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

Unsupported1
Text23
DateTime1

Dataset

Description2022-09-16
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

Reproduction

Analysis started2024-02-10 07:16:41.156810
Analysis finished2024-02-10 07:16:42.339101
Duration1.18 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
2024-02-10T07:16:42.613400image/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%
2024-02-10T07:16:44.027164image/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
2024-02-10T07:16:44.445354image/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%
2024-02-10T07:16:45.477077image/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
2024-02-10T07:16:45.941425image/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 row2022.08 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%
2022.08 1
7.1%
현재 1
7.1%
2024-02-10T07:16:46.819139image/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%
8 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%
8 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%
8 1
 
10.0%
. 1
 
10.0%

Unnamed: 4
Text

MISSING 

Distinct2
Distinct (%)50.0%
Missing31
Missing (%)88.6%
Memory size412.0 B
2024-02-10T07:16:47.127015image/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%
2024-02-10T07:16:48.097569image/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
2024-02-10T07:16:48.462431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length3.8181818
Min length1

Characters and Unicode

Total characters126
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 row133,081
3rd row287,748
4th row963
5th row143
ValueCountFrequency (%)
0 5
 
14.7%
1,428 2
 
5.9%
1,946 1
 
2.9%
1,894 1
 
2.9%
959 1
 
2.9%
288,100 1
 
2.9%
133,511 1
 
2.9%
4 1
 
2.9%
352 1
 
2.9%
430 1
 
2.9%
Other values (19) 19
55.9%
2024-02-10T07:16:49.417935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
18.3%
, 16
12.7%
2 16
12.7%
0 15
11.9%
4 12
9.5%
3 11
8.7%
8 10
7.9%
9 5
 
4.0%
6 5
 
4.0%
7 4
 
3.2%
Other values (5) 9
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 105
83.3%
Other Punctuation 16
 
12.7%
Space Separator 2
 
1.6%
Other Letter 2
 
1.6%
Dash Punctuation 1
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 23
21.9%
2 16
15.2%
0 15
14.3%
4 12
11.4%
3 11
10.5%
8 10
9.5%
9 5
 
4.8%
6 5
 
4.8%
7 4
 
3.8%
5 4
 
3.8%
Other Letter
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 124
98.4%
Hangul 2
 
1.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 23
18.5%
, 16
12.9%
2 16
12.9%
0 15
12.1%
4 12
9.7%
3 11
8.9%
8 10
8.1%
9 5
 
4.0%
6 5
 
4.0%
7 4
 
3.2%
Other values (3) 7
 
5.6%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 124
98.4%
Hangul 2
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 23
18.5%
, 16
12.9%
2 16
12.9%
0 15
12.1%
4 12
9.7%
3 11
8.9%
8 10
8.1%
9 5
 
4.0%
6 5
 
4.0%
7 4
 
3.2%
Other values (3) 7
 
5.6%
Hangul
ValueCountFrequency (%)
합 1
50.0%
계 1
50.0%

Unnamed: 6
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:16:49.884358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.9393939
Min length1

Characters and Unicode

Total characters64
Distinct characters12
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 row2,051
3rd row3,555
4th row27
5th row3
ValueCountFrequency (%)
0 7
21.2%
8 3
 
9.1%
2 3
 
9.1%
3 2
 
6.1%
24 2
 
6.1%
27 2
 
6.1%
2,051 1
 
3.0%
21 1
 
3.0%
13 1
 
3.0%
3,555 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:16:50.928884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
17.2%
0 10
15.6%
1 9
14.1%
3 8
12.5%
5 8
12.5%
4 4
 
6.2%
, 4
 
6.2%
8 3
 
4.7%
7 3
 
4.7%
- 2
 
3.1%
Other values (2) 2
 
3.1%

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 (%)
2 11
19.6%
0 10
17.9%
1 9
16.1%
3 8
14.3%
5 8
14.3%
4 4
 
7.1%
8 3
 
5.4%
7 3
 
5.4%
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 (%)
2 11
17.7%
0 10
16.1%
1 9
14.5%
3 8
12.9%
5 8
12.9%
4 4
 
6.5%
, 4
 
6.5%
8 3
 
4.8%
7 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 (%)
2 11
17.7%
0 10
16.1%
1 9
14.5%
3 8
12.9%
5 8
12.9%
4 4
 
6.5%
, 4
 
6.5%
8 3
 
4.8%
7 3
 
4.8%
- 2
 
3.2%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 7
Text

MISSING 

Distinct21
Distinct (%)63.6%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:16:51.359375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length1.969697
Min length1

Characters and Unicode

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

Unique

Unique16 ?
Unique (%)48.5%

Sample

1st row양3동
2nd row2,179
3rd row4,513
4th row31
5th row0
ValueCountFrequency (%)
0 8
24.2%
1 3
 
