Overview

Dataset statistics

Number of variables25
Number of observations35
Missing cells203
Missing cells (%)23.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.0 KiB
Average record size in memory204.8 B

Variable types

Unsupported1
Text23
DateTime1

Dataset

Description2022-04-15
Author주민등록인구통계
URLhttps://bigdata.gwangju.go.kr/usr/dataSet/getDataDetailView.rd?dataSetUncd=DS000201928

Alerts

Unnamed: 12 has constant value ""Constant
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

Reproduction

Analysis started2024-02-10 07:13:14.757355
Analysis finished2024-02-10 07:13:16.164146
Duration1.41 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
2024-02-10T07:13:16.422485image/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%
2024-02-10T07:13:17.274290image/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
2024-02-10T07:13:17.709298image/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%
2024-02-10T07:13:18.235858image/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
2024-02-10T07:13:18.682164image/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 서구
2nd row2022.02 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%
2022.02 1
7.1%
현재 1
7.1%
2024-02-10T07:13:19.447231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 5
12.2%
2 4
 
9.8%
자 4
 
9.8%
도 4
 
9.8%
3
 
7.3%
계 2
 
4.9%
여 2
 
4.9%
내 2
 
4.9%
간 2
 
4.9%
광 2
 
4.9%
Other values (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%
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 4
66.7%
0 2
33.3%
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 (%)
2 4
40.0%
3
30.0%
0 2
20.0%
. 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 (%)
2 4
40.0%
3
30.0%
0 2
20.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:13:19.722061image/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%
2024-02-10T07:13:20.426777image/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 

Distinct29
Distinct (%)87.9%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:20.704324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.6969697
Min length1

Characters and Unicode

Total characters122
Distinct characters15
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row합 계
2nd row132,931
3rd row291,235
4th row955
5th row140
ValueCountFrequency (%)
0 3
 
8.8%
1 2
 
5.9%
875 2
 
5.9%
1,491 1
 
2.9%
955 1
 
2.9%
140 1
 
2.9%
941 1
 
2.9%
290,550 1
 
2.9%
132,949 1
 
2.9%
14 1
 
2.9%
Other values (20) 20
58.8%
2024-02-10T07:13:21.522362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 26
21.3%
9 17
13.9%
, 14
11.5%
5 11
9.0%
2 10
 
8.2%
0 9
 
7.4%
3 8
 
6.6%
4 8
 
6.6%
8 5
 
4.1%
7 4
 
3.3%
Other values (5) 10
 
8.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 102
83.6%
Other Punctuation 14
 
11.5%
Space Separator 2
 
1.6%
Dash Punctuation 2
 
1.6%
Other Letter 2
 
1.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 26
25.5%
9 17
16.7%
5 11
10.8%
2 10
 
9.8%
0 9
 
8.8%
3 8
 
7.8%
4 8
 
7.8%
8 5
 
4.9%
7 4
 
3.9%
6 4
 
3.9%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 26
21.7%
9 17
14.2%
, 14
11.7%
5 11
9.2%
2 10
 
8.3%
0 9
 
7.5%
3 8
 
6.7%
4 8
 
6.7%
8 5
 
4.2%
7 4
 
3.3%
Other values (3) 8
 
6.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 26
21.7%
9 17
14.2%
, 14
11.7%
5 11
9.2%
2 10
 
8.3%
0 9
 
7.5%
3 8
 
6.7%
4 8
 
6.7%
8 5
 
4.2%
7 4
 
3.3%
Other values (3) 8
 
6.7%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:21.853400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)45.5%

Sample

1st row양동
2nd row2,106
3rd row3,663
4th row29
5th row3
ValueCountFrequency (%)
0 8
24.2%
8 4
 
12.1%
3 2
 
6.1%
27 2
 
6.1%
29 2
 
6.1%
양동 1
 
3.0%
43 1
 
3.0%
19 1
 
3.0%
24 1
 
3.0%
3,663 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:13:22.664077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
17.2%
3 9
14.1%
2 9
14.1%
1 6
9.4%
8 4
 
6.2%
9 4
 
6.2%
4 4
 
6.2%
, 4
 
6.2%
6 4
 
6.2%
7 3
 
4.7%
Other values (4) 6
9.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
87.5%
Other Punctuation 4
 
6.2%
Dash Punctuation 2
 
3.1%
Other Letter 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
19.6%
3 9
16.1%
2 9
16.1%
1 6
10.7%
8 4
 
