Overview

Dataset statistics

Number of variables24
Number of observations35
Missing cells201
Missing cells (%)23.9%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory6.7 KiB
Average record size in memory196.8 B

Variable types

Unsupported1
Text22
DateTime1

Dataset

Description2023-05-25
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201925

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: 22 has 2 (5.7%) missing valuesMissing
Unnamed: 23 has 2 (5.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 09:34:51.399298
Analysis finished2024-02-10 09:34:52.702478
Duration1.3 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

인구이동보고서(1호)
Text

MISSING 

Distinct16
Distinct (%)100.0%
Missing19
Missing (%)54.3%
Memory size412.0 B
2024-02-10T09:34:52.950086image/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 (%)
요 2
 
7.7%
인 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%
소 1
 
3.8%
Other values (13) 13
50.0%
2024-02-10T09:34:54.138726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
12
 
9.5%
수 11
 
8.7%
말 8
 
6.3%
월 8
 
6.3%
인 5
 
4.0%
자 5
 
4.0%
전 4
 
3.2%
감 4
 
3.2%
증 4
 
3.2%
금 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 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 (%)
수 11
 
10.6%
말 8
 
7.7%
월 8
 
7.7%
인 5
 
4.8%
자 5
 
4.8%
전 4
 
3.8%
감 4
 
3.8%
증 4
 
3.8%
금 4
 
3.8%
구 4
 
3.8%
Other values (27) 47
45.2%

Unnamed: 2
Text

MISSING 

Distinct9
Distinct (%)81.8%
Missing24
Missing (%)68.6%
Memory size412.0 B
2024-02-10T09:34:54.580995image/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%
전 2
15.4%
입 1
7.7%
복귀 1
7.7%
출생 1
7.7%
등록 1
7.7%
출 1
7.7%
사망 1
7.7%
말소 1
7.7%
2024-02-10T09:34:55.395592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
15.4%
국 2
 
7.7%
기 2
 
7.7%
타 2
 
7.7%
전 2
 
7.7%
외 2
 
7.7%
출 2
 
7.7%
록 1
 
3.8%
말 1
 
3.8%
망 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 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 (%)
국 2
 
9.1%
기 2
 
9.1%
타 2
 
9.1%
전 2
 
9.1%
외 2
 
9.1%
출 2
 
9.1%
록 1
 
4.5%
말 1
 
4.5%
망 1
 
4.5%
사 1
 
4.5%
Other values (6) 6
27.3%

Unnamed: 3
Text

MISSING 

Distinct7
Distinct (%)58.3%
Missing23
Missing (%)65.7%
Memory size412.0 B
2024-02-10T09:34:55.850935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 남구
2nd row2023.04 현재
3rd row계
4th row남자
5th row여자
ValueCountFrequency (%)
계 2
14.3%
남자 2
14.3%
여자 2
14.3%
시도내 2
14.3%
시도간 2
14.3%
광주광역시 1
7.1%
남구 1
7.1%
2023.04 1
7.1%
현재 1
7.1%
2024-02-10T09:34:56.608131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
12.2%
자 4
 
9.8%
도 4
 
9.8%
남 3
 
7.3%
3
 
7.3%
계 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
광 2
 
4.9%
Other values (10) 12
29.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 31
75.6%
Decimal Number 6
 
14.6%
Space Separator 3
 
7.3%
Other Punctuation 1
 
2.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
남 3
9.7%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
현 1
 
3.2%
Other values (4) 4
12.9%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 2
33.3%
4 1
16.7%
3 1
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 31
75.6%
Common 10
 
24.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
남 3
9.7%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
현 1
 
3.2%
Other values (4) 4
12.9%
Common
ValueCountFrequency (%)
3
30.0%
2 2
20.0%
0 2
20.0%
. 1
 
10.0%
4 1
 
10.0%
3 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 31
75.6%
ASCII 10
 
24.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 5
16.1%
자 4
12.9%
도 4
12.9%
남 3
9.7%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
현 1
 
3.2%
Other values (4) 4
12.9%
ASCII
ValueCountFrequency (%)
3
30.0%
2 2
20.0%
0 2
20.0%
. 1
 
10.0%
4 1
 
10.0%
3 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:34:56.923525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군구내
2nd row시군구간
3rd row시군구내
4th row시군구간
ValueCountFrequency (%)
시군구내 2
50.0%
시군구간 2
50.0%
2024-02-10T09:34:57.882614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 16
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 16
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 4
25.0%
군 4
25.0%
구 4
25.0%
내 2
12.5%
간 2
12.5%

