Overview

Dataset statistics

Number of variables28
Number of observations35
Missing cells207
Missing cells (%)21.1%
Duplicate rows1
Duplicate rows (%)2.9%
Total size in memory7.8 KiB
Average record size in memory228.8 B

Variable types

Unsupported1
Text25
DateTime1
Categorical1

Dataset

Description2023-03-09
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201924

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: 27 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 06:55:31.064687
Analysis finished2024-02-10 06:55:32.720193
Duration1.66 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
2024-02-10T06:55:32.967641image/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%
2024-02-10T06:55:34.064994image/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
2024-02-10T06:55:34.596070image/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%
2024-02-10T06:55:35.462554image/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
2024-02-10T06:55:35.940299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.5
Min length1

Characters and Unicode

Total characters42
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 광산구
2nd row2023.02 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%
광산구 1
7.1%
2023.02 1
7.1%
현재 1
7.1%
2024-02-10T06:55:36.755148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5
11.9%
4
 
9.5%
4
 
9.5%
3
 
7.1%
3
 
7.1%
2 3
 
7.1%
2
 
4.8%
0 2
 
4.8%
2
 
4.8%
2
 
4.8%
Other values (10) 12
28.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 32
76.2%
Decimal Number 6
 
14.3%
Space Separator 3
 
7.1%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
5
15.6%
4
12.5%
4
12.5%
3
9.4%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
1
 
3.1%
Other values (5) 5
15.6%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
3 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 32
76.2%
Common 10
 
23.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
5
15.6%
4
12.5%
4
12.5%
3
9.4%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
1
 
3.1%
Other values (5) 5
15.6%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
. 1
 
10.0%
3 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 32
76.2%
ASCII 10
 
23.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
5
15.6%
4
12.5%
4
12.5%
3
9.4%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
2
 
6.2%
1
 
3.1%
Other values (5) 5
15.6%
ASCII
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
. 1
 
10.0%
3 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T06:55:37.101436image/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%
2024-02-10T06:55:37.756046image/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
2024-02-10T06:55:38.236641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.8484848
Min length1

Characters and Unicode

Total characters127
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 row170,795
3rd row400,228
4th row791
5th row139
ValueCountFrequency (%)
0 3
 
8.8%
74 2
 
5.9%
1,228 2
 
5.9%
1,213 1
 
2.9%
791 1
 
2.9%
139 1
 
2.9%
797 1
 
2.9%
399,669 1
 
2.9%
170,895 1
 
2.9%
6 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T06:55:39.196615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
15.0%
, 16
12.6%
0 14
11.0%
2 14
11.0%
9 13
10.2%
8 10
7.9%
7 8
6.3%
5 8
6.3%
3 7
 
5.5%
6 7
 
5.5%
Other values (5) 11
8.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 106
83.5%
Other Punctuation 16
 
12.6%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
17.9%
0 14
13.2%
2 14
13.2%
9 13
12.3%
8 10
9.4%
7 8
7.5%
5 8
7.5%
3 7
 
6.6%
6 7
 
6.6%
4 6
 
5.7%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 125
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
15.2%
, 16
12.8%
0 14
11.2%
2 14
11.2%
9 13
10.4%
8 10
8.0%
7 8
6.4%
5 8
6.4%
3 7
 
5.6%
6 7
 
5.6%
Other values (3) 9
7.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 125
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
15.2%
, 16
12.8%
0 14
11.2%
2 14
11.2%
9 13
10.4%
8 10
8.0%
7 8
6.4%
5 8
6.4%
3 7
 
5.6%
6 7
 
5.6%
Other values (3) 9
7.2%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:39.631018image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row송정1동
2nd row4,792
3rd row10,556
4th row45
5th row1
ValueCountFrequency (%)
0 8
24.2%
1 2
 
6.1%
46 2
 
6.1%
18 2
 
6.1%
45 2
 
6.1%
39 1
 
3.0%
67 1
 
3.0%
4,789 1
 
3.0%
3 1
 
3.0%
8 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:55:40.386177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.8%
4 10
13.7%
1 10
13.7%
5 6
8.2%
8 6
8.2%
6 5
 
6.8%
, 4
 
5.5%
7 4
 
5.5%
9 4
 
5.5%
3 4
 
5.5%
Other values (5) 7
9.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.3%
4 10
15.6%
1 10
15.6%
5 6
9.4%
8 6
9.4%
6 5
 
7.8%
7 4
 
6.2%
9 4
 
6.2%
3 4
 
6.2%
2 2
 
3.1%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.6%
4 10
14.3%
1 10
14.3%
5 6
8.6%
8 6
8.6%
6 5
 