7.1%
9 4
 
7.1%
4 4
 
7.1%
6 4
 
7.1%
7 3
 
5.4%
5 2
 
3.6%
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 62
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
17.7%
3 9
14.5%
2 9
14.5%
1 6
9.7%
8 4
 
6.5%
9 4
 
6.5%
4 4
 
6.5%
, 4
 
6.5%
6 4
 
6.5%
7 3
 
4.8%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
17.7%
3 9
14.5%
2 9
14.5%
1 6
9.7%
8 4
 
6.5%
9 4
 
6.5%
4 4
 
6.5%
, 4
 
6.5%
6 4
 
6.5%
7 3
 
4.8%
Other values (2) 4
 
6.5%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 7
Text

MISSING 

Distinct20
Distinct (%)60.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:23.153115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
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

Unique16 ?
Unique (%)48.5%

Sample

1st row양3동
2nd row2,174
3rd row4,576
4th row32
5th row0
ValueCountFrequency (%)
0 10
30.3%
7 3
 
9.1%
32 2
 
6.1%
17 2
 
6.1%
13 1
 
3.0%
15 1
 
3.0%
2,172 1
 
3.0%
14 1
 
3.0%
2 1
 
3.0%
6 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:13:24.019873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
15.6%
1 10
15.6%
7 8
12.5%
2 8
12.5%
4 7
10.9%
3 6
9.4%
, 4
 
6.2%
5 3
 
4.7%
6 3
 
4.7%
- 2
 
3.1%
Other values (3) 3
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 56
87.5%
Other Punctuation 4
 
6.2%
Dash Punctuation 2
 
3.1%
Other Letter 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
17.9%
1 10
17.9%
7 8
14.3%
2 8
14.3%
4 7
12.5%
3 6
10.7%
5 3
 
5.4%
6 3
 
5.4%
9 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 62
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
16.1%
1 10
16.1%
7 8
12.9%
2 8
12.9%
4 7
11.3%
3 6
9.7%
, 4
 
6.5%
5 3
 
4.8%
6 3
 
4.8%
- 2
 
3.2%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 62
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 10
16.1%
1 10
16.1%
7 8
12.9%
2 8
12.9%
4 7
11.3%
3 6
9.7%
, 4
 
6.5%
5 3
 
4.8%
6 3
 
4.8%
- 2
 
3.2%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:24.341377image/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

Unique21 ?
Unique (%)63.6%

Sample

1st row농성1동
2nd row6,229
3rd row11,008
4th row80
5th row5
ValueCountFrequency (%)
0 6
18.2%
8 2
 
6.1%
5 2
 
6.1%
1 2
 
6.1%
83 2
 
6.1%
174 1
 
3.0%
91 1
 
3.0%
80 1
 
3.0%
6,229 1
 
3.0%
11,020 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:13:25.092087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.2%
0 12
16.4%
8 10
13.7%
5 7
9.6%
9 5
 
6.8%
2 5
 
6.8%
4 4
 
5.5%
, 4
 
5.5%
7 3
 
4.1%
6 3
 
4.1%
Other values (5) 6
8.2%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
21.5%
0 12
18.5%
8 10
15.4%
5 7
10.8%
9 5
 
7.7%
2 5
 
7.7%
4 4
 
6.2%
7 3
 
4.6%
6 3
 
4.6%
3 2
 
3.1%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 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 14
20.0%
0 12
17.1%
8 10
14.3%
5 7
10.0%
9 5
 
7.1%
2 5
 
7.1%
4 4
 
5.7%
, 4
 
5.7%
7 3
 
4.3%
6 3
 
4.3%
Other values (2) 3
 
4.3%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 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 14
20.0%
0 12
17.1%
8 10
14.3%
5 7
10.0%
9 5
 
7.1%
2 5
 
7.1%
4 4
 
5.7%
, 4
 
5.7%
7 3
 
4.3%
6 3
 
4.3%
Other values (2) 3
 
4.3%
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
2024-02-10T07:13:25.498202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.1212121
Min length1

Characters and Unicode

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

Unique

Unique22 ?
Unique (%)66.7%

Sample

1st row농성2동
2nd row2,956
3rd row4,900
4th row54
5th row2
ValueCountFrequency (%)
0 7
21.2%
46 2
 
6.1%
31 2
 
6.1%
2 2
 
6.1%
1 2
 
6.1%
15 1
 
3.0%
92 1
 
3.0%
4,869 1
 
3.0%
2,949 1
 
3.0%
7 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:13:26.361485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 10
14.3%
0 9
12.9%
4 8
11.4%
9 7
10.0%
1 7
10.0%
3 6
8.6%
6 5
7.1%
, 4
 