9.1%
31 2
 
6.1%
15 2
 
6.1%
7 2
 
6.1%
21 2
 
6.1%
8 1
 
3.0%
20 1
 
3.0%
2,177 1
 
3.0%
2 1
 
3.0%
Other values (10) 10
30.3%
2024-02-10T07:16:52.241733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
21.5%
0 9
13.8%
2 9
13.8%
4 6
9.2%
3 5
 
7.7%
7 5
 
7.7%
5 4
 
6.2%
, 4
 
6.2%
9 2
 
3.1%
8 2
 
3.1%
Other values (4) 5
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 57
87.7%
Other Punctuation 4
 
6.2%
Dash Punctuation 2
 
3.1%
Other Letter 2
 
3.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
24.6%
0 9
15.8%
2 9
15.8%
4 6
10.5%
3 5
 
8.8%
7 5
 
8.8%
5 4
 
7.0%
9 2
 
3.5%
8 2
 
3.5%
6 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 63
96.9%
Hangul 2
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
22.2%
0 9
14.3%
2 9
14.3%
4 6
9.5%
3 5
 
7.9%
7 5
 
7.9%
5 4
 
6.3%
, 4
 
6.3%
9 2
 
3.2%
8 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 63
96.9%
Hangul 2
 
3.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
22.2%
0 9
14.3%
2 9
14.3%
4 6
9.5%
3 5
 
7.9%
7 5
 
7.9%
5 4
 
6.3%
, 4
 
6.3%
9 2
 
3.2%
8 2
 
3.2%
Other values (2) 3
 
4.8%
Hangul
ValueCountFrequency (%)
양 1
50.0%
동 1
50.0%

Unnamed: 8
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:16:52.719746image/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

Unique20 ?
Unique (%)60.6%

Sample

1st row농성1동
2nd row6,432
3rd row11,355
4th row83
5th row5
ValueCountFrequency (%)
0 7
21.2%
33 2
 
6.1%
5 2
 
6.1%
84 2
 
6.1%
82 1
 
3.0%
83 1
 
3.0%
124 1
 
3.0%
6,425 1
 
3.0%
1 1
 
3.0%
40 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:16:53.578537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 10
13.7%
4 9
12.3%
5 9
12.3%
0 8
11.0%
8 8
11.0%
3 8
11.0%
6 7
9.6%
, 4
 
5.5%
2 4
 
5.5%
- 2
 
2.7%
Other values (4) 4
 
5.5%

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 10
15.6%
4 9
14.1%
5 9
14.1%
0 8
12.5%
8 8
12.5%
3 8
12.5%
6 7
10.9%
2 4
 
6.2%
7 1
 
1.6%
Other Letter
ValueCountFrequency (%)
농 1
33.3%
성 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 10
14.3%
4 9
12.9%
5 9
12.9%
0 8
11.4%
8 8
11.4%
3 8
11.4%
6 7
10.0%
, 4
 
5.7%
2 4
 
5.7%
- 2
 
2.9%
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 10
14.3%
4 9
12.9%
5 9
12.9%
0 8
11.4%
8 8
11.4%
3 8
11.4%
6 7
10.0%
, 4
 
5.7%
2 4
 
5.7%
- 2
 
2.9%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 9
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:16:53.997652image/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

Unique19 ?
Unique (%)57.6%

Sample

1st row농성2동
2nd row2,955
3rd row4,783
4th row55
5th row1
ValueCountFrequency (%)
0 8
24.2%
1 3
 
9.1%
32 2
 
6.1%
21 2
 
6.1%
15 1
 
3.0%
19 1
 
3.0%
4,772 1
 
3.0%
2,946 1
 
3.0%
11 1
 
3.0%
9 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:16:55.059597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

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

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
16.7%
2 10
16.7%
1 9
15.0%
3 6
10.0%
5 6
10.0%
6 5
8.3%
4 5
8.3%
9 4
 
6.7%
7 3
 
5.0%
8 2
 
3.3%
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 (%)
0 10
14.9%
2 10
14.9%
1 9
13.4%
3 6
9.0%
5 6
9.0%
6 5
7.5%
4 5
7.5%
, 4
 
6.0%
9 4
 
6.0%
7 3
 
4.5%
Other values (2) 5
7.5%
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 (%)
0 10
14.9%
2 10
14.9%
1 9
13.4%
3 6
9.0%
5 6
9.0%
6 5
7.5%
4 5
7.5%
, 4
 
6.0%
9 4
 
6.0%
7 3
 
4.5%
Other values (2) 5
7.5%
Hangul
ValueCountFrequency (%)
농 1
33.3%
성 1
33.3%
동 1
33.3%