7.1%
, 4
 
5.7%
7 4
 
5.7%
9 4
 
5.7%
3 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.6%
4 10
14.3%
1 10
14.3%
5 6
8.6%
8 6
8.6%
6 5
 
7.1%
, 4
 
5.7%
7 4
 
5.7%
9 4
 
5.7%
3 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:40.729917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1515152
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row송정2동
2nd row3,443
3rd row6,368
4th row58
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
3 3
 
9.1%
54 1
 
3.0%
59 1
 
3.0%
6,334 1
 
3.0%
3,440 1
 
3.0%
1 1
 
3.0%
34 1
 
3.0%
11 1
 
3.0%
36 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:55:41.700842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 15
21.1%
0 9
12.7%
4 8
11.3%
1 6
 
8.5%
2 6
 
8.5%
6 5
 
7.0%
8 5
 
7.0%
, 4
 
5.6%
7 4
 
5.6%
5 3
 
4.2%
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 (%)
3 15
24.2%
0 9
14.5%
4 8
12.9%
1 6
 
9.7%
2 6
 
9.7%
6 5
 
8.1%
8 5
 
8.1%
7 4
 
6.5%
5 3
 
4.8%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 15
22.1%
0 9
13.2%
4 8
11.8%
1 6
 
8.8%
2 6
 
8.8%
6 5
 
7.4%
8 5
 
7.4%
, 4
 
5.9%
7 4
 
5.9%
5 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 15
22.1%
0 9
13.2%
4 8
11.8%
1 6
 
8.8%
2 6
 
8.8%
6 5
 
7.4%
8 5
 
7.4%
, 4
 
5.9%
7 4
 
5.9%
5 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 8
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:42.047573image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row도산동
2nd row6,619
3rd row14,820
4th row20
5th row3
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
3 2
 
6.1%
96 1
 
3.0%
99 1
 
3.0%
14,792 1
 
3.0%
6,630 1
 
3.0%
28 1
 
3.0%
11 1
 
3.0%
2 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:55:42.783510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.2%
0 10
13.7%
9 8
11.0%
6 8
11.0%
2 6
8.2%
5 5
 
6.8%
8 5
 
6.8%
3 4
 
5.5%
, 4
 
5.5%
4 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 (%)
1 14
21.5%
0 10
15.4%
9 8
12.3%
6 8
12.3%
2 6
9.2%
5 5
 
7.7%
8 5
 
7.7%
3 4
 
6.2%
4 3
 
4.6%
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 (%)
- 1
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 10
14.3%
9 8
11.4%
6 8
11.4%
2 6
8.6%
5 5
 
7.1%
8 5
 
7.1%
3 4
 
5.7%
, 4
 
5.7%
4 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 (%)
1 14
20.0%
0 10
14.3%
9 8
11.4%
6 8
11.4%
2 6
8.6%
5 5
 
7.1%
8 5
 
7.1%
3 4
 
5.7%
, 4
 
5.7%
4 3
 
4.3%
Other values (2) 3
 
4.3%
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
2024-02-10T06:55:43.107046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
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

Unique14 ?
Unique (%)42.4%

Sample

1st row신흥동
2nd row2,010
3rd row4,413
4th row21
5th row3
ValueCountFrequency (%)
0 9
27.3%
21 4
12.1%
3 2
 
6.1%
8 2
 
6.1%
15 2
 
6.1%
4,413 1
 
3.0%
47 1
 
3.0%
26 1
 
3.0%
10 1
 
3.0%
16 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T06:55:43.819289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.9%
0 13
20.3%
2 9
14.1%
4 6
9.4%
8 5
 
7.8%
3 4
 
6.2%
, 4
 
6.2%
5 2
 
3.1%
6 2
 
3.1%
9 1
 
1.6%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
89.1%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
24.6%
0 13
22.8%
2 9
15.8%
4 6
10.5%
8 5
 
8.8%
3 4
 
7.0%
5 2
 
3.5%
6 2
 
3.5%
9 1
 
1.8%
7 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61
95.3%
Hangul 3
 
4.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
23.0%
0 13
21.3%
2 9
14.8%
4 6
9.8%
8 5
 
8.2%
3 4
 
6.6%
, 4
 
6.6%
5 2
 
3.3%
6 2
 
3.3%
9 1
 
1.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
95.3%
Hangul 3
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
23.0%
0 13
21.3%
2 9
14.8%
4 6
9.8%
8 5
 
8.2%
3 4
 
6.6%
, 4
 
6.6%
5 2
 
3.3%
6 2
 
3.3%
9 1
 
1.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct29
Distinct (%)85.3%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T06:55:44.161831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6470588
Min length1

