Overview

Dataset statistics

Number of variables28
Number of observations35
Missing cells205
Missing cells (%)20.9%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory7.8 KiB
Average record size in memory228.8 B

Variable types

Unsupported1
Text24
DateTime1
Categorical2

Dataset

Description2023-02-23
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201924

Alerts

Unnamed: 12 has constant value ""Constant
Dataset has 2 (5.7%) duplicate rowsDuplicates
Unnamed: 0 has 35 (100.0%) missing valuesMissing
인구이동보고서(1호) has 19 (54.3%) missing valuesMissing
Unnamed: 2 has 24 (68.6%) missing valuesMissing
Unnamed: 3 has 23 (65.7%) missing valuesMissing
Unnamed: 4 has 31 (88.6%) missing valuesMissing
Unnamed: 5 has 2 (5.7%) missing valuesMissing
Unnamed: 6 has 2 (5.7%) missing valuesMissing
Unnamed: 7 has 2 (5.7%) missing valuesMissing
Unnamed: 8 has 2 (5.7%) missing valuesMissing
Unnamed: 9 has 2 (5.7%) missing valuesMissing
Unnamed: 10 has 1 (2.9%) missing valuesMissing
Unnamed: 11 has 2 (5.7%) missing valuesMissing
Unnamed: 12 has 34 (97.1%) missing valuesMissing
Unnamed: 13 has 2 (5.7%) missing valuesMissing
Unnamed: 14 has 2 (5.7%) missing valuesMissing
Unnamed: 15 has 2 (5.7%) missing valuesMissing
Unnamed: 16 has 2 (5.7%) missing valuesMissing
Unnamed: 17 has 2 (5.7%) missing valuesMissing
Unnamed: 18 has 2 (5.7%) missing valuesMissing
Unnamed: 19 has 2 (5.7%) missing valuesMissing
Unnamed: 20 has 2 (5.7%) missing valuesMissing
Unnamed: 21 has 2 (5.7%) missing valuesMissing
Unnamed: 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 06:54:46.881477
Analysis finished2024-02-10 06:54:48.255912
Duration1.37 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
2024-02-10T06:54:48.468259image/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%
2024-02-10T06:54:49.457758image/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
2024-02-10T06:54:50.030191image/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%
2024-02-10T06:54:50.909979image/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
2024-02-10T06:54:51.278351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length3
Mean length3.5
Min length1

Characters and Unicode

Total characters42
Distinct characters21
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 광산구
2nd row2023.01 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%
2023.01 1
7.1%
현재 1
7.1%
2024-02-10T06:54:52.214463image/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
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
2
 
4.8%
Other values (11) 13
31.0%

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 2
33.3%
0 2
33.3%
3 1
16.7%
1 1
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
1 1
 
10.0%
. 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 2
20.0%
0 2
20.0%
3 1
 
10.0%
1 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T06:54:52.504306image/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%
2024-02-10T06:54:53.313670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

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

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

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

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

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

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:54:53.887770image/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

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row170,776
3rd row400,654
4th row752
5th row140
ValueCountFrequency (%)
0 5
 
14.7%
1,054 2
 
5.9%
1,874 1
 
2.9%
1,922 1
 
2.9%
791 1
 
2.9%
400,228 1
 
2.9%
170,795 1
 
2.9%
39 1
 
2.9%
426 1
 
2.9%
19 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T06:54:54.798514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
14.8%
0 15
12.3%
, 14
11.5%
7 14
11.5%
4 12
9.8%
9 11
9.0%
5 7
 
5.7%
2 7
 
5.7%
8 7
 
5.7%
3 6
 
4.9%
Other values (5) 11
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 103
84.4%
Other Punctuation 14
 
11.5%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 18
17.5%
0 15
14.6%
7 14
13.6%
4 12
11.7%
9 11
10.7%
5 7
 
6.8%
2 7
 
6.8%
8 7
 
6.8%
3 6
 
5.8%
6 6
 
5.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 18
15.0%
0 15
12.5%
, 14
11.7%
7 14
11.7%
4 12
10.0%
9 11
9.2%
5 7
 
5.8%
2 7
 
5.8%
8 7
 
5.8%
3 6
 
5.0%
Other values (3) 9
7.5%
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 18
15.0%
0 15
12.5%
, 14
11.7%
7 14
11.7%
4 12
10.0%
9 11
9.2%
5 7
 
5.8%
2 7
 
5.8%
8 7
 
5.8%
3 6
 
5.0%
Other values (3) 9
7.5%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 6
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:54:55.179556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique20 ?
Unique (%)60.6%

Sample

1st row송정1동
2nd row4,801
3rd row10,574
4th row49
5th row1
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
32 2
 
