%
4 6
 
8.3%
5 4
 
5.6%
6 4
 
5.6%
, 4
 
5.6%
8 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 16
22.2%
0 10
13.9%
3 9
12.5%
7 7
9.7%
9 7
9.7%
4 6
 
8.3%
5 4
 
5.6%
6 4
 
5.6%
, 4
 
5.6%
8 3
 
4.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:10:52.144855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2
Min length1

Characters and Unicode

Total characters66
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

Unique15 ?
Unique (%)45.5%

Sample

1st row농성2동
2nd row2,902
3rd row4,697
4th row34
5th row0
ValueCountFrequency (%)
0 10
30.3%
34 4
 
12.1%
2 2
 
6.1%
32 2
 
6.1%
23 1
 
3.0%
66 1
 
3.0%
2,907 1
 
3.0%
5 1
 
3.0%
15 1
 
3.0%
28 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T07:10:53.291912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
18.2%
2 10
15.2%
3 8
12.1%
9 7
10.6%
4 6
9.1%
6 5
7.6%
1 4
 
6.1%
, 4
 
6.1%
5 3
 
4.5%
7 2
 
3.0%
Other values (4) 5
7.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
89.4%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.3%
2 10
16.9%
3 8
13.6%
9 7
11.9%
4 6
10.2%
6 5
8.5%
1 4
 
6.8%
5 3
 
5.1%
7 2
 
3.4%
8 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
19.0%
2 10
15.9%
3 8
12.7%
9 7
11.1%
4 6
9.5%
6 5
7.9%
1 4
 
6.3%
, 4
 
6.3%
5 3
 
4.8%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
19.0%
2 10
15.9%
3 8
12.7%
9 7
11.1%
4 6
9.5%
6 5
7.9%
1 4
 
6.3%
, 4
 
6.3%
5 3
 
4.8%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct24
Distinct (%)70.6%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:10:53.882320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2352941
Min length1

Characters and Unicode

Total characters76
Distinct characters21
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)58.8%

Sample

1st row출력일자 :
2nd row광천동
3rd row4,080
4th row7,681
5th row68
ValueCountFrequency (%)
0 8
22.9%
25 2
 
5.7%
68 2
 
5.7%
29 2
 
5.7%
47 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
97 1
 
2.9%
7,633 1
 
2.9%
4,063 1
 
2.9%
Other values (15) 15
42.9%
2024-02-10T07:10:55.064210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.1%
2 8
10.5%
4 6
7.9%
6 6
7.9%
8 6
7.9%
7 6
7.9%
1 5
 
6.6%
3 4
 
5.3%
, 4
 
5.3%
5 4
 
5.3%
Other values (11) 14
18.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
80.3%
Other Letter 7
 
9.2%
Other Punctuation 5
 
6.6%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.3%
2 8
13.1%
4 6
9.8%
6 6
9.8%
8 6
9.8%
7 6
9.8%
1 5
 
8.2%
3 4
 
6.6%
5 4
 
6.6%
9 3
 
4.9%
Other Letter
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 69
90.8%
Hangul 7
 
9.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.8%
2 8
11.6%
4 6
8.7%
6 6
8.7%
8 6
8.7%
7 6
8.7%
1 5
 
7.2%
3 4
 
5.8%
, 4
 
5.8%
5 4
 
5.8%
Other values (4) 7
10.1%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 69
90.8%
Hangul 7
 
9.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.8%
2 8
11.6%
4 6
8.7%
6 6
8.7%
8 6
8.7%
7 6
8.7%
1 5
 
7.2%
3 4
 
5.8%
, 4
 
5.8%
5 4
 
5.8%
Other values (4) 7
10.1%
Hangul
ValueCountFrequency (%)
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%
1
14.3%

Unnamed: 11
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:10:55.629858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row유덕동
2nd row4,849
3rd row10,693
4th row15
5th row4
ValueCountFrequency (%)
0 8
24.2%
15 2
 
6.1%
30 2
 
6.1%
28 1
 
3.0%
10,693 1
 
3.0%
48 1
 
3.0%
10,698 1
 
3.0%
4,851 1
 
3.0%
5 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:10:56.778061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
19.4%
4 9
13.4%
8 8
11.9%
3 7
10.4%
1 5
 