Characters and Unicode

Total characters90
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

Unique27 ?
Unique (%)79.4%

Sample

1st row출력일자 :
2nd row어룡동
3rd row14,302
4th row33,277
5th row34
ValueCountFrequency (%)
0 5
 
14.3%
169 2
 
5.7%
7 2
 
5.7%
1 2
 
5.7%
출력일자 1
 
2.9%
354 1
 
2.9%
33 1
 
2.9%
33,270 1
 
2.9%
14,315 1
 
2.9%
13 1
 
2.9%
Other values (18) 18
51.4%
2024-02-10T06:55:45.006509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
18.9%
3 13
14.4%
0 10
11.1%
7 8
8.9%
4 7
7.8%
2 6
 
6.7%
, 4
 
4.4%
9 4
 
4.4%
6 4
 
4.4%
5 4
 
4.4%
Other values (11) 13
14.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
83.3%
Other Letter 7
 
7.8%
Other Punctuation 5
 
5.6%
Dash Punctuation 2
 
2.2%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
22.7%
3 13
17.3%
0 10
13.3%
7 8
10.7%
4 7
9.3%
2 6
 
8.0%
9 4
 
5.3%
6 4
 
5.3%
5 4
 
5.3%
8 2
 
2.7%
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 83
92.2%
Hangul 7
 
7.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
20.5%
3 13
15.7%
0 10
12.0%
7 8
9.6%
4 7
8.4%
2 6
 
7.2%
, 4
 
4.8%
9 4
 
4.8%
6 4
 
4.8%
5 4
 
4.8%
Other values (4) 6
 
7.2%
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 83
92.2%
Hangul 7
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
20.5%
3 13
15.7%
0 10
12.0%
7 8
9.6%
4 7
8.4%
2 6
 
7.2%
, 4
 
4.8%
9 4
 
4.8%
6 4
 
4.8%
5 4
 
4.8%
Other values (4) 6
 
7.2%
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 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:45.329370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5757576
Min length1

Characters and Unicode

Total characters85
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 row우산동
2nd row15,033
3rd row29,499
4th row93
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
91 2
 
6.1%
7 2
 
6.1%
177 1
 
3.0%
351 1
 
3.0%
29,408 1
 
3.0%
14,990 1
 
3.0%
4 1
 
3.0%
43 1
 
3.0%
12 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:55:46.073431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
17.6%
0 12
14.1%
9 11
12.9%
2 9
10.6%
3 7
8.2%
4 7
8.2%
7 5
 
5.9%
5 4
 
4.7%
, 4
 
4.7%
8 3
 
3.5%
Other values (5) 8
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
88.2%
Other Punctuation 4
 
4.7%
Dash Punctuation 3
 
3.5%
Other Letter 3
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.0%
0 12
16.0%
9 11
14.7%
2 9
12.0%
3 7
9.3%
4 7
9.3%
7 5
 
6.7%
5 4
 
5.3%
8 3
 
4.0%
6 2
 
2.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
18.3%
0 12
14.6%
9 11
13.4%
2 9
11.0%
3 7
8.5%
4 7
8.5%
7 5
 
6.1%
5 4
 
4.9%
, 4
 
4.9%
8 3
 
3.7%
Other values (2) 5
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
18.3%
0 12
14.6%
9 11
13.4%
2 9
11.0%
3 7
8.5%
4 7
8.5%
7 5
 
6.1%
5 4
 
4.9%
, 4
 
4.9%
8 3
 
3.7%
Other values (2) 5
 
6.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-03-04 00:00:00
Maximum2023-03-04 00:00:00
2024-02-10T06:55:46.553681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T06:55:46.887429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:47.179349image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row월곡1동
2nd row4,799
3rd row10,292
4th row48
5th row7
ValueCountFrequency (%)
0 7
21.2%
47 2
 
6.1%
7 2
 
6.1%
5 2
 
6.1%
56 1
 
3.0%
48 1
 
3.0%
91 1
 
3.0%
4,786 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:55:47.972092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.9%
7 9
12.2%
4 8
10.8%
1 8
10.8%
5 6
8.1%
2 6
8.1%
, 4
 
5.4%
9 4
 
5.4%
3 4
 
5.4%
8 4
 
5.4%
Other values (5) 10
13.5%

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 (%)
0 11
17.2%
7 9
14.1%
4 8
12.5%
1 8
12.5%
5 6
9.4%
2 6
9.4%
9 4
 