6.1%
37 2
 
6.1%
47 1
 
3.0%
49 1
 
3.0%
83 1
 
3.0%
10,556 1
 
3.0%
4,792 1
 
3.0%
4 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:54:56.515820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.7%
1 10
13.7%
4 10
13.7%
3 7
9.6%
7 6
8.2%
5 5
6.8%
2 4
 
5.5%
8 4
 
5.5%
, 4
 
5.5%
9 4
 
5.5%
Other values (5) 9
12.3%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.9%
1 10
15.9%
4 10
15.9%
3 7
11.1%
7 6
9.5%
5 5
7.9%
2 4
 
6.3%
8 4
 
6.3%
9 4
 
6.3%
6 3
 
4.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.3%
1 10
14.3%
4 10
14.3%
3 7
10.0%
7 6
8.6%
5 5
7.1%
2 4
 
5.7%
8 4
 
5.7%
, 4
 
5.7%
9 4
 
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.3%
1 10
14.3%
4 10
14.3%
3 7
10.0%
7 6
8.6%
5 5
7.1%
2 4
 
5.7%
8 4
 
5.7%
, 4
 
5.7%
9 4
 
5.7%
Other values (2) 6
8.6%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 7
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:54:56.890288image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row송정2동
2nd row3,439
3rd row6,364
4th row58
5th row7
ValueCountFrequency (%)
0 8
24.2%
7 3
 
9.1%
4 2
 
6.1%
58 2
 
6.1%
37 2
 
6.1%
22 1
 
3.0%
1 1
 
3.0%
3,443 1
 
3.0%
23 1
 
3.0%
15 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T06:54:58.279018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

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 (%)
3 10
16.9%
0 8
13.6%
2 8
13.6%
4 7
11.9%
6 7
11.9%
7 6
10.2%
8 4
 
6.8%
5 3
 
5.1%
9 3
 
5.1%
1 3
 
5.1%
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 (%)
3 10
15.9%
0 8
12.7%
2 8
12.7%
4 7
11.1%
6 7
11.1%
7 6
9.5%
8 4
 
6.3%
, 4
 
6.3%
5 3
 
4.8%
9 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 (%)
3 10
15.9%
0 8
12.7%
2 8
12.7%
4 7
11.1%
6 7
11.1%
7 6
9.5%
8 4
 
6.3%
, 4
 
6.3%
5 3
 
4.8%
9 3
 
4.8%
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
2024-02-10T06:54:58.889092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row도산동
2nd row6,629
3rd row14,860
4th row22
5th row3
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
3 2
 
6.1%
105 1
 
3.0%
85 1
 
3.0%
14,820 1
 
3.0%
6,619 1
 
3.0%
2 1
 
3.0%
40 1
 
3.0%
94 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:55:00.279436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17
22.4%
1 11
14.5%
6 6
 
7.9%
2 6
 
7.9%
4 6
 
7.9%
9 5
 
6.6%
3 4
 
5.3%
, 4
 
5.3%
8 4
 
5.3%
5 4
 
5.3%
Other values (5) 9
11.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17
25.8%
1 11
16.7%
6 6
 
9.1%
2 6
 
9.1%
4 6
 
9.1%
9 5
 
7.6%
3 4
 
6.1%
8 4
 
6.1%
5 4
 
6.1%
7 3
 
4.5%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 17
23.3%
1 11
15.1%
6 6
 
8.2%
2 6
 
8.2%
4 6
 
8.2%
9 5
 
6.8%
3 4
 
5.5%
, 4
 
5.5%
8 4
 
5.5%
5 4
 
5.5%
Other values (2) 6
 
8.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17
23.3%
1 11
15.1%
6 6
 
8.2%
2 6
 
8.2%
4 6
 
8.2%
9 5
 
6.8%
3 4
 
5.5%
, 4
 
5.5%
8 4
 
5.5%
5 4
 
5.5%
Other values (2) 6
 
8.2%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 9
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:00.745577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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

Unique20 ?
Unique (%)60.6%

Sample

1st row신흥동
2nd row2,022
3rd row4,441
4th row22
5th row3
ValueCountFrequency (%)
0 6
18.2%
12 3
 
9.1%
1 3
 
9.1%
3 3
 
9.1%
15 1
 
3.0%
22 1
 
3.0%
29 1
 
3.0%
4,413 1
 
3.0%
2,010 1
 
3.0%
28 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:55:01.635947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 14
20.6%
1 13
19.1%
0 11
16.2%
4 7
10.3%
3 6
8.8%
, 4
 
5.9%
- 3
 
4.4%
6 2
 
2.9%
9 2
 
2.9%
5 2
 
2.9%
Other values (4) 4
 
5.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 14
24.1%
1 13
22.4%
0 11
19.0%
4 7
12.1%
3 6
10.3%
6 2
 