5.7%
5 4
 
5.7%
8 3
 
4.3%
Other values (5) 7
10.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 10
16.7%
0 9
15.0%
4 8
13.3%
9 7
11.7%
1 7
11.7%
3 6
10.0%
6 5
8.3%
5 4
 
6.7%
8 3
 
5.0%
7 1
 
1.7%
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 67
95.7%
Hangul 3
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
2 10
14.9%
0 9
13.4%
4 8
11.9%
9 7
10.4%
1 7
10.4%
3 6
9.0%
6 5
7.5%
, 4
 
6.0%
5 4
 
6.0%
8 3
 
4.5%
Other values (2) 4
 
6.0%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 10
14.9%
0 9
13.4%
4 8
11.9%
9 7
10.4%
1 7
10.4%
3 6
9.0%
6 5
7.5%
, 4
 
6.0%
5 4
 
6.0%
8 3
 
4.5%
Other values (2) 4
 
6.0%
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
2024-02-10T07:13:26.662153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5.5
Mean length2.3529412
Min length1

Characters and Unicode

Total characters80
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

Unique24 ?
Unique (%)70.6%

Sample

1st row출력일자 :
2nd row광천동
3rd row4,218
4th row8,044
5th row81
ValueCountFrequency (%)
0 6
 
17.1%
10 2
 
5.7%
2 2
 
5.7%
12 2
 
5.7%
4 1
 
2.9%
27 1
 
2.9%
1
 
2.9%
출력일자 1
 
2.9%
131 1
 
2.9%
7,985 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T07:13:27.308936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 11
13.8%
1 11
13.8%
2 8
10.0%
4 7
8.8%
5 7
8.8%
6 5
 
6.2%
, 4
 
5.0%
8 4
 
5.0%
7 4
 
5.0%
3 4
 
5.0%
Other values (11) 15
18.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 64
80.0%
Other Letter 7
 
8.8%
Other Punctuation 5
 
6.2%
Dash Punctuation 3
 
3.8%
Space Separator 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 11
17.2%
1 11
17.2%
2 8
12.5%
4 7
10.9%
5 7
10.9%
6 5
7.8%
8 4
 
6.2%
7 4
 
6.2%
3 4
 
6.2%
9 3
 
4.7%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 73
91.2%
Hangul 7
 
8.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 11
15.1%
1 11
15.1%
2 8
11.0%
4 7
9.6%
5 7
9.6%
6 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
7 4
 
5.5%
3 4
 
5.5%
Other values (4) 8
11.0%
Hangul
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 73
91.2%
Hangul 7
 
8.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 11
15.1%
1 11
15.1%
2 8
11.0%
4 7
9.6%
5 7
9.6%
6 5
6.8%
, 4
 
5.5%
8 4
 
5.5%
7 4
 
5.5%
3 4
 
5.5%
Other values (4) 8
11.0%
Hangul
ValueCountFrequency (%)
동 1
14.3%
천 1
14.3%
광 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:27.597603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
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

Unique18 ?
Unique (%)54.5%

Sample

1st row유덕동
2nd row4,887
3rd row10,968
4th row15
5th row5
ValueCountFrequency (%)
0 7
21.2%
27 2
 
6.1%
15 2
 
6.1%
53 2
 
6.1%
1 2
 
6.1%
65 1
 
3.0%
5 1
 
3.0%
118 1
 
3.0%
10,960 1
 
3.0%
4,888 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:13:28.293128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
19.7%
0 11
15.5%
5 10
14.1%
8 9
12.7%
4 4
 
5.6%
, 4
 
5.6%
9 4
 
5.6%
2 3
 
4.2%
7 3
 
4.2%
6 3
 
4.2%
Other values (5) 6
8.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
88.7%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 1
 
1.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
22.2%
0 11
17.5%
5 10
15.9%
8 9
14.3%
4 4
 
6.3%
9 4
 
6.3%
2 3
 
4.8%
7 3
 
4.8%
6 3
 
4.8%
3 2
 
3.2%
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 68
95.8%
Hangul 3
 
4.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
20.6%
0 11
16.2%
5 10
14.7%
8 9
13.2%
4 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
2 3
 
4.4%
7 3
 
4.4%
6 3
 
4.4%
Other values (2) 3
 
4.4%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
20.6%
0 11
16.2%
5 10
14.7%
8 9
13.2%
4 4
 