6.2%
3 4
 
6.2%
8 4
 
6.2%
6 4
 
6.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 14
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:48.308188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row월곡2동
2nd row6,409
3rd row14,931
4th row35
5th row6
ValueCountFrequency (%)
0 7
21.2%
74 2
 
6.1%
35 2
 
6.1%
6 2
 
6.1%
72 2
 
6.1%
146 1
 
3.0%
14,931 1
 
3.0%
6,361 1
 
3.0%
126 1
 
3.0%
48 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:55:49.374503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 11
14.7%
0 9
12.0%
6 8
10.7%
1 8
10.7%
9 7
9.3%
7 6
8.0%
3 6
8.0%
2 5
6.7%
5 4
 
5.3%
, 4
 
5.3%
Other values (5) 7
9.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 11
16.7%
0 9
13.6%
6 8
12.1%
1 8
12.1%
9 7
10.6%
7 6
9.1%
3 6
9.1%
2 5
7.6%
5 4
 
6.1%
8 2
 
3.0%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

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

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 15
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:49.874792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
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 row비아동
2nd row3,510
3rd row7,496
4th row25
5th row5
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
1 2
 
6.1%
52 1
 
3.0%
91 1
 
3.0%
26 1
 
3.0%
7,492 1
 
3.0%
3,514 1
 
3.0%
42 1
 
3.0%
20 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:55:51.293653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.6%
2 8
12.1%
3 7
10.6%
4 7
10.6%
1 6
9.1%
5 6
9.1%
9 6
9.1%
, 4
6.1%
6 4
6.1%
7 3
 
4.5%
Other values (5) 6
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
87.9%
Other Punctuation 4
 
6.1%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
15.5%
2 8
13.8%
3 7
12.1%
4 7
12.1%
1 6
10.3%
5 6
10.3%
9 6
10.3%
6 4
6.9%
7 3
 
5.2%
8 2
 
3.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
14.3%
2 8
12.7%
3 7
11.1%
4 7
11.1%
1 6
9.5%
5 6
9.5%
9 6
9.5%
, 4
6.3%
6 4
6.3%
7 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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 9
14.3%
2 8
12.7%
3 7
11.1%
4 7
11.1%
1 6
9.5%
5 6
9.5%
9 6
9.5%
, 4
6.3%
6 4
6.3%
7 3
 
4.8%
Other values (2) 3
 
4.8%
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
2024-02-10T06:55:52.134237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row첨단1동
2nd row10,674
3rd row27,154
4th row22
5th row14
ValueCountFrequency (%)
0 6
 
18.2%
141 2
 
6.1%
14 2
 
6.1%
59 1
 
3.0%
126 1
 
3.0%
27,178 1
 
3.0%
10,717 1
 
3.0%
3 1
 
3.0%
24 1
 
3.0%
43 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:55:53.521772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
21.7%
4 12
14.5%
2 12
14.5%
0 9
10.8%
7 7
 
8.4%
, 4
 
4.8%
6 4
 
4.8%
9 4
 
4.8%
8 4
 
4.8%
5 3
 
3.6%
Other values (4) 6
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
91.6%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
23.7%
4 12
15.8%
2 12
15.8%
0 9
11.8%
7 7
 
9.2%
6 4
 
5.3%
9 4
 
5.3%
8 4
 
5.3%
5 3
 
3.9%
3 3
 
3.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
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%
4 12
15.0%
2 12
15.0%
0 9
11.2%
7 7
 
8.8%
, 4
 
5.0%
6 4
 
5.0%
9 4
 
5.0%
8 4
 
5.0%
5 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%
4 12
15.0%
2 12
15.0%
0 9
11.2%
7 7
 
8.8%
, 4
 
5.0%
6 4
 
5.0%
9 4
 
5.0%
8 4
 
5.0%
5 3
 
3.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:53.881011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.7272727
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row첨단2동
2nd row18,669
3rd row42,482
4th row66
5th row23
ValueCountFrequency (%)
0 7
21.2%
261 2
 
6.1%
23 2
 
6.1%
649 1
 
3.0%
328 1
 
3.0%
42,365 1
 
3.0%
18,693 1
 
3.0%
2 1
 
3.0%
117 1
 
3.0%
24 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:55:54.772003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
17.8%
1 14
15.6%
6 10
11.1%
0 7
7.8%
3 7
7.8%
8 6
 
6.7%
4 6
 
6.7%
5 6
 
6.7%
7 5
 
5.6%
, 4
 
4.4%
Other values (5) 9
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
90.0%
Other Punctuation 4
 
4.4%
Other Letter 3
 
3.3%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16
19.8%
1 14
17.3%
6 10
12.3%
0 7
8.6%
3 7
8.6%
8 6
 