3.4%
9 2
 
3.4%
5 2
 
3.4%
8 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 14
21.5%
1 13
20.0%
0 11
16.9%
4 7
10.8%
3 6
9.2%
, 4
 
6.2%
- 3
 
4.6%
6 2
 
3.1%
9 2
 
3.1%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 14
21.5%
1 13
20.0%
0 11
16.9%
4 7
10.8%
3 6
9.2%
, 4
 
6.2%
- 3
 
4.6%
6 2
 
3.1%
9 2
 
3.1%
5 2
 
3.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T06:55:02.201650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5588235
Min length1

Characters and Unicode

Total characters87
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 row어룡동
3rd row14,279
4th row33,280
5th row26
ValueCountFrequency (%)
0 6
 
17.1%
89 2
 
5.7%
15 2
 
5.7%
6 2
 
5.7%
91 2
 
5.7%
153 1
 
2.9%
4 1
 
2.9%
33,277 1
 
2.9%
14,302 1
 
2.9%
8 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T06:55:03.122545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
14.9%
3 10
11.5%
0 9
10.3%
2 9
10.3%
8 7
8.0%
4 7
8.0%
5 6
6.9%
9 6
6.9%
, 4
 
4.6%
6 3
 
3.4%
Other values (11) 13
14.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
83.9%
Other Letter 7
 
8.0%
Other Punctuation 5
 
5.7%
Space Separator 1
 
1.1%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
17.8%
3 10
13.7%
0 9
12.3%
2 9
12.3%
8 7
9.6%
4 7
9.6%
5 6
8.2%
9 6
8.2%
6 3
 
4.1%
7 3
 
4.1%
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%
Space Separator
ValueCountFrequency (%)
1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
92.0%
Hangul 7
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
16.2%
3 10
12.5%
0 9
11.2%
2 9
11.2%
8 7
8.8%
4 7
8.8%
5 6
7.5%
9 6
7.5%
, 4
 
5.0%
6 3
 
3.8%
Other values (4) 6
7.5%
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 80
92.0%
Hangul 7
 
8.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
16.2%
3 10
12.5%
0 9
11.2%
2 9
11.2%
8 7
8.8%
4 7
8.8%
5 6
7.5%
9 6
7.5%
, 4
 
5.0%
6 3
 
3.8%
Other values (4) 6
7.5%
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 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:03.517551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique27 ?
Unique (%)81.8%

Sample

1st row우산동
2nd row15,064
3rd row29,603
4th row96
5th row8
ValueCountFrequency (%)
0 6
 
18.2%
1 1
 
3.0%
313 1
 
3.0%
93 1
 
3.0%
29,499 1
 
3.0%
15,033 1
 
3.0%
3 1
 
3.0%
104 1
 
3.0%
31 1
 
3.0%
20 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T06:55:04.399919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
18.8%
1 14
16.5%
3 9
10.6%
6 7
8.2%
4 7
8.2%
9 7
8.2%
2 5
 
5.9%
5 4
 
4.7%
, 4
 
4.7%
7 4
 
4.7%
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 (%)
0 16
21.3%
1 14
18.7%
3 9
12.0%
6 7
9.3%
4 7
9.3%
9 7
9.3%
2 5
 
6.7%
5 4
 
5.3%
7 4
 
5.3%
8 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 (%)
0 16
19.5%
1 14
17.1%
3 9
11.0%
6 7
8.5%
4 7
8.5%
9 7
8.5%
2 5
 
6.1%
5 4
 
4.9%
, 4
 
4.9%
7 4
 
4.9%
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 (%)
0 16
19.5%
1 14
17.1%
3 9
11.0%
6 7
8.5%
4 7
8.5%
9 7
8.5%
2 5
 
6.1%
5 4
 
4.9%
, 4
 
4.9%
7 4
 
4.9%
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
Minimum2023-02-10 00:00:00
Maximum2023-02-10 00:00:00
2024-02-10T06:55:04.873995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T06:55:05.157138image/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
2024-02-10T06:55:05.491425image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row월곡1동
2nd row4,799
3rd row10,324
4th row49
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 2
 
6.1%
1 2
 
6.1%
4,799 2
 
6.1%
4 1
 
3.0%
114 1
 
3.0%
10,292 1
 
3.0%
32 1
 
3.0%
5 1
 
3.0%
43 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:55:06.316470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13
18.1%
0 11
15.3%
1 9
12.5%
2 7
9.7%
9 6
8.3%
3 6
8.3%
7 5
 
6.9%
, 4
 
5.6%
8 3
 
4.2%
5 2
 
2.8%
Other values (5) 6
8.3%

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 (%)
4 13
20.6%
0 11
17.5%
1 9
14.3%
2 7
11.1%
9 6
9.5%
3 6
9.5%
7 5
 