5.9%
, 4
 
5.9%
9 4
 
5.9%
2 3
 
4.4%
7 3
 
4.4%
6 3
 
4.4%
Other values (2) 3
 
4.4%
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
Minimum2022-03-02 00:00:00
Maximum2022-03-02 00:00:00
2024-02-10T07:13:28.655378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:13:28.939045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Unnamed: 13
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:29.232216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length2.6060606
Min length1

Characters and Unicode

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

Unique

Unique26 ?
Unique (%)78.8%

Sample

1st row치평동
2nd row13,645
3rd row30,331
4th row71
5th row10
ValueCountFrequency (%)
0 7
21.2%
226 1
 
3.0%
202 1
 
3.0%
68 1
 
3.0%
30,299 1
 
3.0%
13,654 1
 
3.0%
3 1
 
3.0%
32 1
 
3.0%
9 1
 
3.0%
16 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:13:29.952450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
18.6%
0 11
12.8%
2 10
11.6%
3 9
10.5%
6 8
9.3%
7 6
 
7.0%
9 5
 
5.8%
, 4
 
4.7%
4 4
 
4.7%
5 4
 
4.7%
Other values (5) 9
10.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
89.5%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
20.8%
0 11
14.3%
2 10
13.0%
3 9
11.7%
6 8
10.4%
7 6
 
7.8%
9 5
 
6.5%
4 4
 
5.2%
5 4
 
5.2%
8 4
 
5.2%
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 83
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
19.3%
0 11
13.3%
2 10
12.0%
3 9
10.8%
6 8
9.6%
7 6
 
7.2%
9 5
 
6.0%
, 4
 
4.8%
4 4
 
4.8%
5 4
 
4.8%
Other values (2) 6
 
7.2%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
19.3%
0 11
13.3%
2 10
12.0%
3 9
10.8%
6 8
9.6%
7 6
 
7.2%
9 5
 
6.0%
, 4
 
4.8%
4 4
 
4.8%
5 4
 
4.8%
Other values (2) 6
 
7.2%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:30.523659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)63.6%

Sample

1st row상무1동
2nd row12,200
3rd row24,809
4th row124
5th row9
ValueCountFrequency (%)
1 4
 
12.1%
0 4
 
12.1%
10 2
 
6.1%
102 2
 
6.1%
401 1
 
3.0%
24,763 1
 
3.0%
12,213 1
 
3.0%
46 1
 
3.0%
13 1
 
3.0%
166 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:13:31.378684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 24
27.0%
0 15
16.9%
2 13
14.6%
3 7
 
7.9%
6 6
 
6.7%
4 5
 
5.6%
, 4
 
4.5%
8 4
 
4.5%
9 3
 
3.4%
5 3
 
3.4%
Other values (5) 5
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 81
91.0%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 1
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 24
29.6%
0 15
18.5%
2 13
16.0%
3 7
 
8.6%
6 6
 
7.4%
4 5
 
6.2%
8 4
 
4.9%
9 3
 
3.7%
5 3
 
3.7%
7 1
 
1.2%
Other Letter
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 24
27.9%
0 15
17.4%
2 13
15.1%
3 7
 
8.1%
6 6
 
7.0%
4 5
 
5.8%
, 4
 
4.7%
8 4
 
4.7%
9 3
 
3.5%
5 3
 
3.5%
Other values (2) 2
 
2.3%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 24
27.9%
0 15
17.4%
2 13
15.1%
3 7
 
8.1%
6 6
 
7.0%
4 5
 
5.8%
, 4
 
4.7%
8 4
 
4.7%
9 3
 
3.5%
5 3
 
3.5%
Other values (2) 2
 
2.3%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:31.933698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6969697
Min length1

Characters and Unicode

Total characters89
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row상무2동
2nd row13,126
3rd row23,874
4th row126
5th row9
ValueCountFrequency (%)
0 6
 
18.2%
9 2
 
6.1%
204 1
 
3.0%
394 1
 
3.0%
23,832 1
 
3.0%
13,144 1
 
3.0%
6 1
 
3.0%
42 1
 
3.0%
18 1
 
3.0%
20 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:13:33.538663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 21
23.6%
0 12
13.5%
2 10
11.2%
3 9
10.1%
4 9
10.1%
9 6
 
6.7%
6 6
 
6.7%
, 4
 
4.5%
8 4
 
4.5%
7 2
 
2.2%
Other values (5) 6
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
89.9%
Other Punctuation 4
 