7.4%
4 6
 
7.4%
5 6
 
7.4%
7 5
 
6.2%
9 4
 
4.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 16
18.4%
1 14
16.1%
6 10
11.5%
0 7
8.0%
3 7
8.0%
8 6
 
6.9%
4 6
 
6.9%
5 6
 
6.9%
7 5
 
5.7%
, 4
 
4.6%
Other values (2) 6
 
6.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16
18.4%
1 14
16.1%
6 10
11.5%
0 7
8.0%
3 7
8.0%
8 6
 
6.9%
4 6
 
6.9%
5 6
 
6.9%
7 5
 
5.7%
, 4
 
4.6%
Other values (2) 6
 
6.9%
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
2024-02-10T06:55:55.093397image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row신가동
2nd row7,418
3rd row19,445
4th row51
5th row5
ValueCountFrequency (%)
0 7
21.2%
38 2
 
6.1%
81 2
 
6.1%
5 2
 
6.1%
7 2
 
6.1%
51 1
 
3.0%
156 1
 
3.0%
19,407 1
 
3.0%
7,425 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:55:55.903747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 9
12.5%
1 9
12.5%
5 9
12.5%
4 9
12.5%
0 8
11.1%
9 6
8.3%
8 5
6.9%
, 4
5.6%
3 3
 
4.2%
2 3
 
4.2%
Other values (5) 7
9.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 9
14.3%
1 9
14.3%
5 9
14.3%
4 9
14.3%
0 8
12.7%
9 6
9.5%
8 5
7.9%
3 3
 
4.8%
2 3
 
4.8%
6 2
 
3.2%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
7 9
13.0%
1 9
13.0%
5 9
13.0%
4 9
13.0%
0 8
11.6%
9 6
8.7%
8 5
7.2%
, 4
5.8%
3 3
 
4.3%
2 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 (%)
7 9
13.0%
1 9
13.0%
5 9
13.0%
4 9
13.0%
0 8
11.6%
9 6
8.7%
8 5
7.2%
, 4
5.8%
3 3
 
4.3%
2 3
 
4.3%
Other values (2) 4
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:56.240753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

Total characters82
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

Unique24 ?
Unique (%)72.7%

Sample

1st row운남동
2nd row12,236
3rd row30,013
4th row22
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
133 1
 
3.0%
29,932 1
 
3.0%
12,241 1
 
3.0%
1 1
 
3.0%
81 1
 
3.0%
5 1
 
3.0%
12 1
 
3.0%
134 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:55:56.966038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
23.2%
0 12
14.6%
2 11
13.4%
3 8
9.8%
9 6
 
7.3%
5 5
 
6.1%
8 4
 
4.9%
4 4
 
4.9%
, 4
 
4.9%
6 4
 
4.9%
Other values (4) 5
 
6.1%

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 19
26.0%
0 12
16.4%
2 11
15.1%
3 8
11.0%
9 6
 
8.2%
5 5
 
6.8%
8 4
 
5.5%
4 4
 
5.5%
6 4
 
5.5%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
24.1%
0 12
15.2%
2 11
13.9%
3 8
10.1%
9 6
 
7.6%
5 5
 
6.3%
8 4
 
5.1%
4 4
 
5.1%
, 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 19
24.1%
0 12
15.2%
2 11
13.9%
3 8
10.1%
9 6
 
7.6%
5 5
 
6.3%
8 4
 
5.1%
4 4
 
5.1%
, 4
 
5.1%
6 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 20
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:57.344969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.7272727
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row수완동
2nd row28,230
3rd row75,903
4th row116
5th row16
ValueCountFrequency (%)
0 5
 
15.2%
1 2
 
6.1%
16 2
 
6.1%
430 1
 
3.0%
116 1
 
3.0%
75,903 1
 
3.0%
75,834 1
 
3.0%
28,278 1
 
3.0%
2 1
 
3.0%
69 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:55:58.076216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
13.3%
2 11
12.2%
8 11
12.2%
3 10
11.1%
0 9
10.0%
6 7
7.8%
4 6
6.7%
5 6
6.7%
7 5
5.6%
9 5
5.6%
Other values (5) 8
8.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
91.1%
Other Punctuation 4
 
4.4%
Other Letter 3
 
3.3%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
14.6%
2 11
13.4%
8 11
13.4%
3 10
12.2%
0 9
11.0%
6 7
8.5%
4 6
7.3%
5 6
7.3%
7 5
6.1%
9 5
6.1%
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 87
96.7%
Hangul 3
 