7.9%
8 3
 
4.8%
5 2
 
3.2%
6 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 69
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
4 13
18.8%
0 11
15.9%
1 9
13.0%
2 7
10.1%
9 6
8.7%
3 6
8.7%
7 5
 
7.2%
, 4
 
5.8%
8 3
 
4.3%
5 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 (%)
4 13
18.8%
0 11
15.9%
1 9
13.0%
2 7
10.1%
9 6
8.7%
3 6
8.7%
7 5
 
7.2%
, 4
 
5.8%
8 3
 
4.3%
5 2
 
2.9%
Other values (2) 3
 
4.3%
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
2024-02-10T06:55:06.724564image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row월곡2동
2nd row6,425
3rd row14,950
4th row28
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
60 1
 
3.0%
118 1
 
3.0%
35 1
 
3.0%
14,931 1
 
3.0%
6,409 1
 
3.0%
19 1
 
3.0%
16 1
 
3.0%
9 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:55:07.660315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
1 10
15.6%
9 8
12.5%
4 7
10.9%
6 6
9.4%
2 6
9.4%
5 6
9.4%
8 4
 
6.2%
7 3
 
4.7%
3 3
 
4.7%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
1 10
14.3%
9 8
11.4%
4 7
10.0%
6 6
8.6%
2 6
8.6%
5 6
8.6%
, 4
 
5.7%
8 4
 
5.7%
7 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.7%
1 10
14.3%
9 8
11.4%
4 7
10.0%
6 6
8.6%
2 6
8.6%
5 6
8.6%
, 4
 
5.7%
8 4
 
5.7%
7 3
 
4.3%
Other values (2) 5
7.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 15
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:08.060170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row비아동
2nd row3,520
3rd row7,516
4th row26
5th row5
ValueCountFrequency (%)
0 7
21.2%
22 2
 
6.1%
25 2
 
6.1%
26 2
 
6.1%
5 2
 
6.1%
14 2
 
6.1%
18 1
 
3.0%
47 1
 
3.0%
38 1
 
3.0%
3,510 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:55:09.051512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.1%
2 10
14.3%
1 9
12.9%
5 7
10.0%
4 6
8.6%
6 5
7.1%
7 4
 
5.7%
, 4
 
5.7%
3 4
 
5.7%
- 3
 
4.3%
Other values (5) 6
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.0%
2 10
16.7%
1 9
15.0%
5 7
11.7%
4 6
10.0%
6 5
8.3%
7 4
 
6.7%
3 4
 
6.7%
8 2
 
3.3%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.9%
2 10
14.9%
1 9
13.4%
5 7
10.4%
4 6
9.0%
6 5
7.5%
7 4
 
6.0%
, 4
 
6.0%
3 4
 
6.0%
- 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.9%
2 10
14.9%
1 9
13.4%
5 7
10.4%
4 6
9.0%
6 5
7.5%
7 4
 
6.0%
, 4
 
6.0%
3 4
 
6.0%
- 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 16
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:09.471280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique25 ?
Unique (%)75.8%

Sample

1st row첨단1동
2nd row10,624
3rd row27,112
4th row21
5th row15
ValueCountFrequency (%)
0 6
 
18.2%
15 2
 
6.1%
58 1
 
3.0%
118 1
 
3.0%
22 1
 
3.0%
27,154 1
 
3.0%
10,674 1
 
3.0%
1 1
 
3.0%
42 1
 
3.0%
50 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:55:10.374275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
25.0%
2 12
14.3%
0 10
11.9%
4 9
10.7%
3 7
 
8.3%
5 5
 
6.0%
7 5
 
6.0%
6 4
 
4.8%
, 4
 
4.8%
9 2
 
2.4%
Other values (4) 5
 
6.0%

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 21
27.3%
2 12
15.6%
0 10
13.0%
4 9
11.7%
3 7
 
9.1%
5 5
 
6.5%
7 5
 
6.5%
6 4
 
5.2%
9 2
 
2.6%
8 2
 
2.6%
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 21
25.9%
2 12
14.8%
0 10
12.3%
4 9
11.1%
3 7
 
8.6%
5 5
 
6.2%
7 5
 
6.2%
6 4
 
4.9%
, 4
 
4.9%
9 2
 
2.5%
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 21
25.9%
2 12
14.8%
0 10
12.3%
4 9
11.1%
3 7
 
8.6%
5 5
 
6.2%
7 5
 
6.2%
6 4
 
4.9%
, 4
 
4.9%
9 2
 
2.5%
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
2024-02-10T06:55:10.835474image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row첨단2동
2nd row18,677
3rd row42,555
4th row69
5th row23
ValueCountFrequency (%)
0 7
21.2%
120 2
 
