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

Description2022-06-15
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 09:28:47.385098
Analysis finished2024-02-10 09:28:48.708271
Duration1.32 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
2024-02-10T09:28:49.019146image/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%
2024-02-10T09:28:50.138821image/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
2024-02-10T09:28:50.542179image/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%
2024-02-10T09:28:51.545633image/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
2024-02-10T09:28:52.256454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

Total characters41
Distinct characters19
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 row2022.05 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%
2022.05 1
7.1%
현재 1
7.1%
2024-02-10T09:28:53.185910image/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%
2 3
 
7.3%
계 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
Other values (9) 11
26.8%

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 3
50.0%
0 2
33.3%
5 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 3
30.0%
0 2
20.0%
. 1
 
10.0%
5 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 3
30.0%
0 2
20.0%
. 1
 
10.0%
5 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T09:28:53.615149image/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%
2024-02-10T09:28:54.351135image/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 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:54.928372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.4242424
Min length1

Characters and Unicode

Total characters113
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

Unique23 ?
Unique (%)69.7%

Sample

1st row합 계
2nd row96,146
3rd row214,848
4th row537
5th row153
ValueCountFrequency (%)
0 6
 
17.6%
815 2
 
5.9%
153 2
 
5.9%
1,172 1
 
2.9%
2,387 1
 
2.9%
215,251 1
 
2.9%
96,486 1
 
2.9%
4 1
 
2.9%
403 1
 
2.9%
340 1
 
2.9%
Other values (17) 17
50.0%
2024-02-10T09:28:55.850256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 22
19.5%
3 11
9.7%
, 11
9.7%
2 11
9.7%
0 9
8.0%
5 9
8.0%
8 9
8.0%
4 8
 
7.1%
6 7
 
6.2%
7 6
 
5.3%
Other values (5) 10
8.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 97
85.8%
Other Punctuation 11
 
9.7%
Space Separator 2
 
1.8%
Other Letter 2
 
1.8%
Dash Punctuation 1
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 22
22.7%
3 11
11.3%
2 11
11.3%
0 9
9.3%
5 9
9.3%
8 9
9.3%
4 8
 
8.2%
6 7
 
7.2%
7 6
 
6.2%
9 5
 
5.2%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 111
98.2%
Hangul 2
 
1.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 22
19.8%
3 11
9.9%
, 11
9.9%
2 11
9.9%
0 9
8.1%
5 9
8.1%
8 9
8.1%
4 8
 
7.2%
6 7
 
6.3%
7 6
 
5.4%
Other values (3) 8
 
7.2%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 111
98.2%
Hangul 2
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 22
19.8%
3 11
9.9%
, 11
9.9%
2 11
9.9%
0 9
8.1%
5 9
8.1%
8 9
8.1%
4 8
 
7.2%
6 7
 
6.3%
7 6
 
5.4%
Other values (3) 8
 
7.2%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:56.196980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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 row양림동
2nd row3,160
3rd row6,950
4th row21
5th row5
ValueCountFrequency (%)
0 8
24.2%
2 3
 
9.1%
21 3
 
9.1%
5 2
 
6.1%
25 2
 
6.1%
양림동 1
 
3.0%
70 1
 
3.0%
3,158 1
 
3.0%
28 1
 
3.0%
33 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:28:57.006309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 13
19.1%
0 11
16.2%
1 8
11.8%
5 6
8.8%
3 6
8.8%
, 4
 
5.9%
9 4
 
5.9%
6 3
 
4.4%
4 3
 
4.4%
7 3
 
4.4%
Other values (5) 7
10.3%

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 (%)
2 13
22.0%
0 11
18.6%
1 8
13.6%
5 6
10.2%
3 6
10.2%
9 4
 
6.8%
6 3
 
5.1%
4 3
 
5.1%
7 3
 
5.1%
8 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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 13
20.0%
0 11
16.9%
1 8
12.3%
5 6
9.2%
3 6
9.2%
, 4
 