Unnamed: 10
Text

MISSING 

Distinct26
Distinct (%)76.5%
Missing1
Missing (%)2.9%
Memory size412.0 B
2024-02-10T07:16:55.395693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.2941176
Min length1

Characters and Unicode

Total characters78
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

Unique23 ?
Unique (%)67.6%

Sample

1st row출력일자 :
2nd row광천동
3rd row4,146
4th row7,805
5th row80
ValueCountFrequency (%)
0 6
 
17.1%
1 3
 
8.6%
12 2
 
5.7%
1
 
2.9%
71 1
 
2.9%
82 1
 
2.9%
7,772 1
 
2.9%
4,129 1
 
2.9%
2 1
 
2.9%
33 1
 
2.9%
Other values (17) 17
48.6%
2024-02-10T07:16:56.199500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
17.9%
0 10
12.8%
7 7
9.0%
3 6
7.7%
2 6
7.7%
4 6
7.7%
9 4
 
5.1%
8 4
 
5.1%
, 4
 
5.1%
5 3
 
3.8%
Other values (11) 14
17.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
80.8%
Other Letter 7
 
9.0%
Other Punctuation 5
 
6.4%
Dash Punctuation 2
 
2.6%
Space Separator 1
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 14
22.2%
0 10
15.9%
7 7
11.1%
3 6
9.5%
2 6
9.5%
4 6
9.5%
9 4
 
6.3%
8 4
 
6.3%
5 3
 
4.8%
6 3
 
4.8%
Other Letter
ValueCountFrequency (%)
동 1
14.3%
광 1
14.3%
천 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
: 1
 
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 71
91.0%
Hangul 7
 
9.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
19.7%
0 10
14.1%
7 7
9.9%
3 6
8.5%
2 6
8.5%
4 6
8.5%
9 4
 
5.6%
8 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
Other values (4) 7
9.9%
Hangul
ValueCountFrequency (%)
동 1
14.3%
광 1
14.3%
천 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 71
91.0%
Hangul 7
 
9.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 14
19.7%
0 10
14.1%
7 7
9.9%
3 6
8.5%
2 6
8.5%
4 6
8.5%
9 4
 
5.6%
8 4
 
5.6%
, 4
 
5.6%
5 3
 
4.2%
Other values (4) 7
9.9%
Hangul
ValueCountFrequency (%)
동 1
14.3%
광 1
14.3%
천 1
14.3%
출 1
14.3%
력 1
14.3%
일 1
14.3%
자 1
14.3%

Unnamed: 11
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:16:56.595586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.1818182
Min length1

Characters and Unicode

Total characters72
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)60.6%

Sample

1st row유덕동
2nd row4,900
3rd row10,855
4th row18
5th row4
ValueCountFrequency (%)
0 7
21.2%
21 2
 
6.1%
4 2
 
6.1%
44 2
 
6.1%
65 1
 
3.0%
18 1
 
3.0%
66 1
 
3.0%
4,880 1
 
3.0%
3 1
 
3.0%
74 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:16:57.857769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
18.1%
4 10
13.9%
1 8
11.1%
8 8
11.1%
2 6
8.3%
5 6
8.3%
, 4
 
5.6%
6 4
 
5.6%
7 3
 
4.2%
3 3
 
4.2%
Other values (5) 7
9.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 63
87.5%
Other Punctuation 4
 
5.6%
Other Letter 3
 
4.2%
Dash Punctuation 2
 
2.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
20.6%
4 10
15.9%
1 8
12.7%
8 8
12.7%
2 6
9.5%
5 6
9.5%
6 4
 
6.3%
7 3
 
4.8%
3 3
 
4.8%
9 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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
18.8%
4 10
14.5%
1 8
11.6%
8 8
11.6%
2 6
8.7%
5 6
8.7%
, 4
 
5.8%
6 4
 
5.8%
7 3
 
4.3%
3 3
 
4.3%
Other values (2) 4
 
5.8%
Hangul
ValueCountFrequency (%)
유 1
33.3%
덕 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
18.8%
4 10
14.5%
1 8
11.6%
8 8
11.6%
2 6
8.7%
5 6
8.7%
, 4
 
5.8%
6 4
 
5.8%
7 3
 
4.3%
3 3
 
4.3%
Other values (2) 4
 
5.8%
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
Minimum2022-09-01 00:00:00
Maximum2022-09-01 00:00:00
2024-02-10T07:16:58.967712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-02-10T07:16:59.560139image/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
2024-02-10T07:17:00.374655image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row치평동
2nd row13,621
3rd row29,955
4th row74
5th row12
ValueCountFrequency (%)
0 6
 