6.1%
23 2
 
6.1%
19 1
 
3.0%
478 1
 
3.0%
42,482 1
 
3.0%
18,669 1
 
3.0%
3 1
 
3.0%
73 1
 
3.0%
8 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T06:55:11.684920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
14.6%
0 12
13.5%
1 10
11.2%
4 8
9.0%
3 7
7.9%
8 7
7.9%
6 7
7.9%
7 6
6.7%
9 6
6.7%
, 4
 
4.5%
Other values (5) 9
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 79
88.8%
Other Punctuation 4
 
4.5%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
16.5%
0 12
15.2%
1 10
12.7%
4 8
10.1%
3 7
8.9%
8 7
8.9%
6 7
8.9%
7 6
7.6%
9 6
7.6%
5 3
 
3.8%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
15.1%
0 12
14.0%
1 10
11.6%
4 8
9.3%
3 7
8.1%
8 7
8.1%
6 7
8.1%
7 6
7.0%
9 6
7.0%
, 4
 
4.7%
Other values (2) 6
7.0%
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 (%)
2 13
15.1%
0 12
14.0%
1 10
11.6%
4 8
9.3%
3 7
8.1%
8 7
8.1%
6 7
8.1%
7 6
7.0%
9 6
7.0%
, 4
 
4.7%
Other values (2) 6
7.0%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 18
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:12.160580image/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

Unique17 ?
Unique (%)51.5%

Sample

1st row신가동
2nd row7,418
3rd row19,462
4th row37
5th row5
ValueCountFrequency (%)
0 8
24.2%
5 2
 
6.1%
51 2
 
6.1%
7,418 2
 
6.1%
37 2
 
6.1%
70 1
 
3.0%
19,462 1
 
3.0%
72 1
 
3.0%
14 1
 
3.0%
17 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T06:55:12.951833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
1 10
13.9%
7 9
12.5%
4 8
11.1%
5 6
8.3%
3 5
6.9%
, 4
 
5.6%
8 4
 
5.6%
6 4
 
5.6%
2 4
 
5.6%
Other values (5) 7
9.7%

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 11
17.2%
1 10
15.6%
7 9
14.1%
4 8
12.5%
5 6
9.4%
3 5
7.8%
8 4
 
6.2%
6 4
 
6.2%
2 4
 
6.2%
9 3
 
4.7%
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 11
15.9%
1 10
14.5%
7 9
13.0%
4 8
11.6%
5 6
8.7%
3 5
7.2%
, 4
 
5.8%
8 4
 
5.8%
6 4
 
5.8%
2 4
 
5.8%
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 (%)
0 11
15.9%
1 10
14.5%
7 9
13.0%
4 8
11.6%
5 6
8.7%
3 5
7.2%
, 4
 
5.8%
8 4
 
5.8%
6 4
 
5.8%
2 4
 
5.8%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 19
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:13.431760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
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 row운남동
2nd row12,272
3rd row30,128
4th row23
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
1 3
 
9.1%
10 2
 
6.1%
59 2
 
6.1%
23 2
 
6.1%
112 1
 
3.0%
54 1
 
3.0%
30,013 1
 
3.0%
12,236 1
 
3.0%
115 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T06:55:14.331973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.6%
2 15
17.9%
0 12
14.3%
3 9
10.7%
5 5
 
6.0%
4 4
 
4.8%
, 4
 
4.8%
6 4
 
4.8%
8 3
 
3.6%
- 3
 
3.6%
Other values (5) 6
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
88.1%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
25.7%
2 15
20.3%
0 12
16.2%
3 9
12.2%
5 5
 
6.8%
4 4
 
5.4%
6 4
 
5.4%
8 3
 
4.1%
9 2
 
2.7%
7 1
 
1.4%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
23.5%
2 15
18.5%
0 12
14.8%
3 9
11.1%
5 5
 
6.2%
4 4
 
4.9%
, 4
 
4.9%
6 4
 
4.9%
8 3
 
3.7%
- 3
 
3.7%
Other values (2) 3
 
3.7%
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 19
23.5%
2 15
18.5%
0 12
14.8%
3 9
11.1%
5 5
 
6.2%
4 4
 
4.9%
, 4
 
4.9%
6 4
 
4.9%
8 3
 
3.7%
- 3
 
3.7%
Other values (2) 3
 
3.7%
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
2024-02-10T06:55:14.755346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row수완동
2nd row28,194
3rd row75,889
4th row90
5th row15
ValueCountFrequency (%)
0 6
 
18.2%
15 2
 
6.1%
354 1
 
3.0%
696 1
 
3.0%
116 1
 
3.0%
75,903 1
 
3.0%
28,230 1
 
3.0%
26 1
 
3.0%
14 1
 
3.0%
36 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T06:55:16.613422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
13.5%
1 11
12.4%
0 10
11.2%
2 10
11.2%
6 10
11.2%
9 9
10.1%
4 7
7.9%
5 6
6.7%
8 4
 
