Overview

Dataset statistics

Number of variables25
Number of observations35
Missing cells203
Missing cells (%)23.2%
Duplicate rows2
Duplicate rows (%)5.7%
Total size in memory7.0 KiB
Average record size in memory204.8 B

Variable types

Unsupported2
Text22
DateTime1

Dataset

Description2022-05-19
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201928

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: 24 has 2 (5.7%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-02-10 07:12:05.212802
Analysis finished2024-02-10 07:12:06.458412
Duration1.25 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
2024-02-10T07:12:06.746016image/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%
2024-02-10T07:12:07.834452image/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
2024-02-10T07:12:08.252411image/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%
2024-02-10T07:12:09.278907image/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
2024-02-10T07:12:09.823951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length3.4166667
Min length1

Characters and Unicode

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

Unique

Unique2 ?
Unique (%)16.7%

Sample

1st row광주광역시 서구
2nd row2022.04 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%
서구 1
7.1%
2022.04 1
7.1%
현재 1
7.1%
2024-02-10T07:12:10.781637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
12.2%
자 4
 
9.8%
도 4
 
9.8%
3
 
7.3%
2 3
 
7.3%
계 2
 
4.9%
0 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 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%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
0 2
33.3%
4 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%
계 2
 
6.5%
여 2
 
6.5%
내 2
 
6.5%
간 2
 
6.5%
광 2
 
6.5%
남 2
 
6.5%
현 1
 
3.2%
Other values (5) 5
16.1%
Common
ValueCountFrequency (%)
3
30.0%
2 3
30.0%
0 2
20.0%
4 1
 
10.0%
. 1
 
10.0%

Most occurring blocks

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

Most frequent character per block

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

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:12:11.094766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

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

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row시군구내
2nd row시군구간
3rd row시군구내
4th row시군구간
ValueCountFrequency (%)
시군구내 2
50.0%
시군구간 2
50.0%
2024-02-10T07:12:12.200241image/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
2024-02-10T07:12:12.581136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.6363636
Min length1

Characters and Unicode

Total characters120
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 row133,049
3rd row289,789
4th row938
5th row141
ValueCountFrequency (%)
0 5
 
14.7%
906 2
 
5.9%
1,589 1
 
2.9%
1,617 1
 
2.9%
927 1
 
2.9%
289,341 1
 
2.9%
133,103 1
 
2.9%
11 1
 
2.9%
448 1
 
2.9%
54 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T07:12:13.527197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 25
20.8%
0 14
11.7%
, 13
10.8%
8 13
10.8%
4 11
9.2%
9 10
 
8.3%
3 9
 
7.5%
2 7
 
5.8%
6 5
 
4.2%
5 4
 
3.3%
Other values (5) 9
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 101
84.2%
Other Punctuation 13
 
10.8%
Space Separator 2
 
1.7%
Dash Punctuation 2
 
1.7%
Other Letter 2
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
24.8%
0 14
13.9%
8 13
12.9%
4 11
10.9%
9 10
 
9.9%
3 9
 
8.9%
2 7
 
6.9%
6 5
 
5.0%
5 4
 
4.0%
7 3
 
3.0%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 13
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 118
98.3%
Hangul 2
 
1.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 25
21.2%
0 14
11.9%
, 13
11.0%
8 13
11.0%
4 11
9.3%
9 10
 
8.5%
3 9
 
7.6%
2 7
 
5.9%
6 5
 
4.2%
5 4
 
3.4%
Other values (3) 7
 
5.9%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 118
98.3%
Hangul 2
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 25
21.2%
0 14
11.9%
, 13
11.0%
8 13
11.0%
4 11
9.3%
9 10
 
8.5%
3 9
 
7.6%
2 7
 
5.9%
6 5
 
4.2%
5 4
 
3.4%
Other values (3) 7
 
5.9%
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
2024-02-10T07:12:13.942595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length1.9090909
Min length1

Characters and Unicode

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

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row양동
2nd row2,076
3rd row3,619
4th row29
5th row3
ValueCountFrequency (%)
0 8
24.2%
3 3
 