7.5%
2 5
 
7.5%
9 5
 
7.5%
5 4
 
6.0%
, 4
 
6.0%
6 4
 
6.0%
Other values (3) 3
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
89.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.7%
4 9
15.0%
8 8
13.3%
3 7
11.7%
1 5
 
8.3%
2 5
 
8.3%
9 5
 
8.3%
5 4
 
6.7%
6 4
 
6.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
20.3%
4 9
14.1%
8 8
12.5%
3 7
10.9%
1 5
 
7.8%
2 5
 
7.8%
9 5
 
7.8%
5 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
20.3%
4 9
14.1%
8 8
12.5%
3 7
10.9%
1 5
 
7.8%
2 5
 
7.8%
9 5
 
7.8%
5 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-12-01 00:00:00
Maximum2022-12-01 00:00:00
2024-02-10T07:10:57.141220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:10:57.496983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:10:57.839099image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row치평동
2nd row13,577
3rd row29,594
4th row51
5th row15
ValueCountFrequency (%)
0 6
 
18.2%
16 2
 
6.1%
111 2
 
6.1%
1 2
 
6.1%
390 1
 
3.0%
29,473 1
 
3.0%
13,523 1
 
3.0%
121 1
 
3.0%
54 1
 
3.0%
118 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:10:58.709354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 27
30.3%
0 9
 
10.1%
5 9
 
10.1%
2 8
 
9.0%
3 7
 
7.9%
7 5
 
5.6%
4 5
 
5.6%
6 4
 
4.5%
, 4
 
4.5%
9 4
 
4.5%
Other values (5) 7
 
7.9%

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 27
33.8%
0 9
 
11.2%
5 9
 
11.2%
2 8
 
10.0%
3 7
 
8.8%
7 5
 
6.2%
4 5
 
6.2%
6 4
 
5.0%
9 4
 
5.0%
8 2
 
2.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 27
31.4%
0 9
 
10.5%
5 9
 
10.5%
2 8
 
9.3%
3 7
 
8.1%
7 5
 
5.8%
4 5
 
5.8%
6 4
 
4.7%
, 4
 
4.7%
9 4
 
4.7%
Other values (2) 4
 
4.7%
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 27
31.4%
0 9
 
10.5%
5 9
 
10.5%
2 8
 
9.3%
3 7
 
8.1%
7 5
 
5.8%
4 5
 
5.8%
6 4
 
4.7%
, 4
 
4.7%
9 4
 
4.7%
Other values (2) 4
 
4.7%
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
2024-02-10T07:10:59.034944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique24 ?
Unique (%)72.7%

Sample

1st row상무1동
2nd row12,261
3rd row24,449
4th row102
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
10 3
 
9.1%
1 2
 
6.1%
111 1
 
3.0%
102 1
 
3.0%
24,449 1
 
3.0%
24,439 1
 
3.0%
12,255 1
 
3.0%
11 1
 
3.0%
6 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:10:59.858368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
27.3%
2 12
13.6%
0 11
12.5%
9 7
 
8.0%
3 6
 
6.8%
6 5
 
5.7%
4 5
 
5.7%
5 4
 
4.5%
8 4
 
4.5%
, 4
 
4.5%
Other values (5) 6
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
89.8%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
30.4%
2 12
15.2%
0 11
13.9%
9 7
 
8.9%
3 6
 
7.6%
6 5
 
6.3%
4 5
 
6.3%
5 4
 
5.1%
8 4
 
5.1%
7 1
 
1.3%
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 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
28.2%
2 12
14.1%
0 11
12.9%
9 7
 
8.2%
3 6
 
7.1%
6 5
 
5.9%
4 5
 
5.9%
5 4
 
4.7%
8 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 85
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
28.2%
2 12
14.1%
0 11
12.9%
9 7
 
8.2%
3 6
 
7.1%
6 5
 
5.9%
4 5
 
5.9%
5 4
 
4.7%
8 4
 
4.7%
, 4
 
4.7%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:11:00.225559image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row상무2동
2nd row13,012
3rd row23,156
4th row87
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
141 1
 