4.5%
, 4
 
4.5%
Other values (4) 6
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 82
92.1%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
14.6%
1 11
13.4%
0 10
12.2%
2 10
12.2%
6 10
12.2%
9 9
11.0%
4 7
8.5%
5 6
7.3%
8 4
 
4.9%
7 3
 
3.7%
Other Letter
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
14.0%
1 11
12.8%
0 10
11.6%
2 10
11.6%
6 10
11.6%
9 9
10.5%
4 7
8.1%
5 6
7.0%
8 4
 
4.7%
, 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 (%)
3 12
14.0%
1 11
12.8%
0 10
11.6%
2 10
11.6%
6 10
11.6%
9 9
10.5%
4 7
8.1%
5 6
7.0%
8 4
 
4.7%
, 4
 
4.7%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 21
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:17.403631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4848485
Min length1

Characters and Unicode

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

Unique

Unique27 ?
Unique (%)81.8%

Sample

1st row하남동
2nd row11,086
3rd row26,624
4th row43
5th row6
ValueCountFrequency (%)
0 6
 
18.2%
1 1
 
3.0%
275 1
 
3.0%
41 1
 
3.0%
26,656 1
 
3.0%
11,134 1
 
3.0%
2 1
 
3.0%
32 1
 
3.0%
48 1
 
3.0%
9 1
 
3.0%
Other values (18) 18
54.5%
2024-02-10T06:55:18.903411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
20.7%
0 9
11.0%
2 9
11.0%
6 8
9.8%
4 8
9.8%
5 6
 
7.3%
7 6
 
7.3%
3 5
 
6.1%
, 4
 
4.9%
8 3
 
3.7%
Other values (5) 7
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
90.2%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
23.0%
0 9
12.2%
2 9
12.2%
6 8
10.8%
4 8
10.8%
5 6
 
8.1%
7 6
 
8.1%
3 5
 
6.8%
8 3
 
4.1%
9 3
 
4.1%
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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
21.5%
0 9
11.4%
2 9
11.4%
6 8
10.1%
4 8
10.1%
5 6
 
7.6%
7 6
 
7.6%
3 5
 
6.3%
, 4
 
5.1%
8 3
 
3.8%
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 17
21.5%
0 9
11.4%
2 9
11.4%
6 8
10.1%
4 8
10.1%
5 6
 
7.6%
7 6
 
7.6%
3 5
 
6.3%
, 4
 
5.1%
8 3
 
3.8%
Other values (2) 4
 
5.1%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Unnamed: 22
Categorical

Distinct16
Distinct (%)45.7%
Missing0
Missing (%)0.0%
Memory size412.0 B
0
12
2
7
<NA>
Other values (11)
15 

Length

Max length5
Median length1
Mean length1.8
Min length1

Unique

Unique7 ?
Unique (%)20.0%

Sample

1st row<NA>
2nd row<NA>
3rd row임곡동
4th row1,240
5th row2,048

Common Values

ValueCountFrequency (%)
0 9
25.7%
12 3
 
8.6%
2 3
 
8.6%
7 3
 
8.6%
<NA> 2
 
5.7%
9 2
 
5.7%
6 2
 
5.7%
5 2
 
5.7%
3 2
 
5.7%
임곡동 1
 
2.9%
Other values (6) 6
17.1%

Length

2024-02-10T06:55:19.373229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 9
25.7%
12 3
 
8.6%
2 3
 
8.6%
7 3
 
8.6%
na 2
 
5.7%
9 2
 
5.7%
6 2
 
5.7%
5 2
 
5.7%
3 2
 
5.7%
임곡동 1
 
2.9%
Other values (6) 6
17.1%

Unnamed: 23
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:19.780056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.6666667
Min length1

Characters and Unicode

Total characters55
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

Unique13 ?
Unique (%)39.4%

Sample

1st row동곡동
2nd row1,003
3rd row1,757
4th row2
5th row4
ValueCountFrequency (%)
0 9
27.3%
6 3
 
9.1%
2 3
 
9.1%
4 3
 
9.1%
1 2
 
6.1%
5 2
 
6.1%
3 2
 
6.1%
9 1
 
3.0%
1,752 1
 
3.0%
1,000 1
 
3.0%
Other values (6) 6
18.2%
2024-02-10T06:55:20.773552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
27.3%
1 8
14.5%
2 4
 
7.3%
4 4
 
7.3%
, 4
 
7.3%
5 4
 
7.3%
6 3
 
5.5%
7 3
 
5.5%
3 3
 
5.5%
- 2
 
3.6%
Other values (4) 5
 
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 46
83.6%
Other Punctuation 4
 