Unnamed: 5
Text

MISSING 

Distinct28
Distinct (%)84.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:58.267596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.0606061
Min length1

Characters and Unicode

Total characters101
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 row95,778
3rd row211,563
4th row354
5th row151
ValueCountFrequency (%)
0 5
 
14.7%
540 2
 
5.9%
919 1
 
2.9%
937 1
 
2.9%
359 1
 
2.9%
211,329 1
 
2.9%
95,717 1
 
2.9%
5 1
 
2.9%
234 1
 
2.9%
61 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T09:34:59.228366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
14.9%
5 12
11.9%
9 11
10.9%
3 10
9.9%
0 9
8.9%
6 9
8.9%
4 7
6.9%
, 6
 
5.9%
8 6
 
5.9%
7 6
 
5.9%
Other values (5) 10
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 89
88.1%
Other Punctuation 6
 
5.9%
Space Separator 2
 
2.0%
Dash Punctuation 2
 
2.0%
Other Letter 2
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
16.9%
5 12
13.5%
9 11
12.4%
3 10
11.2%
0 9
10.1%
6 9
10.1%
4 7
7.9%
8 6
 
6.7%
7 6
 
6.7%
2 4
 
4.5%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 99
98.0%
Hangul 2
 
2.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
15.2%
5 12
12.1%
9 11
11.1%
3 10
10.1%
0 9
9.1%
6 9
9.1%
4 7
7.1%
, 6
 
6.1%
8 6
 
6.1%
7 6
 
6.1%
Other values (3) 8
8.1%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 99
98.0%
Hangul 2
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
15.2%
5 12
12.1%
9 11
11.1%
3 10
10.1%
0 9
9.1%
6 9
9.1%
4 7
7.1%
, 6
 
6.1%
8 6
 
6.1%
7 6
 
6.1%
Other values (3) 8
8.1%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:34:59.576928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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 row양림동
2nd row3,115
3rd row6,725
4th row15
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
19 2
 
6.1%
15 2
 
6.1%
16 2
 
6.1%
8 1
 
3.0%
42 1
 
3.0%
3,110 1
 
3.0%
5 1
 
3.0%
11 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:35:00.837476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 17
25.4%
0 8
11.9%
5 5
 
7.5%
7 5
 
7.5%
3 5
 
7.5%
2 5
 
7.5%
6 4
 
6.0%
4 4
 
6.0%
, 4
 
6.0%
8 3
 
4.5%
Other values (5) 7
10.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
86.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 17
29.3%
0 8
13.8%
5 5
 
8.6%
7 5
 
8.6%
3 5
 
8.6%
2 5
 
8.6%
6 4
 
6.9%
4 4
 
6.9%
8 3
 
5.2%
9 2
 
3.4%
Other Letter
ValueCountFrequency (%)
양 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 17
26.6%
0 8
12.5%
5 5
 
7.8%
7 5
 
7.8%
3 5
 
7.8%
2 5
 
7.8%
6 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
양 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 17
26.6%
0 8
12.5%
5 5
 
7.8%
7 5
 
7.8%
3 5
 
7.8%
2 5
 
7.8%
6 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
양 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:01.299593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row방림1동
2nd row3,034
3rd row6,677
4th row11
5th row7
ValueCountFrequency (%)
0 8
24.2%
14 2
 
6.1%
44 2
 
6.1%
11 2
 
6.1%
7 2
 
6.1%
26 2
 
6.1%
방림1동 1
 
3.0%
92 1
 
3.0%
48 1
 
3.0%
34 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:35:02.636217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.2%
3 10
14.7%
4 9
13.2%
2 7
10.3%
1 7
10.3%
6 6
8.8%
7 6
8.8%
, 4
 
5.9%
5 3
 
4.4%
방 1
 
1.5%
Other values (4) 4
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
89.7%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
3 10
16.4%
4 9
14.8%
2 7
11.5%
1 7
11.5%
6 6
9.8%
7 6
9.8%
5 3
 
4.9%
8 1
 
1.6%
9 1
 
1.6%
Other Letter
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.9%
3 10
15.4%
4 9
13.8%
2 7
10.8%
1 7
10.8%
6 6
9.2%
7 6
9.2%
, 4
 
6.2%
5 3
 
4.6%
8 1
 
1.5%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
16.9%
3 10
15.4%
4 9
13.8%
2 7
10.8%
1 7
10.8%
6 6
9.2%
7 6
9.2%
, 4
 