4.5%
Other Letter 3
 
3.4%
Dash Punctuation 2
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 21
26.2%
0 12
15.0%
2 10
12.5%
3 9
11.2%
4 9
11.2%
9 6
 
7.5%
6 6
 
7.5%
8 4
 
5.0%
7 2
 
2.5%
5 1
 
1.2%
Other Letter
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 21
24.4%
0 12
14.0%
2 10
11.6%
3 9
10.5%
4 9
10.5%
9 6
 
7.0%
6 6
 
7.0%
, 4
 
4.7%
8 4
 
4.7%
7 2
 
2.3%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 21
24.4%
0 12
14.0%
2 10
11.6%
3 9
10.5%
4 9
10.5%
9 6
 
7.0%
6 6
 
7.0%
, 4
 
4.7%
8 4
 
4.7%
7 2
 
2.3%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:34.061312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.4242424
Min length1

Characters and Unicode

Total characters80
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row화정1동
2nd row8,493
3rd row15,516
4th row44
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
7 2
 
6.1%
122 1
 
3.0%
266 1
 
3.0%
15,493 1
 
3.0%
8,496 1
 
3.0%
23 1
 
3.0%
3 1
 
3.0%
12 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:13:35.493033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.0%
4 10
12.5%
0 9
11.2%
6 7
8.8%
2 7
8.8%
3 6
 
7.5%
7 4
 
5.0%
8 4
 
5.0%
, 4
 
5.0%
9 4
 
5.0%
Other values (5) 9
11.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 71
88.8%
Other Punctuation 4
 
5.0%
Other Letter 3
 
3.8%
Dash Punctuation 2
 
2.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 16
22.5%
4 10
14.1%
0 9
12.7%
6 7
9.9%
2 7
9.9%
3 6
 
8.5%
7 4
 
5.6%
8 4
 
5.6%
9 4
 
5.6%
5 4
 
5.6%
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 77
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
20.8%
4 10
13.0%
0 9
11.7%
6 7
9.1%
2 7
9.1%
3 6
 
7.8%
7 4
 
5.2%
8 4
 
5.2%
, 4
 
5.2%
9 4
 
5.2%
Other values (2) 6
 
7.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 16
20.8%
4 10
13.0%
0 9
11.7%
6 7
9.1%
2 7
9.1%
3 6
 
7.8%
7 4
 
5.2%
8 4
 
5.2%
, 4
 
5.2%
9 4
 
5.2%
Other values (2) 6
 
7.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 17
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:36.032077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
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 row8,008
3rd row20,638
4th row37
5th row17
ValueCountFrequency (%)
0 7
21.2%
107 2
 
6.1%
17 2
 
6.1%
4 1
 
3.0%
140 1
 
3.0%
20,558 1
 
3.0%
8,005 1
 
3.0%
1 1
 
3.0%
80 1
 
3.0%
3 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:13:36.949037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 18
21.7%
1 14
16.9%
7 10
12.0%
2 9
10.8%
8 7
 
8.4%
3 5
 
6.0%
, 4
 
4.8%
6 4
 
4.8%
- 3
 
3.6%
5 3
 
3.6%
Other values (5) 6
 
7.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 73
88.0%
Other Punctuation 4
 
4.8%
Dash Punctuation 3
 
3.6%
Other Letter 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 18
24.7%
1 14
19.2%
7 10
13.7%
2 9
12.3%
8 7
 
9.6%
3 5
 
6.8%
6 4
 
5.5%
5 3
 
4.1%
4 2
 
2.7%
9 1
 
1.4%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 18
22.5%
1 14
17.5%
7 10
12.5%
2 9
11.2%
8 7
 
8.8%
3 5
 
6.2%
, 4
 
5.0%
6 4
 
5.0%
- 3
 
3.8%
5 3
 
3.8%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 18
22.5%
1 14
17.5%
7 10
12.5%
2 9
11.2%
8 7
 
8.8%
3 5
 
6.2%
, 4
 
5.0%
6 4
 
5.0%
- 3
 
3.8%
5 3
 
3.8%
Other values (2) 3
 
3.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:37.296652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters13
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row화정3동
2nd row4,632
3rd row10,069
4th row32
5th row11
ValueCountFrequency (%)
0 8
24.2%
11 2
 