6.2%
9 4
 
6.2%
6 3
 
4.6%
4 3
 
4.6%
7 3
 
4.6%
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 13
20.0%
0 11
16.9%
1 8
12.3%
5 6
9.2%
3 6
9.2%
, 4
 
6.2%
9 4
 
6.2%
6 3
 
4.6%
4 3
 
4.6%
7 3
 
4.6%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
양 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 7
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:57.506620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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 row방림1동
2nd row2,927
3rd row6,563
4th row19
5th row7
ValueCountFrequency (%)
0 6
18.2%
1 3
 
9.1%
7 3
 
9.1%
20 2
 
6.1%
25 2
 
6.1%
3 1
 
3.0%
58 1
 
3.0%
19 1
 
3.0%
6,549 1
 
3.0%
2,934 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T09:28:58.398991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
14.5%
1 9
13.0%
0 8
11.6%
3 8
11.6%
5 6
8.7%
7 5
7.2%
9 5
7.2%
6 4
 
5.8%
, 4
 
5.8%
4 3
 
4.3%
Other values (5) 7
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
16.7%
1 9
15.0%
0 8
13.3%
3 8
13.3%
5 6
10.0%
7 5
8.3%
9 5
8.3%
6 4
 
6.7%
4 3
 
5.0%
8 2
 
3.3%
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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
15.2%
1 9
13.6%
0 8
12.1%
3 8
12.1%
5 6
9.1%
7 5
7.6%
9 5
7.6%
6 4
 
6.1%
, 4
 
6.1%
4 3
 
4.5%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
15.2%
1 9
13.6%
0 8
12.1%
3 8
12.1%
5 6
9.1%
7 5
7.6%
9 5
7.6%
6 4
 
6.1%
, 4
 
6.1%
4 3
 
4.5%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:28:58.793430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
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

Unique21 ?
Unique (%)63.6%

Sample

1st row방림2동
2nd row4,060
3rd row8,764
4th row36
5th row10
ValueCountFrequency (%)
0 8
24.2%
36 2
 
6.1%
10 2
 
6.1%
14 1
 
3.0%
8,764 1
 
3.0%
29 1
 
3.0%
4,053 1
 
3.0%
12 1
 
3.0%
7 1
 
3.0%
8 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:28:59.825288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
21.1%
3 9
12.7%
2 9
12.7%
6 7
9.9%
4 6
 
8.5%
1 5
 
7.0%
5 4
 
5.6%
, 4
 
5.6%
8 3
 
4.2%
7 3
 
4.2%
Other values (5) 6
 
8.5%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
24.2%
3 9
14.5%
2 9
14.5%
6 7
11.3%
4 6
 
9.7%
1 5
 
8.1%
5 4
 
6.5%
8 3
 
4.8%
7 3
 
4.8%
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%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
22.1%
3 9
13.2%
2 9
13.2%
6 7
10.3%
4 6
 
8.8%
1 5
 
7.4%
5 4
 
5.9%
, 4
 
5.9%
8 3
 
4.4%
7 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 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 15
22.1%
3 9
13.2%
2 9
13.2%
6 7
10.3%
4 6
 
8.8%
1 5
 
7.4%
5 4
 
5.9%
, 4
 
5.9%
8 3
 
4.4%
7 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
방 1
33.3%
림 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:00.159109image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row봉선1동
2nd row6,683
3rd row13,382
4th row47
5th row11
ValueCountFrequency (%)
0 7
21.2%
11 2
 
6.1%
47 2
 
6.1%
71 2
 
6.1%
3 2
 
6.1%
61 1
 
3.0%
13,382 1
 
3.0%
124 1
 
3.0%
6,647 1
 
3.0%
36 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:29:01.079246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 18
23.1%
0 9
11.5%
3 9
11.5%
4 7
 
9.0%
6 7
 
9.0%
7 6
 
7.7%
8 5
 
6.4%
, 4
 
5.1%
5 3
 
3.8%
2 3
 
3.8%
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 18
26.1%
0 9
13.0%
3 9
13.0%
4 7
 