9.1%
8 2
 
6.1%
24 2
 
6.1%
1 2
 
6.1%
32 1
 
3.0%
43 1
 
3.0%
3,613 1
 
3.0%
2,077 1
 
3.0%
6 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:12:14.831828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
17.5%
0 10
15.9%
3 9
14.3%
1 6
9.5%
4 4
 
6.3%
, 4
 
6.3%
6 4
 
6.3%
9 4
 
6.3%
8 3
 
4.8%
7 3
 
4.8%
Other values (4) 5
7.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 55
87.3%
Other Punctuation 4
 
6.3%
Dash Punctuation 2
 
3.2%
Other Letter 2
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
20.0%
0 10
18.2%
3 9
16.4%
1 6
10.9%
4 4
 
7.3%
6 4
 
7.3%
9 4
 
7.3%
8 3
 
5.5%
7 3
 
5.5%
5 1
 
1.8%
Other Letter
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
18.0%
0 10
16.4%
3 9
14.8%
1 6
9.8%
4 4
 
6.6%
, 4
 
6.6%
6 4
 
6.6%
9 4
 
6.6%
8 3
 
4.9%
7 3
 
4.9%
Other values (2) 3
 
4.9%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
18.0%
0 10
16.4%
3 9
14.8%
1 6
9.8%
4 4
 
6.6%
, 4
 
6.6%
6 4
 
6.6%
9 4
 
6.6%
8 3
 
4.9%
7 3
 
4.9%
Other values (2) 3
 
4.9%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 7
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:15.315109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2
Min length1

Characters and Unicode

Total characters66
Distinct characters13
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row양3동
2nd row2,171
3rd row4,541
4th row33
5th row0
ValueCountFrequency (%)
0 9
27.3%
18 2
 
6.1%
9 2
 
6.1%
1 2
 
6.1%
13 2
 
6.1%
2,171 1
 
3.0%
45 1
 
3.0%
21 1
 
3.0%
4,532 1
 
3.0%
2,170 1
 
3.0%
Other values (11) 11
33.3%
2024-02-10T07:12:16.210401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 12
18.2%
0 11
16.7%
3 10
15.2%
2 8
12.1%
4 5
7.6%
, 4
 
6.1%
8 3
 
4.5%
7 3
 
4.5%
5 3
 
4.5%
- 3
 
4.5%
Other values (3) 4
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
86.4%
Other Punctuation 4
 
6.1%
Dash Punctuation 3
 
4.5%
Other Letter 2
 
3.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 12
21.1%
0 11
19.3%
3 10
17.5%
2 8
14.0%
4 5
8.8%
8 3
 
5.3%
7 3
 
5.3%
5 3
 
5.3%
9 2
 
3.5%
Other Letter
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 12
18.8%
0 11
17.2%
3 10
15.6%
2 8
12.5%
4 5
7.8%
, 4
 
6.2%
8 3
 
4.7%
7 3
 
4.7%
5 3
 
4.7%
- 3
 
4.7%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 12
18.8%
0 11
17.2%
3 10
15.6%
2 8
12.5%
4 5
7.8%
, 4
 
6.2%
8 3
 
4.7%
7 3
 
4.7%
5 3
 
4.7%
- 3
 
4.7%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:16.661936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

Total characters75
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)54.5%

Sample

1st row농성1동
2nd row6,352
3rd row11,219
4th row80
5th row5
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
80 2
 
6.1%
5 2
 
6.1%
44 2
 
6.1%
137 1
 
3.0%
78 1
 
3.0%
6,393 1
 
3.0%
85 1
 
3.0%
41 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:12:17.581343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.3%
0 12
16.0%
4 9
12.0%
3 7
9.3%
5 6
8.0%
9 6
8.0%
8 4
 
5.3%
2 4
 
5.3%
7 4
 
5.3%
, 4
 
5.3%
Other values (4) 6
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
19.1%
0 12
17.6%
4 9
13.2%
3 7
10.3%
5 6
8.8%
9 6
8.8%
8 4
 
5.9%
2 4
 
5.9%
7 4
 
5.9%
6 3
 
4.4%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
18.1%
0 12
16.7%
4 9
12.5%
3 7
9.7%
5 6
8.3%
9 6
8.3%
8 4
 
5.6%
2 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
18.1%
0 12
16.7%
4 9
12.5%
3 7
9.7%
5 6
8.3%
9 6
8.3%
8 4
 