3.0%
160 1
 
3.0%
23,133 1
 
3.0%
13,006 1
 
3.0%
3 1
 
3.0%
23 1
 
3.0%
6 1
 
3.0%
1 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:11:01.163926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.7%
0 13
15.7%
3 10
12.0%
2 10
12.0%
8 7
 
8.4%
7 4
 
4.8%
, 4
 
4.8%
5 4
 
4.8%
6 4
 
4.8%
9 3
 
3.6%
Other values (5) 6
 
7.2%

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 18
24.3%
0 13
17.6%
3 10
13.5%
2 10
13.5%
8 7
 
9.5%
7 4
 
5.4%
5 4
 
5.4%
6 4
 
5.4%
9 3
 
4.1%
4 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
22.5%
0 13
16.2%
3 10
12.5%
2 10
12.5%
8 7
 
8.8%
7 4
 
5.0%
, 4
 
5.0%
5 4
 
5.0%
6 4
 
5.0%
9 3
 
3.8%
Other values (2) 3
 
3.8%
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 18
22.5%
0 13
16.2%
3 10
12.5%
2 10
12.5%
8 7
 
8.8%
7 4
 
5.0%
, 4
 
5.0%
5 4
 
5.0%
6 4
 
5.0%
9 3
 
3.8%
Other values (2) 3
 
3.8%
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
2024-02-10T07:11:01.527923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4848485
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row화정1동
2nd row8,525
3rd row15,334
4th row40
5th row8
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
15,334 1
 
3.0%
40 1
 
3.0%
15,410 1
 
3.0%
8,507 1
 
3.0%
3 1
 
3.0%
76 1
 
3.0%
18 1
 
3.0%
10 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:11:02.399399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.3%
0 12
14.6%
7 9
11.0%
3 9
11.0%
5 8
9.8%
8 5
 
6.1%
2 5
 
6.1%
6 4
 
4.9%
, 4
 
4.9%
4 4
 
4.9%
Other values (5) 7
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
89.0%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.5%
0 12
16.4%
7 9
12.3%
3 9
12.3%
5 8
11.0%
8 5
 
6.8%
2 5
 
6.8%
6 4
 
5.5%
4 4
 
5.5%
9 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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.0%
0 12
15.2%
7 9
11.4%
3 9
11.4%
5 8
10.1%
8 5
 
6.3%
2 5
 
6.3%
6 4
 
5.1%
, 4
 
5.1%
4 4
 
5.1%
Other values (2) 4
 
5.1%
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 15
19.0%
0 12
15.2%
7 9
11.4%
3 9
11.4%
5 8
10.1%
8 5
 
6.3%
2 5
 
6.3%
6 4
 
5.1%
, 4
 
5.1%
4 4
 
5.1%
Other values (2) 4
 
5.1%
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
2024-02-10T07:11:02.726126image/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 row화정2동
2nd row7,902
3rd row20,049
4th row22
5th row16
ValueCountFrequency (%)
0 6
 
18.2%
6 2
 
6.1%
16 2
 
6.1%
91 1
 
3.0%
22 1
 
3.0%
110 1
 
3.0%
19,959 1
 
3.0%
7,882 1
 
3.0%
1 1
 
3.0%
90 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:11:03.718000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
15.2%
1 10
12.7%
2 10
12.7%
9 9
11.4%
8 8
10.1%
6 7
8.9%
5 4
 
5.1%
, 4
 
5.1%
4 3
 
3.8%
3 3
 
3.8%
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 (%)
0 12
17.4%
1 10
14.5%
2 10
14.5%
9 9
13.0%
8 8
11.6%
6 7
10.1%
5 4
 
5.8%
4 3
 
4.3%
3 3
 
4.3%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
15.8%
1 10
13.2%
2 10
13.2%
9 9
11.8%
8 8
10.5%
6 7
9.2%
5 4
 
5.3%
, 4
 
5.3%
4 3
 
3.9%
3 3
 
3.9%
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 (%)
0 12
15.8%
1 10
13.2%
2 10
13.2%
9 9
11.8%
8 8
10.5%
6 7
9.2%
5 4
 