6.2%
5 3
 
4.6%
8 1
 
1.5%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:02.966224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
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

Unique19 ?
Unique (%)57.6%

Sample

1st row방림2동
2nd row3,962
3rd row8,438
4th row17
5th row10
ValueCountFrequency (%)
0 9
27.3%
17 3
 
9.1%
10 2
 
6.1%
43 1
 
3.0%
8,438 1
 
3.0%
46 1
 
3.0%
3,947 1
 
3.0%
55 1
 
3.0%
15 1
 
3.0%
4 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:35:03.842938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.7%
1 10
13.9%
3 8
11.1%
4 7
9.7%
8 6
8.3%
5 5
6.9%
2 5
6.9%
7 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
Other values (5) 8
11.1%

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 (%)
0 12
19.0%
1 10
15.9%
3 8
12.7%
4 7
11.1%
8 6
9.5%
5 5
7.9%
2 5
7.9%
7 4
 
6.3%
9 3
 
4.8%
6 3
 
4.8%
Other Letter
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 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 (%)
0 12
17.4%
1 10
14.5%
3 8
11.6%
4 7
10.1%
8 6
8.7%
5 5
7.2%
2 5
7.2%
7 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
17.4%
1 10
14.5%
3 8
11.6%
4 7
10.1%
8 6
8.7%
5 5
7.2%
2 5
7.2%
7 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:04.183992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

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

Unique

Unique23 ?
Unique (%)69.7%

Sample

1st row봉선1동
2nd row6,508
3rd row12,939
4th row43
5th row10
ValueCountFrequency (%)
0 6
 
18.2%
44 2
 
6.1%
2 2
 
6.1%
10 2
 
6.1%
62 1
 
3.0%
68 1
 
3.0%
12,915 1
 
3.0%
6,495 1
 
3.0%
24 1
 
3.0%
13 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:35:05.072234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 11
14.3%
4 10
13.0%
0 9
11.7%
2 8
10.4%
6 6
7.8%
5 6
7.8%
3 6
7.8%
9 5
6.5%
, 4
 
5.2%
8 3
 
3.9%
Other values (5) 9
11.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
87.0%
Other Punctuation 4
 
5.2%
Dash Punctuation 3
 
3.9%
Other Letter 3
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 11
16.4%
4 10
14.9%
0 9
13.4%
2 8
11.9%
6 6
9.0%
5 6
9.0%
3 6
9.0%
9 5
7.5%
8 3
 
4.5%
7 3
 
4.5%
Other Letter
ValueCountFrequency (%)
봉 1
33.3%
선 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 11
14.9%
4 10
13.5%
0 9
12.2%
2 8
10.8%
6 6
8.1%
5 6
8.1%
3 6
8.1%
9 5
6.8%
, 4
 
5.4%
8 3
 
4.1%
Other values (2) 6
8.1%
Hangul
ValueCountFrequency (%)
봉 1
33.3%
선 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 11
14.9%
4 10
13.5%
0 9
12.2%
2 8
10.8%
6 6
8.1%
5 6
8.1%
3 6
8.1%
9 5
6.8%
, 4
 
5.4%
8 3
 
4.1%
Other values (2) 6
8.1%
Hangul
ValueCountFrequency (%)
봉 1
33.3%
선 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct28
Distinct (%)82.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:35:05.414351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4117647
Min length1

Characters and Unicode

Total characters82
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 row봉선2동
3rd row9,811
4th row27,957
5th row10
ValueCountFrequency (%)
0 7
 
20.0%
1
 
2.9%
204 1
 
2.9%
11 1
 
2.9%
27,924 1
 
2.9%
9,806 1
 
2.9%
1 1
 
2.9%
33 1
 
2.9%
5 1
 
2.9%
8 1
 
2.9%
Other values (19) 19
54.3%
2024-02-10T09:35:06.263548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
13.4%
1 10
12.2%
9 8
9.8%
6 7
8.5%
7 7
8.5%
5 6
7.3%
2 6
7.3%
8 5
 
6.1%
, 4
 
4.9%
4 4
 
4.9%
Other values (11) 14
17.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
81.7%
Other Letter 7
 
8.5%
Other Punctuation 5
 
6.1%
Dash Punctuation 2
 
2.4%
Space Separator 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.4%
1 10
14.9%
9 8
11.9%
6 7
10.4%
7 7
10.4%
5 6
9.0%
2 6
9.0%
8 5
7.5%
4 4
 