18.2%
11 2
 
6.1%
2 2
 
6.1%
12 2
 
6.1%
157 1
 
3.0%
74 1
 
3.0%
229 1
 
3.0%
29,828 1
 
3.0%
13,614 1
 
3.0%
127 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:17:02.035832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 19
21.3%
2 16
18.0%
0 8
9.0%
9 7
 
7.9%
7 7
 
7.9%
5 6
 
6.7%
4 5
 
5.6%
6 4
 
4.5%
3 4
 
4.5%
, 4
 
4.5%
Other values (5) 9
10.1%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 19
24.1%
2 16
20.3%
0 8
10.1%
9 7
 
8.9%
7 7
 
8.9%
5 6
 
7.6%
4 5
 
6.3%
6 4
 
5.1%
3 4
 
5.1%
8 3
 
3.8%
Other Letter
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 19
22.1%
2 16
18.6%
0 8
9.3%
9 7
 
8.1%
7 7
 
8.1%
5 6
 
7.0%
4 5
 
5.8%
6 4
 
4.7%
3 4
 
4.7%
, 4
 
4.7%
Other values (2) 6
 
7.0%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 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 19
22.1%
2 16
18.6%
0 8
9.3%
9 7
 
8.1%
7 7
 
8.1%
5 6
 
7.0%
4 5
 
5.8%
6 4
 
4.7%
3 4
 
4.7%
, 4
 
4.7%
Other values (2) 6
 
7.0%
Hangul
ValueCountFrequency (%)
치 1
33.3%
평 1
33.3%
동 1
33.3%

Unnamed: 14
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:02.417648image/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

Unique24 ?
Unique (%)72.7%

Sample

1st row상무1동
2nd row12,262
3rd row24,571
4th row138
5th row10
ValueCountFrequency (%)
0 5
 
15.2%
1 3
 
9.1%
10 2
 
6.1%
110 1
 
3.0%
138 1
 
3.0%
24,571 1
 
3.0%
24,551 1
 
3.0%
12,288 1
 
3.0%
20 1
 
3.0%
26 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:17:03.281067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 23
25.8%
0 11
12.4%
2 10
11.2%
8 9
 
10.1%
3 8
 
9.0%
5 6
 
6.7%
6 5
 
5.6%
, 4
 
4.5%
7 4
 
4.5%
4 3
 
3.4%
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 23
28.7%
0 11
13.8%
2 10
12.5%
8 9
 
11.2%
3 8
 
10.0%
5 6
 
7.5%
6 5
 
6.2%
7 4
 
5.0%
4 3
 
3.8%
9 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 23
26.7%
0 11
12.8%
2 10
11.6%
8 9
 
10.5%
3 8
 
9.3%
5 6
 
7.0%
6 5
 
5.8%
, 4
 
4.7%
7 4
 
4.7%
4 3
 
3.5%
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 23
26.7%
0 11
12.8%
2 10
11.6%
8 9
 
10.5%
3 8
 
9.3%
5 6
 
7.0%
6 5
 
5.8%
, 4
 
4.7%
7 4
 
4.7%
4 3
 
3.5%
Other values (2) 3
 
3.5%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 15
Text

MISSING 

Distinct23
Distinct (%)69.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:03.616384image/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

Unique18 ?
Unique (%)54.5%

Sample

1st row상무2동
2nd row13,148
3rd row23,565
4th row122
5th row8
ValueCountFrequency (%)
0 6
18.2%
3 3
 
9.1%
8 2
 
6.1%
105 2
 
6.1%
122 2
 
6.1%
192 1
 
3.0%
193 1
 
3.0%
23,426 1
 
3.0%
13,122 1
 
3.0%
139 1
 
3.0%
Other values (13) 13
39.4%
2024-02-10T07:17:04.316956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 14
16.3%
2 14
16.3%
3 12
14.0%
0 9
10.5%
5 9
10.5%
9 6
7.0%
8 5
 
5.8%
6 4
 
4.7%
, 4
 
4.7%
7 2
 
2.3%
Other values (5) 7
8.1%

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 14
18.2%
2 14
18.2%
3 12
15.6%
0 9
11.7%
5 9
11.7%
9 6
7.8%
8 5
 
6.5%
6 4
 
5.2%
7 2
 
2.6%
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 (%)
- 2
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
1 14
16.9%
2 14
16.9%
3 12
14.5%
0 9
10.8%
5 9
10.8%
9 6
7.2%
8 5
 
6.0%
6 4
 
4.8%
, 4
 
4.8%
7 2
 
2.4%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 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 14
16.9%
2 14
16.9%
3 12
14.5%
0 9
10.8%
5 9
10.8%
9 6
7.2%
8 5
 