3.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
13.8%
2 11
12.6%
8 11
12.6%
3 10
11.5%
0 9
10.3%
6 7
8.0%
4 6
6.9%
5 6
6.9%
7 5
5.7%
9 5
5.7%
Other values (2) 5
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
13.8%
2 11
12.6%
8 11
12.6%
3 10
11.5%
0 9
10.3%
6 7
8.0%
4 6
6.9%
5 6
6.9%
7 5
5.7%
9 5
5.7%
Other values (2) 5
5.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:58.401922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
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 row하남동
2nd row11,134
3rd row26,656
4th row41
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
41 2
 
6.1%
18 1
 
3.0%
355 1
 
3.0%
11,171 1
 
3.0%
49 1
 
3.0%
37 1
 
3.0%
10 1
 
3.0%
163 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:55:59.291067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
26.2%
0 12
14.3%
7 9
10.7%
4 7
 
8.3%
3 6
 
7.1%
5 6
 
7.1%
6 5
 
6.0%
8 5
 
6.0%
, 4
 
4.8%
2 4
 
4.8%
Other values (4) 4
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
91.7%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
28.6%
0 12
15.6%
7 9
11.7%
4 7
 
9.1%
3 6
 
7.8%
5 6
 
7.8%
6 5
 
6.5%
8 5
 
6.5%
2 4
 
5.2%
9 1
 
1.3%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 81
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
27.2%
0 12
14.8%
7 9
11.1%
4 7
 
8.6%
3 6
 
7.4%
5 6
 
7.4%
6 5
 
6.2%
8 5
 
6.2%
, 4
 
4.9%
2 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 81
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
27.2%
0 12
14.8%
7 9
11.1%
4 7
 
8.6%
3 6
 
7.4%
5 6
 
7.4%
6 5
 
6.2%
8 5
 
6.2%
, 4
 
4.9%
2 4
 
4.9%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:59.729400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.9090909
Min length1

Characters and Unicode

Total characters63
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row임곡동
2nd row1,247
3rd row2,052
4th row12
5th row2
ValueCountFrequency (%)
0 8
24.2%
4 2
 
6.1%
5 2
 
6.1%
2 2
 
6.1%
10 2
 
6.1%
11 2
 
6.1%
임곡동 1
 
3.0%
15 1
 
3.0%
12 1
 
3.0%
7 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T06:56:00.630936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
22.2%
0 12
19.0%
2 9
14.3%
4 5
 
7.9%
5 4
 
6.3%
, 4
 
6.3%
3 4
 
6.3%
7 2
 
3.2%
- 2
 
3.2%
9 2
 
3.2%
Other values (4) 5
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54
85.7%
Other Punctuation 4
 
6.3%
Other Letter 3
 
4.8%
Dash Punctuation 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
25.9%
0 12
22.2%
2 9
16.7%
4 5
 
9.3%
5 4
 
7.4%
3 4
 
7.4%
7 2
 
3.7%
9 2
 
3.7%
8 2
 
3.7%
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 60
95.2%
Hangul 3
 
4.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
23.3%
0 12
20.0%
2 9
15.0%
4 5
 
8.3%
5 4
 
6.7%
, 4
 
6.7%
3 4
 
6.7%
7 2
 
3.3%
- 2
 
3.3%
9 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 60
95.2%
Hangul 3
 
4.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
23.3%
0 12
20.0%
2 9
15.0%
4 5
 
8.3%
5 4
 
6.7%
, 4
 
6.7%
3 4
 
6.7%
7 2
 
3.3%
- 2
 
3.3%
9 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 23
Text

MISSING 

Distinct17
Distinct (%)51.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:56:00.938428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6363636
Min length1

Characters and Unicode

Total characters54
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)36.4%

Sample

1st row동곡동
2nd row1,000
3rd row1,752
4th row3
5th row4
ValueCountFrequency (%)
0 9
27.3%
3 5
15.2%
4 3
 
9.1%
15 2
 
6.1%
9 2
 
6.1%
7 1
 
3.0%
2 1
 
3.0%
995 1
 
3.0%
1 1
 
3.0%
10 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T06:56:01.890370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
24.1%
1 8
14.8%
3 6
11.1%
5 6
11.1%
9 5
 
9.3%
4 3
 
5.6%
, 3
 
5.6%
7 3
 
5.6%
2 2
 
3.7%
2
 
3.7%
Other values (3) 3
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 47
87.0%
Other Punctuation 3
 
5.6%
Other Letter 3
 
5.6%
Dash Punctuation 1
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
27.7%
1 8
17.0%
3 6
12.8%
5 6
12.8%
9 5
 