6.0%
3 3
 
4.5%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
선 1
14.3%
봉 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 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 75
91.5%
Hangul 7
 
8.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
14.7%
1 10
13.3%
9 8
10.7%
6 7
9.3%
7 7
9.3%
5 6
8.0%
2 6
8.0%
8 5
6.7%
, 4
 
5.3%
4 4
 
5.3%
Other values (4) 7
9.3%
Hangul
ValueCountFrequency (%)
동 1
14.3%
선 1
14.3%
봉 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 75
91.5%
Hangul 7
 
8.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
14.7%
1 10
13.3%
9 8
10.7%
6 7
9.3%
7 7
9.3%
5 6
8.0%
2 6
8.0%
8 5
6.7%
, 4
 
5.3%
4 4
 
5.3%
Other values (4) 7
9.3%
Hangul
ValueCountFrequency (%)
동 1
14.3%
선 1
14.3%
봉 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:06.751077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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 row사직동
2nd row2,836
3rd row4,848
4th row39
5th row6
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
6 2
 
6.1%
10 1
 
3.0%
23 1
 
3.0%
4,845 1
 
3.0%
2,840 1
 
3.0%
3 1
 
3.0%
1 1
 
3.0%
7 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:35:07.657156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.9%
4 9
13.4%
3 8
11.9%
8 7
10.4%
2 6
9.0%
5 6
9.0%
1 5
7.5%
6 4
 
6.0%
, 4
 
6.0%
7 2
 
3.0%
Other values (5) 6
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
86.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
17.2%
4 9
15.5%
3 8
13.8%
8 7
12.1%
2 6
10.3%
5 6
10.3%
1 5
8.6%
6 4
 
6.9%
7 2
 
3.4%
9 1
 
1.7%
Other Letter
ValueCountFrequency (%)
사 1
33.3%
직 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.6%
4 9
14.1%
3 8
12.5%
8 7
10.9%
2 6
9.4%
5 6
9.4%
1 5
7.8%
6 4
 
6.2%
, 4
 
6.2%
7 2
 
3.1%
Other values (2) 3
 
4.7%
Hangul
ValueCountFrequency (%)
사 1
33.3%
직 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.6%
4 9
14.1%
3 8
12.5%
8 7
10.9%
2 6
9.4%
5 6
9.4%
1 5
7.8%
6 4
 
6.2%
, 4
 
6.2%
7 2
 
3.1%
Other values (2) 3
 
4.7%
Hangul
ValueCountFrequency (%)
사 1
33.3%
직 1
33.3%
동 1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2023-05-11 00:00:00
Maximum2023-05-11 00:00:00
2024-02-10T09:35:08.011843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:35:08.392471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:08.704982image/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

Unique16 ?
Unique (%)48.5%

Sample

1st row월산동
2nd row4,553
3rd row8,774
4th row28
5th row7
ValueCountFrequency (%)
0 7
21.2%
31 2
 
6.1%
33 2
 
6.1%
28 2
 
6.1%
7 2
 
6.1%
3 2
 
6.1%
26 1
 
3.0%
64 1
 
3.0%
23 1
 
3.0%
4,545 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:35:09.696057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 12
17.6%
0 10
14.7%
4 8
11.8%
2 6
8.8%
7 6
8.8%
1 5
7.4%
8 5
7.4%
, 4
 
5.9%
5 4
 
5.9%
6 3
 
4.4%
Other values (4) 5
7.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
86.8%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 12
20.3%
0 10
16.9%
4 8
13.6%
2 6
10.2%
7 6
10.2%
1 5
8.5%
8 5
8.5%
5 4
 
6.8%
6 3
 
5.1%
Other Letter
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 12
18.5%
0 10
15.4%
4 8
12.3%
2 6
9.2%
7 6
9.2%
1 5
7.7%
8 5
7.7%
, 4
 
6.2%
5 4
 
6.2%
6 3
 
4.6%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 12
18.5%
0 10
15.4%
4 8
12.3%
2 6
9.2%
7 6
9.2%
1 5
7.7%
8 5
7.7%
, 4
 
6.2%
5 4
 
6.2%
6 3
 
4.6%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:10.063100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

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

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row월산4동
2nd row4,771
3rd row8,282
4th row30
5th row5
ValueCountFrequency (%)
0 9
27.3%
5 4
 