6.0%
6 4
 
4.8%
, 4
 
4.8%
7 2
 
2.4%
Other values (2) 4
 
4.8%
Hangul
ValueCountFrequency (%)
상 1
33.3%
무 1
33.3%
동 1
33.3%

Unnamed: 16
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:04.698486image/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

Unique23 ?
Unique (%)69.7%

Sample

1st row화정1동
2nd row8,492
3rd row15,340
4th row48
5th row7
ValueCountFrequency (%)
0 7
21.2%
7 3
 
9.1%
142 1
 
3.0%
131 1
 
3.0%
15,277 1
 
3.0%
8,493 1
 
3.0%
3 1
 
3.0%
63 1
 
3.0%
1 1
 
3.0%
11 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:17:05.612537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 16
20.5%
0 10
12.8%
7 9
11.5%
3 8
10.3%
4 8
10.3%
2 6
 
7.7%
8 4
 
5.1%
, 4
 
5.1%
9 3
 
3.8%
5 3
 
3.8%
Other values (5) 7
9.0%

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 16
22.9%
0 10
14.3%
7 9
12.9%
3 8
11.4%
4 8
11.4%
2 6
 
8.6%
8 4
 
5.7%
9 3
 
4.3%
5 3
 
4.3%
6 3
 
4.3%
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 75
96.2%
Hangul 3
 
3.8%

Most frequent character per script

Common
ValueCountFrequency (%)
1 16
21.3%
0 10
13.3%
7 9
12.0%
3 8
10.7%
4 8
10.7%
2 6
 
8.0%
8 4
 
5.3%
, 4
 
5.3%
9 3
 
4.0%
5 3
 
4.0%
Other values (2) 4
 
5.3%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 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 16
21.3%
0 10
13.3%
7 9
12.0%
3 8
10.7%
4 8
10.7%
2 6
 
8.0%
8 4
 
5.3%
, 4
 
5.3%
9 3
 
4.0%
5 3
 
4.0%
Other values (2) 4
 
5.3%
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
2024-02-10T07:17:06.000461image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row화정2동
2nd row7,984
3rd row20,325
4th row32
5th row16
ValueCountFrequency (%)
0 7
21.2%
16 2
 
6.1%
32 2
 
6.1%
13 1
 
3.0%
274 1
 
3.0%
7,956 1
 
3.0%
94 1
 
3.0%
28 1
 
3.0%
6 1
 
3.0%
46 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:17:06.972221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 12
15.0%
0 11
13.8%
1 9
11.2%
7 7
8.8%
4 7
8.8%
6 6
7.5%
9 6
7.5%
3 5
6.2%
, 4
 
5.0%
8 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 (%)
2 12
16.9%
0 11
15.5%
1 9
12.7%
7 7
9.9%
4 7
9.9%
6 6
8.5%
9 6
8.5%
3 5
7.0%
8 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 (%)
2 12
15.6%
0 11
14.3%
1 9
11.7%
7 7
9.1%
4 7
9.1%
6 6
7.8%
9 6
7.8%
3 5
6.5%
, 4
 
5.2%
8 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 (%)
2 12
15.6%
0 11
14.3%
1 9
11.7%
7 7
9.1%
4 7
9.1%
6 6
7.8%
9 6
7.8%
3 5
6.5%
, 4
 
5.2%
8 4
 
5.2%
Other values (2) 6
7.8%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 18
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:07.318577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.3333333
Min length1

Characters and Unicode

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

Unique

Unique25 ?
Unique (%)75.8%

Sample

1st row화정3동
2nd row4,605
3rd row9,879
4th row30
5th row11
ValueCountFrequency (%)
0 6
 
18.2%
11 2
 
6.1%
89 1
 
3.0%
101 1
 
3.0%
9,777 1
 
3.0%
4,577 1
 
3.0%
8 1
 
3.0%
102 1
 
3.0%
28 1
 
3.0%
7 1
 
3.0%
Other values (17) 17
51.5%
2024-02-10T07:17:08.330914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
16.9%
1 11
14.3%
7 9
11.7%
9 6
7.8%
5 6
7.8%
2 6
7.8%
8 5
 
6.5%
4 4
 
5.2%
, 4
 
5.2%
3 4
 
5.2%
Other values (5) 9
11.7%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
19.4%
1 11
16.4%
7 9
13.4%
9 6
9.0%
5 6
9.0%
2 6
9.0%
8 5
 
7.5%
4 4
 
6.0%
3 4
 
6.0%
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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
17.6%
1 11
14.9%
7 9
12.2%
9 6
8.1%
5 6
8.1%
2 6
8.1%
8 5
 