5.3%
, 4
 
5.3%
4 3
 
3.9%
3 3
 
3.9%
Other values (2) 6
7.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:11:04.178556image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row화정3동
2nd row4,546
3rd row9,666
4th row22
5th row11
ValueCountFrequency (%)
0 8
24.2%
22 2
 
6.1%
32 2
 
6.1%
11 2
 
6.1%
48 1
 
3.0%
9,666 1
 
3.0%
70 1
 
3.0%
4,514 1
 
3.0%
45 1
 
3.0%
8 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:11:05.266930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
15.1%
0 10
13.7%
2 9
12.3%
1 8
11.0%
4 7
9.6%
5 6
8.2%
6 6
8.2%
, 4
 
5.5%
9 3
 
4.1%
8 3
 
4.1%
Other values (5) 6
8.2%

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 (%)
3 11
17.2%
0 10
15.6%
2 9
14.1%
1 8
12.5%
4 7
10.9%
5 6
9.4%
6 6
9.4%
9 3
 
4.7%
8 3
 
4.7%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
15.7%
0 10
14.3%
2 9
12.9%
1 8
11.4%
4 7
10.0%
5 6
8.6%
6 6
8.6%
, 4
 
5.7%
9 3
 
4.3%
8 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 11
15.7%
0 10
14.3%
2 9
12.9%
1 8
11.4%
4 7
10.0%
5 6
8.6%
6 6
8.6%
, 4
 
5.7%
9 3
 
4.3%
8 3
 
4.3%
Other values (2) 3
 
4.3%
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
2024-02-10T07:11:05.669979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row화정4동
2nd row7,755
3rd row18,373
4th row22
5th row15
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
22 2
 
6.1%
5 1
 
3.0%
175 1
 
3.0%
7,876 1
 
3.0%
290 1
 
3.0%
121 1
 
3.0%
10 1
 
3.0%
48 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:11:06.767653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.1%
0 11
13.4%
2 10
12.2%
7 10
12.2%
5 8
9.8%
8 5
 
6.1%
4 5
 
6.1%
, 4
 
4.9%
3 4
 
4.9%
6 4
 
4.9%
Other values (4) 7
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
91.5%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
18.7%
0 11
14.7%
2 10
13.3%
7 10
13.3%
5 8
10.7%
8 5
 
6.7%
4 5
 
6.7%
3 4
 
5.3%
6 4
 
5.3%
9 4
 
5.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.7%
0 11
13.9%
2 10
12.7%
7 10
12.7%
5 8
10.1%
8 5
 
6.3%
4 5
 
6.3%
, 4
 
5.1%
3 4
 
5.1%
6 4
 
5.1%
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 14
17.7%
0 11
13.9%
2 10
12.7%
7 10
12.7%
5 8
10.1%
8 5
 
6.3%
4 5
 
6.3%
, 4
 
5.1%
3 4
 
5.1%
6 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:11:07.191762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row서창동
2nd row2,663
3rd row5,694
4th row10
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 2
 
6.1%
28 2
 
6.1%
10 2
 
6.1%
15 1
 
3.0%
27 1
 
3.0%
2,672 1
 
3.0%
1 1
 
3.0%
9 1
 
3.0%
6 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:11:08.283312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
16.9%
0 10
15.4%
1 9
13.8%
6 7
10.8%
5 6
9.2%
4 4
 
6.2%
, 4
 
6.2%
9 4
 
6.2%
7 3
 
4.6%
8 2
 
3.1%
Other values (4) 5
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
89.2%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
19.0%
0 10
17.2%
1 9
15.5%
6 7
12.1%
5 6
10.3%
4 4
 
6.9%
9 4
 
6.9%
7 3
 
5.2%
8 2
 
3.4%
3 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
17.7%
0 10
16.1%
1 9
14.5%
6 7
11.3%
5 6
9.7%
4 4
 
6.5%
, 4
 
6.5%
9 4
 
6.5%
7 3
 
4.8%
8 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
17.7%
0 10
16.1%
1 9
14.5%
6 7
11.3%
5 6
9.7%
4 4
 