12.1%
30 2
 
6.1%
38 2
 
6.1%
18 1
 
3.0%
75 1
 
3.0%
4,776 1
 
3.0%
2 1
 
3.0%
22 1
 
3.0%
35 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:35:10.957557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.4%
7 9
13.4%
3 8
11.9%
2 8
11.9%
5 7
10.4%
8 6
9.0%
1 4
 
6.0%
4 4
 
6.0%
, 4
 
6.0%
6 2
 
3.0%
Other values (4) 4
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 59
88.1%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.6%
7 9
15.3%
3 8
13.6%
2 8
13.6%
5 7
11.9%
8 6
10.2%
1 4
 
6.8%
4 4
 
6.8%
6 2
 
3.4%
Other Letter
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.2%
7 9
14.1%
3 8
12.5%
2 8
12.5%
5 7
10.9%
8 6
9.4%
1 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
6 2
 
3.1%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.2%
7 9
14.1%
3 8
12.5%
2 8
12.5%
5 7
10.9%
8 6
9.4%
1 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
6 2
 
3.1%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:11.405129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row월산5동
2nd row3,487
3rd row6,135
4th row13
5th row4
ValueCountFrequency (%)
0 8
24.2%
13 2
 
6.1%
9 2
 
6.1%
4 2
 
6.1%
30 1
 
3.0%
6,135 1
 
3.0%
36 1
 
3.0%
3,484 1
 
3.0%
3 1
 
3.0%
2 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:35:12.248593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.9%
3 9
13.4%
1 7
10.4%
2 7
10.4%
4 5
7.5%
6 5
7.5%
5 5
7.5%
8 4
 
6.0%
, 4
 
6.0%
7 3
 
4.5%
Other values (5) 8
11.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 58
86.6%
Other Punctuation 4
 
6.0%
Other Letter 3
 
4.5%
Dash Punctuation 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
17.2%
3 9
15.5%
1 7
12.1%
2 7
12.1%
4 5
8.6%
6 5
8.6%
5 5
8.6%
8 4
 
6.9%
7 3
 
5.2%
9 3
 
5.2%
Other Letter
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.6%
3 9
14.1%
1 7
10.9%
2 7
10.9%
4 5
7.8%
6 5
7.8%
5 5
7.8%
8 4
 
6.2%
, 4
 
6.2%
7 3
 
4.7%
Other values (2) 5
7.8%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
15.6%
3 9
14.1%
1 7
10.9%
2 7
10.9%
4 5
7.8%
6 5
7.8%
5 5
7.8%
8 4
 
6.2%
, 4
 
6.2%
7 3
 
4.7%
Other values (2) 5
7.8%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:12.712817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
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

Unique22 ?
Unique (%)66.7%

Sample

1st row백운1동
2nd row5,162
3rd row11,850
4th row13
5th row14
ValueCountFrequency (%)
0 7
21.2%
5 2
 
6.1%
9 2
 
6.1%
14 2
 
6.1%
45 1
 
3.0%
13 1
 
3.0%
11,850 1
 
3.0%
11,841 1
 
3.0%
5,156 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:35:13.663634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
16.9%
5 9
12.7%
0 8
11.3%
2 7
9.9%
3 6
8.5%
4 5
7.0%
8 5
7.0%
9 4
 
5.6%
6 4
 
5.6%
, 4
 
5.6%
Other values (5) 7
9.9%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
19.4%
5 9
14.5%
0 8
12.9%
2 7
11.3%
3 6
9.7%
4 5
8.1%
8 5
8.1%
9 4
 
6.5%
6 4
 
6.5%
7 2
 
3.2%
Other Letter
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 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 (%)
1 12
17.6%
5 9
13.2%
0 8
11.8%
2 7
10.3%
3 6
8.8%
4 5
7.4%
8 5
7.4%
9 4
 
5.9%
6 4
 
5.9%
, 4
 
5.9%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
17.6%
5 9
13.2%
0 8
11.8%
2 7
10.3%
3 6
8.8%
4 5
7.4%
8 5
7.4%
9 4
 
5.9%
6 4
 
5.9%
, 4
 
5.9%
Other values (2) 4
 
5.9%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:14.060018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.030303
Min length1

Characters and Unicode

Total characters67
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

Unique24 ?
Unique (%)72.7%

Sample

1st row백운2동
2nd row3,334
3rd row6,330
4th row26
5th row3
ValueCountFrequency (%)
0 7
21.2%
3 2
 