6.1%
39 2
 
6.1%
4 2
 
6.1%
32 2
 
6.1%
34 1
 
3.0%
113 1
 
3.0%
4,634 1
 
3.0%
2 1
 
3.0%
7 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:13:38.395893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
22.2%
3 12
16.7%
1 10
13.9%
4 8
11.1%
6 6
 
8.3%
2 5
 
6.9%
, 4
 
5.6%
9 3
 
4.2%
5 3
 
4.2%
7 2
 
2.8%
Other values (3) 3
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 65
90.3%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 16
24.6%
3 12
18.5%
1 10
15.4%
4 8
12.3%
6 6
 
9.2%
2 5
 
7.7%
9 3
 
4.6%
5 3
 
4.6%
7 2
 
3.1%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 16
23.2%
3 12
17.4%
1 10
14.5%
4 8
11.6%
6 6
 
8.7%
2 5
 
7.2%
, 4
 
5.8%
9 3
 
4.3%
5 3
 
4.3%
7 2
 
2.9%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 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 16
23.2%
3 12
17.4%
1 10
14.5%
4 8
11.6%
6 6
 
8.7%
2 5
 
7.2%
, 4
 
5.8%
9 3
 
4.3%
5 3
 
4.3%
7 2
 
2.9%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:38.905343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2424242
Min length1

Characters and Unicode

Total characters74
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 row화정4동
2nd row6,505
3rd row15,402
4th row45
5th row11
ValueCountFrequency (%)
0 8
24.2%
45 3
 
9.1%
11 2
 
6.1%
9 2
 
6.1%
44 1
 
3.0%
10 1
 
3.0%
6,514 1
 
3.0%
15 1
 
3.0%
69 1
 
3.0%
30 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:13:39.859994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 13
17.6%
1 13
17.6%
0 12
16.2%
5 11
14.9%
6 6
8.1%
, 4
 
5.4%
9 3
 
4.1%
8 3
 
4.1%
7 3
 
4.1%
3 2
 
2.7%
Other values (4) 4
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
90.5%
Other Punctuation 4
 
5.4%
Other Letter 3
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 13
19.4%
1 13
19.4%
0 12
17.9%
5 11
16.4%
6 6
9.0%
9 3
 
4.5%
8 3
 
4.5%
7 3
 
4.5%
3 2
 
3.0%
2 1
 
1.5%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
4 13
18.3%
1 13
18.3%
0 12
16.9%
5 11
15.5%
6 6
8.5%
, 4
 
5.6%
9 3
 
4.2%
8 3
 
4.2%
7 3
 
4.2%
3 2
 
2.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 13
18.3%
1 13
18.3%
0 12
16.9%
5 11
15.5%
6 6
8.5%
, 4
 
5.6%
9 3
 
4.2%
8 3
 
4.2%
7 3
 
4.2%
3 2
 
2.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:40.328607image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row서창동
2nd row2,699
3rd row5,794
4th row28
5th row4
ValueCountFrequency (%)
0 7
21.2%
41 2
 
6.1%
28 2
 
6.1%
4 2
 
6.1%
1 2
 
6.1%
92 1
 
3.0%
51 1
 
3.0%
2,690 1
 
3.0%
18 1
 
3.0%
9 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:13:41.239505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 9
13.2%
2 9
13.2%
1 7
10.3%
9 7
10.3%
4 5
7.4%
7 5
7.4%
3 5
7.4%
8 4
5.9%
5 4
5.9%
, 4
5.9%
Other values (5) 9
13.2%

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 (%)
0 9
15.3%
2 9
15.3%
1 7
11.9%
9 7
11.9%
4 5
8.5%
7 5
8.5%
3 5
8.5%
8 4
6.8%
5 4
6.8%
6 4
6.8%
Other Letter
ValueCountFrequency (%)
서 1
33.3%
창 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 (%)
0 9
13.8%
2 9
13.8%
1 7
10.8%
9 7
10.8%
4 5
7.7%
7 5
7.7%
3 5
7.7%
8 4
6.2%
5 4
6.2%
, 4
6.2%
Other values (2) 6
9.2%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 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 9
13.8%
2 9
13.8%
1 7
10.8%
9 7
10.8%
4 5
7.7%
7 5
7.7%
3 5
7.7%
8 4
6.2%
5 4
6.2%
, 4
6.2%
Other values (2) 6
9.2%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:41.647709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2727273
Min length1

Characters and Unicode

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

Unique

Unique19 ?
Unique (%)57.6%

Sample

1st row금호1동
2nd row8,823
3rd row20,009
4th row40
5th row4
ValueCountFrequency (%)
0 6
18.2%
4 2
 