10.1%
6 7
 
10.1%
7 6
 
8.7%
8 5
 
7.2%
5 3
 
4.3%
2 3
 
4.3%
9 2
 
2.9%
Other Letter
ValueCountFrequency (%)
봉 1
33.3%
선 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 18
24.0%
0 9
12.0%
3 9
12.0%
4 7
 
9.3%
6 7
 
9.3%
7 6
 
8.0%
8 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
2 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
봉 1
33.3%
선 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 18
24.0%
0 9
12.0%
3 9
12.0%
4 7
 
9.3%
6 7
 
9.3%
7 6
 
8.0%
8 5
 
6.7%
, 4
 
5.3%
5 3
 
4.0%
2 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
봉 1
33.3%
선 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct25
Distinct (%)73.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T09:29:01.570695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique22 ?
Unique (%)64.7%

Sample

1st row출력일자 :
2nd row봉선2동
3rd row10,015
4th row28,765
5th row26
ValueCountFrequency (%)
0 8
22.9%
26 2
 
5.7%
17 2
 
5.7%
294 1
 
2.9%
7 1
 
2.9%
9,988 1
 
2.9%
104 1
 
2.9%
27 1
 
2.9%
8 1
 
2.9%
121 1
 
2.9%
Other values (16) 16
45.7%
2024-02-10T09:29:02.710366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
14.9%
0 11
12.6%
7 9
10.3%
2 9
10.3%
8 8
9.2%
9 7
8.0%
6 6
6.9%
4 4
 
4.6%
5 4
 
4.6%
, 4
 
4.6%
Other values (11) 12
13.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
82.8%
Other Letter 7
 
8.0%
Other Punctuation 5
 
5.7%
Dash Punctuation 2
 
2.3%
Space Separator 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
18.1%
0 11
15.3%
7 9
12.5%
2 9
12.5%
8 8
11.1%
9 7
9.7%
6 6
8.3%
4 4
 
5.6%
5 4
 
5.6%
3 1
 
1.4%
Other Letter
ValueCountFrequency (%)
봉 1
14.3%
선 1
14.3%
동 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
출 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 80
92.0%
Hangul 7
 
8.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
16.2%
0 11
13.8%
7 9
11.2%
2 9
11.2%
8 8
10.0%
9 7
8.8%
6 6
7.5%
4 4
 
5.0%
5 4
 
5.0%
, 4
 
5.0%
Other values (4) 5
 
6.2%
Hangul
ValueCountFrequency (%)
봉 1
14.3%
선 1
14.3%
동 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
출 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%
0 11
13.8%
7 9
11.2%
2 9
11.2%
8 8
10.0%
9 7
8.8%
6 6
7.5%
4 4
 
5.0%
5 4
 
5.0%
, 4
 
5.0%
Other values (4) 5
 
6.2%
Hangul
ValueCountFrequency (%)
봉 1
14.3%
선 1
14.3%
동 1
14.3%
자 1
14.3%
일 1
14.3%
력 1
14.3%
출 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:03.135237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.030303
Min length1

Characters and Unicode

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

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row사직동
2nd row2,952
3rd row5,144
4th row52
5th row6
ValueCountFrequency (%)
0 9
27.3%
33 2
 
6.1%
52 2
 
6.1%
6 2
 
6.1%
2,952 2
 
6.1%
75 1
 
3.0%
3 1
 
3.0%
23 1
 
3.0%
31 1
 
3.0%
21 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T09:29:04.097156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
16.4%
2 11
16.4%
1 10
14.9%
5 8
11.9%
3 7
10.4%
4 6
9.0%
, 4
 
6.0%
9 3
 
4.5%
6 2
 
3.0%
사 1
 
1.5%
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%
2 11
18.6%
1 10
16.9%
5 8
13.6%
3 7
11.9%
4 6
10.2%
9 3
 
5.1%
6 2
 
3.4%
7 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 (%)
- 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%
2 11
17.2%
1 10
15.6%
5 8
12.5%
3 7
10.9%
4 6
9.4%
, 4
 