6.5%
, 4
 
6.5%
9 4
 
6.5%
7 3
 
4.8%
8 2
 
3.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:11:08.666122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row금호1동
2nd row8,969
3rd row20,019
4th row13
5th row4
ValueCountFrequency (%)
0 8
24.2%
13 2
 
6.1%
4 2
 
6.1%
42 1
 
3.0%
20,019 1
 
3.0%
70 1
 
3.0%
20,012 1
 
3.0%
8,973 1
 
3.0%
7 1
 
3.0%
11 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:11:09.485661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
19.4%
1 11
15.3%
4 7
9.7%
3 7
9.7%
9 6
8.3%
2 5
 
6.9%
7 5
 
6.9%
5 5
 
6.9%
, 4
 
5.6%
6 2
 
2.8%
Other values (5) 6
8.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
21.9%
1 11
17.2%
4 7
10.9%
3 7
10.9%
9 6
9.4%
2 5
 
7.8%
7 5
 
7.8%
5 5
 
7.8%
6 2
 
3.1%
8 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.3%
1 11
15.9%
4 7
10.1%
3 7
10.1%
9 6
8.7%
2 5
 
7.2%
7 5
 
7.2%
5 5
 
7.2%
, 4
 
5.8%
6 2
 
2.9%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
20.3%
1 11
15.9%
4 7
10.1%
3 7
10.1%
9 6
8.7%
2 5
 
7.2%
7 5
 
7.2%
5 5
 
7.2%
, 4
 
5.8%
6 2
 
2.9%
Other values (2) 3
 
4.3%
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
2024-02-10T07:11:09.982410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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 row금호2동
2nd row10,494
3rd row27,610
4th row17
5th row7
ValueCountFrequency (%)
0 7
21.2%
56 2
 
6.1%
7 2
 
6.1%
9 1
 
3.0%
113 1
 
3.0%
27,562 1
 
3.0%
10,478 1
 
3.0%
2 1
 
3.0%
48 1
 
3.0%
16 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:11:10.945623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.3%
0 12
15.2%
7 8
10.1%
6 7
8.9%
5 6
 
7.6%
2 6
 
7.6%
8 5
 
6.3%
4 5
 
6.3%
, 4
 
5.1%
9 4
 
5.1%
Other values (5) 6
 
7.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.9%
0 12
17.1%
7 8
11.4%
6 7
10.0%
5 6
 
8.6%
2 6
 
8.6%
8 5
 
7.1%
4 5
 
7.1%
9 4
 
5.7%
3 1
 
1.4%
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 76
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.1%
0 12
15.8%
7 8
10.5%
6 7
9.2%
5 6
 
7.9%
2 6
 
7.9%
8 5
 
6.6%
4 5
 
6.6%
, 4
 
5.3%
9 4
 
5.3%
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 16
21.1%
0 12
15.8%
7 8
10.5%
6 7
9.2%
5 6
 
7.9%
2 6
 
7.9%
8 5
 
6.6%
4 5
 
6.6%
, 4
 
5.3%
9 4
 
5.3%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:11:11.424319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6363636
Min length1

Characters and Unicode

Total characters87
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row풍암동
2nd row15,179
3rd row35,778
4th row55
5th row22
ValueCountFrequency (%)
0 6
18.2%
22 2
 
6.1%
105 2
 
6.1%
1 2
 
6.1%
55 2
 
6.1%
114 1
 
3.0%
174 1
 
3.0%
15,147 1
 
3.0%
103 1
 
3.0%
32 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:11:12.266228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
19.5%
5 13
14.9%
0 10
11.5%
7 10
11.5%
3 8
9.2%
4 7
8.0%
2 6
 
6.9%
, 4
 
4.6%
8 3
 
3.4%
9 2
 
2.3%
Other values (5) 7
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
89.7%
Other Punctuation 4
 
4.6%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
21.8%
5 13
16.7%
0 10
12.8%
7 10
12.8%
3 8
10.3%
4 7
9.0%
2 6
 
7.7%
8 3
 
3.8%
9 2
 
2.6%
6 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 84
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
20.2%
5 13
15.5%
0 10
11.9%
7 10
11.9%
3 8
9.5%
4 7
8.3%
2 6
 