7.3%
Other Letter 3
 
5.5%
Dash Punctuation 2
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
32.6%
1 8
17.4%
2 4
 
8.7%
4 4
 
8.7%
5 4
 
8.7%
6 3
 
6.5%
7 3
 
6.5%
3 3
 
6.5%
9 1
 
2.2%
8 1
 
2.2%
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 52
94.5%
Hangul 3
 
5.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
28.8%
1 8
15.4%
2 4
 
7.7%
4 4
 
7.7%
, 4
 
7.7%
5 4
 
7.7%
6 3
 
5.8%
7 3
 
5.8%
3 3
 
5.8%
- 2
 
3.8%
Other values (2) 2
 
3.8%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52
94.5%
Hangul 3
 
5.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
28.8%
1 8
15.4%
2 4
 
7.7%
4 4
 
7.7%
, 4
 
7.7%
5 4
 
7.7%
6 3
 
5.8%
7 3
 
5.8%
3 3
 
5.8%
- 2
 
3.8%
Other values (2) 2
 
3.8%
Hangul
ValueCountFrequency (%)
2
66.7%
1
33.3%

Unnamed: 24
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:21.140708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length1.9090909
Min length1

Characters and Unicode

Total characters63
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

Unique18 ?
Unique (%)54.5%

Sample

1st row평동
2nd row2,986
3rd row4,889
4th row11
5th row3
ValueCountFrequency (%)
0 7
21.2%
19 2
 
6.1%
33 2
 
6.1%
3 2
 
6.1%
12 2
 
6.1%
26 1
 
3.0%
64 1
 
3.0%
40 1
 
3.0%
2,994 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T06:55:22.033635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8
12.7%
1 8
12.7%
2 8
12.7%
9 8
12.7%
4 8
12.7%
3 6
9.5%
8 5
7.9%
, 4
6.3%
6 3
 
4.8%
5 2
 
3.2%
Other values (3) 3
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
90.5%
Other Punctuation 4
 
6.3%
Other Letter 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8
14.0%
1 8
14.0%
2 8
14.0%
9 8
14.0%
4 8
14.0%
3 6
10.5%
8 5
8.8%
6 3
 
5.3%
5 2
 
3.5%
7 1
 
1.8%
Other Letter
ValueCountFrequency (%)
1
50.0%
1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 61
96.8%
Hangul 2
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8
13.1%
1 8
13.1%
2 8
13.1%
9 8
13.1%
4 8
13.1%
3 6
9.8%
8 5
8.2%
, 4
6.6%
6 3
 
4.9%
5 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 61
96.8%
Hangul 2
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8
13.1%
1 8
13.1%
2 8
13.1%
9 8
13.1%
4 8
13.1%
3 6
9.8%
8 5
8.2%
, 4
6.6%
6 3
 
4.9%
5 2
 
3.3%
Hangul
ValueCountFrequency (%)
1
50.0%
1
50.0%

Unnamed: 25
Text

MISSING 

Distinct18
Distinct (%)54.5%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:22.453882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length1
Mean length1.7272727
Min length1

Characters and Unicode

Total characters57
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st row삼도동
2nd row1,329
3rd row2,168
4th row6
5th row0
ValueCountFrequency (%)
0 11
33.3%
6 3
 
9.1%
8 3
 
9.1%
4 2
 
6.1%
7 2
 
6.1%
2 1
 
3.0%
1,322 1
 
3.0%
14 1
 
3.0%
9 1
 
3.0%
18 1
 
3.0%
Other values (7) 7
21.2%
2024-02-10T06:55:23.331087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
21.1%
1 8
14.0%
2 6
10.5%
8 5
8.8%
6 4
 
7.0%
4 4
 
7.0%
, 4
 
7.0%
3 3
 
5.3%
7 2
 
3.5%
9 2
 
3.5%
Other values (5) 7
12.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 48
84.2%
Other Punctuation 4
 
7.0%
Other Letter 3
 
5.3%
Dash Punctuation 2
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
25.0%
1 8
16.7%
2 6
12.5%
8 5
10.4%
6 4
 
8.3%
4 4
 
8.3%
3 3
 
6.2%
7 2
 
4.2%
9 2
 
4.2%
5 2
 
4.2%
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 54
94.7%
Hangul 3
 
5.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
22.2%
1 8
14.8%
2 6
11.1%
8 5
9.3%
6 4
 
7.4%
4 4
 
7.4%
, 4
 
7.4%
3 3
 
5.6%
7 2
 
3.7%
9 2
 
3.7%
Other values (2) 4
 
7.4%
Hangul
ValueCountFrequency (%)
1
33.3%
1
33.3%
1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 54
94.7%
Hangul 3
 
5.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
22.2%
1 8
14.8%
2 6
11.1%
8 5
9.3%
6 4
 