6.2%
9 3
 
4.7%
6 2
 
3.1%
- 1
 
1.6%
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 11
17.2%
2 11
17.2%
1 10
15.6%
5 8
12.5%
3 7
10.9%
4 6
9.4%
, 4
 
6.2%
9 3
 
4.7%
6 2
 
3.1%
- 1
 
1.6%
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
Minimum2022-06-15 00:00:00
Maximum2022-06-15 00:00:00
2024-02-10T09:29:04.583909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T09:29:04.868441image/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
2024-02-10T09:29:05.455987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
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 row월산동
2nd row4,618
3rd row8,960
4th row49
5th row6
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
6 2
 
6.1%
77 1
 
3.0%
38 1
 
3.0%
48 1
 
3.0%
8,975 1
 
3.0%
4,623 1
 
3.0%
1 1
 
3.0%
15 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:29:06.372254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
14.7%
1 7
10.3%
5 7
10.3%
6 6
8.8%
9 6
8.8%
4 6
8.8%
8 6
8.8%
7 5
7.4%
3 4
 
5.9%
, 4
 
5.9%
Other values (5) 7
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
88.2%
Other Punctuation 4
 
5.9%
Other Letter 3
 
4.4%
Dash Punctuation 1
 
1.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
1 7
11.7%
5 7
11.7%
6 6
10.0%
9 6
10.0%
4 6
10.0%
8 6
10.0%
7 5
8.3%
3 4
 
6.7%
2 3
 
5.0%
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
15.4%
1 7
10.8%
5 7
10.8%
6 6
9.2%
9 6
9.2%
4 6
9.2%
8 6
9.2%
7 5
7.7%
3 4
 
6.2%
, 4
 
6.2%
Other values (2) 4
 
6.2%
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 (%)
0 10
15.4%
1 7
10.8%
5 7
10.8%
6 6
9.2%
9 6
9.2%
4 6
9.2%
8 6
9.2%
7 5
7.7%
3 4
 
6.2%
, 4
 
6.2%
Other values (2) 4
 
6.2%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:06.736817image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row월산4동
2nd row4,826
3rd row8,509
4th row43
5th row5
ValueCountFrequency (%)
0 7
21.2%
5 3
 
9.1%
56 1
 
3.0%
67 1
 
3.0%
8,496 1
 
3.0%
4,821 1
 
3.0%
1 1
 
3.0%
13 1
 
3.0%
9 1
 
3.0%
24 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T09:29:07.630006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
86.1%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 9
14.5%
5 8
12.9%
1 7
11.3%
2 7
11.3%
4 7
11.3%
3 6
9.7%
6 6
9.7%
8 5
8.1%
9 4
6.5%
7 3
 
4.8%
Other Letter
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 9
13.0%
5 8
11.6%
1 7
10.1%
2 7
10.1%
4 7
10.1%
3 6
8.7%
6 6
8.7%
8 5
7.2%
, 4
5.8%
9 4
5.8%
Other values (2) 6
8.7%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 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 9
13.0%
5 8
11.6%
1 7
10.1%
2 7
10.1%
4 7
10.1%
3 6
8.7%
6 6
8.7%
8 5
7.2%
, 4
5.8%
9 4
5.8%
Other values (2) 6
8.7%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:07.999315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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 row월산5동
2nd row3,550
3rd row6,369
4th row22
5th row4
ValueCountFrequency (%)
0 8
24.2%
4 2
 
6.1%
22 2
 
6.1%
34 2
 
6.1%
32 1
 
3.0%
6,369 1
 
3.0%
51 1
 
3.0%
3,549 1
 
3.0%
19 1
 
3.0%
1 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:29:08.896703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
17.4%
3 10
14.5%
2 9
13.0%
5 7
10.1%
1 6
8.7%
4 5
7.2%
6 5
7.2%
, 4
 