10.6%
4 3
 
6.4%
7 3
 
6.4%
2 2
 
4.3%
6 1
 
2.1%
Other Letter
ValueCountFrequency (%)
2
66.7%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 51
94.4%
Hangul 3
 
5.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
25.5%
1 8
15.7%
3 6
11.8%
5 6
11.8%
9 5
 
9.8%
4 3
 
5.9%
, 3
 
5.9%
7 3
 
5.9%
2 2
 
3.9%
6 1
 
2.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51
94.4%
Hangul 3
 
5.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
25.5%
1 8
15.7%
3 6
11.8%
5 6
11.8%
9 5
 
9.8%
4 3
 
5.9%
, 3
 
5.9%
7 3
 
5.9%
2 2
 
3.9%
6 1
 
2.0%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:56:02.234473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row평동
2nd row2,994
3rd row4,894
4th row12
5th row3
ValueCountFrequency (%)
0 7
21.2%
34 2
 
6.1%
8 2
 
6.1%
3 2
 
6.1%
14 1
 
3.0%
28 1
 
3.0%
4,902 1
 
3.0%
2,986 1
 
3.0%
1 1
 
3.0%
6 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:56:03.166520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.7%
4 10
15.2%
2 9
13.6%
3 7
10.6%
1 6
9.1%
9 5
7.6%
8 5
7.6%
, 4
 
6.1%
6 3
 
4.5%
- 2
 
3.0%
Other values (4) 4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
87.9%
Other Punctuation 4
 
6.1%
Dash Punctuation 2
 
3.0%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
19.0%
4 10
17.2%
2 9
15.5%
3 7
12.1%
1 6
10.3%
9 5
8.6%
8 5
8.6%
6 3
 
5.2%
7 1
 
1.7%
5 1
 
1.7%
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 64
97.0%
Hangul 2
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.2%
4 10
15.6%
2 9
14.1%
3 7
10.9%
1 6
9.4%
9 5
7.8%
8 5
7.8%
, 4
 
6.2%
6 3
 
4.7%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 64
97.0%
Hangul 2
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.2%
4 10
15.6%
2 9
14.1%
3 7
10.9%
1 6
9.4%
9 5
7.8%
8 5
7.8%
, 4
 
6.2%
6 3
 
4.7%
- 2
 
3.1%
Other values (2) 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 25
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:56:03.503564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.8181818
Min length1

Characters and Unicode

Total characters60
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row삼도동
2nd row1,322
3rd row2,154
4th row6
5th row0
ValueCountFrequency (%)
0 10
30.3%
8 3
 
9.1%
6 2
 
6.1%
10 2
 
6.1%
14 2
 
6.1%
9 2
 
6.1%
2 1
 
3.0%
1,314 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
Other values (8) 8
24.2%
2024-02-10T06:56:04.468440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
21.7%
1 12
20.0%
2 7
11.7%
4 5
 
8.3%
8 4
 
6.7%
, 4
 
6.7%
3 4
 
6.7%
9 2
 
3.3%
6 2
 
3.3%
5 2
 
3.3%
Other values (4) 5
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 51
85.0%
Other Punctuation 4
 
6.7%
Other Letter 3
 
5.0%
Dash Punctuation 2
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
25.5%
1 12
23.5%
2 7
13.7%
4 5
 
9.8%
8 4
 
7.8%
3 4
 
7.8%
9 2
 
3.9%
6 2
 
3.9%
5 2
 
3.9%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
22.8%
1 12
21.1%
2 7
12.3%
4 5
 
8.8%
8 4
 
7.0%
, 4
 
7.0%
3 4
 
7.0%
9 2
 
3.5%
6 2
 
3.5%
5 2
 
3.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
22.8%
1 12
21.1%
2 7
12.3%
4 5
 
8.8%
8 4
 
7.0%
, 4
 
7.0%
3 4
 
7.0%
9 2
 
3.5%
6 2
 
3.5%
5 2
 
3.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 26
Categorical

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
11 
3
10
<NA>
13
Other values (11)
13 

Length

Max length5
Median length1
Mean length1.8857143
Min length1

Unique

Unique9 ?
Unique (%)25.7%

Sample

1st row<NA>
2nd row<NA>
3rd row본량동
4th row1,180
5th row1,923

Common Values

ValueCountFrequency (%)
0 11
31.4%
3 4
 
11.4%
10 3
 
8.6%
<NA> 2
 
5.7%
13 2
 
5.7%
5 2
 
5.7%
4 2
 
5.7%
본량동 1
 
2.9%
1,180 1
 
2.9%
1,923 1
 
2.9%
Other values (6) 6
17.1%

Length

2024-02-10T06:56:04.960077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 11
31.4%
3 4
 