7.1%
, 4
 
4.8%
8 3
 
3.6%
9 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 84
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
20.2%
5 13
15.5%
0 10
11.9%
7 10
11.9%
3 8
9.5%
4 7
8.3%
2 6
 
7.1%
, 4
 
4.8%
8 3
 
3.6%
9 2
 
2.4%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:11:12.679050image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row동천동
2nd row6,375
3rd row15,870
4th row10
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 4
 
12.1%
10 2
 
6.1%
55 1
 
3.0%
109 1
 
3.0%
6,374 1
 
3.0%
6 1
 
3.0%
1 1
 
3.0%
37 1
 
3.0%
60 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:11:13.573418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
19.7%
5 12
16.9%
1 8
11.3%
6 6
8.5%
3 6
8.5%
, 4
 
5.6%
7 4
 
5.6%
8 4
 
5.6%
4 4
 
5.6%
2 2
 
2.8%
Other values (4) 7
9.9%

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 14
22.6%
5 12
19.4%
1 8
12.9%
6 6
9.7%
3 6
9.7%
7 4
 
6.5%
8 4
 
6.5%
4 4
 
6.5%
2 2
 
3.2%
9 2
 
3.2%
Other Letter
ValueCountFrequency (%)
2
66.7%
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 14
20.6%
5 12
17.6%
1 8
11.8%
6 6
8.8%
3 6
8.8%
, 4
 
5.9%
7 4
 
5.9%
8 4
 
5.9%
4 4
 
5.9%
2 2
 
2.9%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
20.6%
5 12
17.6%
1 8
11.8%
6 6
8.8%
3 6
8.8%
, 4
 
5.9%
7 4
 
5.9%
8 4
 
5.9%
4 4
 
5.9%
2 2
 
2.9%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
2
66.7%
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: 24
0<NA>행정기관 :<NA>광주광역시 서구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.12.01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.11 현재<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 계양동양3동농성1동농성2동광천동유덕동<NA>치평동상무1동상무2동화정1동화정2동화정3동화정4동서창동금호1동금호2동풍암동동천동
3<NA>전월말세대수<NA><NA><NA>133,6022,0102,1696,3342,9024,0804,849<NA>13,57712,26113,0128,5257,9024,5467,7552,6638,96910,49415,1796,375
4<NA>전월말인구수<NA><NA><NA>287,7203,4794,46111,1174,6977,68110,693<NA>29,59424,44923,15615,33420,0499,66618,3735,69420,01927,61035,77815,870
5<NA>전월말거주불명자수<NA><NA><NA>652163137346815<NA>5110287402222221013175510
6<NA>전월말재외국민등록자수<NA><NA><NA>1473140114<NA>151078161115447225
7<NA>증 가 요 인전 입<NA>3,1262139240695489<NA>2732922883331559346956142171239103
8<NA><NA><NA>남자<NA>1,5841119111352949<NA>132169150162865221728698613445
9<NA><NA><NA>여자<NA>1,5421020129342540<NA>141123138171694125228738510558
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: 24
25<NA><NA>말소<NA><NA>3010000<NA>001000000010
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000
28<NA>세대수증감<NA><NA><NA>-54-21-11395-172<NA>-54-6-6-18-20-3212194-16-32-1
29<NA>인구수증감<NA><NA><NA>-113-28-22642-485<NA>-121-10-2376-90-452901-7-48-103-6
30<NA>거주불명자수증감<NA><NA><NA>14001000<NA>1113-3-10000200
31<NA>금월말세대수<NA><NA><NA>133,5481,9892,1586,3732,9074,0634,851<NA>13,52312,25513,0068,5077,8824,5147,8762,6728,97310,47815,1476,374
32<NA>금월말인구수<NA><NA><NA>287,6073,4514,43911,1814,6997,63310,698<NA>29,47324,43923,13315,41019,9599,62118,6635,69520,01227,56235,67515,864
33<NA>금월말거주불명자수<NA><NA><NA>666163138346815<NA>5211390372122221013195510
34<NA>금월말재외국민등록자수<NA><NA><NA>1483140123<NA>161077161115457225

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: 24# duplicates
0<NA>기타<NA><NA>0000000<NA>0000000000002