6.1%
41 1
 
3.0%
6,337 1
 
3.0%
3,350 1
 
3.0%
1 1
 
3.0%
7 1
 
3.0%
16 1
 
3.0%
4 1
 
3.0%
19 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:35:14.878971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 16
23.9%
0 10
14.9%
2 7
10.4%
7 5
 
7.5%
4 5
 
7.5%
9 4
 
6.0%
, 4
 
6.0%
6 4
 
6.0%
1 4
 
6.0%
8 3
 
4.5%
Other values (4) 5
 
7.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 16
26.7%
0 10
16.7%
2 7
11.7%
7 5
 
8.3%
4 5
 
8.3%
9 4
 
6.7%
6 4
 
6.7%
1 4
 
6.7%
8 3
 
5.0%
5 2
 
3.3%
Other Letter
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
3 16
25.0%
0 10
15.6%
2 7
10.9%
7 5
 
7.8%
4 5
 
7.8%
9 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
1 4
 
6.2%
8 3
 
4.7%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 16
25.0%
0 10
15.6%
2 7
10.9%
7 5
 
7.8%
4 5
 
7.8%
9 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
1 4
 
6.2%
8 3
 
4.7%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:15.230957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3636364
Min length1

Characters and Unicode

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

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row주월1동
2nd row9,592
3rd row21,398
4th row19
5th row13
ValueCountFrequency (%)
0 7
21.2%
114 1
 
3.0%
109 1
 
3.0%
21 1
 
3.0%
21,361 1
 
3.0%
9,577 1
 
3.0%
2 1
 
3.0%
37 1
 
3.0%
15 1
 
3.0%
8 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:35:16.563482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.9%
0 9
11.5%
2 9
11.5%
9 8
10.3%
7 8
10.3%
8 6
7.7%
3 5
 
6.4%
, 4
 
5.1%
5 4
 
5.1%
6 4
 
5.1%
Other values (5) 7
9.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 69
88.5%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
20.3%
0 9
13.0%
2 9
13.0%
9 8
11.6%
7 8
11.6%
8 6
8.7%
3 5
 
7.2%
5 4
 
5.8%
6 4
 
5.8%
4 2
 
2.9%
Other Letter
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
18.7%
0 9
12.0%
2 9
12.0%
9 8
10.7%
7 8
10.7%
8 6
8.0%
3 5
 
6.7%
, 4
 
5.3%
5 4
 
5.3%
6 4
 
5.3%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
18.7%
0 9
12.0%
2 9
12.0%
9 8
10.7%
7 8
10.7%
8 6
8.0%
3 5
 
6.7%
, 4
 
5.3%
5 4
 
5.3%
6 4
 
5.3%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct19
Distinct (%)57.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:16.922083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique13 ?
Unique (%)39.4%

Sample

1st row주월2동
2nd row3,971
3rd row7,741
4th row28
5th row5
ValueCountFrequency (%)
0 8
24.2%
28 4
12.1%
22 2
 
6.1%
3 2
 
6.1%
31 2
 
6.1%
5 2
 
6.1%
주월2동 1
 
3.0%
56 1
 
3.0%
18 1
 
3.0%
16 1
 
3.0%
Other values (9) 9
27.3%
2024-02-10T09:35:17.842961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
18.6%
0 9
12.9%
3 8
11.4%
1 8
11.4%
7 7
10.0%
8 5
 
7.1%
5 4
 
5.7%
, 4
 
5.7%
4 3
 
4.3%
9 2
 
2.9%
Other values (5) 7
10.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 13
21.3%
0 9
14.8%
3 8
13.1%
1 8
13.1%
7 7
11.5%
8 5
 
8.2%
5 4
 
6.6%
4 3
 
4.9%
9 2
 
3.3%
6 2
 
3.3%
Other Letter
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
19.4%
0 9
13.4%
3 8
11.9%
1 8
11.9%
7 7
10.4%
8 5
 
7.5%
5 4
 
6.0%
, 4
 
6.0%
4 3
 
4.5%
9 2
 
3.0%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
19.4%
0 9
13.4%
3 8
11.9%
1 8
11.9%
7 7
10.4%
8 5
 
7.5%
5 4
 
6.0%
, 4
 
6.0%
4 3
 
4.5%
9 2
 
3.0%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:18.260293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
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 row진월동
2nd row11,392
3rd row28,377
4th row35
5th row26
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
35 2
 