5.6%
2 4
 
5.6%
7 4
 
5.6%
, 4
 
5.6%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:18.059882image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row농성2동
2nd row2,950
3rd row4,839
4th row54
5th row2
ValueCountFrequency (%)
0 8
24.2%
54 2
 
6.1%
1 2
 
6.1%
53 1
 
3.0%
4,806 1
 
3.0%
2,936 1
 
3.0%
33 1
 
3.0%
14 1
 
3.0%
10 1
 
3.0%
19 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:12:19.034792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.3%
4 8
11.1%
2 8
11.1%
3 8
11.1%
5 6
8.3%
9 6
8.3%
1 6
8.3%
, 4
 
5.6%
6 4
 
5.6%
8 3
 
4.2%
Other values (5) 8
11.1%

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 11
17.7%
4 8
12.9%
2 8
12.9%
3 8
12.9%
5 6
9.7%
9 6
9.7%
1 6
9.7%
6 4
 
6.5%
8 3
 
4.8%
7 2
 
3.2%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 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 11
15.9%
4 8
11.6%
2 8
11.6%
3 8
11.6%
5 6
8.7%
9 6
8.7%
1 6
8.7%
, 4
 
5.8%
6 4
 
5.8%
8 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 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 11
15.9%
4 8
11.6%
2 8
11.6%
3 8
11.6%
5 6
8.7%
9 6
8.7%
1 6
8.7%
, 4
 
5.8%
6 4
 
5.8%
8 3
 
4.3%
Other values (2) 5
7.2%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct27
Distinct (%)79.4%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:12:19.397971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3235294
Min length1

Characters and Unicode

Total characters79
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

Unique25 ?
Unique (%)73.5%

Sample

1st row출력일자 :
2nd row광천동
3rd row4,191
4th row7,943
5th row78
ValueCountFrequency (%)
0 7
 
20.0%
12 2
 
5.7%
1
 
2.9%
출력일자 1
 
2.9%
103 1
 
2.9%
7,904 1
 
2.9%
4,177 1
 
2.9%
3 1
 
2.9%
39 1
 
2.9%
14 1
 
2.9%
Other values (18) 18
51.4%
2024-02-10T07:12:20.237928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 11
13.9%
1 10
12.7%
0 10
12.7%
7 8
10.1%
4 6
7.6%
9 6
7.6%
2 5
 
6.3%
, 4
 
5.1%
5 3
 
3.8%
- 3
 
3.8%
Other values (11) 13
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
79.7%
Other Letter 7
 
8.9%
Other Punctuation 5
 
6.3%
Dash Punctuation 3
 
3.8%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 11
17.5%
1 10
15.9%
0 10
15.9%
7 8
12.7%
4 6
9.5%
9 6
9.5%
2 5
7.9%
5 3
 
4.8%
6 2
 
3.2%
8 2
 
3.2%
Other Letter
ValueCountFrequency (%)
력 1
14.3%
자 1
14.3%
일 1
14.3%
광 1
14.3%
출 1
14.3%
천 1
14.3%
동 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 72
91.1%
Hangul 7
 
8.9%

Most frequent character per script

Common
ValueCountFrequency (%)
3 11
15.3%
1 10
13.9%
0 10
13.9%
7 8
11.1%
4 6
8.3%
9 6
8.3%
2 5
6.9%
, 4
 
5.6%
5 3
 
4.2%
- 3
 
4.2%
Other values (4) 6
8.3%
Hangul
ValueCountFrequency (%)
력 1
14.3%
자 1
14.3%
일 1
14.3%
광 1
14.3%
출 1
14.3%
천 1
14.3%
동 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
91.1%
Hangul 7
 
8.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 11
15.3%
1 10
13.9%
0 10
13.9%
7 8
11.1%
4 6
8.3%
9 6
8.3%
2 5
6.9%
, 4
 
5.6%
5 3
 
4.2%
- 3
 
4.2%
Other values (4) 6
8.3%
Hangul
ValueCountFrequency (%)
력 1
14.3%
자 1
14.3%
일 1
14.3%
광 1
14.3%
출 1
14.3%
천 1
14.3%
동 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:20.629069image/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 row유덕동
2nd row4,891
3rd row10,936
4th row15
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 2
 