7.4%
4 4
 
7.4%
, 4
 
7.4%
3 3
 
5.6%
7 2
 
3.7%
9 2
 
3.7%
Other values (2) 4
 
7.4%
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
5
<NA>
8
Other values (11)
14 

Length

Max length5
Median length1
Mean length1.8571429
Min length1

Unique

Unique8 ?
Unique (%)22.9%

Sample

1st row<NA>
2nd row<NA>
3rd row본량동
4th row1,184
5th row1,927

Common Values

ValueCountFrequency (%)
0 11
31.4%
3 3
 
8.6%
5 3
 
8.6%
<NA> 2
 
5.7%
8 2
 
5.7%
10 2
 
5.7%
7 2
 
5.7%
-4 2
 
5.7%
본량동 1
 
2.9%
1,184 1
 
2.9%
Other values (6) 6
17.1%

Length

2024-02-10T06:55:23.850758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 11
31.4%
3 3
 
8.6%
5 3
 
8.6%
na 2
 
5.7%
8 2
 
5.7%
10 2
 
5.7%
7 2
 
5.7%
4 2
 
5.7%
본량동 1
 
2.9%
1,184 1
 
2.9%
Other values (6) 6
17.1%

Unnamed: 27
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T06:55:24.336424image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row신창동
2nd row13,785
3rd row34,183
4th row59
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
1 3
 
9.1%
10 2
 
6.1%
56 1
 
3.0%
59 1
 
3.0%
34,183 1
 
3.0%
34,148 1
 
3.0%
13,774 1
 
3.0%
35 1
 
3.0%
11 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T06:55:25.225881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.1%
0 9
10.5%
3 8
9.3%
2 7
 
8.1%
4 7
 
8.1%
8 7
 
8.1%
5 6
 
7.0%
6 5
 
5.8%
9 5
 
5.8%
, 4
 
4.7%
Other values (5) 9
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
88.4%
Other Punctuation 4
 
4.7%
Dash Punctuation 3
 
3.5%
Other Letter 3
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
25.0%
0 9
11.8%
3 8
10.5%
2 7
 
9.2%
4 7
 
9.2%
8 7
 
9.2%
5 6
 
7.9%
6 5
 
6.6%
9 5
 
6.6%
7 3
 
3.9%
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 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
22.9%
0 9
10.8%
3 8
9.6%
2 7
 
8.4%
4 7
 
8.4%
8 7
 
8.4%
5 6
 
7.2%
6 5
 
6.0%
9 5
 
6.0%
, 4
 
4.8%
Other values (2) 6
 
7.2%
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 19
22.9%
0 9
10.8%
3 8
9.6%
2 7
 
8.4%
4 7
 
8.4%
8 7
 
8.4%
5 6
 
7.2%
6 5
 
6.0%
9 5
 
6.0%
, 4
 
4.8%
Other values (2) 6
 
7.2%
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>2023.02.10<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.01 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>170,7764,8013,4396,6292,02214,27915,064<NA>4,7996,4253,52010,62418,6777,41812,27228,19411,0861,2401,0032,9861,3291,18413,785
4<NA>전월말인구수<NA><NA><NA>400,65410,5746,36414,8604,44133,28029,603<NA>10,32414,9507,51627,11242,55519,46230,12875,88926,6242,0481,7574,8892,1681,92734,183
5<NA>전월말거주불명자수<NA><NA><NA>752495822222696<NA>492826216937239043122116359
6<NA>전월말재외국민등록자수<NA><NA><NA>140173368<NA>77515235101562430010
7<NA>증 가 요 인전 입<NA>3,367837615129288214<NA>8299472734001301226993041810641316249
8<NA><NA><NA>남자<NA>1,74846398120145105<NA>4059251341866859366165984058140
9<NA><NA><NA>여자<NA>1,6193737709143109<NA>4240221392146263333139922488109
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>4000000<NA>000200100000001
26<NA><NA>국외<NA><NA>0000000<NA>000000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000000
28<NA>세대수증감<NA><NA><NA>19-94-10-1223-31<NA>0-16-1050-80-3636487-38-7-4-11
29<NA>인구수증감<NA><NA><NA>-426-184-40-28-3-104<NA>-32-19-2042-73-17-11514324-55-14-4-35
30<NA>거주불명자수증감<NA><NA><NA>39-40-2-18-3<NA>-17-11-314-126-201100-1
31<NA>금월말세대수<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
32<NA>금월말인구수<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
33<NA>금월말거주불명자수<NA><NA><NA>791455820213493<NA>4835252266512211641123126358
34<NA>금월말재외국민등록자수<NA><NA><NA>139173367<NA>76514235101672430010

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
1<NA>기타<NA><NA>0000000<NA>0000000000000002