6.1%
109 1
 
3.0%
209 1
 
3.0%
28,362 1
 
3.0%
11,407 1
 
3.0%
14 1
 
3.0%
85 1
 
3.0%
72 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:35:19.287772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.8%
0 13
16.2%
2 9
11.2%
5 7
8.8%
9 6
 
7.5%
8 6
 
7.5%
3 5
 
6.2%
7 5
 
6.2%
, 4
 
5.0%
6 4
 
5.0%
Other values (5) 6
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
90.0%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.8%
0 13
18.1%
2 9
12.5%
5 7
9.7%
9 6
 
8.3%
8 6
 
8.3%
3 5
 
6.9%
7 5
 
6.9%
6 4
 
5.6%
4 2
 
2.8%
Other Letter
ValueCountFrequency (%)
진 1
33.3%
월 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.5%
0 13
16.9%
2 9
11.7%
5 7
9.1%
9 6
 
7.8%
8 6
 
7.8%
3 5
 
6.5%
7 5
 
6.5%
, 4
 
5.2%
6 4
 
5.2%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
진 1
33.3%
월 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.5%
0 13
16.9%
2 9
11.7%
5 7
9.1%
9 6
 
7.8%
8 6
 
7.8%
3 5
 
6.5%
7 5
 
6.5%
, 4
 
5.2%
6 4
 
5.2%
Other values (2) 3
 
3.9%
Hangul
ValueCountFrequency (%)
진 1
33.3%
월 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:19.781019image/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 row효덕동
2nd row7,508
3rd row15,671
4th row10
5th row8
ValueCountFrequency (%)
0 8
24.2%
45 3
 
9.1%
10 2
 
6.1%
8 2
 
6.1%
3 2
 
6.1%
66 1
 
3.0%
7,468 1
 
3.0%
40 1
 
3.0%
46 1
 
3.0%
70 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:35:20.774136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.1%
1 8
11.1%
4 8
11.1%
6 8
11.1%
5 7
9.7%
8 5
 
6.9%
3 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
9 3
 
4.2%
Other values (5) 8
11.1%

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 (%)
0 13
20.6%
1 8
12.7%
4 8
12.7%
6 8
12.7%
5 7
11.1%
8 5
 
7.9%
3 4
 
6.3%
7 4
 
6.3%
9 3
 
4.8%
2 3
 
4.8%
Other Letter
ValueCountFrequency (%)
효 1
33.3%
덕 1
33.3%
동 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 (%)
0 13
18.8%
1 8
11.6%
4 8
11.6%
6 8
11.6%
5 7
10.1%
8 5
 
7.2%
3 4
 
5.8%
7 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
 
7.2%
Hangul
ValueCountFrequency (%)
효 1
33.3%
덕 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.8%
1 8
11.6%
4 8
11.6%
6 8
11.6%
5 7
10.1%
8 5
 
7.2%
3 4
 
5.8%
7 4
 
5.8%
, 4
 
5.8%
9 3
 
4.3%
Other values (2) 5
 
7.2%
Hangul
ValueCountFrequency (%)
효 1
33.3%
덕 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:21.088019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1515152
Min length1

Characters and Unicode

Total characters71
Distinct characters14
Distinct 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 row송암동
2nd row8,630
3rd row21,227
4th row12
5th row7
ValueCountFrequency (%)
0 7
21.2%
2 2
 
6.1%
21,227 2
 
6.1%
7 2
 
6.1%
87 2
 
6.1%
12 1
 
3.0%
192 1
 
3.0%
8,636 1
 
3.0%
6 1
 
3.0%
5 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:35:21.911792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.1%
2 10
14.1%
1 9
12.7%
8 8
11.3%
7 8
11.3%
6 7
9.9%
, 4
 
5.6%
9 4
 
5.6%
4 3
 
4.2%
3 3
 
4.2%
Other values (4) 5
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
90.1%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.6%
2 10
15.6%
1 9
14.1%
8 8
12.5%
7 8
12.5%
6 7
10.9%
9 4
 
6.2%
4 3
 
4.7%
3 3
 
4.7%
5 2
 
3.1%
Other Letter
ValueCountFrequency (%)
송 1
33.3%
암 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.7%
2 10
14.7%
1 9
13.2%
8 8
11.8%
7 8
11.8%
6 7
10.3%
, 4
 
5.9%
9 4
 
5.9%
4 3
 
4.4%
3 3
 
4.4%
Hangul
ValueCountFrequency (%)
송 1
33.3%
암 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
14.7%
2 10
14.7%
1 9
13.2%
8 8
11.8%
7 8
11.8%
6 7
10.3%
, 4
 