6.1%
34 2
 
6.1%
15 2
 
6.1%
6 1
 
3.0%
57 1
 
3.0%
10,924 1
 
3.0%
4,906 1
 
3.0%
3 1
 
3.0%
12 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:12:21.559387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.8%
1 11
15.1%
4 9
12.3%
6 7
9.6%
5 6
8.2%
3 6
8.2%
9 5
 
6.8%
, 4
 
5.5%
8 3
 
4.1%
2 3
 
4.1%
Other values (5) 6
8.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.0%
1 11
16.9%
4 9
13.8%
6 7
10.8%
5 6
9.2%
3 6
9.2%
9 5
 
7.7%
8 3
 
4.6%
2 3
 
4.6%
7 2
 
3.1%
Other Letter
ValueCountFrequency (%)
유 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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.6%
1 11
15.7%
4 9
12.9%
6 7
10.0%
5 6
8.6%
3 6
8.6%
9 5
 
7.1%
, 4
 
5.7%
8 3
 
4.3%
2 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 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 (%)
0 13
18.6%
1 11
15.7%
4 9
12.9%
6 7
10.0%
5 6
8.6%
3 6
8.6%
9 5
 
7.1%
, 4
 
5.7%
8 3
 
4.3%
2 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%

Unnamed: 12
Date

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing34
Missing (%)97.1%
Memory size412.0 B
Minimum2022-05-04 00:00:00
Maximum2022-05-04 00:00:00
2024-02-10T07:12:22.077758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:12:22.505795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:22.888427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row치평동
2nd row13,626
3rd row30,139
4th row70
5th row10
ValueCountFrequency (%)
0 7
21.2%
10 2
 
6.1%
157 1
 
3.0%
30,087 1
 
3.0%
13,621 1
 
3.0%
1 1
 
3.0%
52 1
 
3.0%
5 1
 
3.0%
18 1
 
3.0%
115 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:12:24.635967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
22.6%
0 14
16.7%
3 9
10.7%
7 8
9.5%
2 6
 
7.1%
9 6
 
7.1%
5 6
 
7.1%
6 4
 
4.8%
, 4
 
4.8%
8 2
 
2.4%
Other values (5) 6
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 75
89.3%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
25.3%
0 14
18.7%
3 9
12.0%
7 8
10.7%
2 6
 
8.0%
9 6
 
8.0%
5 6
 
8.0%
6 4
 
5.3%
8 2
 
2.7%
4 1
 
1.3%
Other Letter
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
23.5%
0 14
17.3%
3 9
11.1%
7 8
9.9%
2 6
 
7.4%
9 6
 
7.4%
5 6
 
7.4%
6 4
 
4.9%
, 4
 
4.9%
8 2
 
2.5%
Other values (2) 3
 
3.7%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 19
23.5%
0 14
17.3%
3 9
11.1%
7 8
9.9%
2 6
 
7.4%
9 6
 
7.4%
5 6
 
7.4%
6 4
 
4.9%
, 4
 
4.9%
8 2
 
2.5%
Other values (2) 3
 
3.7%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)5.7%
Memory size412.0 B

Unnamed: 15
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:25.408355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6363636
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row상무2동
2nd row13,171
3rd row23,789
4th row117
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
8 2
 
6.1%
1 2
 
6.1%
156 1
 
3.0%
23,728 1
 
3.0%
13,154 1
 
3.0%
61 1
 
3.0%
17 1
 
3.0%
20 1
 
3.0%
115 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:12:27.145456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
26.4%
0 10
11.5%
3 8
 
9.2%
7 7
 
8.0%
8 6
 
6.9%
2 6
 
6.9%
6 6
 
6.9%
5 5
 
5.7%
, 4
 
4.6%
9 4
 
4.6%
Other values (5) 8
 
9.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
88.5%
Other Punctuation 4
 
4.6%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
29.9%
0 10
13.0%
3 8
 
10.4%
7 7
 
9.1%
8 6
 
7.8%
2 6
 
7.8%
6 6
 
7.8%
5 5
 
6.5%
9 4
 
5.2%
4 2
 
2.6%
Other Letter
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 84
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
27.4%
0 10
11.9%
3 8
 