6.8%
4 4
 
5.4%
, 4
 
5.4%
3 4
 
5.4%
Other values (2) 6
8.1%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

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

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
17.6%
1 11
14.9%
7 9
12.2%
9 6
8.1%
5 6
8.1%
2 6
8.1%
8 5
 
6.8%
4 4
 
5.4%
, 4
 
5.4%
3 4
 
5.4%
Other values (2) 6
8.1%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 19
Text

MISSING 

Distinct24
Distinct (%)72.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:08.704397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5757576
Min length1

Characters and Unicode

Total characters85
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

Unique21 ?
Unique (%)63.6%

Sample

1st row화정4동
2nd row6,497
3rd row15,202
4th row43
5th row13
ValueCountFrequency (%)
0 7
21.2%
43 3
 
9.1%
13 2
 
6.1%
46 1
 
3.0%
15,202 1
 
3.0%
74 1
 
3.0%
7,059 1
 
3.0%
1,537 1
 
3.0%
562 1
 
3.0%
1 1
 
3.0%
Other values (14) 14
42.4%
2024-02-10T07:17:09.578788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 13
15.3%
4 11
12.9%
1 10
11.8%
6 9
10.6%
3 8
9.4%
5 8
9.4%
, 6
7.1%
7 6
7.1%
8 4
 
4.7%
2 4
 
4.7%
Other values (4) 6
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 76
89.4%
Other Punctuation 6
 
7.1%
Other Letter 3
 
3.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 13
17.1%
4 11
14.5%
1 10
13.2%
6 9
11.8%
3 8
10.5%
5 8
10.5%
7 6
7.9%
8 4
 
5.3%
2 4
 
5.3%
9 3
 
3.9%
Other Letter
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 82
96.5%
Hangul 3
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 13
15.9%
4 11
13.4%
1 10
12.2%
6 9
11.0%
3 8
9.8%
5 8
9.8%
, 6
7.3%
7 6
7.3%
8 4
 
4.9%
2 4
 
4.9%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 82
96.5%
Hangul 3
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 13
15.9%
4 11
13.4%
1 10
12.2%
6 9
11.0%
3 8
9.8%
5 8
9.8%
, 6
7.3%
7 6
7.3%
8 4
 
4.9%
2 4
 
4.9%
Hangul
ValueCountFrequency (%)
화 1
33.3%
정 1
33.3%
동 1
33.3%

Unnamed: 20
Text

MISSING 

Distinct22
Distinct (%)66.7%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:09.922538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length2
Mean length2.0606061
Min length1

Characters and Unicode

Total characters68
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)51.5%

Sample

1st row서창동
2nd row2,671
3rd row5,703
4th row28
5th row4
ValueCountFrequency (%)
0 7
21.2%
31 3
 
9.1%
4 2
 
6.1%
2 2
 
6.1%
26 2
 
6.1%
6 1
 
3.0%
63 1
 
3.0%
12 1
 
3.0%
2,669 1
 
3.0%
7 1
 
3.0%
Other values (12) 12
36.4%
2024-02-10T07:17:10.884210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 11
16.2%
6 10
14.7%
1 9
13.2%
0 8
11.8%
3 7
10.3%
7 4
 
5.9%
, 4
 
5.9%
4 3
 
4.4%
- 3
 
4.4%
5 3
 
4.4%
Other values (5) 6
8.8%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
19.0%
6 10
17.2%
1 9
15.5%
0 8
13.8%
3 7
12.1%
7 4
 
6.9%
4 3
 
5.2%
5 3
 
5.2%
9 2
 
3.4%
8 1
 
1.7%
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 65
95.6%
Hangul 3
 
4.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
16.9%
6 10
15.4%
1 9
13.8%
0 8
12.3%
3 7
10.8%
7 4
 
6.2%
, 4
 
6.2%
4 3
 
4.6%
- 3
 
4.6%
5 3
 
4.6%
Other values (2) 3
 
4.6%
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 (%)
2 11
16.9%
6 10
15.4%
1 9
13.8%
0 8
12.3%
3 7
10.8%
7 4
 
6.2%
, 4
 
6.2%
4 3
 
4.6%
- 3
 
4.6%
5 3
 
4.6%
Other values (2) 3
 
4.6%
Hangul
ValueCountFrequency (%)
서 1
33.3%
창 1
33.3%
동 1
33.3%

Unnamed: 21
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:11.264596image/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 row금호1동
2nd row8,990
3rd row20,137
4th row41
5th row4
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
88 2
 
6.1%
4 2
 
6.1%
67 1
 
3.0%
176 1
 
3.0%
20,099 1
 
3.0%
8,998 1
 
3.0%
38 1
 
3.0%
8 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:17:12.249761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 12
16.4%
8 9
12.3%
1 8
11.0%
9 8
11.0%
4 7
9.6%
7 5
6.8%
5 5
6.8%
, 4
 