5.8%
9 4
 
5.8%
- 2
 
2.9%
Other values (5) 5
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
20.0%
3 10
16.7%
2 9
15.0%
5 7
11.7%
1 6
10.0%
4 5
8.3%
6 5
8.3%
9 4
 
6.7%
8 1
 
1.7%
7 1
 
1.7%
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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
18.2%
3 10
15.2%
2 9
13.6%
5 7
10.6%
1 6
9.1%
4 5
7.6%
6 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
- 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
18.2%
3 10
15.2%
2 9
13.6%
5 7
10.6%
1 6
9.1%
4 5
7.6%
6 5
7.6%
, 4
 
6.1%
9 4
 
6.1%
- 2
 
3.0%
Other values (2) 2
 
3.0%
Hangul
ValueCountFrequency (%)
월 1
33.3%
산 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:09.408124image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row백운1동
2nd row5,186
3rd row12,127
4th row21
5th row15
ValueCountFrequency (%)
0 7
21.2%
15 2
 
6.1%
21 2
 
6.1%
40 2
 
6.1%
54 1
 
3.0%
12,127 1
 
3.0%
103 1
 
3.0%
5,189 1
 
3.0%
5 1
 
3.0%
3 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:29:10.181483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
20.5%
0 13
17.8%
5 10
13.7%
2 9
12.3%
4 5
 
6.8%
3 5
 
6.8%
, 4
 
5.5%
8 3
 
4.1%
6 2
 
2.7%
9 2
 
2.7%
Other values (5) 5
 
6.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
89.0%
Other Punctuation 4
 
5.5%
Other Letter 3
 
4.1%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
23.1%
0 13
20.0%
5 10
15.4%
2 9
13.8%
4 5
 
7.7%
3 5
 
7.7%
8 3
 
4.6%
6 2
 
3.1%
9 2
 
3.1%
7 1
 
1.5%
Other Letter
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
21.4%
0 13
18.6%
5 10
14.3%
2 9
12.9%
4 5
 
7.1%
3 5
 
7.1%
, 4
 
5.7%
8 3
 
4.3%
6 2
 
2.9%
9 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
21.4%
0 13
18.6%
5 10
14.3%
2 9
12.9%
4 5
 
7.1%
3 5
 
7.1%
, 4
 
5.7%
8 3
 
4.3%
6 2
 
2.9%
9 2
 
2.9%
Other values (2) 2
 
2.9%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:10.503234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters12
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)42.4%

Sample

1st row백운2동
2nd row3,344
3rd row6,336
4th row26
5th row2
ValueCountFrequency (%)
0 8
24.2%
2 3
 
9.1%
28 2
 
6.1%
32 2
 
6.1%
26 2
 
6.1%
6,336 2
 
6.1%
3 1
 
3.0%
87 1
 
3.0%
37 1
 
3.0%
50 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T09:29:11.427856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 13
19.7%
2 12
18.2%
0 11
16.7%
6 8
12.1%
8 5
 
7.6%
4 5
 
7.6%
, 4
 
6.1%
5 3
 
4.5%
7 2
 
3.0%
백 1
 
1.5%
Other values (2) 2
 
3.0%

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 13
22.0%
2 12
20.3%
0 11
18.6%
6 8
13.6%
8 5
 
8.5%
4 5
 
8.5%
5 3
 
5.1%
7 2
 
3.4%
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 63
95.5%
Hangul 3
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
3 13
20.6%
2 12
19.0%
0 11
17.5%
6 8
12.7%
8 5
 
7.9%
4 5
 
7.9%
, 4
 
6.3%
5 3
 
4.8%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 13
20.6%
2 12
19.0%
0 11
17.5%
6 8
12.7%
8 5
 
7.9%
4 5
 
7.9%
, 4
 
6.3%
5 3
 
4.8%
7 2
 
3.2%
Hangul
ValueCountFrequency (%)
백 1
33.3%
운 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:11.922049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4848485
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row주월1동
2nd row9,736
3rd row22,031
4th row45
5th row14
ValueCountFrequency (%)
0 7
21.2%
97 2
 