9.5%
7 7
 
8.3%
8 6
 
7.1%
2 6
 
7.1%
6 6
 
7.1%
5 5
 
6.0%
, 4
 
4.8%
9 4
 
4.8%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 84
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
27.4%
0 10
11.9%
3 8
 
9.5%
7 7
 
8.3%
8 6
 
7.1%
2 6
 
7.1%
6 6
 
7.1%
5 5
 
6.0%
, 4
 
4.8%
9 4
 
4.8%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:27.599223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

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

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row화정1동
2nd row8,487
3rd row15,434
4th row44
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
44 2
 
6.1%
91 1
 
3.0%
15,434 1
 
3.0%
126 1
 
3.0%
8,500 1
 
3.0%
9 1
 
3.0%
13 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:12:28.640699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
17.1%
0 11
14.5%
4 10
13.2%
7 8
10.5%
8 6
7.9%
2 5
 
6.6%
5 5
 
6.6%
6 4
 
5.3%
, 4
 
5.3%
3 3
 
3.9%
Other values (5) 7
9.2%

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 (%)
1 13
19.1%
0 11
16.2%
4 10
14.7%
7 8
11.8%
8 6
8.8%
2 5
 
7.4%
5 5
 
7.4%
6 4
 
5.9%
3 3
 
4.4%
9 3
 
4.4%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 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 (%)
1 13
17.8%
0 11
15.1%
4 10
13.7%
7 8
11.0%
8 6
8.2%
2 5
 
6.8%
5 5
 
6.8%
6 4
 
5.5%
, 4
 
5.5%
3 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 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 (%)
1 13
17.8%
0 11
15.1%
4 10
13.7%
7 8
11.0%
8 6
8.2%
2 5
 
6.8%
5 5
 
6.8%
6 4
 
5.5%
, 4
 
5.5%
3 3
 
4.1%
Other values (2) 4
 
5.5%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:29.145342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.3030303
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row화정2동
2nd row7,988
3rd row20,488
4th row35
5th row17
ValueCountFrequency (%)
0 5
 
15.2%
52 2
 
6.1%
2 2
 
6.1%
17 2
 
6.1%
8 1
 
3.0%
86 1
 
3.0%
20,467 1
 
3.0%
8,001 1
 
3.0%
3 1
 
3.0%
21 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:12:30.095765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
14.5%
7 10
13.2%
2 9
11.8%
8 9
11.8%
1 7
9.2%
3 7
9.2%
5 4
 
5.3%
, 4
 
5.3%
4 4
 
5.3%
9 3
 
3.9%
Other values (5) 8
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
88.2%
Other Punctuation 4
 
5.3%
Other Letter 3
 
3.9%
Dash Punctuation 2
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
16.4%
7 10
14.9%
2 9
13.4%
8 9
13.4%
1 7
10.4%
3 7
10.4%
5 4
 
6.0%
4 4
 
6.0%
9 3
 
4.5%
6 3
 
4.5%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.1%
7 10
13.7%
2 9
12.3%
8 9
12.3%
1 7
9.6%
3 7
9.6%
5 4
 
5.5%
, 4
 
5.5%
4 4
 
5.5%
9 3
 
4.1%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 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 (%)
0 11
15.1%
7 10
13.7%
2 9
12.3%
8 9
12.3%
1 7
9.6%
3 7
9.6%
5 4
 
5.5%
, 4
 
5.5%
4 4
 
5.5%
9 3
 
4.1%
Other values (2) 5
6.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:30.477777image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row화정3동
2nd row4,631
3rd row10,031
4th row31
5th row11
ValueCountFrequency (%)
0 7
21.2%
33 2
 
6.1%
1 2
 
6.1%
11 2
 
6.1%
50 1
 
3.0%
61 1
 
3.0%
9,993 1
 
3.0%
4,636 1
 
3.0%
38 1
 
3.0%
5 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:12:31.377267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
21.9%
3 14
19.2%
0 12
16.4%
4 5
 
6.8%
, 4
 
5.5%
6 4
 
5.5%
8 3
 
4.1%
5 3
 
4.1%
9 3
 
4.1%
7 2
 
2.7%
Other values (5) 7
9.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
25.0%
3 14
21.9%
0 12
18.8%
4 5
 