5.9%
9 4
 
5.9%
4 3
 
4.4%
3 3
 
4.4%
Hangul
ValueCountFrequency (%)
송 1
33.3%
암 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:35:22.246650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

Total characters65
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row대촌동
2nd row4,112
3rd row8,194
4th row5
5th row4
ValueCountFrequency (%)
0 8
24.2%
5 3
 
9.1%
4 2
 
6.1%
18 2
 
6.1%
10 2
 
6.1%
16 1
 
3.0%
8 1
 
3.0%
4,106 1
 
3.0%
6 1
 
3.0%
19 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:35:23.424721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.5%
0 11
16.9%
4 7
10.8%
5 5
 
7.7%
8 5
 
7.7%
, 4
 
6.2%
2 4
 
6.2%
9 4
 
6.2%
6 4
 
6.2%
3 3
 
4.6%
Other values (4) 4
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
87.7%
Other Punctuation 4
 
6.2%
Other Letter 3
 
4.6%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
24.6%
0 11
19.3%
4 7
12.3%
5 5
 
8.8%
8 5
 
8.8%
2 4
 
7.0%
9 4
 
7.0%
6 4
 
7.0%
3 3
 
5.3%
Other Letter
ValueCountFrequency (%)
대 1
33.3%
촌 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
22.6%
0 11
17.7%
4 7
11.3%
5 5
 
8.1%
8 5
 
8.1%
, 4
 
6.5%
2 4
 
6.5%
9 4
 
6.5%
6 4
 
6.5%
3 3
 
4.8%
Hangul
ValueCountFrequency (%)
대 1
33.3%
촌 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
22.6%
0 11
17.7%
4 7
11.3%
5 5
 
8.1%
8 5
 
8.1%
, 4
 
6.5%
2 4
 
6.5%
9 4
 
6.5%
6 4
 
6.5%
3 3
 
4.8%
Hangul
ValueCountFrequency (%)
대 1
33.3%
촌 1
33.3%
동 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: 23
0<NA>행정기관 :<NA>광주광역시 남구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2023.05.11<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2023.04 현재<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 계양림동방림1동방림2동봉선1동봉선2동사직동<NA>월산동월산4동월산5동백운1동백운2동주월1동주월2동진월동효덕동송암동대촌동
3<NA>전월말세대수<NA><NA><NA>95,7783,1153,0343,9626,5089,8112,836<NA>4,5534,7713,4875,1623,3349,5923,97111,3927,5088,6304,112
4<NA>전월말인구수<NA><NA><NA>211,5636,7256,6778,43812,93927,9574,848<NA>8,7748,2826,13511,8506,33021,3987,74128,37715,67121,2278,194
5<NA>전월말거주불명자수<NA><NA><NA>354151117431039<NA>283013132619283510125
6<NA>전월말재외국민등록자수<NA><NA><NA>151771010156<NA>75414313526874
7<NA>증 가 요 인전 입계<NA>1,65043924512617258<NA>6472577388187561989117751
8<NA><NA><NA>남자<NA>817244428737634<NA>3334253943972891399118
9<NA><NA><NA>여자<NA>833194817539624<NA>31383234459028107528633
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: 23
25<NA><NA>말소<NA><NA>3000101<NA>10000000000
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>0000000<NA>00000000000
28<NA>세대수증감<NA><NA><NA>-61-523-15-13-54<NA>-85-3-616-15-1415-406-6
29<NA>인구수증감<NA><NA><NA>-234-726-55-24-33-3<NA>-10-5-9-97-37-20-15-4505
30<NA>거주불명자수증감<NA><NA><NA>5000-21-4<NA>00021230020
31<NA>금월말세대수<NA><NA><NA>95,7173,1103,0573,9476,4959,8062,840<NA>4,5454,7763,4845,1563,3509,5773,95711,4077,4688,6364,106
32<NA>금월말인구수<NA><NA><NA>211,3296,7186,7038,38312,91527,9244,845<NA>8,7648,2776,12611,8416,33721,3617,72128,36215,62621,2278,199
33<NA>금월말거주불명자수<NA><NA><NA>359151117411135<NA>283013152721313510145
34<NA>금월말재외국민등록자수<NA><NA><NA>154771010176<NA>75414312528874

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: 23# duplicates
0<NA>국외<NA><NA>0000000<NA>000000000002
1<NA>기타<NA><NA>0000000<NA>000000000002