6.1%
14 2
 
6.1%
13 2
 
6.1%
284 1
 
3.0%
139 1
 
3.0%
21,954 1
 
3.0%
9,722 1
 
3.0%
1 1
 
3.0%
77 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T09:29:12.645266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
18.3%
4 10
12.2%
0 9
11.0%
9 9
11.0%
7 7
8.5%
2 7
8.5%
3 5
 
6.1%
, 4
 
4.9%
5 4
 
4.9%
8 4
 
4.9%
Other values (5) 8
9.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
87.8%
Other Punctuation 4
 
4.9%
Dash Punctuation 3
 
3.7%
Other Letter 3
 
3.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
20.8%
4 10
13.9%
0 9
12.5%
9 9
12.5%
7 7
9.7%
2 7
9.7%
3 5
 
6.9%
5 4
 
5.6%
8 4
 
5.6%
6 2
 
2.8%
Other Letter
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
19.0%
4 10
12.7%
0 9
11.4%
9 9
11.4%
7 7
8.9%
2 7
8.9%
3 5
 
6.3%
, 4
 
5.1%
5 4
 
5.1%
8 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
19.0%
4 10
12.7%
0 9
11.4%
9 9
11.4%
7 7
8.9%
2 7
8.9%
3 5
 
6.3%
, 4
 
5.1%
5 4
 
5.1%
8 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:12.996457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.0909091
Min length1

Characters and Unicode

Total characters69
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 row주월2동
2nd row4,061
3rd row7,982
4th row32
5th row6
ValueCountFrequency (%)
0 8
24.2%
32 2
 
6.1%
22 2
 
6.1%
6 2
 
6.1%
36 1
 
3.0%
7,982 1
 
3.0%
50 1
 
3.0%
4,053 1
 
3.0%
8 1
 
3.0%
3 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:29:13.948108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.8%
3 10
14.5%
2 10
14.5%
6 8
11.6%
7 5
 
7.2%
9 4
 
5.8%
4 4
 
5.8%
, 4
 
5.8%
1 2
 
2.9%
- 2
 
2.9%
Other values (5) 7
10.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 60
87.0%
Other Punctuation 4
 
5.8%
Other Letter 3
 
4.3%
Dash Punctuation 2
 
2.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
21.7%
3 10
16.7%
2 10
16.7%
6 8
13.3%
7 5
 
8.3%
9 4
 
6.7%
4 4
 
6.7%
1 2
 
3.3%
8 2
 
3.3%
5 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 66
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
19.7%
3 10
15.2%
2 10
15.2%
6 8
12.1%
7 5
 
7.6%
9 4
 
6.1%
4 4
 
6.1%
, 4
 
6.1%
1 2
 
3.0%
- 2
 
3.0%
Other values (2) 4
 
6.1%
Hangul
ValueCountFrequency (%)
주 1
33.3%
월 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 66
95.7%
Hangul 3
 
4.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
19.7%
3 10
15.2%
2 10
15.2%
6 8
12.1%
7 5
 
7.6%
9 4
 
6.1%
4 4
 
6.1%
, 4
 
6.1%
1 2
 
3.0%
- 2
 
3.0%
Other values (2) 4
 
6.1%
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
2024-02-10T09:29:14.278125image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row진월동
2nd row11,470
3rd row29,034
4th row52
5th row26
ValueCountFrequency (%)
0 7
21.2%
52 2
 
6.1%
275 1
 
3.0%
28,948 1
 
3.0%
11,457 1
 
3.0%
86 1
 
3.0%
13 1
 
3.0%
10 1
 
3.0%
104 1
 
3.0%
75 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:29:15.177683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
17.1%
1 13
15.9%
4 10
12.2%
5 7
8.5%
2 7
8.5%
7 5
 
6.1%
9 5
 
6.1%
8 5
 
6.1%
, 4
 
4.9%
6 4
 
4.9%
Other values (5) 8
9.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
19.2%
1 13
17.8%
4 10
13.7%
5 7
9.6%
2 7
9.6%
7 5
 