5.5%
2 4
 
5.5%
3 4
 
5.5%
Other values (5) 7
9.6%

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 12
18.5%
8 9
13.8%
1 8
12.3%
9 8
12.3%
4 7
10.8%
7 5
7.7%
5 5
7.7%
2 4
 
6.2%
3 4
 
6.2%
6 3
 
4.6%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12
17.1%
8 9
12.9%
1 8
11.4%
9 8
11.4%
4 7
10.0%
7 5
7.1%
5 5
7.1%
, 4
 
5.7%
2 4
 
5.7%
3 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 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 12
17.1%
8 9
12.9%
1 8
11.4%
9 8
11.4%
4 7
10.0%
7 5
7.1%
5 5
7.1%
, 4
 
5.7%
2 4
 
5.7%
3 4
 
5.7%
Other values (2) 4
 
5.7%
Hangul
ValueCountFrequency (%)
금 1
33.3%
호 1
33.3%
동 1
33.3%

Unnamed: 22
Text

MISSING 

Distinct27
Distinct (%)81.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:12.691882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
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

Unique25 ?
Unique (%)75.8%

Sample

1st row금호2동
2nd row10,533
3rd row27,971
4th row23
5th row7
ValueCountFrequency (%)
0 6
 
18.2%
1 2
 
6.1%
7 2
 
6.1%
189 1
 
3.0%
379 1
 
3.0%
27,777 1
 
3.0%
10,507 1
 
3.0%
194 1
 
3.0%
26 1
 
3.0%
6 1
 
3.0%
Other values (16) 16
48.5%
2024-02-10T07:17:13.533393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7 13
15.7%
1 13
15.7%
0 12
14.5%
2 7
8.4%
9 7
8.4%
4 6
7.2%
3 5
 
6.0%
, 4
 
4.8%
8 4
 
4.8%
6 4
 
4.8%
Other values (5) 8
9.6%

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 (%)
7 13
17.8%
1 13
17.8%
0 12
16.4%
2 7
9.6%
9 7
9.6%
4 6
8.2%
3 5
 
6.8%
8 4
 
5.5%
6 4
 
5.5%
5 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 (%)
- 3
100.0%

Most occurring scripts

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

Most frequent character per script

Common
ValueCountFrequency (%)
7 13
16.2%
1 13
16.2%
0 12
15.0%
2 7
8.8%
9 7
8.8%
4 6
7.5%
3 5
 
6.2%
, 4
 
5.0%
8 4
 
5.0%
6 4
 
5.0%
Other values (2) 5
 
6.2%
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 (%)
7 13
16.2%
1 13
16.2%
0 12
15.0%
2 7
8.8%
9 7
8.8%
4 6
7.5%
3 5
 
6.2%
, 4
 
5.0%
8 4
 
5.0%
6 4
 
5.0%
Other values (2) 5
 
6.2%
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
2024-02-10T07:17:13.908638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length4
Mean length2.6666667
Min length1

Characters and Unicode

Total characters88
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 row풍암동
2nd row15,245
3rd row36,233
4th row77
5th row22
ValueCountFrequency (%)
0 6
 
18.2%
133 2
 
6.1%
1 2
 
6.1%
22 2
 
6.1%
145 1
 
3.0%
223 1
 
3.0%
36,075 1
 
3.0%
15,243 1
 
3.0%
158 1
 
3.0%
2 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:17:14.710031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 15
17.0%
1 15
17.0%
3 11
12.5%
5 10
11.4%
0 8
9.1%
4 7
8.0%
6 5
 
5.7%
7 5
 
5.7%
, 4
 
4.5%
- 3
 
3.4%
Other values (5) 5
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 78
88.6%
Other Punctuation 4
 
4.5%
Dash Punctuation 3
 
3.4%
Other Letter 3
 
3.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 15
19.2%
1 15
19.2%
3 11
14.1%
5 10
12.8%
0 8
10.3%
4 7
9.0%
6 5
 
6.4%
7 5
 
6.4%
9 1
 
1.3%
8 1
 
1.3%
Other Letter
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85
96.6%
Hangul 3
 
3.4%

Most frequent character per script

Common
ValueCountFrequency (%)
2 15
17.6%
1 15
17.6%
3 11
12.9%
5 10
11.8%
0 8
9.4%
4 7
8.2%
6 5
 
5.9%
7 5
 
5.9%
, 4
 
4.7%
- 3
 
3.5%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
96.6%
Hangul 3
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 15
17.6%
1 15
17.6%
3 11
12.9%
5 10
11.8%
0 8
9.4%
4 7
8.2%
6 5
 