7.8%
6 4
 
6.2%
8 3
 
4.7%
5 3
 
4.7%
9 3
 
4.7%
7 2
 
3.1%
2 2
 
3.1%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
22.9%
3 14
20.0%
0 12
17.1%
4 5
 
7.1%
, 4
 
5.7%
6 4
 
5.7%
8 3
 
4.3%
5 3
 
4.3%
9 3
 
4.3%
7 2
 
2.9%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 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 16
22.9%
3 14
20.0%
0 12
17.1%
4 5
 
7.1%
, 4
 
5.7%
6 4
 
5.7%
8 3
 
4.3%
5 3
 
4.3%
9 3
 
4.3%
7 2
 
2.9%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:31.771365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row화정4동
2nd row6,496
3rd row15,333
4th row43
5th row11
ValueCountFrequency (%)
0 7
21.2%
40 2
 
6.1%
43 2
 
6.1%
45 1
 
3.0%
60 1
 
3.0%
42 1
 
3.0%
15,293 1
 
3.0%
6,498 1
 
3.0%
1 1
 
3.0%
2 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:12:32.792683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.0%
4 12
16.0%
1 10
13.3%
3 8
10.7%
6 8
10.7%
2 5
6.7%
, 4
 
5.3%
9 4
 
5.3%
5 4
 
5.3%
7 2
 
2.7%
Other values (5) 6
8.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12
18.2%
4 12
18.2%
1 10
15.2%
3 8
12.1%
6 8
12.1%
2 5
7.6%
9 4
 
6.1%
5 4
 
6.1%
7 2
 
3.0%
8 1
 
1.5%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
16.7%
4 12
16.7%
1 10
13.9%
3 8
11.1%
6 8
11.1%
2 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
5 4
 
5.6%
7 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12
16.7%
4 12
16.7%
1 10
13.9%
3 8
11.1%
6 8
11.1%
2 5
6.9%
, 4
 
5.6%
9 4
 
5.6%
5 4
 
5.6%
7 2
 
2.8%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:33.146035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
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 row서창동
2nd row2,689
3rd row5,754
4th row28
5th row4
ValueCountFrequency (%)
0 7
21.2%
4 3
 
9.1%
28 2
 
6.1%
22 1
 
3.0%
57 1
 
3.0%
5,724 1
 
3.0%
2,679 1
 
3.0%
1 1
 
3.0%
30 1
 
3.0%
10 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:12:34.113989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.5%
2 10
14.1%
4 8
11.3%
5 8
11.3%
7 7
9.9%
8 4
 
5.6%
, 4
 
5.6%
3 4
 
5.6%
1 4
 
5.6%
9 3
 
4.2%
Other values (5) 8
11.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 61
85.9%
Other Punctuation 4
 
5.6%
Dash Punctuation 3
 
4.2%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
18.0%
2 10
16.4%
4 8
13.1%
5 8
13.1%
7 7
11.5%
8 4
 
6.6%
3 4
 
6.6%
1 4
 
6.6%
9 3
 
4.9%
6 2
 
3.3%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
16.2%
2 10
14.7%
4 8
11.8%
5 8
11.8%
7 7
10.3%
8 4
 
5.9%
, 4
 
5.9%
3 4
 
5.9%
1 4
 
5.9%
9 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 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 11
16.2%
2 10
14.7%
4 8
11.8%
5 8
11.8%
7 7
10.3%
8 4
 
5.9%
, 4
 
5.9%
3 4
 
5.9%
1 4
 
5.9%
9 3
 
4.4%
Other values (2) 5
7.4%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:34.560196image/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

Unique25 ?
Unique (%)75.8%

Sample

1st row금호1동
2nd row8,852
3rd row19,999
4th row40
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
4 2
 
6.1%
1 2
 
6.1%
80 1
 
3.0%
20,131 1
 
3.0%
8,920 1
 
3.0%
132 1
 
3.0%
68 1
 
3.0%
18 1
 
3.0%
70 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:12:35.491805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
19.2%
0 13
16.7%
8 9
11.5%
9 7
9.0%
6 6
 