6.1%
52 2
 
6.1%
1 2
 
6.1%
40 2
 
6.1%
60 1
 
3.0%
95 1
 
3.0%
8,825 1
 
3.0%
55 1
 
3.0%
2 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:13:42.552989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
17.3%
1 12
16.0%
2 9
12.0%
5 8
10.7%
4 6
8.0%
8 5
 
6.7%
9 5
 
6.7%
3 4
 
5.3%
, 4
 
5.3%
6 4
 
5.3%
Other values (5) 5
 
6.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 67
89.3%
Other Punctuation 4
 
5.3%
Other Letter 3
 
4.0%
Dash Punctuation 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.4%
1 12
17.9%
2 9
13.4%
5 8
11.9%
4 6
9.0%
8 5
 
7.5%
9 5
 
7.5%
3 4
 
6.0%
6 4
 
6.0%
7 1
 
1.5%
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 72
96.0%
Hangul 3
 
4.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.1%
1 12
16.7%
2 9
12.5%
5 8
11.1%
4 6
8.3%
8 5
 
6.9%
9 5
 
6.9%
3 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 2
 
2.8%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 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 13
18.1%
1 12
16.7%
2 9
12.5%
5 8
11.1%
4 6
8.3%
8 5
 
6.9%
9 5
 
6.9%
3 4
 
5.6%
, 4
 
5.6%
6 4
 
5.6%
Other values (2) 2
 
2.8%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:42.889144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.5151515
Min length1

Characters and Unicode

Total characters83
Distinct characters14
Distinct 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 row금호2동
2nd row10,566
3rd row28,574
4th row26
5th row6
ValueCountFrequency (%)
0 8
24.2%
26 2
 
6.1%
158 1
 
3.0%
330 1
 
3.0%
28,452 1
 
3.0%
10,562 1
 
3.0%
122 1
 
3.0%
4 1
 
3.0%
12 1
 
3.0%
164 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:13:43.878865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 15
18.1%
2 12
14.5%
1 12
14.5%
6 9
10.8%
5 8
9.6%
8 7
8.4%
4 5
 
6.0%
, 4
 
4.8%
7 4
 
4.8%
- 2
 
2.4%
Other values (4) 5
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 74
89.2%
Other Punctuation 4
 
4.8%
Other Letter 3
 
3.6%
Dash Punctuation 2
 
2.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 15
20.3%
2 12
16.2%
1 12
16.2%
6 9
12.2%
5 8
10.8%
8 7
9.5%
4 5
 
6.8%
7 4
 
5.4%
3 2
 
2.7%
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 80
96.4%
Hangul 3
 
3.6%

Most frequent character per script

Common
ValueCountFrequency (%)
0 15
18.8%
2 12
15.0%
1 12
15.0%
6 9
11.2%
5 8
10.0%
8 7
8.8%
4 5
 
6.2%
, 4
 
5.0%
7 4
 
5.0%
- 2
 
2.5%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 80
96.4%
Hangul 3
 
3.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 15
18.8%
2 12
15.0%
1 12
15.0%
6 9
11.2%
5 8
10.0%
8 7
8.8%
4 5
 
6.2%
, 4
 
5.0%
7 4
 
5.0%
- 2
 
2.5%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 23
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:44.220783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6060606
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row풍암동
2nd row15,264
3rd row36,802
4th row82
5th row22
ValueCountFrequency (%)
0 6
 
18.2%
22 2
 
6.1%
1 2
 
6.1%
259 1
 
3.0%
36,692 1
 
3.0%
15,270 1
 
3.0%
110 1
 
3.0%
6 1
 
3.0%
7 1
 
3.0%
222 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:13:45.005674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 16
18.6%
1 13
15.1%
0 11
12.8%
6 9
10.5%
8 6
 
7.0%
3 6
 
7.0%
9 5
 
5.8%
4 4
 
4.7%
5 4
 
4.7%
, 4
 
4.7%
Other values (5) 8
9.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 77
89.5%
Other Punctuation 4
 
4.7%
Other Letter 3
 
3.5%
Dash Punctuation 2
 
2.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 16
20.8%
1 13
16.9%
0 11
14.3%
6 9
11.7%
8 6
 
7.8%
3 6
 
7.8%
9 5
 
6.5%
4 4
 
5.2%
5 4
 
5.2%
7 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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
2 16
19.3%
1 13
15.7%
0 11
13.3%
6 9
10.8%
8 6
 