11.4%
10 3
 
8.6%
na 2
 
5.7%
13 2
 
5.7%
5 2
 
5.7%
4 2
 
5.7%
본량동 1
 
2.9%
1,180 1
 
2.9%
1,923 1
 
2.9%
Other values (6) 6
17.1%

Unnamed: 27
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:56:05.514841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6060606
Min length1

Characters and Unicode

Total characters86
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row신창동
2nd row13,774
3rd row34,148
4th row58
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
1 1
 
3.0%
397 1
 
3.0%
67 1
 
3.0%
34,146 1
 
3.0%
13,809 1
 
3.0%
9 1
 
3.0%
2 1
 
3.0%
35 1
 
3.0%
12 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T06:56:06.584177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
24.4%
0 12
14.0%
3 7
 
8.1%
4 7
 
8.1%
8 7
 
8.1%
9 7
 
8.1%
2 6
 
7.0%
6 5
 
5.8%
, 4
 
4.7%
7 4
 
4.7%
Other values (5) 6
 
7.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
26.9%
0 12
15.4%
3 7
 
9.0%
4 7
 
9.0%
8 7
 
9.0%
9 7
 
9.0%
2 6
 
7.7%
6 5
 
6.4%
7 4
 
5.1%
5 2
 
2.6%
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 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
25.3%
0 12
14.5%
3 7
 
8.4%
4 7
 
8.4%
8 7
 
8.4%
9 7
 
8.4%
2 6
 
7.2%
6 5
 
6.0%
, 4
 
4.8%
7 4
 
4.8%
Other values (2) 3
 
3.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
25.3%
0 12
14.5%
3 7
 
8.4%
4 7
 
8.4%
8 7
 
8.4%
9 7
 
8.4%
2 6
 
7.2%
6 5
 
6.0%
, 4
 
4.8%
7 4
 
4.8%
Other values (2) 3
 
3.6%
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: 27
0<NA>행정기관 :<NA>광주광역시 광산구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2023.03.04<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.02 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>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계송정1동송정2동도산동신흥동어룡동우산동<NA>월곡1동월곡2동비아동첨단1동첨단2동신가동운남동수완동하남동임곡동동곡동평동삼도동본량동신창동
3<NA>전월말세대수<NA><NA><NA>170,7954,7923,4436,6192,01014,30215,033<NA>4,7996,4093,51010,67418,6697,41812,23628,23011,1341,2471,0002,9941,3221,18013,774
4<NA>전월말인구수<NA><NA><NA>400,22810,5566,36814,8204,41333,27729,499<NA>10,29214,9317,49627,15442,48219,44530,01375,90326,6562,0521,7524,8942,1541,92334,148
5<NA>전월말거주불명자수<NA><NA><NA>791455820213493<NA>4835252266512211641123126358
6<NA>전월말재외국민등록자수<NA><NA><NA>139173367<NA>76514235101672430010
7<NA>증 가 요 인전 입<NA>4,0501047116447349245<NA>9199862905221561997663221519741823390
8<NA><NA><NA>남자<NA>2,06958388521180123<NA>47464914926181953691711015401013208
9<NA><NA><NA>여자<NA>1,98146337926169122<NA>445337141261751043971515434810182
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: 27
25<NA><NA>말소<NA><NA>5001010<NA>000100010000100
26<NA><NA>국외<NA><NA>0000000<NA>000000000000000
27<NA><NA>기타<NA><NA>74000000<NA>0740000000000000
28<NA>세대수증감<NA><NA><NA>100-3-311813-43<NA>-13-4844324754837-3-5-8-8-135
29<NA>인구수증감<NA><NA><NA>-559-18-34-2815-7-91<NA>-15-126-424-117-38-81-6949-1918-147-2
30<NA>거주불명자수증감<NA><NA><NA>60110-1-4<NA>-1013-2-2-12010-1009
31<NA>금월말세대수<NA><NA><NA>170,8954,7893,4406,6302,01814,31514,990<NA>4,7866,3613,51410,71718,6937,42512,24128,27811,1711,2449952,9861,3141,17913,809
32<NA>금월말인구수<NA><NA><NA>399,66910,5386,33414,7924,42833,27029,408<NA>10,27714,8057,49227,17842,36519,40729,93275,83426,7052,0331,7534,9022,1401,93034,146
33<NA>금월말거주불명자수<NA><NA><NA>797455921213389<NA>4735262564492111841133116367
34<NA>금월말재외국민등록자수<NA><NA><NA>143183377<NA>76614235101672430011

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: 27# duplicates
0<NA>국외<NA><NA>0000000<NA>0000000000000002