6.8%
9 5
 
6.8%
8 5
 
6.8%
6 4
 
5.5%
3 3
 
4.1%
Other Letter
ValueCountFrequency (%)
진 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 79
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
17.7%
1 13
16.5%
4 10
12.7%
5 7
8.9%
2 7
8.9%
7 5
 
6.3%
9 5
 
6.3%
8 5
 
6.3%
, 4
 
5.1%
6 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
진 1
33.3%
월 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 14
17.7%
1 13
16.5%
4 10
12.7%
5 7
8.9%
2 7
8.9%
7 5
 
6.3%
9 5
 
6.3%
8 5
 
6.3%
, 4
 
5.1%
6 4
 
5.1%
Other values (2) 5
 
6.3%
Hangul
ValueCountFrequency (%)
진 1
33.3%
월 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:15.610234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique21 ?
Unique (%)63.6%

Sample

1st row효덕동
2nd row7,523
3rd row16,012
4th row2
5th row9
ValueCountFrequency (%)
0 8
24.2%
2 3
 
9.1%
9 2
 
6.1%
108 1
 
3.0%
16,012 1
 
3.0%
98 1
 
3.0%
7,547 1
 
3.0%
24 1
 
3.0%
5 1
 
3.0%
41 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T09:29:16.481698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 14
20.0%
9 10
14.3%
1 9
12.9%
2 6
8.6%
4 6
8.6%
5 5
 
7.1%
7 4
 
5.7%
, 4
 
5.7%
3 3
 
4.3%
6 3
 
4.3%
Other values (5) 6
8.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 14
22.6%
9 10
16.1%
1 9
14.5%
2 6
9.7%
4 6
9.7%
5 5
 
8.1%
7 4
 
6.5%
3 3
 
4.8%
6 3
 
4.8%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
효 1
33.3%
덕 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 14
20.9%
9 10
14.9%
1 9
13.4%
2 6
9.0%
4 6
9.0%
5 5
 
7.5%
7 4
 
6.0%
, 4
 
6.0%
3 3
 
4.5%
6 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
효 1
33.3%
덕 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 (%)
0 14
20.9%
9 10
14.9%
1 9
13.4%
2 6
9.0%
4 6
9.0%
5 5
 
7.5%
7 4
 
6.0%
, 4
 
6.0%
3 3
 
4.5%
6 3
 
4.5%
Other values (2) 3
 
4.5%
Hangul
ValueCountFrequency (%)
효 1
33.3%
덕 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:16.855835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3333333
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row송암동
2nd row8,622
3rd row21,446
4th row19
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
8 2
 
6.1%
4 1
 
3.0%
251 1
 
3.0%
18 1
 
3.0%
21,434 1
 
3.0%
8,630 1
 
3.0%
1 1
 
3.0%
12 1
 
3.0%
81 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T09:29:17.680936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.5%
8 12
15.6%
2 11
14.3%
0 9
11.7%
6 6
 
7.8%
4 5
 
6.5%
, 4
 
5.2%
7 3
 
3.9%
3 3
 
3.9%
9 2
 
2.6%
Other values (5) 7
9.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
88.3%
Other Punctuation 4
 
5.2%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
22.1%
8 12
17.6%
2 11
16.2%
0 9
13.2%
6 6
 
8.8%
4 5
 
7.4%
7 3
 
4.4%
3 3
 
4.4%
9 2
 
2.9%
5 2
 
2.9%
Other Letter
ValueCountFrequency (%)
송 1
33.3%
암 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.3%
8 12
16.2%
2 11
14.9%
0 9
12.2%
6 6
 
8.1%
4 5
 
6.8%
, 4
 
5.4%
7 3
 
4.1%
3 3
 
4.1%
9 2
 
2.7%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
송 1
33.3%
암 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 15
20.3%
8 12
16.2%
2 11
14.9%
0 9
12.2%
6 6
 