7.7%
5 5
 
6.4%
3 5
 
6.4%
4 4
 
5.1%
, 4
 
5.1%
2 4
 
5.1%
Other values (5) 6
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
89.7%
Other Punctuation 4
 
5.1%
Other Letter 3
 
3.8%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
21.4%
0 13
18.6%
8 9
12.9%
9 7
10.0%
6 6
 
8.6%
5 5
 
7.1%
3 5
 
7.1%
4 4
 
5.7%
2 4
 
5.7%
7 2
 
2.9%
Other Letter
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
20.0%
0 13
17.3%
8 9
12.0%
9 7
9.3%
6 6
 
8.0%
5 5
 
6.7%
3 5
 
6.7%
4 4
 
5.3%
, 4
 
5.3%
2 4
 
5.3%
Other values (2) 3
 
4.0%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 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 15
20.0%
0 13
17.3%
8 9
12.0%
9 7
9.3%
6 6
 
8.0%
5 5
 
6.7%
3 5
 
6.7%
4 4
 
5.3%
, 4
 
5.3%
2 4
 
5.3%
Other values (2) 3
 
4.0%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:35.829583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.4545455
Min length1

Characters and Unicode

Total characters81
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 row금호2동
2nd row10,548
3rd row28,281
4th row26
5th row7
ValueCountFrequency (%)
0 8
24.2%
26 2
 
6.1%
7 2
 
6.1%
118 1
 
3.0%
28,281 1
 
3.0%
151 1
 
3.0%
10,527 1
 
3.0%
133 1
 
3.0%
21 1
 
3.0%
9 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:12:37.128366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 13
16.0%
0 11
13.6%
2 10
12.3%
8 9
11.1%
6 6
7.4%
4 6
7.4%
7 5
 
6.2%
5 5
 
6.2%
3 4
 
4.9%
, 4
 
4.9%
Other values (5) 8
9.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 72
88.9%
Other Punctuation 4
 
4.9%
Other Letter 3
 
3.7%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 13
18.1%
0 11
15.3%
2 10
13.9%
8 9
12.5%
6 6
8.3%
4 6
8.3%
7 5
 
6.9%
5 5
 
6.9%
3 4
 
5.6%
9 3
 
4.2%
Other Letter
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 78
96.3%
Hangul 3
 
3.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 13
16.7%
0 11
14.1%
2 10
12.8%
8 9
11.5%
6 6
7.7%
4 6
7.7%
7 5
 
6.4%
5 5
 
6.4%
3 4
 
5.1%
, 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 78
96.3%
Hangul 3
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 13
16.7%
0 11
14.1%
2 10
12.8%
8 9
11.5%
6 6
7.7%
4 6
7.7%
7 5
 
6.4%
5 5
 
6.4%
3 4
 
5.1%
, 4
 
5.1%
Other values (2) 5
 
6.4%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:37.768131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.5454545
Min length1

Characters and Unicode

Total characters84
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row풍암동
2nd row15,278
3rd row36,529
4th row78
5th row22
ValueCountFrequency (%)
0 7
21.2%
22 2
 
6.1%
164 1
 
3.0%
36,470 1
 
3.0%
15,284 1
 
3.0%
1 1
 
3.0%
59 1
 
3.0%
6 1
 
3.0%
20 1
 
3.0%
134 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:12:39.656939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
16.7%
2 12
14.3%
0 11
13.1%
5 8
9.5%
3 7
8.3%
7 7
8.3%
6 5
 
6.0%
4 5
 
6.0%
, 4
 
4.8%
9 4
 
4.8%
Other values (5) 7
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
90.5%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
18.4%
2 12
15.8%
0 11
14.5%
5 8
10.5%
3 7
9.2%
7 7
9.2%
6 5
 
6.6%
4 5
 
6.6%
9 4
 
5.3%
8 3
 
3.9%
Other Letter
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
17.3%
2 12
14.8%
0 11
13.6%
5 8
9.9%
3 7
8.6%
7 7
8.6%
6 5
 
6.2%
4 5
 
6.2%
, 4
 
4.9%
9 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
17.3%
2 12
14.8%
0 11
13.6%
5 8
9.9%
3 7
8.6%
7 7
8.6%
6 5
 