5.9%
7 5
 
5.9%
, 4
 
4.7%
- 3
 
3.5%
Other values (2) 2
 
2.4%
Hangul
ValueCountFrequency (%)
풍 1
33.3%
암 1
33.3%
동 1
33.3%

Unnamed: 24
Text

MISSING 

Distinct25
Distinct (%)75.8%
Missing2
Missing (%)5.7%
Memory size412.0 B
2024-02-10T07:17:15.123590image/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

Unique22 ?
Unique (%)66.7%

Sample

1st row동천동
2nd row6,370
3rd row16,001
4th row13
5th row4
ValueCountFrequency (%)
0 7
21.2%
68 2
 
6.1%
4 2
 
6.1%
6 1
 
3.0%
86 1
 
3.0%
15,972 1
 
3.0%
6,385 1
 
3.0%
1 1
 
3.0%
29 1
 
3.0%
15 1
 
3.0%
Other values (15) 15
45.5%
2024-02-10T07:17:15.924666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 10
13.7%
1 9
12.3%
6 8
11.0%
5 8
11.0%
4 7
9.6%
8 5
6.8%
7 5
6.8%
2 5
6.8%
, 4
 
5.5%
3 4
 
5.5%
Other values (4) 8
11.0%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 10
15.6%
1 9
14.1%
6 8
12.5%
5 8
12.5%
4 7
10.9%
8 5
7.8%
7 5
7.8%
2 5
7.8%
3 4
 
6.2%
9 3
 
4.7%
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 70
95.9%
Hangul 3
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 10
14.3%
1 9
12.9%
6 8
11.4%
5 8
11.4%
4 7
10.0%
8 5
7.1%
7 5
7.1%
2 5
7.1%
, 4
 
5.7%
3 4
 
5.7%
Other values (2) 5
7.1%
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 10
14.3%
1 9
12.9%
6 8
11.4%
5 8
11.4%
4 7
10.0%
8 5
7.1%
7 5
7.1%
2 5
7.1%
, 4
 
5.7%
3 4
 
5.7%
Other values (2) 5
7.1%
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>2022.09.01<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
1<NA>작성기준 :<NA>2022.08 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>133,0812,0512,1796,4322,9554,1464,900<NA>13,62112,26213,1488,4927,9844,6056,4972,6718,99010,53315,2456,370
4<NA>전월말인구수<NA><NA><NA>287,7483,5554,51311,3554,7837,80510,855<NA>29,95524,57123,56515,34020,3259,87915,2025,70320,13727,97136,23316,001
5<NA>전월말거주불명자수<NA><NA><NA>963273183558018<NA>74138122483230432841237713
6<NA>전월말재외국민등록자수<NA><NA><NA>1433051124<NA>121087161113447224
7<NA>증 가 요 인전 입계<NA>4,2222128124629666<NA>299326255214172971,68063145181266127
8<NA><NA><NA>남자<NA>2,120131568324928<NA>152158133111824684431708713368
9<NA><NA><NA>여자<NA>2,10281356304738<NA>147168122103905183632759413359
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>17100000<NA>213007101010
26<NA><NA>국외<NA><NA>0000000<NA>000000000000
27<NA><NA>기타<NA><NA>0000000<NA>000000000000
28<NA>세대수증감<NA><NA><NA>430-8-2-7-9-17-20<NA>-726-261-28-28562-28-26-215
29<NA>인구수증감<NA><NA><NA>352-35-21-40-11-33-74<NA>-127-20-139-63-94-1021,537-7-38-194-158-29
30<NA>거주불명자수증감<NA><NA><NA>-4001-123<NA>-2-1330-80-21-1-1-1
31<NA>금월말세대수<NA><NA><NA>133,5112,0432,1776,4252,9464,1294,880<NA>13,61412,28813,1228,4937,9564,5777,0592,6698,99810,50715,2436,385
32<NA>금월말인구수<NA><NA><NA>288,1003,5204,49211,3154,7727,77210,781<NA>29,82824,55123,42615,27720,2319,77716,7395,69620,09927,77736,07515,972
33<NA>금월말거주불명자수<NA><NA><NA>959273184548221<NA>72137125513222432642227612
34<NA>금월말재외국민등록자수<NA><NA><NA>1423150114<NA>121087161113447224

Duplicate rows

Most frequently occurring

인구이동보고서(1호)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16Unnamed: 17Unnamed: 18Unnamed: 19Unnamed: 20Unnamed: 21Unnamed: 22Unnamed: 23Unnamed: 24# duplicates
0<NA>국외<NA><NA>0000000<NA>0000000000002
1<NA>기타<NA><NA>0000000<NA>0000000000002