7.2%
3 6
 
7.2%
9 5
 
6.0%
4 4
 
4.8%
5 4
 
4.8%
, 4
 
4.8%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 16
19.3%
1 13
15.7%
0 11
13.3%
6 9
10.8%
8 6
 
7.2%
3 6
 
7.2%
9 5
 
6.0%
4 4
 
4.8%
5 4
 
4.8%
, 4
 
4.8%
Other values (2) 5
 
6.0%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Unnamed: 24
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:13:45.334413image/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 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 row동천동
2nd row6,400
3rd row16,258
4th row9
5th row3
ValueCountFrequency (%)
0 7
21.2%
10 3
 
9.1%
3 3
 
9.1%
96 1
 
3.0%
9 1
 
3.0%
105 1
 
3.0%
6,390 1
 
3.0%
1 1
 
3.0%
65 1
 
3.0%
6,400 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:13:46.215766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 16
21.3%
1 12
16.0%
6 9
12.0%
3 7
9.3%
4 5
 
6.7%
9 5
 
6.7%
5 4
 
5.3%
2 4
 
5.3%
, 4
 
5.3%
8 3
 
4.0%
Other values (4) 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 16
24.2%
1 12
18.2%
6 9
13.6%
3 7
10.6%
4 5
 
7.6%
9 5
 
7.6%
5 4
 
6.1%
2 4
 
6.1%
8 3
 
4.5%
7 1
 
1.5%
Other Letter
ValueCountFrequency (%)
동 2
66.7%
천 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 16
22.2%
1 12
16.7%
6 9
12.5%
3 7
9.7%
4 5
 
6.9%
9 5
 
6.9%
5 4
 
5.6%
2 4
 
5.6%
, 4
 
5.6%
8 3
 
4.2%
Other values (2) 3
 
4.2%
Hangul
ValueCountFrequency (%)
동 2
66.7%
천 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 16
22.2%
1 12
16.7%
6 9
12.5%
3 7
9.7%
4 5
 
6.9%
9 5
 
6.9%
5 4
 
5.6%
2 4
 
5.6%
, 4
 
5.6%
8 3
 
4.2%
Other values (2) 3
 
4.2%
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>2022.03.02<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.02 현재<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
2<NA>시, 군, 구(읍면동)<NA><NA><NA>합 계양동양3동농성1동농성2동광천동유덕동<NA>치평동상무1동상무2동화정1동화정2동화정3동화정4동서창동금호1동금호2동풍암동동천동
3<NA>전월말세대수<NA><NA><NA>132,9312,1062,1746,2292,9564,2184,887<NA>13,64512,20013,1268,4938,0084,6326,5052,6998,82310,56615,2646,400
4<NA>전월말인구수<NA><NA><NA>291,2353,6634,57611,0084,9008,04410,968<NA>30,33124,80923,87415,51620,63810,06915,4025,79420,00928,57436,80216,258
5<NA>전월말거주불명자수<NA><NA><NA>955293280548115<NA>7112412644373245284026829
6<NA>전월말재외국민등록자수<NA><NA><NA>1403052125<NA>10997171111446223
7<NA>증 가 요 인전 입계<NA>3,34043241856376111<NA>39535336425022912015878165210368148
8<NA><NA><NA>남자<NA>1,619191798324158<NA>1681881681181225674417310417963
9<NA><NA><NA>여자<NA>1,72124787313553<NA>2271651961321076484379210618985
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>2000000<NA>000000001010
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>1000000<NA>010000000000
28<NA>세대수증감<NA><NA><NA>18-13-216-7-131<NA>913183-329-92-46-10
29<NA>인구수증감<NA><NA><NA>-685-11-1412-31-59-8<NA>-32-46-42-23-80415-18-55-122-110-65
30<NA>거주불명자수증감<NA><NA><NA>-1400-1-1-20<NA>-31-6-1-100000-11
31<NA>금월말세대수<NA><NA><NA>132,9492,0932,1726,2452,9494,2054,888<NA>13,65412,21313,1448,4968,0054,6346,5142,6908,82510,56215,2706,390
32<NA>금월말인구수<NA><NA><NA>290,5503,6524,56211,0204,8697,98510,960<NA>30,29924,76323,83215,49320,55810,07315,4175,77619,95428,45236,69216,193
33<NA>금월말거주불명자수<NA><NA><NA>941293279537915<NA>68125120433632452840268110
34<NA>금월말재외국민등록자수<NA><NA><NA>1423052124<NA>111097171111447223