8.1%
4 5
 
6.8%
, 4
 
5.4%
7 3
 
4.1%
3 3
 
4.1%
9 2
 
2.7%
Other values (2) 4
 
5.4%
Hangul
ValueCountFrequency (%)
송 1
33.3%
암 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T09:29:18.139059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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

Unique23 ?
Unique (%)69.7%

Sample

1st row대촌동
2nd row3,413
3rd row6,474
4th row25
5th row3
ValueCountFrequency (%)
0 6
 
18.2%
7 2
 
6.1%
3 2
 
6.1%
14 1
 
3.0%
25 1
 
3.0%
31 1
 
3.0%
7,353 1
 
3.0%
3,811 1
 
3.0%
1 1
 
3.0%
879 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T09:29:19.056743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 14
18.4%
1 10
13.2%
4 9
11.8%
2 8
10.5%
0 6
7.9%
7 6
7.9%
5 5
 
6.6%
9 5
 
6.6%
8 4
 
5.3%
, 4
 
5.3%
Other values (5) 5
 
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 68
89.5%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 14
20.6%
1 10
14.7%
4 9
13.2%
2 8
11.8%
0 6
8.8%
7 6
8.8%
5 5
 
7.4%
9 5
 
7.4%
8 4
 
5.9%
6 1
 
1.5%
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 73
96.1%
Hangul 3
 
3.9%

Most frequent character per script

Common
ValueCountFrequency (%)
3 14
19.2%
1 10
13.7%
4 9
12.3%
2 8
11.0%
0 6
8.2%
7 6
8.2%
5 5
 
6.8%
9 5
 
6.8%
8 4
 
5.5%
, 4
 
5.5%
Other values (2) 2
 
2.7%
Hangul
ValueCountFrequency (%)
대 1
33.3%
촌 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 14
19.2%
1 10
13.7%
4 9
12.3%
2 8
11.0%
0 6
8.2%
7 6
8.2%
5 5
 
6.8%
9 5
 
6.8%
8 4
 
5.5%
, 4
 
5.5%
Other values (2) 2
 
2.7%
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>2022.06.15<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.05 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>96,1463,1602,9274,0606,68310,0152,952<NA>4,6184,8263,5505,1863,3449,7364,06111,4707,5238,6223,413
4<NA>전월말인구수<NA><NA><NA>214,8486,9506,5638,76413,38228,7655,144<NA>8,9608,5096,36912,1276,33622,0317,98229,03416,01221,4466,474
5<NA>전월말거주불명자수<NA><NA><NA>537211936472652<NA>494322212645325221925
6<NA>전월말재외국민등록자수<NA><NA><NA>153571011176<NA>65415214626973
7<NA>증 가 요 인전 입계<NA>2,81649585612419144<NA>96117631038721176194190226931
8<NA><NA><NA>남자<NA>1,423252526559725<NA>5157345037114399493108493
9<NA><NA><NA>여자<NA>1,393243330699419<NA>4560295350973710097118438
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>0000000<NA>00000000000
26<NA><NA>국외<NA><NA>0000000<NA>00000000000
27<NA><NA>기타<NA><NA>0000000<NA>00000000000
28<NA>세대수증감<NA><NA><NA>340-27-7-36-270<NA>5-5-138-14-8-13248398
29<NA>인구수증감<NA><NA><NA>403-21-14-12-71-104-33<NA>15-13-19-50-77-22-86-2-12879
30<NA>거주불명자수증감<NA><NA><NA>-40-10000<NA>-1-1002-1000-1-1
31<NA>금월말세대수<NA><NA><NA>96,4863,1582,9344,0536,6479,9882,952<NA>4,6234,8213,5495,1893,3529,7224,05311,4577,5478,6303,811
32<NA>금월말인구수<NA><NA><NA>215,2516,9296,5498,75213,31128,6615,111<NA>8,9758,4966,35012,1226,33621,9547,96028,94816,01021,4347,353
33<NA>금월말거주불명자수<NA><NA><NA>533211836472652<NA>484222212844325221824
34<NA>금월말재외국민등록자수<NA><NA><NA>153571011176<NA>75415213627963

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