6.2%
4 5
 
6.2%
, 4
 
4.9%
9 4
 
4.9%
Other values (2) 4
 
4.9%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Unnamed: 24
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:12:40.142243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2121212
Min length1

Characters and Unicode

Total characters73
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)72.7%

Sample

1st row동천동
2nd row6,395
3rd row16,140
4th row10
5th row3
ValueCountFrequency (%)
0 7
21.2%
54 2
 
6.1%
9 2
 
6.1%
6 1
 
3.0%
157 1
 
3.0%
16,086 1
 
3.0%
6,379 1
 
3.0%
1 1
 
3.0%
16 1
 
3.0%
45 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:12:41.010697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
15.1%
1 11
15.1%
6 9
12.3%
5 8
11.0%
9 6
8.2%
4 6
8.2%
3 5
6.8%
, 4
 
5.5%
8 3
 
4.1%
7 3
 
4.1%
Other values (4) 7
9.6%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.5%
1 11
17.5%
6 9
14.3%
5 8
12.7%
9 6
9.5%
4 6
9.5%
3 5
7.9%
8 3
 
4.8%
7 3
 
4.8%
2 1
 
1.6%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.7%
1 11
15.7%
6 9
12.9%
5 8
11.4%
9 6
8.6%
4 6
8.6%
3 5
7.1%
, 4
 
5.7%
8 3
 
4.3%
7 3
 
4.3%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.7%
1 11
15.7%
6 9
12.9%
5 8
11.4%
9 6
8.6%
4 6
8.6%
3 5
7.1%
, 4
 
5.7%
8 3
 
4.3%
7 3
 
4.3%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%

Sample

Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24
0<NA>행정기관 :<NA>광주광역시 서구<NA><NA><NA><NA><NA><NA>출력일자 :<NA>2022.05.04<NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.04 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>NaN<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계양동양3동농성1동농성2동광천동유덕동<NA>치평동상무1동상무2동화정1동화정2동화정3동화정4동서창동금호1동금호2동풍암동동천동
3<NA>전월말세대수<NA><NA><NA>133,0492,0762,1716,3522,9504,1914,891<NA>13,6261225713,1718,4877,9884,6316,4962,6898,85210,54815,2786,395
4<NA>전월말인구수<NA><NA><NA>289,7893,6194,54111,2194,8397,94310,936<NA>30,13924,77523,78915,43420,48810,03115,3335,75419,99928,28136,52916,140
5<NA>전월말거주불명자수<NA><NA><NA>938293380547815<NA>70127117443531432840267810
6<NA>전월말재외국민등록자수<NA><NA><NA>1413052124<NA>101097171111447223
7<NA>증 가 요 인전 입계<NA>2,83845382237669116<NA>273278266218149809473307154273106
8<NA><NA><NA>남자<NA>1,4202218106413860<NA>140145131103703343451487815148
9<NA><NA><NA>여자<NA>1,4182320117353156<NA>133133135115794751281597612258
Unnamed: 0인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24
25<NA><NA>말소<NA><NA>6001000<NA>001120001000
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000
28<NA>세대수증감<NA><NA><NA>541-141-14-1415<NA>-5-12-17131352-1068-216-16
29<NA>인구수증감<NA><NA><NA>-448-6-985-33-39-12<NA>-52-69-61-9-21-38-40-30132-133-59-54
30<NA>거주불명자수증감<NA><NA><NA>-11-1-20-1-33<NA>10-10-3-1-1-1-101-1
31<NA>금월말세대수<NA><NA><NA>133,1032,0772,1706,3932,9364,1774,906<NA>13,62112,24513,1548,5008,0014,6366,4982,6798,92010,52715,2846,379
32<NA>금월말인구수<NA><NA><NA>289,3413,6134,53211,3044,8067,90410,924<NA>30,08724,70623,72815,42520,4679,99315,2935,72420,13128,14836,47016,086
33<NA>금월말거주불명자수<NA><NA><NA>927283180537518<NA>7112711644323042273926799
34<NA>금월말재외국민등록자수<NA><NA><NA>1403051124<NA>101087171110447225

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24# duplicates
0<NA>국외<NA><NA>0000000<NA>000000000002
1<NA>기타<NA><NA>0000000<NA>000000000002